Calcium-deficiency assessment and biomarker identification by an integrated urinary metabonomics analysis

PubMed Central

2013-01-01

Background Calcium deficiency is a global public-health problem. Although the initial stage of calcium deficiency can lead to metabolic alterations or potential pathological changes, calcium deficiency is difficult to diagnose accurately. Moreover, the details of the molecular mechanism of calcium deficiency remain somewhat elusive. To accurately assess and provide appropriate nutritional intervention, we carried out a global analysis of metabolic alterations in response to calcium deficiency. Methods The metabolic alterations associated with calcium deficiency were first investigated in a rat model, using urinary metabonomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis. Correlations between dietary calcium intake and the biomarkers identified from the rat model were further analyzed to confirm the potential application of these biomarkers in humans. Results Urinary metabolic-profiling analysis could preliminarily distinguish between calcium-deficient and non-deficient rats after a 2-week low-calcium diet. We established an integrated metabonomics strategy for identifying reliable biomarkers of calcium deficiency using a time-course analysis of discriminating metabolites in a low-calcium diet experiment, repeating the low-calcium diet experiment and performing a calcium-supplement experiment. In total, 27 biomarkers were identified, including glycine, oxoglutaric acid, pyrophosphoric acid, sebacic acid, pseudouridine, indoxyl sulfate, taurine, and phenylacetylglycine. The integrated urinary metabonomics analysis, which combined biomarkers with regular trends of change (types A, B, and C), could accurately assess calcium-deficient rats at different stages and clarify the dynamic pathophysiological changes and molecular mechanism of calcium deficiency in detail. Significant correlations between calcium intake and two biomarkers, pseudouridine (Pearson correlation, r = 0.53, P = 0.0001) and citrate (Pearson correlation, r = -0.43, P = 0.001), were further confirmed in 70 women. Conclusions To our knowledge, this is the first report of reliable biomarkers of calcium deficiency, which were identified using an integrated strategy. The identified biomarkers give new insights into the pathophysiological changes and molecular mechanisms of calcium deficiency. The correlations between calcium intake and two of the biomarkers provide a rationale or potential for further assessment and elucidation of the metabolic responses of calcium deficiency in humans. PMID:23537001

Serum Albumin and Disease Severity of Non-Cystic Fibrosis Bronchiectasis.

PubMed

Lee, Seung Jun; Kim, Hyo-Jung; Kim, Ju-Young; Ju, Sunmi; Lim, Sujin; Yoo, Jung Wan; Nam, Sung-Jin; Lee, Gi Dong; Cho, Hyun Seop; Kim, Rock Bum; Cho, Yu Ji; Jeong, Yi Yeong; Kim, Ho Cheol; Lee, Jong Deog

2017-08-01

A clinical classification system has been developed to define the severity and predict the prognosis of subjects with non-cystic fibrosis (CF) bronchiectasis. We aimed to identify laboratory parameters that are correlated with the bronchiectasis severity index (BSI) and FACED score. The medical records of 107 subjects with non-CF bronchiectasis for whom BSI and FACED scores could be calculated were retrospectively reviewed. The correlations between the laboratory parameters and BSI or FACED score were assessed, and multiple-linear regression analysis was performed to identify variables independently associated with BSI and FACED score. An additional subgroup analysis was performed according to sex. Among all of the enrolled subjects, 49 (45.8%) were male and 58 (54.2%) were female. The mean BSI and FACED scores were 9.43 ± 3.81 and 1.92 ± 1.59, respectively. The serum albumin level (r = -0.49), bilirubin level (r = -0.31), C-reactive protein level (r = 0.22), hemoglobin level (r = -0.2), and platelet/lymphocyte ratio (r = 0.31) were significantly correlated with BSI. Meanwhile, serum albumin (r = -0.37) and bilirubin level (r = -0.25) showed a significant correlation with the FACED score. Multiple-linear regression analysis showed that the serum bilirubin level was independently associated with BSI, and the serum albumin level was independently associated with both scoring systems. Subgroup analysis revealed that the level of uric acid was also a significant variable independently associated with the BSI in male bronchiectasis subjects. Several laboratory variables were identified as possible prognostic factors for non-CF bronchiectasis. Among them, the serum albumin level exhibited the strongest correlation and was identified as an independent variable associated with the BSI and FACED scores. Copyright © 2017 by Daedalus Enterprises.

[Preliminary study on effective components of Tripterygium wilfordii for liver toxicity based on spectrum-effect correlation analysis].

PubMed

Zhao, Xiao-Mei; Pu, Shi-Biao; Zhao, Qing-Guo; Gong, Man; Wang, Jia-Bo; Ma, Zhi-Jie; Xiao, Xiao-He; Zhao, Kui-Jun

2016-08-01

In this paper, the spectrum-effect correlation analysis method was used to explore the main effective components of Tripterygium wilfordii for liver toxicity, and provide reference for promoting the quality control of T. wilfordii. Chinese medicine T.wilfordii was taken as the study object, and LC-Q-TOF-MS was used to characterize the chemical components in T. wilfordii samples from different areas, and their main components were initially identified after referring to the literature. With the normal human hepatocytes (LO2 cell line)as the carrier, acetaminophen as positive medicine, and cell inhibition rate as testing index, the simple correlation analysis and multivariate linear correlation analysis methods were used to screen the main components of T. wilfordii for liver toxicity. As a result, 10 kinds of main components were identified, and the spectrum-effect correlation analysis showed that triptolide may be the toxic component, which was consistent with previous results of traditional literature. Meanwhile it was found that tripterine and demethylzeylasteral may greatly contribute to liver toxicity in multivariate linear correlation analysis. T. wilfordii samples of different varieties or different origins showed large difference in quality, and the T. wilfordii from southwest China showed lower liver toxicity, while those from Hunan and Anhui province showed higher liver toxicity. This study will provide data support for further rational use of T. wilfordii and research on its liver toxicity ingredients. Copyright© by the Chinese Pharmaceutical Association.

Correlation analysis of targeted proteins and metabolites to assess and engineer microbial isopentenol production.

PubMed

George, Kevin W; Chen, Amy; Jain, Aakriti; Batth, Tanveer S; Baidoo, Edward E K; Wang, George; Adams, Paul D; Petzold, Christopher J; Keasling, Jay D; Lee, Taek Soon

2014-08-01

The ability to rapidly assess and optimize heterologous pathway function is critical for effective metabolic engineering. Here, we develop a systematic approach to pathway analysis based on correlations between targeted proteins and metabolites and apply it to the microbial production of isopentenol, a promising biofuel. Starting with a seven-gene pathway, we performed a correlation analysis to reduce pathway complexity and identified two pathway proteins as the primary determinants of efficient isopentenol production. Aided by the targeted quantification of relevant pathway intermediates, we constructed and subsequently validated a conceptual model of isopentenol pathway function. Informed by our analysis, we assembled a strain which produced isopentenol at a titer 1.5 g/L, or 46% of theoretical yield. Our engineering approach allowed us to accurately identify bottlenecks and determine appropriate pathway balance. Paired with high-throughput cloning techniques and analytics, this strategy should prove useful for the analysis and optimization of increasingly complex heterologous pathways. © 2014 Wiley Periodicals, Inc.

Harnessing pain heterogeneity and RNA transcriptome to identify blood-based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model.

PubMed

Grace, Peter M; Hurley, Daniel; Barratt, Daniel T; Tsykin, Anna; Watkins, Linda R; Rolan, Paul E; Hutchinson, Mark R

2012-09-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. © 2012 The Authors. Journal of Neurochemistry © 2012 International Society for Neurochemistry.

Analysis of Performance Factors for Accounting and Finance Related Business Courses in a Distance Education Environment

ERIC Educational Resources Information Center

Benligiray, Serdar; Onay, Ahmet

2017-01-01

The objective of this study is to explore business courses performance factors with a focus on accounting and finance. Course score interrelations are assumed to represent interpretable constructs of these factors. Factor analysis is proposed to identify the constructs that explain the correlations. Factor analysis results identify three…

Anatomical relationships between serotonin 5-HT2A and dopamine D2 receptors in living human brain.

PubMed

Ishii, Tatsuya; Kimura, Yasuyuki; Ichise, Masanori; Takahata, Keisuke; Kitamura, Soichiro; Moriguchi, Sho; Kubota, Manabu; Zhang, Ming-Rong; Yamada, Makiko; Higuchi, Makoto; Okubo, Yoshinori; Suhara, Tetsuya

2017-01-01

Seven healthy volunteers underwent PET scans with [18F]altanserin and [11C]FLB 457 for 5-HT2A and D2 receptors, respectively. As a measure of receptor density, a binding potential (BP) was calculated from PET data for 76 cerebral cortical regions. A correlation matrix was calculated between the binding potentials of [18F]altanserin and [11C]FLB 457 for those regions. The regional relationships were investigated using a bicluster analysis of the correlation matrix with an iterative signature algorithm. We identified two clusters of regions. The first cluster identified a distinct profile of correlation coefficients between 5-HT2A and D2 receptors, with the former in regions related to sensorimotor integration (supplementary motor area, superior parietal gyrus, and paracentral lobule) and the latter in most cortical regions. The second cluster identified another distinct profile of correlation coefficients between 5-HT2A receptors in the bilateral hippocampi and D2 receptors in most cortical regions. The observation of two distinct clusters in the correlation matrix suggests regional interactions between 5-HT2A and D2 receptors in sensorimotor integration and hippocampal function. A bicluster analysis of the correlation matrix of these neuroreceptors may be beneficial in understanding molecular networks in the human brain.

Analytic uncertainty and sensitivity analysis of models with input correlations

NASA Astrophysics Data System (ADS)

Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

2018-03-01

Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

PubMed

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

2018-01-01

Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other parameters. Thereby, the calculated correlation coefficients ranged from 0.62 to 0.69. Furthermore, K trans related parameters showed multiple slightly to moderate significant correlations with different ADC values. Strongest correlations were identified between ADC P75 and K trans min (p=0.58, P=0.0007), and ADC P75 and K trans P10 (p=0.56, P=0.001). Only four K ep related parameters correlated statistically significant with ADC fractions. Strongest correlation was found between K ep max and ADC mode (p=-0.47, P=0.008). Multiple statistically significant correlations between, DWI and DCE MRI parameters derived from histogram analysis were identified in HNSCC. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

Decoding and Reading Comprehension: A Meta-Analysis to Identify Which Reader and Assessment Characteristics Influence the Strength of the Relationship in English

ERIC Educational Resources Information Center

García, J. Ricardo; Cain, Kate

2014-01-01

The twofold purpose of this meta-analysis was to determine the relative importance of decoding skills to reading comprehension in reading development and to identify which reader characteristics and reading assessment characteristics contribute to differences in the decoding and reading comprehension correlation. A meta-analysis of 110 studies…

Analysis of human nails by laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Hosseinimakarem, Zahra; Tavassoli, Seyed Hassan

2011-05-01

Laser-induced breakdown spectroscopy (LIBS) is applied to analyze human fingernails using nanosecond laser pulses. Measurements on 45 nail samples are carried out and 14 key species are identified. The elements detected with the present system are: Al, C, Ca, Fe, H, K, Mg, N, Na, O, Si, Sr, Ti as well as CN molecule. Sixty three emission lines have been identified in the spectrum that are dominated by calcium lines. A discriminant function analysis is used to discriminate among different genders and age groups. This analysis demonstrates efficient discrimination among these groups. The mean concentration of each element is compared between different groups. Correlation between concentrations of elements in fingernails is calculated. A strong correlation is found between sodium and potassium while calcium and magnesium levels are inversely correlated. A case report on high levels of sodium and potassium in patients with hyperthyroidism is presented. It is shown that LIBS could be a promising technique for the analysis of nails and therefore identification of health problems.

Multimodal neural correlates of cognitive control in the Human Connectome Project.

PubMed

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions hypothesized to be modulated by cognitive control signaling, such as visual cortex. Taken together, these results illustrate the potential utility of multi-modal analyses in identifying the neural correlates of cognitive control across different indicators of brain structure and function. Copyright © 2017 Elsevier Inc. All rights reserved.

Novel Assessment of Interstitial Lung Disease Using the "Computer-Aided Lung Informatics for Pathology Evaluation and Rating" (CALIPER) Software System in Idiopathic Inflammatory Myopathies.

PubMed

Ungprasert, Patompong; Wilton, Katelynn M; Ernste, Floranne C; Kalra, Sanjay; Crowson, Cynthia S; Rajagopalan, Srinivasan; Bartholmai, Brian J

2017-10-01

To evaluate the correlation between measurements from quantitative thoracic high-resolution CT (HRCT) analysis with "Computer-Aided Lung Informatics for Pathology Evaluation and Rating" (CALIPER) software and measurements from pulmonary function tests (PFTs) in patients with idiopathic inflammatory myopathies (IIM)-associated interstitial lung disease (ILD). A cohort of patients with IIM-associated ILD seen at Mayo Clinic was identified from medical record review. Retrospective analysis of HRCT data and PFTs at baseline and 1 year was performed. The abnormalities in HRCT were quantified using CALIPER software. A total of 110 patients were identified. At baseline, total interstitial abnormalities as measured by CALIPER, both by absolute volume and by percentage of total lung volume, had a significant negative correlation with diffusing capacity for carbon monoxide (DLCO), total lung capacity (TLC), and oxygen saturation. Analysis by subtype of interstitial abnormality revealed significant negative correlations between ground glass opacities (GGO) and reticular density (RD) with DLCO and TLC. At one year, changes of total interstitial abnormalities compared with baseline had a significant negative correlation with changes of TLC and oxygen saturation. A negative correlation between changes of total interstitial abnormalities and DLCO was also observed, but it was not statistically significant. Analysis by subtype of interstitial abnormality revealed negative correlations between changes of GGO and RD and changes of DLCO, TLC, and oxygen saturation, but most of the correlations did not achieve statistical significance. CALIPER measurements correlate well with functional measurements in patients with IIM-associated ILD.

Identifying compromised systems through correlation of suspicious traffic from malware behavioral analysis

NASA Astrophysics Data System (ADS)

Camilo, Ana E. F.; Grégio, André; Santos, Rafael D. C.

2016-05-01

Malware detection may be accomplished through the analysis of their infection behavior. To do so, dynamic analysis systems run malware samples and extract their operating system activities and network traffic. This traffic may represent malware accessing external systems, either to steal sensitive data from victims or to fetch other malicious artifacts (configuration files, additional modules, commands). In this work, we propose the use of visualization as a tool to identify compromised systems based on correlating malware communications in the form of graphs and finding isomorphisms between them. We produced graphs from over 6 thousand distinct network traffic files captured during malware execution and analyzed the existing relationships among malware samples and IP addresses.

A hybrid correlation analysis with application to imaging genetics

NASA Astrophysics Data System (ADS)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding the correlation between brain imaging and genomic data.

Multiple Mediation Analysis of the Relationship between Rapid Naming and Reading

ERIC Educational Resources Information Center

Poulsen, Mads; Juul, Holger; Elbro, Carsten

2015-01-01

It is well established that rapid automatised naming (RAN) correlates with reading ability. Despite several attempts, no single component process (mediator) has been identified that fully accounts for the correlation. The present paper estimated the explanatory value of several mediators for the RAN--reading correlation. One hundred and sixty-nine…

Using the Oxford Foot Model to determine the association between objective measures of foot function and results of the AOFAS Ankle-Hindfoot Scale and the Foot Function Index: a prospective gait analysis study in Germany

PubMed Central

Kostuj, Tanja; Stief, Felix; Hartmann, Kirsten Anna; Schaper, Katharina; Arabmotlagh, Mohammad; Baums, Mike H; Meurer, Andrea; Krummenauer, Frank; Lieske, Sebastian

2018-01-01

Objective After cross-cultural adaption for the German translation of the Ankle-Hindfoot Scale of the American Orthopaedic Foot and Ankle Society (AOFAS-AHS) and agreement analysis with the Foot Function Index (FFI-D), the following gait analysis study using the Oxford Foot Model (OFM) was carried out to show which of the two scores better correlates with objective gait dysfunction. Design and participants Results of the AOFAS-AHS and FFI-D, as well as data from three-dimensional gait analysis were collected from 20 patients with mild to severe ankle and hindfoot pathologies. Kinematic and kinetic gait data were correlated with the results of the total AOFAS scale and FFI-D as well as the results of those items representing hindfoot function in the AOFAS-AHS assessment. With respect to the foot disorders in our patients (osteoarthritis and prearthritic conditions), we correlated the total range of motion (ROM) in the ankle and subtalar joints as identified by the OFM with values identified during clinical examination ‘translated’ into score values. Furthermore, reduced walking speed, reduced step length and reduced maximum ankle power generation during push-off were taken into account and correlated to gait abnormalities described in the scores. An analysis of correlations with CIs between the FFI-D and the AOFAS-AHS items and the gait parameters was performed by means of the Jonckheere-Terpstra test; furthermore, exploratory factor analysis was applied to identify common information structures and thereby redundancy in the FFI-D and the AOFAS-AHS items. Results Objective findings for hindfoot disorders, namely a reduced ROM, in the ankle and subtalar joints, respectively, as well as reduced ankle power generation during push-off, showed a better correlation with the AOFAS-AHS total score—as well as AOFAS-AHS items representing ROM in the ankle, subtalar joints and gait function—compared with the FFI-D score. Factor analysis, however, could not identify FFI-D items consistently related to these three indicator parameters (pain, disability and function) found in the AOFAS-AHS. Furthermore, factor analysis did not support stratification of the FFI-D into two subscales. Conclusions The AOFAS-AHS showed a good agreement with objective gait parameters and is therefore better suited to evaluate disability and functional limitations of patients suffering from foot and ankle pathologies compared with the FFI-D. PMID:29626046

Food and drug cues activate similar brain regions: a meta-analysis of functional MRI studies.

PubMed

Tang, D W; Fellows, L K; Small, D M; Dagher, A

2012-06-06

In healthy individuals, food cues can trigger hunger and feeding behavior. Likewise, smoking cues can trigger craving and relapse in smokers. Brain imaging studies report that structures involved in appetitive behaviors and reward, notably the insula, striatum, amygdala and orbital frontal cortex, tend to be activated by both visual food and smoking cues. Here, by carrying out a meta-analysis of human neuro-imaging studies, we investigate the neural network activated by: 1) food versus neutral cues (14 studies, 142 foci) 2) smoking versus neutral cues (15 studies, 176 foci) 3) smoking versus neutral cues when correlated with craving scores (7 studies, 108 foci). PubMed was used to identify cue-reactivity imaging studies that compared brain response to visual food or smoking cues to neutral cues. Fourteen articles were identified for the food meta-analysis and fifteen articles were identified for the smoking meta-analysis. Six articles were identified for the smoking cue correlated with craving analysis. Meta-analyses were carried out using activation likelihood estimation. Food cues were associated with increased blood oxygen level dependent (BOLD) response in the left amygdala, bilateral insula, bilateral orbital frontal cortex, and striatum. Smoking cues were associated with increased BOLD signal in the same areas, with the exception of the insula. However, the smoking meta-analysis of brain maps correlating cue-reactivity with subjective craving did identify the insula, suggesting that insula activation is only found when craving levels are high. The brain areas identified here are involved in learning, memory and motivation, and their cue-induced activity is an index of the incentive salience of the cues. Using meta-analytic techniques to combine a series of studies, we found that food and smoking cues activate comparable brain networks. There is significant overlap in brain regions responding to conditioned cues associated with natural and drug rewards. Copyright © 2012 Elsevier Inc. All rights reserved.

Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis.

PubMed

Stein, Helge Sören; Jiao, Sally; Ludwig, Alfred

2017-01-09

A challenge in combinatorial materials science remains the efficient analysis of X-ray diffraction (XRD) data and its correlation to functional properties. Rapid identification of phase-regions and proper assignment of corresponding crystal structures is necessary to keep pace with the improved methods for synthesizing and characterizing materials libraries. Therefore, a new modular software called htAx (high-throughput analysis of X-ray and functional properties data) is presented that couples human intelligence tasks used for "ground-truth" phase-region identification with subsequent unbiased verification by an algorithm to efficiently analyze which phases are present in a materials library. Identified phases and phase-regions may then be correlated to functional properties in an expedited manner. For the functionality of htAx to be proven, two previously published XRD benchmark data sets of the materials systems Al-Cr-Fe-O and Ni-Ti-Cu are analyzed by htAx. The analysis of ∼1000 XRD patterns takes less than 1 day with htAx. The proposed method reliably identifies phase-region boundaries and robustly identifies multiphase structures. The method also addresses the problem of identifying regions with previously unpublished crystal structures using a special daisy ternary plot.

Protein Sectors: Statistical Coupling Analysis versus Conservation

PubMed Central

Teşileanu, Tiberiu; Colwell, Lucy J.; Leibler, Stanislas

2015-01-01

Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed “sectors”. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. PMID:25723535

Co-expression analysis identifies CRC and AP1 the regulator of Arabidopsis fatty acid biosynthesis.

PubMed

Han, Xinxin; Yin, Linlin; Xue, Hongwei

2012-07-01

Fatty acids (FAs) play crucial rules in signal transduction and plant development, however, the regulation of FA metabolism is still poorly understood. To study the relevant regulatory network, fifty-eight FA biosynthesis genes including de novo synthases, desaturases and elongases were selected as "guide genes" to construct the co-expression network. Calculation of the correlation between all Arabidopsis thaliana (L.) genes with each guide gene by Arabidopsis co-expression dating mining tools (ACT) identifies 797 candidate FA-correlated genes. Gene ontology (GO) analysis of these co-expressed genes showed they are tightly correlated to photosynthesis and carbohydrate metabolism, and function in many processes. Interestingly, 63 transcription factors (TFs) were identified as candidate FA biosynthesis regulators and 8 TF families are enriched. Two TF genes, CRC and AP1, both correlating with 8 FA guide genes, were further characterized. Analyses of the ap1 and crc mutant showed the altered total FA composition of mature seeds. The contents of palmitoleic acid, stearic acid, arachidic acid and eicosadienoic acid are decreased, whereas that of oleic acid is increased in ap1 and crc seeds, which is consistent with the qRT-PCR analysis revealing the suppressed expression of the corresponding guide genes. In addition, yeast one-hybrid analysis and electrophoretic mobility shift assay (EMSA) revealed that CRC can bind to the promoter regions of KCS7 and KCS15, indicating that CRC may directly regulate FA biosynthesis. © 2012 Institute of Botany, Chinese Academy of Sciences.

Correlated mRNAs and miRNAs from co-expression and regulatory networks affect porcine muscle and finally meat properties.

PubMed

Ponsuksili, Siriluck; Du, Yang; Hadlich, Frieder; Siengdee, Puntita; Murani, Eduard; Schwerin, Manfred; Wimmers, Klaus

2013-08-05

Physiological processes aiding the conversion of muscle to meat involve many genes associated with muscle structure and metabolic processes. MicroRNAs regulate networks of genes to orchestrate cellular functions, in turn regulating phenotypes. We applied weighted gene co-expression network analysis to identify co-expression modules that correlated to meat quality phenotypes and were highly enriched for genes involved in glucose metabolism, response to wounding, mitochondrial ribosome, mitochondrion, and extracellular matrix. Negative correlation of miRNA with mRNA and target prediction were used to select transcripts out of the modules of trait-associated mRNAs to further identify those genes that are correlated with post mortem traits. Porcine muscle co-expression transcript networks that correlated to post mortem traits were identified. The integration of miRNA and mRNA expression analyses, as well as network analysis, enabled us to interpret the differentially-regulated genes from a systems perspective. Linking co-expression networks of transcripts and hierarchically organized pairs of miRNAs and mRNAs to meat properties yields new insight into several biological pathways underlying phenotype differences. These pathways may also be diagnostic for many myopathies, which are accompanied by deficient nutrient and oxygen supply of muscle fibers.

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

Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa

Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less

Resting-state low-frequency fluctuations reflect individual differences in spoken language learning.

PubMed

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C M

2016-03-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The "competition" (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest--ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. Copyright © 2015 Elsevier Ltd. All rights reserved.

Resting-state low-frequency fluctuations reflect individual differences in spoken language learning

PubMed Central

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C.M.

2016-01-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The “competition” (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest – ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. PMID:26866283

Quantitative Evaluation of Head and Neck Cancer Treatment-Related Dysphagia in the Development of a Personalized Treatment Deintensification Paradigm.

PubMed

Quon, Harry; Hui, Xuan; Cheng, Zhi; Robertson, Scott; Peng, Luke; Bowers, Michael; Moore, Joseph; Choflet, Amanda; Thompson, Alex; Muse, Mariah; Kiess, Ana; Page, Brandi; Fakhry, Carole; Gourin, Christine; O'Hare, Jolyne; Graham, Peter; Szczesniak, Michal; Maclean, Julia; Cook, Ian; McNutt, Todd

2017-12-01

To test the hypothesis that quantifying swallow function with multiple patient-reported outcome (PRO) instruments is an important strategy to yield insights in the development of personalized deintensified therapies seeking to reduce the risk of head and neck cancer (HNC) treatment-related dysphagia (HNCTD). Irradiated HNC subjects seen in follow-up care (April 2015 to December 2015) who prospectively completed the Sydney Swallow Questionnaire (SSQ) and the MD Anderson Dysphagia Inventory (MDADI) concurrently on the web interface to our Oncospace database were evaluated. A correlation matrix quantified the relationship between the SSQ and MDADI. Machine-learning unsupervised cluster analysis using the elbow criterion and CLUSPLOT analysis to establish its validity was performed. We identified 89 subjects. The MDADI and SSQ scores were moderately but significantly correlated (correlation coefficient -0.69). K-means cluster analysis demonstrated that 3 unique statistical cohorts (elbow criterion) could be identified with CLUSPLOT analysis, confirming that 100% of variances were accounted for. Correlation coefficients between the individual items in the SSQ and the MDADI demonstrated weak to moderate negative correlation, except for SSQ17 (quality of life question). Pilot analysis demonstrates that the MDADI and SSQ are complementary. Three unique clusters of patients can be defined, suggesting that a unique dysphagia signature for HNCTD may be definable. Longitudinal studies relying on only a single PRO, such as MDADI, may be inadequate for classifying HNCTD. Copyright © 2017 Elsevier Inc. All rights reserved.

Personal and psychosocial predictors of doping use in physical activity settings: a meta-analysis.

PubMed

Ntoumanis, Nikos; Ng, Johan Y Y; Barkoukis, Vassilis; Backhouse, Susan

2014-11-01

There is a growing body of empirical evidence on demographic and psychosocial predictors of doping intentions and behaviors utilizing a variety of variables and conceptual models. However, to date there has been no attempt to quantitatively synthesize the available evidence and identify the strongest predictors of doping. Using meta-analysis, we aimed to (i) determine effect sizes of psychological (e.g. attitudes) and social-contextual factors (e.g. social norms), and demographic (e.g. sex and age) variables on doping intentions and use; (ii) examine variables that moderate such effect sizes; and (iii) test a path analysis model, using the meta-analyzed effect sizes, based on variables from the theory of planned behavior (TPB). Articles were identified from online databases, by contacting experts in the field, and searching the World Anti-Doping Agency website. Studies that measured doping behaviors and/or doping intentions, and at least one other demographic, psychological, or social-contextual variable were included. We identified 63 independent datasets. Study information was extracted by using predefined data fields and taking into account study quality indicators. A random effects meta-analysis was carried out, correcting for sampling and measurement error, and identifying moderator variables. Path analysis was conducted on a subset of studies that utilized the TPB. Use of legal supplements, perceived social norms, and positive attitudes towards doping were the strongest positive correlates of doping intentions and behaviors. In contrast, morality and self-efficacy to refrain from doping had the strongest negative association with doping intentions and behaviors. Furthermore, path analysis suggested that attitudes, perceived norms, and self-efficacy to refrain from doping predicted intentions to dope and, indirectly, doping behaviors. Various meta-analyzed effect sizes were based on a small number of studies, which were correlational in nature. This is a limitation of the extant literature. This review identifies a number of important correlates of doping intention and behavior, many of which were measured via self-reports and were drawn from an extended TPB framework. Future research might benefit from embracing other conceptual models of doping behavior and adopting experimental methodologies that will test some of the identified correlates in an effort to develop targeted anti-doping policies and programs.

Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.)

PubMed Central

2011-01-01

Background Global transcriptional analysis of loblolly pine (Pinus taeda L.) is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes). Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01). Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs) including those with significant homology (E-values ≤ 2 × 10-30) to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in roots. Many of the genes identified are known to be up-regulated in response to osmotic stress in pine and other plant species and encode proteins involved in both signal transduction and stress tolerance. Gene expression levels returned to control values within a 48-hour recovery period in all but 76 transcripts. Correlation network analysis indicates a scale-free network topology for the pine root transcriptome and identifies central nodes that may serve as drivers of drought-responsive transcriptome dynamics in the roots of loblolly pine. PMID:21609476

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

PubMed

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets.

PubMed

Mainali, Kumar P; Bewick, Sharon; Thielen, Peter; Mehoke, Thomas; Breitwieser, Florian P; Paudel, Shishir; Adhikari, Arjun; Wolfe, Joshua; Slud, Eric V; Karig, David; Fagan, William F

2017-01-01

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson's correlation coefficient (r) and Jaccard's index (J)-two of the most common metrics for correlation analysis of presence-absence data-can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson's correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard's index of similarity (J) can yield improvements over Pearson's correlation coefficient. However, the standard null model for Jaccard's index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard's index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa.

The cerebrospinal fluid proteome in HIV infection: change associated with disease severity.

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

Angel, Thomas E.; Jacobs, Jon M.; Spudich, Serena S.

2012-03-20

Central nervous system (CNS) infection is a constant feature of systemic HIV infection with a clinical spectrum that ranges from chronic asymptomatic infection to severe cognitive and motor dysfunction. Analysis of cerebrospinal fluid (CSF) has played an important part in defining the character of this evolving infection and response to treatment. To further characterize CNS HIV infection and its effects, we applied advanced high-throughput proteomic methods to CSF to identify novel proteins and their changes with disease progression and treatment. After establishing an accurate mass and time (AMT) tag database containing 23,141 AMT tags for CSF peptides, we analyzed 91more » CSF samples by LC-MS from 12 HIV-uninfected and 14 HIV-infected subjects studied in the context of initiation of antiretroviral and correlated abundances of identified proteins (a) within and between subjects, (b) with all other proteins across the entire sample set, and (c) with 'external' CSF biomarkers of infection (HIV RNA), immune activation (neopterin) and neural injury (neurofilament light chain protein, NFL). We identified a mean of 2,333 +/- 328 (SD) peptides covering 307 +/-16 proteins in the 91 CSF sample set. Protein abundances differed both between and within subjects sampled at different time points and readily separated those with and without HIV infection. Proteins also showed inter-correlations across the sample set that were associated with biologically relevant dynamic processes. One-hundred and fifty proteins showed correlations with the external biomarkers. For example, using a threshold of cross correlation coefficient (Pearson's) {le}0.3 and {ge}0.3 for potentially meaningful relationships, a total of 99 proteins correlated with CSF neopterin (43 negative and 56 positive correlations) and related principally to neuronal plasticity and survival and to innate immunity. Pathway analysis defined several networks connecting the identified proteins, including one with amyloid precursor protein as a central node. Advanced CSF proteomic analysis enabled the identification of an array of novel protein changes across the spectrum of CNS HIV infection and disease. This initial analysis clearly demonstrated the value of contemporary state-of-the-art proteomic CSF analysis as a discovery tool in HIV infection with likely similar application to other neurological inflammatory and degenerative diseases.« less

The cerebrospinal fluid proteome in HIV infection: change associated with disease severity

PubMed Central

2012-01-01

Background Central nervous system (CNS) infection is a nearly universal feature of untreated systemic HIV infection with a clinical spectrum that ranges from chronic asymptomatic infection to severe cognitive and motor dysfunction. Analysis of cerebrospinal fluid (CSF) has played an important part in defining the character of this evolving infection and response to treatment. To further characterize CNS HIV infection and its effects, we applied advanced high-throughput proteomic methods to CSF to identify novel proteins and their changes with disease progression and treatment. Results After establishing an accurate mass and time (AMT) tag database containing 23,141 AMT tags for CSF peptides, we analyzed 91 CSF samples by LC-MS from 12 HIV-uninfected and 14 HIV-infected subjects studied in the context of initiation of antiretroviral therapy and correlated abundances of identified proteins a) within and between subjects, b) with all other proteins across the entire sample set, and c) with "external" CSF biomarkers of infection (HIV RNA), immune activation (neopterin) and neural injury (neurofilament light chain protein, NFL). We identified a mean of 2,333 +/- 328 (SD) peptides covering 307 +/-16 proteins in the 91 CSF sample set. Protein abundances differed both between and within subjects sampled at different time points and readily separated those with and without HIV infection. Proteins also showed inter-correlations across the sample set that were associated with biologically relevant dynamic processes. One-hundred and fifty proteins showed correlations with the external biomarkers. For example, using a threshold of cross correlation coefficient (Pearson's) ≤ -0.3 and ≥0.3 for potentially meaningful relationships, a total of 99 proteins correlated with CSF neopterin (43 negative and 56 positive correlations) and related principally to neuronal plasticity and survival and to innate immunity. Pathway analysis defined several networks connecting the identified proteins, including one with amyloid precursor protein as a central node. Conclusions Advanced CSF proteomic analysis enabled the identification of an array of novel protein changes across the spectrum of CNS HIV infection and disease. This initial analysis clearly demonstrated the value of contemporary state-of-the-art proteomic CSF analysis as a discovery tool in HIV infection with likely similar application to other neurological inflammatory and degenerative diseases. PMID:22433316

Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy

DOE PAGES

Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa; ...

2014-09-01

Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less

Spatial correlation analysis of urban traffic state under a perspective of community detection

NASA Astrophysics Data System (ADS)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

Process Correlation Analysis Model for Process Improvement Identification

PubMed Central

Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data. PMID:24977170

Process correlation analysis model for process improvement identification.

PubMed

Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

Tracing and separating plasma components causing matrix effects in hydrophilic interaction chromatography-electrospray ionization mass spectrometry.

PubMed

Ekdahl, Anja; Johansson, Maria C; Ahnoff, Martin

2013-04-01

Matrix effects on electrospray ionization were investigated for plasma samples analysed by hydrophilic interaction chromatography (HILIC) in gradient elution mode, and HILIC columns of different chemistries were tested for separation of plasma components and model analytes. By combining mass spectral data with post-column infusion traces, the following components of protein-precipitated plasma were identified and found to have significant effect on ionization: urea, creatinine, phosphocholine, lysophosphocholine, sphingomyelin, sodium ion, chloride ion, choline and proline betaine. The observed effect on ionization was both matrix-component and analyte dependent. The separation of identified plasma components and model analytes on eight columns was compared, using pair-wise linear correlation analysis and principal component analysis (PCA). Large changes in selectivity could be obtained by change of column, while smaller changes were seen when the mobile phase buffer was changed from ammonium formate pH 3.0 to ammonium acetate pH 4.5. While results from PCA and linear correlation analysis were largely in accord, linear correlation analysis was judged to be more straight-forward in terms of conduction and interpretation.

Optimization of selective breeding through analysis of morphological traits in Chinese sea bass (Lateolabrax maculatus).

PubMed

Wang, W; Ma, C Y; Chen, W; Ma, H Y; Zhang, H; Meng, Y Y; Ni, Y; Ma, L B

2016-08-19

Determining correlations between certain traits of economic importance constitutes an essential component of selective activities. In this study, our aim was to provide effective indicators for breeding programs of Lateolabrax maculatus, an important aquaculture species in China. We analyzed correlations between 20 morphometric traits and body weight, using correlation and path analyses. The results indicated that the correlations among all 21 traits were highly significant, with the highest correlation coefficient identified between total length and body weight. The path analysis indicated that total length (X 1 ), body width (X 5 ), distance from first dorsal fin origin to anal fin origin (X 10 ), snout length (X 16 ), eye diameter (X 17 ), eye cross (X 18 ), and slanting distance from snout tip to first dorsal fin origin (X 19 ) significantly affected body weight (Y) directly. The following multiple-regression equation was obtained using stepwise multiple-regression analysis: Y = -472.108 + 1.065X 1 + 7.728X 5 + 1.973X 10 - 7.024X 16 - 4.400X 17 - 3.338X 18 + 2.138X 19 , with an adjusted multiple-correlation coefficient of 0.947. Body width had the largest determinant coefficient, as well as the highest positive direct correlation with body weight. At the same time, high indirect effects with six other morphometric traits on L. maculatus body weight, through body width, were identified. Hence, body width could be a key factor that efficiently indicates significant effects on body weight in L. maculatus.

Digital Correlation Microwave Polarimetry: Analysis and Demonstration

NASA Technical Reports Server (NTRS)

Piepmeier, J. R.; Gasiewski, A. J.; Krebs, Carolyn A. (Technical Monitor)

2000-01-01

The design, analysis, and demonstration of a digital-correlation microwave polarimeter for use in earth remote sensing is presented. We begin with an analysis of three-level digital correlation and develop the correlator transfer function and radiometric sensitivity. A fifth-order polynomial regression is derived for inverting the digital correlation coefficient into the analog statistic. In addition, the effects of quantizer threshold asymmetry and hysteresis are discussed. A two-look unpolarized calibration scheme is developed for identifying correlation offsets. The developed theory and calibration method are verified using a 10.7 GHz and a 37.0 GHz polarimeter. The polarimeters are based upon 1-GS/s three-level digital correlators and measure the first three Stokes parameters. Through experiment, the radiometric sensitivity is shown to approach the theoretical as derived earlier in the paper and the two-look unpolarized calibration method is successfully compared with results using a polarimetric scheme. Finally, sample data from an aircraft experiment demonstrates that the polarimeter is highly-useful for ocean wind-vector measurement.

Chinese Public Attention to the Outbreak of Ebola in West Africa: Evidence from the Online Big Data Platform.

PubMed

Liu, Kui; Li, Li; Jiang, Tao; Chen, Bin; Jiang, Zhenggang; Wang, Zhengting; Chen, Yongdi; Jiang, Jianmin; Gu, Hua

2016-08-04

The outbreak of the Ebola epidemic in West Africa in 2014 exerted enormous global public reaction via the Internet and social media. This study aimed to investigate and evaluate the public reaction to Ebola in China and identify the primitive correlation between possible influence factors caused by the outbreak of Ebola in West Africa and Chinese public attention via Internet surveillance. Baidu Index (BDI) and Sina Micro Index (SMI) were collected from their official websites, and the disease-related data were recorded from the websites of the World Health Organization (WHO), U.S. Centers for Disease Control and Prevention (CDC), and U.S. National Ministries of Health. The average BDI of Internet users in different regions were calculated to identify the public reaction to the Ebola outbreak. Spearman's rank correlation was used to check the relationship of epidemic trends with BDI and SMI. Additionally, spatio-temporal analysis and autocorrelation analysis were performed to detect the clustered areas with the high attention to the topic of "Ebola". The related news reports were collected from authoritative websites to identify potential patterns. The BDI and the SMI for "Ebola" showed a similar fluctuating trend with a correlation coefficient = 0.9 (p < 0.05). The average BDI in Beijing, Tibet, and Shanghai was higher than other cities. However, the disease-related indicators did not identify potential correlation with both indices above. A hotspot area was detected in Tibet by local autocorrelation analysis. The most likely cluster identified by spatiotemporal cluster analysis was in the northeast regions of China with the relative risk (RR) of 2.26 (p ≤ 0.01) from 30 July to 14 August in 2014. Qualitative analysis indicated that negative news could lead to a continuous increase of the public's attention until the appearance of a positive news report. Confronted with the risk of cross-border transmission of the infectious disease, online surveillance might be used as an innovative approach to perform public communication and health education through examining the public's reaction and attitude.

Chinese Public Attention to the Outbreak of Ebola in West Africa: Evidence from the Online Big Data Platform

PubMed Central

Liu, Kui; Li, Li; Jiang, Tao; Chen, Bin; Jiang, Zhenggang; Wang, Zhengting; Chen, Yongdi; Jiang, Jianmin; Gu, Hua

2016-01-01

Objective: The outbreak of the Ebola epidemic in West Africa in 2014 exerted enormous global public reaction via the Internet and social media. This study aimed to investigate and evaluate the public reaction to Ebola in China and identify the primitive correlation between possible influence factors caused by the outbreak of Ebola in West Africa and Chinese public attention via Internet surveillance. Methods: Baidu Index (BDI) and Sina Micro Index (SMI) were collected from their official websites, and the disease-related data were recorded from the websites of the World Health Organization (WHO), U.S. Centers for Disease Control and Prevention (CDC), and U.S. National Ministries of Health. The average BDI of Internet users in different regions were calculated to identify the public reaction to the Ebola outbreak. Spearman’s rank correlation was used to check the relationship of epidemic trends with BDI and SMI. Additionally, spatio-temporal analysis and autocorrelation analysis were performed to detect the clustered areas with the high attention to the topic of “Ebola”. The related news reports were collected from authoritative websites to identify potential patterns. Results: The BDI and the SMI for “Ebola” showed a similar fluctuating trend with a correlation coefficient = 0.9 (p < 0.05). The average BDI in Beijing, Tibet, and Shanghai was higher than other cities. However, the disease-related indicators did not identify potential correlation with both indices above. A hotspot area was detected in Tibet by local autocorrelation analysis. The most likely cluster identified by spatiotemporal cluster analysis was in the northeast regions of China with the relative risk (RR) of 2.26 (p ≤ 0.01) from 30 July to 14 August in 2014. Qualitative analysis indicated that negative news could lead to a continuous increase of the public’s attention until the appearance of a positive news report. Conclusions: Confronted with the risk of cross-border transmission of the infectious disease, online surveillance might be used as an innovative approach to perform public communication and health education through examining the public’s reaction and attitude. PMID:27527196

Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data

NASA Astrophysics Data System (ADS)

Manzo, Ciro; Braga, Federica; Zaggia, Luca; Brando, Vittorio Ernesto; Giardino, Claudia; Bresciani, Mariano; Bassani, Cristiana

2018-04-01

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013-2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

Hill, M.C.; Nolan, B.T.

2010-01-01

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

Methodology for fast detection of false sharing in threaded scientific codes

DOEpatents

Chung, I-Hsin; Cong, Guojing; Murata, Hiroki; Negishi, Yasushi; Wen, Hui-Fang

2014-11-25

A profiling tool identifies a code region with a false sharing potential. A static analysis tool classifies variables and arrays in the identified code region. A mapping detection library correlates memory access instructions in the identified code region with variables and arrays in the identified code region while a processor is running the identified code region. The mapping detection library identifies one or more instructions at risk, in the identified code region, which are subject to an analysis by a false sharing detection library. A false sharing detection library performs a run-time analysis of the one or more instructions at risk while the processor is re-running the identified code region. The false sharing detection library determines, based on the performed run-time analysis, whether two different portions of the cache memory line are accessed by the generated binary code.

Using the Oxford Foot Model to determine the association between objective measures of foot function and results of the AOFAS Ankle-Hindfoot Scale and the Foot Function Index: a prospective gait analysis study in Germany.

PubMed

Kostuj, Tanja; Stief, Felix; Hartmann, Kirsten Anna; Schaper, Katharina; Arabmotlagh, Mohammad; Baums, Mike H; Meurer, Andrea; Krummenauer, Frank; Lieske, Sebastian

2018-04-05

After cross-cultural adaption for the German translation of the Ankle-Hindfoot Scale of the American Orthopaedic Foot and Ankle Society (AOFAS-AHS) and agreement analysis with the Foot Function Index (FFI-D), the following gait analysis study using the Oxford Foot Model (OFM) was carried out to show which of the two scores better correlates with objective gait dysfunction. Results of the AOFAS-AHS and FFI-D, as well as data from three-dimensional gait analysis were collected from 20 patients with mild to severe ankle and hindfoot pathologies.Kinematic and kinetic gait data were correlated with the results of the total AOFAS scale and FFI-D as well as the results of those items representing hindfoot function in the AOFAS-AHS assessment. With respect to the foot disorders in our patients (osteoarthritis and prearthritic conditions), we correlated the total range of motion (ROM) in the ankle and subtalar joints as identified by the OFM with values identified during clinical examination 'translated' into score values. Furthermore, reduced walking speed, reduced step length and reduced maximum ankle power generation during push-off were taken into account and correlated to gait abnormalities described in the scores. An analysis of correlations with CIs between the FFI-D and the AOFAS-AHS items and the gait parameters was performed by means of the Jonckheere-Terpstra test; furthermore, exploratory factor analysis was applied to identify common information structures and thereby redundancy in the FFI-D and the AOFAS-AHS items. Objective findings for hindfoot disorders, namely a reduced ROM, in the ankle and subtalar joints, respectively, as well as reduced ankle power generation during push-off, showed a better correlation with the AOFAS-AHS total score-as well as AOFAS-AHS items representing ROM in the ankle, subtalar joints and gait function-compared with the FFI-D score.Factor analysis, however, could not identify FFI-D items consistently related to these three indicator parameters (pain, disability and function) found in the AOFAS-AHS. Furthermore, factor analysis did not support stratification of the FFI-D into two subscales. The AOFAS-AHS showed a good agreement with objective gait parameters and is therefore better suited to evaluate disability and functional limitations of patients suffering from foot and ankle pathologies compared with the FFI-D. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Metabolite profiling and associated gene expression reveal two metabolic shifts during the seed-to-seedling transition in Arabidopsis thaliana.

PubMed

Silva, Anderson Tadeu; Ligterink, Wilco; Hilhorst, Henk W M

2017-11-01

Metabolic and transcriptomic correlation analysis identified two distinctive profiles involved in the metabolic preparation for seed germination and seedling establishment, respectively. Transcripts were identified that may control metabolic fluxes. The transition from a quiescent metabolic state (dry seed) to the active state of a vigorous seedling is crucial in the plant's life cycle. We analysed this complex physiological trait by measuring the changes in primary metabolism that occur during the transition in order to determine which metabolic networks are operational. The transition involves several developmental stages from seed germination to seedling establishment, i.e. between imbibition of the mature dry seed and opening of the cotyledons, the final stage of seedling establishment. We hypothesized that the advancement of growth is associated with certain signature metabolite profiles. Metabolite-metabolite correlation analysis underlined two specific profiles which appear to be involved in the metabolic preparation for seed germination and efficient seedling establishment, respectively. Metabolite profiles were also compared to transcript profiles and although transcriptional changes did not always equate to a proportional metabolic response, in depth correlation analysis identified several transcripts that may directly influence the flux through metabolic pathways during the seed-to-seedling transition. This correlation analysis also pinpointed metabolic pathways which are significant for the seed-to-seedling transition, and metabolite contents that appeared to be controlled directly by transcript abundance. This global view of the transcriptional and metabolic changes during the seed-to-seedling transition in Arabidopsis opens up new perspectives for understanding the complex regulatory mechanism underlying this transition.

EEG Correlates of Fluctuation in Cognitive Performance in an Air Traffic Control Task

DTIC Science & Technology

2014-11-01

using non-parametric statistical analysis to identify neurophysiological patterns due to the time-on-task effect. Significant changes in EEG power...EEG, Cognitive Performance, Power Spectral Analysis , Non-Parametric Analysis Document is available to the public through the Internet...3 Performance Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 EEG

A Canonical Correlation Analysis of AIDS Restriction Genes and Metabolic Pathways Identifies Purine Metabolism as a Key Cooperator.

PubMed

Ye, Hanhui; Yuan, Jinjin; Wang, Zhengwu; Huang, Aiqiong; Liu, Xiaolong; Han, Xiao; Chen, Yahong

2016-01-01

Human immunodeficiency virus causes a severe disease in humans, referred to as immune deficiency syndrome. Studies on the interaction between host genetic factors and the virus have revealed dozens of genes that impact diverse processes in the AIDS disease. To resolve more genetic factors related to AIDS, a canonical correlation analysis was used to determine the correlation between AIDS restriction and metabolic pathway gene expression. The results show that HIV-1 postentry cellular viral cofactors from AIDS restriction genes are coexpressed in human transcriptome microarray datasets. Further, the purine metabolism pathway comprises novel host factors that are coexpressed with AIDS restriction genes. Using a canonical correlation analysis for expression is a reliable approach to exploring the mechanism underlying AIDS.

Analyses of flooding tolerance of soybean varieties at emergence and varietal differences in their proteomes.

PubMed

Nanjo, Yohei; Jang, Hee-Young; Kim, Hong-Sig; Hiraga, Susumu; Woo, Sun-Hee; Komatsu, Setsuko

2014-10-01

Flooding of fields due to heavy and/or continuous rainfall influences soybean production. To identify soybean varieties with flooding tolerance at the seedling emergence stage, 128 soybean varieties were evaluated using a flooding tolerance index, which is based on plant survival rates, the lack of apparent damage and lateral root development, and post-flooding radicle elongation rate. The soybean varieties were ranked according to their flooding tolerance index, and it was found that the tolerance levels of soybean varieties exhibit a continuum of differences between varieties. Subsequently, tolerant, moderately tolerant and sensitive varieties were selected and subjected to comparative proteomic analysis to clarify the tolerance mechanism. Proteomic analysis of the radicles, combined with correlation analysis, showed that the ratios of RNA binding/processing related proteins and flooding stress indicator proteins were significantly correlated with flooding tolerance index. The RNA binding/processing related proteins were positively correlated in untreated soybeans, whereas flooding stress indicator proteins were negatively correlated in flooded soybeans. These results suggest that flooding tolerance is regulated by mechanisms through multiple factors and is associated with abundance levels of the identified proteins. Copyright © 2014 Elsevier Ltd. All rights reserved.

Systematic Correlation Matrix Evaluation (SCoMaE) - a bottom-up, science-led approach to identifying indicators

NASA Astrophysics Data System (ADS)

Mengis, Nadine; Keller, David P.; Oschlies, Andreas

2018-01-01

This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom-up approach which combines expert judgment and statistical information to systematically select transparent, nonredundant indicators for a comprehensive assessment of the state of the Earth system. The methods consists of two basic steps: (1) the calculation of a correlation matrix among variables relevant for a given research question and (2) the systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators. Optional further analysis steps include (3) the interpretation of the identified clusters, enabling a learning effect from the selection of indicators, (4) testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, (5) enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, and (6) the inclusion of expert judgment, for example, to prescribe indicators, to allow for considerations other than statistical consistency. The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate-high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.

GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis.

PubMed

Zheng, Qi; Wang, Xiu-Jie

2008-07-01

Gene Ontology (GO) analysis has become a commonly used approach for functional studies of large-scale genomic or transcriptomic data. Although there have been a lot of software with GO-related analysis functions, new tools are still needed to meet the requirements for data generated by newly developed technologies or for advanced analysis purpose. Here, we present a Gene Ontology Enrichment Analysis Software Toolkit (GOEAST), an easy-to-use web-based toolkit that identifies statistically overrepresented GO terms within given gene sets. Compared with available GO analysis tools, GOEAST has the following improved features: (i) GOEAST displays enriched GO terms in graphical format according to their relationships in the hierarchical tree of each GO category (biological process, molecular function and cellular component), therefore, provides better understanding of the correlations among enriched GO terms; (ii) GOEAST supports analysis for data from various sources (probe or probe set IDs of Affymetrix, Illumina, Agilent or customized microarrays, as well as different gene identifiers) and multiple species (about 60 prokaryote and eukaryote species); (iii) One unique feature of GOEAST is to allow cross comparison of the GO enrichment status of multiple experiments to identify functional correlations among them. GOEAST also provides rigorous statistical tests to enhance the reliability of analysis results. GOEAST is freely accessible at http://omicslab.genetics.ac.cn/GOEAST/

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

PubMed

Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

2017-01-21

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

Detection of moisture and moisture related phenomena from Skylab. [Texas and Kansas

NASA Technical Reports Server (NTRS)

Eagleman, J. R. (Principal Investigator); Lin, W. C.

1974-01-01

The author has identified the following significant results. The high correlations between radiometric temperature and soil moisture content are shown to remain quite high for independent footprints of the S194 sensor. Since an analysis based on overlapping footprints had previously been reported with a high correlation, it was necessary to verify that the correlation did not arise from dependent data.

Analysis of the sleep quality of elderly people using biomedical signals.

PubMed

Moreno-Alsasua, L; Garcia-Zapirain, B; Mendez-Zorrilla, A

2015-01-01

This paper presents a technical solution that analyses sleep signals captured by biomedical sensors to find possible disorders during rest. Specifically, the method evaluates electrooculogram (EOG) signals, skin conductance (GSR), air flow (AS), and body temperature. Next, a quantitative sleep quality analysis determines significant changes in the biological signals, and any similarities between them in a given time period. Filtering techniques such as the Fourier transform method and IIR filters process the signal and identify significant variations. Once these changes have been identified, all significant data is compared and a quantitative and statistical analysis is carried out to determine the level of a person's rest. To evaluate the correlation and significant differences, a statistical analysis has been calculated showing correlation between EOG and AS signals (p=0,005), EOG, and GSR signals (p=0,037) and, finally, the EOG and Body temperature (p=0,04). Doctors could use this information to monitor changes within a patient.

Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

PubMed

Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

2017-11-20

Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Analysis of volatile compounds in exhaled breath condensate in patients with severe pulmonary arterial hypertension.

PubMed

Mansoor, J K; Schelegle, Edward S; Davis, Cristina E; Walby, William F; Zhao, Weixiang; Aksenov, Alexander A; Pasamontes, Alberto; Figueroa, Jennifer; Allen, Roblee

2014-01-01

An important challenge to pulmonary arterial hypertension (PAH) diagnosis and treatment is early detection of occult pulmonary vascular pathology. Symptoms are frequently confused with other disease entities that lead to inappropriate interventions and allow for progression to advanced states of disease. There is a significant need to develop new markers for early disease detection and management of PAH. Exhaled breath condensate (EBC) samples were compared from 30 age-matched normal healthy individuals and 27 New York Heart Association functional class III and IV idiopathic pulmonary arterial hypertenion (IPAH) patients, a subgroup of PAH. Volatile organic compounds (VOC) in EBC samples were analyzed using gas chromatography/mass spectrometry (GC/MS). Individual peaks in GC profiles were identified in both groups and correlated with pulmonary hemodynamic and clinical endpoints in the IPAH group. Additionally, GC/MS data were analyzed using autoregression followed by partial least squares regression (AR/PLSR) analysis to discriminate between the IPAH and control groups. After correcting for medicaitons, there were 62 unique compounds in the control group, 32 unique compounds in the IPAH group, and 14 in-common compounds between groups. Peak-by-peak analysis of GC profiles of IPAH group EBC samples identified 6 compounds significantly correlated with pulmonary hemodynamic variables important in IPAH diagnosis. AR/PLSR analysis of GC/MS data resulted in a distinct and identifiable metabolic signature for IPAH patients. These findings indicate the utility of EBC VOC analysis to discriminate between severe IPAH and a healthy population; additionally, we identified potential novel biomarkers that correlated with IPAH pulmonary hemodynamic variables that may be important in screening for less severe forms IPAH.

Analysis of Volatile Compounds in Exhaled Breath Condensate in Patients with Severe Pulmonary Arterial Hypertension

PubMed Central

Mansoor, J. K.; Schelegle, Edward S.; Davis, Cristina E.; Walby, William F.; Zhao, Weixiang; Aksenov, Alexander A.; Pasamontes, Alberto; Figueroa, Jennifer; Allen, Roblee

2014-01-01

Background An important challenge to pulmonary arterial hypertension (PAH) diagnosis and treatment is early detection of occult pulmonary vascular pathology. Symptoms are frequently confused with other disease entities that lead to inappropriate interventions and allow for progression to advanced states of disease. There is a significant need to develop new markers for early disease detection and management of PAH. Methodolgy and Findings Exhaled breath condensate (EBC) samples were compared from 30 age-matched normal healthy individuals and 27 New York Heart Association functional class III and IV idiopathic pulmonary arterial hypertenion (IPAH) patients, a subgroup of PAH. Volatile organic compounds (VOC) in EBC samples were analyzed using gas chromatography/mass spectrometry (GC/MS). Individual peaks in GC profiles were identified in both groups and correlated with pulmonary hemodynamic and clinical endpoints in the IPAH group. Additionally, GC/MS data were analyzed using autoregression followed by partial least squares regression (AR/PLSR) analysis to discriminate between the IPAH and control groups. After correcting for medicaitons, there were 62 unique compounds in the control group, 32 unique compounds in the IPAH group, and 14 in-common compounds between groups. Peak-by-peak analysis of GC profiles of IPAH group EBC samples identified 6 compounds significantly correlated with pulmonary hemodynamic variables important in IPAH diagnosis. AR/PLSR analysis of GC/MS data resulted in a distinct and identifiable metabolic signature for IPAH patients. Conclusions These findings indicate the utility of EBC VOC analysis to discriminate between severe IPAH and a healthy population; additionally, we identified potential novel biomarkers that correlated with IPAH pulmonary hemodynamic variables that may be important in screening for less severe forms IPAH. PMID:24748102

Identification of key micro-organisms involved in Douchi fermentation by statistical analysis and their use in an experimental fermentation.

PubMed

Chen, C; Xiang, J Y; Hu, W; Xie, Y B; Wang, T J; Cui, J W; Xu, Y; Liu, Z; Xiang, H; Xie, Q

2015-11-01

To screen and identify safe micro-organisms used during Douchi fermentation, and verify the feasibility of producing high-quality Douchi using these identified micro-organisms. PCR-denaturing gradient gel electrophoresis (DGGE) and automatic amino-acid analyser were used to investigate the microbial diversity and free amino acids (FAAs) content of 10 commercial Douchi samples. The correlations between microbial communities and FAAs were analysed by statistical analysis. Ten strains with significant positive correlation were identified. Then an experiment on Douchi fermentation by identified strains was carried out, and the nutritional composition in Douchi was analysed. Results showed that FAAs and relative content of isoflavone aglycones in verification Douchi samples were generally higher than those in commercial Douchi samples. Our study indicated that fungi, yeasts, Bacillus and lactic acid bacteria were the key players in Douchi fermentation, and with identified probiotic micro-organisms participating in fermentation, a higher quality Douchi product was produced. This is the first report to analyse and confirm the key micro-organisms during Douchi fermentation by statistical analysis. This work proves fermentation micro-organisms to be the key influencing factor of Douchi quality, and demonstrates the feasibility of fermenting Douchi using identified starter micro-organisms. © 2015 The Society for Applied Microbiology.

The correlation of initial radiographic characteristics of distal radius fractures and injuries of the triangular fibrocartilage complex.

PubMed

Kasapinova, K; Kamiloski, V

2016-06-01

Our purpose was to determine the correlation of initial radiographic parameters of a distal radius fracture with an injury of the triangular fibrocartilage complex. In a prospective study, 85 patients with surgically treated distal radius fractures were included. Wrist arthroscopy was used to identify and classify triangular fibrocartilage complex lesions. The initial radial length and angulation, dorsal angulation, ulnar variance and distal radioulnar distance were measured. Wrist arthroscopy identified a triangular fibrocartilage complex lesion in 45 patients. Statistical analysis did not identify a correlation with any single radiographic parameter of the distal radius fractures with the associated triangular fibrocartilage complex injuries. The initial radiograph of a distal radius fracture does not predict a triangular fibrocartilage complex injury. III. © The Author(s) 2016.

Temporal evolution of financial-market correlations.

PubMed

Fenn, Daniel J; Porter, Mason A; Williams, Stacy; McDonald, Mark; Johnson, Neil F; Jones, Nick S

2011-08-01

We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007-2008 credit and liquidity crisis.

Temporal evolution of financial-market correlations

NASA Astrophysics Data System (ADS)

Fenn, Daniel J.; Porter, Mason A.; Williams, Stacy; McDonald, Mark; Johnson, Neil F.; Jones, Nick S.

2011-08-01

We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007-2008 credit and liquidity crisis.

Analysis of rocket engine injection combustion processes

NASA Technical Reports Server (NTRS)

Salmon, J. W.

1976-01-01

A critique is given of the JANNAF sub-critical propellant injection/combustion process analysis computer models and application of the models to correlation of well documented hot fire engine data bases. These programs are the distributed energy release (DER) model for conventional liquid propellants injectors and the coaxial injection combustion model (CICM) for gaseous annulus/liquid core coaxial injectors. The critique identifies model inconsistencies while the computer analyses provide quantitative data on predictive accuracy. The program is comprised of three tasks: (1) computer program review and operations; (2) analysis and data correlations; and (3) documentation.

Correlation of maple sap composition with bacterial and fungal communities determined by multiplex automated ribosomal intergenic spacer analysis (MARISA).

PubMed

Filteau, Marie; Lagacé, Luc; LaPointe, Gisèle; Roy, Denis

2011-08-01

During collection, maple sap is contaminated by bacteria and fungi that subsequently colonize the tubing system. The bacterial microbiota has been more characterized than the fungal microbiota, but the impact of both components on maple sap quality remains unclear. This study focused on identifying bacterial and fungal members of maple sap and correlating microbiota composition with maple sap properties. A multiplex automated ribosomal intergenic spacer analysis (MARISA) method was developed to presumptively identify bacterial and fungal members of maple sap samples collected from 19 production sites during the tapping period. Results indicate that the fungal community of maple sap is mainly composed of yeast related to Mrakia sp., Mrakiella sp., Guehomyces pullulans, Cryptococcus victoriae and Williopsis saturnus. Mrakia, Mrakiella and Guehomyces peaks were identified in samples of all production sites and can be considered dominant and stable members of the fungal microbiota of maple sap. A multivariate analysis based on MARISA profiles and maple sap chemical composition data showed correlations between Candida sake, Janthinobacterium lividum, Williopsis sp., Leuconostoc mesenteroides, Mrakia sp., Rhodococcus sp., Pseudomonas tolaasii, G. pullulans and maple sap composition at different flow periods. This study provides new insights on the relationship between microbial community and maple sap quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

Hierarchical multivariate covariance analysis of metabolic connectivity.

PubMed

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Quantitative Analysis of Technological Innovation in Knee Arthroplasty: Using Patent and Publication Metrics to Identify Developments and Trends.

PubMed

Dalton, David M; Burke, Thomas P; Kelly, Enda G; Curtin, Paul D

2016-06-01

Surgery is in a constant continuum of innovation with refinement of technique and instrumentation. Arthroplasty surgery potentially represents an area with highly innovative process. This study highlights key area of innovation in knee arthroplasty over the past 35 years using patent and publication metrics. Growth rates and patterns are analyzed. Patents are correlated to publications as a measure of scientific support. Electronic patent and publication databases were searched over the interval 1980-2014 for "knee arthroplasty" OR "knee replacement." The resulting patent codes were allocated into technology clusters. Citation analysis was performed to identify any important developments missed on initial analysis. The technology clusters identified were further analyzed, individual repeat searches performed, and growth curves plotted. The initial search revealed 3574 patents and 16,552 publications. The largest technology clusters identified were Unicompartmental, Patient-Specific Instrumentation (PSI), Navigation, and Robotic knee arthroplasties. The growth in patent activity correlated strongly with publication activity (Pearson correlation value 0.892, P < .01), but was growing at a faster rate suggesting a decline in vigilance. PSI, objectively the fastest growing technology in the last 5 years, is currently in a period of exponential growth that began a decade ago. Established technologies in the study have double s-shaped patent curves. Identifying trends in emerging technologies is possible using patent metrics and is useful information for training and regulatory bodies. The decline in ratio of publications to patents and the uninterrupted growth of PSI are developments that may warrant further investigation. Copyright © 2015 Elsevier Inc. All rights reserved.

Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences

PubMed Central

Bujkiewicz, Sylwia; Riley, Richard D

2016-01-01

Multivariate random-effects meta-analysis allows the joint synthesis of correlated results from multiple studies, for example, for multiple outcomes or multiple treatment groups. In a Bayesian univariate meta-analysis of one endpoint, the importance of specifying a sensible prior distribution for the between-study variance is well understood. However, in multivariate meta-analysis, there is little guidance about the choice of prior distributions for the variances or, crucially, the between-study correlation, ρB; for the latter, researchers often use a Uniform(−1,1) distribution assuming it is vague. In this paper, an extensive simulation study and a real illustrative example is used to examine the impact of various (realistically) vague prior distributions for ρB and the between-study variances within a Bayesian bivariate random-effects meta-analysis of two correlated treatment effects. A range of diverse scenarios are considered, including complete and missing data, to examine the impact of the prior distributions on posterior results (for treatment effect and between-study correlation), amount of borrowing of strength, and joint predictive distributions of treatment effectiveness in new studies. Two key recommendations are identified to improve the robustness of multivariate meta-analysis results. First, the routine use of a Uniform(−1,1) prior distribution for ρB should be avoided, if possible, as it is not necessarily vague. Instead, researchers should identify a sensible prior distribution, for example, by restricting values to be positive or negative as indicated by prior knowledge. Second, it remains critical to use sensible (e.g. empirically based) prior distributions for the between-study variances, as an inappropriate choice can adversely impact the posterior distribution for ρB, which may then adversely affect inferences such as joint predictive probabilities. These recommendations are especially important with a small number of studies and missing data. PMID:26988929

Risk Factors for Failure of Male Slings and Artificial Urinary Sphincters: Results from a Large Middle European Cohort Study.

PubMed

Hüsch, Tanja; Kretschmer, Alexander; Thomsen, Frauke; Kronlachner, Dominik; Kurosch, Martin; Obaje, Alice; Anding, Ralf; Pottek, Tobias; Rose, Achim; Olianas, Roberto; Friedl, Alexander; Hübner, Wilhelm; Homberg, Roland; Pfitzenmaier, Jesco; Grein, Ulrich; Queissert, Fabian; Naumann, Carsten Maik; Schweiger, Josef; Wotzka, Carola; Nyarangi-Dix, Joanne; Hofmann, Torben; Ulm, Kurt; Bauer, Ricarda M; Haferkamp, Axel

2017-01-01

We analysed the impact of predefined risk factors: age, diabetes, history of pelvic irradiation, prior surgery for stress urinary incontinence (SUI), prior urethral stricture, additional procedure during SUI surgery, duration of incontinence, ASA-classification and cause for incontinence on failure and complications in male SUI surgery. We retrospectively identified 506 patients with an artificial urinary sphincter (AUS) and 513 patients with a male sling (MS) in a multicenter cohort study. Complication rates were correlated to the risk factors in univariate analysis. Subsequently, a multivariate logistic regression adjusted to the risk factors was performed. A p value <0.05 was considered statistically significant. A history of pelvic irradiation was an independent risk factor for explantation in AUS (p < 0.001) and MS (p = 0.018). Moreover, prior urethral stricture (p = 0.036) and higher ASA-classification (p = 0.039) were positively correlated with explantation in univariate analysis for AUS. Urethral erosion was correlated with prior urethral stricture (p < 0.001) and a history of pelvic irradiation (p < 0.001) in AUS. Furthermore, infection was correlated with additional procedures during SUI surgery in univariate analysis (p = 0.037) in MS. We first identified the correlation of higher ASA-classification and explantation in AUS. Nevertheless, only a few novel risk factors had a significant influence on the failure of MS or AUS. © 2016 S. Karger AG, Basel.

Expert golf instructors' student-teacher interaction patterns.

PubMed

Schempp, Paul; McCullick, Bryan; St Pierre, Peter; Woorons, Sophie; You, JeongAe; Clark, Betsy

2004-03-01

The purpose of this study was to identify the dominant instructional interaction patterns of expert golf instructors. Instructors (N = 22) were selected by the Ladies Professional Golf Association (LPGA) Teaching based on the following criteria: (a) 10 or more years of golf teaching experience, (b) LPGA certification, (c) awards received for the quality of their instruction, and (d) peer and student recognition for outstanding teaching. The instructors were videotaped teaching a 60-min lesson to a novice college-age woman with no previous golf experience. The tapes were then analyzed using both the Cheffers Adaptation of Flanders' Interaction Analysis System (CAFIAS) and a qualitative analysis. Based on the findings from descriptive statistics and correlation analyses of the CAFIAS data and qualitative data analysis, several trends were identified. First, the dominant instructional behavior of these teachers was providing information to the students using both explanations and demonstrations. Second, the prevailing instructional interaction pattern of the expert teachers included extensive explanations and demonstrations followed by directions. The student followed the directions by practicing skills and received praise for their achievements. Third, high rates of directions and praise from teachers prompted student practice. Fourth, engaging students in subject-related discussion was positively correlated with teachers' questions but negatively correlated with teachers' criticisms. Finally, teacher acceptance was positively correlated with student analytic behavior, while teachers' talk negatively correlated with students initiating discussions.

ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations.

PubMed

Parvatikar, Akash; Vacaliuc, Gabriel S; Ramanathan, Arvind; Chennubhotla, S Chakra

2018-05-08

Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs-ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Gene expression correlates of postinfective fatigue syndrome after infectious mononucleosis.

PubMed

Cameron, Barbara; Galbraith, Sally; Zhang, Yun; Davenport, Tracey; Vollmer-Conna, Ute; Wakefield, Denis; Hickie, Ian; Dunsmuir, William; Whistler, Toni; Vernon, Suzanne; Reeves, William C; Lloyd, Andrew R

2007-07-01

Infectious mononucleosis (IM) commonly triggers a protracted postinfective fatigue syndrome (PIFS) of unknown pathogenesis. Seven subjects with PIFS with 6 or more months of disabling symptoms and 8 matched control subjects who had recovered promptly from documented IM were studied. The expression of 30,000 genes was examined in the peripheral blood by microarray analysis in 65 longitudinally collected samples. Gene expression patterns associated with PIFS were sought by correlation with symptom factor scores. Differential expression of 733 genes was identified when samples collected early during the illness and at the late (recovered) time point were compared. Of these genes, 234 were found to be significantly correlated with the reported severity of the fatigue symptom factor, and 180 were found to be correlated with the musculoskeletal pain symptom factor. Validation by analysis of the longitudinal expression pattern revealed 35 genes for which changes in expression were consistent with the illness course. These genes included several that are involved in signal transduction pathways, metal ion binding, and ion channel activity. Gene expression correlates of the cardinal symptoms of PIFS after IM have been identified. Further studies of these gene products may help to elucidate the pathogenesis of PIFS.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets

PubMed Central

Bewick, Sharon; Thielen, Peter; Mehoke, Thomas; Breitwieser, Florian P.; Paudel, Shishir; Adhikari, Arjun; Wolfe, Joshua; Slud, Eric V.; Karig, David; Fagan, William F.

2017-01-01

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson’s correlation coefficient (r) and Jaccard’s index (J)–two of the most common metrics for correlation analysis of presence-absence data–can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson’s correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard’s index of similarity (J) can yield improvements over Pearson’s correlation coefficient. However, the standard null model for Jaccard’s index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard’s index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa. PMID:29145425

Applying Recursive Sensitivity Analysis to Multi-Criteria Decision Models to Reduce Bias in Defense Cyber Engineering Analysis

DTIC Science & Technology

2015-10-28

techniques such as regression analysis, correlation, and multicollinearity assessment to identify the change and error on the input to the model...between many of the independent or predictor variables, the issue of multicollinearity may arise [18]. VII. SUMMARY Accurate decisions concerning

Convergent genetic and expression data implicate immunity in Alzheimer's disease

PubMed Central

Jones, Lesley; Lambert, Jean-Charles; Wang, Li-San; Choi, Seung-Hoan; Harold, Denise; Vedernikov, Alexey; Escott-Price, Valentina; Stone, Timothy; Richards, Alexander; Bellenguez, Céline; Ibrahim-Verbaas, Carla A; Naj, Adam C; Sims, Rebecca; Gerrish, Amy; Jun, Gyungah; DeStefano, Anita L; Bis, Joshua C; Beecham, Gary W; Grenier-Boley, Benjamin; Russo, Giancarlo; Thornton-Wells, Tricia A; Jones, Nicola; Smith, Albert V; Chouraki, Vincent; Thomas, Charlene; Ikram, M Arfan; Zelenika, Diana; Vardarajan, Badri N; Kamatani, Yoichiro; Lin, Chiao-Feng; Schmidt, Helena; Kunkle, Brian; Dunstan, Melanie L; Ruiz, Agustin; Bihoreau, Marie-Thérèse; Reitz, Christiane; Pasquier, Florence; Hollingworth, Paul; Hanon, Olivier; Fitzpatrick, Annette L; Buxbaum, Joseph D; Campion, Dominique; Crane, Paul K; Becker, Tim; Gudnason, Vilmundur; Cruchaga, Carlos; Craig, David; Amin, Najaf; Berr, Claudine; Lopez, Oscar L; De Jager, Philip L; Deramecourt, Vincent; Johnston, Janet A; Evans, Denis; Lovestone, Simon; Letteneur, Luc; Kornhuber, Johanes; Tárraga, Lluís; Rubinsztein, David C; Eiriksdottir, Gudny; Sleegers, Kristel; Goate, Alison M; Fiévet, Nathalie; Huentelman, Matthew J; Gill, Michael; Emilsson, Valur; Brown, Kristelle; Kamboh, M Ilyas; Keller, Lina; Barberger-Gateau, Pascale; McGuinness, Bernadette; Larson, Eric B; Myers, Amanda J; Dufouil, Carole; Todd, Stephen; Wallon, David; Love, Seth; Kehoe, Pat; Rogaeva, Ekaterina; Gallacher, John; George-Hyslop, Peter St; Clarimon, Jordi; Lleὀ, Alberti; Bayer, Anthony; Tsuang, Debby W; Yu, Lei; Tsolaki, Magda; Bossù, Paola; Spalletta, Gianfranco; Proitsi, Petra; Collinge, John; Sorbi, Sandro; Garcia, Florentino Sanchez; Fox, Nick; Hardy, John; Naranjo, Maria Candida Deniz; Razquin, Cristina; Bosco, Paola; Clarke, Robert; Brayne, Carol; Galimberti, Daniela; Mancuso, Michelangelo; Moebus, Susanne; Mecocci, Patrizia; del Zompo, Maria; Maier, Wolfgang; Hampel, Harald; Pilotto, Alberto; Bullido, Maria; Panza, Francesco; Caffarra, Paolo; Nacmias, Benedetta; Gilbert, John R; Mayhaus, Manuel; Jessen, Frank; Dichgans, Martin; Lannfelt, Lars; Hakonarson, Hakon; Pichler, Sabrina; Carrasquillo, Minerva M; Ingelsson, Martin; Beekly, Duane; Alavarez, Victoria; Zou, Fanggeng; Valladares, Otto; Younkin, Steven G; Coto, Eliecer; Hamilton-Nelson, Kara L; Mateo, Ignacio; Owen, Michael J; Faber, Kelley M; Jonsson, Palmi V; Combarros, Onofre; O'Donovan, Michael C; Cantwell, Laura B; Soininen, Hilkka; Blacker, Deborah; Mead, Simon; Mosley, Thomas H; Bennett, David A; Harris, Tamara B; Fratiglioni, Laura; Holmes, Clive; de Bruijn, Renee FAG; Passmore, Peter; Montine, Thomas J; Bettens, Karolien; Rotter, Jerome I; Brice, Alexis; Morgan, Kevin; Foroud, Tatiana M; Kukull, Walter A; Hannequin, Didier; Powell, John F; Nalls, Michael A; Ritchie, Karen; Lunetta, Kathryn L; Kauwe, John SK; Boerwinkle, Eric; Riemenschneider, Matthias; Boada, Mercè; Hiltunen, Mikko; Martin, Eden R; Pastor, Pau; Schmidt, Reinhold; Rujescu, Dan; Dartigues, Jean-François; Mayeux, Richard; Tzourio, Christophe; Hofman, Albert; Nöthen, Markus M; Graff, Caroline; Psaty, Bruce M; Haines, Jonathan L; Lathrop, Mark; Pericak-Vance, Margaret A; Launer, Lenore J; Farrer, Lindsay A; van Duijn, Cornelia M; Van Broekhoven, Christine; Ramirez, Alfredo; Schellenberg, Gerard D; Seshadri, Sudha; Amouyel, Philippe; Holmans, Peter A

2015-01-01

Background Late–onset Alzheimer's disease (AD) is heritable with 20 genes showing genome wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (p = 3.27×10-12 after multiple testing correction for pathways), regulation of endocytosis (p = 1.31×10-11), cholesterol transport (p = 2.96 × 10-9) and proteasome-ubiquitin activity (p = 1.34×10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected p 0.002 – 0.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport and protein ubiquitination represent prime targets for AD therapeutics. PMID:25533204

Convergent genetic and expression data implicate immunity in Alzheimer's disease.

PubMed

2015-06-01

Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10(-11)), cholesterol transport (P = 2.96 × 10(-9)), and proteasome-ubiquitin activity (P = 1.34 × 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05). The immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics. Copyright © 2015. Published by Elsevier Inc.

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms

PubMed Central

Esplin, M Sean; Manuck, Tracy A.; Varner, Michael W.; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M.; Ilekis, John

2015-01-01

Objective We sought to employ an innovative tool based on common biological pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB), in order to enhance investigators' ability to identify to highlight common mechanisms and underlying genetic factors responsible for SPTB. Study Design A secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks gestation. Each woman was assessed for the presence of underlying SPTB etiologies. A hierarchical cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis using VEGAS software. Results 1028 women with SPTB were assigned phenotypes. Hierarchical clustering of the phenotypes revealed five major clusters. Cluster 1 (N=445) was characterized by maternal stress, cluster 2 (N=294) by premature membrane rupture, cluster 3 (N=120) by familial factors, and cluster 4 (N=63) by maternal comorbidities. Cluster 5 (N=106) was multifactorial, characterized by infection (INF), decidual hemorrhage (DH) and placental dysfunction (PD). These three phenotypes were highly correlated by Chi-square analysis [PD and DH (p<2.2e-6); PD and INF (p=6.2e-10); INF and DH (p=0.0036)]. Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. Conclusion We identified 5 major clusters of SPTB based on a phenotype tool and hierarchal clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors underlying SPTB. PMID:26070700

Lipidomics study of plasma phospholipid metabolism in early type 2 diabetes rats with ancient prescription Huang-Qi-San intervention by UPLC/Q-TOF-MS and correlation coefficient.

PubMed

Wu, Xia; Zhu, Jian-Cheng; Zhang, Yu; Li, Wei-Min; Rong, Xiang-Lu; Feng, Yi-Fan

2016-08-25

Potential impact of lipid research has been increasingly realized both in disease treatment and prevention. An effective metabolomics approach based on ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF-MS) along with multivariate statistic analysis has been applied for investigating the dynamic change of plasma phospholipids compositions in early type 2 diabetic rats after the treatment of an ancient prescription of Chinese Medicine Huang-Qi-San. The exported UPLC/Q-TOF-MS data of plasma samples were subjected to SIMCA-P and processed by bioMark, mixOmics, Rcomdr packages with R software. A clear score plots of plasma sample groups, including normal control group (NC), model group (MC), positive medicine control group (Flu) and Huang-Qi-San group (HQS), were achieved by principal-components analysis (PCA), partial least-squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Biomarkers were screened out using student T test, principal component regression (PCR), partial least-squares regression (PLS) and important variable method (variable influence on projection, VIP). Structures of metabolites were identified and metabolic pathways were deduced by correlation coefficient. The relationship between compounds was explained by the correlation coefficient diagram, and the metabolic differences between similar compounds were illustrated. Based on KEGG database, the biological significances of identified biomarkers were described. The correlation coefficient was firstly applied to identify the structure and deduce the metabolic pathways of phospholipids metabolites, and the study provided a new methodological cue for further understanding the molecular mechanisms of metabolites in the process of regulating Huang-Qi-San for treating early type 2 diabetes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Reservoir sequence analysis: A new technology for the 90`s and its application to oil and gas fields

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

Wornardt, W.W.

1996-08-01

Reservoir Sequence Analysis when applied to existing fields can increase the production, life of the field and extend the field with a minimum of cost. In this technology we identify reservoir sands in a standard-of-reference well, to establish a seismic sequence stratigraphic well-tie for the entire field. Age date the Maximum Flooding Surfaces and Sequence Boundaries above and below reservoir sands on a well-log and seismic pro- file and/or workstation using High Resolution Biostratigraphic Analysis, species abundance and diversity histograms and their patterns, and paleoenvironmental paleobathymetric changes. Identify the systems tracts and their corresponding reservoir sands in between age datedmore » Maximum Flooding Surfaces. Interpret the reservoir sands as to type, i.e. IVF, point bar, coastal belt, forced regression, falling stage, bottom-set (shingled) turbidites, slope fan channel, channel overbank, and basin floor fans. Identify and correlate the same individual sands in different wells, and note new sands in a well and sands that shale-out in a well. Correlate the Maximum Flooding Surfaces above and below the reservoir section in additional wells to see which part of the reservoir section and sands have been penetrated. Identify systems tracts in additional wells and construct isopach, sand percent maps of individual systems tract interval in each well. Correlate sand packages, with a high degree of confidence, from upthrown to downthrown fault blocks, around salt domes, and updip with downdip.« less

Analysis of Parent Perceptions on Effective School Correlates: A Springboard for Planning.

ERIC Educational Resources Information Center

Murray, David R.

This project was designed to solicit parental perceptions of Caroline Street Elementary School (Saratoga Springs, New York) in terms of Effective Schools, a method of assessing school improvement. Families (n=334) were asked to provide their perceptions regarding correlational characteristics identified as vital to successful school programs:…

Correlation Functions Aid Analyses Of Spectra

NASA Technical Reports Server (NTRS)

Beer, Reinhard; Norton, Robert H., Jr.

1989-01-01

New uses found for correlation functions in analyses of spectra. In approach combining elements of both pattern-recognition and traditional spectral-analysis techniques, spectral lines identified in data appear useless at first glance because they are dominated by noise. New approach particularly useful in measurement of concentrations of rare species of molecules in atmosphere.

Correlational Analysis of Servant Leadership and School Climate

ERIC Educational Resources Information Center

Black, Glenda Lee

2010-01-01

The purpose of this mixed-method research study was to determine the extent that servant leadership was correlated with perceptions of school climate to identify whether there was a relationship between principals' and teachers' perceived practice of servant leadership and of school climate. The study employed a mixed-method approach by first…

Feigned Depression and Feigned Sleepiness: A Voice Acoustical Analysis

ERIC Educational Resources Information Center

Reilly, Nicole; Cannizzaro, Michael S.; Harel, Brian T.; Snyder, Peter J.

2004-01-01

We sought to profile the voice acoustical correlates of simulated, or feigned depression by neurologically and psychiatrically healthy control subjects. We also sought to identify the voice acoustical correlates of feigned sleepiness for these same subjects. Twenty-two participants were asked to speak freely about a cartoon, to count from 1 to 10,…

Latent Profile Analysis of Teacher Perceptions of Parent Contact and Comfort

ERIC Educational Resources Information Center

Stormont, Melissa; Herman, Keith C.; Reinke, Wendy M.; David, Kimberly B.; Goel, Nidhi

2013-01-01

The purpose of the study was to explore patterns of parent involvement as perceived by teachers and identify correlates of these patterns. Parent involvement indicators and correlates were selected from a review of existing research. Participants included 34 teachers and 577 children in kindergarten through third grade. The vast majority of the…

Correlates of picky eating and food neophobia in young children: a systematic review and meta-analysis.

PubMed

Cole, Natasha Chong; An, Ruopeng; Lee, Soo-Yeun; Donovan, Sharon M

2017-07-01

Picky eating behavior is prevalent among toddlers and may negatively impact their growth and development. This article summarizes the correlates of picky eating and food neophobia in young children, which were identified using a socio-ecological framework. A literature search was conducted in 4 electronic databases. Inclusion criteria were English-language peer-reviewed publications that investigated correlate(s) of picky eating or food neophobia in children aged ≤30 months. Correlates were categorized into 4 levels: cell, child, clan (family), and community/country. Thirty-two studies, which examined 89 correlates, were identified from the keyword searches of the databases and manual searches of the reference lists of included articles. The most examined correlates were characteristics related to the child (sex, weight, and dietary intake) and parent (feeding beliefs and practices). A meta-analysis estimated the prevalence of picky eating to be 22%. Each additional month of a child's age was associated with a 0.06 U increase in the Children's Eating Behavior Questionnaire food fussiness score. This review highlights the importance of investigating child-parent dyads and bidirectional feeding interactions and draws attention to the lack of picky eating research at the level of the cell and the community/country. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Identifying technical aliases in SELDI mass spectra of complex mixtures of proteins

PubMed Central

2013-01-01

Background Biomarker discovery datasets created using mass spectrum protein profiling of complex mixtures of proteins contain many peaks that represent the same protein with different charge states. Correlated variables such as these can confound the statistical analyses of proteomic data. Previously we developed an algorithm that clustered mass spectrum peaks that were biologically or technically correlated. Here we demonstrate an algorithm that clusters correlated technical aliases only. Results In this paper, we propose a preprocessing algorithm that can be used for grouping technical aliases in mass spectrometry protein profiling data. The stringency of the variance allowed for clustering is customizable, thereby affecting the number of peaks that are clustered. Subsequent analysis of the clusters, instead of individual peaks, helps reduce difficulties associated with technically-correlated data, and can aid more efficient biomarker identification. Conclusions This software can be used to pre-process and thereby decrease the complexity of protein profiling proteomics data, thus simplifying the subsequent analysis of biomarkers by decreasing the number of tests. The software is also a practical tool for identifying which features to investigate further by purification, identification and confirmation. PMID:24010718

Quantitative analysis of chromosomal CGH in human breast tumors associates copy number abnormalities with p53 status and patient survival

PubMed Central

Jain, Ajay N.; Chin, Koei; Børresen-Dale, Anne-Lise; Erikstein, Bjorn K.; Lonning, Per Eystein; Kaaresen, Rolf; Gray, Joe W.

2001-01-01

We present a general method for rigorously identifying correlations between variations in large-scale molecular profiles and outcomes and apply it to chromosomal comparative genomic hybridization data from a set of 52 breast tumors. We identify two loci where copy number abnormalities are correlated with poor survival outcome (gain at 8q24 and loss at 9q13). We also identify a relationship between abnormalities at two loci and the mutational status of p53. Gain at 8q24 and loss at 5q15-5q21 are linked with mutant p53. The 9q and 5q losses suggest the possibility of gene products involved in breast cancer progression. The analytical techniques are general and also are applicable to the analysis of array-based expression data. PMID:11438741

Multifractal analysis of information processing in hippocampal neural ensembles during working memory under Δ9-tetrahydrocannabinol administration

PubMed Central

Fetterhoff, Dustin; Opris, Ioan; Simpson, Sean L.; Deadwyler, Sam A.; Hampson, Robert E.; Kraft, Robert A.

2014-01-01

Background Multifractal analysis quantifies the time-scale-invariant properties in data by describing the structure of variability over time. By applying this analysis to hippocampal interspike interval sequences recorded during performance of a working memory task, a measure of long-range temporal correlations and multifractal dynamics can reveal single neuron correlates of information processing. New method Wavelet leaders-based multifractal analysis (WLMA) was applied to hippocampal interspike intervals recorded during a working memory task. WLMA can be used to identify neurons likely to exhibit information processing relevant to operation of brain–computer interfaces and nonlinear neuronal models. Results Neurons involved in memory processing (“Functional Cell Types” or FCTs) showed a greater degree of multifractal firing properties than neurons without task-relevant firing characteristics. In addition, previously unidentified FCTs were revealed because multifractal analysis suggested further functional classification. The cannabinoid-type 1 receptor partial agonist, tetrahydrocannabinol (THC), selectively reduced multifractal dynamics in FCT neurons compared to non-FCT neurons. Comparison with existing methods WLMA is an objective tool for quantifying the memory-correlated complexity represented by FCTs that reveals additional information compared to classification of FCTs using traditional z-scores to identify neuronal correlates of behavioral events. Conclusion z-Score-based FCT classification provides limited information about the dynamical range of neuronal activity characterized by WLMA. Increased complexity, as measured with multifractal analysis, may be a marker of functional involvement in memory processing. The level of multifractal attributes can be used to differentially emphasize neural signals to improve computational models and algorithms underlying brain–computer interfaces. PMID:25086297

Characterization of Aroma-Active Components and Antioxidant Activity Analysis of E-jiao (Colla Corii Asini) from Different Geographical Origins.

PubMed

Zhang, Shan; Xu, Lu; Liu, Yang-Xi; Fu, Hai-Yan; Xiao, Zuo-Bing; She, Yuan-Bin

2018-04-01

E-jiao (Colla Corii Asini, CCA) has been widely used as a healthy food and Chinese medicine. Although authentic CCA is characterized by its typical sweet and neutral fragrance, its aroma components have been rarely investigated. This work investigated the aroma-active components and antioxidant activity of 19 CCAs from different geographical origins. CCA extracts obtained by simultaneous distillation and extraction were analyzed by gas chromatography-mass spectrometry (GC-MS), gas chromatography-olfactometry (GC-O) and sensory analysis. The antioxidant activity of CCAs was determined by ABTS and DPPH assays. A total of 65 volatile compounds were identified and quantified by GC-MS and 23 aroma-active compounds were identified by GC-O and aroma extract dilution analysis. The most powerful aroma-active compounds were identified based on the flavor dilution factor and their contents were compared among the 19 CCAs. Principal component analysis of the 23 aroma-active components showed 3 significant clusters. Canonical correlation analysis between antioxidant assays and the 23 aroma-active compounds indicates strong correlation (r = 0.9776, p = 0.0281). Analysis of aroma-active components shows potential for quality evaluation and discrimination of CCAs from different geographical origins.

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs

PubMed Central

Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

2015-01-01

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006–2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources. PMID:26492263

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.

PubMed

Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

2015-10-20

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

The Use of Citation Counting to Identify Research Trends

ERIC Educational Resources Information Center

Rothman, Harry; Woodhead, Michael

1971-01-01

The analysis and application of manpower statistics to identify some long-term international research trends in economic entomology and pest conrol are described. Movements in research interests, particularly towards biological methods of control, correlations between these sectors, and the difficulties encountered in the construction of a…

Identifying Node Role in Social Network Based on Multiple Indicators

PubMed Central

Huang, Shaobin; Lv, Tianyang; Zhang, Xizhe; Yang, Yange; Zheng, Weimin; Wen, Chao

2014-01-01

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role. PMID:25089823

A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions

PubMed Central

2013-01-01

Background Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments. Results Correlation analysis has revealed statistically significant connections between metabolites, where differences in correlations between cells exposed to different oxygen levels have been highlighted as markers of hypoxic metabolism in cancer. Network mapping onto reconstructed human metabolic models is a novel addition to correlation analysis. Correlated metabolites have been mapped onto the Edinburgh human metabolic network (EHMN) with the aim of interlinking metabolites found to be regulated in a similar fashion in response to oxygen. This revealed novel pathways within the metabolic network that may be key to tumour cell survival at low oxygen. Results show that the metabolic responses to lowering oxygen availability can be conserved or specific to a particular cell line. Network-based correlation analysis identified conserved metabolites including malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate. In this way, this method has revealed metabolites not previously linked, or less well recognised, with respect to hypoxia before. Lactate fermentation is one of the key themes discussed in the field of hypoxia; however, malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate, which are connected by a single pathway, may provide a more significant marker of hypoxia in cancer. Conclusions Metabolic networks generated for each cell line were compared to identify conserved metabolite pathway responses to low oxygen environments. Furthermore, we believe this methodology will have general application within metabolomics. PMID:24153255

Identification of stress responsive genes by studying specific relationships between mRNA and protein abundance.

PubMed

Morimoto, Shimpei; Yahara, Koji

2018-03-01

Protein expression is regulated by the production and degradation of mRNAs and proteins but the specifics of their relationship are controversial. Although technological advances have enabled genome-wide and time-series surveys of mRNA and protein abundance, recent studies have shown paradoxical results, with most statistical analyses being limited to linear correlation, or analysis of variance applied separately to mRNA and protein datasets. Here, using recently analyzed genome-wide time-series data, we have developed a statistical analysis framework for identifying which types of genes or biological gene groups have significant correlation between mRNA and protein abundance after accounting for potential time delays. Our framework stratifies all genes in terms of the extent of time delay, conducts gene clustering in each stratum, and performs a non-parametric statistical test of the correlation between mRNA and protein abundance in a gene cluster. Consequently, we revealed stronger correlations than previously reported between mRNA and protein abundance in two metabolic pathways. Moreover, we identified a pair of stress responsive genes ( ADC17 and KIN1 ) that showed a highly similar time series of mRNA and protein abundance. Furthermore, we confirmed robustness of the analysis framework by applying it to another genome-wide time-series data and identifying a cytoskeleton-related gene cluster (keratin 18, keratin 17, and mitotic spindle positioning) that shows similar correlation. The significant correlation and highly similar changes of mRNA and protein abundance suggests a concerted role of these genes in cellular stress response, which we consider provides an answer to the question of the specific relationships between mRNA and protein in a cell. In addition, our framework for studying the relationship between mRNAs and proteins in a cell will provide a basis for studying specific relationships between mRNA and protein abundance after accounting for potential time delays.

Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Zhang, Hong; Gao, You

2017-01-01

Identifying the mutual interaction in aero-engine gas path system is a crucial problem that facilitates the understanding of emerging structures in complex system. By employing the multiscale multifractal detrended cross-correlation analysis method to aero-engine gas path system, the cross-correlation characteristics between gas path system parameters are established. Further, we apply multiscale multifractal detrended cross-correlation distance matrix and minimum spanning tree to investigate the mutual interactions of gas path variables. The results can infer that the low-spool rotor speed (N1) and engine pressure ratio (EPR) are main gas path parameters. The application of proposed method contributes to promote our understanding of the internal mechanisms and structures of aero-engine dynamics.

Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis

PubMed Central

Inouye, Michael; Ripatti, Samuli; Kettunen, Johannes; Lyytikäinen, Leo-Pekka; Oksala, Niku; Laurila, Pirkka-Pekka; Kangas, Antti J.; Soininen, Pasi; Savolainen, Markku J.; Viikari, Jorma; Kähönen, Mika; Perola, Markus; Salomaa, Veikko; Raitakari, Olli; Lehtimäki, Terho; Taskinen, Marja-Riitta; Järvelin, Marjo-Riitta; Ala-Korpela, Mika; Palotie, Aarno; de Bakker, Paul I. W.

2012-01-01

Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis. PMID:22916037

Characterising volcanic cycles at Soufriere Hills Volcano, Montserrat: Time series analysis of multi-parameter satellite data

NASA Astrophysics Data System (ADS)

Flower, Verity J. B.; Carn, Simon A.

2015-10-01

The identification of cyclic volcanic activity can elucidate underlying eruption dynamics and aid volcanic hazard mitigation. Whilst satellite datasets are often analysed individually, here we exploit the multi-platform NASA A-Train satellite constellation to cross-correlate cyclical signals identified using complementary measurement techniques at Soufriere Hills Volcano (SHV), Montserrat. In this paper we present a Multi-taper (MTM) Fast Fourier Transform (FFT) analysis of coincident SO2 and thermal infrared (TIR) satellite measurements at SHV facilitating the identification of cyclical volcanic behaviour. These measurements were collected by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) (respectively) in the A-Train. We identify a correlating cycle in both the OMI and MODIS data (54-58 days), with this multi-week feature attributable to episodes of dome growth. The 50 day cycles were also identified in ground-based SO2 data at SHV, confirming the validity of our analysis and further corroborating the presence of this cycle at the volcano. In addition a 12 day cycle was identified in the OMI data, previously attributed to variable lava effusion rates on shorter timescales. OMI data also display a one week (7-8 days) cycle attributable to cyclical variations in viewing angle resulting from the orbital characteristics of the Aura satellite. Longer period cycles possibly relating to magma intrusion were identified in the OMI record (102-, 121-, and 159 days); in addition to a 238-day cycle identified in the MODIS data corresponding to periodic destabilisation of the lava dome. Through the analysis of reconstructions generated from cycles identified in the OMI and MODIS data, periods of unrest were identified, including the major dome collapse of 20th May 2006 and significant explosive event of 3rd January 2009. Our analysis confirms the potential for identification of cyclical volcanic activity through combined analysis of satellite data, which would be of particular value at poorly monitored volcanic systems.

Functional network connectivity analysis based on partial correlation in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Zhang, Nan; Guan, Xiaoting; Zhang, Yumei; Li, Jingjing; Chen, Hongyan; Chen, Kewei; Fleisher, Adam; Yao, Li; Wu, Xia

2009-02-01

Functional network connectivity (FNC) measures the temporal dependency among the time courses of functional networks. However, the marginal correlation between two networks used in the classic FNC analysis approach doesn't separate the FNC from the direct/indirect effects of other networks. In this study, we proposed an alternative approach based on partial correlation to evaluate the FNC, since partial correlation based FNC can reveal the direct interaction between a pair of networks, removing dependencies or influences from others. Previous studies have demonstrated less task-specific activation and less rest-state activity in Alzheimer's disease (AD). We applied present approach to contrast FNC differences of resting state network (RSN) between AD and normal controls (NC). The fMRI data under resting condition were collected from 15 AD and 16 NC. FNC was calculated for each pair of six RSNs identified using Group ICA, thus resulting in 15 (2 out of 6) pairs for each subject. Partial correlation based FNC analysis indicated 6 pairs significant differences between groups, while marginal correlation only revealed 2 pairs (involved in the partial correlation results). Additionally, patients showed lower correlation than controls among most of the FNC differences. Our results provide new evidences for the disconnection hypothesis in AD.

Neural network post-processing of grayscale optical correlator

NASA Technical Reports Server (NTRS)

Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

2005-01-01

In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

WGCNA: an R package for weighted correlation network analysis.

PubMed

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

WGCNA: an R package for weighted correlation network analysis

PubMed Central

Langfelder, Peter; Horvath, Steve

2008-01-01

Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008

Dimensional Analysis on Forest Fuel Bed Fire Spread.

PubMed

Yang, Jiann C

2018-01-01

A dimensional analysis was performed to correlate the fuel bed fire rate of spread data previously reported in the literature. Under wind condition, six pertinent dimensionless groups were identified, namely dimensionless fire spread rate, dimensionless fuel particle size, fuel moisture content, dimensionless fuel bed depth or dimensionless fuel loading density, dimensionless wind speed, and angle of inclination of fuel bed. Under no-wind condition, five similar dimensionless groups resulted. Given the uncertainties associated with some of the parameters used to estimate the dimensionless groups, the dimensionless correlations using the resulting dimensionless groups correlate the fire rates of spread reasonably well under wind and no-wind conditions.

Impact of distal mutations on the network of coupled motions correlated to hydride transfer in dihydrofolate reductase.

PubMed

Wong, Kim F; Selzer, Tzvia; Benkovic, Stephen J; Hammes-Schiffer, Sharon

2005-05-10

A comprehensive analysis of the network of coupled motions correlated to hydride transfer in dihydrofolate reductase is presented. Hybrid quantum/classical molecular dynamics simulations are combined with a rank correlation analysis method to extract thermally averaged properties that vary along the collective reaction coordinate according to a prescribed target model. Coupled motions correlated to hydride transfer are identified throughout the enzyme. Calculations for wild-type dihydrofolate reductase and a triple mutant, along with the associated single and double mutants, indicate that each enzyme system samples a unique distribution of coupled motions correlated to hydride transfer. These coupled motions provide an explanation for the experimentally measured nonadditivity effects in the hydride transfer rates for these mutants. This analysis illustrates that mutations distal to the active site can introduce nonlocal structural perturbations and significantly impact the catalytic rate by altering the conformational motions of the entire enzyme and the probability of sampling conformations conducive to the catalyzed reaction.

Portable, real-time alloy identification of metallic wear debris from machinery lubrication systems: laser-induced breakdown spectroscopy versus x-ray fluorescence

NASA Astrophysics Data System (ADS)

Suresh, Pooja

2014-05-01

Alloy identification of oil-borne wear debris captured on chip detectors, filters and magnetic plugs allows the machinery maintainer to assess the health of the engine or gearbox and identify specific component damage. Today, such identification can be achieved in real time using portable, at-line laser-induced breakdown spectroscopy (LIBS) and Xray fluorescence (XRF) instruments. Both techniques can be utilized in various industries including aviation, marine, railways, heavy diesel and other industrial machinery with, however, some substantial differences in application and instrument performance. In this work, the performances of a LIBS and an XRF instrument are compared based on measurements of a wide range of typical aerospace alloys including steels, titanium, aluminum and nickel alloys. Measurement results were analyzed with a staged correlation technique specifically developed for the purposes of this study - identifying the particle alloy composition using a pre-recorded library of spectral signatures. The analysis is performed in two stages: first, the base element of the alloy is determined by correlation with the stored elemental spectra and then, the alloy is identified by matching the particle's spectral signature using parametric correlation against the stored spectra of all alloys that have the same base element. The correlation analysis has achieved highly repeatable discrimination between alloys of similar composition. Portable LIBS demonstrates higher detection accuracy and better identification of alloys comprising lighter elements as compared to that of the portable XRF system, and reveals a significant reduction in the analysis time over XRF.

Evaluation of facial attractiveness in black people according to the subjective facial analysis criteria.

PubMed

Melo, Andréa Reis de; Conti, Ana Cláudia de Castro Ferreira; Almeida-Pedrin, Renata Rodrigues; Didier, Victor; Valarelli, Danilo Pinelli; Capelozza Filho, Leopoldino

2017-02-01

The objective of this study was to evaluate the facial attractiveness in 30 black individuals, according to the Subjective Facial Analysis criteria. Frontal and profile view photographs of 30 black individuals were evaluated for facial attractiveness and classified as esthetically unpleasant, acceptable, or pleasant by 50 evaluators: the 30 individuals from the sample, 10 orthodontists, and 10 laymen. Besides assessing the facial attractiveness, the evaluators had to identify the structures responsible for the classification as unpleasant and pleasant. Intraexaminer agreement was assessed by using Spearman's correlation, correlation within each category using Kendall concordance coefficient, and correlation between the 3 categories using chi-square test and proportions. Most of the frontal (53. 5%) and profile view (54. 9%) photographs were classified as esthetically acceptable. The structures most identified as esthetically unpleasant were the mouth, lips, and face, in the frontal view; and nose and chin in the profile view. The structures most identified as esthetically pleasant were harmony, face, and mouth, in the frontal view; and harmony and nose in the profile view. The ratings by the examiners in the sample and laymen groups showed statistically significant correlation in both views. The orthodontists agreed with the laymen on the evaluation of the frontal view and disagreed on profile view, especially regarding whether the images were esthetically unpleasant or acceptable. Based on these results, the evaluation of facial attractiveness according to the Subjective Facial Analysis criteria proved to be applicable and to have a subjective influence; therefore, it is suggested that the patient's opinion regarding the facial esthetics should be considered in orthodontic treatmentplanning.

Application of optical correlation techniques to particle imaging velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1988-01-01

Pulsed laser sheet velocimetry yields nonintrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usually MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the partical image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.

Genetic association of impulsivity in young adults: a multivariate study

PubMed Central

Khadka, S; Narayanan, B; Meda, S A; Gelernter, J; Han, S; Sawyer, B; Aslanzadeh, F; Stevens, M C; Hawkins, K A; Anticevic, A; Potenza, M N; Pearlson, G D

2014-01-01

Impulsivity is a heritable, multifaceted construct with clinically relevant links to multiple psychopathologies. We assessed impulsivity in young adult (N~2100) participants in a longitudinal study, using self-report questionnaires and computer-based behavioral tasks. Analysis was restricted to the subset (N=426) who underwent genotyping. Multivariate association between impulsivity measures and single-nucleotide polymorphism data was implemented using parallel independent component analysis (Para-ICA). Pathways associated with multiple genes in components that correlated significantly with impulsivity phenotypes were then identified using a pathway enrichment analysis. Para-ICA revealed two significantly correlated genotype–phenotype component pairs. One impulsivity component included the reward responsiveness subscale and behavioral inhibition scale of the Behavioral-Inhibition System/Behavioral-Activation System scale, and the second impulsivity component included the non-planning subscale of the Barratt Impulsiveness Scale and the Experiential Discounting Task. Pathway analysis identified processes related to neurogenesis, nervous system signal generation/amplification, neurotransmission and immune response. We identified various genes and gene regulatory pathways associated with empirically derived impulsivity components. Our study suggests that gene networks implicated previously in brain development, neurotransmission and immune response are related to impulsive tendencies and behaviors. PMID:25268255

Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer

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

Zhang, Hui; Liu, Tao; Zhang, Zhen

Ovarian cancer remains the most lethal gynecological malignancy in the developed world, despite recent advances in genomic information and treatment. To better understand this disease, define an integrated proteogenomic landscape, and identify factors associated with homologous repair deficiency (HRD) and overall survival, we performed a comprehensive proteomic characterization of ovarian high-grade serous carcinomas (HGSC) previously characterized by The Cancer Genome Atlas (TCGA). We observed that messenger RNA transcript abundance did not reliably predict abundance for 10,030 proteins across 174 tumors. Clustering of tumors based on protein abundance identified five subtypes, two of which correlated robustly with mesenchymal and proliferative subtypes,more » while tumors characterized as immunoreactive or differentiated at the transcript level were intermixed at the protein level. At the genome level, HGSC is characterized by a complex landscape of somatic copy number alterations (CNA), which individually do not correlate significantly with survival. Correlation of CNAs with protein abundances identified loci with significant trans regulatory effects mapping to pathways associated with proliferation, cell motility/invasion, and immune regulation, three known hallmarks of cancer. Using the trans regulated proteins we also created models significantly correlated with patient survival by multivariate analysis. Integrating protein abundance with specific post-translational modification data identified subnetworks correlated with HRD status; specifically, acetylation of Lys12 and Lys16 on histone H4 was associated with HRD status. Using quantitative phosphoproteomics data covering 4,420 proteins as reflective of pathway activity, we identified the PDGFR and VEGFR signaling pathways as significantly up-regulated in patients with short overall survival, independent of PDGFR and VEGFR protein levels, potentially informing the use of anti-angiogenic therapies. Components of the Rho/Rac/Cdc42 cell motility pathways were also significantly enriched for short survival. Overall, proteomics provided new insights into ovarian cancer not apparent from genomic analysis and enabling a deeper understanding of HGSC with the potential to inform targeted therapeutics.« less

Co-expression modules construction by WGCNA and identify potential prognostic markers of uveal melanoma.

PubMed

Wan, Qi; Tang, Jing; Han, Yu; Wang, Dan

2018-01-01

Uveal melanoma is an aggressive cancer which has a high percentage recurrence and with a worse prognosis. Identify the potential prognostic markers of uveal melanoma may provide information for early detection of recurrence and treatment. RNA sequence data of uveal melanoma and patient clinic traits were obtained from The Cancer Genome Atlas (TCGA) database. Co-expression modules were built by weighted gene co -expression network analysis (WGCNA) and applied to investigate the relationship underlying modules and clinic traits. Besides, functional enrichment analysis was performed on these co-expression genes from interested modules. First, using WGCNA, identified 21 co-expression modules were constructed by the 10975 genes from the 80 human uveal melanoma samples. The number of genes in these modules ranged from 42 to 5091. Found four co -expression modules significantly correlated with three clinic traits (status, recurrence and recurrence Time). Module red, and purple positively correlated with patient's life status and recurrence Time. Module green positively correlates with recurrence. The result of functional enrichment analysis showed that the module magenta was mainly enriched genetic material assemble processes, the purple module was mainly enriched in tissue homeostasis and melanosome membrane and the module red was mainly enriched metastasis of cell, suggesting its critical role in the recurrence and development of the disease. Additionally, identified the hug gene (top connectivity with other genes) in each module. The hub gene SLC17A7, NTRK2, ABTB1 and ADPRHL1 might play a vital role in recurrence of uveal melanoma. Our findings provided the framework of co-expression gene modules of uveal melanoma and identified some prognostic markers might be detection of recurrence and treatment for uveal melanoma. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genomic and protein expression profiling identifies CDK6 as novel independent prognostic marker in medulloblastoma.

PubMed

Mendrzyk, Frank; Radlwimmer, Bernhard; Joos, Stefan; Kokocinski, Felix; Benner, Axel; Stange, Daniel E; Neben, Kai; Fiegler, Heike; Carter, Nigel P; Reifenberger, Guido; Korshunov, Andrey; Lichter, Peter

2005-12-01

Medulloblastoma is the most common malignant brain tumor in children. Despite multimodal aggressive treatment, nearly half of the patients die as a result of this tumor. Identification of molecular markers for prognosis and development of novel pathogenesis-based therapies depends crucially on a better understanding of medulloblastoma pathomechanisms. We performed genome-wide analysis of DNA copy number imbalances in 47 medulloblastomas using comparative genomic hybridization to large insert DNA microarrays (matrix-CGH). The expression of selected candidate genes identified by matrix-CGH was analyzed immunohistochemically on tissue microarrays representing medulloblastomas from 189 clinically well-documented patients. To identify novel prognostic markers, genomic findings and protein expression data were correlated to patient survival. Matrix-CGH analysis revealed frequent DNA copy number alterations of several novel candidate regions. Among these, gains at 17q23.2-qter (P < .01) and losses at 17p13.1 to 17p13.3 (P = .04) were significantly correlated to poor prognosis. Within 17q23.2-qter and 7q21.2, two of the most frequently gained chromosomal regions, confined amplicons were identified that contained the PPM1D and CDK6 genes, respectively. Immunohistochemistry revealed strong expression of PPM1D in 148 (88%) of 168 and CDK6 in 50 (30%) of 169 medulloblastomas. Overexpression of CDK6 correlated significantly with poor prognosis (P < .01) and represented an independent prognostic marker of overall survival on multivariate analysis (P = .02). We identified CDK6 as a novel molecular marker that can be determined by immunohistochemistry on routinely processed tissue specimens and may facilitate the prognostic assessment of medulloblastoma patients. Furthermore, increased protein-levels of PPM1D and CDK6 may link the TP53 and RB1 tumor suppressor pathways to medulloblastoma pathomechanisms.

DGCA: A comprehensive R package for Differential Gene Correlation Analysis.

PubMed

McKenzie, Andrew T; Katsyv, Igor; Song, Won-Min; Wang, Minghui; Zhang, Bin

2016-11-15

Dissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct condition. In this study we develop an R package, DGCA (for Differential Gene Correlation Analysis), which offers a suite of tools for computing and analyzing differential correlations between gene pairs across multiple conditions. To minimize parametric assumptions, DGCA computes empirical p-values via permutation testing. To understand differential correlations at a systems level, DGCA performs higher-order analyses such as measuring the average difference in correlation and multiscale clustering analysis of differential correlation networks. Through a simulation study, we show that the straightforward z-score based method that DGCA employs significantly outperforms the existing alternative methods for calculating differential correlation. Application of DGCA to the TCGA RNA-seq data in breast cancer not only identifies key changes in the regulatory relationships between TP53 and PTEN and their target genes in the presence of inactivating mutations, but also reveals an immune-related differential correlation module that is specific to triple negative breast cancer (TNBC). DGCA is an R package for systematically assessing the difference in gene-gene regulatory relationships under different conditions. This user-friendly, effective, and comprehensive software tool will greatly facilitate the application of differential correlation analysis in many biological studies and thus will help identification of novel signaling pathways, biomarkers, and targets in complex biological systems and diseases.

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma

PubMed Central

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-01-01

Objective This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Methods Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Results Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification (P=0.009) or deletion (P=0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly (P=1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Conclusion Chromosomal CNVs may contribute to their transcript expression in cervical cancer. PMID:29312578

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma.

PubMed

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-12-12

This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification ( P =0.009) or deletion ( P =0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly ( P =1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Chromosomal CNVs may contribute to their transcript expression in cervical cancer.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

Hypomagnesemia predicts postoperative biochemical hypocalcemia after thyroidectomy.

PubMed

Luo, Han; Yang, Hongliu; Zhao, Wanjun; Wei, Tao; Su, Anping; Wang, Bin; Zhu, Jingqiang

2017-05-25

To investigate the role of magnesium in biochemical and symptomatic hypocalcemia, a retrospective study was conducted. Less-than-total thyroidectomy patients were excluded from the final analysis. Identified the risk factors of biochemical and symptomatic hypocalcemia, and investigated the correlation by logistic regression and correlation test respectively. A total of 304 patients were included in the final analysis. General incidence of hypomagnesemia was 23.36%. Logistic regression showed that gender (female) (OR = 2.238, p = 0.015) and postoperative hypomagnesemia (OR = 2.010, p = 0.017) were independent risk factors for biochemical hypocalcemia. Both Pearson and partial correlation tests indicated there was indeed significant relation between calcium and magnesium. However, relative decreasing of iPTH (>70%) (6.691, p < 0.001) and hypocalcemia (2.222, p = 0.046) were identified as risk factors of symptomatic hypocalcemia. The difference remained significant even in normoparathyroidism patients. Postoperative hypomagnesemia was independent risk factor of biochemical hypocalcemia. Relative decline of iPTH was predominating in predicting symptomatic hypocalcemia.

Accurate Structural Correlations from Maximum Likelihood Superpositions

PubMed Central

Theobald, Douglas L; Wuttke, Deborah S

2008-01-01

The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology. PMID:18282091

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma

PubMed Central

Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-01-01

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADCmean, ADCmin, ADCmedian, and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADCmean, ADCmin, ADCmedian, P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading. PMID:29805759

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

PubMed

Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

2015-09-01

We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P < 2.2e-6; PD and INF, P = 6.2e-10; INF and DH, (P = .0036). Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

Hierarchical multivariate covariance analysis of metabolic connectivity

PubMed Central

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-01-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI). PMID:25294129

Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

NASA Astrophysics Data System (ADS)

Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

2012-10-01

In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

A quadratically regularized functional canonical correlation analysis for identifying the global structure of pleiotropy with NGS data

PubMed Central

Zhu, Yun; Fan, Ruzong; Xiong, Momiao

2017-01-01

Investigating the pleiotropic effects of genetic variants can increase statistical power, provide important information to achieve deep understanding of the complex genetic structures of disease, and offer powerful tools for designing effective treatments with fewer side effects. However, the current multiple phenotype association analysis paradigm lacks breadth (number of phenotypes and genetic variants jointly analyzed at the same time) and depth (hierarchical structure of phenotype and genotypes). A key issue for high dimensional pleiotropic analysis is to effectively extract informative internal representation and features from high dimensional genotype and phenotype data. To explore correlation information of genetic variants, effectively reduce data dimensions, and overcome critical barriers in advancing the development of novel statistical methods and computational algorithms for genetic pleiotropic analysis, we proposed a new statistic method referred to as a quadratically regularized functional CCA (QRFCCA) for association analysis which combines three approaches: (1) quadratically regularized matrix factorization, (2) functional data analysis and (3) canonical correlation analysis (CCA). Large-scale simulations show that the QRFCCA has a much higher power than that of the ten competing statistics while retaining the appropriate type 1 errors. To further evaluate performance, the QRFCCA and ten other statistics are applied to the whole genome sequencing dataset from the TwinsUK study. We identify a total of 79 genes with rare variants and 67 genes with common variants significantly associated with the 46 traits using QRFCCA. The results show that the QRFCCA substantially outperforms the ten other statistics. PMID:29040274

Strategy for an Association Study of the Intestinal Microbiome and Brain Metabolome Across the Lifespan of Rats.

PubMed

Chen, Tianlu; You, Yijun; Xie, Guoxiang; Zheng, Xiaojiao; Zhao, Aihua; Liu, Jiajian; Zhao, Qing; Wang, Shouli; Huang, Fengjie; Rajani, Cynthia; Wang, Congcong; Chen, Shaoqiu; Ni, Yan; Yu, Herbert; Deng, Youping; Wang, Xiaoyan; Jia, Wei

2018-02-20

There is increased appreciation for the diverse roles of the microbiome-gut-brain axis on mammalian growth and health throughout the lifespan. Numerous studies have demonstrated that the gut microbiome and their metabolites are extensively involved in the communication between brain and gut. Association study of brain metabolome and gut microbiome is an active field offering large amounts of information on the interaction of microbiome, brain and gut but data size and complicated hierarchical relationships were found to be major obstacles to the formation of significant, reproducible conclusions. This study addressed a two-level strategy of brain metabolome and gut microbiome association analysis of male Wistar rats in the process of growth, employing several analytical platforms and various bioinformatics methods. Trajectory analysis showed that the age-related brain metabolome and gut microbiome had similarity in overall alteration patterns. Four high taxonomical level correlated pairs of "metabolite type-bacterial phylum", including "lipids-Spirochaetes", "free fatty acids (FFAs)-Firmicutes", "bile acids (BAs)-Firmicutes", and "Neurotransmitters-Bacteroidetes", were screened out based on unit- and multivariant correlation analysis and function analysis. Four groups of specific "metabolite-bacterium" association pairs from within the above high level key pairs were further identified. The key correlation pairs were validated by an independent animal study. This two-level strategy is effective in identifying principal correlations in big data sets obtained from the systematic multiomics study, furthering our understanding on the lifelong connection between brain and gut.

Mortality prediction of head Abbreviated Injury Score and Glasgow Coma Scale: analysis of 7,764 head injuries.

PubMed

Demetriades, Demetrios; Kuncir, Eric; Murray, James; Velmahos, George C; Rhee, Peter; Chan, Linda

2004-08-01

We assessed the prognostic value and limitations of Glasgow Coma Scale (GCS) and head Abbreviated Injury Score (AIS) and correlated head AIS with GCS. We studied 7,764 patients with head injuries. Bivariate analysis was performed to examine the relationship of GCS, head AIS, age, gender, and mechanism of injury with mortality. Stepwise logistic regression analysis was used to identify the independent risk factors associated with mortality. The overall mortality in the group of head injury patients with no other major extracranial injuries and no hypotension on admission was 9.3%. Logistic regression analysis identified head AIS, GCS, age, and mechanism of injury as significant independent risk factors of death. The prognostic value of GCS and head AIS was significantly affected by the mechanism of injury and the age of the patient. Patients with similar GCS or head AIS but different mechanisms of injury or ages had significantly different outcomes. The adjusted odds ratio of death in penetrating trauma was 5.2 (3.9, 7.0), p < 0.0001, and in the age group > or = 55 years the adjusted odds ratio was 3.4 (2.6, 4.6), p < 0.0001. There was no correlation between head AIS and GCS (correlation coefficient -0.31). Mechanism of injury and age have a major effect in the predictive value of GCS and head AIS. There is no good correlation between GCS and head AIS.

Effect of rotational alignment on outcome of total knee arthroplasty

PubMed Central

Breugem, Stefan J; van den Bekerom, Michel PJ; Tuinebreijer, Willem E; van Geenen, Rutger C I

2015-01-01

Background and purpose Poor outcomes have been linked to errors in rotational alignment of total knee arthroplasty components. The aims of this study were to determine the correlation between rotational alignment and outcome, to review the success of revision for malrotated total knee arthroplasty, and to determine whether evidence-based guidelines for malrotated total knee arthroplasty can be proposed. Patients and methods We conducted a systematic review including all studies reporting on both rotational alignment and functional outcome. Comparable studies were used in a correlation analysis and results of revision were analyzed separately. Results 846 studies were identified, 25 of which met the inclusion criteria. From this selection, 11 studies could be included in the correlation analysis. A medium positive correlation (ρ = 0.44, 95% CI: 0.27–0.59) and a large positive correlation (ρ = 0.68, 95% CI: 0.64–0.73) were found between external rotation of the tibial component and the femoral component, respectively, and the Knee Society score. Revision for malrotation gave positive results in all 6 studies in this field. Interpretation Medium and large positive correlations were found between tibial and femoral component rotational alignment on the one hand and better functional outcome on the other. Revision of malrotated total knee arthroplasty may be successful. However, a clear cutoff point for revision for malrotated total knee arthroplasty components could not be identified. PMID:25708694

An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection.

PubMed

Antharam, Vijay C; McEwen, Daniel C; Garrett, Timothy J; Dossey, Aaron T; Li, Eric C; Kozlov, Andrew N; Mesbah, Zhubene; Wang, Gary P

2016-01-01

Clostridium difficile infection (CDI) is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS) and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7) and healthy controls (n = 6). From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs) determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA), 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism.

Comprehensive methylome analysis of ovarian tumors reveals hedgehog signaling pathway regulators as prognostic DNA methylation biomarkers.

PubMed

Huang, Rui-Lan; Gu, Fei; Kirma, Nameer B; Ruan, Jianhua; Chen, Chun-Liang; Wang, Hui-Chen; Liao, Yu-Ping; Chang, Cheng-Chang; Yu, Mu-Hsien; Pilrose, Jay M; Thompson, Ian M; Huang, Hsuan-Cheng; Huang, Tim Hui-Ming; Lai, Hung-Cheng; Nephew, Kenneth P

2013-06-01

Women with advanced stage ovarian cancer (OC) have a five-year survival rate of less than 25%. OC progression is associated with accumulation of epigenetic alterations and aberrant DNA methylation in gene promoters acts as an inactivating "hit" during OC initiation and progression. Abnormal DNA methylation in OC has been used to predict disease outcome and therapy response. To globally examine DNA methylation in OC, we used next-generation sequencing technology, MethylCap-sequencing, to screen 75 malignant and 26 normal or benign ovarian tissues. Differential DNA methylation regions (DMRs) were identified, and the Kaplan-Meier method and Cox proportional hazard model were used to correlate methylation with clinical endpoints. Functional role of specific genes identified by MethylCap-sequencing was examined in in vitro assays. We identified 577 DMRs that distinguished (p < 0.001) malignant from non-malignant ovarian tissues; of these, 63 DMRs correlated (p < 0.001) with poor progression free survival (PFS). Concordant hypermethylation and corresponding gene silencing of sonic hedgehog pathway members ZIC1 and ZIC4 in OC tumors was confirmed in a panel of OC cell lines, and ZIC1 and ZIC4 repression correlated with increased proliferation, migration and invasion. ZIC1 promoter hypermethylation correlated (p < 0.01) with poor PFS. In summary, we identified functional DNA methylation biomarkers significantly associated with clinical outcome in OC and suggest our comprehensive methylome analysis has significant translational potential for guiding the design of future clinical investigations targeting the OC epigenome. Methylation of ZIC1, a putative tumor suppressor, may be a novel determinant of OC outcome.

Comparative genome analysis of a large Dutch Legionella pneumophila strain collection identifies five markers highly correlated with clinical strains

PubMed Central

2010-01-01

Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115

Functional brain networks associated with eating behaviors in obesity.

PubMed

Park, Bo-Yong; Seo, Jongbum; Park, Hyunjin

2016-03-31

Obesity causes critical health problems including diabetes and hypertension that affect billions of people worldwide. Obesity and eating behaviors are believed to be closely linked but their relationship through brain networks has not been fully explored. We identified functional brain networks associated with obesity and examined how the networks were related to eating behaviors. Resting state functional magnetic resonance imaging (MRI) scans were obtained for 82 participants. Data were from an equal number of people of healthy weight (HW) and non-healthy weight (non-HW). Connectivity matrices were computed with spatial maps derived using a group independent component analysis approach. Brain networks and associated connectivity parameters with significant group-wise differences were identified and correlated with scores on a three-factor eating questionnaire (TFEQ) describing restraint, disinhibition, and hunger eating behaviors. Frontoparietal and cerebellum networks showed group-wise differences between HW and non-HW groups. Frontoparietal network showed a high correlation with TFEQ disinhibition scores. Both frontoparietal and cerebellum networks showed a high correlation with body mass index (BMI) scores. Brain networks with significant group-wise differences between HW and non-HW groups were identified. Parts of the identified networks showed a high correlation with eating behavior scores.

A novel approach to identify genes that determine grain protein deviation in cereals.

PubMed

Mosleth, Ellen F; Wan, Yongfang; Lysenko, Artem; Chope, Gemma A; Penson, Simon P; Shewry, Peter R; Hawkesford, Malcolm J

2015-06-01

Grain yield and protein content were determined for six wheat cultivars grown over 3 years at multiple sites and at multiple nitrogen (N) fertilizer inputs. Although grain protein content was negatively correlated with yield, some grain samples had higher protein contents than expected based on their yields, a trait referred to as grain protein deviation (GPD). We used novel statistical approaches to identify gene transcripts significantly related to GPD across environments. The yield and protein content were initially adjusted for nitrogen fertilizer inputs and then adjusted for yield (to remove the negative correlation with protein content), resulting in a parameter termed corrected GPD. Significant genetic variation in corrected GPD was observed for six cultivars grown over a range of environmental conditions (a total of 584 samples). Gene transcript profiles were determined in a subset of 161 samples of developing grain to identify transcripts contributing to GPD. Principal component analysis (PCA), analysis of variance (ANOVA) and means of scores regression (MSR) were used to identify individual principal components (PCs) correlating with GPD alone. Scores of the selected PCs, which were significantly related to GPD and protein content but not to the yield and significantly affected by cultivar, were identified as reflecting a multivariate pattern of gene expression related to genetic variation in GPD. Transcripts with consistent variation along the selected PCs were identified by an approach hereby called one-block means of scores regression (one-block MSR). © 2014 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Analysis of Vibration and Noise of Construction Machinery Based on Ensemble Empirical Mode Decomposition and Spectral Correlation Analysis Method

NASA Astrophysics Data System (ADS)

Chen, Yuebiao; Zhou, Yiqi; Yu, Gang; Lu, Dan

In order to analyze the effect of engine vibration on cab noise of construction machinery in multi-frequency bands, a new method based on ensemble empirical mode decomposition (EEMD) and spectral correlation analysis is proposed. Firstly, the intrinsic mode functions (IMFs) of vibration and noise signals were obtained by EEMD method, and then the IMFs which have the same frequency bands were selected. Secondly, we calculated the spectral correlation coefficients between the selected IMFs, getting the main frequency bands in which engine vibration has significant impact on cab noise. Thirdly, the dominated frequencies were picked out and analyzed by spectral analysis method. The study result shows that the main frequency bands and dominated frequencies in which engine vibration have serious impact on cab noise can be identified effectively by the proposed method, which provides effective guidance to noise reduction of construction machinery.

Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis

PubMed Central

Liu, Fang; Shen, Changqing; He, Qingbo; Zhang, Ao; Liu, Yongbin; Kong, Fanrang

2014-01-01

A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the transient modeling analysis method based on correlation filtering analysis, a so-called Parametric-Mother-Doppler-Wavelet (PMDW) is constructed with six parameters, including a center characteristic frequency and five kinematic model parameters. A Doppler effect eliminator containing a PMDW generator, a correlation filtering analysis module, and a signal resampler is invented to eliminate the Doppler effect embedded in the acoustic signal of the recorded bearing. Through the Doppler effect eliminator, the five kinematic model parameters can be identified based on the signal itself. Then, the signal resampler is applied to eliminate the Doppler effect using the identified parameters. With the ability to detect early bearing faults, the transient model analysis method is employed to detect localized bearing faults after the embedded Doppler effect is eliminated. The effectiveness of the proposed fault diagnosis strategy is verified via simulation studies and applications to diagnose locomotive roller bearing defects. PMID:24803197

Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

PubMed

Feng, Yinling; Wang, Xuefeng

2017-03-01

In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

Data Visualization of Item-Total Correlation by Median Smoothing

ERIC Educational Resources Information Center

Yu, Chong Ho; Douglas, Samantha; Lee, Anna; An, Min

2016-01-01

This paper aims to illustrate how data visualization could be utilized to identify errors prior to modeling, using an example with multi-dimensional item response theory (MIRT). MIRT combines item response theory and factor analysis to identify a psychometric model that investigates two or more latent traits. While it may seem convenient to…

Statistical Analysis of Big Data on Pharmacogenomics

PubMed Central

Fan, Jianqing; Liu, Han

2013-01-01

This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Model-driven meta-analyses for informing health care: a diabetes meta-analysis as an exemplar.

PubMed

Brown, Sharon A; Becker, Betsy Jane; García, Alexandra A; Brown, Adama; Ramírez, Gilbert

2015-04-01

A relatively novel type of meta-analysis, a model-driven meta-analysis, involves the quantitative synthesis of descriptive, correlational data and is useful for identifying key predictors of health outcomes and informing clinical guidelines. Few such meta-analyses have been conducted and thus, large bodies of research remain unsynthesized and uninterpreted for application in health care. We describe the unique challenges of conducting a model-driven meta-analysis, focusing primarily on issues related to locating a sample of published and unpublished primary studies, extracting and verifying descriptive and correlational data, and conducting analyses. A current meta-analysis of the research on predictors of key health outcomes in diabetes is used to illustrate our main points. © The Author(s) 2014.

MODEL-DRIVEN META-ANALYSES FOR INFORMING HEALTH CARE: A DIABETES META-ANALYSIS AS AN EXEMPLAR

PubMed Central

Brown, Sharon A.; Becker, Betsy Jane; García, Alexandra A.; Brown, Adama; Ramírez, Gilbert

2015-01-01

A relatively novel type of meta-analysis, a model-driven meta-analysis, involves the quantitative synthesis of descriptive, correlational data and is useful for identifying key predictors of health outcomes and informing clinical guidelines. Few such meta-analyses have been conducted and thus, large bodies of research remain unsynthesized and uninterpreted for application in health care. We describe the unique challenges of conducting a model-driven meta-analysis, focusing primarily on issues related to locating a sample of published and unpublished primary studies, extracting and verifying descriptive and correlational data, and conducting analyses. A current meta-analysis of the research on predictors of key health outcomes in diabetes is used to illustrate our main points. PMID:25142707

The Expression of Inflammatory Mediators in Bladder Pain Syndrome.

PubMed

Offiah, Ifeoma; Didangelos, Athanasios; Dawes, John; Cartwright, Rufus; Khullar, Vik; Bradbury, Elizabeth J; O'Sullivan, Suzanne; Williams, Dic; Chessell, Iain P; Pallas, Kenny; Graham, Gerry; O'Reilly, Barry A; McMahon, Stephen B

2016-08-01

Bladder pain syndrome (BPS) pathology is poorly understood. Treatment strategies are empirical, with limited efficacy, and affected patients have diminished quality of life. We examined the hypothesis that inflammatory mediators within the bladder contribute to BPS pathology. Fifteen women with BPS and 15 women with stress urinary incontinence without bladder pain were recruited from Cork University Maternity Hospital from October 2011 to October 2012. During cystoscopy, 5-mm bladder biopsies were taken and processed for gene expression analysis. The effect of the identified genes was tested in laboratory animals. We studied the expression of 96 inflammation-related genes in diseased and healthy bladders. We measured the correlation between genes and patient clinical profiles using the Pearson correlation coefficient. Analysis revealed 15 differentially expressed genes, confirmed in a replication study. FGF7 and CCL21 correlated significantly with clinical outcomes. Intravesical CCL21 instillation in rats caused increased bladder excitability and increased c-fos activity in spinal cord neurons. CCL21 atypical receptor knockout mice showed significantly more c-fos upon bladder stimulation with CCL21 than wild-type littermates. There was no change in FGF7-treated animals. The variability in patient samples presented as the main limitation. We used principal component analysis to identify similarities within the patient group. Our study identified two biologically relevant inflammatory mediators in BPS and demonstrated an increase in nociceptive signalling with CCL21. Manipulation of this ligand is a potential new therapeutic strategy for BPS. We compared gene expression in bladder biopsies of patients with bladder pain syndrome (BPS) and controls without pain and identified two genes that were increased in BPS patients and correlated with clinical profiles. We tested the effect of these genes in laboratory animals, confirming their role in bladder pain. Manipulating these genes in BPS is a potential treatment strategy. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes.

PubMed

Pillai, S G; Tang, Y; van den Oord, E; Klotsman, M; Barnes, K; Carlsen, K; Gerritsen, J; Lenney, W; Silverman, M; Sly, P; Sundy, J; Tsanakas, J; von Berg, A; Whyte, M; Ortega, H G; Anderson, W H; Helms, P J

2008-03-01

Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the contribution of genes and environments to disease expression. To determine the minimum number of sets of features required to characterize subjects with asthma which will be useful in identifying important genetic and environmental contributors. Methods Probands aged 7-35 years with physician diagnosed asthma and symptomatic siblings were identified in 1022 nuclear families from 11 centres in six countries forming the Genetics of Asthma International Network. Factor analysis was used to identify distinct phenotypes from questionnaire, clinical, and laboratory data, including baseline pulmonary function, allergen skin prick test (SPT). Five distinct factors were identified:(1) baseline pulmonary function measures [forced expiratory volume in 1 s (FEV(1)) and forced vital capacity (FVC)], (2) specific allergen sensitization by SPT, (3) self-reported allergies, (4) symptoms characteristic of rhinitis and (5) symptoms characteristic of asthma. Replication in symptomatic siblings was consistent with shared genetic and/or environmental effects, and was robust across age groups, gender, and centres. Cronbach's alpha ranged from 0.719 to 0.983 suggesting acceptable internal scale consistencies. Derived scales were correlated with serum IgE, methacholine PC(20), age and asthma severity (interrupted sleep). IgE correlated with all three atopy-related factors, the strongest with the SPT factor whereas severity only correlated with baseline lung function, and with symptoms characteristic of rhinitis and of asthma. In children and adolescents with established asthma, five distinct sets of correlated patient characteristics appear to represent important aspects of the disease. Factor scores as quantitative traits may be better phenotypes in epidemiological and genetic analyses than those categories derived from the presence or absence of combinations of +ve SPTs and/or elevated IgE.

Analysis of Factors Influencing Creative Personality of Elementary School Students

ERIC Educational Resources Information Center

Park, Jongman; Kim, Minkee; Jang, Shinho

2017-01-01

This quantitative research examined factors that affect elementary students' creativity and how those factors correlate. Aiming to identify significant factors that affect creativity and to clarify the relationship between these factors by path analysis, this research was designed to be a stepping stone for creativity enhancement studies. Data…

Mathematical Creativity and Mathematical Aptitude: A Cross-Lagged Panel Analysis

ERIC Educational Resources Information Center

Tyagi, Tarun Kumar

2016-01-01

Cross-lagged panel correlation (CLPC) analysis has been used to identify causal relationships between mathematical creativity and mathematical aptitude. For this study, 480 8th standard students were selected through a random cluster technique from 9 intermediate and high schools of Varanasi, India. Mathematical creativity and mathematical…

Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study

PubMed Central

Brawanski, Alexander

2017-01-01

Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data. PMID:28255331

Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study.

PubMed

Proescholdt, Martin A; Faltermeier, Rupert; Bele, Sylvia; Brawanski, Alexander

2017-01-01

Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.

The online social self: an open vocabulary approach to personality.

PubMed

Kern, Margaret L; Eichstaedt, Johannes C; Schwartz, H Andrew; Dziurzynski, Lukasz; Ungar, Lyle H; Stillwell, David J; Kosinski, Michal; Ramones, Stephanie M; Seligman, Martin E P

2014-04-01

We present a new open language analysis approach that identifies and visually summarizes the dominant naturally occurring words and phrases that most distinguished each Big Five personality trait. Using millions of posts from 69,792 Facebook users, we examined the correlation of personality traits with online word usage. Our analysis method consists of feature extraction, correlational analysis, and visualization. The distinguishing words and phrases were face valid and provide insight into processes that underlie the Big Five traits. Open-ended data driven exploration of large datasets combined with established psychological theory and measures offers new tools to further understand the human psyche. © The Author(s) 2013.

Relative validity of a food frequency questionnaire to identify dietary patterns in an adult Mexican population.

PubMed

Denova-Gutiérrez, Edgar; Tucker, Katherine L; Salmerón, Jorge; Flores, Mario; Barquera, Simón

2016-01-01

To examine the validity of a semi-quantitative food frequency questionnaire (SFFQ) to identify dietary patterns in an adult Mexican population. A 140-item SFFQ and two 24-hour dietary recalls (24DRs) were administered. Foods were categorized into 29 food groups used to derive dietary patterns via factor analysis. Pearson and intraclass correlations coefficients between dietary pattern scores identified from the SFFQ and 24DRs were assessed. Pattern 1 was high in snacks, fast food, soft drinks, processed meats and refined grains; pattern 2 was high in fresh vegetables, fresh fruits, and dairy products; and pattern 3 was high in legumes, eggs, sweetened foods and sugars. Pearson correlation coefficients between the SFFQ and the 24DRs for these patterns were 0.66 (P<0.001), 0.41 (P<0.001) and 0.29 (P=0.193) respectively. Our data indicate reasonable validity of the SFFQ, using factor analysis, to derive major dietary patterns in comparison with two 24DR.

Cluster analysis reveals subclinical subgroups with shared autistic and schizotypal traits.

PubMed

Ford, Talitha C; Apputhurai, Pragalathan; Meyer, Denny; Crewther, David P

2018-07-01

Autism and schizophrenia spectrum research is typically based on coarse diagnostic classification, which overlooks individual variation within clinical groups. This method limits the identification of underlying cognitive, genetic and neural correlates of specific symptom dimensions. This study, therefore, aimed to identify homogenous subclinical subgroups of specific autistic and schizotypal traits dimensions, that may be utilised to establish more effective diagnostic and treatment practices. Latent profile analysis of subscale scores derived from an autism-schizotypy questionnaire, completed by 1678 subclinical adults aged 18-40 years (1250 females), identified a local optimum of eight population clusters: High, Moderate and Low Psychosocial Difficulties; High, Moderate and Low Autism-Schizotypy; High Psychosis-Proneness; and Moderate Schizotypy. These subgroups represent the convergent and discriminant dimensions of autism and schizotypy in the subclinical population, and highlight the importance of examining subgroups of specific symptom characteristics across these spectra in order to identify the underlying genetic and neural correlates that can be utilised to advance diagnostic and treatment practices. Copyright © 2018 Elsevier B.V. All rights reserved.

Statistical properties of correlated solar flares and coronal mass ejections in cycles 23 and 24

NASA Astrophysics Data System (ADS)

Aarnio, Alicia

2018-01-01

Outstanding problems in understanding early stellar systems include mass loss, angular momentum evolution, and the effects of energetic events on the surrounding environs. The latter of these drives much research into our own system's space weather and the development of predictive algorithms for geomagnetic storms. So dually motivated, we have leveraged a big-data approach to combine two decades of GOES and LASCO data to identify a large sample of spatially and temporally correlated solar flares and CMEs. In this presentation, we revisit the analysis of Aarnio et al. (2011), adding 10 years of data and further exploring the relationships between correlated flare and CME properties. We compare the updated data set results to those previously obtained, and discuss the effects of selecting smaller time windows within solar cycles 23 and 24 on the empirically defined relationships between correlated flare and CME properties. Finally, we discuss a newly identified large sample of potentially interesting correlated flares and CMEs perhaps erroneously excluded from previous searches.

Identification of ageing-associated naturally occurring peptides in human urine

PubMed Central

Nkuipou-Kenfack, Esther; Bhat, Akshay; Klein, Julie; Jankowski, Vera; Mullen, William; Vlahou, Antonia; Dakna, Mohammed; Koeck, Thomas; Schanstra, Joost P.; Zürbig, Petra; Rudolph, Karl L.; Schumacher, Björn; Pich, Andreas; Mischak, Harald

2015-01-01

To assess normal and pathological peptidomic changes that may lead to an improved understanding of molecular mechanisms underlying ageing, urinary peptidomes of 1227 healthy and 10333 diseased individuals between 20 and 86 years of age were investigated. The diseases thereby comprised diabetes mellitus, renal and cardiovascular diseases. Using age as a continuous variable, 116 peptides were identified that significantly (p < 0.05; |ρ|≥0.2) correlated with age in the healthy cohort. The same approach was applied to the diseased cohort. Upon comparison of the peptide patterns of the two cohorts 112 common age-correlated peptides were identified. These 112 peptides predominantly originated from collagen, uromodulin and fibrinogen. While most fibrillar and basement membrane collagen fragments showed a decreased age-related excretion, uromodulin, beta-2-microglobulin and fibrinogen fragments showed an increase. Peptide-based in silico protease analysis was performed and 32 proteases, including matrix metalloproteinases and cathepsins, were predicted to be involved in ageing. Identified peptides, predicted proteases and patient information were combined in a systems biology pathway analysis to identify molecular pathways associated with normal and/or pathological ageing. While perturbations in collagen homeostasis, trafficking of toll-like receptors and endosomal pathways were commonly identified, degradation of insulin-like growth factor-binding proteins was uniquely identified in pathological ageing. PMID:26431327

An evaluation of a computer code based on linear acoustic theory for predicting helicopter main rotor noise

NASA Astrophysics Data System (ADS)

Davis, S. J.; Egolf, T. A.

1980-07-01

Acoustic characteristics predicted using a recently developed computer code were correlated with measured acoustic data for two helicopter rotors. The analysis, is based on a solution of the Ffowcs-Williams-Hawkings (FW-H) equation and includes terms accounting for both the thickness and loading components of the rotational noise. Computations are carried out in the time domain and assume free field conditions. Results of the correlation show that the Farrassat/Nystrom analysis, when using predicted airload data as input, yields fair but encouraging correlation for the first 6 harmonics of blade passage. It also suggests that although the analysis represents a valuable first step towards developing a truly comprehensive helicopter rotor noise prediction capability, further work remains to be done identifying and incorporating additional noise mechanisms into the code.

Assessment of impacts of climate change on gender in the context of Nepal

NASA Astrophysics Data System (ADS)

Paudel, R.; Acharya, A.

2016-12-01

Climate change and its impact on gender in the context of Nepal has not been clearly understood due to lack of proper scientific research in terms of gender and climate change. Climate induced disasters such as droughts, floods, GLOFs, and landslides affect men and women differently. This study is conducted to analyze the scenario of gender equality, and impacts of climate change on gender in Nepal. This study also identifies gender based adaptation approaches through the use of observed climate data, and projected and modeled demographic data such as Adolescent Fertility Rate, Labor Force Participation Rate, and Maternal Mortality Ratio. The major tasks of this project include the calculation of Gender Inequality Index (GII), trend analysis and correlation between GII and temperature, that helps to evaluate the women vulnerability and identify the gender based adaptation interventions in Nepal. The required data on gender and temperature are obtained from World Bank and Department of Hydrology and Meteorology, Nepal. GII is calculated for almost 26 years starting from the year 1990 by utilizing a tool "Calculating the Indices using Excel" provided through the UNDP. The Reproductive Health Index (RHI), Empowerment Index (EI), and Labor Market Index (LMI) that are required to determine GII are also calculated through the use of same tool. The trend analysis shows that GII follows a decreasing trend indicating higher gender equality. The correlation analysis shows the temperature positively correlated with RHI (r=0.64), EI Female (r=0.61), and EI Male (r=0.73). In case of LMI, temperature is positively correlated with female (r=0.14) and negatively correlated with male (r=-0.57). The analysis depicts negative correlation (r=-0.68) between climate change and GII. This research will provide some valuable insights in the research relating to gender and climate change that could help gender advocates and policymakers in developing further plans for women empowerment.

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

Association between Low-density lipoprotein cholesterol and occipital periventricular hyperintensities in a group of Chinese patients: an observational study.

PubMed

Duan, Dazhi; Shen, Lin; Cui, Chun; Shu, Tongsheng; Zheng, Jian

2017-02-27

While occipital periventricular hyperintensities (OPVHs) are among the most common mild white matter hyperintensities, the clinical factors associated with OPVHs remain unclear. In this study, we investigated the role of clinical factors in development of pure OPVHs. This study included 97 patients with OPVHs and 73 healthy controls. Univariate analysis of clinical factors in OPVH patients and controls was followed by binomial logistic regression analysis to identify clinical factors significantly associated with OPVHs. Univariate analysis indicated that age, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein-B (Apo-B) levels differed significantly between the OPVH patients and controls (p < 0.05). Age and gender were correlated with OPVH scores (p < 0.05), while LDL-C, triglycerides, Apo-B and TC were anti-correlated with OPVHs scores (p < 0.05). Multivariate analysis indicated that LDL-C is negatively correlated with OPVHs (p < 0.05), and age is positively correlated with OPVHs (p < 0.001). In summary, LDL-C was negatively and age was positively associated with OPVHs among Chinese patients in a hospital.

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-05-04

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADC min , ADC median , ADC mode , P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADC mean , ADC min , ADC median , and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADC mean , ADC min , ADC median , P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading.

Whole lesion histogram analysis of meningiomas derived from ADC values. Correlation with several cellularity parameters, proliferation index KI 67, nucleic content, and membrane permeability.

PubMed

Surov, Alexey; Hamerla, Gordian; Meyer, Hans Jonas; Winter, Karsten; Schob, Stefan; Fiedler, Eckhard

2018-09-01

To analyze several histopathological features and their possible correlations with whole lesion histogram analysis derived from ADC maps in meningioma. The retrospective study involved 36 patients with primary meningiomas. For every tumor, the following histogram analysis parameters of apparent diffusion coefficient (ADC) were calculated: ADC mean , ADC max , ADC min , ADC median , ADC mode , ADC percentiles: P10, P25, P75, P90, as well kurtosis, skewness, and entropy. All measures were performed by two radiologists. Proliferation index KI 67, minimal, maximal and mean cell count, total nucleic area, and expression of water channel aquaporin 4 (AQP4) were estimated. Spearman's correlation coefficient was used to analyze associations between investigated parameters. A perfect interobserver agreement for all ADC values (0.84-0.97) was identified. All ADC values correlated inversely with tumor cellularity with the strongest correlation between P10, P25 and mean cell count (-0.558). KI 67 correlated inversely with all ADC values except ADC min . ADC parameters did not correlate with total nucleic area. All ADC values correlated statistically significant with expression of AQP4. ADC histogram analysis is a valid method with an excellent interobserver agreement. Cellularity parameters and proliferation potential are associated with different ADC values. Membrane permeability may play a greater role for water diffusion than cell count and proliferation activity. Copyright © 2018 Elsevier Inc. All rights reserved.

Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

2017-07-15

This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

Water conservation study. Badger Army Ammunition Plant, Baraboo, Wisconsin. Final report

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

NONE

1995-05-01

The purpose of this water conservation study is to identify projects which result in energy maintenance and cost savings in the process water distribution system at Badger Army Ammunition Plant (BAAP) in Baraboo, Wisconsin. A leak detection survey was performed on all process water piping with a diameter of 6 inches or greater. The leak detection analysis was performed using a combination of listening devices and preamplified-transducer systems to identify the majority of leak locations. When the location of the leak could not be readily identified using these methods, a leak correlator was used. The leak correlator determines leak locationmore » based on the time it takes for sound to travel from the leak to a waterline connection point.« less

Coupling detrended fluctuation analysis of Asian stock markets

NASA Astrophysics Data System (ADS)

Wang, Qizhen; Zhu, Yingming; Yang, Liansheng; Mul, Remco A. H.

2017-04-01

This paper uses the coupling detrended fluctuation analysis (CDFA) method to investigate the multifractal characteristics of four Asian stock markets using three stock indices: stock price returns, trading volumes and the composite index. The results show that coupled correlations exist among the four stock markets and the coupled correlations have multifractal characteristics. We then use the chi square (χ2) test to identify the sources of multifractality. For the different stock indices, the contributions of a single series to multifractality are different. In other words, the contributions of each country to coupled correlations are different. The comparative analysis shows that the research on the combine effect of stock price returns and trading volumes may be more comprehensive than on an individual index. By comparing the strength of multifractality for original data with the residual errors of the vector autoregression (VAR) model, we find that the VAR model could not be used to describe the dynamics of the coupled correlations among four financial time series.

Biomechanical Factors Associated With Jump Height: A Comparison of Cross-Sectional and Pre-to-Posttraining Change Findings.

PubMed

Marshall, Brendan M; Moran, Kieran A

2015-12-01

Previous studies investigating the biomechanical factors associated with maximal countermovement jump height have typically used cross-sectional data. An alternative but less common approach is to use pre-to-posttraining change data, where the relationship between an improvement in jump height and a change in a factor is examined more directly. Our study compared the findings of these approaches. Such an evaluation is necessary because cross-sectional studies are currently a primary source of information for coaches when examining what factors to train to enhance performance. The countermovement jump of 44 males was analyzed before and after an 8-week training intervention. Correlations with jump height were calculated using both cross-sectional (pretraining data only) and pre-to-posttraining change data. Eight factors identified in the cross-sectional analysis were not significantly correlated with a change in jump height in the pre-to-post analysis. Additionally, only 6 of 11 factors identified in the pre-to-post analysis were identified in the cross-sectional analysis. These findings imply that (a) not all factors identified in a cross-sectional analysis may be critical to jump height improvement and (b) cross-sectional analyses alone may not provide an insight into all of the potential factors to train to enhance jump height. Coaches must be aware of these limitations when examining cross-sectional studies to identify factors to train to enhance jump ability. Additional findings highlight that although exercises prescribed to improve jump height should aim to enhance concentric power production at all joints, a particular emphasis on enhancing hip joint peak power may be warranted.

HPLC-MS and GC-MS analyses combined with orthogonal partial least squares to identify cytotoxic constituents from turmeric (Curcuma longa L.).

PubMed

Jiang, Jianlan; Zhang, Huan; Li, Zidan; Zhang, Xiaohang; Su, Xin; Li, Yan; Qiao, Bin; Yuan, Yingjin

2013-08-01

We investigated the fingerprints of 48 batches of turmeric total extracts (TTE) by HPLC-MS-MS and GC-MS analyses and 43 characteristic peaks (22 constituents from HPLC-MS-MS; 21 from GC-MS) were analyzed qualitatively and quantitatively. An MTT {3-(4,5-dimethylthiazol-2-yl)- 2,5-diphenyltetrazolium bromide} assay was implemented to measure the cytotoxicity of the TTE against HeLa cells. Then we utilized orthogonal partial least squares analysis, which correlated the chemical composition of the TTE to its cytotoxic activity, to identify potential cytotoxic constituents from turmeric. The result showed that 19 constituents contributed significantly to the cytotoxicity. The obtained result was verified by canonical correlation analysis. Comparison with previous reports also indicated some interaction between the curcuminoids and sesquiterpenoids in turmeric.

Sphingolipids as New Biomarkers for Assessment of Delayed-Type Hypersensitivity and Response to Triptolide

PubMed Central

Qu, Feng; Wu, Cai-Sheng; Hou, Jin-Feng; Jin, Ying; Zhang, Jin-Lan

2012-01-01

Background Hypersensitivity diseases are associated with many severe human illnesses, including leprosy and tuberculosis. Emerging evidence suggests that the pathogenesis and pathological mechanisms of treating these diseases may be attributable to sphingolipid metabolism. Methods High performance liquid chromatography-tandem mass spectrometry was employed to target and measure 43 core sphingolipids in the plasma, kidneys, livers and spleens of BALB/c mice from four experimental groups: control, delayed-type hypersensitivity (DTH) model, DTH+triptolide, and control+triptolide. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to identify potential biomarkers associated with variance between groups. Relationships between the identified biomarkers and disease markers were evaluated by Spearman correlation. Results As a treatment to hypersensitivity disease, triptolide significantly inhibit the ear swelling and recover the reduction of splenic index caused by DTH. The sphingolipidomic result revealed marked alterations in sphingolipid levels between groups that were associated with the effects of the disease and triptolide treatment. Based on this data, 23 potential biomarkers were identified by OPLS-DA, and seven of these biomarkers correlated markedly with the disease markers (p<0.05) by Spearman correlation. Conclusions These data indicate that differences in sphingolipid levels in plasma and tissues are related to DTH and treatment with triptolide. Restoration of proper sphingolipid levels may attribute to the therapeutic effect of triptolide treatment. Furthermore, these findings demonstrate that targeted sphingolipidomic analysis followed by multivariate analysis presents a novel strategy for the identification of biomarkers in biological samples. PMID:23300675

Identifying and Promoting Transition Evidence-Based Practices and Predictors of Success: A Position Paper of the Division on Career Development and Transition

ERIC Educational Resources Information Center

Mazzotti, Valerie L.; Rowe, Dawn A.; Cameto, Renee; Test, David W.; Morningstar, Mary E.

2013-01-01

This position paper describes the Division of Career Development and Transition's stance and recommendations for identifying and promoting secondary transition evidence-based practices and predictors of postschool success for students with disabilities. Recommendations for experimental research, correlational research, and secondary analysis of…

Parcellating an Individual Subject's Cortical and Subcortical Brain Structures Using Snowball Sampling of Resting-State Correlations

PubMed Central

Wig, Gagan S.; Laumann, Timothy O.; Cohen, Alexander L.; Power, Jonathan D.; Nelson, Steven M.; Glasser, Matthew F.; Miezin, Francis M.; Snyder, Abraham Z.; Schlaggar, Bradley L.; Petersen, Steven E.

2014-01-01

We describe methods for parcellating an individual subject's cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability—reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individual's brain into functionally meaningful units. PMID:23476025

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

PubMed Central

Riccioni, Giulia; Stagioni, Marco; Landi, Monica; Ferrara, Giorgia; Barbujani, Guido; Tinti, Fausto

2013-01-01

Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation. PMID:24260341

A systems biology approach to detect key pathways and interaction networks in gastric cancer on the basis of microarray analysis.

PubMed

Guo, Leilei; Song, Chunhua; Wang, Peng; Dai, Liping; Zhang, Jianying; Wang, Kaijuan

2015-11-01

The aim of the present study was to explore key molecular pathways contributing to gastric cancer (GC) and to construct an interaction network between significant pathways and potential biomarkers. Publicly available gene expression profiles of GSE29272 for GC, and data for the corresponding normal tissue, were downloaded from Gene Expression Omnibus. Pre‑processing and differential analysis were performed with R statistical software packages, and a number of differentially expressed genes (DEGs) were obtained. A functional enrichment analysis was performed for all the DEGs with a BiNGO plug‑in in Cytoscape. Their correlation was analyzed in order to construct a network. The modularity analysis and pathway identification operations were used to identify graph clusters and associated pathways. The underlying molecular mechanisms involving these DEGs were also assessed by data mining. A total of 249 DEGs, which were markedly upregulated and downregulated, were identified. The extracellular region contained the most significantly over‑represented functional terms, with respect to upregulated and downregulated genes, and the closest topological matches were identified for taste transduction and regulation of autophagy. In addition, extracellular matrix‑receptor interactions were identified as the most relevant pathway associated with the progression of GC. The genes for fibronectin 1, secreted phosphoprotein 1, collagen type 4 variant α‑1/2 and thrombospondin 1, which are involved in the pathways, may be considered as potential therapeutic targets for GC. A series of associations between candidate genes and key pathways were also identified for GC, and their correlation may provide novel insights into the pathogenesis of GC.

Proteomic analysis of early-stage embryos: implications for egg quality in hapuku (Polyprion oxygeneios).

PubMed

Kohn, Yair Y; Symonds, Jane E; Kleffmann, Torsten; Nakagawa, Shinichi; Lagisz, Malgorzata; Lokman, P Mark

2015-12-01

In order to develop biomarkers that may help predict the egg quality of captive hapuku (Polyprion oxygeneios) and provide potential avenues for its manipulation, the present study (1) sequenced the proteome of early-stage embryos using isobaric tag for relative and absolute quantification analysis, and (2) aimed to establish the predictive value of the abundance of identified proteins with regard to egg quality through regression analysis. Egg quality was determined for eight different egg batches by blastomere symmetry scores. In total, 121 proteins were identified and assigned to one of nine major groups according to their function/pathway. A mixed-effects model analysis revealed a decrease in relative protein abundance that correlated with (decreasing) egg quality in one major group (heat-shock proteins). No differences were found in the other protein groups. Linear regression analysis, performed for each identified protein separately, revealed seven proteins that showed a significant decrease in relative abundance with reduced blastomere symmetry: two correlates that have been named in other studies (vitellogenin, heat-shock protein-70) and a further five new candidate proteins (78 kDa glucose-regulated protein, elongation factor-2, GTP-binding nuclear protein Ran, iduronate 2-sulfatase and 6-phosphogluconate dehydrogenase). Notwithstanding issues associated with multiple statistical testing, we conclude that these proteins, and especially iduronate 2-sulfatase and the generic heat-shock protein group, could serve as biomarkers of egg quality in hapuku.

Sexual dimorphic floral development in dioecious plants revealed by transcriptome, phytohormone, and DNA methylation analysis in Populus tomentosa.

PubMed

Song, Yuepeng; Ma, Kaifeng; Ci, Dong; Chen, Qingqing; Tian, Jiaxing; Zhang, Deqiang

2013-12-01

Dioecious plants have evolved sex-specific floral development mechanisms. However, the precise gene expression patterns in dioecious plant flower development remain unclear. Here, we used andromonoecious poplar, an exceptional model system, to eliminate the confounding effects of genetic background of dioecious plants. Comparative transcriptome and physiological analysis allowed us to characterize sex-specific development of female and male flowers. Transcriptome analysis identified genes significantly differentially expressed between the sexes, including genes related to floral development, phytohormone synthesis and metabolism, and DNA methylation. Correlation analysis revealed a significant correlation between phytohormone signaling and gene expression, identifying specific phytohormone-responsive genes and their cis-regulatory elements. Two genes related to DNA methylation, METHYLTRANSFERASE1 (MET1) and DECREASED DNA METHYLATION 1 (DDM1), which are located in the sex determination region of Chromosome XIX, have differential expression between female and male flowers. A time-course analysis revealed that MET1 and DDM1 expression may produce different DNA methylation levels in female and male flowers. Understanding the interactions of phytohormone signaling, DNA methylation and target gene expression should lead to a better understanding of sexual differences in floral development. Thus, this study identifies a set of candidate genes for further studies of poplar sexual dimorphism and relates sex-specific floral development to physiological and epigenetic changes.

Haplotype analysis of the germacrene A synthase gene and association with cynaropicrin content and biological activities in Cynara cardunculus.

PubMed

Ferro, Ana Margarida; Ramos, Patrícia; Guerra, Ângela; Parreira, Paula; Brás, Teresa; Guerreiro, Olinda; Jerónimo, Eliana; Capel, Carmen; Capel, Juan; Yuste-Lisbona, Fernando J; Duarte, Maria F; Lozano, Rafael; Oliveira, M Margarida; Gonçalves, Sónia

2018-04-01

Cynara cardunculus: L. represents a natural source of terpenic compounds, with the predominant molecule being cynaropicrin. Cynaropicrin is gaining interest since it has been correlated to anti-hyperlipidaemia, antispasmodic and cytotoxicity activity against leukocyte cancer cells. The objective of this work was to screen a collection of C. cardunculus, from different origins, for new allelic variants in germacrene A synthase (GAS) gene involved in the cynaropicrin biosynthesis and correlate them with improved cynaropicrin content and biological activities. Using high-resolution melting, nine haplotypes were identified. The putative impact of the identified allelic variants in GAS protein was evaluated by bioinformatic tools and polymorphisms that putatively lead to protein conformational changes were described. Additionally, cynaropicrin and main pentacyclic triterpenes contents, and antithrombin, antimicrobial and antiproliferative activities were also determined in C. cardunculus leaf lipophilic-derived extracts. In this work we identified allelic variants with putative impact on GAS protein, which are significantly associated with cynaropicrin content and antiproliferative activity. The results obtained suggest that the identified polymorphisms should be explored as putative genetic markers correlated with biological properties in Cynara cardunculus.

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia.

PubMed

Langen, Carolyn D; White, Tonya; Ikram, M Arfan; Vernooij, Meike W; Niessen, Wiro J

2015-01-01

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.

Gene and Metabolite Regulatory Network Analysis of Early Developing Fruit Tissues Highlights New Candidate Genes for the Control of Tomato Fruit Composition and Development1[C][W][OA

PubMed Central

Mounet, Fabien; Moing, Annick; Garcia, Virginie; Petit, Johann; Maucourt, Michael; Deborde, Catherine; Bernillon, Stéphane; Le Gall, Gwénaëlle; Colquhoun, Ian; Defernez, Marianne; Giraudel, Jean-Luc; Rolin, Dominique; Rothan, Christophe; Lemaire-Chamley, Martine

2009-01-01

Variations in early fruit development and composition may have major impacts on the taste and the overall quality of ripe tomato (Solanum lycopersicum) fruit. To get insights into the networks involved in these coordinated processes and to identify key regulatory genes, we explored the transcriptional and metabolic changes in expanding tomato fruit tissues using multivariate analysis and gene-metabolite correlation networks. To this end, we demonstrated and took advantage of the existence of clear structural and compositional differences between expanding mesocarp and locular tissue during fruit development (12–35 d postanthesis). Transcriptome and metabolome analyses were carried out with tomato microarrays and analytical methods including proton nuclear magnetic resonance and liquid chromatography-mass spectrometry, respectively. Pairwise comparisons of metabolite contents and gene expression profiles detected up to 37 direct gene-metabolite correlations involving regulatory genes (e.g. the correlations between glutamine, bZIP, and MYB transcription factors). Correlation network analyses revealed the existence of major hub genes correlated with 10 or more regulatory transcripts and embedded in a large regulatory network. This approach proved to be a valuable strategy for identifying specific subsets of genes implicated in key processes of fruit development and metabolism, which are therefore potential targets for genetic improvement of tomato fruit quality. PMID:19144766

Correlation between the pattern volatiles and the overall aroma of wild edible mushrooms.

PubMed

de Pinho, P Guedes; Ribeiro, Bárbara; Gonçalves, Rui F; Baptista, Paula; Valentão, Patrícia; Seabra, Rosa M; Andrade, Paula B

2008-03-12

Volatile and semivolatile components of 11 wild edible mushrooms, Suillus bellini, Suillus luteus, Suillus granulatus, Tricholomopsis rutilans, Hygrophorus agathosmus, Amanita rubescens, Russula cyanoxantha, Boletus edulis, Tricholoma equestre, Fistulina hepatica, and Cantharellus cibarius, were determined by headspace solid-phase microextraction (HS-SPME) and by liquid extraction combined with gas chromatography-mass spectrometry (GC-MS). Fifty volatiles and nonvolatiles components were formally identified and 13 others were tentatively identified. Using sensorial analysis, the descriptors "mushroomlike", "farm-feed", "floral", "honeylike", "hay-herb", and "nutty" were obtained. A correlation between sensory descriptors and volatiles was observed by applying multivariate analysis (principal component analysis and agglomerative hierarchic cluster analysis) to the sensorial and chemical data. The studied edible mushrooms can be divided in three groups. One of them is rich in C8 derivatives, such as 3-octanol, 1-octen-3-ol, trans-2-octen-1-ol, 3-octanone, and 1-octen-3-one; another one is rich in terpenic volatile compounds; and the last one is rich in methional. The presence and contents of these compounds give a considerable contribution to the sensory characteristics of the analyzed species.

Individual, Social, and Environmental Correlates of Active Transportation Patterns in French Women.

PubMed

Perchoux, Camille; Enaux, Christophe; Oppert, Jean-Michel; Menai, Mehdi; Charreire, Hélène; Salze, Paul; Weber, Christiane; Hercberg, Serge; Feuillet, Thierry; Hess, Franck; Roda, Célina; Simon, Chantal; Nazare, Julie-Anne

2017-01-01

The objectives were (1) to define physical activity (PA) and sedentary behaviors (SB) patterns in daily life contexts (work, leisure, and transportation) in French working women from NutriNet-Santé web-cohort and (2) to identify pattern(s) of active transportation and their individual, social, and environmental correlates. 23,432 participants completed two questionnaires to evaluate PA and SB in daily life contexts and individual representations of residential neighborhood and transportation modes. Hierarchical cluster analysis was performed which identified 6 distinct movement behavior patterns: (i) active occupation, high sedentary leisure, (ii) sedentary occupation, low leisure, (iii) sedentary transportation, (iv) sedentary occupation and leisure, (v) active transportation, and (vi) active leisure. Multinomial logistic regressions were performed to identify correlates of the "active transportation" cluster. The perceived environmental characteristics positively associated with "active transportation" included "high availability of destinations around home," "presence of bicycle paths," and "low traffic." A "positive image of walking/cycling," the "individual feeling of being physically active," and a "high use of active transport modes by relatives/friends" were positively related to "active transportation," identified as a unique pattern regarding individual and environmental correlates. Identification of PA and SB context-specific patterns will help to understand movement behaviors' complexity and to design interventions to promote active transportation in specific subgroups.

[Keys to preventing accidents in children in the school context].

PubMed

Gabari Gambarte, M Inés; Sáenz Mendía, Raquel

2016-11-02

To learn about children's perception of the causes and prevention strategies involved in school accidents. The sample included 584 school children aged 8-9 years from Navarra. A mixed design was chosen by questionnaire with three open-response questions and one multiple-choice assessment. Analysis was performed in two phases: 1) qualitative development of categories and dimensions of the responses of narrative content, and 2) quantitative variables for recoding correlational analysis. 22 categories emerged, which make up three perceptual dimensions: 1) attribution of causality (5), 2) identification of mechanisms of avoidance (11), and 3) development of coping strategies (6). The correlation intra-variables portray varying degrees: on the one hand, moderate positive numbers (r>0.5) in allocating and identifying causality avoidance mechanisms and, on the other hand, high positive correlation values (r>0.7) referred to developing coping strategies. Children are able to identify accidents as a health problem. They question the multiplicity of elements involved and relate the origin and kind of accident to prevention and support mechanisms. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Estimating Cyanobacteria Community Dynamics and its Relationship with Environmental Factors

PubMed Central

Luo, Wenhuai; Chen, Huirong; Lei, Anping; Lu, Jun; Hu, Zhangli

2014-01-01

The cyanobacteria community dynamics in two eutrophic freshwater bodies (Tiegang Reservoir and Shiyan Reservoir) was studied with both a traditional microscopic counting method and a PCR-DGGE genotyping method. Results showed that cyanobacterium Phormidium tenue was the predominant species; twenty-six cyanobacteria species were identified in water samples collected from the two reservoirs, among which fourteen were identified with the morphological method and sixteen with the PCR-DGGE method. The cyanobacteria community composition analysis showed a seasonal fluctuation from July to December. The cyanobacteria population peaked in August in both reservoirs, with cell abundances of 3.78 × 108 cells L-1 and 1.92 × 108 cells L-1 in the Tiegang and Shiyan reservoirs, respectively. Canonical Correspondence Analysis (CCA) was applied to further investigate the correlation between cyanobacteria community dynamics and environmental factors. The result indicated that the cyanobacteria community dynamics was mostly correlated with pH, temperature and total nitrogen. This study demonstrated that data obtained from PCR-DGGE combined with a traditional morphological method could reflect cyanobacteria community dynamics and its correlation with environmental factors in eutrophic freshwater bodies. PMID:24448632

Genomic and Proteomic Profiling Reveals Reduced Mitochondrial Function and Disruption of the Neuromuscular Junction Driving Rat Sarcopenia

PubMed Central

Ibebunjo, Chikwendu; Chick, Joel M.; Kendall, Tracee; Eash, John K.; Li, Christine; Zhang, Yunyu; Vickers, Chad; Wu, Zhidan; Clarke, Brian A.; Shi, Jun; Cruz, Joseph; Fournier, Brigitte; Brachat, Sophie; Gutzwiller, Sabine; Ma, QiCheng; Markovits, Judit; Broome, Michelle; Steinkrauss, Michelle; Skuba, Elizabeth; Galarneau, Jean-Rene; Gygi, Steven P.

2013-01-01

Molecular mechanisms underlying sarcopenia, the age-related loss of skeletal muscle mass and function, remain unclear. To identify molecular changes that correlated best with sarcopenia and might contribute to its pathogenesis, we determined global gene expression profiles in muscles of rats aged 6, 12, 18, 21, 24, and 27 months. These rats exhibit sarcopenia beginning at 21 months. Correlation of the gene expression versus muscle mass or age changes, and functional annotation analysis identified gene signatures of sarcopenia distinct from gene signatures of aging. Specifically, mitochondrial energy metabolism (e.g., tricarboxylic acid cycle and oxidative phosphorylation) pathway genes were the most downregulated and most significantly correlated with sarcopenia. Also, perturbed were genes/pathways associated with neuromuscular junction patency (providing molecular evidence of sarcopenia-related functional denervation and neuromuscular junction remodeling), protein degradation, and inflammation. Proteomic analysis of samples at 6, 18, and 27 months confirmed the depletion of mitochondrial energy metabolism proteins and neuromuscular junction proteins. Together, these findings suggest that therapeutic approaches that simultaneously stimulate mitochondrogenesis and reduce muscle proteolysis and inflammation have potential for treating sarcopenia. PMID:23109432

Correlation of ERTS MSS data and earth coordinate systems

NASA Technical Reports Server (NTRS)

Malila, W. A. (Principal Investigator); Hieber, R. H.; Mccleer, A. P.

1973-01-01

The author has identified the following significant results. Experience has revealed a problem in the analysis and interpretation of ERTS-1 multispectral scanner (MSS) data. The problem is one of accurately correlating ERTS-1 MSS pixels with analysis areas specified on aerial photographs or topographic maps for training recognition computers and/or evaluating recognition results. It is difficult for an analyst to accurately identify which ERTS-1 pixels on a digital image display belong to specific areas and test plots, especially when they are small. A computer-aided procedure to correlate coordinates from topographic maps and/or aerial photographs with ERTS-1 data coordinates has been developed. In the procedure, a map transformation from earth coordinates to ERTS-1 scan line and point numbers is calculated using selected ground control points nad the method of least squares. The map transformation is then applied to the earth coordinates of selected areas to obtain the corresponding ERTS-1 point and line numbers. An optional provision allows moving the boundaries of the plots inward by variable distances so the selected pixels will not overlap adjacent features.

Unsupervised spatiotemporal analysis of fMRI data using graph-based visualizations of self-organizing maps.

PubMed

Katwal, Santosh B; Gore, John C; Marois, Rene; Rogers, Baxter P

2013-09-01

We present novel graph-based visualizations of self-organizing maps for unsupervised functional magnetic resonance imaging (fMRI) analysis. A self-organizing map is an artificial neural network model that transforms high-dimensional data into a low-dimensional (often a 2-D) map using unsupervised learning. However, a postprocessing scheme is necessary to correctly interpret similarity between neighboring node prototypes (feature vectors) on the output map and delineate clusters and features of interest in the data. In this paper, we used graph-based visualizations to capture fMRI data features based upon 1) the distribution of data across the receptive fields of the prototypes (density-based connectivity); and 2) temporal similarities (correlations) between the prototypes (correlation-based connectivity). We applied this approach to identify task-related brain areas in an fMRI reaction time experiment involving a visuo-manual response task, and we correlated the time-to-peak of the fMRI responses in these areas with reaction time. Visualization of self-organizing maps outperformed independent component analysis and voxelwise univariate linear regression analysis in identifying and classifying relevant brain regions. We conclude that the graph-based visualizations of self-organizing maps help in advanced visualization of cluster boundaries in fMRI data enabling the separation of regions with small differences in the timings of their brain responses.

Possible involvement of rumination in gray matter abnormalities in persistent symptoms of major depression: an exploratory magnetic resonance imaging voxel-based morphometry study.

PubMed

Machino, Akihiko; Kunisato, Yoshihiko; Matsumoto, Tomoya; Yoshimura, Shinpei; Ueda, Kazutaka; Yamawaki, Yosuke; Okada, Go; Okamoto, Yasumasa; Yamawaki, Shigeto

2014-10-01

A recent meta-analysis of many magnetic resonance imaging (MRI) studies has identified brain regions with gray matter (GM) abnormalities in patients with major depressive disorder (MDD). A few studies addressing GM abnormalities in patients with treatment-resistant depression (TRD) have yielded inconsistent results. Moreover, although TRD patients tend to exhibit ruminative thoughts, it remains unclear whether rumination is related to GM abnormalities in such patients or not. We conducted structural MRI scans and voxel-based morphometry (VBM) to identify GM differences among 29 TRD patients and 29 healthy age-matched and sex-matched controls. A response style questionnaire was used to assess the respective degrees of rumination in TRD patients. Structural correlates of rumination were examined. TRD patients showed several regions with smaller GM volume than in healthy subjects: the left dorsal anterior cingulate cortex (ACC), right ventral ACC, right superior frontal gyrus, right cerebellum (Crus I), and cerebellar vermis. GM volumes in these regions did not correlate to rumination. However, whole-brain analysis revealed that rumination was positively correlated with the GM volume in the right superior temporal gyrus in TRD patients. Structural correlates of rumination were examined only in TRD patients. Our data provide additional evidence supporting the hypothesis that TRD patients show GM abnormalities compared with healthy subjects. Furthermore, this report is the first to describe a study identifying brain regions for which the GM volume is correlated with rumination in TRD patients. These results improve our understanding of the anatomical characteristics of TRD. Copyright © 2014 Elsevier B.V. All rights reserved.

SOMBI: Bayesian identification of parameter relations in unstructured cosmological data

NASA Astrophysics Data System (ADS)

Frank, Philipp; Jasche, Jens; Enßlin, Torsten A.

2016-11-01

This work describes the implementation and application of a correlation determination method based on self organizing maps and Bayesian inference (SOMBI). SOMBI aims to automatically identify relations between different observed parameters in unstructured cosmological or astrophysical surveys by automatically identifying data clusters in high-dimensional datasets via the self organizing map neural network algorithm. Parameter relations are then revealed by means of a Bayesian inference within respective identified data clusters. Specifically such relations are assumed to be parametrized as a polynomial of unknown order. The Bayesian approach results in a posterior probability distribution function for respective polynomial coefficients. To decide which polynomial order suffices to describe correlation structures in data, we include a method for model selection, the Bayesian information criterion, to the analysis. The performance of the SOMBI algorithm is tested with mock data. As illustration we also provide applications of our method to cosmological data. In particular, we present results of a correlation analysis between galaxy and active galactic nucleus (AGN) properties provided by the SDSS catalog with the cosmic large-scale-structure (LSS). The results indicate that the combined galaxy and LSS dataset indeed is clustered into several sub-samples of data with different average properties (for example different stellar masses or web-type classifications). The majority of data clusters appear to have a similar correlation structure between galaxy properties and the LSS. In particular we revealed a positive and linear dependency between the stellar mass, the absolute magnitude and the color of a galaxy with the corresponding cosmic density field. A remaining subset of data shows inverted correlations, which might be an artifact of non-linear redshift distortions.

Predicting response to primary chemotherapy: gene expression profiling of paraffin-embedded core biopsy tissue.

PubMed

Mina, Lida; Soule, Sharon E; Badve, Sunil; Baehner, Fredrick L; Baker, Joffre; Cronin, Maureen; Watson, Drew; Liu, Mei-Lan; Sledge, George W; Shak, Steve; Miller, Kathy D

2007-06-01

Primary chemotherapy provides an ideal opportunity to correlate gene expression with response to treatment. We used paraffin-embedded core biopsies from a completed phase II trial to identify genes that correlate with response to primary chemotherapy. Patients with newly diagnosed stage II or III breast cancer were treated with sequential doxorubicin 75 mg/M2 q2 wks x 3 and docetaxel 40 mg/M2 weekly x 6; treatment order was randomly assigned. Pretreatment core biopsy samples were interrogated for genes that might correlate with pathologic complete response (pCR). In addition to the individual genes, the correlation of the Oncotype DX Recurrence Score with pCR was examined. Of 70 patients enrolled in the parent trial, core biopsies samples with sufficient RNA for gene analyses were available from 45 patients; 9 (20%) had inflammatory breast cancer (IBC). Six (14%) patients achieved a pCR. Twenty-two of the 274 candidate genes assessed correlated with pCR (p < 0.05). Genes correlating with pCR could be grouped into three large clusters: angiogenesis-related genes, proliferation related genes, and invasion-related genes. Expression of estrogen receptor (ER)-related genes and Recurrence Score did not correlate with pCR. In an exploratory analysis we compared gene expression in IBC to non-inflammatory breast cancer; twenty-four (9%) of the genes were differentially expressed (p < 0.05), 5 were upregulated and 19 were downregulated in IBC. Gene expression analysis on core biopsy samples is feasible and identifies candidate genes that correlate with pCR to primary chemotherapy. Gene expression in IBC differs significantly from noninflammatory breast cancer.

A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network

PubMed Central

RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG

2015-01-01

The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data.

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

PubMed Central

2015-01-01

Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

Correlational analysis for identifying genes whose regulation contributes to chronic neuropathic pain

PubMed Central

Persson, Anna-Karin; Gebauer, Mathias; Jordan, Suzana; Metz-Weidmann, Christiane; Schulte, Anke M; Schneider, Hans-Christoph; Ding-Pfennigdorff, Danping; Thun, Jonas; Xu, Xiao-Jun; Wiesenfeld-Hallin, Zsuzsanna; Darvasi, Ariel; Fried, Kaj; Devor, Marshall

2009-01-01

Background Nerve injury-triggered hyperexcitability in primary sensory neurons is considered a major source of chronic neuropathic pain. The hyperexcitability, in turn, is thought to be related to transcriptional switching in afferent cell somata. Analysis using expression microarrays has revealed that many genes are regulated in the dorsal root ganglion (DRG) following axotomy. But which contribute to pain phenotype versus other nerve injury-evoked processes such as nerve regeneration? Using the L5 spinal nerve ligation model of neuropathy we examined differential changes in gene expression in the L5 (and L4) DRGs in five mouse strains with contrasting susceptibility to neuropathic pain. We sought genes for which the degree of regulation correlates with strain-specific pain phenotype. Results In an initial experiment six candidate genes previously identified as important in pain physiology were selected for in situ hybridization to DRG sections. Among these, regulation of the Na+ channel α subunit Scn11a correlated with levels of spontaneous pain behavior, and regulation of the cool receptor Trpm8 correlated with heat hypersensibility. In a larger scale experiment, mRNA extracted from individual mouse DRGs was processed on Affymetrix whole-genome expression microarrays. Overall, 2552 ± 477 transcripts were significantly regulated in the axotomized L5DRG 3 days postoperatively. However, in only a small fraction of these was the degree of regulation correlated with pain behavior across strains. Very few genes in the "uninjured" L4DRG showed altered expression (24 ± 28). Conclusion Correlational analysis based on in situ hybridization provided evidence that differential regulation of Scn11a and Trpm8 contributes to across-strain variability in pain phenotype. This does not, of course, constitute evidence that the others are unrelated to pain. Correlational analysis based on microarray data yielded a larger "look-up table" of genes whose regulation likely contributes to pain variability. While this list is enriched in genes of potential importance for pain physiology, and is relatively free of the bias inherent in the candidate gene approach, additional steps are required to clarify which transcripts on the list are in fact of functional importance. PMID:19228393

Spatio-temporal interaction between absorbing aerosols and temperature: Correlation and causality based approach

NASA Astrophysics Data System (ADS)

Dave, P.; Bhushan, M.; Venkataraman, C.

2016-12-01

Indian subcontinent, in particular, the Indo-gangetic plain (IGP) has witnessed large temperature anomalies (Ratnam et al., 2016) along with high emission of absorbing aerosols (AA) (Gazala, et al., 2005). The anomalous high temperature observed over this region may bear a relationship with high AA emissions. Different studies have been conducted to understand AA and temperature relationships (Turco et al., 1983; Hansen et al., 1997, 2005; Seinfeld 2008; Ramanathan et al. 2010b; Ban-Weiss et al., 2012). It was found that when the AA was injected in the lower- mid troposphere the surface air temperature increases while injection of AA at higher troposphere-lower stratosphere surface temperature decreases. These studies used simulation based results to establish link between AA and temperature (Hansen et al., 1997, 2005; Ban-Weiss et al., 2012). The current work focuses on identifying the causal influence of AA on temperature using observational and re-analysis data over Indian subcontinent using cross correlation (CCs) and Granger causality (GC) (Granger, 1969). Aerosol index (AI) from TOMS-OMI was used as index for AA while ERA-interim reanalysis data was used for temperature at varying altitude. Period of study was March-April-May-June (MAMJ) for years 1979-2015. CCs were calculated for all the atmospheric layers. In each layer nearby and distant pixels (>500 kms) with high CCs were identified using clustering technique. It was found that that AI and Temperature shows statistically significant cross-correlations for co-located and distant pixels and more prominently over IGP. The CCs fades away with higher altitudes. CCs analysis was followed by GC analysis to identify the lag over which AI can influence the Temperature. GC also supported the findings of CCs analysis. It is an early attempt to link persisting large temperature anomalies with absorbing aerosols and may help in identifying the role of absorbing aerosol in causing heat waves.

Correlative and multivariate analysis of increased radon concentration in underground laboratory.

PubMed

Maletić, Dimitrije M; Udovičić, Vladimir I; Banjanac, Radomir M; Joković, Dejan R; Dragić, Aleksandar L; Veselinović, Nikola B; Filipović, Jelena

2014-11-01

The results of analysis using correlative and multivariate methods, as developed for data analysis in high-energy physics and implemented in the Toolkit for Multivariate Analysis software package, of the relations of the variation of increased radon concentration with climate variables in shallow underground laboratory is presented. Multivariate regression analysis identified a number of multivariate methods which can give a good evaluation of increased radon concentrations based on climate variables. The use of the multivariate regression methods will enable the investigation of the relations of specific climate variable with increased radon concentrations by analysis of regression methods resulting in 'mapped' underlying functional behaviour of radon concentrations depending on a wide spectrum of climate variables. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Long-Term RST Analysis of Anomalous TIR Sequences in Relation with Earthquakes Occurred in Greece in the Period 2004-2013

NASA Astrophysics Data System (ADS)

Eleftheriou, Alexander; Filizzola, Carolina; Genzano, Nicola; Lacava, Teodosio; Lisi, Mariano; Paciello, Rossana; Pergola, Nicola; Vallianatos, Filippos; Tramutoli, Valerio

2016-01-01

Real-time integration of multi-parametric observations is expected to accelerate the process toward improved, and operationally more effective, systems for time-Dependent Assessment of Seismic Hazard (t-DASH) and earthquake short-term (from days to weeks) forecast. However, a very preliminary step in this direction is the identification of those parameters (chemical, physical, biological, etc.) whose anomalous variations can be, to some extent, associated with the complex process of preparation for major earthquakes. In this paper one of these parameters (the Earth's emitted radiation in the Thermal InfraRed spectral region) is considered for its possible correlation with M ≥ 4 earthquakes occurred in Greece in between 2004 and 2013. The Robust Satellite Technique (RST) data analysis approach and Robust Estimator of TIR Anomalies (RETIRA) index were used to preliminarily define, and then to identify, significant sequences of TIR anomalies (SSTAs) in 10 years (2004-2013) of daily TIR images acquired by the Spinning Enhanced Visible and Infrared Imager on board the Meteosat Second Generation satellite. Taking into account the physical models proposed for justifying the existence of a correlation among TIR anomalies and earthquake occurrences, specific validation rules (in line with the ones used by the Collaboratory for the Study of Earthquake Predictability—CSEP—Project) have been defined to drive a retrospective correlation analysis process. The analysis shows that more than 93 % of all identified SSTAs occur in the prefixed space-time window around ( M ≥ 4) earthquake's time and location of occurrence with a false positive rate smaller than 7 %. Molchan error diagram analysis shows that such a correlation is far to be achievable by chance notwithstanding the huge amount of missed events due to frequent space/time data gaps produced by the presence of clouds over the scene. Achieved results, and particularly the very low rate of false positives registered on a so long testing period, seems already sufficient (at least) to qualify TIR anomalies (identified by RST approach and RETIRA index) among the parameters to be considered in the framework of a multi-parametric approach to t-DASH.

Degree-strength correlation reveals anomalous trading behavior.

PubMed

Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Wang, Zhao-Yang

2012-01-01

Manipulation is an important issue for both developed and emerging stock markets. Many efforts have been made to detect manipulation in stock markets. However, it is still an open problem to identify the fraudulent traders, especially when they collude with each other. In this paper, we focus on the problem of identifying the anomalous traders using the transaction data of eight manipulated stocks and forty-four non-manipulated stocks during a one-year period. By analyzing the trading networks of stocks, we find that the trading networks of manipulated stocks exhibit significantly higher degree-strength correlation than the trading networks of non-manipulated stocks and the randomized trading networks. We further propose a method to detect anomalous traders of manipulated stocks based on statistical significance analysis of degree-strength correlation. Experimental results demonstrate that our method is effective at distinguishing the manipulated stocks from non-manipulated ones. Our method outperforms the traditional weight-threshold method at identifying the anomalous traders in manipulated stocks. More importantly, our method is difficult to be fooled by colluded traders.

Relations between CBM (Oral Reading and Maze) and Reading Comprehension on State Achievement Tests: A Meta-Analysis

ERIC Educational Resources Information Center

Shin, Jaehyun

2017-01-01

The purpose of this study was to examine the validity of two widely used Curriculum-Based Measurement (CBM) in reading--oral reading and maze task--in relation to reading comprehension on state tests using a meta-analysis. A total of 61 studies (132 correlations) were identified across Grades 1 to 10. A random-effects meta-analysis was conducted…

Can poison control data be used for pharmaceutical poisoning surveillance?

PubMed

Naun, Christopher A; Olsen, Cody S; Dean, J Michael; Olson, Lenora M; Cook, Lawrence J; Keenan, Heather T

2011-05-01

To determine the association between the frequencies of pharmaceutical exposures reported to a poison control center (PCC) and those seen in the emergency department (ED). A statewide population-based retrospective comparison of frequencies of ED pharmaceutical poisonings with frequencies of pharmaceutical exposures reported to a regional PCC. ED poisonings, identified by International Classification of Diseases, Version 9 (ICD-9) codes, were grouped into substance categories. Using a reproducible algorithm facilitated by probabilistic linkage, codes from the PCC classification system were mapped into the same categories. A readily identifiable subset of PCC calls was selected for comparison. Correlations between frequencies of quarterly exposures by substance categories were calculated using Pearson correlation coefficients and partial correlation coefficients with adjustment for seasonality. PCC reported exposures correlated with ED poisonings in nine of 10 categories. Partial correlation coefficients (r(p)) indicated strong associations (r(p)>0.8) for three substance categories that underwent large changes in their incidences (opiates, benzodiazepines, and muscle relaxants). Six substance categories were moderately correlated (r(p)>0.6). One category, salicylates, showed no association. Limitations Imperfect overlap between ICD-9 and PCC codes may have led to miscategorization. Substances without changes in exposure frequency have inadequate variability to detect association using this method. PCC data are able to effectively identify trends in poisonings seen in EDs and may be useful as part of a pharmaceutical poisoning surveillance system. The authors developed an algorithm-driven technique for mapping American Association of Poison Control Centers codes to ICD-9 codes and identified a useful subset of poison control exposures for analysis.

Optimal Resonant Band Demodulation Based on an Improved Correlated Kurtosis and Its Application in Bearing Fault Diagnosis

PubMed Central

Chen, Xianglong; Zhang, Bingzhi; Feng, Fuzhou; Jiang, Pengcheng

2017-01-01

The kurtosis-based indexes are usually used to identify the optimal resonant frequency band. However, kurtosis can only describe the strength of transient impulses, which cannot differentiate impulse noises and repetitive transient impulses cyclically generated in bearing vibration signals. As a result, it may lead to inaccurate results in identifying resonant frequency bands, in demodulating fault features and hence in fault diagnosis. In view of those drawbacks, this manuscript redefines the correlated kurtosis based on kurtosis and auto-correlative function, puts forward an improved correlated kurtosis based on squared envelope spectrum of bearing vibration signals. Meanwhile, this manuscript proposes an optimal resonant band demodulation method, which can adaptively determine the optimal resonant frequency band and accurately demodulate transient fault features of rolling bearings, by combining the complex Morlet wavelet filter and the Particle Swarm Optimization algorithm. Analysis of both simulation data and experimental data reveal that the improved correlated kurtosis can effectively remedy the drawbacks of kurtosis-based indexes and the proposed optimal resonant band demodulation is more accurate in identifying the optimal central frequencies and bandwidth of resonant bands. Improved fault diagnosis results in experiment verified the validity and advantage of the proposed method over the traditional kurtosis-based indexes. PMID:28208820

An evaluation of a computer code based on linear acoustic theory for predicting helicopter main rotor noise. [CH-53A and S-76 helicopters

NASA Technical Reports Server (NTRS)

Davis, S. J.; Egolf, T. A.

1980-01-01

Acoustic characteristics predicted using a recently developed computer code were correlated with measured acoustic data for two helicopter rotors. The analysis, is based on a solution of the Ffowcs-Williams-Hawkings (FW-H) equation and includes terms accounting for both the thickness and loading components of the rotational noise. Computations are carried out in the time domain and assume free field conditions. Results of the correlation show that the Farrassat/Nystrom analysis, when using predicted airload data as input, yields fair but encouraging correlation for the first 6 harmonics of blade passage. It also suggests that although the analysis represents a valuable first step towards developing a truly comprehensive helicopter rotor noise prediction capability, further work remains to be done identifying and incorporating additional noise mechanisms into the code.

Investigating the Important Correlates of Maternal Education and Childhood Malaria Infections

PubMed Central

Njau, Joseph D.; Stephenson, Rob; Menon, Manoj P.; Kachur, S. Patrick; McFarland, Deborah A.

2014-01-01

The relationship between maternal education and child health has intrigued researchers for decades. This study explored the interaction between maternal education and childhood malaria infection. Cross-sectional survey data from three African countries were used. Descriptive analysis and multivariate logistic regression models were completed in line with identified correlates. Marginal effects and Oaxaca decomposition analysis on maternal education and childhood malaria infection were also estimated. Children with mothers whose education level was beyond primary school were 4.7% less likely to be malaria-positive (P < 0.001). The Oaxaca decomposition analysis exhibited an 8% gap in childhood malaria infection for educated and uneducated mothers. Over 60% of the gap was explained by differences in household wealth (26%), household place of domicile (21%), malaria transmission intensities (14%), and media exposure (12%). All other correlates accounted for only 27%. The full adjusted model showed a robust and significant relationship between maternal education and childhood malaria infection. PMID:25002302

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling*

PubMed Central

Larance, Mark; Kirkwood, Kathryn J.; Tinti, Michele; Brenes Murillo, Alejandro; Ferguson, Michael A. J.; Lamond, Angus I.

2016-01-01

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754). PMID:27114452

Utility of correlation techniques in gravity and magnetic interpretation

NASA Technical Reports Server (NTRS)

Chandler, V. W.; Koski, J. S.; Braice, L. W.; Hinze, W. J.

1977-01-01

Internal correspondence uses Poisson's Theorem in a moving-window linear regression analysis between the anomalous first vertical derivative of gravity and total magnetic field reduced to the pole. The regression parameters provide critical information on source characteristics. The correlation coefficient indicates the strength of the relation between magnetics and gravity. Slope value gives delta j/delta sigma estimates of the anomalous source. The intercept furnishes information on anomaly interference. Cluster analysis consists of the classification of subsets of data into groups of similarity based on correlation of selected characteristics of the anomalies. Model studies are used to illustrate implementation and interpretation procedures of these methods, particularly internal correspondence. Analysis of the results of applying these methods to data from the midcontinent and a transcontinental profile shows they can be useful in identifying crustal provinces, providing information on horizontal and vertical variations of physical properties over province size zones, validating long wavelength anomalies, and isolating geomagnetic field removal problems.

FT-IR spectroscopy and multivariate analysis as an auxiliary tool for diagnosis of mental disorders: Bipolar and schizophrenia cases

NASA Astrophysics Data System (ADS)

Ogruc Ildiz, G.; Arslan, M.; Unsalan, O.; Araujo-Andrade, C.; Kurt, E.; Karatepe, H. T.; Yilmaz, A.; Yalcinkaya, O. B.; Herken, H.

2016-01-01

In this study, a methodology based on Fourier-transform infrared spectroscopy and principal component analysis and partial least square methods is proposed for the analysis of blood plasma samples in order to identify spectral changes correlated with some biomarkers associated with schizophrenia and bipolarity. Our main goal was to use the spectral information for the calibration of statistical models to discriminate and classify blood plasma samples belonging to bipolar and schizophrenic patients. IR spectra of 30 samples of blood plasma obtained from each, bipolar and schizophrenic patients and healthy control group were collected. The results obtained from principal component analysis (PCA) show a clear discrimination between the bipolar (BP), schizophrenic (SZ) and control group' (CG) blood samples that also give possibility to identify three main regions that show the major differences correlated with both mental disorders (biomarkers). Furthermore, a model for the classification of the blood samples was calibrated using partial least square discriminant analysis (PLS-DA), allowing the correct classification of BP, SZ and CG samples. The results obtained applying this methodology suggest that it can be used as a complimentary diagnostic tool for the detection and discrimination of these mental diseases.

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

PubMed Central

Cocco, Simona; Monasson, Remi; Weigt, Martin

2013-01-01

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. PMID:23990764

Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.

PubMed

Mrabet, Yassine; Semmar, Nabil

2010-05-01

Complexity of metabolic systems can be undertaken at different scales (metabolites, metabolic pathways, metabolic network map, biological population) and under different aspects (structural, functional, evolutive). To analyse such a complexity, metabolic systems need to be decomposed into different components according to different concepts. Four concepts are presented here consisting in considering metabolic systems as sets of metabolites, chemical reactions, metabolic pathways or successive processes. From a metabolomic dataset, such decompositions are performed using different mathematical methods including correlation, stiochiometric, ordination, classification, combinatorial and kinetic analyses. Correlation analysis detects and quantifies affinities/oppositions between metabolites. Stoichiometric analysis aims to identify the organisation of a metabolic network into different metabolic pathways on the hand, and to quantify/optimize the metabolic flux distribution through the different chemical reactions of the system. Ordination and classification analyses help to identify different metabolic trends and their associated metabolites in order to highlight chemical polymorphism representing different variability poles of the metabolic system. Then, metabolic processes/correlations responsible for such a polymorphism can be extracted in silico by combining metabolic profiles representative of different metabolic trends according to a weighting bootstrap approach. Finally evolution of metabolic processes in time can be analysed by different kinetic/dynamic modelling approaches.

Optical communication noise rejection using corelated photons

NASA Technical Reports Server (NTRS)

Jackson, D.; Hockney, G. M.; Dowling, J. P.

2002-01-01

This paper describes a completely new way to perform noise rejection using photons correlated through quantum entanglement to improve an optical communications link in the presence of uncorrelated noise. In particular, a detailed analysis is made of the case where a classical link would be saturated by an intense background, such as when a satellite is in front of the sun, and identifies where the quantum correlating system has superior performance.

Physiologic and laboratory correlates of depression, anxiety, and poor sleep in liver cirrhosis.

PubMed

Ko, Fang-Yuan; Yang, Albert C; Tsai, Shih-Jen; Zhou, Yang; Xu, Lie-Ming

2013-01-22

Studies have shown psychological distress in patients with cirrhosis, yet no studies have evaluated the laboratory and physiologic correlates of psychological symptoms in cirrhosis. This study therefore measured both biochemistry data and heart rate variability (HRV) analyses, and aimed to identify the physiologic correlates of depression, anxiety, and poor sleep in cirrhosis. A total of 125 patients with cirrhosis and 55 healthy subjects were recruited. Each subject was assessed through routine biochemistry, 5-minutes ECG monitoring, and psychological ratings of depression, anxiety, and sleep. HRV analysis were used to evaluate autonomic functions. The relationship between depression, sleep, and physiologic correlates was assessed using a multiple regression analysis and stepwise method, controlling for age, duration of illness, and severity of cirrhosis. Reduced vagal-related HRV was found in patients with severe liver cirrhosis. Severity of cirrhosis measured by the Child-Pugh score was not correlated with depression or anxiety, and only had a weak correlation with poor sleep. The psychological distress in cirrhosis such as depression, anxiety, and insomnia were correlated specifically to increased levels of aspartate aminotransferase (AST), increased ratios of low frequency to high frequency power, or reduced nonlinear properties of HRV (α1 exponent of detrended fluctuation analysis). Increased serum AST and abnormal autonomic nervous activities by HRV analysis were associated with psychological distress in cirrhosis. Because AST is an important mediator of inflammatory process, further research is needed to delineate the role of inflammation in the cirrhosis comorbid with depression.

Physiologic and laboratory correlates of depression, anxiety, and poor sleep in liver cirrhosis

PubMed Central

2013-01-01

Background Studies have shown psychological distress in patients with cirrhosis, yet no studies have evaluated the laboratory and physiologic correlates of psychological symptoms in cirrhosis. This study therefore measured both biochemistry data and heart rate variability (HRV) analyses, and aimed to identify the physiologic correlates of depression, anxiety, and poor sleep in cirrhosis. Methods A total of 125 patients with cirrhosis and 55 healthy subjects were recruited. Each subject was assessed through routine biochemistry, 5-minutes ECG monitoring, and psychological ratings of depression, anxiety, and sleep. HRV analysis were used to evaluate autonomic functions. The relationship between depression, sleep, and physiologic correlates was assessed using a multiple regression analysis and stepwise method, controlling for age, duration of illness, and severity of cirrhosis. Results Reduced vagal-related HRV was found in patients with severe liver cirrhosis. Severity of cirrhosis measured by the Child-Pugh score was not correlated with depression or anxiety, and only had a weak correlation with poor sleep. The psychological distress in cirrhosis such as depression, anxiety, and insomnia were correlated specifically to increased levels of aspartate aminotransferase (AST), increased ratios of low frequency to high frequency power, or reduced nonlinear properties of HRV (α1 exponent of detrended fluctuation analysis). Conclusions Increased serum AST and abnormal autonomic nervous activities by HRV analysis were associated with psychological distress in cirrhosis. Because AST is an important mediator of inflammatory process, further research is needed to delineate the role of inflammation in the cirrhosis comorbid with depression. PMID:23339829

Symptom clusters and related factors in bladder cancer patients three months after radical cystectomy.

PubMed

Ren, Hongyan; Tang, Ping; Zhao, Qinghua; Ren, Guosheng

2017-08-23

To identify symptom distress and clusters in patients 3 months after radical cystectomy and to explore their potential predictors. A cross-sectional design was used to investigate 99 bladder cancer patients 3 months after radical cystectomy. Data were collected by demographic and disease characteristic questionnaires, the symptom experience scale of the M.D. Anderson symptom inventory, two additional symptoms specific to radical cystectomy, and the functional assessment of cancer therapy questionnaire. A factor analysis, stepwise regression, and correlation analysis were applied. Three symptom clusters were identified: fatigue-malaise, gastrointestinal, and psycho-urinary. Age, complication severity, albumin post-surgery (negative), orthotropic neobladder reconstruction, adjuvant chemotherapy and American Society of Anesthesiologists (ASA) scores were significant predictors of fatigue-malaise. Adjuvant chemotherapy, orthotropic neobladder reconstruction, female gender, ASA scores and albumin (negative) were significant predictors of gastrointestinal symptoms. Being unmarried, having a higher educational level and complication severity were significant predictors of psycho-urinary symptoms. The correlations between clusters and for each cluster with quality of life were significant, with the highest correlation observed between the psycho-urinary cluster and quality of life. Bladder cancer patients experience concurrent symptoms that appear to cluster and are significantly correlated with quality of life. Moreover, symptom clusters may be predicted by certain demographic and clinical characteristics.

The Impact of Letter Grades on Student Effort, Course Selection, and Major Choice: A Regression-Discontinuity Analysis

ERIC Educational Resources Information Center

Main, Joyce B.; Ost, Ben

2014-01-01

The authors apply a regression-discontinuity design to identify the causal impact of letter grades on student effort within a course, subsequent credit hours taken, and the probability of majoring in economics. Their methodology addresses key issues in identifying the causal impact of letter grades: correlation with unobservable factors, such as…

Segmenting the Stream of Consciousness: The Psychological Correlates of Temporal Structures in the Time Series Data of a Continuous Performance Task

ERIC Educational Resources Information Center

Smallwood, Jonathan; McSpadden, Merrill; Luus, Bryan; Schooler, Joanthan

2008-01-01

Using principal component analysis, we examined whether structural properties in the time series of response time would identify different mental states during a continuous performance task. We examined whether it was possible to identify regular patterns which were present in blocks classified as lacking controlled processing, either…

Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.; Pappa, R. S.

1985-01-01

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

Large modal survey testing using the Ibrahim time domain /ITD/ identification technique

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.; Pappa, R. S.

1981-01-01

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2014-06-01

In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and issue.

fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

PubMed

Madrigal, Pedro

2017-03-01

Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

The Relationship between Teacher Support and Students' Academic Emotions: A Meta-Analysis

PubMed Central

Lei, Hao; Cui, Yunhuo; Chiu, Ming Ming

2018-01-01

This meta-analysis examines the association between teacher support and students' academic emotions [both positive academic emotions (PAEs) and negative academic emotions (NAEs)] and explores how student characteristics moderate these relationships. We identified 65 primary studies with 58,368 students. The results provided strong evidence linking teacher support and students' academic emotions. Furthermore, students' culture, age, and gender moderated these links. The correlation between teacher support and PAEs was stronger for Western European and American students than for East Asian students, while the correlation between teacher support and NAEs was stronger for East Asian students than for Western European and American students. Also, the correlation between teacher support and PAEs was strong among university students and weaker among middle school students, compared to other students. The correlation between teacher support and NAEs was stronger for middle school students and for female students, compared to other students. PMID:29403405

EEG oscillations and recognition memory: theta correlates of memory retrieval and decision making.

PubMed

Jacobs, Joshua; Hwang, Grace; Curran, Tim; Kahana, Michael J

2006-08-15

Studies of memory retrieval have identified electroencephalographic (EEG) correlates of a test item's old-new status, reaction time, and memory load. In the current study, we used a multivariate analysis to disentangle the effects of these correlated variables. During retrieval, power of left-parietal theta (4-8 Hz) oscillations increased in proportion to how well a test item was remembered, and theta in central regions correlated with decision making. We also studied how these oscillatory dynamics complemented event-related potentials. These findings are the first to demonstrate that distinct patterns of theta oscillations can simultaneously relate to different aspects of behavior.

Correlates of the categories of adolescent attachment styles: Perceived rearing, family function, early life events, and personality.

PubMed

Tanaka, Nao; Hasui, Chieko; Uji, Masayo; Hiramura, Hidetoshi; Chen, Zi; Shikai, Noriko; Kitamura, Toshinori

2008-02-01

To identify the psychosocial correlates of adolescents. Unmarried university students (n = 4226) aged 18-23 years were examined in a questionnaire survey. Four clusters of people (indifferent, secure, fearful, and preoccupied) identified by cluster analysis were plotted in 2-D using discriminant function analysis with the first function (father's and mother's Care, Cooperativeness, and family Cohesion on the positive end and Harm Avoidance and father's and mother's Overprotection on the negative end) representing the Self-model and the second function (Reward Dependence and experience of Peer Victimization on the positive end and Self-directedness on the negative end) representing the Other model. These findings partially support Bartholomew's notion that adult attachment is based on the good versus bad representations of the self and the other and that it is influenced by psychosocial environments experienced over the course of development.

Prospective Molecular Profiling of Melanoma Metastases Suggests Classifiers of Immune Responsiveness

PubMed Central

Wang, Ena; Miller, Lance D.; Ohnmacht, Galen A.; Mocellin, Simone; Perez-Diez, Ainhoa; Petersen, David; Zhao, Yingdong; Simon, Richard; Powell, John I.; Asaki, Esther; Alexander, H. Richard; Duray, Paul H.; Herlyn, Meenhard; Restifo, Nicholas P.; Liu, Edison T.; Rosenberg, Steven A.; Marincola, Francesco M.

2008-01-01

We amplified RNAs from 63 fine needle aspiration (FNA) samples from 37 s.c. melanoma metastases from 25 patients undergoing immunotherapy for hybridization to a 6108-gene human cDNA chip. By prospectively following the history of the lesions, we could correlate transcript patterns with clinical outcome. Cluster analysis revealed a tight relationship among autologous synchronously sampled tumors compared with unrelated lesions (average Pearson's r = 0.83 and 0.7, respectively, P < 0.0003). As reported previously, two subgroups of metastatic melanoma lesions were identified that, however, had no predictive correlation with clinical outcome. Ranking of gene expression data from pretreatment samples identified ∼30 genes predictive of clinical response (P < 0.001). Analysis of their annotations denoted that approximately half of them were related to T-cell regulation, suggesting that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition. PMID:12097256

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

PubMed Central

Wade, Len J.; Bartolome, Violeta; Mauleon, Ramil; Vasant, Vivek Deshmuck; Prabakar, Sumeet Mankar; Chelliah, Muthukumar; Kameoka, Emi; Nagendra, K.; Reddy, K. R. Kamalnath; Varma, C. Mohan Kumar; Patil, Kalmeshwar Gouda; Shrestha, Roshi; Al-Shugeairy, Zaniab; Al-Ogaidi, Faez; Munasinghe, Mayuri; Gowda, Veeresh; Semon, Mande; Suralta, Roel R.; Shenoy, Vinay; Vadez, Vincent; Serraj, Rachid; Shashidhar, H. E.; Yamauchi, Akira; Babu, Ranganathan Chandra; Price, Adam; McNally, Kenneth L.; Henry, Amelia

2015-01-01

The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7–40.7 Mb) and on chromosome 8 (20.3–21.9 Mb). Across experiments, the soil type/ growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions. PMID:25909711

Analysis of Skylab fluid mechanics science demonstrations

NASA Technical Reports Server (NTRS)

Tegart, J. R.; Butz, J. R.

1975-01-01

The results of the data reduction and analysis of the Skylab fluid mechanics demonstrations are presented. All the fluid mechanics data available from the Skylab missions were identified and surveyed. The significant fluid mechanics phenomena were identified and reduced to measurable quantities wherever possible. Data correlations were performed using existing theories. Among the phenomena analyzed were: static low-g interface shapes, oscillation frequency and damping of a liquid drop, coalescence, rotating drop, liquid films and low-g ice melting. A survey of the possible applications of the results was made and future experiments are recommended.

A simple method for identifying parameter correlations in partially observed linear dynamic models.

PubMed

Li, Pu; Vu, Quoc Dong

2015-12-14

Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a software packet.

Individual and Work-Related Factors Influencing Burnout of Mental Health Professionals: A Meta-Analysis

ERIC Educational Resources Information Center

Lim, Nayoung; Kim, Eun Kyoung; Kim, Hyunjung; Yang, Eunjoo; Lee, Sang Min

2010-01-01

The current study identifies and assesses individual and work-related factors as correlates of burnout among mental health professionals. Results of a meta-analysis indicate that age and work setting variables are the most significant indicators of emotional exhaustion and depersonalization. In terms of level of personal accomplishment, the age…

Visualizing Calcium Flux in Freely Moving Nematode Embryos.

PubMed

Ardiel, Evan L; Kumar, Abhishek; Marbach, Joseph; Christensen, Ryan; Gupta, Rishi; Duncan, William; Daniels, Jonathan S; Stuurman, Nico; Colón-Ramos, Daniel; Shroff, Hari

2017-05-09

The lack of physiological recordings from Caenorhabditis elegans embryos stands in stark contrast to the comprehensive anatomical and gene expression datasets already available. Using light-sheet fluorescence microscopy to address the challenges associated with functional imaging at this developmental stage, we recorded calcium dynamics in muscles and neurons and developed analysis strategies to relate activity and movement. In muscles, we found that the initiation of twitching was associated with a spreading calcium wave in a dorsal muscle bundle. Correlated activity in muscle bundles was linked with early twitching and eventual coordinated movement. To identify neuronal correlates of behavior, we monitored brainwide activity with subcellular resolution and identified a particularly active cell associated with muscle contractions. Finally, imaging neurons of a well-defined adult motor circuit, we found that reversals in the eggshell correlated with calcium transients in AVA interneurons. Published by Elsevier Inc.

Neural activity in relation to empirically derived personality syndromes in depression using a psychodynamic fMRI paradigm

PubMed Central

Taubner, Svenja; Wiswede, Daniel; Kessler, Henrik

2013-01-01

Objective: The heterogeneity between patients with depression cannot be captured adequately with existing descriptive systems of diagnosis and neurobiological models of depression. Furthermore, considering the highly individual nature of depression, the application of general stimuli in past research efforts may not capture the essence of the disorder. This study aims to identify subtypes of depression by using empirically derived personality syndromes, and to explore neural correlates of the derived personality syndromes. Materials and Methods: In the present exploratory study, an individually tailored and psychodynamically based functional magnetic resonance imaging paradigm using dysfunctional relationship patterns was presented to 20 chronically depressed patients. Results from the Shedler–Westen Assessment Procedure (SWAP-200) were analyzed by Q-factor analysis to identify clinically relevant subgroups of depression and related brain activation. Results: The principle component analysis of SWAP-200 items from all 20 patients lead to a two-factor solution: “Depressive Personality” and “Emotional-Hostile-Externalizing Personality.” Both factors were used in a whole-brain correlational analysis but only the second factor yielded significant positive correlations in four regions: a large cluster in the right orbitofrontal cortex (OFC), the left ventral striatum, a small cluster in the left temporal pole, and another small cluster in the right middle frontal gyrus. Discussion: The degree to which patients with depression score high on the factor “Emotional-Hostile-Externalizing Personality” correlated with relatively higher activity in three key areas involved in emotion processing, evaluation of reward/punishment, negative cognitions, depressive pathology, and social knowledge (OFC, ventral striatum, temporal pole). Results may contribute to an alternative description of neural correlates of depression showing differential brain activation dependent on the extent of specific personality syndromes in depression. PMID:24363644

Dimensional profiles of male to female gender identity disorder: an exploratory research.

PubMed

Fisher, Alessandra D; Bandini, Elisa; Ricca, Valdo; Ferruccio, Naika; Corona, Giovanni; Meriggiola, Maria C; Jannini, Emmanuele A; Manieri, Chiara; Ristori, Jiska; Forti, Gianni; Mannucci, Edoardo; Maggi, Mario

2010-07-01

Male-to-Female Gender Identity Disorder (MtF GID) is a complex phenomenon that could be better evaluated by using a dimensional approach. To explore the aggregation of clinical manifestations of MtF GID in order to identify meaningful variables describing the heterogeneity of the disorder. A consecutive series of 80 MtF GID subjects (mean age 37 +/- 10.3 years), referred to the Interdepartmental Center for Assistance Gender Identity Disorder of Florence and to other Italian centers from July 2008 to June 2009, was studied. Diagnosis was based on formal psychiatric classification criteria. Factor analysis was performed. Several socio-demographic and clinical parameters were investigated. Patients were asked to complete the Bem Sex Role Inventory (BSRI, a self-rating scale to evaluate gender role) and Symptom Checklist-90 Revised (SCL-90-R, a self-rating scale to measure psychological state). Factor analysis identified two dimensional factors: Factor 1 was associated with sexual orientation, and Factor 2 related to behavioral and psychological correlates of early GID development. No correlation was observed between the two factors. A positive correlation between Factor 2 and feminine BSRI score was found, along with a negative correlation between Factor 2 and undifferentiated BSRI score. Moreover, a significant association between SCL-90-R Phobic subscale score and Factor 2 was observed. A variety of other socio-demographic parameters and clinical features were associated with both factors. Behavioral and psychological correlates of Factor 1 (sexual orientation) and Factor 2 (gender identity) do not constitute the framework of two separate clinical entities, but instead represent two dimensions of the complex MtF GID structure, which can be variably intertwined in the same subject. By using factor analysis, we offer a new approach capable of delineating a psychopathological and clinical profile of MtF GID patients.

Importance analysis for Hudson River PCB transport and fate model parameters using robust sensitivity studies

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

Zhang, S.; Toll, J.; Cothern, K.

1995-12-31

The authors have performed robust sensitivity studies of the physico-chemical Hudson River PCB model PCHEPM to identify the parameters and process uncertainties contributing the most to uncertainty in predictions of water column and sediment PCB concentrations, over the time period 1977--1991 in one segment of the lower Hudson River. The term ``robust sensitivity studies`` refers to the use of several sensitivity analysis techniques to obtain a more accurate depiction of the relative importance of different sources of uncertainty. Local sensitivity analysis provided data on the sensitivity of PCB concentration estimates to small perturbations in nominal parameter values. Range sensitivity analysismore » provided information about the magnitude of prediction uncertainty associated with each input uncertainty. Rank correlation analysis indicated which parameters had the most dominant influence on model predictions. Factorial analysis identified important interactions among model parameters. Finally, term analysis looked at the aggregate influence of combinations of parameters representing physico-chemical processes. The authors scored the results of the local and range sensitivity and rank correlation analyses. The authors considered parameters that scored high on two of the three analyses to be important contributors to PCB concentration prediction uncertainty, and treated them probabilistically in simulations. They also treated probabilistically parameters identified in the factorial analysis as interacting with important parameters. The authors used the term analysis to better understand how uncertain parameters were influencing the PCB concentration predictions. The importance analysis allowed us to reduce the number of parameters to be modeled probabilistically from 16 to 5. This reduced the computational complexity of Monte Carlo simulations, and more importantly, provided a more lucid depiction of prediction uncertainty and its causes.« less

Windowed multitaper correlation analysis of multimodal brain monitoring parameters.

PubMed

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

Spatially-Resolved Influence of Temperature and Salinity on Stock and Recruitment Variability of Commercially Important Fishes in the North Sea

PubMed Central

Akimova, Anna; Núñez-Riboni, Ismael; Kempf, Alexander; Taylor, Marc H.

2016-01-01

Understanding of the processes affecting recruitment of commercially important fish species is one of the major challenges in fisheries science. Towards this aim, we investigated the relation between North Sea hydrography (temperature and salinity) and fish stock variables (recruitment, spawning stock biomass and pre-recruitment survival index) for 9 commercially important fishes using spatially-resolved cross-correlation analysis. We used high-resolution (0.2° × 0.2°) hydrographic data fields matching the maximal temporal extent of the fish population assessments (1948–2013). Our approach allowed for the identification of regions in the North Sea where environmental variables seem to be more influential on the fish stocks, as well as the regions of a lesser or nil influence. Our results confirmed previously demonstrated negative correlations between temperature and recruitment of cod and plaice and identified regions of the strongest correlations (German Bight for plaice and north-western North Sea for cod). We also revealed a positive correlation between herring spawning stock biomass and temperature in the Orkney-Shetland area, as well as a negative correlation between sole pre-recruitment survival index and temperature in the German Bight. A strong positive correlation between sprat stock variables and salinity in the central North Sea was also found. To our knowledge the results concerning correlations between North Sea hydrography and stocks’ dynamics of herring, sole and sprat are novel. The new information about spatial distribution of the correlation provides an additional help to identify mechanisms underlying these correlations. As an illustration of the utility of these results for fishery management, an example is provided that incorporates the identified environmental covariates in stock-recruitment models. PMID:27584155

Long-Range Correlations in Sentence Series from A Story of the Stone

PubMed Central

Yang, Tianguang; Gu, Changgui; Yang, Huijie

2016-01-01

A sentence is the natural unit of language. Patterns embedded in series of sentences can be used to model the formation and evolution of languages, and to solve practical problems such as evaluating linguistic ability. In this paper, we apply de-trended fluctuation analysis to detect long-range correlations embedded in sentence series from A Story of the Stone, one of the greatest masterpieces of Chinese literature. We identified a weak long-range correlation, with a Hurst exponent of 0.575±0.002 up to a scale of 104. We used the structural stability to confirm the behavior of the long-range correlation, and found that different parts of the series had almost identical Hurst exponents. We found that noisy records can lead to false results and conclusions, even if the noise covers a limited proportion of the total records (e.g., less than 1%). Thus, the structural stability test is an essential procedure for confirming the existence of long-range correlations, which has been widely neglected in previous studies. Furthermore, a combination of de-trended fluctuation analysis and diffusion entropy analysis demonstrated that the sentence series was generated by a fractional Brownian motion. PMID:27648941

Long-Range Correlations in Sentence Series from A Story of the Stone.

PubMed

Yang, Tianguang; Gu, Changgui; Yang, Huijie

2016-01-01

A sentence is the natural unit of language. Patterns embedded in series of sentences can be used to model the formation and evolution of languages, and to solve practical problems such as evaluating linguistic ability. In this paper, we apply de-trended fluctuation analysis to detect long-range correlations embedded in sentence series from A Story of the Stone, one of the greatest masterpieces of Chinese literature. We identified a weak long-range correlation, with a Hurst exponent of 0.575±0.002 up to a scale of 104. We used the structural stability to confirm the behavior of the long-range correlation, and found that different parts of the series had almost identical Hurst exponents. We found that noisy records can lead to false results and conclusions, even if the noise covers a limited proportion of the total records (e.g., less than 1%). Thus, the structural stability test is an essential procedure for confirming the existence of long-range correlations, which has been widely neglected in previous studies. Furthermore, a combination of de-trended fluctuation analysis and diffusion entropy analysis demonstrated that the sentence series was generated by a fractional Brownian motion.

Correlation between HIV-1 genotype and clinical progression in HIV/AIDS patients in Surabaya, Indonesia

NASA Astrophysics Data System (ADS)

Rachman, B. E.; Khairunisa, S. Q.; Witaningrum, A. M.; Yunifiar, M. Q.; Nasronudin

2018-03-01

Several factors such as host and viral factors can affect the progression of HIV/AIDS. This study aims to identify the correlation viral factors, especially the HIV-1 subtype with HIV/AIDS progression. Inpatient HIV/AIDS during the period March to September 2017 and willing to participate are included in the study. Historical data of disease and treatment was taken by medical record. Blood samples were amplified, sequenced and undergone phylogenetic analysis. Linear regression analysis was used to estimate beta coefficient (β) and 95%CI of HIV/AIDS progression (measured by the CD4 change rate, ΔCD4 cell count/time span in months).This study has 17 samples. The HIV-1 subtype was dominated by CRF01_AE (81.8%) followed by subtype B (18.2%). There was significant correlation between subtype HIV-1 (p = 0.04) and body mass index (p = 0.038) with HIV/AIDS clinical stage. Many factors were assumed to be correlated with increased rate of CD4, but we only subtype HIV-1 had a significant correlation (p = 0.024) with it. From multivariate analysis, we also found that subtype HIV-1 had a significant correlation (β = 0.788, 95%CI: 17.5-38.6, p = 0.004).

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates.

PubMed

Xia, Li C; Steele, Joshua A; Cram, Jacob A; Cardon, Zoe G; Simmons, Sheri L; Vallino, Joseph J; Fuhrman, Jed A; Sun, Fengzhu

2011-01-01

The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa.

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates

PubMed Central

2011-01-01

Background The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. Results We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. Conclusions The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa. PMID:22784572

Evaluation of dietary patterns among Norwegian postmenopausal women using plasma carotenoids as biomarkers.

PubMed

Markussen, Marianne S; Veierød, Marit B; Sakhi, Amrit K; Ellingjord-Dale, Merete; Blomhoff, Rune; Ursin, Giske; Andersen, Lene F

2015-02-28

A number of studies have examined dietary patterns in various populations. However, to study to what extent such patterns capture meaningful differences in consumption of foods is of interest. In the present study, we identified important dietary patterns in Norwegian postmenopausal women (age 50-69 years, n 361), and evaluated these patterns by examining their associations with plasma carotenoids. Diet was assessed by a 253-item FFQ. These 253 food items were categorised into forty-six food groups, and dietary patterns were identified using principal component analysis. We used the partial correlation coefficient (r(adj)) and multiple linear regression analysis to examine the associations between the dietary patterns and the plasma carotenoids α-carotene, β-carotene, β-cryptoxanthin, lutein, lycopene and zeaxanthin. Overall, four dietary patterns were identified: the 'Western'; 'Vegetarian'; 'Continental'; 'High-protein'. The 'Western' dietary pattern scores were significantly inversely correlated with plasma lutein, zeaxanthin, lycopene and total carotenoids (-0·25 ≤ r(adj) ≤ -0·13). The 'Vegetarian' dietary pattern scores were significantly positively correlated with all the plasma carotenoids (0·15 ≤ r(adj) ≤ 0·24). The 'Continental' dietary pattern scores were significantly inversely correlated with plasma lutein and α-carotene (r(adj) = -0·13). No significant association between the 'High-protein' dietary pattern scores and the plasma carotenoids was found. In conclusion, the healthy dietary pattern, the 'Vegetarian' pattern, is associated with a more favourable profile of the plasma carotenoids than our unhealthy dietary patterns, the 'Western' and 'Continental' patterns.

Comment on 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' by Lam et al.

PubMed

Hill, W David

2018-04-01

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as 'trait specific' to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank.

PubMed

Hall, Lynsey S; Adams, Mark J; Arnau-Soler, Aleix; Clarke, Toni-Kim; Howard, David M; Zeng, Yanni; Davies, Gail; Hagenaars, Saskia P; Maria Fernandez-Pujals, Ana; Gibson, Jude; Wigmore, Eleanor M; Boutin, Thibaud S; Hayward, Caroline; Scotland, Generation; Porteous, David J; Deary, Ian J; Thomson, Pippa A; Haley, Chris S; McIntosh, Andrew M

2018-01-10

Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. Recent studies of MDD have identified common risk variants by using a broader phenotype definition in very large samples, or by reducing phenotypic and ancestral heterogeneity. We sought to ascertain whether it is more informative to maximize the sample size using data from all available cases and controls, or to use a sex or recurrent stratified subset of affected individuals. To test this, we compared heritability estimates, genetic correlation with other traits, variance explained by MDD polygenic score, and variants identified by genome-wide meta-analysis for broad and narrow MDD classifications in two large British cohorts - Generation Scotland and UK Biobank. Genome-wide meta-analysis of MDD in males yielded one genome-wide significant locus on 3p22.3, with three genes in this region (CRTAP, GLB1, and TMPPE) demonstrating a significant association in gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD yielded equivalent heritability estimates, showed no detectable difference in association with polygenic scores, and were each genetically correlated with six health-correlated traits (neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder). Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, and the consistent pattern of results in other MDD classifications suggests that phenotypic stratification using recurrence or sex in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.

A Multicenter Analysis of Factors Associated With Apixaban-Related Bleeding in Hospitalized Patients With End-Stage Renal Disease on Hemodialysis.

PubMed

Steuber, Taylor D; Shiltz, Dane L; Cairns, Alex C; Ding, Qian; Binger, Katie J; Courtney, Julia R

2017-11-01

In 2014, the United States Food and Drug Administration approved a labeling change for apixaban to include recommendations for patients with severe renal impairment and patients with end-stage renal disease (ESRD) on hemodialysis (HD), though these recommendations are largely based on pharmacokinetic and pharmacodynamic data. Identify variables associated with bleeding events in hospitalized patients with ESRD on HD receiving apixaban. This retrospective, multicenter cohort study evaluated hospitalized patients with ESRD on HD receiving apixaban from January 1, 2013, through March 31, 2016. Correlational analysis and logistic regression were completed to identify factors associated with bleeding. A total of 114 adults were included in the analysis. The median length of stay (LOS) was 6.2 (interquartile range = 3.8-11.9) days and bleeding events occurred in a total of 17 patients (15%). A weak correlation was identified for higher cumulative apixaban exposure, increased number of HD sessions while receiving apixaban, and increased hospital LOS ( P < 0.05; correlation coefficient < 0.40). When controlling for confounders, logistic regression revealed that composite bleeding events were independently increased by continuation of outpatient apixaban (odds ratio = 13.07; 95% CI = 1.54-110.54; P = 0.018), increased total daily dose of apixaban (odds ratio = 1.72; 95% CI = 1.20 to 2.48; P = 0.003), and total HD sessions while receiving apixaban (odds ratio = 2.04; 95% CI = 1.06-3.92; P = 0.033). The association between these factors and increased bleeding should prompt concern for long-term anticoagulation with apixaban in patients with ESRD receiving chronic HD.

Prevalence and clinical correlates of sarcopenia in community-dwelling older people: application of the EWGSOP definition and diagnostic algorithm.

PubMed

Volpato, Stefano; Bianchi, Lara; Cherubini, Antonio; Landi, Francesco; Maggio, Marcello; Savino, Elisabetta; Bandinelli, Stefania; Ceda, Gian Paolo; Guralnik, Jack M; Zuliani, Giovanni; Ferrucci, Luigi

2014-04-01

Muscle impairment is a common condition in older people and a powerful risk factor for disability and mortality. The aim of this study was to apply the European Working Group on Sarcopenia in Older People criteria to estimate the prevalence and investigate the clinical correlates of sarcopenia, in a sample of Italian community-dwelling older people. Cross-sectional analysis of 730 participants (74% aged 65 years and older) enrolled in the InCHIANTI study. Sarcopenia was defined according to the European Working Group on Sarcopenia in Older People criteria using bioimpedance analysis for muscle mass assessment. Logistic regression analysis was used to identify the factors independently associated with sarcopenia. Sarcopenia defined by the European Working Group on Sarcopenia in Older People criteria increased steeply with age (p < .001), with 31.6% of women and 17.4% of men aged 80 years or older being affected by this condition. Higher education (odds ratio: 0.85; 95% CI: 0.74-0.98), lower insulin-like growth factor I (lowest vs highest tertile, odds ratio: 3.89; 95% CI: 1.03-14.1), and low bioavailable testosterone (odds ratio: 2.67; 95% CI: 1.31-5.44) were independently associated with the likelihood of being sarcopenic. Nutritional intake, physical activity, and level of comorbidity were not associated with sarcopenia. Sarcopenia identified by the European Working Group on Sarcopenia in Older People criteria is a relatively common condition in Italian octogenarians, and its prevalence increases with aging. Correlates of sarcopenia identified in this study might suggest new approaches for prevention and treatment of sarcopenia.

Interactome analysis of longitudinal pharyngeal infection of cynomolgus macaques by group A Streptococcus.

PubMed

Shea, Patrick R; Virtaneva, Kimmo; Kupko, John J; Porcella, Stephen F; Barry, William T; Wright, Fred A; Kobayashi, Scott D; Carmody, Aaron; Ireland, Robin M; Sturdevant, Daniel E; Ricklefs, Stacy M; Babar, Imran; Johnson, Claire A; Graham, Morag R; Gardner, Donald J; Bailey, John R; Parnell, Michael J; Deleo, Frank R; Musser, James M

2010-03-09

Relatively little is understood about the dynamics of global host-pathogen transcriptome changes that occur during bacterial infection of mucosal surfaces. To test the hypothesis that group A Streptococcus (GAS) infection of the oropharynx provokes a distinct host transcriptome response, we performed genome-wide transcriptome analysis using a nonhuman primate model of experimental pharyngitis. We also identified host and pathogen biological processes and individual host and pathogen gene pairs with correlated patterns of expression, suggesting interaction. For this study, 509 host genes and seven biological pathways were differentially expressed throughout the entire 32-day infection cycle. GAS infection produced an initial widespread significant decrease in expression of many host genes, including those involved in cytokine production, vesicle formation, metabolism, and signal transduction. This repression lasted until day 4, at which time a large increase in expression of host genes was observed, including those involved in protein translation, antigen presentation, and GTP-mediated signaling. The interactome analysis identified 73 host and pathogen gene pairs with correlated expression levels. We discovered significant correlations between transcripts of GAS genes involved in hyaluronic capsule production and host endocytic vesicle formation, GAS GTPases and host fibrinolytic genes, and GAS response to interaction with neutrophils. We also identified a strong signal, suggesting interaction between host gammadelta T cells and genes in the GAS mevalonic acid synthesis pathway responsible for production of isopentenyl-pyrophosphate, a short-chain phospholipid that stimulates these T cells. Taken together, our results are unique in providing a comprehensive understanding of the host-pathogen interactome during mucosal infection by a bacterial pathogen.

Statistical analysis of soil geochemical data to identify pathfinders associated with mineral deposits: An example from the Coles Hill uranium deposit, Virginia, USA

USGS Publications Warehouse

Levitan, Denise M.; Zipper, Carl E.; Donovan, Patricia; Schreiber, Madeline E.; Seal, Robert; Engle, Mark A.; Chermak, John A.; Bodnar, Robert J.; Johnson, Daniel K.; Aylor, Joseph G.

2015-01-01

Soil geochemical anomalies can be used to identify pathfinders in exploration for ore deposits. In this study, compositional data analysis is used with multivariate statistical methods to analyse soil geochemical data collected from the Coles Hill uranium deposit, Virginia, USA, to identify pathfinders associated with this deposit. Elemental compositions and relationships were compared between the collected Coles Hill soil and reference soil samples extracted from a regional subset of a national-scale geochemical survey. Results show that pathfinders for the Coles Hill deposit include light rare earth elements (La and Ce), which, when normalised by their Al content, are correlated with U/Al, and elevated Th/Al values, which are not correlated with U/Al, supporting decoupling of U from Th during soil generation. These results can be used in genetic and weathering models of the Coles Hill deposit, and can also be applied to future prospecting for similar U deposits in the eastern United States, and in regions with similar geological/climatic conditions.

Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study

PubMed Central

Liu, Peng; Qin, Wei; Wang, Jingjing; Zeng, Fang; Zhou, Guangyu; Wen, Haixia; von Deneen, Karen M.; Liang, Fanrong; Gong, Qiyong; Tian, Jie

2013-01-01

Background Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neural basis of FD. The main purpose of the current study was thereby to characterize the distinct patterns of resting-state function between FD patients and healthy controls (HCs). Methodology/Principal Findings Thirty FD patients and thirty HCs were enrolled and experienced 5-mintue resting-state scanning. Based on the support vector machine (SVM), we applied multivariate pattern analysis (MVPA) to investigate the differences of resting-state function mapped by regional homogeneity (ReHo). A classifier was designed by using the principal component analysis and the linear SVM. Permutation test was then employed to identify the significant contribution to the final discrimination. The results displayed that the mean classifier accuracy was 86.67%, and highly discriminative brain regions mainly included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), supplementary motor area (SMA), temporal pole (TP), insula, anterior/middle cingulate cortex (ACC/MCC), thalamus, hippocampus (HIPP)/parahippocamus (ParaHIPP) and cerebellum. Correlation analysis revealed significant correlations between ReHo values in certain regions of interest (ROI) and the FD symptom severity and/or duration, including the positive correlations between the dmPFC, pACC and the symptom severity; whereas, the positive correlations between the MCC, OFC, insula, TP and FD duration. Conclusions These findings indicated that significantly distinct patterns existed between FD patients and HCs during the resting-state, which could expand our understanding of the neural basis of FD. Meanwhile, our results possibly showed potential feasibility of functional magnetic resonance imaging diagnostic assay for FD. PMID:23874543

Charlson Comorbidity Index, inappropriate medication use and cognitive impairment : Bermuda Triangle.

PubMed

Silay, Kamile; Yalcin, Ahmet; Akinci, Sema; Gursoy, Fatma Gul; Sener Dede, Didem

2017-11-01

The aim is to evaluate the association between the Charlson Comorbidity Index (CCI), polypharmacy, inappropriate medication use and cognitive impairment in long-term care facility patients. A cross-sectional study including 105 long-term care facility residents was performed. The Charlson Comorbidity Index (CCI) was used. Inappropriate drug use (IDU) was defined according to the STOPP (Screening Tool of Older People's Prescriptions) criteria. Univariate analysis to identify variables associated with patient outcome related with cognitive impairment was investigated with χ 2 , Pearson correlation, Fisher exact, and Mann-Whitney U test where appropriate. For the multivariate analysis, the possible factors identified with univariate analysis were further entered into logistic regression analysis. A significant difference was found between gender, CCI and cognitive impairment (p = 0.038, p = 0.01). While every one point increment in the CCI increases the risk of cognitive impairment 3.1 fold (95% CI = 1.8-5.4, p < 0.001), hypertension increases the risk 12 fold (95% CI = 2.5-67.8, p = 0.002). While the correlation between Mini-Mental Status Examination (MMSE) score and polypharmacy is significant (p = 0.015), the correlation between MMSE and IDU was insignificant (p = 0.739). The association of urogenital system drugs and dementia was significant (p = 0.044). Comorbidities, especially hypertension and old age, are risk factors for cognitive impairment. Polypharmacy correlates with MMSE and is considered a risk factor for cognitive impairment. Inappropriate medication use is high among long-term care facility residents. More studies on large cohorts are needed regarding optimal drug prescription and detection of specific drugs that may have an impact on cognitive performance.

Identification of Putative Genes Involved in Limonoids Biosynthesis in Citrus by Comparative Transcriptomic Analysis

PubMed Central

Wang, Fusheng; Wang, Mei; Liu, Xiaona; Xu, Yuanyuan; Zhu, Shiping; Shen, Wanxia; Zhao, Xiaochun

2017-01-01

Limonoids produced by citrus are a group of highly bioactive secondary metabolites which provide health benefits for humans. Currently there is a lack of information derived from research on the genetic mechanisms controlling the biosynthesis of limonoids, which has limited the improvement of citrus for high production of limonoids. In this study, the transcriptome sequences of leaves, phloems and seeds of pummelo (Citrus grandis (L.) Osbeck) at different development stages with variances in limonoids contents were used for digital gene expression profiling analysis in order to identify the genes corresponding to the biosynthesis of limonoids. Pair-wise comparison of transcriptional profiles between different tissues identified 924 differentially expressed genes commonly shared between them. Expression pattern analysis suggested that 382 genes from three conjunctive groups of K-means clustering could be possibly related to the biosynthesis of limonoids. Correlation analysis with the samples from different genotypes, and different developing tissues of the citrus revealed that the expression of 15 candidate genes were highly correlated with the contents of limonoids. Among them, the cytochrome P450s (CYP450s) and transcriptional factor MYB demonstrated significantly high correlation coefficients, which indicated the importance of those genes on the biosynthesis of limonoids. CiOSC gene encoding the critical enzyme oxidosqualene cyclase (OSC) for biosynthesis of the precursor of triterpene scaffolds was found positively corresponding to the accumulation of limonoids during the development of seeds. Suppressing the expression of CiOSC with VIGS (Virus-induced gene silencing) demonstrated that the level of gene silencing was significantly correlated to the reduction of limonoids contents. The results indicated that the CiOSC gene plays a pivotal role in biosynthesis of limonoids. PMID:28553308

Chemosensory characteristics of regional Vidal icewines from China and Canada.

PubMed

Huang, Ling; Ma, Yue; Tian, Xin; Li, Ji-Ming; Li, Lan-Xiao; Tang, Ke; Xu, Yan

2018-09-30

This work aimed to compare the flavor characteristics of Vidal icewines from China and Canada and to establish relationships between sensory descriptors and chemical composition. Descriptive analysis was performed with a trained panel to obtain the sensory profiles. Thirty important aroma-active compounds were quantified by four different methodologies. Partial least squares discriminant analysis was used to identify candidate compounds, which were unique to certain sensory descriptors. The sensory profiles of icewines from China were characterized by nut and honey aromas, while icewines from Canada expressed caramel and rose aromas. Nut and honey aromas had a close correlation with 1-hexanol, isoamyl acetate, phenethyl acetate and phenylethyl alcohol. Caramel aroma was correlated with ethyl esters and lactones and rose aroma was correlated with terpenes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effect of 21-day head down bed rest on urine proteins related to endothelium: Correlations with changes in carbohydrate metabolism

NASA Astrophysics Data System (ADS)

Kashirina, D.; Pastushkova, L.; Custaud, M. A.; Dobrokhotov, I.; Brzhozovsky, A.; Navasiolava, N.; Nosovsky, A.; Kononikhin, A.; Nikolaev, E.; Larina, I.

2017-08-01

We performed liquid chromatography-mass spectrometric study of the urine proteome in 8 healthy volunteers aged between 20 and 44 y.o. who have completed 21-day head-down bed rest. ANDSystem software which builds associative networks was used to identify the urinary proteins functionally related to the endothelium. We identified 7 endothelium-related biological processes, directly linked to 13 urine proteins. We performed manual annotation of the proteins which were the most important in terms of endothelial functions. Analysis of the correlations with biochemical variables revealed a positive correlation between fasting blood glucose and the following urine proteins: albumin, CD44 antigen, endothelial protein C receptor, mucin-1, osteopontin, receptor tyrosine kinase. As well, we found a positive correlation between HOMA-insulin resistance index and the following urine proteins: endothelial protein C receptor and syndecan-4. These results might suggest the involvement of above-mentioned proteins in glucose metabolism and their participation in the response to changes in blood glucose level.

Correlation approach to identify coding regions in DNA sequences

NASA Technical Reports Server (NTRS)

Ossadnik, S. M.; Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Peng, C. K.; Simons, M.; Stanley, H. E.

1994-01-01

Recently, it was observed that noncoding regions of DNA sequences possess long-range power-law correlations, whereas coding regions typically display only short-range correlations. We develop an algorithm based on this finding that enables investigators to perform a statistical analysis on long DNA sequences to locate possible coding regions. The algorithm is particularly successful in predicting the location of lengthy coding regions. For example, for the complete genome of yeast chromosome III (315,344 nucleotides), at least 82% of the predictions correspond to putative coding regions; the algorithm correctly identified all coding regions larger than 3000 nucleotides, 92% of coding regions between 2000 and 3000 nucleotides long, and 79% of coding regions between 1000 and 2000 nucleotides. The predictive ability of this new algorithm supports the claim that there is a fundamental difference in the correlation property between coding and noncoding sequences. This algorithm, which is not species-dependent, can be implemented with other techniques for rapidly and accurately locating relatively long coding regions in genomic sequences.

Correlation between automatic detection of malaria on thin film and experts' parasitaemia scores

NASA Astrophysics Data System (ADS)

Sunarko, Budi; Williams, Simon; Prescott, William R.; Byker, Scott M.; Bottema, Murk J.

2017-03-01

An algorithm was developed to diagnose the presence of malaria and to estimate the depth of infection by automatically counting individual normal and infected erythrocytes in images of thin blood smears. During the training stage, the parameters of the algorithm were optimized to maximize correlation with estimates of parasitaemia from expert human observers. The correlation was tested on a set of 1590 images from seven thin film blood smears. The correlation between the results from the algorithm and expert human readers was r = 0.836. Results indicate that reliable estimates of parasitaemia may be achieved by computational image analysis methods applied to images of thin film smears. Meanwhile, compared to biological experiments, the algorithm fitted well the three high parasitaemia slides and a mid-level parasitaemia slide, and overestimated the three low parasitaemia slides. To improve the parasitaemia estimation, the sources of the overestimation were identified. Emphasis is laid on the importance of further research in order to identify parasites independently of their erythrocyte hosts

A Meta-Analysis of Mathematics and Working Memory: Moderating Effects of Working Memory Domain, Type of Mathematics Skill, and Sample Characteristics

ERIC Educational Resources Information Center

Peng, Peng; Namkung, Jessica; Barnes, Marcia; Sun, Congying

2016-01-01

The purpose of this meta-analysis was to determine the relation between mathematics and working memory (WM) and to identify possible moderators of this relation including domains of WM, types of mathematics skills, and sample type. A meta-analysis of 110 studies with 829 effect sizes found a significant medium correlation of mathematics and WM, r…

The correlation between obstructive sleep apnea and diabetic neuropathy: A meta-analysis.

PubMed

Gu, Xiandong; Luo, Xuming; Wang, Xiongbiao; Tang, Jihong; Yang, Wei; Cai, Zhuying

2018-05-01

The aim of this study was to explore the correlation between obstructive sleep apnea (OSA) and diabetic neuropathy. After working out searching strategy, literatures were screened from the electronic databases: PubMed, Embase, and the Cochrane library. R 3.12 was utilized to perform meta-analysis, and odds ratio (OR) and its 95% confidence interval (CI) were used to present effect size. Heterogeneity was assessed by χ 2 -based Q test and I 2 statistics. Publication bias was estimated by Egger's test and sensitivity was evaluated by leave one out methods. According to the criteria, a total of 11 studies with 1842 patients were enrolled in this study. With a significant heterogeneity (Q=31.83, I 2 =68.60%), the random effects model was utilized to assess the effect size of pooled data. A remarkable correlation was identified OSA and diabetic neuropathy (OR=1.84, 95% CI: 1.18-2.87) without publication bias (t=1.68, P=0.13). Meanwhile, the result of leave one out performed a well sensitivity. Moreover, the subgroup analyses presented that OSA was significantly correlated with type 1 diabetic neuropathy (OR=1.97, 95% CI: 1.19-3.25), but no remarkable correlation was identified between OSA and type 1 (OR=1.84, 95% CI: 0.86-3.93) or 1+2 (OR=1.30, 95% CI: 0.43-3.92) diabetic neuropathy. OSA was significantly correlated with neuropathy in type 1 diabetes, but not in type 2 and type 1+2 diabetes. Copyright © 2018. Published by Elsevier Ltd.

Synergistic Modification Induced Specific Recognition between Histone and TRIM24 via Fluctuation Correlation Network Analysis

NASA Astrophysics Data System (ADS)

Zhang, Jinmai; Luo, Huajie; Liu, Hao; Ye, Wei; Luo, Ray; Chen, Hai-Feng

2016-04-01

Histone modification plays a key role in gene regulation and gene expression. TRIM24 as a histone reader can recognize histone modification. However the specific recognition mechanism between TRIM24 and histone modification is unsolved. Here, systems biology method of dynamics correlation network based on molecular dynamics simulation was used to answer the question. Our network analysis shows that the dynamics correlation network of H3K23ac is distinctly different from that of wild type and other modifications. A hypothesis of “synergistic modification induced recognition” is then proposed to link histone modification and TRIM24 binding. These observations were further confirmed from community analysis of networks with mutation and network perturbation. Finally, a possible recognition pathway is also identified based on the shortest path search for H3K23ac. Significant difference of recognition pathway was found among different systems due to methylation and acetylation modifications. The analysis presented here and other studies show that the dynamic network-based analysis might be a useful general strategy to study the biology of protein post-translational modification and associated recognition.

Oscillation Baselining and Analysis Tool

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

PNNL developed a new tool for oscillation analysis and baselining. This tool has been developed under a new DOE Grid Modernization Laboratory Consortium (GMLC) Project (GM0072 - “Suite of open-source applications and models for advanced synchrophasor analysis”) and it is based on the open platform for PMU analysis. The Oscillation Baselining and Analysis Tool (OBAT) performs the oscillation analysis and identifies modes of oscillations (frequency, damping, energy, and shape). The tool also does oscillation event baselining (fining correlation between oscillations characteristics and system operating conditions).

Connecting Different Data Sources to Assess the Interconnections between Biosecurity, Health, Welfare, and Performance in Commercial Pig Farms in Great Britain.

PubMed

Pandolfi, Fanny; Edwards, Sandra A; Maes, Dominiek; Kyriazakis, Ilias

2018-01-01

This study aimed to provide an overview of the interconnections between biosecurity, health, welfare, and performance in commercial pig farms in Great Britain. We collected on-farm data about the level of biosecurity and animal performance in 40 fattening pig farms and 28 breeding pig farms between 2015 and 2016. We identified interconnections between these data, slaughterhouse health indicators, and welfare indicator records in fattening pig farms. After achieving the connections between databases, a secondary data analysis was performed to assess the interconnections between biosecurity, health, welfare, and performance using correlation analysis, principal component analysis, and hierarchical clustering. Although we could connect the different data sources the final sample size was limited, suggesting room for improvement in database connection to conduct secondary data analyses. The farm biosecurity scores ranged from 40 to 90 out of 100, with internal biosecurity scores being lower than external biosecurity scores. Our analysis suggested several interconnections between health, welfare, and performance. The initial correlation analysis showed that the prevalence of lameness and severe tail lesions was associated with the prevalence of enzootic pneumonia-like lesions and pyaemia, and the prevalence of severe body marks was associated with several disease indicators, including peritonitis and milk spots ( r  > 0.3; P  < 0.05). Higher average daily weight gain (ADG) was associated with lower prevalence of pleurisy ( r  > 0.3; P  < 0.05), but no connection was identified between mortality and health indicators. A subsequent cluster analysis enabled identification of patterns which considered concurrently indicators of health, welfare, and performance. Farms from cluster 1 had lower biosecurity scores, lower ADG, and higher prevalence of several disease and welfare indicators. Farms from cluster 2 had higher biosecurity scores than cluster 1, but a higher prevalence of pigs requiring hospitalization and lameness which confirmed the correlation between biosecurity and the prevalence of pigs requiring hospitalization ( r  > 0.3; P  < 0.05). Farms from cluster 3 had higher biosecurity, higher ADG, and lower prevalence for some disease and welfare indicators. The study suggests a smaller impact of biosecurity on issues such as mortality, prevalence of lameness, and pig requiring hospitalization. The correlations and the identified clusters suggested the importance of animal welfare for the pig industry.

Multivariate analysis of mixed contaminants (PAHs and heavy metals) at manufactured gas plant site soils.

PubMed

Thavamani, Palanisami; Megharaj, Mallavarapu; Naidu, Ravi

2012-06-01

Principal component analysis (PCA) was used to provide an overview of the distribution pattern of polycyclic aromatic hydrocarbons (PAHs) and heavy metals in former manufactured gas plant (MGP) site soils. PCA is the powerful multivariate method to identify the patterns in data and expressing their similarities and differences. Ten PAHs (naphthalene, acenapthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]pyrene) and four toxic heavy metals - lead (Pb), cadmium (Cd), chromium (Cr) and zinc (Zn) - were detected in the site soils. PAH contamination was contributed equally by both low and high molecular weight PAHs. PCA was performed using the varimax rotation method in SPSS, 17.0. Two principal components accounting for 91.7% of the total variance was retained using scree test. Principle component 1 (PC1) substantially explained the dominance of PAH contamination in the MGP site soils. All PAHs, except anthracene, were positively correlated in PC1. There was a common thread in high molecular weight PAHs loadings, where the loadings were inversely proportional to the hydrophobicity and molecular weight of individual PAHs. Anthracene, which was less correlated with other individual PAHs, deviated well from the origin which can be ascribed to its lower toxicity and different origin than its isomer phenanthrene. Among the four major heavy metals studied in MGP sites, Pb, Cd and Cr were negatively correlated in PC1 but showed strong positive correlation in principle component 2 (PC2). Although metals may not have originated directly from gaswork processes, the correlation between PAHs and metals suggests that the materials used in these sites may have contributed to high concentrations of Pb, Cd, Cr and Zn. Thus, multivariate analysis helped to identify the sources of PAHs, heavy metals and their association in MGP site, and thereby better characterise the site risk, which would not be possible if one uses chemical analysis alone.

Identifier mapping performance for integrating transcriptomics and proteomics experimental results

PubMed Central

2011-01-01

Background Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit. Results We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed. Conclusions The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging. PMID:21619611

Down-Regulation of Olfactory Receptors in Response to Traumatic Brain Injury Promotes Risk for Alzheimers Disease

DTIC Science & Technology

2015-12-01

group assignment of samples in unsupervised hierarchical clustering by the Unweighted Pair-Group Method using Arithmetic averages ( UPGMA ) based on...log2 transformed MAS5.0 signal values; probe set clustering was performed by the UPGMA method using Cosine correlation as the similarity met- ric. For...differentially-regulated genes identified were subjected to unsupervised hierarchical clustering analysis using the UPGMA algorithm with cosine correlation as

Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses.

PubMed

Ogawa, Takeshi; Aihara, Takatsugu; Shimokawa, Takeaki; Yamashita, Okito

2018-04-24

Creative insight occurs with an "Aha!" experience when solving a difficult problem. Here, we investigated large-scale networks associated with insight problem solving. We recruited 232 healthy participants aged 21-69 years old. Participants completed a magnetic resonance imaging study (MRI; structural imaging and a 10 min resting-state functional MRI) and an insight test battery (ITB) consisting of written questionnaires (matchstick arithmetic task, remote associates test, and insight problem solving task). To identify the resting-state functional connectivity (RSFC) associated with individual creative insight, we conducted an exploratory voxel-based morphometry (VBM)-constrained RSFC analysis. We identified positive correlations between ITB score and grey matter volume (GMV) in the right insula and middle cingulate cortex/precuneus, and a negative correlation between ITB score and GMV in the left cerebellum crus 1 and right supplementary motor area. We applied seed-based RSFC analysis to whole brain voxels using the seeds obtained from the VBM and identified insight-positive/negative connections, i.e. a positive/negative correlation between the ITB score and individual RSFCs between two brain regions. Insight-specific connections included motor-related regions whereas creative-common connections included a default mode network. Our results indicate that creative insight requires a coupling of multiple networks, such as the default mode, semantic and cerebral-cerebellum networks.

Parcellating an individual subject's cortical and subcortical brain structures using snowball sampling of resting-state correlations.

PubMed

Wig, Gagan S; Laumann, Timothy O; Cohen, Alexander L; Power, Jonathan D; Nelson, Steven M; Glasser, Matthew F; Miezin, Francis M; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2014-08-01

We describe methods for parcellating an individual subject's cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability-reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individual's brain into functionally meaningful units. © The Author 2013. Published by Oxford University Press.

Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development.

PubMed

Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

2014-12-01

We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named "fight-club hubs" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named "switch genes" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. © 2014 American Society of Plant Biologists. All rights reserved.

Integrated Network Analysis Identifies Fight-Club Nodes as a Class of Hubs Encompassing Key Putative Switch Genes That Induce Major Transcriptome Reprogramming during Grapevine Development[W][OPEN

PubMed Central

Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

2014-01-01

We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named “fight-club hubs” characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named “switch genes” was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. PMID:25490918

Chromatogram-Bioactivity Correlation-Based Discovery and Identification of Three Bioactive Compounds Affecting Endothelial Function in Ginkgo Biloba Extract.

PubMed

Liu, Hong; Tan, Li-Ping; Huang, Xin; Liao, Yi-Qiu; Zhang, Wei-Jian; Li, Pei-Bo; Wang, Yong-Gang; Peng, Wei; Wu, Zhong; Su, Wei-Wei; Yao, Hong-Liang

2018-05-03

Discovery and identification of three bioactive compounds affecting endothelial function in Ginkgo biloba Extract (GBE) based on chromatogram-bioactivity correlation analysis. Three portions were separated from GBE via D101 macroporous resin and then re-combined to prepare nine GBE samples. 21 compounds in GBE samples were identified through UFLC-DAD-Q-TOF-MS/MS. Correlation analysis between compounds differences and endothelin-1 (ET-1) in vivo in nine GBE samples was conducted. The analysis results indicated that three bioactive compounds had close relevance to ET-1: Kaempferol-3- O -α-l-glucoside, 3- O -{2- O -{6- O -[P-OH-trans-cinnamoyl]-β-d-glucosyl}-α-rhamnosyl} Quercetin isomers, and 3- O -{2- O -{6- O -[P-OH-trans-cinnamoyl]-β-d-glucosyl}-α-rhamnosyl} Kaempferide. The discovery of bioactive compounds could provide references for the quality control and novel pharmaceuticals development of GRE. The present work proposes a feasible chromatogram-bioactivity correlation based approach to discover the compounds and define their bioactivities for the complex multi-component systems.

Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks.

PubMed

Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

2013-01-01

Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.

Frequency-phase analysis of resting-state functional MRI

PubMed Central

Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

2017-01-01

We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522

Gaussian graphical modeling reveals specific lipid correlations in glioblastoma cells

NASA Astrophysics Data System (ADS)

Mueller, Nikola S.; Krumsiek, Jan; Theis, Fabian J.; Böhm, Christian; Meyer-Bäse, Anke

2011-06-01

Advances in high-throughput measurements of biological specimens necessitate the development of biologically driven computational techniques. To understand the molecular level of many human diseases, such as cancer, lipid quantifications have been shown to offer an excellent opportunity to reveal disease-specific regulations. The data analysis of the cell lipidome, however, remains a challenging task and cannot be accomplished solely based on intuitive reasoning. We have developed a method to identify a lipid correlation network which is entirely disease-specific. A powerful method to correlate experimentally measured lipid levels across the various samples is a Gaussian Graphical Model (GGM), which is based on partial correlation coefficients. In contrast to regular Pearson correlations, partial correlations aim to identify only direct correlations while eliminating indirect associations. Conventional GGM calculations on the entire dataset can, however, not provide information on whether a correlation is truly disease-specific with respect to the disease samples and not a correlation of control samples. Thus, we implemented a novel differential GGM approach unraveling only the disease-specific correlations, and applied it to the lipidome of immortal Glioblastoma tumor cells. A large set of lipid species were measured by mass spectrometry in order to evaluate lipid remodeling as a result to a combination of perturbation of cells inducing programmed cell death, while the other perturbations served solely as biological controls. With the differential GGM, we were able to reveal Glioblastoma-specific lipid correlations to advance biomedical research on novel gene therapies.

Genomic expression analysis of rat chromosome 4 for skeletal traits at femoral neck.

PubMed

Alam, Imranul; Sun, Qiwei; Liu, Lixiang; Koller, Daniel L; Liu, Yunlong; Edenberg, Howard J; Econs, Michael J; Foroud, Tatiana; Turner, Charles H

2008-10-08

Hip fracture is the most devastating osteoporotic fracture type with significant morbidity and mortality. Several studies in humans and animal models identified chromosomal regions linked to hip size and bone mass. Previously, we identified that the region of 4q21-q41 on rat chromosome (Chr) 4 harbors multiple femoral neck quantitative trait loci (QTLs) in inbred Fischer 344 (F344) and Lewis (LEW) rats. The purpose of this study is to identify the candidate genes for femoral neck structure and density by correlating gene expression in the proximal femur with the femoral neck phenotypes linked to the QTLs on Chr 4. RNA was extracted from proximal femora of 4-wk-old rats from F344 and LEW strains, and two other strains, Copenhagen 2331 and Dark Agouti, were used as a negative control. Microarray analysis was performed using Affymetrix Rat Genome 230 2.0 arrays. A total of 99 genes in the 4q21-q41 region were differentially expressed (P < 0.05) among all strains of rats with a false discovery rate <10%. These 99 genes were then ranked based on the strength of correlation between femoral neck phenotypes measured in F2 animals, homozygous for a particular strain's allele at the Chr 4 QTL and the expression level of the gene in that strain. A total of 18 candidate genes were strongly correlated (r(2) > 0.50) with femoral neck width and prioritized for further analysis. Quantitative PCR analysis confirmed 14 of 18 of the candidate genes. Ingenuity pathway analysis revealed several direct or indirect relationships among the candidate genes related to angiogenesis (VEGF), bone growth (FGF2), bone formation (IGF2 and IGF2BP3), and resorption (TNF). This study provides a shortened list of genetic determinants of skeletal traits at the hip and may lead to novel approaches for prevention and treatment of hip fracture.

Genomic expression analysis of rat chromosome 4 for skeletal traits at femoral neck

PubMed Central

Alam, Imranul; Sun, Qiwei; Liu, Lixiang; Koller, Daniel L.; Liu, Yunlong; Edenberg, Howard J.; Econs, Michael J.; Foroud, Tatiana; Turner, Charles H.

2008-01-01

Hip fracture is the most devastating osteoporotic fracture type with significant morbidity and mortality. Several studies in humans and animal models identified chromosomal regions linked to hip size and bone mass. Previously, we identified that the region of 4q21-q41 on rat chromosome (Chr) 4 harbors multiple femoral neck quantitative trait loci (QTLs) in inbred Fischer 344 (F344) and Lewis (LEW) rats. The purpose of this study is to identify the candidate genes for femoral neck structure and density by correlating gene expression in the proximal femur with the femoral neck phenotypes linked to the QTLs on Chr 4. RNA was extracted from proximal femora of 4-wk-old rats from F344 and LEW strains, and two other strains, Copenhagen 2331 and Dark Agouti, were used as a negative control. Microarray analysis was performed using Affymetrix Rat Genome 230 2.0 arrays. A total of 99 genes in the 4q21-q41 region were differentially expressed (P < 0.05) among all strains of rats with a false discovery rate <10%. These 99 genes were then ranked based on the strength of correlation between femoral neck phenotypes measured in F2 animals, homozygous for a particular strain's allele at the Chr 4 QTL and the expression level of the gene in that strain. A total of 18 candidate genes were strongly correlated (r2 > 0.50) with femoral neck width and prioritized for further analysis. Quantitative PCR analysis confirmed 14 of 18 of the candidate genes. Ingenuity pathway analysis revealed several direct or indirect relationships among the candidate genes related to angiogenesis (VEGF), bone growth (FGF2), bone formation (IGF2 and IGF2BP3), and resorption (TNF). This study provides a shortened list of genetic determinants of skeletal traits at the hip and may lead to novel approaches for prevention and treatment of hip fracture. PMID:18728226

Comparing Pearson, Spearman and Hoeffding's D measure for gene expression association analysis.

PubMed

Fujita, André; Sato, João Ricardo; Demasi, Marcos Angelo Almeida; Sogayar, Mari Cleide; Ferreira, Carlos Eduardo; Miyano, Satoru

2009-08-01

DNA microarrays have become a powerful tool to describe gene expression profiles associated with different cellular states, various phenotypes and responses to drugs and other extra- or intra-cellular perturbations. In order to cluster co-expressed genes and/or to construct regulatory networks, definition of distance or similarity between measured gene expression data is usually required, the most common choices being Pearson's and Spearman's correlations. Here, we evaluate these two methods and also compare them with a third one, namely Hoeffding's D measure, which is used to infer nonlinear and non-monotonic associations, i.e. independence in a general sense. By comparing three different variable association approaches, namely Pearson's correlation, Spearman's correlation and Hoeffding's D measure, we aimed at assessing the most appropriate one for each purpose. Using simulations, we demonstrate that the Hoeffding's D measure outperforms Pearson's and Spearman's approaches in identifying nonlinear associations. Our results demonstrate that Hoeffding's D measure is less sensitive to outliers and is a more powerful tool to identify nonlinear and non-monotonic associations. We have also applied Hoeffding's D measure in order to identify new putative genes associated with tp53. Therefore, we propose the Hoeffding's D measure to identify nonlinear associations between gene expression profiles.

Individual, Social, and Environmental Correlates of Active Transportation Patterns in French Women

PubMed Central

Perchoux, Camille; Enaux, Christophe; Oppert, Jean-Michel; Menai, Mehdi; Charreire, Hélène; Salze, Paul; Weber, Christiane; Hercberg, Serge; Feuillet, Thierry; Hess, Franck; Roda, Célina; Simon, Chantal

2017-01-01

The objectives were (1) to define physical activity (PA) and sedentary behaviors (SB) patterns in daily life contexts (work, leisure, and transportation) in French working women from NutriNet-Santé web-cohort and (2) to identify pattern(s) of active transportation and their individual, social, and environmental correlates. 23,432 participants completed two questionnaires to evaluate PA and SB in daily life contexts and individual representations of residential neighborhood and transportation modes. Hierarchical cluster analysis was performed which identified 6 distinct movement behavior patterns: (i) active occupation, high sedentary leisure, (ii) sedentary occupation, low leisure, (iii) sedentary transportation, (iv) sedentary occupation and leisure, (v) active transportation, and (vi) active leisure. Multinomial logistic regressions were performed to identify correlates of the “active transportation” cluster. The perceived environmental characteristics positively associated with “active transportation” included “high availability of destinations around home,” “presence of bicycle paths,” and “low traffic.” A “positive image of walking/cycling,” the “individual feeling of being physically active,” and a “high use of active transport modes by relatives/friends” were positively related to “active transportation,” identified as a unique pattern regarding individual and environmental correlates. Identification of PA and SB context-specific patterns will help to understand movement behaviors' complexity and to design interventions to promote active transportation in specific subgroups. PMID:28717653

Metabolomic analysis of insulin resistance across different mouse strains and diets.

PubMed

Stöckli, Jacqueline; Fisher-Wellman, Kelsey H; Chaudhuri, Rima; Zeng, Xiao-Yi; Fazakerley, Daniel J; Meoli, Christopher C; Thomas, Kristen C; Hoffman, Nolan J; Mangiafico, Salvatore P; Xirouchaki, Chrysovalantou E; Yang, Chieh-Hsin; Ilkayeva, Olga; Wong, Kari; Cooney, Gregory J; Andrikopoulos, Sofianos; Muoio, Deborah M; James, David E

2017-11-24

Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Contribution to the understanding of how principal component analysis-derived dietary patterns emerge from habitual data on food consumption.

PubMed

Schwedhelm, Carolina; Iqbal, Khalid; Knüppel, Sven; Schwingshackl, Lukas; Boeing, Heiner

2018-02-01

Principal component analysis (PCA) is a widely used exploratory method in epidemiology to derive dietary patterns from habitual diet. Such dietary patterns seem to originate from intakes on multiple days and eating occasions. Therefore, analyzing food intake of study populations with different levels of food consumption can provide additional insights as to how habitual dietary patterns are formed. We analyzed the food intake data of German adults in terms of the relations among food groups from three 24-h dietary recalls (24hDRs) on the habitual, single-day, and main-meal levels, and investigated the contribution of each level to the formation of PCA-derived habitual dietary patterns. Three 24hDRs were collected in 2010-2012 from 816 adults for an European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam subcohort study. We identified PCA-derived habitual dietary patterns and compared cross-sectional food consumption data in terms of correlation (Spearman), consistency (intraclass correlation coefficient), and frequency of consumption across all days and main meals. Contribution to the formation of the dietary patterns was obtained through Spearman correlation of the dietary pattern scores. Among the meals, breakfast appeared to be the most consistent eating occasion within individuals. Dinner showed the strongest correlations with "Prudent" (Spearman correlation = 0.60), "Western" (Spearman correlation = 0.59), and "Traditional" (Spearman correlation = 0.60) dietary patterns identified on the habitual level, and lunch showed the strongest correlations with the "Cereals and legumes" (Spearman correlation = 0.60) habitual dietary pattern. Higher meal consistency was related to lower contributions to the formation of PCA-derived habitual dietary patterns. Absolute amounts of food consumption did not strongly conform to the habitual dietary patterns by meals, suggesting that these patterns are formed by complex combinations of variable food consumption across meals. Dinner showed the highest contribution to the formation of habitual dietary patterns. This study provided information about how PCA-derived dietary patterns are formed and how they could be influenced.

Nonlinear dynamic-based analysis of severe dysphonia in patients with vocal fold scar and sulcus vocalis

PubMed Central

Choi, Seong Hee; Zhang, Yu; Jiang, Jack J.; Bless, Diane M.; Welham, Nathan V.

2011-01-01

Objective The primary goal of this study was to evaluate a nonlinear dynamic approach to the acoustic analysis of dysphonia associated with vocal fold scar and sulcus vocalis. Study Design Case-control study. Methods Acoustic voice samples from scar/sulcus patients and age/sex-matched controls were analyzed using correlation dimension (D2) and phase plots, time-domain based perturbation indices (jitter, shimmer, signal-to-noise ratio [SNR]), and an auditory-perceptual rating scheme. Signal typing was performed to identify samples with bifurcations and aperiodicity. Results Type 2 and 3 acoustic signals were highly represented in the scar/sulcus patient group. When data were analyzed irrespective of signal type, all perceptual and acoustic indices successfully distinguished scar/sulcus patients from controls. Removal of type 2 and 3 signals eliminated the previously identified differences between experimental groups for all acoustic indices except D2. The strongest perceptual-acoustic correlation in our dataset was observed for SNR; the weakest correlation was observed for D2. Conclusions These findings suggest that D2 is inferior to time-domain based perturbation measures for the analysis of dysphonia associated with scar/sulcus; however, time-domain based algorithms are inherently susceptible to inflation under highly aperiodic (i.e., type 2 and 3) signal conditions. Auditory-perceptual analysis, unhindered by signal aperiodicity, is therefore a robust strategy for distinguishing scar/sulcus patient voices from normal voices. Future acoustic analysis research in this area should consider alternative (e.g., frequency- and quefrency-domain based) measures alongside additional nonlinear approaches. PMID:22516315

Photogrammetric Analysis of Attractiveness in Indian Faces

PubMed Central

Duggal, Shveta; Kapoor, DN; Verma, Santosh; Sagar, Mahesh; Lee, Yung-Seop; Moon, Hyoungjin

2016-01-01

Background The objective of this study was to assess the attractive facial features of the Indian population. We tried to evaluate subjective ratings of facial attractiveness and identify which facial aesthetic subunits were important for facial attractiveness. Methods A cross-sectional study was conducted of 150 samples (referred to as candidates). Frontal photographs were analyzed. An orthodontist, a prosthodontist, an oral surgeon, a dentist, an artist, a photographer and two laymen (estimators) subjectively evaluated candidates' faces using visual analog scale (VAS) scores. As an objective method for facial analysis, we used balanced angular proportional analysis (BAPA). Using SAS 10.1 (SAS Institute Inc.), the Turkey's studentized range test and Pearson correlation analysis were performed to detect between-group differences in VAS scores (Experiment 1), to identify correlations between VAS scores and BAPA scores (Experiment 2), and to analyze the characteristic features of facial attractiveness and gender differences (Experiment 3); the significance level was set at P=0.05. Results Experiment 1 revealed some differences in VAS scores according to professional characteristics. In Experiment 2, BAPA scores were found to behave similarly to subjective ratings of facial beauty, but showed a relatively weak correlation coefficient with the VAS scores. Experiment 3 found that the decisive factors for facial attractiveness were different for men and women. Composite images of attractive Indian male and female faces were constructed. Conclusions Our photogrammetric study, statistical analysis, and average composite faces of an Indian population provide valuable information about subjective perceptions of facial beauty and attractive facial structures in the Indian population. PMID:27019809

Identifying tectonic parameters that affect tsunamigenesis

NASA Astrophysics Data System (ADS)

van Zelst, I.; Brizzi, S.; Heuret, A.; Funiciello, F.; van Dinther, Y.

2016-12-01

The role of tectonics in tsunami generation is at present poorly understood. However, the fact thatsome regions produce more tsunamis than others indicates that tectonics could influencetsunamigenesis. Here, we complement a global earthquake database that contains geometrical,mechanical, and seismicity parameters of subduction zones with tsunami data. We statisticallyanalyse the database to identify the tectonic parameters that affect tsunamigenesis. The Pearson'sproduct-moment correlation coefficients reveal high positive correlations of 0.65 between,amongst others, the maximum water height of tsunamis and the seismic coupling in a subductionzone. However, these correlations are mainly caused by outliers. The Spearman's rank correlationcoefficient results in statistically significant correlations of 0.60 between the number of tsunamisin a subduction zone and subduction velocity (positive correlation) and the sediment thickness atthe trench (negative correlation). Interestingly, there is a positive correlation between the latter andtsunami magnitude. These bivariate statistical methods are extended to a binary decision tree(BDT) and multivariate analysis. Using the BDT, the tectonic parameters that distinguish betweensubduction zones with tsunamigenic and non-tsunamigenic earthquakes are identified. To assessphysical causality of the tectonic parameters with regard to tsunamigenesis, we complement ouranalysis by a numerical study of the most promising parameters using a geodynamic seismic cyclemodel. We show that the inclusion of sediments on the subducting plate results in an increase insplay fault activity, which could lead to larger vertical seafloor displacements due to their steeperdips and hence a larger tsunamigenic potential. We also show that the splay fault is the preferredrupture path for a strongly velocity strengthening friction regime in the shallow part of thesubduction zone, which again increases the tsunamigenic potential.

Key drivers for market penetration of biosimilars in Europe.

PubMed

Rémuzat, Cécile; Dorey, Julie; Cristeau, Olivier; Ionescu, Dan; Radière, Guerric; Toumi, Mondher

2017-01-01

Background & Objectives : Potential drivers and barriers of biosimilar uptake were mainly analysed through qualitative approaches. The study objective was to conduct a quantitative analysis and identify drivers of biosimilar uptake of all available biosimilars in the European Union (EU). Methods : A three-step process was established to identify key drivers for the uptake of biosimilars in the top 10 EU member states (MS) pharmaceutical markets (Belgium, France, Germany, Greece, Hungary, Italy, Poland, Spain, Sweden, and the UK): (1) literature review to identify incentive policies in place to enhance biosimilars adoption; (2) assessment of biosimilar market dynamics based on database analysis; (3) regression model analysis on price using the following explicative variables: incentive policies; price difference between the biosimilar and the originator product; distribution channel; generic uptake and generic price cut; pharmaceutical expenditure per capita; and market competition. Results : At the study cut-off date, 20 biosimilars were available on the market. Incentive policies applied to biosimilars were found to be heterogeneous across countries, and uptakes of biosimilars were also very heterogeneous between different therapeutic classes and countries. Results from the model demonstrated that incentive policies and the date of first biosimilar market entry were correlated to biosimilar uptake. Pharmaceutical expenditure per capita and the highest generic uptake were inversely correlated with biosimilar uptake. Average generic price discount over originator and the number of biosimilars showed a trend toward statistical significance for correlation with biosimilar uptake, but did not reach the significance threshold. Biosimilar price discount over original biologic price, the number of analogues, and the distribution channel were not correlated with the biosimilar uptake. Conclusions : Understanding drivers of biosimilar uptake becomes a critical issue to inform policy decision-makers. This study showed that incentive policies to enhance uptake remain an important driver of biosimilar penetration, while biosimilar price discounts have no impact. Future research is warranted when the biosimilar market gains maturity.

Key drivers for market penetration of biosimilars in Europe

PubMed Central

Rémuzat, Cécile; Dorey, Julie; Cristeau, Olivier; Ionescu, Dan; Radière, Guerric; Toumi, Mondher

2017-01-01

ABSTRACT Background & Objectives: Potential drivers and barriers of biosimilar uptake were mainly analysed through qualitative approaches. The study objective was to conduct a quantitative analysis and identify drivers of biosimilar uptake of all available biosimilars in the European Union (EU). Methods: A three-step process was established to identify key drivers for the uptake of biosimilars in the top 10 EU member states (MS) pharmaceutical markets (Belgium, France, Germany, Greece, Hungary, Italy, Poland, Spain, Sweden, and the UK): (1) literature review to identify incentive policies in place to enhance biosimilars adoption; (2) assessment of biosimilar market dynamics based on database analysis; (3) regression model analysis on price using the following explicative variables: incentive policies; price difference between the biosimilar and the originator product; distribution channel; generic uptake and generic price cut; pharmaceutical expenditure per capita; and market competition. Results: At the study cut-off date, 20 biosimilars were available on the market. Incentive policies applied to biosimilars were found to be heterogeneous across countries, and uptakes of biosimilars were also very heterogeneous between different therapeutic classes and countries. Results from the model demonstrated that incentive policies and the date of first biosimilar market entry were correlated to biosimilar uptake. Pharmaceutical expenditure per capita and the highest generic uptake were inversely correlated with biosimilar uptake. Average generic price discount over originator and the number of biosimilars showed a trend toward statistical significance for correlation with biosimilar uptake, but did not reach the significance threshold. Biosimilar price discount over original biologic price, the number of analogues, and the distribution channel were not correlated with the biosimilar uptake. Conclusions: Understanding drivers of biosimilar uptake becomes a critical issue to inform policy decision-makers. This study showed that incentive policies to enhance uptake remain an important driver of biosimilar penetration, while biosimilar price discounts have no impact. Future research is warranted when the biosimilar market gains maturity. PMID:28265349

Looking at the Brains behind Figurative Language--A Quantitative Meta-Analysis of Neuroimaging Studies on Metaphor, Idiom, and Irony Processing

ERIC Educational Resources Information Center

Bohrn, Isabel C.; Altmann, Ulrike; Jacobs, Arthur M.

2012-01-01

A quantitative, coordinate-based meta-analysis combined data from 354 participants across 22 fMRI studies and one positron emission tomography (PET) study to identify the differences in neural correlates of figurative and literal language processing, and to investigate the role of the right hemisphere (RH) in figurative language processing.…

Quantitation of absorbed or deposited materials on a substrate that measures energy deposition

DOEpatents

Grant, Patrick G.; Bakajin, Olgica; Vogel, John S.; Bench, Graham

2005-01-18

This invention provides a system and method for measuring an energy differential that correlates to quantitative measurement of an amount mass of an applied localized material. Such a system and method remains compatible with other methods of analysis, such as, for example, quantitating the elemental or isotopic content, identifying the material, or using the material in biochemical analysis.

Genetic overlap between diagnostic subtypes of ischemic stroke.

PubMed

Holliday, Elizabeth G; Traylor, Matthew; Malik, Rainer; Bevan, Steve; Falcone, Guido; Hopewell, Jemma C; Cheng, Yu-Ching; Cotlarciuc, Ioana; Bis, Joshua C; Boerwinkle, Eric; Boncoraglio, Giorgio B; Clarke, Robert; Cole, John W; Fornage, Myriam; Furie, Karen L; Ikram, M Arfan; Jannes, Jim; Kittner, Steven J; Lincz, Lisa F; Maguire, Jane M; Meschia, James F; Mosley, Thomas H; Nalls, Mike A; Oldmeadow, Christopher; Parati, Eugenio A; Psaty, Bruce M; Rothwell, Peter M; Seshadri, Sudha; Scott, Rodney J; Sharma, Pankaj; Sudlow, Cathie; Wiggins, Kerri L; Worrall, Bradford B; Rosand, Jonathan; Mitchell, Braxton D; Dichgans, Martin; Markus, Hugh S; Levi, Christopher; Attia, John; Wray, Naomi R

2015-03-01

Despite moderate heritability, the phenotypic heterogeneity of ischemic stroke has hampered gene discovery, motivating analyses of diagnostic subtypes with reduced sample sizes. We assessed evidence for a shared genetic basis among the 3 major subtypes: large artery atherosclerosis (LAA), cardioembolism, and small vessel disease (SVD), to inform potential cross-subtype analyses. Analyses used genome-wide summary data for 12 389 ischemic stroke cases (including 2167 LAA, 2405 cardioembolism, and 1854 SVD) and 62 004 controls from the Metastroke consortium. For 4561 cases and 7094 controls, individual-level genotype data were also available. Genetic correlations between subtypes were estimated using linear mixed models and polygenic profile scores. Meta-analysis of a combined LAA-SVD phenotype (4021 cases and 51 976 controls) was performed to identify shared risk alleles. High genetic correlation was identified between LAA and SVD using linear mixed models (rg=0.96, SE=0.47, P=9×10(-4)) and profile scores (rg=0.72; 95% confidence interval, 0.52-0.93). Between LAA and cardioembolism and SVD and cardioembolism, correlation was moderate using linear mixed models but not significantly different from zero for profile scoring. Joint meta-analysis of LAA and SVD identified strong association (P=1×10(-7)) for single nucleotide polymorphisms near the opioid receptor μ1 (OPRM1) gene. Our results suggest that LAA and SVD, which have been hitherto treated as genetically distinct, may share a substantial genetic component. Combined analyses of LAA and SVD may increase power to identify small-effect alleles influencing shared pathophysiological processes. © 2015 American Heart Association, Inc.

Neurointerventional Treatment in Acute Stroke. Whom to Treat? (Endovascular Treatment for Acute Stroke: Utility of THRIVE Score and HIAT Score for Patient Selection)

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

Fjetland, Lars, E-mail: lars.fjetland@lyse.net; Roy, Sumit, E-mail: sumit.roy@sus.no; Kurz, Kathinka D., E-mail: kathinka.dehli.kurz@sus.no

2013-10-15

Purpose: Intra-arterial therapy (IAT) is used increasingly as a treatment option for acute stroke caused by central large vessel occlusions. Despite high rates of recanalization, the clinical outcome is highly variable. The authors evaluated the Houston IAT (HIAT) and the totaled health risks in vascular events (THRIVE) score, two predicting scores designed to identify patients likely to benefit from IAT. Methods: Fifty-two patients treated at the Stavanger University Hospital with IAT from May 2009 to June 2012 were included in this study. We combined the scores in an additional analysis. We also performed an additional analysis according to high agemore » and evaluated the scores in respect of technical efficacy. Results: Fifty-two patients were evaluated by the THRIVE score and 51 by the HIAT score. We found a strong correlation between the level of predicted risk and the actual clinical outcome (THRIVE p = 0.002, HIAT p = 0.003). The correlations were limited to patients successfully recanalized and to patients <80 years. By combining the scores additional 14.3 % of the patients could be identified as poor candidates for IAT. Both scores were insufficient to identify patients with a good clinical outcome. Conclusions: Both scores showed a strong correlation to poor clinical outcome in patients <80 years. The specificity of the scores could be enhanced by combining them. Both scores were insufficient to identify patients with a good clinical outcome and showed no association to clinical outcome in patients aged {>=}80 years.« less

Sarcoidosis in an Italian province. Prevalence and environmental risk factors

PubMed Central

Beghè, Deborah; Dall’Asta, Luca; Garavelli, Claudia; Pastorelli, Augusto Alberto; Muscarella, Marilena; Saccani, Gloria; Aiello, Marina; Corradi, Massimo; Stacchini, Paolo; Chetta, Alfredo; Bertorelli, Giuseppina

2017-01-01

Background and aim Sarcoidosis is a systemic granulomatous inflammatory disease whose causes are still unknown and for which epidemiological data are often discordant. The aim of our study is to investigate prevalence and spatial distribution of cases, and identify environmental exposures associated with sarcoidosis in an Italian province. Methods After georeferentiation of cases, the area under study was subdivided with respect to Municipality and Health Districts and to the altitude in order to identify zonal differences in prevalence. The bioaccumulation levels of 12 metals in lichen tissues were analyzed, in order to determine sources of air pollution. Finally, the analysis of the correlation between metals and between pickup stations was performed. Results 223 patients were identified (58.3% female and 41.7% male of total) and the mean age was 50.6±15.4 years (53.5±15.5 years for the females and 46.5±14.4 for the males). The mean prevalence was 49 per 100.000 individuals. However, we observed very heterogeneous prevalence in the area under study. The correlations among metals revealed different deposition patterns in lowland area respect to hilly and mountain areas. Conclusions The study highlights a high prevalence of sarcoidosis cases, characterized by a very inhomogeneous and patchy distribution with phenomena of local aggregation. Moreover, the bioaccumulation analysis was an effective method to identify the mineral particles that mostly contribute to air pollution in the different areas, but it was not sufficient to establish a clear correlation between the onset of sarcoidosis and environmental risk factors. PMID:28475583

Analysis of a ToxCast™ HTS Toxicity Signature for putative Vascular Disruptor Compounds

EPA Science Inventory

Recent studies have shown the importance of blood vessel formation during embryo development and the strong correlation to developmental toxicity. Several developmental toxicants, such as thalidomide, have been identified which specifically target the forming embryonic vasculatur...

Differential proteomic analysis to identify proteins associated with quality traits of frozen mud shrimp (Solenocera melantho) using an iTRAQ-based strategy.

PubMed

Shi, Jing; Zhang, Longteng; Lei, Yutian; Shen, Huixing; Yu, Xunpei; Luo, Yongkang

2018-06-15

An iTRAQ-based strategy was applied to investigate proteome changes in mud shrimp during long-term frozen storage under different conditions. A total of 226 proteins was identified as differential abundance proteins (DAPs) in mud shrimp from two frozen treatment groups (-20 °C and -40 °C) compared with the fresh control group. The proteome changes in mud shrimp muscle stored under -20 °C was much greater than that under -40 °C. Correlation analysis between DAPs and quality traits of mud shrimp muscle showed that 12 proteins were correlated closely with color (L ∗ , a ∗ , and b ∗ value) and texture (hardness, elasticity, and chewiness). Bioinformatic analysis revealed that most of these proteins were involved in protein structure, metabolic enzymes, and protein turnover. Among them, several proteins might be potential protein markers for color, and some proteins are good candidate predictors for textural properties of mud shrimp muscle. Copyright © 2018 Elsevier Ltd. All rights reserved.

Statistical indicators of collective behavior and functional clusters in gene networks of yeast

NASA Astrophysics Data System (ADS)

Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

Acquisition and analysis of coastal ground-truth data for correlation with ERTS-1 imagery. [surface radiance data for Santa Monica Bay and Santa Barbara Channel

NASA Technical Reports Server (NTRS)

Anikouchine, W. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Radiance profiles drawn along cruise tracks have been examined for use in correlating digital radiance levels with ground truth data. Preliminary examination results are encouraging. Adding weighted levels from the 4 MSS bands appears to enhance specular surface reflections while rendering sensor noise white. Comparing each band signature to the added specular signature ought to enhance non-specular effects caused by ocean turbidity. Preliminary examination of radiance profiles and ground truth turbidity measurements revealed substantial correlation.

Simulation of random road microprofile based on specified correlation function

NASA Astrophysics Data System (ADS)

Rykov, S. P.; Rykova, O. A.; Koval, V. S.; Vlasov, V. G.; Fedotov, K. V.

2018-03-01

The paper aims to develop a numerical simulation method and an algorithm for a random microprofile of special roads based on the specified correlation function. The paper used methods of correlation, spectrum and numerical analysis. It proves that the transfer function of the generating filter for known expressions of spectrum input and output filter characteristics can be calculated using a theorem on nonnegative and fractional rational factorization and integral transformation. The model of the random function equivalent of the real road surface microprofile enables us to assess springing system parameters and identify ranges of variations.

Co-expression network analysis identified six hub genes in association with metastasis risk and prognosis in hepatocellular carcinoma

PubMed Central

Feng, Juerong; Zhou, Rui; Chang, Ying; Liu, Jing; Zhao, Qiu

2017-01-01

Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, and its carcinogenesis and progression are influenced by a complex network of gene interactions. A weighted gene co-expression network was constructed to identify gene modules associated with the clinical traits in HCC (n = 214). Among the 13 modules, high correlation was only found between the red module and metastasis risk (classified by the HCC metastasis gene signature) (R2 = −0.74). Moreover, in the red module, 34 network hub genes for metastasis risk were identified, six of which (ABAT, AGXT, ALDH6A1, CYP4A11, DAO and EHHADH) were also hub nodes in the protein-protein interaction network of the module genes. Thus, a total of six hub genes were identified. In validation, all hub genes showed a negative correlation with the four-stage HCC progression (P for trend < 0.05) in the test set. Furthermore, in the training set, HCC samples with any hub gene lowly expressed demonstrated a higher recurrence rate and poorer survival rate (hazard ratios with 95% confidence intervals > 1). RNA-sequencing data of 142 HCC samples showed consistent results in the prognosis. Gene set enrichment analysis (GSEA) demonstrated that in the samples with any hub gene highly expressed, a total of 24 functional gene sets were enriched, most of which focused on amino acid metabolism and oxidation. In conclusion, co-expression network analysis identified six hub genes in association with HCC metastasis risk and prognosis, which might improve the prognosis by influencing amino acid metabolism and oxidation. PMID:28430663

On the prediction of threshold friction velocity of wind erosion using soil reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Li, Junran; Flagg, Cody; Okin, Gregory S.; Painter, Thomas H.; Dintwe, Kebonye; Belnap, Jayne

2015-12-01

Current approaches to estimate threshold friction velocity (TFV) of soil particle movement, including both experimental and empirical methods, suffer from various disadvantages, and they are particularly not effective to estimate TFVs at regional to global scales. Reflectance spectroscopy has been widely used to obtain TFV-related soil properties (e.g., moisture, texture, crust, etc.), however, no studies have attempted to directly relate soil TFV to their spectral reflectance. The objective of this study was to investigate the relationship between soil TFV and soil reflectance in the visible and near infrared (VIS-NIR, 350-2500 nm) spectral region, and to identify the best range of wavelengths or combinations of wavelengths to predict TFV. Threshold friction velocity of 31 soils, along with their reflectance spectra and texture were measured in the Mojave Desert, California and Moab, Utah. A correlation analysis between TFV and soil reflectance identified a number of isolated, narrow spectral domains that largely fell into two spectral regions, the VIS area (400-700 nm) and the short-wavelength infrared (SWIR) area (1100-2500 nm). A partial least squares regression analysis (PLSR) confirmed the significant bands that were identified by correlation analysis. The PLSR further identified the strong relationship between the first-difference transformation and TFV at several narrow regions around 1400, 1900, and 2200 nm. The use of PLSR allowed us to identify a total of 17 key wavelengths in the investigated spectrum range, which may be used as the optimal spectral settings for estimating TFV in the laboratory and field, or mapping of TFV using airborne/satellite sensors.

Seismic reflection response from cross-correlations of ambient vibrations on non-conventional hidrocarbon reservoir

NASA Astrophysics Data System (ADS)

Huerta, F. V.; Granados, I.; Aguirre, J.; Carrera, R. Á.

2017-12-01

Nowadays, in hydrocarbon industry, there is a need to optimize and reduce exploration costs in the different types of reservoirs, motivating the community specialized in the search and development of alternative exploration geophysical methods. This study show the reflection response obtained from a shale gas / oil deposit through the method of seismic interferometry of ambient vibrations in combination with Wavelet analysis and conventional seismic reflection techniques (CMP & NMO). The method is to generate seismic responses from virtual sources through the process of cross-correlation of records of Ambient Seismic Vibrations (ASV), collected in different receivers. The seismic response obtained is interpreted as the response that would be measured in one of the receivers considering a virtual source in the other. The acquisition of ASV records was performed in northern of Mexico through semi-rectangular arrays of multi-component geophones with instrumental response of 10 Hz. The in-line distance between geophones was 40 m while in cross-line was 280 m, the sampling used during the data collection was 2 ms and the total duration of the records was 6 hours. The results show the reflection response of two lines in the in-line direction and two in the cross-line direction for which the continuity of coherent events have been identified and interpreted as reflectors. There is certainty that the events identified correspond to reflections because the time-frequency analysis performed with the Wavelet Transform has allowed to identify the frequency band in which there are body waves. On the other hand, the CMP and NMO techniques have allowed to emphasize and correct the reflection response obtained during the correlation processes in the frequency band of interest. The results of the processing and analysis of ASV records through the seismic interferometry method have allowed us to see interesting results in light of the cross-correlation process in combination with the Wavelet analysis and conventional seismic reflection techniques. Therefore it was possible to recover the seismic response on each analyzed source-receiver pair, allowing us to obtain the reflection response of each analyzed seismic line.

Analysis of Chuanxiong Rhizoma and its active components by Fourier transform infrared spectroscopy combined with two-dimensional correlation infrared spectroscopy.

PubMed

Guo, Yizhen; Lv, Beiran; Wang, Jingjuan; Liu, Yang; Sun, Suqin; Xiao, Yao; Lu, Lina; Xiang, Li; Yang, Yanfang; Qu, Lei; Meng, Qinghong

2016-01-15

As complicated mixture systems, active components of Chuanxiong Rhizoma are very difficult to identify and discriminate. In this paper, the macroscopic IR fingerprint method including Fourier transform infrared spectroscopy (FT-IR), the second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR), was applied to study and identify Chuanxiong raw materials and its different segmented production of HPD-100 macroporous resin. Chuanxiong Rhizoma is rich in sucrose. In the FT-IR spectra, water eluate is more similar to sucrose than the powder and the decoction. Their second derivative spectra amplified the differences and revealed the potentially characteristic IR absorption bands and combined with the correlation coefficient, concluding that 50% ethanol eluate had more ligustilide than other eluates. Finally, it can be found from 2DCOS-IR spectra that proteins were extracted by ethanol from Chuanxiong decoction by HPD-100 macroporous resin. It was demonstrated that the above three-step infrared spectroscopy could be applicable for quick, non-destructive and effective analysis and identification of very complicated and similar mixture systems of traditional Chinese medicines. Copyright © 2015 Elsevier B.V. All rights reserved.

Effects of correlated parameters and uncertainty in electronic-structure-based chemical kinetic modelling

NASA Astrophysics Data System (ADS)

Sutton, Jonathan E.; Guo, Wei; Katsoulakis, Markos A.; Vlachos, Dionisios G.

2016-04-01

Kinetic models based on first principles are becoming common place in heterogeneous catalysis because of their ability to interpret experimental data, identify the rate-controlling step, guide experiments and predict novel materials. To overcome the tremendous computational cost of estimating parameters of complex networks on metal catalysts, approximate quantum mechanical calculations are employed that render models potentially inaccurate. Here, by introducing correlative global sensitivity analysis and uncertainty quantification, we show that neglecting correlations in the energies of species and reactions can lead to an incorrect identification of influential parameters and key reaction intermediates and reactions. We rationalize why models often underpredict reaction rates and show that, despite the uncertainty being large, the method can, in conjunction with experimental data, identify influential missing reaction pathways and provide insights into the catalyst active site and the kinetic reliability of a model. The method is demonstrated in ethanol steam reforming for hydrogen production for fuel cells.

Validation of a computerized algorithm to quantify fetal heart rate deceleration area.

PubMed

Gyllencreutz, Erika; Lu, Ke; Lindecrantz, Kaj; Lindqvist, Pelle G; Nordstrom, Lennart; Holzmann, Malin; Abtahi, Farhad

2018-05-16

Reliability in visual cardiotocography interpretation is unsatisfying, which has led to development of computerized cardiotocography. Computerized analysis is well established for antenatal fetal surveillance, but has yet not performed sufficiently during labor. We aimed to investigate the capacity of a new computerized algorithm compared to visual assessment in identifying intrapartum fetal heart rate baseline and decelerations. Three-hundred-and-twelve intrapartum cardiotocography tracings with variable decelerations were analysed by the computerized algorithm and visually examined by two observers, blinded to each other and the computer analysis. The width, depth and area of each deceleration was measured. Four cases (>100 variable decelerations) were subject to in-depth detailed analysis. The outcome measures were bias in seconds (width), beats per minute (depth), and beats (area) between computer and observers by using Bland-Altman analysis. Interobserver reliability was determined by calculating intraclass correlation and Spearman rank analysis. The analysis (312 cases) showed excellent intraclass correlation (0.89-0.95) and very strong Spearman correlation (0.82-0.91). The detailed analysis of > 100 decelerations in 4 cases revealed low bias between the computer and the two observers; width 1.4 and 1.4 seconds, depth 5.1 and 0.7 beats per minute, and area 0.1 and -1.7 beats. This was comparable to the bias between the two observers; 0.3 seconds (width), 4.4 beats per minute (depth), and 1.7 beats (area). The intraclass correlation was excellent (0.90-0.98). A novel computerized algorithm for intrapartum cardiotocography analysis is as accurate as gold standard visual assessment with high correlation and low bias. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

SOX9 Is a Progressive Factor in Prostate Cancer

DTIC Science & Technology

2013-09-01

immunohis- tochemical analyses of BCa xenografts or mouse mammary tis- sues are detailed in the supplemental data. Meta- analysis of Gene Expression—SOX9mRNA...accession no. GSE5460) using dChip software (29). The analysis of variance function in dChip identified gene probes with significant correlation to...tumor grade groups (right panel). The p values of the difference analysis (Fisher’s Exact Test) are indicated. SOX9 Controlled Wnt/-catenin Activity

Chemical correlation of some late Cenozoic tuffs of Northern and Central California by neutron activation analysis of glass and comparison with X-ray fluorescence analysis

USGS Publications Warehouse

Sarna-Wojcicki, Andrei M.; Bowman, Harry W.; Russell, Paul C.

1979-01-01

Glasses separated from several dacitic and rhyolitic late Cenozoic tuffs of northern and central California were analyzed by neutron activation for more than 43 elemental abundances. Eighteen elements--scandiurn, manganese, iron, zinc, rubidium, cesium, barium, lanthanum, cerium, samarium, europium, terbiurn, dysprosiurn, ytterbiurn, hafniurn, tantalurn, thorium and uranium--were selected as most suitable for purposes of chemical correlation on the basis of their natural variability in silicic tuffs and the precision obtainable in analysis. Stratigraphic relations between tuffs and replicate chemical analyses on individual tuffs make it possib1e to calibrate a quantitative parameter, the similarity coefficient, which indicates the degree of correlation for the tuffs studied. The highest similarity coefficient (0.99) was obtained for analyses of two tuffs (potassium-argon dated at about' 6.0 m.y.) exposed in the Merced(?) and Petaluma Formations of Sonoma County, which represent different paleoenvironments, shallow-water marine and fresh water or brackish marine, respectively. Corre1ation of these formations on the basis of criteria other than tephrochronoloqy would be difficult. Results of neutron activation analysis in general confirm earlier correlations made on the basis of analysis by X-ray fluorescence but also make it possible to resolve small compositional differences between chemically simi1ar tuffs in stratigraphic proximity. The Lawlor Tuff (potassium-argon dated at about 4.0 m.y.) is identified at two new localities: in a core sample obtained from a bore hole east of Suisun Bay, and from the Kettleman Hills of western San Joaquin Valley. This identification permits correlation of the uppermost part of the marine Etchegoin Formation in the San Joaquin Valley with the continental Livermore Gravels of Clark, the Tassajara Formation, and the upper part of the Sonoma Volcanics in the cel1tral Coast Ranges of California. A younger tuff near the top of the marine San Joaquin Formation in the Kettleman Hills has been identified at both new 1oca1ities .

Lecture Evaluations by Medical Students: Concepts That Correlate With Scores.

PubMed

Jen, Aaron; Webb, Emily M; Ahearn, Bren; Naeger, David M

2016-01-01

The didactic lecture remains one of the most popular teaching formats in medical education; yet, factors that most influence lecturing success in radiology education are unknown. The purpose of this study is to identify patterns of narrative student feedback that are associated with relatively higher and lower evaluation scores. All student evaluations from our core radiology elective during 1 year were compiled. All evaluation comments were tagged, to identify discrete descriptive concepts. Correlation coefficients were calculated, for each tag with mean evaluation scores. Tags that were the most strongly associated with the highest- versus lowest-rated (> or < 1 SD) lectures were identified. A total of 3,262 comments, on 273 lectures, rated by 77 senior medical students, were analyzed. The mean lecture score was 8.96 ± 0.62. Three tags were significantly positively correlated with lecture score: "interactive"; "fun/engaging"; and "practical/important content" (r = 0.39, r = 0.34, and r = 0.32, respectively; all P < .001). More tags (n = 12) were significantly negatively correlated with score; the three tags with the strongest such correlation were: "not interactive"; "poorly structured or unevenly paced"; and "content too detailed or abundant" (r = -0.44, r = -0.39, and r = -0.36, respectively; all P < .001). Analysis of only the highest- and lowest-rated lectures yielded similar results. Several factors were identified that were strongly associated with lecture score. Among the actionable characteristics, interactive lectures with appropriately targeted content (ie, practical/useful) were the most highly rated. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Parallel mRNA, proteomics and miRNA expression analysis in cell line models of the intestine.

PubMed

O'Sullivan, Finbarr; Keenan, Joanne; Aherne, Sinead; O'Neill, Fiona; Clarke, Colin; Henry, Michael; Meleady, Paula; Breen, Laura; Barron, Niall; Clynes, Martin; Horgan, Karina; Doolan, Padraig; Murphy, Richard

2017-11-07

To identify miRNA-regulated proteins differentially expressed between Caco2 and HT-29: two principal cell line models of the intestine. Exponentially growing Caco-2 and HT-29 cells were harvested and prepared for mRNA, miRNA and proteomic profiling. mRNA microarray profiling analysis was carried out using the Affymetrix GeneChip Human Gene 1.0 ST array. miRNA microarray profiling analysis was carried out using the Affymetrix Genechip miRNA 3.0 array. Quantitative Label-free LC-MS/MS proteomic analysis was performed using a Dionex Ultimate 3000 RSLCnano system coupled to a hybrid linear ion trap/Orbitrap mass spectrometer. Peptide identities were validated in Proteome Discoverer 2.1 and were subsequently imported into Progenesis QI software for further analysis. Hierarchical cluster analysis for all three parallel datasets (miRNA, proteomics, mRNA) was conducted in the R software environment using the Euclidean distance measure and Ward's clustering algorithm. The prediction of miRNA and oppositely correlated protein/mRNA interactions was performed using TargetScan 6.1. GO biological process, molecular function and cellular component enrichment analysis was carried out for the DE miRNA, protein and mRNA lists via the Pathway Studio 11.3 Web interface using their Mammalian database. Differential expression (DE) profiling comparing the intestinal cell lines HT-29 and Caco-2 identified 1795 Genes, 168 Proteins and 160 miRNAs as DE between the two cell lines. At the gene level, 1084 genes were upregulated and 711 were downregulated in the Caco-2 cell line relative to the HT-29 cell line. At the protein level, 57 proteins were found to be upregulated and 111 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Finally, at the miRNAs level, 104 were upregulated and 56 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Gene ontology (GO) analysis of the DE mRNA identified cell adhesion, migration and ECM organization, cellular lipid and cholesterol metabolic processes, small molecule transport and a range of responses to external stimuli, while similar analysis of the DE protein list identified gene expression/transcription, epigenetic mechanisms, DNA replication, differentiation and translation ontology categories. The DE protein and gene lists were found to share 15 biological processes including for example epithelial cell differentiation [ P value ≤ 1.81613E-08 (protein list); P ≤ 0.000434311 (gene list)] and actin filament bundle assembly [ P value ≤ 0.001582797 (protein list); P ≤ 0.002733714 (gene list)]. Analysis was conducted on the three data streams acquired in parallel to identify targets undergoing potential miRNA translational repression identified 34 proteins, whose respective mRNAs were detected but no change in expression was observed. Of these 34 proteins, 27 proteins downregulated in the Caco-2 cell line relative to the HT-29 cell line and predicted to be targeted by 19 unique anti-correlated/upregulated microRNAs and 7 proteins upregulated in the Caco-2 cell line relative to the HT-29 cell line and predicted to be targeted by 15 unique anti-correlated/downregulated microRNAs. This first study providing "tri-omics" analysis of the principal intestinal cell line models Caco-2 and HT-29 has identified 34 proteins potentially undergoing miRNA translational repression.

Parallel mRNA, proteomics and miRNA expression analysis in cell line models of the intestine

PubMed Central

O’Sullivan, Finbarr; Keenan, Joanne; Aherne, Sinead; O’Neill, Fiona; Clarke, Colin; Henry, Michael; Meleady, Paula; Breen, Laura; Barron, Niall; Clynes, Martin; Horgan, Karina; Doolan, Padraig; Murphy, Richard

2017-01-01

AIM To identify miRNA-regulated proteins differentially expressed between Caco2 and HT-29: two principal cell line models of the intestine. METHODS Exponentially growing Caco-2 and HT-29 cells were harvested and prepared for mRNA, miRNA and proteomic profiling. mRNA microarray profiling analysis was carried out using the Affymetrix GeneChip Human Gene 1.0 ST array. miRNA microarray profiling analysis was carried out using the Affymetrix Genechip miRNA 3.0 array. Quantitative Label-free LC-MS/MS proteomic analysis was performed using a Dionex Ultimate 3000 RSLCnano system coupled to a hybrid linear ion trap/Orbitrap mass spectrometer. Peptide identities were validated in Proteome Discoverer 2.1 and were subsequently imported into Progenesis QI software for further analysis. Hierarchical cluster analysis for all three parallel datasets (miRNA, proteomics, mRNA) was conducted in the R software environment using the Euclidean distance measure and Ward’s clustering algorithm. The prediction of miRNA and oppositely correlated protein/mRNA interactions was performed using TargetScan 6.1. GO biological process, molecular function and cellular component enrichment analysis was carried out for the DE miRNA, protein and mRNA lists via the Pathway Studio 11.3 Web interface using their Mammalian database. RESULTS Differential expression (DE) profiling comparing the intestinal cell lines HT-29 and Caco-2 identified 1795 Genes, 168 Proteins and 160 miRNAs as DE between the two cell lines. At the gene level, 1084 genes were upregulated and 711 were downregulated in the Caco-2 cell line relative to the HT-29 cell line. At the protein level, 57 proteins were found to be upregulated and 111 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Finally, at the miRNAs level, 104 were upregulated and 56 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Gene ontology (GO) analysis of the DE mRNA identified cell adhesion, migration and ECM organization, cellular lipid and cholesterol metabolic processes, small molecule transport and a range of responses to external stimuli, while similar analysis of the DE protein list identified gene expression/transcription, epigenetic mechanisms, DNA replication, differentiation and translation ontology categories. The DE protein and gene lists were found to share 15 biological processes including for example epithelial cell differentiation [P value ≤ 1.81613E-08 (protein list); P ≤ 0.000434311 (gene list)] and actin filament bundle assembly [P value ≤ 0.001582797 (protein list); P ≤ 0.002733714 (gene list)]. Analysis was conducted on the three data streams acquired in parallel to identify targets undergoing potential miRNA translational repression identified 34 proteins, whose respective mRNAs were detected but no change in expression was observed. Of these 34 proteins, 27 proteins downregulated in the Caco-2 cell line relative to the HT-29 cell line and predicted to be targeted by 19 unique anti-correlated/upregulated microRNAs and 7 proteins upregulated in the Caco-2 cell line relative to the HT-29 cell line and predicted to be targeted by 15 unique anti-correlated/downregulated microRNAs. CONCLUSION This first study providing “tri-omics” analysis of the principal intestinal cell line models Caco-2 and HT-29 has identified 34 proteins potentially undergoing miRNA translational repression. PMID:29151691

Relevant Feature Set Estimation with a Knock-out Strategy and Random Forests

PubMed Central

Ganz, Melanie; Greve, Douglas N.; Fischl, Bruce; Konukoglu, Ender

2015-01-01

Group analysis of neuroimaging data is a vital tool for identifying anatomical and functional variations related to diseases as well as normal biological processes. The analyses are often performed on a large number of highly correlated measurements using a relatively smaller number of samples. Despite the correlation structure, the most widely used approach is to analyze the data using univariate methods followed by post-hoc corrections that try to account for the data’s multivariate nature. Although widely used, this approach may fail to recover from the adverse effects of the initial analysis when local effects are not strong. Multivariate pattern analysis (MVPA) is a powerful alternative to the univariate approach for identifying relevant variations. Jointly analyzing all the measures, MVPA techniques can detect global effects even when individual local effects are too weak to detect with univariate analysis. Current approaches are successful in identifying variations that yield highly predictive and compact models. However, they suffer from lessened sensitivity and instabilities in identification of relevant variations. Furthermore, current methods’ user-defined parameters are often unintuitive and difficult to determine. In this article, we propose a novel MVPA method for group analysis of high-dimensional data that overcomes the drawbacks of the current techniques. Our approach explicitly aims to identify all relevant variations using a “knock-out” strategy and the Random Forest algorithm. In evaluations with synthetic datasets the proposed method achieved substantially higher sensitivity and accuracy than the state-of-the-art MVPA methods, and outperformed the univariate approach when the effect size is low. In experiments with real datasets the proposed method identified regions beyond the univariate approach, while other MVPA methods failed to replicate the univariate results. More importantly, in a reproducibility study with the well-known ADNI dataset the proposed method yielded higher stability and power than the univariate approach. PMID:26272728

Visualization of synchronization of the uterine contraction signals: running cross-correlation and wavelet running cross-correlation methods.

PubMed

Oczeretko, Edward; Swiatecka, Jolanta; Kitlas, Agnieszka; Laudanski, Tadeusz; Pierzynski, Piotr

2006-01-01

In physiological research, we often study multivariate data sets, containing two or more simultaneously recorded time series. The aim of this paper is to present the cross-correlation and the wavelet cross-correlation methods to assess synchronization between contractions in different topographic regions of the uterus. From a medical point of view, it is important to identify time delays between contractions, which may be of potential diagnostic significance in various pathologies. The cross-correlation was computed in a moving window with a width corresponding to approximately two or three contractions. As a result, the running cross-correlation function was obtained. The propagation% parameter assessed from this function allows quantitative description of synchronization in bivariate time series. In general, the uterine contraction signals are very complicated. Wavelet transforms provide insight into the structure of the time series at various frequencies (scales). To show the changes of the propagation% parameter along scales, a wavelet running cross-correlation was used. At first, the continuous wavelet transforms as the uterine contraction signals were received and afterwards, a running cross-correlation analysis was conducted for each pair of transformed time series. The findings show that running functions are very useful in the analysis of uterine contractions.

A study of the correlation between dengue and weather in Kandy City, Sri Lanka (2003 -2012) and lessons learned.

PubMed

Ehelepola, N D B; Ariyaratne, Kusalika; Buddhadasa, W M N P; Ratnayake, Sunil; Wickramasinghe, Malani

2015-09-24

Weather variables affect dengue transmission. This study aimed to identify a dengue weather correlation pattern in Kandy, Sri Lanka, compare the results with results of similar studies, and establish ways for better control and prevention of dengue. We collected data on reported dengue cases in Kandy and mid-year population data from 2003 to 2012, and calculated weekly incidences. We obtained daily weather data from two weather stations and converted it into weekly data. We studied correlation patterns between dengue incidence and weather variables using the wavelet time series analysis, and then calculated cross-correlation coefficients to find magnitudes of correlations. We found a positive correlation between dengue incidence and rainfall in millimeters, the number of rainy and wet days, the minimum temperature, and the night and daytime, as well as average, humidity, mostly with a five- to seven-week lag. Additionally, we found correlations between dengue incidence and maximum and average temperatures, hours of sunshine, and wind, with longer lag periods. Dengue incidences showed a negative correlation with wind run. Our results showed that rainfall, temperature, humidity, hours of sunshine, and wind are correlated with local dengue incidence. We have suggested ways to improve dengue management routines and to control it in these times of global warming. We also noticed that the results of dengue weather correlation studies can vary depending on the data analysis.

Gene-to-metabolite network for biosynthesis of lignans in MeJA-elicited Isatis indigotica hairy root cultures

PubMed Central

Chen, Ruibing; Li, Qing; Tan, Hexin; Chen, Junfeng; Xiao, Ying; Ma, Ruifang; Gao, Shouhong; Zerbe, Philipp; Chen, Wansheng; Zhang, Lei

2015-01-01

Root and leaf tissue of Isatis indigotica shows notable anti-viral efficacy, and are widely used as “Banlangen” and “Daqingye” in traditional Chinese medicine. The plants' pharmacological activity is attributed to phenylpropanoids, especially a group of lignan metabolites. However, the biosynthesis of lignans in I. indigotica remains opaque. This study describes the discovery and analysis of biosynthetic genes and AP2/ERF-type transcription factors involved in lignan biosynthesis in I. indigotica. MeJA treatment revealed differential expression of three genes involved in phenylpropanoid backbone biosynthesis (IiPAL, IiC4H, Ii4CL), five genes involved in lignan biosynthesis (IiCAD, IiC3H, IiCCR, IiDIR, and IiPLR), and 112 putative AP2/ERF transcription factors. In addition, four intermediates of lariciresinol biosynthesis were found to be induced. Based on these results, a canonical correlation analysis using Pearson's correlation coefficient was performed to construct gene-to-metabolite networks and identify putative key genes and rate-limiting reactions in lignan biosynthesis. Over-expression of IiC3H, identified as a key pathway gene, was used for metabolic engineering of I. indigotica hairy roots, and resulted in an increase in lariciresinol production. These findings illustrate the utility of canonical correlation analysis for the discovery and metabolic engineering of key metabolic genes in plants. PMID:26579184

Minimum number of measurements for evaluating soursop (Annona muricata L.) yield.

PubMed

Sánchez, C F B; Teodoro, P E; Londoño, S; Silva, L A; Peixoto, L A; Bhering, L L

2017-05-31

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

Degree-Strength Correlation Reveals Anomalous Trading Behavior

PubMed Central

Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Wang, Zhao-Yang

2012-01-01

Manipulation is an important issue for both developed and emerging stock markets. Many efforts have been made to detect manipulation in stock markets. However, it is still an open problem to identify the fraudulent traders, especially when they collude with each other. In this paper, we focus on the problem of identifying the anomalous traders using the transaction data of eight manipulated stocks and forty-four non-manipulated stocks during a one-year period. By analyzing the trading networks of stocks, we find that the trading networks of manipulated stocks exhibit significantly higher degree-strength correlation than the trading networks of non-manipulated stocks and the randomized trading networks. We further propose a method to detect anomalous traders of manipulated stocks based on statistical significance analysis of degree-strength correlation. Experimental results demonstrate that our method is effective at distinguishing the manipulated stocks from non-manipulated ones. Our method outperforms the traditional weight-threshold method at identifying the anomalous traders in manipulated stocks. More importantly, our method is difficult to be fooled by colluded traders. PMID:23082114

Experimental assessment of the importance of amino acid positions identified by an entropy-based correlation analysis of multiple-sequence alignments.

PubMed

Dietrich, Susanne; Borst, Nadine; Schlee, Sandra; Schneider, Daniel; Janda, Jan-Oliver; Sterner, Reinhard; Merkl, Rainer

2012-07-17

The analysis of a multiple-sequence alignment (MSA) with correlation methods identifies pairs of residue positions whose occupation with amino acids changes in a concerted manner. It is plausible to assume that positions that are part of many such correlation pairs are important for protein function or stability. We have used the algorithm H2r to identify positions k in the MSAs of the enzymes anthranilate phosphoribosyl transferase (AnPRT) and indole-3-glycerol phosphate synthase (IGPS) that show a high conn(k) value, i.e., a large number of significant correlations in which k is involved. The importance of the identified residues was experimentally validated by performing mutagenesis studies with sAnPRT and sIGPS from the archaeon Sulfolobus solfataricus. For sAnPRT, five H2r mutant proteins were generated by replacing nonconserved residues with alanine or the prevalent residue of the MSA. As a control, five residues with conn(k) values of zero were chosen randomly and replaced with alanine. The catalytic activities and conformational stabilities of the H2r and control mutant proteins were analyzed by steady-state enzyme kinetics and thermal unfolding studies. Compared to wild-type sAnPRT, the catalytic efficiencies (k(cat)/K(M)) were largely unaltered. In contrast, the apparent thermal unfolding temperature (T(M)(app)) was lowered in most proteins. Remarkably, the strongest observed destabilization (ΔT(M)(app) = 14 °C) was caused by the V284A exchange, which pertains to the position with the highest correlation signal [conn(k) = 11]. For sIGPS, six H2r mutant and four control proteins with alanine exchanges were generated and characterized. The k(cat)/K(M) values of four H2r mutant proteins were reduced between 13- and 120-fold, and their T(M)(app) values were decreased by up to 5 °C. For the sIGPS control proteins, the observed activity and stability decreases were much less severe. Our findings demonstrate that positions with high conn(k) values have an increased probability of being important for enzyme function or stability.

Pantoea ananatis Genetic Diversity Analysis Reveals Limited Genomic Diversity as Well as Accessory Genes Correlated with Onion Pathogenicity.

PubMed

Stice, Shaun P; Stumpf, Spencer D; Gitaitis, Ron D; Kvitko, Brian H; Dutta, Bhabesh

2018-01-01

Pantoea ananatis is a member of the family Enterobacteriaceae and an enigmatic plant pathogen with a broad host range. Although P. ananatis strains can be aggressive on onion causing foliar necrosis and onion center rot, previous genomic analysis has shown that P. ananatis lacks the primary virulence secretion systems associated with other plant pathogens. We assessed a collection of fifty P. ananatis strains collected from Georgia over three decades to determine genetic factors that correlated with onion pathogenic potential. Previous genetic analysis studies have compared strains isolated from different hosts with varying diseases potential and isolation sources. Strains varied greatly in their pathogenic potential and aggressiveness on different cultivated Allium species like onion, leek, shallot, and chive. Using multi-locus sequence analysis (MLSA) and repetitive extragenic palindrome repeat (rep)-PCR techniques, we did not observe any correlation between onion pathogenic potential and genetic diversity among strains. Whole genome sequencing and pan-genomic analysis of a sub-set of 10 strains aided in the identification of a novel series of genetic regions, likely plasmid borne, and correlating with onion pathogenicity observed on single contigs of the genetic assemblies. We named these loci Onion Virulence Regions (OVR) A-D. The OVR loci contain genes involved in redox regulation as well as pectate lyase and rhamnogalacturonase genes. Previous studies have not identified distinct genetic loci or plasmids correlating with onion foliar pathogenicity or pathogenicity on a single host pathosystem. The lack of focus on a single host system for this phytopathgenic disease necessitates the pan-genomic analysis performed in this study.

Pantoea ananatis Genetic Diversity Analysis Reveals Limited Genomic Diversity as Well as Accessory Genes Correlated with Onion Pathogenicity

PubMed Central

Stice, Shaun P.; Stumpf, Spencer D.; Gitaitis, Ron D.; Kvitko, Brian H.; Dutta, Bhabesh

2018-01-01

Pantoea ananatis is a member of the family Enterobacteriaceae and an enigmatic plant pathogen with a broad host range. Although P. ananatis strains can be aggressive on onion causing foliar necrosis and onion center rot, previous genomic analysis has shown that P. ananatis lacks the primary virulence secretion systems associated with other plant pathogens. We assessed a collection of fifty P. ananatis strains collected from Georgia over three decades to determine genetic factors that correlated with onion pathogenic potential. Previous genetic analysis studies have compared strains isolated from different hosts with varying diseases potential and isolation sources. Strains varied greatly in their pathogenic potential and aggressiveness on different cultivated Allium species like onion, leek, shallot, and chive. Using multi-locus sequence analysis (MLSA) and repetitive extragenic palindrome repeat (rep)-PCR techniques, we did not observe any correlation between onion pathogenic potential and genetic diversity among strains. Whole genome sequencing and pan-genomic analysis of a sub-set of 10 strains aided in the identification of a novel series of genetic regions, likely plasmid borne, and correlating with onion pathogenicity observed on single contigs of the genetic assemblies. We named these loci Onion Virulence Regions (OVR) A-D. The OVR loci contain genes involved in redox regulation as well as pectate lyase and rhamnogalacturonase genes. Previous studies have not identified distinct genetic loci or plasmids correlating with onion foliar pathogenicity or pathogenicity on a single host pathosystem. The lack of focus on a single host system for this phytopathgenic disease necessitates the pan-genomic analysis performed in this study. PMID:29491851

Prediction of early postoperative infections in pediatric liver transplantation by logistic regression

NASA Astrophysics Data System (ADS)

Uzunova, Yordanka; Prodanova, Krasimira; Spassov, Lubomir

2016-12-01

Orthotopic liver transplantation (OLT) is the only curative treatment for end-stage liver disease. Early diagnosis and treatment of infections after OLT are usually associated with improved outcomes. This study's objective is to identify reliable factors that can predict postoperative infectious morbidity. 27 children were included in the analysis. They underwent liver transplantation in our department. The correlation between two parameters (the level of blood glucose at 5th postoperative day and the duration of the anhepatic phase) and postoperative infections was analyzed, using univariate analysis. In this analysis, an independent predictive factor was derived which adequately identifies patients at risk of infectious complications after a liver transplantation.

An Empirical Research on the Correlation between Human Capital and Career Success of Knowledge Workers in Enterprise

NASA Astrophysics Data System (ADS)

Guo, Wenchen; Xiao, Hongjun; Yang, Xi

Human capital plays an important part in employability of knowledge workers, also it is the important intangible assets of company. This paper explores the correlation between human capital and career success of knowledge workers. Based on literature retrieval, we identified measuring tool of career success and modified further; measuring human capital with self-developed scale of high reliability and validity. After exploratory factor analysis, we suggest that human capital contents four dimensions, including education, work experience, learning ability and training; career success contents three dimensions, including perceived internal competitiveness of organization, perceived external competitiveness of organization and career satisfaction. The result of empirical analysis indicates that there is a positive correlation between human capital and career success, and human capital is an excellent predictor of career success beyond demographics variables.

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.

PubMed

Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung

2009-12-15

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

Global trends in the awareness of sepsis: insights from search engine data between 2012 and 2017.

PubMed

Jabaley, Craig S; Blum, James M; Groff, Robert F; O'Reilly-Shah, Vikas N

2018-01-17

Sepsis is an established global health priority with high mortality that can be curtailed through early recognition and intervention; as such, efforts to raise awareness are potentially impactful and increasingly common. We sought to characterize trends in the awareness of sepsis by examining temporal, geographic, and other changes in search engine utilization for sepsis information-seeking online. Using time series analyses and mixed descriptive methods, we retrospectively analyzed publicly available global usage data reported by Google Trends (Google, Palo Alto, CA, USA) concerning web searches for the topic of sepsis between 24 June 2012 and 24 June 2017. Google Trends reports aggregated and de-identified usage data for its search products, including interest over time, interest by region, and details concerning the popularity of related queries where applicable. Outlying epochs of search activity were identified using autoregressive integrated moving average modeling with transfer functions. We then identified awareness campaigns and news media coverage that correlated with epochs of significantly heightened search activity. A second-order autoregressive model with transfer functions was specified following preliminary outlier analysis. Nineteen significant outlying epochs above the modeled baseline were identified in the final analysis that correlated with 14 awareness and news media events. Our model demonstrated that the baseline level of search activity increased in a nonlinear fashion. A recurrent cyclic increase in search volume beginning in 2012 was observed that correlates with World Sepsis Day. Numerous other awareness and media events were correlated with outlying epochs. The average worldwide search volume for sepsis was less than that of influenza, myocardial infarction, and stroke. Analyzing aggregate search engine utilization data has promise as a mechanism to measure the impact of awareness efforts. Heightened information-seeking about sepsis occurs in close proximity to awareness events and relevant news media coverage. Future work should focus on validating this approach in other contexts and comparing its results to traditional methods of awareness campaign evaluation.

The mediating effect of calling on the relationship between medical school students' academic burnout and empathy.

PubMed

Chae, Su Jin; Jeong, So Mi; Chung, Yoon-Sok

2017-09-01

This study is aimed at identifying the relationships between medical school students' academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students' empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. This result demonstrates that calling is a key variable that mediates the relationship between medical students' academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students' empathy skills.

Biotic and abiotic dynamics of a high solid-state anaerobic digestion box-type container system.

PubMed

Walter, Andreas; Probst, Maraike; Hinterberger, Stephan; Müller, Horst; Insam, Heribert

2016-03-01

A solid-state anaerobic digestion box-type container system for biomethane production was observed in 12 three-week batch fermentations. Reactor performance was monitored using physico-chemical analysis and the methanogenic community was identified using ANAEROCHIP-microarrays and quantitative PCR. A resilient community was found in all batches, despite variations in inoculum to substrate ratio, feedstock quality, and fluctuating reactor conditions. The consortia were dominated by mixotrophic Methanosarcina that were accompanied by hydrogenotrophic Methanobacterium, Methanoculleus, and Methanocorpusculum. The relationship between biotic and abiotic variables was investigated using bivariate correlation analysis and univariate analysis of variance. High amounts of biogas were produced in batches with high copy numbers of Methanosarcina. High copy numbers of Methanocorpusculum and extensive percolation, however, were found to negatively correlate with biogas production. Supporting these findings, a negative correlation was detected between Methanocorpusculum and Methanosarcina. Based on these results, this study suggests Methanosarcina as an indicator for well-functioning reactor performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coal-tar-based sealcoated pavement: a major PAH source to urban stream sediments.

PubMed

Witter, Amy E; Nguyen, Minh H; Baidar, Sunil; Sak, Peter B

2014-02-01

We used land-use analysis, PAH concentrations and assemblages, and multivariate statistics to identify sediment PAH sources in a small (~1303 km(2)) urbanizing watershed located in South-Central, Pennsylvania, USA. A geographic information system (GIS) was employed to quantify land-use features that may serve as PAH sources. Urban PAH concentrations were three times higher than rural levels, and were significantly and highly correlated with combined residential/commercial/industrial land use. Principal components analysis (PCA) was used to group sediments with similar PAH assemblages, and correlation analysis compared PAH sediment assemblages to common PAH sources. The strongest correlations were observed between rural sediments (n = 7) and coke-oven emissions sources (r = 0.69-0.78, n = 5), and between urban sediments (n = 22) and coal-tar-based sealcoat dust (r = 0.94, n = 47) suggesting that coal-tar-based sealcoat is an important urban PAH source in this watershed linked to residential and commercial/industrial land use. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multifractal detrended cross-correlation analysis on NO, NO2 and O3 concentrations at traffic sites

NASA Astrophysics Data System (ADS)

Xu, Weijia; Liu, Chunqiong; Shi, Kai; Liu, Yonghong

2018-07-01

NOX plays the important role for O3 production in atmospheric photochemical processes. In this paper, the cross-correlations between NO (NO2) and O3 at three traffic sites in Hong Kong are investigated, using the multifractal detrended cross-correlation analysis (MFDCCA). The results show that the cross-correlations between NO (NO2) and O3 have multifractal nature and long term persistent power-law decaying behavior. The sources of multifractality are discussed based on the shuffling and phase randomization procedure. The chi square test is applied to identify the contributions degree of NO and NO2 to multifractality due to its own long term correlations respectively. And the temporal evolutions of the local contributions degree of NO and NO2 to multifractality are investigated by the sliding windows method. The differences between them are explained by the self-organized criticality mechanism of air pollution, combined with global solar radiation. MFDCCA provides a helpful approach for understanding the quantitative relationship between the O3 and its precursors.

Global miRNA expression and correlation with mRNA levels in primary human bone cells

PubMed Central

Laxman, Navya; Rubin, Carl-Johan; Mallmin, Hans; Nilsson, Olle; Pastinen, Tomi; Grundberg, Elin; Kindmark, Andreas

2015-01-01

MicroRNAs (miRNAs) are important post-transcriptional regulators that have recently introduced an additional level of intricacy to our understanding of gene regulation. The aim of this study was to investigate miRNA–mRNA interactions that may be relevant for bone metabolism by assessing correlations and interindividual variability in miRNA levels as well as global correlations between miRNA and mRNA levels in a large cohort of primary human osteoblasts (HOBs) obtained during orthopedic surgery in otherwise healthy individuals. We identified differential expression (DE) of 24 miRNAs, and found 9 miRNAs exhibiting DE between males and females. We identified hsa-miR-29b, hsa-miR-30c2, and hsa-miR-125b and their target genes as important modulators of bone metabolism. Further, we used an integrated analysis of global miRNA–mRNA correlations, mRNA-expression profiling, DE, bioinformatics analysis, and functional studies to identify novel target genes for miRNAs with the potential to regulate osteoblast differentiation and extracellular matrix production. Functional studies by overexpression and knockdown of miRNAs showed that, the differentially expressed miRNAs hsa-miR-29b, hsa-miR-30c2, and hsa-miR-125b target genes highly relevant to bone metabolism, e.g., collagen, type I, α1 (COL1A1), osteonectin (SPARC), Runt-related transcription factor 2 (RUNX2), osteocalcin (BGLAP), and frizzled-related protein (FRZB). These miRNAs orchestrate the activities of key regulators of osteoblast differentiation and extracellular matrix proteins by their convergent action on target genes and pathways to control the skeletal gene expression. PMID:26078267

Clinical and histopathological factors associated with Ki-67 expression in breast cancer patients

PubMed Central

ALCO, GUL; BOZDOGAN, ATILLA; SELAMOGLU, DERYA; PILANCI, KEZBAN NUR; TUZLALI, SITKI; ORDU, CETIN; IGDEM, SEFIK; OKKAN, SAIT; DINCER, MAKTAV; DEMIR, GOKHAN; OZMEN, VAHIT

2015-01-01

The aim of the present study was to identify the optimal Ki-67 cut-off value in breast cancer (BC) patients, and investigate the association of Ki-67 expression levels with other prognostic factors. Firstly, a retrospective search was performed to identify patients with stage I–III BC (n=462). A range of Ki-67 index values were then assigned to five groups (<10, 10–14, 15–19, 20–24 and ≥25%). The correlation between the Ki-67 index and other prognostic factors [age, tumor type, histological and nuclear grade, tumor size, multifocality, an in situ component, lymphovascular invasion (LVI), estrogen and progesterone receptor (ER/PR) expression, human epidermal growth factor receptor (HER-2) status, axillary involvement and tumor stage] were investigated in each group. The median Ki-67 value was revealed to be 20% (range, 1–95%). A young age (≤40 years old), tumor type, size and grade, LVI, ER/PR negativity and HER-2 positivity were revealed to be associated with the Ki-67 level. Furthermore, Ki-67 was demonstrated to be negatively correlated with ER/PR expression (P<0.001), but positively correlated with tumor size (P<0.001). The multivariate analysis revealed that a Ki-67 value of ≥15% was associated with the largest number of poor prognostic factors (P=0.036). In addition, a Ki-67 value of ≥15% was identified to be statistically significant in association with certain luminal subtypes. The rate of disease-free survival was higher in patients with luminal A subtype BC (P=0.036). Following the correlation analysis for the Ki-67 index and the other prognostic factors, a Ki-67 value of ≥15% was revealed to be the optimal cut-off level for BC patients. PMID:25663855

Secretome Characterization and Correlation Analysis Reveal Putative Pathogenicity Mechanisms and Identify Candidate Avirulence Genes in the Wheat Stripe Rust Fungus Puccinia striiformis f. sp. tritici.

PubMed

Xia, Chongjing; Wang, Meinan; Cornejo, Omar E; Jiwan, Derick A; See, Deven R; Chen, Xianming

2017-01-01

Stripe (yellow) rust, caused by Puccinia striiformis f. sp. tritici ( Pst ), is one of the most destructive diseases of wheat worldwide. Planting resistant cultivars is an effective way to control this disease, but race-specific resistance can be overcome quickly due to the rapid evolving Pst population. Studying the pathogenicity mechanisms is critical for understanding how Pst virulence changes and how to develop wheat cultivars with durable resistance to stripe rust. We re-sequenced 7 Pst isolates and included additional 7 previously sequenced isolates to represent balanced virulence/avirulence profiles for several avirulence loci in seretome analyses. We observed an uneven distribution of heterozygosity among the isolates. Secretome comparison of Pst with other rust fungi identified a large portion of species-specific secreted proteins, suggesting that they may have specific roles when interacting with the wheat host. Thirty-two effectors of Pst were identified from its secretome. We identified candidates for Avr genes corresponding to six Yr genes by correlating polymorphisms for effector genes to the virulence/avirulence profiles of the 14 Pst isolates. The putative AvYr76 was present in the avirulent isolates, but absent in the virulent isolates, suggesting that deleting the coding region of the candidate avirulence gene has produced races virulent to resistance gene Yr76 . We conclude that incorporating avirulence/virulence phenotypes into correlation analysis with variations in genomic structure and secretome, particularly presence/absence polymorphisms of effectors, is an efficient way to identify candidate Avr genes in Pst . The candidate effector genes provide a rich resource for further studies to determine the evolutionary history of Pst populations and the co-evolutionary arms race between Pst and wheat. The Avr candidates identified in this study will lead to cloning avirulence genes in Pst , which will enable us to understand molecular mechanisms underlying Pst -wheat interactions, to determine the effectiveness of resistance genes and further to develop durable resistance to stripe rust.

Evidence for bivariate linkage of obesity and HDL-C levels in the Framingham Heart Study.

PubMed

Arya, Rector; Lehman, Donna; Hunt, Kelly J; Schneider, Jennifer; Almasy, Laura; Blangero, John; Stern, Michael P; Duggirala, Ravindranath

2003-12-31

Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that these traits are correlated in part due to pleiotropy, knowledge on specific genes commonly affecting obesity and dyslipidemia is very limited. To address this issue, we first conducted univariate multipoint linkage analysis for body mass index (BMI) and HDL-C to identify loci influencing variation in these phenotypes using Framingham Heart Study data relating to 1702 subjects distributed across 330 pedigrees. Subsequently, we performed bivariate multipoint linkage analysis to detect common loci influencing covariation between these two traits. We scanned the genome and identified a major locus near marker D6S1009 influencing variation in BMI (LOD = 3.9) using the program SOLAR. We also identified a major locus for HDL-C near marker D2S1334 on chromosome 2 (LOD = 3.5) and another region near marker D6S1009 on chromosome 6 with suggestive evidence for linkage (LOD = 2.7). Since these two phenotypes have been independently mapped to the same region on chromosome 6q, we used the bivariate multipoint linkage approach using SOLAR. The bivariate linkage analysis of BMI and HDL-C implicated the genetic region near marker D6S1009 as harboring a major gene commonly influencing these phenotypes (bivariate LOD = 6.2; LODeq = 5.5) and appears to improve power to map the correlated traits to a region, precisely. We found substantial evidence for a quantitative trait locus with pleiotropic effects, which appears to influence both BMI and HDL-C phenotypes in the Framingham data.

Prevalence and Clinical Correlates of Sarcopenia in Community-Dwelling Older People: Application of the EWGSOP Definition and Diagnostic Algorithm

PubMed Central

2014-01-01

Background. Muscle impairment is a common condition in older people and a powerful risk factor for disability and mortality. The aim of this study was to apply the European Working Group on Sarcopenia in Older People criteria to estimate the prevalence and investigate the clinical correlates of sarcopenia, in a sample of Italian community-dwelling older people. Methods. Cross-sectional analysis of 730 participants (74% aged 65 years and older) enrolled in the InCHIANTI study. Sarcopenia was defined according to the European Working Group on Sarcopenia in Older People criteria using bioimpedance analysis for muscle mass assessment. Logistic regression analysis was used to identify the factors independently associated with sarcopenia. Results. Sarcopenia defined by the European Working Group on Sarcopenia in Older People criteria increased steeply with age (p < .001), with 31.6% of women and 17.4% of men aged 80 years or older being affected by this condition. Higher education (odds ratio: 0.85; 95% CI: 0.74–0.98), lower insulin-like growth factor I (lowest vs highest tertile, odds ratio: 3.89; 95% CI: 1.03–14.1), and low bioavailable testosterone (odds ratio: 2.67; 95% CI: 1.31–5.44) were independently associated with the likelihood of being sarcopenic. Nutritional intake, physical activity, and level of comorbidity were not associated with sarcopenia. Conclusions. Sarcopenia identified by the European Working Group on Sarcopenia in Older People criteria is a relatively common condition in Italian octogenarians, and its prevalence increases with aging. Correlates of sarcopenia identified in this study might suggest new approaches for prevention and treatment of sarcopenia. PMID:24085400

Multiscale analysis of the spatial variability of heavy metals and organic matter in soils and groundwater across Spain

NASA Astrophysics Data System (ADS)

Luque-Espinar, J. A.; Pardo-Igúzquiza, E.; Grima-Olmedo, J.; Grima-Olmedo, C.

2018-06-01

During the last years there has been an increasing interest in assessing health risks caused by exposure to contaminants found in soil, air, and water, like heavy metals or emerging contaminants. This work presents a study on the spatial patterns and interaction effects among relevant heavy metals (Sb, As and Pb) that may occur together in different minerals. Total organic carbon (TOC) have been analyzed too because it is an essential component in the regulatory mechanisms that control the amount of metal in soils. Even more, exposure to these elements is associated with a number of diseases and environmental problems. These metals can have both natural and anthropogenic origins. A key component of any exposure study is a reliable model of the spatial distribution the elements studied. A geostatistical analysis have been performed in order to show that selected metals are auto-correlated and cross-correlated and type and magnitude of such cross-correlation varies depending on the spatial scale under consideration. After identifying general trends, we analyzed the residues left after subtracting the trend from the raw variables. Three scales of variability were identified (compounds or factors) with scales of 5, 35 and 135 km. The first factor (F1) basically identifies anomalies of natural origin but, in some places, of anthropogenics origin as well. The other two are related to geology (F2 and F3) although F3 represents more clearly geochemical background related to large lithological groups. Likewise, mapping of two major structures indicates that significant faults have influence on the distribution of the studied elements. Finally, influence of soil and lithology on groundwater by means of contingency analysis was assessed.

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

Creation and the empirical validation of the dignity card-sort tool to assess factors influencing erosion of dignity at life's end.

PubMed

Periyakoil, Vyjeyanthi S; Kraemer, Helena Chmura; Noda, Arthur

2009-12-01

Patients often experience erosion of dignity as they cope with the dying process. Preserving patient dignity is a sentinel premise of palliative care. This study was conducted to gain a better understanding of factors influencing erosion of dignity at the end of life. We conducted an open-ended written survey of 100 multidisciplinary providers (69% response rate) and responses were categorized to identify 18 themes that were used to create a card-sort tool. The initial 18-item tool was administered to nurses (n = 83), nonhospice community-dwelling subjects (n = 190) and hospice patients (n = 26) and a principal component analysis (PCA) was used to identify the 6 primary factors. The key item in each factor as identified by the PCA was used to create the final 6-item dignity card-sort tool (DCT). The DCT was also administered to physicians caring for palliative care patients (n = 21). For each of the final 6 items, the correlation between the respondents (nurses, physicians, nonterminally ill subjects, and subjects receiving hospice care) was calculated using the Spearman's correlation coefficient. The nurses were very highly positively correlated with the physicians (correlation coefficient = 0.94) and the community-dwelling nonterminally ill subjects were highly positively correlated with the subjects receiving hospice care (correlation coefficient = 0.67). More importantly, both the nurses and physicians were negatively correlated with both community dwelling nonterminally ill subjects and the subjects receiving hospice care. The health professionals in the study felt that treating a patient with disrespect and not carrying out their wishes resulted in erosion of dignity. In contrast patients thought that poor medical care and untreated pain were the most important factors leading to erosion of dignity at life's end. The DCT is a promising tool that may help clinicians identify key factors resulting in perceptions of erosion of dignity in adult palliative care patients.

Creation and the Empirical Validation of the Dignity Card-Sort Tool To Assess Factors Influencing Erosion of Dignity at Life's End

PubMed Central

Chmura Kraemer, Helena; Noda, Arthur

2009-01-01

Abstract Patients often experience erosion of dignity as they cope with the dying process. Preserving patient dignity is a sentinel premise of palliative care. This study was conducted to gain a better understanding of factors influencing erosion of dignity at the end of life. We conducted an open-ended written survey of 100 multidisciplinary providers (69% response rate) and responses were categorized to identify 18 themes that were used to create a card-sort tool. The initial 18-item tool was administered to nurses (n = 83), nonhospice community-dwelling subjects (n = 190) and hospice patients (n = 26) and a principal component analysis (PCA) was used to identify the 6 primary factors. The key item in each factor as identified by the PCA was used to create the final 6-item dignity card-sort tool (DCT). The DCT was also administered to physicians caring for palliative care patients (n = 21). For each of the final 6 items, the correlation between the respondents (nurses, physicians, nonterminally ill subjects, and subjects receiving hospice care) was calculated using the Spearman's correlation coefficient. The nurses were very highly positively correlated with the physicians (correlation coefficient = 0.94) and the community-dwelling nonterminally ill subjects were highly positively correlated with the subjects receiving hospice care (correlation coefficient = 0.67). More importantly, both the nurses and physicians were negatively correlated with both community dwelling nonterminally ill subjects and the subjects receiving hospice care. The health professionals in the study felt that treating a patient with disrespect and not carrying out their wishes resulted in erosion of dignity. In contrast patients thought that poor medical care and untreated pain were the most important factors leading to erosion of dignity at life's end. The DCT is a promising tool that may help clinicians identify key factors resulting in perceptions of erosion of dignity in adult palliative care patients. PMID:19708793

SurvNet: a web server for identifying network-based biomarkers that most correlate with patient survival data.

PubMed

Li, Jun; Roebuck, Paul; Grünewald, Stefan; Liang, Han

2012-07-01

An important task in biomedical research is identifying biomarkers that correlate with patient clinical data, and these biomarkers then provide a critical foundation for the diagnosis and treatment of disease. Conventionally, such an analysis is based on individual genes, but the results are often noisy and difficult to interpret. Using a biological network as the searching platform, network-based biomarkers are expected to be more robust and provide deep insights into the molecular mechanisms of disease. We have developed a novel bioinformatics web server for identifying network-based biomarkers that most correlate with patient survival data, SurvNet. The web server takes three input files: one biological network file, representing a gene regulatory or protein interaction network; one molecular profiling file, containing any type of gene- or protein-centred high-throughput biological data (e.g. microarray expression data or DNA methylation data); and one patient survival data file (e.g. patients' progression-free survival data). Given user-defined parameters, SurvNet will automatically search for subnetworks that most correlate with the observed patient survival data. As the output, SurvNet will generate a list of network biomarkers and display them through a user-friendly interface. SurvNet can be accessed at http://bioinformatics.mdanderson.org/main/SurvNet.

Prison Radicalization: The New Extremist Training Grounds?

DTIC Science & Technology

2007-09-01

distributing and collecting survey data , and the data analysis. The analytical methodology includes descriptive and inferential statistical methods, in... statistical analysis of the responses to identify significant correlations and relationships. B. SURVEY DATA COLLECTION To effectively access a...Q18, Q19, Q20, and Q21. Due to the exploratory nature of this small survey, data analyses were confined mostly to descriptive statistics and

Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters

PubMed Central

Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome. PMID:25821507

Fish functional traits correlated with environmental variables in a temperate biodiversity hotspot.

PubMed

Keck, Benjamin P; Marion, Zachary H; Martin, Derek J; Kaufman, Jason C; Harden, Carol P; Schwartz, John S; Strange, Richard J

2014-01-01

The global biodiversity crisis has invigorated the search for generalized patterns in most disciplines within the natural sciences. Studies based on organismal functional traits attempt to broaden implications of results by identifying the response of functional traits, instead of taxonomic units, to environmental variables. Determining the functional trait responses enables more direct comparisons with, or predictions for, communities of different taxonomic composition. The North American freshwater fish fauna is both diverse and increasingly imperiled through human mediated disturbances, including climate change. The Tennessee River, USA, contains one of the most diverse assemblages of freshwater fish in North America and has more imperiled species than other rivers, but there has been no trait-based study of community structure in the system. We identified 211 localities in the upper Tennessee River that were sampled by the Tennessee Valley Authority between 2009 and 2011 and compiled fish functional traits for the observed species and environmental variables for each locality. Using fourth corner analysis, we identified significant correlations between many fish functional traits and environmental variables. Functional traits associated with an opportunistic life history strategy were correlated with localities subject to greater land use disturbance and less flow regulation, while functional traits associated with a periodic life history strategy were correlated with localities subject to regular disturbance and regulated flow. These are patterns observed at the continental scale, highlighting the generalizability of trait-based methods. Contrary to studies that found no community structure differences when considering riparian buffer zones, we found that fish functional traits were correlated with different environmental variables between analyses with buffer zones vs. entire catchment area land cover proportions. Using existing databases and fourth corner analysis, our results support the broad application potential for trait-based methods and indicate trait-based methods can detect environmental filtering by riparian zone land cover.

Whole-Genome Sequencing Analysis Accurately Predicts Antimicrobial Resistance Phenotypes in Campylobacter spp.

PubMed Central

Tyson, G. H.; Chen, Y.; Li, C.; Mukherjee, S.; Young, S.; Lam, C.; Folster, J. P.; Whichard, J. M.; McDermott, P. F.

2015-01-01

The objectives of this study were to identify antimicrobial resistance genotypes for Campylobacter and to evaluate the correlation between resistance phenotypes and genotypes using in vitro antimicrobial susceptibility testing and whole-genome sequencing (WGS). A total of 114 Campylobacter species isolates (82 C. coli and 32 C. jejuni) obtained from 2000 to 2013 from humans, retail meats, and cecal samples from food production animals in the United States as part of the National Antimicrobial Resistance Monitoring System were selected for study. Resistance phenotypes were determined using broth microdilution of nine antimicrobials. Genomic DNA was sequenced using the Illumina MiSeq platform, and resistance genotypes were identified using assembled WGS sequences through blastx analysis. Eighteen resistance genes, including tet(O), blaOXA-61, catA, lnu(C), aph(2″)-Ib, aph(2″)-Ic, aph(2′)-If, aph(2″)-Ig, aph(2″)-Ih, aac(6′)-Ie-aph(2″)-Ia, aac(6′)-Ie-aph(2″)-If, aac(6′)-Im, aadE, sat4, ant(6′), aad9, aph(3′)-Ic, and aph(3′)-IIIa, and mutations in two housekeeping genes (gyrA and 23S rRNA) were identified. There was a high degree of correlation between phenotypic resistance to a given drug and the presence of one or more corresponding resistance genes. Phenotypic and genotypic correlation was 100% for tetracycline, ciprofloxacin/nalidixic acid, and erythromycin, and correlations ranged from 95.4% to 98.7% for gentamicin, azithromycin, clindamycin, and telithromycin. All isolates were susceptible to florfenicol, and no genes associated with florfenicol resistance were detected. There was a strong correlation (99.2%) between resistance genotypes and phenotypes, suggesting that WGS is a reliable indicator of resistance to the nine antimicrobial agents assayed in this study. WGS has the potential to be a powerful tool for antimicrobial resistance surveillance programs. PMID:26519386

Whole-Genome Sequencing Analysis Accurately Predicts Antimicrobial Resistance Phenotypes in Campylobacter spp.

PubMed

Zhao, S; Tyson, G H; Chen, Y; Li, C; Mukherjee, S; Young, S; Lam, C; Folster, J P; Whichard, J M; McDermott, P F

2016-01-15

The objectives of this study were to identify antimicrobial resistance genotypes for Campylobacter and to evaluate the correlation between resistance phenotypes and genotypes using in vitro antimicrobial susceptibility testing and whole-genome sequencing (WGS). A total of 114 Campylobacter species isolates (82 C. coli and 32 C. jejuni) obtained from 2000 to 2013 from humans, retail meats, and cecal samples from food production animals in the United States as part of the National Antimicrobial Resistance Monitoring System were selected for study. Resistance phenotypes were determined using broth microdilution of nine antimicrobials. Genomic DNA was sequenced using the Illumina MiSeq platform, and resistance genotypes were identified using assembled WGS sequences through blastx analysis. Eighteen resistance genes, including tet(O), blaOXA-61, catA, lnu(C), aph(2″)-Ib, aph(2″)-Ic, aph(2')-If, aph(2″)-Ig, aph(2″)-Ih, aac(6')-Ie-aph(2″)-Ia, aac(6')-Ie-aph(2″)-If, aac(6')-Im, aadE, sat4, ant(6'), aad9, aph(3')-Ic, and aph(3')-IIIa, and mutations in two housekeeping genes (gyrA and 23S rRNA) were identified. There was a high degree of correlation between phenotypic resistance to a given drug and the presence of one or more corresponding resistance genes. Phenotypic and genotypic correlation was 100% for tetracycline, ciprofloxacin/nalidixic acid, and erythromycin, and correlations ranged from 95.4% to 98.7% for gentamicin, azithromycin, clindamycin, and telithromycin. All isolates were susceptible to florfenicol, and no genes associated with florfenicol resistance were detected. There was a strong correlation (99.2%) between resistance genotypes and phenotypes, suggesting that WGS is a reliable indicator of resistance to the nine antimicrobial agents assayed in this study. WGS has the potential to be a powerful tool for antimicrobial resistance surveillance programs. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Fish Functional Traits Correlated with Environmental Variables in a Temperate Biodiversity Hotspot

PubMed Central

Keck, Benjamin P.; Marion, Zachary H.; Martin, Derek J.; Kaufman, Jason C.; Harden, Carol P.; Schwartz, John S.; Strange, Richard J.

2014-01-01

The global biodiversity crisis has invigorated the search for generalized patterns in most disciplines within the natural sciences. Studies based on organismal functional traits attempt to broaden implications of results by identifying the response of functional traits, instead of taxonomic units, to environmental variables. Determining the functional trait responses enables more direct comparisons with, or predictions for, communities of different taxonomic composition. The North American freshwater fish fauna is both diverse and increasingly imperiled through human mediated disturbances, including climate change. The Tennessee River, USA, contains one of the most diverse assemblages of freshwater fish in North America and has more imperiled species than other rivers, but there has been no trait-based study of community structure in the system. We identified 211 localities in the upper Tennessee River that were sampled by the Tennessee Valley Authority between 2009 and 2011 and compiled fish functional traits for the observed species and environmental variables for each locality. Using fourth corner analysis, we identified significant correlations between many fish functional traits and environmental variables. Functional traits associated with an opportunistic life history strategy were correlated with localities subject to greater land use disturbance and less flow regulation, while functional traits associated with a periodic life history strategy were correlated with localities subject to regular disturbance and regulated flow. These are patterns observed at the continental scale, highlighting the generalizability of trait-based methods. Contrary to studies that found no community structure differences when considering riparian buffer zones, we found that fish functional traits were correlated with different environmental variables between analyses with buffer zones vs. entire catchment area land cover proportions. Using existing databases and fourth corner analysis, our results support the broad application potential for trait-based methods and indicate trait-based methods can detect environmental filtering by riparian zone land cover. PMID:24676053

Re-evaluating the link between brain size and behavioural ecology in primates.

PubMed

Powell, Lauren E; Isler, Karin; Barton, Robert A

2017-10-25

Comparative studies have identified a wide range of behavioural and ecological correlates of relative brain size, with results differing between taxonomic groups, and even within them. In primates for example, recent studies contradict one another over whether social or ecological factors are critical. A basic assumption of such studies is that with sufficiently large samples and appropriate analysis, robust correlations indicative of selection pressures on cognition will emerge. We carried out a comprehensive re-examination of correlates of primate brain size using two large comparative datasets and phylogenetic comparative methods. We found evidence in both datasets for associations between brain size and ecological variables (home range size, diet and activity period), but little evidence for an effect of social group size, a correlation which has previously formed the empirical basis of the Social Brain Hypothesis. However, reflecting divergent results in the literature, our results exhibited instability across datasets, even when they were matched for species composition and predictor variables. We identify several potential empirical and theoretical difficulties underlying this instability and suggest that these issues raise doubts about inferring cognitive selection pressures from behavioural correlates of brain size. © 2017 The Author(s).

Minimum number of measurements for evaluating Bertholletia excelsa.

PubMed

Baldoni, A B; Tonini, H; Tardin, F D; Botelho, S C C; Teodoro, P E

2017-09-27

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of Brazil nut tree (Bertholletia excelsa) genotypes based on fruit yield. For this, we assessed the number of fruits and dry mass of seeds of 75 Brazil nut genotypes, from native forest, located in the municipality of Itaúba, MT, for 5 years. To better estimate r, four procedures were used: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (CPCOR), principal component analysis based on the phenotypic variance and covariance matrix (CPCOV), and structural analysis based on the correlation matrix (mean r - AECOR). There was a significant effect of genotypes and measurements, which reveals the need to study the minimum number of measurements for selecting superior Brazil nut genotypes for a production increase. Estimates of r by ANOVA were lower than those observed with the principal component methodology and close to AECOR. The CPCOV methodology provided the highest estimate of r, which resulted in a lower number of measurements needed to identify superior Brazil nut genotypes for the number of fruits and dry mass of seeds. Based on this methodology, three measurements are necessary to predict the true value of the Brazil nut genotypes with a minimum accuracy of 85%.

[Quantitative analysis of drug expenditures variability in dermatology units].

PubMed

Moreno-Ramírez, David; Ferrándiz, Lara; Ramírez-Soto, Gabriel; Muñoyerro, M Dolores

2013-01-01

Variability in adjusted drug expenditures among clinical departments raises the possibility of difficult access to certain therapies at the time that avoidable expenditures may also exist. Nevertheless, drug expenditures are not usually applied to clinical practice variability analysis. To identify and quantify variability in drug expenditures in comparable dermatology department of the Servicio Andaluz de Salud. Comparative economic analysis regarding the drug expenditures adjusted to population and health care production in 18 dermatology departments of the Servicio Andaluz de Salud. The 2012 cost and production data (homogeneous production units -HPU-)were provided by Inforcoan, the cost accounting information system of the Servicio Andaluz de Salud. The observed drug expenditure ratio ranged from 0.97?/inh to 8.90?/inh and from 208.45?/HPU to 1,471.95?/ HPU. The Pearson correlation between drug expenditure and population was 0.25 and 0.35 for the correlation between expenditure and homogeneous production (p=0.32 and p=0,15, respectively), both Pearson coefficients confirming the lack of correlation and arelevant degree of variability in drug expenditures. The quantitative analysis of variability performed through Pearson correlation has confirmed the existence of drug expenditure variability among comparable dermatology departments. Copyright © 2013 SEFH. Published by AULA MEDICA. All rights reserved.

Interplay between past market correlation structure changes and future volatility outbursts.

PubMed

Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T

2016-11-18

We report significant relations between past changes in the market correlation structure and future changes in the market volatility. This relation is made evident by using a measure of "correlation structure persistence" on correlation-based information filtering networks that quantifies the rate of change of the market dependence structure. We also measured changes in the correlation structure by means of a "metacorrelation" that measures a lagged correlation between correlation matrices computed over different time windows. Both methods show a deep interplay between past changes in correlation structure and future changes in volatility and we demonstrate they can anticipate market risk variations and this can be used to better forecast portfolio risk. Notably, these methods overcome the curse of dimensionality that limits the applicability of traditional econometric tools to portfolios made of a large number of assets. We report on forecasting performances and statistical significance of both methods for two different equity datasets. We also identify an optimal region of parameters in terms of True Positive and False Positive trade-off, through a ROC curve analysis. We find that this forecasting method is robust and it outperforms logistic regression predictors based on past volatility only. Moreover the temporal analysis indicates that methods based on correlation structural persistence are able to adapt to abrupt changes in the market, such as financial crises, more rapidly than methods based on past volatility.

Interplay between past market correlation structure changes and future volatility outbursts

NASA Astrophysics Data System (ADS)

Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T.

2016-11-01

We report significant relations between past changes in the market correlation structure and future changes in the market volatility. This relation is made evident by using a measure of “correlation structure persistence” on correlation-based information filtering networks that quantifies the rate of change of the market dependence structure. We also measured changes in the correlation structure by means of a “metacorrelation” that measures a lagged correlation between correlation matrices computed over different time windows. Both methods show a deep interplay between past changes in correlation structure and future changes in volatility and we demonstrate they can anticipate market risk variations and this can be used to better forecast portfolio risk. Notably, these methods overcome the curse of dimensionality that limits the applicability of traditional econometric tools to portfolios made of a large number of assets. We report on forecasting performances and statistical significance of both methods for two different equity datasets. We also identify an optimal region of parameters in terms of True Positive and False Positive trade-off, through a ROC curve analysis. We find that this forecasting method is robust and it outperforms logistic regression predictors based on past volatility only. Moreover the temporal analysis indicates that methods based on correlation structural persistence are able to adapt to abrupt changes in the market, such as financial crises, more rapidly than methods based on past volatility.

Interplay between past market correlation structure changes and future volatility outbursts

PubMed Central

Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T.

2016-01-01

We report significant relations between past changes in the market correlation structure and future changes in the market volatility. This relation is made evident by using a measure of “correlation structure persistence” on correlation-based information filtering networks that quantifies the rate of change of the market dependence structure. We also measured changes in the correlation structure by means of a “metacorrelation” that measures a lagged correlation between correlation matrices computed over different time windows. Both methods show a deep interplay between past changes in correlation structure and future changes in volatility and we demonstrate they can anticipate market risk variations and this can be used to better forecast portfolio risk. Notably, these methods overcome the curse of dimensionality that limits the applicability of traditional econometric tools to portfolios made of a large number of assets. We report on forecasting performances and statistical significance of both methods for two different equity datasets. We also identify an optimal region of parameters in terms of True Positive and False Positive trade-off, through a ROC curve analysis. We find that this forecasting method is robust and it outperforms logistic regression predictors based on past volatility only. Moreover the temporal analysis indicates that methods based on correlation structural persistence are able to adapt to abrupt changes in the market, such as financial crises, more rapidly than methods based on past volatility. PMID:27857144

Detecting PM2.5's Correlations between Neighboring Cities Using a Time-Lagged Cross-Correlation Coefficient.

PubMed

Wang, Fang; Wang, Lin; Chen, Yuming

2017-08-31

In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

Behavioral Pediatrics Feeding Assessment Scale in Young Children With Autism Spectrum Disorder: Psychometrics and Associations With Child and Parent Variables

PubMed Central

Allen, Stephanie L.; Duku, Eric; Vaillancourt, Tracy; Szatmari, Peter; Bryson, Susan; Fombonne, Eric; Volden, Joanne; Waddell, Charlotte; Zwaigenbaum, Lonnie; Roberts, Wendy; Mirenda, Pat; Bennett, Teresa; Elsabbagh, Mayada; Georgiades, Stelios

2015-01-01

Objective The factor structure and validity of the Behavioral Pediatrics Feeding Assessment Scale (BPFAS; Crist & Napier-Phillips, 2001) were examined in preschoolers with autism spectrum disorder (ASD). Methods Confirmatory factor analysis was used to examine the original BPFAS five-factor model, the fit of each latent variable, and a rival one-factor model. None of the models was adequate, thus a categorical exploratory factor analysis (CEFA) was conducted. Correlations were used to examine relations between the BPFAS and concurrent variables of interest. Results The CEFA identified an acceptable three-factor model. Correlational analyses indicated that feeding problems were positively related to parent-reported autism symptoms, behavior problems, sleep problems, and parenting stress, but largely unrelated to performance-based indices of autism symptom severity, language, and cognitive abilities, as well as child age. Conclusion These results provide evidence supporting the use of the identified BPFAS three-factor model for samples of young children with ASD. PMID:25725217

Using canonical correlation analysis to identify environmental attitude groups: considerations for national forest planning in the southwestern U.S.

PubMed

Prera, Alejandro J; Grimsrud, Kristine M; Thacher, Jennifer A; McCollum, Dan W; Berrens, Robert P

2014-10-01

As public land management agencies pursue region-specific resource management plans, with meaningful consideration of public attitudes and values, there is a need to characterize the complex mix of environmental attitudes in a diverse population. The contribution of this investigation is to make use of a unique household, mail/internet survey data set collected in 2007 in the Southwestern United States (Region 3 of the U.S. Forest Service). With over 5,800 survey responses to a set of 25 Public Land Value statements, canonical correlation analysis is able to identify 7 statistically distinct environmental attitudinal groups. We also examine the effect of expected changes in regional demographics on overall environmental attitudes, which may help guide in the development of socially acceptable long-term forest management policies. Results show significant support for conservationist management policies and passive environmental values, as well as a greater role for stakeholder groups in generating consensus for current and future forest management policies.

Correlational structure of ‘frontal’ tests and intelligence tests indicates two components with asymmetrical neurostructural correlates in old age

PubMed Central

Cox, Simon R.; MacPherson, Sarah E.; Ferguson, Karen J.; Nissan, Jack; Royle, Natalie A.; MacLullich, Alasdair M.J.; Wardlaw, Joanna M.; Deary, Ian J.

2014-01-01

Both general fluid intelligence (gf) and performance on some ‘frontal tests’ of cognition decline with age. Both types of ability are at least partially dependent on the integrity of the frontal lobes, which also deteriorate with age. Overlap between these two methods of assessing complex cognition in older age remains unclear. Such overlap could be investigated using inter-test correlations alone, as in previous studies, but this would be enhanced by ascertaining whether frontal test performance and gf share neurobiological variance. To this end, we examined relationships between gf and 6 frontal tests (Tower, Self-Ordered Pointing, Simon, Moral Dilemmas, Reversal Learning and Faux Pas tests) in 90 healthy males, aged ~ 73 years. We interpreted their correlational structure using principal component analysis, and in relation to MRI-derived regional frontal lobe volumes (relative to maximal healthy brain size). gf correlated significantly and positively (.24 ≤ r ≤ .53) with the majority of frontal test scores. Some frontal test scores also exhibited shared variance after controlling for gf. Principal component analysis of test scores identified units of gf-common and gf-independent variance. The former was associated with variance in the left dorsolateral (DL) and anterior cingulate (AC) regions, and the latter with variance in the right DL and AC regions. Thus, we identify two biologically-meaningful components of variance in complex cognitive performance in older age and suggest that age-related changes to DL and AC have the greatest cognitive impact. PMID:25278641

Correlational structure of 'frontal' tests and intelligence tests indicates two components with asymmetrical neurostructural correlates in old age.

PubMed

Cox, Simon R; MacPherson, Sarah E; Ferguson, Karen J; Nissan, Jack; Royle, Natalie A; MacLullich, Alasdair M J; Wardlaw, Joanna M; Deary, Ian J

2014-09-01

Both general fluid intelligence ( g f ) and performance on some 'frontal tests' of cognition decline with age. Both types of ability are at least partially dependent on the integrity of the frontal lobes, which also deteriorate with age. Overlap between these two methods of assessing complex cognition in older age remains unclear. Such overlap could be investigated using inter-test correlations alone, as in previous studies, but this would be enhanced by ascertaining whether frontal test performance and g f share neurobiological variance. To this end, we examined relationships between g f and 6 frontal tests (Tower, Self-Ordered Pointing, Simon, Moral Dilemmas, Reversal Learning and Faux Pas tests) in 90 healthy males, aged ~ 73 years. We interpreted their correlational structure using principal component analysis, and in relation to MRI-derived regional frontal lobe volumes (relative to maximal healthy brain size). g f correlated significantly and positively (.24 ≤  r  ≤ .53) with the majority of frontal test scores. Some frontal test scores also exhibited shared variance after controlling for g f . Principal component analysis of test scores identified units of g f -common and g f -independent variance. The former was associated with variance in the left dorsolateral (DL) and anterior cingulate (AC) regions, and the latter with variance in the right DL and AC regions. Thus, we identify two biologically-meaningful components of variance in complex cognitive performance in older age and suggest that age-related changes to DL and AC have the greatest cognitive impact.

Effects of landscape change on fish assemblage structure in a rapidly growing metropolitan area in North Carolina, USA

USGS Publications Warehouse

Kennen, J.G.; Chang, M.; Tracy, B.H.

2005-01-01

We evaluated a comprehensive set of natural and land-use attributes that represent the major facets of urban development at fish monitoring sites in the rapidly growing Raleigh-Durham, North Carolina metropolitan area. We used principal component and correlation analysis to obtain a nonredundant subset of variables that extracted most variation in the complete set. With this subset of variables, we assessed the effect of urban growth on fish assemblage structure. We evaluated variation in fish assemblage structure with nonmetric multidimensional scaling (NMDS). We used correlation analysis to identify the most important environmental and landscape variables associated with significant NMDS axes. The second NMDS axis is related to many indices of land-use/land-cover change and habitat. Significant correlations with proportion of largest forest patch to total patch size (r = -0.460, P < 0.01), diversity of patch types (r = 0.554, P < 0.001), and population density (r = 0.385, P < 0.05) helped identify NMDS axis 2 as a disturbance gradient. Positive and negative correlations between the abundance of redbreast sunfish Lepomis auritus and bluehead chub Nocomis leptocephalus, respectively, and NMDS axis 2 also were evident. The North Carolina index of biotic integrity and many of its component metrics were highly correlated with urbanization. These results indicate that aquatic ecosystem integrity would be optimized by a comprehensive integrated management strategy that includes the preservation of landscape function by maximizing the conservation of contiguous tracts of forested lands and vegetative cover in watersheds. ?? 2005 by the American Fisheries Society.

A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores

PubMed Central

Wan, Tao; Bloch, B. Nicolas; Plecha, Donna; Thompson, CheryI L.; Gilmore, Hannah; Jaffe, Carl; Harris, Lyndsay; Madabhushi, Anant

2016-01-01

To identify computer extracted imaging features for estrogen receptor (ER)-positive breast cancers on dynamic contrast en-hanced (DCE)-MRI that are correlated with the low and high OncotypeDX risk categories. We collected 96 ER-positivebreast lesions with low (<18, N = 55) and high (>30, N = 41) OncotypeDX recurrence scores. Each lesion was quantitatively charac-terize via 6 shape features, 3 pharmacokinetics, 4 enhancement kinetics, 4 intensity kinetics, 148 textural kinetics, 5 dynamic histogram of oriented gradient (DHoG), and 6 dynamic local binary pattern (DLBP) features. The extracted features were evaluated by a linear discriminant analysis (LDA) classifier in terms of their ability to distinguish low and high OncotypeDX risk categories. Classification performance was evaluated by area under the receiver operator characteristic curve (Az). The DHoG and DLBP achieved Az values of 0.84 and 0.80, respectively. The 6 top features identified via feature selection were subsequently combined with the LDA classifier to yield an Az of 0.87. The correlation analysis showed that DHoG (ρ = 0.85, P < 0.001) and DLBP (ρ = 0.83, P < 0.01) were significantly associated with the low and high risk classifications from the OncotypeDX assay. Our results indicated that computer extracted texture features of DCE-MRI were highly correlated with the high and low OncotypeDX risk categories for ER-positive cancers. PMID:26887643

Evaluation of remote sensing in control of pink cotton bollworm

NASA Technical Reports Server (NTRS)

Lewis, L. N. (Principal Investigator); Coleman, V. B.

1972-01-01

The author has identified the following significant results. This investigation is attempting to evaluate the use of a satellite in monitoring the cotton production regulation program of the State of California as an aid in controlling pink bollworm infestation in the southern deserts of California. Color combined images of ERTS-1 multispectral images simulating color infrared are being used in crop identification. The status of each field is mapped from the imagery and is then compared to ground surveys taken at the time of each ERTS-1 overflight. Correlation has been to date 100%. A computer analysis will be performed to compare field status with the crop calendar in order to identify crops. Correlation is expected to be 80 to 90%. Cotton fields, because of their state regulated season which is exactly coincident with no other crop, are expected to be easily identified.

Analysis of histological findings obtained combining US/mp-MRI fusion-guided biopsies with systematic US biopsies: mp-MRI role in prostate cancer detection and false negative.

PubMed

Faiella, Eliodoro; Santucci, Domiziana; Greco, Federico; Frauenfelder, Giulia; Giacobbe, Viola; Muto, Giovanni; Zobel, Bruno Beomonte; Grasso, Rosario Francesco

2018-02-01

To evaluate the diagnostic accuracy of mp-MRI correlating US/mp-MRI fusion-guided biopsy with systematic random US-guided biopsy in prostate cancer diagnosis. 137 suspected prostatic abnormalities were identified on mp-MRI (1.5T) in 96 patients and classified according to PI-RADS score v2. All target lesions underwent US/mp-MRI fusion biopsy and prostatic sampling was completed by US-guided systematic random 12-core biopsies. Histological analysis and Gleason score were established for all the samples, both target lesions defined by mp-MRI, and random biopsies. PI-RADS score was correlated with the histological results, divided in three groups (benign tissue, atypia and carcinoma) and with Gleason groups, divided in four categories considering the new Grading system of the ISUP 2014, using t test. Multivariate analysis was used to correlate PI-RADS and Gleason categories to PSA level and abnormalities axial diameter. When the random core biopsies showed carcinoma (mp-MRI false-negatives), PSA value and lesions Gleason median value were compared with those of carcinomas identified by mp-MRI (true-positives), using t test. There was statistically significant difference between PI-RADS score in carcinoma, atypia and benign lesions groups (4.41, 3.61 and 3.24, respectively) and between PI-RADS score in Gleason < 7 group and Gleason > 7 group (4.14 and 4.79, respectively). mp-MRI performance was more accurate for lesions > 15 mm and in patients with PSA > 6 ng/ml. In systematic sampling, 130 (11.25%) mp-MRI false-negative were identified. There was no statistic difference in Gleason median value (7.0 vs 7.06) between this group and the mp-MRI true-positives, but a significant lower PSA median value was demonstrated (7.08 vs 7.53 ng/ml). mp-MRI remains the imaging modality of choice to identify PCa lesions. Integrating US-guided random sampling with US/mp-MRI fusion target lesions sampling, 3.49% of false-negative were identified.

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

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

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are consideredmore » for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.« less

Two-dimensional correlation spectroscopy reveals the underlying compositions for FT-NIR identification of the medicinal bulbs of the genus Fritillaria

NASA Astrophysics Data System (ADS)

Chen, Jianbo; Wang, Yue; Liu, Aoxue; Rong, Lixin; Wang, Jingjuan

2018-03-01

Fritillariae Bulbus, the dried bulbs of several species of the genus Fritillaria, is often used in traditional Chinese medicine for the treatment of cough and pulmonary diseases. However, the similar appearances make it difficult to identify different kinds of Fritillariae Bulbus. In this research, Fourier transform near-infrared (FT-NIR) spectroscopy with a reflection fiber probe is employed for the direct testing and automatic identification of different kinds of Fritillariae Bulbus to ensure the authenticity, efficacy and safety. The bulbs can be measured directly without pulverizing. According to the two-dimensional (2D) correlation analysis and statistical analysis, the height ratio of the two peaks near 4860 cm-1 and 4750 cm-1 in the second derivative spectra is specific to the species of Fritillariae Bulbus. This indicates that the relative amount of protein and carbohydrate may be critical to identify Fritillariae Bulbus. With the help of the SIMCA model, the four kinds of Fritillariae Bulbus can be identified correctly by FT-NIR spectroscopy. The results show the potential of FT-NIR spectroscopy with a reflection fiber probe in the rapid testing and identification of Fritillariae Bulbus.

Efficiency of the Bethesda System for Thyroid Cytopathology.

PubMed

Mora-Guzmán, Ismael; Muñoz de Nova, José Luis; Marín-Campos, Cristina; Jiménez-Heffernan, José Antonio; Cuesta Pérez, Juan Julián; Lahera Vargas, Marcos; Torres Mínguez, Emma; Martín-Pérez, Elena

2018-03-28

Fine-needle aspiration biopsies are a key tool for preoperative assessment of thyroid nodules, and the Bethesda system is the preferred method to report cytological analysis. The purpose of this study is to assess the efficiency of the Bethesda system to identify the malignancy risk of thyroid nodules. Patients who underwent thyroid surgery between June 2010 and June 2017 were included. Samples were classified into 6categories according to rates of malignancy associated with each diagnostic category. In order to investigate the correlation between categories, a statistical analysis compared the categories with pathology reports. Diagnostic indicators were calculated as a screening test (categories IV, V, VI as true-positive) and as a method to identify malignancy (V, VI as true-positive). In a series of 522 patients, we found 184 (35.2%) malignant tumours, papillary carcinoma being the most prevalent with 155 cases (84.2%). Malignant rates for diagnostic categories were: I, 0%; II, 1.5%; III, 6.4%; IV, 31%; V, 86.5%; VI, 100%. A robust correlation was identified between categories on statistical analysis. For the «screening test» analysis, sensitivity was 98.9%, specificity 84.4%, positive predictive value 69.6%, negative predictive value 99.5%, and diagnostic accuracy 88.2%. Analysing the accuracy to detect malignancy, values were: sensitivity 98.6%, specificity 97.6%, positive predictive value 93.5%, negative predictive value 99.5%, diagnostic accuracy 97.9%. The Bethesda system is a clear and reliable approach to report thyroid cytology and therefore is an effective tool to identify malignancy risk and guide clinical management. Copyright © 2018 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

Lucero, E.; Russo, T. A.; Zentner, M.; May, J.; Nguy-Robertson, A. L.

2016-12-01

Reservoirs serve multiple functions and are vital for storage, electricity generation, and flood control. For many areas, traditional ground-based reservoir measurements may not be available or data dissemination may be problematic. Consistent monitoring of reservoir levels in data-poor areas can be achieved through remote sensing, providing information to researchers and the international community. Estimates of trends and relative reservoir volume can be used to identify water supply vulnerability, anticipate low power generation, and predict flood risk. Image processing with automated cloud computing provides opportunities to study multiple geographic areas in near real-time. We demonstrate the prediction capability of a cloud environment for identifying water trends at reservoirs in the US, and then apply the method to data-poor areas in North Korea, Iran, Azerbaijan, Zambia, and India. The Google Earth Engine cloud platform hosts remote sensing data and can be used to automate reservoir level estimation with multispectral imagery. We combine automated cloud-based analysis from Landsat image classification to identify reservoir surface area trends and radar altimetry to identify reservoir level trends. The study estimates water level trends using three years of data from four domestic reservoirs to validate the remote sensing method, and five foreign reservoirs to demonstrate the method application. We report correlations between ground-based reservoir level measurements in the US and our remote sensing methods, and correlations between the cloud analysis and altimetry data for reservoirs in data-poor areas. The availability of regular satellite imagery and an automated, near real-time application method provides the necessary datasets for further temporal analysis, reservoir modeling, and flood forecasting. All statements of fact, analysis, or opinion are those of the author and do not reflect the official policy or position of the Department of Defense or any of its components or the U.S. Government

Fluctuation Diagnostics of the Electron Self-Energy: Origin of the Pseudogap Physics.

PubMed

Gunnarsson, O; Schäfer, T; LeBlanc, J P F; Gull, E; Merino, J; Sangiovanni, G; Rohringer, G; Toschi, A

2015-06-12

We demonstrate how to identify which physical processes dominate the low-energy spectral functions of correlated electron systems. We obtain an unambiguous classification through an analysis of the equation of motion for the electron self-energy in its charge, spin, and particle-particle representations. Our procedure is then employed to clarify the controversial physics responsible for the appearance of the pseudogap in correlated systems. We illustrate our method by examining the attractive and repulsive Hubbard model in two dimensions. In the latter, spin fluctuations are identified as the origin of the pseudogap, and we also explain why d-wave pairing fluctuations play a marginal role in suppressing the low-energy spectral weight, independent of their actual strength.

Transcriptome interrogation of human myometrium identifies differentially expressed sense-antisense pairs of protein-coding and long non-coding RNA genes in spontaneous labor at term.

PubMed

Romero, Roberto; Tarca, Adi L; Chaemsaithong, Piya; Miranda, Jezid; Chaiworapongsa, Tinnakorn; Jia, Hui; Hassan, Sonia S; Kalita, Cynthia A; Cai, Juan; Yeo, Lami; Lipovich, Leonard

2014-09-01

To identify differentially expressed long non-coding RNA (lncRNA) genes in human myometrium in women with spontaneous labor at term. Myometrium was obtained from women undergoing cesarean deliveries who were not in labor (n = 19) and women in spontaneous labor at term (n = 20). RNA was extracted and profiled using an Illumina® microarray platform. We have used computational approaches to bound the extent of long non-coding RNA representation on this platform, and to identify co-differentially expressed and correlated pairs of long non-coding RNA genes and protein-coding genes sharing the same genomic loci. We identified co-differential expression and correlation at two genomic loci that contain coding-lncRNA gene pairs: SOCS2-AK054607 and LMCD1-NR_024065 in women in spontaneous labor at term. This co-differential expression and correlation was validated by qRT-PCR, an experimental method completely independent of the microarray analysis. Intriguingly, one of the two lncRNA genes differentially expressed in term labor had a key genomic structure element, a splice site, that lacked evolutionary conservation beyond primates. We provide, for the first time, evidence for coordinated differential expression and correlation of cis-encoded antisense lncRNAs and protein-coding genes with known as well as novel roles in pregnancy in the myometrium of women in spontaneous labor at term.

Genetic Modifiers of Neurofibromatosis Type 1-Associated Café-au-Lait Macule Count Identified Using Multi-platform Analysis

PubMed Central

Pemov, Alexander; Sung, Heejong; Hyland, Paula L.; Sloan, Jennifer L.; Ruppert, Sarah L.; Baldwin, Andrea M.; Boland, Joseph F.; Bass, Sara E.; Lee, Hyo Jung; Jones, Kristine M.; Zhang, Xijun; Mullikin, James C.; Widemann, Brigitte C.; Wilson, Alexander F.; Stewart, Douglas R.

2014-01-01

Neurofibromatosis type 1 (NF1) is an autosomal dominant, monogenic disorder of dysregulated neurocutaneous tissue growth. Pleiotropy, variable expressivity and few NF1 genotype-phenotype correlates limit clinical prognostication in NF1. Phenotype complexity in NF1 is hypothesized to derive in part from genetic modifiers unlinked to the NF1 locus. In this study, we hypothesized that normal variation in germline gene expression confers risk for certain phenotypes in NF1. In a set of 79 individuals with NF1, we examined the association between gene expression in lymphoblastoid cell lines with NF1-associated phenotypes and sequenced select genes with significant phenotype/expression correlations. In a discovery cohort of 89 self-reported European-Americans with NF1 we examined the association between germline sequence variants of these genes with café-au-lait macule (CALM) count, a tractable, tumor-like phenotype in NF1. Two correlated, common SNPs (rs4660761 and rs7161) between DPH2 and ATP6V0B were significantly associated with the CALM count. Analysis with tiled regression also identified SNP rs4660761 as significantly associated with CALM count. SNP rs1800934 and 12 rare variants in the mismatch repair gene MSH6 were also associated with CALM count. Both SNPs rs7161 and rs4660761 (DPH2 and ATP6V0B) were highly significant in a mega-analysis in a combined cohort of 180 self-reported European-Americans; SNP rs1800934 (MSH6) was near-significant in a meta-analysis assuming dominant effect of the minor allele. SNP rs4660761 is predicted to regulate ATP6V0B, a gene associated with melanosome biology. Individuals with homozygous mutations in MSH6 can develop an NF1-like phenotype, including multiple CALMs. Through a multi-platform approach, we identified variants that influence NF1 CALM count. PMID:25329635

Endometrial biopsy in Holstein-Friesian dairy cows. II. Correlations between histological criteria.

PubMed Central

Bonnett, B N; Miller, R B; Martin, S W; Etherington, W G; Buckrell, B C

1991-01-01

Endometrial biopsies were taken for histological assessment from 97 cows which calved in a commercial dairy herd between April and August 1984. The main objectives of this study were to analyze the interrelationships among histological criteria and to identify a shortlist of histological parameters to be included in subsequent analysis of associations with results of bacteriological culture, clinical findings and reproductive performance. Epithelial height and segmented cell counts were highly correlated within biopsy, between horns and between days. Subjective assessment of inflammation in the epithelium and/or stratum compactum generally identified biopsies which had any inflammation present. Cows which had inflammation in a biopsy from day 26 were likely to show inflammatory changes at day 40. Quantitative and subjective assessments of gland number, dilation and fibrosis were highly correlated. There was a positive association between the number of cross sections and the diameter of glands, and both of these criteria were negatively correlated with fibrosis and inflammatory changes. There may be different functional significance of the same histological finding at a different number of days postpartum. PMID:1884296

Year in school and physical activity stage of change as discriminators of variation in the physical activity correlate profile of adolescent females.

PubMed

Burns, Con; Murphy, John J; MacDonncha, Ciaran

2014-05-01

Knowledge of the physical activity correlate profile of adolescent females will provide insight into decreasing physical activity patterns among adolescent females. Correlates of physical activity and physical activity stage of change were assessed during 2007-2008 among 871 Irish adolescent females in years 1-6 in secondary schools (15.28 ± 1.8 years). Multivariate Analysis of Variance was used to identify whether differences in correlates of physical activity could be detected across year in school and physical activity stages of change. Significant differences (P < .01) were found in 11 of the 16 measured correlates across year in school and in 14 of the 16 correlates across stage of change. Effect size estimates and regression analysis revealed perceived competence, peer social support and intention to be physically active (partial eta range (ηp2) .21-.25) to be the most important predictors of physical activity stage of change. Females in more senior years in school and in earlier physical activity stages of change reported a significantly less positive physical activity correlate profile than females in junior years and in later physical activity stages of change. This finding supports the construct validity of the physical activity stages of change.

Application of principal component analysis in protein unfolding: an all-atom molecular dynamics simulation study.

PubMed

Das, Atanu; Mukhopadhyay, Chaitali

2007-10-28

We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide-ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.

Application of principal component analysis in protein unfolding: An all-atom molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Das, Atanu; Mukhopadhyay, Chaitali

2007-10-01

We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide—ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.

Cross-Correlations and Structures of Aero-Engine Gas Path System Based on DCCA Coefficient and Rooted Tree

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Fan, Jie; Gao, You

2015-12-01

Identifying the mutual interaction is a crucial problem that facilitates the understanding of emerging structures in complex system. We here focus on aero-engine dynamic as an example of complex system. By applying the detrended cross-correlation analysis (DCCA) coefficient method to aero-engine gas path system, we find that the low-spool rotor speed (N1) and high-spool rotor speed (N2) fluctuation series exhibit cross-correlation characteristic. Further, we employ detrended cross-correlation coefficient matrix and rooted tree to investigate the mutual interactions of other gas path variables. The results can infer that the exhaust gas temperature (EGT), N1, N2, fuel flow (WF) and engine pressure ratio (EPR) are main gas path parameters.

Correlates of perceived stigma for people living with epilepsy: A meta-analysis.

PubMed

Shi, Ying; Wang, Shouqi; Ying, Jie; Zhang, Meiling; Liu, Pengcheng; Zhang, Huanhuan; Sun, Jiao

2017-05-01

Epilepsy, one of the most common, serious chronic neurological diseases, is accompanied by different levels of perceived stigma that affects people in almost all age groups. This stigma can negatively impact the physical and mental health of people living with epilepsy (PLWE). Good knowledge of perceived stigma for PLWE is important. In this study, we conducted a meta-analysis to identify the correlates of perceived stigma for PLWE. Studies on factors associated with perceived stigma for PLWE, including sociodemographic, psychosocial, and disease-related variables, were searched in PubMed, PsychINFO, EMBASE, and Web of Science. Nineteen variables (k>1) were included in the meta-analysis. For sociodemographic characteristics, findings revealed that the significant weighted mean correlation (R) for "residence" and "poor financial status" were 0.177 and 0.286, respectively. For disease-related characteristics, all variables of significance, including "seizure severity," "seizure frequency," "number of medicines," and "adverse event" (R ranging from 0.190 to 0.362), were positively correlated with perceived stigma. For psychosocial characteristics, "depression" and "anxiety" with R values of 0.414 and 0.369 were significantly associated with perceived stigma. In addition, "social support," "quality of life (QOLIE-31,89)," "knowledge," and "attitude," with R values ranging from -0.444 to -0.200 indicating negative correlation with perceived stigma. The current meta-analysis evaluated the correlates of perceived stigma for PLWE. Results can serve as a basis for policymakers and healthcare professionals for formulating health promotion and prevention strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

Quantifying frontal plane knee motion during single limb squats: reliability and validity of 2-dimensional measures.

PubMed

Gwynne, Craig R; Curran, Sarah A

2014-12-01

Clinical assessment of lower limb kinematics during dynamic tasks may identify individuals who demonstrate abnormal movement patterns that may lead to etiology of exacerbation of knee conditions such as patellofemoral joint (PFJt) pain. The purpose of this study was to determine the reliability, validity and associated measurement error of a clinically appropriate two-dimensional (2-D) procedure of quantifying frontal plane knee alignment during single limb squats. Nine female and nine male recreationally active subjects with no history of PFJt pain had frontal plane limb alignment assessed using three-dimensional (3-D) motion analysis and digital video cameras (2-D analysis) while performing single limb squats. The association between 2-D and 3-D measures was quantified using Pearson's product correlation coefficients. Intraclass correlation coefficients (ICCs) were determined for within- and between-session reliability of 2-D data and standard error of measurement (SEM) was used to establish measurement error. Frontal plane limb alignment assessed with 2-D analysis demonstrated good correlation compared with 3-D methods (r = 0.64 to 0.78, p < 0.001). Within-session (0.86) and between-session ICCs (0.74) demonstrated good reliability for 2-D measures and SEM scores ranged from 2° to 4°. 2-D measures have good consistency and may provide a valid measure of lower limb alignment when compared to existing 3-D methods. Assessment of lower limb kinematics using 2-D methods may be an accurate and clinically useful alternative to 3-D motion analysis when identifying individuals who demonstrate abnormal movement patterns associated with PFJt pain. 2b.

Brain structure and function correlates of cognitive subtypes in schizophrenia.

PubMed

Geisler, Daniel; Walton, Esther; Naylor, Melissa; Roessner, Veit; Lim, Kelvin O; Charles Schulz, S; Gollub, Randy L; Calhoun, Vince D; Sponheim, Scott R; Ehrlich, Stefan

2015-10-30

Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A phase coherence approach to identifying co-located earthquakes and tremor

NASA Astrophysics Data System (ADS)

Hawthorne, J. C.; Ampuero, J.-P.

2018-05-01

We present and use a phase coherence approach to identify seismic signals that have similar path effects but different source time functions: co-located earthquakes and tremor. The method used is a phase coherence-based implementation of empirical matched field processing, modified to suit tremor analysis. It works by comparing the frequency-domain phases of waveforms generated by two sources recorded at multiple stations. We first cross-correlate the records of the two sources at a single station. If the sources are co-located, this cross-correlation eliminates the phases of the Green's function. It leaves the relative phases of the source time functions, which should be the same across all stations so long as the spatial extent of the sources are small compared with the seismic wavelength. We therefore search for cross-correlation phases that are consistent across stations as an indication of co-located sources. We also introduce a method to obtain relative locations between the two sources, based on back-projection of interstation phase coherence. We apply this technique to analyse two tremor-like signals that are thought to be composed of a number of earthquakes. First, we analyse a 20 s long seismic precursor to a M 3.9 earthquake in central Alaska. The analysis locates the precursor to within 2 km of the mainshock, and it identifies several bursts of energy—potentially foreshocks or groups of foreshocks—within the precursor. Second, we examine several minutes of volcanic tremor prior to an eruption at Redoubt Volcano. We confirm that the tremor source is located close to repeating earthquakes identified earlier in the tremor sequence. The amplitude of the tremor diminishes about 30 s before the eruption, but the phase coherence results suggest that the tremor may persist at some level through this final interval.

Influence of aging on the neural correlates of autobiographical, episodic, and semantic memory retrieval.

PubMed

St-Laurent, Marie; Abdi, Hervé; Burianová, Hana; Grady, Cheryl L

2011-12-01

We used fMRI to assess the neural correlates of autobiographical, semantic, and episodic memory retrieval in healthy young and older adults. Participants were tested with an event-related paradigm in which retrieval demand was the only factor varying between trials. A spatio-temporal partial least square analysis was conducted to identify the main patterns of activity characterizing the groups across conditions. We identified brain regions activated by all three memory conditions relative to a control condition. This pattern was expressed equally in both age groups and replicated previous findings obtained in a separate group of younger adults. We also identified regions whose activity differentiated among the different memory conditions. These patterns of differentiation were expressed less strongly in the older adults than in the young adults, a finding that was further confirmed by a barycentric discriminant analysis. This analysis showed an age-related dedifferentiation in autobiographical and episodic memory tasks but not in the semantic memory task or the control condition. These findings suggest that the activation of a common memory retrieval network is maintained with age, whereas the specific aspects of brain activity that differ with memory content are more vulnerable and less selectively engaged in older adults. Our results provide a potential neural mechanism for the well-known age differences in episodic/autobiographical memory, and preserved semantic memory, observed when older adults are compared with younger adults.

Salivary proteomics in lichen planus: A relationship with pathogenesis?

PubMed

Souza, M M; Florezi, G P; Nico, Mms; de Paula, F; Paula, F M; Lourenço, S V

2018-01-30

Oral lichen planus is a chronic, T-cell-mediated, inflammatory disease that affects the oral cavity. The oral lichen planus pathogenesis is still unclear, however, the main evidence is that the mechanisms of activation of different T lymphocyte pathway induce apoptosis with an increase in Th1 and Th17 subtypes cells, triggered by the release of cytokines. This study analysed saliva proteomics to identify protein markers that might be involved in the pathogenesis and development of the disease. Proteins differentially expressed by oral lichen planus and healthy controls were screened using mass spectrometry; the proteins found in oral lichen planus were subjected to bioinformatics analysis, including gene ontology and string networks analysis. The multiplex analysis validation allowed the correlation between the proteins identified and the involved cytokines in Th17 response. One hundred and eight proteins were identified in oral lichen planus, of which 17 proteins showed a high interaction between them and indicated an association with the disease. Expression of these proteins was correlated with the triggering of cytokines, more specifically the Th17 cells. Proteins, such as S100A8, S100A9, haptoglobin, can trigger cytokines and might be associated with a pathological function and antioxidant activities in oral lichen planus. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. All rights reserved.

Proteome analysis during pod, zygotic and somatic embryo maturation of Theobroma cacao.

PubMed

Niemenak, Nicolas; Kaiser, Edward; Maximova, Siela N; Laremore, Tatiana; Guiltinan, Mark J

2015-05-15

Two dimensional electrophoresis and nano-LC-MS were performed in order to identify alterations in protein abundance that correlate with maturation of cacao zygotic and somatic embryos. The cacao pod proteome was also characterized during development. The recently published cacao genome sequence was used to create a predicted proteolytic fragment database. Several hundred protein spots were resolved on each tissue analysis, of which 72 variable spots were subjected to MS analysis, resulting in 49 identifications. The identified proteins represent an array of functional categories, including seed storage, stress response, photosynthesis and translation factors. The seed storage protein was strongly accumulated in cacao zygotic embryos compared to their somatic counterpart. However, sucrose treatment (60 g L(-1)) allows up-regulation of storage protein in SE. A high similarity in the profiles of acidic proteins was observed in mature zygotic and somatic embryos. Differential expression in both tissues was observed in proteins having high pI. Several proteins were detected exclusively in fruit tissues, including a chitinase and a 14-3-3 protein. We also identified a novel cacao protein related to known mabinlin type sweet storage proteins. Moreover, the specific presence of thaumatin-like protein, another sweet protein, was also detected in fruit tissue. We discuss our observed correlations between protein expression profiles, developmental stage and stress responses. Copyright © 2015 Elsevier GmbH. All rights reserved.

Search for Cross-Correlations of Ultrahigh-Energy Cosmic Rays with BL Lacertae Objects

NASA Astrophysics Data System (ADS)

Abbasi, R. U.; Abu-Zayyad, T.; Amann, J. F.; Archbold, G.; Belov, K.; Belz, J. W.; BenZvi, S.; Bergman, D. R.; Blake, S. A.; Boyer, J. H.; Burt, G. W.; Cao, Z.; Connolly, B. M.; Deng, W.; Fedorova, Y.; Findlay, J.; Finley, C. B.; Hanlon, W. F.; Hoffman, C. M.; Holzscheiter, M. H.; Hughes, G. A.; Hüntemeyer, P.; Jui, C. C. H.; Kim, K.; Kirn, M. A.; Knapp, B. C.; Loh, E. C.; Maestas, M. M.; Manago, N.; Mannel, E. J.; Marek, L. J.; Martens, K.; Matthews, J. A. J.; Matthews, J. N.; O'Neill, A.; Painter, C. A.; Perera, L.; Reil, K.; Riehle, R.; Roberts, M. D.; Rodriguez, D.; Sasaki, M.; Schnetzer, S. R.; Seman, M.; Sinnis, G.; Smith, J. D.; Snow, R.; Sokolsky, P.; Springer, R. W.; Stokes, B. T.; Thomas, J. R.; Thomas, S. B.; Thomson, G. B.; Tupa, D.; Westerhoff, S.; Wiencke, L. R.; Zech, A.; HIRES Collaboration

2006-01-01

Data taken in stereo mode by the High Resolution Fly's Eye (HiRes) air fluorescence experiment are analyzed to search for correlations between the arrival directions of ultrahigh-energy cosmic rays with the positions of BL Lacertae objects. Several previous claims of significant correlations between BL Lac objects and cosmic rays observed by other experiments are tested. These claims are not supported by the HiRes data. However, we verify a recent analysis of correlations between HiRes events and a subset of confirmed BL Lac objects from the 10th Veron Catalog, and we study this correlation in detail. Due to the a posteriori nature of the search, the significance level cannot be reliably estimated and the correlation must be tested independently before any claim can be made. We identify the precise hypotheses that will be tested with statistically independent data.

Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2017-07-01

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADC min and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau 2 =0.04 (p<0.0001), I 2 =73%, test for overall effect Z=8.67 (p<0.00001). ADC min correlated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

An approach to functionally relevant clustering of the protein universe: Active site profile‐based clustering of protein structures and sequences

PubMed Central

Knutson, Stacy T.; Westwood, Brian M.; Leuthaeuser, Janelle B.; Turner, Brandon E.; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D.; Harper, Angela F.; Brown, Shoshana D.; Morris, John H.; Ferrin, Thomas E.; Babbitt, Patricia C.

2017-01-01

Abstract Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification—amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two‐Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure‐Function Linkage Database, SFLD) self‐identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self‐identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well‐curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP‐identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F‐measure and performance analysis on the enolase search results and comparison to GEMMA and SCI‐PHY demonstrate that TuLIP avoids the over‐division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. PMID:28054422

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

PubMed

Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S

2017-04-01

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

On the prediction of threshold friction velocity of wind erosion using soil reflectance spectroscopy

USGS Publications Warehouse

Li, Junran; Flagg, Cody B.; Okin, Gregory S.; Painter, Thomas H.; Dintwe, Kebonye; Belnap, Jayne

2015-01-01

Current approaches to estimate threshold friction velocity (TFV) of soil particle movement, including both experimental and empirical methods, suffer from various disadvantages, and they are particularly not effective to estimate TFVs at regional to global scales. Reflectance spectroscopy has been widely used to obtain TFV-related soil properties (e.g., moisture, texture, crust, etc.), however, no studies have attempted to directly relate soil TFV to their spectral reflectance. The objective of this study was to investigate the relationship between soil TFV and soil reflectance in the visible and near infrared (VIS–NIR, 350–2500 nm) spectral region, and to identify the best range of wavelengths or combinations of wavelengths to predict TFV. Threshold friction velocity of 31 soils, along with their reflectance spectra and texture were measured in the Mojave Desert, California and Moab, Utah. A correlation analysis between TFV and soil reflectance identified a number of isolated, narrow spectral domains that largely fell into two spectral regions, the VIS area (400–700 nm) and the short-wavelength infrared (SWIR) area (1100–2500 nm). A partial least squares regression analysis (PLSR) confirmed the significant bands that were identified by correlation analysis. The PLSR further identified the strong relationship between the first-difference transformation and TFV at several narrow regions around 1400, 1900, and 2200 nm. The use of PLSR allowed us to identify a total of 17 key wavelengths in the investigated spectrum range, which may be used as the optimal spectral settings for estimating TFV in the laboratory and field, or mapping of TFV using airborne/satellite sensors.

Singular spectrum decomposition of Bouligand-Minkowski fractal descriptors: an application to the classification of texture Images

NASA Astrophysics Data System (ADS)

Florindo, João. Batista

2018-04-01

This work proposes the use of Singular Spectrum Analysis (SSA) for the classification of texture images, more specifically, to enhance the performance of the Bouligand-Minkowski fractal descriptors in this task. Fractal descriptors are known to be a powerful approach to model and particularly identify complex patterns in natural images. Nevertheless, the multiscale analysis involved in those descriptors makes them highly correlated. Although other attempts to address this point was proposed in the literature, none of them investigated the relation between the fractal correlation and the well-established analysis employed in time series. And SSA is one of the most powerful techniques for this purpose. The proposed method was employed for the classification of benchmark texture images and the results were compared with other state-of-the-art classifiers, confirming the potential of this analysis in image classification.

Real-life assessment of the validity of patient global impression of change in fibromyalgia.

PubMed

Rampakakis, Emmanouil; Ste-Marie, Peter A; Sampalis, John S; Karellis, Angeliki; Shir, Yoram; Fitzcharles, Mary-Ann

2015-01-01

Patient Global Rating of Change (GRC) scales are commonly used in routine clinical care given their ease of use, availability and short completion time. This analysis aimed at assessing the validity of Patient Global Impression of Change (PGIC), a GRC scale commonly used in fibromyalgia, in a Canadian real-life setting. 167 fibromyalgia patients with available PGIC data were recruited in 2005-2013 from a Canadian tertiary-care multidisciplinary clinic. In addition to PGIC, disease severity was assessed with: pain visual analogue scale (VAS); Patient Global Assessment (PGA); Fibromyalgia Impact Questionnaire (FIQ); Health Assessment Questionnaire (HAQ); McGill Pain Questionnaire; body map. Multivariate linear regression assessed the PGIC relationship with disease parameter improvement while adjusting for follow-up duration and baseline parameter levels. The Spearman's rank coefficient assessed parameter correlation. Higher PGIC scores were significantly (p<0.001) associated with greater improvement in pain, PGA, FIQ, HAQ and the body map. A statistically significant moderate positive correlation was observed between PGIC and FIQ improvement (r=0.423; p<0.001); correlation with all remaining disease severity measures was weak. Regression analysis confirmed a significant (p<0.001) positive association between improvement in all disease severity measures and PGIC. Baseline disease severity and follow-up duration were identified as significant independent predictors of PGIC rating. Despite that only a weak correlation was identified between PGIC and standard fibromyalgia outcomes improvement, in the absence of objective outcomes, PGIC remains a clinically relevant tool to assess perceived impact of disease management. However, our analysis suggests that outcome measures data should not be considered in isolation but, within the global clinical context.

Analysis of the effect of local heat island in Seoul using LANDSAT image

NASA Astrophysics Data System (ADS)

Lee, K. I.; Ryu, J.; Jeon, S. W.

2017-12-01

The increase in the rate of industrialization due to urbanization has caused the Urban Heat Island phenomenon which means that the temperature of the city is higher than the surrounding area, and its intensity is increasing with climate change. Among the cities where heat island phenomenon occur, Seoul city has different degree of urbanization, green area ratio, energy consumption, and population density by each district unit. As a result, the strength of heat island phenomenon is also different. The average maximum temperature in each region may differ by more than 3 °, which is bigger than the suburbs in Seoul and it means that analysis of UHI effect by regional unit is needed. Therefore, this study is to extract the UHI Intensity of the regional unit of the Seoul Metropolitan City using the satellite image, analyzed the difference of intensity according to the regional unit. And do linear regression analysis with variables included in three categories(regional meteorological conditions, anthropogenic heat generation, land use factors). As a result, The UHI Intensity value of the Gu unit is significantly different from the UHI Intensity distribution of the Dong unit. The variable having the greatest positive correlation with UHI Intensity was NDBI(Normalized Difference Built-up Index) which shows the distribution of urban area, and Urban area ratio also has high correlation. There was a negative correlation between mean wind speed but there was no significant correlation between population density and power consumption. The result of this study is to identify the regional difference of UHI Intensity and to identify the factors inducing heat island phenomenon. so It is expected that it will provide direction in urban thermal environment design and policy development in the future.

Effect of knee osteoarthritis on the perception of quality of life in Venezuelan patients.

PubMed

Chacón, José G; González, Nancy E; Véliz, Aleida; Losada, Benito R; Paul, Hernando; Santiago, Luís G; Antúnez, Ana; Finol, Yelitza; González, María E; Granados, Isabel; Maldonado, Irama; Maldonado, Teolinda; Marín, Francisco; Zambrano, Gisela; Rodríguez, Martín A

2004-06-15

To measure the perception of quality of life in Venezuelan patients with knee osteoarthritis and to identify those variables that may influence it. A multicenter, cross-sectional study of 126 mestizo patients with knee osteoarthritis recruited from 8 rheumatology centers in Venezuela. We used a Spanish-translated version of the Arthritis Impact Measurement Scales (AIMS), as adapted in Venezuela. One-way analysis of variance was used to compare the AIMS mean total score among subgroups of knee pain, anatomic stage, and socioeconomic status (SES); a post-hoc test was performed to identify significant intragroup differences. Pearson's correlation coefficient was used to examine correlations between age, body mass index (BMI), disease duration, knee pain, and AIMS score. Associations between radiologic stage, SES, and AIMS scores were examined using Spearman's rank correlation. Multiple regression analysis was used to estimate predictor factors of AIMS scores. A significant correlation was found between total AIMS scores and knee pain, age, and socioeconomic status, but not with BMI, disease duration, or anatomic stage. Patients with severe knee pain differed from those with mild and moderate pain, and the highest AIMS mean total score was seen in patients within the severe knee pain subset. Patients in the highest socioeconomic levels differed from those within lowest categories. Patients classified as being at the levels of relative and critical poverty showed the highest AIMS scores. Multiple regression analysis showed that knee pain was the only variable that exerted an independent effect on the quality of life in our patients. The perception of quality of life is negatively affected by increasing levels of joint pain, old age, and low socioeconomic status in Venezuelan patients with knee osteoarthritis. Our study supports the need for an early and vigorous approach to treat pain in this group of patients.

Proteomics provides insights into biological pathways altered by plant growth promoting bacteria and arbuscular mycorrhiza in sorghum grown in marginal soil.

PubMed

Dhawi, Faten; Datta, Rupali; Ramakrishna, Wusirika

2017-02-01

Sorghum is an economically important crop, a model system for gene discovery and a biofuel source. Sorghum seedlings were subjected to three microbial treatments, plant growth promoting bacteria (B), arbuscular mycorrhizal (AM) fungi mix with two Glomus species (G. aggregatum and G. etunicatum), Funelliformis mosseae and Rhizophagus irregularis (My), and B and My combined (My+B). Proteomic analysis was conducted followed by integration with metabolite, plant biomass and nutrient data. Out of 366 differentially expressed proteins in sorghum roots, 44 upregulated proteins overlapping among three treatment groups showed positive correlation with sorghum biomass or element uptake or both. Proteins upregulated only in B group include asparagine synthetase which showed negative correlation with biomass and uptake of elements. Phosphoribosyl amino imidazole succinocarboxamide protein with more than 50-fold change in My and My+B groups correlated positively with Ca, Cu, S and sucrose levels in roots. The B group showed the highest number of upregulated proteins among the three groups with negative correlation with sorghum biomass and element uptake. KEGG pathway analysis identified carbon fixation as the unique pathway associated with common upregulated proteins while biosynthesis of amino acids and fatty acid degradation were associated with common downregulated proteins. Protein-protein interaction analysis using STRING identified a major network with thirteen downregulated proteins. These findings suggest that plant-growth-promoting-bacteria alone or in combination with mycorrhiza enhanced radical scavenging system and increased levels of specific proteins thereby shifting the metabolism towards synthesis of carbohydrates resulting in sorghum biomass increase and uptake of nutrients. Copyright © 2016 Elsevier B.V. All rights reserved.

Multivariate pattern analysis of fMRI data reveals deficits in distributed representations in schizophrenia

PubMed Central

Yoon, Jong H.; Tamir, Diana; Minzenberg, Michael J.; Ragland, J. Daniel; Ursu, Stefan; Carter, Cameron S.

2009-01-01

Background Multivariate pattern analysis is an alternative method of analyzing fMRI data, which is capable of decoding distributed neural representations. We applied this method to test the hypothesis of the impairment in distributed representations in schizophrenia. We also compared the results of this method with traditional GLM-based univariate analysis. Methods 19 schizophrenia and 15 control subjects viewed two runs of stimuli--exemplars of faces, scenes, objects, and scrambled images. To verify engagement with stimuli, subjects completed a 1-back matching task. A multi-voxel pattern classifier was trained to identify category-specific activity patterns on one run of fMRI data. Classification testing was conducted on the remaining run. Correlation of voxel-wise activity across runs evaluated variance over time in activity patterns. Results Patients performed the task less accurately. This group difference was reflected in the pattern analysis results with diminished classification accuracy in patients compared to controls, 59% and 72% respectively. In contrast, there was no group difference in GLM-based univariate measures. In both groups, classification accuracy was significantly correlated with behavioral measures. Both groups showed highly significant correlation between inter-run correlations and classification accuracy. Conclusions Distributed representations of visual objects are impaired in schizophrenia. This impairment is correlated with diminished task performance, suggesting that decreased integrity of cortical activity patterns is reflected in impaired behavior. Comparisons with univariate results suggest greater sensitivity of pattern analysis in detecting group differences in neural activity and reduced likelihood of non-specific factors driving these results. PMID:18822407

Induced wettability and surface-volume correlation of composition for bovine bone derived hydroxyapatite particles

NASA Astrophysics Data System (ADS)

Maidaniuc, Andreea; Miculescu, Florin; Voicu, Stefan Ioan; Andronescu, Corina; Miculescu, Marian; Matei, Ecaterina; Mocanu, Aura Catalina; Pencea, Ion; Csaki, Ioana; Machedon-Pisu, Teodor; Ciocan, Lucian Toma

2018-04-01

Hydroxyapatite powders characteristics need to be determined both for quality control purposes and for a proper control of microstructural features of bone reconstruction products. This study combines bulk morphological and compositional analysis methods (XRF, SEM-EDS, FT-IR) with surface-related methods (XPS, contact angle measurements) in order to correlate the characteristics of hydroxyapatite powders derived from bovine bone for its use in medical applications. An experimental approach for correlating the surface and volume composition was designed based on the analysis depth of each spectral method involved in the study. Next, the influences of powder particle size and forming method on the contact angle between water drops and ceramic surface were evaluated for identifying suitable strategies of tuning hydroxyapatite's wettability. The results revealed a preferential arrangement of chemical elements at the surface of hydroxyapatite particles which could induce a favourable material behaviour in terms of sinterability and biological performance.

Intestinal microbiota-derived metabolomic blood plasma markers for prior radiation injury.

PubMed

Ó Broin, Pilib; Vaitheesvaran, Bhavapriya; Saha, Subhrajit; Hartil, Kirsten; Chen, Emily I; Goldman, Devorah; Fleming, William Harv; Kurland, Irwin J; Guha, Chandan; Golden, Aaron

2015-02-01

Assessing whole-body radiation injury and absorbed dose is essential for remediation efforts following accidental or deliberate exposure in medical, industrial, military, or terrorist incidents. We hypothesize that variations in specific metabolite concentrations extracted from blood plasma would correlate with whole-body radiation injury and dose. Groups of C57BL/6 mice (n=12 per group) were exposed to 0, 2, 4, 8, and 10.4 Gy of whole-body gamma radiation. At 24 hours after treatment, all animals were euthanized, and both plasma and liver biopsy samples were obtained, the latter being used to identify a distinct hepatic radiation injury response within plasma. A semiquantitative, untargeted metabolite/lipid profile was developed using gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry, which identified 354 biochemical compounds. A second set of C57BL/6 mice (n=6 per group) were used to assess a subset of identified plasma markers beyond 24 hours. We identified a cohort of 37 biochemical compounds in plasma that yielded the optimal separation of the irradiated sample groups, with the most correlated metabolites associated with pyrimidine (positively correlated) and tryptophan (negatively correlated) metabolism. The latter were predominantly associated with indole compounds, and there was evidence that these were also correlated between liver and plasma. No evidence of saturation as a function of dose was observed, as has been noted for studies involving metabolite analysis of urine. Plasma profiling of specific metabolites related to pyrimidine and tryptophan pathways can be used to differentiate whole-body radiation injury and dose response. As the tryptophan-associated indole compounds have their origin in the intestinal microbiome and subsequently the liver, these metabolites particularly represent an attractive marker for radiation injury within blood plasma. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Rohrbaugh, Wayne Joseph

Results are reported from an investigation of correlations between molecular structural parameters of selected organophosphorus insecticides and their corresponding toxic effectiveness. The crystal and molecular structures of azinphos-methyl, emidithion, and tetrachlorvinphos were determined via three-dimensional x-ray analysis. Acetylcholinesterase (AChE) in nerve cells was identified as the target for organophosphorus insecticides.

Readability and Understandability of Online Vocal Cord Paralysis Materials.

PubMed

Balakrishnan, Vini; Chandy, Zachariah; Hseih, Amy; Bui, Thanh-Lan; Verma, Sunil P

2016-03-01

Patients use several online resources to learn about vocal cord paralysis (VCP). The objective of this study was to assess the readability and understandability of online VCP patient education materials (PEMs), with readability assessments and the Patient Education Materials Evaluation Tool (PEMAT), respectively. The relationship between readability and understandability was then analyzed. Descriptive and correlational design. Online PEMs were identified by performing a Google search with the term "vocal cord paralysis." After scientific webpages, news articles, and information for medical professionals were excluded, 29 articles from the first 50 search results were considered. Readability analysis was performed with 6 formulas. Four individuals with different educational backgrounds conducted understandability analysis with the PEMAT. Fleiss's Kappa interrater reliability analysis determined consistency among raters. Correlation between readability and understandability was determined with Pearson's correlation test. The reading level of the reviewed articles ranged from grades 9 to 17. Understandability ranged from 29% to 82%. Correlation analysis demonstrated a strong negative correlation between materials' readability and understandability (r = -0.462, P < .05). Online PEMs pertaining to VCP are written above the recommended reading levels. Overall, materials written at lower grade levels are more understandable. However, articles of identical grade levels had varying levels of understandability. The PEMAT may provide a more critical evaluation of the quality of a PEM when compared with readability formulas. Both readability and understandability should be used to evaluate PEMs. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2016.

RP-HPLC method using 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate incorporated with normalization technique in principal component analysis to differentiate the bovine, porcine and fish gelatins.

PubMed

Azilawati, M I; Hashim, D M; Jamilah, B; Amin, I

2015-04-01

The amino acid compositions of bovine, porcine and fish gelatin were determined by amino acid analysis using 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate as derivatization reagent. Sixteen amino acids were identified with similar spectral chromatograms. Data pre-treatment via centering and transformation of data by normalization were performed to provide data that are more suitable for analysis and easier to be interpreted. Principal component analysis (PCA) transformed the original data matrix into a number of principal components (PCs). Three principal components (PCs) described 96.5% of the total variance, and 2 PCs (91%) explained the highest variances. The PCA model demonstrated the relationships among amino acids in the correlation loadings plot to the group of gelatins in the scores plot. Fish gelatin was correlated to threonine, serine and methionine on the positive side of PC1; bovine gelatin was correlated to the non-polar side chains amino acids that were proline, hydroxyproline, leucine, isoleucine and valine on the negative side of PC1 and porcine gelatin was correlated to the polar side chains amino acids that were aspartate, glutamic acid, lysine and tyrosine on the negative side of PC2. Verification on the database using 12 samples from commercial products gelatin-based had confirmed the grouping patterns and the variables correlations. Therefore, this quantitative method is very useful as a screening method to determine gelatin from various sources. Copyright © 2014 Elsevier Ltd. All rights reserved.

Electron Spectroscopy for Chemical Analysis (ESCA) study of atmospheric particles

NASA Technical Reports Server (NTRS)

Dillard, J. G.; Seals, R. D.; Wightman, J. P.

1979-01-01

The results of analyses by ESCA (Electron Spectroscopy for Chemical Analysis) on several Nuclepore filters which were exposed during air pollution studies are presented along with correlative measurements by Neutron Activation Analysis and Scanning Electron Microscopy. Samples were exposed during air pollution studies at Norfolk, Virginia and the NASA Kennedy Space Center (KSC). It was demonstrated that with the ESCA technique it was possible to identify the chemical (bonding) state of elements contained in the atmospheric particulate matter collected on Nuclepore filters. Sulfur, nitrogen, mercury, chlorine, alkali, and alkaline earth metal species were identified in the Norfolk samples. ESCA binding energy data for aluminum indicated that three chemically different types of aluminum are present in the launch and background samples from NASA-KSC.

A new machine-learning method to prognosticate paraquat poisoned patients by combining coagulation, liver, and kidney indices.

PubMed

Hu, Lufeng; Li, Huaizhong; Cai, Zhennao; Lin, Feiyan; Hong, Guangliang; Chen, Huiling; Lu, Zhongqiu

2017-01-01

The prognosis of paraquat (PQ) poisoning is highly correlated to plasma PQ concentration, which has been identified as the most important index in PQ poisoning. This study investigated the predictive value of coagulation, liver, and kidney indices in prognosticating PQ-poisoning patients, when aligned with plasma PQ concentrations. Coagulation, liver, and kidney indices were first analyzed by variance analysis, receiver operating characteristic curves, and Fisher discriminant analysis. Then, a new, intelligent, machine learning-based system was established to effectively provide prognostic analysis of PQ-poisoning patients based on a combination of the aforementioned indices. In the proposed system, an enhanced extreme learning machine wrapped with a grey wolf-optimization strategy was developed to predict the risk status from a pool of 103 patients (56 males and 47 females); of these, 52 subjects were deceased and 51 alive. The proposed method was rigorously evaluated against this real-life dataset, in terms of accuracy, Matthews correlation coefficients, sensitivity, and specificity. Additionally, the feature selection was investigated to identify correlating factors for risk status. The results demonstrated that there were significant differences in the coagulation, liver, and kidney indices between deceased and surviving subjects (p<0.05). Aspartate aminotransferase, prothrombin time, prothrombin activity, total bilirubin, direct bilirubin, indirect bilirubin, alanine aminotransferase, urea nitrogen, and creatinine were the most highly correlated indices in PQ poisoning and showed statistical significance (p<0.05) in predicting PQ-poisoning prognoses. According to the feature selection, the most important correlated indices were found to be associated with aspartate aminotransferase, the aspartate aminotransferase to alanine ratio, creatinine, prothrombin time, and prothrombin activity. The method proposed here showed excellent results that were better than that produced based on blood-PQ concentration alone. These promising results indicated that the combination of these indices can provide a new avenue for prognosticating the outcome of PQ poisoning.

ESUPPO: Next Generation

DTIC Science & Technology

2017-12-01

sessions were correlated quantitatively by the web-based survey , identifying the need to update eSUPPO with specific icons such as Innovation...focus groups and surveys , assesses how well the mobile app meets the needs of the Supply Corps community. The analysis begins by understanding the...the app. After a complete analysis of eSUPPO’s current “As-Is” processes, the study takes the information gathered from both the survey and focus

Agile Airmen: Developing the Capacity to Quickly Create Innovative Ideas

DTIC Science & Technology

2011-03-23

economic growth.26 In contrast, a 2008 statistical analysis finds a high correlation to economic growth. Eric Hanushek and Ludger Woessmann studied... Hanushek and Woessmann analysis identified STEM leaders as vital to America‟s long-term prosperity, but having quality teachers who can teach STEM...accessed November 10, 2010). 27 Eric A. Hanushek & Ludger Woessmann, "Do Better Schools Lead to More Growth? Cognitive Skills, Economic Outcomes

HPLC-ESI-MS(n) Analysis, Fed-Batch Cultivation Enhances Bioactive Compound Biosynthesis and Immune-Regulative Effect of Adventitious Roots in Pseudostellaria heterophylla.

PubMed

Wang, Juan; Li, Jing; Li, Hongfa; Wu, Xiaolei; Gao, Wenyuan

2015-09-01

A electrospray ionization tandem mass spectrometry (ESI-MS(n)) analysis was performed in order to identify the active composition in Pseudostellaria heterophylla adventitious roots. Pseudostellarin A, C, D, and G were identified from P. heterophylla adventitious roots on the basis of LC-MS(n) analysis. The culture conditions of adventitious roots were optimized, and datasets were subjected to a partial least squares discriminant analysis (PLS-DA), in which the growth ratio and some compounds showed a positive correlation with an aeration volume of 0.3 vvm and inoculum density of 0.15 %. Fed-batch cultivation enhanced the contents of total saponin, polysaccharides, and specific oxygen uptaker rate (SOUR). The maximum dry root weight (4.728 g l(-1)) was achieved in the 3/4 Murashige and Skoog (MS) medium group. PLS-DA showed that polysaccharides contributed significantly to the clustering of different groups and showed a positive correlation in the MS medium group. The delayed-type hypersensitivity (DTH) reaction on the mice induced by 2,4-dinitrofluorobenzene (DNFB) was applied to compare the immunocompetence effects of adventitious roots (AR) with field native roots (NR) of P. heterophylla. As a result, AR possessed a similar immunoregulation function as NR.

Ocean wavenumber estimation from wave-resolving time series imagery

USGS Publications Warehouse

Plant, N.G.; Holland, K.T.; Haller, M.C.

2008-01-01

We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution). ?? 2008 IEEE.

Dynamics and causalities of atmospheric and oceanic data identified by complex networks and Granger causality analysis

NASA Astrophysics Data System (ADS)

Charakopoulos, A. K.; Katsouli, G. A.; Karakasidis, T. E.

2018-04-01

Understanding the underlying processes and extracting detailed characteristics of spatiotemporal dynamics of ocean and atmosphere as well as their interaction is of significant interest and has not been well thoroughly established. The purpose of this study was to examine the performance of two main additional methodologies for the identification of spatiotemporal underlying dynamic characteristics and patterns among atmospheric and oceanic variables from Seawatch buoys from Aegean and Ionian Sea, provided by the Hellenic Center for Marine Research (HCMR). The first approach involves the estimation of cross correlation analysis in an attempt to investigate time-lagged relationships, and further in order to identify the direction of interactions between the variables we performed the Granger causality method. According to the second approach the time series are converted into complex networks and then the main topological network properties such as degree distribution, average path length, diameter, modularity and clustering coefficient are evaluated. Our results show that the proposed analysis of complex network analysis of time series can lead to the extraction of hidden spatiotemporal characteristics. Also our findings indicate high level of positive and negative correlations and causalities among variables, both from the same buoy and also between buoys from different stations, which cannot be determined from the use of simple statistical measures.

On the origin of long-range correlations in texts.

PubMed

Altmann, Eduardo G; Cristadoro, Giampaolo; Esposti, Mirko Degli

2012-07-17

The complexity of human interactions with social and natural phenomena is mirrored in the way we describe our experiences through natural language. In order to retain and convey such a high dimensional information, the statistical properties of our linguistic output has to be highly correlated in time. An example are the robust observations, still largely not understood, of correlations on arbitrary long scales in literary texts. In this paper we explain how long-range correlations flow from highly structured linguistic levels down to the building blocks of a text (words, letters, etc..). By combining calculations and data analysis we show that correlations take form of a bursty sequence of events once we approach the semantically relevant topics of the text. The mechanisms we identify are fairly general and can be equally applied to other hierarchical settings.

Prognostic and clinical significance of histone deacetylase 1 expression in breast cancer: A meta-analysis.

PubMed

Qiao, Weiqiang; Liu, Heyang; Liu, Ruidong; Liu, Qipeng; Zhang, Ting; Guo, Wanying; Li, Peng; Deng, Miao

2018-05-05

There are conflicting reports about the role of histone deacetylase 1 (HDAC1) in breast cancer prognosis. Here, we conducted a meta-analysis to investigate the prognostic significance of HDAC1 in breast cancer. We searched different databases to identify studies evaluating the association between HDAC1 expression and its prognostic value in breast cancer. The pooled hazard ratios (HRs) and odds radios (ORs) with 95% confidence intervals (95% CIs) were calculated from these studies to assess specific correlation. Our meta-analysis of four databases identified 7 eligible studies with 1429 total patients. We found that HDAC1 over-expression did not correlate with disease-free survival (DFS) and overall survival (OS) in breast cancer. Subgroup analysis indicated an association between up-regulated HDAC1 expression and better OS (HR = 0.47, 95% CI: 0.23-0.97; P = 0.04) in Asian breast cancer patients. However, false-positive report probability (FPRP) analysis and trial sequential analysis (TSA) indicated that the results need further validation. Furthermore, HDAC1 over-expression was associated with positive estrogen receptor (ER) expression (OR, 3.30; 95% CI, 1.11-9.83; P = 0.03) and negative human epidermal growth factor receptor 2 (HER2) expression (OR, 1.79; 95% CI, 1.22-2.61; P = 0.003), but there were no significant differences between patients based on age, tumor size, lymph node metastasis, nuclear grade, or progesterone receptor (PR) expression. Overall, our meta-analysis demonstrated an association between increased HDAC1 expression and better OS in Asian breast cancer patients. In addition, HDAC1 over-expression correlated with positive ER and negative HER2 expression in breast cancer. However, researches in large patients' randomised controlled trials (RCTs) are needed to confirm the results. Copyright © 2018 Elsevier B.V. All rights reserved.

Systematic correlation of environmental exposure and physiological and self-reported behaviour factors with leukocyte telomere length.

PubMed

Patel, Chirag J; Manrai, Arjun K; Corona, Erik; Kohane, Isaac S

2017-02-01

It is hypothesized that environmental exposures and behaviour influence telomere length, an indicator of cellular ageing. We systematically associated 461 indicators of environmental exposures, physiology and self-reported behaviour with telomere length in data from the US National Health and Nutrition Examination Survey (NHANES) in 1999-2002. Further, we tested whether factors identified in the NHANES participants are also correlated with gene expression of telomere length modifying genes. We correlated 461 environmental exposures, behaviours and clinical variables with telomere length, using survey-weighted linear regression, adjusting for sex, age, age squared, race/ethnicity, poverty level, education and born outside the USA, and estimated the false discovery rate to adjust for multiple hypotheses. We conducted a secondary analysis to investigate the correlation between identified environmental variables and gene expression levels of telomere-associated genes in publicly available gene expression samples. After correlating 461 variables with telomere length, we found 22 variables significantly associated with telomere length after adjustment for multiple hypotheses. Of these varaibales, 14 were associated with longer telomeres, including biomarkers of polychlorinated biphenyls([PCBs; 0.1 to 0.2 standard deviation (SD) increase for 1 SD increase in PCB level, P  < 0.002] and a form of vitamin A, retinyl stearate. Eight variables associated with shorter telomeres, including biomarkers of cadmium, C-reactive protein and lack of physical activity. We could not conclude that PCBs are correlated with gene expression of telomere-associated genes. Both environmental exposures and chronic disease-related risk factors may play a role in telomere length. Our secondary analysis found no evidence of association between PCBs/smoking and gene expression of telomere-associated genes. All correlations between exposures, behaviours and clinical factors and changes in telomere length will require further investigation regarding biological influence of exposure. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association

Participation motivation and competition anxiety among Korean and non-Korean wheelchair tennis players

PubMed Central

Jeong, Irully; Park, Sunghee

2013-01-01

The purpose of this study was to examine differences in participation motivation and competition anxiety between Korean and non-Korean wheelchair tennis players and to identify relations between participation motivation and competition anxiety in each group. Sixty-six wheel-chair tennis players who participated in the 2013 Korea Open Wheel-chair Tennis Tournament in Seoul completed the Participation Motivation Survey and the Competitive State Anxiety Inventory II. Data were analyzed by a frequency analysis, descriptive statistics, Pearson’s correlation analysis, and independent samples t-test to identify participants’ demographic characteristics, differences in participation motivation, competition anxiety between Korean and non-Korean players, and correlations between participation motivation and competition anxiety in each group. Korean players reported significantly higher motivation in purification compared to non-Korean players, whereas non-Korean players reported significantly higher motivation in enjoyment. In addition, non-Korean players demonstrated higher cognitive anxiety and self-confidence compared to Korean players. Moreover, the physical anxiety of Korean players was negatively correlated with learning, health-fitness, and enjoyment motivation. On the other hand, only self-confidence was significantly related to learning motivation and enjoyment motivation in non-Korean players. Thus, the results presented herein provide evidence for the development of specialized counseling programs that consider the psychological characteristics of Korean wheelchair tennis players. PMID:24409429

The BCL2 antagonist of cell death pathway influences endometrial cancer cell sensitivity to cisplatin.

PubMed

Chon, Hye Sook; Marchion, Douglas C; Xiong, Yin; Chen, Ning; Bicaku, Elona; Stickles, Xiaomang Ba; Bou Zgheib, Nadim; Judson, Patricia L; Hakam, Ardeshir; Gonzalez-Bosquet, Jesus; Wenham, Robert M; Apte, Sachin M; Lancaster, Johnathan M

2012-01-01

To identify pathways that influence endometrial cancer (EC) cell sensitivity to cisplatin and to characterize the BCL2 antagonist of cell death (BAD) pathway as a therapeutic target to increase cisplatin sensitivity. Eight EC cell lines (Ishikawa, MFE296, RL 95-2, AN3CA, KLE, MFE280, MFE319, HEC-1-A) were subjected to Affymetrix Human U133A GeneChip expression analysis of approximately 22,000 probe sets. In parallel, endometrial cell line sensitivity to cisplatin was quantified by MTS assay, and IC(50) values were calculated. Pearson's correlation test was used to identify genes associated with response to cisplatin. Genes associated with cisplatin responsiveness were subjected to pathway analysis. The BAD pathway was identified and subjected to targeted modulation, and the effect on cisplatin sensitivity was evaluated. Pearson's correlation analysis identified 1443 genes associated with cisplatin resistance (P<0.05), which included representation of the BAD-apoptosis pathway. Small interfering RNA (siRNA) knockdown of BAD pathway protein phosphatase PP2C expression was associated with increased phosphorylated BAD (serine-155) levels and a parallel increase in cisplatin resistance in Ishikawa (P=0.004) and HEC-1-A (P=0.02) cell lines. In contrast, siRNA knockdown of protein kinase A expression increased cisplatin sensitivity in the Ishikawa (P=0.02) cell line. The BAD pathway influences EC cell sensitivity to cisplatin, likely via modulation of the phosphorylation status of the BAD protein. The BAD pathway represents an appealing therapeutic target to increase EC cell sensitivity to cisplatin. Copyright © 2011 Elsevier Inc. All rights reserved.

Identification of TCT, a novel knockdown resistance allele mutation and analysis of resistance detection methods in the voltage-gated Na⁺ channel of Culex pipiens pallens from Shandong Province, China.

PubMed

Liu, Hong-Mei; Cheng, Peng; Huang, Xiaodan; Dai, Yu-Hua; Wang, Hai-Fang; Liu, Li-Juan; Zhao, Yu-Qiang; Wang, Huai-Wei; Gong, Mao-Qing

2013-02-01

The present study aimed to investigate deltamethrin resistance in Culex pipiens pallens (C. pipiens pallens) mosquitoes and its correlation with knockdown resistance (kdr) mutations. In addition, mosquito‑resistance testing methods were analyzed. Using specific primers in polymerase chain reaction (PCR) and allele-specific (AS)-PCR, kdr gene sequences isolated from wild C. pipiens pallens mosquitoes were sequenced. Linear regression analysis was used to determine the correlation between the mutations and deltamethrin resistance. A kdr allelic gene was cloned and sequenced. Analysis of the DNA sequences revealed the presence of two point mutations at the L1014 residue in the IIS6 transmembrane segment of the voltage‑gated sodium channel (VGSC): L1014F, TTA→TTT, replacing a leucine (L) with a phenylalanine (F); L1014S, TTA→TCA, replacing leucine (L) with serine (S). Two alternative kdr-like mutations, L1014F and L1014S, were identified to be positively correlated with the deltamethrin-resistant phenotype. In addition a novel mutation, TCT, was identified in the VGSC of C. pipiens pallens. PCR and AS-PCR yielded consistent results with respect to mosquito resistance. However, the detection rate of PCR was higher than that of AS-PCR. Further studies are required to determine the specific resistance mechanism. PCR and AS-PCR demonstrated suitability for mosquito resistance field tests, however, the former method may be superior to the latter.

Disparities in the surgical treatment of colorectal liver metastases.

PubMed

Munene, Gitonga; Parker, Robyn D; Shaheen, Abdel Aziz; Myers, Robert P; Quan, May Lynn; Ball, Chad G; Dixon, Elijah

2013-01-01

Hepatectomy is an accepted standard of care for patients with resectable colorectal liver metastases (CLM). Given that it is unclear whether disparities exist between different patient populations, a population-based analysis was performed to analyze this issue with regards to resection rates and surgical mortality in patients with CLM. Using the Nationwide Inpatient Sample, characteristics and outcomes of adult patients with a diagnosis of colorectal cancer and colorectal metastases that subsequently underwent a liver resection during the years 1993-2007 were identified. Multivariate analysis was used to determine the effects of demographic and clinical covariables on resection rates and in-hospital mortality. Incident colorectal and liver metastases were identified in 138,565 patients; 3,528 patients (2.6%) underwent subsequent resection. African American and Hispanic race were associated with lower resection rates compared to Caucasian patients (adjusted OR 0.61 (0.52 - 0.71) and 0.81 (0.68 - 0.96) respectively). Medicaid insurance was associated with decreased resection rates compared to private insurance (AOR 0.47 (0.40 - 0.56)). The overall inpatient mortality rate was 3.1%. Multivariate analysis determined that mortality rate was correlated to both insurance status and geographic region. The national resection rate is significantly lower than has been reported by most case series. Race and insurance status appear to be correlated to the likelihood of surgical resection. In-hospital mortality is equivalent to the rates reported elsewhere, but is correlated to insurance status and region.

Spectroscopic characterization of dissolved organic matter in coking wastewater during bio-treatment: full-scale plant study.

PubMed

Xu, Ronghua; Ou, Huase; Yu, Xubiao; He, Runsheng; Lin, Chong; Wei, Chaohai

2015-01-01

This paper taking a full-scale coking wastewater (CWW) treatment plant as a case study aimed to characterize removal behaviors of dissolved organic matter (DOM) by UV spectra and fluorescence excitation-emission matrix-parallel factor analysis (PARAFAC), and investigate the correlations between spectroscopic indices and water quality parameters. Efficient removal rates of chemical oxygen demand (COD), dissolved organic carbon (DOC) and total nitrogen (TN) after the bio-treatment were 91.3%, 87.3% and 69.1%, respectively. UV270 was proven to be a stable UV absorption peak of CWW that could reflect the mixture of phenols, heterocyclics, polynuclear aromatic hydrocarbons and their derivatives. Molecular weight and aromaticity were increased, and also the content of polar functional groups was greatly reduced after bio-treatment. Three fluorescent components were identified by PARAFAC: C1 (tyrosine-like), C2 (tryptophan-like) and C3 (humic-like). The removal rate of protein-like was higher than that of humic-like and C1 was identified as biodegradable substance. Correlation analysis showed UV270 had an excellent correlation with COD (r=0.921, n=60, P<0.01) and DOC (r=0.959, n=60, P<0.01) and significant correlation (r=0.875, n=60, P<0.01) was also found between C2 and TN. Therefore, spectroscopic characterization could provide novel insights into removal behaviors of DOM and potential to monitor water quality real-time during CWW bio-treatment.

Fractionated analysis of paired-electrode nerve recordings.

PubMed

Fiore, Lorenzo; Lorenzetti, Walter; Ratti, Giovannino; Geppetti, Laura

2003-12-30

Multi-unit activity recorded from two electrodes positioned at a distance on a nerve may be analysed by cross-correlation, but units similar in direction and velocity of propagation cannot be distinguished and separately evaluated by this method. To overcome this limit, we added two features, represented by the impulse amplitudes of the paired recordings, to the dimension given by the impulse delay. The analysis was fractionated according to the new dimensions. In experimental recordings from the locomotor appendage of the lobster Homarus americanus, the fractionated analysis proved capable of identifying the contributions of single active units, even if these were superimposed and indiscernible in the global cross-correlation histogram. Up to 5 motor and 10 sensory units could be identified. The shape of the paired impulses was evaluated by an averaging procedure. Analogous evaluations on simulated recordings made it possible to estimate the influences exerted on performance by variations in noise level and in the number and firing rate of active units. The global signal could be resolved into single units even under the worst conditions. Accuracy in evaluating the amount of unit activity varied, exceeding 90% in about half of the cases tested; a similar performance was attained by evaluation of the impulse shapes.

Do antipsychotics lead to cognitive impairment in dementia? A meta-analysis of randomised placebo-controlled trials.

PubMed

Wolf, Alexander; Leucht, Stefan; Pajonk, Frank-Gerald

2017-04-01

Behavioural and psychological symptoms in dementia (BPSD) are common and often treated with antipsychotics, which are known to have small efficacy and to cause many side effects. One potential side effect might be cognitive decline. We searched MEDLINE, Scopus, CENTRAL and www.ClincalStudyResult.org for randomized, double-blind, placebo-controlled trials using antipsychotics for treating BPSD and evaluated cognitive functioning. The studies identified were summarized in a meta-analysis with the standardized mean difference (SMD, Hedges's g) as the effect size. Meta-regression was additionally performed to identify associated factors. Ten studies provided data on the course of cognitive functioning. The random effects model of the pooled analysis showed a not significant effect (SMD = -0.065, 95 % CI -0.186 to 0.057, I 2  = 41 %). Meta-regression revealed a significant correlation between cognitive impairment and treatment duration (R 2  = 0.78, p < 0.02) as well as baseline MMSE (R 2  = 0.92, p < 0.005). These correlations depend on only two out of ten studies and should interpret cautiously.

Heritability of Nociception IV: Neuropathic pain assays are genetically distinct across methods of peripheral nerve injury

PubMed Central

Young, Erin E.; Costigan, Michael; Herbert, Teri A.; Lariviere, William R.

2013-01-01

Prior genetic correlation analysis of 22 heritable behavioral measures of nociception and hypersensitivity in the mouse identified five genetically distinct pain types. In the present study, we reanalyzed that dataset and included the results of an additional nine assays of nociception and hypersensitivity to: 1) replicate the previously identified five pain types; 2) test whether any of the newly added pain assays represent novel genetically distinct pain types; 3) test the level of genetic relatedness among nine commonly employed neuropathic pain assays. Multivariate analysis of pairwise correlations between assays shows that the newly added zymosan-induced heat hypersensitivity assay does not conform to the two previously identified groups of heat hypersensitivity assays and cyclophosphamide-induced cystitis, the first organ-specific visceral pain model examined, is genetically distinct from other inflammatory assays. The four included mechanical hypersensitivity assays are genetically distinct, and do not comprise a single pain type as previously reported. Among the nine neuropathic pain assays including autotomy, chemotherapy, nerve ligation and spared nerve injury assays, at least four genetically distinct types of neuropathic sensory abnormalities were identified, corresponding to differences in nerve injury method. In addition, two itch assays and Comt genotype were compared to the expanded set of nociception and hypersensitivity assays. Comt genotype was strongly related only to spontaneous inflammatory nociception assays. These results indicate the priority for continued investigation of genetic mechanisms in several assays newly identified to represent genetically distinct pain types. PMID:24071598

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome.

PubMed

Morine, Melissa J; McMonagle, Jolene; Toomey, Sinead; Reynolds, Clare M; Moloney, Aidan P; Gormley, Isobel C; Gaora, Peadar O; Roche, Helen M

2010-10-07

Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways--selenoamino acid metabolism and steroid biosynthesis--illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

PubMed Central

2010-01-01

Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways - selenoamino acid metabolism and steroid biosynthesis - illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease. PMID:20929581

RNA-Seq Analysis Reveals MAPKKK Family Members Related to Drought Tolerance in Maize

PubMed Central

Ren, Wen; Yang, Fengling; He, Hang; Zhao, Jiuran

2015-01-01

The mitogen-activated protein kinase (MAPK) cascade is an evolutionarily conserved signal transduction pathway that is involved in plant development and stress responses. As the first component of this phosphorelay cascade, mitogen-activated protein kinase kinase kinases (MAPKKKs) act as adaptors linking upstream signaling steps to the core MAPK cascade to promote the appropriate cellular responses; however, the functions of MAPKKKs in maize are unclear. Here, we identified 71 MAPKKK genes, of which 14 were novel, based on a computational analysis of the maize (Zea mays L.) genome. Using an RNA-seq analysis in the leaf, stem and root of maize under well-watered and drought-stress conditions, we identified 5,866 differentially expressed genes (DEGs), including 8 MAPKKK genes responsive to drought stress. Many of the DEGs were enriched in processes such as drought stress, abiotic stimulus, oxidation-reduction, and metabolic processes. The other way round, DEGs involved in processes such as oxidation, photosynthesis, and starch, proline, ethylene, and salicylic acid metabolism were clearly co-expressed with the MAPKKK genes. Furthermore, a quantitative real-time PCR (qRT-PCR) analysis was performed to assess the relative expression levels of MAPKKKs. Correlation analysis revealed that there was a significant correlation between expression levels of two MAPKKKs and relative biomass responsive to drought in 8 inbred lines. Our results indicate that MAPKKKs may have important regulatory functions in drought tolerance in maize. PMID:26599013

Is case-chaos methodology an appropriate alternative to conventional case-control studies for investigating outbreaks?

PubMed

Edelstein, Michael; Wallensten, Anders; Kühlmann-Berenzon, Sharon

2014-08-15

Case-chaos methodology is a proposed alternative to case-control studies that simulates controls by randomly reshuffling the exposures of cases. We evaluated the method using data on outbreaks in Sweden. We identified 5 case-control studies from foodborne illness outbreaks that occurred between 2005 and 2012. Using case-chaos methodology, we calculated odds ratios 1,000 times for each exposure. We used the median as the point estimate and the 2.5th and 97.5th percentiles as the confidence interval. We compared case-chaos matched odds ratios with their respective case-control odds ratios in terms of statistical significance. Using Spearman's correlation, we estimated the correlation between matched odds ratios and the proportion of cases exposed to each exposure and quantified the relationship between the 2 using a normal linear mixed model. Each case-control study identified an outbreak vehicle (odds ratios = 4.9-45). Case-chaos methodology identified the outbreak vehicle 3 out of 5 times. It identified significant associations in 22 of 113 exposures that were not associated with outcome and 5 of 18 exposures that were significantly associated with outcome. Log matched odds ratios correlated with their respective proportion of cases exposed (Spearman ρ = 0.91) and increased significantly with the proportion of cases exposed (b = 0.054). Case-chaos methodology missed the outbreak source 2 of 5 times and identified spurious associations between a number of exposures and outcome. Measures of association correlated with the proportion of cases exposed. We recommended against using case-chaos analysis during outbreak investigations. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Adaptation of the contraceptive self-efficacy scale for heterosexual Mexican men and women of reproductive age.

PubMed

Arias, María Luisa Flores; Champion, Jane Dimmitt; Soto, Norma Elva Sáenz

2017-08-01

Development of a Spanish Version Contraceptive Self-efficacy Scale for use among heterosexual Mexican populations of reproductive age inclusive of 18-35years. Methods of family planning have decreased in Mexico which may lead to an increase in unintended pregnancies. Contraceptive self-efficacy is considered a predictor and precursor for use of family planning methods. Cross-sectional, descriptive study design was used to assess contraceptive self-efficacy among a heterosexual Mexican population (N=160) of reproductive age (18-35years). Adaptation of a Spanish Version Contraceptive Self-efficacy scale was conducted prior to instrument administration. Exploratory and confirmatory factorial analyses identified seven factors with a variance of 72.812%. The adapted scale had a Cronbach alpha of 0.771. A significant correlation between the Spanish Version Contraceptive Self-efficacy Scale and the use of family planning methods was identified. The Spanish Version Contraceptive Self-efficacy scale has an acceptable Cronbach alpha. Exploratory factor analysis identified 7 components. A positive correlation between self-reported contraceptive self-efficacy and family planning method use was identified. This scale may be used among heterosexual Mexican men and women of reproductive age. The factor analysis (7 factors versus 4 factors for the original scale) identified a discrepancy for interpretation of the Spanish versus English language versions. Interpretation of findings obtained via the Spanish versión among heterosexual Mexican men and women of reproductive age require interpretation based upon these differences identified in these analyses. Copyright © 2017 Elsevier Inc. All rights reserved.

Correlation analysis of a ground-water level monitoring network, Miami-Dade County, Florida

USGS Publications Warehouse

Prinos, Scott T.

2005-01-01

The U.S. Geological Survey cooperative ground-water monitoring program in Miami-Dade County, Florida, expanded from 4 to 98 continuously recording water-level monitoring wells during the 1939-2001 period. Network design was based on area specific assessments; however, no countywide statistical assessments of network coverage had been performed for the purpose of assessing network redundancy. To aid in the assessment of network redundancy, correlation analyses were performed using S-PLUS 2000 statistical analysis software for daily maximum water-level data from 98 monitoring wells for the November 1, 1973, to October 31, 2000 period. Because of the complexities of the hydrologic, water-supply, and water-management systems in Miami-Dade County and the changes that have occurred to these systems through time, spatial and temporal variations in the degree of correlation had to be considered. To assess temporal variation in correlation, water-level data from each well were subdivided by year and by wet and dry seasons. For each well, year, and season, correlation analyses were performed on the data from those wells that had available data. For selected wells, the resulting correlation coefficients from each year and season were plotted with respect to time. To assess spatial variation in correlation, the coefficients determined from the correlation analysis were averaged. These average wet- and dry-season correlation coefficients were plotted spatially using geographic information system software. Wells with water-level data that correlated with a coefficient of 0.95 or greater were almost always located in relatively close proximity to each other. Five areas were identified where the water-level data from wells within the area remained correlated with that of other wells in the area during the wet and dry seasons. These areas are located in or near the C-1 and C-102 basins (2 wells), in or near the C-6 and C-7 basins (2 wells), near the Florida Keys Aqueduct Authority Well Field (2 wells), near the Hialeah-Miami Springs Well Field (6 wells), and near the West Well Field (21 wells). Data from the remaining 65 wells (most of the wells in the network) generally were not correlated with those of other wells during both the wet and dry seasons with an average coefficient of 0.95 or greater for the comparison. Because many of the wells near the West Well Field and some near the Hialeah-Miami Springs Well Field had not been in operation for very long (most having been installed in 1994), the averaged correlation coefficients for these wells were often determined using only a few seasons of data. For the few instances where water-level data were found to be well correlated on average for a lengthy period of record, short-term declines in correlation were often identified. In general, it would be beneficial to compare data for longer periods of record than currently available.

Identification, Comparison, and Validation of Robust Rumen Microbial Biomarkers for Methane Emissions Using Diverse Bos Taurus Breeds and Basal Diets

PubMed Central

Auffret, Marc D.; Stewart, Robert; Dewhurst, Richard J.; Duthie, Carol-Anne; Rooke, John A.; Wallace, Robert J.; Freeman, Tom C.; Snelling, Timothy J.; Watson, Mick; Roehe, Rainer

2018-01-01

Previous shotgun metagenomic analyses of ruminal digesta identified some microbial information that might be useful as biomarkers to select cattle that emit less methane (CH4), which is a potent greenhouse gas. It is known that methane production (g/kgDMI) and to an extent the microbial community is heritable and therefore biomarkers can offer a method of selecting cattle for low methane emitting phenotypes. In this study a wider range of Bos Taurus cattle, varying in breed and diet, was investigated to determine microbial communities and genetic markers associated with high/low CH4 emissions. Digesta samples were taken from 50 beef cattle, comprising four cattle breeds, receiving two basal diets containing different proportions of concentrate and also including feed additives (nitrate or lipid), that may influence methane emissions. A combination of partial least square analysis and network analysis enabled the identification of the most significant and robust biomarkers of CH4 emissions (VIP > 0.8) across diets and breeds when comparing all potential biomarkers together. Genes associated with the hydrogenotrophic methanogenesis pathway converting carbon dioxide to methane, provided the dominant biomarkers of CH4 emissions and methanogens were the microbial populations most closely correlated with CH4 emissions and identified by metagenomics. Moreover, these genes grouped together as confirmed by network analysis for each independent experiment and when combined. Finally, the genes involved in the methane synthesis pathway explained a higher proportion of variation in CH4 emissions by PLS analysis compared to phylogenetic parameters or functional genes. These results confirmed the reproducibility of the analysis and the advantage to use these genes as robust biomarkers of CH4 emissions. Volatile fatty acid concentrations and ratios were significantly correlated with CH4, but these factors were not identified as robust enough for predictive purposes. Moreover, the methanotrophic Methylomonas genus was found to be negatively correlated with CH4. Finally, this study confirmed the importance of using robust and applicable biomarkers from the microbiome as a proxy of CH4 emissions across diverse production systems and environments. PMID:29375511

Identification, Comparison, and Validation of Robust Rumen Microbial Biomarkers for Methane Emissions Using Diverse Bos Taurus Breeds and Basal Diets.

PubMed

Auffret, Marc D; Stewart, Robert; Dewhurst, Richard J; Duthie, Carol-Anne; Rooke, John A; Wallace, Robert J; Freeman, Tom C; Snelling, Timothy J; Watson, Mick; Roehe, Rainer

2017-01-01

Previous shotgun metagenomic analyses of ruminal digesta identified some microbial information that might be useful as biomarkers to select cattle that emit less methane (CH 4 ), which is a potent greenhouse gas. It is known that methane production (g/kgDMI) and to an extent the microbial community is heritable and therefore biomarkers can offer a method of selecting cattle for low methane emitting phenotypes. In this study a wider range of Bos Taurus cattle, varying in breed and diet, was investigated to determine microbial communities and genetic markers associated with high/low CH 4 emissions. Digesta samples were taken from 50 beef cattle, comprising four cattle breeds, receiving two basal diets containing different proportions of concentrate and also including feed additives (nitrate or lipid), that may influence methane emissions. A combination of partial least square analysis and network analysis enabled the identification of the most significant and robust biomarkers of CH 4 emissions (VIP > 0.8) across diets and breeds when comparing all potential biomarkers together. Genes associated with the hydrogenotrophic methanogenesis pathway converting carbon dioxide to methane, provided the dominant biomarkers of CH 4 emissions and methanogens were the microbial populations most closely correlated with CH 4 emissions and identified by metagenomics. Moreover, these genes grouped together as confirmed by network analysis for each independent experiment and when combined. Finally, the genes involved in the methane synthesis pathway explained a higher proportion of variation in CH 4 emissions by PLS analysis compared to phylogenetic parameters or functional genes. These results confirmed the reproducibility of the analysis and the advantage to use these genes as robust biomarkers of CH 4 emissions. Volatile fatty acid concentrations and ratios were significantly correlated with CH 4 , but these factors were not identified as robust enough for predictive purposes. Moreover, the methanotrophic Methylomonas genus was found to be negatively correlated with CH 4 . Finally, this study confirmed the importance of using robust and applicable biomarkers from the microbiome as a proxy of CH 4 emissions across diverse production systems and environments.

A CRITERION FACTOR ANALYSIS OF THE SIXTEEN PERSONALITY FACTOR QUESTIONNAIRE.

ERIC Educational Resources Information Center

MAZER, GILBERT E.

THE CORRELATION OF REPORTED VARIATIONS IN COUNSELOR PRACTICES WITH WELL-IDENTIFIED PERSONALITY TRAITS WAS STUDIED. THE SIXTEEN PERSONALITY FACTOR QUESTIONNAIRE (WHICH MEASURES 15 PERSONALITY TRAITS AND INTELLIGENCE) AND THE INVENTORY OF COUNSELING PRACTICES (WHICH EVALUATES 75 COUNSELING PRACTICES) WERE GIVEN TO 120 GRADUATE GUIDANCE STUDENTS AT…

Religiosity and Authoritarianism as Predictors of Attitude toward the Disabled: A Regression Analysis.

ERIC Educational Resources Information Center

Tunick, Roy H.; And Others

1979-01-01

This study identifies predictors and correlates of attitudes toward the disabled. Authoritarianism, church attendance, religious orthodoxy, age, and education were significantly related to these attitudes of people in a Rocky Mountain Community. Significant predictors of the criterion were authoritarianism, religiosity, and age. Recommendations…

Factor Analysis of the Autism Spectrum Screening Questionnaire

ERIC Educational Resources Information Center

Posserud, Britt; Lundervold, Astri J.; Steijnen, Maaike C.; Verhoeven, Sophie; Stormark, Kjell Morten; Gillberg, Christopher

2008-01-01

The present study investigated the factor structure of parent and teacher Autism Spectrum Screening Questionnaire (ASSQ) in a population of 7-9 years old children. For validation purposes, factors derived were correlated with results on the Strengths and Difficulties Questionnaire (SDQ). A three-factor solution was identified on both parent and…

Analysis of the Tail Structures of Comet 1P/Halley 1910 II

NASA Astrophysics Data System (ADS)

Voelzke, Marcos Rincon

2013-11-01

For the purpose of identifying, measuring, and correlating the morphological structures along the plasma tail of 1P/Halley, 886 images from September 1909 to May 1911 are analysed. These images are from the Atlas of Comet Halley 1910 II (DONN; RAHE; BRANDT, 1986).

Dimensions, Patterns, and Personality Correlates of Drug Abuse in an Offender Population.

ERIC Educational Resources Information Center

Holland, Terrill R.

1978-01-01

Drug abuse scores from prisoners resulted in two factors describing lifetime use of cannabis versus opiates. Analysis of Minnesota Multiphasic Personality Inventory (MMPI) profiles versus drug abuse patterns indicated moderate, unidimensional relationship between variables. MMPI profiles of opiate users were similar to those identified in research…

Do scores on three commonly used measures of critical thinking correlate with academic success of health professions trainees? A systematic review and meta-analysis.

PubMed

Ross, David; Loeffler, Kim; Schipper, Shirley; Vandermeer, Ben; Allan, G Michael

2013-05-01

To determine whether the three commonly used measures of critical thinking correlate with academic success of medical professionals in training. The search for English-language articles (from 1980 to 2011) used Medline, Embase, Scopus, Cochrane Library on Ovid, Proquest Dissertations, Health and Psychosocial Instruments, PsychINFO, and references of included articles. Studies comparing critical thinking with academic success among medical professionals were included. Two authors performed study selection independently, with disagreement resolved by consensus. Two authors independently abstracted data on study characteristics, quality, and outcomes, with disagreement resolved by a third author. Critical thinking tests studied were the California Critical Thinking Skills Test (CCTST), California Critical Thinking Disposition Inventory (CCTDI), and Watson-Glaser Critical Thinking Appraisal. Correlation coefficients were pooled in meta-analysis. The search identified 557 studies: 52 met inclusion for systematic review, 41 of which were meta-analyzed. Critical thinking was positively correlated with academic success, r=0.31 (95% confidence intervals [CI] 0.26, 0.35), with a moderate statistical heterogeneity (I=67%). In subgroup analysis, only student type had statistical significance for correlation, although bias was likely due to low numbers for some student types. In direct comparison, using studies that employed two critical thinking tests, the CCTDI (r=0.23, 95% CI 0.15, 0.30) was significantly inferior (P<.001) to the CCTST (r=0.39, 95% CI 0.33, 0.45). Critical thinking was moderately correlated with academic success of medical professionals in training. The CCTDI was inferior to the CCTST in correlating with academic success.

General Platform for Systematic Quantitative Evaluation of Small-Molecule Permeability in Bacteria

PubMed Central

2015-01-01

The chemical features that impact small-molecule permeability across bacterial membranes are poorly understood, and the resulting lack of tools to predict permeability presents a major obstacle to the discovery and development of novel antibiotics. Antibacterials are known to have vastly different structural and physicochemical properties compared to nonantiinfective drugs, as illustrated herein by principal component analysis (PCA). To understand how these properties influence bacterial permeability, we have developed a systematic approach to evaluate the penetration of diverse compounds into bacteria with distinct cellular envelopes. Intracellular compound accumulation is quantitated using LC-MS/MS, then PCA and Pearson pairwise correlations are used to identify structural and physicochemical parameters that correlate with accumulation. An initial study using 10 sulfonyladenosines in Escherichia coli, Bacillus subtilis, and Mycobacterium smegmatis has identified nonobvious correlations between chemical structure and permeability that differ among the various bacteria. Effects of cotreatment with efflux pump inhibitors were also investigated. This sets the stage for use of this platform in larger prospective analyses of diverse chemotypes to identify global relationships between chemical structure and bacterial permeability that would enable the development of predictive tools to accelerate antibiotic drug discovery. PMID:25198656

The new platinum-based anticancer agent LA-12 induces retinol binding protein 4 in vivo

PubMed Central

2011-01-01

Background The initial pharmacokinetic study of a new anticancer agent (OC-6-43)-bis(acetato)(1-adamantylamine)amminedichloroplatinum (IV) (LA-12) was complemented by proteomic screening of rat plasma. The objective of the study was to identify new LA-12 target proteins that serve as markers of LA-12 treatment, response and therapy monitoring. Methods Proteomic profiles were measured by surface-enhanced laser desorption-ionization time-of-flight mass spectrometry (SELDI-TOF MS) in 72 samples of rat plasma randomized according to LA-12 dose and time from administration. Correlation of 92 peak clusters with platinum concentration was evaluated using Spearman correlation analysis. Results We identified Retinol-binding protein 4 (RBP4) whose level correlated with LA-12 level in treated rats. Similar results were observed in randomly selected patients involved in Phase I clinical trials. Conclusions RBP4 induction is in agreement with known RBP4 regulation by amantadine and cisplatin. Since retinol metabolism is disrupted in many cancers and inversely associates with malignancy, these data identify a potential novel mechanism for the action of LA-12 and other similar anti-cancer drugs. PMID:22040120

Ecological correlates of population genetic structure: a comparative approach using a vertebrate metacommunity.

PubMed

Manier, Mollie K; Arnold, Stevan J

2006-12-07

Identifying ecological factors associated with population genetic differentiation is important for understanding microevolutionary processes and guiding the management of threatened populations. We identified ecological correlates of several population genetic parameters for three interacting species (two garter snakes and an anuran) that occupy a common landscape. Using multiple regression analysis, we found that species interactions were more important in explaining variation in population genetic parameters than habitat and nearest-neighbour characteristics. Effective population size was best explained by census size, while migration was associated with differences in species abundance. In contrast, genetic distance was poorly explained by the ecological correlates that we tested, but geographical distance was prominent in models for all species. We found substantially different population dynamics for the prey species relative to the two predators, characterized by larger effective sizes, lower gene flow and a state of migration-drift equilibrium. We also identified an escarpment formed by a series of block faults that serves as a barrier to dispersal for the predators. Our results suggest that successful landscape-level management should incorporate genetic and ecological data for all relevant species, because even closely associated species can exhibit very different population genetic dynamics on the same landscape.

Raman chemical imaging of explosive-contaminated fingerprints.

PubMed

Emmons, E D; Tripathi, A; Guicheteau, J A; Christesen, S D; Fountain, A W

2009-11-01

Raman chemical imaging (RCI) has been used to detect and identify explosives in contaminated fingerprints. Bright-field imaging is used to identify regions of interest within a fingerprint, which can then be examined to determine their chemical composition using RCI and fluorescence imaging. Results are presented where explosives in contaminated fingerprints are identified and their spatial distributions are obtained. Identification of explosives is obtained using Pearson's cosine cross-correlation technique using the characteristic region (500-1850 cm(-1)) of the spectrum. This study shows the ability to identify explosives nondestructively so that the fingerprint remains intact for further biometric analysis. Prospects for forensic examination of contaminated fingerprints are discussed.

Indications for axillary ultrasound use in breast cancer patients.

PubMed

Joh, Jennifer E; Han, Gang; Kiluk, John V; Laronga, Christine; Khakpour, Nazanin; Lee, M Catherine

2012-12-01

Axillary ultrasound has been adopted for preoperative planning in breast cancer. Our objective was to determine features predictive of abnormal AUS and/or positive axillary node needle biopsy (NBx). Single-institution database of breast cancer patients identified patients with preoperative AUS. Patient characteristics and outcomes were correlated with AUS and NBx. Significant features were identified using univariable and multivariable analysis and correlative statistics. Three hundred thirteen breast cancers were evaluated. Abnormal AUS was demonstrated in 250 cases (80%). Node needle biopsy was performed in 247 cases (79%). Sensitivity and specificity was 93% and 48% for AUS and 86% and 100% for NBx, respectively. Palpable axillary adenopathy was significant in logistic regression model (P < .05). There were positive correlations between tumor grade, clinical T and tumor-node-metastasis stage, invasive ductal carcinoma histology, and inflammatory breast carcinoma with AUS and NBx (P < .05). Clinicopathologic features (grade, histology, tumor size) might help guide judicious use of AUS. Copyright © 2012 Elsevier Inc. All rights reserved.

Next-generation sequencing of urine specimens: A novel platform for genomic analysis in patients with non-muscle-invasive urothelial carcinoma treated with bacille Calmette-Guérin.

PubMed

Scott, Sasinya N; Ostrovnaya, Irina; Lin, Caroline M; Bouvier, Nancy; Bochner, Bernard H; Iyer, Gopakumar; Solit, David; Berger, Michael F; Lin, Oscar

2017-06-01

Biopsies from patients with high-risk (HR) non-muscle-invasive urothelial carcinoma (NMIUC), especially flat urothelial carcinoma in situ, frequently contain scant diagnostic material or denuded mucosa only, and this precludes further extensive genomic analysis. This study evaluated the use of next-generation sequencing (NGS) analysis of urine cytology material from patients with HR NMIUC in an attempt to identify genetic alterations that might correlate with clinical features and responses to bacille Calmette-Guérin (BCG) treatment. Forty-one cytology slides from patients with HR NMIUC treated with intravesical BCG were selected for this study. Histological confirmation was available for all cases. The specimens were subjected to NGS analysis with a customized targeted exome capture assay composed of 341 genes. In this cohort, genomic alterations were successfully identified in all cytology samples. Mutations were detected down to a 2% allele frequency and chromosomal rearrangements including copy number alterations and gene fusions were identified. The most frequently altered genes included telomerase reverse transcriptase (TERT), tumor protein 53 (TP53), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and chromatin remodeling genes such as lysine demethylase 6A (KDM6A) and AT-rich interaction domain 1A (ARID1A). For patients with matched tumor tissue, cytology specimens revealed all mutations detected in tissue as well as additional mutations, and this suggested that urine might more effectively capture the full genetic heterogeneity of disease than an individual cystectomy. Alterations in multiple genes correlated with clinical and histopathological features, including responses to BCG treatment, flat architecture versus papillary architecture, and smoking history. Urine specimens can replace tissue as a substrate for NGS analysis of HR NMIUC. Several genomic alterations identified in urine specimens might be associated with histological features and clinical characteristics. Cancer Cytopathol 2017;125:416-26. © 2017 American Cancer Society. © 2017 American Cancer Society.

Novel EDA mutation in X-linked hypohidrotic ectodermal dysplasia and genotype-phenotype correlation.

PubMed

Zeng, B; Lu, H; Xiao, X; Zhou, L; Lu, J; Zhu, L; Yu, D; Zhao, W

2015-11-01

X-linked hypohidrotic ectodermal dysplasia (XLHED) is characterized by abnormalities of hair, teeth, and sweat glands, while non-syndromic hypodontia (NSH) affects only teeth. Mutations in Ectodysplasin A (EDA) underlie both XLHED and NSH. This study investigated the genetic causes of six hypohidrotic ectodermal dysplasia (HED) patients and genotype-phenotype correlation. The EDA gene of six patients with HED was sequenced. Bioinformatics analysis and structural modeling for the mutations were performed. The records of 134 patients with XLHED and EDA-related NSH regarding numbers of missing permanent teeth from this study and 20 articles were reviewed. Nonparametric tests were used to analyze genotype-phenotype correlations. In four of the six patients, we identified a novel mutation c.852T>G (p.Phe284Leu) and three reported mutations: c.467G>A (p.Arg156His), c.776C>A (p.Ala259Glu), and c.871G>A (p.Gly291Arg). They were predicted to be pathogenic by bioinformatics analysis and structural modeling. Genotype-phenotype correlation analysis revealed that truncating mutations were associated with more missing teeth. Missense mutations and the mutations affecting the TNF homology domain were correlated with fewer missing teeth. This study extended the mutation spectrum of XLHED and revealed the relationship between genotype and the number of missing permanent teeth. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Parallel Genetic Algorithm to Discover Patterns in Genetic Markers that Indicate Predisposition to Multifactorial Disease

PubMed Central

Rausch, Tobias; Thomas, Alun; Camp, Nicola J.; Cannon-Albright, Lisa A.; Facelli, Julio C.

2008-01-01

This paper describes a novel algorithm to analyze genetic linkage data using pattern recognition techniques and genetic algorithms (GA). The method allows a search for regions of the chromosome that may contain genetic variations that jointly predispose individuals for a particular disease. The method uses correlation analysis, filtering theory and genetic algorithms (GA) to achieve this goal. Because current genome scans use from hundreds to hundreds of thousands of markers, two versions of the method have been implemented. The first is an exhaustive analysis version that can be used to visualize, explore, and analyze small genetic data sets for two marker correlations; the second is a GA version, which uses a parallel implementation allowing searches of higher-order correlations in large data sets. Results on simulated data sets indicate that the method can be informative in the identification of major disease loci and gene-gene interactions in genome-wide linkage data and that further exploration of these techniques is justified. The results presented for both variants of the method show that it can help genetic epidemiologists to identify promising combinations of genetic factors that might predispose to complex disorders. In particular, the correlation analysis of IBD expression patterns might hint to possible gene-gene interactions and the filtering might be a fruitful approach to distinguish true correlation signals from noise. PMID:18547558

Correlation of major components of ocular astigmatism in myopic patients.

PubMed

Mohammadpour, Mehrdad; Heidari, Zahra; Khabazkhoob, Mehdi; Amouzegar, Afsaneh; Hashemi, Hassan

2016-02-01

To investigate the correlation of major components of ocular astigmatism in myopic patients in an academic hospital. This cross-sectional study was conducted on 376 eyes of 188 patients who were referred to Farabi Eye Hospital for refractive surgery. Preoperative examinations including refraction and corneal topography were performed for all candidates to measure refractive and corneal astigmatism. Ocular residual astigmatism was calculated using vector analysis. Pearson's correlation and ANOVA analysis were used to evaluate the strength of the association between different types of astigmatism. Both eyes were defined as cluster and the Generalized Estimating Equations (GEE) analysis were performed. Mean age of 119 women (63.3%) and 69 men (36.7%) was 27.8 ± 5.7 years. Mean refractive error based on spherical equivalent was -3.59 ± 1.95D (range, -0.54 to -10.22D). Mean refractive and corneal astigmatism was 1.97 ± 1.3D and 1.85 ± 1.01D, respectively. Mean amount of ORA was 0.65 ± 0.36D.There was a significant correlation between ORA and refractive astigmatism(r=0.23, p<0.001), corneal and refractive astigmatism (r=0.91, p<0.001) and a weak correlation between ORA and corneal astigmatism (r=0.13, p=0.014). There was a significant correlation between J0 and J45 values of ORA and corneal astigmatism (p<0.001). There is a significant correlation between ORA and refractive astigmatism, refractive and corneal astigmatism and a weak correlation between ORA and corneal astigmatism in refractive surgery candidates. Identifying the type of astigmatism and preoperative measurement of ocular residual astigmatism is highly recommended prior to any refractive surgery, especially in cases with significant astigmatism. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison between a new computer program and the reference software for gray-scale median analysis of atherosclerotic carotid plaques.

PubMed

Casella, Ivan Benaduce; Fukushima, Rodrigo Bono; Marques, Anita Battistini de Azevedo; Cury, Marcus Vinícius Martins; Presti, Calógero

2015-03-01

To compare a new dedicated software program and Adobe Photoshop for gray-scale median (GSM) analysis of B-mode images of carotid plaques. A series of 42 carotid plaques generating ≥50% diameter stenosis was evaluated by a single observer. The best segment for visualization of internal carotid artery plaque was identified on a single longitudinal view and images were recorded in JPEG format. Plaque analysis was performed by both programs. After normalization of image intensity (blood = 0, adventitial layer = 190), histograms were obtained after manual delineation of plaque. Results were compared with nonparametric Wilcoxon signed rank test and Kendall tau-b correlation analysis. GSM ranged from 00 to 100 with Adobe Photoshop and from 00 to 96 with IMTPC, with a high grade of similarity between image pairs, and a highly significant correlation (R = 0.94, p < .0001). IMTPC software appears suitable for the GSM analysis of carotid plaques. © 2014 Wiley Periodicals, Inc.

The impact of oxytocin administration on brain activity: a systematic review and meta-analysis protocol.

PubMed

Quintana, Daniel S; Outhred, Tim; Westlye, Lars T; Malhi, Gin S; Andreassen, Ole A

2016-11-29

Converging evidence demonstrates the important role of the neuropeptide hormone oxytocin (OT) in human behaviour and cognition. Intranasal OT administration has been shown to improve several aspects of social communication, such as the theory of mind performance and gaze to the eye region, and reduce anxiety and related negative cognitive appraisals. While this early research has demonstrated the potential for intranasal OT to treat psychiatric illnesses characterized by social impairments, the neurobiological mechanisms are not well known. Researchers have used functional magnetic resonance imaging (fMRI) to examine the neural correlates of OT response; however, results have been variable and moderating factors are poorly understood. The aim of this meta-analysis is to synthesize data examining the impact of intranasal OT administration on neural activity. Studies that report fMRI data after intranasal OT administration will be identified. PubMed, Embase, PsycINFO, and Google Scholar databases will be searched as well as the citation lists of retrieved articles. Eligible articles written in English from 2005 onwards will be included in the meta-analysis, and corresponding authors of these papers will be invited to contribute t-maps. Data will be collected from eligible studies for synthesis using Seed-based d Mapping (SDM) or Multi-Level Kernel Density Analysis (MKDA), depending on the number of usable t-maps received. Additionally, publication bias and risk of bias will be assessed. This systematic review and meta-analysis will be the first pre-registered synthesis of data to identify the neural correlates of OT nasal spray response. The identification of brain regions underlying OT's observed effects will help guide future research and better identify treatment targets. PROSPERO CRD42016038781.

Characterization and analysis of diesel exhaust odor

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

Shala, F.J.

1983-01-01

An instrumental method known as the Diesel Odor Analysis System or DOAS, has been developed at A.D. Little, Inc. for measuring diesel exhaust odor. It was of interest to determine which compound or compounds in the oxygenated fraction of the exhaust were primarily responsible for the odor correlation as developed at A.D. Little, Inc. This was accomplished by observing how the measurement of the exhaust odor intensity and number of chemical constituents of the oxygenate fraction were changing with respect to the odor values as measured by the DOAS. Benzaldehyde was found to give the best correlation (R = 0.98)more » with odor. A quantitative relationship between exhaust odor as measured by the total intensity of aroma (TIA) and the benzaldehyde concentration (B) in ppm in the exhaust is given by: TIA = 1.11 log/sub 10/(B) + 4.10. This correlation was supported by results obtained from two other diesel engine exhaust sources. A methyl benzaldehyde isomer also yielded a good correlation (R = 0.90) with odor. Air to fuel ratio correlations were determined for the tentatively identified compounds, cinnamaldehyde (R = 0.94) and a C2-benzaldehyde isomer (R = 0.94).« less

Correlates and Predictors of Resilience among Baccalaureate Nursing Students.

PubMed

Mathad, Monali Devaraj; Pradhan, Balaram; Rajesh, Sasidharan K

2017-02-01

A growing body of literature recognizes the importance of resilience in the nursing profession. Both mindfulness and resilience aid in handling stress, stress increases the risk of rumination and/or worry especially in females and they are more empathetic than other healthcare students. To identify correlates and predictors of the resilience among nursing students. This is a descriptive correlation study and we have recruited 194 participants (1-4 th year B.Sc Nursing) from Government College of Nursing and NIMHANS College of Nursing in Bangalore, India. The following instruments were used to collect the data, Freiburg Mindfulness Inventory (FMI), Toronto Empathy Questionnaire (TEQ), Perseverative Thinking Questionnaire (PTQ) and Connor-Davidson Resilience Scale (CD-RISC). Data was analysed using Pearson's correlation test and multiple regression analysis. Resilience is significantly correlated with mindfulness, perseverative thinking and empathy in nursing students. Based on regression analysis this model accounted for almost 33% of variance in resilience. This result is of interest as mindfulness alone explained 23% of the variance and unproductive Repeated Negative Thinking (RNT) and RNT consuming mental capacity predicted 8% and 2% respectively. These results support the importance of resilience and mindfulness in nursing students. Hence, resilience and/or mindfulness enhancing interventions should be inculcated in nursing education.

Study of the influence of Type Ia supernovae environment on the Hubble diagram

NASA Astrophysics Data System (ADS)

Henne, Vincent

2016-06-01

The observational cosmology with distant Type Ia supernovae as standard candles claims that the Universe is in accelerated expansion, caused by a large fraction of dark energy. In this report we investigated SNe Ia environment, studying the impact of the nature of their host galaxies and their distance to the host galactic center on the Hubble diagram fitting. The supernovae used in the analysis were extracted from Joint-Light-curves-Analysis compilation of high-redshift and nearby supernovae. The analysis are based on the empirical fact that SN Ia luminosities depend on their light curve shapes and colors. No conclusive correlation between SN Ia light curve parameters and galocentric distance were identified. Concerning the host morphology, we showed that the stretch parameter of Type Ia supernovae is correlated with the host galaxy type. The supernovae with lower stretch mainly exploded in elliptical and lenticular galaxies. The studies show that into old star population and low dust environment, supernovae are fainter. We did not find any significant correlation between Type Ia supernovae color and host morphology. We confirm that supernova properties depend on their environment and propose to incorporate a host galaxy term into the Hubble diagram fit in the future cosmological analysis.

Urban area thermal monitoring: Liepaja case study using satellite and aerial thermal data

NASA Astrophysics Data System (ADS)

Gulbe, Linda; Caune, Vairis; Korats, Gundars

2017-12-01

The aim of this study is to explore large (60 m/pixel) and small scale (individual building level) temperature distribution patterns from thermal remote sensing data and to conclude what kind of information could be extracted from thermal remote sensing on regular basis. Landsat program provides frequent large scale thermal images useful for analysis of city temperature patterns. During the study correlation between temperature patterns and vegetation content based on NDVI and building coverage based on OpenStreetMap data was studied. Landsat based temperature patterns were independent from the season, negatively correlated with vegetation content and positively correlated with building coverage. Small scale analysis included spatial and raster descriptor analysis for polygons corresponding to roofs of individual buildings for evaluating insulation of roofs. Remote sensing and spatial descriptors are poorly related to heat consumption data, however, thermal aerial data median and entropy can help to identify poorly insulated roofs. Automated quantitative roof analysis has high potential for acquiring city wide information about roof insulation, but quality is limited by reference data quality and information on building types, and roof materials would be crucial for further studies.

Oceanographic variation influences spatial genomic structure in the sea scallop, Placopecten magellanicus.

PubMed

Van Wyngaarden, Mallory; Snelgrove, Paul V R; DiBacco, Claudio; Hamilton, Lorraine C; Rodríguez-Ezpeleta, Naiara; Zhan, Luyao; Beiko, Robert G; Bradbury, Ian R

2018-03-01

Environmental factors can influence diversity and population structure in marine species and accurate understanding of this influence can both improve fisheries management and help predict responses to environmental change. We used 7163 SNPs derived from restriction site-associated DNA sequencing genotyped in 245 individuals of the economically important sea scallop, Placopecten magellanicus , to evaluate the correlations between oceanographic variation and a previously identified latitudinal genomic cline. Sea scallops span a broad latitudinal area (>10 degrees), and we hypothesized that climatic variation significantly drives clinal trends in allele frequency. Using a large environmental dataset, including temperature, salinity, chlorophyll a, and nutrient concentrations, we identified a suite of SNPs (285-621, depending on analysis and environmental dataset) potentially under selection through correlations with environmental variation. Principal components analysis of different outlier SNPs and environmental datasets revealed similar northern and southern clusters, with significant associations between the first axes of each ( R 2 adj  = .66-.79). Multivariate redundancy analysis of outlier SNPs and the environmental principal components indicated that environmental factors explained more than 32% of the variance. Similarly, multiple linear regressions and random-forest analysis identified winter average and minimum ocean temperatures as significant parameters in the link between genetic and environmental variation. This work indicates that oceanographic variation is associated with the observed genomic cline in this species and that seasonal periods of extreme cold may restrict gene flow along a latitudinal gradient in this marine benthic bivalve. Incorporating this finding into management may improve accuracy of management strategies and future predictions.

Individual and Partner Correlates of Sexual Satisfaction and Relationship Happiness in Midlife Couples: Dyadic Analysis of the International Survey of Relationships.

PubMed

Fisher, William A; Donahue, Kelly L; Long, J Scott; Heiman, Julia R; Rosen, Raymond C; Sand, Michael S

2015-08-01

The current research reports a dyadic analysis of sexual satisfaction, relationship happiness, and correlates of these couple outcomes in a large multinational dataset consisting of 1,009 midlife heterosexual couples (2,018 individuals) recruited in Japan, Brazil, Germany, Spain, and the United States (Heiman et al., 2011). Actor-Partner Interdependence Models (Kenny, Kashy, & Cook, 2006) identified correlates of sexual satisfaction that included individuals' reports of good health; frequent kissing, cuddling, and caressing; frequent recent sexual activity; attaching importance to one's own and one's partner's orgasm; better sexual functioning; and greater relationship happiness. Even after controlling for individual-level effects, partners' reports of good health; frequent kissing, cuddling, and caressing; frequent recent sexual activity; attaching importance to one's own and one's partner's orgasm; better sexual functioning; and greater relationship happiness contributed significantly to predicting and understanding individuals' sexual satisfaction. Correlates of relationship happiness included individuals' reports of good health; frequent kissing, cuddling, and caressing; frequent recent sexual activity; attaching importance to one's own and one's partner's orgasm; better sexual functioning; and greater sexual satisfaction, and once again, even after controlling for individual-level effects, partners' reports of each of these correlates contributed significantly to predicting and understanding individuals' relationship happiness. Interactions of individual and partner effects with participant gender are also reported. Current results demonstrate empirically that the partner "matters" to an individual's sexual satisfaction and relationship happiness and indicate that a comprehensive understanding of factors contributing to these couple outcomes requires a couple-level research strategy. Partner effects, even when controlling for individual effects, were consistently observed, and explanation of sexual satisfaction and relationship happiness always depended on identifying and understanding mutual and concurrent individual and partner influences.

ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task.

PubMed

Dasari, Deepika; Shou, Guofa; Ding, Lei

2017-01-01

Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i.e., mental fatigue [also known as time-on-task (TOT) effect], workload and effort, in EEG component signals, which were obtained using an independent component analysis (ICA) on high-density EEG data. EEG data were recorded when subjects performed a realistically simulated air traffic control (ATC) task for 2 h. Five EEG independent component (IC) signals that were associated with specific neural substrates (i.e., the frontal, central medial, motor, parietal, occipital areas) were identified. Their spectral powers at their corresponding dominant bands, i.e., the theta power of the frontal IC and the alpha power of the other four ICs, were detected to be correlated to mental workload and effort levels, measured by behavioral metrics. Meanwhile, a linear regression analysis indicated that spectral powers at five ICs significantly increased with TOT. These findings indicated that different levels of mental factors can be sensitively reflected in EEG signals associated with various brain functions, including visual perception, cognitive processing, and motor outputs, in real-world tasks. These results can potentially aid in the development of efficient operational interfaces to ensure productivity and safety in ATC and beyond.

The Value of the Electrocardiogram for Evaluating Prognosis in Patients with Idiopathic Pulmonary Arterial Hypertension.

PubMed

Cheng, Xiao-Ling; He, Jian-Guo; Liu, Zhi-Hong; Gu, Qing; Ni, Xin-Hai; Zhao, Zhi-Hui; Luo, Qin; Xiong, Chang-Ming

2017-02-01

Association between electrocardiography (ECG) features and right ventricular anatomy and physiology has been established. This study is aimed to identify the value of 12-lead ECG in evaluating prognosis of patients with idiopathic pulmonary arterial hypertension (IPAH). 194 patients with newly diagnosed IPAH were included in this study. Correlations between electrocardiography variables and hemodynamics were assessed. Univariate and multivariable cox regression analysis were performed to identify ECG variables for predicting all-cause mortality in IPAH. Partial correlation analysis showed that P wave amplitude in lead II correlated with the mean pulmonary arterial pressure (mPAP, r = 0.349, p ≤ 0.001) and cardiac index (CI, r = -0.224, p = 0.002); R wave amplitude in V1 correlated with mPAP (r = 0.359, p ≤ 0.001); S wave amplitude in V6 correlated with mPAP (r = 0.259, p = 0.030) and CI (r = -0.220, p = 0.003). P wave amplitude in lead II (HR 1.555, p = 0.033) and R wave amplitude in lead aVR (HR 5.058, p < 0.001) were the independent predictors of all-cause mortality. Kaplan-Meier survival curves showed patients with a p ≥ 0.25 mv in lead II, and R ≥ 0.4 mv in lead aVR had lower 3-year survival (55 vs. 91%, p < 0.001). Specific lead-12 ECG features could reflect right ventricular overload hemodynamics, and are useful to evaluate prognosis of patients with IPAH.

Right ventricular end-systolic area as a simple first-line marker predicting right ventricular enlargement and decreased systolic function in children referred for cardiac magnetic resonance imaging.

PubMed

Barczuk-Falęcka, M; Małek, Ł A; Roik, D; Werys, K; Werner, B; Brzewski, M

2018-06-01

To assess the accuracy of simple cardiovascular magnetic resonance imaging (CMR) parameters for first-line analysis of right ventricle (RV) dysfunction in children to identify those who require in-depth analysis and those in whom simple assessment is sufficient. Sixty paediatric CMR studies were analysed. The following CMR parameters were measured: RV end-diastolic and end-systolic area (4CH EDA and 4CH ESA), fractional area change (FAC), RV diameter in end-diastole (RVD1), tricuspid annular plane systolic excursion (TAPSE), and RV outflow tract diameter in end-diastole (RVOT prox). They were correlated with RV end-diastolic volume (RVEDVI) and RV ejection fraction (RVEF). RVEDVI correlated best with 4CH ESA (r=0.85, <0.001) and EDA (r=0.82, <0.001). For RVEF only a moderate reverse correlation was found for 4CH ESA (-0.56, <0.001), 4CH EDA (-0.49, 0.001) and positive correlation for FAC (0.49, <0.001). There was no correlation between TAPSE and RVEF and only weak between RVD1 and RVEDVI. A 4CH ESA cut-off value of 8.5 cm 2 /m 2 had a very high diagnostic accuracy for predicting an enlarged RV (AUC=0.912, p<0.001, sensitivity 92.3%, specificity 79%) and a cut-off value of 10.5 cm 2 /m 2 was also a good predictor of depressed RV systolic function (AUC=0.873, p<0.001, sensitivity 83%, specificity 89%). For routine screening in clinical practice, 4CH ESA seems a reliable and easy method to identify patients with RV dysfunction. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Behavioral and cognitive outcomes for clinical trials in children with neurofibromatosis type 1.

PubMed

van der Vaart, Thijs; Rietman, André B; Plasschaert, Ellen; Legius, Eric; Elgersma, Ype; Moll, Henriëtte A

2016-01-12

To evaluate the appropriateness of cognitive and behavioral outcome measures in clinical trials in neurofibromatosis type 1 (NF1) by analyzing the degree of deficits compared to reference groups, test-retest reliability, and how scores correlate between outcome measures. Data were analyzed from the Simvastatin for cognitive deficits and behavioral problems in patients with neurofibromatosis type 1 (NF1-SIMCODA) trial, a randomized placebo-controlled trial of simvastatin for cognitive deficits and behavioral problems in children with NF1. Outcome measures were compared with age-specific reference groups to identify domains of dysfunction. Pearson r was computed for before and after measurements within the placebo group to assess test-retest reliability. Principal component analysis was used to identify the internal structure in the outcome data. Strongest mean score deviations from the reference groups were observed for full-scale intelligence (-1.1 SD), Rey Complex Figure Test delayed recall (-2.0 SD), attention problems (-1.2 SD), and social problems (-1.1 SD). Long-term test-retest reliability were excellent for Wechsler scales (r > 0.88), but poor to moderate for other neuropsychological tests (r range 0.52-0.81) and Child Behavioral Checklist subscales (r range 0.40-0.79). The correlation structure revealed 2 strong components in the outcome measures behavior and cognition, with no correlation between these components. Scores on psychosocial quality of life correlate strongly with behavioral problems and less with cognitive deficits. Children with NF1 show distinct deficits in multiple domains. Many outcome measures showed weak test-retest correlations over the 1-year trial period. Cognitive and behavioral outcomes are complementary. This analysis demonstrates the need to include reliable outcome measures on a variety of cognitive and behavioral domains in clinical trials for NF1. © 2015 American Academy of Neurology.

Analysis of Human Proteome Organization Plasma Proteome Project (HUPO PPP) reference specimens using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry: multi-institution correlation of spectra and identification of biomarkers.

PubMed

Rai, Alex J; Stemmer, Paul M; Zhang, Zhen; Adam, Bao-Ling; Morgan, William T; Caffrey, Rebecca E; Podust, Vladimir N; Patel, Manisha; Lim, Lih-Yin; Shipulina, Natalia V; Chan, Daniel W; Semmes, O John; Leung, Hon-Chiu Eastwood

2005-08-01

We report on a multicenter analysis of HUPO reference specimens using SELDI-TOF MS. Eight sites submitted data obtained from serum and plasma reference specimen analysis. Spectra from five sites passed preliminary quality assurance tests and were subjected to further analysis. Intralaboratory CVs varied from 15 to 43%. A correlation coefficient matrix generated using data from these five sites demonstrated high level of correlation, with values >0.7 on 37 of 42 spectra. More than 50 peaks were differentially present among the various sample types, as observed on three chip surfaces. Additionally, peaks at approximately 9200 and approximately 15,950 m/z were present only in select reference specimens. Chromatographic fractionation using anion-exchange, membrane cutoff, and reverse phase chromatography, was employed for protein purification of the approximately 9200 m/z peak. It was identified as the haptoglobin alpha subunit after peptide mass fingerprinting and high-resolution MS/MS analysis. The differential expression of this protein was confirmed by Western blot analysis. These pilot studies demonstrate the potential of the SELDI platform for reproducible and consistent analysis of serum/plasma across multiple sites and also for targeted biomarker discovery and protein identification. This approach could be exploited for population-based studies in all phases of the HUPO PPP.

Analysis of correlated mutations in HIV-1 protease using spectral clustering.

PubMed

Liu, Ying; Eyal, Eran; Bahar, Ivet

2008-05-15

The ability of human immunodeficiency virus-1 (HIV-1) protease to develop mutations that confer multi-drug resistance (MDR) has been a major obstacle in designing rational therapies against HIV. Resistance is usually imparted by a cooperative mechanism that can be elucidated by a covariance analysis of sequence data. Identification of such correlated substitutions of amino acids may be obscured by evolutionary noise. HIV-1 protease sequences from patients subjected to different specific treatments (set 1), and from untreated patients (set 2) were subjected to sequence covariance analysis by evaluating the mutual information (MI) between all residue pairs. Spectral clustering of the resulting covariance matrices disclosed two distinctive clusters of correlated residues: the first, observed in set 1 but absent in set 2, contained residues involved in MDR acquisition; and the second, included those residues differentiated in the various HIV-1 protease subtypes, shortly referred to as the phylogenetic cluster. The MDR cluster occupies sites close to the central symmetry axis of the enzyme, which overlap with the global hinge region identified from coarse-grained normal-mode analysis of the enzyme structure. The phylogenetic cluster, on the other hand, occupies solvent-exposed and highly mobile regions. This study demonstrates (i) the possibility of distinguishing between the correlated substitutions resulting from neutral mutations and those induced by MDR upon appropriate clustering analysis of sequence covariance data and (ii) a connection between global dynamics and functional substitution of amino acids.

Probabilistic and structural reliability analysis of laminated composite structures based on the IPACS code

NASA Technical Reports Server (NTRS)

Sobel, Larry; Buttitta, Claudio; Suarez, James

1993-01-01

Probabilistic predictions based on the Integrated Probabilistic Assessment of Composite Structures (IPACS) code are presented for the material and structural response of unnotched and notched, 1M6/3501-6 Gr/Ep laminates. Comparisons of predicted and measured modulus and strength distributions are given for unnotched unidirectional, cross-ply, and quasi-isotropic laminates. The predicted modulus distributions were found to correlate well with the test results for all three unnotched laminates. Correlations of strength distributions for the unnotched laminates are judged good for the unidirectional laminate and fair for the cross-ply laminate, whereas the strength correlation for the quasi-isotropic laminate is deficient because IPACS did not yet have a progressive failure capability. The paper also presents probabilistic and structural reliability analysis predictions for the strain concentration factor (SCF) for an open-hole, quasi-isotropic laminate subjected to longitudinal tension. A special procedure was developed to adapt IPACS for the structural reliability analysis. The reliability results show the importance of identifying the most significant random variables upon which the SCF depends, and of having accurate scatter values for these variables.

The mediating effect of calling on the relationship between medical school students’ academic burnout and empathy

PubMed Central

2017-01-01

Purpose This study is aimed at identifying the relationships between medical school students’ academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. Methods A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students’ empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. Results The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. Conclusion This result demonstrates that calling is a key variable that mediates the relationship between medical students’ academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students’ empathy skills. PMID:28870019

Cervical vertebral maturation as a biologic indicator of skeletal maturity.

PubMed

Santiago, Rodrigo César; de Miranda Costa, Luiz Felipe; Vitral, Robert Willer Farinazzo; Fraga, Marcelo Reis; Bolognese, Ana Maria; Maia, Lucianne Cople

2012-11-01

To identify and review the literature regarding the reliability of cervical vertebrae maturation (CVM) staging to predict the pubertal spurt. The selection criteria included cross-sectional and longitudinal descriptive studies in humans that evaluated qualitatively or quantitatively the accuracy and reproducibility of the CVM method on lateral cephalometric radiographs, as well as the correlation with a standard method established by hand-wrist radiographs. The searches retrieved 343 unique citations. Twenty-three studies met the inclusion criteria. Six articles had moderate to high scores, while 17 of 23 had low scores. Analysis also showed a moderate to high statistically significant correlation between CVM and hand-wrist maturation methods. There was a moderate to high reproducibility of the CVM method, and only one specific study investigated the accuracy of the CVM index in detecting peak pubertal growth. This systematic review has shown that the studies on CVM method for radiographic assessment of skeletal maturation stages suffer from serious methodological failures. Better-designed studies with adequate accuracy, reproducibility, and correlation analysis, including studies with appropriate sensitivity-specificity analysis, should be performed.

Shuttle structural dynamics characteristics: The analysis and verification

NASA Technical Reports Server (NTRS)

Modlin, C. T., Jr.; Zupp, G. A., Jr.

1985-01-01

The space shuttle introduced a new dimension in the complexity of the structural dynamics of a space vehicle. The four-body configuration exhibited structural frequencies as low as 2 hertz with a model density on the order of 10 modes per hertz. In the verification process, certain mode shapes and frequencies were identified by the users as more important than others and, as such, the test objectives were oriented toward experimentally extracting those modes and frequencies for analysis and test correlation purposes. To provide the necessary experimental data, a series of ground vibration tests (GVT's) was conducted using test articles ranging from the 1/4-scale structural replica of the space shuttle to the full-scale vehicle. The vibration test and analysis program revealed that the mode shapes and frequency correlations below 10 hertz were good. The quality of correlation of modes between 10 and 20 hertz ranged from good to fair and that of modes above 20 hertz ranged from poor to good. Since the most important modes, based on user preference, were below 10 hertz, it was judged that the shuttle structural dynamic models were adequate for flight certifications.

Patient Safety Incidents and Nursing Workload 1

PubMed Central

Carlesi, Katya Cuadros; Padilha, Kátia Grillo; Toffoletto, Maria Cecília; Henriquez-Roldán, Carlos; Juan, Monica Andrea Canales

2017-01-01

ABSTRACT Objective: to identify the relationship between the workload of the nursing team and the occurrence of patient safety incidents linked to nursing care in a public hospital in Chile. Method: quantitative, analytical, cross-sectional research through review of medical records. The estimation of workload in Intensive Care Units (ICUs) was performed using the Therapeutic Interventions Scoring System (TISS-28) and for the other services, we used the nurse/patient and nursing assistant/patient ratios. Descriptive univariate and multivariate analysis were performed. For the multivariate analysis we used principal component analysis and Pearson correlation. Results: 879 post-discharge clinical records and the workload of 85 nurses and 157 nursing assistants were analyzed. The overall incident rate was 71.1%. It was found a high positive correlation between variables workload (r = 0.9611 to r = 0.9919) and rate of falls (r = 0.8770). The medication error rates, mechanical containment incidents and self-removal of invasive devices were not correlated with the workload. Conclusions: the workload was high in all units except the intermediate care unit. Only the rate of falls was associated with the workload. PMID:28403334

Gene network analysis identifies rumen epithelial cell proliferation, differentiation and metabolic pathways perturbed by diet and correlated with methane production

PubMed Central

Xiang, Ruidong; McNally, Jody; Rowe, Suzanne; Jonker, Arjan; Pinares-Patino, Cesar S.; Oddy, V. Hutton; Vercoe, Phil E.; McEwan, John C.; Dalrymple, Brian P.

2016-01-01

Ruminants obtain nutrients from microbial fermentation of plant material, primarily in their rumen, a multilayered forestomach. How the different layers of the rumen wall respond to diet and influence microbial fermentation, and how these process are regulated, is not well understood. Gene expression correlation networks were constructed from full thickness rumen wall transcriptomes of 24 sheep fed two different amounts and qualities of a forage and measured for methane production. The network contained two major negatively correlated gene sub-networks predominantly representing the epithelial and muscle layers of the rumen wall. Within the epithelium sub-network gene clusters representing lipid/oxo-acid metabolism, general metabolism and proliferating and differentiating cells were identified. The expression of cell cycle and metabolic genes was positively correlated with dry matter intake, ruminal short chain fatty acid concentrations and methane production. A weak correlation between lipid/oxo-acid metabolism genes and methane yield was observed. Feed consumption level explained the majority of gene expression variation, particularly for the cell cycle genes. Many known stratified epithelium transcription factors had significantly enriched targets in the epithelial gene clusters. The expression patterns of the transcription factors and their targets in proliferating and differentiating skin is mirrored in the rumen, suggesting conservation of regulatory systems. PMID:27966600

Notch pathway activity identifies cells with cancer stem cell-like properties and correlates with worse survival in lung adenocarcinoma

PubMed Central

Hassan, Khaled A.; Wang, Luo; Korkaya, Hasan; Chen, Guoan; Maillard, Ivan; Beer, David G.; Kalemkerian, Gregory P.; Wicha, Max S.

2013-01-01

Purpose The cancer stem cell theory postulates that tumors contain a subset of cells with stem cell properties of self-renewal, differentiation and tumor-initiation. The purpose of this study is to determine the role of Notch activity in identifying lung cancer stem cells. Experimental Design We investigated the role of Notch activity in lung adenocarcinoma utilizing a Notch GFP-reporter construct and a gamma-secretase inhibitor (GSI), which inhibits Notch pathway activity. Results Transduction of lung cancer cells with Notch GFP-reporter construct identified a subset of cells with high Notch activity (GFP-bright). GFP-bright cells had the ability to form more tumor spheres in serum-free media, and were able to generate both GFP-bright and GFP-dim (lower Notch activity) cell populations. GFP-bright cells were resistant to chemotherapy and were tumorigenic in serial xenotransplantation assays. Tumor xenografts of mice treated with GSI had decreased expression of downstream effectors of Notch pathway and failed to regenerate tumors upon reimplantation in NOD/SCID mice. Using multivariate analysis, we detected a statistically significant correlation between poor clinical outcome and Notch activity (reflected in increased Notch ligand expression or decreased expression of the negative modulators), in a group of 441 lung adenocarcinoma patients. This correlation was further confirmed in an independent group of 89 adenocarcinoma patients where Hes-1 overexpression correlated with poor overall survival. Conclusions Notch activity can identify lung cancer stem cell-like population and its inhibition may be an appropriate target for treating lung adenocarcinoma. PMID:23444212

Genome-Wide Association Mapping of Correlated Traits in Cassava: Dry Matter and Total Carotenoid Content.

PubMed

Rabbi, Ismail Y; Udoh, Lovina I; Wolfe, Marnin; Parkes, Elizabeth Y; Gedil, Melaku A; Dixon, Alfred; Ramu, Punna; Jannink, Jean-Luc; Kulakow, Peter

2017-11-01

Cassava is a starchy root crop cultivated in the tropics for fresh consumption and commercial processing. Primary selection objectives in cassava breeding include dry matter content and micronutrient density, particularly provitamin A carotenoids. These traits are negatively correlated in the African germplasm. This study aimed at identifying genetic markers associated with these traits and uncovering whether linkage and/or pleiotropy were responsible for observed negative correlation. A genome-wide association mapping using 672 clones genotyped at 72,279 single nucleotide polymorphism (SNP) loci was performed. Root yellowness was used indirectly to assess variation in carotenoid content. Two major loci for root yellowness were identified on chromosome 1 at positions 24.1 and 30.5 Mbp. A single locus for dry matter content that colocated with the 24.1 Mbp peak for carotenoids was identified. Haplotypes at these loci explained 70 and 37% of the phenotypic variability for root yellowness and dry matter content, respectively. Evidence of megabase-scale linkage disequilibrium (LD) around the major loci of the two traits and detection of the major dry matter locus in independent analysis for the white- and yellow-root subpopulations suggests that physical linkage rather that pleiotropy is more likely to be the cause of the negative correlation between the target traits. Moreover, candidate genes for carotenoid () and starch biosynthesis ( and ) occurred in the vicinity of the identified locus at 24.1 Mbp. These findings elucidate the genetic architecture of carotenoids and dry matter in cassava and provide an opportunity to accelerate breeding of these traits. Copyright © 2017 Crop Science Society of America.

The HDL receptor SR-BI is associated with human prostate cancer progression and plays a possible role in establishing androgen independence.

PubMed

Schörghofer, David; Kinslechner, Katharina; Preitschopf, Andrea; Schütz, Birgit; Röhrl, Clemens; Hengstschläger, Markus; Stangl, Herbert; Mikula, Mario

2015-08-07

Human prostate cancer represents one of the most frequently diagnosed cancers in men worldwide. Currently, diagnostic methods are insufficient to identify patients at risk for aggressive prostate cancer, which is essential for early treatment. Recent data indicate that elevated cholesterol levels in the plasma are a prerequisite for the progression of prostate cancer. Here, we analyzed clinical prostate cancer samples for the expression of receptors involved in cellular cholesterol uptake. We screened mRNA microarray files of prostate cancer samples for alterations in the expression levels of cholesterol transporters. Furthermore, we performed immunohistochemistry analysis on human primary prostate cancer tissue sections derived from patients to investigate the correlation of SR-BI with clinicopathological parameters and the mTOR target pS6. In contrast to LDLR, we identified SR-BI mRNA and protein expression to be induced in high Gleason grade primary prostate cancers. Histologic analysis of prostate biopsies revealed that 53.6 % of all cancer samples and none of the non-cancer samples showed high SR-BI staining intensity. The disease-free survival time was reduced (P = 0.02) in patients expressing high intra-tumor levels of SR-BI. SR-BI mRNA correlated with HSD17B1 and HSD3B1 and SR-BI protein staining showed correlation with active ribosomal protein S6 (RS = 0.828, P < 0.00001). We identified SR-BI to indicate human prostate cancer formation, suggesting that increased levels of SR-BI may be involved in the generation of a castration-resistant phenotype.

Socio-demographic and lifestyle determinants of dietary patterns in French-speaking Switzerland, 2009-2012.

PubMed

Marques-Vidal, Pedro; Waeber, Gérard; Vollenweider, Peter; Guessous, Idris

2018-01-12

Food intake is a complex behaviour which can be assessed using dietary patterns. Our aim was to characterize dietary patterns and associated factors in French-speaking Switzerland. Cross-sectional study conducted between 2009 and 2012 in the city of Lausanne, Switzerland, including 4372 participants (54% women, 57.3 ± 10.3 years). Food consumption was assessed using a validated food frequency questionnaire. Dietary patterns were assessed by principal components analysis. Three patterns were identified: "Meat & fries"; "Fruits & Vegetables" and "Fatty & sugary". The "Meat & fries" pattern showed the strongest correlations with total and animal protein and cholesterol carbohydrates, dietary fibre and calcium. The "Fruits & Vegetables" pattern showed the strongest correlations with dietary fibre, carotene and vitamin D. The "Fatty & sugary" pattern showed the strongest correlations with total energy and saturated fat. On multivariate analysis, male gender, low educational level and sedentary status were positively associated with the "Meat & fries" and the "Fatty & sugary" patterns, and negatively associated with the "Fruits & Vegetables" pattern. Increasing age was inversely associated with the "Meat & fries" pattern; smoking status was inversely associated with the "Fruits & Vegetables" pattern. Being born in Portugal or Spain was positively associated with the "Meat & fries" and the "Fruits & Vegetables" patterns. Increasing body mass index was positively associated with the "Meat & fries" pattern and inversely associated with the "Fatty & sugary" pattern. Three dietary patterns, one healthy and two unhealthy, were identified in the Swiss population. Several associated modifiable behaviours were identified; the information on socio- demographic determinants allows targeting of the most vulnerable groups in the context of public health interventions.

The role of climatic variables in winter cereal yields: a retrospective analysis.

PubMed

Luo, Qunying; Wen, Li

2015-02-01

This study examined the effects of observed climate including [CO2] on winter cereal [winter wheat (Triticum aestivum), barley (Hordeum vulgare) and oat (Avena sativa)] yields by adopting robust statistical analysis/modelling approaches (i.e. autoregressive fractionally integrated moving average, generalised addition model) based on long time series of historical climate data and cereal yield data at three locations (Moree, Dubbo and Wagga Wagga) in New South Wales, Australia. Research results show that (1) growing season rainfall was significantly, positively and non-linearly correlated with crop yield at all locations considered; (2) [CO2] was significantly, positively and non-linearly correlated with crop yields in all cases except wheat and barley yields at Wagga Wagga; (3) growing season maximum temperature was significantly, negatively and non-linearly correlated with crop yields at Dubbo and Moree (except for barley); and (4) radiation was only significantly correlated with oat yield at Wagga Wagga. This information will help to identify appropriate management adaptation options in dealing with the risk and in taking the opportunities of climate change.

Correlations and forecast of death tolls in the Syrian conflict.

PubMed

Fujita, Kazuki; Shinomoto, Shigeru; Rocha, Luis E C

2017-11-16

The Syrian armed conflict has been ongoing since 2011 and has already caused thousands of deaths. The analysis of death tolls helps to understand the dynamics of the conflict and to better allocate resources and aid to the affected areas. In this article, we use information on the daily number of deaths to study temporal and spatial correlations in the data, and exploit this information to forecast events of deaths. We found that the number of violent deaths per day in Syria varies more widely than that in England in which non-violent deaths dominate. We have identified strong positive auto-correlations in Syrian cities and non-trivial cross-correlations across some of them. The results indicate synchronization in the number of deaths at different times and locations, suggesting respectively that local attacks are followed by more attacks at subsequent days and that coordinated attacks may also take place across different locations. Thus the analysis of high temporal resolution data across multiple cities makes it possible to infer attack strategies, warn potential occurrence of future events, and hopefully avoid further deaths.

Clinical Correlations of Transcriptional Profile in Patients Infected with Avian Influenza H7N9 Virus.

PubMed

Guan, Wenda; Wu, Nicholas C; Lee, Horace H Y; Li, Yimin; Jiang, Wenxin; Shen, Lihan; Wu, Douglas C; Chen, Rongchang; Zhong, Nanshan; Wilson, Ian A; Peiris, Malik; Yang, Zifeng; Mok, Chris K P

2018-05-28

Avian influenza A (H7N9) viruses emerged in China in 2013 and caused zoonotic disease associated with a case-fatality ratio of over 30%. Transcriptional profiles in peripheral blood reflect host responses and can help to elucidate disease pathogenesis. We correlated serial blood transcriptomic profiles of patients with avian influenza A (H7N9) virus infection and determined the biological significances from the analysis. We found that specific gene expression profiles in the blood were strongly correlated with the PaO2/FiO2 ratio and viral load in the lower respiratory tract (LRT). Cell cycle and leukocyte-related immunity were activated at the acute stage of the infection while T cell functions and various metabolic processes were associated with the recovery phase of the illness. A transition from systemic innate to adaptive immunity was found. We developed a novel approach for transcriptomic analysis to identify key host responses that were strongly correlated with specific clinical and virologic parameters in patients with H7N9 infection.

Concentration, distribution and source apportionment of atmospheric polycyclic aromatic hydrocarbons in the southeast suburb of Beijing, China.

PubMed

Zhang, Shucai; Zhang, Wei; Wang, Kaiyan; Shen, Yating; Hu, Lianwu; Wang, Xuejun

2009-04-01

Total suspended particle samples and gas phase samples were collected at three representative sampling sites in the southeastern suburb of Beijing from March 2005 to January 2006. The samples were analyzed for 16 US EPA priority PAHs using GC/MS. Concentrations of Sigma PAHs in particle and gas phases were 0.21-1.18 x 10(3) ng m(-3) and 9.5 x 10(2) ng-1.03 x 10(5) ng m(-3), respectively. PAH concentrations displayed seasonal variation in the order of winter>spring>autumn>summer for particle phase, and winter>autumn>summer>spring for gas phase. Partial correlation analysis indicates that PAH concentrations in particle phase are negatively correlated with temperature and positively correlated with air pollution index of SO(2). No significant correlation is observed between gas phase PAHs and the auxiliary parameters. Sources of PAH are identified through principal component analysis, and source contributions are estimated through multiple linear regression. Major sources of atmospheric PAHs in the study area include coal combustion, coke industry, vehicular emission and natural gas combustion.

Variation in Phytochemical Composition Reveals Distinct Divergence of Aloe vera (L.) Burm.f. From Other Aloe Species: Rationale Behind Selective Preference of Aloe vera in Nutritional and Therapeutic Use

PubMed Central

Dey, Priyankar; Dutta, Somit; Chowdhury, Anurag; Das, Abhaya Prasad; Chaudhuri, Tapas Kumar

2017-01-01

In the present study, we have phytochemically characterized 5 different abundant Aloe species, including Aloe vera (L.) Burm.f., using silylation followed by Gas Chromatography-Mass Spectrometry technique and compared the data using multivariate statistical analysis. The results demonstrated clear distinction of the overall phytochemical profile of A vera, highlighted by its divergent spatial arrangement in the component plot. Lowest correlation of the phytochemical profiles were found between A vera and A aristata Haw. (−0.626), whereas highest correlation resided between A aristata and A aspera Haw. (0.899). Among the individual phytochemicals, palmitic acid was identified in highest abundance cumulatively, and carboxylic acids were the most predominant phytochemical species in all the Aloe species. Compared to A vera, linear correlation analysis revealed highest and lowest correlation with A aspera (R 2 = 0.9162) and A aristata (R 2 = 0.6745), respectively. Therefore, A vera demonstrated distinct spatial allocation, reflecting its greater phytochemical variability. PMID:29228808

[Meteorological risk factors of stroke].

PubMed

Lebedev, I A; Gilvanov, V A; Akinina, S A; Anishchenko, L I

2013-01-01

Based on correlation analysis of stroke, recorded in Khanty-Mansiysk during 5 years, and standard meteorological factors, we found the significant relationship between the frequency of stroke and daily temperature amplitude. The positive correlation between the frequency of stroke and between-day changes in air temperature in the combination with changes in atmospheric pressure during 3 h was identified. A maximal number of strokes was recorded in December, April, May and July and a minimal number was in January, June, August and September. The frequency of stroke and fatal outcomes did not depend on the season.

Local Breast Cancer Spatial Patterning: A Tool for Community Health Resource Allocation to Address Local Disparities in Breast Cancer Mortality

PubMed Central

Brantley-Sieders, Dana M.; Fan, Kang-Hsien; Deming-Halverson, Sandra L.; Shyr, Yu; Cook, Rebecca S.

2012-01-01

Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community. PMID:23028869

SCD-HeFT: Use of RR Interval Statistics for Long-term Risk Stratification for Arrhythmic Sudden Cardiac Death

PubMed Central

Au-yeung, Wan-tai M.; Reinhall, Per; Poole, Jeanne E.; Anderson, Jill; Johnson, George; Fletcher, Ross D.; Moore, Hans J.; Mark, Daniel B.; Lee, Kerry L.; Bardy, Gust H.

2015-01-01

Background In the SCD-HeFT a significant fraction of the congestive heart failure (CHF) patients ultimately did not die suddenly from arrhythmic causes. CHF patients will benefit from better tools to identify if ICD therapy is needed. Objective To identify predictor variables from baseline SCD-HeFT patients’ RR intervals that correlate to arrhythmic sudden cardiac death (SCD) and mortality and to design an ICD therapy screening test. Methods Ten predictor variables were extracted from pre-randomization Holter data from 475 patients enrolled in the SCD-HeFT ICD arm using novel and traditional heart rate variability methods. All variables were correlated to SCD using Mann Whitney-Wilcoxon test and receiver operating characteristic analysis. ICD therapy screening tests were designed by minimizing the cost of false classifications. Survival analysis, including log-rank test and Cox models, was also performed. Results α1 and α2 from detrended fluctuation analysis, the ratio of low to high frequency power, the number of PVCs per hour and heart rate turbulence slope are all statistically significant for predicting the occurrences of SCD (p<0.001) and survival (log-rank p<0.01). The most powerful multivariate predictor tool using the Cox Proportional Hazards was α2 with a hazard ratio of 0.0465 (95% CI: 0.00528 – 0.409, p<0.01). Conclusion Predictor variables from RR intervals correlate to the occurrences of SCD and distinguish survival among SCD-HeFT ICD patients. We believe SCD prediction models should incorporate Holter based RR interval analysis to refine ICD patient selection especially in removing patients who are unlikely to benefit from ICD therapy. PMID:26096609

Neuromuscular Characterization of the Urethra in Continent Women

PubMed Central

Kenton, Kimberly; Mueller, Elizabeth; Brubaker, Linda

2011-01-01

Objectives To describe quantitative urethral function parameters in a racially diverse group of continent women. Materials and Methods Following Institutional Review Board approval, we recruited women without urinary incontinence from the community. To be considered continent, participants answered “never” to the first six questions on the stress subscale of the Medical, Epidemiologic, and Social Aspects of Aging urinary incontinence (MESA) questionnaire. Participants all underwent quantitative concentric urethral electromyography (EMG) and urodynamic testing (UDS). Results Thirty-one women with a mean±SD age of 39±14 years underwent EMG and UDS. The cohort was racially diverse with 13 Caucasians (43%), 13 African Americans (43%), and 4 Hispanics (14%). Body mass index (BMI) (P=.12, .06), age (P=.40, .64), and vaginal parity (P=.53, .76) did not differ by race or ethnicity. We did not detect differences in any EMG parameter by race, ethnicity or vaginally parity. A mean (range) of 30 motor unit action potential analysis (MUP) (10-55) were identified and analyzed in Multi-MUP analysis and 14 (8-21) were identified and analyzed in IP analysis. On average, 37±20% MUPs were polyphasic. Age significantly correlated with several measures of urethral sphincter function. Increasing age was inversely correlated with interference analysis (IP) turns (−.57, p=.001), IP amplitude (r=−.43, p=.02), IP turns/amplitude (r=−.54, p=.003), maximum urethral closure pressures (MUCP) (r=−.41, p=.04). Similarly, MUCP correlated with IP amplitude (r=.38, p=.04). Conclusions This urethral neuromuscular function data on the largest cohort of continent women fully characterized with quantitative urethral EMG demonstrates significant neuropathic MUP changes with advancing age. PMID:22453105

MCM - 2 and Ki - 67 as proliferation markers in renal cell carcinoma: A quantitative and semi - quantitative analysis

PubMed Central

Mehdi, Muhammad Zain; Nagi, Abdul Hanan; Naseem, Nadia

2016-01-01

ABSTRACT Introduction/Background: Fuhrman nuclear grade is the most important histological parameter to predict prognosis in a patient of renal cell carcinoma (RCC). However, it suffers from inter-observer and intra-observer variation giving rise to need of a parameter that not only correlates with nuclear grade but is also objective and reproducible. Proliferation is the measure of aggressiveness of a tumour and it is strongly correlated with Fuhrman nuclear grade, clinical survival and recurrence in RCC. Ki-67 is conventionally used to assess proliferation. Mini-chromosome maintenance 2 (MCM-2) is a lesser known marker of proliferation and identifies a greater proliferation faction. This study was designed to assess the prognostic significance of MCM-2 by comparing it with Fuhrman nuclear grade and Ki-67. Material and Methods: n=50 cases of various ages, stages, histological subtypes and grades of RCC were selected for this study. Immunohistochemical staining using Ki-67(MIB-1, Mouse monoclonal antibody, Dako) and MCM-2 (Mouse monoclonal antibody, Thermo) was performed on the paraffin embedded blocks in the department of Morbid anatomy and Histopathology, University of Health Sciences, Lahore. Labeling indices (LI) were determined by two pathologists independently using quantitative and semi-quantitative analysis. Statistical analysis was carried out using SPSS 20.0. Kruskall-Wallis test was used to determine a correlation of proliferation markers with grade, and Pearson's correlate was used to determine correlation between the two proliferation markers. Results: Labeling index of MCM-2 (median=24.29%) was found to be much higher than Ki-67(median=13.05%). Both markers were significantly related with grade (p=0.00; Kruskall-Wallis test). LI of MCM-2 was found to correlate significantly with LI of Ki-67(r=0.0934;p=0.01 with Pearson's correlate). Results of semi-quantitative analysis correlated well with quantitative analysis. Conclusion: Both Ki-67 and MCM-2 are markers of proliferation which are closely linked to grade. Therefore, they can act as surrogate markers for grade in a manner that is more objective and reproducible. PMID:27532114

MCM - 2 and Ki - 67 as proliferation markers in renal cell carcinoma: A quantitative and semi - quantitative analysis.

PubMed

Mehdi, Muhammad Zain; Nagi, Abdul Hanan; Naseem, Nadia

2016-01-01

Fuhrman nuclear grade is the most important histological parameter to predict prognosis in a patient of renal cell carcinoma (RCC). However, it suffers from inter-observer and intra-observer variation giving rise to need of a parameter that not only correlates with nuclear grade but is also objective and reproducible. Proliferation is the measure of aggressiveness of a tumour and it is strongly correlated with Fuhrman nuclear grade, clinical survival and recurrence in RCC. Ki-67 is conventionally used to assess proliferation. Mini-chromosome maintenance 2 (MCM-2) is a lesser known marker of proliferation and identifies a greater proliferation faction. This study was designed to assess the prognostic significance of MCM-2 by comparing it with Fuhrman nuclear grade and Ki-67. n=50 cases of various ages, stages, histological subtypes and grades of RCC were selected for this study. Immunohistochemical staining using Ki-67(MIB-1, Mouse monoclonal antibody, Dako) and MCM-2 (Mouse monoclonal antibody, Thermo) was performed on the paraffin embedded blocks in the department of Morbid anatomy and Histopathology, University of Health Sciences, Lahore. Labeling indices (LI) were determined by two pathologists independently using quantitative and semi-quantitative analysis. Statistical analysis was carried out using SPSS 20.0. Kruskall-Wallis test was used to determine a correlation of proliferation markers with grade, and Pearson's correlate was used to determine correlation between the two proliferation markers. Labeling index of MCM-2 (median=24.29%) was found to be much higher than Ki-67(median=13.05%). Both markers were significantly related with grade (p=0.00; Kruskall-Wallis test). LI of MCM-2 was found to correlate significantly with LI of Ki-67(r=0.0934;p=0.01 with Pearson's correlate). Results of semi-quantitative analysis correlated well with quantitative analysis. Both Ki-67 and MCM-2 are markers of proliferation which are closely linked to grade. Therefore, they can act as surrogate markers for grade in a manner that is more objective and reproducible. Copyright® by the International Brazilian Journal of Urology.

Comprehensive Investigation of White Matter Tracts in Professional Chess Players and Relation to Expertise: Region of Interest and DMRI Connectometry.

PubMed

Mayeli, Mahsa; Rahmani, Farzaneh; Aarabi, Mohammad Hadi

2018-01-01

Purpose: Expertise is the product of training. Few studies have used functional connectivity or conventional diffusometric methods to identify neural underpinnings of chess expertise. Diffusometric variables of white matter might reflect these adaptive changes, along with changes in structural connectivity, which is a sensitive measure of microstructural changes. Method: Diffusometric variables of 29 professional chess players and 29 age-sex matched controls were extracted for white matter regions based on John Hopkin's Mori white matter atlas and partially correlated against professional training time and level of chess proficiency. Diffusion MRI connectometry was implemented to identify changes in structural connectivity in professional players compared to novices. Result: Compared to novices, higher planar anisotropy (CP) was observed in inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF) and cingulate gyrus, in professional chess players, which correlated with higher RPM score in this group. Higher fractional anisotropy (FA) was observed in ILF, uncinate fasciculus (UF) and hippocampus and correlated with better scores in Raven's progressive matrices (RPM) score and longer duration of chess training in professional players. Consistently, radial diffusivity in bilateral IFOF, bilateral ILF and bilateral SLF was inversely correlated with level of training in professional players. DMRI connectometry analysis identified increased connectivity in bilateral UF, bilateral IFOF, bilateral cingulum, and corpus callosum in chess player's compared to controls. Conclusion: Structural connectivity of major associational subcortical white matter fibers are increased in professional chess players. FA and CP of ILF, SLF and UF directly correlates with duration of professional training and RPM score, in professional chess players.

Comprehensive Investigation of White Matter Tracts in Professional Chess Players and Relation to Expertise: Region of Interest and DMRI Connectometry

PubMed Central

Mayeli, Mahsa; Rahmani, Farzaneh; Aarabi, Mohammad Hadi

2018-01-01

Purpose: Expertise is the product of training. Few studies have used functional connectivity or conventional diffusometric methods to identify neural underpinnings of chess expertise. Diffusometric variables of white matter might reflect these adaptive changes, along with changes in structural connectivity, which is a sensitive measure of microstructural changes. Method: Diffusometric variables of 29 professional chess players and 29 age-sex matched controls were extracted for white matter regions based on John Hopkin's Mori white matter atlas and partially correlated against professional training time and level of chess proficiency. Diffusion MRI connectometry was implemented to identify changes in structural connectivity in professional players compared to novices. Result: Compared to novices, higher planar anisotropy (CP) was observed in inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF) and cingulate gyrus, in professional chess players, which correlated with higher RPM score in this group. Higher fractional anisotropy (FA) was observed in ILF, uncinate fasciculus (UF) and hippocampus and correlated with better scores in Raven's progressive matrices (RPM) score and longer duration of chess training in professional players. Consistently, radial diffusivity in bilateral IFOF, bilateral ILF and bilateral SLF was inversely correlated with level of training in professional players. DMRI connectometry analysis identified increased connectivity in bilateral UF, bilateral IFOF, bilateral cingulum, and corpus callosum in chess player's compared to controls. Conclusion: Structural connectivity of major associational subcortical white matter fibers are increased in professional chess players. FA and CP of ILF, SLF and UF directly correlates with duration of professional training and RPM score, in professional chess players. PMID:29773973

Identifying Crucial Parameter Correlations Maintaining Bursting Activity

PubMed Central

Doloc-Mihu, Anca; Calabrese, Ronald L.

2014-01-01

Recent experimental and computational studies suggest that linearly correlated sets of parameters (intrinsic and synaptic properties of neurons) allow central pattern-generating networks to produce and maintain their rhythmic activity regardless of changing internal and external conditions. To determine the role of correlated conductances in the robust maintenance of functional bursting activity, we used our existing database of half-center oscillator (HCO) model instances of the leech heartbeat CPG. From the database, we identified functional activity groups of burster (isolated neuron) and half-center oscillator model instances and realistic subgroups of each that showed burst characteristics (principally period and spike frequency) similar to the animal. To find linear correlations among the conductance parameters maintaining functional leech bursting activity, we applied Principal Component Analysis (PCA) to each of these four groups. PCA identified a set of three maximal conductances (leak current, Leak; a persistent K current, K2; and of a persistent Na+ current, P) that correlate linearly for the two groups of burster instances but not for the HCO groups. Visualizations of HCO instances in a reduced space suggested that there might be non-linear relationships between these parameters for these instances. Experimental studies have shown that period is a key attribute influenced by modulatory inputs and temperature variations in heart interneurons. Thus, we explored the sensitivity of period to changes in maximal conductances of Leak, K2, and P, and we found that for our realistic bursters the effect of these parameters on period could not be assessed because when varied individually bursting activity was not maintained. PMID:24945358

Discovering cell types in flow cytometry data with random matrix theory

NASA Astrophysics Data System (ADS)

Shen, Yang; Nussenblatt, Robert; Losert, Wolfgang

Flow cytometry is a widely used experimental technique in immunology research. During the experiments, peripheral blood mononuclear cells (PBMC) from a single patient, labeled with multiple fluorescent stains that bind to different proteins, are illuminated by a laser. The intensity of each stain on a single cell is recorded and reflects the amount of protein expressed by that cell. The data analysis focuses on identifying specific cell types related to a disease. Different cell types can be identified by the type and amount of protein they express. To date, this has most often been done manually by labelling a protein as expressed or not while ignoring the amount of expression. Using a cross correlation matrix of stain intensities, which contains both information on the proteins expressed and their amount, has been largely ignored by researchers as it suffers from measurement noise. Here we present an algorithm to identify cell types in flow cytometry data which uses random matrix theory (RMT) to reduce noise in a cross correlation matrix. We demonstrate our method using a published flow cytometry data set. Compared with previous analysis techniques, we were able to rediscover relevant cell types in an automatic way. Department of Physics, University of Maryland, College Park, MD 20742.

Preoperative partitioning of pulmonary vascular resistance correlates with early outcome after thromboendarterectomy for chronic thromboembolic pulmonary hypertension.

PubMed

Kim, Nick H S; Fesler, Pierre; Channick, Richard N; Knowlton, Kirk U; Ben-Yehuda, Ori; Lee, Stephen H; Naeije, Robert; Rubin, Lewis J

2004-01-06

Pulmonary thromboendarterectomy (PTE) is the preferred treatment for chronic thromboembolic pulmonary hypertension (CTEPH), but persistent pulmonary hypertension after PTE, as a result of either inaccessible distal thrombotic material or coexistent intrinsic small-vessel disease, remains a major determinant of poor outcome. Conventional preoperative evaluation is unreliable in identifying patients at risk for persistent pulmonary hypertension or predicting postoperative hemodynamic outcome. We postulated that pulmonary arterial occlusion pressure waveform analysis, a technique that has been used for partitioning pulmonary vascular resistance, might identify CTEPH patients with significant distal, small-vessel disease. Twenty-six patients underwent preoperative right heart catheterization before PTE. Pulmonary artery occlusion waveform recordings were performed in triplicate. Postoperative hemodynamics after PTE were compared with preoperative partitioning of pulmonary vascular resistance derived from the occlusion data. Preoperative assessment of upstream resistance (Rup) correlated with both postoperative total pulmonary resistance index (R2=0.79, P<0.001) and postoperative mean pulmonary artery pressure (R2=0.75, P<0.001). All 4 postoperative deaths occurred in patients with a preoperative Rup <60%. Pulmonary arterial occlusion pressure waveform analysis may identify CTEPH patients at risk for persistent pulmonary hypertension and poor outcome after PTE. Patients with CTEPH and Rup value <60% appear to be at highest risk.

Variations in the correlation between teleconnections and Taiwan's streamflow

NASA Astrophysics Data System (ADS)

Chen, Chia-Jeng; Lee, Tsung-Yu

2017-07-01

Interannual variations in catchment streamflow represent an integrated response to anomalies in regional moisture transport and atmospheric circulations and are ultimately linked to large-scale climate oscillations. This study conducts correlation analysis to calculate how summertime (July-September, JAS) streamflow data derived at 28 upstream and 13 downstream gauges in Taiwan correlate with 14 teleconnection indices in the current or preceding seasons. We find that the western Pacific (WP) and Pacific-Japan (PJ) patterns, both of which play a critical role in determining cyclonic activity in the western North Pacific basin, exhibit the highest concurrent correlations (most significant r = 0. 50) with the JAS flows in Taiwan. Alternatively, the Quasi-Biennial Oscillation (QBO) averaged over the period from the previous October to June of the current year is significantly correlated with the JAS flows (most significant r = -0. 66), indicating some forecasting utility. By further examining the correlation results using a 20-year moving window, peculiar temporal variations and possible climate regime shifts (CRSs) can be revealed. A CRS test is employed to identify suspicious and abrupt changes in the correlation. The late 1970s and 1990s are identified as two significant change points. During the intermediate period, Taiwan's streamflow and the PJ index exhibit a marked in-phase relationship (r > 0. 8). It is verified that the two shifts are in concordance with the alteration of large-scale circulations in the Pacific basin by investigating the changes in pattern correlation and composite maps before and after the change point. Our results suggest that empirical forecasting techniques should take into account the effect of CRSs on predictor screening.

Nursing leadership style and psychosocial work environment.

PubMed

Malloy, Terry; Penprase, Barbara

2010-09-01

This study examines the relationship between leadership style and the psychosocial work environment of registered nurses. Research consistently supports the positive relationship between transformational leadership style and job satisfaction. There is less evidence, which identifies the relationship between leadership style and psychosocial work environment. The Multifactor Leadership Questionnaire 5× was used to identify the leadership style. The Copenhagen Psychosocial Questionnaire was used to measure psychosocial work environment dimensions. Statistical analysis included Pearson's r correlation between leadership style and psychosocial work environment and anova to analyse group means. There is a significant correlation between leadership style and 22 out of the 37 dimensions of the psychosocial work environment. This correlation was significant ranging from r = 0.88, P < 0.01 to r = 0.18, P < 0.05. Nurses divided into groups based on transformational leadership scores of the immediate supervisor report significant differences in their psychosocial work environment. This study supports the significant correlation between leadership style and psychosocial work environment for registered nurses. The results of this study suggest that there would be an improvement in the nursing psychosocial work environment by implementation of transformational and contingent reward leadership behaviours. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

Application of objective clinical human reliability analysis (OCHRA) in assessment of technical performance in laparoscopic rectal cancer surgery.

PubMed

Foster, J D; Miskovic, D; Allison, A S; Conti, J A; Ockrim, J; Cooper, E J; Hanna, G B; Francis, N K

2016-06-01

Laparoscopic rectal resection is technically challenging, with outcomes dependent upon technical performance. No robust objective assessment tool exists for laparoscopic rectal resection surgery. This study aimed to investigate the application of the objective clinical human reliability analysis (OCHRA) technique for assessing technical performance of laparoscopic rectal surgery and explore the validity and reliability of this technique. Laparoscopic rectal cancer resection operations were described in the format of a hierarchical task analysis. Potential technical errors were defined. The OCHRA technique was used to identify technical errors enacted in videos of twenty consecutive laparoscopic rectal cancer resection operations from a single site. The procedural task, spatial location, and circumstances of all identified errors were logged. Clinical validity was assessed through correlation with clinical outcomes; reliability was assessed by test-retest. A total of 335 execution errors identified, with a median 15 per operation. More errors were observed during pelvic tasks compared with abdominal tasks (p < 0.001). Within the pelvis, more errors were observed during dissection on the right side than the left (p = 0.03). Test-retest confirmed reliability (r = 0.97, p < 0.001). A significant correlation was observed between error frequency and mesorectal specimen quality (r s = 0.52, p = 0.02) and with blood loss (r s = 0.609, p = 0.004). OCHRA offers a valid and reliable method for evaluating technical performance of laparoscopic rectal surgery.

Examining the relationship of ethnicity, gender and social cognitive factors with the academic achievement of first-year engineering students

NASA Astrophysics Data System (ADS)

Carr, Bruce Henry

The purpose of the study was to examine the relationships of social cognitive factors and their influence on the academic performance of first-year engineering students. The nine social cognitive variables identified were under the groupings of personal support, occupational self-efficacy, academic self-efficacy, vocational interests, coping, encouragement, discouragement, outcome expectations, and perceived stress. The primary student participants in this study were first-year engineering students from underrepresented groups which include African American, Hispanic American students and women. With this in mind, the researcher sought to examine the interactive influence of race/ethnicity and gender based on the aforementioned social cognitive factors. Differences in academic performance (university GPA of first-year undergraduate engineering students) were analyzed by ethnicity and gender. There was a main effect for ethnicity only. Gender was found not to be significant. Hispanics were not found to be significantly different in their GPAs than Whites but Blacks were found to have lower GPAs than Whites. Also, Pearson correlation coefficients were used to examine the relationship between and among the nine identified social cognitive variables. The data from the analysis uncovered ten significant correlations which were as follows: occupational self-efficacy and academic self-efficacy, occupational self-efficacy and vocational interest, occupational self-efficacy and perceived stress, academic self-efficacy and encouragement, academic self-efficacy and outcome expectations, academic self-efficacy and perceived stress, vocational interest and outcome expectations, discouragement and encouragement, coping and perceived stress, outcome expectations and perceived stress. Next, a Pearson correlation coefficient was utilized to examine the relationship between academic performance (college GPA) of first-year undergraduate engineering students and the nine identified social cognitive variables. The data analysis revealed three significant correlations which were as follows academic performance and occupational self-efficacy, academic performance and academic self-efficacy, and academic performance and encouragement. Finally, a Pearson correlation coefficient was used to examine the relationship between high school GPA and the nine identified social cognitive variables. The Pearson correlational coefficient indicated that there was one statistically significant correlation which was high school GPA and academic self-efficacy. Recommendations for further study included (a) future research involving investigations that compare a variety of institutions in different regions of the country; (b) further investigations utilizing open-ended responses from engineering students based on interviews; (c) a replicated study in 5 to 10 years to evaluate whether differences emerged relating to ethnicity and gender due to possible societal or cultural changes; and (d) a study involving a pretest and posttest of students' self-efficacy beliefs. Finally, the researcher recommends a qualitative study specifically involving interview questions aimed at students with moderate level grades and SAT scores who exhibited above average academic performance. (Abstract shortened by UMI.).

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer.

PubMed

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando; Treviño, Victor

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures.

Relationships among body weight, joint moments generated during functional activities, and hip bone mass in older adults

PubMed Central

Wang, Man-Ying; Flanagan, Sean P.; Song, Joo-Eun; Greendale, Gail A.; Salem, George J.

2012-01-01

Objective To investigate the relationships among hip joint moments produced during functional activities and hip bone mass in sedentary older adults. Methods Eight male and eight female older adults (70–85 yr) performed functional activities including walking, chair sit–stand–sit, and stair stepping at a self-selected pace while instrumented for biomechanical analysis. Bone mass at proximal femur, femoral neck, and greater trochanter were measured by dual-energy X-ray absorptiometry. Three-dimensional hip moments were obtained using a six-camera motion analysis system, force platforms, and inverse dynamics techniques. Pearson’s correlation coefficients were employed to assess the relationships among hip bone mass, height, weight, age, and joint moments. Stepwise regression analyses were performed to determine the factors that significantly predicted bone mass using all significant variables identified in the correlation analysis. Findings Hip bone mass was not significantly correlated with moments during activities in men. Conversely, in women bone mass at all sites were significantly correlated with weight, moments generated with stepping, and moments generated with walking (p < 0.05 to p < 0.001). Regression analysis results further indicated that the overall moments during stepping independently predicted up to 93% of the variability in bone mass at femoral neck and proximal femur; whereas weight independently predicted up to 92% of the variability in bone mass at greater trochanter. Interpretation Submaximal loading events produced during functional activities were highly correlated with hip bone mass in sedentary older women, but not men. The findings may ultimately be used to modify exercise prescription for the preservation of bone mass. PMID:16631283

A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence.

PubMed

Hill, W D; Marioni, R E; Maghzian, O; Ritchie, S J; Hagenaars, S P; McIntosh, A M; Gale, C R; Davies, G; Deary, I J

2018-01-11

Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (r g  = 0.70). We used these findings as foundations for our use of a novel approach-multi-trait analysis of genome-wide association studies (MTAG; Turley et al. 2017)-to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination-as well as genes expressed in the synapse, and those involved in the regulation of the nervous system-may explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer

PubMed Central

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures. PMID:29596496

Short-time windowed covariance: A metric for identifying non-stationary, event-related covariant cortical sites

PubMed Central

Blakely, Timothy; Ojemann, Jeffrey G.; Rao, Rajesh P.N.

2014-01-01

Background Electrocorticography (ECoG) signals can provide high spatio-temporal resolution and high signal to noise ratio recordings of local neural activity from the surface of the brain. Previous studies have shown that broad-band, spatially focal, high-frequency increases in ECoG signals are highly correlated with movement and other cognitive tasks and can be volitionally modulated. However, significant additional information may be present in inter-electrode interactions, but adding additional higher order inter-electrode interactions can be impractical from a computational aspect, if not impossible. New method In this paper we present a new method of calculating high frequency interactions between electrodes called Short-Time Windowed Covariance (STWC) that builds on mathematical techniques currently used in neural signal analysis, along with an implementation that accelerates the algorithm by orders of magnitude by leveraging commodity, off-the-shelf graphics processing unit (GPU) hardware. Results Using the hardware-accelerated implementation of STWC, we identify many types of event-related inter-electrode interactions from human ECoG recordings on global and local scales that have not been identified by previous methods. Unique temporal patterns are observed for digit flexion in both low- (10 mm spacing) and high-resolution (3 mm spacing) electrode arrays. Comparison with existing methods Covariance is a commonly used metric for identifying correlated signals, but the standard covariance calculations do not allow for temporally varying covariance. In contrast STWC allows and identifies event-driven changes in covariance without identifying spurious noise correlations. Conclusions: STWC can be used to identify event-related neural interactions whose high computational load is well suited to GPU capabilities. PMID:24211499

HRCT findings of collagen vascular disease-related interstitial pneumonia (CVD-IP): a comparative study among individual underlying diseases.

PubMed

Tanaka, N; Kunihiro, Y; Kubo, M; Kawano, R; Oishi, K; Ueda, K; Gondo, T

2018-05-29

To identify characteristic high-resolution computed tomography (CT) findings for individual collagen vascular disease (CVD)-related interstitial pneumonias (IPs). The HRCT findings of 187 patients with CVD, including 55 patients with rheumatoid arthritis (RA), 50 with systemic sclerosis (SSc), 46 with polymyositis/dermatomyositis (PM/DM), 15 with mixed connective tissue disease, 11 with primary Sjögren's syndrome, and 10 with systemic lupus erythematosus, were evaluated. Lung parenchymal abnormalities were compared among CVDs using χ 2 test, Kruskal-Wallis test, and multiple logistic regression analysis. A CT-pathology correlation was performed in 23 patients. In RA-IP, honeycombing was identified as the significant indicator based on multiple logistic regression analyses. Traction bronchiectasis (81.8%) was further identified as the most frequent finding based on χ 2 test. In SSc IP, lymph node enlargement and oesophageal dilatation were identified as the indicators based on multiple logistic regression analyses, and ground-glass opacity (GGO) was the most extensive based on Kruskal-Wallis test, which reflects the higher frequency of the pathological nonspecific interstitial pneumonia (NSIP) pattern present in the CT-pathology correlation. In PM/DM IP, airspace consolidation and the absence of honeycombing were identified as the indicators based on multiple logistic regression analyses, and predominance of consolidation over GGO (32.6%) and predominant subpleural distribution of GGO/consolidation (41.3%) were further identified as the most frequent findings based on χ 2 test, which reflects the higher frequency of the pathological NSIP and/or the organising pneumonia patterns present in the CT-pathology correlation. Several characteristic high-resolution CT findings with utility for estimating underlying CVD were identified. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Urban and regional land use analysis: CARETS and Census Cities experiment package

NASA Technical Reports Server (NTRS)

Alexander, R. H. (Principal Investigator); Milazzo, V. A.

1973-01-01

The author has identified the following significant results. Areas of post 1970 and 1972 land use changes were identified solely from the Skylab imagery from comparisons with 1970 land use maps. Most land use changes identified involved transition from agriculture to single family residential land use. The second most prominent changes identified from the Skylab imagery were areas presently under construction. Post 1970 changes from Skylab were compared with the 1972 changes noted from the high altitude photographs. A good correlation existed between the change polygons mapped from Skylab and those mapped from the 1972 high altitude aerial photos. In addition, there were a number of instances where additional built-up land use not noted in the 1972 aerial photo as being developed were identified on the Skylab imagery. While these cases have not been documented by field observation, by correlating these areas with the appearance of similar land use areas whose identity has been determined, we can safely say that we have been able to map further occurrences of land use change beyond existing high altitude photo coverage from the Skylab imagery. It was concluded that Skylab data can be used to detect areas of land use change within an urban setting.

TreeGenes and CartograTree: Enabling visualization and analysis in forest tree genomics

Treesearch

E.S. Grau; S.A. Demurjian; H.A. Vasquez-Gross; D.G. Gessler; D.B. Neale; J.L. Wegrzyn

2017-01-01

Association studies integrating environmental, phenotypic, and genetic data are key in understanding forest tree resilience to climate change and disease. As genomic resources increase, both in terms of complete reference sequences and magnitude of individuals genotyped, researchers are better equipped to identify correlations between genetic variation and adaptive or...

Promoting College Students' Problem Understanding Using Schema-Emphasizing Worked Examples

ERIC Educational Resources Information Center

Yan, Jie; Lavigne, Nancy C.

2014-01-01

Statistics learners often bypass the critical step of understanding a problem before executing solutions. Worked-out examples that identify problem information (e.g., data type, number of groups, purpose of analysis) key to determining a solution (e.g., "t" test, chi-square, correlation) can address this concern. The authors examined the…

Seeking the Cause of Correlations among Mental Abilities: Large Twin Analysis in a National Testing Program.

ERIC Educational Resources Information Center

Page, Ellis B.; Jarjoura, David

1979-01-01

A computer scan of ACT Assessment records identified 3,427 sets of twins. The Hardy-Weinberg rule was used to estimate the proportion of monozygotic twins in the sample. Matrices of genetic and environmental influences were produced. The heaviest loadings were clearly in the genetic matrix. (SJL)

Empirical Validation of a New Category System: One Example.

ERIC Educational Resources Information Center

Rosenshine, Barak; And Others

This study found that data from previous research can be used to validate a new observational category system and that subscripting of the original ten categories of the Flanders Interaction Analysis System is useful in identifying more specific behaviors which correlate with student achievement. The new category system was the Expanded…

An Integrated Framework for the Analysis of Adolescent Cigarette Smoking in Middle School Latino Youth

ERIC Educational Resources Information Center

Guilamo-Ramos, Vincent; Dittus, Patricia; Holloway, Ian; Bouris, Alida; Crossett, Linda

2011-01-01

A framework based on five major theories of health behavior was used to identify the correlates of adolescent cigarette smoking. The framework emphasizes intentions to smoke cigarettes, factors that influence these intentions, and factors that moderate the intention-behavior relationship. Five hundred sixteen randomly selected Latino middle school…

Efficacy Trade-Offs in Individuals' Support for Climate Change Policies

ERIC Educational Resources Information Center

Rosentrater, Lynn D.; Saelensminde, Ingrid; Ekström, Frida; Böhm, Gisela; Bostrom, Ann; Hanss, Daniel; O'Connor, Robert E.

2013-01-01

Using survey data, the authors developed an architecture of climate change beliefs in Norway and their correlation with support for policies aimed at reducing greenhouse gas emissions. A strong majority of respondents believe that anthropogenic climate change is occurring and identify carbon dioxide emissions as a cause. Regression analysis shows…

The Reliability and Validity of a Campus Caring Instrument Developed for Undergraduate Students in Hong Kong

ERIC Educational Resources Information Center

Ng, Petrus; Su, Xiqing Susan; Chan, Vivien; Leung, Heidi; Cheung, Wendy; Tsun, Angela

2013-01-01

This study validated a Perceived Campus Caring Scale with 1,520 university students. Using factor analysis, seven factors namely, Faculty Support, Nonfaculty Support, Peer Relationship, Sense of Detachment, Sense of Belonging, Caring Attitude, and Campus Involvement, are identified with high reliability, validity, and close correlation with the…

Partner Schemas and Relationship Functioning: A States of Mind Analysis

ERIC Educational Resources Information Center

Chatav, Yael; Whisman, Mark A.

2009-01-01

Cognitions such as relationship attributions and beliefs, measured by self-report, have been identified as robust correlates of relationship (e.g., marital) satisfaction. This study sought to build on the theory and assessment of cognitions in relationships by evaluating partner schemas, defined in terms of self-ratings and recall of positive and…

Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

PubMed Central

Lo, Min-Tzu; Hinds, David A.; Tung, Joyce Y.; Franz, Carol; Fan, Chun-Chieh; Wang, Yunpeng; Smeland, Olav B.; Schork, Andrew; Holland, Dominic; Kauppi, Karolina; Sanyal, Nilotpal; Escott-Price, Valentina; Smith, Daniel J.; O'Donovan, Michael; Stefansson, Hreinn; Bjornsdottir, Gyda; Thorgeirsson, Thorgeir E.; Stefansson, Kari; McEvoy, Linda K.; Dale, Anders M.; Andreassen, Ole A.; Chen, Chi-Hua

2017-01-01

Summary Personality is influenced by genetic and environmental factors1, and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N=123,132–260,861). Of these genome-wide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N=5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit/hyperactivity disorder (ADHD), and between openness and schizophrenia/bipolar disorder. The second genetic dimension was closely aligned with extraversion-introversion and grouped neuroticism with internalizing psychopathology (e.g., depression/anxiety). PMID:27918536

Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders.

PubMed

Lo, Min-Tzu; Hinds, David A; Tung, Joyce Y; Franz, Carol; Fan, Chun-Chieh; Wang, Yunpeng; Smeland, Olav B; Schork, Andrew; Holland, Dominic; Kauppi, Karolina; Sanyal, Nilotpal; Escott-Price, Valentina; Smith, Daniel J; O'Donovan, Michael; Stefansson, Hreinn; Bjornsdottir, Gyda; Thorgeirsson, Thorgeir E; Stefansson, Kari; McEvoy, Linda K; Dale, Anders M; Andreassen, Ole A; Chen, Chi-Hua

2017-01-01

Personality is influenced by genetic and environmental factors and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132-260,861). Of these genome-wide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422-18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit-hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion-introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety).

Accuracy improvement of the H-drive air-levitating wafer inspection stage based on error analysis and compensation

NASA Astrophysics Data System (ADS)

Zhang, Fan; Liu, Pinkuan

2018-04-01

In order to improve the inspection precision of the H-drive air-bearing stage for wafer inspection, in this paper the geometric error of the stage is analyzed and compensated. The relationship between the positioning errors and error sources are initially modeled, and seven error components are identified that are closely related to the inspection accuracy. The most effective factor that affects the geometric error is identified by error sensitivity analysis. Then, the Spearman rank correlation method is applied to find the correlation between different error components, aiming at guiding the accuracy design and error compensation of the stage. Finally, different compensation methods, including the three-error curve interpolation method, the polynomial interpolation method, the Chebyshev polynomial interpolation method, and the B-spline interpolation method, are employed within the full range of the stage, and their results are compared. Simulation and experiment show that the B-spline interpolation method based on the error model has better compensation results. In addition, the research result is valuable for promoting wafer inspection accuracy and will greatly benefit the semiconductor industry.

[Development of an evaluation instrument for service quality in nursing homes].

PubMed

Lee, Jia; Ji, Eun Sun

2011-08-01

The purposes of this study were to identify the factors influencing service quality in nursing homes, and to develop an evaluation instrument for service quality. A three-phase process was employed for the study. 1) The important factors to evaluate the service quality in nursing homes were identified through a literature review, panel discussion and focus group interview, 2) the evaluation instrument was developed, and 3) validity and reliability of the study instrument were tested by factor analysis, Pearson correlation coefficient, Cronbach's α and Cohen's Kappa. Factor analysis showed that the factors influencing service quality in nursing homes were healthcare, diet/assistance, therapy, environment and staff. To improve objectivity of the instrument, quantitative as well as qualitative evaluation approaches were adopted. The study instrument was developed with 30 items and showed acceptable construct validity. The criterion-related validity was a Pearson correlation coefficient of .85 in 151 care facilities. The internal consistency was Cronbach's α=.95. The instrument has acceptable validity and a high degree of reliability. Staff in nursing homes can continuously improve and manage their services using the results of the evaluation instrument.

Behavioral Pediatrics Feeding Assessment Scale in Young Children With Autism Spectrum Disorder: Psychometrics and Associations With Child and Parent Variables.

PubMed

Allen, Stephanie L; Smith, Isabel M; Duku, Eric; Vaillancourt, Tracy; Szatmari, Peter; Bryson, Susan; Fombonne, Eric; Volden, Joanne; Waddell, Charlotte; Zwaigenbaum, Lonnie; Roberts, Wendy; Mirenda, Pat; Bennett, Teresa; Elsabbagh, Mayada; Georgiades, Stelios

2015-07-01

The factor structure and validity of the Behavioral Pediatrics Feeding Assessment Scale (BPFAS; Crist & Napier-Phillips, 2001) were examined in preschoolers with autism spectrum disorder (ASD). Confirmatory factor analysis was used to examine the original BPFAS five-factor model, the fit of each latent variable, and a rival one-factor model. None of the models was adequate, thus a categorical exploratory factor analysis (CEFA) was conducted. Correlations were used to examine relations between the BPFAS and concurrent variables of interest. The CEFA identified an acceptable three-factor model. Correlational analyses indicated that feeding problems were positively related to parent-reported autism symptoms, behavior problems, sleep problems, and parenting stress, but largely unrelated to performance-based indices of autism symptom severity, language, and cognitive abilities, as well as child age. These results provide evidence supporting the use of the identified BPFAS three-factor model for samples of young children with ASD. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Topologic analysis and comparison of brain activation in children with epilepsy versus controls: an fMRI study

NASA Astrophysics Data System (ADS)

Oweis, Khalid J.; Berl, Madison M.; Gaillard, William D.; Duke, Elizabeth S.; Blackstone, Kaitlin; Loew, Murray H.; Zara, Jason M.

2010-03-01

This paper describes the development of novel computer-aided analysis algorithms to identify the language activation patterns at a certain Region of Interest (ROI) in Functional Magnetic Resonance Imaging (fMRI). Previous analysis techniques have been used to compare typical and pathologic activation patterns in fMRI images resulting from identical tasks but none of them analyzed activation topographically in a quantitative manner. This paper presents new analysis techniques and algorithms capable of identifying a pattern of language activation associated with localization related epilepsy. fMRI images of 64 healthy individuals and 31 patients with localization related epilepsy have been studied and analyzed on an ROI basis. All subjects are right handed with normal MRI scans and have been classified into three age groups (4-6, 7-9, 10-12 years). Our initial efforts have focused on investigating activation in the Left Inferior Frontal Gyrus (LIFG). A number of volumetric features have been extracted from the data. The LIFG has been cut into slices and the activation has been investigated topographically on a slice by slice basis. Overall, a total of 809 features have been extracted, and correlation analysis was applied to eliminate highly correlated features. Principal Component analysis was then applied to account only for major components in the data and One-Way Analysis of Variance (ANOVA) has been applied to test for significantly different features between normal and patient groups. Twenty Nine features have were found to be significantly different (p<0.05) between patient and control groups

Importance and use of correlational research.

PubMed

Curtis, Elizabeth A; Comiskey, Catherine; Dempsey, Orla

2016-07-01

The importance of correlational research has been reported in the literature yet few research texts discuss design in any detail. To discuss important issues and considerations in correlational research, and suggest ways to avert potential problems during the preparation and application of the design. This article targets the gap identified in the literature regarding correlational research design. Specifically, it discusses the importance and purpose of correlational research, its application, analysis and interpretation with contextualisations to nursing and health research. Findings from correlational research can be used to determine prevalence and relationships among variables, and to forecast events from current data and knowledge. In spite of its many uses, prudence is required when using the methodology and analysing data. To assist researchers in reducing mistakes, important issues are singled out for discussion and several options put forward for analysing data. Correlational research is widely used and this paper should be particularly useful for novice nurse researchers. Furthermore, findings generated from correlational research can be used, for example, to inform decision-making, and to improve or initiate health-related activities or change.

Detection of indoor biological hazards using the man-portable laser induced breakdown spectrometer

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

Munson, Chase A.; Gottfried, Jennifer L.; Snyder, Emily Gibb

2008-11-01

The performance of a man-portable laser induced breakdown spectrometer was evaluated for the detection of biological powders on indoor office surfaces and wipe materials. Identification of pure unknown powders was performed by comparing against a library of spectra containing biological agent surrogates and confusant materials, such as dusts, diesel soot, natural and artificial sweeteners, and drink powders, using linear correlation analysis. Simple models constructed using a second technique, partial least squares discriminant analysis, successfully identified Bacillus subtilis (BG) spores on wipe materials and office surfaces. Furthermore, these models were able to identify BG on materials not used in the trainingmore » of the model.« less