Mixture modelling for cluster analysis.

PubMed

McLachlan, G J; Chang, S U

2004-10-01

Cluster analysis via a finite mixture model approach is considered. With this approach to clustering, the data can be partitioned into a specified number of clusters g by first fitting a mixture model with g components. An outright clustering of the data is then obtained by assigning an observation to the component to which it has the highest estimated posterior probability of belonging; that is, the ith cluster consists of those observations assigned to the ith component (i = 1,..., g). The focus is on the use of mixtures of normal components for the cluster analysis of data that can be regarded as being continuous. But attention is also given to the case of mixed data, where the observations consist of both continuous and discrete variables.

Hierarchical cluster analysis of progression patterns in open-angle glaucoma patients with medical treatment.

PubMed

Bae, Hyoung Won; Rho, Seungsoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

2014-04-29

To classify medically treated open-angle glaucoma (OAG) by the pattern of progression using hierarchical cluster analysis, and to determine OAG progression characteristics by comparing clusters. Ninety-five eyes of 95 OAG patients who received medical treatment, and who had undergone visual field (VF) testing at least once per year for 5 or more years. OAG was classified into subgroups using hierarchical cluster analysis based on the following five variables: baseline mean deviation (MD), baseline visual field index (VFI), MD slope, VFI slope, and Glaucoma Progression Analysis (GPA) printout. After that, other parameters were compared between clusters. Two clusters were made after a hierarchical cluster analysis. Cluster 1 showed -4.06 ± 2.43 dB baseline MD, 92.58% ± 6.27% baseline VFI, -0.28 ± 0.38 dB per year MD slope, -0.52% ± 0.81% per year VFI slope, and all "no progression" cases in GPA printout, whereas cluster 2 showed -8.68 ± 3.81 baseline MD, 77.54 ± 12.98 baseline VFI, -0.72 ± 0.55 MD slope, -2.22 ± 1.89 VFI slope, and seven "possible" and four "likely" progression cases in GPA printout. There were no significant differences in age, sex, mean IOP, central corneal thickness, and axial length between clusters. However, cluster 2 included more high-tension glaucoma patients and used a greater number of antiglaucoma eye drops significantly compared with cluster 1. Hierarchical cluster analysis of progression patterns divided OAG into slow and fast progression groups, evidenced by assessing the parameters of glaucomatous progression in VF testing. In the fast progression group, the prevalence of high-tension glaucoma was greater and the number of antiglaucoma medications administered was increased versus the slow progression group. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

[Analysis of epidemic features of scrub typhus between year 2006 and 2010 in Shandong province, China].

PubMed

Ding, Lei; Li, Zhong; Wang, Xian-jun; Ding, Shu-jun; Zhang, Meng; Zhao, Zhong-tang

2012-04-01

To explore the epidemic features of scrub typhus between year 2006 and 2010 in Shandong Province. Based on the data collected through Diseases Reporting Information System between year 2006 and 2010 in Shandong province, 1291 cases of scrub typhus were selected. The study described the population distribution features of the scrub typhus patients, and explored the temporal and spatial distribution features of the disease by applying the methods of spatial thematic mapping, inverse distance weighted, spatial autocorrelation analysis, spatial clustering analysis, temporal clustering analysis and spatial variation analysis in temporal trends based on Geographic Information software (ArcGIS 9.3) and Spatial Clustering Software (SatScan 7.0). The onset age of the 1291 patients ranged between 1 and 92 years old.639 out of 1291 patients were over 55 years old, accounting for 49.5%.640 patients were male and the other 651 patients were female, occupying 49.6% and 50.4% respectively. The gender ratio was 1:1.02. Patients were found in farmers, workers, students and preschool children. However, most of the cases were farmers, up to 84.8% (1095/1291). Global Moran's I index was 0.324 (P < 0.01). The local Moran's I index in 8 locations were proved to have statistical significance (P < 0.01); all of which were H-H clustering areas. Gangcheng (38 cases), Laicheng (154 cases), Xintai (160 cases) and Donggang (105 cases) were important locations, whose local Moran's I index were 2.111, 1.642, 1.277 and 0.775 respectively. The clustering period of scrub typhus in respective year were as follows: 2006.09.23 - 2006.11.20 (202 cases), 2007.10.02 - 2007.11.11 (197 cases), 2008.09.30 - 2008.11.07 (302 cases), 2009.09.25 - 2009.11.10 (204 cases), and 2010.10.05 - 2010.11.13 (226 cases), whose RR values were separately 45.55, 34.60, 50.64, 53.09 and 79.84 (P < 0.01). Two spatial clustering area were found in the study, one was the area centered Taian and Xintai with radiation radius at 58.28 km (542 cases) and the other one was the area centered Rizhao and Donggang with radiation radius at 22.68 km (134 cases), whose RR values were 4.52 and 3.96 (P < 0.01). The spatial features of the two clustering areas were inland low hills area and coastal hills area. The highest annual growth rate of the disease was 45.04%, found in the area centered Linyi and Mengyin counties, with the radiation radius at 45.82 km. The RR value was 3.68 (P < 0.01). The majority of the scrub typhus patients were middle-aged and elderly farmers. The epidemic peak was between the last 10 days of September and the first 10 days of November. A positive spatial correlation of the disease was found; and most cases clustered in inland low hills area and costal hills area; especially the area around Linyi and Mengyin, with the highest annual growth rates of the disease.

International linkage of two food-borne hepatitis A clusters through traceback of mussels, the Netherlands, 2012.

PubMed

Boxman, Ingeborg L A; Verhoef, Linda; Vennema, Harry; Ngui, Siew-Lin; Friesema, Ingrid H M; Whiteside, Chris; Lees, David; Koopmans, Marion

2016-01-01

This report describes an outbreak investigation starting with two closely related suspected food-borne clusters of Dutch hepatitis A cases, nine primary cases in total, with an unknown source in the Netherlands. The hepatitis A virus (HAV) genotype IA sequences of both clusters were highly similar (459/460 nt) and were not reported earlier. Food questionnaires and a case-control study revealed an association with consumption of mussels. Analysis of mussel supply chains identified the most likely production area. International enquiries led to identification of a cluster of patients near this production area with identical HAV sequences with onsets predating the first Dutch cluster of cases. The most likely source for this cluster was a case who returned from an endemic area in Central America, and a subsequent household cluster from which treated domestic sewage was discharged into the suspected mussel production area. Notably, mussels from this area were also consumed by a separate case in the United Kingdom sharing an identical strain with the second Dutch cluster. In conclusion, a small number of patients in a non-endemic area led to geographically dispersed hepatitis A outbreaks with food as vehicle. This link would have gone unnoticed without sequence analyses and international collaboration.

A clustering method of Chinese medicine prescriptions based on modified firefly algorithm.

PubMed

Yuan, Feng; Liu, Hong; Chen, Shou-Qiang; Xu, Liang

2016-12-01

This paper is aimed to study the clustering method for Chinese medicine (CM) medical cases. The traditional K-means clustering algorithm had shortcomings such as dependence of results on the selection of initial value, trapping in local optimum when processing prescriptions form CM medical cases. Therefore, a new clustering method based on the collaboration of firefly algorithm and simulated annealing algorithm was proposed. This algorithm dynamically determined the iteration of firefly algorithm and simulates sampling of annealing algorithm by fitness changes, and increased the diversity of swarm through expansion of the scope of the sudden jump, thereby effectively avoiding premature problem. The results from confirmatory experiments for CM medical cases suggested that, comparing with traditional K-means clustering algorithms, this method was greatly improved in the individual diversity and the obtained clustering results, the computing results from this method had a certain reference value for cluster analysis on CM prescriptions.

Rhodium clustering process on defective (8,0) SWCNT: Analysis of chemical and physical properties using density functional theory

NASA Astrophysics Data System (ADS)

Ambrusi, Ruben E.; Luna, C. Romina; Sandoval, Mario G.; Bechthold, Pablo; Pronsato, M. Estela; Juan, Alfredo

2017-12-01

The Spin-polarized density functional theory is used to study the effect of a single vacancy in a (8,0) single-walled carbon nanotube (SWCNT) on the Rh clustering process. The vacancy is considered oxygenated and non-oxygenated and, in each case, different Rhn cluster sizes (n = 1-4) are taken into account. For the analysis of these systems some physical and chemical properties are calculated, such as binding energy (Eb), work function (WF), magnetic moment, charge transfer, bond length, band gap (Eg), and density of state (DOS). From this analysis it can be concluded that: a single Rh atom and Rh2 dimer are adsorbed on vacancy without oxygen, whereas Rh3 and Rh4 clusters prefer to be adsorbed on oxygenated vacancy. In all cases, Rh adsorption induces a magnetic moment. When the Rh atom and Rh2 dimer are bonded to the defective SWCNT, it has been found that they show a semiconductor behavior that could be interesting to use in the spintronic area. In the case of Rh3 and Rh4 clusters our results show a metallic behavior suggesting that these systems are good candidates for nanotube contact.

Clustering "N" Objects into "K" Groups under Optimal Scaling of Variables.

ERIC Educational Resources Information Center

van Buuren, Stef; Heiser, Willem J.

1989-01-01

A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)

Spatial Analysis of the Human Immunodeficiency Virus Epidemic among Men Who Have Sex with Men in China, 2006-2015.

PubMed

Qin, Qianqian; Guo, Wei; Tang, Weiming; Mahapatra, Tanmay; Wang, Liyan; Zhang, Nanci; Ding, Zhengwei; Cai, Chang; Cui, Yan; Sun, Jiangping

2017-04-01

Studies have shown a recent upsurge in human immunodeficiency virus (HIV) burden among men who have sex with men (MSM) in China, especially in urban areas. For intervention planning and resource allocation, spatial analyses of HIV/AIDS case-clusters were required to identify epidemic foci and trends among MSM in China. Information regarding MSM recorded as HIV/AIDS cases during 2006-2015 were extracted from the National Case Reporting System. Demographic trends were determined through Cochran-Armitage trend tests. Distribution of case-clusters was examined using spatial autocorrelation. Spatial-temporal scan was used to detect disease clustering. Spatial correlations between cases and socioenvironmental factors were determined by spatial regression. Between 2006 and 2015, in China, 120 371 HIV/AIDS cases were identified among MSM. Newly identified HIV/AIDS cases among self-reported MSM increased from 487 cases in 2006 to >30 000 cases in 2015. Among those HIV/AIDS cases recorded during 2006-2015, 47.0% were 20-29 years old and 24.9% were aged 30-39 years. Based on clusters of HIV/AIDS cases identified through spatial analysis, the epidemic was concentrated among MSM in large cities. Spatial-temporal clusters contained municipalities, provincial capitals, and main cities such as Beijing, Shanghai, Chongqing, Chengdu, and Guangzhou. Spatial regression analysis showed that sociodemographic indicators such as population density, per capita gross domestic product, and number of county-level medical institutions had statistically significant positive correlations with HIV/AIDS among MSM. Assorted spatial analyses revealed an increasingly concentrated HIV epidemic among young MSM in Chinese cities, calling for targeted health education and intensive interventions at an early age. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Space-Time Analysis of Testicular Cancer Clusters Using Residential Histories: A Case-Control Study in Denmark

PubMed Central

Sloan, Chantel D.; Nordsborg, Rikke B.; Jacquez, Geoffrey M.; Raaschou-Nielsen, Ole; Meliker, Jaymie R.

2015-01-01

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population. PMID:25756204

Space-time analysis of testicular cancer clusters using residential histories: a case-control study in Denmark.

PubMed

Sloan, Chantel D; Nordsborg, Rikke B; Jacquez, Geoffrey M; Raaschou-Nielsen, Ole; Meliker, Jaymie R

2015-01-01

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population.

The Impact of Multilocus Variable-Number Tandem-Repeat Analysis on PulseNet Canada Escherichia coli O157:H7 Laboratory Surveillance and Outbreak Support, 2008-2012.

PubMed

Rumore, Jillian Leigh; Tschetter, Lorelee; Nadon, Celine

2016-05-01

The lack of pattern diversity among pulsed-field gel electrophoresis (PFGE) profiles for Escherichia coli O157:H7 in Canada does not consistently provide optimal discrimination, and therefore, differentiating temporally and/or geographically associated sporadic cases from potential outbreak cases can at times impede investigations. To address this limitation, DNA sequence-based methods such as multilocus variable-number tandem-repeat analysis (MLVA) have been explored. To assess the performance of MLVA as a supplemental method to PFGE from the Canadian perspective, a retrospective analysis of all E. coli O157:H7 isolated in Canada from January 2008 to December 2012 (inclusive) was conducted. A total of 2285 E. coli O157:H7 isolates and 63 clusters of cases (by PFGE) were selected for the study. Based on the qualitative analysis, the addition of MLVA improved the categorization of cases for 60% of clusters and no change was observed for ∼40% of clusters investigated. In such situations, MLVA serves to confirm PFGE results, but may not add further information per se. The findings of this study demonstrate that MLVA data, when used in combination with PFGE-based analyses, provide additional resolution to the detection of clusters lacking PFGE diversity as well as demonstrate good epidemiological concordance. In addition, MLVA is able to identify cluster-associated isolates with variant PFGE pattern combinations that may have been previously missed by PFGE alone. Optimal laboratory surveillance in Canada is achieved with the application of PFGE and MLVA in tandem for routine surveillance, cluster detection, and outbreak response.

[Spatial analysis of syphilis and gonorrhea infections in a Public Health Service in Madrid].

PubMed

Wijers, Irene G M; Sánchez Gómez, Amaya; Taveira Jiménez, Jose Antonio

2017-06-21

Sexually transmitted diseases are a significant public health problem. Within the Madrid Autonomous Region, the districts with the highest syphilis and gonorrhea incidences are part of the same Public Health Service (Servicio de Salud Pública del Área 7, SSPA 7). The objective of this study was to identify, by spatial analysis, clusters of syphilis and gonorrhea infections in this SSPA in Madrid. All confirmed syphilis and gonorrhea cases registered in SSPA 7 in Madrid were selected. Moran's I was calculated in order to identify the existence of spatial autocorrelation and a cluster analysis was performed. Clusters and cumulative incidences (CI) per health zone were mapped. The district with most cases was Centro (CI: 67.5 and 160.7 per 100.000 inhabitants for syphilis and gonorrhea, respectively) with the highest CI (120.0 and 322.6 per 100.000 inhabitants) in the Justicia health zone.91.6% of all syphilis cases and 89.6% of gonorrhea cases were among men who have sex with men (MSM). Moran's I was 0.54 and 0.55 (p=0.001) for syphilis and gonorrhea, respectively. For syphilis, a cluster was identified including the six health zones of the Centro district, with a relative risk (RR)of 6.66 (p=0.001). For gonorrhea, a cluster was found including the Centro district, three health zones of the Chamberí district and one of Latina (RR 5.05; p=0.001). Centro was the district with most cases of syphilis and gonorrhea and the most affected population were MSM. For both infections, clusters were found with an important overlap. By identifying the most vulnerable health zones and populations, these results can help to design public health measures for preventing sexually transmitted diseases.

Human avian influenza in Indonesia: are they really clustered?

PubMed

Eyanoer, Putri Chairani; Singhasivanon, Pratap; Kaewkungwal, Jaranit; Apisarnthanarak, Anucha

2011-05-01

Understanding the epidemiology of human H5N1 cases in Indonesia is important. The question of whether cases are clustered or not is unclear. An increase in clustered cases suggests greater transmissibility. In the present study, 107 confirmed and 302 suspected human H5N1 cases in Indonesia during 2005-2007 were analyzed for spatial and temporal distribution. Most confirmed cases (97.2%) occurred on two main islands (Java and Sumatera). There were no patterns of disease occurrence over time. There were also no correlations between occurrence patterns in humans and poultry. Statistical analysis showed confirmed cases were clustered within an area on Java island covered by 8 districts along the border of three neighboring provinces (Jakarta, West Java, and Banten). This study shows human H5N1 cases in Indonesia were clustered at two sites where there was a high rate of infection among poultry. These findings are important since they highlight areas of high risk for possible human H5N1 infection in Indonesia, thus, preventive measures may be taken.

Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogan, Emilie A.; Cotilla Sanchez, Jose E.; Halappanavar, Mahantesh

2013-11-30

Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques onmore » two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.« less

The cosmological analysis of X-ray cluster surveys - I. A new method for interpreting number counts

NASA Astrophysics Data System (ADS)

Clerc, N.; Pierre, M.; Pacaud, F.; Sadibekova, T.

2012-07-01

We present a new method aimed at simplifying the cosmological analysis of X-ray cluster surveys. It is based on purely instrumental observable quantities considered in a two-dimensional X-ray colour-magnitude diagram (hardness ratio versus count rate). The basic principle is that even in rather shallow surveys, substantial information on cluster redshift and temperature is present in the raw X-ray data and can be statistically extracted; in parallel, such diagrams can be readily predicted from an ab initio cosmological modelling. We illustrate the methodology for the case of a 100-deg2XMM survey having a sensitivity of ˜10-14 erg s-1 cm-2 and fit at the same time, the survey selection function, the cluster evolutionary scaling relations and the cosmology; our sole assumption - driven by the limited size of the sample considered in the case study - is that the local cluster scaling relations are known. We devote special attention to the realistic modelling of the count-rate measurement uncertainties and evaluate the potential of the method via a Fisher analysis. In the absence of individual cluster redshifts, the count rate and hardness ratio (CR-HR) method appears to be much more efficient than the traditional approach based on cluster counts (i.e. dn/dz, requiring redshifts). In the case where redshifts are available, our method performs similar to the traditional mass function (dn/dM/dz) for the purely cosmological parameters, but constrains better parameters defining the cluster scaling relations and their evolution. A further practical advantage of the CR-HR method is its simplicity: this fully top-down approach totally bypasses the tedious steps consisting in deriving cluster masses from X-ray temperature measurements.

Antioxidant properties of different edible mushroom species and increased bioconversion efficiency of Pleurotus eryngii using locally available casing materials.

PubMed

Mishra, K K; Pal, R S; Arunkumar, R; Chandrashekara, C; Jain, S K; Bhatt, J C

2013-06-01

Total phenolics, radical scavenging activity (RSA) on DPPH, ascorbic acid content and chelating activity on Fe(2+) of Pleurotus citrinopileatus, Pleurotus djamor, Pleurotus eryngii, Pleurotus flabellatus, Pleurotus florida, Pleurotus ostreatus, Pleurotus sajor-caju and Hypsizygus ulmarius have been evaluated. The assayed mushrooms contained 3.94-21.67 mg TAE of phenolics, 13.63-69.67% DPPH scavenging activity, 3.76-6.76 mg ascorbic acid and 60.25-82.7% chelating activity. Principal Component Analysis (PCA) revealed that significantly higher total phenolics, RSA on DPPH and growth/day was present in P. eryngii whereas P. citrinopileatus showed higher ascorbic acid and chelating activity. Agglomerative hierarchical clustering analysis revealed that studied mushroom species fall into two clusters; Cluster I included P. djamor, P. eryngii and P. flabellatus, while Cluster II included H. ulmarius, P. sajor-caju, P. citrinopileatus, P. ostreatus and P. florida. Enhanced yield of P. eryngii was achieved on spent compost casing material. Use of casing materials enhanced yield by 21-107% over non-cased substrate. Copyright © 2012 Elsevier Ltd. All rights reserved.

The contribution of psychological factors to recovery after mild traumatic brain injury: is cluster analysis a useful approach?

PubMed

Snell, Deborah L; Surgenor, Lois J; Hay-Smith, E Jean C; Williman, Jonathan; Siegert, Richard J

2015-01-01

Outcomes after mild traumatic brain injury (MTBI) vary, with slow or incomplete recovery for a significant minority. This study examines whether groups of cases with shared psychological factors but with different injury outcomes could be identified using cluster analysis. This is a prospective observational study following 147 adults presenting to a hospital-based emergency department or concussion services in Christchurch, New Zealand. This study examined associations between baseline demographic, clinical, psychological variables (distress, injury beliefs and symptom burden) and outcome 6 months later. A two-step approach to cluster analysis was applied (Ward's method to identify clusters, K-means to refine results). Three meaningful clusters emerged (high-adapters, medium-adapters, low-adapters). Baseline cluster-group membership was significantly associated with outcomes over time. High-adapters appeared recovered by 6-weeks and medium-adapters revealed improvements by 6-months. The low-adapters continued to endorse many symptoms, negative recovery expectations and distress, being significantly at risk for poor outcome more than 6-months after injury (OR (good outcome) = 0.12; CI = 0.03-0.53; p < 0.01). Cluster analysis supported the notion that groups could be identified early post-injury based on psychological factors, with group membership associated with differing outcomes over time. Implications for clinical care providers regarding therapy targets and cases that may benefit from different intensities of intervention are discussed.

Allergen Sensitization Pattern by Sex: A Cluster Analysis in Korea.

PubMed

Ohn, Jungyoon; Paik, Seung Hwan; Doh, Eun Jin; Park, Hyun-Sun; Yoon, Hyun-Sun; Cho, Soyun

2017-12-01

Allergens tend to sensitize simultaneously. Etiology of this phenomenon has been suggested to be allergen cross-reactivity or concurrent exposure. However, little is known about specific allergen sensitization patterns. To investigate the allergen sensitization characteristics according to gender. Multiple allergen simultaneous test (MAST) is widely used as a screening tool for detecting allergen sensitization in dermatologic clinics. We retrospectively reviewed the medical records of patients with MAST results between 2008 and 2014 in our Department of Dermatology. A cluster analysis was performed to elucidate the allergen-specific immunoglobulin (Ig)E cluster pattern. The results of MAST (39 allergen-specific IgEs) from 4,360 cases were analyzed. By cluster analysis, 39items were grouped into 8 clusters. Each cluster had characteristic features. When compared with female, the male group tended to be sensitized more frequently to all tested allergens, except for fungus allergens cluster. The cluster and comparative analysis results demonstrate that the allergen sensitization is clustered, manifesting allergen similarity or co-exposure. Only the fungus cluster allergens tend to sensitize female group more frequently than male group.

Performance analysis of clustering techniques over microarray data: A case study

NASA Astrophysics Data System (ADS)

Dash, Rasmita; Misra, Bijan Bihari

2018-03-01

Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with this problem a grading approach is introduced over many clustering techniques to identify a stable technique. But the grading approach depends on the characteristic of dataset as well as on the validity indices. So a two stage grading approach is implemented. In this study the grading approach is implemented over five clustering techniques like hybrid swarm based clustering (HSC), k-means, partitioning around medoids (PAM), vector quantization (VQ) and agglomerative nesting (AGNES). The experimentation is conducted over five microarray datasets with seven validity indices. The finding of grading approach that a cluster technique is significant is also established by Nemenyi post-hoc hypothetical test.

Applications of cluster analysis to satellite soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.; Kalnay, E.; Piraino, P.

1984-01-01

The advantages of the use of cluster analysis in the improvement of satellite temperature retrievals were evaluated since the use of natural clusters, which are associated with atmospheric temperature soundings characteristic of different types of air masses, has the potential for improving stratified regression schemes in comparison with currently used methods which stratify soundings based on latitude, season, and land/ocean. The method of discriminatory analysis was used. The correct cluster of temperature profiles from satellite measurements was located in 85% of the cases. Considerable improvement was observed at all mandatory levels using regression retrievals derived in the clusters of temperature (weighted and nonweighted) in comparison with the control experiment and with the regression retrievals derived in the clusters of brightness temperatures of 3 MSU and 5 IR channels.

Effects of Group Size and Lack of Sphericity on the Recovery of Clusters in K-means Cluster Analysis.

PubMed

Craen, Saskia de; Commandeur, Jacques J F; Frank, Laurence E; Heiser, Willem J

2006-06-01

K-means cluster analysis is known for its tendency to produce spherical and equally sized clusters. To assess the magnitude of these effects, a simulation study was conducted, in which populations were created with varying departures from sphericity and group sizes. An analysis of the recovery of clusters in the samples taken from these populations showed a significant effect of lack of sphericity and group size. This effect was, however, not as large as expected, with still a recovery index of more than 0.5 in the "worst case scenario." An interaction effect between the two data aspects was also found. The decreasing trend in the recovery of clusters for increasing departures from sphericity is different for equal and unequal group sizes.

Network Analysis Tools: from biological networks to clusters and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Clustering analysis for muon tomography data elaboration in the Muon Portal project

NASA Astrophysics Data System (ADS)

Bandieramonte, M.; Antonuccio-Delogu, V.; Becciani, U.; Costa, A.; La Rocca, P.; Massimino, P.; Petta, C.; Pistagna, C.; Riggi, F.; Riggi, S.; Sciacca, E.; Vitello, F.

2015-05-01

Clustering analysis is one of multivariate data analysis techniques which allows to gather statistical data units into groups, in order to minimize the logical distance within each group and to maximize the one between different groups. In these proceedings, the authors present a novel approach to the muontomography data analysis based on clustering algorithms. As a case study we present the Muon Portal project that aims to build and operate a dedicated particle detector for the inspection of harbor containers to hinder the smuggling of nuclear materials. Clustering techniques, working directly on scattering points, help to detect the presence of suspicious items inside the container, acting, as it will be shown, as a filter for a preliminary analysis of the data.

[Analysis on HIV-1 subtypes and transmission clusters in newly reported HIV/AIDS cases in Yiwu, Zhejiang Province, 2016].

PubMed

Zhang, J F; Yao, J M; Fan, Q; Chen, W J; Pan, X H; Ding, X B; Yang, J Z; Fu, T

2017-12-10

Objective: To understand the characteristics of distribution on HIV-1 subtypes and the transmission clusters in Yiwu in Zhejiang province. Methods: A cross-sectional study of molecular epidemiology was carried out on newly reported HIV/AIDS cases in Yiwu. RNA was extracted from 168 plasma samples, followed by RT-PCR and nest-PCR for pol gene amplification, sequencing, phylogenetic tree construction used for analyzing the subtypes and transmission clusters. Mutations on drug resistance was analyzed by CPR 6.0 online tool. Results: Subjects were mainly males (86.3%, 145/168), with average age as (39.1±13.4) years old and most of them were migrants (66.7%, 112/168). The major routes of transmission included homosexual (51.2%, 86/168) and heterosexual (48.8%, 82/168) contacts. The rate of success for sequence acquisition was 89.9% (151/168). The dominant subtypes showed as CRF01_AE (74, 49.0%) and CRF07_BC (64, 42.4%), followed by CRF08_BC (5, 3.3%), CRF55_01B (3, 2.0%), each case of subtype B, CRF45_cpx, CRF59_01B, CRF85_BC and URF (B/C). CRF45_cpx and CRF85_BC were discovered the first time in Zhejiang province. Twenty-six transmission clusters involving 65 cases were found, with the total clustered rate as 43.0% (65/151), in which the CRF01_AE clustered rate appeared as 54.1% (40/74), higher than that of CRF07_BC (21/64, 32.8%). The average size of cluster was 2.5 cases/cluster, with average size of cluster in CRF01_AE patients infected through heterosexual transmission as the largest (3.5 cases/cluster). The prevalence of transmitted drug resistance was 4.6% (7/151). Seven cases with surveillance drug resistant mutations (SDRM) were found, including 5 cases of M46L (3.3%), and one case of F77L or Y181C. Conclusion: HIV genetic diversity and a variety of transmission clusters had been noticed in this study area (Yiwu). Programs on monitoring the subtypes and transmission clusters should be continued and strengthened.

Space-time analysis of Down syndrome: results consistent with transient pre-disposing contagious agent.

PubMed

McNally, Richard J Q; Rankin, Judith; Shirley, Mark D F; Rushton, Stephen P; Pless-Mulloli, Tanja

2008-10-01

Whilst maternal age is an established risk factor for Patau syndrome (trisomy 13), Edwards syndrome (trisomy 18) and Down syndrome (trisomy 21), the aetiology and contribution of genetic and environmental factors remains unclear. We analysed for space-time clustering using high quality fully population-based data from a geographically defined region. The study included all cases of Patau, Edwards and Down syndrome, delivered during 1985-2003 and resident in the former Northern Region of England, including terminations of pregnancy for fetal anomaly. We applied the K-function test for space-time clustering with fixed thresholds of close in space and time using residential addresses at time of delivery. The Knox test was used to indicate the range over which the clustering effect occurred. Tests were repeated using nearest neighbour (NN) thresholds to adjust for variable population density. The study analysed 116 cases of Patau syndrome, 240 cases of Edwards syndrome and 1084 cases of Down syndrome. There was evidence of space-time clustering for Down syndrome (fixed threshold of close in space: P = 0.01, NN threshold: P = 0.02), but little or no clustering for Patau (P = 0.57, P = 0.19) or Edwards (P = 0.37, P = 0.06) syndromes. Clustering of Down syndrome was associated with cases from more densely populated areas and evidence of clustering persisted when cases were restricted to maternal age <40 years. The highly novel space-time clustering for Down syndrome suggests an aetiological role for transient environmental factors, such as infections.

Ongoing large measles outbreak with nosocomial transmission in Milan, northern Italy, March-August 2017.

PubMed

Amendola, Antonella; Bianchi, Silvia; Frati, Elena R; Ciceri, Giulia; Faccini, Marino; Senatore, Sabrina; Colzani, Daniela; Lamberti, Anna; Baggieri, Melissa; Cereda, Danilo; Gramegna, Maria; Nicoletti, Loredana; Magurano, Fabio; Tanzi, Elisabetta

2017-08-17

A large measles outbreak has been ongoing in Milan and surrounding areas. From 1 March to 30 June 2017, 203 measles cases were laboratory-confirmed (108 sporadic cases and 95 related to 47 clusters). Phylogenetic analysis revealed the co-circulation of two different genotypes, D8 and B3. Both genotypes caused nosocomial clusters in two hospitals. The rapid analysis of epidemiological and phylogenetic data allowed effective surveillance and tracking of transmission pathways. This article is copyright of The Authors, 2017.

Ongoing large measles outbreak with nosocomial transmission in Milan, northern Italy, March–August 2017

PubMed Central

Amendola, Antonella; Bianchi, Silvia; Frati, Elena R; Ciceri, Giulia; Faccini, Marino; Senatore, Sabrina; Colzani, Daniela; Lamberti, Anna; Baggieri, Melissa; Cereda, Danilo; Gramegna, Maria; Nicoletti, Loredana; Magurano, Fabio; Tanzi, Elisabetta

2017-01-01

A large measles outbreak has been ongoing in Milan and surrounding areas. From 1 March to 30 June 2017, 203 measles cases were laboratory-confirmed (108 sporadic cases and 95 related to 47 clusters). Phylogenetic analysis revealed the co-circulation of two different genotypes, D8 and B3. Both genotypes caused nosocomial clusters in two hospitals. The rapid analysis of epidemiological and phylogenetic data allowed effective surveillance and tracking of transmission pathways. PMID:28840825

20 Years Spatial-Temporal Analysis of Dengue Fever and Hemorrhagic Fever in Mexico.

PubMed

Hernández-Gaytán, Sendy Isarel; Díaz-Vásquez, Francisco Javier; Duran-Arenas, Luis Gerardo; López Cervantes, Malaquías; Rothenberg, Stephen J

2017-10-01

Dengue Fever (DF) is a human vector-borne disease and a major public health problem worldwide. In Mexico, DF and Dengue Hemorrhagic Fever (DHF) cases have increased in recent years. The aim of this study was to identify variations in the spatial distribution of DF and DHF cases over time using space-time statistical analysis and geographic information systems. Official data of DF and DHF cases were obtained in 32 states from 1995-2015. Space-time scan statistics were used to determine the space-time clusters of DF and DHF cases nationwide, and a geographic information system was used to display the location of clusters. A total of 885,748 DF cases was registered of which 13.4% (n = 119,174) correspond to DHF in the 32 states from 1995-2015. The most likely cluster of DF (relative risk = 25.5) contained the states of Jalisco, Colima, and Nayarit, on the Pacific coast in 2009, and the most likely cluster of DHF (relative risk = 8.5) was in the states of Chiapas, Tabasco, Campeche, Oaxaca, Veracruz, Quintana Roo, Yucatán, Puebla, Morelos, and Guerrero principally on the Gulf coast over 2006-2015. The geographic distribution of DF and DHF cases has increased in recent years and cases are significantly clustered in two coastal areas (Pacific and Gulf of Mexico). This provides the basis for further investigation of risk factors as well as interventions in specific areas. Copyright © 2018 IMSS. Published by Elsevier Inc. All rights reserved.

Evaluating the Use of Multilocus Variable Number Tandem Repeat Analysis of Shiga Toxin-Producing Escherichia coli O157 as a Routine Public Health Tool in England

PubMed Central

Byrne, Lisa; Elson, Richard; Dallman, Timothy J.; Perry, Neil; Ashton, Philip; Wain, John; Adak, Goutam K.; Grant, Kathie A.; Jenkins, Claire

2014-01-01

Multilocus variable number tandem repeat analysis (MLVA) provides microbiological support for investigations of clusters of cases of infection with Shiga toxin-producing E. coli (STEC) O157. All confirmed STEC O157 isolated in England and submitted to the Gastrointestinal Bacteria Reference Unit (GBRU) during a six month period were typed using MLVA, with the aim of assessing the impact of this approach on epidemiological investigations. Of 539 cases investigated, 341 (76%) had unique (>2 single locus variants) MLVA profiles, 12% of profiles occurred more than once due to known household transmission and 12% of profiles occurred as part of 41 clusters, 21 of which were previously identified through routine public health investigation of cases. The remaining 20 clusters were not previously detected and STEC enhanced surveillance data for associated cases were retrospectively reviewed for epidemiological links including shared exposures, geography and/or time. Additional evidence of a link between cases was found in twelve clusters. Compared to phage typing, the number of sporadic cases was reduced from 69% to 41% and the diversity index for MLVA was 0.996 versus 0.782 for phage typing. Using MLVA generates more data on the spatial and temporal dispersion of cases, better defining the epidemiology of STEC infection than phage typing. The increased detection of clusters through MLVA typing highlights the challenges to health protection practices, providing a forerunner to the advent of whole genome sequencing as a diagnostic tool. PMID:24465775

Evaluating the use of multilocus variable number tandem repeat analysis of Shiga toxin-producing Escherichia coli O157 as a routine public health tool in England.

PubMed

Byrne, Lisa; Elson, Richard; Dallman, Timothy J; Perry, Neil; Ashton, Philip; Wain, John; Adak, Goutam K; Grant, Kathie A; Jenkins, Claire

2014-01-01

Multilocus variable number tandem repeat analysis (MLVA) provides microbiological support for investigations of clusters of cases of infection with Shiga toxin-producing E. coli (STEC) O157. All confirmed STEC O157 isolated in England and submitted to the Gastrointestinal Bacteria Reference Unit (GBRU) during a six month period were typed using MLVA, with the aim of assessing the impact of this approach on epidemiological investigations. Of 539 cases investigated, 341 (76%) had unique (>2 single locus variants) MLVA profiles, 12% of profiles occurred more than once due to known household transmission and 12% of profiles occurred as part of 41 clusters, 21 of which were previously identified through routine public health investigation of cases. The remaining 20 clusters were not previously detected and STEC enhanced surveillance data for associated cases were retrospectively reviewed for epidemiological links including shared exposures, geography and/or time. Additional evidence of a link between cases was found in twelve clusters. Compared to phage typing, the number of sporadic cases was reduced from 69% to 41% and the diversity index for MLVA was 0.996 versus 0.782 for phage typing. Using MLVA generates more data on the spatial and temporal dispersion of cases, better defining the epidemiology of STEC infection than phage typing. The increased detection of clusters through MLVA typing highlights the challenges to health protection practices, providing a forerunner to the advent of whole genome sequencing as a diagnostic tool.

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Gulgundi, Mohammad Shahid; Shetty, Amba

2018-03-01

Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water.

Cluster analysis of molecular simulation trajectories for systems where both conformation and orientation of the sampled states are important.

PubMed

Abramyan, Tigran M; Snyder, James A; Thyparambil, Aby A; Stuart, Steven J; Latour, Robert A

2016-08-05

Clustering methods have been widely used to group together similar conformational states from molecular simulations of biomolecules in solution. For applications such as the interaction of a protein with a surface, the orientation of the protein relative to the surface is also an important clustering parameter because of its potential effect on adsorbed-state bioactivity. This study presents cluster analysis methods that are specifically designed for systems where both molecular orientation and conformation are important, and the methods are demonstrated using test cases of adsorbed proteins for validation. Additionally, because cluster analysis can be a very subjective process, an objective procedure for identifying both the optimal number of clusters and the best clustering algorithm to be applied to analyze a given dataset is presented. The method is demonstrated for several agglomerative hierarchical clustering algorithms used in conjunction with three cluster validation techniques. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

2013 multistate outbreaks of Cyclospora cayetanensis infections associated with fresh produce: focus on the Texas investigations.

PubMed

Abanyie, F; Harvey, R R; Harris, J R; Wiegand, R E; Gaul, L; Desvignes-Kendrick, M; Irvin, K; Williams, I; Hall, R L; Herwaldt, B; Gray, E B; Qvarnstrom, Y; Wise, M E; Cantu, V; Cantey, P T; Bosch, S; DA Silva, A J; Fields, A; Bishop, H; Wellman, A; Beal, J; Wilson, N; Fiore, A E; Tauxe, R; Lance, S; Slutsker, L; Parise, M

2015-12-01

The 2013 multistate outbreaks contributed to the largest annual number of reported US cases of cyclosporiasis since 1997. In this paper we focus on investigations in Texas. We defined an outbreak-associated case as laboratory-confirmed cyclosporiasis in a person with illness onset between 1 June and 31 August 2013, with no history of international travel in the previous 14 days. Epidemiological, environmental, and traceback investigations were conducted. Of the 631 cases reported in the multistate outbreaks, Texas reported the greatest number of cases, 270 (43%). More than 70 clusters were identified in Texas, four of which were further investigated. One restaurant-associated cluster of 25 case-patients was selected for a case-control study. Consumption of cilantro was most strongly associated with illness on meal date-matched analysis (matched odds ratio 19·8, 95% confidence interval 4·0-∞). All case-patients in the other three clusters investigated also ate cilantro. Traceback investigations converged on three suppliers in Puebla, Mexico. Cilantro was the vehicle of infection in the four clusters investigated; the temporal association of these clusters with the large overall increase in cyclosporiasis cases in Texas suggests cilantro was the vehicle of infection for many other cases. However, the paucity of epidemiological and traceback information does not allow for a conclusive determination; moreover, molecular epidemiological tools for cyclosporiasis that could provide more definitive linkage between case clusters are needed.

Multiple imputation methods for bivariate outcomes in cluster randomised trials.

PubMed

DiazOrdaz, K; Kenward, M G; Gomes, M; Grieve, R

2016-09-10

Missing observations are common in cluster randomised trials. The problem is exacerbated when modelling bivariate outcomes jointly, as the proportion of complete cases is often considerably smaller than the proportion having either of the outcomes fully observed. Approaches taken to handling such missing data include the following: complete case analysis, single-level multiple imputation that ignores the clustering, multiple imputation with a fixed effect for each cluster and multilevel multiple imputation. We contrasted the alternative approaches to handling missing data in a cost-effectiveness analysis that uses data from a cluster randomised trial to evaluate an exercise intervention for care home residents. We then conducted a simulation study to assess the performance of these approaches on bivariate continuous outcomes, in terms of confidence interval coverage and empirical bias in the estimated treatment effects. Missing-at-random clustered data scenarios were simulated following a full-factorial design. Across all the missing data mechanisms considered, the multiple imputation methods provided estimators with negligible bias, while complete case analysis resulted in biased treatment effect estimates in scenarios where the randomised treatment arm was associated with missingness. Confidence interval coverage was generally in excess of nominal levels (up to 99.8%) following fixed-effects multiple imputation and too low following single-level multiple imputation. Multilevel multiple imputation led to coverage levels of approximately 95% throughout. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Identification of Urban Leprosy Clusters

PubMed Central

Paschoal, José Antonio Armani; Paschoal, Vania Del'Arco; Nardi, Susilene Maria Tonelli; Rosa, Patrícia Sammarco; Ismael, Manuela Gallo y Sanches; Sichieri, Eduvaldo Paulo

2013-01-01

Overpopulation of urban areas results from constant migrations that cause disordered urban growth, constituting clusters defined as sets of people or activities concentrated in relatively small physical spaces that often involve precarious conditions. Aim. Using residential grouping, the aim was to identify possible clusters of individuals in São José do Rio Preto, Sao Paulo, Brazil, who have or have had leprosy. Methods. A population-based, descriptive, ecological study using the MapInfo and CrimeStat techniques, geoprocessing, and space-time analysis evaluated the location of 425 people treated for leprosy between 1998 and 2010. Clusters were defined as concentrations of at least 8 people with leprosy; a distance of up to 300 meters between residences was adopted. Additionally, the year of starting treatment and the clinical forms of the disease were analyzed. Results. Ninety-eight (23.1%) of 425 geocoded cases were located within one of ten clusters identified in this study, and 129 cases (30.3%) were in the region of a second-order cluster, an area considered of high risk for the disease. Conclusion. This study identified ten clusters of leprosy cases in the city and identified an area of high risk for the appearance of new cases of the disease. PMID:24288467

Primary syphilis cases in Guangdong Province 1995-2008: opportunities for linking syphilis control and regional development.

PubMed

Yang, Li-Gang; Tucker, Joseph D; Yang, Bin; Shen, Song-Ying; Sun, Xi-Feng; Chen, Yong-Feng; Chen, Xiang-Sheng

2010-12-30

Syphilis cases have risen in many parts of China, with developed regions reporting the greatest share of cases. Since syphilis increases in these areas are likely driven by both increased screening and changes in sexual behaviours, distinguishing between these two factors is important. Examining municipal-level primary syphilis cases with spatial analysis allows a more direct understanding of changing sexual behaviours at a more policy-relevant level. In this study we examined all reported primary syphilis cases from Guangdong Province, a southern province in China, since the disease was first incorporated into the mandatory reporting system in 1995. Spatial autocorrelation statistics were used to correlate municipal-level clustering of reported primary syphilis cases and gross domestic product (GDP). A total of 52,036 primary syphilis cases were reported over the period 1995-2008, and the primary syphilis cases increased from 0.88 per 100,000 population in 1995 to 7.61 per 100,000 in 2008. The Pearl River Delta region has a disproportionate share (44.7%) of syphilis cases compared to other regions. Syphilis cases were spatially clustered (p = 0.01) and Moran's I analysis found that syphilis cases were clustered in municipalities with higher GDP (p = 0.004). Primary syphilis cases continue to increase in Guangdong Province, especially in the Pearl River Delta region. Considering the economic impact of syphilis and its tendency to spatially cluster, expanded syphilis testing in specific municipalities and further investigating the costs and benefits of syphilis screening are critical next steps.

Global, local and focused geographic clustering for case-control data with residential histories

PubMed Central

Jacquez, Geoffrey M; Kaufmann, Andy; Meliker, Jaymie; Goovaerts, Pierre; AvRuskin, Gillian; Nriagu, Jerome

2005-01-01

Background This paper introduces a new approach for evaluating clustering in case-control data that accounts for residential histories. Although many statistics have been proposed for assessing local, focused and global clustering in health outcomes, few, if any, exist for evaluating clusters when individuals are mobile. Methods Local, global and focused tests for residential histories are developed based on sets of matrices of nearest neighbor relationships that reflect the changing topology of cases and controls. Exposure traces are defined that account for the latency between exposure and disease manifestation, and that use exposure windows whose duration may vary. Several of the methods so derived are applied to evaluate clustering of residential histories in a case-control study of bladder cancer in south eastern Michigan. These data are still being collected and the analysis is conducted for demonstration purposes only. Results Statistically significant clustering of residential histories of cases was found but is likely due to delayed reporting of cases by one of the hospitals participating in the study. Conclusion Data with residential histories are preferable when causative exposures and disease latencies occur on a long enough time span that human mobility matters. To analyze such data, methods are needed that take residential histories into account. PMID:15784151

A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

PubMed

Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

2016-02-01

Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

Spatial distribution and cluster analysis of retail drug shop characteristics and antimalarial behaviors as reported by private medicine retailers in western Kenya: informing future interventions.

PubMed

Rusk, Andria; Highfield, Linda; Wilkerson, J Michael; Harrell, Melissa; Obala, Andrew; Amick, Benjamin

2016-02-19

Efforts to improve malaria case management in sub-Saharan Africa have shifted focus to private antimalarial retailers to increase access to appropriate treatment. Demands to decrease intervention cost while increasing efficacy requires interventions tailored to geographic regions with demonstrated need. Cluster analysis presents an opportunity to meet this demand, but has not been applied to the retail sector or antimalarial retailer behaviors. This research conducted cluster analysis on medicine retailer behaviors in Kenya, to improve malaria case management and inform future interventions. Ninety-seven surveys were collected from medicine retailers working in the Webuye Health and Demographic Surveillance Site. Survey items included retailer training, education, antimalarial drug knowledge, recommending behavior, sales, and shop characteristics, and were analyzed using Kulldorff's spatial scan statistic. The Bernoulli purely spatial model for binomial data was used, comparing cases to controls. Statistical significance of found clusters was tested with a likelihood ratio test, using the null hypothesis of no clustering, and a p value based on 999 Monte Carlo simulations. The null hypothesis was rejected with p values of 0.05 or less. A statistically significant cluster of fewer than expected pharmacy-trained retailers was found (RR = .09, p = .001) when compared to the expected random distribution. Drug recommending behavior also yielded a statistically significant cluster, with fewer than expected retailers recommending the correct antimalarial medication to adults (RR = .018, p = .01), and fewer than expected shops selling that medication more often than outdated antimalarials when compared to random distribution (RR = 0.23, p = .007). All three of these clusters were co-located, overlapping in the northwest of the study area. Spatial clustering was found in the data. A concerning amount of correlation was found in one specific region in the study area where multiple behaviors converged in space, highlighting a prime target for interventions. These results also demonstrate the utility of applying geospatial methods in the study of medicine retailer behaviors, making the case for expanding this approach to other regions.

Malaria control and prevention towards elimination: data from an eleven-year surveillance in Shandong Province, China.

PubMed

Kong, Xiangli; Liu, Xin; Tu, Hong; Xu, Yan; Niu, Jianbing; Wang, Yongbin; Zhao, Changlei; Kou, Jingxuan; Feng, Jun

2017-01-31

Shandong Province experienced a declining malaria trend of local-acquired transmission, but the increasing imported malaria remains a challenge. Therefore, understanding the epidemiological characteristics of malaria and the control and elimination strategy and interventions is needed for better planning to achieve the overall elimination goal in Shandong Province. A retrospective study was conducted and all individual cases from a web-based reporting system were reviewed and analysed to explore malaria-endemic characteristics in Shandong from 2005 to 2015. Annual malaria incidence reported in 2005-2015 were geo-coded and matched to the county-level. Spatial cluster analysis was performed to evaluate any identified spatial disease clusters for statistical significance. The space-time cluster was detected with high rates through the retrospective space-time analysis scanning using the discrete Poisson model. The overall malaria incidence decreased to a low level during 2005-2015. In total, 1564 confirmed malaria cases were reported, 27.1% of which (n = 424) were indigenous cases. Most of the indigenous case (n = 339, 80.0%) occurred from June to October. However, the number and scale of imported cases have been increased but no significant difference was observed during months. Shandong is endemic for both Plasmodium vivax (n = 730) and Plasmodium falciparum (n = 674). The disease is mainly distributed in Southern (n = 710) and Eastern region (n = 424) of Shandong, such as Jinning (n = 214 [13.7%]), Weihai (n = 151 [9.7%]), and Yantai (n = 107 [6.8%]). Furthermore, the spatial cluster analysis of malaria cases from 2005 to 2015 indicated that the diseased was not randomly distributed. For indigenous cases, a total of 15 and 2 high-risk counties were determined from 2005 to 2009 (control phase) and from 2010 to 2015 (elimination phase), respectively. For imported cases, a total of 26 and 29 high-risk counties were determined from 2005 to 2009 (control phase) and from 2010 to 2015 (elimination phase), respectively. The method of spatial scan statistics identified different 13 significant spatial clusters between 2005 and 2015. The space-time clustering analysis determined that the most likely cluster included 14 and 19 counties for indigenous and imported, respectively. In order to cope with the requirements of malaria elimination phase, the surveillance system should be strengthened particularity on the frequent migration regions as well as the effective multisectoral cooperation and coordination mechanisms. Specific response packages should be tailored among different types of cities and capacity building should also be improved mainly focus on the emergence response and case management. Fund guarantees for scientific research should be maintained both during the elimination and post-elimination phase to consolidate the achievements of malaria elimination.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadgu, Teklu; Appel, Gordon John

Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014) and Hadgu et al. (2015). The TSPA computing hardware (CL2014) and storage system described in Hadgu et al. (2015) were used for the currentmore » analysis. One floating license of GoldSim with Versions 9.60.300, 10.5 and 11.1.6 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA-type analysis on the server cluster. The current tasks included verification of the TSPA-LA uncertainty and sensitivity analyses, and preliminary upgrade of the TSPA-LA from Version 9.60.300 to the latest version 11.1. All the TSPA-LA uncertainty and sensitivity analyses modeling cases were successfully tested and verified for the model reproducibility on the upgraded 2014 server cluster (CL2014). The uncertainty and sensitivity analyses used TSPA-LA modeling cases output generated in FY15 based on GoldSim Version 9.60.300 documented in Hadgu et al. (2015). The model upgrade task successfully converted the Nominal Modeling case to GoldSim Version 11.1. Upgrade of the remaining of the modeling cases and distributed processing tasks will continue. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.« less

Quantifying the impact of fixed effects modeling of clusters in multiple imputation for cluster randomized trials

PubMed Central

Andridge, Rebecca. R.

2011-01-01

In cluster randomized trials (CRTs), identifiable clusters rather than individuals are randomized to study groups. Resulting data often consist of a small number of clusters with correlated observations within a treatment group. Missing data often present a problem in the analysis of such trials, and multiple imputation (MI) has been used to create complete data sets, enabling subsequent analysis with well-established analysis methods for CRTs. We discuss strategies for accounting for clustering when multiply imputing a missing continuous outcome, focusing on estimation of the variance of group means as used in an adjusted t-test or ANOVA. These analysis procedures are congenial to (can be derived from) a mixed effects imputation model; however, this imputation procedure is not yet available in commercial statistical software. An alternative approach that is readily available and has been used in recent studies is to include fixed effects for cluster, but the impact of using this convenient method has not been studied. We show that under this imputation model the MI variance estimator is positively biased and that smaller ICCs lead to larger overestimation of the MI variance. Analytical expressions for the bias of the variance estimator are derived in the case of data missing completely at random (MCAR), and cases in which data are missing at random (MAR) are illustrated through simulation. Finally, various imputation methods are applied to data from the Detroit Middle School Asthma Project, a recent school-based CRT, and differences in inference are compared. PMID:21259309

Cluster analysis of the clinical histories of cattle affected with bovine anaemia associated with Theileria orientalis Ikeda type infection.

PubMed

Lawrence, K E; Forsyth, S F; Vaatstra, B L; McFadden, Amj; Pulford, D J; Govindaraju, K; Pomroy, W E

2017-11-01

AIM To determine the most commonly used words in the clinical histories of animals naturally infected with Theileria orientalis Ikeda type; whether these words differed between cases categorised by age, farm type or haematocrit (HCT), and if there was any clustering of the common words in relation to these categories. METHODS Clinical histories were transcribed for 605 cases of bovine anaemia associated with T. orientalis (TABA), that were submitted to laboratories with blood samples which tested positive for T. orientalis Ikeda type infection by PCR analysis, between October 2012 and November 2014. χ 2 tests were used to determine whether the proportion of submissions for each word was similar across the categories of HCT (normal, moderate anaemia or severe anaemia), farm type (dairy or beef) and age (young or old). Correspondence analysis (CA) was carried out on a contingency table of the frequency of the 28 most commonly used history words, cross-tabulated by age categories (young, old or unknown). Agglomerative hierarchical clustering, using Ward's method, was then performed on the coordinates from the correspondence analysis. RESULTS The six most commonly used history words were jaundice (204/605), lethargic (162/605), pale mucous membranes (161/605), cow (151/605), anaemia (147/605), and off milk (115/605). The proportion of cases with some history words differed between categories of age, farm type and HCT. The cluster analysis indicated that the recorded history words were grouped in two main clusters. The first included the words weight loss, tachycardia, pale mucous membranes, anaemia, lethargic and thin, and was associated with adult (p<0.001), severe anaemia (p<0.001) and dairy (p<0.001). The second cluster included the words deaths, ill-thrift, calves, calf and diarrhoea, and was associated with young (p<0.001), normal HCT (p<0.001), beef (p<0.001) and moderate anaemia (p<0.001). CONCLUSIONS AND CLINICAL RELEVANCE Cluster analysis of words recorded in clinical histories submitted with blood samples from cases of TABA indicates that two potentially different disease syndromes were associated with T. orientalis Ikeda type infection. One was consistent with the affected cattle suffering from a severe regenerative extravascular haemolytic anaemia, the second displaying as ill thrift and diarrhoea, particularly in young beef cattle.

Geographical Analysis of the Distribution and Spread of Human Rabies in China from 2005 to 2011

PubMed Central

Yin, Wenwu; Yu, Hongjie; Si, Yali; Li, Jianhui; Zhou, Yuanchun; Zhou, Xiaoyan; Magalhães, Ricardo J. Soares.

2013-01-01

Background Rabies is a significant public health problem in China in that it records the second highest case incidence globally. Surveillance data on canine rabies in China is lacking and human rabies notifications can be a useful indicator of areas where animal and human rabies control could be integrated. Previous spatial epidemiological studies lacked adequate spatial resolution to inform targeted rabies control decisions. We aimed to describe the spatiotemporal distribution of human rabies and model its geographical spread to provide an evidence base to inform future integrated rabies control strategies in China. Methods We geo-referenced a total of 17,760 human rabies cases of China from 2005 to 2011. In our spatial analyses we used Gaussian kernel density analysis, average nearest neighbor distance, Spatial Temporal Density-Based Spatial Clustering of Applications with Noise and developed a model of rabies spatiotemporal spread. Findings Human rabies cases increased from 2005 to 2007 and decreased during 2008 to 2011 companying change of the spatial distribution. The ANN distance among human rabies cases increased between 2005 and 2011, and the degree of clustering of human rabies cases decreased during that period. A total 480 clusters were detected by ST-DBSCAN, 89.4% clusters initiated before 2007. Most of clusters were mainly found in South of China. The number and duration of cluster decreased significantly after 2008. Areas with the highest density of human rabies cases varied spatially each year and in some areas remained with high outbreak density for several years. Though few places have recovered from human rabies, most of affected places are still suffering from the disease. Conclusion Human rabies in mainland China is geographically clustered and its spatial extent changed during 2005 to 2011. The results provide a scientific basis for public health authorities in China to improve human rabies control and prevention program. PMID:23991098

[Analysis of 4 clustered high risk acute flaccid paralysis cases in Shanxi Province in 2006].

PubMed

Yan, Dong-mei; Zhang, Yong; Wang, Dong-yan

2010-04-01

Analysis of epidemiology of 4 clustered high risk acute flaccid paralysis(AFP) cases reported by Shanxi province in 2006 and VP1 gene characteristic for type III poliovirus isolated from the four AFP cases. Virus isolation and identification were conducted according to the 4th edition of WHO polio laboratory manual. The sequence of VP1 region were amplified and sequenced. The phylogenetic trees based on VP1 region were constructed. Three of four high risk AFP cases were suspected as vaccine associated paralysis poliomyelitis (VAPP), the onset date of them were close. VP1 sequencing of the four type III isolates revealed that the identity were 99.7%, 99.9%, 99.4% and 99.9% respectively compared with vaccine reference strain-BJOPV3. According to WHO criteria, the four isolates were identified as type III vaccine-related poliovirus. Phylogenetic analysis based on VP1 coding sequence showed that the four type III poliovirus were not related significantly. The type III poliovirus isolated from 3 suspected VAPP cases shared one nucleotide mutation at 2637 (C-->U), which result in the amino acid mutation from Val into Ala. The improvement of laboratory surveillance for clustered high risk AFP cases should be strengthened so as to detect and prevent poliovirus circulation timely.

Emergy-based comparative analysis on industrial clusters: economic and technological development zone of Shenyang area, China.

PubMed

Liu, Zhe; Geng, Yong; Zhang, Pan; Dong, Huijuan; Liu, Zuoxi

2014-09-01

In China, local governments of many areas prefer to give priority to the development of heavy industrial clusters in pursuit of high value of gross domestic production (GDP) growth to get political achievements, which usually results in higher costs from ecological degradation and environmental pollution. Therefore, effective methods and reasonable evaluation system are urgently needed to evaluate the overall efficiency of industrial clusters. Emergy methods links economic and ecological systems together, which can evaluate the contribution of ecological products and services as well as the load placed on environmental systems. This method has been successfully applied in many case studies of ecosystem but seldom in industrial clusters. This study applied the methodology of emergy analysis to perform the efficiency of industrial clusters through a series of emergy-based indices as well as the proposed indicators. A case study of Shenyang Economic Technological Development Area (SETDA) was investigated to show the emergy method's practical potential to evaluate industrial clusters to inform environmental policy making. The results of our study showed that the industrial cluster of electric equipment and electronic manufacturing produced the most economic value and had the highest efficiency of energy utilization among the four industrial clusters. However, the sustainability index of the industrial cluster of food and beverage processing was better than the other industrial clusters.

Identification of clusters of individuals relevant to temporomandibular disorders and other chronic pain conditions: the OPPERA study

PubMed Central

Bair, Eric; Gaynor, Sheila; Slade, Gary D.; Ohrbach, Richard; Fillingim, Roger B.; Greenspan, Joel D.; Dubner, Ronald; Smith, Shad B.; Diatchenko, Luda; Maixner, William

2016-01-01

The classification of most chronic pain disorders gives emphasis to anatomical location of the pain to distinguish one disorder from the other (eg, back pain vs temporomandibular disorder [TMD]) or to define subtypes (eg, TMD myalgia vs arthralgia). However, anatomical criteria overlook etiology, potentially hampering treatment decisions. This study identified clusters of individuals using a comprehensive array of biopsychosocial measures. Data were collected from a case–control study of 1031 chronic TMD cases and 3247 TMD-free controls. Three subgroups were identified using supervised cluster analysis (referred to as the adaptive, pain-sensitive, and global symptoms clusters). Compared with the adaptive cluster, participants in the pain-sensitive cluster showed heightened sensitivity to experimental pain, and participants in the global symptoms cluster showed both greater pain sensitivity and greater psychological distress. Cluster membership was strongly associated with chronic TMD: 91.5% of TMD cases belonged to the pain-sensitive and global symptoms clusters, whereas 41.2% of controls belonged to the adaptive cluster. Temporomandibular disorder cases in the pain-sensitive and global symptoms clusters also showed greater pain intensity, jaw functional limitation, and more comorbid pain conditions. Similar results were obtained when the same methodology was applied to a smaller case–control study consisting of 199 chronic TMD cases and 201 TMD-free controls. During a median 3-year follow-up period of TMD-free individuals, participants in the global symptoms cluster had greater risk of developing first-onset TMD (hazard ratio = 2.8) compared with participants in the other 2 clusters. Cross-cohort predictive modeling was used to demonstrate the reliability of the clusters. PMID:26928952

Serratia marcescens Bacteremia: Nosocomial Cluster Following Narcotic Diversion.

PubMed

Schuppener, Leah M; Pop-Vicas, Aurora E; Brooks, Erin G; Duster, Megan N; Crnich, Christopher J; Sterkel, Alana K; Webb, Aaron P; Safdar, Nasia

2017-09-01

OBJECTIVE To describe the investigation and control of a cluster of Serratia marcescens bacteremia in a 505-bed tertiary-care center. METHODS Cluster cases were defined as all patients with S. marcescens bacteremia between March 2 and April 7, 2014, who were found to have identical or related blood isolates determined by molecular typing with pulsed-field gel electrophoresis. Cases were compared using bivariate analysis with controls admitted at the same time and to the same service as the cases, in a 4:1 ratio. RESULTS In total, 6 patients developed S. marcescens bacteremia within 48 hours after admission within the above period. Of these, 5 patients had identical Serratia isolates determined by molecular typing, and were included in a case-control study. Exposure to the post-anesthesia care unit was a risk factor identified in bivariate analysis. Evidence of tampered opioid-containing syringes on several hospital units was discovered soon after the initial cluster case presented, and a full narcotic diversion investigation was conducted. A nurse working in the post-anesthesia care unit was identified as the employee responsible for the drug diversion and was epidemiologically linked to all 5 patients in the cluster. No further cases were identified once the implicated employee's job was terminated. CONCLUSION Illicit drug use by healthcare workers remains an important mechanism for the development of bloodstream infections in hospitalized patients. Active mechanisms and systems should remain in place to prevent, detect, and control narcotic drug diversions and associated patient harm in the healthcare setting. Infect Control Hosp Epidemiol 2017;38:1027-1031.

Identification of a current hot spot of HIV type 1 transmission in Mongolia by molecular epidemiological analysis.

PubMed

Davaalkham, Jagdagsuren; Unenchimeg, Puntsag; Baigalmaa, Chultem; Erdenetuya, Gombo; Nyamkhuu, Dulmaa; Shiino, Teiichiro; Tsuchiya, Kiyoto; Hayashida, Tsunefusa; Gatanaga, Hiroyuki; Oka, Shinichi

2011-10-01

We investigated the current molecular epidemiological status of HIV-1 in Mongolia, a country with very low incidence of HIV-1 though with rapid expansion in recent years. HIV-1 pol (1065 nt) and env (447 nt) genes were sequenced to construct phylogenetic trees. The evolutionary rates, molecular clock phylogenies, and other evolutionary parameters were estimated from heterochronous genomic sequences of HIV-1 subtype B by the Bayesian Markov chain Monte Carlo method. We obtained 41 sera from 56 reported HIV-1-positive cases as of May 2009. The main route of infection was men who have sex with men (MSM). Dominant subtypes were subtype B in 32 cases (78%) followed by subtype CRF02_AG (9.8%). The phylogenetic analysis of the pol gene identified two clusters in subtype B sequences. Cluster 1 consisted of 21 cases including MSM and other routes of infection, and cluster 2 consisted of eight MSM cases. The tree analyses demonstrated very short branch lengths in cluster 1, suggesting a surprisingly active expansion of HIV-1 transmission during a short period with the same ancestor virus. Evolutionary analysis indicated that the outbreak started around the early 2000s. This study identified a current hot spot of HIV-1 transmission and potential seed of the epidemic in Mongolia. Comprehensive preventive measures targeting this group are urgently needed.

DICON: interactive visual analysis of multidimensional clusters.

PubMed

Cao, Nan; Gotz, David; Sun, Jimeng; Qu, Huamin

2011-12-01

Clustering as a fundamental data analysis technique has been widely used in many analytic applications. However, it is often difficult for users to understand and evaluate multidimensional clustering results, especially the quality of clusters and their semantics. For large and complex data, high-level statistical information about the clusters is often needed for users to evaluate cluster quality while a detailed display of multidimensional attributes of the data is necessary to understand the meaning of clusters. In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information. We further develop a novel layout algorithm which can generate similar icons for similar clusters, making comparisons of clusters easier. User interaction and clutter reduction are integrated into the system to help users more effectively analyze and refine clustering results for large datasets. We demonstrate the power of DICON through a user study and a case study in the healthcare domain. Our evaluation shows the benefits of the technique, especially in support of complex multidimensional cluster analysis. © 2011 IEEE

Extreme weather events and environmental contamination are associated with case-clusters of melioidosis in the Northern Territory of Australia.

PubMed

Cheng, Allen C; Jacups, Susan P; Gal, Daniel; Mayo, Mark; Currie, Bart J

2006-04-01

Melioidosis, the infection due to the environmental organism Burkholderia pseudomallei, is endemic to northern Australia and South East Asia. It is associated with exposure to mud and pooled surface water, but environmental determinants of this disease are poorly understood. We defined case-clusters in northern Australia, determined their contribution to the observed rate of melioidosis, and explored clinical features and associated environmental factors. Using geographical information systems data, we examined clustering of melioidosis cases in time and geographical space in the Top End of the Northern Territory of Australia between 1990 and 2002 using a scan statistic. DNA macrorestriction analysis, resolved by pulsed field gel electrophoresis, was performed on isolates from patients. We defined five case-clusters involving 27 patients that occurred within 7-28 days and/or a radius of 100-300 km. Clustered cases were associated with extreme weather events or environmental contamination; no difference in the clinical pattern of disease was noted from other patients not involved in clusters. Isolates from patients linked to environmental contamination were caused by isolates with similar DNA macrorestriction patterns, but isolates from patients linked to severe weather events had more diverse DNA macrorestriction patterns. Case-clusters of melioidosis where isolates exhibit diverse DNA macrorestriction patterns in our region are linked to extreme weather events and outbreaks where isolates are predominantly of the same DNA macrorestriction pattern are linked with contamination of an environmental source.

Investigating a cluster of Legionnaires' cases: public health implications.

PubMed

Carr, R; Warren, R; Towers, L; Bartholomew, A; Duggal, H V; Rehman, Y; Harrison, T G; Olowokure, B

2010-06-01

To describe the multidisciplinary investigation and management of a rapidly increasing number of cases of Legionnaires' disease in the North Shropshire area, UK during August 2006. Epidemiological and environmental investigation of a cluster of cases of Legionnaires' disease. Outbreak investigation included: agreeing case definitions; case finding; epidemiological survey; identification and environmental investigation of potential sources; microbiological analysis of clinical and environmental samples; mapping the location of potential sources; and the movement and residence of cases. Three cases of Legionnaires' disease were admitted to a local hospital between 30 and 31 August 2006. Two of these cases were Shropshire residents, with the third living in Wales. A fourth case was also identified which, it was thought, may have been linked to this cluster as the patient had a history of travel to the same area as the two Shropshire residents. Over the next few weeks, three more cases were identified, two of whom were admitted to hospital. Subsequent detailed environmental, epidemiological and microbiological investigation did not support the hypothesis that any of these cases could be linked to a common source. The results of this investigation strongly suggest that a single source was not responsible for the cluster, and it was concluded that this incident was a pseudo-outbreak. This investigation serves as a reminder that clusters can and do occur, and that an apparent outbreak may be a collection of sporadic cases distinguishable only by rigorous epidemiological, environmental and microbiological investigation. Copyright 2010. Published by Elsevier Ltd.

Spatial-temporal clustering of companion animal enteric syndrome: detection and investigation through the use of electronic medical records from participating private practices.

PubMed

Anholt, R M; Berezowski, J; Robertson, C; Stephen, C

2015-09-01

There is interest in the potential of companion animal surveillance to provide data to improve pet health and to provide early warning of environmental hazards to people. We implemented a companion animal surveillance system in Calgary, Alberta and the surrounding communities. Informatics technologies automatically extracted electronic medical records from participating veterinary practices and identified cases of enteric syndrome in the warehoused records. The data were analysed using time-series analyses and a retrospective space-time permutation scan statistic. We identified a seasonal pattern of reports of occurrences of enteric syndromes in companion animals and four statistically significant clusters of enteric syndrome cases. The cases within each cluster were examined and information about the animals involved (species, age, sex), their vaccination history, possible exposure or risk behaviour history, information about disease severity, and the aetiological diagnosis was collected. We then assessed whether the cases within the cluster were unusual and if they represented an animal or public health threat. There was often insufficient information recorded in the medical record to characterize the clusters by aetiology or exposures. Space-time analysis of companion animal enteric syndrome cases found evidence of clustering. Collection of more epidemiologically relevant data would enhance the utility of practice-based companion animal surveillance.

Developing appropriate methods for cost-effectiveness analysis of cluster randomized trials.

PubMed

Gomes, Manuel; Ng, Edmond S-W; Grieve, Richard; Nixon, Richard; Carpenter, James; Thompson, Simon G

2012-01-01

Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering--seemingly unrelated regression (SUR) without a robust standard error (SE)--and 4 methods that recognized clustering--SUR and generalized estimating equations (GEEs), both with robust SE, a "2-stage" nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92-0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters.

Fuzzy Clustering Analysis in Environmental Impact Assessment--A Complement Tool to Environmental Quality Index.

ERIC Educational Resources Information Center

Kung, Hsiang-Te; And Others

1993-01-01

In spite of rapid progress achieved in the methodological research underlying environmental impact assessment (EIA), the problem of weighting various parameters has not yet been solved. This paper presents a new approach, fuzzy clustering analysis, which is illustrated with an EIA case study on Baoshan-Wusong District in Shanghai, China. (Author)

Spatio-temporal pattern of sylvatic rabies in the Sultanate of Oman, 2006-2010.

PubMed

Hussain, Muhammad Hammad; Ward, Michael P; Body, Mohammed; Al-Rawahi, Abdulmajeed; Wadir, Ali Awlad; Al-Habsi, Saif; Saqib, Muhammad; Ahmed, Mohammed Sayed; Almaawali, Mahir Gharib

2013-07-01

Rabies was first reported in the Sultanate of Oman is 1990. We analysed passive surveillance data (444 samples) collected and reported between 2006 and 2010. During this period, between 45 and 75% of samples submitted from suspect animals were subsequently confirmed (fluorescent antibody test, histopathology and reverse transcription PCR) as rabies cases. Overall, 63% of submitted samples were confirmed as rabies cases. The spatial distribution of species-specific cases were similar (centred in north-central Oman with a northeast-southwest distribution), although fox cases had a wider distribution and an east-west orientation. Clustering of cases was detected using interpolation, local spatial autocorrelation and scan statistical analysis. Several local government areas (wilayats) in north-central Oman were identified where higher than expected numbers of laboratory-confirmed rabies cases were reported. For fox rabies, more clusters (local spatial autocorrelation analysis) and a larger clustered area (scan statistical analysis) were detected. In Oman, monthly reports of fox rabies cases were highly correlated (rSP>0.5) with reports of camel, cattle, sheep and goat rabies. The best-fitting ARIMA model included a seasonality component. Fox rabies cases reported 6 months previously best explained rabies reported cases in other animal species. Despite likely reporting bias, results suggest that rabies exists as a sylvatic cycle of transmission in Oman and an opportunity still exists to prevent establishment of dog-mediated rabies. Copyright © 2013 Elsevier B.V. All rights reserved.

Retrospective space-time cluster analysis of whooping cough, re-emergence in Barcelona, Spain, 2000-2011.

PubMed

Solano, Rubén; Gómez-Barroso, Diana; Simón, Fernando; Lafuente, Sarah; Simón, Pere; Rius, Cristina; Gorrindo, Pilar; Toledo, Diana; Caylà, Joan A

2014-05-01

A retrospective, space-time study of whooping cough cases reported to the Public Health Agency of Barcelona, Spain between the years 2000 and 2011 is presented. It is based on 633 individual whooping cough cases and the 2006 population census from the Spanish National Statistics Institute, stratified by age and sex at the census tract level. Cluster identification was attempted using space-time scan statistic assuming a Poisson distribution and restricting temporal extent to 7 days and spatial distance to 500 m. Statistical calculations were performed with Stata 11 and SatScan and mapping was performed with ArcGis 10.0. Only clusters showing statistical significance (P <0.05) were mapped. The most likely cluster identified included five census tracts located in three neighbourhoods in central Barcelona during the week from 17 to 23 August 2011. This cluster included five cases compared with the expected level of 0.0021 (relative risk = 2436, P <0.001). In addition, 11 secondary significant space-time clusters were detected with secondary clusters occurring at different times and localizations. Spatial statistics is felt to be useful by complementing epidemiological surveillance systems through visualizing excess in the number of cases in space and time and thus increase the possibility of identifying outbreaks not reported by the surveillance system.

Two Introductions of Lyme Disease into Connecticut: A Geospatial Analysis of Human Cases from 1984 to 2012.

PubMed

Xue, Ling; Scoglio, Caterina; McVey, D Scott; Boone, Rebecca; Cohnstaedt, Lee W

2015-09-01

Lyme disease has become the most prevalent vector-borne disease in the United States and results in morbidity in humans, especially children. We used historical case distributions to explain vector-borne disease introductions and subsequent geographic expansion in the absence of disease vector data. We used geographic information system analysis of publicly available Connecticut Department of Public Health case data from 1984, 1985, and 1991 to 2012 for the 169 towns in Connecticut to identify the yearly clusters of Lyme disease cases. Our analysis identified the spatial and temporal origins of two separate introductions of Lyme disease into Connecticut and identified the subsequent direction and rate of spread. We defined both epidemic clusters of cases using significant long-term spatial autocorrelation. The incidence-weighted geographic mean analysis indicates a northern trend of geographic expansion for both epidemic clusters. In eastern Connecticut, as the epidemic progressed, the yearly shift in the geographic mean (rate of epidemic expansion) decreased each year until spatial equilibrium was reached in 2007. The equilibrium indicates a transition from epidemic Lyme disease spread to stable endemic transmission, and we associate this with a reduction in incidence. In western Connecticut, the parabolic distribution of the yearly geographic mean indicates that following the establishment of Lyme disease (1988) the epidemic quickly expanded northward and established equilibrium in 2009.

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.

PubMed

Wardenaar, K J; van Loo, H M; Cai, T; Fava, M; Gruber, M J; Li, J; de Jonge, P; Nierenberg, A A; Petukhova, M V; Rose, S; Sampson, N A; Schoevers, R A; Wilcox, M A; Alonso, J; Bromet, E J; Bunting, B; Florescu, S E; Fukao, A; Gureje, O; Hu, C; Huang, Y Q; Karam, A N; Levinson, D; Medina Mora, M E; Posada-Villa, J; Scott, K M; Taib, N I; Viana, M C; Xavier, M; Zarkov, Z; Kessler, R C

2014-11-01

Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question. Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes. Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors. Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

Spatial patterns in electoral wards with high lymphoma incidence in Yorkshire health region.

PubMed Central

Barnes, N.; Cartwright, R. A.; O'Brien, C.; Roberts, B.; Richards, I. D.; Bird, C. C.

1987-01-01

The possibilities of clustering between those electoral wards which display higher than expected incidences of cases of the lymphomas occurring between 1978 and 1982 are examined. Clusters are defined as being those wards with cases in excess (at a probability of less than 10%) which are geographically adjacent to each other. A separate analysis extends the definition of cluster to include high incidence wards that are adjacent or separated by one other ward. The results indicate that many high incidence lymphoma wards do occur close together and when computer simulations are used to compute expected results, many of the observed results are shown to be highly improbable both in the overall number of clustering wards and in the largest number of wards comprising a 'cluster'. PMID:3663469

Extended phenotype and clinical subgroups in unilateral Meniere disease: A cross-sectional study with cluster analysis.

PubMed

Frejo, L; Martin-Sanz, E; Teggi, R; Trinidad, G; Soto-Varela, A; Santos-Perez, S; Manrique, R; Perez, N; Aran, I; Almeida-Branco, M S; Batuecas-Caletrio, A; Fraile, J; Espinosa-Sanchez, J M; Perez-Guillen, V; Perez-Garrigues, H; Oliva-Dominguez, M; Aleman, O; Benitez, J; Perez, P; Lopez-Escamez, J A

2017-12-01

To define clinical subgroups by cluster analysis in patients with unilateral Meniere disease (MD) and to compare them with the clinical subgroups found in bilateral MD. A cross-sectional study with a two-step cluster analysis. A tertiary referral multicenter study. Nine hundred and eighty-eight adult patients with unilateral MD. best predictors to define clinical subgroups with potential different aetiologies. We established five clusters in unilateral MD. Group 1 is the most frequently found, includes 53% of patients, and it is defined as the sporadic, classic MD without migraine and without autoimmune disorder (AD). Group 2 is found in 8% of patients, and it is defined by hearing loss, which antedates the vertigo episodes by months or years (delayed MD), without migraine or AD in most of cases. Group 3 involves 13% of patients, and it is considered familial MD, while group 4, which includes 15% of patients, is linked to the presence of migraine in all cases. Group 5 is found in 11% of patients and is defined by a comorbid AD. We found significant differences in the distribution of AD in clusters 3, 4 and 5 between patients with uni- and bilateral MD. Cluster analysis defines clinical subgroups in MD, and it extends the phenotype beyond audiovestibular symptoms. This classification will help to improve the phenotyping in MD and facilitate the selection of patients for randomised clinical trials. © 2017 John Wiley & Sons Ltd.

Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Ju; Chang, Hang; Giricz, Orsi

Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associationsmore » with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPAR? has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPAR? has been validated through two supporting biological assays.« less

Emergence of sporadic non-clustered cases of hospital-associated listeriosis among immunocompromised adults in southern Taiwan from 1992 to 2013: effect of precipitating immunosuppressive agents.

PubMed

Lee, Chun-Yuan; Tsai, Hung-Chin; Kunin, Calvin M; Lee, Susan Shin-Jung; Wu, Kuan-Sheng; Chen, Yao-Shen

2014-03-19

Sporadic non-clustered hospital-associated listeriosis is an emerging infectious disease in immunocompromised hosts. The current study was designed to determine the impact of long-term and precipitating immunosuppressive agents and underlying diseases on triggering the expression of the disease, and to compare the clinical features and outcome of hospital-associated and community-associated listeriosis. We reviewed the medical records of all patients with Listeria monocytogenes isolated from sterile body sites at a large medical center in southern Taiwan during 1992-2013. Non-clustered cases were defined as those unrelated to any other in time or place. Multivariable regression analysis was used to determine factors associated with prognosis. Thirty-five non-clustered cases of listeriosis were identified. Twelve (34.2%) were hospital-associated, and 23 (65.7%) were community-associated. The 60-day mortality was significantly greater in hospital-associated than in community-associated cases (66.7% vs. 17.4%, p = 0.007). Significantly more hospital-associated than community-associated cases were treated with a precipitating immunosuppressive agent within 4 weeks prior to onset of listeriosis (91.7% vs. 4.3%, respectively p < 0.001). The median period from the start of precipitating immunosuppressive treatment to the onset of listeriosis-related symptoms was 12 days (range, 4-27 days) in 11 of the 12 hospital-associated cases. In the multivariable analysis, APACHE II score >21 (p = 0.04) and receipt of precipitating immunosuppressive therapy (p = 0.02) were independent risk factors for 60-day mortality. Sporadic non-clustered hospital-associated listeriosis needs to be considered in the differential diagnosis of sepsis in immunocompromised patients, particularly in those treated with new or increased doses of immunosuppressive agents.

The spatio-temporal mapping of epileptic networks: Combination of EEG–fMRI and EEG source imaging

PubMed Central

Vulliemoz, S.; Thornton, R.; Rodionov, R.; Carmichael, D.W.; Guye, M.; Lhatoo, S.; McEvoy, A.W.; Spinelli, L.; Michel, C.M.; Duncan, J.S.; Lemieux, L.

2009-01-01

Simultaneous EEG–fMRI acquisitions in patients with epilepsy often reveal distributed patterns of Blood Oxygen Level Dependant (BOLD) change correlated with epileptiform discharges. We investigated if electrical source imaging (ESI) performed on the interictal epileptiform discharges (IED) acquired during fMRI acquisition could be used to study the dynamics of the networks identified by the BOLD effect, thereby avoiding the limitations of combining results from separate recordings. Nine selected patients (13 IED types identified) with focal epilepsy underwent EEG–fMRI. Statistical analysis was performed using SPM5 to create BOLD maps. ESI was performed on the IED recorded during fMRI acquisition using a realistic head model (SMAC) and a distributed linear inverse solution (LAURA). ESI could not be performed in one case. In 10/12 remaining studies, ESI at IED onset (ESIo) was anatomically close to one BOLD cluster. Interestingly, ESIo was closest to the positive BOLD cluster with maximal statistical significance in only 4/12 cases and closest to negative BOLD responses in 4/12 cases. Very small BOLD clusters could also have clinical relevance in some cases. ESI at later time frame (ESIp) showed propagation to remote sources co-localised with other BOLD clusters in half of cases. In concordant cases, the distance between maxima of ESI and the closest EEG–fMRI cluster was less than 33 mm, in agreement with previous studies. We conclude that simultaneous ESI and EEG–fMRI analysis may be able to distinguish areas of BOLD response related to initiation of IED from propagation areas. This combination provides new opportunities for investigating epileptic networks. PMID:19408351

Epidemiological analysis of Salmonella clusters identified by whole genome sequencing, England and Wales 2014.

PubMed

Waldram, Alison; Dolan, Gayle; Ashton, Philip M; Jenkins, Claire; Dallman, Timothy J

2018-05-01

The unprecedented level of bacterial strain discrimination provided by whole genome sequencing (WGS) presents new challenges with respect to the utility and interpretation of the data. Whole genome sequences from 1445 isolates of Salmonella belonging to the most commonly identified serotypes in England and Wales isolated between April and August 2014 were analysed. Single linkage single nucleotide polymorphism thresholds at the 10, 5 and 0 level were explored for evidence of epidemiological links between clustered cases. Analysis of the WGS data organised 566 of the 1445 isolates into 32 clusters of five or more. A statistically significant epidemiological link was identified for 17 clusters. The clusters were associated with foreign travel (n = 8), consumption of Chinese takeaways (n = 4), chicken eaten at home (n = 2), and one each of the following; eating out, contact with another case in the home and contact with reptiles. In the same time frame, one cluster was detected using traditional outbreak detection methods. WGS can be used for the highly specific and highly sensitive detection of biologically related isolates when epidemiological links are obscured. Improvements in the collection of detailed, standardised exposure information would enhance cluster investigations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial Analysis of Hemorrhagic Fever with Renal Syndrome in Zibo City, China, 2009–2012

PubMed Central

Wang, Ling; Yang, Shuxia; Zhang, Ling; Cao, Haixia; Zhang, Yan; Hu, Haodong; Zhai, Shenyong

2013-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China, where human cases account for 90% of the total global cases. Zibo City is one of the most serious affected areas in Shandong Province China with the HFRS incidence increasing sharply from 2009 to 2012. However, the hotspots of HFRS in Zibo remained unclear. Thus, a spatial analysis was conducted with the aim to explore the spatial, spatial-temporal and seasonal patterns of HFRS in Zibo from 2009 to 2012, and to provide guidance for formulating regional prevention and control strategies. Methods The study was based on the reported cases of HFRS from the National Notifiable Disease Surveillance System. Annualized incidence maps and seasonal incidence maps were produced to analyze the spatial and seasonal distribution of HFRS in Zibo City. Then spatial scan statistics and space-time scan statistics were conducted to identify clusters of HFRS. Results There were 200 cases reported in Zibo City during the 4-year study period. One most likely cluster and one secondary cluster for high incidence of HFRS were identified by the space-time analysis. And the most likely cluster was found to exist at Yiyuan County in October to December 2012. The human infections in the fall and winter reflected a seasonal characteristic pattern of Hantaan virus (HTNV) transmission. The secondary cluster was detected at the center of Zibo in May to June 2009, presenting a seasonal characteristic of Seoul virus (SEOV) transmission. Conclusion To control and prevent HFRS in Zibo city, the comprehensive preventive strategy should be implemented in the southern areas of Zibo in autumn and in the northern areas of Zibo in spring. PMID:23840719

Cluster mass profile reconstruction with size and flux magnification on the HST STAGES survey.

PubMed

Duncan, Christopher A J; Heymans, Catherine; Heavens, Alan F; Joachimi, Benjamin

2016-03-21

We present the first measurement of individual cluster mass estimates using weak lensing size and flux magnification. Using data from the HST STAGES (Space Telescope A901/902 Galaxy Evolution Survey) survey of the A901/902 supercluster we detect the four known groups in the supercluster at high significance using magnification alone. We discuss the application of a fully Bayesian inference analysis, and investigate a broad range of potential systematics in the application of the method. We compare our results to a previous weak lensing shear analysis of the same field finding the recovered signal-to-noise of our magnification-only analysis to range from 45 to 110 per cent of the signal-to-noise in the shear-only analysis. On a case-by-case basis we find consistent magnification and shear constraints on cluster virial radius, and finding that for the full sample, magnification constraints to be a factor 0.77 ± 0.18 lower than the shear measurements.

Identification and characterization of near-fatal asthma phenotypes by cluster analysis.

PubMed

Serrano-Pariente, J; Rodrigo, G; Fiz, J A; Crespo, A; Plaza, V

2015-09-01

Near-fatal asthma (NFA) is a heterogeneous clinical entity and several profiles of patients have been described according to different clinical, pathophysiological and histological features. However, there are no previous studies that identify in a unbiased way--using statistical methods such as clusters analysis--different phenotypes of NFA. Therefore, the aim of the present study was to identify and to characterize phenotypes of near fatal asthma using a cluster analysis. Over a period of 2 years, 33 Spanish hospitals enrolled 179 asthmatics admitted for an episode of NFA. A cluster analysis using two-steps algorithm was performed from data of 84 of these cases. The analysis defined three clusters of patients with NFA: cluster 1, the largest, including older patients with clinical and therapeutic criteria of severe asthma; cluster 2, with an high proportion of respiratory arrest (68%), impaired consciousness level (82%) and mechanical ventilation (93%); and cluster 3, which included younger patients, characterized by an insufficient anti-inflammatory treatment and frequent sensitization to Alternaria alternata and soybean. These results identify specific asthma phenotypes involved in NFA, confirming in part previous findings observed in studies with a clinical approach. The identification of patients with a specific NFA phenotype could suggest interventions to prevent future severe asthma exacerbations. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entomologic and molecular investigation into Plasmodium vivax transmission in Singapore, 2009.

PubMed

Ng, Lee-Ching; Lee, Kim-Sung; Tan, Cheong-Huat; Ooi, Peng-Lim; Lam-Phua, Sai-Gek; Lin, Raymond; Pang, Sook-Cheng; Lai, Yee-Ling; Solhan, Suhana; Chan, Pei-Pei; Wong, Kit-Yin; Ho, Swee-Tuan; Vythilingam, Indra

2010-10-29

Singapore has been certified malaria free since November 1982 by the World Health Organization and despite occasional local transmission, the country has maintained the standing. In 2009, three clusters of malaria cases were reported in Singapore. Epidemiological, entomological and molecular studies were carried out to investigate the three clusters, namely Mandai-Sungei Kadut, Jurong Island and Sembawang. A total of 29 malaria patients, with no recent travel history, were reported in the three clusters. Molecular analysis based on the msp3α and msp1 genes showed two independent local transmissions: one in Mandai-Sungei Kadut and another in Sembawang. Almost all cases within each cluster were epidemiologically linked. In Jurong Island cluster, epidemiological link remains uncertain, as almost all cases had a unique genetic profile. Only two cases shared a common profile and were found to be linked to the Mandai-Sungei Kadut cluster. Entomological investigation found Anopheles sinensis to be the predominant Anopheline in the two areas where local transmission of P. vivax was confirmed. Anopheles sinensis was found to be attracted to human bait and bites as early as 19:45 hrs. However, all Anopheles mosquitoes caught were negative for sporozoites and oocysts by dissection. Investigation of P. vivax cases from the three cluster areas confirmed the occurrence of local transmission in two areas. Although An. sinensis was the predominant Anopheline found in areas with confirmed transmission, the vector/s responsible for the outbreaks still remains cryptic.

Developing Appropriate Methods for Cost-Effectiveness Analysis of Cluster Randomized Trials

PubMed Central

Gomes, Manuel; Ng, Edmond S.-W.; Nixon, Richard; Carpenter, James; Thompson, Simon G.

2012-01-01

Aim. Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Methods. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering—seemingly unrelated regression (SUR) without a robust standard error (SE)—and 4 methods that recognized clustering—SUR and generalized estimating equations (GEEs), both with robust SE, a “2-stage” nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Results. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92–0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. Conclusions. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters. PMID:22016450

Calibrating the Planck cluster mass scale with CLASH

NASA Astrophysics Data System (ADS)

Penna-Lima, M.; Bartlett, J. G.; Rozo, E.; Melin, J.-B.; Merten, J.; Evrard, A. E.; Postman, M.; Rykoff, E.

2017-08-01

We determine the mass scale of Planck galaxy clusters using gravitational lensing mass measurements from the Cluster Lensing And Supernova survey with Hubble (CLASH). We have compared the lensing masses to the Planck Sunyaev-Zeldovich (SZ) mass proxy for 21 clusters in common, employing a Bayesian analysis to simultaneously fit an idealized CLASH selection function and the distribution between the measured observables and true cluster mass. We used a tiered analysis strategy to explicitly demonstrate the importance of priors on weak lensing mass accuracy. In the case of an assumed constant bias, bSZ, between true cluster mass, M500, and the Planck mass proxy, MPL, our analysis constrains 1-bSZ = 0.73 ± 0.10 when moderate priors on weak lensing accuracy are used, including a zero-mean Gaussian with standard deviation of 8% to account for possible bias in lensing mass estimations. Our analysis explicitly accounts for possible selection bias effects in this calibration sourced by the CLASH selection function. Our constraint on the cluster mass scale is consistent with recent results from the Weighing the Giants program and the Canadian Cluster Comparison Project. It is also consistent, at 1.34σ, with the value needed to reconcile the Planck SZ cluster counts with Planck's base ΛCDM model fit to the primary cosmic microwave background anisotropies.

Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014.

PubMed

Acharya, Bipin Kumar; Cao, ChunXiang; Lakes, Tobia; Chen, Wei; Naeem, Shahid

2016-08-22

Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to fill this gap by analyzing spatiotemporal patterns based on monthly surveillance data aggregated at district. Dengue cases from 2010 to 2014 at district level were collected from the Nepal government's health and mapping agencies respectively. GeoDa software was used to map crude incidence, excess hazard and spatially smoothed incidence. Cluster analysis was performed in SaTScan software to explore spatiotemporal clusters of dengue during the above-mentioned time period. Spatiotemporal distribution of dengue fever in Nepal from 2010 to 2014 was mapped at district level in terms of crude incidence, excess risk and spatially smoothed incidence. Results show that the distribution of dengue fever was not random but clustered in space and time. Chitwan district was identified as the most likely cluster and Jhapa district was the first secondary cluster in both spatial and spatiotemporal scan. July to September of 2010 was identified as a significant temporal cluster. This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

Immature MEF2C-dysregulated T-cell leukemia patients have an early T-cell precursor acute lymphoblastic leukemia gene signature and typically have non-rearranged T-cell receptors

PubMed Central

Zuurbier, Linda; Gutierrez, Alejandro; Mullighan, Charles G.; Canté-Barrett, Kirsten; Gevaert, A. Olivier; de Rooi, Johan; Li, Yunlei; Smits, Willem K.; Buijs-Gladdines, Jessica G.C.A.M.; Sonneveld, Edwin; Look, A. Thomas; Horstmann, Martin; Pieters, Rob; Meijerink, Jules P.P.

2014-01-01

Three distinct immature T-cell acute lymphoblastic leukemia entities have been described including cases that express an early T-cell precursor immunophenotype or expression profile, immature MEF2C-dysregulated T-cell acute lymphoblastic leukemia cluster cases based on gene expression analysis (immature cluster) and cases that retain non-rearranged TRG@ loci. Early T-cell precursor acute lymphoblastic leukemia cases exclusively overlap with immature cluster samples based on the expression of early T-cell precursor acute lymphoblastic leukemia signature genes, indicating that both are featuring a single disease entity. Patients lacking TRG@ rearrangements represent only 40% of immature cluster cases, but no further evidence was found to suggest that cases with absence of bi-allelic TRG@ deletions reflect a distinct and even more immature disease entity. Immature cluster/early T-cell precursor acute lymphoblastic leukemia cases are strongly enriched for genes expressed in hematopoietic stem cells as well as genes expressed in normal early thymocyte progenitor or double negative-2A T-cell subsets. Identification of early T-cell precursor acute lymphoblastic leukemia cases solely by defined immunophenotypic criteria strongly underestimates the number of cases that have a corresponding gene signature. However, early T-cell precursor acute lymphoblastic leukemia samples correlate best with a CD1 negative, CD4 and CD8 double negative immunophenotype with expression of CD34 and/or myeloid markers CD13 or CD33. Unlike various other studies, immature cluster/early T-cell precursor acute lymphoblastic leukemia patients treated on the COALL-97 protocol did not have an overall inferior outcome, and demonstrated equal sensitivity levels to most conventional therapeutic drugs compared to other pediatric T-cell acute lymphoblastic leukemia patients. PMID:23975177

Spatial analysis of malaria in Anhui province, China

PubMed Central

Zhang, Wenyi; Wang, Liping; Fang, Liqun; Ma, Jiaqi; Xu, Youfu; Jiang, Jiafu; Hui, Fengming; Wang, Jianjun; Liang, Song; Yang, Hong; Cao, Wuchun

2008-01-01

Background Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province. Methods The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level. Results The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria (P < 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively. Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region. PMID:18847489

An Approach to Cluster EU Member States into Groups According to Pathways of Salmonella in the Farm-to-Consumption Chain for Pork Products.

PubMed

Vigre, Håkan; Domingues, Ana Rita Coutinho Calado; Pedersen, Ulrik Bo; Hald, Tine

2016-03-01

The aim of the project as the cluster analysis was to in part to develop a generic structured quantitative microbiological risk assessment (QMRA) model of human salmonellosis due to pork consumption in EU member states (MSs), and the objective of the cluster analysis was to group the EU MSs according to the relative contribution of different pathways of Salmonella in the farm-to-consumption chain of pork products. In the development of the model, by selecting a case study MS from each cluster the model was developed to represent different aspects of pig production, pork production, and consumption of pork products across EU states. The objective of the cluster analysis was to aggregate MSs into groups of countries with similar importance of different pathways of Salmonella in the farm-to-consumption chain using available, and where possible, universal register data related to the pork production and consumption in each country. Based on MS-specific information about distribution of (i) small and large farms, (ii) small and large slaughterhouses, (iii) amount of pork meat consumed, and (iv) amount of sausages consumed we used nonhierarchical and hierarchical cluster analysis to group the MSs. The cluster solutions were validated internally using statistic measures and externally by comparing the clustered MSs with an estimated human incidence of salmonellosis due to pork products in the MSs. Finally, each cluster was characterized qualitatively using the centroids of the clusters. © 2016 Society for Risk Analysis.

Changing cluster composition in cluster randomised controlled trials: design and analysis considerations

PubMed Central

2014-01-01

Background There are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition. To illustrate this, we focus on the issue of cluster merging, considering the impact on the design, analysis and interpretation of trial outcomes. Methods We explored the effects of merging clusters on study power using standard methods of power calculation. We assessed the potential impacts on study findings of both homogeneous cluster merges (involving clusters randomised to the same arm of a trial) and heterogeneous merges (involving clusters randomised to different arms of a trial) by simulation. To determine the impact on bias and precision of treatment effect estimates, we applied standard methods of analysis to different populations under analysis. Results Cluster merging produced a systematic reduction in study power. This effect depended on the number of merges and was most pronounced when variability in cluster size was at its greatest. Simulations demonstrate that the impact on analysis was minimal when cluster merges were homogeneous, with impact on study power being balanced by a change in observed intracluster correlation coefficient (ICC). We found a decrease in study power when cluster merges were heterogeneous, and the estimate of treatment effect was attenuated. Conclusions Examples of cluster merges found in previously published reports of cluster randomised trials were typically homogeneous rather than heterogeneous. Simulations demonstrated that trial findings in such cases would be unbiased. However, simulations also showed that any heterogeneous cluster merges would introduce bias that would be hard to quantify, as well as having negative impacts on the precision of estimates obtained. Further methodological development is warranted to better determine how to analyse such trials appropriately. Interim recommendations include avoidance of cluster merges where possible, discontinuation of clusters following heterogeneous merges, allowance for potential loss of clusters and additional variability in cluster size in the original sample size calculation, and use of appropriate ICC estimates that reflect cluster size. PMID:24884591

Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles.

PubMed

Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F; Perez, Danny

2017-10-21

Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.

Cluster analysis of accelerated molecular dynamics simulations: A case study of the decahedron to icosahedron transition in Pt nanoparticles

NASA Astrophysics Data System (ADS)

Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F.; Perez, Danny

2017-10-01

Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.

Predicting lower mantle heterogeneity from 4-D Earth models

NASA Astrophysics Data System (ADS)

Flament, Nicolas; Williams, Simon; Müller, Dietmar; Gurnis, Michael; Bower, Dan J.

2016-04-01

The Earth's lower mantle is characterized by two large-low-shear velocity provinces (LLSVPs), approximately ˜15000 km in diameter and 500-1000 km high, located under Africa and the Pacific Ocean. The spatial stability and chemical nature of these LLSVPs are debated. Here, we compare the lower mantle structure predicted by forward global mantle flow models constrained by tectonic reconstructions (Bower et al., 2015) to an analysis of five global tomography models. In the dynamic models, spanning 230 million years, slabs subducting deep into the mantle deform an initially uniform basal layer containing 2% of the volume of the mantle. Basal density, convective vigour (Rayleigh number Ra), mantle viscosity, absolute plate motions, and relative plate motions are varied in a series of model cases. We use cluster analysis to classify a set of equally-spaced points (average separation ˜0.45°) on the Earth's surface into two groups of points with similar variations in present-day temperature between 1000-2800 km depth, for each model case. Below ˜2400 km depth, this procedure reveals a high-temperature cluster in which mantle temperature is significantly larger than ambient and a low-temperature cluster in which mantle temperature is lower than ambient. The spatial extent of the high-temperature cluster is in first-order agreement with the outlines of the African and Pacific LLSVPs revealed by a similar cluster analysis of five tomography models (Lekic et al., 2012). Model success is quantified by computing the accuracy and sensitivity of the predicted temperature clusters in predicting the low-velocity cluster obtained from tomography (Lekic et al., 2012). In these cases, the accuracy varies between 0.61-0.80, where a value of 0.5 represents the random case, and the sensitivity ranges between 0.18-0.83. The largest accuracies and sensitivities are obtained for models with Ra ≈ 5 x 107, no asthenosphere (or an asthenosphere restricted to the oceanic domain), and a basal layer ˜ 4% denser than ambient mantle. Increasing convective vigour (Ra ≈ 5 x 108) or decreasing the density of the basal layer decreases both the accuracy and sensitivity of the predicted lower mantle structure. References: D. J. Bower, M. Gurnis, N. Flament, Assimilating lithosphere and slab history in 4-D Earth models. Phys. Earth Planet. Inter. 238, 8-22 (2015). V. Lekic, S. Cottaar, A. Dziewonski, B. Romanowicz, Cluster analysis of global lower mantle tomography: A new class of structure and implications for chemical heterogeneity. Earth Planet. Sci. Lett. 357, 68-77 (2012).

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

PubMed Central

2015-01-01

Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

K-means cluster analysis of tourist destination in special region of Yogyakarta using spatial approach and social network analysis (a case study: post of @explorejogja instagram account in 2016)

NASA Astrophysics Data System (ADS)

Iswandhani, N.; Muhajir, M.

2018-03-01

This research was conducted in Department of Statistics Islamic University of Indonesia. The data used are primary data obtained by post @explorejogja instagram account from January until December 2016. In the @explorejogja instagram account found many tourist destinations that can be visited by tourists both in the country and abroad, Therefore it is necessary to form a cluster of existing tourist destinations based on the number of likes from user instagram assumed as the most popular. The purpose of this research is to know the most popular distribution of tourist spot, the cluster formation of tourist destinations, and central popularity of tourist destinations based on @explorejogja instagram account in 2016. Statistical analysis used is descriptive statistics, k-means clustering, and social network analysis. The results of this research were obtained the top 10 most popular destinations in Yogyakarta, map of html-based tourist destination distribution consisting of 121 tourist destination points, formed 3 clusters each consisting of cluster 1 with 52 destinations, cluster 2 with 9 destinations and cluster 3 with 60 destinations, and Central popularity of tourist destinations in the special region of Yogyakarta by district.

Data depth based clustering analysis

DOE PAGES

Jeong, Myeong -Hun; Cai, Yaping; Sullivan, Clair J.; ...

2016-01-01

Here, this paper proposes a new algorithm for identifying patterns within data, based on data depth. Such a clustering analysis has an enormous potential to discover previously unknown insights from existing data sets. Many clustering algorithms already exist for this purpose. However, most algorithms are not affine invariant. Therefore, they must operate with different parameters after the data sets are rotated, scaled, or translated. Further, most clustering algorithms, based on Euclidean distance, can be sensitive to noises because they have no global perspective. Parameter selection also significantly affects the clustering results of each algorithm. Unlike many existing clustering algorithms, themore » proposed algorithm, called data depth based clustering analysis (DBCA), is able to detect coherent clusters after the data sets are affine transformed without changing a parameter. It is also robust to noises because using data depth can measure centrality and outlyingness of the underlying data. Further, it can generate relatively stable clusters by varying the parameter. The experimental comparison with the leading state-of-the-art alternatives demonstrates that the proposed algorithm outperforms DBSCAN and HDBSCAN in terms of affine invariance, and exceeds or matches the ro-bustness to noises of DBSCAN or HDBSCAN. The robust-ness to parameter selection is also demonstrated through the case study of clustering twitter data.« less

Personalized Medicine in Veterans with Traumatic Brain Injuries

DTIC Science & Technology

2013-05-01

Pair-Group Method using Arithmetic averages ( UPGMA ) based on cosine correlation of row mean centered log2 signal values; this was the top 50%-tile...cluster- ing was performed by the UPGMA method using Cosine correlation as the similarity metric. For comparative purposes, clustered heat maps included...non-mTBI cases were subjected to unsupervised hierarchical clustering analysis using the UPGMA algorithm with cosine correlation as the similarity

Personalized Medicine in Veterans with Traumatic Brain Injuries

DTIC Science & Technology

2014-07-01

9 control cases are subjected to unsupervised hierarchical clustering analysis using the UPGMA algorithm with cosine correlation as the similarity...in unsu- pervised hierarchical clustering by the Un- weighted Pair-Group Method using Arithmetic averages ( UPGMA ) based on cosine correlation of row...of log2 trans- formed MAS5.0 signal values; probe set cluster- ing was performed by the UPGMA method using Cosine correlation as the similarity

Consanguinity and family clustering of male factor infertility in Lebanon.

PubMed

Inhorn, Marcia C; Kobeissi, Loulou; Nassar, Zaher; Lakkis, Da'ad; Fakih, Michael H

2009-04-01

To investigate the influence of consanguineous marriage on male factor infertility in Lebanon, where rates of consanguineous marriage remain high (29.6% among Muslims, 16.5% among Christians). Clinic-based, case-control study, using reproductive history, risk factor interview, and laboratory-based semen analysis. Two IVF clinics in Beirut, Lebanon, during an 8-month period (January-August 2003). One hundred twenty infertile male patients and 100 fertile male controls, distinguished by semen analysis and reproductive history. None. Standard clinical semen analysis. The rates of consanguineous marriage were relatively high among the study sample. Patients (46%) were more likely than controls (37%) to report first-degree (parental) and second-degree (grandparental) consanguinity. The study demonstrated a clear pattern of family clustering of male factor infertility, with patients significantly more likely than controls to report infertility among close male relatives (odds ratio = 2.58). Men with azoospermia and severe oligospermia showed high rates of both consanguinity (50%) and family clustering (41%). Consanguineous marriage is a socially supported institution throughout the Muslim world, yet its relationship to infertility is poorly understood. This study demonstrated a significant association between consanguinity and family clustering of male factor infertility cases, suggesting a strong genetic component.

A CLIPS expert system for clinical flow cytometry data analysis

NASA Technical Reports Server (NTRS)

Salzman, G. C.; Duque, R. E.; Braylan, R. C.; Stewart, C. C.

1990-01-01

An expert system is being developed using CLIPS to assist clinicians in the analysis of multivariate flow cytometry data from cancer patients. Cluster analysis is used to find subpopulations representing various cell types in multiple datasets each consisting of four to five measurements on each of 5000 cells. CLIPS facts are derived from results of the clustering. CLIPS rules are based on the expertise of Drs. Stewart, Duque, and Braylan. The rules incorporate certainty factors based on case histories.

Evaluation of data quality, timeliness and acceptability of the tuberculosis surveillance system in Brazil's micro-regions.

PubMed

Silva, Gabriela Drummond Marques da; Bartholomay, Patrícia; Cruz, Oswaldo Gonçalves; Garcia, Leila Posenato

2017-10-01

This study aimed to evaluate quality, acceptability and timeliness of the data in the tuberculosis surveillance system in Brazilian micro-regions. An ecological cross-sectional study was carried out, after a qualitative stage for selecting indicators. All 558 Brazilian micro-regions were used as units of analysis. Data available in the National Notifiable Diseases Information System (SINAN), from 2012 to 2014, were used to calculate 14 indicators relating to four attributes: completeness, consistency, timeliness and acceptability. The study made use of cluster analysis to group micro-regions according to acceptability and timeliness. Three clusters were identified among the 473 micro-regions with optimal or regular completeness (70% to 100%) and with over five notifications. Cluster 1 (n = 109) presented mean timeliness of notification and treatment equal to 62.8% and 24.9%, respectively. Cluster 2 (n = 143) had a mean percentage of cases tested for HIV equal to 55.9%. Cluster 3 (n = 221) had the best performing tuberculosis indicators. Results suggest priority areas for improving surveillance of tuberculosis, predominantly in the central-north part of the country. They also point to the need to increase the timeliness of treatment and the percentage of cases tested for HIV.

ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices.

PubMed

Wilderjans, Tom F; Ceulemans, Eva; Van Mechelen, Iven; Depril, Dirk

2011-03-01

In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix.

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

PubMed

Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

2018-01-01

In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

Phonologic errors as a clinical marker of the logopenic variant of PPA.

PubMed

Leyton, Cristian E; Ballard, Kirrie J; Piguet, Olivier; Hodges, John R

2014-05-06

To disentangle the clinical heterogeneity of nonsemantic variants of primary progressive aphasia (PPA) and to identify a coherent linguistic-anatomical marker for the logopenic variant of PPA (lv-PPA). Key speech and language features of 14 cases of lv-PPA and 18 cases of nonfluent/agrammatic variant of PPA were systematically evaluated and scored by an independent rater blinded to diagnosis. Every case underwent a structural MRI and a Pittsburgh compound B (PiB)-PET scan, a putative biomarker of Alzheimer disease. Key speech and language features that showed association with the PiB-PET status were entered into a hierarchical cluster analysis. The linguistic features and patterns of cortical thinning in each resultant cluster were analyzed. The cluster analysis revealed 3 coherent clinical groups, each of which was linked to a specific PiB-PET status. The first cluster was linked to high PiB retention and characterized by phonologic errors and cortical thinning focused on the left superior temporal gyrus. The second and third clusters were characterized by grammatical production errors and motor speech disorders, respectively, and were associated with low PiB brain retention. A fourth cluster, however, demonstrated nonspecific language deficits and unpredictable PiB-PET status. These findings suggest that despite the clinical and pathologic heterogeneity of nonsemantic variants, discrete clinical syndromes can be distinguished and linked to specific likelihood of PiB-PET status. Phonologic errors seem to be highly predictive of high amyloid burden in PPA and can provide a specific clinical marker for lv-PPA.

Detection of neonatal unit clusters of Candida parapsilosis fungaemia by microsatellite genotyping: Results from laboratory-based sentinel surveillance, South Africa, 2009-2010.

PubMed

Magobo, Rindidzani E; Naicker, Serisha D; Wadula, Jeannette; Nchabeleng, Maphoshane; Coovadia, Yacoob; Hoosen, Anwar; Lockhart, Shawn R; Govender, Nelesh P

2017-05-01

Neonatal candidaemia is a common, deadly and costly hospital-associated disease. To determine the genetic diversity of Candida parapsilosis causing fungaemia in South African neonatal intensive care units (NICUs). From February 2009 through to August 2010, cases of candidaemia were reported through laboratory-based surveillance. C. parapsilosis isolates from neonatal cases were submitted for identification by internal transcribed spacer (ITS) region sequencing, antifungal susceptibility testing and microsatellite genotyping. Cluster analysis was performed using Unweighted Pair Group Method with Arithmetic Mean (UPGMA). Of 1671 cases with a viable Candida isolate, 393 (24%) occurred among neonates. Isolates from 143 neonatal cases were confirmed as C. parapsilosis sensu stricto. Many isolates were resistant to fluconazole (77/143; 54%) and voriconazole (20/143; 14%). Of 79 closely-related genotypes, 18 were represented by ≥2 isolates; 61 genotypes had a single isolate each. Seven clusters, comprised of 82 isolates, were identified at five hospitals in three provinces. Isolates belonging to certain clusters were significantly more likely to be fluconazole resistant: all cluster 7 isolates and the majority of cluster 4 (78%), 5 (89%) and 6 (67%) isolates (P<.001). Candida parapsilosis-associated candidaemia in public-sector NICUs was caused by closely related genotypes and there was molecular evidence of undetected outbreaks as well as intra-hospital transmission. © 2017 Blackwell Verlag GmbH.

Limitations of cytochrome oxidase I for the barcoding of Neritidae (Mollusca: Gastropoda) as revealed by Bayesian analysis.

PubMed

Chee, S Y

2015-05-25

The mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) gene has been universally and successfully utilized as a barcoding gene, mainly because it can be amplified easily, applied across a wide range of taxa, and results can be obtained cheaply and quickly. However, in rare cases, the gene can fail to distinguish between species, particularly when exposed to highly sensitive methods of data analysis, such as the Bayesian method, or when taxa have undergone introgressive hybridization, over-splitting, or incomplete lineage sorting. Such cases require the use of alternative markers, and nuclear DNA markers are commonly used. In this study, a dendrogram produced by Bayesian analysis of an mtDNA COI dataset was compared with that of a nuclear DNA ATPS-α dataset, in order to evaluate the efficiency of COI in barcoding Malaysian nerites (Neritidae). In the COI dendrogram, most of the species were in individual clusters, except for two species: Nerita chamaeleon and N. histrio. These two species were placed in the same subcluster, whereas in the ATPS-α dendrogram they were in their own subclusters. Analysis of the ATPS-α gene also placed the two genera of nerites (Nerita and Neritina) in separate clusters, whereas COI gene analysis placed both genera in the same cluster. Therefore, in the case of the Neritidae, the ATPS-α gene is a better barcoding gene than the COI gene.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties

NASA Astrophysics Data System (ADS)

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-01

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi4, NLi5, CLi6, BLI7 and Al12Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability (β ) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties.

PubMed

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-25

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi 4 , NLi 5 , CLi 6 , BLI 7 and Al 12 Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability ([Formula: see text]) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Chaos theory perspective for industry clusters development

NASA Astrophysics Data System (ADS)

Yu, Haiying; Jiang, Minghui; Li, Chengzhang

2016-03-01

Industry clusters have outperformed in economic development in most developing countries. The contributions of industrial clusters have been recognized as promotion of regional business and the alleviation of economic and social costs. It is no doubt globalization is rendering clusters in accelerating the competitiveness of economic activities. In accordance, many ideas and concepts involve in illustrating evolution tendency, stimulating the clusters development, meanwhile, avoiding industrial clusters recession. The term chaos theory is introduced to explain inherent relationship of features within industry clusters. A preferred life cycle approach is proposed for industrial cluster recessive theory analysis. Lyapunov exponents and Wolf model are presented for chaotic identification and examination. A case study of Tianjin, China has verified the model effectiveness. The investigations indicate that the approaches outperform in explaining chaos properties in industrial clusters, which demonstrates industrial clusters evolution, solves empirical issues and generates corresponding strategies.

Fascioliasis risk factors and space-time clusters in domestic ruminants in Bangladesh.

PubMed

Rahman, A K M Anisur; Islam, S K Shaheenur; Talukder, Md Hasanuzzaman; Hassan, Md Kumrul; Dhand, Navneet K; Ward, Michael P

2017-05-08

A retrospective observational study was conducted to identify fascioliasis hotspots, clusters, potential risk factors and to map fascioliasis risk in domestic ruminants in Bangladesh. Cases of fascioliasis in cattle, buffalo, sheep and goats from all districts in Bangladesh between 2011 and 2013 were identified via secondary surveillance data from the Department of Livestock Services' Epidemiology Unit. From each case report, date of report, species affected and district data were extracted. The total number of domestic ruminants in each district was used to calculate fascioliasis cases per ten thousand animals at risk per district, and this was used for cluster and hotspot analysis. Clustering was assessed with Moran's spatial autocorrelation statistic, hotspots with the local indicator of spatial association (LISA) statistic and space-time clusters with the scan statistic (Poisson model). The association between district fascioliasis prevalence and climate (temperature, precipitation), elevation, land cover and water bodies was investigated using a spatial regression model. A total of 1,723,971 cases of fascioliasis were reported in the three-year study period in cattle (1,164,560), goats (424,314), buffalo (88,924) and sheep (46,173). A total of nine hotspots were identified; one of these persisted in each of the three years. Only two local clusters were found. Five space-time clusters located within 22 districts were also identified. Annual risk maps of fascioliasis cases correlated with the hotspots and clusters detected. Cultivated and managed (P < 0.001) and artificial surface (P = 0.04) land cover areas, and elevation (P = 0.003) were positively and negatively associated with fascioliasis in Bangladesh, respectively. Results indicate that due to land use characteristics some areas of Bangladesh are at greater risk of fascioliasis. The potential risk factors, hot spots and clusters identified in this study can be used to guide science-based treatment and control decisions for fascioliasis in Bangladesh and in other similar geo-climatic zones throughout the world.

Comprehensive analysis of cutaneous T-cell lymphoma (CTCL) incidence and mortality in Canada reveals changing trends and geographic clustering for this malignancy.

PubMed

Ghazawi, Feras M; Netchiporouk, Elena; Rahme, Elham; Tsang, Matthew; Moreau, Linda; Glassman, Steven; Provost, Nathalie; Gilbert, Martin; Jean, Sara-Elizabeth; Pehr, Kevin; Sasseville, Denis; Litvinov, Ivan V

2017-09-15

Previous reports of geographic clustering of cutaneous T-cell lymphoma (CTCL) in Texas, Pittsburgh, and Sweden as well as the occurrence of CTCL in married couples and family members raise a possibility of the existence of an external and potentially preventable trigger(s) for this rare skin cancer. The authors studied CTCL incidence and mortality in Canada using 3 distinct population-based cancer databases. Data on patients' sex, age at the time of diagnosis, subtype of CTCL malignancy, reporting province, city, and postal code were analyzed. CTCL cases were mapped across Canada using geographic information systems software. In total, 6685 patients with CTCL were identified in Canada during 1992 through 2010 (CTCL incidence rate, 11.32 cases per million individuals per year), of which 58% were males. The mean age at diagnosis was 59.4 ± 21.5 years. Geographic analysis of patients revealed increased CTCL incidence on the provincial and city levels in several eastern provinces and in Manitoba. An analysis according to postal codes (Forward Sortation Area [FSA]) identified select communities in which several high-incidence FSAs were contiguous or adjacent. Several of these FSAs were located in industrial regions of Canadian cities. Conversely, 3 of 8 low-incidence FSAs were clustered in Ottawa, Ontario, which has very little industrial presence. An analysis of CTCL mortality in Canada corroborated the current incidence findings. The current results provide a comprehensive analysis of CTCL burden in Canada and highlight several important areas of geographic case clustering. These findings argue that industrial exposures may play an important role in promoting CTCL pathogenesis. Cancer 2017;123:3550-67. © 2017 American Cancer Society. © 2017 American Cancer Society.

Parallel and Scalable Clustering and Classification for Big Data in Geosciences

NASA Astrophysics Data System (ADS)

Riedel, M.

2015-12-01

Machine learning, data mining, and statistical computing are common techniques to perform analysis in earth sciences. This contribution will focus on two concrete and widely used data analytics methods suitable to analyse 'big data' in the context of geoscience use cases: clustering and classification. From the broad class of available clustering methods we focus on the density-based spatial clustering of appliactions with noise (DBSCAN) algorithm that enables the identification of outliers or interesting anomalies. A new open source parallel and scalable DBSCAN implementation will be discussed in the light of a scientific use case that detects water mixing events in the Koljoefjords. The second technique we cover is classification, with a focus set on the support vector machines algorithm (SVMs), as one of the best out-of-the-box classification algorithm. A parallel and scalable SVM implementation will be discussed in the light of a scientific use case in the field of remote sensing with 52 different classes of land cover types.

Emergence of sporadic non-clustered cases of hospital-associated listeriosis among immunocompromised adults in southern Taiwan from 1992 to 2013: effect of precipitating immunosuppressive agents

PubMed Central

2014-01-01

Background Sporadic non-clustered hospital-associated listeriosis is an emerging infectious disease in immunocompromised hosts. The current study was designed to determine the impact of long-term and precipitating immunosuppressive agents and underlying diseases on triggering the expression of the disease, and to compare the clinical features and outcome of hospital-associated and community-associated listeriosis. Methods We reviewed the medical records of all patients with Listeria monocytogenes isolated from sterile body sites at a large medical center in southern Taiwan during 1992–2013. Non-clustered cases were defined as those unrelated to any other in time or place. Multivariable regression analysis was used to determine factors associated with prognosis. Results Thirty-five non-clustered cases of listeriosis were identified. Twelve (34.2%) were hospital-associated, and 23 (65.7%) were community-associated. The 60-day mortality was significantly greater in hospital-associated than in community-associated cases (66.7% vs. 17.4%, p = 0.007). Significantly more hospital-associated than community-associated cases were treated with a precipitating immunosuppressive agent within 4 weeks prior to onset of listeriosis (91.7% vs. 4.3%, respectively p < 0.001). The median period from the start of precipitating immunosuppressive treatment to the onset of listeriosis-related symptoms was 12 days (range, 4–27 days) in 11 of the 12 hospital-associated cases. In the multivariable analysis, APACHE II score >21 (p = 0.04) and receipt of precipitating immunosuppressive therapy (p = 0.02) were independent risk factors for 60-day mortality. Conclusions Sporadic non-clustered hospital-associated listeriosis needs to be considered in the differential diagnosis of sepsis in immunocompromised patients, particularly in those treated with new or increased doses of immunosuppressive agents. PMID:24641498

Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study

DOE PAGES

Maljovec, D.; Liu, S.; Wang, B.; ...

2015-07-14

Here, dynamic probabilistic risk assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP and MELCOR) with simulation controller codes (e.g., RAVEN and ADAPT). Whereas system simulator codes model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic and operating procedures) and stochastic (e.g., component failures and parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by sampling values of a set of parameters and simulating the system behavior for that specific set of parameter values. For complex systems, a major challenge in using DPRA methodologies is to analyze the large number of scenarios generated,more » where clustering techniques are typically employed to better organize and interpret the data. In this paper, we focus on the analysis of two nuclear simulation datasets that are part of the risk-informed safety margin characterization (RISMC) boiling water reactor (BWR) station blackout (SBO) case study. We provide the domain experts a software tool that encodes traditional and topological clustering techniques within an interactive analysis and visualization environment, for understanding the structures of such high-dimensional nuclear simulation datasets. We demonstrate through our case study that both types of clustering techniques complement each other for enhanced structural understanding of the data.« less

Spatial patterns of leprosy in a hyperendemic state in Northern Brazil, 2001-2012

PubMed Central

Monteiro, Lorena Dias; Martins-Melo, Francisco Rogerlândio; Brito, Aline Lima; Alencar, Carlos Henrique; Heukelbach, Jorg

2015-01-01

ABSTRACT OBJECTIVE To describe the spatial patterns of leprosy in the Brazilian state of Tocantins. METHODS This study was based on morbidity data obtained from the Sistema de Informações de Agravos de Notificação (SINAN – Brazilian Notifiable Diseases Information System), of the Ministry of Health. All new leprosy cases in individuals residing in the state of Tocantins, between 2001 and 2012, were included. In addition to the description of general disease indicators, a descriptive spatial analysis, empirical Bayesian analysis and spatial dependence analysis were performed by means of global and local Moran’s indexes. RESULTS A total of 14,542 new cases were recorded during the period under study. Based on the annual case detection rate, 77.0% of the municipalities were classified as hyperendemic (> 40 cases/100,000 inhabitants). Regarding the annual case detection rate in < 15 years-olds, 65.4% of the municipalities were hyperendemic (10.0 to 19.9 cases/100,000 inhabitants); 26.6% had a detection rate of grade 2 disability cases between 5.0 and 9.9 cases/100,000 inhabitants. There was a geographical overlap of clusters of municipalities with high detection rates in hyperendemic areas. Clusters with high disease risk (global Moran’s index: 0.51; p < 0.001), ongoing transmission (0.47; p < 0.001) and late diagnosis (0.44; p < 0.001) were identified mainly in the central-north and southwestern regions of Tocantins. CONCLUSIONS We identified high-risk clusters for transmission and late diagnosis of leprosy in the Brazilian state of Tocantins. Surveillance and control measures should be prioritized in these high-risk municipalities. PMID:26603352

First Description of a Cluster of Acute/Subacute Paracoccidioidomycosis Cases and Its Association with a Climatic Anomaly

PubMed Central

Silva, Maria Elisa Siqueira; Bagagli, Eduardo; Marques, Silvio Alencar; Mendes, Rinaldo Poncio

2010-01-01

Background Identifying clusters of acute paracoccidioidomycosis cases could potentially help in identifying the environmental factors that influence the incidence of this mycosis. However, unlike other endemic mycoses, there are no published reports of clusters of paracoccidioidomycosis. Methodology/Principal Findings A retrospective cluster detection test was applied to verify if an excess of acute form (AF) paracoccidioidomycosis cases in time and/or space occurred in Botucatu, an endemic area in São Paulo State. The scan-test SaTScan v7.0.3 was set to find clusters for the maximum temporal period of 1 year. The temporal test indicated a significant cluster in 1985 (P<0.005). This cluster comprised 10 cases, although 2.19 were expected for this year in this area. Age and clinical presentation of these cases were typical of AF paracccidioidomycosis. The space-time test confirmed the temporal cluster in 1985 and showed the localities where the risk was higher in that year. The cluster suggests that some particularities took place in the antecedent years in those localities. Analysis of climate variables showed that soil water storage was atypically high in 1982/83 (∼2.11/2.5 SD above mean), and the absolute air humidity in 1984, the year preceding the cluster, was much higher than normal (∼1.6 SD above mean), conditions that may have favored, respectively, antecedent fungal growth in the soil and conidia liberation in 1984, the probable year of exposure. These climatic anomalies in this area was due to the 1982/83 El Niño event, the strongest in the last 50 years. Conclusions/Significance We describe the first cluster of AF paracoccidioidomycosis, which was potentially linked to a climatic anomaly caused by the 1982/83 El Niño Southern Oscillation. This finding is important because it may help to clarify the conditions that favor Paracoccidioides brasiliensis survival and growth in the environment and that enhance human exposure, thus allowing the development of preventive measures. PMID:20361032

Determining the Optimal Number of Clusters with the Clustergram

NASA Technical Reports Server (NTRS)

Fluegemann, Joseph K.; Davies, Misty D.; Aguirre, Nathan D.

2011-01-01

Cluster analysis aids research in many different fields, from business to biology to aerospace. It consists of using statistical techniques to group objects in large sets of data into meaningful classes. However, this process of ordering data points presents much uncertainty because it involves several steps, many of which are subject to researcher judgment as well as inconsistencies depending on the specific data type and research goals. These steps include the method used to cluster the data, the variables on which the cluster analysis will be operating, the number of resulting clusters, and parts of the interpretation process. In most cases, the number of clusters must be guessed or estimated before employing the clustering method. Many remedies have been proposed, but none is unassailable and certainly not for all data types. Thus, the aim of current research for better techniques of determining the number of clusters is generally confined to demonstrating that the new technique excels other methods in performance for several disparate data types. Our research makes use of a new cluster-number-determination technique based on the clustergram: a graph that shows how the number of objects in the cluster and the cluster mean (the ordinate) change with the number of clusters (the abscissa). We use the features of the clustergram to make the best determination of the cluster-number.

Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China

PubMed Central

Bao, Changjun; Hu, Jianli; Liu, Wendong; Liang, Qi; Wu, Ying; Norris, Jessie; Peng, Zhihang; Yu, Rongbin; Shen, Hongbing; Chen, Feng

2014-01-01

Objective This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission. Methods County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions. Results The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, P<0.001). The time series model was established as ARIMA (1, 12, 0), which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64) and not having access to a safe water source (OR = 2.04) as the main causes of Shigella in Jiangsu Province. Conclusion Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time. PMID:24416167

Sample size calculation for stepped wedge and other longitudinal cluster randomised trials.

PubMed

Hooper, Richard; Teerenstra, Steven; de Hoop, Esther; Eldridge, Sandra

2016-11-20

The sample size required for a cluster randomised trial is inflated compared with an individually randomised trial because outcomes of participants from the same cluster are correlated. Sample size calculations for longitudinal cluster randomised trials (including stepped wedge trials) need to take account of at least two levels of clustering: the clusters themselves and times within clusters. We derive formulae for sample size for repeated cross-section and closed cohort cluster randomised trials with normally distributed outcome measures, under a multilevel model allowing for variation between clusters and between times within clusters. Our formulae agree with those previously described for special cases such as crossover and analysis of covariance designs, although simulation suggests that the formulae could underestimate required sample size when the number of clusters is small. Whether using a formula or simulation, a sample size calculation requires estimates of nuisance parameters, which in our model include the intracluster correlation, cluster autocorrelation, and individual autocorrelation. A cluster autocorrelation less than 1 reflects a situation where individuals sampled from the same cluster at different times have less correlated outcomes than individuals sampled from the same cluster at the same time. Nuisance parameters could be estimated from time series obtained in similarly clustered settings with the same outcome measure, using analysis of variance to estimate variance components. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Cluster Adjusted Regression for Displaced Subject Data (CARDS): Marginal Inference under Potentially Informative Temporal Cluster Size Profiles

PubMed Central

Bible, Joe; Beck, James D.; Datta, Somnath

2016-01-01

Summary Ignorance of the mechanisms responsible for the availability of information presents an unusual problem for analysts. It is often the case that the availability of information is dependent on the outcome. In the analysis of cluster data we say that a condition for informative cluster size (ICS) exists when the inference drawn from analysis of hypothetical balanced data varies from that of inference drawn on observed data. Much work has been done in order to address the analysis of clustered data with informative cluster size; examples include Inverse Probability Weighting (IPW), Cluster Weighted Generalized Estimating Equations (CWGEE), and Doubly Weighted Generalized Estimating Equations (DWGEE). When cluster size changes with time, i.e., the data set possess temporally varying cluster sizes (TVCS), these methods may produce biased inference for the underlying marginal distribution of interest. We propose a new marginalization that may be appropriate for addressing clustered longitudinal data with TVCS. The principal motivation for our present work is to analyze the periodontal data collected by Beck et al. (1997, Journal of Periodontal Research 6, 497–505). Longitudinal periodontal data often exhibits both ICS and TVCS as the number of teeth possessed by participants at the onset of study is not constant and teeth as well as individuals may be displaced throughout the study. PMID:26682911

Descriptive epidemiology of typhoid fever during an epidemic in Harare, Zimbabwe, 2012.

PubMed

Polonsky, Jonathan A; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J

2014-01-01

Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range.

Descriptive Epidemiology of Typhoid Fever during an Epidemic in Harare, Zimbabwe, 2012

PubMed Central

Polonsky, Jonathan A.; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J.

2014-01-01

Background Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. Methods A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. Principal Findings We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. Conclusions This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range. PMID:25486292

Computer-assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis.

PubMed

Momeni-Boroujeni, Amir; Yousefi, Elham; Somma, Jonathan

2017-12-01

Fine-needle aspiration (FNA) biopsy is an accurate method for the diagnosis of solid pancreatic masses. However, a significant number of cases still pose a diagnostic challenge. The authors have attempted to design a computer model to aid in the diagnosis of these biopsies. Images were captured of cell clusters on ThinPrep slides from 75 pancreatic FNA cases (20 malignant, 24 benign, and 31 atypical). A K-means clustering algorithm was used to segment the cell clusters into separable regions of interest before extracting features similar to those used for cytomorphologic assessment. A multilayer perceptron neural network (MNN) was trained and then tested for its ability to distinguish benign from malignant cases. A total of 277 images of cell clusters were obtained. K-means clustering identified 68,301 possible regions of interest overall. Features such as contour, perimeter, and area were found to be significantly different between malignant and benign images (P <.05). The MNN was 100% accurate for benign and malignant categories. The model's predictions from the atypical data set were 77% accurate. The results of the current study demonstrate that computer models can be used successfully to distinguish benign from malignant pancreatic cytology. The fact that the model can categorize atypical cases into benign or malignant with 77% accuracy highlights the great potential of this technology. Although further study is warranted to validate its clinical applications in pancreatic and perhaps other areas of cytology as well, the potential for improved patient outcomes using MNN for image analysis in pathology is significant. Cancer Cytopathol 2017;125:926-33. © 2017 American Cancer Society. © 2017 American Cancer Society.

Association of Interleukin-1 gene clusters polymorphisms with primary open-angle glaucoma: a meta-analysis.

PubMed

Li, Junhua; Feng, Yifan; Sung, Mi Sun; Lee, Tae Hee; Park, Sang Woo

2017-11-28

Previous studies have associated the Interleukin-1 (IL-1) gene clusters polymorphisms with the risk of primary open-angle glaucoma (POAG). However, the results were not consistent. Here, we performed a meta-analysis to evaluate the role of IL-1 gene clusters polymorphisms in POAG susceptibility. PubMed, EMBASE and Cochrane Library (up to July 15, 2017) were searched by two independent investigators. All case-control studies investigating the association between single-nucleotide polymorphisms (SNPs) of IL-1 gene clusters and POAG risk were included. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for quantifying the strength of association that has been involved in at least two studies. Five studies on IL-1β rs16944 (c. -511C > T) (1053 cases and 986 controls), 4 studies on IL-1α rs1800587 (c. -889C > T) (822 cases and 714 controls), and 4 studies on IL-1β rs1143634 (c. +3953C > T) (798 cases and 730 controls) were included. The results suggest that all three SNPs were not associated with POAG risk. Stratification analyses indicated that the rs1143634 has a suggestive associated with high tension glaucoma (HTG) under dominant (P = 0.03), heterozygote (P = 0.04) and allelic models (P = 0.02), however, the weak association was nullified after Bonferroni adjustments for multiple tests. Based on current meta-analysis, we indicated that there is lack of association between the three SNPs of IL-1 and POAG. However, this conclusion should be interpreted with caution and further well designed studies with large sample-size are required to validate the conclusion as low statistical powers.

Event Networks and the Identification of Crime Pattern Motifs

PubMed Central

2015-01-01

In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

Workplace cluster of Bell’s palsy in Lima, Peru

PubMed Central

2014-01-01

Background We report on a workplace cluster of Bell’s palsy that occurred within a four-month period in 2011 among employees of a three-story office building in Lima, Peru and our investigation to determine the etiology and associated risk factors. Findings An outbreak investigation was conducted to identify possible common infectious or environmental exposures and included patient interviews, reviews of medical records, an epidemiologic survey, serological analysis for IgM and IgG antibodies to putative Bell’s palsy-inducing pathogens, and an environmental exposure assessment of the office building. Three cases of Bell’s palsy were reported among 65 at-risk employees, attack rate 4.6%. Although two patients had underlying risk factors, there was no clear association or common identifiable risk factor among all cases. Serologic analysis showed no evidence of recent infections, and air and water sample measures of all known chemical or neurotoxins were below maximum allowable concentrations for exposure. Conclusions An infection spread among workplace employees could not be excluded as a potential cause of this cluster; however, it was unlikely a pathogen commonly associated with individual cases of Bell’s palsy. Although a specific etiology was not identified among all cases, we believe this methodology will aid future outbreak investigations of Bell’s palsy and a better understanding of its etiology. While environmental assessments may be useful in their ability to ascertain the cause of clusters of Bell’s palsy, future investigations should prioritize focus on common infectious etiology. PMID:24885256

Near real-time monitoring of HIV transmission hotspots from routine HIV genotyping: an implementation case study

PubMed Central

Poon, Art F. Y.; Gustafson, Réka; Daly, Patricia; Zerr, Laura; Demlow, S. Ellen; Wong, Jason; Woods, Conan K; Hogg, Robert S.; Krajden, Mel; Moore, David; Kendall, Perry; Montaner, Julio S. G.; Harrigan, P. Richard

2016-01-01

Background Due to the rapid evolution of HIV, infections with similar genetic sequences are likely to be related by recent transmission events. Clusters of related infections can represent subpopulations with high rates of HIV transmission. Here we describe the implementation of an automated “near real-time” system using clustering analysis of routinely collected HIV resistance genotypes to monitor and characterize HIV transmission hotspots in British Columbia (BC). Methods A monitoring system was implemented on the BC Drug Treatment Database, which currently holds over 32000 anonymized HIV genotypes for nearly 9000 residents of BC living with HIV. On average, five to six new HIV genotypes are deposited in the database every day, which triggers an automated re-analysis of the entire database. Clusters of five or more individuals were extracted on the basis of short phylogenetic distances between their respective HIV sequences. Monthly reports on the growth and characteristics of clusters were generated by the system and distributed to public health officers. Findings In June 2014, the monitoring system detected the expansion of a cluster by 11 new cases over three months, including eight cases with transmitted drug resistance. This cluster generally comprised young men who have sex with men. The subsequent report precipitated an enhanced public health follow-up to ensure linkage to care and treatment initiation in the affected subpopulation. Of the nine cases associated with this follow-up, all had already been linked to care and five cases had started treatment. Subsequent to the follow-up, three additional cases started treatment and the majority of cases achieved suppressed viral loads. Over the following 12 months, 12 new cases were detected in this cluster with a marked reduction in the onward transmission of drug resistance. Interpretation Our findings demonstrate the first application of an automated phylogenetic system monitoring a clinical database to detect a recent HIV outbreak and support the ensuing public health response. By making secondary use of routinely collected HIV genotypes, this approach is cost-effective, attains near realtime monitoring of new cases, and can be implemented in all settings where HIV genotyping is the standard of care. Funding This work was supported by the BC Centre for Excellence in HIV/AIDS and by grants from the Canadian Institutes for Health Research (CIHR HOP-111406, HOP-107544), the Genome BC, Genome Canada and CIHR Partnership in Genomics and Personalized Health (Large-Scale Applied Research Project HIV142 contract to PRH, JSGM, and AFYP), and by the US National Institute on Drug Abuse (1-R01-DA036307-01, 5-R01-031055-02, R01-DA021525-06, and R01-DA011591). PMID:27126490

Integrated cluster- and case-based surveillance for detecting stage III zoonotic pathogens: an example of Nipah virus surveillance in Bangladesh.

PubMed

Naser, A M; Hossain, M J; Sazzad, H M S; Homaira, N; Gurley, E S; Podder, G; Afroj, S; Banu, S; Rollin, P E; Daszak, P; Ahmed, B-N; Rahman, M; Luby, S P

2015-07-01

This paper explores the utility of cluster- and case-based surveillance established in government hospitals in Bangladesh to detect Nipah virus, a stage III zoonotic pathogen. Physicians listed meningo-encephalitis cases in the 10 surveillance hospitals and identified a cluster when ⩾2 cases who lived within 30 min walking distance of one another developed symptoms within 3 weeks of each other. Physicians collected blood samples from the clustered cases. As part of case-based surveillance, blood was collected from all listed meningo-encephalitis cases in three hospitals during the Nipah season (January-March). An investigation team visited clustered cases' communities to collect epidemiological information and blood from the living cases. We tested serum using Nipah-specific IgM ELISA. Up to September 2011, in 5887 listed cases, we identified 62 clusters comprising 176 encephalitis cases. We collected blood from 127 of these cases. In 10 clusters, we identified a total of 62 Nipah cases: 18 laboratory-confirmed and 34 probable. We identified person-to-person transmission of Nipah virus in four clusters. From case-based surveillance, we identified 23 (4%) Nipah cases. Faced with thousands of encephalitis cases, integrated cluster surveillance allows targeted deployment of investigative resources to detect outbreaks by stage III zoonotic pathogens in resource-limited settings.

Cluster headache and the hypocretin receptor 2 reconsidered: a genetic association study and meta-analysis.

PubMed

Weller, Claudia M; Wilbrink, Leopoldine A; Houwing-Duistermaat, Jeanine J; Koelewijn, Stephany C; Vijfhuizen, Lisanne S; Haan, Joost; Ferrari, Michel D; Terwindt, Gisela M; van den Maagdenberg, Arn M J M; de Vries, Boukje

2015-08-01

Cluster headache is a severe neurological disorder with a complex genetic background. A missense single nucleotide polymorphism (rs2653349; p.Ile308Val) in the HCRTR2 gene that encodes the hypocretin receptor 2 is the only genetic factor that is reported to be associated with cluster headache in different studies. However, as there are conflicting results between studies, we re-evaluated its role in cluster headache. We performed a genetic association analysis for rs2653349 in our large Leiden University Cluster headache Analysis (LUCA) program study population. Systematic selection of the literature yielded three additional studies comprising five study populations, which were included in our meta-analysis. Data were extracted according to predefined criteria. A total of 575 cluster headache patients from our LUCA study and 874 controls were genotyped for HCRTR2 SNP rs2653349 but no significant association with cluster headache was found (odds ratio 0.91 (95% confidence intervals 0.75-1.10), p = 0.319). In contrast, the meta-analysis that included in total 1167 cluster headache cases and 1618 controls from the six study populations, which were part of four different studies, showed association of the single nucleotide polymorphism with cluster headache (random effect odds ratio 0.69 (95% confidence intervals 0.53-0.90), p = 0.006). The association became weaker, as the odds ratio increased to 0.80, when the meta-analysis was repeated without the initial single South European study with the largest effect size. Although we did not find evidence for association of rs2653349 in our LUCA study, which is the largest investigated study population thus far, our meta-analysis provides genetic evidence for a role of HCRTR2 in cluster headache. Regardless, we feel that the association should be interpreted with caution as meta-analyses with individual populations that have limited power have diminished validity. © International Headache Society 2014.

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

NASA Technical Reports Server (NTRS)

Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.

1992-01-01

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches.

PubMed

Bolin, Jocelyn H; Edwards, Julianne M; Finch, W Holmes; Cassady, Jerrell C

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches

PubMed Central

Bolin, Jocelyn H.; Edwards, Julianne M.; Finch, W. Holmes; Cassady, Jerrell C.

2014-01-01

Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering. PMID:24795683

BiCluE - Exact and heuristic algorithms for weighted bi-cluster editing of biomedical data

PubMed Central

2013-01-01

Background The explosion of biological data has dramatically reformed today's biology research. The biggest challenge to biologists and bioinformaticians is the integration and analysis of large quantity of data to provide meaningful insights. One major problem is the combined analysis of data from different types. Bi-cluster editing, as a special case of clustering, which partitions two different types of data simultaneously, might be used for several biomedical scenarios. However, the underlying algorithmic problem is NP-hard. Results Here we contribute with BiCluE, a software package designed to solve the weighted bi-cluster editing problem. It implements (1) an exact algorithm based on fixed-parameter tractability and (2) a polynomial-time greedy heuristics based on solving the hardest part, edge deletions, first. We evaluated its performance on artificial graphs. Afterwards we exemplarily applied our implementation on real world biomedical data, GWAS data in this case. BiCluE generally works on any kind of data types that can be modeled as (weighted or unweighted) bipartite graphs. Conclusions To our knowledge, this is the first software package solving the weighted bi-cluster editing problem. BiCluE as well as the supplementary results are available online at http://biclue.mpi-inf.mpg.de. PMID:24565035

Detecting synchronization clusters in multivariate time series via coarse-graining of Markov chains.

PubMed

Allefeld, Carsten; Bialonski, Stephan

2007-12-01

Synchronization cluster analysis is an approach to the detection of underlying structures in data sets of multivariate time series, starting from a matrix R of bivariate synchronization indices. A previous method utilized the eigenvectors of R for cluster identification, analogous to several recent attempts at group identification using eigenvectors of the correlation matrix. All of these approaches assumed a one-to-one correspondence of dominant eigenvectors and clusters, which has however been shown to be wrong in important cases. We clarify the usefulness of eigenvalue decomposition for synchronization cluster analysis by translating the problem into the language of stochastic processes, and derive an enhanced clustering method harnessing recent insights from the coarse-graining of finite-state Markov processes. We illustrate the operation of our method using a simulated system of coupled Lorenz oscillators, and we demonstrate its superior performance over the previous approach. Finally we investigate the question of robustness of the algorithm against small sample size, which is important with regard to field applications.

Comparison of organs' shapes with geometric and Zernike 3D moments.

PubMed

Broggio, D; Moignier, A; Ben Brahim, K; Gardumi, A; Grandgirard, N; Pierrat, N; Chea, M; Derreumaux, S; Desbrée, A; Boisserie, G; Aubert, B; Mazeron, J-J; Franck, D

2013-09-01

The morphological similarity of organs is studied with feature vectors based on geometric and Zernike 3D moments. It is particularly investigated if outliers and average models can be identified. For this purpose, the relative proximity to the mean feature vector is defined, principal coordinate and clustering analyses are also performed. To study the consistency and usefulness of this approach, 17 livers and 76 hearts voxel models from several sources are considered. In the liver case, models with similar morphological feature are identified. For the limited amount of studied cases, the liver of the ICRP male voxel model is identified as a better surrogate than the female one. For hearts, the clustering analysis shows that three heart shapes represent about 80% of the morphological variations. The relative proximity and clustering analysis rather consistently identify outliers and average models. For the two cases, identification of outliers and surrogate of average models is rather robust. However, deeper classification of morphological feature is subject to caution and can only be performed after cross analysis of at least two kinds of feature vectors. Finally, the Zernike moments contain all the information needed to re-construct the studied objects and thus appear as a promising tool to derive statistical organ shapes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Non-small cell lung cancer detection using microRNA expression profiling of bronchoalveolar lavage fluid and sputum.

PubMed

Kim, Julian O; Gazala, Sayf; Razzak, Rene; Guo, Linghong; Ghosh, Sunita; Roa, Wilson H; Bédard, Eric L R

2015-04-01

To assess if miRNA expression profiling of bronchoalveolar lavage (BAL) fluid and sputum could be used to detect early-stage non-small cell lung cancer (NSCLC). Hierarchical cluster analysis was performed on the expression levels of 5 miRNAs (miR-21, miR-143, miR-155, miR-210, and miR-372) which were quantified using RNA reverse transcription and quantitative real-time polymerase chain reaction in sputum and BAL samples from NSCLC cases and cancer-free controls. Cluster analysis of the miRNA expression levels in BAL samples from 21 NSCLC cases and sputum samples from 10 cancer-free controls yielded a diagnostic sensitivity of 85.7% and specificity of 100%. Cluster analysis of sputum samples from the same patients yielded a diagnostic sensitivity of 67.8% and specificity of 90%. miRNA expression profiling of sputum and BAL fluids represent a potential means to detect early-stage NSCLC. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Clustering Financial Time Series by Network Community Analysis

NASA Astrophysics Data System (ADS)

Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

Assessing different measures of population-level vaccine protection using a case-control study.

PubMed

Ali, Mohammad; You, Young Ae; Kanungo, Suman; Manna, Byomkesh; Deen, Jacqueline L; Lopez, Anna Lena; Wierzba, Thomas F; Bhattacharya, Sujit K; Sur, Dipika; Clemens, John D

2015-11-27

Case-control studies have not been examined for their utility in assessing population-level vaccine protection in individually randomized trials. We used the data of a randomized, placebo-controlled trial of a cholera vaccine to compare the results of case-control analyses with those of cohort analyses. Cases of cholera were selected from the trial population followed for three years following dosing. For each case, we selected 4 age-matched controls who had not developed cholera. For each case and control, GIS was used to calculate vaccine coverage of individuals in a surrounding "virtual" cluster. Specific selection strategies were used to evaluate the vaccine protective effects. 66,900 out of 108,389 individuals received two doses of the assigned regimen. For direct protection among subjects in low vaccine coverage clusters, we observed 78% (95% CI: 47-91%) protection in a cohort analysis and 84% (95% CI: 60-94%) in case-control analysis after adjusting for confounding factors. Using our GIS-based approach, estimated indirect protection was 52% (95% CI: 10-74%) in cohort and 76% (95% CI: 47-89%) in case control analysis. Estimates of total and overall effectiveness were similar for cohort and case-control analyses. The findings show that case-control analyses of individually randomized vaccine trials may be used to evaluate direct as well as population-level vaccine protection. Copyright © 2015. Published by Elsevier Ltd.

Sirenomelia in Argentina: Prevalence, geographic clusters and temporal trends analysis.

PubMed

Groisman, Boris; Liascovich, Rosa; Gili, Juan Antonio; Barbero, Pablo; Bidondo, María Paz

2016-07-01

Sirenomelia is a severe malformation of the lower body characterized by a single medial lower limb and a variable combination of visceral abnormalities. Given that Sirenomelia is a very rare birth defect, epidemiological studies are scarce. The aim of this study is to evaluate prevalence, geographic clusters and time trends of sirenomelia in Argentina, using data from the National Network of Congenital Anomalies of Argentina (RENAC) from November 2009 until December 2014. This is a descriptive study using data from the RENAC, a hospital-based surveillance system for newborns affected with major morphological congenital anomalies. We calculated sirenomelia prevalence throughout the period, searched for geographical clusters, and evaluated time trends. The prevalence of confirmed cases of sirenomelia throughout the period was 2.35 per 100,000 births. Cluster analysis showed no statistically significant geographical aggregates. Time-trends analysis showed that the prevalence was higher in years 2009 to 2010. The observed prevalence was higher than the observed in previous epidemiological studies in other geographic regions. We observed a likely real increase in the initial period of our study. We used strict diagnostic criteria, excluding cases that only had clinical diagnosis of sirenomelia. Therefore, real prevalence could be even higher. This study did not show any geographic clusters. Because etiology of sirenomelia has not yet been established, studies of epidemiological features of this defect may contribute to define its causes. Birth Defects Research (Part A) 106:604-611, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Examining DNA fingerprinting as an epidemiology tool in the tuberculosis program in the Northwest Territories, Canada

PubMed Central

Case, Cheryl; Kandola, Kami; Chui, Linda; Li, Vincent; Nix, Nancy; Johnson, Rhonda

2013-01-01

Background Tuberculosis (TB) is an important public health problem in the Northwest Territories (NWT), particularly among Canadian Aboriginal people. Objective To analyse the transmission patterns of tuberculosis among the population living in the NWT, a territorial jurisdiction located within Northern Canada. Methods This population-based retrospective study examined the DNA fingerprints of all laboratory confirmed cases of TB in the NWT, Canada, between 1990 and 2009. An isolate of each lab-confirmed case had genotyping done using IS6110 Restriction Fragment Length Polymorphism. DNA patterns were assigned to each DNA fingerprint, and indistinguishable fingerprints patterns were assigned a cluster. Social network analysis (SNA) was used to examine direct linkages among cases determined through conventional contact tracing (CCT), their DNA fingerprint and home community. Results Of the 225 lab-confirmed cases identified, the study was limited to 195 subjects due to DNA fingerprinting data availability. The mean age of the cases was 43.8 years (±22.6) and 120 (61.5%) males. The Dene (First Nations) encompassed 120 of the cases (87.7%), 8 cases (4.1%) were Inuit, 2 cases (1.0%) were Metis, 7 cases (3.6%) were Immigrants and 1 case had unknown ethnicity. One hundred and eighty six (95.4%) subjects were clustered, resulting in 8 clusters. Trend analysis showed significant relationships between with risk factors for unemployment (p=0.020), geographic location (p≤0.001) and homelessness (p≤0.001). Other significant risk factors included excessive alcohol consumption, prior infection with Mycobacterium tuberculosis and prior contact with a case of TB. Conclusions This study demonstrates how DNA fingerprinting and SNA can be additional epidemiological tools, along with CCT method, to determine transmission patterns of TB. PMID:23671837

The smart cluster method. Adaptive earthquake cluster identification and analysis in strong seismic regions

NASA Astrophysics Data System (ADS)

Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

2017-07-01

Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

A hybrid clustering approach for multivariate time series - A case study applied to failure analysis in a gas turbine.

PubMed

Fontes, Cristiano Hora; Budman, Hector

2017-11-01

A clustering problem involving multivariate time series (MTS) requires the selection of similarity metrics. This paper shows the limitations of the PCA similarity factor (SPCA) as a single metric in nonlinear problems where there are differences in magnitude of the same process variables due to expected changes in operation conditions. A novel method for clustering MTS based on a combination between SPCA and the average-based Euclidean distance (AED) within a fuzzy clustering approach is proposed. Case studies involving either simulated or real industrial data collected from a large scale gas turbine are used to illustrate that the hybrid approach enhances the ability to recognize normal and fault operating patterns. This paper also proposes an oversampling procedure to create synthetic multivariate time series that can be useful in commonly occurring situations involving unbalanced data sets. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Molecular clustering of patients with diabetes and pulmonary tuberculosis: A systematic review and meta-analysis.

PubMed

Blanco-Guillot, Francles; Delgado-Sánchez, Guadalupe; Mongua-Rodríguez, Norma; Cruz-Hervert, Pablo; Ferreyra-Reyes, Leticia; Ferreira-Guerrero, Elizabeth; Yanes-Lane, Mercedes; Montero-Campos, Rogelio; Bobadilla-Del-Valle, Miriam; Torres-González, Pedro; Ponce-de-León, Alfredo; Sifuentes-Osornio, José; Garcia-Garcia, Lourdes

2017-01-01

Many studies have explored the relationship between diabetes mellitus (DM) and tuberculosis (TB) demonstrating increased risk of TB among patients with DM and poor prognosis of patients suffering from the association of DM/TB. Owing to a paucity of studies addressing this question, it remains unclear whether patients with DM and TB are more likely than TB patients without DM to be grouped into molecular clusters defined according to the genotype of the infecting Mycobacterium tuberculosis bacillus. That is, whether there is convincing molecular epidemiological evidence for TB transmission among DM patients. Objective: We performed a systematic review and meta-analysis to quantitatively evaluate the propensity for patients with DM and pulmonary TB (PTB) to cluster according to the genotype of the infecting M. tuberculosis bacillus. We conducted a systematic search in MEDLINE and LILACS from 1990 to June, 2016 with the following combinations of key words "tuberculosis AND transmission" OR "tuberculosis diabetes mellitus" OR "Mycobacterium tuberculosis molecular epidemiology" OR "RFLP-IS6110" OR "Spoligotyping" OR "MIRU-VNTR". Studies were included if they met the following criteria: (i) studies based on populations from defined geographical areas; (ii) use of genotyping by IS6110- restriction fragment length polymorphism (RFLP) analysis and spoligotyping or mycobacterial interspersed repetitive unit-variable number of tandem repeats (MIRU-VNTR) or other amplification methods to identify molecular clustering; (iii) genotyping and analysis of 50 or more cases of PTB; (iv) study duration of 11 months or more; (v) identification of quantitative risk factors for molecular clustering including DM; (vi) > 60% coverage of the study population; and (vii) patients with PTB confirmed bacteriologically. The exclusion criteria were: (i) Extrapulmonary TB; (ii) TB caused by nontuberculous mycobacteria; (iii) patients with PTB and HIV; (iv) pediatric PTB patients; (v) TB in closed environments (e.g. prisons, elderly homes, etc.); (vi) diabetes insipidus and (vii) outbreak reports. Hartung-Knapp-Sidik-Jonkman method was used to estimate the odds ratio (OR) of the association between DM with molecular clustering of cases with TB. In order to evaluate the degree of heterogeneity a statistical Q test was done. The publication bias was examined with Begg and Egger tests. Review Manager 5.3.5 CMA v.3 and Biostat and Software package R were used. Selection criteria were met by six articles which included 4076 patients with PTB of which 13% had DM. Twenty seven percent of the cases were clustered. The majority of cases (48%) were reported in a study in China with 31% clustering. The highest incidence of TB occurred in two studies from China. The global OR for molecular clustering was 0.84 (IC 95% 0.40-1.72). The heterogeneity between studies was moderate (I2 = 55%, p = 0.05), although there was no publication bias (Beggs test p = 0.353 and Eggers p = 0.429). There were very few studies meeting our selection criteria. The wide confidence interval indicates that there is not enough evidence to draw conclusions about the association. Clustering of patients with DM in TB transmission chains should be investigated in areas where both diseases are prevalent and focus on specific contexts.

On the Distribution of Orbital Poles of Milky Way Satellites

NASA Astrophysics Data System (ADS)

Palma, Christopher; Majewski, Steven R.; Johnston, Kathryn V.

2002-01-01

In numerous studies of the outer Galactic halo some evidence for accretion has been found. If the outer halo did form in part or wholly through merger events, we might expect to find coherent streams of stars and globular clusters following orbits similar to those of their parent objects, which are assumed to be present or former Milky Way dwarf satellite galaxies. We present a study of this phenomenon by assessing the likelihood of potential descendant ``dynamical families'' in the outer halo. We conduct two analyses: one that involves a statistical analysis of the spatial distribution of all known Galactic dwarf satellite galaxies (DSGs) and globular clusters, and a second, more specific analysis of those globular clusters and DSGs for which full phase space dynamical data exist. In both cases our methodology is appropriate only to members of descendant dynamical families that retain nearly aligned orbital poles today. Since the Sagittarius dwarf (Sgr) is considered a paradigm for the type of merger/tidal interaction event for which we are searching, we also undertake a case study of the Sgr system and identify several globular clusters that may be members of its extended dynamical family. In our first analysis, the distribution of possible orbital poles for the entire sample of outer (Rgc>8 kpc) halo globular clusters is tested for statistically significant associations among globular clusters and DSGs. Our methodology for identifying possible associations is similar to that used by Lynden-Bell & Lynden-Bell, but we put the associations on a more statistical foundation. Moreover, we study the degree of possible dynamical clustering among various interesting ensembles of globular clusters and satellite galaxies. Among the ensembles studied, we find the globular cluster subpopulation with the highest statistical likelihood of association with one or more of the Galactic DSGs to be the distant, outer halo (Rgc>25 kpc), second-parameter globular clusters. The results of our orbital pole analysis are supported by the great circle cell count methodology of Johnston, Hernquist, & Bolte. The space motions of the clusters Pal 4, NGC 6229, NGC 7006, and Pyxis are predicted to be among those most likely to show the clusters to be following stream orbits, since these clusters are responsible for the majority of the statistical significance of the association between outer halo, second-parameter globular clusters and the Milky Way DSGs. In our second analysis, we study the orbits of the 41 globular clusters and six Milky Way-bound DSGs having measured proper motions to look for objects with both coplanar orbits and similar angular momenta. Unfortunately, the majority of globular clusters with measured proper motions are inner halo clusters that are less likely to retain memory of their original orbit. Although four potential globular cluster/DSG associations are found, we believe three of these associations involving inner halo clusters to be coincidental. While the present sample of objects with complete dynamical data is small and does not include many of the globular clusters that are more likely to have been captured by the Milky Way, the methodology we adopt will become increasingly powerful as more proper motions are measured for distant Galactic satellites and globular clusters, and especially as results from the Space Interferometry Mission (SIM) become available.

Using molecular tools to identify the geographical origin of a case of human brucellosis.

PubMed

Muchowski, J K; Koylass, M S; Dainty, A C; Stack, J A; Perrett, L; Whatmore, A M; Perrier, C; Chircop, S; Demicoli, N; Gatt, A B; Caruana, P A; Gopaul, K K

2015-10-01

Although Malta is historically linked with the zoonosis brucellosis, there had not been a case of the disease in either the human or livestock population for several years. However, in July 2013 a case of human brucellosis was identified on the island. To determine whether this recent case originated in Malta, four isolates from this case were subjected to molecular analysis. Molecular profiles generated using multilocus sequence analysis and multilocus variable number tandem repeat for the recent human case isolates and 11 Brucella melitensis strains of known Maltese origin were compared with others held on in-house and global databases. While the 11 isolates of Maltese origin formed a distinct cluster, the recent human isolation was not associated with these strains but instead clustered with isolates originating from the Horn of Africa. These data was congruent with epidemiological trace-back showed that the individual had travelled to Malta from Eritrea. This work highlights the potential of using molecular typing data to aid in epidemiological trace-back of Brucella isolations and assist in monitoring of the effectiveness of brucellosis control schemes.

[Hierarchical regionalization for spatial epidemiology: a case study of thyroid cancer incidence in Yiwu, Zhejiang].

PubMed

Teng, Shizhu; Jia, Qiaojuan; Huang, Yijian; Chen, Liangcao; Fei, Xufeng; Wu, Jiaping

2015-10-01

Sporadic cases occurring in mall geographic unit could lead to extreme value of incidence due to the small population bases, which would influence the analysis of actual incidence. This study introduced a method of hierarchy clustering and partitioning regionalization, which integrates areas with small population into larger areas with enough population by using Geographic Information System (GIS) based on the principles of spatial continuity and geographical similarity (homogeneity test). This method was applied in spatial epidemiology by using a data set of thyroid cancer incidence in Yiwu, Zhejiang province, between 2010 and 2013. Thyroid cancer incidence data were more reliable and stable in the new regionalized areas. Hotspot analysis (Getis-Ord) on the incidence in new areas indicated that there was obvious case clustering in the central area of Yiwu. This method can effectively solve the problem of small population base in small geographic units in spatial epidemiological analysis of thyroid cancer incidence and can be used for other diseases and in other areas.

An Enhanced K-Means Algorithm for Water Quality Analysis of The Haihe River in China.

PubMed

Zou, Hui; Zou, Zhihong; Wang, Xiaojing

2015-11-12

The increase and the complexity of data caused by the uncertain environment is today's reality. In order to identify water quality effectively and reliably, this paper presents a modified fast clustering algorithm for water quality analysis. The algorithm has adopted a varying weights K-means cluster algorithm to analyze water monitoring data. The varying weights scheme was the best weighting indicator selected by a modified indicator weight self-adjustment algorithm based on K-means, which is named MIWAS-K-means. The new clustering algorithm avoids the margin of the iteration not being calculated in some cases. With the fast clustering analysis, we can identify the quality of water samples. The algorithm is applied in water quality analysis of the Haihe River (China) data obtained by the monitoring network over a period of eight years (2006-2013) with four indicators at seven different sites (2078 samples). Both the theoretical and simulated results demonstrate that the algorithm is efficient and reliable for water quality analysis of the Haihe River. In addition, the algorithm can be applied to more complex data matrices with high dimensionality.

Strains of Mycobacterium tuberculosis transmitting infection in Brazilian households and those associated with community transmission of tuberculosis.

PubMed

Vinhas, Solange Alves; Jones-López, Edward C; Ribeiro Rodrigues, Rodrigo; Gaeddert, Mary; Peres, Renata Lyrio; Marques-Rodrigues, Patricia; de Aguiar, Paola Poloni Lobo; White, Laura Forsberg; Alland, David; Salgame, Padmini; Hom, David; Ellner, Jerrold J; Dietze, Reynaldo; Collins, Lauren F; Shashkina, Elena; Kreiswirth, Barry; Palaci, Moisés

2017-05-01

Molecular epidemiologic studies have shown that the dynamics of tuberculosis transmission varies geographically. We sought to determine which strains of Mycobacterium tuberculosis (MTB) were infecting household contacts (HHC), and which were causing clusters of tuberculosis (TB) disease in Vitoria-ES, Brazil. A total of 741 households contacts (445 TST +) and 139 index cases were characterized according to the proportion of contacts in each household that had a tuberculin skin test positive: low (LT) (≤40% TST+), high (HT) (≥70% TST+) and (40-70% TST+) intermediate (IT) transmission. IS6110-RFLP and spoligotyping analysis were performed only 139 MTB isolates from index cases and 841 community isolates. Clustering occurred in 45% of the entire study population. There was no statistically significant association between MTB household transmission category and clustering. Within the household study population, the proportion of clusters in HT and LT groups was similar (31% and 36%, respectively; p = 0.82). Among index cases isolates associated with households demonstrating TST conversion, the frequency of unique pattern genotypes was higher for index cases of the LT compared to HT households (p = 0.03). We concluded that clusters and lineages associated with MTB infection in HT households had no proclivity for increased transmission of TB in the community. Copyright © 2017 Elsevier Ltd. All rights reserved.

The myeloproliferative neoplasms, unclassifiable: clinical and pathological considerations.

PubMed

Gianelli, Umberto; Cattaneo, Daniele; Bossi, Anna; Cortinovis, Ivan; Boiocchi, Leonardo; Liu, Yen-Chun; Augello, Claudia; Bonometti, Arturo; Fiori, Stefano; Orofino, Nicola; Guidotti, Francesca; Orazi, Attilio; Iurlo, Alessandra

2017-02-01

In this study, we investigate in detail the morphological, clinical and molecular features of 71 consecutive patients with a diagnosis of myeloproliferative neoplasms, unclassifiable. We performed a meticulous morphological analysis and found that most of the cases displayed a hypercellular bone marrow (70%) with normal erythropoiesis without left-shifting (59%), increased granulopoiesis with left-shifting (73%) and increased megakaryocytes with loose clustering (96%). Megakaryocytes displayed frequent giant forms with hyperlobulated or bulbous nuclei and/or other maturation defects. Interestingly, more than half of the cases displayed severe bone marrow fibrosis (59%). Median values of hemoglobin level and white blood cells count were all within the normal range; in contrast, median platelets count and lactate dehydrogenase were increased. Little less than half of the patients (44%) showed splenomegaly. JAK2V617F mutation was detected in 72% of all patients. Among the JAK2-negative cases, MPLW515L mutation was found in 17% and CALR mutations in 67% of the investigated cases, respectively. Finally, by multiple correspondence analysis of the morphological profiles, we found that all but four of the cases could be grouped in three morphological clusters with some features similar to those of the classic BCR-ABL1-negative myeloproliferative neoplasms. Analysis of the clinical parameters in these three clusters revealed discrepancies with the morphological profile in about 55% of the patients. In conclusion, we found that the category of myeloproliferative neoplasm, unclassifiable is heterogeneous but identification of different subgroups is possible and should be recommended for a better management of these patients.

Measuring Spatial Dependence for Infectious Disease Epidemiology

PubMed Central

Grabowski, M. Kate; Cummings, Derek A. T.

2016-01-01

Global spatial clustering is the tendency of points, here cases of infectious disease, to occur closer together than expected by chance. The extent of global clustering can provide a window into the spatial scale of disease transmission, thereby providing insights into the mechanism of spread, and informing optimal surveillance and control. Here the authors present an interpretable measure of spatial clustering, τ, which can be understood as a measure of relative risk. When biological or temporal information can be used to identify sets of potentially linked and likely unlinked cases, this measure can be estimated without knowledge of the underlying population distribution. The greater our ability to distinguish closely related (i.e., separated by few generations of transmission) from more distantly related cases, the more closely τ will track the true scale of transmission. The authors illustrate this approach using examples from the analyses of HIV, dengue and measles, and provide an R package implementing the methods described. The statistic presented, and measures of global clustering in general, can be powerful tools for analysis of spatially resolved data on infectious diseases. PMID:27196422

Semi-supervised clustering methods.

PubMed

Bair, Eric

2013-01-01

Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as "semi-supervised clustering" methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided.

Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies

PubMed Central

Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario

2014-01-01

Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565

A Dimensionally Reduced Clustering Methodology for Heterogeneous Occupational Medicine Data Mining.

PubMed

Saâdaoui, Foued; Bertrand, Pierre R; Boudet, Gil; Rouffiac, Karine; Dutheil, Frédéric; Chamoux, Alain

2015-10-01

Clustering is a set of techniques of the statistical learning aimed at finding structures of heterogeneous partitions grouping homogenous data called clusters. There are several fields in which clustering was successfully applied, such as medicine, biology, finance, economics, etc. In this paper, we introduce the notion of clustering in multifactorial data analysis problems. A case study is conducted for an occupational medicine problem with the purpose of analyzing patterns in a population of 813 individuals. To reduce the data set dimensionality, we base our approach on the Principal Component Analysis (PCA), which is the statistical tool most commonly used in factorial analysis. However, the problems in nature, especially in medicine, are often based on heterogeneous-type qualitative-quantitative measurements, whereas PCA only processes quantitative ones. Besides, qualitative data are originally unobservable quantitative responses that are usually binary-coded. Hence, we propose a new set of strategies allowing to simultaneously handle quantitative and qualitative data. The principle of this approach is to perform a projection of the qualitative variables on the subspaces spanned by quantitative ones. Subsequently, an optimal model is allocated to the resulting PCA-regressed subspaces.

Two-year population-based molecular epidemiological study of tuberculosis transmission in the metropolitan area of Milan, Italy.

PubMed

Moro, M L; Salamina, G; Gori, A; Penati, V; Sacchetti, R; Mezzetti, F; Infuso, A; Sodano, L

2002-02-01

A 2-year, population-based, molecular epidemiological study was conducted in Milan, Italy, to determine the proportion of tuberculosis (TB) cases attributable to recent transmission. All strains were typed by restriction fragment length polymorphism (RFLP) analysis; clustering was considered indicative of recent transmission. Of the 581 cases, 239 (41.1%) belonged to clusters that consisted of 2 to 11 patients; 28.1% were attributable to recent transmission (number of clustered patients minus 1). Clustering was associated with multidrug-resistant Mycobacterium tuberculosis strains (74.2% of cases), AIDS (60.2%), and a history of incarceration (67.4%). The frequency of multidrug-resistant Mycobacterium tuberculosis was 5.3% overall (15.4% among AIDS patients). Among AIDS patients, infection with a resistant strain was independently associated with clustering (odds ratio, 1.32; 95% confidence interval, 1.07-1.163), while among non-AIDS patients, three factors were associated with clustering: history of incarceration (odds ratio, 2.03; 95% confidence interval, 1.41-2.92), age <30 years (odds ratio, 1.43; 95% confidence interval, 1.05-1.94), and native-born Italian nationality (odds ratio, 1.44; 95% confidence interval, 1.08-1.92). Of the 118 patients who belonged to either the smallest or the largest cluster, 19 (16.1%) reported an epidemiological link with another study patient. The results of this study highlight the need for control programs that focus on selected high-risk groups consisting primarily of HIV-infected individuals and persons with social and lifestyle risks for TB. These programs should be aimed at reducing the probability of transmission of drug-resistant TB through early identification of cases and provision of effective treatment until the individual is cured.

Principal component and clustering analysis on molecular dynamics data of the ribosomal L11·23S subdomain.

PubMed

Wolf, Antje; Kirschner, Karl N

2013-02-01

With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations. Specifically, we explored how clustering different PC subspaces effects the resulting clusters versus clustering the complete trajectory data. As a case example, we used the trajectory data from an explicitly solvated simulation of a bacteria's L11·23S ribosomal subdomain, which is a target of thiopeptide antibiotics. Clustering was performed, using K-means and average-linkage algorithms, on data involving the first two to the first five PC subspace dimensions. For the average-linkage algorithm we found that data-point membership, cluster shape, and cluster size depended on the selected PC subspace data. In contrast, K-means provided very consistent results regardless of the selected subspace. Since we present results on a single model system, generalization concerning the clustering of different PC subspaces of other molecular systems is currently premature. However, our hope is that this study illustrates a) the complexities in selecting the appropriate clustering algorithm, b) the complexities in interpreting and validating their results, and c) by combining PC analysis with subsequent clustering valuable dynamic and conformational information can be obtained.

Application of Geostatistical Methods and Machine Learning for spatio-temporal Earthquake Cluster Analysis

NASA Astrophysics Data System (ADS)

Schaefer, A. M.; Daniell, J. E.; Wenzel, F.

2014-12-01

Earthquake clustering tends to be an increasingly important part of general earthquake research especially in terms of seismic hazard assessment and earthquake forecasting and prediction approaches. The distinct identification and definition of foreshocks, aftershocks, mainshocks and secondary mainshocks is taken into account using a point based spatio-temporal clustering algorithm originating from the field of classic machine learning. This can be further applied for declustering purposes to separate background seismicity from triggered seismicity. The results are interpreted and processed to assemble 3D-(x,y,t) earthquake clustering maps which are based on smoothed seismicity records in space and time. In addition, multi-dimensional Gaussian functions are used to capture clustering parameters for spatial distribution and dominant orientations. Clusters are further processed using methodologies originating from geostatistics, which have been mostly applied and developed in mining projects during the last decades. A 2.5D variogram analysis is applied to identify spatio-temporal homogeneity in terms of earthquake density and energy output. The results are mitigated using Kriging to provide an accurate mapping solution for clustering features. As a case study, seismic data of New Zealand and the United States is used, covering events since the 1950s, from which an earthquake cluster catalogue is assembled for most of the major events, including a detailed analysis of the Landers and Christchurch sequences.

Does the impact of case management vary in different subgroups of multimorbidity? Secondary analysis of a quasi-experiment.

PubMed

Stokes, Jonathan; Kristensen, Søren Rud; Checkland, Kath; Cheraghi-Sohi, Sudeh; Bower, Peter

2017-08-03

Health systems must transition from catering primarily to acute conditions, to meet the increasing burden of chronic disease and multimorbidity. Case management is a popular method of integrating care, seeking to accomplish this goal. However, the intervention has shown limited effectiveness. We explore whether the effects of case management vary in patients with different types of multimorbidity. We extended a previously published quasi-experiment (difference-in-differences analysis) with 2049 propensity matched case management intervention patients, adding an additional interaction term to determine subgroup effects (difference-in-difference-in-differences) by different conceptualisations of multimorbidity: 1) Mental-physical comorbidity versus others; 2) 3+ chronic conditions versus <3; 3) Discordant versus concordant conditions; 4) Cardiovascular/metabolic cluster conditions only versus others; 5) Mental health-associated cluster conditions only versus others; 6) Musculoskeletal disorder cluster conditions only versus others 7) Charlson index >5 versus others. Outcome measures included a variety of secondary care utilisation and cost measures. The majority of conceptualisations suggested little to no difference in effect between subgroups. Where results were significant, the vast majority of effect sizes identified in either direction were very small. The trend across the majority of the results appeared to show very slight increases of admissions with treatment for the most complex patients (highest risk). The exceptions to this, patients with a Charlson index >5 may benefit slightly more from case management with decreased ACSC admissions (effect size (ES): −0.06) and inpatient re-admissions (30 days, ES: −0.05), and patients with only cardiovascular/metabolic cluster conditions may benefit slightly more with decreased inpatient non-elective admissions (ES: −0.12). Only the three significant estimates for the musculoskeletal disorder cluster met the minimum requirement for at least a ‘small’ effect. Two of these estimates in particular were very large. This cluster represented only 0.5% of the total patients analysed, however, so is hugely vulnerable to the effects of outliers, and makes us very cautious of interpreting these as ‘real’ effects. Our results indicate no appropriate multimorbidity subgroup at which to target the case management intervention in terms of secondary care utilisation/cost outcomes. The most complex, highest risk patients may legitimately require hospitalisation, and the intensified management may better identify these unmet needs. End of life patients (e.g. Charlson index >5)/those with only conditions particularly amenable to primary care management (e.g. cardiovascular/metabolic cluster conditions) may benefit very slightly more than others.

A Cyber-Attack Detection Model Based on Multivariate Analyses

NASA Astrophysics Data System (ADS)

Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

Population-based study of Streptococcus suis infection in humans in Phayao Province in northern Thailand.

PubMed

Takeuchi, Dan; Kerdsin, Anusak; Pienpringam, Anupong; Loetthong, Phacharaphan; Samerchea, Sutit; Luangsuk, Pakkinee; Khamisara, Kasean; Wongwan, Nithita; Areeratana, Prasanee; Chiranairadul, Piphat; Lertchayanti, Suwat; Petcharat, Sininat; Yowang, Amara; Chaiwongsaen, Phanupong; Nakayama, Tatsuya; Akeda, Yukihiro; Hamada, Shigeyuki; Sawanpanyalert, Pathom; Dejsirilert, Surang; Oishi, Kazunori

2012-01-01

Streptococcus suis infection in humans has received increasing worldwide recognition. A prospective study of S. suis infection in humans was conducted in Phayao Province in northern Thailand to determine the incidence and the risk behaviors of the disease in this region in 2010. Thirty-one cases were confirmed. The case fatality rate was 16.1%, and the estimated incidence rate was 6.2 per 100,000 in the general population. The peak incidence occurred in May. The median age of the patients was 53 years and 64.5% were men. Consumption of raw pork products was confirmed in 22 cases and the median incubation period (range) was 2 days (0-11) after consumption of raw pork products. Isolates from 31 patients were confirmed as serotype 2 in 23 patients (74.2%) and serotype 14 in eight patients (25.8%). The major sequence types (STs) were ST1 (n = 20) for serotype 2 and ST105 (n = 8) for serotype 14. The epidemiological analysis suggested three possible clusters, which included 17 cases. In the largest possible cluster of 10 cases in Chiang Kham and its neighboring districts in May, the source of infection in four cases was identified as a raw pork dish served at the same restaurant in this district. Microbiological analysis confirmed that three of four cases associated with consumption of raw pork at this restaurant were attributable to an identical strain of serotype 2 with ST1 and pulsotype A2. Our data suggest a high incidence rate of S. suis infection in the general population in Phayao Province in 2010 and confirm a cluster of three cases in 31 human cases. Food safety control should be strengthened especially for raw pork products in northern Thailand.

Semi-supervised clustering methods

PubMed Central

Bair, Eric

2013-01-01

Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as “semi-supervised clustering” methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided. PMID:24729830

Universal patterns of equilibrium cluster growth in aqueous sugars observed by dynamic light scattering.

PubMed

Sidebottom, D L; Tran, Tri D

2010-11-01

Dynamic light scattering performed on aqueous solutions of three sugars (glucose, maltose and sucrose) reveal a common pattern of sugar cluster formation with a narrow cluster size distribution. In each case, equilibrium clusters form whose size increases with increasing sugar content in an identical power law manner in advance of a common, critical-like, percolation threshold near 83 wt % sugar. The critical exponent of the power law divergence of the cluster size varies with temperature, increasing with decreasing temperature, due to changes in the strength of the intermolecular hydrogen bond and appears to vanish for temperatures in excess of 90 °C. Detailed analysis of the cluster growth process suggests a two-stage process: an initial cluster phase formed at low volume fractions, ϕ, consisting of noninteracting, monodisperse sugar clusters whose size increases ϕ(1/3) followed by an aggregation stage, active at concentrations above about ϕ=40%, where cluster-cluster contact first occurs.

Typhoid fever acquired in the United States, 1999–2010: epidemiology, microbiology, and use of a space–time scan statistic for outbreak detection

PubMed Central

IMANISHI, M.; NEWTON, A. E.; VIEIRA, A. R.; GONZALEZ-AVILES, G.; KENDALL SCOTT, M. E.; MANIKONDA, K.; MAXWELL, T. N.; HALPIN, J. L.; FREEMAN, M. M.; MEDALLA, F.; AYERS, T. L.; DERADO, G.; MAHON, B. E.; MINTZ, E. D.

2016-01-01

SUMMARY Although rare, typhoid fever cases acquired in the United States continue to be reported. Detection and investigation of outbreaks in these domestically acquired cases offer opportunities to identify chronic carriers. We searched surveillance and laboratory databases for domestically acquired typhoid fever cases, used a space–time scan statistic to identify clusters, and classified clusters as outbreaks or non-outbreaks. From 1999 to 2010, domestically acquired cases accounted for 18% of 3373 reported typhoid fever cases; their isolates were less often multidrug-resistant (2% vs. 15%) compared to isolates from travel-associated cases. We identified 28 outbreaks and two possible outbreaks within 45 space–time clusters of ⩾2 domestically acquired cases, including three outbreaks involving ⩾2 molecular subtypes. The approach detected seven of the ten outbreaks published in the literature or reported to CDC. Although this approach did not definitively identify any previously unrecognized outbreaks, it showed the potential to detect outbreaks of typhoid fever that may escape detection by routine analysis of surveillance data. Sixteen outbreaks had been linked to a carrier. Every case of typhoid fever acquired in a non-endemic country warrants thorough investigation. Space–time scan statistics, together with shoe-leather epidemiology and molecular subtyping, may improve outbreak detection. PMID:25427666

Typhoid fever acquired in the United States, 1999-2010: epidemiology, microbiology, and use of a space-time scan statistic for outbreak detection.

PubMed

Imanishi, M; Newton, A E; Vieira, A R; Gonzalez-Aviles, G; Kendall Scott, M E; Manikonda, K; Maxwell, T N; Halpin, J L; Freeman, M M; Medalla, F; Ayers, T L; Derado, G; Mahon, B E; Mintz, E D

2015-08-01

Although rare, typhoid fever cases acquired in the United States continue to be reported. Detection and investigation of outbreaks in these domestically acquired cases offer opportunities to identify chronic carriers. We searched surveillance and laboratory databases for domestically acquired typhoid fever cases, used a space-time scan statistic to identify clusters, and classified clusters as outbreaks or non-outbreaks. From 1999 to 2010, domestically acquired cases accounted for 18% of 3373 reported typhoid fever cases; their isolates were less often multidrug-resistant (2% vs. 15%) compared to isolates from travel-associated cases. We identified 28 outbreaks and two possible outbreaks within 45 space-time clusters of ⩾2 domestically acquired cases, including three outbreaks involving ⩾2 molecular subtypes. The approach detected seven of the ten outbreaks published in the literature or reported to CDC. Although this approach did not definitively identify any previously unrecognized outbreaks, it showed the potential to detect outbreaks of typhoid fever that may escape detection by routine analysis of surveillance data. Sixteen outbreaks had been linked to a carrier. Every case of typhoid fever acquired in a non-endemic country warrants thorough investigation. Space-time scan statistics, together with shoe-leather epidemiology and molecular subtyping, may improve outbreak detection.

Role of mtDNA haplogroups in the prevalence of osteoarthritis in different geographic populations: a meta-analysis.

PubMed

Shen, Jin-Ming; Feng, Lei; Feng, Chun

2014-01-01

Osteoarthritis (OA) is the most common form of arthritis and has become an increasingly important public-health problem. However, the pathogenesis of OA is still unclear. In recent years, its correlation with mtDNA haplogroups attracts much attention. We aimed to perform a meta-analysis to investigate the association between mtDNA haplogroups and OA. Published English or Chinese literature from PubMed, Web of Science, SDOS, and CNKI was retrieved up until April 15, 2014. Case-control or cohort studies that detected the frequency of mtDNA haplogroups in OA patients and controls were included. The quality of the included studies was evaluated by the Newcastle-Ottawa Scale (NOS) assessment. A meta-analysis was conducted to calculate pooled odds ratio (OR) with 95% confidence interval (CI) through the random or fixed effect model, which was selected based on the between-study heterogeneity assessed by Q test and I2 test. Subgroup analysis was performed to explore the origin of heterogeneity. A total of 6 case-control studies (10590 cases and 7161 controls) with an average NOS score of 6.9 were involved. For the analysis between mtDNA haplogroup J and OA, random model was selected due to high heterogeneity. No significant association was found initially (OR = 0.73, 95%CI: 0.52-1.03), however, once any study from UK population was removed the association emerged. Further subgroup analysis demonstrated that there was a significant association in Spain population (OR = 0.57, 95%CI: 0.46-0.71), but not in UK population. Also, subgroup analysis revealed that there was a significant correlation between cluster TJ and OA in Spain population (OR = 0.70, 95%CI: 0.58-0.84), although not in UK population. No significant correlation was found between haplogroup T/cluster HV/cluster KU and OA. Our current meta-analysis suggests that mtDNA haplogroup J and cluster TJ correlate with the risk of OA in Spanish population, but the associations in other populations require further investigation.

A geo-computational algorithm for exploring the structure of diffusion progression in time and space.

PubMed

Chin, Wei-Chien-Benny; Wen, Tzai-Hung; Sabel, Clive E; Wang, I-Hsiang

2017-10-03

A diffusion process can be considered as the movement of linked events through space and time. Therefore, space-time locations of events are key to identify any diffusion process. However, previous clustering analysis methods have focused only on space-time proximity characteristics, neglecting the temporal lag of the movement of events. We argue that the temporal lag between events is a key to understand the process of diffusion movement. Using the temporal lag could help to clarify the types of close relationships. This study aims to develop a data exploration algorithm, namely the TrAcking Progression In Time And Space (TaPiTaS) algorithm, for understanding diffusion processes. Based on the spatial distance and temporal interval between cases, TaPiTaS detects sub-clusters, a group of events that have high probability of having common sources, identifies progression links, the relationships between sub-clusters, and tracks progression chains, the connected components of sub-clusters. Dengue Fever cases data was used as an illustrative case study. The location and temporal range of sub-clusters are presented, along with the progression links. TaPiTaS algorithm contributes a more detailed and in-depth understanding of the development of progression chains, namely the geographic diffusion process.

Chronological, geographical, and seasonal trends of human cases of avian influenza A (H5N1) in Vietnam, 2003-2014: a spatial analysis.

PubMed

Manabe, Toshie; Yamaoka, Kazue; Tango, Toshiro; Binh, Nguyen Gia; Co, Dao Xuan; Tuan, Nguyen Dang; Izumi, Shinyu; Takasaki, Jin; Chau, Ngo Quy; Kudo, Koichiro

2016-02-04

Human cases of highly pathogenic avian influenza A (H5N1) virus infection continue to occur in Southeast Asia. The objective of this study was to identify when and where human H5N1 cases have occurred in Vietnam and how the situation has changed from the beginning of the H5N1 outbreaks in 2003 through 2014, to assist with implementing methods of targeted disease management. We assessed the disease clustering and seasonal variation of human H5N1 cases in Vietnam to evaluate the geographical and monthly timing trends. The clustering of H5N1 cases and associated mortality were examined over three time periods: the outbreak period (2003-2005), the post-outbreak (2006-2009), and the recent period (2010-2014) using the flexibly shaped space-time scan statistic. The most likely cases to co-cluster and the elevated risks for incidence and mortality were assessed via calculation of the relative risk (RR). The H5N1 case seasonal variation was analysed as the cyclic trend in incidence data using Roger's statistical test. Between 2003 and 2005, H5N1 cases (RR: 2.15, p = 0.001) and mortality (RR: 2.49, p = 0.021) were significantly clustered in northern Vietnam. After 2010, H5N1 cases tended to occur on the border with Cambodia in the south, while H5N1 mortality clustered significantly in the Mekong delta area (RR: 6.62, p = 0.002). A significant seasonal variation was observed (p < 0.001), with a higher incidence of morbidity in December through April. These findings indicate that clinical preparedness for H5N1 in Vietnam needs to be strengthened in southern Vietnam in December-April.

Merging history of three bimodal clusters

NASA Astrophysics Data System (ADS)

Maurogordato, S.; Sauvageot, J. L.; Bourdin, H.; Cappi, A.; Benoist, C.; Ferrari, C.; Mars, G.; Houairi, K.

2011-01-01

We present a combined X-ray and optical analysis of three bimodal galaxy clusters selected as merging candidates at z ~ 0.1. These targets are part of MUSIC (MUlti-Wavelength Sample of Interacting Clusters), which is a general project designed to study the physics of merging clusters by means of multi-wavelength observations. Observations include spectro-imaging with XMM-Newton EPIC camera, multi-object spectroscopy (260 new redshifts), and wide-field imaging at the ESO 3.6 m and 2.2 m telescopes. We build a global picture of these clusters using X-ray luminosity and temperature maps together with galaxy density and velocity distributions. Idealized numerical simulations were used to constrain the merging scenario for each system. We show that A2933 is very likely an equal-mass advanced pre-merger ~200 Myr before the core collapse, while A2440 and A2384 are post-merger systems (~450 Myr and ~1.5 Gyr after core collapse, respectively). In the case of A2384, we detect a spectacular filament of galaxies and gas spreading over more than 1 h-1 Mpc, which we infer to have been stripped during the previous collision. The analysis of the MUSIC sample allows us to outline some general properties of merging clusters: a strong luminosity segregation of galaxies in recent post-mergers; the existence of preferential axes - corresponding to the merging directions - along which the BCGs and structures on various scales are aligned; the concomitance, in most major merger cases, of secondary merging or accretion events, with groups infalling onto the main cluster, and in some cases the evidence of previous merging episodes in one of the main components. These results are in good agreement with the hierarchical scenario of structure formation, in which clusters are expected to form by successive merging events, and matter is accreted along large-scale filaments. Based on data obtained with the European Southern Observatory, Chile (programs 072.A-0595, 075.A-0264, and 079.A-0425).Tables 5-7 are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/525/A79

From the Superatom Model to a Diverse Array of Super-Elements: A Systematic Study of Dopant Influence on the Electronic Structure of Thiolate-Protected Gold Clusters.

PubMed

Schacht, Julia; Gaston, Nicola

2016-10-18

The electronic properties of doped thiolate-protected gold clusters are often referred to as tunable, but their study to date, conducted at different levels of theory, does not allow a systematic evaluation of this claim. Here, using density functional theory, the applicability of the superatomic model to these clusters is critically evaluated, and related to the degree of structural distortion and electronic inhomogeneity in the differently doped clusters, with dopant atoms Pd, Pt, Cu, and Ag. The effect of electron number is systematically evaluated by varying the charge on the overall cluster, and the nominal number of delocalized electrons, employed in the superatomic model, is compared to the numbers obtained from Bader analysis of individual atomic charges. We find that the superatomic model is highly applicable to all of these clusters, and is able to predict and explain the changing electronic structure as a function of charge. However, significant perturbations of the model arise due to doping, due to distortions of the core structure of the Au 13 [RS(AuSR) 2 ] 6 - cluster. In addition, analysis of the electronic structure indicates that the superatomic character is distributed further across the ligand shell in the case of the doped clusters, which may have implications for the self-assembly of these clusters into materials. The prediction of appropriate clusters for such superatomic solids relies critically on such quantitative analysis of the tunability of the electronic structure. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Newspaper coverage of suicide and initiation of suicide clusters in teenagers in the USA, 1988-96: a retrospective, population-based, case-control study.

PubMed

Gould, Madelyn S; Kleinman, Marjorie H; Lake, Alison M; Forman, Judith; Midle, Jennifer Bassett

2014-06-01

Public health and clinical efforts to prevent suicide clusters are seriously hampered by the unanswered question of why such outbreaks occur. We aimed to establish whether an environmental factor-newspaper reports of suicide-has a role in the emergence of suicide clusters. In this retrospective, population-based, case-control study, we identified suicide clusters in young people aged 13-20 years in the USA from 1988 to 1996 (preceding the advent of social media) using the time-space Scan statistic. For each cluster community, we selected two matched non-cluster control communities in which suicides of similarly aged youth occurred, from non-contiguous counties within the same state as the cluster. We examined newspapers within each cluster community for stories about suicide published in the days between the first and second suicides in the cluster. In non-cluster communities, we examined a matched length of time after the matched control suicide. We used a content-analysis procedure to code the characteristics of each story and compared newspaper stories about suicide published in case and control communities with mixed-effect regression analyses. We identified 53 suicide clusters, of which 48 were included in the media review. For one cluster we could identify only one appropriate control; therefore, 95 matched control communities were included. The mean number of news stories about suicidal individuals published after an index cluster suicide (7·42 [SD 10·02]) was significantly greater than the mean number of suicide stories published after a non-cluster suicide (5·14 [6.00]; p<0·0001). Several story characteristics, including front-page placement, headlines containing the word suicide or a description of the method used, and detailed descriptions of the suicidal individual and act, appeared more often in stories published after the index cluster suicides than after non-cluster suicides. Our identification of an association between newspaper reports about suicide (including specific story characteristics) and the initiation of teenage suicide clusters should provide an empirical basis to support efforts by mental health professionals, community officials, and the media to work together to identify and prevent the onset of suicide clusters. US National Institute of Mental Health and American Foundation for Suicide Prevention. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using conjoint and cluster analysis in developing new product for micro, small and medium enterprises (SMEs) based on customer preferences (Case study: Lampung province's banana chips)

NASA Astrophysics Data System (ADS)

Kosasih, Wilson; Salomon, Lithrone Laricha; Hutomo, Reynaldo

2017-08-01

This paper discusses the development of new products of Micro, Small and Medium Entreprises (SMEs) to identify what attributes are considered by consumers, as well as combinations of attributes that need to be analyzed into the main preferences of consumers. The purpose of this research is to increase the added value and competitiveness of SMEs through product innovation. The object of this study is banana chips produced by SMEs from the province of Lampung which it considered to be unique souvenirs of the province. The research data were collected by distributing questionnaires in Jakarta which has heterogeneous population, in order to develop banana chip's marketing and increase its market share in Indonesia. Data processing was performed using conjoint analysis and cluster analysis. Segmentation was performed using conjoint analysis based on the importance level of attributes and part-worth of level attributes of each cluster. Finally, characteristics and consumer preferences of each cluster will be a consideration in determining the product development and marketing strategies.

Person mobility in the design and analysis of cluster-randomized cohort prevention trials.

PubMed

Vuchinich, Sam; Flay, Brian R; Aber, Lawrence; Bickman, Leonard

2012-06-01

Person mobility is an inescapable fact of life for most cluster-randomized (e.g., schools, hospitals, clinic, cities, state) cohort prevention trials. Mobility rates are an important substantive consideration in estimating the effects of an intervention. In cluster-randomized trials, mobility rates are often correlated with ethnicity, poverty and other variables associated with disparity. This raises the possibility that estimated intervention effects may generalize to only the least mobile segments of a population and, thus, create a threat to external validity. Such mobility can also create threats to the internal validity of conclusions from randomized trials. Researchers must decide how to deal with persons who leave study clusters during a trial (dropouts), persons and clusters that do not comply with an assigned intervention, and persons who enter clusters during a trial (late entrants), in addition to the persons who remain for the duration of a trial (stayers). Statistical techniques alone cannot solve the key issues of internal and external validity raised by the phenomenon of person mobility. This commentary presents a systematic, Campbellian-type analysis of person mobility in cluster-randomized cohort prevention trials. It describes four approaches for dealing with dropouts, late entrants and stayers with respect to data collection, analysis and generalizability. The questions at issue are: 1) From whom should data be collected at each wave of data collection? 2) Which cases should be included in the analyses of an intervention effect? and 3) To what populations can trial results be generalized? The conclusions lead to recommendations for the design and analysis of future cluster-randomized cohort prevention trials.

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Genome-Based Comparison of Clostridioides difficile: Average Amino Acid Identity Analysis of Core Genomes.

PubMed

Cabal, Adriana; Jun, Se-Ran; Jenjaroenpun, Piroon; Wanchai, Visanu; Nookaew, Intawat; Wongsurawat, Thidathip; Burgess, Mary J; Kothari, Atul; Wassenaar, Trudy M; Ussery, David W

2018-02-14

Infections due to Clostridioides difficile (previously known as Clostridium difficile) are a major problem in hospitals, where cases can be caused by community-acquired strains as well as by nosocomial spread. Whole genome sequences from clinical samples contain a lot of information but that needs to be analyzed and compared in such a way that the outcome is useful for clinicians or epidemiologists. Here, we compare 663 public available complete genome sequences of C. difficile using average amino acid identity (AAI) scores. This analysis revealed that most of these genomes (640, 96.5%) clearly belong to the same species, while the remaining 23 genomes produce four distinct clusters within the Clostridioides genus. The main C. difficile cluster can be further divided into sub-clusters, depending on the chosen cutoff. We demonstrate that MLST, either based on partial or full gene-length, results in biased estimates of genetic differences and does not capture the true degree of similarity or differences of complete genomes. Presence of genes coding for C. difficile toxins A and B (ToxA/B), as well as the binary C. difficile toxin (CDT), was deduced from their unique PfamA domain architectures. Out of the 663 C. difficile genomes, 535 (80.7%) contained at least one copy of ToxA or ToxB, while these genes were missing from 128 genomes. Although some clusters were enriched for toxin presence, these genes are variably present in a given genetic background. The CDT genes were found in 191 genomes, which were restricted to a few clusters only, and only one cluster lacked the toxin A/B genes consistently. A total of 310 genomes contained ToxA/B without CDT (47%). Further, published metagenomic data from stools were used to assess the presence of C. difficile sequences in blinded cases of C. difficile infection (CDI) and controls, to test if metagenomic analysis is sensitive enough to detect the pathogen, and to establish strain relationships between cases from the same hospital. We conclude that metagenomics can contribute to the identification of CDI and can assist in characterization of the most probable causative strain in CDI patients.

Narcolepsy with and without cataplexy, idiopathic hypersomnia with and without long sleep time: a cluster analysis.

PubMed

Šonka, Karel; Šusta, Marek; Billiard, Michel

2015-02-01

The successive editions of the International Classification of Sleep Disorders (ICSD) reflect the evolution of the concepts of various sleep disorders. This is particularly the case for central disorders of hypersomnolence, with continuous changes in terminology and divisions of narcolepsy, idiopathic hypersomnia, and recurrent hypersomnia. According to the ICSD 2nd Edition (ICSD-2), narcolepsy with cataplexy (NwithC), narcolepsy without cataplexy (Nw/oC), idiopathic hypersomnia with long sleep time (IHwithLST), and idiopathic hypersomnia without long sleep time (IHw/oLST) are four, well-defined hypersomnias of central origin. However, in the absence of biological markers, doubts have been raised as to the relevance of a division of idiopathic hypersomnia into two forms, and it is not yet clear whether Nw/oC and IHw/oLST are two distinct entities. With this in mind, it was decided to empirically review the ICSD-2 classification by using a hierarchical cluster analysis to see whether this division has some relevance, even though the terms "with long sleep time" and "without long sleep time" are inappropriate. The cluster analysis differentiated three main clusters: Cluster 1, "combined monosymptomatic hypersomnia/narcolepsy type 2" (people initially diagnosed with IHw/oLST and Nw/oC); Cluster 2 "polysymptomatic hypersomnia" (people initially diagnosed with IHwithLST); and Cluster 3, narcolepsy type 1 (people initially diagnosed with NwithC). Cluster analysis confirmed that narcolepsy type 1 and polysymptomatic hypersomnia are independent sleep disorders. People who were initially diagnosed with Nw/oC and IHw/oLST formed a single cluster, referred to as "combined monosymptomatic hypersomnia/narcolepsy type 2." Copyright © 2014 Elsevier B.V. All rights reserved.

Molecular clustering of patients with diabetes and pulmonary tuberculosis: A systematic review and meta-analysis

PubMed Central

Blanco-Guillot, Francles; Delgado-Sánchez, Guadalupe; Mongua-Rodríguez, Norma; Cruz-Hervert, Pablo; Ferreyra-Reyes, Leticia; Ferreira-Guerrero, Elizabeth; Yanes-Lane, Mercedes; Montero-Campos, Rogelio; Bobadilla-del-Valle, Miriam; Torres-González, Pedro; Ponce-de-León, Alfredo; Sifuentes-Osornio, José; Garcia-Garcia, Lourdes

2017-01-01

Introduction Many studies have explored the relationship between diabetes mellitus (DM) and tuberculosis (TB) demonstrating increased risk of TB among patients with DM and poor prognosis of patients suffering from the association of DM/TB. Owing to a paucity of studies addressing this question, it remains unclear whether patients with DM and TB are more likely than TB patients without DM to be grouped into molecular clusters defined according to the genotype of the infecting Mycobacterium tuberculosis bacillus. That is, whether there is convincing molecular epidemiological evidence for TB transmission among DM patients. Objective: We performed a systematic review and meta-analysis to quantitatively evaluate the propensity for patients with DM and pulmonary TB (PTB) to cluster according to the genotype of the infecting M. tuberculosis bacillus. Materials and methods We conducted a systematic search in MEDLINE and LILACS from 1990 to June, 2016 with the following combinations of key words “tuberculosis AND transmission” OR “tuberculosis diabetes mellitus” OR “Mycobacterium tuberculosis molecular epidemiology” OR “RFLP-IS6110” OR “Spoligotyping” OR “MIRU-VNTR”. Studies were included if they met the following criteria: (i) studies based on populations from defined geographical areas; (ii) use of genotyping by IS6110- restriction fragment length polymorphism (RFLP) analysis and spoligotyping or mycobacterial interspersed repetitive unit-variable number of tandem repeats (MIRU-VNTR) or other amplification methods to identify molecular clustering; (iii) genotyping and analysis of 50 or more cases of PTB; (iv) study duration of 11 months or more; (v) identification of quantitative risk factors for molecular clustering including DM; (vi) > 60% coverage of the study population; and (vii) patients with PTB confirmed bacteriologically. The exclusion criteria were: (i) Extrapulmonary TB; (ii) TB caused by nontuberculous mycobacteria; (iii) patients with PTB and HIV; (iv) pediatric PTB patients; (v) TB in closed environments (e.g. prisons, elderly homes, etc.); (vi) diabetes insipidus and (vii) outbreak reports. Hartung-Knapp-Sidik-Jonkman method was used to estimate the odds ratio (OR) of the association between DM with molecular clustering of cases with TB. In order to evaluate the degree of heterogeneity a statistical Q test was done. The publication bias was examined with Begg and Egger tests. Review Manager 5.3.5 CMA v.3 and Biostat and Software package R were used. Results Selection criteria were met by six articles which included 4076 patients with PTB of which 13% had DM. Twenty seven percent of the cases were clustered. The majority of cases (48%) were reported in a study in China with 31% clustering. The highest incidence of TB occurred in two studies from China. The global OR for molecular clustering was 0.84 (IC 95% 0.40–1.72). The heterogeneity between studies was moderate (I2 = 55%, p = 0.05), although there was no publication bias (Beggs test p = 0.353 and Eggers p = 0.429). Conclusion There were very few studies meeting our selection criteria. The wide confidence interval indicates that there is not enough evidence to draw conclusions about the association. Clustering of patients with DM in TB transmission chains should be investigated in areas where both diseases are prevalent and focus on specific contexts. PMID:28902922

Cosmology with the largest galaxy cluster surveys: going beyond Fisher matrix forecasts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khedekar, Satej; Majumdar, Subhabrata, E-mail: satej@mpa-garching.mpg.de, E-mail: subha@tifr.res.in

2013-02-01

We make the first detailed MCMC likelihood study of cosmological constraints that are expected from some of the largest, ongoing and proposed, cluster surveys in different wave-bands and compare the estimates to the prevalent Fisher matrix forecasts. Mock catalogs of cluster counts expected from the surveys — eROSITA, WFXT, RCS2, DES and Planck, along with a mock dataset of follow-up mass calibrations are analyzed for this purpose. A fair agreement between MCMC and Fisher results is found only in the case of minimal models. However, for many cases, the marginalized constraints obtained from Fisher and MCMC methods can differ bymore » factors of 30-100%. The discrepancy can be alarmingly large for a time dependent dark energy equation of state, w(a); the Fisher methods are seen to under-estimate the constraints by as much as a factor of 4-5. Typically, Fisher estimates become more and more inappropriate as we move away from ΛCDM, to a constant-w dark energy to varying-w dark energy cosmologies. Fisher analysis, also, predicts incorrect parameter degeneracies. There are noticeable offsets in the likelihood contours obtained from Fisher methods that is caused due to an asymmetry in the posterior likelihood distribution as seen through a MCMC analysis. From the point of mass-calibration uncertainties, a high value of unknown scatter about the mean mass-observable relation, and its redshift dependence, is seen to have large degeneracies with the cosmological parameters σ{sub 8} and w(a) and can degrade the cosmological constraints considerably. We find that the addition of mass-calibrated cluster datasets can improve dark energy and σ{sub 8} constraints by factors of 2-3 from what can be obtained from CMB+SNe+BAO only . Finally, we show that a joint analysis of datasets of two (or more) different cluster surveys would significantly tighten cosmological constraints from using clusters only. Since, details of future cluster surveys are still being planned, we emphasize that optimal survey design must be done using MCMC analysis rather than Fisher forecasting.« less

A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications.

PubMed

Sun, Liping; Luo, Yonglong; Ding, Xintao; Zhang, Ji

2014-01-01

An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

BCR-ABL1- positive chronic myeloid leukemia with erythrocytosis presenting as polycythemia vera: a case report.

PubMed

Cornea, Mihaela I Precup; Levrat, Emmanuel; Pugin, Paul; Betticher, Daniel C

2015-04-08

The World Health Organization classification of chronic myeloproliferative disease encompasses eight entities of bone marrow neoplasms, among them Breakpoint cluster region-Abelson murine leukemia viral oncogene homolog 1-positive chronic myeloid leukemia and polycythemia vera. Polycythemia vera requires, in the majority of cases (95%), the negativity of Breakpoint cluster region-Abelson murine leukemia viral oncogene homolog 1 rearrangement and the presence of the Janus kinase 2 mutation. We report a case of erythrocytosis as the primary manifestation of a chronic myeloid leukemia, with the presence of the Philadelphia chromosome and the Breakpoint cluster region-Abelson murine leukemia viral oncogene homolog 1 fusion gene, and in the absence of any Janus kinase 2 mutation. A 68-year-old Caucasian woman, with a history of cigarette consumption and obstructive sleep apnoea syndrome (undergoing continuous positive airway pressure treatment) had presented to our institution with fatigue and a hemoglobin level of 18.6g/L, with slight leukocytosis at 16G/L, and no other anomalies on her complete blood cell count. Examination of her arterial blood gases found only a slight hypoxemia; erythropoietin and ferritin levels were very low and could not explain a secondary erythrocytosis. Further analyses revealed the absence of any Janus kinase 2 mutation, thus excluding polycythemia vera. Taken together with a high vitamin B12 level, we conducted a Breakpoint cluster region-Abelson murine leukemia viral oncogene homolog 1 gene analysis and bone marrow cytogenetic analysis, both of which returned positive, leading to the diagnosis of chronic myeloid leukemia. To date, this case is the first description of a Breakpoint cluster region-Abelson murine leukemia viral oncogene homolog 1-positive chronic myeloid leukemia, presenting with erythrocytosis as the initial manifestation, and mimicking a Janus kinase 2 V617F-negative polycythemia vera. Her impressive response to imatinib therapy underscores the importance of not missing this diagnosis.

Spatiotemporal patterns of severe fever with thrombocytopenia syndrome in China, 2011-2016.

PubMed

Sun, Jimin; Lu, Liang; Wu, Haixia; Yang, Jun; Liu, Keke; Liu, Qiyong

2018-05-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and the number of SFTS cases have increased year by year in China. However, spatiotemporal patterns and trends of SFTS are less clear up to date. In order to explore spatiotemporal patterns and predict SFTS incidences, we analyzed temporal trends of SFTS using autoregressive integrated moving average (ARIMA) model, spatial patterns, and spatiotemporal clusters of SFTS cases at the county level based on SFTS data in China during 2011-2016. We determined the optimal time series model was ARIMA (2, 0, 1) × (0, 0, 1) 12 which fitted the SFTS cases reasonably well during the training process and forecast process. In the spatial clustering analysis, the global autocorrelation suggested that SFTS cases were not of random distribution. Local spatial autocorrelation analysis of SFTS identified foci mainly concentrated in Hubei Province, Henan Province, Anhui Province, Shandong Province, Liaoning Province, and Zhejiang Province. A most likely cluster including 21 counties in Henan Province and Hubei Province was observed in the central region of China from April 2015 to August 2016. Our results will provide a sound evidence base for future prevention and control programs of SFTS such as allocation of the health resources, surveillance in high-risk regions, health education, improvement of diagnosis and so on. Copyright © 2018 Elsevier GmbH. All rights reserved.

An Enhanced K-Means Algorithm for Water Quality Analysis of The Haihe River in China

PubMed Central

Zou, Hui; Zou, Zhihong; Wang, Xiaojing

2015-01-01

The increase and the complexity of data caused by the uncertain environment is today’s reality. In order to identify water quality effectively and reliably, this paper presents a modified fast clustering algorithm for water quality analysis. The algorithm has adopted a varying weights K-means cluster algorithm to analyze water monitoring data. The varying weights scheme was the best weighting indicator selected by a modified indicator weight self-adjustment algorithm based on K-means, which is named MIWAS-K-means. The new clustering algorithm avoids the margin of the iteration not being calculated in some cases. With the fast clustering analysis, we can identify the quality of water samples. The algorithm is applied in water quality analysis of the Haihe River (China) data obtained by the monitoring network over a period of eight years (2006–2013) with four indicators at seven different sites (2078 samples). Both the theoretical and simulated results demonstrate that the algorithm is efficient and reliable for water quality analysis of the Haihe River. In addition, the algorithm can be applied to more complex data matrices with high dimensionality. PMID:26569283

Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

PubMed Central

Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

2013-01-01

Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

Fatality rate of pedestrians and fatal crash involvement rate of drivers in pedestrian crashes: a case study of Iran.

PubMed

Kashani, Ali Tavakoli; Besharati, Mohammad Mehdi

2017-06-01

The aim of this study was to uncover patterns of pedestrian crashes. In the first stage, 34,178 pedestrian-involved crashes occurred in Iran during a four-year period were grouped into homogeneous clusters using a clustering analysis. Next, some in-cluster and inter-cluster crash patterns were analysed. The clustering analysis yielded six pedestrian crash groups. Car/van/pickup crashes on rural roads as well as heavy vehicle crashes were found to be less frequent but more likely to be fatal compared to other crash clusters. In addition, after controlling for crash frequency in each cluster, it was found that the fatality rate of each pedestrian age group as well as the fatal crash involvement rate of each driver age group varies across the six clusters. Results of present study has some policy implications including, promoting pedestrian safety training sessions for heavy vehicle drivers, imposing limitations over elderly heavy vehicle drivers, reinforcing penalties toward under 19 drivers and motorcyclists. In addition, road safety campaigns in rural areas may be promoted to inform people about the higher fatality rate of pedestrians on rural roads. The crash patterns uncovered in this study might also be useful for prioritizing future pedestrian safety research areas.

Two novel translocation breakpoints upstream of SOX9 define borders of the proximal and distal breakpoint cluster region in campomelic dysplasia.

PubMed

Leipoldt, M; Erdel, M; Bien-Willner, G A; Smyk, M; Theurl, M; Yatsenko, S A; Lupski, J R; Lane, A H; Shanske, A L; Stankiewicz, P; Scherer, G

2007-01-01

The semilethal skeletal malformation syndrome campomelic dysplasia (CD) with or without XY sex reversal is caused by mutations within the SOX9 gene on 17q24.3 or by chromosomal aberrations (translocations, inversions or deletions) with breakpoints outside the SOX9 coding region. The previously published CD translocation breakpoints upstream of SOX9 fall into two clusters: a proximal cluster with breakpoints between 50-300 kb and a distal cluster with breakpoints between 899-932 kb. Here, we present clinical, cytogenetic and molecular data from two novel CD translocation cases. Case 1 with karyotype 46,XY,t(1;17)(q42.1;q24.3) has characteristic symptoms of CD, including mild tibial bowing, cryptorchidism and hypospadias. By standard fluorescence in situ hybridization (FISH) and by high-resolution fiber FISH, the 17q breakpoint was mapped 375 kb from SOX9, defining the centromeric border of the proximal breakpoint cluster region. Case 2 with karyotype 46,X,t(Y;17)(q11.2;q24.3) has the acampomelic form of CD and complete XY sex reversal. By FISH and somatic cell hybrid analysis, the 17q breakpoint was mapped 789 kb from SOX9, defining the telomeric border of the distal breakpoint cluster region. We discuss the structure of the 1 Mb cis-control region upstream of SOX9 and the correlation between the position of the 14 mapped translocation breakpoints with respect to disease severity and XY sex reversal.

Use of molecular testing to identify a cluster of patients with polycythemia vera in eastern Pennsylvania.

PubMed

Seaman, Vincent; Jumaan, Aisha; Yanni, Emad; Lewis, Brian; Neyer, Jonathan; Roda, Paul; Xu, Mingjiang; Hoffman, Ronald

2009-02-01

The role of the environment in the origin of polycythemia vera has not been well documented. Recently, molecular diagnostic tools have been developed to facilitate the diagnosis of polycythemia vera. A cluster of patients with polycythemia vera was suspected in three countries in eastern Pennsylvania where there have long been a concern about environment hazards. Rigorous clinical criteria and JAK2 617V>F testing were used to confirm the diagnosis of polycythemia vera in patients in this area. Participants included cases of polycythemia vera from the 2001 to 2005 state cancer registry as well as self- and physician-referred cases. A diagnosis of polycythemia vera was confirmed in 53% of 62 participants using WHO criteria, which includes JAK2 617V>F testing. A statistically significant cluster of cases (P < 0.001) was identified where the incidence of polycythemia vera was 4.3 times that of the rest of the study area. The area of the cluster contained numerous sources of hazardous material including waste-coal power plants and U.S. Environmental Protection Agency Superfund sites. The diagnosis of polycythemia vera based solely on clinical criteria is frequently erroneous, suggesting that our prior knowledge of the epidemiology of this disease might be inaccurate. The JAK2 617V>F mutational analysis provides diagnostic clarity and permitted the confirmation of a cluster of polycythemia vera cases not identified by traditional clinical and pathologic diagnostic criteria. The close proximity of this cluster to known areas of hazardous material exposure raises concern that such environmental factors might play a role in the origin of polycythemia vera.

Identification of different nutritional status groups in institutionalized elderly people by cluster analysis.

PubMed

López-Contreras, María José; López, Maria Ángeles; Canteras, Manuel; Candela, María Emilia; Zamora, Salvador; Pérez-Llamas, Francisca

2014-03-01

To apply a cluster analysis to groups of individuals of similar characteristics in an attempt to identify undernutrition or the risk of undernutrition in this population. A cross-sectional study. Seven public nursing homes in the province of Murcia, on the Mediterranean coast of Spain. 205 subjects aged 65 and older (131 women and 74 men). Dietary intake (energy and nutrients), anthropometric (body mass index, skinfold thickness, mid-arm muscle circumference, mid-arm muscle area, corrected arm muscle area, waist to hip ratio) and biochemical and haematological (serum albumin, transferrin, total cholesterol, total lymphocyte count). Variables were analyzed by cluster analysis. The results of the cluster analysis, including intake, anthropometric and analytical data showed that, of the 205 elderly subjects, 66 (32.2%) were over - weight/obese, 72 (35.1%) had an adequate nutritional status and 67 (32.7%) were undernourished or at risk of undernutrition. The undernourished or at risk of undernutrition group showed the lowest values for dietary intake and the anthropometric and analytical parameters measured. Our study shows that cluster analysis is a useful statistical method for assessing the nutritional status of institutionalized elderly populations. In contrast, use of the specific reference values frequently described in the literature might fail to detect real cases of undernourishment or those at risk of undernutrition. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Canine parvovirus in Australia: the role of socio-economic factors in disease clusters.

PubMed

Brady, S; Norris, J M; Kelman, M; Ward, M P

2012-08-01

To identify clusters of canine parvoviral related disease occurring in Australia during 2010 and investigate the role of socio-economic factors contributing to these clusters, reported cases of canine parvovirus were extracted from an on-line disease surveillance system. Reported residential postcode was used to locate cases, and clusters were identified using a scan statistic. Cases included in clusters were compared to those not included in such clusters with respect to human socioeconomic factors (postcode area relative socioeconomic disadvantage, economic resources, education and occupation) and dog factors (neuter status, breed, age, gender, vaccination status). During 2010, there were 1187 cases of canine parvovirus reported. Nineteen significant (P<0.05) disease clusters were identified, most commonly located in New South Wales. Eleven (58%) clusters occurred between April and July, and the average cluster length was 5.7 days. All clusters occurred in postcodes with a significantly (P<0.05) greater level of relative socioeconomic disadvantage and a lower rank in education and occupation, and it was noted that clustered cases were less likely to have been neutered (P=0.004). No significant difference (P>0.05) was found between cases reported from cluster postcodes and those not within clusters for dog age, gender, breed or vaccination status (although the latter needs to be interpreted with caution, since vaccination was absent in most of the cases). Further research is required to investigate the apparent association between indicators of poor socioeconomic status and clusters of reported canine parvovirus diseases; however these initial findings may be useful for developing geographically- and temporally-targeted prevention and disease control programs. Copyright © 2012 Elsevier Ltd. All rights reserved.

The use of the temporal scan statistic to detect methicillin-resistant Staphylococcus aureus clusters in a community hospital.

PubMed

Faires, Meredith C; Pearl, David L; Ciccotelli, William A; Berke, Olaf; Reid-Smith, Richard J; Weese, J Scott

2014-07-08

In healthcare facilities, conventional surveillance techniques using rule-based guidelines may result in under- or over-reporting of methicillin-resistant Staphylococcus aureus (MRSA) outbreaks, as these guidelines are generally unvalidated. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting MRSA clusters, validate clusters using molecular techniques and hospital records, and determine significant differences in the rate of MRSA cases using regression models. Patients admitted to a community hospital between August 2006 and February 2011, and identified with MRSA>48 hours following hospital admission, were included in this study. Between March 2010 and February 2011, MRSA specimens were obtained for spa typing. MRSA clusters were investigated using a retrospective temporal scan statistic. Tests were conducted on a monthly scale and significant clusters were compared to MRSA outbreaks identified by hospital personnel. Associations between the rate of MRSA cases and the variables year, month, and season were investigated using a negative binomial regression model. During the study period, 735 MRSA cases were identified and 167 MRSA isolates were spa typed. Nine different spa types were identified with spa type 2/t002 (88.6%) the most prevalent. The temporal scan statistic identified significant MRSA clusters at the hospital (n=2), service (n=16), and ward (n=10) levels (P ≤ 0.05). Seven clusters were concordant with nine MRSA outbreaks identified by hospital staff. For the remaining clusters, seven events may have been equivalent to true outbreaks and six clusters demonstrated possible transmission events. The regression analysis indicated years 2009-2011, compared to 2006, and months March and April, compared to January, were associated with an increase in the rate of MRSA cases (P ≤ 0.05). The application of the temporal scan statistic identified several MRSA clusters that were not detected by hospital personnel. The identification of specific years and months with increased MRSA rates may be attributable to several hospital level factors including the presence of other pathogens. Within hospitals, the incorporation of the temporal scan statistic to standard surveillance techniques is a valuable tool for healthcare workers to evaluate surveillance strategies and aid in the identification of MRSA clusters.

Efficacy and effectiveness of an rVSV-vectored vaccine expressing Ebola surface glycoprotein: interim results from the Guinea ring vaccination cluster-randomised trial.

PubMed

Henao-Restrepo, Ana Maria; Longini, Ira M; Egger, Matthias; Dean, Natalie E; Edmunds, W John; Camacho, Anton; Carroll, Miles W; Doumbia, Moussa; Draguez, Bertrand; Duraffour, Sophie; Enwere, Godwin; Grais, Rebecca; Gunther, Stephan; Hossmann, Stefanie; Kondé, Mandy Kader; Kone, Souleymane; Kuisma, Eeva; Levine, Myron M; Mandal, Sema; Norheim, Gunnstein; Riveros, Ximena; Soumah, Aboubacar; Trelle, Sven; Vicari, Andrea S; Watson, Conall H; Kéïta, Sakoba; Kieny, Marie Paule; Røttingen, John-Arne

2015-08-29

A recombinant, replication-competent vesicular stomatitis virus-based vaccine expressing a surface glycoprotein of Zaire Ebolavirus (rVSV-ZEBOV) is a promising Ebola vaccine candidate. We report the results of an interim analysis of a trial of rVSV-ZEBOV in Guinea, west Africa. For this open-label, cluster-randomised ring vaccination trial, suspected cases of Ebola virus disease in Basse-Guinée (Guinea, west Africa) were independently ascertained by Ebola response teams as part of a national surveillance system. After laboratory confirmation of a new case, clusters of all contacts and contacts of contacts were defined and randomly allocated 1:1 to immediate vaccination or delayed (21 days later) vaccination with rVSV-ZEBOV (one dose of 2 × 10(7) plaque-forming units, administered intramuscularly in the deltoid muscle). Adults (age ≥18 years) who were not pregnant or breastfeeding were eligible for vaccination. Block randomisation was used, with randomly varying blocks, stratified by location (urban vs rural) and size of rings (≤20 vs >20 individuals). The study is open label and masking of participants and field teams to the time of vaccination is not possible, but Ebola response teams and laboratory workers were unaware of allocation to immediate or delayed vaccination. Taking into account the incubation period of the virus of about 10 days, the prespecified primary outcome was laboratory-confirmed Ebola virus disease with onset of symptoms at least 10 days after randomisation. The primary analysis was per protocol and compared the incidence of Ebola virus disease in eligible and vaccinated individuals in immediate vaccination clusters with the incidence in eligible individuals in delayed vaccination clusters. This trial is registered with the Pan African Clinical Trials Registry, number PACTR201503001057193. Between April 1, 2015, and July 20, 2015, 90 clusters, with a total population of 7651 people were included in the planned interim analysis. 48 of these clusters (4123 people) were randomly assigned to immediate vaccination with rVSV-ZEBOV, and 42 clusters (3528 people) were randomly assigned to delayed vaccination with rVSV-ZEBOV. In the immediate vaccination group, there were no cases of Ebola virus disease with symptom onset at least 10 days after randomisation, whereas in the delayed vaccination group there were 16 cases of Ebola virus disease from seven clusters, showing a vaccine efficacy of 100% (95% CI 74·7-100·0; p=0·0036). No new cases of Ebola virus disease were diagnosed in vaccinees from the immediate or delayed groups from 6 days post-vaccination. At the cluster level, with the inclusion of all eligible adults, vaccine effectiveness was 75·1% (95% CI -7·1 to 94·2; p=0·1791), and 76·3% (95% CI -15·5 to 95·1; p=0·3351) with the inclusion of everyone (eligible or not eligible for vaccination). 43 serious adverse events were reported; one serious adverse event was judged to be causally related to vaccination (a febrile episode in a vaccinated participant, which resolved without sequelae). Assessment of serious adverse events is ongoing. The results of this interim analysis indicate that rVSV-ZEBOV might be highly efficacious and safe in preventing Ebola virus disease, and is most likely effective at the population level when delivered during an Ebola virus disease outbreak via a ring vaccination strategy. WHO, with support from the Wellcome Trust (UK); Médecins Sans Frontières; the Norwegian Ministry of Foreign Affairs through the Research Council of Norway; and the Canadian Government through the Public Health Agency of Canada, Canadian Institutes of Health Research, International Development Research Centre, and Department of Foreign Affairs, Trade and Development. Copyright © 2015 World Health Organization. Published by Elsevier Ltd/Inc/BV. All rights reserved. Published by Elsevier Ltd.. All rights reserved.

A comparison of hair colour measurement by digital image analysis with reflective spectrophotometry.

PubMed

Vaughn, Michelle R; van Oorschot, Roland A H; Baindur-Hudson, Swati

2009-01-10

While reflective spectrophotometry is an established method for measuring macroscopic hair colour, it can be cumbersome to use on a large number of individuals and not all reflective spectrophotometry instruments are easily portable. This study investigates the use of digital photographs to measure hair colour and compares its use to reflective spectrophotometry. An understanding of the accuracy of colour determination by these methods is of relevance when undertaking specific investigations, such as those on the genetics of hair colour. Measurements of hair colour may also be of assistance in cases where a photograph is the only evidence of hair colour available (e.g. surveillance). Using the CIE L(*)a(*)b(*) colour space, the hair colour of 134 individuals of European ancestry was measured by both reflective spectrophotometry and by digital image analysis (in V++). A moderate correlation was found along all three colour axes, with Pearson correlation coefficients of 0.625, 0.593 and 0.513 for L(*), a(*) and b(*) respectively (p-values=0.000), with means being significantly overestimated by digital image analysis for all three colour components (by an average of 33.42, 3.38 and 8.00 for L(*), a(*) and b(*) respectively). When using digital image data to group individuals into clusters previously determined by reflective spectrophotometric analysis using a discriminant analysis, individuals were classified into the correct clusters 85.8% of the time when there were two clusters. The percentage of cases correctly classified decreases as the number of clusters increases. It is concluded that, although more convenient, hair colour measurement from digital images has limited use in situations requiring accurate and consistent measurements.

Finding approximate gene clusters with Gecko 3.

PubMed

Winter, Sascha; Jahn, Katharina; Wehner, Stefanie; Kuchenbecker, Leon; Marz, Manja; Stoye, Jens; Böcker, Sebastian

2016-11-16

Gene-order-based comparison of multiple genomes provides signals for functional analysis of genes and the evolutionary process of genome organization. Gene clusters are regions of co-localized genes on genomes of different species. The rapid increase in sequenced genomes necessitates bioinformatics tools for finding gene clusters in hundreds of genomes. Existing tools are often restricted to few (in many cases, only two) genomes, and often make restrictive assumptions such as short perfect conservation, conserved gene order or monophyletic gene clusters. We present Gecko 3, an open-source software for finding gene clusters in hundreds of bacterial genomes, that comes with an easy-to-use graphical user interface. The underlying gene cluster model is intuitive, can cope with low degrees of conservation as well as misannotations and is complemented by a sound statistical evaluation. To evaluate the biological benefit of Gecko 3 and to exemplify our method, we search for gene clusters in a dataset of 678 bacterial genomes using Synechocystis sp. PCC 6803 as a reference. We confirm detected gene clusters reviewing the literature and comparing them to a database of operons; we detect two novel clusters, which were confirmed by publicly available experimental RNA-Seq data. The computational analysis is carried out on a laptop computer in <40 min. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Salmonella enterica Pulsed-Field Gel Electrophoresis Clusters, Minnesota, USA, 2001–2007

PubMed Central

Hedberg, Craig W.; Meyer, Stephanie; Boxrud, David J.; Smith, Kirk E.

2010-01-01

We determined characteristics of Salmonella enterica pulsed-field gel electrophoresis clusters that predict their being solved (i.e., that result in identification of a confirmed outbreak). Clusters were investigated by the Minnesota Department of Health by using a dynamic iterative model. During 2001–2007, a total of 43 (12.5%) of 344 clusters were solved. Clusters of >4 isolates were more likely to be solved than clusters of 2 isolates. Clusters in which the first 3 case isolates were received at the Minnesota Department of Health within 7 days were more likely to be solved than were clusters in which the first 3 case isolates were received over a period >14 days. If resources do not permit investigation of all S. enterica pulsed-field gel electrophoresis clusters, investigation of clusters of >4 cases and clusters in which the first 3 case isolates were received at a public health laboratory within 7 days may improve outbreak investigations. PMID:21029524

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Identification of PM10 air pollution origins at a rural background site

NASA Astrophysics Data System (ADS)

Reizer, Magdalena; Orza, José A. G.

2018-01-01

Trajectory cluster analysis and concentration weighted trajectory (CWT) approach have been applied to investigate the origins of PM10 air pollution recorded at a rural background site in North-eastern Poland (Diabla Góra). Air mass back-trajectories used in this study have been computed with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model for a 10-year period of 2006-2015. A cluster analysis grouped back-trajectories into 7 clusters. Most of the trajectories correspond to fast and moderately moving westerly and northerly flows (45% and 25% of the cases, respectively). However, significantly higher PM10 concentrations were observed for slow moving easterly (11%) and southerly (20%) air masses. The CWT analysis shows that high PM10 levels are observed at Diabla Góra site when air masses are originated and passed over the heavily industrialized areas in Central-Eastern Europe located to the south and south-east of the site.

Unlearning of Mixed States in the Hopfield Model —Extensive Loading Case—

NASA Astrophysics Data System (ADS)

Hayashi, Kao; Hashimoto, Chinami; Kimoto, Tomoyuki; Uezu, Tatsuya

2018-05-01

We study the unlearning of mixed states in the Hopfield model for the extensive loading case. Firstly, we focus on case I, where several embedded patterns are correlated with each other, whereas the rest are uncorrelated. Secondly, we study case II, where patterns are divided into clusters in such a way that patterns in any cluster are correlated but those in two different clusters are not correlated. By using the replica method, we derive the saddle point equations for order parameters under the ansatz of replica symmetry. The same equations are also derived by self-consistent signal-to-noise analysis in case I. In both cases I and II, we find that when the correlation between patterns is large, the network loses its ability to retrieve the embedded patterns and, depending on the parameters, a confused memory, which is a mixed state and/or spin glass state, emerges. By unlearning the mixed state, the network acquires the ability to retrieve the embedded patterns again in some parameter regions. We find that to delete the mixed state and to retrieve the embedded patterns, the coefficient of unlearning should be chosen appropriately. We perform Markov chain Monte Carlo simulations and find that the simulation and theoretical results agree reasonably well, except for the spin glass solution in a parameter region due to the replica symmetry breaking. Furthermore, we find that the existence of many correlated clusters reduces the stabilities of both embedded patterns and mixed states.

Spatial analysis of county-based gonorrhoea incidence in mainland China, from 2004 to 2009.

PubMed

Yin, Fei; Feng, Zijian; Li, Xiaosong

2012-07-01

Gonorrhoea is one of the most common sexually transmissible infections in mainland China. Effective spatial monitoring of gonorrhoea incidence is important for successful implementation of control and prevention programs. The county-level gonorrhoea incidence rates for all of mainland China was monitored through examining spatial patterns. County-level data on gonorrhoea cases between 2004 and 2009 were obtained from the China Information System for Disease Control and Prevention. Bayesian smoothing and exploratory spatial data analysis (ESDA) methods were used to characterise the spatial distribution pattern of gonorrhoea cases. During the 6-year study period, the average annual gonorrhoea incidence was 12.41 cases per 100000 people. Using empirical Bayes smoothed rates, the local Moran test identified one significant single-centre cluster and two significant multi-centre clusters of high gonorrhoea risk (all P-values <0.01). Bayesian smoothing and ESDA methods can assist public health officials in using gonorrhoea surveillance data to identify high risk areas. Allocating more resources to such areas could effectively reduce gonorrhoea incidence.

Coronal Mass Ejection Data Clustering and Visualization of Decision Trees

NASA Astrophysics Data System (ADS)

Ma, Ruizhe; Angryk, Rafal A.; Riley, Pete; Filali Boubrahimi, Soukaina

2018-05-01

Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.

Rationalizing the role of structural motif and underlying electronic structure in the finite temperature behavior of atomic clusters

NASA Astrophysics Data System (ADS)

Susan, Anju; Joshi, Kavita

2014-04-01

Melting in finite size systems is an interesting but complex phenomenon. Many factors affect melting and owing to their interdependencies it is a challenging task to rationalize their roles in the phase transition. In this work, we demonstrate how structural motif of the ground state influences melting transition in small clusters. Here, we report a case with clusters of aluminum and gallium having same number of atoms, valence electrons, and similar structural motif of the ground state but drastically different melting temperatures. We have employed Born-Oppenheimer molecular dynamics to simulate the solid-like to liquid-like transition in these clusters. Our simulations have reproduced the experimental trends fairly well. Further, the detailed analysis of isomers has brought out the role of the ground state structure and underlying electronic structure in the finite temperature behavior of these clusters. For both clusters, isomers accessible before cluster melts have striking similarities and does have strong influence of the structural motif of the ground state. Further, the shape of the heat capacity curve is similar in both the cases but the transition is more spread over for Al36 which is consistent with the observed isomerization pattern. Our simulations also suggest a way to characterize transition region on the basis of accessibility of the ground state at a specific temperature.

Cluster: Mission Overview and End-of-Life Analysis

NASA Technical Reports Server (NTRS)

Pallaschke, S.; Munoz, I.; Rodriquez-Canabal, J.; Sieg, D.; Yde, J. J.

2007-01-01

The Cluster mission is part of the scientific programme of the European Space Agency (ESA) and its purpose is the analysis of the Earth's magnetosphere. The Cluster project consists of four satellites. The selected polar orbit has a shape of 4.0 and 19.2 Re which is required for performing measurements near the cusp and the tail of the magnetosphere. When crossing these regions the satellites form a constellation which in most of the cases so far has been a regular tetrahedron. The satellite operations are carried out by the European Space Operations Centre (ESOC) at Darmstadt, Germany. The paper outlines the future orbit evolution and the envisaged operations from a Flight Dynamics point of view. In addition a brief summary of the LEOP and routine operations is included beforehand.

Haplotypic Analysis of Wellcome Trust Case Control Consortium Data

PubMed Central

Browning, Brian L.; Browning, Sharon R.

2008-01-01

We applied a recently developed multilocus association testing method (localized haplotype clustering) to Wellcome Trust Case Control Consortium data (14,000 cases of seven common diseases and 3,000 shared controls genotyped on the Affymetrix 500K array). After rigorous data quality filtering, we identified three disease-associated loci with strong statistical support from localized haplotype cluster tests but with only marginal significance in single marker tests. These loci are chromosomes 10p15.1 with type 1 diabetes (p = 5.1 × 10-9), 12q15 with type 2 diabetes (p = 1.9 × 10-7) and 15q26.2 with hypertension (p = 2.8 × 10-8). We also detected the association of chromosome 9p21.3 with type 2 diabetes (p = 2.8 × 10-8), although this locus did not pass our stringent genotype quality filters. The association of 10p15.1 with type 1 diabetes and 9p21.3 with type 2 diabetes have both been replicated in other studies using independent data sets. Overall, localized haplotype cluster analysis had better success detecting disease associated variants than a previous single-marker analysis of imputed HapMap SNPs. We found that stringent application of quality score thresholds to genotype data substantially reduced false-positive results arising from genotype error. In addition, we demonstrate that it is possible to simultaneously phase 16,000 individuals genotyped on genome-wide data (450K markers) using the Beagle software package. PMID:18224336

A two-stage method for microcalcification cluster segmentation in mammography by deformable models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.

Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods aremore » applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST{sub cluster}, average of minimum distance—AMINDIST{sub cluster}) and the area overlap measure (AOM{sub cluster}). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross-validation methodology. A previously developed B-spline active rays segmentation method was also considered for comparison purposes. Results: Interobserver and intraobserver segmentation agreements (median and [25%, 75%] quartile range) were substantial with respect to the distance metrics HDIST{sub cluster} (2.3 [1.8, 2.9] and 2.5 [2.1, 3.2] pixels) and AMINDIST{sub cluster} (0.8 [0.6, 1.0] and 1.0 [0.8, 1.2] pixels), while moderate with respect to AOM{sub cluster} (0.64 [0.55, 0.71] and 0.59 [0.52, 0.66]). The proposed segmentation method outperformed (0.80 ± 0.04) statistically significantly (Mann-Whitney U-test, p < 0.05) the B-spline active rays segmentation method (0.69 ± 0.04), suggesting the significance of the proposed semiautomated method. Conclusions: Results indicate a reliable semiautomated segmentation method for MC clusters offered by deformable models, which could be utilized in MC cluster quantitative image analysis.« less

Validation of hierarchical cluster analysis for identification of bacterial species using 42 bacterial isolates

NASA Astrophysics Data System (ADS)

Ghebremedhin, Meron; Yesupriya, Shubha; Luka, Janos; Crane, Nicole J.

2015-03-01

Recent studies have demonstrated the potential advantages of the use of Raman spectroscopy in the biomedical field due to its rapidity and noninvasive nature. In this study, Raman spectroscopy is applied as a method for differentiating between bacteria isolates for Gram status and Genus species. We created models for identifying 28 bacterial isolates using spectra collected with a 785 nm laser excitation Raman spectroscopic system. In order to investigate the groupings of these samples, partial least squares discriminant analysis (PLSDA) and hierarchical cluster analysis (HCA) was implemented. In addition, cluster analyses of the isolates were performed using various data types consisting of, biochemical tests, gene sequence alignment, high resolution melt (HRM) analysis and antimicrobial susceptibility tests of minimum inhibitory concentration (MIC) and degree of antimicrobial resistance (SIR). In order to evaluate the ability of these models to correctly classify bacterial isolates using solely Raman spectroscopic data, a set of 14 validation samples were tested using the PLSDA models and consequently the HCA models. External cluster evaluation criteria of purity and Rand index were calculated at different taxonomic levels to compare the performance of clustering using Raman spectra as well as the other datasets. Results showed that Raman spectra performed comparably, and in some cases better than, the other data types with Rand index and purity values up to 0.933 and 0.947, respectively. This study clearly demonstrates that the discrimination of bacterial species using Raman spectroscopic data and hierarchical cluster analysis is possible and has the potential to be a powerful point-of-care tool in clinical settings.

Applying spatial analysis tools in public health: an example using SaTScan to detect geographic targets for colorectal cancer screening interventions.

PubMed

Sherman, Recinda L; Henry, Kevin A; Tannenbaum, Stacey L; Feaster, Daniel J; Kobetz, Erin; Lee, David J

2014-03-20

Epidemiologists are gradually incorporating spatial analysis into health-related research as geocoded cases of disease become widely available and health-focused geospatial computer applications are developed. One health-focused application of spatial analysis is cluster detection. Using cluster detection to identify geographic areas with high-risk populations and then screening those populations for disease can improve cancer control. SaTScan is a free cluster-detection software application used by epidemiologists around the world to describe spatial clusters of infectious and chronic disease, as well as disease vectors and risk factors. The objectives of this article are to describe how spatial analysis can be used in cancer control to detect geographic areas in need of colorectal cancer screening intervention, identify issues commonly encountered by SaTScan users, detail how to select the appropriate methods for using SaTScan, and explain how method selection can affect results. As an example, we used various methods to detect areas in Florida where the population is at high risk for late-stage diagnosis of colorectal cancer. We found that much of our analysis was underpowered and that no single method detected all clusters of statistical or public health significance. However, all methods detected 1 area as high risk; this area is potentially a priority area for a screening intervention. Cluster detection can be incorporated into routine public health operations, but the challenge is to identify areas in which the burden of disease can be alleviated through public health intervention. Reliance on SaTScan's default settings does not always produce pertinent results.

[Surveillance data on typhoid fever and paratyphoid fever in 2015, China].

PubMed

Liu, F F; Zhao, S L; Chen, Q; Chang, Z R; Zhang, J; Zheng, Y M; Luo, L; Ran, L; Liao, Q H

2017-06-10

Objective: Through analyzing the surveillance data on typhoid fever and paratyphoid fever in 2015 to understand the related epidemiological features and most possible clustering areas of high incidence. Methods: Individual data was collected from the passive surveillance program and analyzed by descriptive statistic method. Characteristics on seasonal, regional and distribution of the diseases were described. Spatial-temporal clustering characteristics were estimated, under the retrospective space-time method. Results: A total of 8 850 typhoid fever cases were reported from the surveillance system, with incidence rate as 0.65/100 000. The number of paratyphoid fever cases was 2 794, with incidence rate as 0.21/100 000. Both cases of typhoid fever and paratyphoid fever occurred all year round, with high epidemic season from May to October. Most cases involved farmers (39.68 % ), children (15.89 % ) and students (12.01 % ). Children under 5 years showed the highest incidence rate. Retrospective space-time analysis for provinces with high incidence rates would include Yunnan, Guangxi, Guizhou, Hunan and Guangdong, indicating the first and second class clusters were mainly distributed near the bordering adjacent districts and counties among the provinces. Conclusion: In 2015, the prevalence rates of typhoid fever and paratyphoid fever were low, however with regional high prevalence areas. Cross regional transmission existed among provinces with high incidence rates which might be responsible for the clusters to appear in these areas.

Finding reproducible cluster partitions for the k-means algorithm

PubMed Central

2013-01-01

K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total i.e. within cluster variance, is both reproducible under repeated initialisations and also the closest that k-means can provide to true structure, when applied to synthetic data. We show that this is generally the case for small numbers of clusters, but for values of k that are still of theoretical and practical interest, similar values of SSQ can correspond to markedly different cluster partitions. This paper extends stability measures previously presented in the context of finding optimal values of cluster number, into a component of a 2-d map of the local minima found by the k-means algorithm, from which not only can values of k be identified for further analysis but, more importantly, it is made clear whether the best SSQ is a suitable solution or whether obtaining a consistently good partition requires further application of the stability index. The proposed method is illustrated by application to five synthetic datasets replicating a real world breast cancer dataset with varying data density, and a large bioinformatics dataset. PMID:23369085

Finding reproducible cluster partitions for the k-means algorithm.

PubMed

Lisboa, Paulo J G; Etchells, Terence A; Jarman, Ian H; Chambers, Simon J

2013-01-01

K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total i.e. within cluster variance, is both reproducible under repeated initialisations and also the closest that k-means can provide to true structure, when applied to synthetic data. We show that this is generally the case for small numbers of clusters, but for values of k that are still of theoretical and practical interest, similar values of SSQ can correspond to markedly different cluster partitions. This paper extends stability measures previously presented in the context of finding optimal values of cluster number, into a component of a 2-d map of the local minima found by the k-means algorithm, from which not only can values of k be identified for further analysis but, more importantly, it is made clear whether the best SSQ is a suitable solution or whether obtaining a consistently good partition requires further application of the stability index. The proposed method is illustrated by application to five synthetic datasets replicating a real world breast cancer dataset with varying data density, and a large bioinformatics dataset.

Performance of cancer cluster Q-statistics for case-control residential histories

PubMed Central

Sloan, Chantel D.; Jacquez, Geoffrey M.; Gallagher, Carolyn M.; Ward, Mary H.; Raaschou-Nielsen, Ole; Nordsborg, Rikke Baastrup; Meliker, Jaymie R.

2012-01-01

Few investigations of health event clustering have evaluated residential mobility, though causative exposures for chronic diseases such as cancer often occur long before diagnosis. Recently developed Q-statistics incorporate human mobility into disease cluster investigations by quantifying space- and time-dependent nearest neighbor relationships. Using residential histories from two cancer case-control studies, we created simulated clusters to examine Q-statistic performance. Results suggest the intersection of cases with significant clustering over their life course, Qi, with cases who are constituents of significant local clusters at given times, Qit, yielded the best performance, which improved with increasing cluster size. Upon comparison, a larger proportion of true positives were detected with Kulldorf’s spatial scan method if the time of clustering was provided. We recommend using Q-statistics to identify when and where clustering may have occurred, followed by the scan method to localize the candidate clusters. Future work should investigate the generalizability of these findings. PMID:23149326

Prevalence and risk factors for scrub typhus in South India.

PubMed

Trowbridge, Paul; P, Divya; Premkumar, Prasanna S; Varghese, George M

2017-05-01

To determine the prevalence and risk factors of scrub typhus in Tamil Nadu, South India. We performed a clustered seroprevalence study of the areas around Vellore. All participants completed a risk factor survey, with seropositive and seronegative participants acting as cases and controls, respectively, in a risk factor analysis. After univariate analysis, variables found to be significant underwent multivariate analysis. Of 721 people participating in this study, 31.8% tested seropositive. By univariate analysis, after accounting for clustering, having a house that was clustered with other houses, having a fewer rooms in a house, having fewer people living in a household, defecating outside, female sex, age >60 years, shorter height, lower weight, smaller body mass index and smaller mid-upper arm circumference were found to be significantly associated with seropositivity. After multivariate regression modelling, living in a house clustered with other houses, female sex and age >60 years were significantly associated with scrub typhus exposure. Overall, scrub typhus is much more common than previously thought. Previously described individual environmental and habitual risk factors seem to have less importance in South India, perhaps because of the overall scrub typhus-conducive nature of the environment in this region. © 2017 John Wiley & Sons Ltd.

D Geomarketing Segmentation: a Higher Spatial Dimension Planning Perspective

NASA Astrophysics Data System (ADS)

Suhaibah, A.; Uznir, U.; Rahman, A. A.; Anton, F.; Mioc, D.

2016-09-01

Geomarketing is a discipline which uses geographic information in the process of planning and implementation of marketing activities. It can be used in any aspect of the marketing such as price, promotion or geo targeting. The analysis of geomarketing data use a huge data pool such as location residential areas, topography, it also analyzes demographic information such as age, genre, annual income and lifestyle. This information can help users to develop successful promotional campaigns in order to achieve marketing goals. One of the common activities in geomarketing is market segmentation. The segmentation clusters the data into several groups based on its geographic criteria. To refine the search operation during analysis, we proposed an approach to cluster the data using a clustering algorithm. However, with the huge data pool, overlap among clusters may happen and leads to inefficient analysis. Moreover, geomarketing is usually active in urban areas and requires clusters to be organized in a three-dimensional (3D) way (i.e. multi-level shop lots, residential apartments). This is a constraint with the current Geographic Information System (GIS) framework. To avoid this issue, we proposed a combination of market segmentation based on geographic criteria and clustering algorithm for 3D geomarketing data management. The proposed approach is capable in minimizing the overlap region during market segmentation. In this paper, geomarketing in urban area is used as a case study. Based on the case study, several locations of customers and stores in 3D are used in the test. The experiments demonstrated in this paper substantiated that the proposed approach is capable of minimizing overlapping segmentation and reducing repetitive data entries. The structure is also tested for retrieving the spatial records from the database. For marketing purposes, certain radius of point is used to analyzing marketing targets. Based on the presented tests in this paper, we strongly believe that the structure is capable in handling and managing huge pool of geomarketing data. For future outlook, this paper also discusses the possibilities of expanding the structure.

DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data.

PubMed

Lee, Alexandra J; Chang, Ivan; Burel, Julie G; Lindestam Arlehamn, Cecilia S; Mandava, Aishwarya; Weiskopf, Daniela; Peters, Bjoern; Sette, Alessandro; Scheuermann, Richard H; Qian, Yu

2018-04-17

Computational methods for identification of cell populations from polychromatic flow cytometry data are changing the paradigm of cytometry bioinformatics. Data clustering is the most common computational approach to unsupervised identification of cell populations from multidimensional cytometry data. However, interpretation of the identified data clusters is labor-intensive. Certain types of user-defined cell populations are also difficult to identify by fully automated data clustering analysis. Both are roadblocks before a cytometry lab can adopt the data clustering approach for cell population identification in routine use. We found that combining recursive data filtering and clustering with constraints converted from the user manual gating strategy can effectively address these two issues. We named this new approach DAFi: Directed Automated Filtering and Identification of cell populations. Design of DAFi preserves the data-driven characteristics of unsupervised clustering for identifying novel cell subsets, but also makes the results interpretable to experimental scientists through mapping and merging the multidimensional data clusters into the user-defined two-dimensional gating hierarchy. The recursive data filtering process in DAFi helped identify small data clusters which are otherwise difficult to resolve by a single run of the data clustering method due to the statistical interference of the irrelevant major clusters. Our experiment results showed that the proportions of the cell populations identified by DAFi, while being consistent with those by expert centralized manual gating, have smaller technical variances across samples than those from individual manual gating analysis and the nonrecursive data clustering analysis. Compared with manual gating segregation, DAFi-identified cell populations avoided the abrupt cut-offs on the boundaries. DAFi has been implemented to be used with multiple data clustering methods including K-means, FLOCK, FlowSOM, and the ClusterR package. For cell population identification, DAFi supports multiple options including clustering, bisecting, slope-based gating, and reversed filtering to meet various autogating needs from different scientific use cases. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

A West Virginia case study: does erosion differ between streambanks clustered by the bank assessment of nonpoint source consequences of sediment (BANCS) model parameters?

Treesearch

Abby L. McQueen; Nicolas P. Zegre; Danny L. Welsch

2013-01-01

The integration of factors and processes responsible for streambank erosion is complex. To explore the influence of physical variables on streambank erosion, parameters for the bank assessment of nonpoint source consequences of sediment (BANCS) model were collected on a 1-km reach of Horseshoe Run in Tucker County, West Virginia. Cluster analysis was used to establish...

Search For Cosmic-Ray-Induced Gamma-Ray Emission In Galaxy Clusters

DOE PAGES

Ackermann, M.

2014-04-30

Current theories predict relativistic hadronic particle populations in clusters of galaxies in addition to the already observed relativistic leptons. In these scenarios hadronic interactions give rise to neutral pions which decay into rays that are potentially observable with the Large Area Telescope (LAT) on board the Fermi space telescope. We present a joint likelihood analysis searching for spatially extended γ-ray emission at the locations of 50 galaxy clusters in 4 years of Fermi-LAT data under the assumption of the universal cosmic-ray model proposed by Pinzke & Pfrommer (2010). We find an excess at a significance of 2.7 σ which uponmore » closer inspection is however correlated to individual excess emission towards three galaxy clusters: Abell 400, Abell 1367 and Abell 3112. We discuss these cases in detail and conservatively attribute the emission to unmodeled background (for example, radio galaxies within the clusters). Through the combined analysis of 50 clusters we exclude hadronic injection efficiencies in simple hadronic models above 21% and establish limits on the cosmic-ray to thermal pressure ratio within the virial radius, R200, to be below 1.2-1.4% depending on the morphological classification. In addition we derive new limits on the γ-ray flux from individual clusters in our sample.« less

Search for Cosmic-Ray-Induced Gamma-Ray Emission in Galaxy Clusters

NASA Technical Reports Server (NTRS)

Ackermann, M.; Ajello, M.; Albert, A.; Allafort, A.; Atwood, W. B.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Bechtol, K.;

A measure for objects clustering in principal component analysis biplot: A case study in inter-city buses maintenance cost data

NASA Astrophysics Data System (ADS)

Ginanjar, Irlandia; Pasaribu, Udjianna S.; Indratno, Sapto W.

2017-03-01

This article presents the application of the principal component analysis (PCA) biplot for the needs of data mining. This article aims to simplify and objectify the methods for objects clustering in PCA biplot. The novelty of this paper is to get a measure that can be used to objectify the objects clustering in PCA biplot. Orthonormal eigenvectors, which are the coefficients of a principal component model representing an association between principal components and initial variables. The existence of the association is a valid ground to objects clustering based on principal axes value, thus if m principal axes used in the PCA, then the objects can be classified into 2m clusters. The inter-city buses are clustered based on maintenance costs data by using two principal axes PCA biplot. The buses are clustered into four groups. The first group is the buses with high maintenance costs, especially for lube, and brake canvass. The second group is the buses with high maintenance costs, especially for tire, and filter. The third group is the buses with low maintenance costs, especially for lube, and brake canvass. The fourth group is buses with low maintenance costs, especially for tire, and filter.

Space-Time Cluster Analysis to Detect Innovative Clinical Practices: A Case Study of Aripiprazole in the Department of Veterans Affairs.

PubMed

Penfold, Robert B; Burgess, James F; Lee, Austin F; Li, Mingfei; Miller, Christopher J; Nealon Seibert, Marjorie; Semla, Todd P; Mohr, David C; Kazis, Lewis E; Bauer, Mark S

2018-02-01

To identify space-time clusters of changes in prescribing aripiprazole for bipolar disorder among providers in the VA. VA administrative data from 2002 to 2010 were used to identify prescriptions of aripiprazole for bipolar disorder. Prescriber characteristics were obtained using the Personnel and Accounting Integrated Database. We conducted a retrospective space-time cluster analysis using the space-time permutation statistic. All VA service users with a diagnosis of bipolar disorder were included in the patient population. Individuals with any schizophrenia spectrum diagnoses were excluded. We also identified all clinicians who wrote a prescription for any bipolar disorder medication. The study population included 32,630 prescribers. Of these, 8,643 wrote qualifying prescriptions. We identified three clusters of aripiprazole prescribing centered in Massachusetts, Ohio, and the Pacific Northwest. Clusters were associated with prescribing by VA-employed (vs. contracted) prescribers. Nurses with prescribing privileges were more likely to make a prescription for aripiprazole in cluster locations compared with psychiatrists. Primary care physicians were less likely. Early prescribing of aripiprazole for bipolar disorder clustered geographically and was associated with prescriber subgroups. These methods support prospective surveillance of practice changes and identification of associated health system characteristics. © Health Research and Educational Trust.

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

PubMed Central

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han; Lim, Jing Quan; Huang, Mi Ni; Padmanabhan, Nisha; Nellore, Vishwa; Kongpetch, Sarinya; Ng, Alvin Wei Tian; Ng, Ley Moy; Choo, Su Pin; Myint, Swe Swe; Thanan, Raynoo; Nagarajan, Sanjanaa; Lim, Weng Khong; Ng, Cedric Chuan Young; Boot, Arnoud; Liu, Mo; Ong, Choon Kiat; Rajasegaran, Vikneswari; Lie, Stefanus; Lim, Alvin Soon Tiong; Lim, Tse Hui; Tan, Jing; Loh, Jia Liang; McPherson, John R.; Khuntikeo, Narong; Bhudhisawasdi, Vajaraphongsa; Yongvanit, Puangrat; Wongkham, Sopit; Totoki, Yasushi; Nakamura, Hiromi; Arai, Yasuhito; Yamasaki, Satoshi; Chow, Pierce Kah-Hoe; Chung, Alexander Yaw Fui; Ooi, London Lucien Peng Jin; Lim, Kiat Hon; Dima, Simona; Duda, Dan G.; Popescu, Irinel; Broet, Philippe; Hsieh, Sen-Yung; Yu, Ming-Chin; Scarpa, Aldo; Lai, Jiaming; Luo, Di-Xian; Carvalho, André Lopes; Vettore, André Luiz; Rhee, Hyungjin; Park, Young Nyun; Alexandrov, Ludmil B.; Gordân, Raluca; Rozen, Steven G.; Shibata, Tatsuhiro; Pairojkul, Chawalit; Teh, Bin Tean; Tan, Patrick

2017-01-01

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters – Fluke-Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3′UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores – mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer. PMID:28667006

Minimal disease detection of B-cell lymphoproliferative disorders by flow cytometry: multidimensional cluster analysis.

PubMed

Duque, Ricardo E

2012-04-01

Flow cytometric analysis of cell suspensions involves the sequential 'registration' of intrinsic and extrinsic parameters of thousands of cells in list mode files. Thus, it is almost irresistible to describe phenomena in numerical terms or by 'ratios' that have the appearance of 'accuracy' due to the presence of numbers obtained from thousands of cells. The concepts involved in the detection and characterization of B cell lymphoproliferative processes are revisited in this paper by identifying parameters that, when analyzed appropriately, are both necessary and sufficient. The neoplastic process (cluster) can be visualized easily because the parameters that distinguish it form a cluster in multidimensional space that is unique and distinguishable from neighboring clusters that are not of diagnostic interest but serve to provide a background. For B cell neoplasia it is operationally necessary to identify the multidimensional space occupied by a cluster whose kappa:lambda ratio is 100:0 or 0:100. Thus, the concept of kappa:lambda ratio is without meaning and would not detect B cell neoplasia in an unacceptably high number of cases.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters - Fluke- Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3’UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation ofmore » H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores - mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Lastly, our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.« less

Gas and galaxies in filaments between clusters of galaxies. The study of A399-A401

NASA Astrophysics Data System (ADS)

Bonjean, V.; Aghanim, N.; Salomé, P.; Douspis, M.; Beelen, A.

2018-01-01

We have performed a multi-wavelength analysis of two galaxy cluster systems selected with the thermal Sunyaev-Zel'dovich (tSZ) effect and composed of cluster pairs and an inter-cluster filament. We have focused on one pair of particular interest: A399-A401 at redshift z 0.073 seperated by 3 Mpc. We have also performed the first analysis of one lower-significance newly associated pair: A21-PSZ2 G114.09-34.34 at z 0.094, separated by 4.2 Mpc. We have characterised the intra-cluster gas using the tSZ signal from Planck and, when possible, the galaxy optical and infrared (IR) properties based on two photometric redshift catalogues: 2MPZ and WISExSCOS. From the tSZ data, we measured the gas pressure in the clusters and in the inter-cluster filaments. In the case of A399-A401, the results are in perfect agreement with previous studies and, using the temperature measured from the X-rays, we further estimate the gas density in the filament and find n0 = (4.3 ± 0.7) × 10-4 cm-3. The optical and IR colour-colour and colour-magnitude analyses of the galaxies selected in the cluster system, together with their star formation rate, show no segregation between galaxy populations, both in the clusters and in the filament of A399-A401. Galaxies are all passive, early type, and red and dead. The gas and galaxy properties of this system suggest that the whole system formed at the same time and corresponds to a pre-merger, with a cosmic filament gas heated by the collapse. For the other cluster system, the tSZ analysis was performed and the pressure in the clusters and in the inter-cluster filament was constrained. However, the limited or nonexistent optical and IR data prevent us from concluding on the presence of an actual cosmic filament or from proposing a scenario.

Cloning and Characterization of the Pyrrolomycin Biosynthetic Gene Clusters from Actinosporangium vitaminophilum ATCC 31673 and Streptomyces sp. Strain UC 11065▿

PubMed Central

Zhang, Xiujun; Parry, Ronald J.

2007-01-01

The pyrrolomycins are a family of polyketide antibiotics, some of which contain a nitro group. To gain insight into the nitration mechanism associated with the formation of these antibiotics, the pyrrolomycin biosynthetic gene cluster from Actinosporangium vitaminophilum was cloned. Sequencing of ca. 56 kb of A. vitaminophilum DNA revealed 35 open reading frames (ORFs). Sequence analysis revealed a clear relationship between some of these ORFs and the biosynthetic gene cluster for pyoluteorin, a structurally related antibiotic. Since a gene transfer system could not be devised for A. vitaminophilum, additional proof for the identity of the cloned gene cluster was sought by cloning the pyrrolomycin gene cluster from Streptomyces sp. strain UC 11065, a transformable pyrrolomycin producer. Sequencing of ca. 26 kb of UC 11065 DNA revealed the presence of 17 ORFs, 15 of which exhibit strong similarity to ORFs in the A. vitaminophilum cluster as well as a nearly identical organization. Single-crossover disruption of two genes in the UC 11065 cluster abolished pyrrolomycin production in both cases. These results confirm that the genetic locus cloned from UC 11065 is essential for pyrrolomycin production, and they also confirm that the highly similar locus in A. vitaminophilum encodes pyrrolomycin biosynthetic genes. Sequence analysis revealed that both clusters contain genes encoding the two components of an assimilatory nitrate reductase. This finding suggests that nitrite is required for the formation of the nitrated pyrrolomycins. However, sequence analysis did not provide additional insights into the nitration process, suggesting the operation of a novel nitration mechanism. PMID:17158935

Spatiotemporal Analysis of the Malaria Epidemic in Mainland China, 2004-2014.

PubMed

Huang, Qiang; Hu, Lin; Liao, Qi-Bin; Xia, Jing; Wang, Qian-Ru; Peng, Hong-Juan

2017-08-01

The purpose of this study is to characterize spatiotemporal heterogeneities in malaria distribution at a provincial level and investigate the association between malaria incidence and climate factors from 2004 to 2014 in China to inform current malaria control efforts. National malaria incidence peaked (4.6/100,000) in 2006 and decreased to a very low level (0.21/100,000) in 2014, and the proportion of imported cases increased from 16.2% in 2004 to 98.2% in 2014. Statistical analyses of global and local spatial autocorrelations and purely spatial scan statistics revealed that malaria was localized in Hainan, Anhui, and Yunnan during 2004-2009 and then gradually shifted and clustered in Yunnan after 2010. Purely temporal clusters shortened to less than 5 months during 2012-2014. The two most likely clusters detected using spatiotemporal analysis occurred in Anhui between July 2005 and November 2007 and Yunnan between January 2010 and June 2012. Correlation coefficients for the association between malaria incidence and climate factors sharply decreased after 2010, and there were zero-month lag effects for climate factors during 2010-2014. Overall, the spatiotemporal distribution of malaria in China changed from relatively scattered (2004-2009) to relatively clustered (2010-2014). As the proportion of imported cases increased, the effect of climate factors on malaria incidence has gradually become weaker since 2011. Therefore, new warning systems should be applied to monitor resurgence and outbreaks of malaria in mainland China, and quarantine at borders should be reinforced to control the increasingly trend of imported malaria cases.

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2017-06-06

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Voronoi distance based prospective space-time scans for point data sets: a dengue fever cluster analysis in a southeast Brazilian town

PubMed Central

2011-01-01

Background The Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated. Results A fast method for the detection and inference of point data set space-time disease clusters is presented, the Voronoi Based Scan (VBScan). A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi cells boundaries intercepted by the line segment joining two cases points defines the Voronoi distance between those points. That distance is used to approximate the density of the heterogeneous population and build the Voronoi distance MST linking the cases. The successive removal of edges from the Voronoi distance MST generates sub-trees which are the potential space-time clusters. Finally, those clusters are evaluated through the scan statistic. Monte Carlo replications of the original data are used to evaluate the significance of the clusters. An application for dengue fever in a small Brazilian city is presented. Conclusions The ability to promptly detect space-time clusters of disease outbreaks, when the number of individuals is large, was shown to be feasible, due to the reduced computational load of VBScan. Instead of changing the map, VBScan modifies the metric used to define the distance between cases, without requiring the cartogram construction. Numerical simulations showed that VBScan has higher power of detection, sensitivity and positive predicted value than the Elliptic PST. Furthermore, as VBScan also incorporates topological information from the point neighborhood structure, in addition to the usual geometric information, it is more robust than purely geometric methods such as the elliptic scan. Those advantages were illustrated in a real setting for dengue fever space-time clusters. PMID:21513556

A ground truth based comparative study on clustering of gene expression data.

PubMed

Zhu, Yitan; Wang, Zuyi; Miller, David J; Clarke, Robert; Xuan, Jianhua; Hoffman, Eric P; Wang, Yue

2008-05-01

Given the variety of available clustering methods for gene expression data analysis, it is important to develop an appropriate and rigorous validation scheme to assess the performance and limitations of the most widely used clustering algorithms. In this paper, we present a ground truth based comparative study on the functionality, accuracy, and stability of five data clustering methods, namely hierarchical clustering, K-means clustering, self-organizing maps, standard finite normal mixture fitting, and a caBIG toolkit (VIsual Statistical Data Analyzer--VISDA), tested on sample clustering of seven published microarray gene expression datasets and one synthetic dataset. We examined the performance of these algorithms in both data-sufficient and data-insufficient cases using quantitative performance measures, including cluster number detection accuracy and mean and standard deviation of partition accuracy. The experimental results showed that VISDA, an interactive coarse-to-fine maximum likelihood fitting algorithm, is a solid performer on most of the datasets, while K-means clustering and self-organizing maps optimized by the mean squared compactness criterion generally produce more stable solutions than the other methods.

Spectroscopic determination of fundamental parameters of small angular diameter galactic open clusters

NASA Astrophysics Data System (ADS)

Ahumada, A. V.; Claria, J. J.; Bica, E.; Parisi, M. C.; Torres, M. C.; Pavani, D. B.

We present integrated spectra obtained at CASLEO (Argentina) for 9 galactic open clusters of small angular diameter. Two of them (BH 55 and Rup 159) have not been the target of previous research. The flux-calibrated spectra cover the spectral range approx. 3600-6900 A. Using the equivalent widths (EWs) of the Balmer lines and comparing the cluster spectra with template spectra, we determined E(B-V) colour excesses and ages for the present cluster sample. The parameters obtained for 6 of the clusters show good agreement with previous determinations based mainly on photometric methods. This is not the case, however, for BH 90, a scarcely reddened cluster, for which Moffat and Vogt (1975, Astron. and Astroph. SS, 20, 125) derived E(B-V) = 0.51. We explain and justify the strong discrepancy found for this object. According to the present analysis, 3 clusters are very young (Bo 14, Tr 15 and Tr 27), 2 are moderately young (NGC 6268 and BH 205), 3 are Hyades-like clusters (Rup 164, BH 90 and BH 55) and only one is an intermediate-age cluster (Rup 159).

Inflammatory endotypes of chronic rhinosinusitis based on cluster analysis of biomarkers.

PubMed

Tomassen, Peter; Vandeplas, Griet; Van Zele, Thibaut; Cardell, Lars-Olaf; Arebro, Julia; Olze, Heidi; Förster-Ruhrmann, Ulrike; Kowalski, Marek L; Olszewska-Ziąber, Agnieszka; Holtappels, Gabriele; De Ruyck, Natalie; Wang, Xiangdong; Van Drunen, Cornelis; Mullol, Joaquim; Hellings, Peter; Hox, Valerie; Toskala, Elina; Scadding, Glenis; Lund, Valerie; Zhang, Luo; Fokkens, Wytske; Bachert, Claus

2016-05-01

Current phenotyping of chronic rhinosinusitis (CRS) into chronic rhinosinusitis with nasal polyps (CRSwNP) and chronic rhinosinusitis without nasal polyps (CRSsNP) might not adequately reflect the pathophysiologic diversity within patients with CRS. We sought to identify inflammatory endotypes of CRS. Therefore we aimed to cluster patients with CRS based solely on immune markers in a phenotype-free approach. Secondarily, we aimed to match clusters to phenotypes. In this multicenter case-control study patients with CRS and control subjects underwent surgery, and tissue was analyzed for IL-5, IFN-γ, IL-17A, TNF-α, IL-22, IL-1β, IL-6, IL-8, eosinophilic cationic protein, myeloperoxidase, TGF-β1, IgE, Staphylococcus aureus enterotoxin-specific IgE, and albumin. We used partition-based clustering. Clustering of 173 cases resulted in 10 clusters, of which 4 clusters with low or undetectable IL-5, eosinophilic cationic protein, IgE, and albumin concentrations, and 6 clusters with high concentrations of those markers. The group of IL-5-negative clusters, 3 clusters clinically resembled a predominant chronic rhinosinusitis without nasal polyps (CRSsNP) phenotype without increased asthma prevalence, and 1 cluster had a TH17 profile and had mixed CRSsNP/CRSwNP. The IL-5-positive clusters were divided into a group with moderate IL-5 concentrations, a mixed CRSsNP/CRSwNP and increased asthma phenotype, and a group with high IL-5 levels, an almost exclusive nasal polyp phenotype with strongly increased asthma prevalence. In the latter group, 2 clusters demonstrated the highest concentrations of IgE and asthma prevalence, with all samples expressing Staphylococcus aureus enterotoxin-specific IgE. Distinct CRS clusters with diverse inflammatory mechanisms largely correlated with phenotypes and further differentiated them and provided a more accurate description of the inflammatory mechanisms involved than phenotype information only. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Regional heatwaves in china: a cluster analysis

NASA Astrophysics Data System (ADS)

Wang, Pinya; Tang, Jianping; Wang, Shuyu; Dong, Xinning; Fang, Juan

2018-03-01

With the consideration of spatial extension of heatwave events, two kind of regional heatwaves using absolute and relative thresholds, namely RHWs-A and RHWs-R, are investigated during 1959-2013. The temperature data is derived from the daily maximum temperatures (DMTs) of 587 stations in China. Totally 298 RHWs-A and 374 RHWs-R are identified during the past 55 years, and both of them are growing more frequent since the mid-1980s. By utilizing the cluster analysis, several typical spatial distributions of RHWs-A/RHWs-R are obtained. For RHWs-A, there are three clusters covering the southeastern, northwestern China and the lower reaches of Yangtze River, of which the southeastern cluster groups the most heatwaves. For RHWs-R, there are seven clusters distributed throughout the whole regions of China. The clusters in the northwestern and northeastern China are more stable than others for both RHWs-A and RHWs-R, and the northern clusters are of larger intensity than that of the southern ones. All RHWs-A/RHWs-R are accompanied by the anomalous high systems along with the reduced soil moisture. The southern clusters are controlled by Northwestern Pacific subtropical high (WPSH), and the northern ones are influenced by the mid-latitude high systems. The influences of atmospheric circulations and soil moisture on regional heatwaves are further demonstrated by two case analyses of the severe RHW-A in 2003 and the RHW-R in 2013.

Population-Based Study of Streptococcus suis Infection in Humans in Phayao Province in Northern Thailand

PubMed Central

Takeuchi, Dan; Kerdsin, Anusak; Pienpringam, Anupong; Loetthong, Phacharaphan; Samerchea, Sutit; Luangsuk, Pakkinee; Khamisara, Kasean; Wongwan, Nithita; Areeratana, Prasanee; Chiranairadul, Piphat; Lertchayanti, Suwat; Petcharat, Sininat; Yowang, Amara; Chaiwongsaen, Phanupong; Nakayama, Tatsuya; Akeda, Yukihiro; Hamada, Shigeyuki; Sawanpanyalert, Pathom; Dejsirilert, Surang; Oishi, Kazunori

2012-01-01

Background Streptococcus suis infection in humans has received increasing worldwide recognition. Methods and Findings A prospective study of S. suis infection in humans was conducted in Phayao Province in northern Thailand to determine the incidence and the risk behaviors of the disease in this region in 2010. Thirty-one cases were confirmed. The case fatality rate was 16.1%, and the estimated incidence rate was 6.2 per 100,000 in the general population. The peak incidence occurred in May. The median age of the patients was 53 years and 64.5% were men. Consumption of raw pork products was confirmed in 22 cases and the median incubation period (range) was 2 days (0–11) after consumption of raw pork products. Isolates from 31 patients were confirmed as serotype 2 in 23 patients (74.2%) and serotype 14 in eight patients (25.8%). The major sequence types (STs) were ST1 (n = 20) for serotype 2 and ST105 (n = 8) for serotype 14. The epidemiological analysis suggested three possible clusters, which included 17 cases. In the largest possible cluster of 10 cases in Chiang Kham and its neighboring districts in May, the source of infection in four cases was identified as a raw pork dish served at the same restaurant in this district. Microbiological analysis confirmed that three of four cases associated with consumption of raw pork at this restaurant were attributable to an identical strain of serotype 2 with ST1 and pulsotype A2. Conclusions Our data suggest a high incidence rate of S. suis infection in the general population in Phayao Province in 2010 and confirm a cluster of three cases in 31 human cases. Food safety control should be strengthened especially for raw pork products in northern Thailand. PMID:22363601

Different Patterns of the Urban Heat Island Intensity from Cluster Analysis

NASA Astrophysics Data System (ADS)

Silva, F. B.; Longo, K.

2014-12-01

This study analyzes the different variability patterns of the Urban Heat Island intensity (UHII) in the Metropolitan Area of Rio de Janeiro (MARJ), one of the largest urban agglomerations in Brazil. The UHII is defined as the difference in the surface air temperature between the urban/suburban and rural/vegetated areas. To choose one or more stations that represent those areas we used the technique of cluster analysis on the air temperature observations from 14 surface weather stations in the MARJ. The cluster analysis aims to classify objects based on their characteristics, gathering similar groups. The results show homogeneity patterns between air temperature observations, with 6 homogeneous groups being defined. Among those groups, one might be a natural choice for the representative urban area (Central station); one corresponds to suburban area (Afonsos station); and another group referred as rural area is compound of three stations (Ecologia, Santa Cruz and Xerém) that are located in vegetated regions. The arithmetic mean of temperature from the three rural stations is taken to represent the rural station temperature. The UHII is determined from these homogeneous groups. The first UHII is estimated from urban and rural temperature areas (Case 1), whilst the second UHII is obtained from suburban and rural temperature areas (Case 2). In Case 1, the maximum UHII occurs in two periods, one in the early morning and the other at night, while the minimum UHII occurs in the afternoon. In Case 2, the maximum UHII is observed during afternoon/night and the minimum during dawn/early morning. This study demonstrates that the stations choice reflects different UHII patterns, evidencing that distinct behaviors of this phenomenon can be identified.

Artificial neural network modeling and cluster analysis for organic facies and burial history estimation using well log data: A case study of the South Pars Gas Field, Persian Gulf, Iran

NASA Astrophysics Data System (ADS)

Alizadeh, Bahram; Najjari, Saeid; Kadkhodaie-Ilkhchi, Ali

2012-08-01

Intelligent and statistical techniques were used to extract the hidden organic facies from well log responses in the Giant South Pars Gas Field, Persian Gulf, Iran. Kazhdomi Formation of Mid-Cretaceous and Kangan-Dalan Formations of Permo-Triassic Data were used for this purpose. Initially GR, SGR, CGR, THOR, POTA, NPHI and DT logs were applied to model the relationship between wireline logs and Total Organic Carbon (TOC) content using Artificial Neural Networks (ANN). The correlation coefficient (R2) between the measured and ANN predicted TOC equals to 89%. The performance of the model is measured by the Mean Squared Error function, which does not exceed 0.0073. Using Cluster Analysis technique and creating a binary hierarchical cluster tree the constructed TOC column of each formation was clustered into 5 organic facies according to their geochemical similarity. Later a second model with the accuracy of 84% was created by ANN to determine the specified clusters (facies) directly from well logs for quick cluster recognition in other wells of the studied field. Each created facies was correlated to its appropriate burial history curve. Hence each and every facies of a formation could be scrutinized separately and directly from its well logs, demonstrating the time and depth of oil or gas generation. Therefore potential production zone of Kazhdomi probable source rock and Kangan- Dalan reservoir formation could be identified while well logging operations (especially in LWD cases) were in progress. This could reduce uncertainty and save plenty of time and cost for oil industries and aid in the successful implementation of exploration and exploitation plans.

The Grism Lens-Amplified Survey from Space (GLASS). V. Extent and Spatial Distribution of Star Formation in z ~ 0.5 Cluster Galaxies

NASA Astrophysics Data System (ADS)

Vulcani, Benedetta; Treu, Tommaso; Schmidt, Kasper B.; Poggianti, Bianca M.; Dressler, Alan; Fontana, Adriano; Bradač, Marusa; Brammer, Gabriel B.; Hoag, Austin; Huang, Kuan-Han; Malkan, Matthew; Pentericci, Laura; Trenti, Michele; von der Linden, Anja; Abramson, Louis; He, Julie; Morris, Glenn

2015-12-01

We present the first study of the spatial distribution of star formation in z ˜ 0.5 cluster galaxies. The analysis is based on data taken with the Wide Field Camera 3 as part of the Grism Lens-Amplified Survey from Space (GLASS). We illustrate the methodology by focusing on two clusters (MACS 0717.5+3745 and MACS 1423.8+2404) with different morphologies (one relaxed and one merging) and use foreground and background galaxies as a field control sample. The cluster+field sample consists of 42 galaxies with stellar masses in the range 108-1011 M⊙ and star formation rates in the range 1-20 M⊙ yr-1. Both in clusters and in the field, Hα is more extended than the rest-frame UV continuum in 60% of the cases, consistent with diffuse star formation and inside-out growth. In ˜20% of the cases, the Hα emission appears more extended in cluster galaxies than in the field, pointing perhaps to ionized gas being stripped and/or star formation being enhanced at large radii. The peak of the Hα emission and that of the continuum are offset by less than 1 kpc. We investigate trends with the hot gas density as traced by the X-ray emission, and with the surface mass density as inferred from gravitational lens models, and find no conclusive results. The diversity of morphologies and sizes observed in Hα illustrates the complexity of the environmental processes that regulate star formation. Upcoming analysis of the full GLASS data set will increase our sample size by almost an order of magnitude, verifying and strengthening the inference from this initial data set.

Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering.

PubMed

He, Zhaoshui; Xie, Shengli; Zdunek, Rafal; Zhou, Guoxu; Cichocki, Andrzej

2011-12-01

Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on symmetric NMF (SNMF), which is a special case of NMF decomposition. Three parallel multiplicative update algorithms using level 3 basic linear algebra subprograms directly are developed for this problem. First, by minimizing the Euclidean distance, a multiplicative update algorithm is proposed, and its convergence under mild conditions is proved. Based on it, we further propose another two fast parallel methods: α-SNMF and β -SNMF algorithms. All of them are easy to implement. These algorithms are applied to probabilistic clustering. We demonstrate their effectiveness for facial image clustering, document categorization, and pattern clustering in gene expression.

Effect of Policy Analysis on Indonesia’s Maritime Cluster Development Using System Dynamics Modeling

NASA Astrophysics Data System (ADS)

Nursyamsi, A.; Moeis, A. O.; Komarudin

2018-03-01

As an archipelago with two third of its territory consist of water, Indonesia should address more attention to its maritime industry development. One of the catalyst to fasten the maritime industry growth is by developing a maritime cluster. The purpose of this research is to gain understanding of the effect if Indonesia implement maritime cluster policy to the growth of maritime economic and its role to enhance the maritime cluster performance, hence enhancing Indonesia’s maritime industry as well. The result of the constructed system dynamic model simulation shows that with the effect of maritime cluster, the growth of employment rate and maritime economic is much bigger that the business as usual case exponentially. The result implies that the government should act fast to form a legitimate cluster maritime organizer institution so that there will be a synergize, sustainable, and positive maritime cluster environment that will benefit the performance of Indonesia’s maritime industry.

Fuzzy Subspace Clustering

NASA Astrophysics Data System (ADS)

Borgelt, Christian

In clustering we often face the situation that only a subset of the available attributes is relevant for forming clusters, even though this may not be known beforehand. In such cases it is desirable to have a clustering algorithm that automatically weights attributes or even selects a proper subset. In this paper I study such an approach for fuzzy clustering, which is based on the idea to transfer an alternative to the fuzzifier (Klawonn and Höppner, What is fuzzy about fuzzy clustering? Understanding and improving the concept of the fuzzifier, In: Proc. 5th Int. Symp. on Intelligent Data Analysis, 254-264, Springer, Berlin, 2003) to attribute weighting fuzzy clustering (Keller and Klawonn, Int J Uncertain Fuzziness Knowl Based Syst 8:735-746, 2000). In addition, by reformulating Gustafson-Kessel fuzzy clustering, a scheme for weighting and selecting principal axes can be obtained. While in Borgelt (Feature weighting and feature selection in fuzzy clustering, In: Proc. 17th IEEE Int. Conf. on Fuzzy Systems, IEEE Press, Piscataway, NJ, 2008) I already presented such an approach for a global selection of attributes and principal axes, this paper extends it to a cluster-specific selection, thus arriving at a fuzzy subspace clustering algorithm (Parsons, Haque, and Liu, 2004).

Visceral leishmaniasis in the state of Sao Paulo, Brazil: spatial and space-time analysis

PubMed Central

Cardim, Marisa Furtado Mozini; Guirado, Marluci Monteiro; Dibo, Margareth Regina; Chiaravalloti, Francisco

2016-01-01

ABSTRACT OBJECTIVE To perform both space and space-time evaluations of visceral leishmaniasis in humans in the state of Sao Paulo, Brazil. METHODS The population considered in the study comprised autochthonous cases of visceral leishmaniasis and deaths resulting from it in Sao Paulo, between 1999 and 2013. The analysis considered the western region of the state as its studied area. Thematic maps were created to show visceral leishmaniasis dissemination in humans in the municipality. Spatial analysis tools Kernel and Kernel ratio were used to respectively obtain the distribution of cases and deaths and the distribution of incidence and mortality. Scan statistics were used in order to identify spatial and space-time clusters of cases and deaths. RESULTS The visceral leishmaniasis cases in humans, during the studied period, were observed to occur in the western portion of Sao Paulo, and their territorial extension mainly followed the eastbound course of the Marechal Rondon highway. The incidences were characterized as two sequences of concentric ellipses of decreasing intensities. The first and more intense one was found to have its epicenter in the municipality of Castilho (where the Marechal Rondon highway crosses the border of the state of Mato Grosso do Sul) and the second one in Bauru. Mortality was found to have a similar behavior to incidence. The spatial and space-time clusters of cases were observed to coincide with the two areas of highest incidence. Both the space-time clusters identified, even without coinciding in time, were started three years after the human cases were detected and had the same duration, that is, six years. CONCLUSIONS The expansion of visceral leishmaniasis in Sao Paulo has been taking place in an eastbound direction, focusing on the role of highways, especially Marechal Rondon, in this process. The space-time analysis detected the disease occurred in cycles, in different spaces and time periods. These meetings, if considered, may contribute to the adoption of actions that aim to prevent the disease from spreading throughout the whole territory of São Paulo or to at least reducing its expansion speed. PMID:27533364

Molecular Subtyping to Detect Human Listeriosis Clusters

PubMed Central

Sauders, Brian D.; Fortes, Esther D.; Morse, Dale L.; Dumas, Nellie; Kiehlbauch, Julia A.; Schukken, Ynte; Hibbs, Jonathan R.

2003-01-01

We analyzed the diversity (Simpson’s Index, D) and distribution of Listeria monocytogenes in human listeriosis cases in New York State (excluding New York City) from November 1996 to June 2000 by using automated ribotyping and pulsed-field gel electrophoresis (PFGE). We applied a scan statistic (p<0.05) to detect listeriosis clusters caused by a specific Listeria monocytogenes subtype. Of 131 human isolates, 34 (D=0.923) ribotypes and 74 (D=0.975) PFGE types were found. Nine (31% of cases) clusters were identified by ribotype or PFGE; five (18% of cases) clusters were identified by using both methods. Two of the nine clusters (13% of cases) identified corresponded with investigated multistate listeriosis outbreaks. While most human listeriosis cases are considered sporadic, highly discriminatory molecular subtyping approaches thus indicated that 13% to 31% of cases reported in New York State may represent single-source clusters. Listeriosis control and reduction efforts should include broad-based subtyping of human isolates and consider that a large number of cases may represent outbreaks. PMID:12781006

Automated Image Analysis of HER2 Fluorescence In Situ Hybridization to Refine Definitions of Genetic Heterogeneity in Breast Cancer Tissue

PubMed Central

Radziuviene, Gedmante; Rasmusson, Allan; Augulis, Renaldas; Lesciute-Krilaviciene, Daiva; Laurinaviciene, Aida; Clim, Eduard

2017-01-01

Human epidermal growth factor receptor 2 gene- (HER2-) targeted therapy for breast cancer relies primarily on HER2 overexpression established by immunohistochemistry (IHC) with borderline cases being further tested for amplification by fluorescence in situ hybridization (FISH). Manual interpretation of HER2 FISH is based on a limited number of cells and rather complex definitions of equivocal, polysomic, and genetically heterogeneous (GH) cases. Image analysis (IA) can extract high-capacity data and potentially improve HER2 testing in borderline cases. We investigated statistically derived indicators of HER2 heterogeneity in HER2 FISH data obtained by automated IA of 50 IHC borderline (2+) cases of invasive ductal breast carcinoma. Overall, IA significantly underestimated the conventional HER2, CEP17 counts, and HER2/CEP17 ratio; however, it collected more amplified cells in some cases below the lower limit of GH definition by manual procedure. Indicators for amplification, polysomy, and bimodality were extracted by factor analysis and allowed clustering of the tumors into amplified, nonamplified, and equivocal/polysomy categories. The bimodality indicator provided independent cell diversity characteristics for all clusters. Tumors classified as bimodal only partially coincided with the conventional GH heterogeneity category. We conclude that automated high-capacity nonselective tumor cell assay can generate evidence-based HER2 intratumor heterogeneity indicators to refine GH definitions. PMID:28752092

Automated Image Analysis of HER2 Fluorescence In Situ Hybridization to Refine Definitions of Genetic Heterogeneity in Breast Cancer Tissue.

PubMed

Radziuviene, Gedmante; Rasmusson, Allan; Augulis, Renaldas; Lesciute-Krilaviciene, Daiva; Laurinaviciene, Aida; Clim, Eduard; Laurinavicius, Arvydas

2017-01-01

Human epidermal growth factor receptor 2 gene- (HER2-) targeted therapy for breast cancer relies primarily on HER2 overexpression established by immunohistochemistry (IHC) with borderline cases being further tested for amplification by fluorescence in situ hybridization (FISH). Manual interpretation of HER2 FISH is based on a limited number of cells and rather complex definitions of equivocal, polysomic, and genetically heterogeneous (GH) cases. Image analysis (IA) can extract high-capacity data and potentially improve HER2 testing in borderline cases. We investigated statistically derived indicators of HER2 heterogeneity in HER2 FISH data obtained by automated IA of 50 IHC borderline (2+) cases of invasive ductal breast carcinoma. Overall, IA significantly underestimated the conventional HER2, CEP17 counts, and HER2/CEP17 ratio; however, it collected more amplified cells in some cases below the lower limit of GH definition by manual procedure. Indicators for amplification, polysomy, and bimodality were extracted by factor analysis and allowed clustering of the tumors into amplified, nonamplified, and equivocal/polysomy categories. The bimodality indicator provided independent cell diversity characteristics for all clusters. Tumors classified as bimodal only partially coincided with the conventional GH heterogeneity category. We conclude that automated high-capacity nonselective tumor cell assay can generate evidence-based HER2 intratumor heterogeneity indicators to refine GH definitions.

Characterizing tuberculosis genotype clusters along the United States-Mexico border.

PubMed

Baker, B J; Moonan, P K

2014-03-01

We examined the growth of tuberculosis (TB) genotype clusters during 2005-2010 in the United States, categorized by country of origin and ethnicity of the index case and geographic proximity to the US-Mexico border at the time of TB diagnosis. Nationwide, 38.9% of cases subsequent to Mexico-born index cases were US-born. Among clusters following US-born Hispanic and US-born non-Hispanic index cases, respectively 29.2% and 5.3% of subsequent cluster members were Mexico-born. In border areas, the majority of subsequent cases were Mexico-born following US-born Hispanic (56.4%) and US-born non-Hispanic (55.6%) index cases. These findings suggest that TB transmission commonly occurs between US-born and Mexico-born persons. Along the US-Mexico border, prioritizing TB genotype clusters following US-born index cases for investigation may prevent subsequent cases among both US-born and Mexico-born persons.

FY17 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Appel, Gordon John; Hadgu, Teklu; Appel, Gordon John

Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014), Hadgu et al. (2015) and Hadgu and Appel (2016). The TSPA computing hardware (CL2014) and storage system described in Hadgu et al. (2015) weremore » used for the current analysis. One floating license of GoldSim with Versions 9.60.300, 10.5, 11.1 and 12.0 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA- type analysis on the server cluster. The current tasks included preliminary upgrade of the TSPA-LA from Version 9.60.300 to the latest version 12.0 and address DLL-related issues observed in the FY16 work. The model upgrade task successfully converted the Nominal Modeling case to GoldSim Versions 11.1/12. Conversions of the rest of the TSPA models were also attempted but program and operational difficulties precluded this. Upgrade of the remaining of the modeling cases and distributed processing tasks is expected to continue. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.« less

IoT Big-Data Centred Knowledge Granule Analytic and Cluster Framework for BI Applications: A Case Base Analysis.

PubMed

Chang, Hsien-Tsung; Mishra, Nilamadhab; Lin, Chung-Chih

2015-01-01

The current rapid growth of Internet of Things (IoT) in various commercial and non-commercial sectors has led to the deposition of large-scale IoT data, of which the time-critical analytic and clustering of knowledge granules represent highly thought-provoking application possibilities. The objective of the present work is to inspect the structural analysis and clustering of complex knowledge granules in an IoT big-data environment. In this work, we propose a knowledge granule analytic and clustering (KGAC) framework that explores and assembles knowledge granules from IoT big-data arrays for a business intelligence (BI) application. Our work implements neuro-fuzzy analytic architecture rather than a standard fuzzified approach to discover the complex knowledge granules. Furthermore, we implement an enhanced knowledge granule clustering (e-KGC) mechanism that is more elastic than previous techniques when assembling the tactical and explicit complex knowledge granules from IoT big-data arrays. The analysis and discussion presented here show that the proposed framework and mechanism can be implemented to extract knowledge granules from an IoT big-data array in such a way as to present knowledge of strategic value to executives and enable knowledge users to perform further BI actions.

IoT Big-Data Centred Knowledge Granule Analytic and Cluster Framework for BI Applications: A Case Base Analysis

PubMed Central

Chang, Hsien-Tsung; Mishra, Nilamadhab; Lin, Chung-Chih

2015-01-01

The current rapid growth of Internet of Things (IoT) in various commercial and non-commercial sectors has led to the deposition of large-scale IoT data, of which the time-critical analytic and clustering of knowledge granules represent highly thought-provoking application possibilities. The objective of the present work is to inspect the structural analysis and clustering of complex knowledge granules in an IoT big-data environment. In this work, we propose a knowledge granule analytic and clustering (KGAC) framework that explores and assembles knowledge granules from IoT big-data arrays for a business intelligence (BI) application. Our work implements neuro-fuzzy analytic architecture rather than a standard fuzzified approach to discover the complex knowledge granules. Furthermore, we implement an enhanced knowledge granule clustering (e-KGC) mechanism that is more elastic than previous techniques when assembling the tactical and explicit complex knowledge granules from IoT big-data arrays. The analysis and discussion presented here show that the proposed framework and mechanism can be implemented to extract knowledge granules from an IoT big-data array in such a way as to present knowledge of strategic value to executives and enable knowledge users to perform further BI actions. PMID:26600156

Surveillance should be strengthened to improve epidemiological understandings of mosquito-borne Barmah Forest virus infection.

PubMed

Ehlkes, Lutz; Eastwood, Keith; Webb, Cameron; Durrheim, David

2012-07-01

Barmah Forest virus (BFV) is a mosquito-borne virus causing epidemic polyarthritis in Australia. This study used case follow-up of cases from the surveillance system to demonstrate that routinely collected BFV notification data were an unreliable indicator of the true location of exposure. BFV notifications from June 2001 to May 2011 were extracted from the New South Wales (NSW) Notifiable Conditions Information Management System to study case distribution. Disease cluster analysis was performed using spatial scan statistics. Exposure history data were collected from cases notified in 2010 and 2011 to accurately determine travel to high-risk areas. Cluster analysis using address data identified an area of increased BFV disease incidence in the mid-north coast of NSW contiguous with estuarine wetlands. When travel to this area was investigated, 96.7% (29/30) cases reported having visited coastal regions within four weeks of developing symptoms. Along the central NSW coastline, extensive wetlands occur in close proximity to populated areas. These wetlands provide ideal breeding habitats for a range of mosquito species implicated in the transmission of BFV. This is the first study to fully assess case exposure with findings suggesting that sporadic cases of BFV in people living further away from the coast do not reflect alternative exposure sites but are likely to result from travel to coastal regions. Spatial analysis by case address alone may lead to inaccurate understandings of the true distribution of arboviral diseases. Subsequently, this information has important implications for the collection of mosquito-borne disease surveillance information and public health response strategies.

Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan.

PubMed

Umer, Muhammad Farooq; Zofeen, Shumaila; Majeed, Abdul; Hu, Wenbiao; Qi, Xin; Zhuang, Guihua

2018-06-07

Despite tremendous progress, malaria remains a serious public health problem in Pakistan. Very few studies have been done on spatiotemporal evaluation of malaria infection in Pakistan. The study aimed to detect the spatiotemporal pattern of malaria infection at the district level in Pakistan, and to identify the clusters of high-risk disease areas in the country. Annual data on malaria for two dominant species ( Plasmodium falciparum , Plasmodium vivax ) and mixed infections from 2011 to 2016 were obtained from the Directorate of Malaria Control Program, Pakistan. Population data were collected from the Pakistan Bureau of Statistics. A geographical information system was used to display the spatial distribution of malaria at the district level throughout Pakistan. Purely spatiotemporal clustering analysis was performed to identify the high-risk areas of malaria infection in Pakistan. A total of 1,593,409 positive cases were included in this study over a period of 6 years (2011⁻2016). The maximum number of P . vivax cases (474,478) were reported in Khyber Pakhtunkhwa (KPK). The highest burden of P . falciparum (145,445) was in Balochistan, while the highest counts of mixed Plasmodium cases were reported in Sindh (22,421) and Balochistan (22,229), respectively. In Balochistan, incidence of all three types of malaria was very high. Cluster analysis showed that primary clusters of P . vivax malaria were in the same districts in 2014, 2015 and 2016 (total 24 districts, 12 in Federally Administered Tribal Areas (FATA), 9 in KPK, 2 in Punjab and 1 in Balochistan); those of P . falciparum malaria were unchanged in 2012 and 2013 (total 18 districts, all in Balochistan), and mixed infections remained the same in 2014 and 2015 (total 7 districts, 6 in Balochistan and 1 in FATA). This study indicated that the transmission cycles of malaria infection vary in different spatiotemporal settings in Pakistan. Efforts in controlling P . vivax malaria in particular need to be enhanced in high-risk areas. Based on these findings, further research is needed to investigate the impact of risk factors on transmission of malaria in Pakistan.

Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

PubMed Central

Fan, Yaxin; Zhu, Xinyan; Guo, Wei; Guo, Tao

2018-01-01

The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. PMID:29672551

A large community outbreak of blastomycosis in Wisconsin with geographic and ethnic clustering.

PubMed

Roy, Monika; Benedict, Kaitlin; Deak, Eszter; Kirby, Miles A; McNiel, Jena T; Sickler, Carrie J; Eckardt, Eileen; Marx, Ruth K; Heffernan, Richard T; Meece, Jennifer K; Klein, Bruce S; Archer, John R; Theurer, Joan; Davis, Jeffrey P; Park, Benjamin J

2013-09-01

Blastomycosis is a potentially life-threatening infection caused by the soil-based dimorphic fungus Blastomyces dermatitidis, which is endemic throughout much of the Midwestern United States. We investigated an increase in reported cases of blastomycosis that occurred during 2009-2010 in Marathon County, Wisconsin. Case detection was conducted using the Wisconsin Electronic Disease Surveillance System (WEDSS). WEDSS data were used to compare demographic, clinical, and exposure characteristics between outbreak-related and historical case patients, and to calculate blastomycosis incidence rates. Because initial mapping of outbreak case patients' homes and recreational sites demonstrated unusual neighborhood and household case clustering, we conducted a 1:3 matched case-control study to identify factors associated with being in a geographic cluster. Among the 55 patients with outbreak-related cases, 33 (70%) were hospitalized, 2 (5%) died, 30 (55%) had cluster-related cases, and 20 (45%) were Hmong. The overall incidence increased significantly since 2005 (average 11% increase per year, P < .001), and incidence during 2005-2010 was significantly higher among Asians than non-Asians (2010 incidence: 168 vs 13 per 100 000 population). Thirty of the outbreak cases grouped into 5 residential clusters. Outdoor activities were not risk factors for blastomycosis among cluster case patients or when comparing outbreak cases to historical cases. This outbreak of blastomycosis, the largest ever reported, was characterized by unique household and neighborhood clustering likely related to multifocal environmental sources. The reasons for the large number of Hmong affected are unclear, but may involve genetic predisposition.

Use of LANDSAT imagery for wildlife habitat mapping in northeast and east central Alaska

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Two scenes were analyzed by applying an iterative cluster analysis to a 2% random data sample and then using the resulting clusters as a training set basis for maximum likelihood classification. Twenty-six and twenty-seven categorical classes, respectively resulted from this process. The majority of classes in each case were quite specific vegetation types; each of these types has specific value as moose habitat.

High diversity of multidrug-resistant Mycobacterium tuberculosis Central Asian Strain isolates in Nepal.

PubMed

Shah, Yogendra; Maharjan, Bhagwan; Thapa, Jeewan; Poudel, Ajay; Diab, Hassan Mahmoud; Pandey, Basu Dev; Solo, Eddie S; Isoda, Norikazu; Suzuki, Yasuhiko; Nakajima, Chie

2017-10-01

Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) poses a major public health problem in Nepal. Although it has been reported as one of the dominant genotypes of MTB in Nepal, little information on the Central Asian Strain (CAS) family is available, especially isolates related to multidrug resistance (MDR) cases. This study aimed to elucidate the genetic and epidemiological characteristics of MDR CAS isolates in Nepal. A total of 145 MDR CAS isolates collected in Nepal from 2008 to 2013 were characterized by spoligotyping, mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) analysis, and drug resistance-associated gene sequencing. Spoligotyping analysis showed CAS1_Delhi SIT26 as predominant (60/145, 41.4%). However, by combining spoligotyping and MIRU-VNTR typing, it was possible to successfully discriminate all 145 isolates into 116 different types including 18 clusters with 47 isolates (clustering rate 32.4%). About a half of these clustered isolates shared the same genetic and geographical characteristics with other isolates in each cluster, and some of them shared rare point mutations in rpoB that are thought to be associated with rifampicin resistance. Although the data obtained show little evidence that large outbreaks of MDR-TB caused by the CAS family have occurred in Nepal, they strongly suggest several MDR-MTB transmission cases. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

A HIV-1 heterosexual transmission chain in Guangzhou, China: a molecular epidemiological study.

PubMed

Han, Zhigang; Leung, Tommy W C; Zhao, Jinkou; Wang, Ming; Fan, Lirui; Li, Kai; Pang, Xinli; Liang, Zhenbo; Lim, Wilina W L; Xu, Huifang

2009-09-25

We conducted molecular analyses to confirm four clustering HIV-1 infections (Patient A, B, C & D) in Guangzhou, China. These cases were identified by epidemiological investigation and suspected to acquire the infection through a common heterosexual transmission chain. Env C2V3V4 region, gag p17/p24 junction and partial pol gene of HIV-1 genome from serum specimens of these infected cases were amplified by reverse transcription polymerase chain reaction (RT-PCR) and nucleotide sequenced. Phylogenetic analyses indicated that their viral nucleotide sequences were significantly clustered together (bootstrap value is 99%, 98% and 100% in env, gag and pol tree respectively). Evolutionary distance analysis indicated that their genetic diversities of env, gag and pol genes were significantly lower than non-clustered controls, as measured by unpaired t-test (env gene comparison: p < 0.005; gag gene comparison: p < 0.005; pol gene comparison: p < 0.005). Epidemiological results and molecular analyses consistently illustrated these four cases represented a transmission chain which dispersed in the locality through heterosexual contact involving commercial sex worker.

Accident patterns for construction-related workers: a cluster analysis

NASA Astrophysics Data System (ADS)

Liao, Chia-Wen; Tyan, Yaw-Yauan

2012-01-01

The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

Accident patterns for construction-related workers: a cluster analysis

NASA Astrophysics Data System (ADS)

Liao, Chia-Wen; Tyan, Yaw-Yauan

2011-12-01

The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

Testing Fundamental Physics with Distant Star Clusters: Analysis of Observational Data on Palomar 14

NASA Astrophysics Data System (ADS)

Jordi, K.; Grebel, E. K.; Hilker, M.; Baumgardt, H.; Frank, M.; Kroupa, P.; Haghi, H.; Côté, P.; Djorgovski, S. G.

2009-06-01

We use the distant outer halo globular cluster Palomar 14 as a test case for classical versus modified Newtonian dynamics (MOND). Previous theoretical calculations have shown that the line-of-sight velocity dispersion predicted by these theories can differ by up to a factor of 3 for such sparse, remote clusters like Pal 14. We determine the line-of-sight velocity dispersion of Palomar 14 by measuring radial velocities of 17 red giant cluster members obtained using the Very Large Telescope and Keck telescope. The systemic velocity of Palomar 14 is (72.28 ± 0.12) km s-1. The derived velocity dispersion of (0.38 ± 0.12) km s-1 of the 16 definite member stars is in agreement with the theoretical prediction for the classical Newtonian case according to Baumgardt et al. In order to exclude the possibility that a peculiar mass function might have influenced our measurements, we derived the cluster's main-sequence mass function down to 0.53 M sun using archival images obtained with the Hubble Space Telescope. We found a mass function slope of α = 1.27 ± 0.44, which is, compared to the canonical mass function, a significantly shallower slope. The derived lower limit on the cluster's mass is higher than the theoretically predicted mass in the case of MOND. Our data are consistent with a central density of ρ0 = 0.1 M sun pc-3. We need no dark matter in Palomar 14. If the cluster is on a circular orbit, our spectroscopic and photometric results argue against MOND, unless the cluster experienced significant mass loss. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Social Network Analysis as a Methodological Approach to Explore Health Systems: A Case Study Exploring Support among Senior Managers/Executives in a Hospital Network.

PubMed

De Brún, Aoife; McAuliffe, Eilish

2018-03-13

Health systems research recognizes the complexity of healthcare, and the interacting and interdependent nature of components of a health system. To better understand such systems, innovative methods are required to depict and analyze their structures. This paper describes social network analysis as a methodology to depict, diagnose, and evaluate health systems and networks therein. Social network analysis is a set of techniques to map, measure, and analyze social relationships between people, teams, and organizations. Through use of a case study exploring support relationships among senior managers in a newly established hospital group, this paper illustrates some of the commonly used network- and node-level metrics in social network analysis, and demonstrates the value of these maps and metrics to understand systems. Network analysis offers a valuable approach to health systems and services researchers as it offers a means to depict activity relevant to network questions of interest, to identify opinion leaders, influencers, clusters in the network, and those individuals serving as bridgers across clusters. The strengths and limitations inherent in the method are discussed, and the applications of social network analysis in health services research are explored.

[Genetic characterization of echovirus 6 isolated from meningitis and encephalitis cases in Shandong Province, China].

PubMed

Lin, Xiao-Juan; Tao, Ze-Xin; Liu, Gui-Fang; Wang, Min; Song, Li-Zhi; Wang, Su-Ting; Ji, Feng; Wang, Hai-Yan; Xu, Ai-Qiang

2014-03-01

To analyze the genetic characteristics of echovirus 6 (E6) isolated from meningitis and encephalitis cases in Shandong Province, China, we collected cerebrospinal fluid samples from meningitis and encephalitis cases in Shandong Province from 2007 to 2012 for virus isolation. Viral RNAs were extracted from positive isolates, and complete VP1 coding regions were amplified by RT-PCR and sequenced. Homology comparison and phylogenetic analysis were performed. Six isolates were identified as E6 by microneutralization assay and molecular typing. The homology analysis showed that the six isolates had 78. 6%-99. 8% nucleotide and 95. 5%-100. 0% amino acid identities with each other, as well as 76. 9%-78. 4% nucleotide and 92. 3%-95. 1% amino acid identities with the prototype strain (D' Amori). The phylogenetic analysis based on the integrated VP1 sequences indicated that all Shandong E6 isolates could be separated into four clusters, designated as A, B, C, and D. The six E6 isolates belonged to clusters A, B, and D. Our study reveals high genetic differences between Shandong E6 isolates and suggests different transmission lineages of E6 co-circulated in Shandong Province.

The Internet and Services Marketing--The Case of Danish Retail Banking.

ERIC Educational Resources Information Center

Mols, Niels Peter

2000-01-01

Examines various aspects of the motives, perceptions, and expectations connected with the introduction of Internet banking in Danish retail banking. Responses from questionnaires and results from a factor analysis and a hierarchical cluster analysis indicate a belief that Internet banking will become more important in the future. (Author/LRW)

Factors Affecting Herd Status for Bovine Tuberculosis in Dairy Cattle in Northern Thailand

PubMed Central

Singhla, Tawatchai; Punyapornwithaya, Veerasak; VanderWaal, Kimberly L.; Alvarez, Julio; Sreevatsan, Srinand; Phornwisetsirikun, Somphorn; Sankwan, Jamnong; Srijun, Mongkol; Wells, Scott J.

2017-01-01

The objective of this case-control study was to identify farm-level risk factors associated with bovine tuberculosis (bTB) in dairy cows in northern Thailand. Spatial analysis was performed to identify geographical clustering of case-farms located in Chiang Mai and Chiang Rai provinces in northern Thailand. To identify management factors affecting bTB status, a matched case-control study was conducted with 20 case-farms and 38 control-farms. Case-farms were dairy farms with at least single intradermal tuberculin test- (SIT-) reactor(s) in the farms during 2011 to 2015. Control-farms were dairy farms with no SIT-reactors in the same period and located within 5 km from case-farms. Questionnaires were administered for data collection with questions based on epidemiological plausibility and characteristics of the local livestock industry. Data were analyzed using multiple logistic regressions. A significant geographic cluster was identified only in Chiang Mai province (p < 0.05). The risk factor associated with presence of SIT-reactors in dairy herds located in this region was purchasing dairy cows from dealers (OR = 5.85, 95% CI = 1.66–20.58, and p = 0.006). From this study, it was concluded that geographic clustering was identified for dairy farms with SIT-reactors in these provinces, and the cattle movements through cattle dealers increased the risks for SIT-reactor farm status. PMID:28553557

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research), CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

FLOCK cluster analysis of plasma cell flow cytometry data predicts bone marrow involvement by plasma cell neoplasia.

PubMed

Dorfman, David M; LaPlante, Charlotte D; Li, Betty

2016-09-01

We analyzed plasma cell populations in bone marrow samples from 353 patients with possible bone marrow involvement by a plasma cell neoplasm, using FLOCK (FLOw Clustering without K), an unbiased, automated, computational approach to identify cell subsets in multidimensional flow cytometry data. FLOCK identified discrete plasma cell populations in the majority of bone marrow specimens found by standard histologic and immunophenotypic criteria to be involved by a plasma cell neoplasm (202/208 cases; 97%), including 34 cases that were negative by standard flow cytometric analysis that included clonality assessment. FLOCK identified discrete plasma cell populations in only a minority of cases negative for involvement by a plasma cell neoplasm by standard histologic and immunophenotypic criteria (38/145 cases; 26%). Interestingly, 55% of the cases negative by standard analysis, but containing a FLOCK-identified discrete plasma cell population, were positive for monoclonal gammopathy by serum protein electrophoresis and immunofixation. FLOCK-identified and quantitated plasma cell populations accounted for 3.05% of total cells on average in cases positive for involvement by a plasma cell neoplasm by standard histologic and immunophenotypic criteria, and 0.27% of total cells on average in cases negative for involvement by a plasma cell neoplasm by standard histologic and immunophenotypic criteria (p<0.0001; area under the curve by ROC analysis=0.96). The presence of a FLOCK-identified discrete plasma cell population was predictive of the presence of plasma cell neoplasia with a sensitivity of 97%, compared with only 81% for standard flow cytometric analysis, and had specificity of 74%, PPV of 84% and NPV of 95%. FLOCK analysis, which has been shown to provide useful diagnostic information for evaluating patients with suspected systemic mastocytosis, is able to identify neoplastic plasma cell populations analyzed by flow cytometry, and may be helpful in the diagnostic evaluation of bone marrow samples for involvement by plasma cell neoplasia. Copyright © 2016 Elsevier Ltd. All rights reserved.

DNA methylation-based reclassification of olfactory neuroblastoma.

PubMed

Capper, David; Engel, Nils W; Stichel, Damian; Lechner, Matt; Glöss, Stefanie; Schmid, Simone; Koelsche, Christian; Schrimpf, Daniel; Niesen, Judith; Wefers, Annika K; Jones, David T W; Sill, Martin; Weigert, Oliver; Ligon, Keith L; Olar, Adriana; Koch, Arend; Forster, Martin; Moran, Sebastian; Tirado, Oscar M; Sáinz-Japeado, Miguel; Mora, Jaume; Esteller, Manel; Alonso, Javier; Del Muro, Xavier Garcia; Paulus, Werner; Felsberg, Jörg; Reifenberger, Guido; Glatzel, Markus; Frank, Stephan; Monoranu, Camelia M; Lund, Valerie J; von Deimling, Andreas; Pfister, Stefan; Buslei, Rolf; Ribbat-Idel, Julika; Perner, Sven; Gudziol, Volker; Meinhardt, Matthias; Schüller, Ulrich

2018-05-05

Olfactory neuroblastoma/esthesioneuroblastoma (ONB) is an uncommon neuroectodermal neoplasm thought to arise from the olfactory epithelium. Little is known about its molecular pathogenesis. For this study, a retrospective cohort of n = 66 tumor samples with the institutional diagnosis of ONB was analyzed by immunohistochemistry, genome-wide DNA methylation profiling, copy number analysis, and in a subset, next-generation panel sequencing of 560 tumor-associated genes. DNA methylation profiles were compared to those of relevant differential diagnoses of ONB. Unsupervised hierarchical clustering analysis of DNA methylation data revealed four subgroups among institutionally diagnosed ONB. The largest group (n = 42, 64%, Core ONB) presented with classical ONB histology and no overlap with other classes upon methylation profiling-based t-distributed stochastic neighbor embedding (t-SNE) analysis. A second DNA methylation group (n = 7, 11%) with CpG island methylator phenotype (CIMP) consisted of cases with strong expression of cytokeratin, no or scarce chromogranin A expression and IDH2 hotspot mutation in all cases. T-SNE analysis clustered these cases together with sinonasal carcinoma with IDH2 mutation. Four cases (6%) formed a small group characterized by an overall high level of DNA methylation, but without CIMP. The fourth group consisted of 13 cases that had heterogeneous DNA methylation profiles and strong cytokeratin expression in most cases. In t-SNE analysis, these cases mostly grouped among sinonasal adenocarcinoma, squamous cell carcinoma, and undifferentiated carcinoma. Copy number analysis indicated highly recurrent chromosomal changes among Core ONB with a high frequency of combined loss of chromosome 1-4, 8-10, and 12. NGS sequencing did not reveal highly recurrent mutations in ONB, with the only recurrently mutated genes being TP53 and DNMT3A. In conclusion, we demonstrate that institutionally diagnosed ONB are a heterogeneous group of tumors. Expression of cytokeratin, chromogranin A, the mutational status of IDH2 as well as DNA methylation patterns may greatly aid in the precise classification of ONB.

Using preoperative unsupervised cluster analysis of chronic rhinosinusitis to inform patient decision and endoscopic sinus surgery outcome.

PubMed

Adnane, Choaib; Adouly, Taoufik; Khallouk, Amine; Rouadi, Sami; Abada, Redallah; Roubal, Mohamed; Mahtar, Mohamed

2017-02-01

The purpose of this study is to use unsupervised cluster methodology to identify phenotype and mucosal eosinophilia endotype subgroups of patients with medical refractory chronic rhinosinusitis (CRS), and evaluate the difference in quality of life (QOL) outcomes after endoscopic sinus surgery (ESS) between these clusters for better surgical case selection. A prospective cohort study included 131 patients with medical refractory CRS who elected ESS. The Sino-Nasal Outcome Test (SNOT-22) was used to evaluate QOL before and 12 months after surgery. Unsupervised two-step clustering method was performed. One hundred and thirteen subjects were retained in this study: 46 patients with CRS without nasal polyps and 67 patients with nasal polyps. Nasal polyps, gender, mucosal eosinophilia profile, and prior sinus surgery were the most discriminating factors in the generated clusters. Three clusters were identified. A significant clinical improvement was observed in all clusters 12 months after surgery with a reduction of SNOT-22 scores. There was a significant difference in QOL outcomes between clusters; cluster 1 had the worst QOL improvement after FESS in comparison with the other clusters 2 and 3. All patients in cluster 1 presented CRSwNP with the highest mucosal eosinophilia endotype. Clustering method is able to classify CRS phenotypes and endotypes with different associated surgical outcomes.

Assessing and grouping chemicals applying partial ordering Alkyl anilines as an illustrative example.

PubMed

Carlsen, Lars; Bruggemann, Rainer

2018-06-03

In chemistry there is a long tradition in classification. Usually methods are adopted from the wide field of cluster analysis. Here, based on the example of 21 alkyl anilines we show that also concepts taken out from the mathematical discipline of partially ordered sets may also be applied. The chemical compounds are described by a multi-indicator system. For the present study four indicators, mainly taken from the field of environmental chemistry were applied and a Hasse diagram was constructed. A Hasse diagram is an acyclic, transitively reduced, triangle free graph that may have several components. The crucial question is, whether or not the Hasse diagram can be interpreted from a structural chemical point of view. This is indeed the case, but it must be clearly stated that a guarantee for meaningful results in general cannot be given. For that further theoretical work is needed. Two cluster analysis methods are applied (K-means and a hierarchical cluster method). In both cases the partitioning of the set of 21 compounds by the component structure of the Hasse diagram appears to be better interpretable. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Statistical analysis of donation--transfusion data with complex correlation.

PubMed

Reilly, Marie; Szulkin, Robert

2007-12-30

Blood-borne transmission of disease is estimated from linked data records from blood donors and transfusion recipients. However, such data are characterized by complex correlation due to donors typically contributing many donations and recipients being transfused with multiple units of blood product. In this paper, we present a method for analysing such data, by using a modification of a nested case-control design. For recipients who develop the disease of interest (cases) and their matched controls, all donors who contributed blood to these individuals define clusters or 'families' of related individuals. Using a Cox regression model for the hazard of the individuals within clusters of donors, we estimate the risk of transmission, and a bootstrap step provides valid standard errors provided the clusters are independent. As an illustration, we apply the method to the analysis of a large database of Swedish donor and recipient records linked to the population cancer register. We investigate whether there is an increased risk of cancer in recipients transfused with blood from donors who develop cancer after donating. Our method provides a powerful alternative to the small 'look-back' studies typical of transfusion medicine and can make an important contribution to haemovigilance efforts. Copyright (c) 2007 John Wiley & Sons, Ltd.

Whole genome sequencing improved case ascertainment in an outbreak of Shiga toxin-producing Escherichia coli O157 associated with raw drinking milk.

PubMed

Butcher, H; Elson, R; Chattaway, M A; Featherstone, C A; Willis, C; Jorgensen, F; Dallman, T J; Jenkins, C; McLAUCHLIN, J; Beck, C R; Harrison, S

2016-10-01

Five cases of STEC O157 phage type (PT) 21/28 reported consumption of raw cows' drinking milk (RDM) produced at a dairy farm in the South West of England. STEC O157 PT21/28 was isolated from faecal specimens from milking cows on the implicated farm. Whole genome sequencing (WGS) showed that human and cattle isolates were the same strain. Further analysis of WGS data confirmed that sequences of isolates from an additional four cases (who did not report consumption of RDM when first questioned) fell within the same five single nucleotide polymorphism cluster as the initial five cases epidemiologically linked to the consumption of RDM. These four additional cases identified by WGS were investigated further and were, ultimately, associated with the implicated farm. The RDM outbreak strain encoded stx2a, which is associated with increased pathogenicity and severity of symptoms. Further epidemiological analysis showed that 70% of isolates within a wider cluster containing the outbreak strain were from cases residing in, or linked to, the same geographical region of England. During this RDM outbreak, use of WGS improved case ascertainment and provided insights into the evolution of a highly pathogenic clade of STEC O157 PT21/28 stx2a associated with the South West of England.

Molecular Fingerprinting of Mycobacterium tuberculosis and Risk Factors for Tuberculosis Transmission in Paris, France, and Surrounding Area

PubMed Central

Gutiérrez, M. C.; Vincent, V.; Aubert, D.; Bizet, J.; Gaillot, O.; Lebrun, L.; Le Pendeven, C.; Le Pennec, M. P.; Mathieu, D.; Offredo, C.; Pangon, B.; Pierre-Audigier, C.

1998-01-01

Forty-three percent of the tuberculosis cases reported in France are from the Ile de France region. The incidence of tuberculosis in this region is 33 cases per 100,000 inhabitants, twice the national average. A restriction fragment length polymorphism (RFLP) analysis was performed with clinical isolates of Mycobacterium tuberculosis isolated during 1995 in 10 hospitals in Paris and surrounding areas to detect tuberculosis transmission and define the factors associated with clustering in this population. The molecular markers used were the insertion sequence IS6110 and the direct repeat (DR) sequence. Social, demographic, and clinical data were collected from the patients’ medical files. Ten patients with isolates with a single copy of IS6110 were excluded from further analysis. Twenty-four patients with false-positive cultures due to laboratory contamination (based on RFLP analysis with IS6110 and examination of patient data) were also excluded. The study was then conducted with 272 strains isolated from 272 patients. Further fingerprinting was performed by using the DR element with strains with patterns by RFLP analysis with IS6110 that differed by one band only and strains with identical patterns by RFLP analysis with IS6110 and with low numbers of copies of IS6110. The combined use of both markers identified unique patterns for 177 strains and clustered 95 (35.7%) strains in 26 groups, each containing isolates from 2 to 12 patients. The clustering was strongly associated with homelessness and the male sex. It was not associated with age, birth in a foreign country, human immunodeficiency virus positivity, or residence in hostels or prison. Isolates from homeless people were often included in large clusters, and homeless people could be the source of tuberculosis transmission for more than 50% of the clustered patients. These results suggest that homeless people play a key role in the spread of M. tuberculosis in the community and that poor socioeconomic conditions are the main risk factors associated with active tuberculosis transmission. PMID:9466764

Characterization of Shigella sonnei isolates from travel-associated cases in Japan.

PubMed

Izumiya, Hidemasa; Tada, Yuki; Ito, Kenichiro; Morita-Ishihara, Tomoko; Ohnishi, Makoto; Terajima, Jun; Watanabe, Haruo

2009-11-01

Shigella sonnei infection in industrialized countries is often associated with foreign travel. A total of 195 S. sonnei isolates in Japan, isolated from cases associated with foreign travel, were analysed by biotyping and molecular typing using PFGE and multilocus variable-number tandem-repeat analysis (MLVA); their antimicrobial susceptibilities were also evaluated. The isolates were from 26 countries, most of which were Asian. Molecular typing revealed a correlation among the genotypes, biotypes and their geographical areas of origin. The isolates were classified into two biotypes, a and g. Biotype g isolates (n=178) were further divided into distinct clusters mainly on the basis of their geographical areas of origin by both PFGE and MLVA. Isolates from South Asian countries constituted one of the distinct clusters. Biotype g isolates from countries other than South Asia constituted other distinct clusters. Most of the isolates from other countries and continents, excluding the South Asian countries, were included in one major cluster by PFGE analysis. However, by MLVA, they were further divided into minor subclusters mainly on the basis of their countries of origin. MLVA was also demonstrated to be useful in molecular epidemiological analysis, even when only seven loci were applied, resulting in a high resolution with Simpson's index of diversity (D) of 0.993. A core drug-resistance pattern of streptomycin, sulfisoxazole, tetracycline and trimethoprim-sulfamethoxazole was observed in 108 isolates, irrespective of their geographical areas of origin, but the frequency of resistance to nalidixic acid was high among the South Asian and East Asian isolates. Two isolates from China and India were resistant to cefotaxime and harboured the bla(CTX-M-14) and bla(CTX-M-15) genes, respectively; these isolates were also resistant to nalidixic acid, which is a matter of concern in terms of shigellosis treatment. Use of a combination of methods was found to be effective for epidemiological investigation in the case of S. sonnei infection.

Molecular characterisation of enteroviruses and clinical findings from a cluster of paediatric viral meningitis cases in Tshwane, South Africa 2010-2011.

PubMed

Wolfaardt, Marianne; Büchner, Ané; Myburgh, Marcelle; Avenant, Theunis; du Plessis, Nicolette M; Taylor, Maureen B

2014-11-01

Human enteroviruses (HEVs) are the most common viral pathogen associated with paediatric aseptic meningitis. From October 2010 to February 2011 a cluster of HEV-associated meningitis cases was identified in paediatric patients who had presented at two large tertiary hospitals in Pretoria in the Tshwane Metropolitan Area, Gauteng, South Africa (SA). The aim of this study was to review the clinical features and to characterise the HEV strains associated with this cluster of meningitis cases. In this retrospective study HEVs, detected by real time reverse transcription-polymerase chain reaction in acute phase cerebrospinal fluid specimens from 30 patients with aseptic meningitis, were characterised and the clinical presentations of these patients were described. Fever (83%), headache (70%) and vomiting (67%) were the most prominent symptoms with signs of meningeal irritation recorded in 67% of the patients. There was a neutrophil predominance in the cerebrospinal fluid of 57% of the patients with pleocytosis. Based on partial nucleotide sequence analysis of the HEV viral protein 1 gene, echovirus (E) serotype 4 (E-4) was identified in 80% (24/30) of specimens with E-9 (3/30) and coxsackie virus B5 (1/30) detected less frequently. In this cluster of aseptic meningitis cases E-4 was the predominant strain with E-9, and to a lesser extent other HEVs, identified less frequently. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatial clustering of malaria and associated risk factors during an epidemic in a highland area of western Kenya.

PubMed

Brooker, Simon; Clarke, Siân; Njagi, Joseph Kiambo; Polack, Sarah; Mugo, Benbolt; Estambale, Benson; Muchiri, Eric; Magnussen, Pascal; Cox, Jonathan

2004-07-01

The epidemiology of malaria over small areas remains poorly understood, and this is particularly true for malaria during epidemics in highland areas of Africa, where transmission intensity is low and characterized by acute within and between year variations. We report an analysis of the spatial distribution of clinical malaria during an epidemic and investigate putative risk factors. Active case surveillance was undertaken in three schools in Nandi District, Western Kenya for 10 weeks during a malaria outbreak in May-July 2002. Household surveys of cases and age-matched controls were conducted to collect information on household construction, exposure factors and socio-economic status. Household geographical location and altitude were determined using a hand-held geographical positioning system and landcover types were determined using high spatial resolution satellite sensor data. Among 129 cases identified during the surveillance, which were matched to 155 controls, we identified significant spatial clusters of malaria cases as determined using the spatial scan statistic. Conditional multiple logistic regression analysis showed that the risk of malaria was higher in children who were underweight, who lived at lower altitudes, and who lived in households where drugs were not kept at home. Copyright 2004 Blackwell Publishing Ltd

The Cluster AgeS Experiment (CASE). Detecting Aperiodic Photometric Variability with the Friends of Friends Algorithm

NASA Astrophysics Data System (ADS)

Rozyczka, M.; Narloch, W.; Pietrukowicz, P.; Thompson, I. B.; Pych, W.; Poleski, R.

2018-03-01

We adapt the friends of friends algorithm to the analysis of light curves, and show that it can be succesfully applied to searches for transient phenomena in large photometric databases. As a test case we search OGLE-III light curves for known dwarf novae. A single combination of control parameters allows us to narrow the search to 1% of the data while reaching a ≍90% detection efficiency. A search involving ≍2% of the data and three combinations of control parameters can be significantly more effective - in our case a 100% efficiency is reached. The method can also quite efficiently detect semi-regular variability. In particular, 28 new semi-regular variables have been found in the field of the globular cluster M22, which was examined earlier with the help of periodicity-searching algorithms.

Compatible poliomyelitis cases in India during 2000.

PubMed Central

Kohler, Kathryn A.; Hlady, W. Gary; Banerjee, Kaushik; Gupta, Dhananjoy; Francis, Paul; Durrani, Sunita; Zuber, Patrick L. F.; Sutter, Roland W.

2003-01-01

OBJECTIVE: To describe the characteristics of compatible poliomyelitis cases and to assess the programmatic implications of clusters of such cases in India. METHODS: We described the characteristics of compatible poliomyelitis cases, identified clusters of compatible cases (two or more in the same district or neighbouring districts within two months), and examined their relationship to wild poliovirus cases. FINDINGS: There were 362 compatible cases in 2000. The incidence of compatible cases was higher in districts with laboratory-confirmed poliomyelitis cases than in districts without laboratory-confirmed cases. Of 580 districts, 96 reported one compatible case and 72 reported two or more compatible cases. Among these 168 districts with at least one compatible case, 123 had internal or cross- border clusters of compatible cases. In 27 districts with clusters of compatible cases, no wild poliovirus was isolated either in the same district or in neighbouring districts. Three of these 27 districts presented laboratory-confirmed poliomyelitis cases during 2001. CONCLUSION: Most clusters of compatible cases occurred in districts identified as areas with continuing wild poliovirus transmission and where mopping-up vaccination campaigns were carried out. As certification nears, areas with compatible poliomyelitis cases should be investigated and deficiencies in surveillance should be corrected in order to ensure that certification is justified. PMID:12640469

Optical spectroscopy and velocity dispersions of galaxy clusters from the SPT-SZ survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruel, J.; Bayliss, M.; Bazin, G.

2014-09-01

We present optical spectroscopy of galaxies in clusters detected through the Sunyaev-Zel'dovich (SZ) effect with the South Pole Telescope (SPT). We report our own measurements of 61 spectroscopic cluster redshifts, and 48 velocity dispersions each calculated with more than 15 member galaxies. This catalog also includes 19 dispersions of SPT-observed clusters previously reported in the literature. The majority of the clusters in this paper are SPT-discovered; of these, most have been previously reported in other SPT cluster catalogs, and five are reported here as SPT discoveries for the first time. By performing a resampling analysis of galaxy velocities, we findmore » that unbiased velocity dispersions can be obtained from a relatively small number of member galaxies (≲ 30), but with increased systematic scatter. We use this analysis to determine statistical confidence intervals that include the effect of membership selection. We fit scaling relations between the observed cluster velocity dispersions and mass estimates from SZ and X-ray observables. In both cases, the results are consistent with the scaling relation between velocity dispersion and mass expected from dark-matter simulations. We measure a ∼30% log-normal scatter in dispersion at fixed mass, and a ∼10% offset in the normalization of the dispersion-mass relation when compared to the expectation from simulations, which is within the expected level of systematic uncertainty.« less

[Epidemiology of human infection with avian influenza A(H7N9) virus in China, 2013-2017].

PubMed

Han, D D; Han, C X; Li, L Y; Wang, M; Yang, J H; Li, M

2018-01-10

Objective: To understand the epidemiological characteristics of human infection with avian influenza A (H7N9) virus in China, and provide evidence for the prevention and control of human infection with H7N9 virus. Methods: The published incidence data of human infection with H7N9 virus in China from March 2013 to April 2017 were collected. Excel 2007 software was used to perform the analysis. The characteristics of distribution of the disease, exposure history, cluster of the disease were described. Results: By the end of April 2017, a total of 1 416 cases of human infection with H7N9 virus were confirmed in China, including 559 deaths, the case fatality rate was 39.5%. In 2016, the case number was lowest (127 cases), with the highest fatality rate (57.5%). The first three provinces with high case numbers were Zhejiang, Guangdong and Jiangsu. The median age of the cases was 55 years and the male to female ratio was 2.3∶1. Up to 66% of cases had clear live poultry exposure history before illness onset, 31% of cases had unknown exposure history and only 3% of the cases had no live poultry exposure history. There were 35 household clusters (5 in 2013, 9 in 2014, 6 in 2015, 5 in 2016, 10 in 2017), which involved 72 cases, accounting for 5% of the total cases. Conclusions: The epidemic of human infection with H7N9 virus in China during 2013-2017 had obvious seasonality and spatial distribution. There was limited family clustering. Infection cases were mostly related to poultry contact.

Case-control geographic clustering for residential histories accounting for risk factors and covariates.

PubMed

Jacquez, Geoffrey M; Meliker, Jaymie R; Avruskin, Gillian A; Goovaerts, Pierre; Kaufmann, Andy; Wilson, Mark L; Nriagu, Jerome

2006-08-03

Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn - we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters), Ingham (2) and Jackson (1) counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically assessed in the case-control study design.

Spatial analysis of lung, colorectal, and breast cancer on Cape Cod: An application of generalized additive models to case-control data

PubMed Central

Vieira, Verónica; Webster, Thomas; Weinberg, Janice; Aschengrau, Ann; Ozonoff, David

2005-01-01

Background The availability of geographic information from cancer and birth defect registries has increased public demands for investigation of perceived disease clusters. Many neighborhood-level cluster investigations are methodologically problematic, while maps made from registry data often ignore latency and many known risk factors. Population-based case-control and cohort studies provide a stronger foundation for spatial epidemiology because potential confounders and disease latency can be addressed. Methods We investigated the association between residence and colorectal, lung, and breast cancer on upper Cape Cod, Massachusetts (USA) using extensive data on covariates and residential history from two case-control studies for 1983–1993. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. The resulting continuous surface estimates disease rates relative to the whole study area. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk. Results Maps of colorectal cancer were relatively flat. Assuming 15 years of latency, lung cancer was significantly elevated just northeast of the Massachusetts Military Reservation, although the result did not hold when we restricted to residences of longest duration. Earlier non-spatial epidemiology had found a weak association between lung cancer and proximity to gun and mortar positions on the reservation. Breast cancer hot spots tended to increase in magnitude as we increased latency and adjusted for covariates, indicating that confounders were partly hiding these areas. Significant breast cancer hot spots were located near known groundwater plumes and the Massachusetts Military Reservation. Discussion Spatial epidemiology of population-based case-control studies addresses many methodological criticisms of cluster studies and generates new exposure hypotheses. Our results provide evidence for spatial clustering of breast cancer on upper Cape Cod. The analysis suggests further investigation of the potential association between breast cancer and pollution plumes based on detailed exposure modeling. PMID:15955253

Spatial analysis of lung, colorectal, and breast cancer on Cape Cod: an application of generalized additive models to case-control data.

PubMed

Vieira, Verónica; Webster, Thomas; Weinberg, Janice; Aschengrau, Ann; Ozonoff, David

2005-06-14

The availability of geographic information from cancer and birth defect registries has increased public demands for investigation of perceived disease clusters. Many neighborhood-level cluster investigations are methodologically problematic, while maps made from registry data often ignore latency and many known risk factors. Population-based case-control and cohort studies provide a stronger foundation for spatial epidemiology because potential confounders and disease latency can be addressed. We investigated the association between residence and colorectal, lung, and breast cancer on upper Cape Cod, Massachusetts (USA) using extensive data on covariates and residential history from two case-control studies for 1983-1993. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. The resulting continuous surface estimates disease rates relative to the whole study area. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk. Maps of colorectal cancer were relatively flat. Assuming 15 years of latency, lung cancer was significantly elevated just northeast of the Massachusetts Military Reservation, although the result did not hold when we restricted to residences of longest duration. Earlier non-spatial epidemiology had found a weak association between lung cancer and proximity to gun and mortar positions on the reservation. Breast cancer hot spots tended to increase in magnitude as we increased latency and adjusted for covariates, indicating that confounders were partly hiding these areas. Significant breast cancer hot spots were located near known groundwater plumes and the Massachusetts Military Reservation. Spatial epidemiology of population-based case-control studies addresses many methodological criticisms of cluster studies and generates new exposure hypotheses. Our results provide evidence for spatial clustering of breast cancer on upper Cape Cod. The analysis suggests further investigation of the potential association between breast cancer and pollution plumes based on detailed exposure modeling.

Cluster analysis of Scedosporium boydii infections in a single hospital.

PubMed

Bernhardt, Anne; Seibold, Michael; Rickerts, Volker; Tintelnot, Kathrin

2015-10-01

Scedosporiosis is a rare, but often fatal mycotic infection occurring in immunosuppressed as well as in immunocompetent patients. Over a period of 14 months, Scedosporium boydii isolates were sent to our reference laboratory from six immunocompetent patients treated at a single hospital in Germany. In analogy to the EORTC/MSG criteria, four patients were classified as proven invasive scedosporiosis cases, and two patients as probable or possible cases. Of note, in five patients scedosporiosis was diagnosed between 1 and 14 months (median 5.0 months) after cardiac surgery. Despite antimycotic treatment two patients died, and three were lost for long-term follow-up. All clinical S. boydii isolates were characterized by molecular analysis using multilocus sequence typing (MLST). An identical MLST type was found in five patients who had been treated in the surgery unit, suggesting a link between these infections. The source of S. boydii has not been identified. Within an observation period of 2 years before and after this cluster of infections no further cases of scedosporiosis were reported from this hospital. Copyright © 2015 Elsevier GmbH. All rights reserved.

Time-space clustering of Vibrio cholerae 01 in Matlab, Bangladesh, 1970-1982.

PubMed

Craig, M

1988-01-01

Growing evidence for the existence of an aquatic reservoir of Vibrio cholerae has led some observers to postulate the existence of two distinct modes of disease transmission: primary and secondary. In primary transmission vibrios pass from the aquatic reservoir to humans via edible aquatic flora or fauna, or drinking water. Secondary transmission consists of faecal-oral transmission from person-to-person and may spawn epidemics. Cholera outbreaks are particularly well documented for the Matlab area of Bangladesh, where a field station has been run since 1963, at which patients from a study population of nearly 200,000 are treated for diarrhoeal diseases and monitored in a longitudinal demographic surveillance system. This paper seeks to illuminate the process of secondary transmission by presenting preliminary results of an analysis of the time-space distribution of cholera cases in Matlab for the period 1970-1982. It is argued that the detection of time-space clusters of cases resulting from secondary transmission requires locational data below the level of the village, that is at the level of the bari, or patrilineally-related household group because this is where inter-personal contact is greatest. The mapping of the study area at the bari level is described briefly and it is argued that the proportion of all asymptomatic infections and cases which can be mapped is great enough to enable inferences about transmission processes to be drawn. Results of the analysis of time-space interaction using the Knox method are presented and provide some support for within-bari clustering of cases resulting from secondary transmission.(ABSTRACT TRUNCATED AT 250 WORDS)

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters - Fluke- Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3’UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation ofmore » H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores - mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Lastly, our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.« less

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

DOE PAGES

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han; ...

2017-06-30

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters - Fluke- Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3’UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation ofmore » H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores - mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Lastly, our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.« less

Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes.

PubMed

Uchikoga, Nobuyuki; Hirokawa, Takatsugu

2010-05-11

Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG), CaM kinase kinase (CaMKK) and the plasma membrane Ca2+ ATPase pump (PMCA), and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

Use of Fouler Transforms to define landscape scales of analysis for disturbances: A case study of thinned and unthinned forest stands

Treesearch

J. E. Lundquist; R. A. Sommerfeld

2002-01-01

Various disturbances such as disease and management practices cause canopy gaps that change patterns of forest stand structure. This study examined the usefulness of digital image analysis using aerial photos, Fourier Tranforms, and cluster analysis to investigate how different spatial statistics are affected by spatial scale. The specific aims were to: 1) evaluate how...

An open source software for fast grid-based data-mining in spatial epidemiology (FGBASE).

PubMed

Baker, David M; Valleron, Alain-Jacques

2014-10-30

Examining whether disease cases are clustered in space is an important part of epidemiological research. Another important part of spatial epidemiology is testing whether patients suffering from a disease are more, or less, exposed to environmental factors of interest than adequately defined controls. Both approaches involve determining the number of cases and controls (or population at risk) in specific zones. For cluster searches, this often must be done for millions of different zones. Doing this by calculating distances can lead to very lengthy computations. In this work we discuss the computational advantages of geographical grid-based methods, and introduce an open source software (FGBASE) which we have created for this purpose. Geographical grids based on the Lambert Azimuthal Equal Area projection are well suited for spatial epidemiology because they preserve area: each cell of the grid has the same area. We describe how data is projected onto such a grid, as well as grid-based algorithms for spatial epidemiological data-mining. The software program (FGBASE), that we have developed, implements these grid-based methods. The grid based algorithms perform extremely fast. This is particularly the case for cluster searches. When applied to a cohort of French Type 1 Diabetes (T1D) patients, as an example, the grid based algorithms detected potential clusters in a few seconds on a modern laptop. This compares very favorably to an equivalent cluster search using distance calculations instead of a grid, which took over 4 hours on the same computer. In the case study we discovered 4 potential clusters of T1D cases near the cities of Le Havre, Dunkerque, Toulouse and Nantes. One example of environmental analysis with our software was to study whether a significant association could be found between distance to vineyards with heavy pesticide. None was found. In both examples, the software facilitates the rapid testing of hypotheses. Grid-based algorithms for mining spatial epidemiological data provide advantages in terms of computational complexity thus improving the speed of computations. We believe that these methods and this software tool (FGBASE) will lower the computational barriers to entry for those performing epidemiological research.

Comparative Study of IS6110 Restriction Fragment Length Polymorphism and Variable-Number Tandem-Repeat Typing of Mycobacterium tuberculosis Isolates in the Netherlands, Based on a 5-Year Nationwide Survey

PubMed Central

de Beer, Jessica L.; van Ingen, Jakko; de Vries, Gerard; Erkens, Connie; Sebek, Maruschka; Mulder, Arnout; Sloot, Rosa; van den Brandt, Anne-Marie; Enaimi, Mimount; Kremer, Kristin; Supply, Philip

2013-01-01

In order to switch from IS6110 and polymorphic GC-rich repetitive sequence (PGRS) restriction fragment length polymorphism (RFLP) to 24-locus variable-number tandem-repeat (VNTR) typing of Mycobacterium tuberculosis complex isolates in the national tuberculosis control program in The Netherlands, a detailed evaluation on discriminatory power and agreement with findings in a cluster investigation was performed on 3,975 tuberculosis cases during the period of 2004 to 2008. The level of discrimination of the two typing methods did not differ substantially: RFLP typing yielded 2,733 distinct patterns compared to 2,607 in VNTR typing. The global concordance, defined as isolates labeled unique or identically distributed in clusters by both methods, amounted to 78.5% (n = 3,123). Of the remaining 855 cases, 12% (n = 479) of the cases were clustered only by VNTR, 7.7% (n = 305) only by RFLP typing, and 1.8% (n = 71) revealed different cluster compositions in the two approaches. A cluster investigation was performed for 87% (n = 1,462) of the cases clustered by RFLP. For the 740 cases with confirmed or presumed epidemiological links, 92% were concordant with VNTR typing. In contrast, only 64% of the 722 cases without an epidemiological link but clustered by RFLP typing were also clustered by VNTR typing. We conclude that VNTR typing has a discriminatory power equal to IS6110 RFLP typing but is in better agreement with findings in a cluster investigation performed on an RFLP-clustering-based cluster investigation. Both aspects make VNTR typing a suitable method for tuberculosis surveillance systems. PMID:23363841

[Temporal-spatial analysis of bacillary dysentery in the Three Gorges Area of China, 2005-2016].

PubMed

Zhang, P; Zhang, J; Chang, Z R; Li, Z J

2018-01-10

Objective: To analyze the spatial and temporal distributions of bacillary dysentery in Chongqing, Yichang and Enshi (the Three Gorges Area) from 2005 to 2016, and provide evidence for the disease prevention and control. Methods: The incidence data of bacillary dysentery in the Three Gorges Area during this period were collected from National Notifiable Infectious Disease Reporting System. The spatial-temporal scan statistic was conducted with software SaTScan 9.4 and bacillary dysentery clusters were visualized with software ArcGIS 10.3. Results: A total of 126 196 cases were reported in the Three Gorges Area during 2005-2016, with an average incidence rate of 29.67/100 000. The overall incidence was in a downward trend, with an average annual decline rate of 4.74%. Cases occurred all the year round but with an obvious seasonal increase between May and October. Among the reported cases, 44.71% (56 421/126 196) were children under 5-year-old, the cases in children outside child care settings accounted for 41.93% (52 918/126 196) of the total. The incidence rates in districts of Yuzhong, Dadukou, Jiangbei, Shapingba, Jiulongpo, Nanan, Yubei, Chengkou of Chongqing and districts of Xiling and Wujiagang of Yichang city of Hubei province were high, ranging from 60.20/100 000 to 114.81/100 000. Spatial-temporal scan statistic for the spatial and temporal distributions of bacillary dysentery during this period revealed that the temporal distribution was during May-October, and there were 12 class Ⅰ clusters, 35 class Ⅱ clusters, and 9 clusters without statistical significance in counties with high incidence. All the class Ⅰ clusters were in urban area of Chongqing (Yuzhong, Dadukou, Jiangbei, Shapingba, Jiulongpo, Nanan, Beibei, Yubei, Banan) and surrounding counties, and the class Ⅱ clusters transformed from concentrated distribution to scattered distribution. Conclusions: Temporal and spatial cluster of bacillary dysentery incidence existed in the three gorges area during 2005-2016. It is necessary to strengthen the bacillary dysentery prevention and control in urban areas of Chongqing and Yichang.

Childhood cancer in small geographical areas and proximity to air-polluting industries.

PubMed

Ortega-García, Juan A; López-Hernández, Fernando A; Cárceles-Álvarez, Alberto; Fuster-Soler, José L; Sotomayor, Diana I; Ramis, Rebeca

2017-07-01

Pediatric cancer has been associated with exposure to certain environmental carcinogens. The purpose of this work is to analyse the relationship between environmental pollution and pediatric cancer risk. We analysed all incidences of pediatric cancer (<15) diagnosed in a Spanish region during the period 1998-2015. The place of residence of each patient and the exact geographical coordinates of main industrial facilities was codified in order to analyse the spatial distribution of cases of cancer in relation to industrial areas. Focal tests and focused Scan methodology were used for the identification of high-incidence-rate spatial clusters around the main industrial pollution foci. The crude rate for the period was 148.0 cases per 1,000,0000 children. The incidence of pediatric cancer increased significantly along the period of study. With respect to spatial distribution, results showed significant high incidence around some industrial pollution foci group and the Scan methodology identify spatial clustering. We observe a global major incidence of non Hodgkin lymphomas (NHL) considering all foci, and high incidence of Sympathetic Nervous System Tumour (SNST) around Energy and Electric and organic and inorganic chemical industries foci group. In the analysis foci to foci, the focused Scan test identifies several significant spatial clusters. Particularly, three significant clusters were identified: the first of SNST was around energy-generating chemical industries (2 cases versus the expected 0.26), another of NHL was around residue-valorisation plants (5 cases versus the expected 0.91) and finally one cluster of Hodgkin lymphoma around building materials (3 cases versus the expected 2.2) CONCLUSION: Results suggest a possible association between proximity to certain industries and pediatric cancer risk. More evidences are necessary before establishing the relationship between industrial pollution and pediatric cancer incidence. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Accounting for measurement error in biomarker data and misclassification of subtypes in the analysis of tumor data

PubMed Central

Nevo, Daniel; Zucker, David M.; Tamimi, Rulla M.; Wang, Molin

2017-01-01

A common paradigm in dealing with heterogeneity across tumors in cancer analysis is to cluster the tumors into subtypes using marker data on the tumor, and then to analyze each of the clusters separately. A more specific target is to investigate the association between risk factors and specific subtypes and to use the results for personalized preventive treatment. This task is usually carried out in two steps–clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The first is the measurement error in the biomarker values. The second is the misclassification error when assigning observations to clusters. We consider the case with a specified set of relevant markers and propose a unified single-likelihood approach for normally distributed biomarkers. As an alternative, we consider a two-step procedure with the tumor type misclassification error taken into account in the second-step risk factor analysis. We describe our method for binary data and also for survival analysis data using a modified version of the Cox model. We present asymptotic theory for the proposed estimators. Simulation results indicate that our methods significantly lower the bias with a small price being paid in terms of variance. We present an analysis of breast cancer data from the Nurses’ Health Study to demonstrate the utility of our method. PMID:27558651

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Statistical analysis and handling of missing data in cluster randomized trials: a systematic review.

PubMed

Fiero, Mallorie H; Huang, Shuang; Oren, Eyal; Bell, Melanie L

2016-02-09

Cluster randomized trials (CRTs) randomize participants in groups, rather than as individuals and are key tools used to assess interventions in health research where treatment contamination is likely or if individual randomization is not feasible. Two potential major pitfalls exist regarding CRTs, namely handling missing data and not accounting for clustering in the primary analysis. The aim of this review was to evaluate approaches for handling missing data and statistical analysis with respect to the primary outcome in CRTs. We systematically searched for CRTs published between August 2013 and July 2014 using PubMed, Web of Science, and PsycINFO. For each trial, two independent reviewers assessed the extent of the missing data and method(s) used for handling missing data in the primary and sensitivity analyses. We evaluated the primary analysis and determined whether it was at the cluster or individual level. Of the 86 included CRTs, 80 (93%) trials reported some missing outcome data. Of those reporting missing data, the median percent of individuals with a missing outcome was 19% (range 0.5 to 90%). The most common way to handle missing data in the primary analysis was complete case analysis (44, 55%), whereas 18 (22%) used mixed models, six (8%) used single imputation, four (5%) used unweighted generalized estimating equations, and two (2%) used multiple imputation. Fourteen (16%) trials reported a sensitivity analysis for missing data, but most assumed the same missing data mechanism as in the primary analysis. Overall, 67 (78%) trials accounted for clustering in the primary analysis. High rates of missing outcome data are present in the majority of CRTs, yet handling missing data in practice remains suboptimal. Researchers and applied statisticians should carry out appropriate missing data methods, which are valid under plausible assumptions in order to increase statistical power in trials and reduce the possibility of bias. Sensitivity analysis should be performed, with weakened assumptions regarding the missing data mechanism to explore the robustness of results reported in the primary analysis.

Health issues in the Arab American community. Male infertility in Lebanon: a case-controlled study.

PubMed

Kobeissi, Loulou; Inhorn, Marcia C

2007-01-01

The impact of risk factors, such as consanguinity and familial clustering, reproductive infections, traumas, and diseases, lifestyle factors and occupational and war exposures on male infertility, was investigated in a case-controlled study conducted in Lebanon. One-hundred-twenty males and 100 controls of Lebanese, Syrian or Lebanese-Palestinian descents were selected from two in-vitro fertilization (IVF) clinics located in Beirut, Lebanon. All cases suffered from impaired sperm count and function, according to World Health Organization guidelines for semen analysis. Controls were the fertile husbands of infertile women. Data were collected using a semi-structured interview, laboratory blood testing and the results of the most recent semen analysis. Univariate, bivariate and multivariate logistic regression analyses were used for data analysis, along with checks for effect modification and control of confounders. Consanguinity and the familial clustering of male infertility cases, as well as reproductive illnesses and war exposures were independently significant risk factors for male infertility. The odds of having infertility problems in the immediate family were 2.6 times higher in cases than controls. The odds of reproductive illness were 2 times higher in cases than controls. The odds of war exposures were 1.57 times higher in cases than controls. Occupational exposures, such as smoking and caffeine intake, were not shown to be important risk factors. This case-controlled study highlights the importance of investigating the etiology of male infertility in Middle Eastern communities. It suggests the need to expand research on male reproductive health in the Middle East in order to improve the prevention and management of male infertility and other male reproductive health problems.

Herpes simplex virus type 2: Cluster of unrelated cases in an intensive care unit.

PubMed

Troché, Gilles; Marque Juillet, Stephanie; Burrel, Sonia; Boutolleau, David; Bédos, Jean-Pierre; Legriel, Stephane

2016-10-01

Herpes simplex viruses, which are associated with various clinical manifestations, can be transmitted to critically ill patients from other patients or health care staff. We report an apparent outbreak of mucocutaneous herpes simplex virus 2 infections (5 cases in 10 weeks). An epidemiologic investigation and genotype analysis showed no connections among the 5 cases. Copyright © 2016 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Including the third dimension: a spatial analysis of TB cases in Houston Harris County.

PubMed

Feske, Marsha L; Teeter, Larry D; Musser, James M; Graviss, Edward A

2011-12-01

To reach the tuberculosis (TB) elimination goals established by the Institute of Medicine (IOM) and the Centers for Disease Control and Prevention (CDC), measures must be taken to speed the currently stagnant TB elimination rate and curtail a future peak in TB incidence. Increases in TB incidence have historically coincided with immigration, poverty, and joblessness; all situations that are currently occurring worldwide. Effective TB elimination strategies will require the geographical elucidation of areas within the U.S. that have endemic TB, and systematic surveillance of the locations and location-based risk factors associated with TB transmission. Surveillance data was used to assess the spatial distribution of cases, the yearly TB incidence by census tract, and the statistical significance of case clustering. The analysis revealed that there are neighborhoods within Houston/Harris County that had a heavy TB burden. The maximum yearly incidence varied from 245/100,000-754/100,000 and was not exclusively dependent of the number of cases reported. Geographically weighted regression identified risk factors associated with the spatial distribution of cases such as: poverty, age, Black race, and foreign birth. Public transportation was also associated with the spatial distribution of cases and census tracts identified as high incidence were found to be irregularly clustered within communities of varied SES. Copyright © 2011 Elsevier Ltd. All rights reserved.

Enhanced Scattering of Diffuse Ions on Front of the Earth's Quasi-Parallel Bow Shock: a Case Study

NASA Astrophysics Data System (ADS)

Kis, A.; Matsukiyo, S.; Otsuka, F.; Hada, T.; Lemperger, I.; Dandouras, I. S.; Barta, V.; Facsko, G. I.

2017-12-01

In the analysis we present a case study of three energetic upstream ion events at the Earth's quasi-parallel bow shock based on multi-spacecraft data recorded by Cluster. The CIS-HIA instrument onboard Cluster provides partial energetic ion densities in 4 energy channels between 10 and 32 keV.The difference of the partial ion densities recorded by the individual spacecraft at various distances from the bow shock surface makes possible the determination of the spatial gradient of energetic ions.Using the gradient values we determined the spatial profile of the energetic ion partial densities as a function of distance from the bow shock and we calculated the e-folding distance and the diffusion coefficient for each event and each ion energy range. Results show that in two cases the scattering of diffuse ions takes place in a normal way, as "by the book", and the e-folding distance and diffusion coefficient values are comparable with previous results. On the other hand, in the third case the e-folding distance and the diffusion coefficient values are significantly lower, which suggests that in this case the scattering process -and therefore the diffusive shock acceleration (DSA) mechanism also- is much more efficient. Our analysis provides an explanation for this "enhanced" scattering process recorded in the third case.

Benthic foraminiferal assemblages as bio-indicators of metals contamination in sediments, Qarun Lake as a case study, Egypt

NASA Astrophysics Data System (ADS)

Abd El Naby, Ahmed; Al Menoufy, Safia; Gad, Ahmed

2018-03-01

Qarun Lake, in the Fayoum Depression of the Western Desert of Egypt, lies within the deepest area in the River Nile flood plain. The drainage water in the Qarun Lake is derived from the discharge of the natural and artificial drainage systems in the Fayoum. Mixed domestic and agricultural pollutants, including heavy metals, nitrates, phosphates, sulfates and pesticides, are discharged into Qarun Lake. Forty-six samples, collected from the undisturbed layer of sediments were used for benthic foraminiferal analysis. Concentrations of some selected trace metal elements (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sr, V, and Zn) were also determined. Statistical analysis of the abiotic variables (Texture distribution of sediments, Physico-chemical parameters, and metals concentrations) and of the biotic variables (distribution of benthic foraminiferal species) were also performed. The Q-mode cluster analysis of benthic foraminiferal distribution has provided evidence that the Qarun Lake can be subdivided into two cluster groups (A and B), reflecting environmental changes in the lake ecosystem. Cluster B can also be subdivided into two sub-clusters (B1 and B2). The presence of only pollution tolerant taxa with higher faunal density and lower diversity and the absence of the other foraminiferal assemblages in cluster A were attributed to the high concentration of trace metal elements and the strong environmental stress at the eastern and central parts of the Qarun Lake.

Variable number of tandem repeats and pulsed-field gel electrophoresis cluster analysis of enterohemorrhagic Escherichia coli serovar O157 strains.

PubMed

Yokoyama, Eiji; Uchimura, Masako

2007-11-01

Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.

National sample survey to assess the new case disease burden of leprosy in India

PubMed Central

Katoch, Kiran; Aggarwal, Abha; Yadav, Virendra Singh; Pandey, Arvind

2017-01-01

A national sample survey of leprosy was undertaken in partnership with Indian Council of Medical Research (ICMR) institutions, National Leprosy Eradication Programme (NLEP), Panchayati Raj members, and treated leprosy patients to detect new cases of leprosy in India. The objectives of the survey were to estimate the new leprosy case load; record both Grade 1 and Grade 2 disabilities in the new cases; and to assess the magnitude of stigma and discrimination prevalent in the society. A cluster based, cross-sectional survey involving all States was used for the door-to-door survey using inverse sampling methodology. Rural and urban clusters were sampled separately. The population screened for detecting 28 new cases in rural and 30 in urban clusters was enumerated, recorded and analyzed. Data capture and analysis in different schedules were the main tools used. For quality control three tiers of experts were utilized for the confirmation of cases and disabilities. Self-stigma was assessed in more than half of the total new patients detected with disabilities by the approved questionnaire. A different questionnaire was used to assess the stigma in the community. A population of 14,725,525 (10,302,443 rural; 4,423,082 urban) was screened and 2161 new cases - 1300 paucibacillary (PB) and 861 multibacillary (MB) were detected. New case estimates for leprosy was 330,346 (95% Confidence limits, 287,445-380,851). Disabilities observed in these cases were 2.05/100,000 population and 13.9 per cent (302/2161) in new cases. Self-stigma in patients with disabilities was reduced, and the patients were well accepted by the spouse, neighbour, at workplace and in social functions. PMID:29512601

Whole genome sequencing as a tool to investigate a cluster of seven cases of listeriosis in Austria and Germany, 2011-2013.

PubMed

Schmid, D; Allerberger, F; Huhulescu, S; Pietzka, A; Amar, C; Kleta, S; Prager, R; Preußel, K; Aichinger, E; Mellmann, A

2014-05-01

A cluster of seven human cases of listeriosis occurred in Austria and in Germany between April 2011 and July 2013. The Listeria monocytogenes serovar (SV) 1/2b isolates shared pulsed-field gel electrophoresis (PFGE) and fluorescent amplified fragment length polymorphism (fAFLP) patterns indistinguishable from those from five food producers. The seven human isolates, a control strain with a different PFGE/fAFLP profile and ten food isolates were subjected to whole genome sequencing (WGS) in a blinded fashion. A gene-by-gene comparison (multilocus sequence typing (MLST)+) was performed, and the resulting whole genome allelic profiles were compared using SeqSphere(+) software version 1.0. On analysis of 2298 genes, the four human outbreak isolates from 2012 to 2013 had different alleles at ≤6 genes, i.e. differed by ≤6 genes from each other; the dendrogram placed these isolates in between five Austrian unaged soft cheese isolates from producer A (≤19-gene difference from the human cluster) and two Austrian ready-to-eat meat isolates from producer B (≤8-gene difference from the human cluster). Both food products appeared on grocery bills prospectively collected by these outbreak cases after hospital discharge. Epidemiological results on food consumption and MLST+ clearly separated the three cases in 2011 from the four 2012-2013 outbreak cases (≥48 different genes). We showed that WGS is capable of discriminating L. monocytogenes SV1/2b clones not distinguishable by PFGE and fAFLP. The listeriosis outbreak described clearly underlines the potential of sequence-based typing methods to offer enhanced resolution and comparability of typing systems for public health applications. © 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.

Energy Innovation Clusters and their Influence on Manufacturing: A Case Study Perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engel-Cox, Jill; Hill, Derek

Innovation clusters have been important for recent development of clean energy technologies and their emergence as mature, globally competitive industries. However, the factors that influence the co-location of manufacturing activities with innovation clusters are less clear. A central question for government agencies seeking to grow manufacturing as part of economic development in their location is how innovation clusters influence manufacturing. Thus, this paper examines case studies of innovation clusters for three different clean energy technologies that have developed in at least two locations: solar PV clusters in California and the province of Jiangsu in China, wind turbine clusters in Germanymore » and the U.S. Great Lakes region, and ethanol clusters in the U.S. Midwest and the state of Sao Paulo in Brazil. These case studies provide initial insight into factors and conditions that contribute to technology manufacturing facility location decisions.« less

Analysis of Changes in Recent Tuberculosis Transmission Patterns after a Sharp Increase in Immigration▿

PubMed Central

Iñigo, Jesús; García de Viedma, Darío; Arce, Araceli; Palenque, Elia; Alonso Rodríguez, Noelia; Rodríguez, Elena; Ruiz Serrano, María Jesús; Andrés, Sandra; Bouza, Emilio; Chaves, Fernando

2007-01-01

We conducted a population-based molecular epidemiological study of tuberculosis (TB) in Madrid, Spain (2002 to 2004), to define transmission patterns and factors associated with clustering. We particularly focused on examining how the increase in TB cases among immigrants in recent years (2.8% in 1997 to 1999 to 36.2% during the current study) was modifying transmission patterns. Mycobacterium tuberculosis isolates obtained from patients living in nine districts of Madrid (1,459,232 inhabitants) were genotyped. The TB case rate among foreign-born people was three to four times that of Spanish-born people, and the median time from arrival to the onset of treatment was 22.4 months. During the study period, 227 (36.3%) patients were grouped in 64 clusters, and 115 (50.7%) of them were in 21 clusters with mixed Spanish-born and foreign-born patients. Three of the 21 mixed clusters accounted for 21.1% of clustered patients. Twenty-two of 38 (57.9%) immigrants in mixed clusters were infected with TB strains that had already been identified in the native population in 1997 to 1999, including the three most prevalent strains. Factors identified as independent predictors of clustering were homelessness (odds ratio [OR], 2.3; 95% confidence interval [95% CI], 1.2 to 4.5; P = 0.011) and to be born in Spain (OR, 1.8; 95% CI, 1.2 to 2.6; P = 0.002). The results indicated that (i) TB transmission was higher in Spanish-born people, associated mainly with homelessness, (ii) that foreign-born people were much less likely to be clustered, suggesting a higher percentage of infection before arriving in Spain, and (iii) that an extensive transmission between Spanish- and foreign-born populations, caused mainly by autochthonous strains, was taking place in Madrid. PMID:17108076

Non-targeted analyses of animal plasma: betaine and choline represent the nutritional and metabolic status.

PubMed

Katayama, K; Sato, T; Arai, T; Amao, H; Ohta, Y; Ozawa, T; Kenyon, P R; Hickson, R E; Tazaki, H

2013-02-01

Simple liquid chromatography-mass spectrometry (LC-MS) was applied to non-targeted metabolic analyses to discover new metabolic markers in animal plasma. Principle component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA) were used to analyse LC-MS multivariate data. PCA clearly generated two separate clusters for artificially induced diabetic mice and healthy control mice. PLS-DA of time-course changes in plasma metabolites of chicks after feeding generated three clusters (pre- and immediately after feeding, 0.5-3 h after feeding and 4 h after feeding). Two separate clusters were also generated for plasma metabolites of pregnant Angus heifers with differing live-weight change profiles (gaining or losing). The accompanying PLS-DA loading plot detailed the metabolites that contribute the most to the cluster separation. In each case, the same highly hydrophilic metabolite was strongly correlated to the group separation. The metabolite was identified as betaine by LC-MS/MS. This result indicates that betaine and its metabolic precursor, choline, may be useful biomarkers to evaluate the nutritional and metabolic status of animals. © 2011 Blackwell Verlag GmbH.

Epidemiological links between tuberculosis cases identified twice as efficiently by whole genome sequencing than conventional molecular typing: A population-based study.

PubMed

Jajou, Rana; de Neeling, Albert; van Hunen, Rianne; de Vries, Gerard; Schimmel, Henrieke; Mulder, Arnout; Anthony, Richard; van der Hoek, Wim; van Soolingen, Dick

2018-01-01

Patients with Mycobacterium tuberculosis isolates sharing identical DNA fingerprint patterns can be epidemiologically linked. However, municipal health services in the Netherlands are able to confirm an epidemiological link in only around 23% of the patients with isolates clustered by the conventional variable number of tandem repeat (VNTR) genotyping. This research aims to investigate whether whole genome sequencing (WGS) is a more reliable predictor of epidemiological links between tuberculosis patients than VNTR genotyping. VNTR genotyping and WGS were performed in parallel on all Mycobacterium tuberculosis complex isolates received at the Netherlands National Institute for Public Health and the Environment in 2016. Isolates were clustered by VNTR when they shared identical 24-loci VNTR patterns; isolates were assigned to a WGS cluster when the pair-wise genetic distance was ≤ 12 single nucleotide polymorphisms (SNPs). Cluster investigation was performed by municipal health services on all isolates clustered by VNTR in 2016. The proportion of epidemiological links identified among patients clustered by either method was calculated. In total, 535 isolates were genotyped, of which 25% (134/535) were clustered by VNTR and 14% (76/535) by WGS; the concordance between both typing methods was 86%. The proportion of epidemiological links among WGS clustered cases (57%) was twice as common than among VNTR clustered cases (31%). When WGS was applied, the number of clustered isolates was halved, while all epidemiologically linked cases remained clustered. WGS is therefore a more reliable tool to predict epidemiological links between tuberculosis cases than VNTR genotyping and will allow more efficient transmission tracing, as epidemiological investigations based on false clustering can be avoided.

Emission of terahertz waves in the interaction of a laser pulse with clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frolov, A. A., E-mail: frolov@ihed.ras.ru

2016-07-15

A theory of generation of terahertz radiation in the interaction of a femtosecond laser pulse with a spherical cluster is developed for the case in which the density of free electrons in the cluster plasma exceeds the critical value. The spectral, angular, and energy characteristics of the emitted terahertz radiation are investigated, as well as its spatiotemporal structure. It is shown that the directional pattern of radiation has a quadrupole structure and that the emission spectrum has a broad maximum at a frequency nearly equal to the reciprocal of the laser pulse duration. It is found that the total radiatedmore » energy depends strongly on the cluster size. Analysis of the spatiotemporal profile of the terahertz signal shows that it has a femtosecond duration and contains only two oscillation cycles.« less

Remote sensing of a NTC radio source from a Cluster tilted spacecraft pair

NASA Astrophysics Data System (ADS)

Décréau, Pierrette; Kougblénou, Séna; Lointier, Guillaume; Rauch, Jean Louis; Trotignon, Jean Gabriel; Vallières, Xavier; Canu, Patrick; Rochel Grimald, Sandrine; El-Lemdani Mazouz, Farida; Darrouzet, Fabien

2014-05-01

The non-thermal continuum (NTC) radiation is a radio wave produced within the magnetosphere of a planet. It has been observed in space around Earth since the '70s, and within the magnetospheres of other planets since the late '80s. A new study using ESA's Cluster mission has shown improved precision in determining the source of various radio emissions produced by the Earth. The experiment involved tilting one of the four identical Cluster spacecraft to measure the electric field of this emission in three dimensions for the first time. Our analysis of a NTC case event pinpointed a small deviation from the generally assumed (circular) polarization of this emission. We show that classical triangulation, in this case using three of the spacecraft located thousands of kilometres apart, can lead to an erroneous source location. A second method, using the new 3D electric field measurements, indicated a source located along the plasmapause at medium geomagnetic latitude, far away from the source location estimated by triangulation. Cluster observations reveal that this NTC source emits from the flank of the plasmapause towards the polar cap. Understanding the source of NTC waves will help with the broader understanding of their generation, amplification, and propagation.

Into the complexity of coseismic landslide clustering

NASA Astrophysics Data System (ADS)

Meunier, Patrick; Marc, Odin; Uchida, Taro; Hovius, Niels

2014-05-01

Earthquake-triggered landslides tend to cluster along topographic crests while rainfall-induced landslides are more uniformly distributed on hillslopes [1]. In theory, rainfall induced landslides should even occur downslope preferentially, where pore pressure induced by groundwater flows is the highest. Past studies on landslide clustering are all based on the analysis of complete dataset or subdataset of landslides associated with a given event (seismic or climatic) as a whole. In this work, we document the spatial variation of the landslide position (on hillslopes) within the epicentral area for the cases of the 1999 Chichi, the 2004 Niigata and the 2008 Iwate earthquakes. We show that landslide clustering is not uniform in space and exhibit patterns that vary a lot from one case to another. These patterns are not easy to interpret as they don't seem to be controlled by a single governing parameter but result from a complex interaction between local (hillslope length and gradient, lithology) and seismic (distance to source, slope aspect, radiation pattern, coseismic uplift) parameters. [1] Meunier, P., Hovius, N., & Haines, J. A. (2008). Topographic site effects and the location of earthquake induced landslides. Earth and Planetary Science Letters, 275(3), 221-232.

Tisettanta case study: the interoperation of furniture production companies

NASA Astrophysics Data System (ADS)

Amarilli, Fabrizio; Spreafico, Alberto

This chapter presents the Tisettanta case study, focusing on the definition of the possible innovations that ICT technologies can bring to the Italian wood-furniture industry. This sector is characterized by industrial clusters composed mainly of a few large companies with international brand reputations and a large base of SMEs that manufacture finished products or are specialized in the production of single components/processes (such as the Brianza cluster, where Tisettanta operates). In this particular business ecosystem, ICT technologies can bring relevant support and improvements to the supply chain process, where collaborations between enterprises are put into action through the exchange of business documents such as orders, order confirmation, bills of lading, invoices, etc. The analysis methodology adopted in the Tisettanta case study refers to the TEKNE Methodology of Change (see Chapter 2), which defines a framework for supporting firms in the adoption of the Internetworked Enterprise organizational paradigm.

Combining evidence from multiple electronic health care databases: performances of one-stage and two-stage meta-analysis in matched case-control studies.

PubMed

La Gamba, Fabiola; Corrao, Giovanni; Romio, Silvana; Sturkenboom, Miriam; Trifirò, Gianluca; Schink, Tania; de Ridder, Maria

2017-10-01

Clustering of patients in databases is usually ignored in one-stage meta-analysis of multi-database studies using matched case-control data. The aim of this study was to compare bias and efficiency of such a one-stage meta-analysis with a two-stage meta-analysis. First, we compared the approaches by generating matched case-control data under 5 simulated scenarios, built by varying: (1) the exposure-outcome association; (2) its variability among databases; (3) the confounding strength of one covariate on this association; (4) its variability; and (5) the (heterogeneous) confounding strength of two covariates. Second, we made the same comparison using empirical data from the ARITMO project, a multiple database study investigating the risk of ventricular arrhythmia following the use of medications with arrhythmogenic potential. In our study, we specifically investigated the effect of current use of promethazine. Bias increased for one-stage meta-analysis with increasing (1) between-database variance of exposure effect and (2) heterogeneous confounding generated by two covariates. The efficiency of one-stage meta-analysis was slightly lower than that of two-stage meta-analysis for the majority of investigated scenarios. Based on ARITMO data, there were no evident differences between one-stage (OR = 1.50, CI = [1.08; 2.08]) and two-stage (OR = 1.55, CI = [1.12; 2.16]) approaches. When the effect of interest is heterogeneous, a one-stage meta-analysis ignoring clustering gives biased estimates. Two-stage meta-analysis generates estimates at least as accurate and precise as one-stage meta-analysis. However, in a study using small databases and rare exposures and/or outcomes, a correct one-stage meta-analysis becomes essential. Copyright © 2017 John Wiley & Sons, Ltd.

Origin and evolution of the Perm Anomaly

NASA Astrophysics Data System (ADS)

Flament, N. E.; Williams, S.; Müller, D.; Gurnis, M.; Bower, D. J.

2016-12-01

Earth's lower mantle is characterized by two large-low-shear velocity provinces (LLSVPs, 15000 km in diameter, 500-1000 km high) located under Africa and the Pacific Ocean. In addition, a single, much smaller ( 1000 km in diameter, 500 km high) deep mantle structure named the "Perm Anomaly" was recently identified through the analysis of seismic tomography models. This discovery challenges current reconstructions of the evolution of the plate-mantle system that invoke plumes rising from the edges of the two LLSVPs, assumed spatially fixed and non-deforming in time. Here, we present mantle flow models constrained by tectonic reconstructions that reproduce the present-day structure of the lower mantle, and show a Perm-like anomaly. In the dynamic models, spanning 230 Myr, subducting slabs deform an initially uniform basal layer containing 2% of the volume of the mantle. Basal density, convective vigour, mantle viscosity, absolute plate motions, and relative plate motions are varied in a series of model cases. We use cluster analysis to classify equally-spaced points on Earth's surface into two groups with similar variations in present-day temperature between 1000-2800 km depth, for each model case. The procedure reveals a high-temperature cluster and a low-temperature cluster with respect to ambient mantle temperature below 2400 km depth. The spatial extent of the high-temperature cluster is in first-order agreement with the outlines of the LLSVPs and of the Perm Anomaly revealed by a similar cluster analysis of seven tomography models. Model success is quantified by computing the accuracy (between 0.56 and 0.76) of the temperature clusters in predicting the low-velocity cluster obtained from tomography, and qualified by the occurrence of a separate Perm-like anomaly. The anomaly formed in isolation prior to 150 Ma within a long-lived subduction network 22000 km in circumference composed of the Mongol-Okhotsk subduction along Eurasia to the west, northern Tethys subduction to the south, and east Asia subduction to the east, then migrated 2500 km westward at an average rate of 1.7 cm/yr, indicating a greater mobility of deep mantle structures than previously recognized. We infer that the mobile Perm Anomaly could be linked to the Emeishan volcanics, in contrast to the previously proposed Siberian Traps.

Cemeteries Are Effective Sites For Monitoring La Crosse Virus (LACv) and these Environments May Play a Role in LACv Infection

PubMed Central

Trout Fryxell, Rebecca T.; Freyman, Kimberly; Ulloa, Armando; Hendricks, Brian; Paulsen, Dave; Odoi, Agricola; Moncayo, Abelardo

2015-01-01

La Crosse encephalitis (LAC) is the leading arboviral disease among children, and was previously limited to the upper Midwest. In 2012 nine pediatric cases of LAC occurred in eastern Tennessee, including one fatal case. In an attempt to identify sites near an active LACv infection and describe the abundance and distribution of potential LACv vectors near a fatal LAC case in the Appalachian region, we initiated an end of season study using a combination of questing and oviposition mosquito traps placed at forty-nine sites consisting of cemeteries and houses within 16 radial kilometers of two pediatric infections. LACv was isolated from three Aedes triseriatus pools collected from cemeteries and spatial clustering analysis identified clusters of Ae. triseriatus and Ae. albopictus populations that overlapped in the same area as the 2012 LACv cases. Results indicate cemeteries are effective sites for monitoring LACv. The role of cemeteries and specific environmental features will be the focus of future investigations. PMID:25860584

On Mass Polarization Effect in Three-Body Nuclear Systems

NASA Astrophysics Data System (ADS)

Filikhin, I.; Kezerashvili, R. Ya.; Suslov, V. M.; Vlahovic, B.

2018-05-01

The mass polarization effect is considered for different three-body nuclear AAB systems having a strongly bound AB and unbound AA subsystems. We employ the Faddeev equations for calculations and the Schrödinger equation for analysis of the contribution of the mass polarization term of the kinetic-energy operator. For a three-boson system the mass polarization effect is determined by the difference of the doubled binding energy of the AB subsystem 2E2 and the three-body binding energy E3(V_{AA}=0) when the interaction between the identical particles is omitted. In this case: | E3(V_{AA}=0)| >2| E2| . In the case of a system complicated by isospins(spins), such as the kaonic clusters K-K-p and ppK-, a similar evaluation is impossible. For these systems it is found that | E3(V_{AA}=0)| <2| E2| . A model with an AB potential averaged over spin(isospin) variables transforms the latter case to the first one. The mass polarization effect calculated within this model is essential for the kaonic clusters. In addition we have obtained the relation |E_3|≤|2E_2| for the binding energy of the kaonic clusters.

Detecting space-time cancer clusters using residential histories

NASA Astrophysics Data System (ADS)

Jacquez, Geoffrey M.; Meliker, Jaymie R.

2007-04-01

Methods for analyzing geographic clusters of disease typically ignore the space-time variability inherent in epidemiologic datasets, do not adequately account for known risk factors (e.g., smoking and education) or covariates (e.g., age, gender, and race), and do not permit investigation of the latency window between exposure and disease. Our research group recently developed Q-statistics for evaluating space-time clustering in cancer case-control studies with residential histories. This technique relies on time-dependent nearest neighbor relationships to examine clustering at any moment in the life-course of the residential histories of cases relative to that of controls. In addition, in place of the widely used null hypothesis of spatial randomness, each individual's probability of being a case is instead based on his/her risk factors and covariates. Case-control clusters will be presented using residential histories of 220 bladder cancer cases and 440 controls in Michigan. In preliminary analyses of this dataset, smoking, age, gender, race and education were sufficient to explain the majority of the clustering of residential histories of the cases. Clusters of unexplained risk, however, were identified surrounding the business address histories of 10 industries that emit known or suspected bladder cancer carcinogens. The clustering of 5 of these industries began in the 1970's and persisted through the 1990's. This systematic approach for evaluating space-time clustering has the potential to generate novel hypotheses about environmental risk factors. These methods may be extended to detect differences in space-time patterns of any two groups of people, making them valuable for security intelligence and surveillance operations.

Association of paraoxonase gene cluster polymorphisms with ALS in France, Quebec, and Sweden.

PubMed

Valdmanis, P N; Kabashi, E; Dyck, A; Hince, P; Lee, J; Dion, P; D'Amour, M; Souchon, F; Bouchard, J-P; Salachas, F; Meininger, V; Andersen, P M; Camu, W; Dupré, N; Rouleau, G A

2008-08-12

The paraoxonase gene cluster on chromosome 7 comprising the PON1-3 genes is an attractive candidate for association in amyotrophic lateral sclerosis (ALS) given the role of paraoxonase genes during the response to oxidative stress and their contribution to the enzymatic break down of nerve toxins. Oxidative stress is considered one of the mechanisms involved in ALS pathogenesis. Evidence for this includes the fact that mutations of SOD1, which normally reduce the production of toxic superoxide anion, account for 12% to 23% of familial cases in ALS. In addition, PON variants were shown to be associated with susceptibility to ALS in several North American and European populations. We extended this analysis to examine 20 single nucleotide polymorphisms (SNPs) across the PON gene cluster in a set of patients from France (480 cases, 475 controls), Quebec (159 cases, 95 controls), and Sweden (558 cases, 506 controls). Although individual SNPs were not considered associated on their own, a haplotype of SNPs at the C-terminal portion of PON2 that includes the PON2 C311S amino acid change was significant in the French (p value 0.0075) and Quebec (p value 0.026) populations as well as all three populations combined (p value 1.69 x 10(-6)). Stratification of the samples showed that this variation was pertinent to ALS susceptibility as a whole, and not to a particular subset of patients. These findings contribute to the increasing weight of evidence that genetic variants in the paraoxonase gene cluster are associated with amyotrophic lateral sclerosis.

Spatio-temporal pattern analysis for evaluation of the spread of human infections with avian influenza A(H7N9) virus in China, 2013-2014.

PubMed

Dong, Wen; Yang, Kun; Xu, Quanli; Liu, Lin; Chen, Juan

2017-10-24

A large number (n = 460) of A(H7N9) human infections have been reported in China from March 2013 through December 2014, and H7N9 outbreaks in humans became an emerging issue for China health, which have caused numerous disease outbreaks in domestic poultry and wild bird populations, and threatened human health severely. The aims of this study were to investigate the directional trend of the epidemic and to identify the significant presence of spatial-temporal clustering of influenza A(H7N9) human cases between March 2013 and December 2014. Three distinct epidemic phases of A(H7N9) human infections were identified in this study. In each phase, standard deviational ellipse analysis was conducted to examine the directional trend of disease spreading, and retrospective space-time permutation scan statistic was then used to identify the spatio-temporal cluster patterns of H7N9 outbreaks in humans. The ever-changing location and the increasing size of the three identified standard deviational ellipses showed that the epidemic moved from east to southeast coast, and hence to some central regions, with a future epidemiological trend of continue dispersing to more central regions of China, and a few new human cases might also appear in parts of the western China. Furthermore, A(H7N9) human infections were clustering in space and time in the first two phases with five significant spatio-temporal clusters (p < 0.05), but there was no significant cluster identified in phase III. There was a new epidemiologic pattern that the decrease in significant spatio-temporal cluster of A(H7N9) human infections was accompanied with an obvious spatial expansion of the outbreaks during the study period, and identification of the spatio-temporal patterns of the epidemic can provide valuable insights for better understanding the spreading dynamics of the disease in China.

Case-control geographic clustering for residential histories accounting for risk factors and covariates

PubMed Central

2006-01-01

Background Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. Results Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters), Ingham (2) and Jackson (1) counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. Conclusion These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically assessed in the case-control study design. PMID:16887016

Using kernel density estimates to investigate lymphatic filariasis in northeast Brazil

PubMed Central

Medeiros, Zulma; Bonfim, Cristine; Brandão, Eduardo; Netto, Maria José Evangelista; Vasconcellos, Lucia; Ribeiro, Liany; Portugal, José Luiz

2012-01-01

After more than 10 years of the Global Program to Eliminate Lymphatic Filariasis (GPELF) in Brazil, advances have been seen, but the endemic disease persists as a public health problem. The aim of this study was to describe the spatial distribution of lymphatic filariasis in the municipality of Jaboatão dos Guararapes, Pernambuco, Brazil. An epidemiological survey was conducted in the municipality, and positive filariasis cases identified in this survey were georeferenced in point form, using the GPS. A kernel intensity estimator was applied to identify clusters with greater intensity of cases. We examined 23 673 individuals and 323 individuals with microfilaremia were identified, representing a mean prevalence rate of 1.4%. Around 88% of the districts surveyed presented cases of filarial infection, with prevalences of 0–5.6%. The male population was more affected by the infection, with 63.8% of the cases (P<0.005). Positive cases were found in all age groups examined. The kernel intensity estimator identified the areas of greatest intensity and least intensity of filarial infection cases. The case distribution was heterogeneous across the municipality. The kernel estimator identified spatial clusters of cases, thus indicating locations with greater intensity of transmission. The main advantage of this type of analysis lies in its ability to rapidly and easily show areas with the highest concentration of cases, thereby contributing towards planning, monitoring, and surveillance of filariasis elimination actions. Incorporation of geoprocessing and spatial analysis techniques constitutes an important tool for use within the GPELF. PMID:22943547

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

NASA Astrophysics Data System (ADS)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-07-17

The explosion of biological data has largely influenced the focus of today’s biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-06-01

The explosion of biological data has largely influenced the focus of today's biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Methods for sample size determination in cluster randomized trials

PubMed Central

Rutterford, Clare; Copas, Andrew; Eldridge, Sandra

2015-01-01

Background: The use of cluster randomized trials (CRTs) is increasing, along with the variety in their design and analysis. The simplest approach for their sample size calculation is to calculate the sample size assuming individual randomization and inflate this by a design effect to account for randomization by cluster. The assumptions of a simple design effect may not always be met; alternative or more complicated approaches are required. Methods: We summarise a wide range of sample size methods available for cluster randomized trials. For those familiar with sample size calculations for individually randomized trials but with less experience in the clustered case, this manuscript provides formulae for a wide range of scenarios with associated explanation and recommendations. For those with more experience, comprehensive summaries are provided that allow quick identification of methods for a given design, outcome and analysis method. Results: We present first those methods applicable to the simplest two-arm, parallel group, completely randomized design followed by methods that incorporate deviations from this design such as: variability in cluster sizes; attrition; non-compliance; or the inclusion of baseline covariates or repeated measures. The paper concludes with methods for alternative designs. Conclusions: There is a large amount of methodology available for sample size calculations in CRTs. This paper gives the most comprehensive description of published methodology for sample size calculation and provides an important resource for those designing these trials. PMID:26174515

Advanced analysis of forest fire clustering

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

Analysis of point pattern clustering is an important topic in spatial statistics and for many applications: biodiversity, epidemiology, natural hazards, geomarketing, etc. There are several fundamental approaches used to quantify spatial data clustering using topological, statistical and fractal measures. In the present research, the recently introduced multi-point Morisita index (mMI) is applied to study the spatial clustering of forest fires in Portugal. The data set consists of more than 30000 fire events covering the time period from 1975 to 2013. The distribution of forest fires is very complex and highly variable in space. mMI is a multi-point extension of the classical two-point Morisita index. In essence, mMI is estimated by covering the region under study by a grid and by computing how many times more likely it is that m points selected at random will be from the same grid cell than it would be in the case of a complete random Poisson process. By changing the number of grid cells (size of the grid cells), mMI characterizes the scaling properties of spatial clustering. From mMI, the data intrinsic dimension (fractal dimension) of the point distribution can be estimated as well. In this study, the mMI of forest fires is compared with the mMI of random patterns (RPs) generated within the validity domain defined as the forest area of Portugal. It turns out that the forest fires are highly clustered inside the validity domain in comparison with the RPs. Moreover, they demonstrate different scaling properties at different spatial scales. The results obtained from the mMI analysis are also compared with those of fractal measures of clustering - box counting and sand box counting approaches. REFERENCES Golay J., Kanevski M., Vega Orozco C., Leuenberger M., 2014: The multipoint Morisita index for the analysis of spatial patterns. Physica A, 406, 191-202. Golay J., Kanevski M. 2015: A new estimator of intrinsic dimension based on the multipoint Morisita index. Pattern Recognition, 48, 4070-4081.

Visualizing statistical significance of disease clusters using cartograms.

PubMed

Kronenfeld, Barry J; Wong, David W S

2017-05-15

Health officials and epidemiological researchers often use maps of disease rates to identify potential disease clusters. Because these maps exaggerate the prominence of low-density districts and hide potential clusters in urban (high-density) areas, many researchers have used density-equalizing maps (cartograms) as a basis for epidemiological mapping. However, we do not have existing guidelines for visual assessment of statistical uncertainty. To address this shortcoming, we develop techniques for visual determination of statistical significance of clusters spanning one or more districts on a cartogram. We developed the techniques within a geovisual analytics framework that does not rely on automated significance testing, and can therefore facilitate visual analysis to detect clusters that automated techniques might miss. On a cartogram of the at-risk population, the statistical significance of a disease cluster is determinate from the rate, area and shape of the cluster under standard hypothesis testing scenarios. We develop formulae to determine, for a given rate, the area required for statistical significance of a priori and a posteriori designated regions under certain test assumptions. Uniquely, our approach enables dynamic inference of aggregate regions formed by combining individual districts. The method is implemented in interactive tools that provide choropleth mapping, automated legend construction and dynamic search tools to facilitate cluster detection and assessment of the validity of tested assumptions. A case study of leukemia incidence analysis in California demonstrates the ability to visually distinguish between statistically significant and insignificant regions. The proposed geovisual analytics approach enables intuitive visual assessment of statistical significance of arbitrarily defined regions on a cartogram. Our research prompts a broader discussion of the role of geovisual exploratory analyses in disease mapping and the appropriate framework for visually assessing the statistical significance of spatial clusters.

A Cluster Analytic Approach to Identifying Predictors and Moderators of Psychosocial Treatment for Bipolar Depression: Results from STEP-BD

PubMed Central

Deckersbach, Thilo; Peters, Amy T.; Sylvia, Louisa G.; Gold, Alexandra K.; da Silva Magalhaes, Pedro Vieira; Henry, David B.; Frank, Ellen; Otto, Michael W.; Berk, Michael; Dougherty, Darin D.; Nierenberg, Andrew A.; Miklowitz, David J.

2016-01-01

Background We sought to address how predictors and moderators of psychotherapy for bipolar depression – identified individually in prior analyses – can inform the development of a metric for prospectively classifying treatment outcome in intensive psychotherapy (IP) versus collaborative care (CC) adjunctive to pharmacotherapy in the Systematic Treatment Enhancement Program (STEP-BD) study. Methods We conducted post-hoc analyses on 135 STEP-BD participants using cluster analysis to identify subsets of participants with similar clinical profiles and investigated this combined metric as a moderator and predictor of response to IP. We used agglomerative hierarchical cluster analyses and k-means clustering to determine the content of the clinical profiles. Logistic regression and Cox proportional hazard models were used to evaluate whether the resulting clusters predicted or moderated likelihood of recovery or time until recovery. Results The cluster analysis yielded a two-cluster solution: 1) “less-recurrent/severe” and 2) “chronic/recurrent.” Rates of recovery in IP were similar for less-recurrent/severe and chronic/recurrent participants. Less-recurrent/severe patients were more likely than chronic/recurrent patients to achieve recovery in CC (p = .040, OR = 4.56). IP yielded a faster recovery for chronic/recurrent participants, whereas CC led to recovery sooner in the less-recurrent/severe cluster (p = .034, OR = 2.62). Limitations Cluster analyses require list-wise deletion of cases with missing data so we were unable to conduct analyses on all STEP-BD participants. Conclusions A well-powered, parametric approach can distinguish patients based on illness history and provide clinicians with symptom profiles of patients that confer differential prognosis in CC vs. IP. PMID:27289316

Spatial distribution and cluster analysis of risky sexual behaviours and STDs reported by Chinese adults in Guangzhou, China: a representative population-based study

PubMed Central

Chen, Wen; Zhou, Fangjing; Hall, Brian J; Wang, Yu; Latkin, Carl; Ling, Li; Tucker, Joseph D

2016-01-01

Objectives To assess associations between residences location, risky sexual behaviours and sexually transmitted diseases (STDs) among adults living in Guangzhou, China. Methods Data were obtained from 751 Chinese adults aged 18–59 years in Guangzhou, China, using stratified random sampling by using spatial epidemiological methods. Face-to-face household interviews were conducted to collect self-report data on risky sexual behaviours and diagnosed STDs. Kulldorff’s spatial scan statistic was implemented to identify and detect spatial distribution and clusters of risky sexual behaviours and STDs. The presence and location of statistically significant clusters were mapped in the study areas using ArcGIS software. Results The prevalence of self-reported risky sexual behaviours was between 5.1% and 50.0%. The self-reported lifetime prevalence of diagnosed STDs was 7.06%. Anal intercourse clustered in an area located along the border within the rural–urban continuum (p=0.001). High rate clusters for alcohol or other drugs using before sex (p=0.008) and migrants who lived in Guangzhou <1 year (p=0.007) overlapped this cluster. Excess cases for unprotected sex (p=0.031) overlapped the cluster for college students (p<0.001). Five of nine (55.6%) students who had sexual experience during the last 12 months located in the cluster of unprotected sex. Conclusions Short-term migrants and college students reported greater risky sexual behaviours. Programmes to increase safer sex within these communities to reduce the risk of STDs are warranted in Guangzhou. Spatial analysis identified geographical clusters of risky sexual behaviours, which is critical for optimising surveillance and targeting control measures for these locations in the future. PMID:26843400

Tuberculosis outbreaks predicted by characteristics of first patients in a DNA fingerprint cluster.

PubMed

Kik, Sandra V; Verver, Suzanne; van Soolingen, Dick; de Haas, Petra E W; Cobelens, Frank G; Kremer, Kristin; van Deutekom, Henk; Borgdorff, Martien W

2008-07-01

Some clusters of patients who have Mycobacterium tuberculosis isolates with identical DNA fingerprint patterns grow faster than others. It is unclear what predictors determine cluster growth. To assess whether the development of a tuberculosis (TB) outbreak can be predicted by the characteristics of its first two patients. Demographic and clinical data of all culture-confirmed patients with TB in the Netherlands from 1993 through 2004 were combined with DNA fingerprint data. Clusters were restricted to cluster episodes of 2 years to only detect newly arising clusters. Characteristics of the first two patients were compared between small (2-4 cases) and large (5 or more cases) cluster episodes. Of 5,454 clustered cases, 1,756 (32%) were part of a cluster episode of 2 years. Of 622 cluster episodes, 54 (9%) were large and 568 (91%) were small episodes. Independent predictors for large cluster episodes were as follows: less than 3 months' time between the diagnosis of the first two patients, one or both patients were young (<35 yr), both patients lived in an urban area, and both patients came from sub-Saharan Africa. In the Netherlands, patients in new cluster episodes should be screened for these risk factors. When the risk pattern applies, targeted interventions (e.g., intensified contact investigation) should be considered to prevent further cluster expansion.

Detecting communities in large networks

NASA Astrophysics Data System (ADS)

Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

2005-07-01

We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

VLA observations of radio sources in interacting galaxy pairs in poor clusters

NASA Technical Reports Server (NTRS)

Batuski, David J.; Hanisch, Robert J.; Burns, Jack O.

1992-01-01

Observations of 16 radio sources in interacting galaxies in 14 poor clusters were made using the Very Large Array in the B configuration at lambda of 6 and 2 cm. These sources had been unresolved in earlier observations at lambda of 21 cm, and were chosen as a sample to determine which of three models for radio source formation actually pertains in interacting galaxies. From the analysis of this sample, the starburst model appears most successful, but the 'central monster' model could pertain in some cases.

Effects of Image Compression on Automatic Count of Immunohistochemically Stained Nuclei in Digital Images

PubMed Central

López, Carlos; Lejeune, Marylène; Escrivà, Patricia; Bosch, Ramón; Salvadó, Maria Teresa; Pons, Lluis E.; Baucells, Jordi; Cugat, Xavier; Álvaro, Tomás; Jaén, Joaquín

2008-01-01

This study investigates the effects of digital image compression on automatic quantification of immunohistochemical nuclear markers. We examined 188 images with a previously validated computer-assisted analysis system. A first group was composed of 47 images captured in TIFF format, and other three contained the same images converted from TIFF to JPEG format with 3×, 23× and 46× compression. Counts of TIFF format images were compared with the other three groups. Overall, differences in the count of the images increased with the percentage of compression. Low-complexity images (≤100 cells/field, without clusters or with small-area clusters) had small differences (<5 cells/field in 95–100% of cases) and high-complexity images showed substantial differences (<35–50 cells/field in 95–100% of cases). Compression does not compromise the accuracy of immunohistochemical nuclear marker counts obtained by computer-assisted analysis systems for digital images with low complexity and could be an efficient method for storing these images. PMID:18755997

Igs expressed by chronic lymphocytic leukemia B cells show limited binding-site structure variability.

PubMed

Marcatili, Paolo; Ghiotto, Fabio; Tenca, Claudya; Chailyan, Anna; Mazzarello, Andrea N; Yan, Xiao-Jie; Colombo, Monica; Albesiano, Emilia; Bagnara, Davide; Cutrona, Giovanna; Morabito, Fortunato; Bruno, Silvia; Ferrarini, Manlio; Chiorazzi, Nicholas; Tramontano, Anna; Fais, Franco

2013-06-01

Ag selection has been suggested to play a role in chronic lymphocytic leukemia (CLL) pathogenesis, but no large-scale analysis has been performed so far on the structure of the Ag-binding sites (ABSs) of leukemic cell Igs. We sequenced both H and L chain V(D)J rearrangements from 366 CLL patients and modeled their three-dimensional structures. The resulting ABS structures were clustered into a small number of discrete sets, each containing ABSs with similar shapes and physicochemical properties. This structural classification correlates well with other known prognostic factors such as Ig mutation status and recurrent (stereotyped) receptors, but it shows a better prognostic value, at least in the case of one structural cluster for which clinical data were available. These findings suggest, for the first time, to our knowledge, on the basis of a structural analysis of the Ab-binding sites, that selection by a finite quota of antigenic structures operates on most CLL cases, whether mutated or unmutated.

Genotyping comparison of Mycobacterium leprae isolates by VNTR analysis from nasal samples in a Brazilian endemic region.

PubMed

Lima, Luana Nepomueceno Costa; Frota, Cristiane Cunha; Suffys, Phillip Noel; Fontes, Amanda Nogueira Brum; Mota, Rosa Maria Salani; Almeida, Rosa Livia Freitas; Andrade Pontes, Maria Araci de; Gonçalves, Heitor de Sá; Kendall, Carl; Kerr, Ligia Regina Sansigolo

2018-02-06

This study analyzed the genetic diversity by MIRU-VNTR of Mycobacterium leprae isolates from nasal cavities and related to epidemiological and clinical data. The sample consisted of 48 newly diagnosed leprosy cases that tested positive for M. leprae PCR in nasal secretion (NS) attending to the National Reference Center of Dermatology Dona Libania (CDERM), Fortaleza, Brazil. Total DNA was extracted from NS of each patient and used for amplification of four M. leprae VNTR loci. Four clusters of M. leprae isolates were formed with identical genotypes. In the spatial analysis, 12 leprosy cases presented similar genotypes organized into 4 clusters. The most common genotypes in the current study was AC8b: 8, AC9: 7, AC8a: 8, GTA9: 10, which may represent a genotype of circulating strains most often in Ceará. A minimum set of four MIRU-VNTR loci was demonstrated to study the genetic diversity of M. leprae isolates from NS.

The application of data mining techniques to oral cancer prognosis.

PubMed

Tseng, Wan-Ting; Chiang, Wei-Fan; Liu, Shyun-Yeu; Roan, Jinsheng; Lin, Chun-Nan

2015-05-01

This study adopted an integrated procedure that combines the clustering and classification features of data mining technology to determine the differences between the symptoms shown in past cases where patients died from or survived oral cancer. Two data mining tools, namely decision tree and artificial neural network, were used to analyze the historical cases of oral cancer, and their performance was compared with that of logistic regression, the popular statistical analysis tool. Both decision tree and artificial neural network models showed superiority to the traditional statistical model. However, as to clinician, the trees created by the decision tree models are relatively easier to interpret compared to that of the artificial neural network models. Cluster analysis also discovers that those stage 4 patients whose also possess the following four characteristics are having an extremely low survival rate: pN is N2b, level of RLNM is level I-III, AJCC-T is T4, and cells mutate situation (G) is moderate.

The use of whole-genome sequencing in cluster investigation of a multidrug-resistant tuberculosis outbreak.

PubMed

Lalor, Maeve K; Casali, Nicola; Walker, Timothy M; Anderson, Laura F; Davidson, Jennifer A; Ratna, Natasha; Mullarkey, Cathy; Gent, Mike; Foster, Kirsty; Brown, Tim; Magee, John; Barrett, Anne; Crook, Derrick W; Drobniewski, Francis; Thomas, H Lucy; Abubakar, Ibrahim

2018-06-01

We used whole-genome sequencing (WGS) to delineate transmission networks and investigate the benefits of WGS during cluster investigation.We included clustered cases of multidrug-resistant (MDR) tuberculosis (TB)/extensively drug-resistant (XDR) TB linked by mycobacterial interspersed repetitive unit variable tandem repeat (MIRU-VNTR) strain typing or epidemiological information in the national cluster B1006, notified between 2007 and 2013 in the UK. We excluded from further investigation cases whose isolates differed by greater than 12 single nucleotide polymorphisms (SNPs). Data relating to patients' social networks were collected.27 cases were investigated and 22 had WGS, eight of which (36%) were excluded as their isolates differed by more than 12 SNPs to other cases. 18 cases were ruled into the transmission network based on genomic and epidemiological information. Evidence of transmission was inconclusive in seven out of 18 cases (39%) in the transmission network following WGS and epidemiological investigation.This investigation of a drug-resistant TB cluster illustrates the opportunities and limitations of WGS in understanding transmission in a setting with a high proportion of migrant cases. The use of WGS should be combined with classical epidemiological methods. However, not every cluster will be solvable, regardless of the quality of genomic data. Copyright ©ERS 2018.

A Mixed-Method Analysis of Reports on 100 Cases of Improper Prescribing of Controlled Substances

PubMed Central

DuBois, James M.; Chibnall, John T.; Anderson, Emily E.; Eggers, Michelle; Baldwin, Kari; Vasher, Meghan

2017-01-01

Improper prescribing of controlled substances contributes to opioid addictions and deaths by overdose. Studies conducted to-date have largely lacked a theoretical framework and ignored the interaction of individual with environmental factors. We conducted a mixed-method analysis of published reports on 100 cases that occurred in the United States. An average of 17 reports (e.g., from medical boards) per case were coded for 38 dichotomous variables describing the physician, setting, patients, and investigation. A theory on how the case occurred was developed for each case. Explanatory typologies were developed and then validated through hierarchical cluster analysis. Most cases involved physicians who were male (88%), >40 years old (90%), non-board certified (63%), and in small private practices (97%); 54% of cases reported facts about the physician indicative of self-centered personality traits. Three explanatory typologies were validated. Increasing oversight provided by peers and trainees may help prevent improper prescribing of controlled substances. PMID:28663601

A unique measles B3 cluster in the United Kingdom and the Netherlands linked to air travel and transit at a large international airport, February to April 2014.

PubMed

Nic Lochlainn, Laura; Mandal, Sema; de Sousa, Rita; Paranthaman, Karthik; van Binnendijk, Rob; Ramsay, Mary; Hahné, Susan; Brown, Kevin E

2016-01-01

This report describes a joint measles outbreak investigation between public health officials in the United Kingdom (UK) and the Netherlands following detection of a measles cluster with a unique measles virus strain. From 1 February to 30 April 2014, 33 measles cases with a unique measles virus strain of genotype B3 were detected in the UK and the Netherlands, of which nine secondary cases were epidemiologically linked to an infectious measles case travelling from the Philippines. Through a combination of epidemiological investigation and sequence analysis, we found that measles transmission occurred in flight, airport and household settings. The secondary measles cases included airport workers, passengers in transit at the same airport or travelling on the same flight as the infectious case and also household contacts. This investigation highlighted the particular importance of measles genotyping in identifying transmission networks and the need to improve vaccination, public health follow-up and management of travellers and airport staff exposed to measles.

Evaporation rate of nucleating clusters.

PubMed

Zapadinsky, Evgeni

2011-11-21

The Becker-Döring kinetic scheme is the most frequently used approach to vapor liquid nucleation. In the present study it has been extended so that master equations for all cluster configurations are included into consideration. In the Becker-Döring kinetic scheme the nucleation rate is calculated through comparison of the balanced steady state and unbalanced steady state solutions of the set of kinetic equations. It is usually assumed that the balanced steady state produces equilibrium cluster distribution, and the evaporation rates are identical in the balanced and unbalanced steady state cases. In the present study we have shown that the evaporation rates are not identical in the equilibrium and unbalanced steady state cases. The evaporation rate depends on the number of clusters at the limit of the cluster definition. We have shown that the ratio of the number of n-clusters at the limit of the cluster definition to the total number of n-clusters is different in equilibrium and unbalanced steady state cases. This causes difference in evaporation rates for these cases and results in a correction factor to the nucleation rate. According to rough estimation it is 10(-1) by the order of magnitude and can be lower if carrier gas effectively equilibrates the clusters. The developed approach allows one to refine the correction factor with Monte Carlo and molecular dynamic simulations.

The differentiation of camel breeds based on meat measurements using discriminant analysis.

PubMed

Al-Atiyat, Raed Mahmoud; Suliman, Gamal; AlSuhaibani, Entissar; El-Waziry, Ahmad; Al-Owaimer, Abdullah; Basmaeil, Saeid

2016-06-01

The meat productivity of camel in the tropics is still under investigation for identification of better meat breed or type. Therefore, four one-humped Saudi Arabian (SA) camel breeds, Majaheem, Maghateer, Hamrah, and Safrah were experimented in order to differentiate them from each other based on meat measurements. The measurements were biometrical meat traits measured on six intact males from each breed. The results showed higher values of the Majaheem breed than that obtained for the other breeds except few cases such dressing percentage and rib-eye area. In differentiation analysis, the most discriminating meat variables were myofibrillar protein index, meat color components (L* and a*, b*), and cooking loss. Consequently, the Safrah and the Majaheem breeds presented the largest dissimilarity as evidenced by their multivariate means. The canonical discriminant analysis allowed an additional understanding of the differentiation between breeds. Furthermore, two large clusters, one formed by Hamrah and Maghateer in one group along with Safrah. These classifications may assign each breed into one cluster considering they are better as meat producers. The Majaheem was clustered alone in another cluster that might be a result of being better as milk producers. Nevertheless, the productivity type of the camel breeds of SA needs further morphology and genetic descriptions.

Whole Genome Sequencing Demonstrates Limited Transmission within Identified Mycobacterium tuberculosis Clusters in New South Wales, Australia

PubMed Central

Gurjav, Ulziijargal; Outhred, Alexander C.; Jelfs, Peter; McCallum, Nadine; Wang, Qinning; Hill-Cawthorne, Grant A.; Marais, Ben J.; Sintchenko, Vitali

2016-01-01

Australia has a low tuberculosis incidence rate with most cases occurring among recent immigrants. Given suboptimal cluster resolution achieved with 24-locus mycobacterium interspersed repetitive unit (MIRU-24) genotyping, the added value of whole genome sequencing was explored. MIRU-24 profiles of all Mycobacterium tuberculosis culture-confirmed tuberculosis cases diagnosed between 2009 and 2013 in New South Wales (NSW), Australia, were examined and clusters identified. The relatedness of cases within the largest MIRU-24 clusters was assessed using whole genome sequencing and phylogenetic analyses. Of 1841 culture-confirmed TB cases, 91.9% (1692/1841) had complete demographic and genotyping data. East-African Indian (474; 28.0%) and Beijing (470; 27.8%) lineage strains predominated. The overall rate of MIRU-24 clustering was 20.1% (340/1692) and was highest among Beijing lineage strains (35.7%; 168/470). One Beijing and three East-African Indian (EAI) clonal complexes were responsible for the majority of observed clusters. Whole genome sequencing of the 4 largest clusters (30 isolates) demonstrated diverse single nucleotide polymorphisms (SNPs) within identified clusters. All sequenced EAI strains and 70% of Beijing lineage strains clustered by MIRU-24 typing demonstrated distinct SNP profiles. The superior resolution provided by whole genome sequencing demonstrated limited M. tuberculosis transmission within NSW, even within identified MIRU-24 clusters. Routine whole genome sequencing could provide valuable public health guidance in low burden settings. PMID:27737005

Search for gamma-ray lines towards galaxy clusters with the Fermi-LAT

DOE PAGES

Anderson, B.; Zimmer, S.; Conrad, J.; ...

2016-02-09

We report on a search for monochromatic γ-ray features in the spectra of galaxy clusters observed by the Fermi Large Area Telescope. Galaxy clusters are the largest structures in the Universe that are bound by dark matter (DM), making them an important testing ground for possible selfinteractions or decays of the DM particles. Monochromatic γ-ray lines provide a unique signature due to the absence of astrophysical backgrounds and are as such considered a smoking-gun signature for new physics. An unbinned joint likelihood analysis of the sixteen most promising clusters using five years of data at energies between 10 and 400more » GeV revealed no significant features. For the case of self-annihilation, we set upper limits on the monochromatic velocity-averaged interaction cross section. These limits are compatible with those obtained from observations of the Galactic Center, albeit weaker due to the larger distance to the studied clusters.« less

Spatial Clustering of Occupational Injuries in Communities

PubMed Central

Friedman, Lee; Chin, Brian; Madigan, Dana

2015-01-01

Objectives. Using the social-ecological model, we hypothesized that the home residences of injured workers would be clustered predictably and geographically. Methods. We linked health care and publicly available datasets by home zip code for traumatically injured workers in Illinois from 2000 to 2009. We calculated numbers and rates of injuries, determined the spatial relationships, and developed 3 models. Results. Among the 23 200 occupational injuries, 80% of cases were located in 20% of zip codes and clustered in 10 locations. After component analysis, numbers and clusters of injuries correlated directly with immigrants; injury rates inversely correlated with urban poverty. Conclusions. Traumatic occupational injuries were clustered spatially by home location of the affected workers and in a predictable way. This put an inequitable burden on communities and provided evidence for the possible value of community-based interventions for prevention of occupational injuries. Work should be included in health disparities research. Stakeholders should determine whether and how to intervene at the community level to prevent occupational injuries. PMID:25905838

Suicide by cop: clinical risks and subtypes.

PubMed

Dewey, Lauren; Allwood, Maureen; Fava, Joanna; Arias, Elizabeth; Pinizzotto, Anthony; Schlesinger, Louis

2013-01-01

This study examines whether clinical classification schemes from general suicide research are applicable for cases of suicide by cop (SbC) and whether there are indicators as to why the police might be engaged in the suicide. Using archival law enforcement data, 13 clinical risks were examined among 68 cases of SbC using exploratory factor analysis and k-means cluster analysis. Three subtypes of SbC cases emerged: Mental Illness, Criminality, and Not Otherwise Specified. The subtypes varied significantly on their levels of mental illness, substance use, and criminal activity. Findings suggest that reducing fragmentation between law enforcement and mental health service providers might be a crucial goal for suicide intervention and prevention, at least among cases of SbC.

Analysis of perceived similarity between pairs of microcalcification clusters in mammograms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Juan; Jing, Hao; Wernick, Miles N.

2014-05-15

Purpose: Content-based image retrieval aims to assist radiologists by presenting example images with known pathology that are visually similar to the case being evaluated. In this work, the authors investigate several fundamental issues underlying the similarity ratings between pairs of microcalcification (MC) lesions on mammograms as judged by radiologists: the degree of variability in the similarity ratings, the impact of this variability on agreement between readers in retrieval of similar lesions, and the factors contributing to the readers’ similarity ratings. Methods: The authors conduct a reader study on a set of 1000 image pairs of MC lesions, in which amore » group of experienced breast radiologists rated the degree of similarity between each image pair. The image pairs are selected, from among possible pairings of 222 cases (110 malignant, 112 benign), based on quantitative image attributes (features) and the results of a preliminary reader study. Next, the authors apply analysis of variance (ANOVA) to quantify the level of variability in the readers’ similarity ratings, and study how the variability in individual reader ratings affects consistency between readers. The authors also measure the extent to which readers agree on images which are most similar to a given query, for which the Dice coefficient is used. To investigate how the similarity ratings potentially relate to the attributes underlying the cases, the authors study the fraction of perceptually similar images that also share the same benign or malignant pathology as the query image; moreover, the authors apply multidimensional scaling (MDS) to embed the cases according to their mutual perceptual similarity in a two-dimensional plot, which allows the authors to examine the manner in which similar lesions relate to one another in terms of benign or malignant pathology and clustered MCs. Results: The ANOVA results show that the coefficient of determination in the reader similarity ratings is 0.59. The variability level in the similarity ratings is proved to be a limiting factor, leading to only moderate correlation between the readers in their readings. The Dice coefficient, measuring agreement between readers in retrieval of similar images, can vary from 0.45 to 0.64 with different levels of similarity for individual readers, but is higher for average ratings from a group of readers (from 0.59 to 0.78). More importantly, the fraction of retrieved cases that match the benign or malignant pathology of the query image was found to increase with the degree of similarity among the retrieved images, reaching average value as high as 0.69 for the radiologists (p-value <10{sup −4} compared to random guessing). Moreover, MDS embedding of all the cases shows that cases having the same pathology tend to cluster together, and that neighboring cases in the plot tend to be similar in their clustered MCs. Conclusions: While individual readers exhibit substantial variability in their similarity ratings, similarity ratings averaged from a group of readers can achieve a high level of intergroup consistency and agreement in retrieval of similar images. More importantly, perceptually similar cases are also likely to be similar in their underlying benign or malignant pathology and image features of clustered MCs, which could be of diagnostic value in computer-aided diagnosis for lesions with clustered MCs.« less

Hydrogen bonding in water clusters and their ionized counterparts.

PubMed

Neela, Y Indra; Mahadevi, A Subha; Sastry, G Narahari

2010-12-30

Ab initio and DFT computations were carried out on four distinct hydrogen-bonded arrangements of water clusters (H(2)O)(n), n = 2-20, represented as W1D, W2D, W2DH, and W3D. The variation in the strength of hydrogen bond as a function of the chain length is studied. In all the four cases, there is a substantial cooperative interaction, albeit in different degrees. The effect of basis set superposition error (BSSE) on the complexation energy of water clusters has been analyzed. Atoms in molecules (AIM) analysis performed to evaluate the nature of the hydrogen bonding shows a high correlation between hydrogen bond strength and the trends in complexation energy. Solvated water clusters exhibit lower complexation energies compared to corresponding gas-phase geometries on PCM (polarized continuum model) optimization. The feasibility of stripping an electron or addition of an electron increases dramatically as the cluster size increases. Although W3D caged structures are stable for neutral clusters, the helical W2DH arrangement appeared to be an optimal choice for its ionized counterparts.

Cluster Randomized Test-Negative Design (CR-TND) Trials: A Novel and Efficient Method to Assess the Efficacy of Community Level Dengue Interventions.

PubMed

Anders, Katherine L; Cutcher, Zoe; Kleinschmidt, Immo; Donnelly, Christl A; Ferguson, Neil M; Indriani, Citra; O'Neill, Scott L; Jewell, Nicholas P; Simmons, Cameron P

2018-05-07

Cluster randomized trials are the gold standard for assessing efficacy of community-level interventions, such as vector control strategies against dengue. We describe a novel cluster randomized trial methodology with a test-negative design, which offers advantages over traditional approaches. It utilizes outcome-based sampling of patients presenting with a syndrome consistent with the disease of interest, who are subsequently classified as test-positive cases or test-negative controls on the basis of diagnostic testing. We use simulations of a cluster trial to demonstrate validity of efficacy estimates under the test-negative approach. This demonstrates that, provided study arms are balanced for both test-negative and test-positive illness at baseline and that other test-negative design assumptions are met, the efficacy estimates closely match true efficacy. We also briefly discuss analytical considerations for an odds ratio-based effect estimate arising from clustered data, and outline potential approaches to analysis. We conclude that application of the test-negative design to certain cluster randomized trials could increase their efficiency and ease of implementation.

Electrostatic effects on clustering and ion dynamics in ionomer melts

NASA Astrophysics Data System (ADS)

Ma, Boran; Nguyen, Trung; Pryamitsyn, Victor; Olvera de La Cruz, Monica

An understanding of the relationships between ionomer chain morphology, dynamics and counter-ion mobility is a key factor in the design of ion conducting membranes for battery applications. In this study, we investigate the influence of electrostatic coupling between randomly charged copolymers (ionomers) and counter ions on the structural and dynamic features of a model system of ionomer melts. Using coarse-grained molecular dynamics (CGMD) simulations, we found that variations in electrostatic coupling strength (Γ) remarkably affect the formation of ion-counter ion clusters, ion mobility, and polymer dynamics for a range of charged monomer fractions. Specifically, an increase in Γ leads to larger ionic cluster sizes and reduced polymer and ion mobility. Analysis of the distribution of the radius of gyration of the clusters further reveals that the fractal dimension of the ion clusters is nearly independent from Γ for all the cases studied. Finally, at sufficiently high values of Γ, we observed arrested heterogeneous ions mobility, which is correlated with an increase in ion cluster size. These findings provide insight into the role of electrostatics in governing the nanostructures formed by ionomers.

First principles study of vibrational dynamics of ceria-titania hybrid clusters

NASA Astrophysics Data System (ADS)

Majid, Abdul; Bibi, Maryam

2017-04-01

Density functional theory based calculations were performed to study vibrational properties of ceria, titania, and ceria-titania hybrid clusters. The findings revealed the dominance of vibrations related to oxygen when compared to those of metallic atoms in the clusters. In case of hybrid cluster, the softening of normal modes related to exterior oxygen atoms in ceria and softening/hardening of high/low frequency modes related to titania dimmers are observed. The results calculated for monomers conform to symmetry predictions according to which three IR and three Raman active modes were detected for TiO2, whereas two IR active and one Raman active modes were observed for CeO2. The comparative analysis indicates that the hybrid cluster CeTiO4 contains simultaneous vibrational fingerprints of the component dimmers. The symmetry, nature of vibrations, IR and Raman activity, intensities, and atomic involvement in different modes of the clusters are described in detail. The study points to engineering of CeTiO4 to tailor its properties for technological visible region applications in photocatalytic and electrochemical devices.

Extraction of heavy metals characteristics of the 2011 Tohoku tsunami deposits using multiple classification analysis.

PubMed

Nakamura, Kengo; Kuwatani, Tatsu; Kawabe, Yoshishige; Komai, Takeshi

2016-02-01

Tsunami deposits accumulated on the Tohoku coastal area in Japan due to the impact of the Tohoku-oki earthquake. In the study reported in this paper, we applied principal component analysis (PCA) and cluster analysis (CA) to determine the concentrations of heavy metals in tsunami deposits that had been diluted with water or digested using 1 M HCl. The results suggest that the environmental risk is relatively low, evidenced by the following geometric mean concentrations: Pb, 16 mg kg(-1) and 0.003 ml L(-1); As, 1.8 mg kg(-1) and 0.004 ml L(-1); and Cd, 0.17 mg kg(-1) and 0.0001 ml L(-1). CA was performed after outliers were excluded using PCA. The analysis grouped the concentrations of heavy metals for leaching in water and acid. For the acid case, the first cluster contained Ni, Fe, Cd, Cu, Al, Cr, Zn, and Mn; while the second contained Pb, Sb, As, and Mo. For water, the first cluster contained Ni, Fe, Al, and Cr; and the second cluster contained Mo, Sb, As, Cu, Zn, Pb, and Mn. Statistical analysis revealed that the typical toxic elements, As, Pb, and Cd have steady correlations for acid leaching but are relatively sparse for water leaching. Pb and As from the tsunami deposits seemed to reveal a kind of redox elution mechanism using 1 M HCl. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Accounting for measurement error in biomarker data and misclassification of subtypes in the analysis of tumor data.

PubMed

Nevo, Daniel; Zucker, David M; Tamimi, Rulla M; Wang, Molin

2016-12-30

A common paradigm in dealing with heterogeneity across tumors in cancer analysis is to cluster the tumors into subtypes using marker data on the tumor, and then to analyze each of the clusters separately. A more specific target is to investigate the association between risk factors and specific subtypes and to use the results for personalized preventive treatment. This task is usually carried out in two steps-clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The first is the measurement error in the biomarker values. The second is the misclassification error when assigning observations to clusters. We consider the case with a specified set of relevant markers and propose a unified single-likelihood approach for normally distributed biomarkers. As an alternative, we consider a two-step procedure with the tumor type misclassification error taken into account in the second-step risk factor analysis. We describe our method for binary data and also for survival analysis data using a modified version of the Cox model. We present asymptotic theory for the proposed estimators. Simulation results indicate that our methods significantly lower the bias with a small price being paid in terms of variance. We present an analysis of breast cancer data from the Nurses' Health Study to demonstrate the utility of our method. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Classification of cassava genotypes based on qualitative and quantitative data.

PubMed

Oliveira, E J; Oliveira Filho, O S; Santos, V S

2015-02-02

We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

Competing Effects Between Screen Media Time and Physical Activity in Adolescent Girls: Clustering a Self-Organizing Maps Analysis.

PubMed

Valencia-Peris, Alexandra; Devís-Devís, José; García-Massó, Xavier; Lizandra, Jorge; Pérez-Gimeno, Esther; Peiró-Velert, Carmen

2016-06-01

Previous research shows contradictory findings on potential competing effects between sedentary screen media usage (SMU) and physical activity (PA). This study examined these effects on adolescent girls via self-organizing maps analysis focusing on 3 target profiles. A sample of 1,516 girls aged 12 to 18 years self-reported daily time engagement in PA (moderate and vigorous intensity) and in screen media activities (TV/video/DVD, computer, and videogames), separately and combined. Topological interrelationships from the 13 emerging maps indicated a moderate competing effect between physically active and sedentary SMU patterns. Higher SES and overweight status were linked to either active or inactive behaviors. Three target clusters were explored in more detail. Cluster 1, named temperate-media actives, showed capabilities of being active while engaging in a moderate level of SMU (TV/video/DVD mainly). In Cluster 2, named prudent-media inactives, and Cluster 3, compulsive-media inactives, a competing effect between SMU and PA emerged, being sedentary SMU behaviors responsible for a low involvement in active pursuits. SMU and PA emerge as both related and independent behaviors in girls, resulting in a moderate competing effect. Findings support the case for recommending the timing of PA and SMU for recreational purposes considering different profiles, sociodemographic factors and types of SMU.

Investigating a tuberculosis cluster among Filipino health care workers in a low-incidence country.

PubMed

Davidson, J A; Fulton, N; Thomas, H L; Lalor, M K; Zenner, D; Brown, T; Murphy, S; Anderson, L F

2018-03-01

Nearly 8% of adult tuberculosis (TB) cases in England, Wales and Northern Ireland (EW&NI) occur among health care workers (HCWs), the majority of whom are from high TB incidence countries. To determine if a TB cluster containing multiple HCWs was due to nosocomial transmission. A cluster of TB cases notified in EW&NI from 2009 to 2014, with indistinguishable 24-locus mycobacterial interspersed repetitive unit-variable number of tandem repeats (MIRU-VNTR) profiles, was identified through routine national cluster review. Cases were investigated to identify epidemiological links, and occupational health (OH) information was collected for HCW cases. To further discriminate strains, typing of eight additional loci was conducted. Of the 53 cases identified, 22 were HCWs. The majority (n = 43), including 21 HCWs, were born in the Philippines. Additional typing split the cluster into three subclusters and seven unique strains. No epidemiological links were identified beyond one household and a common residential area. HCWs in this cluster received no or inadequate OH assessment. The MIRU-VNTR profile of this cluster probably reflects common endemic strains circulating in the Philippines, with reactivation occurring in the UK. Furthermore, 32-locus typing showed that 24-locus MIRU-VNTR failed to distinguish strain diversity. The lack of OH assessment indicates that latent tuberculous infection could have been identified and treated, thereby preventing active cases from occurring.

Effects of single atom doping on the ultrafast electron dynamics of M1Au24(SR)18 (M = Pd, Pt) nanoclusters

NASA Astrophysics Data System (ADS)

Zhou, Meng; Qian, Huifeng; Sfeir, Matthew Y.; Nobusada, Katsuyuki; Jin, Rongchao

2016-03-01

Atomically precise, doped metal clusters are receiving wide research interest due to their synergistic properties dependent on the metal composition. To understand the electronic properties of doped clusters, it is highly desirable to probe the excited state behavior. Here, we report the ultrafast relaxation dynamics of doped M1@Au24(SR)18 (M = Pd, Pt; R = CH2CH2Ph) clusters using femtosecond visible and near infrared transient absorption spectroscopy. Three relaxation components are identified for both mono-doped clusters: (1) sub-picosecond relaxation within the M1Au12 core states; (2) core to shell relaxation in a few picoseconds; and (3) relaxation back to the ground state in more than one nanosecond. Despite similar relaxation pathways for the two doped nanoclusters, the coupling between the metal core and surface ligands is accelerated by over 30% in the case of the Pt dopant compared with the Pd dopant. Compared to Pd doping, the case of Pt doping leads to much more drastic changes in the steady state and transient absorption of the clusters, which indicates that the 5d orbitals of the Pt atom are more strongly mixed with Au 5d and 6s orbitals than the 4d orbitals of the Pd dopant. These results demonstrate that a single foreign atom can lead to entirely different excited state spectral features of the whole cluster compared to the parent Au25(SR)18 cluster. The detailed excited state dynamics of atomically precise Pd/Pt doped gold clusters help further understand their properties and benefit the development of energy-related applications.Atomically precise, doped metal clusters are receiving wide research interest due to their synergistic properties dependent on the metal composition. To understand the electronic properties of doped clusters, it is highly desirable to probe the excited state behavior. Here, we report the ultrafast relaxation dynamics of doped M1@Au24(SR)18 (M = Pd, Pt; R = CH2CH2Ph) clusters using femtosecond visible and near infrared transient absorption spectroscopy. Three relaxation components are identified for both mono-doped clusters: (1) sub-picosecond relaxation within the M1Au12 core states; (2) core to shell relaxation in a few picoseconds; and (3) relaxation back to the ground state in more than one nanosecond. Despite similar relaxation pathways for the two doped nanoclusters, the coupling between the metal core and surface ligands is accelerated by over 30% in the case of the Pt dopant compared with the Pd dopant. Compared to Pd doping, the case of Pt doping leads to much more drastic changes in the steady state and transient absorption of the clusters, which indicates that the 5d orbitals of the Pt atom are more strongly mixed with Au 5d and 6s orbitals than the 4d orbitals of the Pd dopant. These results demonstrate that a single foreign atom can lead to entirely different excited state spectral features of the whole cluster compared to the parent Au25(SR)18 cluster. The detailed excited state dynamics of atomically precise Pd/Pt doped gold clusters help further understand their properties and benefit the development of energy-related applications. Electronic supplementary information (ESI) available: The pump dependent transient absorption spectra and the corresponding global analysis results. See DOI: 10.1039/c6nr01008c

Rural cases of equine West Nile virus encephalomyelitis and the normalized difference vegetation index

USGS Publications Warehouse

Ward, M.P.; Ramsay, B.H.; Gallo, K.

2005-01-01

Data from an outbreak (August to October, 2002) of West Nile virus (WNV) encephalomyelitis in a population of horses located in northern Indiana was scanned for clusters in time and space. One significant (p = 0.04) cluster of case premises was detected, occurring between September 4 and 10 in the south-west part of the study area (85.70??N, 45.50??W). It included 10 case premises (3.67 case premises expected) within a radius of 2264 m. Image data were acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard a National Oceanic and Atmospheric Administration polar-orbiting satellite. The Normalized Difference Vegetation Index (NDVI) was calculated from visible and near-infrared data of daily observations, which were composited to produce a weekly-1km2 resolution raster image product. During the epidemic, a significant (p<0.01) decrease (0.025 per week) in estimated NDVI was observed at all case and control premise sites. The median estimated NDVI (0.659) for case premises within the cluster identified was significantly (p<0.01) greater than the median estimated NDVI for other case (0.571) and control (0.596) premises during the same period. The difference in median estimated NDVI for case premises within this cluster, compared to cases not included in this cluster, was greatest (5.3% and 5.1%, respectively) at 1 and 5 weeks preceding occurrence of the cluster. The NDVI may be useful for identifying foci of WNV transmission. ?? Mary Ann Liebert, Inc.

Global aphasia without hemiparesis: language profiles and lesion distribution

PubMed Central

Hanlon, R.; Lux, W.; Dromerick, A.

1999-01-01

OBJECTIVES—Global aphasia without hemiparesis (GAWH) is an uncommon stroke syndrome involving receptive and expressive language impairment, without the hemiparesis typically manifested by patients with global aphasia after large left perisylvian lesions. A few cases of GAWH have been reported with conflicting conclusions regarding pathogenesis, lesion localisation, and recovery. The current study was conducted to attempt to clarify these issues.
METHODS—Ten cases of GAWH were prospectively studied with language profiles and lesion analysis; five patients had multiple lesions, four patients had a single lesion, and one had a subarachnoid haemorrhage. Eight patients met criteria for cardioembolic ischaemic stroke.
RESULTS—Cluster analysis based on acute language profiles disclosed three subtypes of patients with GAWH; these clusters persisted on follow up language assessment. Each cluster evolved into a different aphasia subtype: persistent GAWH, Wernicke's aphasia, or transcortical motor aphasia (TCM). Composite lesion analysis showed that persistent GAWH was related to lesioning of the left superior temporal gyrus. Patients with acute GAWH who evolved into TCM type aphasia had common lesioning of the left inferior frontal gyrus and adjacent subcortical white matter. Patients with acute GAWH who evolved into Wernicke's type aphasia were characterised by lesioning of the left precentral and postcentral gyri. Recovery of language was poor in all but one patient.
CONCLUSIONS—Although patients with acute GAWH are similar on neurological examination, they are heterogeneous with respect to early aphasia profile, language recovery, and lesion profile.

 PMID:10084536

Search for Gamma-Ray Emission from the Coma Cluster with Six Years of Fermi-LAT Data

NASA Technical Reports Server (NTRS)

Ackermann, M.; Ajello, M.; Albert, A.; Atwood, W. B.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Bechtol, K.; Bellazzini, R.;

Search for gamma-ray emission from the Coma Cluster with six years of Fermi-LAT data

DOE PAGES

Ackermann, M.

2016-03-08

We present results from γ-ray observations of the Coma cluster incorporating 6 years of Fermi-LAT data and the newly released “Pass 8” event-level analysis. Our analysis of the region reveals low-significance residual structures within the virial radius of the cluster that are too faint for a detailed investigation with the current data. Using a likelihood approach that is free of assumptions on the spectral shape we derive upper limits on the γ-ray flux that is expected from energetic particle interactions in the cluster. We also consider a benchmark spatial and spectral template motivated by models in which the observed radiomore » halo is mostly emission by secondary electrons. In this case, the median expected and observed upper limits for the flux above 100MeV are 1.7 x 10 -9 ph cm -2 s -1 and 5.2 x 10 -9 ph cm -2 s -1 respectively (the latter corresponds to residual emission at the level of 1:8σ). These bounds are comparable to or higher than predicted levels of hadronic gamma-ray emission in cosmic-ray models with or without reacceleration of secondary electrons, although direct comparisons are sensitive to assumptions regarding the origin and propagation mode of cosmic rays and magnetic field properties. The minimal expected γ-ray flux from radio and star-forming galaxies within the Coma cluster is roughly an order of magnitude below the median sensitivity of our analysis.« less

Geographical variation in anophthalmia and microphthalmia in England, 1988-94

PubMed Central

Dolk, H; Busby, A; Armstrong, B G; Walls, P H

1998-01-01

Objective: To investigate the geographical variation and clustering of congenital anophthalmia and microphthalmia in England, in response to media reports of clusters. Design: Comparison of pattern of residence at birth of cases of anophthalmia and microphthalmia in England in 1988-94, notified to a special register, with pattern of residence of all births. Three groups studied included all cases, all severe cases, and all severe cases of unknown aetiology. Outcome measures: Prevalence rates of anophthalmia and microphthalmia by region and district, and by ward population density and socioeconomic deprivation index of enumeration district grouped into fifths. Clustering expressed as the tendency for the three nearest neighbours of a case to be more likely to be cases than expected by chance, or for there to be more cases within circles of fixed radius of a case than expected by chance. Results: The overall prevalence of anophthalmia and microphthalmia was 1.0 per 10 000 births. Regional and district variation in prevalence did not reach statistical significance. Prevalence was higher in rural than urban areas: the relative risk in the group of wards of lowest population density compared with the most densely populated group was 1.79 (95% confidence interval 1.15 to 2.81) for all cases and 2.37 (1.38 to 4.08) for severe cases. There was no evidence of a trend in risk with socioeconomic deprivation. There was very little evidence of localised clustering. Conclusions: There is very little evidence to support the presence of strongly localised environmental exposures causing clusters of children to be born with anophthalmia or microphthalmia. The excess risk in rural areas requires further investigation. Key messagesClusters of anophthalmia and microphthalmia in England have been alleged in the media, with hypothesised links to environmental exposure such as pesticidesTo answer concerns about clustering a register has been established of all cases of anophthalmia and microphthalmia born in England in 1988-94There is no large regional or district variation in prevalence Rural areas have a roughly twofold excess in prevalence, which requires further confirmation and investigationThere is very little evidence for localised clustering in England in 1988-94 PMID:9756803

Untangling Topic Threads in Chat-Based Communication: A Case Study

DTIC Science & Technology

2011-08-01

learning techniques such as clustering are very popular for analyzing text for topic identification (Anjewierden,, Kollöffel and Hulshof 2007; Adams...Anjewierden, A., Kollöffel, B., and Hulshof , C. (2007). Towards educational data mining: Using data mining methods for automated chat analysis to

Mortality and Case Fatality Due to Visceral Leishmaniasis in Brazil: A Nationwide Analysis of Epidemiology, Trends and Spatial Patterns

PubMed Central

Martins-Melo, Francisco Rogerlândio; Lima, Mauricélia da Silveira; Ramos, Alberto Novaes; Alencar, Carlos Henrique; Heukelbach, Jorg

2014-01-01

Background Visceral leishmaniasis (VL) is a significant public health problem in Brazil and several regions of the world. This study investigated the magnitude, temporal trends and spatial distribution of mortality related to VL in Brazil. Methods We performed a study based on secondary data obtained from the Brazilian Mortality Information System. We included all deaths in Brazil from 2000 to 2011, in which VL was recorded as cause of death. We present epidemiological characteristics, trend analysis of mortality and case fatality rates by joinpoint regression models, and spatial analysis using municipalities as geographical units of analysis. Results In the study period, 12,491,280 deaths were recorded in Brazil. VL was mentioned in 3,322 (0.03%) deaths. Average annual age-adjusted mortality rate was 0.15 deaths per 100,000 inhabitants and case fatality rate 8.1%. Highest mortality rates were observed in males (0.19 deaths/100,000 inhabitants), <1 year-olds (1.03 deaths/100,000 inhabitants) and residents in Northeast region (0.30 deaths/100,000 inhabitants). Highest case fatality rates were observed in males (8.8%), ≥70 year-olds (43.8%) and residents in South region (17.7%). Mortality and case fatality rates showed a significant increase in Brazil over the period, with different patterns between regions: increasing mortality rates in the North (Annual Percent Change – APC: 9.4%; 95% confidence interval – CI: 5.3 to 13.6), and Southeast (APC: 8.1%; 95% CI: 2.6 to 13.9); and increasing case fatality rates in the Northeast (APC: 4.0%; 95% CI: 0.8 to 7.4). Spatial analysis identified a major cluster of high mortality encompassing a wide geographic range in North and Northeast Brazil. Conclusions Despite ongoing control strategies, mortality related to VL in Brazil is increasing. Mortality and case fatality vary considerably between regions, and surveillance and control measures should be prioritized in high-risk clusters. Early diagnosis and treatment are fundamental strategies for reducing case fatality of VL in Brazil. PMID:24699517

Epidemiological analysis of a cluster within the outbreak of Shiga toxin-producing Escherichia coli serotype O104:H4 in Northern Germany, 2011.

PubMed

Scharlach, Martina; Diercke, Michaela; Dreesman, Johannes; Jahn, Nicola; Krieck, Manuela; Beyrer, Konrad; Claußen, Katja; Pulz, Matthias; Floride, Regina

2013-06-01

In May 2011 one of the worldwide largest outbreaks of haemolytic uraemic syndrome (HUS) and bloody diarrhoea caused by Shiga toxin-producing Escherichia coli (STEC) serotype O104:H4 occurred in Germany. One of the most affected federal states was Lower Saxony. We present the investigation of a cluster of STEC and HUS cases within this outbreak by means of a retrospective cohort study. After a 70th birthday celebration which took place on 7th of May 2011 among 72 attendants seven confirmed cases and four probable cases were identified, two of them developed HUS. Median incubation period was 10 days. Only 35 persons (48.6%) definitely answered the question whether they had eaten the sprouts that were used for garnishing the salad. Univariable analysis revealed different food items, depending on the case definition, with Odds Ratio (OR)>1 indicating an association with STEC infection, but multivariable logistic regression showed no increased risk for STEC infection for any food item and any case definition. Sprouts as the source for the infection had to be assumed based on the results of a tracing back of the delivery ways from the catering company to the sprouts producer who was finally identified as the source of the entire German outbreak. In this large outbreak several case-control studies failed to identify the source of infection. Copyright © 2012 Elsevier GmbH. All rights reserved.

Growth of perturbations in dark energy parametrization scenarios

NASA Astrophysics Data System (ADS)

Mehrabi, Ahmad

2018-04-01

In this paper, we study the evolution of dark matter perturbations in the linear regime by considering the possibility of dark energy perturbations. To do this, two popular parametrizations, Chevallier-Polarski-Linder (CPL) and Barboza-Alcaniz (BA), with the same number of free parameters and different redshift dependency have been considered. We integrate the full relativistic equations to obtain the growth of matter fluctuations for both clustering and smooth versions of CPL and BA dark energy. The growth rate is larger (smaller) than the Λ CDM in the smooth cases when w <-1 (w >-1 ), but the dark energy clustering gives a larger (smaller) growth index when w >-1 (w <-1 ). We measure the relative difference of the growth rate with respect to concordance Λ CDM and study how it changes depending on the free parameters. Furthermore, it is found that the difference of growth rates between smooth CPL and BA is negligible, less than 0.5%, while for the clustering case, the difference is considerable and might be as large as 2%. Eventually, using the latest geometrical and growth rate observational data, we perform an overall likelihood analysis and show that both smooth and clustering cases of CPL and BA parametrizations are consistent with observations. In particular, we find the dark energy figure of merit is approximately 70 for the BA and approximately 30 for the CPL, which indicates the BA model constrains relatively better than the CPL one.

Spatial analysis of leprosy incidence and associated socioeconomic factors.

PubMed

Cury, Maria Rita de Cassia Oliveira; Paschoal, Vania Del'Arco; Nardi, Susilene Maria Tonelli; Chierotti, Ana Patrícia; Rodrigues Júnior, Antonio Luiz; Chiaravalloti-Neto, Francisco

2012-02-01

To identify clusters of the major occurrences of leprosy and their associated socioeconomic and demographic factors. Cases of leprosy that occurred between 1998 and 2007 in São José do Rio Preto (southeastern Brazil) were geocodified and the incidence rates were calculated by census tract. A socioeconomic classification score was obtained using principal component analysis of socioeconomic variables. Thematic maps to visualize the spatial distribution of the incidence of leprosy with respect to socioeconomic levels and demographic density were constructed using geostatistics. While the incidence rate for the entire city was 10.4 cases per 100,000 inhabitants annually between 1998 and 2007, the incidence rates of individual census tracts were heterogeneous, with values that ranged from 0 to 26.9 cases per 100,000 inhabitants per year. Areas with a high leprosy incidence were associated with lower socioeconomic levels. There were identified clusters of leprosy cases, however there was no association between disease incidence and demographic density. There was a disparity between the places where the majority of ill people lived and the location of healthcare services. The spatial analysis techniques utilized identified the poorer neighborhoods of the city as the areas with the highest risk for the disease. These data show that health departments must prioritize politico-administrative policies to minimize the effects of social inequality and improve the standards of living, hygiene, and education of the population in order to reduce the incidence of leprosy.

A cluster of fentanyl-related deaths among drug addicts in Sweden.

PubMed

Kronstrand, R; Druid, H; Holmgren, P; Rajs, J

1997-08-22

During a 16-month period, nine fatalities occurred among white male drug-addicts, where fentanyl was detected at postmortem toxicological analysis. The street samples associated with these cases confirmed the presence of fentanyl as an additive in low-concentration amphetamine powders with caffeine, phenazone and sugar as cutting agents. In seven of the cases, an acute intoxication by fentanyl was considered to be the immediate cause of death, and in one case, it was likely, but no analysis of fentanyl was performed in blood, and in another case the death was suicide by hanging. This appears to be the first report of a cluster of fentanyl-related deaths outside the United States, and the occurrence of fentanyl in combination with amphetamine has not previously been reported. In addition, in all cases, femoral blood was collected, and samples were handled and analysed according to standardized, quality-controlled procedures. The previous history, circumstances surrounding the death, autopsy findings, histology and toxicology examination of each case are presented. The gas chromatographic-mass spectrometric method for fentanyl is also described. Fentanyl concentrations ranged from 0.5 to 17 ng g-1 blood, and from 5 to 160 ng ml-1 urine. Other drugs found were amphetamine (8 cases), ethanol (5 cases) and benzodiazepines (5 cases). Morphine was found in only one case. The average age of men was 33.9 years (range 22-44); six were found in their own of friend's apartment, two inside buildings (stairways) and one was found outdoors. We conclude that fentanyl is a dangerous substance that should be considered in drug-addict deaths even outside the United States, particularly when the remaining toxicology is unremarkable, and the cause of death cannot be ascertained

Towards a methodology for cluster searching to provide conceptual and contextual "richness" for systematic reviews of complex interventions: case study (CLUSTER).

PubMed

Booth, Andrew; Harris, Janet; Croot, Elizabeth; Springett, Jane; Campbell, Fiona; Wilkins, Emma

2013-09-28

Systematic review methodologies can be harnessed to help researchers to understand and explain how complex interventions may work. Typically, when reviewing complex interventions, a review team will seek to understand the theories that underpin an intervention and the specific context for that intervention. A single published report from a research project does not typically contain this required level of detail. A review team may find it more useful to examine a "study cluster"; a group of related papers that explore and explain various features of a single project and thus supply necessary detail relating to theory and/or context.We sought to conduct a preliminary investigation, from a single case study review, of techniques required to identify a cluster of related research reports, to document the yield from such methods, and to outline a systematic methodology for cluster searching. In a systematic review of community engagement we identified a relevant project - the Gay Men's Task Force. From a single "key pearl citation" we conducted a series of related searches to find contextually or theoretically proximate documents. We followed up Citations, traced Lead authors, identified Unpublished materials, searched Google Scholar, tracked Theories, undertook ancestry searching for Early examples and followed up Related projects (embodied in the CLUSTER mnemonic). Our structured, formalised procedure for cluster searching identified useful reports that are not typically identified from topic-based searches on bibliographic databases. Items previously rejected by an initial sift were subsequently found to inform our understanding of underpinning theory (for example Diffusion of Innovations Theory), context or both. Relevant material included book chapters, a Web-based process evaluation, and peer reviewed reports of projects sharing a common ancestry. We used these reports to understand the context for the intervention and to explore explanations for its relative lack of success. Additional data helped us to challenge simplistic assumptions on the homogeneity of the target population. A single case study suggests the potential utility of cluster searching, particularly for reviews that depend on an understanding of context, e.g. realist synthesis. The methodology is transparent, explicit and reproducible. There is no reason to believe that cluster searching is not generalizable to other review topics. Further research should examine the contribution of the methodology beyond improved yield, to the final synthesis and interpretation, possibly by utilizing qualitative sensitivity analysis.

Spatio-Temporal Dynamics of Asymptomatic Malaria: Bridging the Gap Between Annual Malaria Resurgences in a Sahelian Environment.

PubMed

Coulibaly, Drissa; Travassos, Mark A; Tolo, Youssouf; Laurens, Matthew B; Kone, Abdoulaye K; Traore, Karim; Sissoko, Mody; Niangaly, Amadou; Diarra, Issa; Daou, Modibo; Guindo, Boureima; Rebaudet, Stanislas; Kouriba, Bourema; Dessay, Nadine; Piarroux, Renaud; Plowe, Christopher V; Doumbo, Ogobara K; Thera, Mahamadou A; Gaudart, Jean

2017-12-01

In areas of seasonal malaria transmission, the incidence rate of malaria infection is presumed to be near zero at the end of the dry season. Asymptomatic individuals may constitute a major parasite reservoir during this time. We conducted a longitudinal analysis of the spatio-temporal distribution of clinical malaria and asymptomatic parasitemia over time in a Malian town to highlight these malaria transmission dynamics. For a cohort of 300 rural children followed over 2009-2014, periodicity and phase shift between malaria and rainfall were determined by spectral analysis. Spatial risk clusters of clinical episodes or carriage were identified. A nested-case-control study was conducted to assess the parasite carriage factors. Malaria infection persisted over the entire year with seasonal peaks. High transmission periods began 2-3 months after the rains began. A cluster with a low risk of clinical malaria in the town center persisted in high and low transmission periods. Throughout 2009-2014, cluster locations did not vary from year to year. Asymptomatic and gametocyte carriage were persistent, even during low transmission periods. For high transmission periods, the ratio of asymptomatic to clinical cases was approximately 0.5, but was five times higher during low transmission periods. Clinical episodes at previous high transmission periods were a protective factor for asymptomatic carriage, but carrying parasites without symptoms at a previous high transmission period was a risk factor for asymptomatic carriage. Stable malaria transmission was associated with sustained asymptomatic carriage during dry seasons. Control strategies should target persistent low-level parasitemia clusters to interrupt transmission.

Spatial spread of dengue in a non-endemic tropical city in northern Argentina.

PubMed

Gil, José F; Palacios, Maximiliano; Krolewiecki, Alejandro J; Cortada, Pedro; Flores, Rosana; Jaime, Cesar; Arias, Luis; Villalpando, Carlos; Alberti DÁmato, Anahí M; Nasser, Julio R; Aparicio, Juan P

2016-06-01

After more than eighty years dengue reemerged in Argentina in 1997. Since then, the largest epidemic in terms of geographical extent, magnitude and mortality, was recorded in 2009. In this report we analyzed the DEN-1 epidemic spread in Orán, a mid-size city in a non-endemic tropical area in Northern Argentina, and its correlation with demographic and socioeconomic factors. Cases were diagnosed by ELISA between January and June 2009. We applied a space-time and spatial scan statistic under a Poisson model. Possible association between dengue incidence and socio-economic variables was studied with the Spearman correlation test. The epidemic started from an imported case from Bolivia and space-time analysis detected two clusters: one on February and other in April (in the south and the northeast of the city respectively) with risk ratios of 25.24 and 4.07 (p<0.01). Subsequent cases spread widely around the city without significant space-temporal clustering. Maximum values of the entomological indices were observed in January, at the beginning of the epidemic (B=21.96; LH=8.39). No statistically significant association between socioeconomic variables and dengue incidence was found but positive correlation between population size and the number of cases (p<0.05) was detected. Two mechanisms may explain the observed pattern of epidemic spread in this non-endemic tropical city: a) Short range dispersal of mosquitoes and people generates clusters of cases and b) long-distance (within the city) human movement contributes to a quasi-random distribution of cases. Copyright © 2016 Elsevier B.V. All rights reserved.

Theory for electron transfer from a mixed-valence dimer with paramagnetic sites to a mononuclear acceptor

NASA Astrophysics Data System (ADS)

Bominaar, E. L.; Achim, C.; Borshch, S. A.

1999-06-01

Polynuclear transition-metal complexes, such as Fe-S clusters, are the prosthetic groups in a large number of metalloproteins and serve as temporary electron storage units in a number of important redox-based biological processes. Polynuclearity distinguishes clusters from mononuclear centers and confers upon them unique properties, such as spin ordering and the presence of thermally accessible excited spin states in clusters with paramagnetic sites, and fractional valencies in clusters of the mixed-valence type. In an earlier study we presented an effective-mode (EM) analysis of electron transfer from a binuclear mixed-valence donor with paramagnetic sites to a mononuclear acceptor which revealed that the cluster-specific attributes have an important impact on the kinetics of long-range electron transfer. In the present study, the validity of these results is tested in the framework of more detailed theories which we have termed the multimode semiclassical (SC) model and the quantum-mechanical (QM) model. It is found that the qualitative trends in the rate constant are the same in all treatments and that the semiclassical models provide a good approximation of the more rigorous quantum-mechanical description of electron transfer under physiologically relevant conditions. In particular, the present results corroborate the importance of electron transfer via excited spin states in reactions with a low driving force and justify the use of semiclassical theory in cases in which the QM model is computationally too demanding. We consider cases in which either one or two donor sites of a dimer are electronically coupled to the acceptor. In the case of multiconnectivity, the rate constant for electron transfer from a valence-delocalized (class-III) donor is nonadditive with respect to transfer from individual metal sites of the donor and undergoes an order-of-magnitude change by reversing the sign of the intradimer metal-metal resonance parameter (β). In the case of single connectivity, the rate constant for electron transfer from a valence-localized (class-II) donor can readily be tuned over several orders of magnitude by introducing differences in the electronic potentials at the two metal sites of the donor. These results indicate that theories of cluster-based electron transfer, in order to be realistic, need to consider both intrinsic electronic structure and extrinsic interactions of the cluster with the protein environment.

Statistical Analysis of Small-Scale Magnetic Flux Emergence Patterns: A Useful Subsurface Diagnostic?

NASA Astrophysics Data System (ADS)

Lamb, Derek A.

2016-10-01

While sunspots follow a well-defined pattern of emergence in space and time, small-scale flux emergence is assumed to occur randomly at all times in the quiet Sun. HMI's full-disk coverage, high cadence, spatial resolution, and duty cycle allow us to probe that basic assumption. Some case studies of emergence suggest that temporal clustering on spatial scales of 50-150 Mm may occur. If clustering is present, it could serve as a diagnostic of large-scale subsurface magnetic field structures. We present the results of a manual survey of small-scale flux emergence events over a short time period, and a statistical analysis addressing the question of whether these events show spatio-temporal behavior that is anything other than random.

Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers

PubMed Central

Jackson, Monica C; Huang, Lan; Luo, Jun; Hachey, Mark; Feuer, Eric

2009-01-01

Background The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated. Methods We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*pop; and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. Results For simulated data with outlier patterns, Tango's MEET, Moran's I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*pop (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. Conclusion SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango's method should be used for global clustering evaluation instead of SaTScan. PMID:19822013

Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers.

PubMed

Jackson, Monica C; Huang, Lan; Luo, Jun; Hachey, Mark; Feuer, Eric

2009-10-12

The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated. We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*(pop); and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. For simulated data with outlier patterns, Tango's MEET, Moran's I and I*(pop) had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*(pop) (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*(pop) perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango's method should be used for global clustering evaluation instead of SaTScan.

Research fronts analysis : A bibliometric to identify emerging fields of research

NASA Astrophysics Data System (ADS)

Miwa, Sayaka; Ando, Satoko

Research fronts analysis identifies emerging areas of research through observing co-clustering in highly-cited papers. This article introduces the concept of research fronts analysis, explains its methodology and provides case examples. It also demonstrates developing research fronts in Japan by looking at the past winners of Thomson Reuters Research Fronts Awards. Research front analysis is currently being used by the Japanese government to determine new trends in science and technology. Information professionals can also utilize this bibliometric as a research evaluation tool.

Genetic k-Means Clustering Approach for Mapping Human Vulnerability to Chemical Hazards in the Industrialized City: A Case Study of Shanghai, China

PubMed Central

Shi, Weifang; Zeng, Weihua

2013-01-01

Reducing human vulnerability to chemical hazards in the industrialized city is a matter of great urgency. Vulnerability mapping is an alternative approach for providing vulnerability-reducing interventions in a region. This study presents a method for mapping human vulnerability to chemical hazards by using clustering analysis for effective vulnerability reduction. Taking the city of Shanghai as the study area, we measure human exposure to chemical hazards by using the proximity model with additionally considering the toxicity of hazardous substances, and capture the sensitivity and coping capacity with corresponding indicators. We perform an improved k-means clustering approach on the basis of genetic algorithm by using a 500 m × 500 m geographical grid as basic spatial unit. The sum of squared errors and silhouette coefficient are combined to measure the quality of clustering and to determine the optimal clustering number. Clustering result reveals a set of six typical human vulnerability patterns that show distinct vulnerability dimension combinations. The vulnerability mapping of the study area reflects cluster-specific vulnerability characteristics and their spatial distribution. Finally, we suggest specific points that can provide new insights in rationally allocating the limited funds for the vulnerability reduction of each cluster. PMID:23787337

Regional health care planning: a methodology to cluster facilities using community utilization patterns

PubMed Central

2013-01-01

Background Community-based health care planning and regulation necessitates grouping facilities and areal units into regions of similar health care use. Limited research has explored the methodologies used in creating these regions. We offer a new methodology that clusters facilities based on similarities in patient utilization patterns and geographic location. Our case study focused on Hospital Groups in Michigan, the allocation units used for predicting future inpatient hospital bed demand in the state’s Bed Need Methodology. The scientific, practical, and political concerns that were considered throughout the formulation and development of the methodology are detailed. Methods The clustering methodology employs a 2-step K-means + Ward’s clustering algorithm to group hospitals. The final number of clusters is selected using a heuristic that integrates both a statistical-based measure of cluster fit and characteristics of the resulting Hospital Groups. Results Using recent hospital utilization data, the clustering methodology identified 33 Hospital Groups in Michigan. Conclusions Despite being developed within the politically charged climate of Certificate of Need regulation, we have provided an objective, replicable, and sustainable methodology to create Hospital Groups. Because the methodology is built upon theoretically sound principles of clustering analysis and health care service utilization, it is highly transferable across applications and suitable for grouping facilities or areal units. PMID:23964905

Regional health care planning: a methodology to cluster facilities using community utilization patterns.

PubMed

Delamater, Paul L; Shortridge, Ashton M; Messina, Joseph P

2013-08-22

Community-based health care planning and regulation necessitates grouping facilities and areal units into regions of similar health care use. Limited research has explored the methodologies used in creating these regions. We offer a new methodology that clusters facilities based on similarities in patient utilization patterns and geographic location. Our case study focused on Hospital Groups in Michigan, the allocation units used for predicting future inpatient hospital bed demand in the state's Bed Need Methodology. The scientific, practical, and political concerns that were considered throughout the formulation and development of the methodology are detailed. The clustering methodology employs a 2-step K-means + Ward's clustering algorithm to group hospitals. The final number of clusters is selected using a heuristic that integrates both a statistical-based measure of cluster fit and characteristics of the resulting Hospital Groups. Using recent hospital utilization data, the clustering methodology identified 33 Hospital Groups in Michigan. Despite being developed within the politically charged climate of Certificate of Need regulation, we have provided an objective, replicable, and sustainable methodology to create Hospital Groups. Because the methodology is built upon theoretically sound principles of clustering analysis and health care service utilization, it is highly transferable across applications and suitable for grouping facilities or areal units.

Technical support for creating an artificial intelligence system for feature extraction and experimental design

NASA Technical Reports Server (NTRS)

Glick, B. J.

1985-01-01

Techniques for classifying objects into groups or clases go under many different names including, most commonly, cluster analysis. Mathematically, the general problem is to find a best mapping of objects into an index set consisting of class identifiers. When an a priori grouping of objects exists, the process of deriving the classification rules from samples of classified objects is known as discrimination. When such rules are applied to objects of unknown class, the process is denoted classification. The specific problem addressed involves the group classification of a set of objects that are each associated with a series of measurements (ratio, interval, ordinal, or nominal levels of measurement). Each measurement produces one variable in a multidimensional variable space. Cluster analysis techniques are reviewed and methods for incuding geographic location, distance measures, and spatial pattern (distribution) as parameters in clustering are examined. For the case of patterning, measures of spatial autocorrelation are discussed in terms of the kind of data (nominal, ordinal, or interval scaled) to which they may be applied.

Rosacea assessment by erythema index and principal component analysis segmentation maps

NASA Astrophysics Data System (ADS)

Kuzmina, Ilona; Rubins, Uldis; Saknite, Inga; Spigulis, Janis

2017-12-01

RGB images of rosacea were analyzed using segmentation maps of principal component analysis (PCA) and erythema index (EI). Areas of segmented clusters were compared to Clinician's Erythema Assessment (CEA) values given by two dermatologists. The results show that visible blood vessels are segmented more precisely on maps of the erythema index and the third principal component (PC3). In many cases, a distribution of clusters on EI and PC3 maps are very similar. Mean values of clusters' areas on these maps show a decrease of the area of blood vessels and erythema and an increase of lighter skin area after the therapy for the patients with diagnosis CEA = 2 on the first visit and CEA=1 on the second visit. This study shows that EI and PC3 maps are more useful than the maps of the first (PC1) and second (PC2) principal components for indicating vascular structures and erythema on the skin of rosacea patients and therapy monitoring.

Analysis of the heat capacity of nanoclusters of FCC metals on the example of Al, Ni, Cu, Pd, and Au

NASA Astrophysics Data System (ADS)

Gafner, Yu. Ya.; Gafner, S. L.; Zamulin, I. S.; Redel, L. V.; Baidyshev, V. S.

2015-06-01

The heat capacity of ideal nickel, copper, gold, aluminum, and palladium fcc clusters with diameter of up to 6 nm has been studied in the temperature range of 150-800 K in terms of the molecular-dynamics theory using a tight-binding potential. The heat capacity of individual metallic nanoclusters has been found to exceed that characteristic of the bulk state, but by no more than 16-20%, even in the case of very small clusters. To explain the discrepancy between the simulated data and the experimental results on the compacted metals, aluminum and palladium samples with 80% theoretical density have also been investigated. Based on the simulation results and analysis of the experimental data, it has been established that the increased heat capacity of the compacted nanomaterials does not depend on the enhanced heat capacity of the individual clusters but rather, can be due to either the disordered state of the nanomaterial or a significant content of impurities (mainly, hydrogen).

[Cluster of multidrug-resistant tuberculosis cases in a school of the district of Ica, Peru].

PubMed

Torres, Julio; Sardón, Victoria; Soto, Mirtha G; Anicama, Rolado; Arroyo-Hernández, Hugo; Munayco, César V

2011-01-01

We describe the evolution and features of a cluster of Multidrug-resistant tuberculosis (MDR TB) cases that occurred in 2001, in a school located in a sub-urban area of the district of Ica, Peru. We identified 15 students related before becoming infected with tuberculosis. The mean age of the cluster was 15 years. A total of 12 students were MDR-TB cases and 7 were drug-resistant to 5 first-line drugs (RHEZS). Five out of the 15 cases received at least 3 different anti-tuberculosis treatment schemes. The average treatment duration was 37 months (minimum 21 and maximum 59 months). A total of 13 cases recovered and 2 died. This study describes a cluster of MDR -TB cases in an educational facility, which due to the epidemiological link and time presentation, is probably an outbreak of MDR TB with a satisfactory outcome after prolonged treatment.

Spatial clustering of childhood leukaemia in Switzerland: A nationwide study.

PubMed

Konstantinoudis, Garyfallos; Kreis, Christian; Ammann, Roland A; Niggli, Felix; Kuehni, Claudia E; Spycher, Ben D

2017-10-01

The aetiology of childhood leukaemia remains largely unknown. Several hypotheses involve environmental exposures that could implicate spatial clustering of cases. The evidence from previous clustering studies is inconclusive. Most of them used areal data and thus had limited spatial resolution. We investigated whether childhood leukaemia tends to cluster in space using exact geocodes of place of residence both at the time of birth or diagnosis. We included 1,871 leukaemia cases diagnosed between 1985 and 2015 at age 0-15 years from the Swiss Childhood Cancer Registry. For each case, we randomly sampled 10 age and sex matched controls from national censuses closest in time. We used the difference of k-functions, Cuzick-Edwards' test and Tango's index for point data to assess spatial clustering and Kulldorff's circular scan to detect clusters. We separately investigated acute lymphoid leukaemia (ALL), acute myeloid leukaemia (AML), different age groups at diagnosis (0-4, 5-15 years) and adjusted for multiple testing. After adjusting for multiple testing, we found no evidence of spatial clustering of childhood leukaemia neither around time of birth (p = 0.52) nor diagnosis (p = 0.51). Individual tests indicated spatial clustering for leukaemia diagnosed at age 5-15 years, p k-functions = 0.05 and p Cuzick-Edwards' = 0.04 and a cluster of ALL cases diagnosed at age 0-4 years in a small rural area (p = 0.05). This study provides little evidence of spatial clustering of childhood leukaemia in Switzerland and highlights the importance of accounting for multiple testing in clustering studies. © 2017 UICC.

Spatial patterns of multidrug resistant tuberculosis and relationships to socio-economic, demographic and household factors in northwest Ethiopia.

PubMed

Alene, Kefyalew Addis; Viney, Kerri; McBryde, Emma S; Clements, Archie C A

2017-01-01

Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia. An ecological study was conducted using data on patients diagnosed with MDR-TB at the University of Gondar Hospital MDR-TB treatment centre, for the period 2010 to 2015. District level population data were extracted from the Ethiopia National and Regional Census Report. Spatial autocorrelation was explored using Moran's I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate Poisson regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo (MCMC) simulation approach with Gibbs sampling, in WinBUGS. A total of 264 MDR-TB patients were included in the analysis. The overall crude incidence rate of MDR-TB for the six-year period was 3.0 cases per 100,000 population. The highest incidence rate was observed in Metema (21 cases per 100,000 population) and Humera (18 cases per 100,000 population) districts; whereas nine districts had zero cases. Spatial clustering of MDR-TB was observed in districts located in the Ethiopia-Sudan and Ethiopia-Eritrea border regions, where large numbers of seasonal migrants live. Spatial clustering of MDR-TB was positively associated with urbanization (RR: 1.02; 95%CI: 1.01, 1.04) and the percentage of men (RR: 1.58; 95% CI: 1.26, 1.99) in the districts; after accounting for these factors there was no residual spatial clustering. Spatial clustering of MDR-TB, fully explained by demographic factors (urbanization and percent male), was detected in the border regions of northwest Ethiopia, in locations where seasonal migrants live and work. Cross-border initiatives including options for mobile TB treatment and follow up are important for the effective control of MDR-TB in the region.

Spatial overlap links seemingly unconnected genotype-matched TB cases in rural Uganda

PubMed Central

Kato-Maeda, Midori; Emperador, Devy M.; Wandera, Bonnie; Mugagga, Olive; Crandall, John; Janes, Michael; Marquez, Carina; Kamya, Moses R.; Charlebois, Edwin D.; Havlir, Diane V.

2018-01-01

Introduction Incomplete understanding of TB transmission dynamics in high HIV prevalence settings remains an obstacle for prevention. Understanding where transmission occurs could provide a platform for case finding and interrupting transmission. Methods From 2012–2015, we sought to recruit all adults starting TB treatment in a Ugandan community. Participants underwent household (HH) contact investigation, and provided names of social contacts, sites of work, healthcare and socializing, and two sputum samples. Mycobacterium tuberculosis culture-positive specimens underwent 24-loci MIRU-VNTR and spoligotyping. We sought to identify epidemiologic links between genotype-matched cases by analyzing social networks and mapping locations where cases reported spending ≥12 hours over the one-month pre-treatment. Sites of spatial overlap (≤100m) between genotype-matched cases were considered potential transmission sites. We analyzed social networks stratified by genotype clustering status, with cases linked by shared locations, and compared network density by location type between clustered vs. non-clustered cases. Results Of 173 adults with TB, 131 (76%) were enrolled, 108 provided sputum, and 84/131 (78%) were MTB culture-positive: 52% (66/131) tested HIV-positive. Of 118 adult HH contacts, 105 (89%) were screened and 3 (2.5%) diagnosed with active TB. Overall, 33 TB cases (39%) belonged to 15 distinct MTB genotype-matched clusters. Within each cluster, no cases shared a HH or reported shared non-HH contacts. In 6/15 (40%) clusters, potential epidemiologic links were identified by spatial overlap at specific locations: 5/6 involved health care settings. Genotype-clustered TB social networks had significantly greater network density based on shared clinics (p<0.001) and decreased density based on shared marketplaces (p<0.001), compared to non-clustered networks. Conclusions In this molecular epidemiologic study, links between MTB genotype-matched cases were only identifiable via shared locations, healthcare locations in particular, rather than named contacts. This suggests most transmission is occurring between casual contacts, and emphasizes the need for improved infection control in healthcare settings in rural Africa. PMID:29438413

A dengue outbreak on a floating village at Cat Ba Island in Vietnam.

PubMed

Le Viet, Thanh; Choisy, Marc; Bryant, Juliet E; Vu Trong, Duoc; Pham Quang, Thai; Horby, Peter; Nguyen Tran, Hien; Tran Thi Kieu, Huong; Nguyen Vu, Trung; Nguyen Van, Kinh; Le Quynh, Mai; Wertheim, Heiman F L

2015-09-22

A dengue outbreak in an ecotourism destination spot in Vietnam, from September to November 2013, impacted a floating village of fishermen on the coastal island of Cat Ba. The outbreak raises questions about how tourism may impact disease spread in rural areas. Epidemiological data were obtained from the Hai Phong Preventive Medical Center (PMC), including case histories and residential location from all notified dengue cases from this outbreak. All household addresses were geo-located. Knox test, a spatio-temporal analysis that enables inference dengue clustering constrained by space and time, was performed on the geocoded locations. From the plasma available from two patients, positive for Dengue serotype 3 virus (DENV3), the Envelope (E) gene was sequenced, and their genetic relationships compared to other E sequences in the region. Of 192 dengue cases, the odds ratio of contracting dengue infections for people living in the floating villages compared to those living on the island was 4.9 (95 % CI: 3.6-6.7). The space-time analyses on 111 geocoded dengue residences found the risk of dengue infection to be the highest within 4 days and a radius of 20 m of a given case. Of the total of ten detected clusters with an excess risk greater than 2, the cluster with the highest number of cases was in the floating village area (24 patients for a total duration of 31 days). Phylogenetic analysis revealed a high homology of the two DENV3 strains (genotype III) from Cat Ba with DENV3 viruses circulating in Hanoi in the same year (99.1 %). Our study showed that dengue transmission is unlikely to be sustained on Cat Ba Island and that the 2013 epidemic likely originated through introduction of viruses from the mainland, potentially Hanoi. These findings suggest that prevention efforts should be focused on mainland rather than on the island.

Spatial Analysis of Case-Mix and Dialysis Modality Associations.

PubMed

Phirtskhalaishvili, Tamar; Bayer, Florian; Edet, Stephane; Bongiovanni, Isabelle; Hogan, Julien; Couchoud, Cécile

2016-01-01

♦ Health-care systems must attempt to provide appropriate, high-quality, and economically sustainable care that meets the needs and choices of patients with end-stage renal disease (ESRD). France offers 9 different modalities of dialysis, each characterized by dialysis technique, the extent of professional assistance, and the treatment site. The aim of this study was 1) to describe the various dialysis modalities in France and the patient characteristics associated with each of them, and 2) to analyze their regional patterns to identify possible unexpected associations between case-mixes and dialysis modalities. ♦ The clinical characteristics of the 37,421 adult patients treated by dialysis were described according to their treatment modality. Agglomerative hierarchical cluster analysis was used to aggregate the regions into clusters according to their use of these modalities and the characteristics of their patients. ♦ The gradient of patient characteristics was similar from home hemodialyis (HD) to in-center HD and from non-assisted automated peritoneal dialysis (APD) to assisted continuous ambulatory peritoneal dialysis (CAPD). Analyzing their spatial distribution, we found differences in the patient case-mix on dialysis across regions but also differences in the health-care provided for them. The classification of the regions into 6 different clusters allowed us to detect some unexpected associations between case-mixes and treatment modalities. ♦ The 9 modalities of treatment available make it theoretically possible to adapt treatment to patients' clinical characteristics and abilities. However, although we found an overall appropriate association of dialysis modalities to the case-mix, major inter-region heterogeneity and the low rate of peritoneal dialysis (PD) and home HD suggest that factors besides patients' clinical conditions impact the choice of dialysis modality. The French organization should now be evaluated in terms of patients' quality of life, satisfaction, survival, and global efficiency. Copyright © 2016 International Society for Peritoneal Dialysis.

Epidemiological analysis, detection, and comparison of space-time patterns of Beijing hand-foot-mouth disease (2008-2012).

PubMed

Wang, Jiaojiao; Cao, Zhidong; Zeng, Daniel Dajun; Wang, Quanyi; Wang, Xiaoli; Qian, Haikun

2014-01-01

Hand, foot, and mouth disease (HFMD) mostly affects the health of infants and preschool children. Many studies of HFMD in different regions have been published. However, the epidemiological characteristics and space-time patterns of individual-level HFMD cases in a major city such as Beijing are unknown. The objective of this study was to investigate epidemiological features and identify high relative risk space-time HFMD clusters at a fine spatial scale. Detailed information on age, occupation, pathogen and gender was used to analyze the epidemiological features of HFMD epidemics. Data on individual-level HFMD cases were examined using Local Indicators of Spatial Association (LISA) analysis to identify the spatial autocorrelation of HFMD incidence. Spatial filtering combined with scan statistics methods were used to detect HFMD clusters. A total of 157,707 HFMD cases (60.25% were male, 39.75% were female) reported in Beijing from 2008 to 2012 included 1465 severe cases and 33 fatal cases. The annual average incidence rate was 164.3 per 100,000 (ranged from 104.2 in 2008 to 231.5 in 2010). Male incidence was higher than female incidence for the 0 to 14-year age group, and 93.88% were nursery children or lived at home. Areas at a higher relative risk were mainly located in the urban-rural transition zones (the percentage of the population at risk ranged from 33.89% in 2011 to 39.58% in 2012) showing High-High positive spatial association for HFMD incidence. The most likely space-time cluster was located in the mid-east part of the Fangshan district, southwest of Beijing. The spatial-time patterns of Beijing HFMD (2008-2012) showed relatively steady. The population at risk were mainly distributed in the urban-rural transition zones. Epidemiological features of Beijing HFMD were generally consistent with the previous research. The findings generated computational insights useful for disease surveillance, risk assessment and early warning.

Spatial Analysis of Case-Mix and Dialysis Modality Associations

PubMed Central

Phirtskhalaishvili, Tamar; Bayer, Florian; Edet, Stephane; Bongiovanni, Isabelle; Hogan, Julien; Couchoud, Cécile

2016-01-01

♦ Background: Health-care systems must attempt to provide appropriate, high-quality, and economically sustainable care that meets the needs and choices of patients with end-stage renal disease (ESRD). France offers 9 different modalities of dialysis, each characterized by dialysis technique, the extent of professional assistance, and the treatment site. The aim of this study was 1) to describe the various dialysis modalities in France and the patient characteristics associated with each of them, and 2) to analyze their regional patterns to identify possible unexpected associations between case-mixes and dialysis modalities. ♦ Methods: The clinical characteristics of the 37,421 adult patients treated by dialysis were described according to their treatment modality. Agglomerative hierarchical cluster analysis was used to aggregate the regions into clusters according to their use of these modalities and the characteristics of their patients. ♦ Result: The gradient of patient characteristics was similar from home hemodialyis (HD) to in-center HD and from non-assisted automated peritoneal dialysis (APD) to assisted continuous ambulatory peritoneal dialysis (CAPD). Analyzing their spatial distribution, we found differences in the patient case-mix on dialysis across regions but also differences in the health-care provided for them. The classification of the regions into 6 different clusters allowed us to detect some unexpected associations between case-mixes and treatment modalities. ♦ Conclusions: The 9 modalities of treatment available make it theoretically possible to adapt treatment to patients' clinical characteristics and abilities. However, although we found an overall appropriate association of dialysis modalities to the case-mix, major inter-region heterogeneity and the low rate of peritoneal dialysis (PD) and home HD suggest that factors besides patients' clinical conditions impact the choice of dialysis modality. The French organization should now be evaluated in terms of patients' quality of life, satisfaction, survival, and global efficiency. PMID:26475843

Integrating participatory community mobilization processes to improve dengue prevention: an eco-bio-social scaling up of local success in Machala, Ecuador.

PubMed

Mitchell-Foster, Kendra; Ayala, Efraín Beltrán; Breilh, Jaime; Spiegel, Jerry; Wilches, Ana Arichabala; Leon, Tania Ordóñez; Delgado, Jefferson Adrian

2015-02-01

This project investigates the effectiveness and feasibility of scaling-up an eco-bio-social approach for implementing an integrated community-based approach for dengue prevention in comparison with existing insecticide-based and emerging biolarvicide-based programs in an endemic setting in Machala, Ecuador. An integrated intervention strategy (IIS) for dengue prevention (an elementary school-based dengue education program, and clean patio and safe container program) was implemented in 10 intervention clusters from November 2012 to November 2013 using a randomized controlled cluster trial design (20 clusters: 10 intervention, 10 control; 100 households per cluster with 1986 total households). Current existing dengue prevention programs served as the control treatment in comparison clusters. Pupa per person index (PPI) is used as the main outcome measure. Particular attention was paid to social mobilization and empowerment with IIS. Overall, IIS was successful in reducing PPI levels in intervention communities versus control clusters, with intervention clusters in the six paired clusters that followed the study design experiencing a greater reduction of PPI compared to controls (2.2 OR, 95% CI: 1.2 to 4.7). Analysis of individual cases demonstrates that consideration for contexualizing programs and strategies to local neighborhoods can be very effective in reducing PPI for dengue transmission risk reduction. In the rapidly evolving political climate for dengue control in Ecuador, integration of successful social mobilization and empowerment strategies with existing and emerging biolarvicide-based government dengue prevention and control programs is promising in reducing PPI and dengue transmission risk in southern coastal communities like Machala. However, more profound analysis of social determination of health is called for to assess sustainability prospects. © The author 2015. The World Health Organization has granted Oxford University Press permission for the reproduction of this article.

Integrating participatory community mobilization processes to improve dengue prevention: an eco-bio-social scaling up of local success in Machala, Ecuador

PubMed Central

Mitchell-Foster, Kendra; Ayala, Efraín Beltrán; Breilh, Jaime; Spiegel, Jerry; Wilches, Ana Arichabala; Leon, Tania Ordóñez; Delgado, Jefferson Adrian

2015-01-01

Background This project investigates the effectiveness and feasibility of scaling-up an eco-bio-social approach for implementing an integrated community-based approach for dengue prevention in comparison with existing insecticide-based and emerging biolarvicide-based programs in an endemic setting in Machala, Ecuador. Methods An integrated intervention strategy (IIS) for dengue prevention (an elementary school-based dengue education program, and clean patio and safe container program) was implemented in 10 intervention clusters from November 2012 to November 2013 using a randomized controlled cluster trial design (20 clusters: 10 intervention, 10 control; 100 households per cluster with 1986 total households). Current existing dengue prevention programs served as the control treatment in comparison clusters. Pupa per person index (PPI) is used as the main outcome measure. Particular attention was paid to social mobilization and empowerment with IIS. Results Overall, IIS was successful in reducing PPI levels in intervention communities versus control clusters, with intervention clusters in the six paired clusters that followed the study design experiencing a greater reduction of PPI compared to controls (2.2 OR, 95% CI: 1.2 to 4.7). Analysis of individual cases demonstrates that consideration for contexualizing programs and strategies to local neighborhoods can be very effective in reducing PPI for dengue transmission risk reduction. Conclusions In the rapidly evolving political climate for dengue control in Ecuador, integration of successful social mobilization and empowerment strategies with existing and emerging biolarvicide-based government dengue prevention and control programs is promising in reducing PPI and dengue transmission risk in southern coastal communities like Machala. However, more profound analysis of social determination of health is called for to assess sustainability prospects. PMID:25604763

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Core Serial Titles in an Interdisciplinary Field: The Case of Environmental Geology.

ERIC Educational Resources Information Center

Zipp, Louise S.

1999-01-01

Identifies core journals in environmental geology and explores facets of interdisciplinarity to consider the visibility of this field to collection-development librarians. Intercitation analysis of citing and cited patterns in 1995 articles revealed the journal network of environmental geology. Titles clustered into three categories:…

Epidemiology of the epidemic of bovine anaemia associated with Theileria orientalis (Ikeda) between August 2012 and March 2014.

PubMed

Lawrence, K; McFadden, Amj; Gias, E; Pulford, D J; Pomroy, W E

2016-01-01

To describe the epidemiology of the epidemic of bovine anaemia associated with Theileria orientalis infection (TABA) in New Zealand between 30 August 2012 and 4 March 2014. Blood samples and associated data were obtained from cases of TABA. The case definition for TABA was met when piroplasms were present on blood smears and the haematocrit was ≤0.24 L/L. Samples were analysed using quantitative PCR (qPCR) assays for the detection of T. orientalis Ikeda type. Only cases that were positive in the qPCR assays were included in the analysis. A case herd was defined as a herd that had ≥1 animal positive for T. orientalis Ikeda. Movement records for farms were accessed through the national animal identification and tracing scheme. The OR for cattle movements onto a case farm compared to a non-case farm was estimated using a generalised estimating equation model and the geodesic distance for movements onto case and non-case farms compared using Student's t-test. The kernel-smoothed risk of disease at the farm level was calculated using an extraction map and the clustering of diseased farms in time and space was measured using the spatial temporal inhomogeneous pair correlation function. In the first 18 months there were 496 case herds; 392 (79%) were dairy and 104 (21%) beef herds. Of 882 individual cases, 820 (93.0%) were positive for T. orientalis Ikeda in the qPCR assays. Case herds were initially clustered in the Northland, then the Waikato regions. The OR for a case farm compared to a non-case farm having ≥1 inward cattle movements was 2.03 (95% CI=1.52-2.71) and the distance moved was 26 (95% CI=20.8-31.3) km greater for case farms. The risk of disease was highest in a north, north-eastern to south, south-western belt across the Waikato region. The spatial-temporal analysis showed significant clustering of infected herds within 20-30 days and up to 15 km distant from a case farm. Theileria orientalis Ikeda type is likely to have been introduced into regions populated with naïve cattle by the movement of parasitaemic cattle from affected areas. Local spread through dispersed ticks then probably became more important for disease transmission between herds once the disease established in a new area. Dairy and beef farming in the North Island of New Zealand will be significantly changed in the coming years by the incursion of this new disease.

Clustering and phase transitions on a neutral landscape

NASA Astrophysics Data System (ADS)

Scott, Adam D.; King, Dawn M.; Marić, Nevena; Bahar, Sonya

2013-06-01

Recent computational studies have shown that speciation can occur under neutral conditions, i.e., when the simulated organisms all have identical fitness. These works bear comparison with mathematical studies of clustering on neutral landscapes in the context of branching and coalescing random walks. Here, we show that sympatric clustering/speciation can occur on a neutral landscape whose dimensions specify only the simulated organisms’ phenotypes. We demonstrate that clustering occurs not only in the case of assortative mating, but also in the case of asexual fission; it is not observed in the control case of random mating. We find that the population size and the number of clusters undergo a second-order non-equilibrium phase transition as the maximum mutation size is varied.

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. Results We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. Conclusion We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis. PMID:18257938

Spatial-temporal epidemiology of human Salmonella Enteritidis infections with major phage types (PTs 1, 4, 5b, 8, 13, and 13a) in Ontario, Canada, 2008-2009.

PubMed

Varga, Csaba; Pearl, David L; McEwen, Scott A; Sargeant, Jan M; Pollari, Frank; Guerin, Michele T

2015-12-17

In Ontario and Canada, the incidence of human Salmonella enterica serotype Enteritidis (S. Enteritidis) infections have increased steadily during the last decade. Our study evaluated the spatial and temporal epidemiology of the major phage types (PTs) of S. Enteritidis infections to aid public health practitioners design effective prevention and control programs. Data on S. Enteritidis infections between January 1, 2008 and December 31, 2009 were obtained from Ontario's disease surveillance system. Salmonella Enteritidis infections with major phage types were classified by their annual health region-level incidence rates (IRs), monthly IRs, clinical symptoms, and exposure settings. A scan statistic was employed to detect retrospective phage type-specific spatial, temporal, and space-time clusters of S. Enteritidis infections. Space-time cluster cases' exposure settings were evaluated to identify common exposures. 1,336 cases were available for analysis. The six most frequently reported S. Enteritidis PTs were 8 (n = 398), 13a (n = 218), 13 (n = 198), 1 (n = 132), 5b (n = 83), and 4 (n = 76). Reported rates of S. Enteritidis infections with major phage types varied by health region and month. International travel and unknown exposure settings were the most frequently reported settings for PT 5b, 4, and 1 cases, whereas unknown exposure setting, private home, food premise, and international travel were the most frequently reported settings for PT 8, 13, and 13a cases. Diarrhea, abdominal pain, and fever were the most commonly reported clinical symptoms. A number of phage type-specific spatial, temporal, and space-time clusters were identified. Space-time clusters of PTs 1, 4, and 5b occurred mainly during the winter and spring months in the North West, North East, Eastern, Central East, and Central West regions. Space-time clusters of PTs 13 and 13a occurred at different times of the year in the Toronto region. Space-time clusters of PT 8 occurred at different times of the year in the North West and South West regions. Phage type-specific differences in exposure settings, and spatial-temporal clustering of S. Enteritidis infections were demonstrated that might guide public health surveillance of disease outbreaks. Our study methodology could be applied to other foodborne disease surveillance data to detect retrospective high disease rate clusters, which could aid public health authorities in developing effective prevention and control programs.

Measuring Health Information Dissemination and Identifying Target Interest Communities on Twitter: Methods Development and Case Study of the @SafetyMD Network.

PubMed

Kandadai, Venk; Yang, Haodong; Jiang, Ling; Yang, Christopher C; Fleisher, Linda; Winston, Flaura Koplin

2016-05-05

Little is known about the ability of individual stakeholder groups to achieve health information dissemination goals through Twitter. This study aimed to develop and apply methods for the systematic evaluation and optimization of health information dissemination by stakeholders through Twitter. Tweet content from 1790 followers of @SafetyMD (July-November 2012) was examined. User emphasis, a new indicator of Twitter information dissemination, was defined and applied to retweets across two levels of retweeters originating from @SafetyMD. User interest clusters were identified based on principal component analysis (PCA) and hierarchical cluster analysis (HCA) of a random sample of 170 followers. User emphasis of keywords remained across levels but decreased by 9.5 percentage points. PCA and HCA identified 12 statistically unique clusters of followers within the @SafetyMD Twitter network. This study is one of the first to develop methods for use by stakeholders to evaluate and optimize their use of Twitter to disseminate health information. Our new methods provide preliminary evidence that individual stakeholders can evaluate the effectiveness of health information dissemination and create content-specific clusters for more specific targeted messaging.

Free-energy landscape, principal component analysis, and structural clustering to identify representative conformations from molecular dynamics simulations: the myoglobin case.

PubMed

Papaleo, Elena; Mereghetti, Paolo; Fantucci, Piercarlo; Grandori, Rita; De Gioia, Luca

2009-01-01

Several molecular dynamics (MD) simulations were used to sample conformations in the neighborhood of the native structure of holo-myoglobin (holo-Mb), collecting trajectories spanning 0.22 micros at 300 K. Principal component (PCA) and free-energy landscape (FEL) analyses, integrated by cluster analysis, which was performed considering the position and structures of the individual helices of the globin fold, were carried out. The coherence between the different structural clusters and the basins of the FEL, together with the convergence of parameters derived by PCA indicates that an accurate description of the Mb conformational space around the native state was achieved by multiple MD trajectories spanning at least 0.14 micros. The integration of FEL, PCA, and structural clustering was shown to be a very useful approach to gain an overall view of the conformational landscape accessible to a protein and to identify representative protein substates. This method could be also used to investigate the conformational and dynamical properties of Mb apo-, mutant, or delete versions, in which greater conformational variability is expected and, therefore identification of representative substates from the simulations is relevant to disclose structure-function relationship.

Molecular epidemiological characteristics of Salmonella enterica serovars Enteritidis, Typhimurium and Livingstone strains isolated in a Tunisian university hospital.

PubMed

Ktari, Sonia; Ksibi, Boutheina; Gharsallah, Houda; Mnif, Basma; Maalej, Sonda; Rhimi, Fouzia; Hammami, Adnene

2016-03-01

Enteritidis, Typhimurium and Livingstone are the main Salmonella enterica serovars recovered in Tunisia. Here, we aimed to assess the genetic diversity of fifty-seven Salmonella enterica strains from different sampling periods, origins and settings using pulsed-field gel electrophoresis (PFGE), multi-locus sequence typing (MLST) and multi-locus variable-number tandem repeat analysis (MLVA). Salmonella Enteritidis, isolated from human and food sources from two regions in Sfax in 2007, were grouped into one cluster using PFGE. However, using MLVA these strains were divided into two clusters. Salmonella Typhimurium strains, recovered in 2012 and represent sporadic cases of human clinical isolates, were included in one PFGE cluster. Nevertheless, the MLVA technique, divided Salmonella Typhimurium isolates into six clusters with diversity index reaching (DI = 0.757). For Salmonella Livingstone which was responsible of two nosocomial outbreaks during 2000-2003, the PFGE and MLVA methods showed that these strains were genetically closely related. Salmonella Enteritidis and Salmonella Livingstone populations showed a single ST lineage ST11 and ST543 respectively. For Salmonella Typhimurium, two MLST sequence types ST19 and ST328 were defined. Salmonella Enteritidis and Salmonella Typhimurium strains were clearly differentiated by MLVA which was not the case using PFGE. © 2015 APMIS. Published by John Wiley & Sons Ltd.

A tripartite clustering analysis on microRNA, gene and disease model.

PubMed

Shen, Chengcheng; Liu, Ying

2012-02-01

Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

The X-CLASS-redMaPPer galaxy cluster comparison. I. Identification procedures

NASA Astrophysics Data System (ADS)

Sadibekova, T.; Pierre, M.; Clerc, N.; Faccioli, L.; Gastaud, R.; Le Fevre, J.-P.; Rozo, E.; Rykoff, E.

2014-11-01

Context. This paper is the first in a series undertaking a comprehensive correlation analysis between optically selected and X-ray-selected cluster catalogues. The rationale of the project is to develop a holistic picture of galaxy clusters utilising optical and X-ray-cluster-selected catalogues with well-understood selection functions. Aims: Unlike most of the X-ray/optical cluster correlations to date, the present paper focuses on the non-matching objects in either waveband. We investigate how the differences observed between the optical and X-ray catalogues may stem from (1) a shortcoming of the detection algorithms; (2) dispersion in the X-ray/optical scaling relations; or (3) substantial intrinsic differences between the cluster populations probed in the X-ray and optical bands. The aim is to inventory and elucidate these effects in order to account for selection biases in the further determination of X-ray/optical cluster scaling relations. Methods: We correlated the X-CLASS serendipitous cluster catalogue extracted from the XMM archive with the redMaPPer optical cluster catalogue derived from the Sloan Digital Sky Survey (DR8). We performed a detailed and, in large part, interactive analysis of the matching output from the correlation. The overlap between the two catalogues has been accurately determined and possible cluster positional errors were manually recovered. The final samples comprise 270 and 355 redMaPPer and X-CLASS clusters, respectively. X-ray cluster matching rates were analysed as a function of optical richness. In the second step, the redMaPPer clusters were correlated with the entire X-ray catalogue, containing point and uncharacterised sources (down to a few 10-15 erg s-1 cm-2 in the [0.5-2] keV band). A stacking analysis was performed for the remaining undetected optical clusters. Results: We find that all rich (λ ≥ 80) clusters are detected in X-rays out to z = 0.6. Below this redshift, the richness threshold for X-ray detection steadily decreases with redshift. Likewise, all X-ray bright clusters are detected by redMaPPer. After correcting for obvious pipeline shortcomings (about 10% of the cases both in optical and X-ray), ~50% of the redMaPPer (down to a richness of 20) are found to coincide with an X-CLASS cluster; when considering X-ray sources of any type, this fraction increases to ~80%; for the remaining objects, the stacking analysis finds a weak signal within 0.5 Mpc around the cluster optical centres. The fraction of clusters totally dominated by AGN-type emission appears to be a few percent. Conversely, ~40% of the X-CLASS clusters are identified with a redMaPPer (down to a richness of 20) - part of the non-matches being due to the X-CLASS sample extending further out than redMaPPer (z< 1.5 vs. z< 0.6), but extending the correlation down to a richness of 5 raises the matching rate to ~65%. Conclusions: This state-of-the-art study involving two well-validated cluster catalogues has shown itself to be complex, and it points to a number of issues inherent to blind cross-matching, owing both to pipeline shortcomings and cluster peculiar properties. These can only been accounted for after a manual check. The combined X-ray and optical scaling relations will be presented in a subsequent article.

Autogrid-based clustering of kinases: selection of representative conformations for docking purposes.

PubMed

Marzaro, Giovanni; Ferrarese, Alessandro; Chilin, Adriana

2014-08-01

The selection of the most appropriate protein conformation is a crucial aspect in molecular docking experiments. In order to reduce the errors arising from the use of a single protein conformation, several authors suggest the use of several tridimensional structures for the target. However, the selection of the most appropriate protein conformations still remains a challenging goal. The protein 3D-structures selection is mainly performed based on pairwise root-mean-square-deviation (RMSD) values computation, followed by hierarchical clustering. Herein we report an alternative strategy, based on the computation of only two atom affinity map for each protein conformation, followed by multivariate analysis and hierarchical clustering. This methodology was applied on seven different kinases of pharmaceutical interest. The comparison with the classical RMSD-based strategy was based on cross-docking of co-crystallized ligands. In the case of epidermal growth factor receptor kinase, also the docking performance on 220 known ligands were evaluated, followed by 3D-QSAR studies. In all the cases, the herein proposed methodology outperformed the RMSD-based one.

On aggregation in CA models in biology

NASA Astrophysics Data System (ADS)

Alber, Mark S.; Kiskowski, Audi

2001-12-01

Aggregation of randomly distributed particles into clusters of aligned particles is modeled using a cellular automata (CA) approach. The CA model accounts for interactions between more than one type of particle, in which pressures for angular alignment with neighbors compete with pressures for grouping by cell type. In the case of only one particle type clusters tend to unite into one big cluster. In the case of several types of particles the dynamics of clusters is more complicated and for specific choices of parameters particle sorting occurs simultaneously with the formation of clusters of aligned particles.

Global survey of star clusters in the Milky Way. VI. Age distribution and cluster formation history

NASA Astrophysics Data System (ADS)

Piskunov, A. E.; Just, A.; Kharchenko, N. V.; Berczik, P.; Scholz, R.-D.; Reffert, S.; Yen, S. X.

2018-06-01

Context. The all-sky Milky Way Star Clusters (MWSC) survey provides uniform and precise ages, along with other relevant parameters, for a wide variety of clusters in the extended solar neighbourhood. Aims: In this study we aim to construct the cluster age distribution, investigate its spatial variations, and discuss constraints on cluster formation scenarios of the Galactic disk during the last 5 Gyrs. Methods: Due to the spatial extent of the MWSC, we have considered spatial variations of the age distribution along galactocentric radius RG, and along Z-axis. For the analysis of the age distribution we used 2242 clusters, which all lie within roughly 2.5 kpc of the Sun. To connect the observed age distribution to the cluster formation history we built an analytical model based on simple assumptions on the cluster initial mass function and on the cluster mass-lifetime relation, fit it to the observations, and determined the parameters of the cluster formation law. Results: Comparison with the literature shows that earlier results strongly underestimated the number of evolved clusters with ages t ≳ 100 Myr. Recent studies based on all-sky catalogues agree better with our data, but still lack the oldest clusters with ages t ≳ 1 Gyr. We do not observe a strong variation in the age distribution along RG, though we find an enhanced fraction of older clusters (t > 1 Gyr) in the inner disk. In contrast, the distribution strongly varies along Z. The high altitude distribution practically does not contain clusters with t < 1 Gyr. With simple assumptions on the cluster formation history, the cluster initial mass function and the cluster lifetime we can reproduce the observations. The cluster formation rate and the cluster lifetime are strongly degenerate, which does not allow us to disentangle different formation scenarios. In all cases the cluster formation rate is strongly declining with time, and the cluster initial mass function is very shallow at the high mass end.

A Polyphasic and Taxogenomic Evaluation Uncovers Arcobacter cryaerophilus as a Species Complex That Embraces Four Genomovars

PubMed Central

Pérez-Cataluña, Alba; Collado, Luis; Salgado, Oscar; Lefiñanco, Violeta; Figueras, María J.

2018-01-01

The species Arcobacter cryaerophilus is found in many food products of animal origin and is the dominating species in wastewater. In addition, it is associated with cases of farm animal and human infectious diseases,. The species embraces two subgroups i.e., 1A (LMG 24291T = LMG 9904T) and 1B (LMG 10829) that can be differentiated by their 16S rRNA-RFLP pattern. However, some authors, on the basis of the shared intermediate levels of DNA-DNA hybridization, have suggested abandoning the subgroup classification. This contradiction indicates that the taxonomy of this species is not yet resolved. The objective of the present study was to perform a taxonomic evaluation of the diversity of A. cryaerophilus. Genomic information was used along with a Multilocus Phylogenetic Analysis (MLPA) and phenotypic characterization on a group of 52 temporally and geographically dispersed strains, coming from different types of samples and hosts from nine countries. The MLPA analysis showed that those strains formed four clusters (I–IV). Values of Average Nucleotide Identity (ANI) and in silico DNA-DNA Hybridization (isDDH) obtained between 13 genomes representing strains of the four clusters were below the proposed cut-offs of 96 and 70%, respectively, confirming that each of the clusters represented a different genomic species. However, none of the evaluated phenotypic tests enabled their unequivocal differentiation into species. Therefore, the genomic delimited clusters should be considered genomovars of the species A. cryaerophilus. These genomovars could have different clinical importance, since only the cluster I included strains isolated from human specimens. The discovery of at least one stable distinctive phenotypic character would be needed to define each cluster or genomovar as a different species. Until then, we propose naming them “A. cryaerophilus gv. pseudocryaerophilus” (Cluster I = LMG 10229T), “A. cryaerophilus gv. crypticus” (Cluster II = LMG 9065T), “A. cryaerophilus gv. cryaerophilus” (Cluster III = LMG 24291T) and “A. cryaerophilus gv. occultus” (Cluster IV = LMG 29976T).

Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010.

PubMed

Jentsch, Franziska; Allen, Jennifer; Fuchs, Judith; von der Lippe, Elena

2017-04-04

Modifiable health risk factors (MHRFs) significantly affect morbidity and mortality rates and frequently occur in specific combinations or risk clusters. Using five MHRFs (smoking, high-risk alcohol consumption, physical inactivity, low intake of fruits and vegetables, and obesity) this study investigates the extent to which risk clusters are observed in a representative sample of women aged 65 and older in Germany. Additionally, the structural composition of the clusters is systematically compared with data and findings from other countries. A pooled data set of Germany's representative cross-sectional surveys GEDA09 and GEDA10 was used. The cohort comprised 4,617 women aged 65 and older. Specific risk clusters based on five MHRFs are identified, using hierarchical cluster analysis. The MHRFs were defined as current smoking (daily or occasionally), risk alcohol consumption (according to the Alcohol Use Disorders Identification Test, a sum score of 4 or more points), physical inactivity (less active than 5 days per week for at least 30 min and lack of sports-related activity in the last three months), low intake of fruits and vegetables (less than one serving of fruits and one of vegetables per day), and obesity (a body mass index equal to or greater than 30). A total of 4,292 cases with full information on these factors are included in the cluster analysis. Extended analyses were also performed to include the number of chronic diseases by age and socioeconomic status of group members. A total of seven risk clusters were identified. In a comparison with data from international studies, the seven risk clusters were found to be stable with a high degree of structural equivalency. Evidence of the stability of risk clusters across various study populations provides a useful starting point for long-term targeted health interventions. The structural clusters provide information through which various MHRFs can be evaluated simultaneously.

Ongoing outbreaks of hepatitis A among men who have sex with men (MSM), Berlin, November 2016 to January 2017 - linked to other German cities and European countries.

PubMed

Werber, Dirk; Michaelis, Kai; Hausner, Marius; Sissolak, Dagmar; Wenzel, Jürgen; Bitzegeio, Julia; Belting, Anne; Sagebiel, Daniel; Faber, Mirko

2017-02-02

Since 14 November 2016, 38 cases of hepatitis A have been notified in Berlin; of these, 37 were male and 30 reported to have sex with men (MSM). Median age of MSM cases is 31 years (range: 24-52 years). Phylogenetic analysis revealed three distinct sequences, linking cases in Berlin to those in other German cities and to clusters recognised in other European countries in 2016. This article is copyright of The Authors, 2017.

Ongoing outbreaks of hepatitis A among men who have sex with men (MSM), Berlin, November 2016 to January 2017 – linked to other German cities and European countries

PubMed Central

Werber, Dirk; Michaelis, Kai; Hausner, Marius; Sissolak, Dagmar; Wenzel, Jürgen; Bitzegeio, Julia; Belting, Anne; Sagebiel, Daniel; Faber, Mirko

2017-01-01

Since 14 November 2016, 38 cases of hepatitis A have been notified in Berlin; of these, 37 were male and 30 reported to have sex with men (MSM). Median age of MSM cases is 31 years (range: 24–52 years). Phylogenetic analysis revealed three distinct sequences, linking cases in Berlin to those in other German cities and to clusters recognised in other European countries in 2016. PMID:28183391

Implementation of spectral clustering on microarray data of carcinoma using k-means algorithm

NASA Astrophysics Data System (ADS)

Frisca, Bustamam, Alhadi; Siswantining, Titin

2017-03-01

Clustering is one of data analysis methods that aims to classify data which have similar characteristics in the same group. Spectral clustering is one of the most popular modern clustering algorithms. As an effective clustering technique, spectral clustering method emerged from the concepts of spectral graph theory. Spectral clustering method needs partitioning algorithm. There are some partitioning methods including PAM, SOM, Fuzzy c-means, and k-means. Based on the research that has been done by Capital and Choudhury in 2013, when using Euclidian distance k-means algorithm provide better accuracy than PAM algorithm. So in this paper we use k-means as our partition algorithm. The major advantage of spectral clustering is in reducing data dimension, especially in this case to reduce the dimension of large microarray dataset. Microarray data is a small-sized chip made of a glass plate containing thousands and even tens of thousands kinds of genes in the DNA fragments derived from doubling cDNA. Application of microarray data is widely used to detect cancer, for the example is carcinoma, in which cancer cells express the abnormalities in his genes. The purpose of this research is to classify the data that have high similarity in the same group and the data that have low similarity in the others. In this research, Carcinoma microarray data using 7457 genes. The result of partitioning using k-means algorithm is two clusters.

Spatiotemporal clusters of malaria cases at village level, northwest Ethiopia.

PubMed

Alemu, Kassahun; Worku, Alemayehu; Berhane, Yemane; Kumie, Abera

2014-06-06

Malaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions. Spatial scan statistics using the Bernoulli method were employed to identify spatial and temporal clusters of malaria in high-altitude villages. Daily malaria data were collected, using a passive surveillance system, from patients visiting local health facilities. Georeference data were collected at villages using hand-held global positioning system devices and linked to patient data. Bernoulli model using Bayesian approaches and Marcov Chain Monte Carlo (MCMC) methods were used to identify the effects of factors on spatial clusters of malaria cases. The deviance information criterion (DIC) was used to assess the goodness-of-fit of the different models. The smaller the DIC, the better the model fit. Malaria cases were clustered in both space and time in high-altitude villages. Spatial scan statistics identified a total of 56 spatial clusters of malaria in high-altitude villages. Of these, 39 were the most likely clusters (LLR = 15.62, p < 0.00001) and 17 were secondary clusters (LLR = 7.05, p < 0.03). The significant most likely temporal malaria clusters were detected between August and December (LLR = 17.87, p < 0.001). Travel away home, males and age above 15 years had statistically significant effect on malaria clusters at high-altitude villages. The study identified spatial clusters of malaria cases occurring at high elevation villages within the district. A patient who travelled away from home to a malaria-endemic area might be the most probable source of malaria infection in a high-altitude village. Malaria interventions in high altitude villages should address factors associated with malaria clustering.

Focal cortical malformations in children with early infantile epilepsy and PCDH19 mutations: case report.

PubMed

Kurian, Mary; Korff, Christian M; Ranza, Emmanuelle; Bernasconi, Andrea; Lübbig, Anja; Nangia, Srishti; Ramelli, Gian Paolo; Wohlrab, Gabriele; Nordli, Douglas R; Bast, Thomas

2018-01-01

In this case report we assess the occurrence of cortical malformations in children with early infantile epilepsy associated with variants of the gene protocadherin 19 (PCDH19). We describe the clinical course, and electrographic, imaging, genetic, and neuropathological features in a cohort of female children with pharmacoresistant epilepsy. All five children (mean age 10y) had an early onset of epilepsy during infancy and a predominance of fever sensitive seizures occurring in clusters. Cognitive impairment was noted in four out of five patients. Radiological evidence of cortical malformations was present in all cases and, in two patients, validated by histology. Sanger sequencing and Multiplex Ligation-dependent Probe Amplification analysis of PCDH19 revealed pathogenic variants in four patients. In one patient, array comparative genomic hybridization showed a microdeletion encompassing PCDH19. We propose molecular testing and analysis of PCDH19 in patients with pharmacoresistant epilepsy, with onset in early infancy, seizures in clusters, and fever sensitivity. Structural lesions are to be searched in patients with PCDH19 pathogenic variants. Further, PCDH19 analysis should be considered in epilepsy surgery evaluation even in the presence of cerebral structural lesions. Focal cortical malformations and monogenic epilepsy syndromes may coexist. Structural lesions are to be searched for in patients with protocadherin 19 (PCDH19) pathogenic variants with refractory focal seizures. © 2017 Mac Keith Press.

Molecular epidemiology of tuberculosis after declining incidence, New York City, 2001-2003.

PubMed

Driver, C R; Kreiswirth, B; Macaraig, M; Clark, C; Munsiff, S S; Driscoll, J; Zhao, B

2007-05-01

Tuberculosis incidence in New York City (NYC) declined between 1992 and 2000 from 51.1 to 16.6 cases per 100,000 population. In January 2001, universal real-time genotyping of TB cases was implemented in NYC. Isolates from culture-confirmed tuberculosis cases from 2001 to 2003 were genotyped using IS6110 and spoligotype to describe the extent and factors associated with genotype clustering after declining TB incidence. Of 2408 (91.8%) genotyped case isolates, 873 (36.2%) had a pattern indistinguishable from that of another study period case, forming 212 clusters; 248 (28.4%) of the clustered cases had strains believed to have been widely transmitted during the epidemic years in the early 1990s in NYC. An estimated 27.4% (873 minus 212) of the 2408 cases were due to recent infection that progressed to active disease during the study period. Younger age, birth in the United States, homelessness, substance abuse and presence of TB symptoms were independently associated with greater odds of clustering.

Effect of Active Case Finding on Prevalence and Transmission of Pulmonary Tuberculosis in Dhaka Central Jail, Bangladesh

PubMed Central

Banu, Sayera; Rahman, Md. Toufiq; Uddin, Mohammad Khaja Mafij; Khatun, Razia; Khan, Md. Siddiqur Rahman; Rahman, Md. Mojibur; Uddin, Syed Iftekhar; Ahmed, Tahmeed; Heffelfinger, James D.

2015-01-01

Background Understanding tuberculosis (TB) transmission dynamics is essential for establishing effective TB control strategies in settings where the burden and risk of transmission are high. The objectives of this study were to evaluate the effect of active screening on controlling TB transmission and also to characterize Mycobacterium tuberculosis strains for investigating transmission dynamics in a correctional setting. Methods The study was carried out in Dhaka Central Jail (DCJ), from October 2005 to February 2010. An active case finding strategy for pulmonary TB was established both at the entry point to the prison and inside the prison. Three sputum specimens were collected from all pulmonary TB suspects and subjected to smear microscopy, culture, and drug susceptibility testing as well as genotyping which included deletion analysis, spoligotyping and analysis of mycobacterial interspersed repetitive units (MIRU). Results A total of 60,585 inmates were screened during the study period. We found 466 inmates with pulmonary TB of whom 357 (77%) had positive smear microscopy results and 109 (23%) had negative smear microscopy results but had positive results on culture. The number of pulmonary TB cases declined significantly, from 49 cases during the first quarter to 8 cases in the final quarter of the study period (p=0.001). Deletion analysis identified all isolates as M. tuberculosis and further identified 229 (70%) strains as ‘modern’ and 100 (30%) strains as ‘ancestral’. Analysis of MIRU showed that 347 strains (85%) exhibited unique patterns, whereas 61 strains (15%) clustered into 22 groups. The largest cluster comprised eight strains of the Beijing M. tuberculosis type. The rate of recent transmission was estimated to be 9.6%. Conclusions Implementation of active screening for TB was associated with a decline in TB cases in DCJ. Implementation of active screening in prison settings might substantially reduce the national burden of TB in Bangladesh. PMID:25933377

Effect of active case finding on prevalence and transmission of pulmonary tuberculosis in Dhaka Central Jail, Bangladesh.

PubMed

Banu, Sayera; Rahman, Md Toufiq; Uddin, Mohammad Khaja Mafij; Khatun, Razia; Khan, Md Siddiqur Rahman; Rahman, Md Mojibur; Uddin, Syed Iftekhar; Ahmed, Tahmeed; Heffelfinger, James D

2015-01-01

Understanding tuberculosis (TB) transmission dynamics is essential for establishing effective TB control strategies in settings where the burden and risk of transmission are high. The objectives of this study were to evaluate the effect of active screening on controlling TB transmission and also to characterize Mycobacterium tuberculosis strains for investigating transmission dynamics in a correctional setting. The study was carried out in Dhaka Central Jail (DCJ), from October 2005 to February 2010. An active case finding strategy for pulmonary TB was established both at the entry point to the prison and inside the prison. Three sputum specimens were collected from all pulmonary TB suspects and subjected to smear microscopy, culture, and drug susceptibility testing as well as genotyping which included deletion analysis, spoligotyping and analysis of mycobacterial interspersed repetitive units (MIRU). A total of 60,585 inmates were screened during the study period. We found 466 inmates with pulmonary TB of whom 357 (77%) had positive smear microscopy results and 109 (23%) had negative smear microscopy results but had positive results on culture. The number of pulmonary TB cases declined significantly, from 49 cases during the first quarter to 8 cases in the final quarter of the study period (p=0.001). Deletion analysis identified all isolates as M. tuberculosis and further identified 229 (70%) strains as 'modern' and 100 (30%) strains as 'ancestral'. Analysis of MIRU showed that 347 strains (85%) exhibited unique patterns, whereas 61 strains (15%) clustered into 22 groups. The largest cluster comprised eight strains of the Beijing M. tuberculosis type. The rate of recent transmission was estimated to be 9.6%. Implementation of active screening for TB was associated with a decline in TB cases in DCJ. Implementation of active screening in prison settings might substantially reduce the national burden of TB in Bangladesh.

Automated modal parameter estimation using correlation analysis and bootstrap sampling

NASA Astrophysics Data System (ADS)

Yaghoubi, Vahid; Vakilzadeh, Majid K.; Abrahamsson, Thomas J. S.

2018-02-01

The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods have been developed to automate this procedure. The common approach is to identify models with different orders and cluster similar modes together. However, most proposed methods based on this approach suffer from high-dimensional optimization problems in either the estimation or clustering step. To overcome this problem, this study presents an algorithm for autonomous modal parameter estimation in which the only required optimization is performed in a three-dimensional space. To this end, a subspace-based identification method is employed for the estimation and a non-iterative correlation-based method is used for the clustering. This clustering is at the heart of the paper. The keys to success are correlation metrics that are able to treat the problems of spatial eigenvector aliasing and nonunique eigenvectors of coalescent modes simultaneously. The algorithm commences by the identification of an excessively high-order model from frequency response function test data. The high number of modes of this model provides bases for two subspaces: one for likely physical modes of the tested system and one for its complement dubbed the subspace of noise modes. By employing the bootstrap resampling technique, several subsets are generated from the same basic dataset and for each of them a model is identified to form a set of models. Then, by correlation analysis with the two aforementioned subspaces, highly correlated modes of these models which appear repeatedly are clustered together and the noise modes are collected in a so-called Trashbox cluster. Stray noise modes attracted to the mode clusters are trimmed away in a second step by correlation analysis. The final step of the algorithm is a fuzzy c-means clustering procedure applied to a three-dimensional feature space to assign a degree of physicalness to each cluster. The proposed algorithm is applied to two case studies: one with synthetic data and one with real test data obtained from a hammer impact test. The results indicate that the algorithm successfully clusters similar modes and gives a reasonable quantification of the extent to which each cluster is physical.

Classification of microvascular patterns via cluster analysis reveals their prognostic significance in glioblastoma.

PubMed

Chen, Long; Lin, Zhi-Xiong; Lin, Guo-Shi; Zhou, Chang-Fu; Chen, Yu-Peng; Wang, Xing-Fu; Zheng, Zong-Qing

2015-01-01

There are limited researches focusing on microvascular patterns (MVPs) in human glioblastoma and their prognostic impact. We evaluated MVPs of 78 glioblastomas by CD34/periodic acid-Schiff dual staining and by cluster analysis of the percentage of microvascular area for distinct microvascular formations. The distribution of 5 types of basic microvascular formations, that is, microvascular sprouting (MS), vascular cluster (VC), vascular garland (VG), glomeruloid vascular proliferation (GVP), and vasculogenic mimicry (VM), was variable. Accordingly, cluster analysis classified MVPs into 2 types: type I MVP displayed prominent MSs and VCs, whereas type II MVP had numerous VGs, GVPs, and VMs. By analyzing the proportion of microvascular area for each type of formation, we determined that glioblastomas with few MSs and VCs had many GVPs and VMs, and vice versa. VG seemed to be a transitional type of formation. In case of type I MVP, expression of Ki-67 and p53 but not MGMT was significantly higher as compared with those of type II MVP (P < .05). Survival analysis showed that the type of MVPs presented as an independent prognostic factor of progression-free survival (PFS) and overall survival (OS) (both P < .001). Type II MVP had a more negative influence on PFS and OS than did type I MVP. We conclude that the heterogeneous MVPs in glioblastoma can be categorized properly by certain histopathologic and statistical analyses and may influence clinical outcome. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Extending the Functionality of Behavioural Change-Point Analysis with k-Means Clustering: A Case Study with the Little Penguin (Eudyptula minor)

PubMed Central

Zhang, Jingjing; Dennis, Todd E.

2015-01-01

We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known ‘artificial behaviours’ comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified. PMID:25922935

Extending the Functionality of Behavioural Change-Point Analysis with k-Means Clustering: A Case Study with the Little Penguin (Eudyptula minor).

PubMed

Zhang, Jingjing; O'Reilly, Kathleen M; Perry, George L W; Taylor, Graeme A; Dennis, Todd E

2015-01-01

We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known 'artificial behaviours' comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified.

Social deprivation and population density are not associated with small area risk of amyotrophic lateral sclerosis.

PubMed

Rooney, James P K; Tobin, Katy; Crampsie, Arlene; Vajda, Alice; Heverin, Mark; McLaughlin, Russell; Staines, Anthony; Hardiman, Orla

2015-10-01

Evidence of an association between areal ALS risk and population density has been previously reported. We aim to examine ALS spatial incidence in Ireland using small areas, to compare this analysis with our previous analysis of larger areas and to examine the associations between population density, social deprivation and ALS incidence. Residential area social deprivation has not been previously investigated as a risk factor for ALS. Using the Irish ALS register, we included all cases of ALS diagnosed in Ireland from 1995-2013. 2006 census data was used to calculate age and sex standardised expected cases per small area. Social deprivation was assessed using the pobalHP deprivation index. Bayesian smoothing was used to calculate small area relative risk for ALS, whilst cluster analysis was performed using SaTScan. The effects of population density and social deprivation were tested in two ways: (1) as covariates in the Bayesian spatial model; (2) via post-Bayesian regression. 1701 cases were included. Bayesian smoothed maps of relative risk at small area resolution matched closely to our previous analysis at a larger area resolution. Cluster analysis identified two areas of significant low risk. These areas did not correlate with population density or social deprivation indices. Two areas showing low frequency of ALS have been identified in the Republic of Ireland. These areas do not correlate with population density or residential area social deprivation, indicating that other reasons, such as genetic admixture may account for the observed findings. Copyright © 2015 Elsevier Inc. All rights reserved.

Echovirus 15 and autumn meningitis outbreak among children, Patras, Greece, 2005.

PubMed

Frantzidou, Filanthi; Dumaidi, Kamal; Spiliopoulou, Adamantia; Antoniadis, Antonis; Papa, Anna

2007-09-01

Enteroviruses are the most common cause of aseptic meningitis, presenting in epidemic or endemic form. To determine the causative agent of an aseptic meningitis outbreak in autumn, 2005 in Patras, Greece. Cerebrospinal fluid (CSF) samples taken during May 2005-February 2006 from children admitted to the Children Hospital of Patras with signs of aseptic meningitis were tested for the presence of enteroviral RNA. Typing was performed by nucleotide analysis. Enteroviruses were detected in 11 (57.9%) of 19 tested CSF samples. In a 12-day period (27 October-7 November 2005) five aseptic meningitis cases were observed. Echovirus 15 was detected in all five cases, and differed from the prototype strain by 27.6%. Enteroviruses before and after this cluster of cases were of different serotypes (Echovirus 9, Echovirus 6). All patients with Echovirus 15 infection were male with a mean age of 7.7 years (2 months-13 years), all recovered successfully. This is the first report of a cluster of aseptic meningitis cases caused by Echovirus 15. The causative agent was a new variant of Echovirus 15.

Admixture in Humans of Two Divergent Plasmodium knowlesi Populations Associated with Different Macaque Host Species

PubMed Central

Divis, Paul C. S.; Singh, Balbir; Anderios, Fread; Hisam, Shamilah; Matusop, Asmad; Kocken, Clemens H.; Assefa, Samuel A.; Duffy, Craig W.; Conway, David J.

2015-01-01

Human malaria parasite species were originally acquired from other primate hosts and subsequently became endemic, then spread throughout large parts of the world. A major zoonosis is now occurring with Plasmodium knowlesi from macaques in Southeast Asia, with a recent acceleration in numbers of reported cases particularly in Malaysia. To investigate the parasite population genetics, we developed sensitive and species-specific microsatellite genotyping protocols and applied these to analysis of samples from 10 sites covering a range of >1,600 km within which most cases have occurred. Genotypic analyses of 599 P. knowlesi infections (552 in humans and 47 in wild macaques) at 10 highly polymorphic loci provide radical new insights on the emergence. Parasites from sympatric long-tailed macaques (Macaca fascicularis) and pig-tailed macaques (M. nemestrina) were very highly differentiated (FST = 0.22, and K-means clustering confirmed two host-associated subpopulations). Approximately two thirds of human P. knowlesi infections were of the long-tailed macaque type (Cluster 1), and one third were of the pig-tailed-macaque type (Cluster 2), with relative proportions varying across the different sites. Among the samples from humans, there was significant indication of genetic isolation by geographical distance overall and within Cluster 1 alone. Across the different sites, the level of multi-locus linkage disequilibrium correlated with the degree of local admixture of the two different clusters. The widespread occurrence of both types of P. knowlesi in humans enhances the potential for parasite adaptation in this zoonotic system. PMID:26020959

Evidence from Molecular Fingerprinting of Limited Spread of Drug-Resistant Tuberculosis in Texas

PubMed Central

Wilson, Rebecca W.; Yang, Zhenhua; Kelley, Michael; Cave, M. Donald; Pogoda, Janice M.; Wallace, Richard J.; Cegielski, J. Peter; Dunbar, Denise F.; Bergmire-Sweat, David; Elliott, L. Bruce; Barnes, Peter F.

1999-01-01

To determine the contribution of recent transmission to spread of drug-resistant tuberculosis in Texas, we performed IS6110-based and pTBN12-based restriction fragment length polymorphism (RFLP) analyses on Mycobacterium tuberculosis isolates. Isolates collected from 201 patients in Texas between 1992 and 1994 were studied. The distribution of cases was strikingly focal. All cases were reported from 35 of the 254 counties in Texas, and 74% (148 of 201) were reported from only 9 counties. One hundred sixty-one (80%) of the patients had M. tuberculosis isolates with unique RFLP patterns, and 41 (20%) patients were in 20 clusters, each comprising 2 to 3 patients. The largest number of cases of drug-resistant tuberculosis were reported in counties bordering Mexico, but the percentage of clustered cases was highest in northeast Texas and in counties that included the cities of Dallas, Fort Worth, and Houston. Compared to nonclustered patients, clustered patients were more likely to be African American and to have been born in the United States. Clustered patients were significantly more likely to be from the same geographic area, and clustered patients from the same geographic area were more likely to have isolates with identical drug susceptibility patterns, suggesting that they were linked by recent transmission. In 11 of 20 clusters, clustered patients were from geographically separate regions, and most isolates did not have identical drug susceptibility patterns, suggesting that tuberculosis was contracted from a common source in the remote past. Based on the low percentage of clustered cases and the small cluster size, we conclude that there is no evidence for the extensive transmission of drug-resistant tuberculosis in Texas. PMID:10488188

Individual factors associated with L- and H-type Bovine Spongiform Encephalopathy in France

PubMed Central

2012-01-01

Background Cattle with L-type (L-BSE) and H-type (H-BSE) atypical Bovine Spongiform encephalopathy (BSE) were identified in 2003 in Italy and France respectively before being identified in other countries worldwide. As of December 2011, around 60 atypical BSE cases have currently been reported in 13 countries, with over one third in France. While the epidemiology of classical BSE (C-BSE) has been widely described, atypical BSEs are still poorly documented, but appear to differ from C-BSE. We analysed the epidemiological characteristics of the 12 cases of L-BSE and 11 cases of H-BSE detected in France from January 2001 to late 2009 and looked for individual risk factors. As L-BSE cases did not appear to be homogeneously distributed throughout the country, two complementary methods were used: spatial analysis and regression modelling. L-BSE and H-BSE were studied separately as both the biochemical properties of their pathological prion protein and their features differ in animal models. Results The median age at detection for L-BSE and H-BSE cases was 12.4 (range 8.4-18.7) and 12.5 (8.3-18.2) years respectively, with no significant difference between the two distributions. However, this median age differed significantly from that of classical BSE (7.0 (range 3.5-15.4) years). A significant geographical cluster was detected for L-BSE. Among animals over eight years of age, we showed that the risk of being detected as a L-BSE case increased with age at death. This was not the case for H-BSE. Conclusion To the best of our knowledge this is the first study to describe the epidemiology of the two types of atypical BSE. The geographical cluster detected for L-BSE could be partly due to the age structure of the background-tested bovine population. Our regression analyses, which adjusted for the effect of age and birth cohort showed an age effect for L-BSE and the descriptive analysis showed a particular age structure in the area where the cluster was detected. No birth cohort effect was evident. The relatively small number of cases of atypical BSE and the few individual data available for the tested population limited our analysis to the investigation of age and cohort effect only. We conclude that it is essential to maintain BSE surveillance to further elucidate our findings. PMID:22647660

Spatial and Temporal Distribution of Tuberculosis in the State of Mexico, Mexico

PubMed Central

Zaragoza Bastida, Adrian; Hernández Tellez, Marivel; Bustamante Montes, Lilia P.; Medina Torres, Imelda; Jaramillo Paniagua, Jaime Nicolás; Mendoza Martínez, Germán David; Ramírez Durán, Ninfa

2012-01-01

Tuberculosis (TB) is one of the oldest human diseases that still affects large population groups. According to the World Health Organization (WHO), there were approximately 9.4 million new cases worldwide in the year 2010. In Mexico, there were 18,848 new cases of TB of all clinical variants in 2010. The identification of clusters in space-time is of great interest in epidemiological studies. The objective of this research was to identify the spatial and temporal distribution of TB during the period 2006–2010 in the State of Mexico, using geographic information system (GIS) and SCAN statistics program. Nine significant clusters (P < 0.05) were identified using spatial and space-time analysis. The conclusion is that TB in the State of Mexico is not randomly distributed but is concentrated in areas close to Mexico City. PMID:22919337

Nationwide analysis on the impact of socioeconomic land use factors and incidence of urothelial carcinoma.

PubMed

Brandt, Maximilian P; Gust, Kilian M; Mani, Jens; Vallo, Stefan; Höfner, Thomas; Borgmann, Hendrik; Tsaur, Igor; Thomas, Christian; Haferkamp, Axel; Herrmann, Eva; Bartsch, Georg

2018-02-01

Incidence rates for urothelial carcinoma (UC) have been reported to differ between countries within the European Union (EU). Besides occupational exposure to chemicals, other substances such as tobacco and nitrite in groundwater have been identified as risk factors for UC. We investigated if regional differences in UC incidence rates are associated with agricultural, industrial and residential land use. Newly diagnosed cases of UC between 2003 and 2010 were included. Information within 364 administrative districts of Germany from 2004 for land use factors were obtained and calculated as a proportion of the total area of the respective administrative district and as a smoothed proportion. Furthermore, information on smoking habits was included in our analysis. Kulldorff spatial clustering was used to detect different clusters. A negative binomial model was used to test the spatial association between UC incidence as a ratio of observed versus expected incidence rates, land use and smoking habits. We identified 437,847,834 person years with 171,086 cases of UC. Cluster analysis revealed areas with higher incidence of UC than others (p=0.0002). Multivariate analysis including significant pairwise interactions showed that the environmental factors were independently associated with UC (p<0.001). The RR was 1.066 (95% CI 1.052-1.080), 1.066 (95% CI 1.042-1.089) and 1.067 (95% CI 1.045-1.093) for agricultural, industrial and residential areas, respectively, and 0.996 (95% CI 0.869-0.999) for the proportion of never smokers. This study displays regional differences in incidence of UC in Germany. Additionally, results suggest that socioeconomic factors based on agricultural, industrial and residential land use may be associated with UC incidence rates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Space and space-time distributions of dengue in a hyper-endemic urban space: the case of Girardot, Colombia.

PubMed

Fuentes-Vallejo, Mauricio

2017-07-24

Dengue is a widely spread vector-borne disease. Dengue cases in the Americas have increased over the last few decades, affecting various urban spaces throughout these continents, including the tourism-oriented city of Girardot, Colombia. Interactions among mosquitoes, pathogens and humans have recently been examined using different temporal and spatial scales in attempts to determine the roles that social and ecological systems play in dengue transmission. The current work characterizes the spatial and temporal behaviours of dengue in Girardot and discusses the potential territorial dynamics related to the distribution of this disease. Based on officially reported dengue cases (2012-2015) corresponding to epidemic (2013) and inter-epidemic years (2012, 2014, 2015), space (Getis-Ord index) and space-time (Kulldorff's scan statistics) analyses were performed. Geocoded dengue cases (n = 2027) were slightly overrepresented by men (52.1%). As expected, the cases were concentrated in the 0- to 15-year-old age group according to the actual trends of Colombia. The incidence rates of dengue during the rainy and dry seasons as well as those for individual years (2012, 2013 and 2014) were significant using the global Getis-Ord index. Local clusters shifted across seasons and years; nevertheless, the incidence rates clustered towards the southwest region of the city under different residential conditions. Space-time clusters shifted from the northeast to the southwest of the city (2012-2014). These clusters represented only 4.25% of the total cases over the same period (n = 1623). A general trend was observed, in which dengue cases increased during the dry seasons, especially between December and February. Despite study limitations related to official dengue records and available fine-scale demographic information, the spatial analysis results were promising from a geography of health perspective. Dengue did not show linear association with poverty or with vulnerable peripheral spaces in intra-urban settings, supporting the idea that the pathogenic complex of dengue is driven by different factors. A coordinated collaboration of epidemiological, public health and social science expertise is needed to assess the effect of "place" from a relational perspective in which geography has an important role to play.

Altitude as a risk factor for the development of hypospadias. Geographical cluster distribution analysis in South America.

PubMed

Fernández, Nicolas; Lorenzo, Armando; Bägli, Darius; Zarante, Ignacio

2016-10-01

Hypospadias is the most common congenital anomaly affecting the genitals. It has been established as a multifactorial disease with increasing prevalence. Many risk factors have been identified such as prematurity, birth weight, mother's age, and exposure to endocrine disruptors. In recent decades multiple authors using surveillance systems have described an increase in prevalence of hypospadias, but most of the published literature comes from developed countries in Europe and North America and few of the published studies have involved cluster analysis. Few large-scale studies have been performed addressing the effect of altitude and other geographical aspects on the development of hypospadias. Acknowledging this limitation, we present novel results of a multinational spatial scan statistical analysis over a 30-year period in South America and an altitude analysis of hypospadias distribution on a continent level. A retrospective review was performed of the Latin American collaborative study of congenital malformations (ECLAMC). A total of 4,020,384 newborns was surveyed between 1982 and December 2011 in all participating centers. We selected all patients with hypospadias. All degrees of clinical severity were included in the analysis. Each participating center was geographically identified with its coordinates and altitude above sea level. A spatial scan statistical analysis was performed using Kulldorf's methodology and a prevalence trend analysis over time in centers below and above 2000 m. During the study period we found 159 hospitals in six different countries (Colombia, Bolivia, Brazil, Argentina, Chile, and Uruguay) with 4,537 cases of hypospadias and a global prevalence rate of 11.3/10,000 newborns. Trend analysis showed that centers below 2000 m had an increasing trend with an average of 10/10,000 newborns as opposed to those centers above 2000 m that showed a reducing trend with an average prevalence of 7.8 (p = 0.1246). We identified clusters with significant increases of prevalence in five centers along the coast at an average altitude of 219.8 m above sea level (p > 0.0000). Reduction in prevalence was found in clusters located in two centers on the Andes mountains. Altitude of 2,000 m was associated with hypospadias (Figure), with an OR 0.59 (0.5-0.69). There are ethnic arguments to support our results supported by protective polymorphism distribution in high lands. Altitude above 2,000 m is suggested to have a protective effect for hypospadias. Specific clusters have been identified with increased risk for hypospadias. Environmental risk factors in these areas need to be further studied given the association seen between altitude and the distribution of more severe cases. Copyright © 2016 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Integration K-Means Clustering Method and Elbow Method For Identification of The Best Customer Profile Cluster

NASA Astrophysics Data System (ADS)

Syakur, M. A.; Khotimah, B. K.; Rochman, E. M. S.; Satoto, B. D.

2018-04-01

Clustering is a data mining technique used to analyse data that has variations and the number of lots. Clustering was process of grouping data into a cluster, so they contained data that is as similar as possible and different from other cluster objects. SMEs Indonesia has a variety of customers, but SMEs do not have the mapping of these customers so they did not know which customers are loyal or otherwise. Customer mapping is a grouping of customer profiling to facilitate analysis and policy of SMEs in the production of goods, especially batik sales. Researchers will use a combination of K-Means method with elbow to improve efficient and effective k-means performance in processing large amounts of data. K-Means Clustering is a localized optimization method that is sensitive to the selection of the starting position from the midpoint of the cluster. So choosing the starting position from the midpoint of a bad cluster will result in K-Means Clustering algorithm resulting in high errors and poor cluster results. The K-means algorithm has problems in determining the best number of clusters. So Elbow looks for the best number of clusters on the K-means method. Based on the results obtained from the process in determining the best number of clusters with elbow method can produce the same number of clusters K on the amount of different data. The result of determining the best number of clusters with elbow method will be the default for characteristic process based on case study. Measurement of k-means value of k-means has resulted in the best clusters based on SSE values on 500 clusters of batik visitors. The result shows the cluster has a sharp decrease is at K = 3, so K as the cut-off point as the best cluster.

The spatial heterogeneity between Japanese encephalitis incidence distribution and environmental variables in Nepal.

PubMed

Impoinvil, Daniel E; Solomon, Tom; Schluter, W William; Rayamajhi, Ajit; Bichha, Ram Padarath; Shakya, Geeta; Caminade, Cyril; Baylis, Matthew

2011-01-01

To identify potential environmental drivers of Japanese Encephalitis virus (JE) transmission in Nepal, we conducted an ecological study to determine the spatial association between 2005 Nepal JE incidence, and climate, agricultural, and land-cover variables at district level. District-level data on JE cases were examined using Local Indicators of Spatial Association (LISA) analysis to identify spatial clusters from 2004 to 2008 and 2005 data was used to fit a spatial lag regression model with climate, agriculture and land-cover variables. Prior to 2006, there was a single large cluster of JE cases located in the Far-West and Mid-West terai regions of Nepal. After 2005, the distribution of JE cases in Nepal shifted with clusters found in the central hill areas. JE incidence during the 2005 epidemic had a stronger association with May mean monthly temperature and April mean monthly total precipitation compared to mean annual temperature and precipitation. A parsimonious spatial lag regression model revealed, 1) a significant negative relationship between JE incidence and April precipitation, 2) a significant positive relationship between JE incidence and percentage of irrigated land 3) a non-significant negative relationship between JE incidence and percentage of grassland cover, and 4) a unimodal non-significant relationship between JE Incidence and pig-to-human ratio. JE cases clustered in the terai prior to 2006 where it seemed to shift to the Kathmandu region in subsequent years. The spatial pattern of JE cases during the 2005 epidemic in Nepal was significantly associated with low precipitation and the percentage of irrigated land. Despite the availability of an effective vaccine, it is still important to understand environmental drivers of JEV transmission since the enzootic cycle of JEV transmission is not likely to be totally interrupted. Understanding the spatial dynamics of JE risk factors may be useful in providing important information to the Nepal immunization program.

The Spatial Heterogeneity between Japanese Encephalitis Incidence Distribution and Environmental Variables in Nepal

PubMed Central

Impoinvil, Daniel E.; Solomon, Tom; Schluter, W. William; Rayamajhi, Ajit; Bichha, Ram Padarath; Shakya, Geeta; Caminade, Cyril; Baylis, Matthew

2011-01-01

Background To identify potential environmental drivers of Japanese Encephalitis virus (JE) transmission in Nepal, we conducted an ecological study to determine the spatial association between 2005 Nepal JE incidence, and climate, agricultural, and land-cover variables at district level. Methods District-level data on JE cases were examined using Local Indicators of Spatial Association (LISA) analysis to identify spatial clusters from 2004 to 2008 and 2005 data was used to fit a spatial lag regression model with climate, agriculture and land-cover variables. Results Prior to 2006, there was a single large cluster of JE cases located in the Far-West and Mid-West terai regions of Nepal. After 2005, the distribution of JE cases in Nepal shifted with clusters found in the central hill areas. JE incidence during the 2005 epidemic had a stronger association with May mean monthly temperature and April mean monthly total precipitation compared to mean annual temperature and precipitation. A parsimonious spatial lag regression model revealed, 1) a significant negative relationship between JE incidence and April precipitation, 2) a significant positive relationship between JE incidence and percentage of irrigated land 3) a non-significant negative relationship between JE incidence and percentage of grassland cover, and 4) a unimodal non-significant relationship between JE Incidence and pig-to-human ratio. Conclusion JE cases clustered in the terai prior to 2006 where it seemed to shift to the Kathmandu region in subsequent years. The spatial pattern of JE cases during the 2005 epidemic in Nepal was significantly associated with low precipitation and the percentage of irrigated land. Despite the availability of an effective vaccine, it is still important to understand environmental drivers of JEV transmission since the enzootic cycle of JEV transmission is not likely to be totally interrupted. Understanding the spatial dynamics of JE risk factors may be useful in providing important information to the Nepal immunization program. PMID:21811573

Social phobia subtypes in the general population revealed by cluster analysis.

PubMed

Furmark, T; Tillfors, M; Stattin, H; Ekselius, L; Fredrikson, M

2000-11-01

Epidemiological data on subtypes of social phobia are scarce and their defining features are debated. Hence, the present study explored the prevalence and descriptive characteristics of empirically derived social phobia subgroups in the general population. To reveal subtypes, data on social distress, functional impairment, number of social fears and criteria fulfilled for avoidant personality disorder were extracted from a previously published epidemiological study of 188 social phobics and entered into an hierarchical cluster analysis. Criterion validity was evaluated by comparing clusters on the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS). Finally, profile analyses were performed in which clusters were compared on a set of sociodemographic and descriptive characteristics. Three clusters emerged, consisting of phobics scoring either high (generalized subtype), intermediate (non-generalized subtype) or low (discrete subtype) on all variables. Point prevalence rates were 2.0%, 5.9% and 7.7% respectively. All subtypes were distinguished on both SPS and SIAS. Generalized or severe social phobia tended to be over-represented among individuals with low levels of educational attainment and social support. Overall, public-speaking was the most common fear. Although categorical distinctions may be used, the present data suggest that social phobia subtypes in the general population mainly differ dimensionally along a mild moderate-severe continuum, and that the number of cases declines with increasing severity.

Genotyping and spatial analysis of pulmonary tuberculosis and diabetes cases in the state of Veracruz, Mexico.

PubMed

Blanco-Guillot, Francles; Castañeda-Cediel, M Lucía; Cruz-Hervert, Pablo; Ferreyra-Reyes, Leticia; Delgado-Sánchez, Guadalupe; Ferreira-Guerrero, Elizabeth; Montero-Campos, Rogelio; Bobadilla-Del-Valle, Miriam; Martínez-Gamboa, Rosa Areli; Torres-González, Pedro; Téllez-Vazquez, Norma; Canizales-Quintero, Sergio; Yanes-Lane, Mercedes; Mongua-Rodríguez, Norma; Ponce-de-León, Alfredo; Sifuentes-Osornio, José; García-García, Lourdes

2018-01-01

Genotyping and georeferencing in tuberculosis (TB) have been used to characterize the distribution of the disease and occurrence of transmission within specific groups and communities. The objective of this study was to test the hypothesis that diabetes mellitus (DM) and pulmonary TB may occur in spatial and molecular aggregations. Retrospective cohort study of patients with pulmonary TB. The study area included 12 municipalities in the Sanitary Jurisdiction of Orizaba, Veracruz, México. Patients with acid-fast bacilli in sputum smears and/or Mycobacterium tuberculosis in sputum cultures were recruited from 1995 to 2010. Clinical (standardized questionnaire, physical examination, chest X-ray, blood glucose test and HIV test), microbiological, epidemiological, and molecular evaluations were carried out. Patients were considered "genotype-clustered" if two or more isolates from different patients were identified within 12 months of each other and had six or more IS6110 bands in an identical pattern, or < 6 bands with identical IS6110 RFLP patterns and spoligotype with the same spacer oligonucleotides. Residential and health care centers addresses were georeferenced. We used a Jeep hand GPS. The coordinates were transferred from the GPS files to ArcGIS using ArcMap 9.3. We evaluated global spatial aggregation of patients in IS6110-RFLP/ spoligotype clusters using global Moran´s I. Since global distribution was not random, we evaluated "hotspots" using Getis-Ord Gi* statistic. Using bivariate and multivariate analysis we analyzed sociodemographic, behavioral, clinic and bacteriological conditions associated with "hotspots". We used STATA® v13.1 for all statistical analysis. From 1995 to 2010, 1,370 patients >20 years were diagnosed with pulmonary TB; 33% had DM. The proportion of isolates that were genotyped was 80.7% (n = 1105), of which 31% (n = 342) were grouped in 91 genotype clusters with 2 to 23 patients each; 65.9% of total clusters were small (2 members) involving 35.08% of patients. Twenty three (22.7) percent of cases were classified as recent transmission. Moran`s I indicated that distribution of patients in IS6110-RFLP/spoligotype clusters was not random (Moran`s I = 0.035468, Z value = 7.0, p = 0.00). Local spatial analysis showed statistically significant spatial aggregation of patients in IS6110-RFLP/spoligotype clusters identifying "hotspots" and "coldspots". GI* statistic showed that the hotspot for spatial clustering was located in Camerino Z. Mendoza municipality; 14.6% (50/342) of patients in genotype clusters were located in a hotspot; of these, 60% (30/50) lived with DM. Using logistic regression the statistically significant variables associated with hotspots were: DM [adjusted Odds Ratio (aOR) 7.04, 95% Confidence interval (CI) 3.03-16.38] and attending the health center in Camerino Z. Mendoza (aOR18.04, 95% CI 7.35-44.28). The combination of molecular and epidemiological information with geospatial data allowed us to identify the concurrence of molecular clustering and spatial aggregation of patients with DM and TB. This information may be highly useful for TB control programs.

A Case Report About Cluster-Tic Syndrome Due to Venous Compression of the Trigeminal Nerve.

PubMed

de Coo, Ilse; van Dijk, J Marc C; Metzemaekers, Jan D M; Haan, Joost

2017-04-01

The term "cluster-tic syndrome" is used for the rare ipsilateral co-occurrence of attacks of cluster headache and trigeminal neuralgia. Medical treatment should combine treatment for cluster headache and trigeminal neuralgia, but is very often unsatisfactory. Here, we describe a 41-year-old woman diagnosed with cluster-tic syndrome who underwent microvascular decompression of the trigeminal nerve, primarily aimed at the "trigeminal neuralgia" part of her pain syndrome. After venous decompression of the trigeminal nerve both a decrease in trigeminal neuralgia and cluster headache attacks was seen. However, the headache did not disappear completely. Furthermore, she reported a decrease in pain intensity of the remaining cluster headache attacks. This case description suggests that venous vascular decompression in cluster-tic syndrome can be remarkably effective, both for trigeminal neuralgia and cluster headache. © 2016 American Headache Society.

Employment relations and global health: a typological study of world labor markets.

PubMed

Chung, Haejoo; Muntaner, Carles; Benach, Joan

2010-01-01

In this study, the authors investigate the global labor market and employment relations, which are central building blocks of the welfare state; the aim is to propose a global typology of labor markets to explain global inequalities in population health. Countries are categorized into core (21), semi-peripheral (42), and peripheral (71) countries, based on gross national product per capita (Atlas method). Labor market-related variables and factors are then used to generate clusters of countries with principal components and cluster analysis methods. The authors then examine the relationship between the resulting clusters and health outcomes. The clusters of countries are largely geographically defined, each cluster with similar historical background and developmental strategy. However, there are interesting exceptions, which warrant further elaboration. The relationship between health outcomes and clusters largely follows the authors' expectations (except for communicable diseases): more egalitarian labor institutions have better health outcomes. The world system, then, can be divided according to different types of labor markets that are predictive of population health outcomes at each level of economic development. As is the case for health and social policies, variability in labor market characteristics is likely to reflect, in part, the relative strength of a country's political actors.

Complete characterization of the stability of cluster synchronization in complex dynamical networks.

PubMed

Sorrentino, Francesco; Pecora, Louis M; Hagerstrom, Aaron M; Murphy, Thomas E; Roy, Rajarshi

2016-04-01

Synchronization is an important and prevalent phenomenon in natural and engineered systems. In many dynamical networks, the coupling is balanced or adjusted to admit global synchronization, a condition called Laplacian coupling. Many networks exhibit incomplete synchronization, where two or more clusters of synchronization persist, and computational group theory has recently proved to be valuable in discovering these cluster states based on the topology of the network. In the important case of Laplacian coupling, additional synchronization patterns can exist that would not be predicted from the group theory analysis alone. Understanding how and when clusters form, merge, and persist is essential for understanding collective dynamics, synchronization, and failure mechanisms of complex networks such as electric power grids, distributed control networks, and autonomous swarming vehicles. We describe a method to find and analyze all of the possible cluster synchronization patterns in a Laplacian-coupled network, by applying methods of computational group theory to dynamically equivalent networks. We present a general technique to evaluate the stability of each of the dynamically valid cluster synchronization patterns. Our results are validated in an optoelectronic experiment on a five-node network that confirms the synchronization patterns predicted by the theory.

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma.

PubMed

Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han; Lim, Jing Quan; Huang, Mi Ni; Padmanabhan, Nisha; Nellore, Vishwa; Kongpetch, Sarinya; Ng, Alvin Wei Tian; Ng, Ley Moy; Choo, Su Pin; Myint, Swe Swe; Thanan, Raynoo; Nagarajan, Sanjanaa; Lim, Weng Khong; Ng, Cedric Chuan Young; Boot, Arnoud; Liu, Mo; Ong, Choon Kiat; Rajasegaran, Vikneswari; Lie, Stefanus; Lim, Alvin Soon Tiong; Lim, Tse Hui; Tan, Jing; Loh, Jia Liang; McPherson, John R; Khuntikeo, Narong; Bhudhisawasdi, Vajaraphongsa; Yongvanit, Puangrat; Wongkham, Sopit; Totoki, Yasushi; Nakamura, Hiromi; Arai, Yasuhito; Yamasaki, Satoshi; Chow, Pierce Kah-Hoe; Chung, Alexander Yaw Fui; Ooi, London Lucien Peng Jin; Lim, Kiat Hon; Dima, Simona; Duda, Dan G; Popescu, Irinel; Broet, Philippe; Hsieh, Sen-Yung; Yu, Ming-Chin; Scarpa, Aldo; Lai, Jiaming; Luo, Di-Xian; Carvalho, André Lopes; Vettore, André Luiz; Rhee, Hyungjin; Park, Young Nyun; Alexandrov, Ludmil B; Gordân, Raluca; Rozen, Steven G; Shibata, Tatsuhiro; Pairojkul, Chawalit; Teh, Bin Tean; Tan, Patrick

2017-10-01

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analyzed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined 4 CCA clusters-fluke-positive CCAs (clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations; conversely, fluke-negative CCAs (clusters 3/4) exhibit high copy-number alterations and PD-1 / PD-L2 expression, or epigenetic mutations ( IDH1/2, BAP1 ) and FGFR / PRKA -related gene rearrangements. Whole-genome analysis highlighted FGFR2 3' untranslated region deletion as a mechanism of FGFR2 upregulation. Integration of noncoding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores-mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics, and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer. Significance: Integrated whole-genome and epigenomic analysis of CCA on an international scale identifies new CCA driver genes, noncoding promoter mutations, and structural variants. CCA molecular landscapes differ radically by etiology, underscoring how distinct cancer subtypes in the same organ may arise through different extrinsic and intrinsic carcinogenic processes. Cancer Discov; 7(10); 1116-35. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 1047 . ©2017 American Association for Cancer Research.

Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sreepathi, Sarat; Kumar, Jitendra; Mills, Richard T.

A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like themore » Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.« less

Spatio-temporal diffusion pattern and hotspot detection of dengue in Chachoengsao province, Thailand.

PubMed

Jeefoo, Phaisarn; Tripathi, Nitin Kumar; Souris, Marc

2011-01-01

In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999-2007) was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group), data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall), spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999-2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.

Occupational brain cancer risks in Umbria (Italy), with a particular focus on steel foundry workers.

PubMed

Oddone, Enrico; Scaburri, Alessandra; Bai, Edoardo; Modonesi, Carlo; Stracci, Fabrizio; Marchionna, Giuliano; Crosignani, Paolo; Imbriani, Marcello

2014-01-01

As a part of the Occupational Cancer Monitoring (OCCAM) project, a routine analysis based on Umbria region cancer registry (RTUP) database in 2002-2008 was performed. Among other results, the incidental finding of brain cancer increased risk in steel foundry workers in Terni province (Italy), lead us to deepen the analysis, focusing on this specific industrial sector. A monitoring study, based on Umbria Regional Cancer Registry data, was recently carried out. Brain cancer cases and controls identified within this preliminary study were selected. Therefore, we considered all incident cases (in Umbria region 2002-2008) of brain cancer occurred among workers occupied for at least one year in private companies since 1974 and controls randomly sampled from the same population. Afterwards, taking in to account results from steel foundry in Terni province, we further deepened our analysis, focusing on this productive sector. Odds ratios (ORs) and corresponding 90% confidence intervals (CIs) were calculated using multiple logistic regression models, adjusted by age at diagnosis or sampling, sex and province of residence, when appropriate. Statistical analyses were carried out on 14913 subjects, 56 cases and 14857 controls. Significantly increased ORs were observed for garment, mechanical manufacturing and chemical industries. Moreover, the risk estimates were strongly correlated with exposures in iron and steel foundries and a cluster of 14 cases in the same foundry in Terni was observed (OR 9.59, 90% CI 2.76-33.34). Results of this explorative study showed increased ORs of brain cancer in some productive branches, involving possible exposures to chemical compounds and/or solvents. Moreover, our results pointed out a significantly increased risk in Terni foundry workers, determining an interesting brain cancer cluster (14 cases). Further studies on this industrial sector are needed with improved definitions of tasks and exposures.

Aerodynamic Analysis of Tektites and Their Parent Bodies

NASA Technical Reports Server (NTRS)

Adams, E. W.; Huffaker, R. M.

1962-01-01

Experiment and analysis indicate that the button-type australites were derived from glassy spheres which entered or re-entered the atmosphere as cold solid bodies; in case of average-size specimens, the entry direction was nearly horizontal and the entry speed between 6.5 and 11.2 km/sec. Terrestrial origin of such spheres is impossible because of extremely high deceleration rates at low altitudes. The limited extension of the strewn fields rules out extraterrestrial origin of clusters of such spheres because of stability considerations for clusters in space. However, tektites may have been released as liquid droplets from glassy parent bodies ablating in the atmosphere of the earth. The australites then have skipped together with the parent body in order to re-enter as cold spheres. Terrestrial origin of a parent body would require an extremely violent natural event. Ablation analysis shows that fusion of opaque siliceous stone into glass by aerodynamic heating is impossible.

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

A description of how metal pollution occurs in the Tinto-Odiel rias (Huelva-Spain) through the application of cluster analysis.

PubMed

Grande, J A; Borrego, J; Morales, J A; de la Torre, M L

2003-04-01

In the last few decades, the study of space-time distribution and variations of heavy metals in estuaries has been extensively studied as an environmental indicator. In the case described here, the combination of acid water from mines, industrial effluents and sea water plays a determining role in the evolutionary process of the chemical makeup of the water in the estuary of the Tinto and Odiel Rivers, located in the southwest of the Iberian Peninsula. Based on the statistical treatment of the data from the analysis of the water samples from this system, which has been affected by processes of industrial and mining pollution, the 16 variables analyzed can be grouped into two large families. Each family presents high, positive Pearson r values that suggest common origins (fluvial or sea) for the pollutants present in the water analyzed and allow their subsequent contrast through cluster analysis.

Micro-PIXE analysis of trace element concentrations of natural rubies from different locations in Myanmar

NASA Astrophysics Data System (ADS)

Sanchez, J. L.; Osipowicz, T.; Tang, S. M.; Tay, T. S.; Win, T. T.

1997-07-01

The trace element concentrations found in geological samples can shed light on the formation process. In the case of gemstones, which might be of artificial or natural origin, there is also considerable interest in the development of methods that provide identification of the origin of a sample. For rubies, trace element concentrations present in natural samples were shown previously to be significant indicators of the region of origin [S.M. Tang et al., Appl. Spectr. 42 (1988) 44, and 43 (1989) 219]. Here we report the results of micro-PIXE analyses of trace element (Ti, V, Cr, Fe, Cu and Ga) concentrations of a large set ( n = 130) of natural rough rubies from nine locations in Myanmar (Burma). The resulting concentrations are subjected to statistical analysis. Six of the nine groups form clusters when the data base is evaluated using tree clustering and principal component analysis.

Urban Transmission of American Cutaneous Leishmaniasis in Argentina: Spatial Analysis Study

PubMed Central

Gil, José F.; Nasser, Julio R.; Cajal, Silvana P.; Juarez, Marisa; Acosta, Norma; Cimino, Rubén O.; Diosque, Patricio; Krolewiecki, Alejandro J.

2010-01-01

We used kernel density and scan statistics to examine the spatial distribution of cases of pediatric and adult American cutaneous leishmaniasis in an urban disease-endemic area in Salta Province, Argentina. Spatial analysis was used for the whole population and stratified by women > 14 years of age (n = 159), men > 14 years of age (n = 667), and children < 15 years of age (n = 213). Although kernel density for adults encompassed nearly the entire city, distribution in children was most prevalent in the peripheral areas of the city. Scan statistic analysis for adult males, adult females, and children found 11, 2, and 8 clusters, respectively. Clusters for children had the highest odds ratios (P < 0.05) and were located in proximity of plantations and secondary vegetation. The data from this study provide further evidence of the potential urban transmission of American cutaneous leishmaniasis in northern Argentina. PMID:20207869

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality

PubMed Central

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; MacEachren, Alan M

2008-01-01

Background Kulldorff's spatial scan statistic and its software implementation – SaTScan – are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. Results We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. Conclusion The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. Method We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit. PMID:18992163

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality.

PubMed

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M

2008-11-07

Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit.

Globular and Open Clusters Observed by SDSS/SEGUE: the Giant Stars

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morrison, Heather L.; Ma, Zhibo; Clem, James L.

We present griz observations for the clusters M92, M13 and NGC 6791 and gr photometry for M71, Be 29 and NGC 7789. In addition we present new membership identifications for all these clusters, which have been observed spectroscopically as calibrators for the SDSS/SEGUE survey; this paper focuses in particular on the red giant branch stars in the clusters. In a number of cases, these giants were too bright to be observed in the normal SDSS survey operations, and we describe the procedure used to obtain spectra for these stars. For M71, also present a new variable reddening map and amore » new fiducial for the gr giant branch. For NGC 7789, we derived a transformation from Teff to g-r for giants of near solar abundance, using IRFM Teff measures of stars with good ugriz and 2MASS photometry and SEGUE spectra. The result of our analysis is a robust list of known cluster members with correctly dereddened and (if needed) transformed gr photometry for crucial calibration efforts for SDSS and SEGUE.« less

Globular and Open Clusters Observed by SDSS/SEGUE: The Giant Stars

NASA Astrophysics Data System (ADS)

Morrison, Heather L.; Ma, Zhibo; Clem, James L.; An, Deokkeun; Connor, Thomas; Schechtman-Rook, Andrew; Casagrande, Luca; Rockosi, Constance; Yanny, Brian; Harding, Paul; Beers, Timothy C.; Johnson, Jennifer A.; Schneider, Donald P.

2016-01-01

We present griz observations for the clusters M92, M13 and NGC 6791 and gr photometry for M71, Be 29 and NGC 7789. In addition we present new membership identifications for all these clusters, which have been observed spectroscopically as calibrators for the Sloan Digital Sky Survey (SDSS)/SEGUE survey; this paper focuses in particular on the red giant branch stars in the clusters. In a number of cases, these giants were too bright to be observed in the normal SDSS survey operations, and we describe the procedure used to obtain spectra for these stars. For M71, we also present a new variable reddening map and a new fiducial for the gr giant branch. For NGC 7789, we derived a transformation from Teff to g-r for giants of near solar abundance, using IRFM Teff measures of stars with good ugriz and 2MASS photometry and SEGUE spectra. The result of our analysis is a robust list of known cluster members with correctly dereddened and (if needed) transformed gr photometry for crucial calibration efforts for SDSS and SEGUE.

Globular and Open Clusters Observed by SDSS/SEGUE: the Giant Stars

DOE PAGES

Morrison, Heather L.; Ma, Zhibo; Clem, James L.; ...

2015-12-18

We present griz observations for the clusters M92, M13 and NGC 6791 and gr photometry for M71, Be 29 and NGC 7789. In addition we present new membership identifications for all these clusters, which have been observed spectroscopically as calibrators for the SDSS/SEGUE survey; this paper focuses in particular on the red giant branch stars in the clusters. In a number of cases, these giants were too bright to be observed in the normal SDSS survey operations, and we describe the procedure used to obtain spectra for these stars. For M71, also present a new variable reddening map and amore » new fiducial for the gr giant branch. For NGC 7789, we derived a transformation from Teff to g-r for giants of near solar abundance, using IRFM Teff measures of stars with good ugriz and 2MASS photometry and SEGUE spectra. The result of our analysis is a robust list of known cluster members with correctly dereddened and (if needed) transformed gr photometry for crucial calibration efforts for SDSS and SEGUE.« less

Model of cholera dissemination using geographic information systems and fuzzy clustering means: case study, Chabahar, Iran.

PubMed

Pezeshki, Z; Tafazzoli-Shadpour, M; Mansourian, A; Eshrati, B; Omidi, E; Nejadqoli, I

2012-10-01

Cholera is spread by drinking water or eating food that is contaminated by bacteria, and is related to climate changes. Several epidemics have occurred in Iran, the most recent of which was in 2005 with 1133 cases and 12 deaths. This study investigated the incidence of cholera over a 10-year period in Chabahar district, a region with one of the highest incidence rates of cholera in Iran. Descriptive retrospective study on data of patients with Eltor and NAG cholera reported to the Iranian Centre of Disease Control between 1997 and 2006. Data on the prevalence of cholera were gathered through a surveillance system, and a spatial database was developed using geographic information systems (GIS) to describe the relation of spatial and climate variables to cholera incidences. Fuzzy clustering (fuzzy C) method and statistical analysis based on logistic regression were used to develop a model of cholera dissemination. The variables were demographic characteristics, specifications of cholera infection, climate conditions and some geographical parameters. The incidence of cholera was found to be significantly related to higher temperature and humidity, lower precipitation, shorter distance to the eastern border of Iran and local health centres, and longer distance to the district health centre. The fuzzy C means algorithm showed that clusters were geographically distributed in distinct regions. In order to plan, manage and monitor any public health programme, GIS provide ideal platforms for the convergence of disease-specific information, analysis and computation of new data for statistical analysis. Copyright © 2012 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Superstition and post-tonsillectomy hemorrhage.

PubMed

Kumar, Veena V; Kumar, Naveen V; Isaacson, Glenn

2004-11-01

The objective was to determine whether post-tonsillectomy hemorrhages occur more frequently in redheaded children, in patterns of threes, on Friday-the-13th days, or with the full moon. Case-control analysis. The authors performed multiple statistical analyses of all children undergoing tonsillectomy at Temple University Children's Medical Center (Philadelphia, PA) during a 29-month period. Children readmitted to the hospital with or without surgical control of bleeding were compared with children who did not bleed. Relation of post-tonsillectomy hemorrhages to the phase of the moon was evaluated using a standard normal deviate. The frequency of surgery performed on Friday-the-13th days was compared with a differently dated Friday chosen at random. Clusters of three hemorrhages in a 7-day period were recorded. Families of children were contacted and asked whether their child had red hair. A chi analysis compared redheaded and non-redheaded tonsillectomy patients. Twenty-eight of 589 tonsillectomy cases performed required readmission for bleeding events. Twenty tonsillectomies occurred on a full-moon day, resulting in one bleeding event. One cluster of three post-tonsillectomy hemorrhages occurred in a 7-day period. Four of the children who bled had red hair. Two tonsillectomies occurred on Friday the 13th, with no associated hemorrhage. Statistical analysis revealed a random pattern to post-tonsillectomy hemorrhage. Post-tonsillectomy hemorrhages do not occur in clusters of three and are not more frequent with the full moon or on Friday the 13th. The bleeding rate among children with red hair is similar to that of non-redheaded children.

X-ray spectral observations of clusters of galaxies undergoing merger events

NASA Astrophysics Data System (ADS)

Henriksen, Mark J.

1993-09-01

We have analyzed the HEAO 1 A2 observations of two clusters whose optical and X-ray isophotes are suggestive of merging subclusters, A119 and A754, and find evidence of nonisothermal X-ray emission from both clusters. The X-ray spectrum of both clusters, when fitted with a single isothermal model, shows residual soft X-ray emission. There is a statistically significant reduction in chi-squared (98 percent probability based on the F-test) when a second temperature component is added. If the asymmetric isophotes seen in the soft X-ray image are indicative of merging subclusters, then our analysis of the Einstein IPC spectra and Solid State Spectrometer observations of A754, which provide some spatial and spectral resolution, suggests that the two temperature components seen in the HEAO 1 A2 spectra are associated with gas trapped in the subcluster potential wells. The implied subcluster isothermal masses suggest that a more massive cluster is accreting a less massive companion in A754. The present observations cannot rule out the alternative possibility that the cooler gas is associated with the outer cluster atmosphere rather than individual subclusters, as appears to be the case for A119. Astro D observations will be necessary to distinguish between these two possibilities for both clusters.

Syphilis Networks in Louisiana: An Analysis of Network Configuration and Disease Transmission

NASA Astrophysics Data System (ADS)

Desmarais, Catherine Theresa

Background: In 2009, Louisiana had the highest rate of primary and secondary syphilis in the country. Recent partner notification approaches have been insufficient in addressing Louisiana's deeply entrenched areas of syphilis infection. Prior researchers have suggested that surveillance systems may benefit from utilizing social and spatial network analysis in syphilis control efforts. Objective: To expand the understanding of the spread of syphilis in Louisiana, and to add new tools to the state's case finding resources through the description of the characteristics of cases of early syphilis and their partners in Louisiana, the socio-sexual networks of these cases, and the geospatial clustering of cases and partners. Methods: Utilizing state surveillance data, all cases of primary, secondary, and early latent syphilis that were diagnosed in 2009 and data on their sexual or needle sharing partners were analyzed using a combination of descriptive, network, and geospatial measures. Results: In 2009, Louisiana experienced a high rate of heterosexual syphilis transmission. Within syphilis transmission networks, 50.8% of all cases were female and 84.2% of all cases were black. The average and median ages of males with reactive syphilis tests were higher than that of females in Louisiana, and in 88.9% of regions, older individuals were more likely to have a syphilis test than no test. A greater proportion of males (11.4%) refused to discuss partners than females (7.4%) and a greater proportion of males (5.5%) refused testing and prophylactic treatment than females (2.8%). No distinct patterns were seen in disease prevalence between regions based upon demographic data. Classic summary network measures such as density, degree, centrality, and betweenness provided little information on similarities and differences between the different regions in Louisiana. All measures indicated low density and extreme fragmentation of networks in Louisiana. The majority of network structures were dendritic in nature. A total of 121 cases did not report any partners and an additional 15.9% reported only being involved in dyads. Several large connected components were also observed in syphilis transmission networks in Louisiana. The average age of persons in these large components was greater than in the regional network. A total of 27.3% of male partnerships were with other males in Louisiana, and 4.0% of female pairings were with other females. Blacks practiced assortative mixing, with 93.1% of contacts with a reported race/ethnicity also being black, while 58.9% of contacts reported by whites were also white. Visualization of networks at the regional level illustrated different patterns, with some regions having large disconnected networks while others had more highly connected components. Visualization also uncovered a high concentration of males that had sex with males and females within Region 2 that were note detected during descriptive analyses. Graphs also highlighted highly connected persons within networks that did not have reactive syphilis tests. Upon geocoding the addresses of network members, it was found that most persons lived adjacent to major highways and in major urban areas. Cluster analyses detected a large number of geographic clusters of study subjects throughout the state. Several different patterns were identified; regions with many clusters in a small geographic area, regions with many clusters over a wide geographic area, regions with few clusters, and regions with no small clusters. Most regions had geographically small clusters of a size that could benefit from targeted interventions. Conclusion: This study provides a more in-depth understanding of syphilis spread in the state of Louisiana and demonstrates the feasibility of using network and geospatial methods in future state surveillance and prevention activities. By tying these two approaches together with the addition of basic demographic information, regional patterns can be identified to improve syphilis prevention practices. In areas with disconnected networks but close geographic clustering, community and street level testing has the potential to reduce morbidity more than partner elicitation, which has resulted in highly fragmented networks. The combination of these analyses also identified subpopulations in need of special messaging or intervention, such as sex workers and males that have sex with both males and females, and identified persons within the networks that would not typically be targeted for cluster interviews but, due to network position, may be helpful in finding additional morbidity in the region. These analyses are feasible to be carried out in an ongoing manner at the state level using current data collection processes and have the potential to inform syphilis elimination activities in each region and within the state as a whole. The addition of risk behaviors, HIV status, venues where partners are met, and the use of the internet and apps in finding partners to future analyses will further improve these disease elimination approaches in Louisiana.

Using Cluster Analysis to Examine Husband-Wife Decision Making

ERIC Educational Resources Information Center

Bonds-Raacke, Jennifer M.

2006-01-01

Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

Epidemiology of toe tip necrosis syndrome (TTNS) of North American feedlot cattle.

PubMed

Jelinski, Murray; Fenton, Kent; Perrett, Tye; Paetsch, Chad

2016-08-01

Toe Tip Necrosis Syndrome (TTNS) is predominantly a hind limb lameness of feedlot cattle that develops early in the feeding period. Retrospective analyses of feedlot health records were conducted in order to describe the epidemiology of the disease at the level of the individual animal, lot, and feedyard. Analysis of 1904 lots (cohorts of > 100 head) of cattle, from 48 feedyards, found that TTNS occurred sporadically, but clustered by both lots and feedyards. Only 3.8% of lots had ≥ 1 case of TTNS; however, 26.4% of these lots were associated with 1 feedyard. Analysis of 702 cases of TTNS found that the disease clusters early in the feeding period; the mean (median; range) number of days on feed at death was 42.3 d (27.0 d; 4 to 302 d). The disease occurred in all months of the year and affected calves, yearlings, steers, and heifers. It was equivocal as to whether the source of the animals was associated with how quickly they died of TTNS in the feedyard.

Spatiotemporal Dynamics of Scrub Typhus Transmission in Mainland China, 2006-2014

PubMed Central

Hu, Wen-Biao; Haque, Ubydul; Weppelmann, Thomas A.; Wang, Yong; Liu, Yun-Xi; Li, Xin-Lou; Sun, Hai-Long; Sun, Yan-Song; Clements, Archie C. A.; Li, Shen-Long; Zhang, Wen-Yi

2016-01-01

Background Scrub typhus is endemic in the Asia-Pacific region including China, and the number of reported cases has increased dramatically in the past decade. However, the spatial-temporal dynamics and the potential risk factors in transmission of scrub typhus in mainland China have yet to be characterized. Objective This study aims to explore the spatiotemporal dynamics of reported scrub typhus cases in mainland China between January 2006 and December 2014, to detect the location of high risk spatiotemporal clusters of scrub typhus cases, and identify the potential risk factors affecting the re-emergence of the disease. Method Monthly cases of scrub typhus reported at the county level between 2006 and 2014 were obtained from the Chinese Center for Diseases Control and Prevention. Time-series analyses, spatiotemporal cluster analyses, and spatial scan statistics were used to explore the characteristics of the scrub typhus incidence. To explore the association between scrub typhus incidence and environmental variables panel Poisson regression analysis was conducted. Results During the time period between 2006 and 2014 a total of 54,558 scrub typhus cases were reported in mainland China, which grew exponentially. The majority of cases were reported each year between July and November, with peak incidence during October every year. The spatiotemporal dynamics of scrub typhus varied over the study period with high-risk clusters identified in southwest, southern, and middle-eastern part of China. Scrub typhus incidence was positively correlated with the percentage of shrub and meteorological variables including temperature and precipitation. Conclusions The results of this study demonstrate areas in China that could be targeted with public health interventions to mitigate the growing threat of scrub typhus in the country. PMID:27479297

Spatiotemporal Dynamics of Scrub Typhus Transmission in Mainland China, 2006-2014.

PubMed

Wu, Yi-Cheng; Qian, Quan; Soares Magalhaes, Ricardo J; Han, Zhi-Hai; Hu, Wen-Biao; Haque, Ubydul; Weppelmann, Thomas A; Wang, Yong; Liu, Yun-Xi; Li, Xin-Lou; Sun, Hai-Long; Sun, Yan-Song; Clements, Archie C A; Li, Shen-Long; Zhang, Wen-Yi

2016-08-01

Scrub typhus is endemic in the Asia-Pacific region including China, and the number of reported cases has increased dramatically in the past decade. However, the spatial-temporal dynamics and the potential risk factors in transmission of scrub typhus in mainland China have yet to be characterized. This study aims to explore the spatiotemporal dynamics of reported scrub typhus cases in mainland China between January 2006 and December 2014, to detect the location of high risk spatiotemporal clusters of scrub typhus cases, and identify the potential risk factors affecting the re-emergence of the disease. Monthly cases of scrub typhus reported at the county level between 2006 and 2014 were obtained from the Chinese Center for Diseases Control and Prevention. Time-series analyses, spatiotemporal cluster analyses, and spatial scan statistics were used to explore the characteristics of the scrub typhus incidence. To explore the association between scrub typhus incidence and environmental variables panel Poisson regression analysis was conducted. During the time period between 2006 and 2014 a total of 54,558 scrub typhus cases were reported in mainland China, which grew exponentially. The majority of cases were reported each year between July and November, with peak incidence during October every year. The spatiotemporal dynamics of scrub typhus varied over the study period with high-risk clusters identified in southwest, southern, and middle-eastern part of China. Scrub typhus incidence was positively correlated with the percentage of shrub and meteorological variables including temperature and precipitation. The results of this study demonstrate areas in China that could be targeted with public health interventions to mitigate the growing threat of scrub typhus in the country.

Theory of scattering of electromagnetic waves of the microwave range in a turbid medium

NASA Astrophysics Data System (ADS)

Konstantinov, O. V.; Matveentsev, A. V.

2013-02-01

The coefficient of extinction of electromagnetic waves of the microwave range due to their scattering from clusters suspended in an amorphous medium and responsible for turbidity is calculated. Turbidity resembles the case when butter clusters transform water into milk. In the case under investigation, the clusters are conductors (metallic or semiconducting). The extinction coefficient is connected in a familiar way with the cross section of light scattering from an individual cluster. A new formula is derived for the light scattering cross section in the case when damping of oscillations of an electron is due only to spontaneous emission of light quanta. In this case, the resonant scattering cross section for light can be very large. It is shown that this can be observed only in a whisker nanocluster. In addition, the phonon energy on a whisker segment must be higher than the photon energy, which is close to the spacing between the electron energy levels in the cluster.

The Spread of Dengue in an Endemic Urban Milieu–The Case of Delhi, India

PubMed Central

Telle, Olivier; Vaguet, Alain; Yadav, N. K.; Lefebvre, B.; Daudé, Eric; Paul, Richard E.; Cebeillac, A.; Nagpal, B. N.

2016-01-01

Background Dengue is a major international public health concern, one of the most important arthropod-borne diseases. More than 3.5 billion people are at risk of dengue infection and there are an estimated 390 million dengue infections annually. This prolific increase has been connected to societal changes such as population growth and increasing urbanization generating intense agglomeration leading to proliferation of synanthropic mosquito species. Quantifying the spatio-temporal epidemiology of dengue in large cities within the context of a Geographic Information System is a first step in the identification of socio-economic risk factors. Methodology/Principal Findings This Project has been approved by the ethical committee of Institut Pasteur. Data has been anonymized and de-identified prior to geolocalisation and analysis. A GIS was developed for Delhi, enabling typological characterization of the urban environment. Dengue cases identified in the Delhi surveillance system from 2008 to 2010 were collated, localised and embedded within this GIS. The spatio-temporal distribution of dengue cases and extent of clustering were analyzed. Increasing distance from the forest in Delhi reduced the risk of occurrence of a dengue case. Proximity to a hospital did not increase risk of a notified dengue case. Overall, there was high heterogeneity in incidence rate within areas with the same socio-economical profiles and substantial inter-annual variability. Dengue affected the poorest areas with high density of humans, but rich areas were also found to be infected, potentially because of their central location with respect to the daily mobility network of Delhi. Dengue cases were highly clustered in space and there was a strong relationship between the time of introduction of the virus and subsequent cluster size. At a larger scale, earlier introduction predicted the total number of cases. Conclusions/Significance DENV epidemiology within Delhi has a forest fire signature. The stochastic nature of this invasion process likely smothers any detectable socio-economic risk factors. However, the significant finding that the size of the dengue case cluster depends on the timing of its emergence emphasizes the need for early case detection and implementation of effective mosquito control. A better understanding of the role of population mobility in contributing to dengue risk could also help focus control on areas at particular risk of dengue virus importation. PMID:26808518

The Spread of Dengue in an Endemic Urban Milieu--The Case of Delhi, India.

PubMed

Telle, Olivier; Vaguet, Alain; Yadav, N K; Lefebvre, B; Cebeillac, A; Nagpal, B N; Daudé, Eric; Paul, Richard E

2016-01-01

Dengue is a major international public health concern, one of the most important arthropod-borne diseases. More than 3.5 billion people are at risk of dengue infection and there are an estimated 390 million dengue infections annually. This prolific increase has been connected to societal changes such as population growth and increasing urbanization generating intense agglomeration leading to proliferation of synanthropic mosquito species. Quantifying the spatio-temporal epidemiology of dengue in large cities within the context of a Geographic Information System is a first step in the identification of socio-economic risk factors. This Project has been approved by the ethical committee of Institut Pasteur. Data has been anonymized and de-identified prior to geolocalisation and analysis. A GIS was developed for Delhi, enabling typological characterization of the urban environment. Dengue cases identified in the Delhi surveillance system from 2008 to 2010 were collated, localised and embedded within this GIS. The spatio-temporal distribution of dengue cases and extent of clustering were analyzed. Increasing distance from the forest in Delhi reduced the risk of occurrence of a dengue case. Proximity to a hospital did not increase risk of a notified dengue case. Overall, there was high heterogeneity in incidence rate within areas with the same socio-economical profiles and substantial inter-annual variability. Dengue affected the poorest areas with high density of humans, but rich areas were also found to be infected, potentially because of their central location with respect to the daily mobility network of Delhi. Dengue cases were highly clustered in space and there was a strong relationship between the time of introduction of the virus and subsequent cluster size. At a larger scale, earlier introduction predicted the total number of cases. DENV epidemiology within Delhi has a forest fire signature. The stochastic nature of this invasion process likely smothers any detectable socio-economic risk factors. However, the significant finding that the size of the dengue case cluster depends on the timing of its emergence emphasizes the need for early case detection and implementation of effective mosquito control. A better understanding of the role of population mobility in contributing to dengue risk could also help focus control on areas at particular risk of dengue virus importation.

Geographical distribution and spatio-temporal patterns of hospitalization due to dengue infection at a leading specialist hospital in Malaysia.

PubMed

Low, Gary K K; Papapreponis, Panayoti; Isa, Ridzuan M; Gan, Seng Chiew; Chee, Hui Yee; Te, Kian Keong; Hatta, Nadia M

2018-05-07

Increasing numbers of dengue infection worldwide have led to a rise in deaths due to complications caused by this disease. We present here a cross-sectional study of dengue patients who attended the Emergency and Trauma Department of Ampang Hospital, one of Malaysia's leading specialist hospitals. The objective was to search for potential clustering of severe dengue, in space and/or time, among the annual admissions with the secondary objective to describe the spatio-temporal pattern of all dengue cases admitted to this hospital. The dengue status of the patients was confirmed serologically with the geographic location of the patients determined by residency, but not more specific than the street level. A total of 1165 dengue patients were included in the analysis using SaTScan software. The mean age of these patients was 27.8 years, with a standard deviation of 14.2 years and an age range from 1 to 77 years, among whom 54 (4.6%) were cases of severe dengue. A cluster of general dengue cases was identified occurring from October to December in the study year of 2015 but the inclusion of severe dengue in that cluster was not statistically significant (P=0.862). The standardized incidence ratio was 1.51. General presence of dengue cases was, however, detected to be concentrated at the end of the year, which should be useful for hospital planning and management if this pattern holds.

Spatiotemporal epidemiology of scarlet fever in Jiangsu Province, China, 2005-2015.

PubMed

Zhang, Qi; Liu, Wendong; Ma, Wang; Shi, Yingying; Wu, Ying; Li, Yuan; Liang, Shuyi; Zhu, Yefei; Zhou, Minghao

2017-08-30

A marked increase in the incidence rate of scarlet fever imposed a considerable burden on the health of children aged 5 to 15 years. The main purpose of this study was to depict the spatiotemporal epidemiological characteristics of scarlet fever in Jiangsu Province, China in order to develop and implement effective scientific prevention and control strategies. Smoothed map was used to demonstrate the spatial distribution of scarlet fever in Jiangsu Province. In addition, a retrospective space-time analysis based on a discrete Poisson model was utilized to detect clusters of scarlet fever from 2005 to 2015. During the years 2005-2015, a total of 15,873 scarlet fever cases occurred in Jiangsu Province, with an average annual incidence rate of 1.87 per 100,000. A majority of the cases (83.67%) occurred in children aged 3 to 9 years. Each year, two seasonal incidence peaks were observed, the higher occurring between March and July, the lower between November and the following January. The incidence in the southern regions of the province was generally higher than that in the northern regions. Seven clusters, all of which occurred during incidence peaks, were detected via space-time scan statistical analysis. The most likely cluster and one of the secondary clusters were detected in the southern and northern high endemic regions, respectively. The prevalence of scarlet fever in Jiangsu Province had a marked seasonality variation and was relatively endemic in some regions. Children aged 3 to 9 years were the major victims of this disease, and kindergartens and primary schools were the focus of surveillance and control. Targeted strategies and measures should be taken to reduce the incidence.

Phylogeographic analysis of rabies viruses in the Philippines.

PubMed

Tohma, Kentaro; Saito, Mariko; Kamigaki, Taro; Tuason, Laarni T; Demetria, Catalino S; Orbina, Jun Ryan C; Manalo, Daria L; Miranda, Mary E; Noguchi, Akira; Inoue, Satoshi; Suzuki, Akira; Quiambao, Beatriz P; Oshitani, Hitoshi

2014-04-01

Rabies still remains a public health threat in the Philippines. A significant number of human rabies cases, about 200-300 cases annually, have been reported, and the country needs an effective strategy for rabies control. To develop an effective control strategy, it is important to understand the transmission patterns of the rabies viruses. We conducted phylogenetic analyses by considering the temporal and spatial evolution of rabies viruses to reveal the transmission dynamics in the Philippines. After evaluating the molecular clock and phylogeographic analysis, we estimated that the Philippine strains were introduced from China around the beginning of 20th century. Upon this introduction, the rabies viruses evolved within the Philippines to form three major clades, and there was no indication of introduction of other rabies viruses from any other country. However, within the Philippines, island-to-island migrations were observed. Since then, the rabies viruses have diffused and only evolved within each island group. The evolutionary pattern of these viruses was strongly shaped by geographical boundaries. The association index statistics demonstrated a strong spatial structure within the island group, indicating that the seas were a significant geographical barrier for viral dispersal. Strong spatial structure was also observed even at a regional level, and most of the viral migrations (79.7% of the total median number) in Luzon were observed between neighboring regions. Rabies viruses were genetically clustered at a regional level, and this strong spatial structure suggests a geographical clustering of transmission chains and the potential effectiveness of rabies control that targets geographical clustering. Dog vaccination campaigns have been conducted independently by local governments in the Philippines, but it could be more effective to implement a coordinated vaccination campaign among neighboring areas to eliminate geographically-clustered rabies transmission chains. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Recent transmission of drug-resistant Mycobacterium tuberculosis in a prison population in southern Brazil.

PubMed

Reis, Ana Julia; David, Simone Maria Martini de; Nunes, Luciana de Souza; Valim, Andreia Rosane de Moura; Possuelo, Lia Gonçalves

2016-01-01

We conducted a cross-sectional, retrospective study, characterized by classical and molecular epidemiology, involving M. tuberculosis isolates from a regional prison in southern Brazil. Between January of 2011 and August of 2014, 379 prisoners underwent sputum smear microscopy and culture; 53 (13.9%) were diagnosed with active tuberculosis. Of those, 8 (22.9%) presented with isoniazid-resistant tuberculosis. Strain genotyping was carried out by 15-locus mycobacterial interspersed repetitive unit-variable-number tandem-repeat analysis; 68.6% of the patients were distributed into five clusters, and 87.5% of the resistant cases were in the same cluster. The frequency of drug-resistant tuberculosis cases and the rate of recent transmission were high. Our data suggest the need to implement an effective tuberculosis control program within the prison system. RESUMO Estudo transversal, retrospectivo, com isolados de M. tuberculosis de pacientes de um presídio regional no sul do Brasil, caracterizado através de epidemiologia clássica e molecular. Entre janeiro de 2011 e agosto de 2014, 379 detentos foram submetidos a baciloscopia e cultura, sendo 53 (13,9%) diagnosticados com tuberculose ativa. Desses, 8 (22,9%) apresentavam tuberculose resistente a isoniazida. A genotipagem das cepas foi realizada por 15-locus mycobacterial interspersed repetitive units-variable number of tandem repeat analysis; 68,6% dos pacientes estavam distribuídos em cinco clusters, e 87,5% dos casos resistentes estavam em um mesmo cluster. Verificou-se uma frequência elevada de casos de resistência e alta taxa de transmissão recente. Estes dados sugerem a necessidade da implantação de um programa efetivo de controle da tuberculose no sistema prisional.

Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions.

PubMed

Meesters, Stephan; Ossenblok, Pauly; Colon, Albert; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Fuster, Andrea

2018-06-01

The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. A network approach is promising in case of complex epilepsies. Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

CLUSTERnGO: a user-defined modelling platform for two-stage clustering of time-series data.

PubMed

Fidaner, Işık Barış; Cankorur-Cetinkaya, Ayca; Dikicioglu, Duygu; Kirdar, Betul; Cemgil, Ali Taylan; Oliver, Stephen G

2016-02-01

Simple bioinformatic tools are frequently used to analyse time-series datasets regardless of their ability to deal with transient phenomena, limiting the meaningful information that may be extracted from them. This situation requires the development and exploitation of tailor-made, easy-to-use and flexible tools designed specifically for the analysis of time-series datasets. We present a novel statistical application called CLUSTERnGO, which uses a model-based clustering algorithm that fulfils this need. This algorithm involves two components of operation. Component 1 constructs a Bayesian non-parametric model (Infinite Mixture of Piecewise Linear Sequences) and Component 2, which applies a novel clustering methodology (Two-Stage Clustering). The software can also assign biological meaning to the identified clusters using an appropriate ontology. It applies multiple hypothesis testing to report the significance of these enrichments. The algorithm has a four-phase pipeline. The application can be executed using either command-line tools or a user-friendly Graphical User Interface. The latter has been developed to address the needs of both specialist and non-specialist users. We use three diverse test cases to demonstrate the flexibility of the proposed strategy. In all cases, CLUSTERnGO not only outperformed existing algorithms in assigning unique GO term enrichments to the identified clusters, but also revealed novel insights regarding the biological systems examined, which were not uncovered in the original publications. The C++ and QT source codes, the GUI applications for Windows, OS X and Linux operating systems and user manual are freely available for download under the GNU GPL v3 license at http://www.cmpe.boun.edu.tr/content/CnG. sgo24@cam.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Necessary Sequencing Depth and Clustering Method to Obtain Relatively Stable Diversity Patterns in Studying Fish Gut Microbiota.

PubMed

Xiao, Fanshu; Yu, Yuhe; Li, Jinjin; Juneau, Philippe; Yan, Qingyun

2018-05-25

The 16S rRNA gene is one of the most commonly used molecular markers for estimating bacterial diversity during the past decades. However, there is no consistency about the sequencing depth (from thousand to millions of sequences per sample), and the clustering methods used to generate OTUs may also be different among studies. These inconsistent premises make effective comparisons among studies difficult or unreliable. This study aims to examine the necessary sequencing depth and clustering method that would be needed to ensure a stable diversity patterns for studying fish gut microbiota. A total number of 42 samples dataset of Siniperca chuatsi (carnivorous fish) gut microbiota were used to test how the sequencing depth and clustering may affect the alpha and beta diversity patterns of fish intestinal microbiota. Interestingly, we found that the sequencing depth (resampling 1000-11,000 per sample) and the clustering methods (UPARSE and UCLUST) did not bias the estimates of the diversity patterns during the fish development from larva to adult. Although we should acknowledge that a suitable sequencing depth may differ case by case, our finding indicates that a shallow sequencing such as 1000 sequences per sample may be also enough to reflect the general diversity patterns of fish gut microbiota. However, we have shown in the present study that strict pre-processing of the original sequences is required to ensure reliable results. This study provides evidences to help making a strong scientific choice of the sequencing depth and clustering method for future studies on fish gut microbiota patterns, but at the same time reducing as much as possible the costs related to the analysis.

Performance comparison analysis library communication cluster system using merge sort

NASA Astrophysics Data System (ADS)

Wulandari, D. A. R.; Ramadhan, M. E.

2018-04-01

Begins by using a single processor, to increase the speed of computing time, the use of multi-processor was introduced. The second paradigm is known as parallel computing, example cluster. The cluster must have the communication potocol for processing, one of it is message passing Interface (MPI). MPI have many library, both of them OPENMPI and MPICH2. Performance of the cluster machine depend on suitable between performance characters of library communication and characters of the problem so this study aims to analyze the comparative performances libraries in handling parallel computing process. The case study in this research are MPICH2 and OpenMPI. This case research execute sorting’s problem to know the performance of cluster system. The sorting problem use mergesort method. The research method is by implementing OpenMPI and MPICH2 on a Linux-based cluster by using five computer virtual then analyze the performance of the system by different scenario tests and three parameters for to know the performance of MPICH2 and OpenMPI. These performances are execution time, speedup and efficiency. The results of this study showed that the addition of each data size makes OpenMPI and MPICH2 have an average speed-up and efficiency tend to increase but at a large data size decreases. increased data size doesn’t necessarily increased speed up and efficiency but only execution time example in 100000 data size. OpenMPI has a execution time greater than MPICH2 example in 1000 data size average execution time with MPICH2 is 0,009721 and OpenMPI is 0,003895 OpenMPI can customize communication needs.

Naratriptan in the Prophylactic Treatment of Cluster Headache.

PubMed

Ito, Yasuo; Mitsufuji, Takashi; Asano, Yoshio; Shimazu, Tomokazu; Kato, Yuji; Tanahashi, Norio; Maruki, Yuichi; Sakai, Fumihiko; Yamamoto, Toshimasa; Araki, Nobuo

2017-10-01

Objective Naratriptan has been reported to reduce the frequency of cluster headache. The purpose of this study was to determine whether naratriptan is effective as a prophylactic treatment for cluster headache in Japan. Methods We retrospectively reviewed all 43 patients with cluster headache who received preventive treatment with naratriptan from April 2009 to April 2015. The International Classification of Headache Disorders, 3rd Edition (beta version) (ICHD-3 beta) was used to diagnose cluster headache. This study was conducted at 3 centers (Department of Neurology, Saitama Medical University; Saitama Neuropsychiatric Institute; Saitama Medical University International Medical Center). Patients were recruited from these specialized headache outpatient centers. Naratriptan was taken before the patient went to bed. Results The study population included 30 men (69.8%) and 13 women (30.2%). Twenty-two cases received other preventive treatments (51.2%), while 21 cases only received naratriptan (48.8%). Among the 43 cases, 37 patients (86.0%) achieved an improvement of cluster headache on naratriptan. Conclusion Naratriptan has been suggested as a preventive medicine for cluster headache because of the longer the biological half-life in comparison to other triptans. The internal use of naratriptan 2 hours before attacks appears to achieve a good response in patients with cluster headache.

Application of Artificial Intelligence For Euler Solutions Clustering

NASA Astrophysics Data System (ADS)

Mikhailov, V.; Galdeano, A.; Diament, M.; Gvishiani, A.; Agayan, S.; Bogoutdinov, Sh.; Graeva, E.; Sailhac, P.

Results of Euler deconvolution strongly depend on the selection of viable solutions. Synthetic calculations using multiple causative sources show that Euler solutions clus- ter in the vicinity of causative bodies even when they do not group densely about perimeter of the bodies. We have developed a clustering technique to serve as a tool for selecting appropriate solutions. The method RODIN, employed in this study, is based on artificial intelligence and was originally designed for problems of classification of large data sets. It is based on a geometrical approach to study object concentration in a finite metric space of any dimension. The method uses a formal definition of cluster and includes free parameters that facilitate the search for clusters of given proper- ties. Test on synthetic and real data showed that the clustering technique successfully outlines causative bodies more accurate than other methods of discriminating Euler solutions. In complicated field cases such as the magnetic field in the Gulf of Saint Malo region (Brittany, France), the method provides geologically insightful solutions. Other advantages of the clustering method application are: - Clusters provide solutions associated with particular bodies or parts of bodies permitting the analysis of different clusters of Euler solutions separately. This may allow computation of average param- eters for individual causative bodies. - Those measurements of the anomalous field that yield clusters also form dense clusters themselves. The application of cluster- ing technique thus outlines areas where the influence of different causative sources is more prominent. This allows one to focus on areas for reinterpretation, using different window sizes, structural indices and so on.

Cluster Free Energies from Simple Simulations of Small Numbers of Aggregants: Nucleation of Liquid MTBE from Vapor and Aqueous Phases.

PubMed

Patel, Lara A; Kindt, James T

2017-03-14

We introduce a global fitting analysis method to obtain free energies of association of noncovalent molecular clusters using equilibrated cluster size distributions from unbiased constant-temperature molecular dynamics (MD) simulations. Because the systems simulated are small enough that the law of mass action does not describe the aggregation statistics, the method relies on iteratively determining a set of cluster free energies that, using appropriately weighted sums over all possible partitions of N monomers into clusters, produces the best-fit size distribution. The quality of these fits can be used as an objective measure of self-consistency to optimize the cutoff distance that determines how clusters are defined. To showcase the method, we have simulated a united-atom model of methyl tert-butyl ether (MTBE) in the vapor phase and in explicit water solution over a range of system sizes (up to 95 MTBE in the vapor phase and 60 MTBE in the aqueous phase) and concentrations at 273 K. The resulting size-dependent cluster free energy functions follow a form derived from classical nucleation theory (CNT) quite well over the full range of cluster sizes, although deviations are more pronounced for small cluster sizes. The CNT fit to cluster free energies yielded surface tensions that were in both cases lower than those for the simulated planar interfaces. We use a simple model to derive a condition for minimizing non-ideal effects on cluster size distributions and show that the cutoff distance that yields the best global fit is consistent with this condition.

A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa

PubMed Central

Petegrosso, Raphael; Tolar, Jakub

2018-01-01

Single-cell RNA sequencing (scRNA-seq) has been widely applied to discover new cell types by detecting sub-populations in a heterogeneous group of cells. Since scRNA-seq experiments have lower read coverage/tag counts and introduce more technical biases compared to bulk RNA-seq experiments, the limited number of sampled cells combined with the experimental biases and other dataset specific variations presents a challenge to cross-dataset analysis and discovery of relevant biological variations across multiple cell populations. In this paper, we introduce a method of variance-driven multitask clustering of single-cell RNA-seq data (scVDMC) that utilizes multiple single-cell populations from biological replicates or different samples. scVDMC clusters single cells in multiple scRNA-seq experiments of similar cell types and markers but varying expression patterns such that the scRNA-seq data are better integrated than typical pooled analyses which only increase the sample size. By controlling the variance among the cell clusters within each dataset and across all the datasets, scVDMC detects cell sub-populations in each individual experiment with shared cell-type markers but varying cluster centers among all the experiments. Applied to two real scRNA-seq datasets with several replicates and one large-scale droplet-based dataset on three patient samples, scVDMC more accurately detected cell populations and known cell markers than pooled clustering and other recently proposed scRNA-seq clustering methods. In the case study applied to in-house Recessive Dystrophic Epidermolysis Bullosa (RDEB) scRNA-seq data, scVDMC revealed several new cell types and unknown markers validated by flow cytometry. MATLAB/Octave code available at https://github.com/kuanglab/scVDMC. PMID:29630593

Comparative analysis of bones, mites, soil chemistry, nematodes and soil micro-eukaryotes from a suspected homicide to estimate the post-mortem interval.

PubMed

Szelecz, Ildikó; Lösch, Sandra; Seppey, Christophe V W; Lara, Enrique; Singer, David; Sorge, Franziska; Tschui, Joelle; Perotti, M Alejandra; Mitchell, Edward A D

2018-01-08

Criminal investigations of suspected murder cases require estimating the post-mortem interval (PMI, or time after death) which is challenging for long PMIs. Here we present the case of human remains found in a Swiss forest. We have used a multidisciplinary approach involving the analysis of bones and soil samples collected beneath the remains of the head, upper and lower body and "control" samples taken a few meters away. We analysed soil chemical characteristics, mites and nematodes (by microscopy) and micro-eukaryotes (by Illumina high throughput sequencing). The PMI estimate on hair 14 C-data via bomb peak radiocarbon dating gave a time range of 1 to 3 years before the discovery of the remains. Cluster analyses for soil chemical constituents, nematodes, mites and micro-eukaryotes revealed two clusters 1) head and upper body and 2) lower body and controls. From mite evidence, we conclude that the body was probably brought to the site after death. However, chemical analyses, nematode community analyses and the analyses of micro-eukaryotes indicate that decomposition took place at least partly on site. This study illustrates the usefulness of combining several lines of evidence for the study of homicide cases to better calibrate PMI inference tools.

Epidemic characteristics and spatio-temporal patterns of scrub typhus during 2006-2013 in Tai'an, Northern China.

PubMed

Zheng, L; Yang, H-L; Bi, Z-W; Kou, Z-Q; Zhang, L-Y; Zhang, A-H; Yang, L; Zhao, Z-T

2015-08-01

Tai'an, a famous cultural tourist district, is a new endemic foci of scrub typhus in northern China. Frequent reports of travel-acquired cases and absence of effective vaccine indicated a significant health problem of scrub typhus in Tai'an. Thus, descriptive epidemiological methods and spatial-temporal scan statistics were used to describe the epidemic characteristics and detect the significant clusters of the high incidence of scrub typhus at the town level in Tai'an. Results of descriptive epidemiological analysis showed a total of 490 cases were reported in Tai'an with the annual average incidence ranging from 0·48 to 2·27/100 000 during 2006-2013. Females, the elderly and farmers are the high-risk groups. Monthly changes of scrub typhus cases indicated an obvious epidemic period in autumn. Spatial-temporal distribution analysis, showed significant clusters of high incidence mainly located in eastern and northern Tai'an. Our study suggests that more effective, targeted measures for local residents should be implemented in the eastern and northern areas of Tai'an in autumn. Meanwhile, it may prove beneficial for health policy makers to advise travellers to take preventive measures in order to minimize the risk of infection of scrub typhus in Tai'an.

Clustering and Phase Transitions on a Neutral Landscape

NASA Astrophysics Data System (ADS)

Scott, Adam; King, Dawn; Maric, Nevena; Bahar, Sonya

2012-02-01

The problem of speciation and species aggregation on a neutral landscape, subject to random mutational fluctuations rather than selective drive, has been a focus of research since the seminal work of Kimura on genetic drift. These ideas have received increased attention due to the more recent development of a neutral ecological theory by Hubbell. De Aguiar et al. recently demonstrated, in a computational model, that speciation can occur under neutral conditions; this study bears some comparison with more mathematical studies of clustering on neutral landscapes in the context of branching and annihilating random walks. Here, we show that clustering can occur on a neutral landscape where the dimensions specify the simulated organisms' phenotypes. Unlike the De Aguiar et al. model, we simulate sympatric speciation: the organisms cluster phenotypically, but are not spatially separated. Moreover, we find that clustering occurs not only in the case of assortative mating, but also in the case of asexual fission. Clustering is not observed in a control case where organisms can mate randomly. We find that the population size and the number of clusters undergo phase-transition-like behavior as the maximum mutation size is varied.

A spatial scan statistic for compound Poisson data.

PubMed

Rosychuk, Rhonda J; Chang, Hsing-Ming

2013-12-20

The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits. Copyright © 2013 John Wiley & Sons, Ltd.

Computer-aided tracking and characterization of homicides and sexual assaults (CATCH)

NASA Astrophysics Data System (ADS)

Kangas, Lars J.; Terrones, Kristine M.; Keppel, Robert D.; La Moria, Robert D.

1999-03-01

When a serial offender strikes, it usually means that the investigation is unprecedented for that police agency. The volume of incoming leads and pieces of information in the case(s) can be overwhelming as evidenced by the thousands of leads gathered in the Ted Bundy Murders, Atlanta Child Murders, and the Green River Murders. Serial cases can be long term investigations in which the suspect remains unknown and continues to perpetrate crimes. With state and local murder investigative systems beginning to crop up, it will become important to manage that information in a timely and efficient way by developing computer programs to assist in that task. One vital function will be to compare violent crime cases from different jurisdictions so investigators can approach the investigation knowing that similar cases exist. CATCH (Computer Aided Tracking and Characterization of Homicides) is being developed to assist crime investigations by assessing likely characteristics of unknown offenders, by relating a specific crime case to other cases, and by providing a tool for clustering similar cases that may be attributed to the same offenders. CATCH is a collection of tools that assist the crime analyst in the investigation process by providing advanced data mining and visualization capabilities.These tools include clustering maps, query tools, geographic maps, timelines, etc. Each tool is designed to give the crime analyst a different view of the case data. The clustering tools in CATCH are based on artificial neural networks (ANNs). The ANNs learn to cluster similar cases from approximately 5000 murders and 3000 sexual assaults residing in a database. The clustering algorithm is applied to parameters describing modus operandi (MO), signature characteristics of the offenders, and other parameters describing the victim and offender. The proximity of cases within a two-dimensional representation of the clusters allows the analyst to identify similar or serial murders and sexual assaults.

Constraining neutrino properties with a Euclid-like galaxy cluster survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cerbolini, M. Costanzi Alunno; Sartoris, B.; Borgani, S.

2013-06-01

We perform a forecast analysis on how well a Euclid-like photometric galaxy cluster survey will constrain the total neutrino mass and effective number of neutrino species. We base our analysis on the Monte Carlo Markov Chains technique by combining information from cluster number counts and cluster power spectrum. We find that combining cluster data with Cosmic Microwave Background (CMB) measurements from Planck improves by more than an order of magnitude the constraint on neutrino masses compared to each probe used independently. For the ΛCDM+m{sub ν} model the 2σ upper limit on total neutrino mass shifts from Σm{sub ν} < 0.35more » eV using cluster data alone to Σm{sub ν} < 0.031 eV when combined with Planck data. When a non-standard scenario with N{sub eff}≠3.046 number of neutrino species is considered, we estimate an upper limit of N{sub eff} < 3.14 (95%CL), while the bounds on neutrino mass are relaxed to Σm{sub ν} < 0.040 eV. This accuracy would be sufficient for a 2σ detection of neutrino mass even in the minimal normal hierarchy scenario (Σm{sub ν} ≅ 0.05 eV). In addition to the extended ΛCDM+m{sub ν}+N{sub eff} model we also consider scenarios with a constant dark energy equation of state and a non-vanishing curvature. When these models are considered the error on Σm{sub ν} is only slightly affected, while there is a larger impact of the order of ∼ 15% and ∼ 20% respectively on the 2σ error bar of N{sub eff} with respect to the standard case. To assess the effect of an uncertain knowledge of the relation between cluster mass and optical richness, we also treat the ΛCDM+m{sub ν}+N{sub eff} case with free nuisance parameters, which parameterize the uncertainties on the cluster mass determination. Adopting the over-conservative assumption of no prior knowledge on the nuisance parameter the loss of information from cluster number counts leads to a large degradation of neutrino constraints. In particular, the upper bounds for Σm{sub ν} are relaxed by a factor larger than two, Σm{sub ν} < 0.083 eV (95%CL), hence compromising the possibility of detecting the total neutrino mass with good significance. We thus confirm the potential that a large optical/near-IR cluster survey, like that to be carried out by Euclid, could have in constraining neutrino properties, and we stress the importance of a robust measurement of masses, e.g. from weak lensing within the Euclid survey, in order to full exploit the cosmological information carried by such survey.« less

Transmission of Extensively Drug-Resistant Tuberculosis in South Africa

PubMed Central

Shah, N. Sarita; Auld, Sara C.; Brust, James C.M.; Mathema, Barun; Ismail, Nazir; Moodley, Pravi; Mlisana, Koleka; Allana, Salim; Campbell, Angela; Mthiyane, Thuli; Morris, Natashia; Mpangase, Primrose; van der Meulen, Hermina; Omar, Shaheed V.; Brown, Tyler S.; Narechania, Apurva; Shaskina, Elena; Kapwata, Thandi; Kreiswirth, Barry; Gandhi, Neel R.

2017-01-01

BACKGROUND Drug-resistant tuberculosis threatens recent gains in the treatment of tuberculosis and human immunodeficiency virus (HIV) infection worldwide. A widespread epidemic of extensively drug-resistant (XDR) tuberculosis is occurring in South Africa, where cases have increased substantially since 2002. The factors driving this rapid increase have not been fully elucidated, but such knowledge is needed to guide public health interventions. METHODS We conducted a prospective study involving 404 participants in KwaZulu-Natal Province, South Africa, with a diagnosis of XDR tuberculosis between 2011 and 2014. Interviews and medical-record reviews were used to elicit information on the participants’ history of tuberculosis and HIV infection, hospitalizations, and social networks. Mycobacterium tuberculosis isolates underwent insertion sequence (IS)6110 restriction-fragment– length polymorphism analysis, targeted gene sequencing, and whole-genome sequencing. We used clinical and genotypic case definitions to calculate the proportion of cases of XDR tuberculosis that were due to inadequate treatment of multidrug-resistant (MDR) tuberculosis (i.e., acquired resistance) versus those that were due to transmission (i.e., transmitted resistance). We used social-network analysis to identify community and hospital locations of transmission. RESULTS Of the 404 participants, 311 (77%) had HIV infection; the median CD4+ count was 340 cells per cubic millimeter (interquartile range, 117 to 431). A total of 280 participants (69%) had never received treatment for MDR tuberculosis. Genotypic analysis in 386 participants revealed that 323 (84%) belonged to 1 of 31 clusters. Clusters ranged from 2 to 14 participants, except for 1 large cluster of 212 participants (55%) with a LAM4/KZN strain. Person-to-person or hospital-based epidemiologic links were identified in 123 of 404 participants (30%). CONCLUSIONS The majority of cases of XDR tuberculosis in KwaZulu-Natal, South Africa, an area with a high tuberculosis burden, were probably due to transmission rather than to inadequate treatment of MDR tuberculosis. These data suggest that control of the epidemic of drug-resistant tuberculosis requires an increased focus on interrupting transmission. (Funded by the National Institute of Allergy and Infectious Diseases and others.) PMID:28099825

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

NASA Astrophysics Data System (ADS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.

Using exploratory data analysis to identify and predict patterns of human Lyme disease case clustering within a multistate region, 2010-2014.

PubMed

Hendricks, Brian; Mark-Carew, Miguella

2017-02-01

Lyme disease is the most commonly reported vectorborne disease in the United States. The objective of our study was to identify patterns of Lyme disease reporting after multistate inclusion to mitigate potential border effects. County-level human Lyme disease surveillance data were obtained from Kentucky, Maryland, Ohio, Pennsylvania, Virginia, and West Virginia state health departments. Rate smoothing and Local Moran's I was performed to identify clusters of reporting activity and identify spatial outliers. A logistic generalized estimating equation was performed to identify significant associations in disease clustering over time. Resulting analyses identified statistically significant (P=0.05) clusters of high reporting activity and trends over time. High reporting activity aggregated near border counties in high incidence states, while low reporting aggregated near shared county borders in non-high incidence states. Findings highlight the need for exploratory surveillance approaches to describe the extent to which state level reporting affects accurate estimation of Lyme disease progression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clusters of cultures: diversity in meaning of family value and gender role items across Europe.

PubMed

van Vlimmeren, Eva; Moors, Guy B D; Gelissen, John P T M

2017-01-01

Survey data are often used to map cultural diversity by aggregating scores of attitude and value items across countries. However, this procedure only makes sense if the same concept is measured in all countries. In this study we argue that when (co)variances among sets of items are similar across countries, these countries share a common way of assigning meaning to the items. Clusters of cultures can then be observed by doing a cluster analysis on the (co)variance matrices of sets of related items. This study focuses on family values and gender role attitudes. We find four clusters of cultures that assign a distinct meaning to these items, especially in the case of gender roles. Some of these differences reflect response style behavior in the form of acquiescence. Adjusting for this style effect impacts on country comparisons hence demonstrating the usefulness of investigating the patterns of meaning given to sets of items prior to aggregating scores into cultural characteristics.

Investigating the usefulness of a cluster-based trend analysis to detect visual field progression in patients with open-angle glaucoma.

PubMed

Aoki, Shuichiro; Murata, Hiroshi; Fujino, Yuri; Matsuura, Masato; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Hirasawa, Kazunori; Shoji, Nobuyuki; Asaoka, Ryo

2017-12-01

To investigate the usefulness of the Octopus (Haag-Streit) EyeSuite's cluster trend analysis in glaucoma. Ten visual fields (VFs) with the Humphrey Field Analyzer (Carl Zeiss Meditec), spanning 7.7 years on average were obtained from 728 eyes of 475 primary open angle glaucoma patients. Mean total deviation (mTD) trend analysis and EyeSuite's cluster trend analysis were performed on various series of VFs (from 1st to 10th: VF1-10 to 6th to 10th: VF6-10). The results of the cluster-based trend analysis, based on different lengths of VF series, were compared against mTD trend analysis. Cluster-based trend analysis and mTD trend analysis results were significantly associated in all clusters and with all lengths of VF series. Between 21.2% and 45.9% (depending on VF series length and location) of clusters were deemed to progress when the mTD trend analysis suggested no progression. On the other hand, 4.8% of eyes were observed to progress using the mTD trend analysis when cluster trend analysis suggested no progression in any two (or more) clusters. Whole field trend analysis can miss local VF progression. Cluster trend analysis appears as robust as mTD trend analysis and useful to assess both sectorial and whole field progression. Cluster-based trend analyses, in particular the definition of two or more progressing cluster, may help clinicians to detect glaucomatous progression in a timelier manner than using a whole field trend analysis, without significantly compromising specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005–2014

PubMed Central

Mahara, Gehendra; Wang, Chao; Huo, Da; Xu, Qin; Huang, Fangfang; Tao, Lixin; Guo, Jin; Cao, Kai; Long, Liu; Chhetri, Jagadish K.; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-01-01

Objective: To probe the spatiotemporal patterns of the incidence of scarlet fever in Beijing, China, from 2005 to 2014. Methods: A spatiotemporal analysis was conducted at the district/county level in the Beijing region based on the reported cases of scarlet fever during the study period. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. Likewise, the space-time scan statistic was used to detect the space-time clusters, including the relative risk of scarlet fever incidence across all settings. Results: A total of 26,860 scarlet fever cases were reported in Beijing during the study period (2005–2014). The average annual incidence of scarlet fever was 14.25 per 100,000 population (range, 6.76 to 32.03 per 100,000). The incidence among males was higher than that among females, and more than two-thirds of scarlet fever cases (83.8%) were among children 3–8 years old. The seasonal incidence peaks occurred from March to July. A higher relative risk area was mainly in the city and urban districts of Beijing. The most likely space-time clusters and secondary clusters were detected to be diversely distributed in every study year. Conclusions: The spatiotemporal patterns of scarlet fever were relatively unsteady in Beijing from 2005 to 2014. The at-risk population was mainly scattered in urban settings and dense districts with high population, indicating a positive relationship between population density and increased risk of scarlet fever exposure. Children under 15 years of age were the most susceptible to scarlet fever. PMID:26784213

Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005-2014.

PubMed

Mahara, Gehendra; Wang, Chao; Huo, Da; Xu, Qin; Huang, Fangfang; Tao, Lixin; Guo, Jin; Cao, Kai; Long, Liu; Chhetri, Jagadish K; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-01-15

To probe the spatiotemporal patterns of the incidence of scarlet fever in Beijing, China, from 2005 to 2014. A spatiotemporal analysis was conducted at the district/county level in the Beijing region based on the reported cases of scarlet fever during the study period. Moran's autocorrelation coefficient was used to examine the spatial autocorrelation of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. Likewise, the space-time scan statistic was used to detect the space-time clusters, including the relative risk of scarlet fever incidence across all settings. A total of 26,860 scarlet fever cases were reported in Beijing during the study period (2005-2014). The average annual incidence of scarlet fever was 14.25 per 100,000 population (range, 6.76 to 32.03 per 100,000). The incidence among males was higher than that among females, and more than two-thirds of scarlet fever cases (83.8%) were among children 3-8 years old. The seasonal incidence peaks occurred from March to July. A higher relative risk area was mainly in the city and urban districts of Beijing. The most likely space-time clusters and secondary clusters were detected to be diversely distributed in every study year. The spatiotemporal patterns of scarlet fever were relatively unsteady in Beijing from 2005 to 2014. The at-risk population was mainly scattered in urban settings and dense districts with high population, indicating a positive relationship between population density and increased risk of scarlet fever exposure. Children under 15 years of age were the most susceptible to scarlet fever.

Detection of major climatic and environmental predictors of liver fluke exposure risk in Ireland using spatial cluster analysis.

PubMed

Selemetas, Nikolaos; de Waal, Theo

2015-04-30

Fasciolosis caused by Fasciola hepatica (liver fluke) can cause significant economic and production losses in dairy cow farms. The aim of the current study was to identify important weather and environmental predictors of the exposure risk to liver fluke by detecting clusters of fasciolosis in Ireland. During autumn 2012, bulk-tank milk samples from 4365 dairy farms were collected throughout Ireland. Using an in-house antibody-detection ELISA, the analysis of BTM samples showed that 83% (n=3602) of dairy farms had been exposed to liver fluke. The Getis-Ord Gi* statistic identified 74 high-risk and 130 low-risk significant (P<0.01) clusters of fasciolosis. The low-risk clusters were mostly located in the southern regions of Ireland, whereas the high-risk clusters were mainly situated in the western part. Several climatic variables (monthly and seasonal mean rainfall and temperatures, total wet days and rain days) and environmental datasets (soil types, enhanced vegetation index and normalised difference vegetation index) were used to investigate dissimilarities in the exposure to liver fluke between clusters. Rainfall, total wet days and rain days, and soil type were the significant classes of climatic and environmental variables explaining the differences between significant clusters. A discriminant function analysis was used to predict the exposure risk to liver fluke using 80% of data for modelling and the remaining subset of 20% for post hoc model validation. The most significant predictors of the model risk function were total rainfall in August and September and total wet days. The risk model presented 100% sensitivity and 91% specificity and an accuracy of 95% correctly classified cases. A risk map of exposure to liver fluke was constructed with higher probability of exposure in western and north-western regions. The results of this study identified differences between clusters of fasciolosis in Ireland regarding climatic and environmental variables and detected significant predictors of the exposure risk to liver fluke. Copyright © 2015 Elsevier B.V. All rights reserved.

Demographic characterization and spatial cluster analysis of human Salmonella 1,4,[5],12:i:- infections in Portugal: A 10year study.

PubMed

Seixas, R; Nunes, T; Machado, J; Tavares, L; Owen, S P; Bernardo, F; Oliveira, M

Salmonella 1,4,[5],12:i:- is presently considered one of the major serovars responsible for human salmonellosis worldwide. Due to its recent emergence, studies assessing the demographic characterization and spatial epidemiology of salmonellosis 1,4,[5],12:i:- at local- or country-level are lacking. In this study, a analysis was conducted over a 10year period, from 2000 to the first quarter of 2011 at the Portuguese National Laboratory in Portugal mainland, with a total of 215 Salmonella 1,4,[5],12:i:- serotyped isolates obtained from human infections by a passive surveillance system. Data regarding source, year and month of sampling, gender, age, district and municipality of the patients were registered. Descriptive statistical analysis and a spatial scan statistic combined with a geographic information system were employed to characterize the epidemiology and identify spatial clusters. Results showed that most districts have reports of Salmonella 1,4,[5],12:i:-, with a higher number of cases at the Portuguese coastland, including districts like Porto (n=60, 27.9%), Lisboa (n=29, 13.5%) and Aveiro (n=28, 13.0%). An increased incidence was observed in the period from 2004 to 2011 and most infections occurred during May and October. Spatial analysis revealed 4 clusters of higher than expected infection rates. Three were located in the north of Portugal, including two at the coastland (Cluster 1 [RR=3.58, p≤0.001] and 4 [RR=10.42 p≤0.230]), and one at the countryside (Cluster 3 [RR=17.76, p≤0.001]). A larger cluster was detected involving the center and south of Portugal (Cluster 2 [RR=4.85, p≤0.001]). The present study was elaborated with data provided by a passive surveillance system, which may originate an underestimation of disease burden. However, this is the first report describing the incidence and the distribution of areas with higher risk of infection in Portugal, revealing that Salmonella 1,4,[5],12:i:- displayed a significant geographic clustering and these areas should be further evaluated to identify risk factors in order to establish prevention programs. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Photosensitized Reduction of Carbon Dioxide in Solution Using Noble-Metal Clusters for Electron Transfer

NASA Astrophysics Data System (ADS)

Toshima, Naoki; Yamaji, Yumi; Teranishi, Toshiharu; Yonezawa, Tetsu

1995-03-01

Carbon dioxide was reduced to methane by visible-light irradiation of a solution composed of tris(bipyridine)ruthenium(III) as photosensitizer, ethylenediaminetetraacetic acid disodium salt as sacrificial reagent, methyl viologen as electron relay, and a colloidal dispersion of polymer-protected noble-metal clusters, prepared by alcohol-reduction, as catalyst. Among the noble-metal clusters examined, Pt clusters showed the highest activity for the formation of methane as well as hydrogen. In order to improve the activity, oxidized clusters and bimetallic clusters were also applied. For example, the CH4 yield in 3-h irradiation increased from 51 x 10-3 μmol with unoxidized Pt clusters to 72 x 10-3 μmol with partially oxidized ones. In the case of Pt/Ru bimetalic systems, the improvement of the catalytic activity by air treatment was much greater than in case of monometallic clusters.

Teenage suicide cluster formation and contagion: implications for primary care

PubMed Central

Johansson, Lars; Lindqvist, Per; Eriksson, Anders

2006-01-01

Background We have previously studied unintentional as well as intentional injury deaths among teenagers living in the four northernmost counties, forming approximately 55% of Sweden with 908,000 inhabitants in 1991. During this work, we found what we suspected to be a suicide cluster among teenagers and we also suspected contagion since there were links between these cases. In this present study, we investigate the occurrence of suicide clustering among teenagers, analyze cluster definitions, and suggest preventive measures. Methods A retrospective study of teenager suicides autopsied at the Department of Forensic Medicine in Umeå, Sweden, during 1981 through 2000. Police reports, autopsy protocols, and medical records were studied in all cases, and the police officers that conducted the investigation at the scene were interviewed in all cluster cases. Parents of the suicide victims of the first cluster were also interviewed. Two aggregations of teenager suicides were detected and evaluated as possible suicide clusters using the US Centers for Disease Control definition of a suicide cluster. Results Two clusters including six teenagers were confirmed, and contagion was established within each cluster. Conclusion The general practitioner is identified as a key person in the aftermath of a teenage suicide since the general practitioner often meet the family, friends of the deceased, and other acquaintances early in the process after a suicide. This makes the general practitioner suitable to initiate contacts with others involved in the well-being of the young, in order to prevent suicide cluster formation and para-suicidal activities. PMID:16707009

[Space-time suicide clustering in the community of Antequera (Spain)].

PubMed

Pérez-Costillas, Lucía; Blasco-Fontecilla, Hilario; Benítez, Nicolás; Comino, Raquel; Antón, José Miguel; Ramos-Medina, Valentín; Lopez, Amalia; Palomo, José Luis; Madrigal, Lucía; Alcalde, Javier; Perea-Millá, Emilio; Artieda-Urrutia, Paula; de León-Martínez, Victoria; de Diego Otero, Yolanda

2015-01-01

Approximately 3,500 people commit suicide every year in Spain. The main aim of this study is to explore if a spatial and temporal clustering of suicide exists in the region of Antequera (Málaga, España). Sample and procedure: All suicides from January 1, 2004 to December 31, 2008 were identified using data from the Forensic Pathology Department of the Institute of Legal Medicine, Málaga (España). Geolocalisation. Google Earth was used to calculate the coordinates for each suicide decedent's address. Statistical analysis. A spatiotemporal permutation scan statistic and the Ripley's K function were used to explore spatiotemporal clustering. Pearson's chi-squared was used to determine whether there were differences between suicides inside and outside the spatiotemporal clusters. A total of 120 individuals committed suicide within the region of Antequera, of which 96 (80%) were included in our analyses. Statistically significant evidence for 7 spatiotemporal suicide clusters emerged within critical limits for the 0-2.5 km distance and for the first and second semanas (P<.05 in both cases) after suicide. There was not a single subject diagnosed with a current psychotic disorder, among suicides within clusters, whereas outside clusters, 20% had this diagnosis (X2=4.13; df=1; P<.05). There are spatiotemporal suicide clusters in the area surrounding Antequera. Patients diagnosed with current psychotic disorder are less likely to be influenced by the factors explaining suicide clustering. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

Variation of gunshot injury patterns in mortality associated with human rights abuses and armed conflict: an exploratory study.

PubMed

Baraybar, Jose Pablo

2015-09-01

The analysis of the distribution of gunshot injuries in a sample of 777 sets of human remains of proven human rights abuse from Somaliland, the Balkans and Peru is compared to frequencies of injuries sustained by combatants in contemporary conflicts reported in the literature. Principal Component Analysis (PCA) reduced the data to three components accounting for 82.94% of the variance. The first component with 38.31% of variance shows segments Arms and thorax/abdomen to be positively correlated (0.887 and 0.662, respectively); the segment head/neck is strongly correlated (0.951) to the second component while the segment thorax/abdomen shows a low, negative correlation (-0.388). Finally in the third component only the legs are strongly correlated (0.991). Data was further subjected to a K-means cluster analysis to determine the likely groupings combining the four types of injuries. Each of the three clusters reproduced similar patterns observed in the PCA: Cluster 1 shows the prevalence of injuries to the thorax/abdomen and extremities in addition to injuries to the head/neck; Cluster 2 shows injuries to the head/neck and Cluster 3 injuries to the thorax/abdomen and a lower representation of the arms and legs. Most of the cases (70.5%), irrespective of geography and type of site (attack or detention), were grouped into Cluster 2. Such comparison shows that in human rights abuse, irrespective of their geography, gunshot injuries tend to follow a pattern favouring the head/neck and thorax/abdomen areas over the extremities, the reverse pattern observed in contemporary combat operations. In those settings gunshot wound trauma is the second cause of mortality/morbidity (after fragmenting ammunition) and its distribution concentrates on the extremities, thorax/abdomen and head; following the pattern of protective armour when it is used. Considering that human rights abuses are often presented as encounters between two armed groups in the context of counter-insurgency operations, a careful analysis of gunshot injury patterns could serve as an indicator that in fact murder, rather than combat, took place and the intention was to kill rather than to maim or render people unfit for battle. To compare the variation of gunshot injury patterns between mortality associated with human rights abuses and armed conflict in selected samples from different countries. Literature review and case analysis. Original statistical analysis of gunshot injuries on human remains (n=777) recovered from mass or clandestine graves associated with human rights abuses in countries in Somaliland, the Balkans and Peru (1983-1995) and literature review of mortality caused by armed conflicts. Mechanism of gunshot injury and wound distribution pattern in geographically diverse samples of human rights abuse. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

QMRA for Drinking Water: 2. The Effect of Pathogen Clustering in Single-Hit Dose-Response Models.

PubMed

Nilsen, Vegard; Wyller, John

2016-01-01

Spatial and/or temporal clustering of pathogens will invalidate the commonly used assumption of Poisson-distributed pathogen counts (doses) in quantitative microbial risk assessment. In this work, the theoretically predicted effect of spatial clustering in conventional "single-hit" dose-response models is investigated by employing the stuttering Poisson distribution, a very general family of count distributions that naturally models pathogen clustering and contains the Poisson and negative binomial distributions as special cases. The analysis is facilitated by formulating the dose-response models in terms of probability generating functions. It is shown formally that the theoretical single-hit risk obtained with a stuttering Poisson distribution is lower than that obtained with a Poisson distribution, assuming identical mean doses. A similar result holds for mixed Poisson distributions. Numerical examples indicate that the theoretical single-hit risk is fairly insensitive to moderate clustering, though the effect tends to be more pronounced for low mean doses. Furthermore, using Jensen's inequality, an upper bound on risk is derived that tends to better approximate the exact theoretical single-hit risk for highly overdispersed dose distributions. The bound holds with any dose distribution (characterized by its mean and zero inflation index) and any conditional dose-response model that is concave in the dose variable. Its application is exemplified with published data from Norovirus feeding trials, for which some of the administered doses were prepared from an inoculum of aggregated viruses. The potential implications of clustering for dose-response assessment as well as practical risk characterization are discussed. © 2016 Society for Risk Analysis.

Pseudomonas aeruginosa in Dairy Goats: Genotypic and Phenotypic Comparison of Intramammary and Environmental Isolates

PubMed Central

Scaccabarozzi, Licia; Leoni, Livia; Ballarini, Annalisa; Barberio, Antonio; Locatelli, Clara; Casula, Antonio; Bronzo, Valerio; Pisoni, Giuliano; Jousson, Olivier; Morandi, Stefano; Rapetti, Luca; García-Fernández, Aurora; Moroni, Paolo

2015-01-01

Following the identification of a case of severe clinical mastitis in a Saanen dairy goat (goat A), an average of 26 lactating goats in the herd was monitored over a period of 11 months. Milk microbiological analysis revealed the presence of Pseudomonas aeruginosa in 7 of the goats. Among these 7 does, only goat A showed clinical signs of mastitis. The 7 P. aeruginosa isolates from the goat milk and 26 P. aeruginosa isolates from environmental samples were clustered by RAPD-PCR and PFGE analyses in 3 genotypes (G1, G2, G3) and 4 clusters (A, B, C, D), respectively. PFGE clusters A and B correlated with the G1 genotype and included the 7 milk isolates. Although it was not possible to identify the infection source, these results strongly suggest a spreading of the infection from goat A. Clusters C and D overlapped with genotypes G2 and G3, respectively, and included only environmental isolates. The outcome of the antimicrobial susceptibility test performed on the isolates revealed 2 main patterns of multiple resistance to beta-lactam antibiotics and macrolides. Virulence related phenotypes were analyzed, such as swarming and swimming motility, production of biofilm and production of secreted virulence factors. The isolates had distinct phenotypic profiles, corresponding to genotypes G1, G2 and G3. Overall, correlation analysis showed a strong correlation between sampling source, RAPD genotype, PFGE clusters, and phenotypic clusters. The comparison of the levels of virulence related phenotypes did not indicate a higher pathogenic potential in the milk isolates as compared to the environmental isolates. PMID:26606430

Towards the use of computationally inserted lesions for mammographic CAD assessment

NASA Astrophysics Data System (ADS)

Ghanian, Zahra; Pezeshk, Aria; Petrick, Nicholas; Sahiner, Berkman

2018-03-01

Computer-aided detection (CADe) devices used for breast cancer detection on mammograms are typically first developed and assessed for a specific "original" acquisition system, e.g., a specific image detector. When CADe developers are ready to apply their CADe device to a new mammographic acquisition system, they typically assess the CADe device with images acquired using the new system. Collecting large repositories of clinical images containing verified cancer locations and acquired by the new image acquisition system is costly and time consuming. Our goal is to develop a methodology to reduce the clinical data burden in the assessment of a CADe device for use with a different image acquisition system. We are developing an image blending technique that allows users to seamlessly insert lesions imaged using an original acquisition system into normal images or regions acquired with a new system. In this study, we investigated the insertion of microcalcification clusters imaged using an original acquisition system into normal images acquired with that same system utilizing our previously-developed image blending technique. We first performed a reader study to assess whether experienced observers could distinguish between computationally inserted and native clusters. For this purpose, we applied our insertion technique to clinical cases taken from the University of South Florida Digital Database for Screening Mammography (DDSM) and the Breast Cancer Digital Repository (BCDR). Regions of interest containing microcalcification clusters from one breast of a patient were inserted into the contralateral breast of the same patient. The reader study included 55 native clusters and their 55 inserted counterparts. Analysis of the reader ratings using receiver operating characteristic (ROC) methodology indicated that inserted clusters cannot be reliably distinguished from native clusters (area under the ROC curve, AUC=0.58±0.04). Furthermore, CADe sensitivity was evaluated on mammograms with native and inserted microcalcification clusters using a commercial CADe system. For this purpose, we used full field digital mammograms (FFDMs) from 68 clinical cases, acquired at the University of Michigan Health System. The average sensitivities for native and inserted clusters were equal, 85.3% (58/68). These results demonstrate the feasibility of using the inserted microcalcification clusters for assessing mammographic CAD devices.

1 H-NMR with Multivariate Analysis for Automobile Lubricant Comparison.

PubMed

Kim, Siwon; Yoon, Dahye; Lee, Dong-Kye; Yoon, Changshin; Kim, Suhkmann

2017-07-01

Identification of suspected automobile-related lubricants could provide valuable information in forensic cases. We examined that automobile lubricants might exhibit the chemometric characteristics to their individual usages. To compare the degree of clustering in the plots, we co-plotted general industrial oils that were highly dissimilar with automobile lubricants in additive compositions. 1 H-NMR spectroscopy was used with multivariate statistics as a tool for grouping, clustering, and identification of automobile lubricants in laboratory conditions. We analyzed automobile lubricants including automobile engine oils, automobile transmission oils, automobile gear oils, and motorcycle oils. In contrast to the general industrial oils, automobile lubricants showed relatively high tendencies of clustering to their usages. Our pilot study demonstrated that the comparison of known and questioned samples to their usages might be possible in forensic fields. © 2017 American Academy of Forensic Sciences.

SSAW: A new sequence similarity analysis method based on the stationary discrete wavelet transform.

PubMed

Lin, Jie; Wei, Jing; Adjeroh, Donald; Jiang, Bing-Hua; Jiang, Yue

2018-05-02

Alignment-free sequence similarity analysis methods often lead to significant savings in computational time over alignment-based counterparts. A new alignment-free sequence similarity analysis method, called SSAW is proposed. SSAW stands for Sequence Similarity Analysis using the Stationary Discrete Wavelet Transform (SDWT). It extracts k-mers from a sequence, then maps each k-mer to a complex number field. Then, the series of complex numbers formed are transformed into feature vectors using the stationary discrete wavelet transform. After these steps, the original sequence is turned into a feature vector with numeric values, which can then be used for clustering and/or classification. Using two different types of applications, namely, clustering and classification, we compared SSAW against the the-state-of-the-art alignment free sequence analysis methods. SSAW demonstrates competitive or superior performance in terms of standard indicators, such as accuracy, F-score, precision, and recall. The running time was significantly better in most cases. These make SSAW a suitable method for sequence analysis, especially, given the rapidly increasing volumes of sequence data required by most modern applications.

Factors associated with recently transmitted Mycobacterium tuberculosis strain MS0006 in Hinds County, Mississippi.

PubMed

Temple, Brian; Kwara, Awewura; Sunesara, Imran; Mena, Leandro; Dobbs, Thomas; Henderson, Harold; Holcomb, Mike; Webb, Risa

2011-12-01

The objective of this study was to investigate risk factors associated with tuberculosis (TB) transmission that was caused by Mycobacterium tuberculosis strain MS0006 from 2004 to 2009 in Hinds County, Mississippi. DNA fingerprinting using spoligotyping, mycobacterial interspersed repetitive unit, and IS6110-based restriction fragment length polymorphism of culture-confirmed cases of TB was performed. Clinical and demographic factors associated with strain MS0006 were analyzed by univariate and multivariate analysis. Of the 144 cases of TB diagnosed during the study period, 117 were culture positive with fingerprints available. There were 48 different strains, of which 6 clustered strains were distributed among 74 patients. The MS0006 strain accounted for 46.2% of all culture-confirmed cases. Risk factors for having the MS0006 strain in a univariate analysis included homelessness, HIV co-infection, sputum smear negativity, tuberculin skin test negativity, and noninjectable drug use. Multivariate analysis identified homelessness (odds ratio 7.88, 95% confidence interval 2.90-21.35) and African American race (odds ratio 5.80, 95% confidence interval 1.37-24.55) as independent predictors of having TB caused by the MS0006 strain of M. tuberculosis. Our findings suggest that a majority of recently transmitted TB in the studied county was caused by the MS0006 strain. African American race and homelessness were significant risk factors for inclusion in the cluster. Molecular epidemiology techniques continue to provide in-depth analysis of disease transmission and play a vital role in effective contact tracing and interruption of ongoing transmission.

Computer aided detection of clusters of microcalcifications on full field digital mammograms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ge Jun; Sahiner, Berkman; Hadjiiski, Lubomir M.

2006-08-15

We are developing a computer-aided detection (CAD) system to identify microcalcification clusters (MCCs) automatically on full field digital mammograms (FFDMs). The CAD system includes six stages: preprocessing; image enhancement; segmentation of microcalcification candidates; false positive (FP) reduction for individual microcalcifications; regional clustering; and FP reduction for clustered microcalcifications. At the stage of FP reduction for individual microcalcifications, a truncated sum-of-squares error function was used to improve the efficiency and robustness of the training of an artificial neural network in our CAD system for FFDMs. At the stage of FP reduction for clustered microcalcifications, morphological features and features derived from themore » artificial neural network outputs were extracted from each cluster. Stepwise linear discriminant analysis (LDA) was used to select the features. An LDA classifier was then used to differentiate clustered microcalcifications from FPs. A data set of 96 cases with 192 images was collected at the University of Michigan. This data set contained 96 MCCs, of which 28 clusters were proven by biopsy to be malignant and 68 were proven to be benign. The data set was separated into two independent data sets for training and testing of the CAD system in a cross-validation scheme. When one data set was used to train and validate the convolution neural network (CNN) in our CAD system, the other data set was used to evaluate the detection performance. With the use of a truncated error metric, the training of CNN could be accelerated and the classification performance was improved. The CNN in combination with an LDA classifier could substantially reduce FPs with a small tradeoff in sensitivity. By using the free-response receiver operating characteristic methodology, it was found that our CAD system can achieve a cluster-based sensitivity of 70, 80, and 90 % at 0.21, 0.61, and 1.49 FPs/image, respectively. For case-based performance evaluation, a sensitivity of 70, 80, and 90 % can be achieved at 0.07, 0.17, and 0.65 FPs/image, respectively. We also used a data set of 216 mammograms negative for clustered microcalcifications to further estimate the FP rate of our CAD system. The corresponding FP rates were 0.15, 0.31, and 0.86 FPs/image for cluster-based detection when negative mammograms were used for estimation of FP rates.« less

DTM-based automatic mapping and fractal clustering of putative mud volcanoes in Arabia Terra craters

NASA Astrophysics Data System (ADS)

Pozzobon, R. P.; Mazzarini, F. M.; Massironi, M. M.; Cremonese, G. C.; Rossi, A. P. R.; Pondrelli, M. P.; Marinangeli, L. M.

2017-09-01

Arabia Terra is a region of Mars where occurrence of past-water manifests at surface and subsurface. To date, several landforms associated with this activity were recognized and mapped, directly influencing the models of fluid circulation. In particular, within several craters such as Firsoff and an unnamed southern crater, putative mud volcanoes were described by several authors. In fact, numerous mounds (from 30 m of diameter in the case of monogenic cones, up to 3-400 m in the case of coalescing mounds) present an apical vent-like depression, resembling subaerial Azerbaijan mud volcanoes and gryphons. To this date, landform analysis through topographic position index and curvatures based on topography was never attempted. We hereby present a landform classification method suitable for mounds automatic mapping. Their resulting spatial distribution is then studied in terms of self-similar clustering.

Time fluctuation analysis of forest fire sequences

NASA Astrophysics Data System (ADS)

Vega Orozco, Carmen D.; Kanevski, Mikhaïl; Tonini, Marj; Golay, Jean; Pereira, Mário J. G.

2013-04-01

Forest fires are complex events involving both space and time fluctuations. Understanding of their dynamics and pattern distribution is of great importance in order to improve the resource allocation and support fire management actions at local and global levels. This study aims at characterizing the temporal fluctuations of forest fire sequences observed in Portugal, which is the country that holds the largest wildfire land dataset in Europe. This research applies several exploratory data analysis measures to 302,000 forest fires occurred from 1980 to 2007. The applied clustering measures are: Morisita clustering index, fractal and multifractal dimensions (box-counting), Ripley's K-function, Allan Factor, and variography. These algorithms enable a global time structural analysis describing the degree of clustering of a point pattern and defining whether the observed events occur randomly, in clusters or in a regular pattern. The considered methods are of general importance and can be used for other spatio-temporal events (i.e. crime, epidemiology, biodiversity, geomarketing, etc.). An important contribution of this research deals with the analysis and estimation of local measures of clustering that helps understanding their temporal structure. Each measure is described and executed for the raw data (forest fires geo-database) and results are compared to reference patterns generated under the null hypothesis of randomness (Poisson processes) embedded in the same time period of the raw data. This comparison enables estimating the degree of the deviation of the real data from a Poisson process. Generalizations to functional measures of these clustering methods, taking into account the phenomena, were also applied and adapted to detect time dependences in a measured variable (i.e. burned area). The time clustering of the raw data is compared several times with the Poisson processes at different thresholds of the measured function. Then, the clustering measure value depends on the threshold which helps to understand the time pattern of the studied events. Our findings detected the presence of overdensity of events in particular time periods and showed that the forest fire sequences in Portugal can be considered as a multifractal process with a degree of time-clustering of the events. Key words: time sequences, Morisita index, fractals, multifractals, box-counting, Ripley's K-function, Allan Factor, variography, forest fires, point process. Acknowledgements This work was partly supported by the SNFS Project No. 200021-140658, "Analysis and Modelling of Space-Time Patterns in Complex Regions". References - Kanevski M. (Editor). 2008. Advanced Mapping of Environmental Data: Geostatistics, Machine Learning and Bayesian Maximum Entropy. London / Hoboken: iSTE / Wiley. - Telesca L. and Pereira M.G. 2010. Time-clustering investigation of fire temporal fluctuations in Portugal, Nat. Hazards Earth Syst. Sci., vol. 10(4): 661-666. - Vega Orozco C., Tonini M., Conedera M., Kanevski M. (2012) Cluster recognition in spatial-temporal sequences: the case of forest fires, Geoinformatica, vol. 16(4): 653-673.

Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility.

PubMed

Jacquez, Geoffrey M; Shi, Chen; Meliker, Jaymie R

2015-01-01

In case control studies disease risk not explained by the significant risk factors is the unexplained risk. Considering unexplained risk for specific populations, places and times can reveal the signature of unidentified risk factors and risk factors not fully accounted for in the case-control study. This potentially can lead to new hypotheses regarding disease causation. Global, local and focused Q-statistics are applied to data from a population-based case-control study of 11 southeast Michigan counties. Analyses were conducted using both year- and age-based measures of time. The analyses were adjusted for arsenic exposure, education, smoking, family history of bladder cancer, occupational exposure to bladder cancer carcinogens, age, gender, and race. Significant global clustering of cases was not found. Such a finding would indicate large-scale clustering of cases relative to controls through time. However, highly significant local clusters were found in Ingham County near Lansing, in Oakland County, and in the City of Jackson, Michigan. The Jackson City cluster was observed in working-ages and is thus consistent with occupational causes. The Ingham County cluster persists over time, suggesting a broad-based geographically defined exposure. Focused clusters were found for 20 industrial sites engaged in manufacturing activities associated with known or suspected bladder cancer carcinogens. Set-based tests that adjusted for multiple testing were not significant, although local clusters persisted through time and temporal trends in probability of local tests were observed. Q analyses provide a powerful tool for unpacking unexplained disease risk from case-control studies. This is particularly useful when the effect of risk factors varies spatially, through time, or through both space and time. For bladder cancer in Michigan, the next step is to investigate causal hypotheses that may explain the excess bladder cancer risk localized to areas of Oakland and Ingham counties, and to the City of Jackson.