Selection Indices and Multivariate Analysis Show Similar Results in the Evaluation of Growth and Carcass Traits in Beef Cattle

PubMed Central

Brito Lopes, Fernando; da Silva, Marcelo Corrêa; Magnabosco, Cláudio Ulhôa; Goncalves Narciso, Marcelo; Sainz, Roberto Daniel

2016-01-01

This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection. PMID:26789008

Selection Indices and Multivariate Analysis Show Similar Results in the Evaluation of Growth and Carcass Traits in Beef Cattle.

PubMed

Brito Lopes, Fernando; da Silva, Marcelo Corrêa; Magnabosco, Cláudio Ulhôa; Goncalves Narciso, Marcelo; Sainz, Roberto Daniel

2016-01-01

This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection.

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from satellites, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate time series method, the singular spectrum analysis (SSA), has been a fruitful extension of the PCA technique. The common drawback of these classical methods is that only linear structures can be correctly extracted from the data. Since the late 1980s, neural network methods have become popular for performing nonlinear regression and classification. More recently, neural network methods have been extended to perform nonlinear PCA (NLPCA), nonlinear CCA (NLCCA), and nonlinear SSA (NLSSA). This paper presents a unified view of the NLPCA, NLCCA, and NLSSA techniques and their applications to various data sets of the atmosphere and the ocean (especially for the El Niño-Southern Oscillation and the stratospheric quasi-biennial oscillation). These data sets reveal that the linear methods are often too simplistic to describe real-world systems, with a tendency to scatter a single oscillatory phenomenon into numerous unphysical modes or higher harmonics, which can be largely alleviated in the new nonlinear paradigm.

Community analysis of pitcher plant bogs of the Little River Canyon National Preserve, Alabama

Treesearch

Robert Carter; Terry Boyer; Heather McCoy; Andrew J. Londo

2006-01-01

Pitcher plant bogs of the Little River Canyon National Preserve in northern Alabama contain the federally endangered green pitcher plant [Sarracenia oreophila (Kearney) Wherry]. Multivariate analysis of the bog vegetation and environmental variables revealed three communities with unique species compositions and soil characteristics. The significant...

MGAS: a powerful tool for multivariate gene-based genome-wide association analysis.

PubMed

Van der Sluis, Sophie; Dolan, Conor V; Li, Jiang; Song, Youqiang; Sham, Pak; Posthuma, Danielle; Li, Miao-Xin

2015-04-01

Standard genome-wide association studies, testing the association between one phenotype and a large number of single nucleotide polymorphisms (SNPs), are limited in two ways: (i) traits are often multivariate, and analysis of composite scores entails loss in statistical power and (ii) gene-based analyses may be preferred, e.g. to decrease the multiple testing problem. Here we present a new method, multivariate gene-based association test by extended Simes procedure (MGAS), that allows gene-based testing of multivariate phenotypes in unrelated individuals. Through extensive simulation, we show that under most trait-generating genotype-phenotype models MGAS has superior statistical power to detect associated genes compared with gene-based analyses of univariate phenotypic composite scores (i.e. GATES, multiple regression), and multivariate analysis of variance (MANOVA). Re-analysis of metabolic data revealed 32 False Discovery Rate controlled genome-wide significant genes, and 12 regions harboring multiple genes; of these 44 regions, 30 were not reported in the original analysis. MGAS allows researchers to conduct their multivariate gene-based analyses efficiently, and without the loss of power that is often associated with an incorrectly specified genotype-phenotype models. MGAS is freely available in KGG v3.0 (http://statgenpro.psychiatry.hku.hk/limx/kgg/download.php). Access to the metabolic dataset can be requested at dbGaP (https://dbgap.ncbi.nlm.nih.gov/). The R-simulation code is available from http://ctglab.nl/people/sophie_van_der_sluis. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Is a multivariate consensus representation of genetic relationships among populations always meaningful?

PubMed Central

Moazami-Goudarzi, K; Laloë, D

2002-01-01

To determine the relationships among closely related populations or species, two methods are commonly used in the literature: phylogenetic reconstruction or multivariate analysis. The aim of this article is to assess the reliability of multivariate analysis. We describe a method that is based on principal component analysis and Mantel correlations, using a two-step process: The first step consists of a single-marker analysis and the second step tests if each marker reveals the same typology concerning population differentiation. We conclude that if single markers are not congruent, the compromise structure is not meaningful. Our model is not based on any particular mutation process and it can be applied to most of the commonly used genetic markers. This method is also useful to determine the contribution of each marker to the typology of populations. We test whether our method is efficient with two real data sets based on microsatellite markers. Our analysis suggests that for closely related populations, it is not always possible to accept the hypothesis that an increase in the number of markers will increase the reliability of the typology analysis. PMID:12242255

Immediate versus delayed intramedullary nailing for open fractures of the tibial shaft: a multivariate analysis of factors affecting deep infection and fracture healing.

PubMed

Yokoyama, Kazuhiko; Itoman, Moritoshi; Uchino, Masataka; Fukushima, Kensuke; Nitta, Hiroshi; Kojima, Yoshiaki

2008-10-01

The purpose of this study was to evaluate contributing factors affecting deep infection and fracture healing of open tibia fractures treated with locked intramedullary nailing (IMN) by multivariate analysis. We examined 99 open tibial fractures (98 patients) treated with immediate or delayed locked IMN in static fashion from 1991 to 2002. Multivariate analyses following univariate analyses were derived to determine predictors of deep infection, nonunion, and healing time to union. The following predictive variables of deep infection were selected for analysis: age, sex, Gustilo type, fracture grade by AO type, fracture location, timing or method of IMN, reamed or unreamed nailing, debridement time (< or =6 h or >6 h), method of soft-tissue management, skin closure time (< or =1 week or >1 week), existence of polytrauma (ISS< 18 or ISS> or =18), existence of floating knee injury, and existence of superficial/pin site infection. The predictive variables of nonunion selected for analysis was the same as those for deep infection, with the addition of deep infection for exchange of pin site infection. The predictive variables of union time selected for analysis was the same as those for nonunion, excluding of location, debridement time, and existence of floating knee and superficial infection. Six (6.1%; type II Gustilo n=1, type IIIB Gustilo n=5) of the 99 open tibial fractures developed deep infections. Multivariate analysis revealed that timing or method of IMN, debridement time, method of soft-tissue management, and existence of superficial or pin site infection significantly correlated with the occurrence of deep infection (P< 0.0001). In the immediate nailing group alone, the deep infection rate in type IIIB + IIIC was significantly higher than those in type I + II and IIIA (P = 0.016). Nonunion occurred in 17 fractures (20.3%, 17/84). Multivariate analysis revealed that Gustilo type, skin closure time, and existence of deep infection significantly correlated with occurrence of nonunion (P < 0.05). Gustilo type and existence of deep infection were significantly correlated with healing time to union on multivariate analysis (r(2) = 0.263, P = 0.0001). Multivariate analyses for open tibial fractures treated with IMN showed that IMN after EF (especially in existence of pin site infection) was at high risk of deep infection, and that debridement within 6 h and appropriate soft-tissue managements were also important factor in preventing deep infections. These analyses postulated that both the Gustilo type and the existence of deep infection is related with fracture healing in open fractures treated with IMN. In addition, immediate IMN for type IIIB and IIIC is potentially risky, and canal reaming did not increase the risk of complication for open tibial fractures treated with IMN.

A multivariate time series approach to modeling and forecasting demand in the emergency department.

PubMed

Jones, Spencer S; Evans, R Scott; Allen, Todd L; Thomas, Alun; Haug, Peter J; Welch, Shari J; Snow, Gregory L

2009-02-01

The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

Sleep and Nutritional Deprivation and Performance of House Officers.

ERIC Educational Resources Information Center

Hawkins, Michael R.; And Others

1985-01-01

A study to compare cognitive functioning in acutely and chronically sleep-deprived house officers is described. A multivariate analysis of variance revealed significant deficits in primary mental tasks involving basic rote memory, language, and numeric skills. (Author/MLW)

Multivariate analysis of heavy metal contamination using river sediment cores of Nankan River, northern Taiwan

NASA Astrophysics Data System (ADS)

Lee, An-Sheng; Lu, Wei-Li; Huang, Jyh-Jaan; Chang, Queenie; Wei, Kuo-Yen; Lin, Chin-Jung; Liou, Sofia Ya Hsuan

2016-04-01

Through the geology and climate characteristic in Taiwan, generally rivers carry a lot of suspended particles. After these particles settled, they become sediments which are good sorbent for heavy metals in river system. Consequently, sediments can be found recording contamination footprint at low flow energy region, such as estuary. Seven sediment cores were collected along Nankan River, northern Taiwan, which is seriously contaminated by factory, household and agriculture input. Physico-chemical properties of these cores were derived from Itrax-XRF Core Scanner and grain size analysis. In order to interpret these complex data matrices, the multivariate statistical techniques (cluster analysis, factor analysis and discriminant analysis) were introduced to this study. Through the statistical determination, the result indicates four types of sediment. One of them represents contamination event which shows high concentration of Cu, Zn, Pb, Ni and Fe, and low concentration of Si and Zr. Furthermore, three possible contamination sources of this type of sediment were revealed by Factor Analysis. The combination of sediment analysis and multivariate statistical techniques used provides new insights into the contamination depositional history of Nankan River and could be similarly applied to other river systems to determine the scale of anthropogenic contamination.

New strategy to identify radicals in a time evolving EPR data set by multivariate curve resolution-alternating least squares.

PubMed

Fadel, Maya Abou; de Juan, Anna; Vezin, Hervé; Duponchel, Ludovic

2016-12-01

Electron paramagnetic resonance (EPR) spectroscopy is a powerful technique that is able to characterize radicals formed in kinetic reactions. However, spectral characterization of individual chemical species is often limited or even unmanageable due to the severe kinetic and spectral overlap among species in kinetic processes. Therefore, we applied, for the first time, multivariate curve resolution-alternating least squares (MCR-ALS) method to EPR time evolving data sets to model and characterize the different constituents in a kinetic reaction. Here we demonstrate the advantage of multivariate analysis in the investigation of radicals formed along the kinetic process of hydroxycoumarin in alkaline medium. Multiset analysis of several EPR-monitored kinetic experiments performed in different conditions revealed the individual paramagnetic centres as well as their kinetic profiles. The results obtained by MCR-ALS method demonstrate its prominent potential in analysis of EPR time evolved spectra. Copyright © 2016 Elsevier B.V. All rights reserved.

The Fourier decomposition method for nonlinear and non-stationary time series analysis.

PubMed

Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-03-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.

The Fourier decomposition method for nonlinear and non-stationary time series analysis

PubMed Central

Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-01-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of ‘Fourier intrinsic band functions’ (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time–frequency–energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms. PMID:28413352

Risk factors for superficial surgical site infection after elective rectal cancer resection: a multivariate analysis of 8880 patients from the American College of Surgeons National Surgical Quality Improvement Program database.

PubMed

Sutton, Elie; Miyagaki, Hiromichi; Bellini, Geoffrey; Shantha Kumara, H M C; Yan, Xiaohong; Howe, Brett; Feigel, Amanda; Whelan, Richard L

2017-01-01

Superficial surgical site infection (sSSI) is one of the most common complications after colorectal resection. The goal of this study was to determine the comorbidities and operative characteristics that place patients at risk for sSSI in patients who underwent rectal cancer resection. The American College of Surgeons National Surgical Quality Improvement Program database was queried (via diagnosis and Current Procedural Terminology codes) for patients with rectal cancer who underwent elective resection between 2005 and 2012. Patients for whom data concerning 27 demographic factors, comorbidities, and operative characteristics were available were eligible. A univariate and multivariate analysis was performed to identify possible risk factors for sSSI. A total of 8880 patients met the entry criteria and were included. sSSIs were diagnosed in 861 (9.7%) patients. Univariate analysis found 14 patients statistically significant risk factors for sSSI. Multivariate analysis revealed the following risk factors: male gender, body mass index (BMI) >30, current smoking, history of chronic obstructive pulmonary disease (COPD), American Society of Anesthesiologists III/IV, abdominoperineal resection (APR), stoma formation, open surgery (versus laparoscopic), and operative time >217 min. The greatest difference in sSSI rates was noted in patients with COPD (18.9 versus 9.5%). Of note, 54.2% of sSSIs was noted after hospital discharge. With regard to the timing of presentation, univariate analysis revealed a statistically significant delay in sSSI presentation in patients with the following factors and/or characteristics: BMI <30, previous radiation therapy (RT), APR, minimally invasive surgery, and stoma formation. Multivariate analysis suggested that only laparoscopic surgery (versus open) and preoperative RT were risk factors for delay. Rectal cancer resections are associated with a high incidence of sSSIs, over half of which are noted after discharge. Nine patient and operative characteristics, including smoking, BMI, COPD, APR, and open surgery were found to be significant risk factors for SSI on multivariate analysis. Furthermore, sSSI presentation in patients who had laparoscopic surgery and those who had preoperative RT is significantly delayed for unclear reasons. Copyright © 2016 Elsevier Inc. All rights reserved.

The Relationship of Self-Concept and Perceived Athletic Competence to Physical Activity Level and Gender among Turkish Early Adolescents.

ERIC Educational Resources Information Center

Kosar, F. Hulya Asci S. Nazan; Isler, Ayse Kin

2001-01-01

Examined self-concept and perceived athletic competence of Turkish early adolescents in relation to physical activity level and gender. Multivariate analysis of variance revealed significant main effects for gender and physical activity level but no significant gender by physical activity interaction. Univariate analysis demonstrated significant…

Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model.

PubMed

Snell, Kym I E; Hua, Harry; Debray, Thomas P A; Ensor, Joie; Look, Maxime P; Moons, Karel G M; Riley, Richard D

2016-01-01

Our aim was to improve meta-analysis methods for summarizing a prediction model's performance when individual participant data are available from multiple studies for external validation. We suggest multivariate meta-analysis for jointly synthesizing calibration and discrimination performance, while accounting for their correlation. The approach estimates a prediction model's average performance, the heterogeneity in performance across populations, and the probability of "good" performance in new populations. This allows different implementation strategies (e.g., recalibration) to be compared. Application is made to a diagnostic model for deep vein thrombosis (DVT) and a prognostic model for breast cancer mortality. In both examples, multivariate meta-analysis reveals that calibration performance is excellent on average but highly heterogeneous across populations unless the model's intercept (baseline hazard) is recalibrated. For the cancer model, the probability of "good" performance (defined by C statistic ≥0.7 and calibration slope between 0.9 and 1.1) in a new population was 0.67 with recalibration but 0.22 without recalibration. For the DVT model, even with recalibration, there was only a 0.03 probability of "good" performance. Multivariate meta-analysis can be used to externally validate a prediction model's calibration and discrimination performance across multiple populations and to evaluate different implementation strategies. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

An analysis of prognostic factors after percutaneous endoscopic gastrostomy placement in Japanese patients with amyotrophic lateral sclerosis.

PubMed

Nagashima, Kazuaki; Furuta, Natsumi; Makioka, Kouki; Fujita, Yukio; Ikeda, Masaki; Ikeda, Yoshio

2017-05-15

A percutaneous endoscopic gastrostomy (PEG) is an useful intervention for feeding of amyotrophic lateral sclerosis (ALS) patients who have lost oral intake function. The aim of this study was to investigate the risk factors for early death and the survival after PEG placement. A total of 102 ALS patients who underwent PEG placement were enrolled in this study. Patients were divided into two groups; the poor prognosis group included patients who died or needed permanent mechanical ventilation within 30days after PEG placement, and the good prognosis group included patients who did not meet the criteria of the poor prognosis group. Clinical characteristics, respiratory function, and nutritional parameters were compared for the two groups to assess the correlations between clinical and laboratory variables and early death after PEG placement. Multivariate analysis between two groups revealed that higher arterial carbon dioxide pressure (PaCO 2 ) and aphagia before PEG placement were significantly associated with the poor prognosis group. Multivariate analysis for survival also revealed that higher PaCO 2 and shorter duration from onset to PEG placement were significantly associated with shorter survival after PEG placement. In conclusion, respiratory and nutritional parameters are revealed to be important prognostic factors for ALS patients who undergo PEG placement. Copyright © 2017 Elsevier B.V. All rights reserved.

Multivariate and geo-spatial approach for seawater quality of Chidiyatappu Bay, south Andaman Islands, India.

PubMed

Jha, Dilip Kumar; Vinithkumar, Nambali Valsalan; Sahu, Biraja Kumar; Dheenan, Palaiya Sukumaran; Das, Apurba Kumar; Begum, Mehmuna; Devi, Marimuthu Prashanthi; Kirubagaran, Ramalingam

2015-07-15

Chidiyatappu Bay is one of the least disturbed marine environments of Andaman & Nicobar Islands, the union territory of India. Oceanic flushing from southeast and northwest direction is prevalent in this bay. Further, anthropogenic activity is minimal in the adjoining environment. Considering the pristine nature of this bay, seawater samples collected from 12 sampling stations covering three seasons were analyzed. Principal Component Analysis (PCA) revealed 69.9% of total variance and exhibited strong factor loading for nitrite, chlorophyll a and phaeophytin. In addition, analysis of variance (ANOVA-one way), regression analysis, box-whisker plots and Geographical Information System based hot spot analysis further simplified and supported multivariate results. The results obtained are important to establish reference conditions for comparative study with other similar ecosystems in the region. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interactions between macromolecule-bound antioxidants and Trolox during liposome autoxidation: A multivariate approach.

PubMed

Çelik, Ecem Evrim; Rubio, Jose Manuel Amigo; Andersen, Mogens L; Gökmen, Vural

2017-12-15

The interactions between free and macromolecule-bound antioxidants were investigated in order to evaluate their combined effects on the antioxidant environment. Dietary fiber (DF), protein and lipid-bound antioxidants, obtained from whole wheat, soybean and olive oil products, respectively and Trolox were used for this purpose. Experimental studies were carried out in autoxidizing liposome medium by monitoring the development of fluorescent products formed by lipid oxidation. Chemometric methods were used both at experimental design and multivariate data analysis stages. Comparison of the simple addition effects of Trolox and bound antioxidants with measured values on lipid oxidation revealed synergetic interactions for DF and refined olive oil-bound antioxidants, and antagonistic interactions for protein and extra virgin olive oil-bound antioxidants with Trolox. A generalized version of logistic function was successfully used for modelling the oxidation curve of liposomes. Principal component analysis revealed two separate phases of liposome autoxidation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Race and Older Mothers’ Differentiation: A Sequential Quantitative and Qualitative Analysis

PubMed Central

Sechrist, Jori; Suitor, J. Jill; Riffin, Catherine; Taylor-Watson, Kadari; Pillemer, Karl

2011-01-01

The goal of this paper is to demonstrate a process by which qualitative and quantitative approaches are combined to reveal patterns in the data that are unlikely to be detected and confirmed by either method alone. Specifically, we take a sequential approach to combining qualitative and quantitative data to explore race differences in how mothers differentiate among their adult children. We began with a standard multivariate analysis examining race differences in mothers’ differentiation among their adult children regarding emotional closeness and confiding. Finding no race differences in this analysis, we conducted an in-depth comparison of the Black and White mothers’ narratives to determine whether there were underlying patterns that we had been unable to detect in our first analysis. Using this method, we found that Black mothers were substantially more likely than White mothers to emphasize interpersonal relationships within the family when describing differences among their children. In our final step, we developed a measure of familism based on the qualitative data and conducted a multivariate analysis to confirm the patterns revealed by the in-depth comparison of the mother’s narratives. We conclude that using such a sequential mixed methods approach to data analysis has the potential to shed new light on complex family relations. PMID:21967639

The Multivariate Nature of Professional Job Satisfaction.

ERIC Educational Resources Information Center

Wood, Donald A.; LeBold, William K.

Discussed are two theories of professional job satisfaction--(1) unidimensional and (2) multidimensional with special reference to Herzberg's two factor theory. A national sample of over 3,000 engineering graduates responded to a questionnaire and satisfaction index. Analysis of results revealed that job satisfaction is multidimensional. Job…

Reading Ability as a Predictor of Academic Procrastination among African American Graduate Students

ERIC Educational Resources Information Center

Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.; Jiao, Qun G.

2008-01-01

The present study examined the relationship between reading ability (i.e., reading comprehension and reading vocabulary) and academic procrastination among 120 African American graduate students. A canonical correlation analysis revealed statistically significant and practically significant multivariate relationships between these two reading…

Large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

2016-03-01

We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

Combining ANOVA-PCA with POCHEMON to analyse micro-organism development in a polymicrobial environment.

PubMed

Geurts, Brigitte P; Neerincx, Anne H; Bertrand, Samuel; Leemans, Manja A A P; Postma, Geert J; Wolfender, Jean-Luc; Cristescu, Simona M; Buydens, Lutgarde M C; Jansen, Jeroen J

2017-04-22

Revealing the biochemistry associated to micro-organismal interspecies interactions is highly relevant for many purposes. Each pathogen has a characteristic metabolic fingerprint that allows identification based on their unique multivariate biochemistry. When pathogen species come into mutual contact, their co-culture will display a chemistry that may be attributed both to mixing of the characteristic chemistries of the mono-cultures and to competition between the pathogens. Therefore, investigating pathogen development in a polymicrobial environment requires dedicated chemometric methods to untangle and focus upon these sources of variation. The multivariate data analysis method Projected Orthogonalised Chemical Encounter Monitoring (POCHEMON) is dedicated to highlight metabolites characteristic for the interaction of two micro-organisms in co-culture. However, this approach is currently limited to a single time-point, while development of polymicrobial interactions may be highly dynamic. A well-known multivariate implementation of Analysis of Variance (ANOVA) uses Principal Component Analysis (ANOVA-PCA). This allows the overall dynamics to be separated from the pathogen-specific chemistry to analyse the contributions of both aspects separately. For this reason, we propose to integrate ANOVA-PCA with the POCHEMON approach to disentangle the pathogen dynamics and the specific biochemistry in interspecies interactions. Two complementary case studies show great potential for both liquid and gas chromatography - mass spectrometry to reveal novel information on chemistry specific to interspecies interaction during pathogen development. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Principal component analysis-based pattern analysis of dose-volume histograms and influence on rectal toxicity.

PubMed

Söhn, Matthias; Alber, Markus; Yan, Di

2007-09-01

The variability of dose-volume histogram (DVH) shapes in a patient population can be quantified using principal component analysis (PCA). We applied this to rectal DVHs of prostate cancer patients and investigated the correlation of the PCA parameters with late bleeding. PCA was applied to the rectal wall DVHs of 262 patients, who had been treated with a four-field box, conformal adaptive radiotherapy technique. The correlated changes in the DVH pattern were revealed as "eigenmodes," which were ordered by their importance to represent data set variability. Each DVH is uniquely characterized by its principal components (PCs). The correlation of the first three PCs and chronic rectal bleeding of Grade 2 or greater was investigated with uni- and multivariate logistic regression analyses. Rectal wall DVHs in four-field conformal RT can primarily be represented by the first two or three PCs, which describe approximately 94% or 96% of the DVH shape variability, respectively. The first eigenmode models the total irradiated rectal volume; thus, PC1 correlates to the mean dose. Mode 2 describes the interpatient differences of the relative rectal volume in the two- or four-field overlap region. Mode 3 reveals correlations of volumes with intermediate doses ( approximately 40-45 Gy) and volumes with doses >70 Gy; thus, PC3 is associated with the maximal dose. According to univariate logistic regression analysis, only PC2 correlated significantly with toxicity. However, multivariate logistic regression analysis with the first two or three PCs revealed an increased probability of bleeding for DVHs with more than one large PC. PCA can reveal the correlation structure of DVHs for a patient population as imposed by the treatment technique and provide information about its relationship to toxicity. It proves useful for augmenting normal tissue complication probability modeling approaches.

Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects.

PubMed

Mostafa, Hamza; Amin, Arwa M; Teh, Chin-Hoe; Murugaiyah, Vikneswaran; Arif, Nor Hayati; Ibrahim, Baharudin

2016-12-01

Alcohol-dependence (AD) is a ravaging public health and social problem. AD diagnosis depends on questionnaires and some biomarkers, which lack specificity and sensitivity, however, often leading to less precise diagnosis, as well as delaying treatment. This represents a great burden, not only on AD individuals but also on their families. Metabolomics using nuclear magnetic resonance spectroscopy (NMR) can provide novel techniques for the identification of novel biomarkers of AD. These putative biomarkers can facilitate early diagnosis of AD. To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics. Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC). The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0). This study revealed that metabolomics analysis of urine using NMR identified AD novel biomarkers which can discriminate AD from social drinkers and controls with high accuracy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Investigation of cell wall composition related to stem lodging resistance in wheat (Triticum aestivum L.) by FTIR spectroscopy.

PubMed

Wang, Jian; Zhu, Jinmao; Huang, RuZhu; Yang, YuSheng

2012-07-01

We explored the rapid qualitative analysis of wheat cultivars with good lodging resistances by Fourier transform infrared resonance (FTIR) spectroscopy and multivariate statistical analysis. FTIR imaging showing that wheat stem cell walls were mainly composed of cellulose, pectin, protein, and lignin. Principal components analysis (PCA) was used to eliminate multicollinearity among multiple peak absorptions. PCA revealed the developmental internodes of wheat stems could be distributed from low to high along the load of the second principal component, which was consistent with the corresponding bands of cellulose in the FTIR spectra of the cell walls. Furthermore, four distinct stem populations could also be identified by spectral features related to their corresponding mechanical properties via PCA and cluster analysis. Histochemical staining of four types of wheat stems with various abilities to resist lodging revealed that cellulose contributed more than lignin to the ability to resist lodging. These results strongly suggested that the main cell wall component responsible for these differences was cellulose. Therefore, the combination of multivariate analysis and FTIR could rapidly screen wheat cultivars with good lodging resistance. Furthermore, the application of these methods to a much wider range of cultivars of unknown mechanical properties promises to be of interest.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8.

PubMed

Ferreira, Fábio S; Pereira, João M S; Duarte, João V; Castelo-Branco, Miguel

2017-01-01

Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8

PubMed Central

Ferreira, Fábio S.; Pereira, João M.S.; Duarte, João V.; Castelo-Branco, Miguel

2017-01-01

Background: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Objective: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). Method: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately – using standard univariate VBM - and simultaneously, with multivariate analyses. Results: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. Conclusion: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities. PMID:28761571

Quantifying team cooperation through intrinsic multi-scale measures: respiratory and cardiac synchronization in choir singers and surgical teams.

PubMed

Hemakom, Apit; Powezka, Katarzyna; Goverdovsky, Valentin; Jaffer, Usman; Mandic, Danilo P

2017-12-01

A highly localized data-association measure, termed intrinsic synchrosqueezing transform (ISC), is proposed for the analysis of coupled nonlinear and non-stationary multivariate signals. This is achieved based on a combination of noise-assisted multivariate empirical mode decomposition and short-time Fourier transform-based univariate and multivariate synchrosqueezing transforms. It is shown that the ISC outperforms six other combinations of algorithms in estimating degrees of synchrony in synthetic linear and nonlinear bivariate signals. Its advantage is further illustrated in the precise identification of the synchronized respiratory and heart rate variability frequencies among a subset of bass singers of a professional choir, where it distinctly exhibits better performance than the continuous wavelet transform-based ISC. We also introduce an extension to the intrinsic phase synchrony (IPS) measure, referred to as nested intrinsic phase synchrony (N-IPS), for the empirical quantification of physically meaningful and straightforward-to-interpret trends in phase synchrony. The N-IPS is employed to reveal physically meaningful variations in the levels of cooperation in choir singing and performing a surgical procedure. Both the proposed techniques successfully reveal degrees of synchronization of the physiological signals in two different aspects: (i) precise localization of synchrony in time and frequency (ISC), and (ii) large-scale analysis for the empirical quantification of physically meaningful trends in synchrony (N-IPS).

Complex codon usage pattern and compositional features of retroviruses.

PubMed

RoyChoudhury, Sourav; Mukherjee, Debaprasad

2013-01-01

Retroviruses infect a wide range of organisms including humans. Among them, HIV-1, which causes AIDS, has now become a major threat for world health. Some of these viruses are also potential gene transfer vectors. In this study, the patterns of synonymous codon usage in retroviruses have been studied through multivariate statistical methods on ORFs sequences from the available 56 retroviruses. The principal determinant for evolution of the codon usage pattern in retroviruses seemed to be the compositional constraints, while selection for translation of the viral genes plays a secondary role. This was further supported by multivariate analysis on relative synonymous codon usage. Thus, it seems that mutational bias might have dominated role over translational selection in shaping the codon usage of retroviruses. Codon adaptation index was used to identify translationally optimal codons among genes from retroviruses. The comparative analysis of the preferred and optimal codons among different retroviral groups revealed that four codons GAA, AAA, AGA, and GGA were significantly more frequent in most of the retroviral genes inspite of some differences. Cluster analysis also revealed that phylogenetically related groups of retroviruses have probably evolved their codon usage in a concerted manner under the influence of their nucleotide composition.

Information spreading by a combination of MEG source estimation and multivariate pattern classification.

PubMed

Sato, Masashi; Yamashita, Okito; Sato, Masa-Aki; Miyawaki, Yoichi

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of "information spreading" may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined.

Information spreading by a combination of MEG source estimation and multivariate pattern classification

PubMed Central

Sato, Masashi; Yamashita, Okito; Sato, Masa-aki

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of “information spreading” may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined. PMID:29912968

A Quality by Design approach to investigate tablet dissolution shift upon accelerated stability by multivariate methods.

PubMed

Huang, Jun; Goolcharran, Chimanlall; Ghosh, Krishnendu

2011-05-01

This paper presents the use of experimental design, optimization and multivariate techniques to investigate root-cause of tablet dissolution shift (slow-down) upon stability and develop control strategies for a drug product during formulation and process development. The effectiveness and usefulness of these methodologies were demonstrated through two application examples. In both applications, dissolution slow-down was observed during a 4-week accelerated stability test under 51°C/75%RH storage condition. In Application I, an experimental design was carried out to evaluate the interactions and effects of the design factors on critical quality attribute (CQA) of dissolution upon stability. The design space was studied by design of experiment (DOE) and multivariate analysis to ensure desired dissolution profile and minimal dissolution shift upon stability. Multivariate techniques, such as multi-way principal component analysis (MPCA) of the entire dissolution profiles upon stability, were performed to reveal batch relationships and to evaluate the impact of design factors on dissolution. In Application II, an experiment was conducted to study the impact of varying tablet breaking force on dissolution upon stability utilizing MPCA. It was demonstrated that the use of multivariate methods, defined as Quality by Design (QbD) principles and tools in ICH-Q8 guidance, provides an effective means to achieve a greater understanding of tablet dissolution upon stability. Copyright © 2010 Elsevier B.V. All rights reserved.

Investigating College and Graduate Students' Multivariable Reasoning in Computational Modeling

ERIC Educational Resources Information Center

Wu, Hsin-Kai; Wu, Pai-Hsing; Zhang, Wen-Xin; Hsu, Ying-Shao

2013-01-01

Drawing upon the literature in computational modeling, multivariable reasoning, and causal attribution, this study aims at characterizing multivariable reasoning practices in computational modeling and revealing the nature of understanding about multivariable causality. We recruited two freshmen, two sophomores, two juniors, two seniors, four…

A Survey Study of Chinese In-Service Teachers' Self-Efficacy about Inclusive Education

ERIC Educational Resources Information Center

Wang, Mian; Zan, Fei; Liu, Jiaqiu; Liu, Chunling; Sharma, Umesh

2012-01-01

A survey study was conducted to a total of 323 in-service teachers (110 special education teachers and 213 general education teachers) in Shanghai regarding their self-efficacy and concerns about inclusive education. Multivariate analysis results reveal that special teachers have significantly higher self-efficacy about inclusive education than…

Multivariate analysis of the cotton seed ionome reveals integrated genetic signatures of abiotic stress-response

USDA-ARS?s Scientific Manuscript database

To mitigate the effects of heat and drought stress, an understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in...

An Investigation of Age and Gender Differences in Physical Self-Concept among Turkish Late Adolescents.

ERIC Educational Resources Information Center

Asci, F. Hulya

2002-01-01

Evaluates age and gender differences in physical self-concept of Turkish university students. The Physical Self-Perception Profile was administered to participants for assessing physical self-concept. Multivariate analysis of variance revealed a significant main effect for gender, but no significant main effect for year in school. Univariate…

Multivariate modelling of endophenotypes associated with the metabolic syndrome in Chinese twins.

PubMed

Pang, Z; Zhang, D; Li, S; Duan, H; Hjelmborg, J; Kruse, T A; Kyvik, K O; Christensen, K; Tan, Q

2010-12-01

The common genetic and environmental effects on endophenotypes related to the metabolic syndrome have been investigated using bivariate and multivariate twin models. This paper extends the pairwise analysis approach by introducing independent and common pathway models to Chinese twin data. The aim was to explore the common genetic architecture in the development of these phenotypes in the Chinese population. Three multivariate models including the full saturated Cholesky decomposition model, the common factor independent pathway model and the common factor common pathway model were fitted to 695 pairs of Chinese twins representing six phenotypes including BMI, total cholesterol, total triacylglycerol, fasting glucose, HDL and LDL. Performances of the nested models were compared with that of the full Cholesky model. Cross-phenotype correlation coefficients gave clear indication of common genetic or environmental backgrounds in the phenotypes. Decomposition of phenotypic correlation by the Cholesky model revealed that the observed phenotypic correlation among lipid phenotypes had genetic and unique environmental backgrounds. Both pathway models suggest a common genetic architecture for lipid phenotypes, which is distinct from that of the non-lipid phenotypes. The declining performance with model restriction indicates biological heterogeneity in development among some of these phenotypes. Our multivariate analyses revealed common genetic and environmental backgrounds for the studied lipid phenotypes in Chinese twins. Model performance showed that physiologically distinct endophenotypes may follow different genetic regulations.

Multivariate statistical analysis of stream-sediment geochemistry in the Grazer Paläozoikum, Austria

USGS Publications Warehouse

Weber, L.; Davis, J.C.

1990-01-01

The Austrian reconnaissance study of stream-sediment composition — more than 30000 clay-fraction samples collected over an area of 40000 km2 — is summarized in an atlas of regional maps that show the distributions of 35 elements. These maps, rich in information, reveal complicated patterns of element abundance that are difficult to compare on more than a small number of maps at one time. In such a study, multivariate procedures such as simultaneous R-Q mode components analysis may be helpful. They can compress a large number of variables into a much smaller number of independent linear combinations. These composite variables may be mapped and relationships sought between them and geological properties. As an example, R-Q mode components analysis is applied here to the Grazer Paläozoikum, a tectonic unit northeast of the city of Graz, which is composed of diverse lithologies and contains many mineral deposits.

Computer-based self-organized tectonic zoning: a tentative pattern recognition for Iran

NASA Astrophysics Data System (ADS)

Zamani, Ahmad; Hashemi, Naser

2004-08-01

Conventional methods of tectonic zoning are frequently characterized by two deficiencies. The first one is the large uncertainty involved in tectonic zoning based on non-quantitative and subjective analysis. Failure to interpret accurately a large amount of data "by eye" is the second. In order to alleviate each of these deficiencies, the multivariate statistical method of cluster analysis has been utilized to seek and separate zones with similar tectonic pattern and construct automated self-organized multivariate tectonic zoning maps. This analytical method of tectonic regionalization is particularly useful for showing trends in tectonic evolution of a region that could not be discovered by any other means. To illustrate, this method has been applied for producing a general-purpose numerical tectonic zoning map of Iran. While there are some similarities between the self-organized multivariate numerical maps and the conventional maps, the cluster solution maps reveal some remarkable features that cannot be observed on the current tectonic maps. The following specific examples need to be noted: (1) The much disputed extent and rigidity of the Lut Rigid Block, described as the microplate of east Iran, is clearly revealed on the self-organized numerical maps. (2) The cluster solution maps reveal a striking similarity between this microplate and the northern Central Iran—including the Great Kavir region. (3) Contrary to the conventional map, the cluster solution maps make a clear distinction between the East Iranian Ranges and the Makran Mountains. (4) Moreover, an interesting similarity between the Azarbaijan region in the northwest and the Makran Mountains in the southeast and between the Kopet Dagh Ranges in the northeast and the Zagros Folded Belt in the southwest of Iran are revealed in the clustering process. This new approach to tectonic zoning is a starting point and is expected to be improved and refined by collection of new data. The method is also a useful tool in studying neotectonics, seismotectonics, seismic zoning, and hazard estimation of the seismogenic regions.

Combined data preprocessing and multivariate statistical analysis characterizes fed-batch culture of mouse hybridoma cells for rational medium design.

PubMed

Selvarasu, Suresh; Kim, Do Yun; Karimi, Iftekhar A; Lee, Dong-Yup

2010-10-01

We present an integrated framework for characterizing fed-batch cultures of mouse hybridoma cells producing monoclonal antibody (mAb). This framework systematically combines data preprocessing, elemental balancing and statistical analysis technique. Initially, specific rates of cell growth, glucose/amino acid consumptions and mAb/metabolite productions were calculated via curve fitting using logistic equations, with subsequent elemental balancing of the preprocessed data indicating the presence of experimental measurement errors. Multivariate statistical analysis was then employed to understand physiological characteristics of the cellular system. The results from principal component analysis (PCA) revealed three major clusters of amino acids with similar trends in their consumption profiles: (i) arginine, threonine and serine, (ii) glycine, tyrosine, phenylalanine, methionine, histidine and asparagine, and (iii) lysine, valine and isoleucine. Further analysis using partial least square (PLS) regression identified key amino acids which were positively or negatively correlated with the cell growth, mAb production and the generation of lactate and ammonia. Based on these results, the optimal concentrations of key amino acids in the feed medium can be inferred, potentially leading to an increase in cell viability and productivity, as well as a decrease in toxic waste production. The study demonstrated how the current methodological framework using multivariate statistical analysis techniques can serve as a potential tool for deriving rational medium design strategies. Copyright © 2010 Elsevier B.V. All rights reserved.

Assessment of trace elements levels in patients with Type 2 diabetes using multivariate statistical analysis.

PubMed

Badran, M; Morsy, R; Soliman, H; Elnimr, T

2016-01-01

The trace elements metabolism has been reported to possess specific roles in the pathogenesis and progress of diabetes mellitus. Due to the continuous increase in the population of patients with Type 2 diabetes (T2D), this study aims to assess the levels and inter-relationships of fast blood glucose (FBG) and serum trace elements in Type 2 diabetic patients. This study was conducted on 40 Egyptian Type 2 diabetic patients and 36 healthy volunteers (Hospital of Tanta University, Tanta, Egypt). The blood serum was digested and then used to determine the levels of 24 trace elements using an inductive coupled plasma mass spectroscopy (ICP-MS). Multivariate statistical analysis depended on correlation coefficient, cluster analysis (CA) and principal component analysis (PCA), were used to analysis the data. The results exhibited significant changes in FBG and eight of trace elements, Zn, Cu, Se, Fe, Mn, Cr, Mg, and As, levels in the blood serum of Type 2 diabetic patients relative to those of healthy controls. The statistical analyses using multivariate statistical techniques were obvious in the reduction of the experimental variables, and grouping the trace elements in patients into three clusters. The application of PCA revealed a distinct difference in associations of trace elements and their clustering patterns in control and patients group in particular for Mg, Fe, Cu, and Zn that appeared to be the most crucial factors which related with Type 2 diabetes. Therefore, on the basis of this study, the contributors of trace elements content in Type 2 diabetic patients can be determine and specify with correlation relationship and multivariate statistical analysis, which confirm that the alteration of some essential trace metals may play a role in the development of diabetes mellitus. Copyright © 2015 Elsevier GmbH. All rights reserved.

The result of adjuvant chemotherapy for localized pT3 upper urinary tract carcinoma in a multi-institutional study.

PubMed

Kawashima, Atsunari; Nakai, Yasutomo; Nakayama, Masashi; Ujike, Takeshi; Tanigawa, Go; Ono, Yutaka; Kamoto, Akihito; Takada, Tsuyosi; Yamaguchi, Yuichiro; Takayama, Hitoshi; Nishimura, Kazuo; Nonomura, Norio; Tsujimura, Akira

2012-10-01

To determine through the analysis of our multi-institutional database whether postoperative adjuvant chemotherapy for upper urinary tract carcinoma with localized invasive upper urinary tract carcinoma (UUTC) is beneficial. A study population of 93 patients with pT3N0/xM0 UUTC was eligible for this study. Clinical features evaluated were sex, tumor location, adjuvant chemotherapy status, tumor pathology (histology, grade, infiltrating growth, lymphovascular invasion (LVI)), and cause of death. Cancer-specific survival (CSS) was estimated by Kaplan-Meier method. Prognostic factors related to CSS were analyzed by Cox proportional hazards regression model for multivariate analysis. In pT3 patients, overall 5-year CSS rate was 68.4% and median CSS time was 31 months (range 3-114 months). In the adjuvant chemotherapy group, 5-year CSS rate was 80.8%, whereas 5-year CSS rate was 64.4% in the non-adjuvant chemotherapy group. By multivariate analysis, adjuvant chemotherapy status was significantly associated with CSS (P = 0.008) were sex, tumor grade, tumor histology, and LVI presence. This study, although it was retrospective study, revealed that adjuvant chemotherapy after RNU may be beneficial in pT3N0/X patients by multivariate analysis. Prospective studies evaluating adjuvant therapy regimens for UTTC are required.

Evaluation of the Risk Factors for a Rotator Cuff Retear After Repair Surgery.

PubMed

Lee, Yeong Seok; Jeong, Jeung Yeol; Park, Chan-Deok; Kang, Seung Gyoon; Yoo, Jae Chul

2017-07-01

A retear is a significant clinical problem after rotator cuff repair. However, no study has evaluated the retear rate with regard to the extent of footprint coverage. To evaluate the preoperative and intraoperative factors for a retear after rotator cuff repair, and to confirm the relationship with the extent of footprint coverage. Cohort study; Level of evidence, 3. Data were retrospectively collected from 693 patients who underwent arthroscopic rotator cuff repair between January 2006 and December 2014. All repairs were classified into 4 types of completeness of repair according to the amount of footprint coverage at the end of surgery. All patients underwent magnetic resonance imaging (MRI) after a mean postoperative duration of 5.4 months. Preoperative demographic data, functional scores, range of motion, and global fatty degeneration on preoperative MRI and intraoperative variables including the tear size, completeness of rotator cuff repair, concomitant subscapularis repair, number of suture anchors used, repair technique (single-row or transosseous-equivalent double-row repair), and surgical duration were evaluated. Furthermore, the factors associated with failure using the single-row technique and transosseous-equivalent double-row technique were analyzed separately. The retear rate was 7.22%. Univariate analysis revealed that rotator cuff retears were affected by age; the presence of inflammatory arthritis; the completeness of rotator cuff repair; the initial tear size; the number of suture anchors; mean operative time; functional visual analog scale scores; Simple Shoulder Test findings; American Shoulder and Elbow Surgeons scores; and fatty degeneration of the supraspinatus, infraspinatus, and subscapularis. Multivariate logistic regression analysis revealed patient age, initial tear size, and fatty degeneration of the supraspinatus as independent risk factors for a rotator cuff retear. Multivariate logistic regression analysis of the single-row group revealed patient age and fatty degeneration of the supraspinatus as independent risk factors for a rotator cuff retear. Multivariate logistic regression analysis of the transosseous-equivalent double-row group revealed a frozen shoulder as an independent risk factor for a rotator cuff retear. Our results suggest that patient age, initial tear size, and fatty degeneration of the supraspinatus are independent risk factors for a rotator cuff retear, whereas the completeness of rotator cuff repair based on the extent of footprint coverage and repair technique are not.

Understanding and reaching family forest owners: lessons from social marketing research

Treesearch

Brett J. Butler; Mary Tyrrell; Geoff Feinberg; Scott VanManen; Larry Wiseman; Scott Wallinger

2007-01-01

Social marketing--the use of commercial marketing techniques to effect positive social change--is a promising means by which to develop more effective and efficient outreach, policies, and services for family forest owners. A hierarchical, multivariate analysis based on landowners' attitudes reveals four groups of owners to whom programs can be tailored: woodland...

Effects of Social Class and School Conditions on Educational Enrollment and Achievement of Boys and Girls in Rural Viet Nam

ERIC Educational Resources Information Center

Nguyen, Phuong L.

2006-01-01

This study examines the effects of parental SES, school quality, and community factors on children's enrollment and achievement in rural areas in Viet Nam, using logistic regression and ordered logistic regression. Multivariate analysis reveals significant differences in educational enrollment and outcomes by level of household expenditures and…

Rapid differentiation of Ghana cocoa beans by FT-NIR spectroscopy coupled with multivariate classification

NASA Astrophysics Data System (ADS)

Teye, Ernest; Huang, Xingyi; Dai, Huang; Chen, Quansheng

2013-10-01

Quick, accurate and reliable technique for discrimination of cocoa beans according to geographical origin is essential for quality control and traceability management. This current study presents the application of Near Infrared Spectroscopy technique and multivariate classification for the differentiation of Ghana cocoa beans. A total of 194 cocoa bean samples from seven cocoa growing regions were used. Principal component analysis (PCA) was used to extract relevant information from the spectral data and this gave visible cluster trends. The performance of four multivariate classification methods: Linear discriminant analysis (LDA), K-nearest neighbors (KNN), Back propagation artificial neural network (BPANN) and Support vector machine (SVM) were compared. The performances of the models were optimized by cross validation. The results revealed that; SVM model was superior to all the mathematical methods with a discrimination rate of 100% in both the training and prediction set after preprocessing with Mean centering (MC). BPANN had a discrimination rate of 99.23% for the training set and 96.88% for prediction set. While LDA model had 96.15% and 90.63% for the training and prediction sets respectively. KNN model had 75.01% for the training set and 72.31% for prediction set. The non-linear classification methods used were superior to the linear ones. Generally, the results revealed that NIR Spectroscopy coupled with SVM model could be used successfully to discriminate cocoa beans according to their geographical origins for effective quality assurance.

Structural changes in cross-border liabilities: A multidimensional approach

NASA Astrophysics Data System (ADS)

Araújo, Tanya; Spelta, Alessandro

2014-01-01

We study the international interbank market through a geometric analysis of empirical data. The geometric analysis of the time series of cross-country liabilities shows that the systematic information of the interbank international market is contained in a space of small dimension. Geometric spaces of financial relations across countries are developed, for which the space volume, multivariate skewness and multivariate kurtosis are computed. The behavior of these coefficients reveals an important modification acting in the financial linkages since 1997 and allows us to relate the shape of the geometric space that emerges in recent years to the globally turbulent period that has characterized financial systems since the late 1990s. Here we show that, besides a persistent decrease in the volume of the geometric space since 1997, the observation of a generalized increase in the values of the multivariate skewness and kurtosis sheds some light on the behavior of cross-border interdependencies during periods of financial crises. This was found to occur in such a systematic fashion, that these coefficients may be used as a proxy for systemic risk.

Effects of Flavor and Texture on the Sensory Perception of Gouda-Type Cheese Varieties during Ripening Using Multivariate Analysis.

PubMed

Shiota, Makoto; Iwasawa, Ai; Suzuki-Iwashima, Ai; Iida, Fumiko

2015-12-01

The impact of flavor composition, texture, and other factors on desirability of different commercial sources of Gouda-type cheese using multivariate analyses on the basis of sensory and instrumental analyses were investigated. Volatile aroma compounds were measured using headspace solid-phase microextraction gas chromatography/mass spectrometry (GC/MS) and steam distillation extraction (SDE)-GC/MS, and fatty acid composition, low-molecular-weight compounds, including amino acids, and organic acids, as well pH, texture, and color were measured to determine their relationship with sensory perception. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was performed to discriminate between 2 different ripening periods in 7 sample sets, revealing that ethanol, ethyl acetate, hexanoic acid, and octanoic acid increased with increasing sensory attribute scores for sweetness, fruity, and sulfurous. A partial least squares (PLS) regression model was constructed to predict the desirability of cheese using these parameters. We showed that texture and buttery flavors are important factors affecting the desirability of Gouda-type cheeses for Japanese consumers using these multivariate analyses. © 2015 Institute of Food Technologists®

Stone loaches of Choman River system, Kurdistan, Iran (Teleostei: Cypriniformes: Nemacheilidae).

PubMed

Kamangar, Barzan Bahrami; Prokofiev, Artem M; Ghaderi, Edris; Nalbant, Theodore T

2014-01-20

For the first time, we present data on species composition and distributions of nemacheilid loaches in the Choman River basin of Kurdistan province, Iran. Two genera and four species are recorded from the area, of which three species are new for science: Oxynoemacheilus kurdistanicus, O. zagrosensis, O. chomanicus spp. nov., and Turcinoemacheilus kosswigi Băn. et Nalb. Detailed and illustrated morphological descriptions and univariate and multivariate analysis of morphometric and meristic features are for each of these species. Forty morphometric and eleven meristic characters were used in multivariate analysis to select characters that could discriminate between the four loach species. Discriminant Function Analysis revealed that sixteen morphometric measures and five meristic characters have the most variability between the loach species. The dendrograms based on cluster analysis of Mahalanobis distances of morphometrics and a combination of both characters confirmed two distinct groups: Oxynoemacheilus spp. and T. kosswigi. Within Oxynoemacheilus, O. zagrosensis and O. chomanicus are more similar to one other rather to either is to O. kurdistanicus.

Simultaneous Evaluation of Life Cycle Dynamics between a Host Paramecium and the Endosymbionts of Paramecium bursaria Using Capillary Flow Cytometry.

PubMed

Takahashi, Toshiyuki

2016-08-17

Endosymbioses are driving forces underlying cell evolution. The endosymbiosis exhibited by Paramecium bursaria is an excellent model with which to study symbiosis. A single-cell microscopic analysis of P. bursaria reveals that endosymbiont numbers double when the host is in the division phase. Consequently, endosymbionts must arrange their cell cycle schedule if the culture-condition-dependent change delays the generation time of P. bursaria. However, it remains poorly understood whether endosymbionts keep pace with the culture-condition-dependent behaviors of P. bursaria, or not. Using microscopy and flow cytometry, this study investigated the life cycle behaviors occurring between endosymbionts and the host. To establish a connection between the host cell cycle and endosymbionts comprehensively, multivariate analysis was applied. The multivariate analysis revealed important information related to regulation between the host and endosymbionts. Results show that dividing endosymbionts underwent transition smoothly from the division phase to interphase, when the host was in the logarithmic phase. In contrast, endosymbiont division stagnated when the host was in the stationary phase. This paper explains that endosymbionts fine-tune their cell cycle pace with their host and that a synchronous life cycle between the endosymbionts and the host is guaranteed in the symbiosis of P. bursaria.

Simultaneous Evaluation of Life Cycle Dynamics between a Host Paramecium and the Endosymbionts of Paramecium bursaria Using Capillary Flow Cytometry

PubMed Central

Takahashi, Toshiyuki

2016-01-01

Endosymbioses are driving forces underlying cell evolution. The endosymbiosis exhibited by Paramecium bursaria is an excellent model with which to study symbiosis. A single-cell microscopic analysis of P. bursaria reveals that endosymbiont numbers double when the host is in the division phase. Consequently, endosymbionts must arrange their cell cycle schedule if the culture-condition-dependent change delays the generation time of P. bursaria. However, it remains poorly understood whether endosymbionts keep pace with the culture-condition-dependent behaviors of P. bursaria, or not. Using microscopy and flow cytometry, this study investigated the life cycle behaviors occurring between endosymbionts and the host. To establish a connection between the host cell cycle and endosymbionts comprehensively, multivariate analysis was applied. The multivariate analysis revealed important information related to regulation between the host and endosymbionts. Results show that dividing endosymbionts underwent transition smoothly from the division phase to interphase, when the host was in the logarithmic phase. In contrast, endosymbiont division stagnated when the host was in the stationary phase. This paper explains that endosymbionts fine-tune their cell cycle pace with their host and that a synchronous life cycle between the endosymbionts and the host is guaranteed in the symbiosis of P. bursaria. PMID:27531180

The risk factors for recurrence of chronic subdural hematoma.

PubMed

Ohba, Shigeo; Kinoshita, Yu; Nakagawa, Toru; Murakami, Hideki

2013-01-01

Chronic subdural hematoma (CSDH) is a common disease in the elderly, and the recurrence rate of CSDH is reported to range from 2.3 to 33%. We performed a retrospective review of a number of CSDH cases and the potential factors associated with CSDH recurrence. The patient population comprised 112 men and 65 women with a mean age of 74.7 years. We analyzed the following factors: age, sex, antiplatelet and anticoagulant use, hematoma laterality, hematoma thickness, degree of midline shift and internal architecture of the hematoma in the preoperative CT films, use of irrigation, direction of the drainage tube, width of the subdural space, and degree of midline shift and the presence of a massive subdural air collection in the postoperative CT films. Univariate analysis revealed that there was a trend for different rates of recurrence among the different types of hematomas. The presence of a postoperative massive subdural air collection tended to be associated with the recurrence of hematoma. Multivariate analysis revealed that separated hematomas were significantly associated with CSDH recurrence, whereas the presence of postoperative massive subdural air collection tended to be associated with hematoma recurrence. Neither univariate nor multivariate analysis could demonstrate an association between the direction of the drainage tube and the recurrence of CSDH.

The source identification of ambient aerosols in Beijing, China by multivariate analysis coupled with {sup 14}C tracer

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

Xiaoyan Tang; Min Shao; Yuanhang Zhang

1996-12-31

Ambient aerosol is one of most important pollutants in China. This paper showed the results of aerosol sources of Beijing area revealed by combination of multivariate analysis models and 14C tracer measured on Accelerator Mass Spectrometry (AMS). The results indicated that the mass concentration of particulate (<100 (M)) didn`t increase rapidly, compared with economic development in Beijing city. The multivariate analysis showed that the predominant source was soil dust which contributed more than 50% to atmospheric particles. However, it would be a risk to conclude that the aerosol pollution from anthropogenic sources was less important in Beijing city based onmore » above phenomenon. Due to lack of reliable tracers, it was very hard to distinguish coal burning from soil source. Thus, it was suspected that the soil source above might be the mixture of soil dust and coal burning. The 14C measurement showed that carbonaceous species of aerosol had quite different emission sources. For carbonaceous aerosols in Beijing, the contribution from fossil fuel to ambient particles was nearly 2/3, as the man-made activities ( coal-burning, etc.) increased, the fossil part would contribute more to atmospheric carbonaceous particles. For example, in downtown Beijing at space-heating seasons, the fossil fuel even contributed more than 95% to carbonaceous particles, which would be potential harmful to population. By using multivariate analysis together with 14C data, two important sources of aerosols in Beijing (soil and coal) combustion were more reliably distinguished, which was critical important for the assessment of aerosol problem in China.« less

Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study.

PubMed

Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong; Cox, Dennis D

2017-07-01

Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific process, and a joint analysis that integrates information across them may provide new insights into the underlying mechanism for the phenomenon under study. Motivated by fluorescence spectroscopy data in a cervical pre-cancer study, a multivariate functional response regression model is proposed, which treats multivariate functional observations as responses and a common set of covariates as predictors. This novel modeling framework simultaneously accounts for correlations between functional variables and potential multi-level structures in data that are induced by experimental design. The model is fitted by performing a two-stage linear transformation-a basis expansion to each functional variable followed by principal component analysis for the concatenated basis coefficients. This transformation effectively reduces the intra-and inter-function correlations and facilitates fast and convenient calculation. A fully Bayesian approach is adopted to sample the model parameters in the transformed space, and posterior inference is performed after inverse-transforming the regression coefficients back to the original data domain. The proposed approach produces functional tests that flag local regions on the functional effects, while controlling the overall experiment-wise error rate or false discovery rate. It also enables functional discriminant analysis through posterior predictive calculation. Analysis of the fluorescence spectroscopy data reveals local regions with differential expressions across the pre-cancer and normal samples. These regions may serve as biomarkers for prognosis and disease assessment.

Intratumoral heterogeneity analysis reveals hidden associations between protein expression losses and patient survival in clear cell renal cell carcinoma

PubMed Central

Devarajan, Karthik; Parsons, Theodore; Wang, Qiong; O'Neill, Raymond; Solomides, Charalambos; Peiper, Stephen C.; Testa, Joseph R.; Uzzo, Robert; Yang, Haifeng

2017-01-01

Intratumoral heterogeneity (ITH) is a prominent feature of kidney cancer. It is not known whether it has utility in finding associations between protein expression and clinical parameters. We used ITH that is detected by immunohistochemistry (IHC) to aid the association analysis between the loss of SWI/SNF components and clinical parameters.160 ccRCC tumors (40 per tumor stage) were used to generate tissue microarray (TMA). Four foci from different regions of each tumor were selected. IHC was performed against PBRM1, ARID1A, SETD2, SMARCA4, and SMARCA2. Statistical analyses were performed to correlate biomarker losses with patho-clinical parameters. Categorical variables were compared between groups using Fisher's exact tests. Univariate and multivariable analyses were used to correlate biomarker changes and patient survivals. Multivariable analyses were performed by constructing decision trees using the classification and regression trees (CART) methodology. IHC detected widespread ITH in ccRCC tumors. The statistical analysis of the “Truncal loss” (root loss) found additional correlations between biomarker losses and tumor stages than the traditional “Loss in tumor (total)”. Losses of SMARCA4 or SMARCA2 significantly improved prognosis for overall survival (OS). Losses of PBRM1, ARID1A or SETD2 had the opposite effect. Thus “Truncal Loss” analysis revealed hidden links between protein losses and patient survival in ccRCC. PMID:28445125

Discerning mild cognitive impairment and Alzheimer Disease from normal aging: morphologic characterization based on univariate and multivariate models.

PubMed

Liao, Weiqi; Long, Xiaojing; Jiang, Chunxiang; Diao, Yanjun; Liu, Xin; Zheng, Hairong; Zhang, Lijuan

2014-05-01

Differentiating mild cognitive impairment (MCI) and Alzheimer Disease (AD) from healthy aging remains challenging. This study aimed to explore the cerebral structural alterations of subjects with MCI or AD as compared to healthy elderly based on the individual and collective effects of cerebral morphologic indices using univariate and multivariate analyses. T1-weighted images (T1WIs) were retrieved from Alzheimer Disease Neuroimaging Initiative database for 116 subjects who were categorized into groups of healthy aging, MCI, and AD. Analysis of covariance (ANCOVA) and multivariate analysis of covariance (MANCOVA) were performed to explore the intergroup morphologic alterations indexed by surface area, curvature index, cortical thickness, and subjacent white matter volume with age and sex controlled as covariates, in 34 parcellated gyri regions of interest (ROIs) for both cerebral hemispheres based on the T1WI. Statistical parameters were mapped on the anatomic images to facilitate visual inspection. Global rather than region-specific structural alterations were revealed in groups of MCI and AD relative to healthy elderly using MANCOVA. ANCOVA revealed that the cortical thickness decreased more prominently in entorhinal, temporal, and cingulate cortices and was positively correlated with patients' cognitive performance in AD group but not in MCI. The temporal lobe features marked atrophy of white matter during the disease dynamics. Significant intercorrelations were observed among the morphologic indices with univariate analysis for given ROIs. Significant global structural alterations were identified in MCI and AD based on MANCOVA model with improved sensitivity. The intercorrelation among the morphologic indices may dampen the use of individual morphological parameter in featuring cerebral structural alterations. Decrease in cortical thickness is not reflective of the cognitive performance at the early stage of AD. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Multivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurement.

PubMed

Riley, Richard D; Elia, Eleni G; Malin, Gemma; Hemming, Karla; Price, Malcolm P

2015-07-30

A prognostic factor is any measure that is associated with the risk of future health outcomes in those with existing disease. Often, the prognostic ability of a factor is evaluated in multiple studies. However, meta-analysis is difficult because primary studies often use different methods of measurement and/or different cut-points to dichotomise continuous factors into 'high' and 'low' groups; selective reporting is also common. We illustrate how multivariate random effects meta-analysis models can accommodate multiple prognostic effect estimates from the same study, relating to multiple cut-points and/or methods of measurement. The models account for within-study and between-study correlations, which utilises more information and reduces the impact of unreported cut-points and/or measurement methods in some studies. The applicability of the approach is improved with individual participant data and by assuming a functional relationship between prognostic effect and cut-point to reduce the number of unknown parameters. The models provide important inferential results for each cut-point and method of measurement, including the summary prognostic effect, the between-study variance and a 95% prediction interval for the prognostic effect in new populations. Two applications are presented. The first reveals that, in a multivariate meta-analysis using published results, the Apgar score is prognostic of neonatal mortality but effect sizes are smaller at most cut-points than previously thought. In the second, a multivariate meta-analysis of two methods of measurement provides weak evidence that microvessel density is prognostic of mortality in lung cancer, even when individual participant data are available so that a continuous prognostic trend is examined (rather than cut-points). © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Gas-water two-phase flow characterization with Electrical Resistance Tomography and Multivariate Multiscale Entropy analysis.

PubMed

Tan, Chao; Zhao, Jia; Dong, Feng

2015-03-01

Flow behavior characterization is important to understand gas-liquid two-phase flow mechanics and further establish its description model. An Electrical Resistance Tomography (ERT) provides information regarding flow conditions at different directions where the sensing electrodes implemented. We extracted the multivariate sample entropy (MSampEn) by treating ERT data as a multivariate time series. The dynamic experimental results indicate that the MSampEn is sensitive to complexity change of flow patterns including bubbly flow, stratified flow, plug flow and slug flow. MSampEn can characterize the flow behavior at different direction of two-phase flow, and reveal the transition between flow patterns when flow velocity changes. The proposed method is effective to analyze two-phase flow pattern transition by incorporating information of different scales and different spatial directions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

The Effect of Alcohol Abuse and Dependence and School Experiences on Depression: A National Study of Adolescents

ERIC Educational Resources Information Center

Merianos, Ashley L.; King, Keith A.; Vidourek, Rebecca A.; Hardee, Angelica M.

2016-01-01

The study purpose was to examine the effect alcohol abuse/dependence and school experiences have on depression among a nationwide sample of adolescents. A secondary analysis of the 2013 National Survey on Drug Use and Health was conducted. The results of the final multivariable logistic regression model revealed that adolescents who reported…

Treatment of dogs with lymphoma using a 12-week, maintenance-free combination chemotherapy protocol.

PubMed

Simon, D; Nolte, I; Eberle, N; Abbrederis, N; Killich, M; Hirschberger, J

2006-01-01

Treatment of lymphoma in dogs by long-term chemotherapy has favorable results. However, the efficacy of short-term, maintenance-free treatment protocols on remission and survival times in dogs has not been determined. That treatment using a 12-week chemotherapy protocol would be associated with satisfactory treatment outcome in dogs with lymphoma. 77 dogs with histologically or cytologically confirmed diagnosis of lymphoma. Prospective clinical trial in which dogs were treated with a 12-week chemotherapy protocol consisting of L-asparaginase, vincristine, cyclophosphamide, doxorubicin, and prednisolone. Complete remission rate was 76.3%. Multivariate logistic regression analysis revealed that clinical substage (P = .006) and immunophenotype (P = .003) had a significant influence on the likelihood of a dog achieving complete remission. Median duration of first complete remission was 243 days (range 19-1,191 days). The 6-month, 1-year, and 2-year remission rates were 68%, 28%, and 16%, respectively. In the multivariate analysis of patient variables, immunophenotype (P = .022) revealed a significant influence on first remission duration. Toxicosis was mild with the exception of 1 treatment-associated death. In this group of dogs the 12-week maintenance-free chemotherapy protocol was well tolerated and had satisfactory results.

[Correlation between gaseous exchange rate, body temperature, and mitochondrial protein content in the liver of mice].

PubMed

Muradian, Kh K; Utko, N O; Mozzhukhina, T H; Pishel', I M; Litoshenko, O Ia; Bezrukov, V V; Fraĭfel'd, V E

2002-01-01

Correlative and regressive relations between the gaseous exchange, thermoregulation and mitochondrial protein content were analyzed by two- and three-dimensional statistics in mice. It has been shown that the pair wise linear methods of analysis did not reveal any significant correlation between the parameters under exploration. However, it became evident at three-dimensional and non-linear plotting for which the coefficients of multivariable correlation reached and even exceeded 0.7-0.8. The calculations based on partial differentiation of the multivariable regression equations allow to conclude that at certain values of VO2, VCO2 and body temperature negative relations between the systems of gaseous exchange and thermoregulation become dominating.

Multivariate statistical analysis to characterize/discriminate between anthropogenic and geogenic trace elements occurrence in the Campania Plain, Southern Italy.

PubMed

Busico, Gianluigi; Cuoco, Emilio; Kazakis, Nerantzis; Colombani, Nicolò; Mastrocicco, Micòl; Tedesco, Dario; Voudouris, Konstantinos

2018-03-01

Shallow aquifers are the most accessible reservoirs of potable groundwater; nevertheless, they are also prone to various sources of pollution and it is usually difficult to distinguish between human and natural sources at the watershed scale. The area chosen for this study (the Campania Plain) is characterized by high spatial heterogeneities both in geochemical features and in hydraulic properties. Groundwater mineralization is driven by many processes such as, geothermal activity, weathering of volcanic products and intense human activities. In such a landscape, multivariate statistical analysis has been used to differentiate among the main hydrochemical processes occurring in the area, using three different approaches of factor analysis: (i) major elements, (ii) trace elements, (iii) both major and trace elements. The elaboration of the factor analysis approaches has revealed seven distinct hydrogeochemical processes: i) Salinization (Cl - , Na + ); ii) Carbonate rocks dissolution; iii) Anthropogenic inputs (NO 3 - , SO 4 2- , U, V); iv) Reducing conditions (Fe 2+ , Mn 2+ ); v) Heavy metals contamination (Cr and Ni); vi) Geothermal fluids influence (Li + ); and vii) Volcanic products contribution (As, Rb). Results from this study highlight the need to separately apply factor analysis when a large data set of trace elements is available. In fact, the impact of geothermal fluids in the shallow aquifer was identified from the application of the factor analysis using only trace elements. This study also reveals that the factor analysis of major and trace elements can differentiate between anthropogenic and geogenic sources of pollution in intensively exploited aquifers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multivariate analysis of matrix-assisted laser desorption/ionization mass spectrometric data related to glycoxidation products of human globins in nephropathic patients.

PubMed

Lapolla, Annunziata; Ragazzi, Eugenio; Andretta, Barbara; Fedele, Domenico; Tubaro, Michela; Seraglia, Roberta; Molin, Laura; Traldi, Pietro

2007-06-01

To clarify the possible pathogenetic role of oxidation products originated from the glycation of proteins, human globins from nephropathic patients have been studied by matrix-assisted laser desorption/ionization mass spectrometry (MALDI), revealing not only unglycated and monoglycated globins, but also a series of different species. For the last ones, structural assignments were tentatively done on the basis of observed masses and expectations for the Maillard reaction pattern. Consequently, they must be considered only propositive, and the discussion which will follow must be considered in this view. In our opinion this approach does not seem to compromise the intended diagnostic use of the data because distinctions are valid even if the assignments are uncertain. We studied nine healthy subjects and 19 nephropathic patients and processed the data obtained from the MALDI spectra using a multivariate analysis. Our results showed that multivariate analytical techniques enable differential aspects of the profile of molecular species to be identified in the blood of end stage nephropathic patients. A correct grouping can be achieved by principal component analysis (PCA) and the results suggest that several products involved in carbonyl stress exist in nephropathic patients. These compounds may have a relevant role as specific markers of the pathological state.

Multivariate fMRI and Eye Tracking Reveal Differential Effects of Visual Interference on Recognition Memory Judgments for Objects and Scenes.

PubMed

O'Neil, Edward B; Watson, Hilary C; Dhillon, Sonya; Lobaugh, Nancy J; Lee, Andy C H

2015-09-01

Recent work has demonstrated that the perirhinal cortex (PRC) supports conjunctive object representations that aid object recognition memory following visual object interference. It is unclear, however, how these representations interact with other brain regions implicated in mnemonic retrieval and how congruent and incongruent interference influences the processing of targets and foils during object recognition. To address this, multivariate partial least squares was applied to fMRI data acquired during an interference match-to-sample task, in which participants made object or scene recognition judgments after object or scene interference. This revealed a pattern of activity sensitive to object recognition following congruent (i.e., object) interference that included PRC, prefrontal, and parietal regions. Moreover, functional connectivity analysis revealed a common pattern of PRC connectivity across interference and recognition conditions. Examination of eye movements during the same task in a separate study revealed that participants gazed more at targets than foils during correct object recognition decisions, regardless of interference congruency. By contrast, participants viewed foils more than targets for incorrect object memory judgments, but only after congruent interference. Our findings suggest that congruent interference makes object foils appear familiar and that a network of regions, including PRC, is recruited to overcome the effects of interference.

Association between systemic inflammation and serum prostate-specific antigen in a healthy Korean population

PubMed Central

Yun, Jonghyun; Lee, Hyunyoung; Yang, Wonjae

2017-01-01

Objective Serum prostate-specific antigen (PSA) may be elevated in healthy men with systemic inflammation. We aimed to investigate the association between systemic inflammation markers and serum PSA in a healthy Korean population. Material and methods A cohort of 20,151 healthy native Korean men without prostate disease between the ages of 40 and 65 years who underwent medical checkups were studied from January 2007 to December 2013. Serum total PSA and serum C-reactive protein concentrations, neutrophil, lymphocyte, and platelet counts were determined. The neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) were calculated. We checked the correlation between systemic inflammation markers and PSA. Results Data obtained from 18,800 healthy men were analyzed. The mean age of the study subjects was 50.72±7.62 years and the mean NLR was 1.764±0.804. Correlation analysis after adjustment for age and body mass index (BMI) revealed that neutrophil count (coefficient = 0.028, p value <0.001), and NLR (coefficient = 0.027, p value <0.001) correlated with PSA. Multivariate analysis using the full model revealed that age, neutrophil count and NLR were positively correlated with PSA (p<0.001, 0.001, and 0.043 respectively). Multivariate analysis using a stepwise model revealed that age, neutrophil count and NLR were positively correlated with PSA (p<0.001, 0.001, and 0.040, respectively) and BMI was negatively correlated with PSA (p<0.001). Conclusion Systemic inflammation markers are useful with a serum PSA in a healthy Korean population. NLR in particular is significantly associated with serum PSA. PMID:28861299

Locomotor Recovery in Spinal Cord Injury: Insights Beyond Walking Speed and Distance.

PubMed

Awai, Lea; Curt, Armin

2016-08-01

Recovery of locomotor function after incomplete spinal cord injury (iSCI) is clinically assessed through walking speed and distance, while improvements in these measures might not be in line with a normalization of gait quality and are, on their own, insensitive at revealing potential mechanisms underlying recovery. The objective of this study was to relate changes of gait parameters to the recovery of walking speed while distinguishing between parameters that rather reflect speed improvements from factors contributing to overall recovery. Kinematic data of 16 iSCI subjects were repeatedly recorded during in-patient rehabilitation. The responsiveness of gait parameters to walking speed was assessed by linear regression. Principal component analysis (PCA) was applied on the multivariate data across time to identify factors that contribute to recovery after iSCI. Parameters of gait cycle and movement dynamics were both responsive and closely related to the recovery of walking speed, which increased by 96%. Multivariate analysis revealed specific gait parameters (intralimb shape normality and consistency) that, although less related to speed increments, loaded highly on principal component one (PC1) (58.6%) explaining the highest proportion of variance (i.e., recovery of outcome over time). Interestingly, measures of hip, knee, and ankle range of motion showed varying degrees of responsiveness (from very high to very low) while not contributing to gait recovery as revealed by PCA. The conjunct application of two analysis methods distinguishes gait parameters that simply reflect increased walking speed from parameters that actually contribute to gait recovery in iSCI. This distinction may be of value for the evaluation of interventions for locomotor recovery.

Plasma metabolic profiling analysis of nephrotoxicity induced by acyclovir using metabonomics coupled with multivariate data analysis.

PubMed

Zhang, Xiuxiu; Li, Yubo; Zhou, Huifang; Fan, Simiao; Zhang, Zhenzhu; Wang, Lei; Zhang, Yanjun

2014-08-01

Acyclovir (ACV) is an antiviral agent. However, its use is limited by adverse side effect, particularly by its nephrotoxicity. Metabonomics technology can provide essential information on the metabolic profiles of biofluids and organs upon drug administration. Therefore, in this study, mass spectrometry-based metabonomics coupled with multivariate data analysis was used to identify the plasma metabolites and metabolic pathways related to nephrotoxicity caused by intraperitoneal injection of low (50mg/kg) and high (100mg/kg) doses of acyclovir. Sixteen biomarkers were identified by metabonomics and nephrotoxicity results revealed the dose-dependent effect of acyclovir on kidney tissues. The present study showed that the top four metabolic pathways interrupted by acyclovir included the metabolisms of arachidonic acid, tryptophan, arginine and proline, and glycerophospholipid. This research proves the established metabonomic approach can provide information on changes in metabolites and metabolic pathways, which can be applied to in-depth research on the mechanism of acyclovir-induced kidney injury. Copyright © 2014 Elsevier B.V. All rights reserved.

Bioprospecting Chemical Diversity and Bioactivity in a Marine Derived Aspergillus terreus.

PubMed

Adpressa, Donovon A; Loesgen, Sandra

2016-02-01

A comparative metabolomic study of a marine derived fungus (Aspergillus terreus) grown under various culture conditions is presented. The fungus was grown in eleven different culture conditions using solid agar, broth cultures, or grain based media (OSMAC). Multivariate analysis of LC/MS data from the organic extracts revealed drastic differences in the metabolic profiles and guided our subsequent isolation efforts. The compound 7-desmethylcitreoviridin was isolated and identified, and is fully described for the first time. In addition, 16 known fungal metabolites were also isolated and identified. All compounds were elucidated by detailed spectroscopic analysis and tested for antibacterial activities against five human pathogens and tested for cytotoxicity. This study demonstrates that LC/MS based multivariate analysis provides a simple yet powerful tool to analyze the metabolome of a single fungal strain grown under various conditions. This approach allows environmentally-induced changes in metabolite expression to be rapidly visualized, and uses these differences to guide the discovery of new bioactive molecules. Copyright © 2016 Verlag Helvetica Chimica Acta AG, Zürich.

A cross-species socio-emotional behaviour development revealed by a multivariate analysis.

PubMed

Koshiba, Mamiko; Senoo, Aya; Mimura, Koki; Shirakawa, Yuka; Karino, Genta; Obara, Saya; Ozawa, Shinpei; Sekihara, Hitomi; Fukushima, Yuta; Ueda, Toyotoshi; Kishino, Hirohisa; Tanaka, Toshihisa; Ishibashi, Hidetoshi; Yamanouchi, Hideo; Yui, Kunio; Nakamura, Shun

2013-01-01

Recent progress in affective neuroscience and social neurobiology has been propelled by neuro-imaging technology and epigenetic approach in neurobiology of animal behaviour. However, quantitative measurements of socio-emotional development remains lacking, though sensory-motor development has been extensively studied in terms of digitised imaging analysis. Here, we developed a method for socio-emotional behaviour measurement that is based on the video recordings under well-defined social context using animal models with variously social sensory interaction during development. The behaviour features digitized from the video recordings were visualised in a multivariate statistic space using principal component analysis. The clustering of the behaviour parameters suggested the existence of species- and stage-specific as well as cross-species behaviour modules. These modules were used to characterise the behaviour of children with or without autism spectrum disorders (ASDs). We found that socio-emotional behaviour is highly dependent on social context and the cross-species behaviour modules may predict neurobiological basis of ASDs.

[Prevalence and determinants of exclusive breastfeeding in the city of Serrana, São Paulo, Brazil].

PubMed

Queluz, Mariângela Carletti; Pereira, Maria José Bistafa; dos Santos, Claudia Benedita; Leite, Adriana Moraes; Ricco, Rubens Garcia

2012-06-01

The objective of this cross-sectional and quantitative study was to identify the prevalence and determinants of exclusive breastfeeding among infants less than six months of age in the city of Serrana, Sao Paulo, Brazil in 2009. A validated semi-structured questionnaire was administered to the guardians of the children less than six months of age who attended the second phase of a Brazilian vaccination campaign against polio. Univariate and multivariate analysis presented in odds ratios and confidence intervals was accomplished. Of the total of 275 infant participants, only 29.8% were exclusively breastfed. Univariate analysis revealed that mothers who work outside the home without maternity leave, mothers who did not work outside the home, adolescent mothers, and the use of pacifiers have a greater chance of interrupting exclusive breastfeeding. In the multivariate analysis, mothers who work outside the home without maternity leave are three times more likely to wean their children early. Results provide suggestions for the redirection and planning of interventions targeting breastfeeding.

Multivariate information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity.

PubMed

Lizier, Joseph T; Heinzle, Jakob; Horstmann, Annette; Haynes, John-Dylan; Prokopenko, Mikhail

2011-02-01

The human brain undertakes highly sophisticated information processing facilitated by the interaction between its sub-regions. We present a novel method for interregional connectivity analysis, using multivariate extensions to the mutual information and transfer entropy. The method allows us to identify the underlying directed information structure between brain regions, and how that structure changes according to behavioral conditions. This method is distinguished in using asymmetric, multivariate, information-theoretical analysis, which captures not only directional and non-linear relationships, but also collective interactions. Importantly, the method is able to estimate multivariate information measures with only relatively little data. We demonstrate the method to analyze functional magnetic resonance imaging time series to establish the directed information structure between brain regions involved in a visuo-motor tracking task. Importantly, this results in a tiered structure, with known movement planning regions driving visual and motor control regions. Also, we examine the changes in this structure as the difficulty of the tracking task is increased. We find that task difficulty modulates the coupling strength between regions of a cortical network involved in movement planning and between motor cortex and the cerebellum which is involved in the fine-tuning of motor control. It is likely these methods will find utility in identifying interregional structure (and experimentally induced changes in this structure) in other cognitive tasks and data modalities.

Impact of Gender on 30-Day Complications After Primary Total Joint Arthroplasty.

PubMed

Robinson, Jonathan; Shin, John I; Dowdell, James E; Moucha, Calin S; Chen, Darwin D

2017-08-01

Impact of gender on 30-day complications has been investigated in other surgical procedures but has not yet been studied in total hip arthroplasty (THA) or total knee arthroplasty (TKA). Patients who received THA or TKA from 2012 to 2014 were identified in the National Surgical Quality Improvement Program database. Patients were divided into 2 groups based on gender. Bivariate and multivariate analyses were performed to assess associations between gender and patient factors and complications after THA or TKA and to assess whether gender was an independent risk factor. THA patients consisted of 45.1% male and 54.9% female. In a multivariate analysis, female gender was found to be a protective factor for mortality, sepsis, cardiovascular complications, unplanned reintubation, and renal complications and as an independent risk factor for urinary tract infection, blood transfusion, and nonhome discharge after THA. TKA patients consisted of 36.7% male and 62.3% female. Multivariate analysis revealed female gender as a protective factor for sepsis, cardiovascular complications, and renal complications and as an independent risk factor for urinary tract infection, blood transfusion, and nonhome discharge after TKA. There are discrepancies in the THA or TKA complications based on gender, and the multivariate analyses confirmed gender as an independent risk factor for certain complications. Physicians should be mindful of patient's gender for better risk stratification and informed consent. Copyright © 2017 Elsevier Inc. All rights reserved.

Incidence of cervical lymph node metastasis and its association with outcomes in patients with adenoid cystic carcinoma. An international collaborative study

PubMed Central

Amit, Moran; Binenbaum, Yoav; Sharma, Kanika; Ramer, Naomi; Ramer, Ilana; Agbetoba, Abib; Glick, Joelle; Yang, Xinjie; Lei, Delin; Bjørndal, Kristine; Godballe, Christian; Mücke, Thomas; Wolff, Klaus-Dietrich; Fliss, Dan; Eckardt, André M.; Copelli, Chiara; Sesenna, Enrico; Palmer, Frank; Ganly, Ian; Patel, Snehal; Gil, Ziv

2016-01-01

Background The patterns of regional metastasis in adenoid cystic carcinoma (ACC) of the head and neck and its association with outcome is not established. Methods We conducted a retrospective multicentered multivariate analysis of 270 patients who underwent neck dissection. Results The incidence rate of neck metastases was 29%. The rate observed in the oral cavity is 37%, and in the major salivary glands is 19% (p = .001). The rate of occult nodal metastases was 17%. Overall 5-year survival rates were 44% in patients undergoing therapeutic neck dissections, and 65% and 73% among those undergoing elective neck dissections, with and without nodal metastases, respectively (p = .017). Multivariate analysis revealed that the primary site, nodal classification, and margin status were independent predictors of survival. Conclusion Our findings support the consideration of elective neck treatment in patients with ACC of the oral cavity. PMID:25060927

Pneumonia in multiple injured patients: a prospective controlled trial on early prediction using clinical and immunological parameters.

PubMed

Andermahr, J; Greb, A; Hensler, T; Helling, H J; Bouillon, B; Sauerland, S; Rehm, K E; Neugebauer, E

2002-05-01

In a prospective trial 266 multiple injured patients were included to evaluate clinical risk factors and immune parameters related to pneumonia. Clinical and humoral parameters were assessed and multivariate analysis performed. The multivariate analysis (odds ratio with 95% confidence interval (CI)) revealed male gender (3.65), traumatic brain injury (TBI) (2.52), thorax trauma (AIS(thorax) > or = 3) (2.05), antibiotic prophylaxis (1.30), injury severity score (ISS) (1.03 per ISS point) and the age (1.02 per year) as risk factors for pneumonia. The main pathogens were Acinetobacter Baumannii (40%) and Staphylococcus aureus (25%). A tendency towards higher Procalcitonin (PCT) and Interleukin (IL)-6 levels two days after trauma was observed for pneumonia patients. The immune parameters (PCT, IL-6, IL-10, soluble tumor necrosis factor p-55 and p-75) could not confirm the diagnosis of pneumonia earlier than the clinical parameters.

Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

NASA Astrophysics Data System (ADS)

Gu, Huaying; Liu, Zhixue; Weng, Yingliang

2017-04-01

The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

Multivariate temporal pattern analysis applied to the study of rat behavior in the elevated plus maze: methodological and conceptual highlights.

PubMed

Casarrubea, M; Magnusson, M S; Roy, V; Arabo, A; Sorbera, F; Santangelo, A; Faulisi, F; Crescimanno, G

2014-08-30

Aim of this article is to illustrate the application of a multivariate approach known as t-pattern analysis in the study of rat behavior in elevated plus maze. By means of this multivariate approach, significant relationships among behavioral events in the course of time can be described. Both quantitative and t-pattern analyses were utilized to analyze data obtained from fifteen male Wistar rats following a trial 1-trial 2 protocol. In trial 2, in comparison with the initial exposure, mean occurrences of behavioral elements performed in protected zones of the maze showed a significant increase counterbalanced by a significant decrease of mean occurrences of behavioral elements in unprotected zones. Multivariate t-pattern analysis, in trial 1, revealed the presence of 134 t-patterns of different composition. In trial 2, the temporal structure of behavior become more simple, being present only 32 different t-patterns. Behavioral strings and stripes (i.e. graphical representation of each t-pattern onset) of all t-patterns were presented both for trial 1 and trial 2 as well. Finally, percent distributions in the three zones of the maze show a clear-cut increase of t-patterns in closed arm and a significant reduction in the remaining zones. Results show that previous experience deeply modifies the temporal structure of rat behavior in the elevated plus maze. In addition, this article, by highlighting several conceptual, methodological and illustrative aspects on the utilization of t-pattern analysis, could represent a useful background to employ such a refined approach in the study of rat behavior in elevated plus maze. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis.

PubMed

Cohen, Mitchell J; Grossman, Adam D; Morabito, Diane; Knudson, M Margaret; Butte, Atul J; Manley, Geoffrey T

2010-01-01

Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome. Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality. We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters. Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.

Environmental assessment of Al-Hammar Marsh, Southern Iraq.

PubMed

Al-Gburi, Hind Fadhil Abdullah; Al-Tawash, Balsam Salim; Al-Lafta, Hadi Salim

2017-02-01

(a) To determine the spatial distributions and levels of major and minor elements, as well as heavy metals, in water, sediment, and biota (plant and fish) in Al-Hammar Marsh, southern Iraq, and ultimately to supply more comprehensive information for policy-makers to manage the contaminants input into the marsh so that their concentrations do not reach toxic levels. (b) to characterize the seasonal changes in the marsh surface water quality. (c) to address the potential environmental risk of these elements by comparison with the historical levels and global quality guidelines (i.e., World Health Organization (WHO) standard limits). (d) to define the sources of these elements (i.e., natural and/or anthropogenic) using combined multivariate statistical techniques such as Principal Component Analysis (PCA) and Agglomerative Hierarchical Cluster Analysis (AHCA) along with pollution analysis (i.e., enrichment factor analysis). Water, sediment, plant, and fish samples were collected from the marsh, and analyzed for major and minor ions, as well as heavy metals, and then compared to historical levels and global quality guidelines (WHO guidelines). Then, multivariate statistical techniques, such as PCA and AHCA, were used to determine the element sourcing. Water analyses revealed unacceptable values for almost all physio-chemical and biological properties, according to WHO standard limits for drinking water. Almost all major ions and heavy metal concentrations in water showed a distinct decreasing trend at the marsh outlet station compared to other stations. In general, major and minor ions, as well as heavy metals exhibit higher concentrations in winter than in summer. Sediment analyses using multivariate statistical techniques revealed that Mg, Fe, S, P, V, Zn, As, Se, Mo, Co, Ni, Cu, Sr, Br, Cd, Ca, N, Mn, Cr, and Pb were derived from anthropogenic sources, while Al, Si, Ti, K, and Zr were primarily derived from natural sources. Enrichment factor analysis gave results compatible with multivariate statistical techniques findings. Analysis of heavy metals in plant samples revealed that there is no pollution in plants in Al-Hammar Marsh. However, the concentrations of heavy metals in fish samples showed that all samples were contaminated by Pb, Mn, and Ni, while some samples were contaminated by Pb, Mn, and Ni. Decreasing of Tigris and Euphrates discharges during the past decades due to drought conditions and upstream damming, as well as the increasing stress of wastewater effluents from anthropogenic activities, led to degradation of the downstream Al-Hammar Marsh water quality in terms of physical, chemical, and biological properties. As such properties were found to consistently exceed the historical and global quality objectives. However, element concentration decreasing trend at the marsh outlet station compared to other stations indicate that the marsh plays an important role as a natural filtration and bioremediation system. Higher element concentrations in winter were due to runoff from the washing of the surrounding Sabkha during flooding by winter rainstorms. Finally, the high concentrations of heavy metals in fish samples can be attributed to bioaccumulation and biomagnification processes.

Association between breastfeeding duration, non-nutritive sucking habits and dental arch dimensions in deciduous dentition: a cross-sectional study.

PubMed

Agarwal, Shiv Shankar; Nehra, Karan; Sharma, Mohit; Jayan, Balakrishna; Poonia, Anish; Bhattal, Hiteshwar

2014-10-31

This cross-sectional retrospective study was conducted to determine association between breastfeeding duration, non-nutritive sucking habits, dental arch transverse diameters, posterior crossbite and anterior open bite in deciduous dentition. 415 children (228 males and 187 females), 4 to 6 years old, from a mixed Indian population were clinically examined. Based on written questionnaire answered by parents, children were divided into two groups: group 1 (breastfed for <6 months (n = 158)) and group 2 (breastfed for ≥6 months (n = 257)). The associations were analysed using chi-square test (P < 0.05 taken as statistically significant). Odds ratio (OR) was calculated to determine the strength of associations tested. Multivariate logistic regression analysis was done for obtaining independent predictors of posterior crossbite and maxillary and mandibular IMD (Inter-molar distance) and ICD (Inter-canine distance). Non-nutritive sucking (NNS) was present in 15.18% children (20.3% in group 1 as compared to 12.1% in group 2 (P = 0.024)). The average ICD and IMD in maxilla and average IMD in mandible were significantly higher among group 2 as compared to group 1 (P < 0.01). In mandible, average ICD did not differ significantly between the two groups (P = 0.342). The distribution of anterior open bite did not differ significantly between the two groups (P = 0.865). The distribution of posterior crossbite was significantly different between the two groups (P = 0.001). OR assessment (OR = 1.852) revealed that group 1 had almost twofold higher prevalence of NNS habits than group 2. Multivariate logistic regression analysis revealed that the first group had independently fourfold increased risk of developing crossbite compared to the second group (OR = 4.3). Multivariate linear regression analysis also revealed that age and breastfeeding duration were the most significant determinants of ICD and IMD. An increased prevalence of NNS in the first group suggests that NNS is a dominant variable in the association between breastfeeding duration and reduced intra-arch transverse diameters which leads to increased prevalence of posterior crossbites as seen in our study. Mandibular inter-canine width is however unaffected due to a lowered tongue posture seen in these children.

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing.

PubMed

Stamate, Mirela Cristina; Todor, Nicolae; Cosgarea, Marcel

2015-01-01

The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies.

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing

PubMed Central

STAMATE, MIRELA CRISTINA; TODOR, NICOLAE; COSGAREA, MARCEL

2015-01-01

Background and aim The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. Methods The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. Results We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Conclusion Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies. PMID:26733749

Prognostic value of MLH1 promoter methylation in male patients with esophageal squamous cell carcinoma.

PubMed

Wu, Dongping; Chen, Xiaoying; Xu, Yan; Wang, Haiyong; Yu, Guangmao; Jiang, Luping; Hong, Qingxiao; Duan, Shiwei

2017-04-01

The DNA mismatch repair (MMR) gene MutL homolog 1 ( MLH1 ) is critical for the maintenance of genomic integrity. Methylation of the MLH1 gene promoter was identified as a prognostic marker for numerous types of cancer including glioblastoma, colorectal, ovarian and gastric cancer. The present study aimed to determine whether MLH1 promoter methylation was associated with survival in male patients with esophageal squamous cell carcinoma (ESCC). Formalin-fixed, paraffin-embedded ESCC tissues were collected from 87 male patients. MLH1 promoter methylation was assessed using the methylation-specific polymerase chain reaction approach. Kaplan-Meier survival curves and log-rank tests were used to evaluate the association between MLH1 promoter methylation and overall survival (OS) in patients with ESCC. Cox regression analysis was used to obtain crude and multivariate hazard ratios (HR), and 95% confidence intervals (CI). The present study revealed that MLH1 promoter methylation was observed in 53/87 (60.9%) of male patients with ESCC. Kaplan-Meier survival analysis demonstrated that MLH1 promoter hypermethylation was significantly associated with poorer prognosis in patients with ESCC (P=0.048). Multivariate survival analysis revealed that MLH1 promoter hypermethylation was an independent predictor of poor OS in male patients with ESCC (HR=1.716; 95% CI=1.008-2.921). Therefore, MLH1 promoter hypermethylation may be a predictor of prognosis in male patients with ESCC.

Determinants of elevated healthcare utilization in patients with COPD.

PubMed

Simon-Tuval, Tzahit; Scharf, Steven M; Maimon, Nimrod; Bernhard-Scharf, Barbara J; Reuveni, Haim; Tarasiuk, Ariel

2011-01-13

Chronic obstructive pulmonary disease (COPD) imparts a substantial economic burden on western health systems. Our objective was to analyze the determinants of elevated healthcare utilization among patients with COPD in a single-payer health system. Three-hundred eighty-nine adults with COPD were matched 1:3 to controls by age, gender and area of residency. Total healthcare cost 5 years prior recruitment and presence of comorbidities were obtained from a computerized database. Health related quality of life (HRQoL) indices were obtained using validated questionnaires among a subsample of 177 patients. Healthcare utilization was 3.4-fold higher among COPD patients compared with controls (p < 0.001). The "most-costly" upper 25% of COPD patients (n = 98) consumed 63% of all costs. Multivariate analysis revealed that independent determinants of being in the "most costly" group were (OR; 95% CI): age-adjusted Charlson Comorbidity Index (1.09; 1.01-1.2), history of: myocardial infarct (2.87; 1.5-5.5), congestive heart failure (3.52; 1.9-6.4), mild liver disease (3.83; 1.3-11.2) and diabetes (2.02; 1.1-3.6). Bivariate analysis revealed that cost increased as HRQoL declined and severity of airflow obstruction increased but these were not independent determinants in a multivariate analysis. Comorbidity burden determines elevated utilization for COPD patients. Decision makers should prioritize scarce health care resources to a better care management of the "most costly" patients.

Crayfish: a newly recognized vehicle for vibrio infections.

PubMed

Bean, N H; Maloney, E K; Potter, M E; Korazemo, P; Ray, B; Taylor, J P; Seigler, S; Snowden, J

1998-10-01

We conducted a 1-year case-control study of sporadic vibrio infections to identify risk factors related to consumption of seafood products in two coastal areas of Louisiana and Texas. Twenty-six persons with sporadic vibrio infections and 77 matched controls were enrolled. Multivariate analysis revealed that crayfish (P < 0.025) and raw oysters (P < 0.009) were independently associated with illness. Species-specific analysis revealed an association between consumption of cooked crayfish and Vibrio parahemolyticus infection (OR 9.24, P < 0.05). No crayfish consumption was reported by persons with V. vulnificus infection. Although crayfish had been suspected as a vehicle for foodborne disease, this is the first time to our knowledge that consumption of cooked crayfish has been demonstrated to be associated with vibrio infection.

Fatty acid composition and its association with chemical and sensory analysis of boar taint.

PubMed

Liu, Xiaoye; Trautmann, Johanna; Wigger, Ruth; Zhou, Guanghong; Mörlein, Daniel

2017-09-15

A certain level of disagreement between the chemical analysis of androstenone and skatole and the human perception of boar taint has been found in many studies. Here we analyze whether the fatty acid composition can explain such inconsistency between sensory evaluation and chemical analysis of boar taint compounds. Therefore, back fat samples (n=143) were selected according to their sensory evaluation by a 10-person sensory panel, and the chemical analysis (stable isotope dilution analysis with headspace solid-phase microextraction and gas chromatography-mass spectrometry) of androstenone and skatole. Subsequently a quantification of fatty acids using gas chromatography-flame ionization detection was conducted. The correlation analyses revealed that several fatty acids are significantly correlated with androstenone, skatole, and the sensory rating. However, multivariate analyses (principal component analysis) revealed no explanation of the fatty acid composition with respect to the (dis-)agreement between sensory and chemical analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of an artificial oyster shell reef on macrobenthic communities in Rongcheng Bay, East China

NASA Astrophysics Data System (ADS)

Xu, Qinzeng; Zhang, Libin; Zhang, Tao; Zhou, Yi; Xia, Sudong; Liu, Hui; Yang, Hongsheng

2014-01-01

An artificial oyster shell reef was deployed in Rongcheng Bay, East China. However, the effects of this reef on the surrounding macrobenthic communities were unknown. We compared sedimentary factors, macrobenthic biomass, abundance, and community composition and ecological indicators between the reef and non-reef areas over a one year period. The mean values for chlorophyll a (Chl a), total organic matter (TOM), total organic carbon (TOC), and total nitrogen (TN) content in surface sediments in the reef area were slightly higher than those in the non-reef area. The Chl a levels differed significantly between the two areas, but the TOM, TOC, and TN were not significantly different. The abundance of crustaceans was significantly different between the two areas, but the abundance and biomass of polychaetes, echinoderms, mollusk did not differ significantly. The permutational multivariate analysis of variance (PERMANOVA) revealed that the macrobenthic community differed significantly through time and analysis of similarity multivariate analyses (ANOSIM) revealed that the macrobenthic community differed significantly in some months. The ecological indicators revealed that the environmental quality of the reef area was slightly better than that of the non-reef area. Overall, our results suggest that the artificial oyster shell reef may change the macrobenthic community and the quality of the environment. Despite the lack of an effect in the short term, long-term monitoring is still needed to evaluate the effects of artificial oyster shell reefs on macrobenthic communities.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

Differentiation between borderline and benign ovarian tumors: combined analysis of MRI with tumor markers for large cystic masses (≥5 cm).

PubMed

Park, Sung Yoon; Oh, Young Taik; Jung, Dae Chul

2016-05-01

There is overlap in imaging features between borderline and benign ovarian tumors. To analyze diagnostic performance of magnetic resonance imaging (MRI) combined with tumor markers for differentiating borderline from benign ovarian tumor. Ninety-nine patient with MRI and surgically confirmed ovarian tumors 5 cm or larger (borderline, n = 37; benign, n = 62) were included. On MRI, tumor size, septal number (0; 1-4; 5 or more), and presence of solid portion such as papillary projection or septal thickening 0.5 cm or larger were investigated. Serum tumor markers (carbohydrate antigen 125 [CA 125] and CA 19-9) were recorded. Multivariate analysis was conducted for assessing whether combined MRI with tumor markers could differentiate borderline from benign tumor. The diagnostic performance was also analyzed. Incidence of solid portion was 67.6% (25/37) in borderline and 3.2% (2/62) in benign tumors (P < 0.05). In all patients, without combined analysis of MRI with tumor markers, multivariate analysis revealed solid portion (P < 0.001) and CA 125 (P = 0.039) were significant for predicting borderline tumors. When combined analysis of MRI with CA 125 ((i) the presence of solid portion or (ii) CA 125 > 44.1 U/mL with septal number ≥5 for borderline tumor) is incorporated to multivariate analysis, it was only significant (P = 0.001). The sensitivity, specificity, PPV, NPV, and accuracy of combined analysis of MRI with CA 125 were 89.1%, 91.9%, 86.8%, 93.4, and 90.9%, respectively. Combined analysis of MRI with CA 125 may allow better differentiation between borderline and benign ovarian tumor compared with MRI alone. © The Foundation Acta Radiologica 2015.

Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data.

PubMed

Levine, Matthew E; Albers, David J; Hripcsak, George

2016-01-01

Time series analysis methods have been shown to reveal clinical and biological associations in data collected in the electronic health record. We wish to develop reliable high-throughput methods for identifying adverse drug effects that are easy to implement and produce readily interpretable results. To move toward this goal, we used univariate and multivariate lagged regression models to investigate associations between twenty pairs of drug orders and laboratory measurements. Multivariate lagged regression models exhibited higher sensitivity and specificity than univariate lagged regression in the 20 examples, and incorporating autoregressive terms for labs and drugs produced more robust signals in cases of known associations among the 20 example pairings. Moreover, including inpatient admission terms in the model attenuated the signals for some cases of unlikely associations, demonstrating how multivariate lagged regression models' explicit handling of context-based variables can provide a simple way to probe for health-care processes that confound analyses of EHR data.

Medial prefrontal aberrations in major depressive disorder revealed by cytoarchitectonically informed voxel-based morphometry

PubMed Central

Bludau, Sebastian; Bzdok, Danilo; Gruber, Oliver; Kohn, Nils; Riedl, Valentin; Sorg, Christian; Palomero-Gallagher, Nicola; Müller, Veronika I.; Hoffstaedter, Felix; Amunts, Katrin; Eickhoff, Simon B.

2017-01-01

Objective The heterogeneous human frontal pole has been identified as a node in the dysfunctional network of major depressive disorder. The contribution of the medial (socio-affective) versus lateral (cognitive) frontal pole to major depression pathogenesis is currently unclear. The present study performs morphometric comparison of the microstructurally informed subdivisions of human frontal pole between depressed patients and controls using both uni- and multivariate statistics. Methods Multi-site voxel- and region-based morphometric MRI analysis of 73 depressed patients and 73 matched controls without psychiatric history. Frontal pole volume was first compared between depressed patients and controls by subdivision-wise classical morphometric analysis. In a second approach, frontal pole volume was compared by subdivision-naive multivariate searchlight analysis based on support vector machines. Results Subdivision-wise morphometric analysis found a significantly smaller medial frontal pole in depressed patients with a negative correlation of disease severity and duration. Histologically uninformed multivariate voxel-wise statistics provided converging evidence for structural aberrations specific to the microstructurally defined medial area of the frontal pole in depressed patients. Conclusions Across disparate methods, we demonstrated subregion specificity in the left medial frontal pole volume in depressed patients. Indeed, the frontal pole was shown to structurally and functionally connect to other key regions in major depression pathology like the anterior cingulate cortex and the amygdala via the uncinate fasciculus. Present and previous findings consolidate the left medial portion of the frontal pole as particularly altered in major depression. PMID:26621569

HPLC-TOF-MS and HPLC-MS/MS combined with multivariate analysis for the characterization and discrimination of phenolic profiles in nonfumigated and sulfur-fumigated rhubarb.

PubMed

Yan, Yan; Zhang, Qianqian; Feng, Fang

2016-07-01

Sulfur fumigation has recently been used during the postharvest handling of rhubarb to reduce the drying duration and control pests. However, a few reports question the effect of sulfur fumigation on the bioactive components of rhubarb, which is crucial for the quality evaluation of the herbal medicine. The bottleneck limiting the study comes from the complex compounds that exist in herb samples with diverse structural features, wide concentration range and the difficulty to obtain all the reference standards. In this study, an integrated strategy based on the highly effective separation and analysis by liquid chromatography coupled with diode-array detection and time-of-flight/triple-quadruple tandem mass spectrometry combined with multivariate analysis was established. 68 phenolic compounds that exist in nonfumigated and sulfur-fumigated herb samples of rhubarb were tentatively assigned based on their retention behavior, UV spectra, accurate molecular weight, and mass spectral fragments. Qualitative and semiquantitative comparison revealed a serious reduction of the majority of phenolic compounds in sulfur-fumigated rhubarb. Furthermore, multivariate analysis was applied to holistically discriminate nonfumigated from sulfur-fumigated rhubarb and explore the characteristic chemical markers. The established approach was specific and rapid for characterizing and screening sulfur-fumigated rhubarb among commercial samples and could be applied for the quality assessment of other sulfur-fumigated herbs. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Understanding and predicting the impact of critical dissolution variables for nifedipine immediate release capsules by multivariate data analysis.

PubMed

Mercuri, A; Pagliari, M; Baxevanis, F; Fares, R; Fotaki, N

2017-02-25

In this study the selection of in vivo predictive in vitro dissolution experimental set-ups using a multivariate analysis approach, in line with the Quality by Design (QbD) principles, is explored. The dissolution variables selected using a design of experiments (DoE) were the dissolution apparatus [USP1 apparatus (basket) and USP2 apparatus (paddle)], the rotational speed of the basket/or paddle, the operator conditions (dissolution apparatus brand and operator), the volume, the pH, and the ethanol content of the dissolution medium. The dissolution profiles of two nifedipine capsules (poorly soluble compound), under conditions mimicking the intake of the capsules with i. water, ii. orange juice and iii. an alcoholic drink (orange juice and ethanol) were analysed using multiple linear regression (MLR). Optimised dissolution set-ups, generated based on the mathematical model obtained via MLR, were used to build predicted in vitro-in vivo correlations (IVIVC). IVIVC could be achieved using physiologically relevant in vitro conditions mimicking the intake of the capsules with an alcoholic drink (orange juice and ethanol). The multivariate analysis revealed that the concentration of ethanol used in the in vitro dissolution experiments (47% v/v) can be lowered to less than 20% v/v, reflecting recently found physiological conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Categorical speech processing in Broca's area: an fMRI study using multivariate pattern-based analysis.

PubMed

Lee, Yune-Sang; Turkeltaub, Peter; Granger, Richard; Raizada, Rajeev D S

2012-03-14

Although much effort has been directed toward understanding the neural basis of speech processing, the neural processes involved in the categorical perception of speech have been relatively less studied, and many questions remain open. In this functional magnetic resonance imaging (fMRI) study, we probed the cortical regions mediating categorical speech perception using an advanced brain-mapping technique, whole-brain multivariate pattern-based analysis (MVPA). Normal healthy human subjects (native English speakers) were scanned while they listened to 10 consonant-vowel syllables along the /ba/-/da/ continuum. Outside of the scanner, individuals' own category boundaries were measured to divide the fMRI data into /ba/ and /da/ conditions per subject. The whole-brain MVPA revealed that Broca's area and the left pre-supplementary motor area evoked distinct neural activity patterns between the two perceptual categories (/ba/ vs /da/). Broca's area was also found when the same analysis was applied to another dataset (Raizada and Poldrack, 2007), which previously yielded the supramarginal gyrus using a univariate adaptation-fMRI paradigm. The consistent MVPA findings from two independent datasets strongly indicate that Broca's area participates in categorical speech perception, with a possible role of translating speech signals into articulatory codes. The difference in results between univariate and multivariate pattern-based analyses of the same data suggest that processes in different cortical areas along the dorsal speech perception stream are distributed on different spatial scales.

Reexamining Sample Size Requirements for Multivariate, Abundance-Based Community Research: When Resources are Limited, the Research Does Not Have to Be.

PubMed

Forcino, Frank L; Leighton, Lindsey R; Twerdy, Pamela; Cahill, James F

2015-01-01

Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, oversampling (too many individuals counted per sample) also comes at a cost, particularly for ecological systems in which identification and quantification is substantially more resource consuming than the field expedition itself. In such systems, an increasingly larger sample size will eventually result in diminishing returns in improving any pattern or gradient revealed by the data, but will also lead to continually increasing costs. Here, we examine 396 datasets: 44 previously published and 352 created datasets. Using meta-analytic and simulation-based approaches, the research within the present paper seeks (1) to determine minimal sample sizes required to produce robust multivariate statistical results when conducting abundance-based, community ecology research. Furthermore, we seek (2) to determine the dataset parameters (i.e., evenness, number of taxa, number of samples) that require larger sample sizes, regardless of resource availability. We found that in the 44 previously published and the 220 created datasets with randomly chosen abundances, a conservative estimate of a sample size of 58 produced the same multivariate results as all larger sample sizes. However, this minimal number varies as a function of evenness, where increased evenness resulted in increased minimal sample sizes. Sample sizes as small as 58 individuals are sufficient for a broad range of multivariate abundance-based research. In cases when resource availability is the limiting factor for conducting a project (e.g., small university, time to conduct the research project), statistically viable results can still be obtained with less of an investment.

Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

PubMed

Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

2014-09-01

Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-05-01

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

Interaction of Soil Heavy Metal Pollution with Industrialisation and the Landscape Pattern in Taiyuan City, China

PubMed Central

Liu, Yong; Su, Chao; Zhang, Hong; Li, Xiaoting; Pei, Jingfei

2014-01-01

Many studies indicated that industrialization and urbanization caused serious soil heavy metal pollution from industrialized age. However, fewer previous studies have conducted a combined analysis of the landscape pattern, urbanization, industrialization, and heavy metal pollution. This paper was aimed at exploring the relationships of heavy metals in the soil (Pb, Cu, Ni, As, Cd, Cr, Hg, and Zn) with landscape pattern, industrialisation, urbanisation in Taiyuan city using multivariate analysis. The multivariate analysis included correlation analysis, analysis of variance (ANOVA), independent-sample T test, and principal component analysis (PCA). Geographic information system (GIS) was also applied to determine the spatial distribution of the heavy metals. The spatial distribution maps showed that the heavy metal pollution of the soil was more serious in the centre of the study area. The results of the multivariate analysis indicated that the correlations among heavy metals were significant, and industrialisation could significantly affect the concentrations of some heavy metals. Landscape diversity showed a significant negative correlation with the heavy metal concentrations. The PCA showed that a two-factor model for heavy metal pollution, industrialisation, and the landscape pattern could effectively demonstrate the relationships between these variables. The model explained 86.71% of the total variance of the data. Moreover, the first factor was mainly loaded with the comprehensive pollution index (P), and the second factor was primarily loaded with landscape diversity and dominance (H and D). An ordination of 80 samples could show the pollution pattern of all the samples. The results revealed that local industrialisation caused heavy metal pollution of the soil, but such pollution could respond negatively to the landscape pattern. The results of the study could provide a basis for agricultural, suburban, and urban planning. PMID:25251460

Interaction of soil heavy metal pollution with industrialisation and the landscape pattern in Taiyuan city, China.

PubMed

Liu, Yong; Su, Chao; Zhang, Hong; Li, Xiaoting; Pei, Jingfei

2014-01-01

Many studies indicated that industrialization and urbanization caused serious soil heavy metal pollution from industrialized age. However, fewer previous studies have conducted a combined analysis of the landscape pattern, urbanization, industrialization, and heavy metal pollution. This paper was aimed at exploring the relationships of heavy metals in the soil (Pb, Cu, Ni, As, Cd, Cr, Hg, and Zn) with landscape pattern, industrialisation, urbanisation in Taiyuan city using multivariate analysis. The multivariate analysis included correlation analysis, analysis of variance (ANOVA), independent-sample T test, and principal component analysis (PCA). Geographic information system (GIS) was also applied to determine the spatial distribution of the heavy metals. The spatial distribution maps showed that the heavy metal pollution of the soil was more serious in the centre of the study area. The results of the multivariate analysis indicated that the correlations among heavy metals were significant, and industrialisation could significantly affect the concentrations of some heavy metals. Landscape diversity showed a significant negative correlation with the heavy metal concentrations. The PCA showed that a two-factor model for heavy metal pollution, industrialisation, and the landscape pattern could effectively demonstrate the relationships between these variables. The model explained 86.71% of the total variance of the data. Moreover, the first factor was mainly loaded with the comprehensive pollution index (P), and the second factor was primarily loaded with landscape diversity and dominance (H and D). An ordination of 80 samples could show the pollution pattern of all the samples. The results revealed that local industrialisation caused heavy metal pollution of the soil, but such pollution could respond negatively to the landscape pattern. The results of the study could provide a basis for agricultural, suburban, and urban planning.

Stature and jumping height are required in female volleyball, but motor coordination is a key factor for future elite success.

PubMed

Pion, Johan A; Fransen, Job; Deprez, Dieter N; Segers, Veerle I; Vaeyens, Roel; Philippaerts, Renaat M; Lenoir, Matthieu

2015-06-01

It was hypothesized that differences in anthropometry, physical performance, and motor coordination would be found between Belgian elite and sub-elite level female volleyball players using a retrospective analysis of test results gathered over a 5-year period. The test sample in this study consisted of 21 young female volleyball players (15.3 ± 1.5 years) who were selected to train at the Flemish Top Sports Academy for Volleyball in 2008. All players (elite, n = 13; sub-elite, n = 8) were included in the same talent development program, and the elite-level athletes were of a high to very high performance levels according to European competition level in 2013. Five multivariate analyses of variance were used. There was no significant effect of playing level on measures of anthropometry (F = 0.455, p = 0.718, (Equation is included in full-text article.)= 0.07), flexibility (F = 1.861, p = 0.188, (Equation is included in full-text article.)= 0.19), strength (F = 1.218, p = 0.355, (Equation is included in full-text article.)= 0.32); and speed and agility (F = 1.176, p = 0.350, (Equation is included in full-text article.)= 0.18). Multivariate analyses of variance revealed significant multivariate effects between playing levels for motor coordination (F = 3.470, p = 0.036, (Equation is included in full-text article.)= 0.59). A Mann-Whitney U test and a sequential discriminant analysis confirmed these results. Previous research revealed that stature and jump height are prerequisites for talent identification in female volleyball. In addition, the results show that motor coordination is an important factor in determining inclusion into the elite level in female volleyball.

Multiple expression patterns of biopathological markers in primary invasive breast carcinoma: a useful tool for elucidating its biological behaviour.

PubMed

Ceccarelli, C; Santini, D; Chieco, P; Taffurelli, M; Marrano, D; Mancini, A M

1995-03-01

Commonly used clinical and morphologic criteria have been reported to be of limited value in predicting the outcome of malignant tumours of the breast. Integrated information from the quantitative analysis in tumour tissue of biological parameters such as oestrogen and progesterone receptors (ER and PGR), proliferative activity, and proto-oncogene p53, c-erB2, and bcl-2 expression, may be useful for defining the biology of growth of breast carcinoma and to plan effective therapeutic strategies. Immunohistochemistry with antibodies recognizing ER, PGR, Ki-67, and the p53, c-erbB2, and bcl-2 encoded proteins was performed on 291 primary breast carcinomas. Results were integrated with clinico-pathological indicators and examined with multivariate statistical procedures and modeling. P53, c-erbB2, and bcl-2 gene products were detected, respectively, in 30.6%, 31.6%, and 85.9% of the examined invasive breast carcinomas, revealing variable associations with cellular differentiation and proliferation as defined by ER/PGR status, Ki-67, tumour mass and histologic and nuclear grading. A multivariate graphical display on a subset of the most informative cases revealed that bcl-2 expression parallels ER/PGR status and is of importance in separating tumour clusters with different degrees of aggressiveness. The results of this study indicate that multivariate explorative analyses conducted on biological and clinico-pathological parameters might constitute an integrated approach to data analysis useful for distinguishing different biological behaviours and therapeutic groups in breast carcinoma. Our findings also suggest that bcl-2 expression may play a pivotal role in tumours lacking ER-mediated growth regulation.

Influence of Time-Series Normalization, Number of Nodes, Connectivity and Graph Measure Selection on Seizure-Onset Zone Localization from Intracranial EEG.

PubMed

van Mierlo, Pieter; Lie, Octavian; Staljanssens, Willeke; Coito, Ana; Vulliémoz, Serge

2018-04-26

We investigated the influence of processing steps in the estimation of multivariate directed functional connectivity during seizures recorded with intracranial EEG (iEEG) on seizure-onset zone (SOZ) localization. We studied the effect of (i) the number of nodes, (ii) time-series normalization, (iii) the choice of multivariate time-varying connectivity measure: Adaptive Directed Transfer Function (ADTF) or Adaptive Partial Directed Coherence (APDC) and (iv) graph theory measure: outdegree or shortest path length. First, simulations were performed to quantify the influence of the various processing steps on the accuracy to localize the SOZ. Afterwards, the SOZ was estimated from a 113-electrodes iEEG seizure recording and compared with the resection that rendered the patient seizure-free. The simulations revealed that ADTF is preferred over APDC to localize the SOZ from ictal iEEG recordings. Normalizing the time series before analysis resulted in an increase of 25-35% of correctly localized SOZ, while adding more nodes to the connectivity analysis led to a moderate decrease of 10%, when comparing 128 with 32 input nodes. The real-seizure connectivity estimates localized the SOZ inside the resection area using the ADTF coupled to outdegree or shortest path length. Our study showed that normalizing the time-series is an important pre-processing step, while adding nodes to the analysis did only marginally affect the SOZ localization. The study shows that directed multivariate Granger-based connectivity analysis is feasible with many input nodes (> 100) and that normalization of the time-series before connectivity analysis is preferred.

Multivariable Regression Analysis in Schistosoma mansoni-Infected Individuals in the Sudan Reveals Unique Immunoepidemiological Profiles in Uninfected, egg+ and Non-egg+ Infected Individuals.

PubMed

Elfaki, Tayseer Elamin Mohamed; Arndts, Kathrin; Wiszniewsky, Anna; Ritter, Manuel; Goreish, Ibtisam A; Atti El Mekki, Misk El Yemen A; Arriens, Sandra; Pfarr, Kenneth; Fimmers, Rolf; Doenhoff, Mike; Hoerauf, Achim; Layland, Laura E

2016-05-01

In the Sudan, Schistosoma mansoni infections are a major cause of morbidity in school-aged children and infection rates are associated with available clean water sources. During infection, immune responses pass through a Th1 followed by Th2 and Treg phases and patterns can relate to different stages of infection or immunity. This retrospective study evaluated immunoepidemiological aspects in 234 individuals (range 4-85 years old) from Kassala and Khartoum states in 2011. Systemic immune profiles (cytokines and immunoglobulins) and epidemiological parameters were surveyed in n = 110 persons presenting patent S. mansoni infections (egg+), n = 63 individuals positive for S. mansoni via PCR in sera but egg negative (SmPCR+) and n = 61 people who were infection-free (Sm uninf). Immunoepidemiological findings were further investigated using two binary multivariable regression analysis. Nearly all egg+ individuals had no access to latrines and over 90% obtained water via the canal stemming from the Atbara River. With regards to age, infection and an egg+ status was linked to young and adolescent groups. In terms of immunology, S. mansoni infection per se was strongly associated with increased SEA-specific IgG4 but not IgE levels. IL-6, IL-13 and IL-10 were significantly elevated in patently-infected individuals and positively correlated with egg load. In contrast, IL-2 and IL-1β were significantly lower in SmPCR+ individuals when compared to Sm uninf and egg+ groups which was further confirmed during multivariate regression analysis. Schistosomiasis remains an important public health problem in the Sudan with a high number of patent individuals. In addition, SmPCR diagnostics revealed another cohort of infected individuals with a unique immunological profile and provides an avenue for future studies on non-patent infection states. Future studies should investigate the downstream signalling pathways/mechanisms of IL-2 and IL-1β as potential diagnostic markers in order to distinguish patent from non-patent individuals.

Integration of community structure data reveals observable effects below sediment guideline thresholds in a large estuary.

PubMed

Tremblay, Louis A; Clark, Dana; Sinner, Jim; Ellis, Joanne I

2017-09-20

The sustainable management of estuarine and coastal ecosystems requires robust frameworks due to the presence of multiple physical and chemical stressors. In this study, we assessed whether ecological health decline, based on community structure composition changes along a pollution gradient, occurred at levels below guideline threshold values for copper, zinc and lead. Canonical analysis of principal coordinates (CAP) was used to characterise benthic communities along a metal contamination gradient. The analysis revealed changes in benthic community distribution at levels below the individual guideline values for the three metals. These results suggest that field-based measures of ecological health analysed with multivariate tools can provide additional information to single metal guideline threshold values to monitor large systems exposed to multiple stressors.

Multivariate analysis in thoracic research.

PubMed

Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

2015-03-01

Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

Multivariate analysis of variance of designed chromatographic data. A case study involving fermentation of rooibos tea.

PubMed

Marini, Federico; de Beer, Dalene; Walters, Nico A; de Villiers, André; Joubert, Elizabeth; Walczak, Beata

2017-03-17

An ultimate goal of investigations of rooibos plant material subjected to different stages of fermentation is to identify the chemical changes taking place in the phenolic composition, using an untargeted approach and chromatographic fingerprints. Realization of this goal requires, among others, identification of the main components of the plant material involved in chemical reactions during the fermentation process. Quantitative chromatographic data for the compounds for extracts of green, semi-fermented and fermented rooibos form the basis of preliminary study following a targeted approach. The aim is to estimate whether treatment has a significant effect based on all quantified compounds and to identify the compounds, which contribute significantly to it. Analysis of variance is performed using modern multivariate methods such as ANOVA-Simultaneous Component Analysis, ANOVA - Target Projection and regularized MANOVA. This study is the first one in which all three approaches are compared and evaluated. For the data studied, all tree methods reveal the same significance of the fermentation effect on the extract compositions, but they lead to its different interpretation. Copyright © 2017 Elsevier B.V. All rights reserved.

The Japanese Histologic Classification and T-score in the Oxford Classification system could predict renal outcome in Japanese IgA nephropathy patients.

PubMed

Kaihan, Ahmad Baseer; Yasuda, Yoshinari; Katsuno, Takayuki; Kato, Sawako; Imaizumi, Takahiro; Ozeki, Takaya; Hishida, Manabu; Nagata, Takanobu; Ando, Masahiko; Tsuboi, Naotake; Maruyama, Shoichi

2017-12-01

The Oxford Classification is utilized globally, but has not been fully validated. In this study, we conducted a comparative analysis between the Oxford Classification and Japanese Histologic Classification (JHC) to predict renal outcome in Japanese patients with IgA nephropathy (IgAN). A retrospective cohort study including 86 adult IgAN patients was conducted. The Oxford Classification and the JHC were evaluated by 7 independent specialists. The JHC, MEST score in the Oxford Classification, and crescents were analyzed in association with renal outcome, defined as a 50% increase in serum creatinine. In multivariate analysis without the JHC, only the T score was significantly associated with renal outcome. While, a significant association was revealed only in the JHC on multivariate analysis with JHC. The JHC and T score in the Oxford Classification were associated with renal outcome among Japanese patients with IgAN. Superiority of the JHC as a predictive index should be validated with larger study population and cohort studies in different ethnicities.

Impact of hospital transfer on surgical outcomes of intestinal atresia.

PubMed

Erickson, T; Vana, P G; Blanco, B A; Brownlee, S A; Paddock, H N; Kuo, P C; Kothari, A N

2017-03-01

Examine effects of hospital transfer into a quaternary care center on surgical outcomes of intestinal atresia. Children <1 yo principally diagnosed with intestinal atresia were identified using the Kids' Inpatient Database (2012). Exposure variable was patient transfer status. Outcomes measured were inpatient mortality, hospital length of stay (LOS) and discharge status. Linearized standard errors, design-based F tests, and multivariable logistic regression were performed. 1672 weighted discharges represented a national cohort. The highest income group and those with private insurance had significantly lower odds of transfer (OR:0.53 and 0.74, p < 0.05). Rural patients had significantly higher transfer rates (OR: 2.73, p < 0.05). Multivariate analysis revealed no difference in mortality (OR:0.71, p = 0.464) or non-home discharge (OR: 0.79, p = 0.166), but showed prolonged LOS (OR:1.79, p < 0.05) amongst transferred patients. Significant differences in hospital LOS and treatment access reveal a potential healthcare gap. Post-acute care resources should be improved for transferred patients. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

Predictors of obesity in Michigan Operating Engineers.

PubMed

Duffy, Sonia A; Cohen, Kathleen A; Choi, Seung Hee; McCullagh, Marjorie C; Noonan, Devon

2012-06-01

Blue collar workers are at risk for obesity. Little is known about obesity in Operating Engineers, a group of blue collar workers, who operate heavy earth-moving equipment in road building and construction. Therefore, 498 Operating Engineers in Michigan were recruited to participate in a cross-sectional survey to determine variables related to obesity in this group. Bivariate and multivariate analyses were conducted to determine personal, psychological, and behavioral factors predicting obesity. Approximately 45% of the Operating Engineers screened positive for obesity, and another 40% were overweight. Multivariate analysis revealed that younger age, male sex, higher numbers of self-reported co-morbidities, not smoking, and low physical activity levels were significantly associated with obesity among Operating Engineers. Operating Engineers are significantly at risk for obesity, and workplace interventions are needed to address this problem.

Estimation and Psychometric Analysis of Component Profile Scores via Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

Extraction, isolation, and purification of analytes from samples of marine origin--a multivariate task.

PubMed

Liguori, Lucia; Bjørsvik, Hans-René

2012-12-01

The development of a multivariate study for a quantitative analysis of six different polybrominated diphenyl ethers (PBDEs) in tissue of Atlantic Salmo salar L. is reported. An extraction, isolation, and purification process based on an accelerated solvent extraction system was designed, investigated, and optimized by means of statistical experimental design and multivariate data analysis and regression. An accompanying gas chromatography-mass spectrometry analytical method was developed for the identification and quantification of the analytes, BDE 28, BDE 47, BDE 99, BDE 100, BDE 153, and BDE 154. These PBDEs have been used in commercial blends that were used as flame-retardants for a variety of materials, including electronic devices, synthetic polymers and textiles. The present study revealed that an extracting solvent mixture composed of hexane and CH₂Cl₂ (10:90) provided excellent recoveries of all of the six PBDEs studied herein. A somewhat lower polarity in the extracting solvent, hexane and CH₂Cl₂ (40:60) decreased the analyte %-recoveries, which still remain acceptable and satisfactory. The study demonstrates the necessity to perform an intimately investigation of the extraction and purification process in order to achieve quantitative isolation of the analytes from the specific matrix. Copyright © 2012 Elsevier B.V. All rights reserved.

Label-free Chemical Imaging of Fungal Spore Walls by Raman Microscopy and Multivariate Curve Resolution Analysis

PubMed Central

Noothalapati, Hemanth; Sasaki, Takahiro; Kaino, Tomohiro; Kawamukai, Makoto; Ando, Masahiro; Hamaguchi, Hiro-o; Yamamoto, Tatsuyuki

2016-01-01

Fungal cell walls are medically important since they represent a drug target site for antifungal medication. So far there is no method to directly visualize structurally similar cell wall components such as α-glucan, β-glucan and mannan with high specificity, especially in a label-free manner. In this study, we have developed a Raman spectroscopy based molecular imaging method and combined multivariate curve resolution analysis to enable detection and visualization of multiple polysaccharide components simultaneously at the single cell level. Our results show that vegetative cell and ascus walls are made up of both α- and β-glucans while spore wall is exclusively made of α-glucan. Co-localization studies reveal the absence of mannans in ascus wall but are distributed primarily in spores. Such detailed picture is believed to further enhance our understanding of the dynamic spore wall architecture, eventually leading to advancements in drug discovery and development in the near future. PMID:27278218

Image-based compound profiling reveals a dual inhibitor of tyrosine kinase and microtubule polymerization.

PubMed

Tanabe, Kenji

2016-04-27

Small-molecule compounds are widely used as biological research tools and therapeutic drugs. Therefore, uncovering novel targets of these compounds should provide insights that are valuable in both basic and clinical studies. I developed a method for image-based compound profiling by quantitating the effects of compounds on signal transduction and vesicle trafficking of epidermal growth factor receptor (EGFR). Using six signal transduction molecules and two markers of vesicle trafficking, 570 image features were obtained and subjected to multivariate analysis. Fourteen compounds that affected EGFR or its pathways were classified into four clusters, based on their phenotypic features. Surprisingly, one EGFR inhibitor (CAS 879127-07-8) was classified into the same cluster as nocodazole, a microtubule depolymerizer. In fact, this compound directly depolymerized microtubules. These results indicate that CAS 879127-07-8 could be used as a chemical probe to investigate both the EGFR pathway and microtubule dynamics. The image-based multivariate analysis developed herein has potential as a powerful tool for discovering unexpected drug properties.

NMR Spectroscopy Identifies Metabolites Translocated from Powdery Mildew Resistant Rootstocks to Susceptible Watermelon Scions.

PubMed

Mahmud, Iqbal; Kousik, Chandrasekar; Hassell, Richard; Chowdhury, Kamal; Boroujerdi, Arezue F

2015-09-16

Powdery mildew (PM) disease causes significant loss in watermelon. Due to the unavailability of a commercial watermelon variety that is resistant to PM, grafting susceptible cultivars on wild resistant rootstocks is being explored as a short-term management strategy to combat this disease. Nuclear magnetic resonance-based metabolic profiles of susceptible and resistant rootstocks of watermelon and their corresponding susceptible scions (Mickey Lee) were compared to screen for potential metabolites related to PM resistance using multivariate principal component analysis. Significant score plot differences between the susceptible and resistant groups were revealed through Mahalanobis distance analysis. Significantly different spectral buckets and their corresponding metabolites (including choline, fumarate, 5-hydroxyindole-3-acetate, and melatonin) have been identified quantitatively using multivariate loading plots and verified by volcano plot analyses. The data suggest that these metabolites were translocated from the powdery mildew resistant rootstocks to their corresponding powdery mildew susceptible scions and can be related to PM disease resistance.

Towards the authentication of European sea bass origin through a combination of biometric measurements and multiple analytical techniques.

PubMed

Farabegoli, Federica; Pirini, Maurizio; Rotolo, Magda; Silvi, Marina; Testi, Silvia; Ghidini, Sergio; Zanardi, Emanuela; Remondini, Daniel; Bonaldo, Alessio; Parma, Luca; Badiani, Anna

2018-06-08

The authenticity of fish products has become an imperative issue for authorities involved in the protection of consumers against fraudulent practices and in the market stabilization. The present study aimed to provide a method for authentication of European sea bass (Dicentrarchus labrax) according to the requirements for seafood labels (Regulation 1379/2013/EU). Data on biometric traits, fatty acid profile, elemental composition, and isotopic abundance of wild and reared (intensively, semi-intensively and extensively) specimens from 18 Southern European sources (n = 160) were collected and clustered in 6 sets of parameters, then subjected to multivariate analysis. Correct allocations of subjects according to their production method, origin and stocking density were demonstrated with good approximation rates (94%, 92% and 92%, respectively) using fatty acid profiles. Less satisfying results were obtained using isotopic abundance, biometric traits, and elemental composition. The multivariate analysis also revealed that extensively reared subjects cannot be analytically discriminated from wild ones.

Biometrics from the carbon isotope ratio analysis of amino acids in human hair.

PubMed

Jackson, Glen P; An, Yan; Konstantynova, Kateryna I; Rashaid, Ayat H B

2015-01-01

This study compares and contrasts the ability to classify individuals into different grouping factors through either bulk isotope ratio analysis or amino-acid-specific isotope ratio analysis of human hair. Using LC-IRMS, we measured the isotope ratios of 14 amino acids in hair proteins independently, and leucine/isoleucine as a co-eluting pair, to provide 15 variables for classification. Multivariate analysis confirmed that the essential amino acids and non-essential amino acids were mostly independent variables in the classification rules, thereby enabling the separation of dietary factors of isotope intake from intrinsic or phenotypic factors of isotope fractionation. Multivariate analysis revealed at least two potential sources of non-dietary factors influencing the carbon isotope ratio values of the amino acids in human hair: body mass index (BMI) and age. These results provide evidence that compound-specific isotope ratio analysis has the potential to go beyond region-of-origin or geospatial movements of individuals-obtainable through bulk isotope measurements-to the provision of physical and characteristic traits about the individuals, such as age and BMI. Further development and refinement, for example to genetic, metabolic, disease and hormonal factors could ultimately be of great assistance in forensic and clinical casework. Copyright © 2014 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

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

Evaluation of volatile metabolites as markers in Lycopersicon esculentum L. cultivars discrimination by multivariate analysis of headspace solid phase microextraction and mass spectrometry data.

PubMed

Figueira, José; Câmara, Hugo; Pereira, Jorge; Câmara, José S

2014-02-15

To gain insights on the effects of cultivar on the volatile metabolomic expression of different tomato (Lycopersicon esculentum L.) cultivars--Plum, Campari, Grape, Cherry and Regional, cultivated under similar edafoclimatic conditions, and to identify the most discriminate volatile marker metabolites related to the cultivar, the chromatographic profiles resulting from headspace solid phase microextraction (HS-SPME) and gas chromatography-mass spectrometry (GC-qMS) analysis, combined with multivariate analysis were investigated. The data set composed by the 77 volatile metabolites identified in the target tomato cultivars, 5 of which (2,2,6-trimethylcyclohexanone, 2-methyl-6-methyleneoctan-2-ol, 4-octadecyl-morpholine, (Z)-methyl-3-hexenoate and 3-octanone) are reported for the first time in tomato volatile metabolomic composition, was evaluated by chemometrics. Firstly, principal component analysis was carried out in order to visualise data trends and clusters, and then, linear discriminant analysis in order to detect the set of volatile metabolites able to differentiate groups according to tomato cultivars. The results obtained revealed a perfect discrimination between the different Lycopersicon esculentum L. cultivars considered. The assignment success rate was 100% in classification and 80% in prediction ability by using "leave-one-out" cross-validation procedure. The volatile profile was able to differentiate all five cultivars and revealed complex interactions between them including the participation in the same biosynthetic pathway. The volatile metabolomic platform for tomato samples obtained by HS-SPME/GC-qMS here described, and the interrelationship detected among the volatile metabolites can be used as a roadmap for biotechnological applications, namely to improve tomato aroma and their acceptance in the final consumer, and for traceability studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Partial Least Squares Calibration Modeling Towards the Multivariate Limit of Detection for Enriched Isotopic Mixtures via Laser Ablation Molecular Isotopic Spectroscopy

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

Harris, Candace; Profeta, Luisa; Akpovo, Codjo

The psuedo univariate limit of detection was calculated to compare to the multivariate interval. ompared with results from the psuedounivariate LOD, the multivariate LOD includes other factors (i.e. signal uncertainties) and the reveals the significance in creating models that not only use the analyte’s emission line but also its entire molecular spectra.

Raman Spectroscopy Reveals New Insights into the Zonal Organization of Native and Tissue-Engineered Articular Cartilage

PubMed Central

2016-01-01

Tissue architecture is intimately linked with its functions, and loss of tissue organization is often associated with pathologies. The intricate depth-dependent extracellular matrix (ECM) arrangement in articular cartilage is critical to its biomechanical functions. In this study, we developed a Raman spectroscopic imaging approach to gain new insight into the depth-dependent arrangement of native and tissue-engineered articular cartilage using bovine tissues and cells. Our results revealed previously unreported tissue complexity into at least six zones above the tidemark based on a principal component analysis and k-means clustering analysis of the distribution and orientation of the main ECM components. Correlation of nanoindentation and Raman spectroscopic data suggested that the biomechanics across the tissue depth are influenced by ECM microstructure rather than composition. Further, Raman spectroscopy together with multivariate analysis revealed changes in the collagen, glycosaminoglycan, and water distributions in tissue-engineered constructs over time. These changes were assessed using simple metrics that promise to instruct efforts toward the regeneration of a broad range of tissues with native zonal complexity and functional performance. PMID:28058277

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Correlation between species-specific metabolite profiles and bioactivities of blueberries (Vaccinium spp.).

PubMed

Lee, Sarah; Jung, Eun Sung; Do, Seon-Gil; Jung, Ga-Young; Song, Gwanpil; Song, Jung-Min; Lee, Choong Hwan

2014-03-05

Metabolite profiling of three blueberry species (Vaccinium bracteatum Thunb., V. oldhamii Miquel., and V. corymbosum L.) was performed using gas chromatography-time-of-flight-mass spectrometry (GC-TOF-MS) and ultraperformance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS) combined multivariate analysis. Partial least-squares discriminant analysis clearly showed metabolic differences among species. GC-TOF-MS analysis revealed significant differences in amino acids, organic acids, fatty acids, sugars, and phenolic acids among the three blueberry species. UPLC-Q-TOF-MS analysis indicated that anthocyanins were the major metabolites distinguishing V. bracteatum from V. oldhamii. The contents of anthocyanins such as glycosides of cyanidin were high in V. bracteatum, while glycosides of delphinidin, petunidin, and malvidin were high in V. oldhamii. Antioxidant activities assessed using ABTS and DPPH assays showed the greatest activity in V. oldhamii and revealed the highest correlation with total phenolic, total flavonoid, and total anthocyanin contents and their metabolites.

Revealing representational content with pattern-information fMRI--an introductory guide.

PubMed

Mur, Marieke; Bandettini, Peter A; Kriegeskorte, Nikolaus

2009-03-01

Conventional statistical analysis methods for functional magnetic resonance imaging (fMRI) data are very successful at detecting brain regions that are activated as a whole during specific mental activities. The overall activation of a region is usually taken to indicate involvement of the region in the task. However, such activation analysis does not consider the multivoxel patterns of activity within a brain region. These patterns of activity, which are thought to reflect neuronal population codes, can be investigated by pattern-information analysis. In this framework, a region's multivariate pattern information is taken to indicate representational content. This tutorial introduction motivates pattern-information analysis, explains its underlying assumptions, introduces the most widespread methods in an intuitive way, and outlines the basic sequence of analysis steps.

Diet of diamondback terrapins (Malaclemys terrapin) in subtropical mangrove habitats in South Florida

USGS Publications Warehouse

Denton, Mathew J.; Hart, Kristen M.; Demopoulos, Amanda W.J.; Oleinik, Anton; Baldwin, John N.

2016-01-01

Unique among turtles as the only exclusively estuarine species, the diamondback terrapin’s (Malaclemys terrapin) life history predisposes it to impacts from humans both on land and in the near-shore environment. Terrapins are found in salt marshes and mangroves along the Atlantic and Gulf coasts from Massachusetts to Texas. Whereas previous dietary studies have elucidated terrapins’ role in temperate salt marsh food webs, food resources for terrapins inhabiting subtropical mangrove habitats have not been studied. We examined dietary resource use for diamondback terrapins in subtropical mangrove creek and island habitats within Everglades National Park, Florida, to determine foraging strategies of terrapins inhabiting south Florida (SF) mangrove systems. Fecal analysis revealed 6 categories of food items, with gastropods, crabs, and bivalves being the dominant food items. Multivariate analysis revealed differences in food sources based on habitat more so than by terrapin size class. Our results revealed that like their counterparts in temperate salt marshes, SF terrapins consume similar prey categories but with different species and abundances comprising each category.

Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra.

PubMed

Martyna, Agnieszka; Zadora, Grzegorz; Neocleous, Tereza; Michalska, Aleksandra; Dean, Nema

2016-08-10

Many chemometric tools are invaluable and have proven effective in data mining and substantial dimensionality reduction of highly multivariate data. This becomes vital for interpreting various physicochemical data due to rapid development of advanced analytical techniques, delivering much information in a single measurement run. This concerns especially spectra, which are frequently used as the subject of comparative analysis in e.g. forensic sciences. In the presented study the microtraces collected from the scenarios of hit-and-run accidents were analysed. Plastic containers and automotive plastics (e.g. bumpers, headlamp lenses) were subjected to Fourier transform infrared spectrometry and car paints were analysed using Raman spectroscopy. In the forensic context analytical results must be interpreted and reported according to the standards of the interpretation schemes acknowledged in forensic sciences using the likelihood ratio approach. However, for proper construction of LR models for highly multivariate data, such as spectra, chemometric tools must be employed for substantial data compression. Conversion from classical feature representation to distance representation was proposed for revealing hidden data peculiarities and linear discriminant analysis was further applied for minimising the within-sample variability while maximising the between-sample variability. Both techniques enabled substantial reduction of data dimensionality. Univariate and multivariate likelihood ratio models were proposed for such data. It was shown that the combination of chemometric tools and the likelihood ratio approach is capable of solving the comparison problem of highly multivariate and correlated data after proper extraction of the most relevant features and variance information hidden in the data structure. Copyright © 2016 Elsevier B.V. All rights reserved.

Predictive impact of polymorphism of PNPLA3 on HCC development after interferon therapy in Japanese patients with chronic hepatitis C.

PubMed

Moritou, Yuki; Ikeda, Fusao; Iwasaki, Yoshiaki; Baba, Nobuyuki; Takaguchi, Kouichi; Senoh, Tomonori; Nagano, Takuya; Takeuchi, Yasuto; Yasunaka, Tetsuya; Ohnishi, Hideki; Miyake, Yasuhiro; Takaki, Akinobu; Nouso, Kazuhiro; Yamamoto, Kazuhide

2013-12-01

The impact of single-nucleotide polymorphisms (SNP) of patatin-like phospholipase domain-containing protein 3 (PNPLA3) on development of hepatocellular carcinoma (HCC) is not clarified for Japanese patients with chronic hepatitis C. The present study investigated the associations of rs738409 PNPLA3 with HCC development after the antiviral therapy with peg-interferon and ribavirin for Japanese patients with hepatitis C virus serotype 1 and high viral load. Of the 271 patients enrolled in the study, 20 patients developed HCC, during a median follow-up period of 4.6 years. Multivariate analysis in the proportional hazards models revealed that sex, body mass index, platelet counts, and alpha feroprotein (AFP) had significant associations with HCC development (p = 0.011, 0.029, 0.0002, and 0.046, respectively). Multivariate regression analysis revealed that PNPLA3 148 M was significantly associated with serum AFP level (p = 0.032), other than body mass index, platelet count, and alanine aminotransferase (p = 0.0006, 0.0002, and 0.037, respectively), and that serum AFP level was significantly associated with PNPLA3 148 M (p = 0.017). Serum AFP level is an important factor in predicting HCC development after the antiviral therapy for Japanese patients with chronic hepatitis C, the mechanism of which might involve its significant associations with the SNP genotype of PNPLA3.

Diagnostic value of history and physical examination in patients suspected of lumbosacral nerve root compression

PubMed Central

Vroomen, P; de Krom, M C T F M; Wilmink, J; Kester, A; Knottnerus, J

2002-01-01

Objective: To evaluate patient characteristics, symptoms, and examination findings in the clinical diagnosis of lumbosacral nerve root compression causing sciatica. Methods: The study involved 274 patients with pain radiating into the leg. All had a standardised clinical assessment and magnetic resonance (MR) imaging. The associations between patient characteristics, clinical findings, and lumbosacral nerve root compression on MR imaging were analysed. Results: Nerve root compression was associated with three patient characteristics, three symptoms, and four physical examination findings (paresis, absence of tendon reflexes, a positive straight leg raising test, and increased finger-floor distance). Multivariate analysis, analysing the independent diagnostic value of the tests, showed that nerve root compression was predicted by two patient characteristics, four symptoms, and two signs (increased finger-floor distance and paresis). The straight leg raise test was not predictive. The area under the curve of the receiver-operating characteristic was 0.80 for the history items. It increased to 0.83 when the physical examination items were added. Conclusions: Various clinical findings were found to be associated with nerve root compression on MR imaging. While this set of findings agrees well with those commonly used in daily practice, the tests tended to have lower sensitivity and specificity than previously reported. Stepwise multivariate analysis showed that most of the diagnostic information revealed by physical examination findings had already been revealed by the history items. PMID:11971050

Distinct roles of cell wall biogenesis in yeast morphogenesis as revealed by multivariate analysis of high-dimensional morphometric data

PubMed Central

Okada, Hiroki; Ohnuki, Shinsuke; Roncero, Cesar; Konopka, James B.; Ohya, Yoshikazu

2014-01-01

The cell wall of budding yeast is a rigid structure composed of multiple components. To thoroughly understand its involvement in morphogenesis, we used the image analysis software CalMorph to quantitatively analyze cell morphology after treatment with drugs that inhibit different processes during cell wall synthesis. Cells treated with cell wall–affecting drugs exhibited broader necks and increased morphological variation. Tunicamycin, which inhibits the initial step of N-glycosylation of cell wall mannoproteins, induced morphologies similar to those of strains defective in α-mannosylation. The chitin synthase inhibitor nikkomycin Z induced morphological changes similar to those of mutants defective in chitin transglycosylase, possibly due to the critical role of chitin in anchoring the β-glucan network. To define the mode of action of echinocandin B, a 1,3-β-glucan synthase inhibitor, we compared the morphology it induced with mutants of Fks1 that contains the catalytic domain for 1,3-β-glucan synthesis. Echinocandin B exerted morphological effects similar to those observed in some fks1 mutants, with defects in cell polarity and reduced glucan synthesis activity, suggesting that echinocandin B affects not only 1,3-β-glucan synthesis, but also another functional domain. Thus our multivariate analyses reveal discrete functions of cell wall components and increase our understanding of the pharmacology of antifungal drugs. PMID:24258022

Multivariate Analysis of the Cotton Seed Ionome Reveals a Shared Genetic Architecture

PubMed Central

Pauli, Duke; Ziegler, Greg; Ren, Min; Jenks, Matthew A.; Hunsaker, Douglas J.; Zhang, Min; Baxter, Ivan; Gore, Michael A.

2018-01-01

To mitigate the effects of heat and drought stress, a better understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in a hot, arid environment. The elemental concentrations (ionome) of seed samples from the population were profiled in addition to those of soil samples taken from throughout the field site to better model environmental variation. The elements profiled in seeds exhibited moderate to high heritabilities, as well as strong phenotypic and genotypic correlations between elements that were not altered by the imposed irrigation regimes. Quantitative trait loci (QTL) mapping results from a Bayesian classification method identified multiple genomic regions where QTL for individual elements colocalized, suggesting that genetic control of the ionome is highly interrelated. To more fully explore this genetic architecture, multivariate QTL mapping was implemented among groups of biochemically related elements. This analysis revealed both additional and pleiotropic QTL responsible for coordinated control of phenotypic variation for elemental accumulation. Machine learning algorithms that utilized only ionomic data predicted the irrigation regime under which genotypes were evaluated with very high accuracy. Taken together, these results demonstrate the extent to which the seed ionome is genetically interrelated and predictive of plant physiological responses to adverse environmental conditions. PMID:29437829

Interpreting Popov criteria in Lure´ systems with complex scaling stability analysis

NASA Astrophysics Data System (ADS)

Zhou, J.

2018-06-01

The paper presents a novel frequency-domain interpretation of Popov criteria for absolute stability in Lure´ systems by means of what we call complex scaling stability analysis. The complex scaling technique is developed for exponential/asymptotic stability in LTI feedback systems, which dispenses open-loop poles distribution, contour/locus orientation and prior frequency sweeping. Exploiting the technique for alternatively revealing positive realness of transfer functions, re-interpreting Popov criteria is explicated. More specifically, the suggested frequency-domain stability conditions are conformable both in scalar and multivariable cases, and can be implemented either graphically with locus plotting or numerically without; in particular, the latter is suitable as a design tool with auxiliary parameter freedom. The interpretation also reveals further frequency-domain facts about Lure´ systems. Numerical examples are included to illustrate the main results.

Inflammation-based prognostic score is a novel predictor of postoperative outcome in patients with colorectal cancer.

PubMed

Ishizuka, Mitsuru; Nagata, Hitoshi; Takagi, Kazutoshi; Horie, Toru; Kubota, Keiichi

2007-12-01

To investigate the significance of preoperative Glasgow prognostic score (GPS) for postoperative prognostication of patients with colorectal cancer. Recent studies have revealed that the GPS, an inflammation-based prognostic score that includes only C-reactive protein (CRP) and albumin, is a useful tool for predicting postoperative outcome in cancer patients. However, few studies have investigated the GPS in the field of colorectal surgery. The GPS was calculated on the basis of admission data as follows: patients with an elevated level of both CRP (>10 mg/L) and hypoalbuminemia (Alb <35 g/L) were allocated a score of 2, and patients showing 1 or none of these blood chemistry abnormalities were allocated a score of 1 or 0, respectively. Prognostic significance was analyzed by univariate and multivariate analyses. A total of 315 patients were evaluated. Kaplan-Meier analysis and log-rank test revealed that a higher GPS predicted a higher risk of postoperative mortality (P < 0.01). Univariate analyses revealed that postoperative TNM was the most sensitive predictor of postoperative mortality (odds ratio, 0.148; 95% confidence interval, 0.072-0.304; P < 0.0001). Multivariate analyses using factors such as age, sex, tumor site, serum carcinoembryonic antigen, CA19-9, CA72-4, CRP, albumin, and GPS revealed that GPS (odds ratio, 0.165; 95% confidence interval, 0.037-0.732; P = 0.0177) was associated with postoperative mortality. Preoperative GPS is considered to be a useful predictor of postoperative mortality in patients with colorectal cancer.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

Influence of shifting cultivation practices on soil-plant-beetle interactions.

PubMed

Ibrahim, Kalibulla Syed; Momin, Marcy D; Lalrotluanga, R; Rosangliana, David; Ghatak, Souvik; Zothansanga, R; Kumar, Nachimuthu Senthil; Gurusubramanian, Guruswami

2016-08-01

Shifting cultivation (jhum) is a major land use practice in Mizoram. It was considered as an eco-friendly and efficient method when the cycle duration was long (15-30 years), but it poses the problem of land degradation and threat to ecology when shortened (4-5 years) due to increased intensification of farming systems. Studying beetle community structure is very helpful in understanding how shifting cultivation affects the biodiversity features compared to natural forest system. The present study examines the beetle species diversity and estimates the effects of shifting cultivation practices on the beetle assemblages in relation to change in tree species composition and soil nutrients. Scarabaeidae and Carabidae were observed to be the dominant families in the land use systems studied. Shifting cultivation practice significantly (P < 0.05) affected the beetle and tree species diversity as well as the soil nutrients as shown by univariate (one-way analysis of variance (ANOVA), correlation and regression, diversity indices) and multivariate (cluster analysis, principal component analysis (PCA), detrended correspondence analysis (DCA), canonical variate analysis (CVA), permutational multivariate analysis of variance (PERMANOVA), permutational multivariate analysis of dispersion (PERMDISP)) statistical analyses. Besides changing the tree species composition and affecting the soil fertility, shifting cultivation provides less suitable habitat conditions for the beetle species. Bioindicator analysis categorized the beetle species into forest specialists, anthropogenic specialists (shifting cultivation habitat specialist), and habitat generalists. Molecular analysis of bioindicator beetle species was done using mitochondrial cytochrome oxidase subunit I (COI) marker to validate the beetle species and describe genetic variation among them in relation to heterogeneity, transition/transversion bias, codon usage bias, evolutionary distance, and substitution pattern. The present study revealed the fact that shifting cultivation practice significantly affects the beetle species in terms of biodiversity pattern as well as evolutionary features. Spatiotemporal assessment of soil-plant-beetle interactions in shifting cultivation system and their influence in land degradation and ecology will be helpful in making biodiversity conservation decisions in the near future.

Rapid discrimination of sea buckthorn berries from different H. rhamnoides subspecies by multi-step IR spectroscopy coupled with multivariate data analysis

NASA Astrophysics Data System (ADS)

Liu, Yue; Zhang, Ying; Zhang, Jing; Fan, Gang; Tu, Ya; Sun, Suqin; Shen, Xudong; Li, Qingzhu; Zhang, Yi

2018-03-01

As an important ethnic medicine, sea buckthorn was widely used to prevent and treat various diseases due to its nutritional and medicinal properties. According to the Chinese Pharmacopoeia, sea buckthorn was originated from H. rhamnoides, which includes five subspecies distributed in China. Confusion and misidentification usually occurred due to their similar morphology, especially in dried and powdered forms. Additionally, these five subspecies have vital differences in quality and physiological efficacy. This paper focused on the quick classification and identification method of sea buckthorn berry powders from five H. rhamnoides subspecies using multi-step IR spectroscopy coupled with multivariate data analysis. The holistic chemical compositions revealed by the FT-IR spectra demonstrated that flavonoids, fatty acids and sugars were the main chemical components. Further, the differences in FT-IR spectra regarding their peaks, positions and intensities were used to identify H. rhamnoides subspecies samples. The discrimination was achieved using principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). The results showed that the combination of multi-step IR spectroscopy and chemometric analysis offered a simple, fast and reliable method for the classification and identification of the sea buckthorn berry powders from different H. rhamnoides subspecies.

Ripening-dependent metabolic changes in the volatiles of pineapple (Ananas comosus (L.) Merr.) fruit: II. Multivariate statistical profiling of pineapple aroma compounds based on comprehensive two-dimensional gas chromatography-mass spectrometry.

PubMed

Steingass, Christof Björn; Jutzi, Manfred; Müller, Jenny; Carle, Reinhold; Schmarr, Hans-Georg

2015-03-01

Ripening-dependent changes of pineapple volatiles were studied in a nontargeted profiling analysis. Volatiles were isolated via headspace solid phase microextraction and analyzed by comprehensive 2D gas chromatography and mass spectrometry (HS-SPME-GC×GC-qMS). Profile patterns presented in the contour plots were evaluated applying image processing techniques and subsequent multivariate statistical data analysis. Statistical methods comprised unsupervised hierarchical cluster analysis (HCA) and principal component analysis (PCA) to classify the samples. Supervised partial least squares discriminant analysis (PLS-DA) and partial least squares (PLS) regression were applied to discriminate different ripening stages and describe the development of volatiles during postharvest storage, respectively. Hereby, substantial chemical markers allowing for class separation were revealed. The workflow permitted the rapid distinction between premature green-ripe pineapples and postharvest-ripened sea-freighted fruits. Volatile profiles of fully ripe air-freighted pineapples were similar to those of green-ripe fruits postharvest ripened for 6 days after simulated sea freight export, after PCA with only two principal components. However, PCA considering also the third principal component allowed differentiation between air-freighted fruits and the four progressing postharvest maturity stages of sea-freighted pineapples.

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

Multivariate pattern dependence

PubMed Central

Saxe, Rebecca

2017-01-01

When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD): a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS) and to the fusiform face area (FFA), using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity. PMID:29155809

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

Wavelet analysis for the study of the relations among soil radon anomalies, volcanic and seismic events: the case of Mt. Etna (Italy)

NASA Astrophysics Data System (ADS)

Ferrera, Elisabetta; Giammanco, Salvatore; Cannata, Andrea; Montalto, Placido

2013-04-01

From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol® probe located on the upper NE flank of Mt. Etna volcano, close either to the Piano Provenzana fault or to the NE-Rift. Seismic and volcanological data have been analyzed together with radon data. We also analyzed air and soil temperature, barometric pressure, snow and rain fall data. In order to find possible correlations among the above parameters, and hence to reveal possible anomalies in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-days time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-days moving averages showed that, similar to multivariate linear regression analysis, the summer period is characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allows to study the relations among different signals either in time or frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Our work suggests that in order to make an accurate analysis of the relations among distinct signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be very effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Monotherapy versus Combination Therapy against Nonbacteremic Carbapenem-resistant Gram-negative Infections: A Retrospective Observational Study.

PubMed

Ghafur, Abdul; Devarajan, Vidyalakshmi; Raja, T; Easow, Jose; Raja, M A; Sreenivas, Sankar; Ramakrishnan, Balasubramaniam; Raman, S G; Devaprasad, Dedeepiya; Venkatachalam, Balaji; Nimmagadda, Ramesh

2017-12-01

Superiority of colistin-carbapenem combination therapy (CCCT) over colistin monotherapy (CMT) against carbapenem-resistant Gram-negative bacterial (CRGNB) infections is not conclusively proven. The aim of the current study was to analyze the effectiveness of both strategies against CRGNB nonbacteremic infections. This was a retrospective observational cohort study. Case record analysis of patients who had CRGNB nonbacteremic infections identified over a period of 4 years (January 2012-December 2015) was done by medical record review at a tertiary care center in India. P < 0.05 was considered as significant. Multivariate analysis was performed using Cox regression. Out of 153 patients (pneumonia 115, urinary tract infection 17, complicated skin and soft-tissue infection 18, intra-abdominal infection 1, and meningitis 2), 92 patients received CCCT and 61 received CMT. Univariate analysis revealed higher Acute Physiology and Chronic Health Evaluation II (APACHE II) score, pneumonia as the diagnosis, and Klebsiella as the causative organism to be the risk factors for higher 28-day mortality ( P = 0.036, 0.006, 0.016, respectively). Combination therapy had no significant impact on mortality (odds ratio [OR] = 0.91, 95% confidence interval [CI] = 0.327-2.535, P = 0.857). Multivariate analysis revealed that higher APACHE II score and infection due to Klebsiella were found to be independent risk factors for higher mortality (OR = 3.16 and 4.9, 95% CI = 1.34-7.4 and 2.19-11.2, P = 0.008 and 0.0001, respectively). In our retrospective single-center series of CRGNB nonbacteremic infections, CCCT was not superior to CMT. Multicenter large observational studies or prospective randomized clinical trials are the need of the hour.

Chordee and Penile Shortening Rather Than Voiding Function Are Associated With Patient Dissatisfaction After Urethroplasty.

PubMed

Maciejewski, Conrad C; Haines, Trevor; Rourke, Keith F

2017-05-01

To identify factors that predict patient satisfaction after urethroplasty by prospectively examining patient-reported quality of life scores using 3 validated instruments. A 3-part prospective survey consisting of the International Prostate Symptom Score (IPSS), the International Index of Erectile Function (IIEF) score, and a urethroplasty quality of life survey was completed by patients who underwent urethroplasty preoperatively and at 6 months postoperatively. The quality of life score included questions on genitourinary pain, urinary tract infection (UTI), postvoid dribbling, chordee, shortening, overall satisfaction, and overall health. Data were analyzed using descriptive statistics, paired t test, univariate and multivariate logistic regression analyses, and Wilcoxon signed-rank analysis. Patients were enrolled in the study from February 2011 to December 2014, and a total of 94 patients who underwent a total of 102 urethroplasties completed the study. Patients reported statistically significant improvements in IPSS (P < .001). Ordinal linear regression analysis revealed no association between age, IPSS, or IIEF score and patient satisfaction. Wilcoxon signed-rank analysis revealed significant improvements in pain scores (P = .02), UTI (P < .001), perceived overall health (P = .01), and satisfaction (P < .001). Univariate logistic regression identified a length >4 cm and the absence of UTI, pain, shortening, and chordee as predictors of patient satisfaction. Multivariate analysis of quality of life domain scores identified absence of shortening and absence of chordee as independent predictors of patient satisfaction following urethroplasty (P < .01). Patient voiding function and quality of life improve significantly following urethroplasty, but improvement in voiding function is not associated with patient satisfaction. Chordee status and perceived penile shortening impact patient satisfaction, and should be included in patient-reported outcome measures. Copyright © 2017 Elsevier Inc. All rights reserved.

The Raman spectrum character of skin tumor induced by UVB

NASA Astrophysics Data System (ADS)

Wu, Shulian; Hu, Liangjun; Wang, Yunxia; Li, Yongzeng

2016-03-01

In our study, the skin canceration processes induced by UVB were analyzed from the perspective of tissue spectrum. A home-made Raman spectral system with a millimeter order excitation laser spot size combined with a multivariate statistical analysis for monitoring the skin changed irradiated by UVB was studied and the discrimination were evaluated. Raman scattering signals of the SCC and normal skin were acquired. Spectral differences in Raman spectra were revealed. Linear discriminant analysis (LDA) based on principal component analysis (PCA) were employed to generate diagnostic algorithms for the classification of skin SCC and normal. The results indicated that Raman spectroscopy combined with PCA-LDA demonstrated good potential for improving the diagnosis of skin cancers.

A multivariate analysis of age-related differences in functional networks supporting conflict resolution.

PubMed

Salami, Alireza; Rieckmann, Anna; Fischer, Håkan; Bäckman, Lars

2014-02-01

Functional neuroimaging studies demonstrate age-related differences in recruitment of a large-scale attentional network during interference resolution, especially within dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC). These alterations in functional responses have been frequently observed despite equivalent task performance, suggesting age-related reallocation of neural resources, although direct evidence for a facilitating effect in aging is sparse. We used the multi-source interference task and multivariate partial-least-squares to investigate age-related differences in the neuronal signature of conflict resolution, and their behavioral implications in younger and older adults. There were interference-related increases in activity, involving fronto-parietal and basal ganglia networks that generalized across age. In addition an age-by-task interaction was observed within a distributed network, including DLPFC and ACC, with greater activity during interference in the old. Next, we combined brain-behavior and functional connectivity analyses to investigate whether compensatory brain changes were present in older adults, using DLPFC and ACC as regions of interest (i.e. seed regions). This analysis revealed two networks differentially related to performance across age groups. A structural analysis revealed age-related gray-matter losses in regions facilitating performance in the young, suggesting that functional reorganization may partly reflect structural alterations in aging. Collectively, these findings suggest that age-related structural changes contribute to reductions in the efficient recruitment of a youth-like interference network, which cascades into instantiation of a different network facilitating conflict resolution in elderly people. © 2013. Published by Elsevier Inc. All rights reserved.

Carbapenemase-producing Enterobacteriaceae: Risk factors for infection and impact of resistance on outcomes

PubMed Central

Mariappan, Shanthi; Sekar, Uma; Kamalanathan, Arunagiri

2017-01-01

Background: Carbapenemase-producing Enterobacteriaceae (CPE) have increased in recent years leading to limitations of treatment options. The present study was undertaken to detect CPE, risk factors for acquiring them and their impact on clinical outcomes. Methods: This retrospective observational study included 111 clinically significant Enterobacteriaceae resistant to cephalosporins subclass III and exhibiting a positive modified Hodge test. Screening for carbapenemase production was done by phenotypic methods, and polymerase chain reaction was performed to detect genes encoding them. Retrospectively, the medical records of the patients were perused to assess risk factors for infections with CPE and their impact. The data collected were duration of hospital stay, Intensive Care Unit (ICU) stay, use of invasive devices, mechanical ventilation, the presence of comorbidities, and antimicrobial therapy. The outcome was followed up. Univariate and multivariate analysis of the data were performed using SPSS software. Results: Carbapenemase-encoding genes were detected in 67 isolates. The genes detected were New Delhi metallo-β-lactamase, Verona integron-encoded metallo-β-lactamase, and oxacillinase-181.Although univariate analysis identified risk factors associated with acquiring CPE infections as ICU stay (P = 0.021), mechanical ventilation (P = 0.013), indwelling device (P = 0.011), diabetes mellitus (P = 0.036), usage of multiple antimicrobial agents (P = 0.007), administration of carbapenems (P = 0.042), presence of focal infection or sepsis (P = 0.013), and surgical interventions (P = 0.016), multivariate analysis revealed that all these factors were insignificant. Mortality rate was 56.7% in patients with CPE infections. By both univariate and multivariate analysis of impact of the variables on mortality in these patients, the significant factors were mechanical ventilation (odds ratio [OR]: 0.141, 95% confidence interval [CI]: 0.024–0.812) and presence of indwelling invasive device (OR: 8.034; 95% CI: 2.060–31.335). Conclusion: In this study, no specific factor was identified as an independent risk for acquisition of CPE infection. However, as it is evident by multivariate analysis, there is an increased risk of mortality in patients with CPE infections when they are ventilated and are supported by indwelling devices. PMID:28251105

Apolipoprotein E Polymorphism and Left Ventricular Failure in Beta-Thalassemia: A Multivariate Meta-Analysis.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Bagos, Pantelis G

2017-09-01

Apolipoprotein E (ApoE) is potentially a genetic risk factor for the development of left ventricular failure (LVF), the main cause of death in beta-thalassemia homozygotes. In the present study, we synthesize the results of independent studies examining the effect of ApoE on LVF development in thalassemic patients through a meta-analytic approach. However, all studies report more than one outcome, as patients are classified into three groups according to the severity of the symptoms and the genetic polymorphism. Thus, a multivariate meta-analytic method that addresses simultaneously multiple exposures and multiple comparison groups was developed. Four individual studies were included in the meta-analysis involving 613 beta-thalassemic patients and 664 controls. The proposed method that takes into account the correlation of log odds ratios (log(ORs)), revealed a statistically significant overall association (P-value  =  0.009), mainly attributed to the contrast of E4 versus E3 allele for patients with evidence (OR: 2.32, 95% CI: 1.19, 4.53) or patients with clinical and echocardiographic findings (OR: 3.34, 95% CI: 1.78, 6.26) of LVF. This study suggests that E4 is a genetic risk factor for LVF in beta-thalassemia major. The presented multivariate approach can be applied in several fields of research. © 2017 John Wiley & Sons Ltd/University College London.

Socio-economic Correlates of Malnutrition among Married Women in Bangladesh.

PubMed

Mostafa Kamal, S M; Md Aynul, Islam

2010-12-01

This paper examines the prevalence and socio-economic correlates of malnutrition among ever married non-pregnant women of reproductive age of Bangladesh using a nationally representative weighted sample of 10,145. Body mass index was used to measure nutritional status. Both bivariate and multivariate statistical analyses were employed to assess the relationship between socio-economic characteristics and women's nutritional status. Overall, 28.5% of the women were found to be underweight. The fixed effect multivariate binary logistic regression analysis yielded significantly increased risk of underweight for the young, currently working, non-Muslim, rural residents, widowed, divorced or separated women. Significant wide variations of malnourishment prevailed in the administrative regions of the country. Wealth index and women's education were the most important determinants of underweight. The multivariate logistic regression analysis revealed that the risk of being underweight was almost seven times higher (OR=6.76, 95% CI=5.20-8.80) among women with no formal education as compared to those with higher education and the likelihood of underweight was significantly (p<0.001) 5.2 times (OR=5.23, 95% CI=4.51-6.07) in the poorest as compared to their richest counterparts. Poverty alleviation programmes should be strengthened targeting the poor. Effective policies, information and health education programmes for women are required to ensure adequate access to health services and for them to understand the components of a healthy diet.

Changes in Concurrent Risk of Warm and Dry Years under Impact of Climate Change

NASA Astrophysics Data System (ADS)

Sarhadi, A.; Wiper, M.; Touma, D. E.; Ausín, M. C.; Diffenbaugh, N. S.

2017-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena. The changing concurrence of multiple climatic extremes (warm and dry years) may result in intensification of undesirable consequences for water resources, human and ecosystem health, and environmental equity. The present study assesses how global warming influences the probability that warm and dry years co-occur in a global scale. In the first step of the study a designed multivariate Mann-Kendall trend analysis is used to detect the areas in which the concurrence of warm and dry years has increased in the historical climate records and also climate models in the global scale. The next step investigates the concurrent risk of the extremes under dynamic nonstationary conditions. A fully generalized multivariate risk framework is designed to evolve through time under dynamic nonstationary conditions. In this methodology, Bayesian, dynamic copulas are developed to model the time-varying dependence structure between the two different climate extremes (warm and dry years). The results reveal an increasing trend in the concurrence risk of warm and dry years, which are in agreement with the multivariate trend analysis from historical and climate models. In addition to providing a novel quantification of the changing probability of compound extreme events, the results of this study can help decision makers develop short- and long-term strategies to prepare for climate stresses now and in the future.

Digital Citizenship and Health Promotion Programs: The Power of Knowing.

PubMed

Hicks, Elaine R

2016-11-03

Patterns of Internet access and use among disadvantaged subgroups of Americans reveal that not all disparities are the same, a distinction crucial for appropriate public policies and health promotion program planning. In their book, Digital Citizenship: The Internet, Society, and Participation, authors Karen Mossberger, Caroline Tolbert, and Ramona McNeal deconstructed national opinion surveys and used multivariate methods of data analysis to demonstrate the impact of exclusion from online society economically, socially, and politically among disadvantaged Americans. © 2016 Society for Public Health Education.

A single determinant dominates the rate of yeast protein evolution.

PubMed

Drummond, D Allan; Raval, Alpan; Wilke, Claus O

2006-02-01

A gene's rate of sequence evolution is among the most fundamental evolutionary quantities in common use, but what determines evolutionary rates has remained unclear. Here, we carry out the first combined analysis of seven predictors (gene expression level, dispensability, protein abundance, codon adaptation index, gene length, number of protein-protein interactions, and the gene's centrality in the interaction network) previously reported to have independent influences on protein evolutionary rates. Strikingly, our analysis reveals a single dominant variable linked to the number of translation events which explains 40-fold more variation in evolutionary rate than any other, suggesting that protein evolutionary rate has a single major determinant among the seven predictors. The dominant variable explains nearly half the variation in the rate of synonymous and protein evolution. We show that the two most commonly used methods to disentangle the determinants of evolutionary rate, partial correlation analysis and ordinary multivariate regression, produce misleading or spurious results when applied to noisy biological data. We overcome these difficulties by employing principal component regression, a multivariate regression of evolutionary rate against the principal components of the predictor variables. Our results support the hypothesis that translational selection governs the rate of synonymous and protein sequence evolution in yeast.

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

[Risk indicators associated with the consumption of illicit drugs by schoolchildren in a community in the south of Brazil].

PubMed

Backes, Dirce Stein; Zanatta, Fabrício Batistin; Costenaro, Regina Santini; Rangel, Rosiane Filipin; Vidal, Janice; Kruel, Cristina Saling; de Mattos, Karen Mallo

2014-03-01

This study sought to identify the risk indicators associated with the consumption of illicit drugs by schoolchildren in public schools in a community in the south of Brazil. This is a non-experimental cross-sectional study conducted with 535 students of primary schoolchildren from six public schools. Data were collected using a questionnaire between October 2011 and March 2012. The results were presented by simple and relative distribution of frequency and odds ratio (OR) and the 95% reliability intervals were calculated to verify the association between the dependent and independent variables. Multivariate analysis was also performed using the question "have you ever used illicit drugs?" Univariate analysis revealed an association between family income, color, period in which the child studied, failure to pass annual tests, use of methods of prevention, smoking habit and knowing someone who uses drugs with the fact of having experimented with the use of illicit drugs. After multivariate analysis, the smoking habit was the only indicator significantly associated with the question of having made use of illicit drugs. The results indicate that the smoking habit is an important indicator of the predictive risk for the use of illicit drugs.

Illustration of compositional variations over time of Chinese porcelain glazes combining micro-X-ray Fluorescence spectrometry, multivariate data analysis and Seger formulas

NASA Astrophysics Data System (ADS)

Van Pevenage, J.; Verhaeven, E.; Vekemans, B.; Lauwers, D.; Herremans, D.; De Clercq, W.; Vincze, L.; Moens, L.; Vandenabeele, P.

2015-01-01

In this research, the transparent glaze layers of Chinese porcelain samples were investigated. Depending on the production period, these samples can be divided into two groups: the samples of group A dating from the Kangxi period (1661-1722), and the samples of group B produced under emperor Qianlong (1735-1795). Due to the specific sample preparation method and the small spot size of the X-ray beam, investigation of the transparent glaze layers is enabled. Despite the many existing research papers about glaze investigations of ceramics and/or porcelain ware, this research reveals new insights into the glaze composition and structure of Chinese porcelain samples. In this paper it is demonstrated, using micro-X-ray Fluorescence (μ-XRF) spectrometry, multivariate data analysis and statistical analysis (Hotelling's T-Square test) that the transparent glaze layers of the samples of groups A and B are significantly different (95% confidence level). Calculation of the Seger formulas, enabled classification of the glazes. Combining all the information, the difference in composition of the Chinese porcelain glazes of the Kangxi period and the Qianlong period can be demonstrated.

Cohort comparisons: emotional well-being among adolescents and older adults

PubMed Central

Momtaz, Yadollah Abolfathi; Hamid, Tengku Aizan; Ibrahim, Rahimah

2014-01-01

Background There are several negative stereotypes about older adults that have negatively influenced people’s attitude about aging. The present study compared emotional well-being between older adults and adolescents. Methods Data for this study came from 1,403 community-dwelling elderly persons and 1,190 secondary school students and were obtained from two national cross-sectional surveys. Emotional well-being was measured using the World Health Organization-Five Well-Being Index. Data analysis was conducted using a multivariate analysis of covariance with SPSS software version 20 (IBM Corporation, Armonk, NY, USA). Results Elderly people significantly scored higher levels of emotional well-being (mean, 62.3; standard deviation, 22.55) than younger people (mean, 57.9; standard deviation, 18.46; t, 5.32; P≤0.001). The findings from the multivariate analysis of covariance revealed a significant difference between older adults and younger people in emotional well-being [F(3, 2587)=120.21; P≤0.001; η2=0.122] after controlling for sex. Conclusion Contrary to negative stereotypes about aging, our findings show a higher level of emotional well-being among older adults compared with younger people. PMID:24872683

Variation of Water Quality Parameters with Siltation Depth for River Ichamati Along International Border with Bangladesh Using Multivariate Statistical Techniques

NASA Astrophysics Data System (ADS)

Roy, P. K.; Pal, S.; Banerjee, G.; Biswas Roy, M.; Ray, D.; Majumder, A.

2014-12-01

River is considered as one of the main sources of freshwater all over the world. Hence analysis and maintenance of this water resource is globally considered a matter of major concern. This paper deals with the assessment of surface water quality of the Ichamati river using multivariate statistical techniques. Eight distinct surface water quality observation stations were located and samples were collected. For the samples collected statistical techniques were applied to the physico-chemical parameters and depth of siltation. In this paper cluster analysis is done to determine the relations between surface water quality and siltation depth of river Ichamati. Multiple regressions and mathematical equation modeling have been done to characterize surface water quality of Ichamati river on the basis of physico-chemical parameters. It was found that surface water quality of the downstream river was different from the water quality of the upstream. The analysis of the water quality parameters of the Ichamati river clearly indicate high pollution load on the river water which can be accounted to agricultural discharge, tidal effect and soil erosion. The results further reveal that with the increase in depth of siltation, water quality degraded.

Effects of Lacunar Infarctions on Cognitive Impairment in Patients with Cerebral Autosomal-Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy

PubMed Central

Choi, Jay Chol; Kang, Sa-Yoon; Kang, Ji-Hoon; Na, Hae Ri; Park, Ji-Kang

2011-01-01

Background and Purpose Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited microangiopathy caused by mutations in the Notch3 gene. Although previous studies have shown an association between lacunar infarction and cognitive impairment, the relationship between MRI parameters and cognition remains unclear. In this study we investigated the influence of MRI parameters on cognitive impairment in CADASIL. Methods We applied a prospective protocol to 40 patients. MRI analysis included the normalized volume of white-matter hyperintensities (nWMHs), number of lacunes, and number of cerebral microbleeds. Cognition was assessed with the aid of psychometric tests [Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-cognition (ADAS-cog), Trail-Making Test, and Stroop interference (Stroop IF)]. Results A multivariate regression analysis revealed that the total number of lacunes influenced the performance in the MMSE, ADAS-cog, and Stroop IF, while nWMHs had a strong univariate association with ADAS-cog and Stroop IF scores. However, this association disappeared in the multivariate analysis. Conclusions These findings demonstrate that the number of lacunes is the main predictive factor of cognitive impairment in CADASIL. PMID:22259617

Elemental content of Vietnamese rice. Part 2. Multivariate data analysis.

PubMed

Kokot, S; Phuong, T D

1999-04-01

Rice samples were obtained from the Red River region and some other parts of Vietnam as well as from Yanco, Australia. These samples were analysed for 14 elements (P, K, Mg, Ca, Mn, Zn, Fe, Cu, Al, Na, Ni, As, Mo and Cd) by ICP-AES, ICP-MS and FAAS as described in Part 1. This data matrix was then submitted to multivariate data analysis by principal component analysis to investigate the influences of environmental and crop cultivation variables on the elemental content of rice. Results revealed that geographical location, grain variety, seasons and soil conditions are the most likely significant factors causing changes in the elemental content between the rice samples. To assess rice quality according to its elemental content and physio-biological properties, a multicriteria decision making method (PROMETHEE) was applied. With the Vietnamese rice, the sticky rice appeared to contain somewhat higher levels of nutritionally significant elements such as P, K and Mg than the non-sticky rice. Also, rice samples grown during the wet season have better levels of nutritionally significant mineral elements than those of the dry season, but in general, the wet season seemed to provide better overall elemental and physio-biological rice quality.

Uninsured Migrants: Health Insurance Coverage and Access to Care Among Mexican Return Migrants.

PubMed

Wassink, Joshua

2018-01-01

Despite an expansive body of research on health and access to medical care among Mexican immigrants in the United States, research on return migrants focuses primarily on their labor market mobility and contributions to local development. Motivated by recent scholarship that documents poor mental and physical health among Mexican return migrants, this study investigates return migrants' health insurance coverage and access to medical care. I use descriptive and multivariate techniques to analyze data from the 2009 and 2014 rounds of Mexico's National Survey of Demographic Dynamics (ENADID, combined n=632,678). Analyses reveal a large and persistent gap between recent return migrants and non-migrants, despite rising overall health coverage in Mexico. Multivariate analyses suggest that unemployment among recent arrivals contributes to their lack of insurance. Relative to non-migrants, recently returned migrants rely disproportionately on private clinics, pharmacies, self-medication, or have no regular source of care. Mediation analysis suggests that returnees' high rate of uninsurance contributes to their inadequate access to care. This study reveals limited access to medical care among the growing population of Mexican return migrants, highlighting the need for targeted policies to facilitate successful reintegration and ensure access to vital resources such as health care.

Exposure to tobacco secondhand smoke and its associated factors among non-smoking adults in smoking-restricted and non-restricted areas: findings from a nationwide study in Malaysia

PubMed Central

Lim, Kuang Hock; Teh, Chien Huey; Nik Mohamed, Mohamad Haniki; Pan, Sayan; Ling, Miaw Yn; Mohd Yusoff, Muhammad Fadhli; Hassan, Noraryana; Baharom, Nizam; Dawam, Netty Darwina; Ismail, Norliana; Ghazali, Sumarni Mohd; Cheong, Kee Chee; Chong, Kar Hon; Lim, Hui Li

2018-01-01

Objectives Secondhand smoke (SHS) has been associated with increased morbidity and mortality. Therefore, the aims of the paper are to assess SHS exposure among non-smoking adults in Malaysia attending various smoking-restricted and non-restricted public areas according to the Control of Tobacco Product Regulations (CTPR) as well as its relationship with various sociodemographic variables. Design Data were extracted from a cross-sectional study, the Global Adults Tobacco Survey (GATS) 2011 which involved 3269 non-smokers in Malaysia. Data was obtained through face-to-face interviews using a validated pre-tested questionnaire. Factors associated with exposure to SHS were identified via multivariable analysis. Results The study revealed that almost two-thirds of respondents were exposed to SHS in at least one public area in the past 1 month, with a significantly higher exposure among males (70.6%), those with higher educational attainment (81.4%) and higher income (quintile 1%–73.9%). Besides, the exposure to SHS was almost four times higher in non-restricted areas compared with restricted areas under the CTPR (81.9% vs 22.9). Multivariable analysis revealed that males and younger adults at non-restricted areas were more likely to be exposed to SHS while no significant associated factors of SHS exposure was observed in restricted areas. Conclusions The study revealed the prevalence of SHS exposure was higher among Malaysian adults. Although smoke-free laws offer protection to non-smokers from exposure to SHS, enforcement activities in restricted areas should be enhanced to ensure strict public abidance. In addition, legislation of restricted areas should also be extended to greatly reduce the SHS exposure among non-smokers in Malaysia. PMID:29317411

Revealing hidden spectral information of chlorine and sulfur in data of a mobile Laser-induced Breakdown Spectroscopy system using chemometrics

NASA Astrophysics Data System (ADS)

Gottlieb, C.; Millar, S.; Günther, T.; Wilsch, G.

2017-06-01

For the damage assessment of reinforced concrete structures the quantified ingress profiles of harmful species like chlorides, sulfates and alkali need to be determined. In order to provide on-site analysis of concrete a fast and reliable method is necessary. Low transition probabilities as well as the high ionization energies for chlorine and sulfur in the near-infrared range makes the detection of Cl I and S I in low concentrations a difficult task. For the on-site analysis a mobile LIBS-system (λ = 1064 nm, Epulse ≤ 3 mJ, τ = 1.5 ns) with an automated scanner has been developed at BAM. Weak chlorine and sulfur signal intensities do not allow classical univariate analysis for process data derived from the mobile system. In order to improve the analytical performance multivariate analysis like PLS-R will be presented in this work. A comparison to standard univariate analysis will be carried out and results covering important parameters like detection and quantification limits (LOD, LOQ) as well as processing variances will be discussed (Allegrini and Olivieri, 2014 [1]; Ostra et al., 2008 [2]). It will be shown that for the first time a low cost mobile system is capable of providing reproducible chlorine and sulfur analysis on concrete by using a low sensitive system in combination with multivariate evaluation.

A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series.

PubMed

Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

2015-01-01

Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze (RAM) task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC), but not in the primary visual cortex (V1). Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel activity.

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

The relationship of self-concept and perceived athletic competence to physical activity level and gender among Turkish early adolescents.

PubMed

Aşçi, F H; Koşar, S N; Işler, A K

2001-01-01

The purpose of this study was to examine the self-concept and perceived athletic competence of Turkish early adolescents in relation to physical activity level and gender. Self-concept was assessed using the Piers-Harris Children's Self-Concept Scale, and perceived athletic competence was assessed by means of the Athletic Competence subscale of Harter's Self-Perception Profile for Children. In addition, the Weekly Activity Checklist was used for assessing physical activity level. Males and females were assigned to low and high physical activity level groups based on their mean scores. Multivariate analysis of variance revealed significant main effects for gender and physical activity level, but there was no significant gender by physical activity interaction. Univariate analysis demonstrated a significant main effect for physical activity level on perceived athletic competence but not global self-concept. In addition, univariate analysis did not reveal a significant difference in either global self-concept or perceived athletic competence with respect to gender.

Effect of membrane flux and dialyzer biocompatibility on survival in end-stage diabetic nephropathy.

PubMed

Götz, Angela K; Böger, Carsten A; Popal, Massoud; Banas, Bernhard; Krämer, Bernhard K

2008-01-01

We examined the effects of dialyzer membrane flux and biocompatibility on mortality in diabetic dialysis patients. We enrolled 402 prevalent chronic hemodialysis patients from 30 centers in Germany in 1999 for a prospective observational study until 2003. We compared 2 groups in post hoc analysis: high-flux (HF, n = 166) versus low-flux (LF, n = 236) membrane, and high biocompatibility (HB, n = 300) versus low biocompatibility (LB, n = 102). All-cause mortality (ACM) was the primary endpoint. Death causes were the secondary endpoints. Multivariate Cox regression analysis showed no significant difference in risk for ACM with respect to flux (hazard ratio, HR, 0.79; p = 0.08; ACM 63% in HF vs. 70% in LF dialysis) and biocompatibility level (HR 1.00; p = 0.98; ACM 67% for HB vs. 66% for LB). The multivariate analysis of different causes of death did not reveal any outcome differences dependent on flux and biocompatibility level apart from a slightly better cumulative survival regarding the death cause 'infectious' in our HF dialysis group (HR 0.48; p = 0.07, Kaplan-Meier analysis p = 0.03). Our data indicate that mortality of hemodialysis patients with type-2 diabetic nephropathy is influenced neither by dialyzer flux level nor by biocompatibility. Copyright 2008 S. Karger AG, Basel.

Chemical Species, Micromorphology, and XRD Fingerprint Analysis of Tibetan Medicine Zuotai Containing Mercury

PubMed Central

Li, Cen; Yang, Hongxia; Xiao, Yuancan; Zhandui; Sanglao; Wang, Zhang; Ladan, Duojie; Bi, Hongtao

2016-01-01

Zuotai (gTso thal) is one of the famous drugs containing mercury in Tibetan medicine. However, little is known about the chemical substance basis of its pharmacodynamics and the intrinsic link of different samples sources so far. Given this, energy dispersive spectrometry of X-ray (EDX), scanning electron microscopy (SEM), atomic force microscopy (AFM), and powder X-ray diffraction (XRD) were used to assay the elements, micromorphology, and phase composition of nine Zuotai samples from different regions, respectively; the XRD fingerprint features of Zuotai were analyzed by multivariate statistical analysis. EDX result shows that Zuotai contains Hg, S, O, Fe, Al, Cu, and other elements. SEM and AFM observations suggest that Zuotai is a kind of ancient nanodrug. Its particles are mainly in the range of 100–800 nm, which commonly further aggregate into 1–30 μm loosely amorphous particles. XRD test shows that β-HgS, S8, and α-HgS are its main phase compositions. XRD fingerprint analysis indicates that the similarity degrees of nine samples are very high, and the results of multivariate statistical analysis are broadly consistent with sample sources. The present research has revealed the physicochemical characteristics of Zuotai, and it would play a positive role in interpreting this mysterious Tibetan drug. PMID:27738409

Chemical Species, Micromorphology, and XRD Fingerprint Analysis of Tibetan Medicine Zuotai Containing Mercury.

PubMed

Li, Cen; Yang, Hongxia; Du, Yuzhi; Xiao, Yuancan; Zhandui; Sanglao; Wang, Zhang; Ladan, Duojie; Bi, Hongtao; Wei, Lixin

2016-01-01

Zuotai ( gTso thal ) is one of the famous drugs containing mercury in Tibetan medicine. However, little is known about the chemical substance basis of its pharmacodynamics and the intrinsic link of different samples sources so far. Given this, energy dispersive spectrometry of X-ray (EDX), scanning electron microscopy (SEM), atomic force microscopy (AFM), and powder X-ray diffraction (XRD) were used to assay the elements, micromorphology, and phase composition of nine Zuotai samples from different regions, respectively; the XRD fingerprint features of Zuotai were analyzed by multivariate statistical analysis. EDX result shows that Zuotai contains Hg, S, O, Fe, Al, Cu, and other elements. SEM and AFM observations suggest that Zuotai is a kind of ancient nanodrug. Its particles are mainly in the range of 100-800 nm, which commonly further aggregate into 1-30  μ m loosely amorphous particles. XRD test shows that β -HgS, S 8 , and α -HgS are its main phase compositions. XRD fingerprint analysis indicates that the similarity degrees of nine samples are very high, and the results of multivariate statistical analysis are broadly consistent with sample sources. The present research has revealed the physicochemical characteristics of Zuotai , and it would play a positive role in interpreting this mysterious Tibetan drug.

Multispectral UV imaging for surface analysis of MUPS tablets with special focus on the pellet distribution.

PubMed

Novikova, Anna; Carstensen, Jens M; Rades, Thomas; Leopold, Prof Dr Claudia S

2016-12-30

In the present study the applicability of multispectral UV imaging in combination with multivariate image analysis for surface evaluation of MUPS tablets was investigated with respect to the differentiation of the API pellets from the excipients matrix, estimation of the drug content as well as pellet distribution, and influence of the coating material and tablet thickness on the predictive model. Different formulations consisting of coated drug pellets with two coating polymers (Aquacoat ® ECD and Eudragit ® NE 30 D) at three coating levels each were compressed to MUPS tablets with various amounts of coated pellets and different tablet thicknesses. The coated drug pellets were clearly distinguishable from the excipients matrix using a partial least squares approach regardless of the coating layer thickness and coating material used. Furthermore, the number of the detected drug pellets on the tablet surface allowed an estimation of the true drug content in the respective MUPS tablet. In addition, the pellet distribution in the MUPS formulations could be estimated by UV image analysis of the tablet surface. In conclusion, this study revealed that UV imaging in combination with multivariate image analysis is a promising approach for the automatic quality control of MUPS tablets during the manufacturing process. Copyright © 2016 Elsevier B.V. All rights reserved.

Targeted metabolomic profiling in rat tissues reveals sex differences.

PubMed

Ruoppolo, Margherita; Caterino, Marianna; Albano, Lucia; Pecce, Rita; Di Girolamo, Maria Grazia; Crisci, Daniela; Costanzo, Michele; Milella, Luigi; Franconi, Flavia; Campesi, Ilaria

2018-03-16

Sex differences affect several diseases and are organ-and parameter-specific. In humans and animals, sex differences also influence the metabolism and homeostasis of amino acids and fatty acids, which are linked to the onset of diseases. Thus, the use of targeted metabolite profiles in tissues represents a powerful approach to examine the intermediary metabolism and evidence for any sex differences. To clarify the sex-specific activities of liver, heart and kidney tissues, we used targeted metabolomics, linear discriminant analysis (LDA), principal component analysis (PCA), cluster analysis and linear correlation models to evaluate sex and organ-specific differences in amino acids, free carnitine and acylcarnitine levels in male and female Sprague-Dawley rats. Several intra-sex differences affect tissues, indicating that metabolite profiles in rat hearts, livers and kidneys are organ-dependent. Amino acids and carnitine levels in rat hearts, livers and kidneys are affected by sex: male and female hearts show the greatest sexual dimorphism, both qualitatively and quantitatively. Finally, multivariate analysis confirmed the influence of sex on the metabolomics profiling. Our data demonstrate that the metabolomics approach together with a multivariate approach can capture the dynamics of physiological and pathological states, which are essential for explaining the basis of the sex differences observed in physiological and pathological conditions.

Multivariate Analysis as a Method for Evaluating the Conceptual Perceptions of Korean Medicine Students regarding Phlegm Pattern

PubMed Central

Kim, Hyungsuk; Park, Young-Jae; Park, Young-Bae

2013-01-01

Individuals may perceive the concepts in Korean medicine pattern classification differently because it is performed according to the integration of a variety of information. Therefore, analysis about individual perspective is very important for examining the cross-sectional perspective state of Korean medicine concepts and developing both the clinical guideline including diagnosis and the curriculum of Korean medicine colleges. Moreover, because this conceptual difference is thought to begin with college education, it is worthwhile to observe students' viewpoints. So, we suggested multivariate analysis to explore the dimensional structure of Korean medicine students' conceptual perceptions regarding phlegm pattern. We surveyed 326 students divided into 5 groups based on their year of study. Data were analyzed using multidimensional scaling and factor analysis. Within-group difference was the smallest for third-year students, who have received Korean medicine education in full for the first time. With the exception of first-year students, the conceptual map revealed that each group's mean perceptions of phlegm pattern were distributed in almost linear fashion. To determine the effect of education, we investigated the preference rankings and scores of each symptom. We also extracted factors to identify latent variables and to compare the between-group conceptual characteristics regarding phlegm pattern. PMID:24062789

Benthic foraminifera as bio-indicators of trace element pollution in the heavily contaminated Santa Gilla lagoon (Cagliari, Italy).

PubMed

Frontalini, Fabrizio; Buosi, Carla; Da Pelo, Stefania; Coccioni, Rodolfo; Cherchi, Antonietta; Bucci, Carla

2009-06-01

In order to assess the response of benthic foraminifera to trace element pollution, a study of benthic foraminiferal assemblages was carried out into sediment samples collected from the Santa Gilla lagoon (Sardinia, Italy). The lagoon has been contaminated by industrial waste, mainly trace elements, as well as by agricultural and domestic effluent. The analysis of surficial sediment shows enrichment in trace elements, including Cr, Cu, Hg, Ni, Pb and Zn. Biotic and abiotic data, analyzed with multivariate techniques of statistical analysis, reveal a distinct separation of both the highly polluted and less polluted sampling sites. The innermost part of the lagoon, comprising the industrial complex at Macchiareddu, is exposed to a high load of trace elements which are probably enhanced by their accumulation in the finer sediment fraction. This area reveals lower diversity and higher percentages of abnormalities when compared to the outermost part of the lagoon.

Non-destructive analysis of the conformational differences among feedstock sources and their corresponding co-products from bioethanol production with molecular spectroscopy.

PubMed

Gamage, I H; Jonker, A; Zhang, X; Yu, P

2014-01-24

The objective of this study was to determine the possibility of using molecular spectroscopy with multivariate technique as a fast method to detect the source effects among original feedstock sources of wheat and their corresponding co-products, wheat DDGS, from bioethanol production. Different sources of the bioethanol feedstock and their corresponding bioethanol co-products, three samples per source, were collected from the same newly-built bioethanol plant with current bioethanol processing technology. Multivariate molecular spectral analyses were carried out using agglomerative hierarchical cluster analysis (AHCA) and principal component analysis (PCA). The molecular spectral data of different feedstock sources and their corresponding co-products were compared at four different regions of ca. 1800-1725 cm(-1) (carbonyl CO ester, mainly related to lipid structure conformation), ca. 1725-1482 cm(-1) (amide I and amide II region mainly related to protein structure conformation), ca. 1482-1180 cm(-1) (mainly associated with structural carbohydrate) and ca. 1180-800 cm(-1) (mainly related to carbohydrates) in complex plant-based system. The results showed that the molecular spectroscopy with multivariate technique could reveal the structural differences among the bioethanol feedstock sources and among their corresponding co-products. The AHCA and PCA analyses were able to distinguish the molecular structure differences associated with chemical functional groups among the different sources of the feedstock and their corresponding co-products. The molecular spectral differences indicated the differences in functional, biomolecular and biopolymer groups which were confirmed by wet chemical analysis. These biomolecular and biopolymer structural differences were associated with chemical and nutrient profiles and nutrient utilization and availability. Molecular spectral analyses had the potential to identify molecular structure difference among bioethanol feedstock sources and their corresponding co-products. Copyright © 2013 Elsevier B.V. All rights reserved.

Positron emission tomography–computed tomography predictors of progression after DA-R-EPOCH for PMBCL

PubMed Central

Ng, Andrea K.; Dabaja, Bouthaina S.; Milgrom, Sarah A.; Gunther, Jillian R.; Fuller, C. David; Smith, Grace L.; Abou Yehia, Zeinab; Qiao, Wei; Wogan, Christine F.; Akhtari, Mani; Mawlawi, Osama; Medeiros, L. Jeffrey; Chuang, Hubert H.; Martin-Doyle, William; Armand, Philippe; LaCasce, Ann S.; Oki, Yasuhiro; Fanale, Michelle; Westin, Jason; Neelapu, Sattva; Nastoupil, Loretta

2018-01-01

Dose-adjusted rituximab plus etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin (DA-R-EPOCH) has produced good outcomes in primary mediastinal B-cell lymphoma (PMBCL), but predictors of resistance to this treatment are unclear. We investigated whether [18F]fluorodeoxyglucose positron emission tomography–computed tomography (PET-CT) findings could identify patients with PMBCL who would not respond completely to DA-R-EPOCH. We performed a retrospective analysis of 65 patients with newly diagnosed stage I to IV PMBCL treated at 2 tertiary cancer centers who had PET-CT scans available before and after frontline therapy with DA-R-EPOCH. Pretreatment variables assessed included metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Optimal cutoff points for progression-free survival (PFS) were determined by a machine learning approach. Univariate and multivariable models were constructed to assess associations between radiographic variables and PFS. At a median follow-up of 36.6 months (95% confidence interval, 28.1-45.1), 2-year PFS and overall survival rates for the 65 patients were 81.4% and 98.4%, respectively. Machine learning–derived thresholds for baseline MTV and TLG were associated with inferior PFS (elevated MTV: hazard ratio [HR], 11.5; P = .019; elevated TLG: HR, 8.99; P = .005); other pretreatment clinical factors, including International Prognostic Index and bulky (>10 cm) disease, were not. On multivariable analysis, only TLG retained statistical significance (P = .049). Univariate analysis of posttreatment variables revealed that residual CT tumor volume, maximum standardized uptake value, and Deauville score were associated with PFS; a Deauville score of 5 remained significant on multivariable analysis (P = .006). A model combining baseline TLG and end-of-therapy Deauville score identified patients at increased risk of progression. PMID:29895624

Influence of microclimatic ammonia levels on productive performance of different broilers' breeds estimated with univariate and multivariate approaches.

PubMed

Soliman, Essam S; Moawed, Sherif A; Hassan, Rania A

2017-08-01

Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people's health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Ammonia levels were significantly higher (p< 0.01) in the Ross compared to the Hubbard breed farm, although no significant differences (p>0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (p< 0.01) during fall compared to winter irrespective of broiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p< 0.01), but not with the ambient temperature (r=-0.045; p>0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. The study revealed that broiler's growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers' growth performance parameters data using multivariate discriminant function analysis.

Influence of microclimatic ammonia levels on productive performance of different broilers’ breeds estimated with univariate and multivariate approaches

PubMed Central

Soliman, Essam S.; Moawed, Sherif A.; Hassan, Rania A.

2017-01-01

Background and Aim: Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people’s health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. Materials and Methods: A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Results: Ammonia levels were significantly higher (p< 0.01) in the Ross compared to the Hubbard breed farm, although no significant differences (p>0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (p< 0.01) during fall compared to winter irrespective of broiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p< 0.01), but not with the ambient temperature (r=−0.045; p>0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. Conclusion: The study revealed that broiler’s growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers’ growth performance parameters data using multivariate discriminant function analysis. PMID:28919677

Non-destructive analysis of the conformational differences among feedstock sources and their corresponding co-products from bioethanol production with molecular spectroscopy

NASA Astrophysics Data System (ADS)

Gamage, I. H.; Jonker, A.; Zhang, X.; Yu, P.

2014-01-01

The objective of this study was to determine the possibility of using molecular spectroscopy with multivariate technique as a fast method to detect the source effects among original feedstock sources of wheat and their corresponding co-products, wheat DDGS, from bioethanol production. Different sources of the bioethanol feedstock and their corresponding bioethanol co-products, three samples per source, were collected from the same newly-built bioethanol plant with current bioethanol processing technology. Multivariate molecular spectral analyses were carried out using agglomerative hierarchical cluster analysis (AHCA) and principal component analysis (PCA). The molecular spectral data of different feedstock sources and their corresponding co-products were compared at four different regions of ca. 1800-1725 cm-1 (carbonyl Cdbnd O ester, mainly related to lipid structure conformation), ca. 1725-1482 cm-1 (amide I and amide II region mainly related to protein structure conformation), ca. 1482-1180 cm-1 (mainly associated with structural carbohydrate) and ca. 1180-800 cm-1 (mainly related to carbohydrates) in complex plant-based system. The results showed that the molecular spectroscopy with multivariate technique could reveal the structural differences among the bioethanol feedstock sources and among their corresponding co-products. The AHCA and PCA analyses were able to distinguish the molecular structure differences associated with chemical functional groups among the different sources of the feedstock and their corresponding co-products. The molecular spectral differences indicated the differences in functional, biomolecular and biopolymer groups which were confirmed by wet chemical analysis. These biomolecular and biopolymer structural differences were associated with chemical and nutrient profiles and nutrient utilization and availability. Molecular spectral analyses had the potential to identify molecular structure difference among bioethanol feedstock sources and their corresponding co-products.

Positron emission tomography-computed tomography predictors of progression after DA-R-EPOCH for PMBCL.

PubMed

Pinnix, Chelsea C; Ng, Andrea K; Dabaja, Bouthaina S; Milgrom, Sarah A; Gunther, Jillian R; Fuller, C David; Smith, Grace L; Abou Yehia, Zeinab; Qiao, Wei; Wogan, Christine F; Akhtari, Mani; Mawlawi, Osama; Medeiros, L Jeffrey; Chuang, Hubert H; Martin-Doyle, William; Armand, Philippe; LaCasce, Ann S; Oki, Yasuhiro; Fanale, Michelle; Westin, Jason; Neelapu, Sattva; Nastoupil, Loretta

2018-06-12

Dose-adjusted rituximab plus etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin (DA-R-EPOCH) has produced good outcomes in primary mediastinal B-cell lymphoma (PMBCL), but predictors of resistance to this treatment are unclear. We investigated whether [ 18 F]fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) findings could identify patients with PMBCL who would not respond completely to DA-R-EPOCH. We performed a retrospective analysis of 65 patients with newly diagnosed stage I to IV PMBCL treated at 2 tertiary cancer centers who had PET-CT scans available before and after frontline therapy with DA-R-EPOCH. Pretreatment variables assessed included metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Optimal cutoff points for progression-free survival (PFS) were determined by a machine learning approach. Univariate and multivariable models were constructed to assess associations between radiographic variables and PFS. At a median follow-up of 36.6 months (95% confidence interval, 28.1-45.1), 2-year PFS and overall survival rates for the 65 patients were 81.4% and 98.4%, respectively. Machine learning-derived thresholds for baseline MTV and TLG were associated with inferior PFS (elevated MTV: hazard ratio [HR], 11.5; P = .019; elevated TLG: HR, 8.99; P = .005); other pretreatment clinical factors, including International Prognostic Index and bulky (>10 cm) disease, were not. On multivariable analysis, only TLG retained statistical significance ( P = .049). Univariate analysis of posttreatment variables revealed that residual CT tumor volume, maximum standardized uptake value, and Deauville score were associated with PFS; a Deauville score of 5 remained significant on multivariable analysis ( P = .006). A model combining baseline TLG and end-of-therapy Deauville score identified patients at increased risk of progression. © 2018 by The American Society of Hematology.

Different MR features for differentiation of intrahepatic mass-forming cholangiocarcinoma from hepatocellular carcinoma according to tumor size.

PubMed

Ni, Ting; Shang, Xiao-Sha; Wang, Wen-Tao; Hu, Xin-Xing; Zeng, Meng-Su; Rao, Sheng-Xiang

2018-06-05

To identify reliable magnetic resonance (MR) features for distinguishing mass-forming type of intrahepatic cholangiocarcinoma (IMCC) from hepatocellular carcinoma (HCC) based on tumor size. This retrospective study included 395 patients with pathologically confirmed IMCCs (n = 180) and HCCs (n = 215) who underwent pre-operative contrast-enhanced MRI including diffusion-weighted imaging (DWI). MR features were evaluated and clinical data were also recorded. All the characteristics were compared in small (≤3 cm) and large tumor (>3 cm) groups by univariate analysis and subsequently calculated by multivariable logistic regression analysis. Multivariable analysis revealed that rim arterial phase hyperenhancement [odds ratios (ORs) = 13.16], biliary dilation (OR = 23.42) and CA19-9 (OR = 21.45) were significant predictors of large IMCCs (n = 138), and washout appearance (OR = 0.036), enhancing capsule appearance (OR = 0.039), fat in mass (OR = 0.057), chronic liver disease (OR = 0.088) and alpha fetoprotein (OR = 0.019) were more frequently found in large HCCs (n = 143). For small IMCCs (n = 42) and HCCs (n = 72), rim arterial phase hyperenhancement (OR = 9.68), target appearance at DWI (OR = 12.51), alpha fetoprotein (OR = 0.12) and sex (OR = 0.20) were independent predictors in multivariate analysis. Valuable MR features and clinical factors varied for differential diagnosis of IMCCs and HCCs according to tumor size. Advances in knowledge: MR features for differential diagnosis of large IMCC and HCC (>3 cm) are in keeping with that recommended by LI-RADS. However, for small IMCCs and HCCs (≤3 cm), only rim enhancement on arterial phase and target appearance at DWI are reliable predictors.

Principal Component Analysis of Chlorophyll Content in Tobacco, Bean and Petunia Plants Exposed to Different Tropospheric Ozone Concentrations

NASA Astrophysics Data System (ADS)

Borowiak, Klaudia; Zbierska, Janina; Budka, Anna; Kayzer, Dariusz

2014-06-01

Three plant species were assessed in this study - ozone-sensitive and -resistant tobacco, ozone-sensitive petunia and bean. Plants were exposed to ambient air conditions for several weeks in two sites differing in tropospheric ozone concentrations in the growing season of 2009. Every week chlorophyll contents were analysed. Cumulative ozone effects on the chlorophyll content in relation to other meteorological parameters were evaluated using principal component analysis, while the relation between certain days of measurements of the plants were analysed using multivariate analysis of variance. Results revealed variability between plant species response. However, some similarities were noted. Positive relations of all chlorophyll forms to cumulative ozone concentration (AOT 40) were found for all the plant species that were examined. The chlorophyll b/a ratio revealed an opposite position to ozone concentration only in the ozone-resistant tobacco cultivar. In all the plant species the highest average chlorophyll content was noted after the 7th day of the experiment. Afterwards, the plants usually revealed various responses. Ozone-sensitive tobacco revealed decrease of chlorophyll content, and after few weeks of decline again an increase was observed. Probably, due to the accommodation for the stress factor. While during first three weeks relatively high levels of chlorophyll contents were noted in ozone-resistant tobacco. Petunia revealed a slow decrease of chlorophyll content and the lowest values at the end of the experiment. A comparison between the plant species revealed the highest level of chlorophyll contents in ozone-resistant tobacco.

Utility of Inflammatory Marker- and Nutritional Status-based Prognostic Factors for Predicting the Prognosis of Stage IV Gastric Cancer Patients Undergoing Non-curative Surgery.

PubMed

Mimatsu, Kenji; Fukino, Nobutada; Ogasawara, Yasuo; Saino, Yoko; Oida, Takatsugu

2017-08-01

The present study aimed to compare the utility of various inflammatory marker- and nutritional status-based prognostic factors, including many previous established prognostic factors, for predicting the prognosis of stage IV gastric cancer patients undergoing non-curative surgery. A total of 33 patients with stage IV gastric cancer who had undergone palliative gastrectomy and gastrojejunostomy were included in the study. Univariate and multivariate analyses were performed to evaluate the relationships between the mGPS, PNI, NLR, PLR, the CONUT, various clinicopathological factors and cancer-specific survival (CS). Among patients who received non-curative surgery, univariate analysis of CS identified the following significant risk factors: chemotherapy, mGPS and NLR, and multivariate analysis revealed that the mGPS was independently associated with CS. The mGPS was a more useful prognostic factor than the PNI, NLR, PLR and CONUT in patients undergoing non-curative surgery for stage IV gastric cancer. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Prognostic nutritional index is associated with survival after total gastrectomy for patients with gastric cancer.

PubMed

Ishizuka, Mitsuru; Oyama, Yusuke; Abe, Akihito; Tago, Kazuma; Tanaka, Genki; Kubota, Keiichi

2014-08-01

To investigate the influence of clinical characteristics including nutritional markers on postoperative survival in patients undergoing total gastrectomy (TG) for gastric cancer (GC). One hundred fifty-four patients were enrolled. Uni- and multivariate analyses using the Cox proportional hazard model were performed to explore the most valuable clinical characteristic that was associated with postoperative survival. Multivariate analysis using twelve clinical characteristics selected from univariate analyses revealed that age (≤ 72/>72), carcinoembryonic antigen (≤ 20/>20) (ng/ml), white blood cell count (≤ 9.5/>9.5) (× 10(3)/mm(3)), prognostic nutritional index (PNI) (≤ 45/>45) and lymph node metastasis (negative/positive) were associated with postoperative survival. Kaplan-Meier analysis and log-rank test showed that patients with higher PNI (>45) had a higher postoperative survival rate than those with lower PNI (≤ 45) (p<0.001). PNI is associated with postoperative survival of patients undergoing TG for GC and is able to divide such patients into two independent groups before surgery. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Watch what happens: using a web-based multimedia platform to enhance intraoperative learning and development of clinical reasoning.

PubMed

Fingeret, Abbey L; Martinez, Rebecca H; Hsieh, Christine; Downey, Peter; Nowygrod, Roman

2016-02-01

We aim to determine whether observed operations or internet-based video review predict improved performance in the surgery clerkship. A retrospective review of students' usage of surgical videos, observed operations, evaluations, and examination scores were used to construct an exploratory principal component analysis. Multivariate regression was used to determine factors predictive of clerkship performance. Case log data for 231 students revealed a median of 25 observed cases. Students accessed the web-based video platform a median of 15 times. Principal component analysis yielded 4 factors contributing 74% of the variability with a Kaiser-Meyer-Olkin coefficient of .83. Multivariate regression predicted shelf score (P < .0001), internal clinical skills examination score (P < .0001), subjective evaluations (P < .001), and video website utilization (P < .001) but not observed cases to be significantly associated with overall performance. Utilization of a web-based operative video platform during a surgical clerkship is an independently associated with improved clinical reasoning, fund of knowledge, and overall evaluation. Thus, this modality can serve as a useful adjunct to live observation. Copyright © 2016 Elsevier Inc. All rights reserved.

Síndrome metabólico y otros factores asociados a gonartrosis.

PubMed

Charles-Lozoya, Sergio; Treviño-Báez, Joaquín Darío; Ramos-Rivera, Jesús Alejandro; Rangel-Flores, Jesús María; Tamez-Montes, Juan Carlos; Brizuela-Ventura, Jesús Miguel

2017-01-01

To evaluate whether an association exists between gonarthrosis and metabolic syndrome X (MS) as well as other potential risk factors. Comparative cross-sectional study of 310 patients evaluated by pathology of knee grouped in patients with gonarthrosis and without it. Sociodemographic, anthropometric and laboratory data was obtained. Gonarthrosis was defined as a ≥ 2 score in Kellgren-Lawrence radiological scale, and MS was assessed using the International Diabetes Federation criteria. Odds ratio and logistic regression were used for bivariate and multivariate analysis respectively. The prevalence of MS in patients who had gonarthrosis was 79.9%, statistically higher than in patients without gonarthrosis (p = 0.001). Other factors that had a statistically higher frequency in this group included diabetes mellitus (p = 0.02) and hypertension (p = 0.02). Multivariate analysis revealed MS had an association with a higher prevalence of gonarthrosis (p = 0.003), while high density lipoproteins (p = 0.02) was associated with a lower prevalence. MS and its related alterations are associated to gonarthrosis; their adequate control could prevent patients from developing the disease. Copyright: © 2017 SecretarÍa de Salud

Comparative multivariate analysis of biometric traits of West African Dwarf and Red Sokoto goats.

PubMed

Yakubu, Abdulmojeed; Salako, Adebowale E; Imumorin, Ikhide G

2011-03-01

The population structure of 302 randomly selected West African Dwarf (WAD) and Red Sokoto (RS) goats was examined using multivariate morphometric analyses. This was to make the case for conservation, rational management and genetic improvement of these two most important Nigerian goat breeds. Fifteen morphometric measurements were made on each individual animal. RS goats were superior (P<0.05) to the WAD for the body size and skeletal proportions investigated. The phenotypic variability between the two breeds was revealed by their mutual responses in the principal components. While four principal components were extracted for WAD goats, three components were obtained for their RS counterparts with variation in the loading traits of each component for each breed. The Mahalanobis distance of 72.28 indicated a high degree of spatial racial separation in morphology between the genotypes. The Ward's option of the cluster analysis consolidated the morphometric distinctness of the two breeds. Application of selective breeding to genetic improvement would benefit from the detected phenotypic differentiation. Other implications for management and conservation of the goats are highlighted.

Correlates of HIV knowledge and Sexual risk behaviors among Female Military Personnel

PubMed Central

Essien, E. James; Monjok, Emmanuel; Chen, Hua; Abughosh, Susan; Ekong, Ernest; Peters, Ronald J.; Holmes, Laurens; Holstad, Marcia M.; Mgbere, Osaro

2010-01-01

Objective Uniformed services personnel are at an increased risk of HIV infection. We examined the HIV/AIDS knowledge and sexual risk behaviors among female military personnel to determine the correlates of HIV risk behaviors in this population. Method The study used a cross-sectional design to examine HIV/AIDS knowledge and sexual risk behaviors in a sample of 346 females drawn from two military cantonments in Southwestern Nigeria. Data was collected between 2006 and 2008. Using bivariate analysis and multivariate logistic regression, HIV/AIDS knowledge and sexual behaviors were described in relation to socio-demographic characteristics of the participants. Results Multivariate logistic regression analysis revealed that level of education and knowing someone with HIV/AIDS were significant (p<0.05) predictors of HIV knowledge in this sample. HIV prevention self-efficacy was significantly (P<0.05) predicted by annual income and race/ethnicity. Condom use attitudes were also significantly (P<0.05) associated with number of children, annual income, and number of sexual partners. Conclusion Data indicates the importance of incorporating these predictor variables into intervention designs. PMID:20387111

Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing

PubMed Central

Kujala, Jan; Sudre, Gustavo; Vartiainen, Johanna; Liljeström, Mia; Mitchell, Tom; Salmelin, Riitta

2014-01-01

Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG–fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing. PMID:24518260

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy.

PubMed

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. The results showed that 86.0% ([Formula: see text]) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Multivariable Regression Analysis in Schistosoma mansoni-Infected Individuals in the Sudan Reveals Unique Immunoepidemiological Profiles in Uninfected, egg+ and Non-egg+ Infected Individuals

PubMed Central

Wiszniewsky, Anna; Ritter, Manuel; Goreish, Ibtisam A.; Atti El Mekki, Misk El Yemen A.; Arriens, Sandra; Pfarr, Kenneth; Fimmers, Rolf; Doenhoff, Mike; Hoerauf, Achim; Layland, Laura E.

2016-01-01

Background In the Sudan, Schistosoma mansoni infections are a major cause of morbidity in school-aged children and infection rates are associated with available clean water sources. During infection, immune responses pass through a Th1 followed by Th2 and Treg phases and patterns can relate to different stages of infection or immunity. Methodology This retrospective study evaluated immunoepidemiological aspects in 234 individuals (range 4–85 years old) from Kassala and Khartoum states in 2011. Systemic immune profiles (cytokines and immunoglobulins) and epidemiological parameters were surveyed in n = 110 persons presenting patent S. mansoni infections (egg+), n = 63 individuals positive for S. mansoni via PCR in sera but egg negative (SmPCR+) and n = 61 people who were infection-free (Sm uninf). Immunoepidemiological findings were further investigated using two binary multivariable regression analysis. Principal Findings Nearly all egg+ individuals had no access to latrines and over 90% obtained water via the canal stemming from the Atbara River. With regards to age, infection and an egg+ status was linked to young and adolescent groups. In terms of immunology, S. mansoni infection per se was strongly associated with increased SEA-specific IgG4 but not IgE levels. IL-6, IL-13 and IL-10 were significantly elevated in patently-infected individuals and positively correlated with egg load. In contrast, IL-2 and IL-1β were significantly lower in SmPCR+ individuals when compared to Sm uninf and egg+ groups which was further confirmed during multivariate regression analysis. Conclusions/Significance Schistosomiasis remains an important public health problem in the Sudan with a high number of patent individuals. In addition, SmPCR diagnostics revealed another cohort of infected individuals with a unique immunological profile and provides an avenue for future studies on non-patent infection states. Future studies should investigate the downstream signalling pathways/mechanisms of IL-2 and IL-1β as potential diagnostic markers in order to distinguish patent from non-patent individuals. PMID:27152725

Lymphopenia Association With Gross Tumor Volume and Lung V5 and Its Effects on Non-Small Cell Lung Cancer Patient Outcomes

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

Tang, Chad; Liao, Zhongxing, E-mail: zliao@mdanderson.org; Gomez, Daniel

2014-08-01

Purpose: Radiation therapy (RT) can both suppress and stimulate the immune system. We sought to investigate the mechanisms underlying radiation-induced lymphopenia and its associations with patient outcomes in non-small cell lung cancer (NSCLC). Methods and Materials: Subjects consisted of 711 patients who had received definitive RT for NSCLC. A lymphocyte nadir was calculated as the minimum lymphocyte value measured during definitive RT. Associations between gross tumor volumes (GTVs) and lung dose-volume histogram (DVH) parameters with lymphocyte nadirs were assessed with Spearman correlation coefficients. Relationships between lymphocyte nadirs with overall survival (OS) and event free survival (EFS) were evaluated with Kaplan-Meiermore » analysis and compared with log-rank test results. Multivariate regressions were conducted with linear and Cox regression analyses. All variables were analyzed as continuous if possible. Results: Larger GTVs were correlated with lower lymphocyte nadirs regardless of concurrent chemotherapy receipt (with concurrent: r = −0.26, P<.0001; without: r = −0.48, P<.0001). Analyses of lung DVH parameters revealed significant correlations at lower doses (lung V5-V10: P<.0001) that incrementally decreased and became nonsignificant at higher doses (lung V60-V70: P>.05). Of note, no significant associations were detected between GTV and lung DVH parameters with total leukocyte, neutrophil, or monocyte nadirs during RT or with lymphocyte count prior to RT. Multivariate analysis revealed larger GTV (P<.0001), receipt of concurrent chemotherapy (P<.0001), twice-daily radiation fractionation (P=.02), and stage III disease (P=.05) to be associated with lower lymphocyte nadirs. On univariate analysis, patients with higher lymphocyte nadirs exhibited significantly improved OS (hazard ratio [HR] = 0.51 per 10{sup 3} lymphocytes/μL, P=.01) and EFS (HR = 0.46 per 10{sup 3} lymphocytes/μL, P<.0001). These differences held on multivariate analyses, controlling for common disease and treatment characteristics including GTV. Conclusions: Lower lymphocyte nadirs during definitive RT were associated with larger GTVs and worse patient outcomes.« less

Diversity pattern in Sesamum mutants selected for a semi-arid cropping system.

PubMed

Murty, B R; Oropeza, F

1989-02-01

Due to the complex requirements of moisture stress, substantial genetic diversity with a wide array of character combinations and effective simultaneous selection for several variables is necessary for improving the productivity and adaptation of a component crop in order for it to fit into a cropping system under semi-arid tropical conditions. Sesamum indicum L. is grown in Venezuela after rice/sorghum/or maize under such conditions. A mutation breeding program was undertaken using six locally adapted varieties to develop genotypes suitable for the above system. The diversity pattern for nine variables was assessed by multivariate analysis in 301 M4 progenies. Analysis of the characteristic roots and principal components in three methods of selection, i.e., M2 bulks (A), individual plant selection throughout (B), and selection in M3 for single variable (C), revealed differences in the pattern of variation between varieties, selection methods, and varieties x methods interactions. Method B was superior to the others and gave 17 of the 21 best M5 progenies. 'Piritu' and 'CF' varieties yielded the most productive progenies in M5 and M6. Diversity was large and selection was effective for such developmental traits as earliness and synchrony, combined with multiple disease resistance, which could be related to their importance by multivariate analyses. Considerable differences in the variety of character combinations among the high yielding. M5 progenies of 'CF' and 'Piritu' suggested possible further yield improvement. The superior response of 'Piritu' and 'CF' over other varieties in yield and adaptation was due to major changes in plant type and character associations. Multilocation testing of M5 generations revealed that the mutant progenies had a 40%-100% yield superiority over the parents; this was combined with earliness, synchrony, and multiple disease resistance, and was confirmed in the M6 generation grown on a commercial scale. This study showed that multivariate analysis is an effective tool for assessing diversity patterns, choice of appropriate variety, and selection methodology in order to make rapid progress in meeting the complex requirements of semi-arid cropping systems.

Investigating conflict in ICUs - Is the clinicians’ perspective enough?

PubMed Central

Schuster, Rachel A.; Hong, Seo Yeon; Arnold, Robert M.; White, Douglas B.

2013-01-01

Objective Most studies have assessed conflict between clinicians and surrogate decision makers in ICUs from only clinicians’ perspectives. It is unknown if surrogates’ perceptions differ from clinicians’. We sought to determine the degree of agreement between physicians and surrogates about conflict, and to identify predictors of physician-surrogate conflict. Design Prospective cohort study. Setting Four ICUs of two hospitals in San Francisco, California. Patients 230 surrogate decision makers and 100 physicians of 175 critically ill patients. Measurements Questionnaires addressing participants’ perceptions of whether there was physician-surrogate conflict, as well as attitudes and preferences about clinician-surrogate communication; kappa scores to quantify physician-surrogate concordance about the presence of conflict; and hierarchical multivariate modeling to determine predictors of conflict. Main Results Either the physician or surrogate identified conflict in 63% of cases. Physicians were less likely to perceive conflict than surrogates (27.8% vs 42.3%; p=0.007). Agreement between physicians and surrogates about conflict was poor (kappa = 0.14). Multivariable analysis with surrogate-assessed conflict as the outcome revealed that higher levels of surrogates’ satisfaction with physicians’ bedside manner were associated with lower odds of conflict (OR: 0.75 per 1 point increase in satisfaction, 95% CI 0.59–0.96). Multivariable analysis with physician-assessed conflict as the outcome revealed that the surrogate having felt discriminated against in the healthcare setting was associated with higher odds of conflict (OR 17.5, 95% CI 1.6–190.1) while surrogates’ satisfaction with physicians’ bedside manner was associated with lower odds of conflict (0–10 scale, OR 0.76 per 1 point increase, 95% CI 0.58–0.99). Conclusions Conflict between physicians and surrogates is common in ICUs. There is little agreement between physicians and surrogates about whether physician-surrogate conflict has occurred. Further work is needed to develop reliable and valid methods to assess conflict. In the interim, future studies should assess conflict from the perspective of both clinicians and surrogates. PMID:24434440

Epidemiological study of phylogenetic transmission clusters in a local HIV-1 epidemic reveals distinct differences between subtype B and non-B infections.

PubMed

Chalmet, Kristen; Staelens, Delfien; Blot, Stijn; Dinakis, Sylvie; Pelgrom, Jolanda; Plum, Jean; Vogelaers, Dirk; Vandekerckhove, Linos; Verhofstede, Chris

2010-09-07

The number of HIV-1 infected individuals in the Western world continues to rise. More in-depth understanding of regional HIV-1 epidemics is necessary for the optimal design and adequate use of future prevention strategies. The use of a combination of phylogenetic analysis of HIV sequences, with data on patients' demographics, infection route, clinical information and laboratory results, will allow a better characterization of individuals responsible for local transmission. Baseline HIV-1 pol sequences, obtained through routine drug-resistance testing, from 506 patients, newly diagnosed between 2001 and 2009, were used to construct phylogenetic trees and identify transmission-clusters. Patients' demographics, laboratory and clinical data, were retrieved anonymously. Statistical analysis was performed to identify subtype-specific and transmission-cluster-specific characteristics. Multivariate analysis showed significant differences between the 59.7% of individuals with subtype B infection and the 40.3% non-B infected individuals, with regard to route of transmission, origin, infection with Chlamydia (p = 0.01) and infection with Hepatitis C virus (p = 0.017). More and larger transmission-clusters were identified among the subtype B infections (p < 0.001). Overall, in multivariate analysis, clustering was significantly associated with Caucasian origin, infection through homosexual contact and younger age (all p < 0.001). Bivariate analysis additionally showed a correlation between clustering and syphilis (p < 0.001), higher CD4 counts (p = 0.002), Chlamydia infection (p = 0.013) and primary HIV (p = 0.017). Combination of phylogenetics with demographic information, laboratory and clinical data, revealed that HIV-1 subtype B infected Caucasian men-who-have-sex-with-men with high prevalence of sexually transmitted diseases, account for the majority of local HIV-transmissions. This finding elucidates observed epidemiological trends through molecular analysis, and justifies sustained focus in prevention on this high risk group.

Survival analysis of platinum-refractory patients with advanced esophageal cancer treated with docetaxel or best supportive care alone: a retrospective study.

PubMed

Moriwaki, T; Kajiwara, T; Matsumoto, T; Suzuki, H; Hiroshima, Y; Matsuda, K; Hirai, S; Yamamoto, Y; Yamada, T; Sugaya, A; Kobayashi, M; Endo, S; Ishige, K; Nishina, T; Hyodo, I

2014-01-01

The survival benefit of second-line chemotherapy with docetaxel in platinum-refractory patients with advanced esophageal cancer (AEC) remains unclear. A retrospective analysis of AEC patients with Eastern Cooperative Oncology Group performance status (PS)≤2 was performed, and major organ functions were preserved, who determined to receive docetaxel or best supportive care (BSC) alone after failure of platinum-based chemotherapy. The post-progression survival (PPS), defined as survival time after disease progression following platinum-based chemotherapy, was analyzed by multivariate Cox regression analysis using factors identified as significant in univariate analysis of various 20 characteristics (age, sex, PS, primary tumor location, etc) including Glasgow prognostic score (GPS), which is a well-known prognostic factor in many malignant tumors. Sixty-six and 45 patients were determined to receive docetaxel and BSC between January 2007 and December 2011, respectively. The median PPS was 5.4 months (95% confidence interval [CI] 4.8-6.0) in the docetaxel group and 3.3 months (95% CI 2.5-4.0) in the BSC group (hazard ratio [HR] 0.56, 95% CI 0.38-0.84, P=0.005). Univariate analysis revealed six significant factors: treatment, PS, GPS, number of metastatic organs, liver metastasis, and bone metastasis. Multivariate analysis including these significant factors revealed three independent prognostic factors: docetaxel treatment (HR 0.62, 95% CI 0.39-0.99, P=0.043), better GPS (HR 0.61, 95% CI 0.46-0.81, P=0.001), and no bone metastasis (HR 0.31, 95% CI 0.15-0.68, P=0.003). There was a trend for PPS in favor of the docetaxel group compared with patients who refused docetaxel treatment in the BSC group (adjusted HR 0.61, 95% CI 0.29-1.29, P=0.20). Docetaxel treatment may have prolonged survival in platinum-refractory patients with AEC. © 2014 International Society for Diseases of the Esophagus.

Predicting Outcomes After Chemo-Embolization in Patients with Advanced-Stage Hepatocellular Carcinoma: An Evaluation of Different Radiologic Response Criteria

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

Gunn, Andrew J., E-mail: agunn@uabmc.edu; Sheth, Rahul A.; Luber, Brandon

2017-01-15

PurposeThe purpse of this study was to evaluate the ability of various radiologic response criteria to predict patient outcomes after trans-arterial chemo-embolization with drug-eluting beads (DEB-TACE) in patients with advanced-stage (BCLC C) hepatocellular carcinoma (HCC).Materials and methodsHospital records from 2005 to 2011 were retrospectively reviewed. Non-infiltrative lesions were measured at baseline and on follow-up scans after DEB-TACE according to various common radiologic response criteria, including guidelines of the World Health Organization (WHO), Response Evaluation Criteria in Solid Tumors (RECIST), the European Association for the Study of the Liver (EASL), and modified RECIST (mRECIST). Statistical analysis was performed to see which,more » if any, of the response criteria could be used as a predictor of overall survival (OS) or time-to-progression (TTP).Results75 patients met inclusion criteria. Median OS and TTP were 22.6 months (95 % CI 11.6–24.8) and 9.8 months (95 % CI 7.1–21.6), respectively. Univariate and multivariate Cox analyses revealed that none of the evaluated criteria had the ability to be used as a predictor for OS or TTP. Analysis of the C index in both univariate and multivariate models showed that the evaluated criteria were not accurate predictors of either OS (C-statistic range: 0.51–0.58 in the univariate model; range: 0.54–0.58 in the multivariate model) or TTP (C-statistic range: 0.55–0.59 in the univariate model; range: 0.57–0.61 in the multivariate model).ConclusionCurrent response criteria are not accurate predictors of OS or TTP in patients with advanced-stage HCC after DEB-TACE.« less

Predicting Outcomes After Chemo-Embolization in Patients with Advanced-Stage Hepatocellular Carcinoma: An Evaluation of Different Radiologic Response Criteria.

PubMed

Gunn, Andrew J; Sheth, Rahul A; Luber, Brandon; Huynh, Minh-Huy; Rachamreddy, Niranjan R; Kalva, Sanjeeva P

2017-01-01

The purpse of this study was to evaluate the ability of various radiologic response criteria to predict patient outcomes after trans-arterial chemo-embolization with drug-eluting beads (DEB-TACE) in patients with advanced-stage (BCLC C) hepatocellular carcinoma (HCC). Hospital records from 2005 to 2011 were retrospectively reviewed. Non-infiltrative lesions were measured at baseline and on follow-up scans after DEB-TACE according to various common radiologic response criteria, including guidelines of the World Health Organization (WHO), Response Evaluation Criteria in Solid Tumors (RECIST), the European Association for the Study of the Liver (EASL), and modified RECIST (mRECIST). Statistical analysis was performed to see which, if any, of the response criteria could be used as a predictor of overall survival (OS) or time-to-progression (TTP). 75 patients met inclusion criteria. Median OS and TTP were 22.6 months (95 % CI 11.6-24.8) and 9.8 months (95 % CI 7.1-21.6), respectively. Univariate and multivariate Cox analyses revealed that none of the evaluated criteria had the ability to be used as a predictor for OS or TTP. Analysis of the C index in both univariate and multivariate models showed that the evaluated criteria were not accurate predictors of either OS (C-statistic range: 0.51-0.58 in the univariate model; range: 0.54-0.58 in the multivariate model) or TTP (C-statistic range: 0.55-0.59 in the univariate model; range: 0.57-0.61 in the multivariate model). Current response criteria are not accurate predictors of OS or TTP in patients with advanced-stage HCC after DEB-TACE.

THE AFRICAN DESCENT AND GLAUCOMA EVALUATION STUDY (ADAGES): PREDICTORS OF VISUAL FIELD DAMAGE IN GLAUCOMA SUSPECTS

PubMed Central

Khachatryan, Naira; Medeiros, Felipe A.; Sharpsten, Lucie; Bowd, Christopher; Sample, Pamela A.; Liebmann, Jeffrey M.; Girkin, Christopher A.; Weinreb, Robert N.; Miki, Atsuya; Hammel, Na’ama; Zangwill, Linda M.

2015-01-01

Purpose To evaluate racial differences in the development of visual field (VF) damage in glaucoma suspects. Design Prospective, observational cohort study. Methods Six hundred thirty six eyes from 357 glaucoma suspects with normal VF at baseline were included from the multicenter African Descent and Glaucoma Evaluation Study (ADAGES). Racial differences in the development of VF damage were examined using multivariable Cox Proportional Hazard models. Results Thirty one (25.4%) of 122 African descent participants and 47 (20.0%) of 235 European descent participants developed VF damage (p=0.078). In multivariable analysis, worse baseline VF mean deviation, higher mean arterial pressure during follow up, and a race *mean intraocular pressure (IOP) interaction term were significantly associated with the development of VF damage suggesting that racial differences in the risk of VF damage varied by IOP. At higher mean IOP levels, race was predictive of the development of VF damage even after adjusting for potentially confounding factors. At mean IOPs during follow-up of 22, 24 and 26 mmHg, multivariable hazard ratios (95%CI) for the development of VF damage in African descent compared to European descent subjects were 2.03 (1.15–3.57), 2.71 (1.39–5.29), and 3.61 (1.61–8.08), respectively. However, at lower mean IOP levels (below 22 mmHg) during follow-up, African descent was not predictive of the development of VF damage. Conclusion In this cohort of glaucoma suspects with similar access to treatment, multivariate analysis revealed that at higher mean IOP during follow-up, individuals of African descent were more likely to develop VF damage than individuals of European descent. PMID:25597839

Multivariate Genetic Correlates of the Auditory Paired Stimuli-Based P2 Event-Related Potential in the Psychosis Dimension From the BSNIP Study.

PubMed

Mokhtari, Mohammadreza; Narayanan, Balaji; Hamm, Jordan P; Soh, Pauline; Calhoun, Vince D; Ruaño, Gualberto; Kocherla, Mohan; Windemuth, Andreas; Clementz, Brett A; Tamminga, Carol A; Sweeney, John A; Keshavan, Matcheri S; Pearlson, Godfrey D

2016-05-01

The complex molecular etiology of psychosis in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is not well defined, presumably due to their multifactorial genetic architecture. Neurobiological correlates of psychosis can be identified through genetic associations of intermediate phenotypes such as event-related potential (ERP) from auditory paired stimulus processing (APSP). Various ERP components of APSP are heritable and aberrant in SZ, PBP and their relatives, but their multivariate genetic factors are less explored. We investigated the multivariate polygenic association of ERP from 64-sensor auditory paired stimulus data in 149 SZ, 209 PBP probands, and 99 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Multivariate association of 64-channel APSP waveforms with a subset of 16 999 single nucleotide polymorphisms (SNPs) (reduced from 1 million SNP array) was examined using parallel independent component analysis (Para-ICA). Biological pathways associated with the genes were assessed using enrichment-based analysis tools. Para-ICA identified 2 ERP components, of which one was significantly correlated with a genetic network comprising multiple linearly coupled gene variants that explained ~4% of the ERP phenotype variance. Enrichment analysis revealed epidermal growth factor, endocannabinoid signaling, glutamatergic synapse and maltohexaose transport associated with P2 component of the N1-P2 ERP waveform. This ERP component also showed deficits in SZ and PBP. Aberrant P2 component in psychosis was associated with gene networks regulating several fundamental biologic functions, either general or specific to nervous system development. The pathways and processes underlying the gene clusters play a crucial role in brain function, plausibly implicated in psychosis. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Population differences in the postcrania of modern South Africans and the implications for ancestry estimation.

PubMed

Liebenberg, Leandi; L'Abbé, Ericka N; Stull, Kyra E

2015-12-01

The cranium is widely recognized as the most important skeletal element to use when evaluating population differences and estimating ancestry. However, the cranium is not always intact or available for analysis, which emphasizes the need for postcranial alternatives. The purpose of this study was to quantify postcraniometric differences among South Africans that can be used to estimate ancestry. Thirty-nine standard measurements from 11 postcranial bones were collected from 360 modern black, white and coloured South Africans; the sex and ancestry distribution were equal. Group differences were explored with analysis of variance (ANOVA) and Tukey's honestly significant difference (HSD) test. Linear and flexible discriminant analysis (LDA and FDA, respectively) were conducted with bone models as well as numerous multivariate subsets to identify the model and method that yielded the highest correct classifications. Leave-one-out (LDA) and k-fold (k=10; FDA) cross-validation with equal priors were used for all models. ANOVA and Tukey's HSD results reveal statistically significant differences between at least two of the three groups for the majority of the variables, with varying degrees of group overlap. Bone models, which consisted of all measurements per bone, resulted in low accuracies that ranged from 46% to 63% (LDA) and 41% to 66% (FDA). In contrast, the multivariate subsets, which consisted of different variable combinations from all elements, achieved accuracies as high as 85% (LDA) and 87% (FDA). Thus, when using a multivariate approach, the postcranial skeleton can distinguish among three modern South African groups with high accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a 'black box' approach and how to avoid them

NASA Astrophysics Data System (ADS)

Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.

2018-06-01

The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Multivariate Cluster Analysis.

ERIC Educational Resources Information Center

McRae, Douglas J.

Procedures for grouping students into homogeneous subsets have long interested educational researchers. The research reported in this paper is an investigation of a set of objective grouping procedures based on multivariate analysis considerations. Four multivariate functions that might serve as criteria for adequate grouping are given and…

Keratins 17 and 19 expression as prognostic markers in oral squamous cell carcinoma.

PubMed

Coelho, B A; Peterle, G T; Santos, M; Agostini, L P; Maia, L L; Stur, E; Silva, C V M; Mendes, S O; Almança, C C J; Freitas, F V; Borçoi, A R; Archanjo, A B; Mercante, A M C; Nunes, F D; Carvalho, M B; Tajara, E H; Louro, I D; Silva-Conforti, A M A

2015-11-25

Five-year survival rates for oral squamous cell carcinoma (OSCC) are 30% and the mortality rate is 50%. Immunohistochemistry panels are used to evaluate proliferation, vascularization, apoptosis, HPV infection, and keratin expression, which are important markers of malignant progression. Keratins are a family of intermediate filaments predominantly expressed in epithelial cells and have an essential role in mechanical support and cytoskeleton formation, which is essential for the structural integrity and stability of the cell. In this study, we analyzed the expressions of keratins 17 and 19 (K17 and K19) by immunohistochemistry in tumoral and non-tumoral tissues from patients with OSCC. The results show that expression of these keratins is higher in tumor tissues compared to non-tumor tissues. Positive K17 expression correlates with lymph node metastasis and multivariate analysis confirmed this relationship, revealing a 6-fold increase in lymph node metastasis when K17 is expressed. We observed a correlation between K17 expression with disease-free survival and disease-specific death in patients who received surgery and radiotherapy. Multivariate analysis revealed that low expression of K17 was an independent marker for early disease relapse and disease-specific death in patients treated with surgery and radiotherapy, with an approximately 4-fold increased risk when compared to high K17 expression. Our results suggest a potential role for K17 and K19 expression profiles as tumor prognostic markers in OSCC patients.

Psychological well-being and social support in chronic myeloid leukemia patients receiving lifelong targeted therapies.

PubMed

Efficace, Fabio; Breccia, Massimo; Cottone, Francesco; Okumura, Iris; Doro, Maribel; Riccardi, Francesca; Rosti, Gianantonio; Baccarani, Michele

2016-12-01

The main objective of this study was to investigate whether social support is independently associated with psychological well-being in chronic myeloid leukemia (CML) patients. Secondary objectives were to compare the psychological well-being profile of CML patients with that of their peers in general population and to examine possible age- and sex-related differences. Analysis was performed on 417 patients in treatment with lifelong molecularly targeted therapies. Mean age of patients analyzed was 56 years (range 19-87 years) and 247 (59 %) were male and 170 (41 %) were female. Social support was assessed with the Multidimensional Scale of Perceived Social Support and psychological well-being was evaluated with the short version of the Psychological General Well-Being Index. Descriptive statistics and multivariate logistic regression analyses were used. Multivariate logistic regression analysis revealed that a greater social support was independently associated with lower anxiety and depression, as well as with higher positive well-being, self-control, and vitality (p < 0.001). Female patients reported statistically significant worse outcomes in all dimensions of psychological well-being. Age- and sex-adjusted comparisons with population norms revealed that depression (ES = -0.42, p < 0.001) and self-control (ES = -0.48, p < 0.001) were the two main impaired psychological dimensions. This study indicates that social support is a critical factor associated with psychological well-being of CML patients treated with modern lifelong targeted therapies.

Comparative forensic soil analysis of New Jersey state parks using a combination of simple techniques with multivariate statistics.

PubMed

Bonetti, Jennifer; Quarino, Lawrence

2014-05-01

This study has shown that the combination of simple techniques with the use of multivariate statistics offers the potential for the comparative analysis of soil samples. Five samples were obtained from each of twelve state parks across New Jersey in both the summer and fall seasons. Each sample was examined using particle-size distribution, pH analysis in both water and 1 M CaCl2 , and a loss on ignition technique. Data from each of the techniques were combined, and principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for multivariate data transformation. Samples from different locations could be visually differentiated from one another using these multivariate plots. Hold-one-out cross-validation analysis showed error rates as low as 3.33%. Ten blind study samples were analyzed resulting in no misclassifications using Mahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications. © 2014 American Academy of Forensic Sciences.

Generating level-dependent models of cervical and thoracic spinal cord injury: Exploring the interplay of neuroanatomy, physiology, and function.

PubMed

Wilcox, Jared T; Satkunendrarajah, Kajana; Nasirzadeh, Yasmin; Laliberte, Alex M; Lip, Alyssa; Cadotte, David W; Foltz, Warren D; Fehlings, Michael G

2017-09-01

The majority of spinal cord injuries (SCI) occur at the cervical level, which results in significant impairment. Neurologic level and severity of injury are primary endpoints in clinical trials; however, how level-specific damages relate to behavioural performance in cervical injury is incompletely understood. We hypothesized that ascending level of injury leads to worsening forelimb performance, and correlates with loss of neural tissue and muscle-specific neuron pools. A direct comparison of multiple models was made with injury realized at the C5, C6, C7 and T7 vertebral levels using clip compression with sham-operated controls. Animals were assessed for 10weeks post-injury with numerous (40) outcome measures, including: classic behavioural tests, CatWalk, non-invasive MRI, electrophysiology, histologic lesion morphometry, neuron counts, and motor compartment quantification, and multivariate statistics on the total dataset. Histologic staining and T1-weighted MR imaging revealed similar structural changes and distinct tissue loss with cystic cavitation across all injuries. Forelimb tests, including grip strength, F-WARP motor scale, Inclined Plane, and forelimb ladder walk, exhibited stratification between all groups and marked impairment with C5 and C6 injuries. Classic hindlimb tests including BBB, hindlimb ladder walk, bladder recovery, and mortality were not different between cervical and thoracic injuries. CatWalk multivariate gait analysis showed reciprocal and progressive changes forelimb and hindlimb function with ascending level of injury. Electrophysiology revealed poor forelimb axonal conduction in cervical C5 and C6 groups alone. The cervical enlargement (C5-T2) showed progressive ventral horn atrophy and loss of specific motor neuron populations with ascending injury. Multivariate statistics revealed a robust dataset, rank-order contribution of outcomes, and allowed prediction of injury level with single-level discrimination using forelimb performance and neuron counts. Level-dependent models were generated using clip-compression SCI, with marked and reliable differences in forelimb performance and specific neuron pool loss. Copyright © 2017 Elsevier Inc. All rights reserved.

Combined high-field intraoperative magnetic resonance imaging and endoscopy increase extent of resection and progression-free survival for pituitary adenomas

PubMed Central

Sylvester, Peter T.; Evans, John A.; Zipfel, Gregory J.; Chole, Richard A.; Uppaluri, Ravindra; Haughey, Bruce H.; Getz, Anne E.; Silverstein, Julie; Rich, Keith M.; Kim, Albert H.; Dacey, Ralph G.

2014-01-01

Purpose The clinical benefit of combined intraoperative magnetic resonance imaging (iMRI) and endoscopy for transsphenoidal pituitary adenoma resection has not been completely characterized. This study assessed the impact of microscopy, endoscopy, and/or iMRI on progression-free survival, extent of resection status (gross-, near-, and subtotal resection), and operative complications. Methods Retrospective analyses were performed on 446 transsphenoidal pituitary adenoma surgeries at a single institution between 1998 and 2012. Multivariate analyses were used to control for baseline characteristics, differences during extent of resection status, and progression-free survival analysis. Results Additional surgery was performed after iMRI in 56/156 cases (35.9 %), which led to increased extent of resection status in 15/156 cases (9.6 %). Multivariate ordinal logistic regression revealed no increase in extent of resection status following iMRI or endoscopy alone; however, combining these modalities increased extent of resection status (odds ratio 2.05, 95 % CI 1.21–3.46) compared to conventional transsphenoidal microsurgery. Multivariate Cox regression revealed that reduced extent of resection status shortened progression-free survival for near- versus gross-total resection [hazard ratio (HR) 2.87, 95 % CI 1.24–6.65] and sub- versus near-total resection (HR 2.10; 95 % CI 1.00–4.40). Complication comparisons between microscopy, endoscopy, and iMRI revealed increased perioperative deaths for endoscopy versus microscopy (4/209 and 0/237, respectively), but this difference was non-significant considering multiple post hoc comparisons (Fisher exact, p = 0.24). Conclusions Combined use of endoscopy and iMRI increased pituitary adenoma extent of resection status compared to conventional transsphenoidal microsurgery, and increased extent of resection status was associated with longer progression-free survival. Treatment modality combination did not significantly impact complication rate. PMID:24599833

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

Trochanteric entry femoral nails yield better femoral version and lower revision rates-A large cohort multivariate regression analysis.

PubMed

Yoon, Richard S; Gage, Mark J; Galos, David K; Donegan, Derek J; Liporace, Frank A

2017-06-01

Intramedullary nailing (IMN) has become the standard of care for the treatment of most femoral shaft fractures. Different IMN options include trochanteric and piriformis entry as well as retrograde nails, which may result in varying degrees of femoral rotation. The objective of this study was to analyze postoperative femoral version between three types of nails and to delineate any significant differences in femoral version (DFV) and revision rates. Over a 10-year period, 417 patients underwent IMN of a diaphyseal femur fracture (AO/OTA 32A-C). Of these patients, 316 met inclusion criteria and obtained postoperative computed tomography (CT) scanograms to calculate femoral version and were thus included in the study. In this study, our main outcome measure was the difference in femoral version (DFV) between the uninjured limb and the injured limb. The effect of the following variables on DFV and revision rates were determined via univariate, multivariate, and ordinal regression analyses: gender, age, BMI, ethnicity, mechanism of injury, operative side, open fracture, and table type/position. Statistical significance was set at p<0.05. A total of 316 patients were included. Piriformis entry nails made up the majority (n=141), followed by retrograde (n=108), then trochanteric entry nails (n=67). Univariate regression analysis revealed that a lower BMI was significantly associated with a lower DFV (p=0.006). Controlling for possible covariables, multivariate analysis yielded a significantly lower DFV for trochanteric entry nails than piriformis or retrograde nails (7.9±6.10 vs. 9.5±7.4 vs. 9.4±7.8°, p<0.05). Using revision as an endpoint, trochanteric entry nails also had a significantly lower revision rate, even when controlling for all other variables (p<0.05). Comparative, objective comparisons between DFV between different nails based on entry point revealed that trochanteric nails had a significantly lower DFV and a lower revision rate, even after regression analysis. However, this is not to state that the other nail types exhibited abnormal DFV. Translation to the clinical impact of a few degrees of DFV is also unknown. Future studies to more in-depth study the intricacies of femoral version may lead to improved technology in addition to potentially improved clinical outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Starch as a major integrator in the regulation of plant growth

PubMed Central

Sulpice, Ronan; Pyl, Eva-Theresa; Ishihara, Hirofumi; Trenkamp, Sandra; Steinfath, Matthias; Witucka-Wall, Hanna; Gibon, Yves; Usadel, Björn; Poree, Fabien; Piques, Maria Conceição; Von Korff, Maria; Steinhauser, Marie Caroline; Keurentjes, Joost J. B.; Guenther, Manuela; Hoehne, Melanie; Selbig, Joachim; Fernie, Alisdair R.; Altmann, Thomas; Stitt, Mark

2009-01-01

Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1-phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production. PMID:19506259

Propensity score analysis of recurrence for neutrophil-to-lymphocyte ratio in colorectal cancer.

PubMed

Balde, Alpha I; Fang, Suzhen; He, Linyun; Cai, Zhai; Han, Shuai; Wang, Weiwei; Li, Zhou; Kang, Liang

2017-11-01

The perioperative serum neutrophil-to-lymphocyte ratio (NLR) has been proposed to predict adverse prognosis in colorectal cancer (CRC). However, its interpretation remains unclear. The present study aimed to clarify the prognostic value of NLR in predicting survival among CRC patients. A single-centre, retrospective, propensity score-matched study of adenocarcinoma patients who underwent D3 lymphadenectomy via laparoscopic or open surgery between 2010 and 2016 was conducted. A cutoff of 3.5 was used based on the receiver operating characteristic curve. To overcome selection biases, we performed a 1:1 match using six covariates. The high-preoperative NLR group had a higher recurrence rate than the low group (P < 0.001). Univariate analysis showed that increased NLR (P < 0.001), N1 (P = 0.016), and N2 (P < 0.001) were associated with worse recurrence-free survival (RFS). Multivariate analysis showed that N2 (hazard ratio [HR], 2.492; P = 0.008) was an adverse prognostic factor for RFS. Univariate analysis for overall survival (OS) revealed that high perioperative NLR (P = 0.001), N1 (P = 0.01), N2 (P < 0.001), and distant metastasis (P < 0.001) were adverse prognostic factors. Subsequent multivariate analysis showed that M1 (HR, 3.973; P < 0.001) and N2 (HR, 2.381; P = 0.013) were highly adverse factors for OS. Clinical assessments performed during a 21.14 (±16.20)-mo follow-up revealed that OS (P = 0.001) and RFS (P < 0.001) were worse in the high-perioperative group than in the low group between the matched groups. An elevated preoperative NLR is a strong predictor of worse RFS and OS in CRC patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Chemokine-like factor-like MARVEL transmembrane domain-containing 3 expression is associated with a favorable prognosis in esophageal squamous cell carcinoma.

PubMed

Han, Tianci; Shu, Tianci; Dong, Siyuan; Li, Peiwen; Li, Weinan; Liu, Dali; Qi, Ruiqun; Zhang, Shuguang; Zhang, Lin

2017-05-01

Decreased expression of human chemokine-like factor-like MARVEL transmembrane domain-containing 3 (CMTM3) has been identified in a number of human tumors and tumor cell lines, including gastric and testicular cancer, and PC3, CAL27 and Tca-83 cell lines. However, the association between CMTM3 expression and the clinicopathological features and prognosis of esophageal squamous cell carcinoma (ESCC) patients remains unclear. The aim of the present study was to investigate the correlation between CMTM3 expression and clinicopathological parameters and prognosis in ESCC. CMTM3 mRNA and protein expression was analyzed in ESCC and paired non-tumor tissues by quantitative real-time polymerase chain reaction, western blotting and immunohistochemical analysis. The Kaplan-Meier method was used to plot survival curves and the Cox proportional hazards regression model was also used for univariate and multivariate survival analysis. The results revealed that CMTM3 mRNA and protein expression levels were lower in 82.5% (30/40) and 75% (30/40) of ESCC tissues, respectively, when compared with matched non-tumor tissues. Statistical analysis demonstrated that CMTM3 expression was significantly correlated with lymph node metastasis (P=0.002) and clinical stage (P<0.001) in ESCC tissues. Furthermore, the survival time of ESCC patients exhibiting low CMTM3 expression was significantly shorter than that of ESCC patients exhibiting high CMTM3 expression (P=0.01). In addition, Kaplan-Meier survival analysis revealed that the overall survival time of patients exhibiting low CMTM3 expression was significantly decreased compared with patients exhibiting high CMTM3 expression (P=0.010). Cox multivariate analysis indicated that CMTM3 protein expression was an independent prognostic predictor for ESCC after resection. This study indicated that CMTM3 expression is significantly decreased in ESCC tissues and CMTM3 protein expression in resected tumors may present an effective prognostic biomarker.

Analysis techniques for multivariate root loci. [a tool in linear control systems

NASA Technical Reports Server (NTRS)

Thompson, P. M.; Stein, G.; Laub, A. J.

1980-01-01

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

Methods for presentation and display of multivariate data

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

Methods for the presentation and display of multivariate data are discussed with emphasis placed on the multivariate analysis of variance problems and the Hotelling T(2) solution in the two-sample case. The methods utilize the concepts of stepwise discrimination analysis and the computation of partial correlation coefficients.

A Primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists

ERIC Educational Resources Information Center

Warne, Russell T.

2014-01-01

Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant.

PubMed

Zamani, Abbas Ali; Yaftian, Mohammad Reza; Parizanganeh, Abdolhossein

2012-12-17

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area.

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant

PubMed Central

2012-01-01

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area. PMID:23369182

Trends, Frequency, and Nature of Surgeon-Reported Conflicts of Interest in Plastic Surgery.

PubMed

Lopez, Joseph; Musavi, Leila; Quan, Amy; Calotta, Nicholas; Juan, Ilona; Park, Angela; Tufaro, Anthony P; May, James W; Dorafshar, Amir H

2017-10-01

The purpose of this study was to identify types and trends in industry sponsorship of plastic surgery research since the establishment of conflict-of-interest reporting policies in plastic surgery. The authors analyzed the frequency and types of self-reported conflicts of interest in the plastic surgery literature since the adoption of reporting policies in 2007. All original articles that met the authors' inclusion criteria and were published in the following three journals from 2008 to 2013 were included: Annals of Plastic Surgery, Plastic and Reconstructive Surgery, and Journal of Plastic, Reconstructive & Aesthetic Surgery. A multivariate regression analysis was performed to determine what study-specific variables were associated with conflict-of-interest disclosures. A total of 3722 articles were analyzed. The incidence of conflicts of interest increased from 14 percent in 2008 to 24 percent in 2009. However, thereafter, the incidence of conflicts of interest decreased steadily from 21 percent in 2010 to 9 percent in 2013. Furthermore, the authors' analysis revealed that from 2008 to 2013, industry decreased direct research support but steadily increased the rate of consultantships (p < 0.001). A multivariate regression analysis revealed that, after adjusting for potential confounders, self-reported conflicts of interest have decreased since 2008 (p = 0.03) and the prevalence of conflicts of interest differs by plastic surgery subspecialty (p < 0.0001), country of origin (p < 0.0001), and journal of publication (p = 0.05). If self-reporting of conflicts of interest is assumed to be accurate, the number of surgeon-reported conflicts of interest in plastic surgery declined overall. Although the absolute number of consultantships did not change, the rate of consultantships rather than direct research support increased over this period.

Use of trastuzumab as an adjuvant/neoadjuvant therapy in patients with HER2-positive breast cancer in China: The Nvwa study.

PubMed

Li, Junjie; Shao, Zhimin; Xu, Binghe; Jiang, Zefei; Cui, Shude; Zhang, Jin; Liao, Ning; Jiang, Jun; Wang, Yongsheng; Ouyang, Quchang; Ying, Ziwei

2018-05-01

The aim of this study was to understand current trends in trastuzumab use in China as a neoadjuvant/adjuvant therapy for human epidermal growth factor receptor-2 positive (HER2+) breast cancer and identify factors influencing trastuzumab use.This was a retrospective, multicenter, cross-sectional study of patients diagnosed with HER2+ breast cancer (stage I-III), between July 2013 and June 2014, at 155 hospitals in 29 provinces/cities in China. Demographic and clinical data, including tumor characteristics and details of adjuvant/neoadjuvant therapies used, were collected. Data analysis included univariate analysis, multivariate logistic regression, and subgroup analyses.Of 4994 HER2+ patients (mean age 51.1 ± 9.9 years) included, only 29.8% received trastuzumab, with 30.5% in adjuvant therapy and 18.3% in neoadjuvant therapy. The highest rates of adjuvant trastuzumab were in Beijing (59.3%), Jiangsu (57.1%), and Ningxia (50.0%), while those of neoadjuvant trastuzumab were in Guangdong (24.8%), Beijing (14.1%), and Zhejiang (10.7%). Multivariate regression results revealed that factors associated with trastuzumab use were medical insurance cover for trastuzumab, residing locally to the hospital, more lymph node involvement, and more advanced tumor stage. Subgroup analysis revealed that patients receiving neoadjuvant therapy were likely to be younger, premenopausal and non-local, and had lymph node metastases, more advanced tumor, and progesterone receptor positive tumor.Trastuzumab use in patients with HER2+ breast cancer is relatively low in China, especially for neoadjuvant therapy. Insurance coverage seems to be the most correlated factor that influences the use of trastuzumab in Chinese patients with HER2+ breast cancer.

Metabolite profiling in Trigonella seeds via UPLC-MS and GC-MS analyzed using multivariate data analyses.

PubMed

Farag, Mohamed A; Rasheed, Dalia M; Kropf, Matthias; Heiss, Andreas G

2016-11-01

Trigonella foenum-graecum is a plant of considerable value for its nutritive composition as well as medicinal effects. This study aims to examine Trigonella seeds using a metabolome-based ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) in parallel to gas chromatography-mass spectrometry (GC-MS) coupled with multivariate data analyses. The metabolomic differences of seeds derived from three Trigonella species, i.e., T. caerulea, T. corniculata, and T. foenum-graecum, were assessed. Under specified conditions, we were able to identify 93 metabolites including 5 peptides, 2 phenolic acids, 22 C/O-flavonoid conjugates, 26 saponins, and 9 fatty acids using UPLC-MS. Several novel dipeptides, saponins, and flavonoids were found in Trigonella herein for the first time. Samples were classified via unsupervised principal component analysis (PCA) followed by supervised orthogonal projection to latent structures-discriminant analysis (OPLS-DA). A distinct separation among the investigated Trigonella species was revealed, with T. foenum-graecum samples found most enriched in apigenin-C-glycosides, viz. vicenins 1/3 and 2, compared to the other two species. In contrast to UPLC-MS, GC-MS was less efficient to classify specimens, with differences among specimens mostly attributed to fatty acyl esters. GC-MS analysis of Trigonella seed extracts led to the identification of 91 metabolites belonging mostly to fatty acyl esters, free fatty acids followed by organic acids, sugars, and amino acids. This study presents the first report on primary and secondary metabolite compositional differences among Trigonella seeds via a metabolomics approach and reveals that, among the species examined, the official T. foenum-graecum presents a better source of Trigonella secondary bioactive metabolites.

MDAS: an integrated system for metabonomic data analysis.

PubMed

Liu, Juan; Li, Bo; Xiong, Jiang-Hui

2009-03-01

Metabonomics, the latest 'omics' research field, shows great promise as a tool in biomarker discovery, drug efficacy and toxicity analysis, disease diagnosis and prognosis. One of the major challenges now facing researchers is how to process this data to yield useful information about a biological system, e.g., the mechanism of diseases. Traditional methods employed in metabonomic data analysis use multivariate analysis methods developed independently in chemometrics research. Additionally, with the development of machine learning approaches, some methods such as SVMs also show promise for use in metabonomic data analysis. Aside from the application of general multivariate analysis and machine learning methods to this problem, there is also a need for an integrated tool customized for metabonomic data analysis which can be easily used by biologists to reveal interesting patterns in metabonomic data.In this paper, we present a novel software tool MDAS (Metabonomic Data Analysis System) for metabonomic data analysis which integrates traditional chemometrics methods and newly introduced machine learning approaches. MDAS contains a suite of functional models for metabonomic data analysis and optimizes the flow of data analysis. Several file formats can be accepted as input. The input data can be optionally preprocessed and can then be processed with operations such as feature analysis and dimensionality reduction. The data with reduced dimensionalities can be used for training or testing through machine learning models. The system supplies proper visualization for data preprocessing, feature analysis, and classification which can be a powerful function for users to extract knowledge from the data. MDAS is an integrated platform for metabonomic data analysis, which transforms a complex analysis procedure into a more formalized and simplified one. The software package can be obtained from the authors.

Horabagrus melanosoma: a junior synonym of Horabagrus brachysoma (Teleostei: Horabagridae).

PubMed

Ali, Anvar; Katwate, Unmesh; Philip, Siby; Dhaneesh, K V; Bijukumar, A; Raghavan, Rajeev; Dahanukar, Neelesh

2014-11-06

Horabagrus melanosoma was described from West Venpala in the lower reaches of the Manimala River, in the state of Kerala, India. It was distinguished from its nearest congener, H. brachysoma based on a combination of characters including darker body colour, shorter pelvic fin and greater number of anal fin rays. Examination of the type material revealed significant morphometric and meristic discrepancies with the original description. Based on multivariate morphometric, and genetic analysis of topotypical specimens, we propose that H. melanosoma should be treated as a junior synonym of H. brachysoma.

Multivariate Analysis and Machine Learning in Cerebral Palsy Research

PubMed Central

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP. PMID:29312134

Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

PubMed

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

Quality by design case study: an integrated multivariate approach to drug product and process development.

PubMed

Huang, Jun; Kaul, Goldi; Cai, Chunsheng; Chatlapalli, Ramarao; Hernandez-Abad, Pedro; Ghosh, Krishnendu; Nagi, Arwinder

2009-12-01

To facilitate an in-depth process understanding, and offer opportunities for developing control strategies to ensure product quality, a combination of experimental design, optimization and multivariate techniques was integrated into the process development of a drug product. A process DOE was used to evaluate effects of the design factors on manufacturability and final product CQAs, and establish design space to ensure desired CQAs. Two types of analyses were performed to extract maximal information, DOE effect & response surface analysis and multivariate analysis (PCA and PLS). The DOE effect analysis was used to evaluate the interactions and effects of three design factors (water amount, wet massing time and lubrication time), on response variables (blend flow, compressibility and tablet dissolution). The design space was established by the combined use of DOE, optimization and multivariate analysis to ensure desired CQAs. Multivariate analysis of all variables from the DOE batches was conducted to study relationships between the variables and to evaluate the impact of material attributes/process parameters on manufacturability and final product CQAs. The integrated multivariate approach exemplifies application of QbD principles and tools to drug product and process development.

A Comparison of Tissue Spray and Lipid Extract Direct Injection Electrospray Ionization Mass Spectrometry for the Differentiation of Eutopic and Ectopic Endometrial Tissues

NASA Astrophysics Data System (ADS)

Chagovets, Vitaliy; Wang, Zhihao; Kononikhin, Alexey; Starodubtseva, Natalia; Borisova, Anna; Salimova, Dinara; Popov, Igor; Kozachenko, Andrey; Chingin, Konstantin; Chen, Huanwen; Frankevich, Vladimir; Adamyan, Leila; Sukhikh, Gennady

2018-02-01

Recent research revealed that tissue spray mass spectrometry enables rapid molecular profiling of biological tissues, which is of great importance for the search of disease biomarkers as well as for online surgery control. However, the payback for the high speed of analysis in tissue spray analysis is the generally lower chemical sensitivity compared with the traditional approach based on the offline chemical extraction and electrospray ionization mass spectrometry detection. In this study, high resolution mass spectrometry analysis of endometrium tissues of different localizations obtained using direct tissue spray mass spectrometry in positive ion mode is compared with the results of electrospray ionization analysis of lipid extracts. Identified features in both cases belong to three lipid classes: phosphatidylcholines, phosphoethanolamines, and sphingomyelins. Lipids coverage is validated by hydrophilic interaction liquid chromatography with mass spectrometry of lipid extracts. Multivariate analysis of data from both methods reveals satisfactory differentiation of eutopic and ectopic endometrium tissues. Overall, our results indicate that the chemical information provided by tissue spray ionization is sufficient to allow differentiation of endometrial tissues by localization with similar reliability but higher speed than in the traditional approach relying on offline extraction.

The antagonistic effect between STAT1 and Survivin and its clinical significance in gastric cancer.

PubMed

Deng, Hao; Zhen, Hongyan; Fu, Zhengqi; Huang, Xuan; Zhou, Hongyan; Liu, Lijiang

2012-01-01

In previous studies, we observed that STAT1 and Survivin correlated negatively with gastric cancer tissues, and that the functions of the IFN-γ-STAT1 pathway and Survivin in gastric cancer are the same as those reported for other types of cancer. In this study, the SGC7901 gastric cancer cell line and 83 gastric cancer specimens were used to confirm the relationship between STAT1 and Survivin, as well as the clinical significance of this relationship in gastric cancer. IFN-γ and STAT1 and Survivin antisense oligonucleotides (ASONs) were used to knock down the expression in SGC7901 cells. The protein expression of STAT1 and Survivin was tested by immunocytochemical and image analysis methods. A gastric cancer tissue microarray was prepared and tested by immunohistochemical methods. Data were analyzed by the Spearman's rank correlation analysis, the χ(2) test and Cox's multivariate regression analysis. Upon knockdown of IFN-γ, STAT1 and Survivin expression by ASON in the SGC7901 cell line, an antagonistic effect was observed between STAT1 and Survivin. In gastric cancer tissues, STAT1 showed a negative correlation with depth of invasion (p<0.05) in gastric cancer tissues exhibiting a negative Survivin protein expression. Furthermore, in tissues exhibiting a negative STAT1 protein expression, Survivin correlated negatively with N stage (p<0.05). Pathological and molecular markers were used to conduct Cox's multivariate regression analysis, and depth of invasion and N stage were found to be prognostic factors (p<0.05). On the other hand, in tissues exhibiting a negative Survivin protein expression, Cox's multivariate regression analysis revealed that the differentiation type and STAT1 protein expression were prognostic factors (p<0.05). There is an antagonistic effect between STAT1 and Survivin in gastric cancer, and this antagonistic effect is of clinical significance in gastric cancer.

Multidisciplinary therapy for patients with locally oligo-recurrent pelvic malignancies.

PubMed

Sole, Claudio V; Calvo, Felipe A; de Sierra, Pedro Alvarez; Herranz, Rafael; Gonzalez-Bayon, Luis; García-Sabrido, Jose Luis

2014-07-01

To analyze prognostic factors and long-term outcomes in patients with locally recurrent pelvic cancer (LRPC) treated with a multidisciplinary approach. From January 1995 to December 2011, 81 patients [rectal (47 %); gynecologic (39 %); retroperitoneal sarcoma (14 %)] underwent extended surgery [multiorgan (58 %), bone (35 %), vascular (9 %), soft tissue (63 %)] and intraoperative electron beam radiation therapy (IOERT) to treat recurrent tumors in the pelvic region. Thirty-five patients (43 %) received external beam radiotherapy (EBRT). Survival was estimated using the Kaplan-Meier method, and risk factors were identified using univariate and multivariate analysis. Median follow-up was 39 months (6-189 months); the 1- 3- and 5-year rates of locoregional control (LRC) were 83, 53, and 41 %, respectively. Univariate Cox proportional hazard analysis revealed worse LRC in patients who did not receive integrated EBRT as rescue treatment of pelvic recurrence (p = 0.003) or underwent non-radical resection (p = 0.01). In the multivariate analysis EBRT, non-radical resection, and tumor fragmentation retained significance (p = 0.002, p = 0.004, and p = 0.05, respectively). Radical resection, absence of tumor fragmentation and addition of EBRT for rescue are associated with improved LRC in patients with LRPC. Our results suggest that this group can benefit from EBRT combined with extended surgical resection and IOERT.

Analysis of some metallic elements and metalloids composition and relationships in parasol mushroom Macrolepiota procera.

PubMed

Falandysz, Jerzy; Sapkota, Atindra; Dryżałowska, Anna; Mędyk, Małgorzata; Feng, Xinbin

2017-06-01

The aim of the study was to characterise the multi-elemental composition and associations between a group of 32 elements and 16 rare earth elements collected by mycelium from growing substrates and accumulated in fruiting bodies of Macrolepiota procera from 16 sites from the lowland areas of Poland. The elements were quantified by inductively coupled plasma quadrupole mass spectrometry using validated method. The correlation matrix obtained from a possible 48 × 16 data matrix has been used to examine if any association exits between 48 elements in mushrooms foraged from 16 sampling localizations by multivariate approach using principal component (PC) analysis. The model could explain up to 93% variability by eight factors for which an eigenvalue value was ≥1. Absolute values of the correlation coefficient were above 0.72 (significance at p < 0.05) for 43 elements. From a point of view by consumer, the absolute content of Cd, Hg, Pb in caps of M. procera collected from background (unpolluted) areas could be considered elevated while sporadic/occasional ingestion of this mushroom is considered safe. The multivariate functional analysis revealed on associated accumulation of many elements in this mushroom. M. procera seem to possess some features of a bio-indicative species for anthropogenic Pb but also for some geogenic metals.

Fludarabine Melphalan reduced-intensity conditioning allotransplanation provides similar disease control in lymphoid and myeloid malignancies: analysis of 344 patients.

PubMed

Bryant, A; Nivison-Smith, I; Pillai, E S; Kennedy, G; Kalff, A; Ritchie, D; George, B; Hertzberg, M; Patil, S; Spencer, A; Fay, K; Cannell, P; Berkahn, L; Doocey, R; Spearing, R; Moore, J

2014-01-01

This was an Australasian Bone Marrow Transplant Recipient Registry (ABMTRR)-based retrospective study assessing the outcome of Fludarabine Melphalan (FluMel) reduced-intensity conditioning between 1998 and 2008. Median follow-up was 3.4 years. There were 344 patients with a median age of 54 years (18-68). In all, 234 patients had myeloid malignancies, with AML (n=166) being the commonest indication. There were 110 lymphoid patients with non-hodgkins lymphoma (NHL) (n=64) the main indication. TRM at day 100 was 14% with no significant difference between the groups. OS and disease-free survival (DFS) were similar between myeloid and lymphoid patients (57 and 50% at 3 years, respectively). There was no difference in cumulative incidence of relapse or GVHD between groups. Multivariate analysis revealed four significant adverse risk factors for DFS: donor other than HLA-identical sibling donor, not in remission at transplant, previous autologous transplant and recipient CMV positive. Chronic GVHD was associated with improved DFS in multivariate analysis predominantly due to a marked reduction in relapse (HR:0.44, P=0.003). This study confirms that FluMel provides durable and equivalent remissions in both myeloid and lymphoid malignancies. Disease stage and chronic GVHD remain important determinants of outcome for FluMel allografting.

Factors associated with sealant outcome in 2 pediatric dental clinics: a multivariate hierarchical analysis.

PubMed

West, Nathan G; Ilief-Ala, Melina A; Douglass, Joanna M; Hagadorn, James I

2011-01-01

This study's purpose was to determine whether one-time sealants placed by pediatric dental residents vs dental students have different outcomes. The effect of isolation technique, behavior, duration of follow-up, and caries history was also examined. Records from 2 inner-city pediatric dental clinics were audited for 6- to 10-year-old patients with a permanent first molar sealant with at least 2 years of follow-up. A successful sealant was a one-time sealant that received no further treatment and was sealed or unsealed but not carious or restored at the final audit. Charts from 203 children with 481 sealants were audited. Of these, 281 sealants were failures. Univariate analysis revealed longer follow-up and younger age were associated with sealant failure. Operator type, child behavior, and isolation technique were not associated with sealant failure. After adjusting for follow-up duration, increased age at treatment reduced the odds of sealant failure while a history of caries reduced the protective effect of increased age. After adjusting for these factors, practitioner type, behavior, and type of isolation were not associated with sealant outcome in multivariate analysis. Age at sealant placement, history of caries prior to placement, and longer duration of follow-up are associated with sealant failure.

Discrimination of snipefish Macroramphosus species and boarfish Capros aper morphotypes through multivariate analysis of body shape

NASA Astrophysics Data System (ADS)

Lopes, Marta; Murta, Alberto G.; Cabral, Henrique N.

2006-03-01

The existence of two species of the genus Macroramphosus Lacepède 1803, has been discussed based on morphometric characters, diet composition and depth distribution. Another species, the boarfish Capros aper (Linnaeus 1758), caugth along the Portuguese coast, shows two different morphotypes, one type with smaller eyes and a deeper body than the other, occurring with intermediate forms. In both snipefish and boarfish no sexual dimorphism was found with respect to shape and length relationships. However, females in both genera were on average bigger than males. A multidimensional scaling analysis was performed using Procrustes distances, in order to check if shape geometry was effective in distinguishing the species of snipefish as well as the morphotypes of boarfish. A multivariate discriminant analysis using morphometric characters of snipefish and boarfish was carried out to validate the visual criteria for a distinction of species and morphotypes, respectively. Morphometric characters revealed a great discriminatory power to distinguish morphotypes. Both snipefish and boarfish are very abundant in Portuguese waters, showing two well-defined morphologies and intermediate forms. This study suggests that there may be two different species in each genus and that further studies on these fish should be carried out to investigate if there is reproductive isolation between the morphotypes of boarfish and to validate the species of snipefish.

H. Pylori as a predictor of marginal ulceration: A nationwide analysis.

PubMed

Schulman, Allison R; Abougergi, Marwan S; Thompson, Christopher C

2017-03-01

Helicobacter pylori has been implicated as a risk factor for development of marginal ulceration following gastric bypass, although studies have been small and yielded conflicting results. This study sought to determine the relationship between H. pylori infection and development of marginal ulceration following bariatric surgery in a nationwide analysis. This was a retrospective cohort study using the 2012 Nationwide Inpatient Sample (NIS) database. Discharges with ICD-9-CM code indicating marginal ulceration and a secondary ICD-9-CM code for bariatric surgery were included. Primary outcome was incidence of marginal ulceration. A stepwise forward selection model was used to build the multivariate logistic regression model based on known risk factors. A P value of 0.05 was considered significant. There were 253,765 patients who met inclusion criteria. Prevalence of marginal ulceration was 3.90%. Of those patients found to have marginal ulceration, 31.20% of patients were H. pylori-positive. Final multivariate regression analysis revealed that H. pylori was the strongest independent predictor of marginal ulceration. H. pylori is an independent predictor of marginal ulceration using a large national database. Preoperative testing for and eradication of H. pylori prior to bariatric surgery may be an important preventive measure to reduce the incidence of ulcer development. © 2017 The Obesity Society.

[Risk factors of benign anastomostic strictures after esophagectomy with cervical reconstruction].

PubMed

Zhong, Sheng; Wu, Qinquan; Sun, Su'an; Gu, Biao; Zhao, Ming; Chen, Qiyou

2014-09-01

To identify the risk factors of benign cervical anastomotic strictures after esophagectomy. Clinical data of 946 esophageal cancer patients undergoing esophagectomy with cervical anastomosis between 2003 and 2012 were analyzed retrospectively. Benign stricture was defined as dysphagia for which endoscopic dilation of the anastomosis was needed. Histologically proven malignant stricture was not regarded as benign stricture. χ(2) test and logistic regression model were used for univariate and multivariate analysis respectively. A total of 146 patients(16.5%) developed benign stricture during follow-up. Univariate analysis showed that the patients with cardiovascular disease (P=0.001), diabetes mellitus(P=0.041), gastric tube reconstruction(P=0.050), end-to-end anastomosis (P=0.013), or postoperative anastomotic leakage(P=0.008) had higher stricture rate. Multivariate analysis revealed that cardiovascular disease(P=0.004), gastric tube reconstruction (P=0.026), end-to-end anastomosis(P=0.043), and postoperative anastomotic leakage(P=0.001) were independently predictive factors for development of benign stricture. The benign cervical stricture rate after esophagetomy with cervical gastric anastomosis is quite high. In order to prevent benign stricture formation, end-to-end anastomosis should be avoid. Blood pressure should be controlled for those with cardiovascular disease. Endoscopic dilation in an earlier stage postoperatively should be considered for those who develop anastomotic leakage.

Effects of Traditional Chinese Medicine on Chemotherapy-Induced Myelosuppression and Febrile Neutropenia in Breast Cancer Patients

PubMed Central

Tian, Huan; Qin, Wei; Wu, Wenjing; Guo, Pi; Lu, Yong; Liu, Pengxi; Liu, Qiang; Su, Fengxi

2015-01-01

Title. Chemotherapy-induced myelosuppression lowers the quality of life in breast cancer patients and causes many complications. Traditional Chinese Medicine (TCM) is a widely used complementary and alternative medicine therapies. Objective. To study whether TCM can reduce the incidence of chemotherapy-induced leukopenia, neutropenia, and febrile neutropenia (FN) in breast cancer patients. Methods. The data were analyzed retrospectively between patients who received TCM treatment (group 1, n = 453) and patients who did not receive TCM treatment (group 2, n = 359). Significant risk factors associated with the occurrence of chemotherapy-induced leukopenia, neutropenia, and FN were identified using multivariate analysis. Propensity score-matched patients were analyzed to adjust for any baseline differences. Results. Group 1 patients had a significantly lower rate of chemotherapy-induced severe leukopenia, neutropenia, and FN, compared with group 2 (43% versus 71%, P < 0.0001, 72% versus 78%, P = 0.005, 6% versus 24%, P < 0.0001, resp.). Multivariate analysis revealed that chemotherapy regimens containing anthracyclines combined with paclitaxel or docetaxel were the most significant predictor. Subgroup analysis indicated that TCM treatment showed benefit in relieving chemotherapy-induced leukopenia and FN in most chemotherapy regimens. Conclusions. TCM treatment could lower the risk of severe chemotherapy-induced leukopenia, neutropenia, and FN in breast cancer patients. PMID:26347793

Multivariable harmonic balance analysis of the neuronal oscillator for leech swimming.

PubMed

Chen, Zhiyong; Zheng, Min; Friesen, W Otto; Iwasaki, Tetsuya

2008-12-01

Biological systems, and particularly neuronal circuits, embody a very high level of complexity. Mathematical modeling is therefore essential for understanding how large sets of neurons with complex multiple interconnections work as a functional system. With the increase in computing power, it is now possible to numerically integrate a model with many variables to simulate behavior. However, such analysis can be time-consuming and may not reveal the mechanisms underlying the observed phenomena. An alternative, complementary approach is mathematical analysis, which can demonstrate direct and explicit relationships between a property of interest and system parameters. This paper introduces a mathematical tool for analyzing neuronal oscillator circuits based on multivariable harmonic balance (MHB). The tool is applied to a model of the central pattern generator (CPG) for leech swimming, which comprises a chain of weakly coupled segmental oscillators. The results demonstrate the effectiveness of the MHB method and provide analytical explanations for some CPG properties. In particular, the intersegmental phase lag is estimated to be the sum of a nominal value and a perturbation, where the former depends on the structure and span of the neuronal connections and the latter is roughly proportional to the period gradient, communication delay, and the reciprocal of the intersegmental coupling strength.

Nationwide analysis of adrenocortical carcinoma reveals higher perioperative morbidity in functional tumors.

PubMed

Parikh, Punam P; Rubio, Gustavo A; Farra, Josefina C; Lew, John I

2017-08-25

Current adrenalectomy outcomes for functional adrenocortical carcinoma (ACC) remain unclear. This study examines nationwide in-hospital post-adrenalectomy outcomes for ACC. A retrospective analysis of the Nationwide Inpatient Sample database (2006-2011) to identify unilateral adrenalectomy patients for functional or nonfunctional ACC was performed. Patient demographics, comorbidities and postoperative outcomes were evaluated by t-test, Chi-square and multivariate regression. Of 2199 patients who underwent adrenalectomy, 87% had nonfunctional and 13% had functional ACC (86% hypercortisolism, 16% hyperaldosteronism, 4% hyperandrogenism). Functional ACC patients had significantly more comorbidities, and experienced certain postoperative complications more frequently including wound issues, adrenocortical insufficiency and acute kidney injury with longer hospital stay compared to nonfunctional ACC (P < 0.01). On multivariate analysis, functional ACC was an independent prognosticator for wound complications (28.1, 95%CI 4.59-176.6). Patients with functional ACC manifest significant comorbidities with certain in-hospital complications. Such high-risk patients require appropriate preoperative medical optimization prior to adrenalectomy. Patients with functional adrenocortical carcinoma (ACC) have significant preoperative comorbidities and experience higher rates of certain postoperative complications including wound complications, hematoma formation, adrenal insufficiency, pulmonary embolism and acute kidney injury. Functional ACC patients also necessitate longer hospitalizations. These patients should undergo appropriate preoperative counseling in preparation for adrenalectomy. Copyright © 2017 Elsevier Inc. All rights reserved.

Characterization of cytochrome c as marker for retinal cell degeneration by uv/vis spectroscopic imaging

NASA Astrophysics Data System (ADS)

Hollmach, Julia; Schweizer, Julia; Steiner, Gerald; Knels, Lilla; Funk, Richard H. W.; Thalheim, Silko; Koch, Edmund

2011-07-01

Retinal diseases like age-related macular degeneration have become an important cause of visual loss depending on increasing life expectancy and lifestyle habits. Due to the fact that no satisfying treatment exists, early diagnosis and prevention are the only possibilities to stop the degeneration. The protein cytochrome c (cyt c) is a suitable marker for degeneration processes and apoptosis because it is a part of the respiratory chain and involved in the apoptotic pathway. The determination of the local distribution and oxidative state of cyt c in living cells allows the characterization of cell degeneration processes. Since cyt c exhibits characteristic absorption bands between 400 and 650 nm wavelength, uv/vis in situ spectroscopic imaging was used for its characterization in retinal ganglion cells. The large amount of data, consisting of spatial and spectral information, was processed by multivariate data analysis. The challenge consists in the identification of the molecular information of cyt c. Baseline correction, principle component analysis (PCA) and cluster analysis (CA) were performed in order to identify cyt c within the spectral dataset. The combination of PCA and CA reveals cyt c and its oxidative state. The results demonstrate that uv/vis spectroscopic imaging in conjunction with sophisticated multivariate methods is a suitable tool to characterize cyt c under in situ conditions.

Estimating an Effect Size in One-Way Multivariate Analysis of Variance (MANOVA)

ERIC Educational Resources Information Center

Steyn, H. S., Jr.; Ellis, S. M.

2009-01-01

When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…

Dangers in Using Analysis of Covariance Procedures.

ERIC Educational Resources Information Center

Campbell, Kathleen T.

Problems associated with the use of analysis of covariance (ANCOVA) as a statistical control technique are explained. Three problems relate to the use of "OVA" methods (analysis of variance, analysis of covariance, multivariate analysis of variance, and multivariate analysis of covariance) in general. These are: (1) the wasting of information when…

MANOVA vs nonlinear mixed effects modeling: The comparison of growth patterns of female and male quail

NASA Astrophysics Data System (ADS)

Gürcan, Eser Kemal

2017-04-01

The most commonly used methods for analyzing time-dependent data are multivariate analysis of variance (MANOVA) and nonlinear regression models. The aim of this study was to compare some MANOVA techniques and nonlinear mixed modeling approach for investigation of growth differentiation in female and male Japanese quail. Weekly individual body weight data of 352 male and 335 female quail from hatch to 8 weeks of age were used to perform analyses. It is possible to say that when all the analyses are evaluated, the nonlinear mixed modeling is superior to the other techniques because it also reveals the individual variation. In addition, the profile analysis also provides important information.

Application of MCR-ALS to reveal intermediate conformations in the thermally induced α-β transition of poly-L-lysine monitored by FT-IR spectroscopy

NASA Astrophysics Data System (ADS)

Alcaráz, Mirta R.; Schwaighofer, Andreas; Goicoechea, Héctor; Lendl, Bernhard

2017-10-01

Temperature-induced conformational transitions of poly-L-lysine were monitored with Fourier-transform infrared (FT-IR) spectroscopy between 10 °C and 70 °C. Chemometric analysis of dynamic IR spectra was performed by multivariate curve analysis-alternating least squares (MCR-ALS) of the amide I‧ and amide II‧ spectral region. With this approach, the pure spectral and concentration profiles of the conformational transition were obtained. Beside the initial α-helical, the intermediate random coil/extended helices and the final β-sheet structure, an additional intermediate PLL conformation was identified and attributed to a transient β-sheet structure.

Exploring the Interaction of Motor and Social Skills With Autism Severity Using the SFARI Dataset.

PubMed

Colombo-Dougovito, Andrew M; Reeve, Ronald E

2017-04-01

Social communicative deficits and stereotyped or repetitive interests or behaviors are the defining features of autism spectrum disorder (ASD). A growing body of research suggests that gross motor deficits are also present in most children with ASD. This study sought to understand how pediatric ASD severity is related to motor skills and social skills. A multivariate analysis of variance analysis of 483 children with autism ( N = 444) and ASD ( N = 39) revealed a nonsignificant difference between groups. Results suggest little difference between severity groups on gross motor and social skills within the limited age range of the participants (about 5.6 years of age).

Multivariate genetic architecture of the Anolis dewlap reveals both shared and sex-specific features of a sexually dimorphic ornament.

PubMed

Cox, R M; Costello, R A; Camber, B E; McGlothlin, J W

2017-07-01

Darwin viewed the ornamentation of females as an indirect consequence of sexual selection on males and the transmission of male phenotypes to females via the 'laws of inheritance'. Although a number of studies have supported this view by demonstrating substantial between-sex genetic covariance for ornament expression, the majority of this work has focused on avian plumage. Moreover, few studies have considered the genetic basis of ornaments from a multivariate perspective, which may be crucial for understanding the evolution of sex differences in general, and of complex ornaments in particular. Here, we provide a multivariate, quantitative-genetic analysis of a sexually dimorphic ornament that has figured prominently in studies of sexual selection: the brightly coloured dewlap of Anolis lizards. Using data from a paternal half-sibling breeding experiment in brown anoles (Anolis sagrei), we show that multiple aspects of dewlap size and colour exhibit significant heritability and a genetic variance-covariance structure (G) that is broadly similar in males (G m ) and females (G f ). Whereas sexually monomorphic aspects of the dewlap, such as hue, exhibit significant between-sex genetic correlations (r mf ), sexually dimorphic features, such as area and brightness, exhibit reduced r mf values that do not differ from zero. Using a modified random skewers analysis, we show that the between-sex genetic variance-covariance matrix (B) should not strongly constrain the independent responses of males and females to sexually antagonistic selection. Our microevolutionary analysis is in broad agreement with macroevolutionary perspectives indicating considerable scope for the independent evolution of coloration and ornamentation in males and females. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Effects of intranasal oxytocin on symptoms of schizophrenia: A multivariate Bayesian meta-analysis.

PubMed

Williams, Donald R; Bürkner, Paul-Christian

2017-01-01

Schizophrenia is a heterogeneous disorder in which psychiatric symptoms are classified into two general subgroups-positive and negative symptoms. Current antipsychotic drugs are effective for treating positive symptoms, whereas negative symptoms are less responsive. Since the neuropeptide oxytocin (OT) has been shown to mediate social behavior in animals and humans, it has been used as an experimental therapeutic for treating schizophrenia and in particular negative symptoms which includes social deficits. Through eight randomized controlled trials (RCTs) and three meta-analyses, evidence for an effect of intranasal OT (IN-OT) has been inconsistent. We therefore conducted an updated meta-analysis that offers several advantages when compared to those done previously: (1) We used a multivariate analysis which allows for comparisons between symptoms and accounts for correlations between symptoms; (2) We controlled for baseline scores; (3) We used a fully Bayesian framework that allows for assessment of evidence in favor of the null hypothesis using Bayes factors; and (4) We addressed inconsistencies in the primary studies and previous meta-analyses. Eight RCTs (n=238) were included in the present study and we found that oxytocin did not improve any aspect of symptomology in schizophrenic patients and there was moderate evidence in favor of the null (no effect of oxytocin) for negative symptoms. Multivariate comparisons between symptom types revealed that oxytocin was not especially beneficial for treating negative symptoms. The effect size estimates were not moderated, publication bias was absent, and our estimates were robust to sensitivity analyses. These results suggest that IN-OT is not an effective therapeutic for schizophrenia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Time to antibiotics and outcomes in cancer patients with febrile neutropenia

PubMed Central

2014-01-01

Background Febrile neutropenia is an oncologic emergency. The timing of antibiotics administration in patients with febrile neutropenia may result in adverse outcomes. Our study aims to determine time-to- antibiotic administration in patients with febrile neutropenia, and its relationship with length of hospital stay, intensive care unit monitoring, and hospital mortality. Methods The study population was comprised of adult cancer patients with febrile neutropenia who were hospitalized, at a tertiary care hospital, between January 2010 and December 2011. Using Multination Association of Supportive Care in Cancer (MASCC) risk score, the study cohort was divided into high and low risk groups. A multivariate regression analysis was performed to assess relationship between time-to- antibiotic administration and various outcome variables. Results One hundred and five eligible patients with median age of 60 years (range: 18–89) and M:F of 43:62 were identified. Thirty-seven (35%) patients were in MASCC high risk group. Median time-to- antibiotic administration was 2.5 hrs (range: 0.03-50) and median length of hospital stay was 6 days (range: 1–57). In the multivariate analysis time-to- antibiotic administration (regression coefficient [RC]: 0.31 days [95% CI: 0.13-0.48]), known source of fever (RC: 4.1 days [95% CI: 0.76-7.5]), and MASCC high risk group (RC: 4 days [95% CI: 1.1-7.0]) were significantly correlated with longer hospital stay. Of 105 patients, 5 (4.7%) died & or required ICU monitoring. In multivariate analysis no variables significantly correlated with mortality or ICU monitoring. Conclusions Our study revealed that delay in antibiotics administration has been associated with a longer hospital stay. PMID:24716604

Searching for forcing signatures in decadal patterns of shoreline change

NASA Astrophysics Data System (ADS)

Burningham, H.; French, J.

2016-12-01

Analysis of shoreline position at spatial scales of the order 10 - 100 km and at a multi-decadal time-scale has the potential to reveal regional coherence (or lack of) in the primary controls on shoreline tendencies and trends. Such information is extremely valuable for the evaluation of climate forcing on coastal behaviour. Segmenting a coast into discrete behaviour units based on these types of analyses is often subjective, however, and in the context of pervasive human interventions and alongshore variability in ocean climate, determining the most important controls on shoreline dynamics can be challenging. Multivariate analyses provide one means to resolve common behaviours across shoreline position datasets, thereby underpinning a more objective evaluation of possible coupling between shorelines at different scales. In an analysis of the Suffolk coast (eastern England) we explore the use of multivariate statistics to understand and classify mesoscale coastal behaviour. Suffolk comprises a relatively linear shoreline that shifts from east-facing in the north to southeast-facing in the south. Although primarily formed of a beach foreshore backed by cliffs or shingle barrier, the shoreline is punctuated at 3 locations by narrow tidal inlets with offset entrances that imply a persistent north to south sediment transport direction. Tidal regime decreases south to north from mesotidal (3.6m STR) to microtidal (1.9m STR), and the bimodal wave climate (northeast and southwest modes) presents complex local-scale variability in nearshore conditions. Shorelines exhibit a range of decadal behaviours from rapid erosion (up to 4m/yr) to quasi-stability that cannot be directly explained by the spatial organisation of contemporary landforms or coastal defences. A multivariate statistical approach to shoreline change analysis helps to define the key modes of change and determine the most likely forcing factors.

Vitamin D insufficiency and subclinical atherosclerosis in non-diabetic males living with HIV.

PubMed

Portilla, Joaquín; Moreno-Pérez, Oscar; Serna-Candel, Carmen; Escoín, Corina; Alfayate, Rocio; Reus, Sergio; Merino, Esperanza; Boix, Vicente; Giner, Livia; Sánchez-Payá, José; Picó, Antonio

2014-01-01

Vitamin D insufficiency (VDI) has been associated with increased cardiovascular risk in the non-HIV population. This study evaluates the relationship among serum 25-hydroxyvitamin D [25(OH)D] levels, cardiovascular risk factors, adipokines, antiviral therapy (ART) and subclinical atherosclerosis in HIV-infected males. A cross-sectional study in ambulatory care was made in non-diabetic patients living with HIV. VDI was defined as 25(OH)D serum levels <75 nmol/L. Fasting lipids, glucose, inflammatory markers (tumour necrosis factor-α, interleukin-6, high-sensitivity C-reactive protein) and endothelial markers (plasminogen activator inhibitor-1, or PAI-I) were measured. The common carotid artery intima-media thickness (C-IMT) was determined. A multivariate logistic regression analysis was made to identify factors associated with the presence of VDI, while multivariate linear regression analysis was used to identify factors associated with common C-IMT. Eighty-nine patients were included (age 42 ± 8 years), 18.9% were in CDC (US Centers for Disease Control and Prevention) stage C and 75 were on ART. VDI was associated with ART exposure, sedentary lifestyle, higher triglycerides levels and PAI-I. In univariate analysis, VDI was associated with greater common C-IMT. The multivariate linear regression model, adjusted by confounding factors, revealed an independent association between common C-IMT and patient age, time of exposure to protease inhibitors (PIs) and impaired fasting glucose (IFG). In contrast, there were no independent associations between common C-IMT and VDI or inflammatory and endothelial markers. VDI was not independently associated with subclinical atherosclerosis in non-diabetic males living with HIV. Older age, a longer exposure to PIs, and IFG were independent factors associated with common C-IMT in this population.

Multivariate analysis of DSC-XRD simultaneous measurement data: a study of multistage crystalline structure changes in a linear poly(ethylene imine) thin film.

PubMed

Kakuda, Hiroyuki; Okada, Tetsuo; Otsuka, Makoto; Katsumoto, Yukiteru; Hasegawa, Takeshi

2009-01-01

A multivariate analytical technique has been applied to the analysis of simultaneous measurement data from differential scanning calorimetry (DSC) and X-ray diffraction (XRD) in order to study thermal changes in crystalline structure of a linear poly(ethylene imine) (LPEI) film. A large number of XRD patterns generated from the simultaneous measurements were subjected to an augmented alternative least-squares (ALS) regression analysis, and the XRD patterns were readily decomposed into chemically independent XRD patterns and their thermal profiles were also obtained at the same time. The decomposed XRD patterns and the profiles were useful in discussing the minute peaks in the DSC. The analytical results revealed the following changes of polymorphisms in detail: An LPEI film prepared by casting an aqueous solution was composed of sesquihydrate and hemihydrate crystals. The sesquihydrate one was lost at an early stage of heating, and the film changed into an amorphous state. Once the sesquihydrate was lost by heating, it was not recovered even when it was cooled back to room temperature. When the sample was heated again, structural changes were found between the hemihydrate and the amorphous components. In this manner, the simultaneous DSC-XRD measurements combined with ALS analysis proved to be powerful for obtaining a better understanding of the thermally induced changes of the crystalline structure in a polymer film.

Reduced miR-300 expression predicts poor prognosis in patients with laryngeal squamous cell carcinoma.

PubMed

He, F-Y; Liu, H-J; Guo, Q; Sheng, J-L

2017-02-01

miR-300 has been demonstrated to play an important role in the progression of several tumors, but its role in tumorigenesis of laryngeal squamous cell carcinoma (LSCC) is still unclear. The purpose of this study was to explore miR-300 expression in LSCC patients and analyze its association with clinicopathological factors and prognosis. In the present study, we measured the expression level of miR-300 in LSCC tissues by RT-PCR. Associations between miRNA-300 expressions and various clinicopathological characteristics were analyzed. Patient survival and their differences were determined by Kaplan-Meier method and log-rank test. The univariate and multivariate analysis were performed using the Cox proportional hazard analysis. miR-300 expression was significantly increased in LSCC tissues compared with that in adjacent non-cancerous tissues (p < 0.01). In addition, lymph node metastasis (p = 0.004) and TNM stage (p = 0.001) were obvious influence factors for the expression of miR-300. More importantly, Kaplan-Meier analysis showed that LSCC patients with low miR-300 expression tended to have shorter overall survival (p < 0.001). Finally, multivariate analysis revealed that miR-300 expression was an independent prognostic factor for LSCC patients. Our results pointed to miR-300 as a powerful prognostic marker in LSCC and as a novel target for tumor-suppressive therapy.

A study of pH-dependent photodegradation of amiloride by a multivariate curve resolution approach to combined kinetic and acid-base titration UV data.

PubMed

De Luca, Michele; Ioele, Giuseppina; Mas, Sílvia; Tauler, Romà; Ragno, Gaetano

2012-11-21

Amiloride photostability at different pH values was studied in depth by applying Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) to the UV spectrophotometric data from drug solutions exposed to stressing irradiation. Resolution of all degradation photoproducts was possible by simultaneous spectrophotometric analysis of kinetic photodegradation and acid-base titration experiments. Amiloride photodegradation showed to be strongly dependent on pH. Two hard modelling constraints were sequentially used in MCR-ALS for the unambiguous resolution of all the species involved in the photodegradation process. An amiloride acid-base system was defined by using the equilibrium constraint, and the photodegradation pathway was modelled taking into account the kinetic constraint. The simultaneous analysis of photodegradation and titration experiments revealed the presence of eight different species, which were differently distributed according to pH and time. Concentration profiles of all the species as well as their pure spectra were resolved and kinetic rate constants were estimated. The values of rate constants changed with pH and under alkaline conditions the degradation pathway and photoproducts also changed. These results were compared to those obtained by LC-MS analysis from drug photodegradation experiments. MS analysis allowed the identification of up to five species and showed the simultaneous presence of more than one acid-base equilibrium.

Assessment of heavy metals contamination in sediments from three adjacent regions of the Yellow River using metal chemical fractions and multivariate analysis techniques.

PubMed

Ma, Xiaoling; Zuo, Hang; Tian, Mengjing; Zhang, Liyang; Meng, Jia; Zhou, Xuening; Min, Na; Chang, Xinyuan; Liu, Ying

2016-02-01

Metal chemical fractions obtained by optimized BCR three-stage extraction procedure and multivariate analysis techniques were exploited for assessing 7 heavy metals (Cr, Pb, Cd, Co, Cu, Zn and Ni) in sediments from Gansu province, Ningxia and Inner Mongolia Autonomous Regions of the Yellow River in Northern China. The results indicated that higher susceptibility and bioavailability of Cr and Cd with a strong anthropogenic source were due to their higher availability in the exchangeable fraction. A portion of Pb, Cd, Co, Zn, and Ni in reducible fraction may be due to the fact that they can form stable complexes with Fe and Mn oxides. Substantial amount of Pb, Co, Ni and Cu was observed as oxidizable fraction because of their strong affinity to the organic matters so that they can complex with humic substances in sediments. The high geo-accumulation indexes (I(geo)) for Cr and Cd showed their higher environmental risk to the aquatic biota. Principal component analysis (PCA) revealed that high toxic Cr and Cd in polluted sites (Cd in S10, S11 and Cr in S13) may be contributed to anthropogenic sources, it was consistent with the results of dual hierarchical clustering analysis (DHCA), which could give more details about contributing sources. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Baseline for the Multivariate Comparison of Resting-State Networks

PubMed Central

Allen, Elena A.; Erhardt, Erik B.; Damaraju, Eswar; Gruner, William; Segall, Judith M.; Silva, Rogers F.; Havlicek, Martin; Rachakonda, Srinivas; Fries, Jill; Kalyanam, Ravi; Michael, Andrew M.; Caprihan, Arvind; Turner, Jessica A.; Eichele, Tom; Adelsheim, Steven; Bryan, Angela D.; Bustillo, Juan; Clark, Vincent P.; Feldstein Ewing, Sarah W.; Filbey, Francesca; Ford, Corey C.; Hutchison, Kent; Jung, Rex E.; Kiehl, Kent A.; Kodituwakku, Piyadasa; Komesu, Yuko M.; Mayer, Andrew R.; Pearlson, Godfrey D.; Phillips, John P.; Sadek, Joseph R.; Stevens, Michael; Teuscher, Ursina; Thoma, Robert J.; Calhoun, Vince D.

2011-01-01

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease. PMID:21442040

Oral pathology follow-up by means of micro-Raman spectroscopy on tissue and blood serum samples: an application of wavelet and multivariate data analysis

NASA Astrophysics Data System (ADS)

Delfino, I.; Camerlingo, C.; Zenone, F.; Perna, G.; Capozzi, V.; Cirillo, N.; Gaeta, G. M.; De Mol, E.; Lepore, M.

2009-02-01

Pemphigus vulgaris (PV) is a potentially fatal autoimmune disease that cause blistering of the skin and oral cavity. It is characterized by disruption of cell-cell adhesion within the suprabasal layers of epithelium, a phenomenon termed acantholysis Patients with PV develop IgG autoantibodies against normal constituents of the intercellular substance of keratinocytes. The mechanisms by which such autoantibodies induce blisters are not clearly understood. The qualitative analysis of such effects provides important clues in the search for a specific diagnosis, and the quantitative analysis of biochemical abnormalities is important in measuring the extent of the disease process, designing therapy and evaluating the efficacy of treatment. Improved diagnostic techniques could permit the recognition of more subtle forms of disease and reveal incipient lesions clinically unapparent, so that progression of potentially severe forms could be reversed with appropriate treatment. In this paper, we report the results of our micro-Raman spectroscopy study on tissue and blood serum samples from ill, recovered and under therapy PV patients. The complexity of the differences among their characteristic Raman spectra has required a specific strategy to obtain reliable information on the illness stage of the patients For this purpose, wavelet techniques and advanced multivariate analysis methods have been developed and applied to the experimental Raman spectra. Promising results have been obtained.

Relations among soil radon, environmental parameters, volcanic and seismic events at Mt. Etna (Italy)

NASA Astrophysics Data System (ADS)

Giammanco, S.; Ferrera, E.; Cannata, A.; Montalto, P.; Neri, M.

2013-12-01

From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol probe located on the upper NE flank of Mt. Etna volcano (Italy), close both to the Piano Provenzana fault and to the NE-Rift. Seismic, volcanological and radon data were analysed together with data on environmental parameters, such as air and soil temperature, barometric pressure, snow and rain fall. In order to find possible correlations among the above parameters, and hence to reveal possible anomalous trends in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-day time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-day moving averages showed that, similar to multivariate linear regression analysis, the summer period was characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allowed to study the relations among different signals either in the time or in the frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Using the above analysis, two periods were recognized when radon variations were significantly correlated with marked soil temperature changes and also with local seismic or volcanic activity. This allowed to produce two different physical models of soil gas transport that explain the observed anomalies. Our work suggests that in order to make an accurate analysis of the relations among different signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be the most effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.

Secondary ion mass spectrometry imaging and multivariate data analysis reveal co-aggregation patterns of Populus trichocarpa leaf surface compounds on a micrometer scale.

PubMed

Kulkarni, Purva; Dost, Mina; Bulut, Özgül Demir; Welle, Alexander; Böcker, Sebastian; Boland, Wilhelm; Svatoš, Aleš

2018-01-01

Spatially resolved analysis of a multitude of compound classes has become feasible with the rapid advancement in mass spectrometry imaging strategies. In this study, we present a protocol that combines high lateral resolution time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging with a multivariate data analysis (MVA) approach to probe the complex leaf surface chemistry of Populus trichocarpa. Here, epicuticular waxes (EWs) found on the adaxial leaf surface of P. trichocarpa were blotted on silicon wafers and imaged using TOF-SIMS at 10 μm and 1 μm lateral resolution. Intense M +● and M -● molecular ions were clearly visible, which made it possible to resolve the individual compound classes present in EWs. Series of long-chain aliphatic saturated alcohols (C 21 -C 30 ), hydrocarbons (C 25 -C 33 ) and wax esters (WEs; C 44 -C 48 ) were clearly observed. These data correlated with the 7 Li-chelation matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis, which yielded mostly molecular adduct ions of the analyzed compounds. Subsequently, MVA was used to interrogate the TOF-SIMS dataset for identifying hidden patterns on the leaf's surface based on its chemical profile. After the application of principal component analysis (PCA), a small number of principal components (PCs) were found to be sufficient to explain maximum variance in the data. To further confirm the contributions from pure components, a five-factor multivariate curve resolution (MCR) model was applied. Two distinct patterns of small islets, here termed 'crystals', were apparent from the resulting score plots. Based on PCA and MCR results, the crystals were found to be formed by C 23 or C 29 alcohols. Other less obvious patterns observed in the PCs revealed that the adaxial leaf surface is coated with a relatively homogenous layer of alcohols, hydrocarbons and WEs. The ultra-high-resolution TOF-SIMS imaging combined with the MVA approach helped to highlight the diverse patterns underlying the leaf's surface. Currently, the methods available to analyze the surface chemistry of waxes in conjunction with the spatial information related to the distribution of compounds are limited. This study uses tools that may provide important biological insights into the composition of the wax layer, how this layer is repaired after mechanical damage or insect feeding, and which transport mechanisms are involved in deploying wax constituents to specific regions on the leaf surface. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

PHI and PCA3 improve the prognostic performance of PRIAS and Epstein criteria in predicting insignificant prostate cancer in men eligible for active surveillance.

PubMed

Cantiello, Francesco; Russo, Giorgio Ivan; Cicione, Antonio; Ferro, Matteo; Cimino, Sebastiano; Favilla, Vincenzo; Perdonà, Sisto; De Cobelli, Ottavio; Magno, Carlo; Morgia, Giuseppe; Damiano, Rocco

2016-04-01

To assess the performance of prostate health index (PHI) and prostate cancer antigen 3 (PCA3) when added to the PRIAS or Epstein criteria in predicting the presence of pathologically insignificant prostate cancer (IPCa) in patients who underwent radical prostatectomy (RP) but eligible for active surveillance (AS). An observational retrospective study was performed in 188 PCa patients treated with laparoscopic or robot-assisted RP but eligible for AS according to Epstein or PRIAS criteria. Blood and urinary specimens were collected before initial prostate biopsy for PHI and PCA3 measurements. Multivariate logistic regression analyses and decision curve analysis were carried out to identify predictors of IPCa using the updated ERSPC definition. At the multivariate analyses, the inclusion of both PCA3 and PHI significantly increased the accuracy of the Epstein multivariate model in predicting IPCa with an increase of 17 % (AUC = 0.77) and of 32 % (AUC = 0.92), respectively. The inclusion of both PCA3 and PHI also increased the predictive accuracy of the PRIAS multivariate model with an increase of 29 % (AUC = 0.87) and of 39 % (AUC = 0.97), respectively. DCA revealed that the multivariable models with the addition of PHI or PCA3 showed a greater net benefit and performed better than the reference models. In a direct comparison, PHI outperformed PCA3 performance resulting in higher net benefit. In a same cohort of patients eligible for AS, the addition of PHI and PCA3 to Epstein or PRIAS models improved their prognostic performance. PHI resulted in greater net benefit in predicting IPCa compared to PCA3.

Correlation between smoking habit and surgical outcomes on viral-associated hepatocellular carcinomas

PubMed Central

Kai, Keita; Komukai, Sho; Koga, Hiroki; Yamaji, Koutaro; Ide, Takao; Kawaguchi, Atsushi; Aishima, Shinichi; Noshiro, Hirokazu

2018-01-01

AIM To investigate the association between smoking habits and surgical outcomes in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) (B-HCC) and hepatitis C virus (HCV)-related HCC (C-HCC) and clarify the clinicopathological features associated with smoking status in B-HCC and C-HCC patients. METHODS We retrospectively examined the cases of the 341 consecutive patients with viral-associated HCC (C-HCC, n = 273; B-HCC, n = 68) who underwent curative surgery for their primary lesion. We categorized smoking status at the time of surgery into never, ex- and current smoker. We analyzed the B-HCC and C-HCC groups’ clinicopathological features and surgical outcomes, i.e., disease-free survival (DFS), overall survival (OS), and disease-specific survival (DSS). Univariate and multivariate analyses were performed using a Cox proportional hazards regression model. We also performed subset analyses in both patient groups comparing the current smokers to the other patients. RESULTS The multivariate analysis in the C-HCC group revealed that current-smoker status was significantly correlated with both OS (P = 0.0039) and DSS (P = 0.0416). In the B-HCC patients, no significant correlation was observed between current-smoker status and DFS, OS, or DSS in the univariate or multivariate analyses. The subset analyses comparing the current smokers to the other patients in both the C-HCC and B-HCC groups revealed that the current smokers developed HCC at significantly younger ages than the other patients irrespective of viral infection status. CONCLUSION A smoking habit is significantly correlated with the overall and disease-specific survivals of patients with C-HCC. In contrast, the B-HCC patients showed a weak association between smoking status and surgical outcomes. PMID:29358882

Correlation between smoking habit and surgical outcomes on viral-associated hepatocellular carcinomas.

PubMed

Kai, Keita; Komukai, Sho; Koga, Hiroki; Yamaji, Koutaro; Ide, Takao; Kawaguchi, Atsushi; Aishima, Shinichi; Noshiro, Hirokazu

2018-01-07

To investigate the association between smoking habits and surgical outcomes in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) (B-HCC) and hepatitis C virus (HCV)-related HCC (C-HCC) and clarify the clinicopathological features associated with smoking status in B-HCC and C-HCC patients. We retrospectively examined the cases of the 341 consecutive patients with viral-associated HCC (C-HCC, n = 273; B-HCC, n = 68) who underwent curative surgery for their primary lesion. We categorized smoking status at the time of surgery into never, ex- and current smoker. We analyzed the B-HCC and C-HCC groups' clinicopathological features and surgical outcomes, i.e ., disease-free survival (DFS), overall survival (OS), and disease-specific survival (DSS). Univariate and multivariate analyses were performed using a Cox proportional hazards regression model. We also performed subset analyses in both patient groups comparing the current smokers to the other patients. The multivariate analysis in the C-HCC group revealed that current-smoker status was significantly correlated with both OS ( P = 0.0039) and DSS ( P = 0.0416). In the B-HCC patients, no significant correlation was observed between current-smoker status and DFS, OS, or DSS in the univariate or multivariate analyses. The subset analyses comparing the current smokers to the other patients in both the C-HCC and B-HCC groups revealed that the current smokers developed HCC at significantly younger ages than the other patients irrespective of viral infection status. A smoking habit is significantly correlated with the overall and disease-specific survivals of patients with C-HCC. In contrast, the B-HCC patients showed a weak association between smoking status and surgical outcomes.

Lower risk taking and exploratory behavior in alcohol-preferring sP rats than in alcohol non-preferring sNP rats in the multivariate concentric square field (MCSF) test.

PubMed

Roman, Erika; Colombo, Giancarlo

2009-12-14

The present investigation continues previous behavioral profiling studies of selectively bred alcohol-drinking and alcohol non-drinking rats. In this study, alcohol-naïve adult Sardinian alcohol-preferring (sP) and non-preferring (sNP) rats were tested in the multivariate concentric square field (MCSF) test. The MCSF test has an ethoexperimental approach and measures general activity, exploration, risk assessment, risk taking, and shelter seeking in laboratory rodents. The multivariate design enables behavioral profiling in one and the same test situation. Age-matched male Wistar rats were included as a control group. Five weeks after the first MCSF trial, a repeated testing was done to explore differences in acquired experience. The results revealed distinct differences in exploratory strategies and behavioral profiles between sP and sNP rats. The sP rats were characterized by lower activity, lower exploratory drive, higher risk assessment, and lower risk taking behavior than in sNP rats. In the repeated trial, risk-taking behavior was almost abolished in sP rats. When comparing the performance of sP and sNP rats with that of Wistar rats, the principal component analysis revealed that the sP rats were the most divergent group. The vigilant behavior observed in sP rats with low exploratory drive and low risk-taking behavior is interpreted here as high innate anxiety-related behaviors and may be related to their propensity for high voluntary alcohol intake and preference. We suggest that the different lines of alcohol-preferring rats with different behavioral characteristics constitute valuable animal models that mimic the heterogeneity in human alcohol dependence.

Physical activity in Black breast cancer survivors: implications for quality of life and mood at baseline and 6-month follow-up.

PubMed

Diggins, Allyson D; Hearn, Lauren E; Lechner, Suzanne C; Annane, Debra; Antoni, Michael H; Whitehead, Nicole Ennis

2017-06-01

The present study sought to examine the influence of physical activity on quality of life and negative mood in a sample of Black breast cancer survivors to determine if physical activity (dichotomized) predicted mean differences in negative mood and quality of life in this population. Study participants include 114 women diagnosed with breast cancer (any stage of disease, any type of breast cancer) recruited to participate in an adaptive cognitive-behavioral stress management intervention. The mean body mass index of the sample at baseline was 31.39 (standard deviation = 7.17). A multivariate analysis of covariance (MANCOVA) was conducted to determine if baseline physical activity predicted mean differences in negative mood and quality of life at baseline and at follow ups while controlling for relevant covariates. A one-way MANCOVA revealed a significant multivariate effect by physical activity group for the combined dependent variables at Time 2 (post 10-week intervention), p = .039. The second one-way MANCOVA revealed a significant multivariate effect at Time 3 (6 months after Time 2), p = .034. Specifically, Black breast cancer survivors who engaged in physical activity experienced significantly lower negative mood and higher social/family well-being at Time 2 and higher spiritual and functional well-being at Times 2 and 3. Results show that baseline physical activity served protective functions for breast cancer survivors over time. Developing culturally relevant physical activity interventions specifically for Black breast cancer survivors may prove vital to improving quality of life and mood in this population. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Water conservation behavior in Australia.

PubMed

Dolnicar, Sara; Hurlimann, Anna; Grün, Bettina

2012-08-30

Ensuring a nation's long term water supply requires the use of both supply-sided approaches such as water augmentation through water recycling, and demand-sided approaches such as water conservation. Conservation behavior can only be increased if the key drivers of such behavior are understood. The aim of this study is to reveal the main drivers from a comprehensive pool of hypothesized factors. An empirical study was conducted with 3094 Australians. Data was analyzed using multivariate linear regression analysis and decision trees to determine which factors best predict self-reported water conservation behavior. Two key factors emerge: high level of pro-environmental behavior; and pro-actively seeking out information about water. A number of less influential factors are also revealed. Public communication strategy implications are derived. Copyright © 2012 Elsevier Ltd. All rights reserved.

Increased plasma proline concentrations are associated with sarcopenia in the elderly.

PubMed

Toyoshima, Kenji; Nakamura, Marie; Adachi, Yusuke; Imaizumi, Akira; Hakamada, Tomomi; Abe, Yasuko; Kaneko, Eiji; Takahashi, Soiciro; Shimokado, Kentaro

2017-01-01

Metabolome analyses have shown that plasma amino acid profiles reflect various pathological conditions, such as cancer and diabetes mellitus. It remains unclear, however, whether plasma amino acid profiles change in patients with sarcopenia. This study therefore aimed to investigate whether sarcopenia-specific changes occur in plasma amino acid profiles. A total of 153 community-dwelling and seven institutionalized elderly individuals (56 men, 104 women; mean age, 77.7±7.0 years) were recruited for this cross-sectional analysis. We performed a comprehensive geriatric assessment, which included an evaluation of hand grip strength, gait speed, muscle mass and blood chemistry, including the concentration of 18 amino acids. Twenty-eight of the 160 participants met the criteria for sarcopenia established by the Asian Working Group on Sarcopenia in Older People. Univariate analysis revealed associations between the presence of sarcopenia and a higher plasma concentration of proline and glutamine, lower concentrations of histidine and tryptophan. Multivariable analysis revealed that a higher concentration of proline was the only variable independently associated with sarcopenia. The plasma concentration of proline may be useful for understanding the underlying pathophysiology of sarcopenia.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Objective. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. Approach. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. Main results. The results showed that 86.0% (p<0.001 ) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. Significance. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Contribution made by multivariate curve resolution applied to gel permeation chromatography-Fourier transform infrared data for an in-depth characterization of styrene-butadiene rubber blends.

PubMed

Ruckebusch, C; Vilmin, F; Coste, N; Huvenne, J P

2008-07-01

We evaluate the contribution made by multivariate curve resolution-alternating least squares (MCR-ALS) for resolving gel permeation chromatography-Fourier transform infrared (GPC-FT-IR) data collected on butadiene rubber (BR) and styrene butadiene rubber (SBR) blends in order to access in-depth knowledge of polymers along the molecular weight distribution (MWD). In the BR-SBR case, individual polymers differ in chemical composition but share almost the same MWD. Principal component analysis (PCA) gives a general overview of the data structure and attests to the feasibility of modeling blends as a binary system. MCR-ALS is then performed. It allows resolving the chromatographic coelution and validates the chosen methodology. For SBR-SBR blends, the problem is more challenging since the individual elastomers present the same chemical composition. Rank deficiency is detected from the PCA data structure analysis. MCR-ALS is thus performed on column-wise augmented matrices. It brings very useful insight into the composition of the analyzed blends. In particular, a weak change in the composition of individual SBR in the MWD's lowest mass region is revealed.

Clinical factors affecting pathological fracture and healing of unicameral bone cysts

PubMed Central

2014-01-01

Background Unicameral bone cyst (UBC) is the most common benign lytic bone lesion seen in children. The aim of this study is to investigate clinical factors affecting pathological fracture and healing of UBC. Methods We retrospectively reviewed 155 UBC patients who consulted Nagoya musculoskeletal oncology group hospitals in Japan. Sixty of the 155 patients had pathological fracture at presentation. Of 141 patients with follow-up periods exceeding 6 months, 77 were followed conservatively and 64 treated by surgery. Results The fracture risk was significantly higher in the humerus than other bones. In multivariate analysis, ballooning of bone, cyst in long bone, male sex, thin cortical thickness and multilocular cyst were significant adverse prognostic factors for pathological fractures at presentation. The healing rates were 30% and 83% with observation and surgery, respectively. Multivariate analysis revealed that fracture at presentation and history of biopsy were good prognostic factors for healing of UBC in patients under observation. Conclusion The present results suggest that mechanical disruption of UBC such as fracture and biopsy promotes healing, and thus watchful waiting is indicated in these patients, whereas patients with poor prognostic factors for fractures should be considered for surgery. PMID:24884661

Clinical factors affecting pathological fracture and healing of unicameral bone cysts.

PubMed

Urakawa, Hiroshi; Tsukushi, Satoshi; Hosono, Kozo; Sugiura, Hideshi; Yamada, Kenji; Yamada, Yoshihisa; Kozawa, Eiji; Arai, Eisuke; Futamura, Naohisa; Ishiguro, Naoki; Nishida, Yoshihiro

2014-05-17

Unicameral bone cyst (UBC) is the most common benign lytic bone lesion seen in children. The aim of this study is to investigate clinical factors affecting pathological fracture and healing of UBC. We retrospectively reviewed 155 UBC patients who consulted Nagoya musculoskeletal oncology group hospitals in Japan. Sixty of the 155 patients had pathological fracture at presentation. Of 141 patients with follow-up periods exceeding 6 months, 77 were followed conservatively and 64 treated by surgery. The fracture risk was significantly higher in the humerus than other bones. In multivariate analysis, ballooning of bone, cyst in long bone, male sex, thin cortical thickness and multilocular cyst were significant adverse prognostic factors for pathological fractures at presentation. The healing rates were 30% and 83% with observation and surgery, respectively. Multivariate analysis revealed that fracture at presentation and history of biopsy were good prognostic factors for healing of UBC in patients under observation. The present results suggest that mechanical disruption of UBC such as fracture and biopsy promotes healing, and thus watchful waiting is indicated in these patients, whereas patients with poor prognostic factors for fractures should be considered for surgery.

Loneliness in Men 60 Years and Over: The Association With Purpose in Life.

PubMed

Neville, Stephen; Adams, Jeffery; Montayre, Jed; Larmer, Peter; Garrett, Nick; Stephens, Christine; Alpass, Fiona

2018-07-01

Loneliness as a consequence of getting older negatively impacts on the health and well-being of men as they age. Having a purpose in life may mitigate loneliness and therefore positively impact on health and well-being. Limited research into loneliness and purpose in life has been undertaken in older men. This study seeks to understand the relationship between loneliness and purpose in life in a group of older men. Using data from a cross-sectional survey of 614 men aged 60 years and over living in New Zealand, bivariate and multivariate analyses were undertaken to examine the relationship between loneliness and purpose in life using a range of demographic, health, and social connection variables. Bivariate analysis revealed that being unpartnered and having low socioeconomic status, limited social networks, low levels of participation, and mental health issues were associated with loneliness. Multivariate analysis showed that having poor mental health and lower purpose in life were indicators of loneliness. Consequently, improving mental health and purpose in life are likely to reduce loneliness in at-risk older men. As older men are a heterogeneous group from a variety of sociocultural and ethnic backgrounds, a multidimensional approach to any intervention initiatives needs to occur.

Attitudes and exercise adherence: test of the Theories of Reasoned Action and Planned Behaviour.

PubMed

Smith, R A; Biddle, S J

1999-04-01

Three studies of exercise adherence and attitudes are reported that tested the Theory of Reasoned Action and the Theory of Planned Behaviour. In a prospective study of adherence to a private fitness club, structural equation modelling path analysis showed that attitudinal and social normative components of the Theory of Reasoned Action accounted for 13.1% of the variance in adherence 4 months later, although only social norm significantly predicted intention. In a second study, the Theory of Planned Behaviour was used to predict both physical activity and sedentary behaviour. Path analyses showed that attitude and perceived control, but not social norm, predicted total physical activity. Physical activity was predicted from intentions and control over sedentary behaviour. Finally, an intervention study with previously sedentary adults showed that intentions to be active measured at the start and end of a 10-week intervention were associated with the planned behaviour variables. A multivariate analysis of variance revealed no significant multivariate effects for time on the planned behaviour variables measured before and after intervention. Qualitative data provided evidence that participants had a positive experience on the intervention programme and supported the role of social normative factors in the adherence process.

[Violence and post-traumatic stress disorder in childhood].

PubMed

Ximenes, Liana Furtado; de Oliveira, Raquel de Vasconcelos Carvalhães; de Assis, Simone Gonçalves

2009-01-01

This study presents the prevalence of symptoms of Posttraumatic Stress Disorder (PTSD) in 500 schoolchildren (6-13 years old) in São Gonçalo, Rio de Janeiro. It also investigates the association between PTSD, violence and other adverse events in the lives of these children. The multi-stage cluster sampling strategy involved three selection stages. Parents were interviewed about their children's behavior. The instrument used to screen symptoms of PTSD was the Child Behavior Checklist-Posttraumatic Stress Disorder Scale (CBCL-PTSD). Conflict Tactics Scales (CTS) were applied to evaluate family violence and other scales to investigate the socioeconomic profile, familiar relationship, characteristics and adverse events in the lives of the children. Multivariate analysis was performed using a hierarchical model with a significance level of 5%. The prevalence of clinical symptoms of PTSD was of 6.5%. The multivariate analysis suggested an explanation model of PTSD characterized by 18 variables, such as the child's characteristics; specific life events; family violence; and other family factors. The results reveal that it is necessary to work with the child in particularly difficult moments of his/her life in order to prevent or minimize the impact of adverse events on their mental and social functioning.

A multivariate analysis of prognostic factors for melanoma patients with lesions greater than or equal to 3.65 mm in thickness. The importance of revealing alternative Cox models.

PubMed Central

Day, C L; Lew, R A; Mihm, M C; Sober, A J; Harris, M N; Kopf, A W; Fitzpatrick, T B; Harrist, T J; Golomb, F M; Postel, A; Hennessey, P; Gumport, S L; Raker, J W; Malt, R A; Cosimi, A B; Wood, W C; Roses, D F; Gorstein, F; Rigel, D; Friedman, R J; Mintzis, M M; Grier, R W

1982-01-01

Fourteen prognostic factors were examined in 79 patients with clinical Stage I melanoma greater than or equal to 3.65 mm in thickness. All nine patients with melanoma of the hands or feet died of melanoma. A Cox proportional hazards (multivariate) analysis of the remaining 70 patients showed that a combination of the following four variables best predicted bony or visceral metastases: 1) a nearly absent or minimal lymphocyte response at the base of the tumor, 2) histologic type other than superficial spreading melanoma, 3) location on the trunk, and 4) positive nodes or no initial node dissection. Ulceration and/or ulceration width were not useful in predicting outcome either singly or in combination with other variables. Patients with negative lymph nodes and primary tumors of the trunk, hands, and feet did not do better than patients with positive nodes at those sites. Conversely, non of 16 patients with negative lymph nodes and extremity melanomas (excluding the hands and feet) or head and neck melanomas developed visceral or bony metastases (i.e., five-year disease-free survival rate 100%). PMID:7055383

Musculoskeletal ultrasonography delineates ankle symptoms in rheumatoid arthritis.

PubMed

Toyota, Yukihiro; Tamura, Maasa; Kirino, Yohei; Sugiyama, Yumiko; Tsuchida, Naomi; Kunishita, Yosuke; Kishimoto, Daiga; Kamiyama, Reikou; Miura, Yasushi; Minegishi, Kaoru; Yoshimi, Ryusuke; Ueda, Atsuhisa; Nakajima, Hideaki

2017-05-01

To clarify the use of musculoskeletal ultrasonography (US) of ankle joints in rheumatoid arthritis (RA). Consecutive RA patients with or without ankle symptoms participated in the study. The US, clinical examination (CE), and patients' visual analog scale for pain (pVAS) for ankles were assessed. Prevalence of tibiotalar joint synovitis and tenosynovitis were assessed by grayscale (GS) and power Doppler (PD) US using a semi-quantitative grading (0-3). The positive US and CE findings were defined as GS score ≥2 and/or PD score ≥1, and joint swelling and/or tenderness, respectively. Multivariate analysis with the generalized linear mixed model was performed by assigning ankle pVAS as a dependent variable. Among a total of 120 ankles from 60 RA patients, positive ankle US findings were found in 21 (35.0%) patients. The concordance rate of CE and US was moderate (kappa 0.57). Of the 88 CE negative ankles, US detected positive findings in 9 (10.2%) joints. Multivariate analysis revealed that ankle US, clinical disease activity index, and foot Health Assessment Questionnaire, but not CE, was independently associated with ankle pVAS. US examination is useful to illustrate RA ankle involvement, especially for patients who complain ankle pain but lack CE findings.

Difference in Postsurgical Prognostic Factors between Lung Adenocarcinoma and Squamous Cell Carcinoma

PubMed Central

Sakai, Hiroki; Kimura, Hiroyuki; Miyazawa, Tomoyuki; Marushima, Hideki; Saji, Hisashi

2017-01-01

Purpose: The aim of this study was to compare the clinicopathologic prognostic factors between patients who underwent lung resection for adenocarcinoma (AD) and those with squamous cell carcinoma (SQ). Methods: A database of patients with lung AD or SQ who underwent surgery with curative intent in our department from January 2008 to December 2014 was reviewed. Associations between various clinicopathologic factors, postsurgical recurrence-free survival (RFS), and overall survival (OS) were analyzed to find significant prognostic factors. Results: A total of 537 lung cancer patients (AD, 434; SQ, 103) were included in this study. Although RFS was similar in patients with AD and SQ, OS was significantly poorer in those with SQ. Multivariate analysis in patients with AD revealed that age (≥69 vs. <69), lymphatic invasion, and histologic pleural invasion (p0 vs. p1–3) were associated with RFS, while gender and pleural invasion were associated with OS. In SQ, however, smoking, clinical stage, and pulmonary metastasis were associated with RFS in the multivariate analysis. Conclusion: Since significant postoperative prognostic factors are quite different between lung AD and SQ, these two histologic types should be differently analyzed in a clinical study. PMID:28966230

Multivariate analysis of the geochemistry and mineralogy of soils along two continental-scale transects in North America

USGS Publications Warehouse

Drew, L.J.; Grunsky, E.C.; Sutphin, D.M.; Woodruff, L.G.

2010-01-01

Soils collected in 2004 along two North American continental-scale transects were subjected to geochemical and mineralogical analyses. In previous interpretations of these analyses, data were expressed in weight percent and parts per million, and thus were subject to the effect of the constant-sum phenomenon. In a new approach to the data, this effect was removed by using centered log-ratio transformations to 'open' the mineralogical and geochemical arrays. Multivariate analyses, including principal component and linear discriminant analyses, of the centered log-ratio data reveal the effects of soil-forming processes, including soil parent material, weathering, and soil age, at the continental-scale of the data arrays that were not readily apparent in the more conventionally presented data. Linear discriminant analysis of the data arrays indicates that the majority of the soil samples collected along the transects can be more successfully classified with Level 1 ecological regional-scale classification by the soil geochemistry than soil mineralogy. A primary objective of this study is to discover and describe, in a parsimonious way, geochemical processes that are both independent and inter-dependent and manifested through compositional data including estimates of the elements and corresponding mineralogy. ?? 2010.

Impact of FAB classification on predicting outcome in acute myeloid leukemia, not otherwise specified, patients undergoing allogeneic stem cell transplantation in CR1: An analysis of 1690 patients from the acute leukemia working party of EBMT.

PubMed

Canaani, Jonathan; Beohou, Eric; Labopin, Myriam; Socié, Gerard; Huynh, Anne; Volin, Liisa; Cornelissen, Jan; Milpied, Noel; Gedde-Dahl, Tobias; Deconinck, Eric; Fegueux, Nathalie; Blaise, Didier; Mohty, Mohamad; Nagler, Arnon

2017-04-01

The French, American, and British (FAB) classification system for acute myeloid leukemia (AML) is extensively used and is incorporated into the AML, not otherwise specified (NOS) category in the 2016 WHO edition of myeloid neoplasm classification. While recent data proposes that FAB classification does not provide additional prognostic information for patients for whom NPM1 status is available, it is unknown whether FAB still retains a current prognostic role in predicting outcome of AML patients undergoing allogeneic stem cell transplantation. Using the European Society of Blood and Bone Marrow Transplantation registry we analyzed outcome of 1690 patients transplanted in CR1 to determine if FAB classification provides additional prognostic value. Multivariate analysis revealed that M6/M7 patients had decreased leukemia free survival (hazard ratio (HR) of 1.41, 95% confidence interval (CI), 1.01-1.99; P = .046) in addition to increased nonrelapse mortality (NRM) rates (HR, 1.79; 95% CI, 1.06-3.01; P = .028) compared with other FAB types. In the NPM1 wt AML, NOS cohort, FAB M6/M7 was also associated with increased NRM (HR, 2.17; 95% CI, 1.14-4.16; P = .019). Finally, in FLT3-ITD + patients, multivariate analyses revealed that specific FAB types were tightly associated with adverse outcome. In conclusion, FAB classification may predict outcome following transplantation in AML, NOS patients. © 2017 Wiley Periodicals, Inc.

Selective use of preoperative endoscopic retrograde cholangiopancreatography in the era of laparoscopic cholecystectomy.

PubMed

Nataly, Yogesh; Merrie, Arend E; Stewart, Ian D

2002-03-01

The use of endoscopic retrograde cholangiopancreatography (ERCP) in the management of suspected common bile duct (CBD) stones prior to laparoscopic cholecystectomy is common. The associated morbidity can be significant. The present study determines significant predictors of CBD stones and improves the selection of patients for preoperative ERCP. All preoperative ERCP for suspected CBD stones in the year 1998 were studied retrospectively. Univariate and multivariate analyses of a number of clinical, biochemical and radiological variables were carried out to determine the best predictors of CBD stones. A total of 112 patients had successful preoperative ERCP. Sixty-one per cent of these were negative for stones and the morbidity was 9%. Univariate analysis revealed the following variables as predictors: cholangitis (P = 0.006), abnormal serum bilirubin > or = 3 days (P = 0.002), serum alkaline phosphatase > or = 130 U/L (P = 0.002), deranged liver function tests (P = < 0.001) and CBD diameter > or = 8 mm (P = 0.009) with positive predictive values of 80%, 68%, 49%, 38% and 52%, respectively. Multivariate analysis revealed the model with the best ability to discriminate for CBD stones (P = 0.0005) was cholangitis, abnormal serum bilirubin for > or = 3 days and CBD diameter > or = 8 mm. The best predictors from this study had a sensitivity of 80% and a specificity of 27%. The predictors of CBD stones are imprecise. Until laparoscopic exploration of CBD becomes widely available, ERCP prior to cholecystectomy will remain popular. The use of stricter selection criteria can reduce the number of negative preoperative ERCP.

Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.

Interactions and accumulation differences of metal(loid)s in three sea cucumber species collected from the Northern Mediterranean Sea.

PubMed

Tunca, Evren; Aydın, Mehmet; Şahin, ÜlküAlver

2016-10-01

This study was conducted on Holothuria polii, Holothuria tubulosa, and Holothuria mammata collected from five stations with different depths in the Northern Mediterranean Sea. The body walls and guts of these holothurians were examined in terms of interactions of 10 metals (iron (Fe), copper (Cu), manganese (Mn), zinc (Zn), chromium (Cr), cobalt (Co), vanadium (V), nickel (Ni), cadmium (Cd), and lead (Pb)) and one metalloid (arsenic (As)) using a multivariate analysis, and interspecies differences were determined. The multivariate analysis of variance (MANOVA) revealed significant differences between the species in terms of metal(loid) accumulations. The principal component analysis (PCA) showed a more association between H. tubulosa and H. polii with regard to the accumulation. The cluster analysis (CA) located Pb concentrations of the guts to the farthest place from all elements regardless of the species. A correlation analysis displayed that the element concentrations of the guts were more closely related to each other compared with those of the walls. The most inconsistent element in terms of correlations was the gut Fe contents. Accordingly, while Fe concentrations of H. mammata and H. tubulosa were correlated with all elements (except Pb) in divalent metal transporter 1 (DMT1) (divalent cation transporter 1 (DCT1) or natural resistance-associated macrophage protein 2 (NRAMP2)) belonging to the NRAM protein family, this was not the case in H. polii. Consequently, significant relationships between accumulated metal(loid)s that changed by tissues and sea cucumber species were observed.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

PubMed

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-07-01

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

PubMed Central

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T.; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-01-01

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153689

Differential Adjustment Among Rural Adolescents Exposed to Family Violence

PubMed Central

Sianko, Natallia; Hedge, Jasmine M.; McDonell, James R.

2016-01-01

This study examines differences in psychological adjustment in a sample of rural adolescents who have been exposed to family violence. Self-report questionnaires were administered to 580 adolescents and their primary caregivers. The results revealed that over two thirds of the study participants (68.8%) had been exposed to violence in their families. As hypothesized, cluster analysis identified several profiles among adolescents, distinguished by their psychological and emotional functioning: well adjusted (46.2%), moderately adjusted (44.3%), and struggling (9.5%). Discriminant function analysis confirmed the groupings and revealed that family functioning was among the most influential factors explaining adjustment differences. Multivariate analyses of variance (MANOVAs) further showed that adolescents from each of the three adjustment profiles reported significantly different levels of family social support, parental involvement, and perceived neighborhood safety. Overall, the results confirm heterogeneity of adolescent adaptation in the aftermath of family violence and provide insights into family and neighborhood factors that account for variability in adolescents’ reactions to violence. Implications for future research and practical interventions are discussed. PMID:27106255

The predictive factors for lymph node metastasis in early gastric cancer: A clinical study.

PubMed

Wang, Yinzhong

2015-01-01

To detect the clinicopathological factors associated with lymph node metastases in early gastric cancer. We retrospectively evaluated the distribution of metastatic nodes in 198 patients with early gastric cancer treated in our hospital between May 2008 and January 2015, the clinicopathological factors including age, gender, tumor location, tumor size, macroscopic type, depth of invasion, histological type and venous invasion were studied, and the relationship between various parameters and lymph node metastases was analyzed. In this study, one hundred and ninety-eight patients with early gastric cancer were included, and lymph node metastasis was detected in 28 patients. Univariate analysis revealed a close relationship between tumor size, depth of invasion, histological type, venous invasion, local ulceration and lymph node metastases. Multivariate analysis revealed that the five factors were independent risk factors for lymph node metastases. The clinicopathological parameters including tumor size, depth of invasion, local ulceration, histological type and venous invasion are closely correlated with lymph node metastases, should be paid high attention in early gastric cancer patients.

Insulin-like growth factor II messenger RNA-binding protein-3 is an independent prognostic factor in uterine leiomyosarcoma.

PubMed

Yasutake, Nobuko; Ohishi, Yoshihiro; Taguchi, Kenichi; Hiraki, Yuka; Oya, Masafumi; Oshiro, Yumi; Mine, Mari; Iwasaki, Takeshi; Yamamoto, Hidetaka; Kohashi, Kenichi; Sonoda, Kenzo; Kato, Kiyoko; Oda, Yoshinao

2018-04-01

The aim of this study was to identify the prognostic factors of uterine leiomyosarcoma (ULMS). We reviewed 60 cases of surgically resected ULMSs and investigated conventional clinicopathological factors, together with the expression of insulin-like growth factor II messenger RNA-binding protein-3 (IMP3), hormone receptors and cell cycle regulatory markers by immunohistochemistry. Mediator complex subunit 12 (MED12) mutation analysis was also performed. Univariate analyses revealed that advanced stage (P < 0.0001), older age (P = 0.0244) and IMP3 expression (P = 0.0011) were significant predictors of a poor outcome. Multivariate analysis revealed advanced stage (P < 0.0001) and IMP3 (P = 0.0373) as independent predictors of a poor prognosis. Expressions of cell cycle markers and hormone receptors, and MED12 mutations (12% in ULMSs) were not identified as prognostic markers in this study. IMP3 expression in ULMS could be a marker of a poor prognosis. © 2017 John Wiley & Sons Ltd.

Assessment of cardio-respiratory interactions in preterm infants by bivariate autoregressive modeling and surrogate data analysis.

PubMed

Indic, Premananda; Bloch-Salisbury, Elisabeth; Bednarek, Frank; Brown, Emery N; Paydarfar, David; Barbieri, Riccardo

2011-07-01

Cardio-respiratory interactions are weak at the earliest stages of human development, suggesting that assessment of their presence and integrity may be an important indicator of development in infants. Despite the valuable research devoted to infant development, there is still a need for specifically targeted standards and methods to assess cardiopulmonary functions in the early stages of life. We present a new methodological framework for the analysis of cardiovascular variables in preterm infants. Our approach is based on a set of mathematical tools that have been successful in quantifying important cardiovascular control mechanisms in adult humans, here specifically adapted to reflect the physiology of the developing cardiovascular system. We applied our methodology in a study of cardio-respiratory responses for 11 preterm infants. We quantified cardio-respiratory interactions using specifically tailored multivariate autoregressive analysis and calculated the coherence as well as gain using causal approaches. The significance of the interactions in each subject was determined by surrogate data analysis. The method was tested in control conditions as well as in two different experimental conditions; with and without use of mild mechanosensory intervention. Our multivariate analysis revealed a significantly higher coherence, as confirmed by surrogate data analysis, in the frequency range associated with eupneic breathing compared to the other ranges. Our analysis validates the models behind our new approaches, and our results confirm the presence of cardio-respiratory coupling in early stages of development, particularly during periods of mild mechanosensory intervention, thus encouraging further application of our approach. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A modal analysis of flexible aircraft dynamics with handling qualities implications

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

A multivariable modal analysis technique is presented for evaluating flexible aircraft dynamics, focusing on meaningful vehicle responses to pilot inputs and atmospheric turbulence. Although modal analysis is the tool, vehicle time response is emphasized, and the analysis is performed on the linear, time-domain vehicle model. In evaluating previously obtained experimental pitch tracking data for a family of vehicle dynamic models, it is shown that flexible aeroelastic effects can significantly affect pitch attitude handling qualities. Consideration of the eigenvalues alone, of both rigid-body and aeroelastic modes, does not explain the simulation results. Modal analysis revealed, however, that although the lowest aeroelastic mode frequency was still three times greater than the short-period frequency, the rigid-body attitude response was dominated by this aeroelastic mode. This dominance was defined in terms of the relative magnitudes of the modal residues in selected vehicle responses.

Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

ERIC Educational Resources Information Center

Valero-Mora, Pedro M.; Ledesma, Ruben D.

2011-01-01

This paper discusses the use of interactive graphics to teach multivariate data analysis to Psychology students. Three techniques are explored through separate activities: parallel coordinates/boxplots; principal components/exploratory factor analysis; and cluster analysis. With interactive graphics, students may perform important parts of the…

Identification of six polymorphisms as novel susceptibility loci for ischemic or hemorrhagic stroke by exome-wide association studies

PubMed Central

Yamada, Yoshiji; Sakuma, Jun; Takeuchi, Ichiro; Yasukochi, Yoshiki; Kato, Kimihiko; Oguri, Mitsutoshi; Fujimaki, Tetsuo; Horibe, Hideki; Muramatsu, Masaaki; Sawabe, Motoji; Fujiwara, Yoshinori; Taniguchi, Yu; Obuchi, Shuichi; Kawai, Hisashi; Shinkai, Shoji; Mori, Seijiro; Arai, Tomio; Tanaka, Masashi

2017-01-01

In this study, we performed exome-wide association studies (EWASs) to identify genetic variants that confer susceptibility to ischemic stroke, intracerebral hemorrhage (ICH), or subarachnoid hemorrhage (SAH). EWAS for ischemic stroke was performed using 1,575 patients with this condition and 9,210 controls, and EWASs for ICH and SAH were performed using 673 patients with ICH, 265 patients with SAH and 9,158 controls. Analyses were performed with Illumina HumanExome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The relation of allele frequencies for 41,339 or 41,332 single nucleotide polymorphisms (SNPs) that passed quality control to ischemic or hemorrhagic stroke, respectively, was examined with Fisher's exact test. Based on Bonferroni's correction, a P-value of <1.21×10−6 was considered statistically significant. EWAS for ischemic stroke revealed that 77 SNPs were significantly associated with this condition. Multivariable logistic regression analysis with adjustment for age, sex and the prevalence of hypertension and diabetes mellitus revealed that 4 of these SNPs [rs3212335 of GABRB3 (P=0.0036; odds ratio, 1.29), rs147783135 of TMPRSS7 (P=0.0024; odds ratio, 0.37), rs2292661 of PDIA5 (P=0.0054; odds ratio, 0.35) and rs191885206 of CYP4F12 (P=0.0082; odds ratio, 2.60)] were related (P<0.01) to ischemic stroke. EWASs for ICH or SAH revealed that 48 and 12 SNPs, respectively, were significantly associated with these conditions. Multivariable logistic regression analysis with adjustment for age, sex and the prevalence of hypertension revealed that rs138533962 of STYK1 (P<1.0×10−23; odds ratio, 111.3) was significantly (P<2.60×10−4) associated with ICH and that rs117564807 of COL17A1 (P=0.0009; odds ratio, 2.23×10−8) was significantly (P<0.0010) associated with SAH. GABRB3, TMPRSS7, PDIA5 and CYP4F12 may thus be novel susceptibility loci for ischemic stroke, whereas STYK1 and COL17A1 may be such loci for ICH and SAH, respectively. PMID:28487959

A power analysis for multivariate tests of temporal trend in species composition.

PubMed

Irvine, Kathryn M; Dinger, Eric C; Sarr, Daniel

2011-10-01

Long-term monitoring programs emphasize power analysis as a tool to determine the sampling effort necessary to effectively document ecologically significant changes in ecosystems. Programs that monitor entire multispecies assemblages require a method for determining the power of multivariate statistical models to detect trend. We provide a method to simulate presence-absence species assemblage data that are consistent with increasing or decreasing directional change in species composition within multiple sites. This step is the foundation for using Monte Carlo methods to approximate the power of any multivariate method for detecting temporal trends. We focus on comparing the power of the Mantel test, permutational multivariate analysis of variance, and constrained analysis of principal coordinates. We find that the power of the various methods we investigate is sensitive to the number of species in the community, univariate species patterns, and the number of sites sampled over time. For increasing directional change scenarios, constrained analysis of principal coordinates was as or more powerful than permutational multivariate analysis of variance, the Mantel test was the least powerful. However, in our investigation of decreasing directional change, the Mantel test was typically as or more powerful than the other models.

A climatology of total ozone mapping spectrometer data using rotated principal component analysis

NASA Astrophysics Data System (ADS)

Eder, Brian K.; Leduc, Sharon K.; Sickles, Joseph E.

1999-02-01

The spatial and temporal variability of total column ozone (Ω) obtained from the total ozone mapping spectrometer (TOMS version 7.0) during the period 1980-1992 was examined through the use of a multivariate statistical technique called rotated principal component analysis. Utilization of Kaiser's varimax orthogonal rotation led to the identification of 14, mostly contiguous subregions that together accounted for more than 70% of the total Ω variance. Each subregion displayed statistically unique Ω characteristics that were further examined through time series and spectral density analyses, revealing significant periodicities on semiannual, annual, quasi-biennial, and longer term time frames. This analysis facilitated identification of the probable mechanisms responsible for the variability of Ω within the 14 homogeneous subregions. The mechanisms were either dynamical in nature (i.e., advection associated with baroclinic waves, the quasi-biennial oscillation, or El Niño-Southern Oscillation) or photochemical in nature (i.e., production of odd oxygen (O or O3) associated with the annual progression of the Sun). The analysis has also revealed that the influence of a data retrieval artifact, found in equatorial latitudes of version 6.0 of the TOMS data, has been reduced in version 7.0.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of LANDSAT digital data

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

Characterizing backcountry camping impacts in Great Smoky Mountains National Park

USGS Publications Warehouse

Leung, Y.-F.; Marion, J.L.

1999-01-01

This investigates resource impacts on backcounty campsites in the Great Smoky Mountains National Park, USA. Study objectives were to enhance our understanding of camping impacts and to improve campsite impact assessment procedures by means of multivariate techniques. Three-hundred and eight campsites at designated backcountry campgrounds, and 69 additional unofficial campsites were assessed. Factor analysis of 195 established campsites on eight impact indicator variables revealed three dimensions of campsite impact: area disturbance, soil and groundcover damage, and tree-related damage. Four distinctive backcountry campsite types were identified, three of which were derived from cluster analyses of factor scores. These four backcountry campsite types characterize the intensity and areal extent of resource impacts, and they vary in locational and environmental attributes. At an aggregate level, different campsite types contributed unequally to the cumulative level of impact. The dimensional structure and typology developed in this study demonstrates that campsite impacts can be viewed and examined holistically with the use of multivariate methods. Implications for assessment procedures, management and further research are discussed.

The Potential of Multivariate Analysis in Assessing Students' Attitude to Curriculum Subjects

ERIC Educational Resources Information Center

Gaotlhobogwe, Michael; Laugharne, Janet; Durance, Isabelle

2011-01-01

Background: Understanding student attitudes to curriculum subjects is central to providing evidence-based options to policy makers in education. Purpose: We illustrate how quantitative approaches used in the social sciences and based on multivariate analysis (categorical Principal Components Analysis, Clustering Analysis and General Linear…

Value of dual contrast liver MRI at 3.0 T in differentiating well-differentiated hepatocellular carcinomas from dysplastic nodules: preliminary results of multivariate analysis.

PubMed

Yoon, Min A; Kim, Se Hyung; Park, Hee Sun; Lee, Dong Ho; Lee, Jae Young; Han, Joon Koo; Choi, Byung Ihn

2009-10-01

To assess the diagnostic value of dual contrast magnetic resonance imaging (DC-MRI) in the differentiation of well-differentiated hepatocellular carcinomas (WD-HCCs) from dysplastic nodules (DNs) and to determine the significant MRI predictors using univariate and multivariate analyses. Thirty-two WD-HCCs and 33 DNs in 28 patients who underwent liver transplantation with available histopathology as a gold standard were enrolled in this study. All patients underwent DC-MRI using superparamagnetic iron oxide (SPIO) and gadolinium (Gd) agents on a 3 T MRI unit. For all patients, precontrast T1- and T2-weighted (T2W) images as well as post-SPIO T2- and T2*W images were obtained. Then, for dynamic MRI, arterial (AP), portal, and equilibrium images were also obtained. Two radiologists reviewed the MR images for analyzing signal intensity on the all MR sequences in consensus. On AP images, the degree of enhancement was subjectively categorized into 4 groups: no, minimal, moderate, and strong enhancement. For quantitative analysis, relative arterial enhancement ratio was calculated by averaging 3 regions of interest values of each nodule on pre-Gd T1W and AP images. Each variable was initially evaluated using univariate analyses to assess statistically significant MRI findings differentiating HCCs and DNs, then with multivariate logistic regression analysis to find the most predictable MRI findings. Twenty WD-HCCs showed iso- or high SI on precontrast T2W images, whereas 23 DNs showed low SI (P = 0.003). Most DNs showed low SI on post-SPIO T2W (30/33) and T2*W (25/33) images, whereas HCCs tended to show heterogeneous high or high SI (16/32 and 19/32) (P < 0.012). On post-SPIO and pre-Gd T1W GRE images, 28 WD-HCCs showed iso- or high SI, whereas 24 DNs showed low SI (P < 0.001). On AP images, 20 HCCs revealed more than minimal degree of enhancement, whereas 32 DNs did not show any enhancement (P < 0.001). Mean relative arterial enhancement ratio of HCCs (39.4%) was also significantly larger than that of DNs (15.6%) (P = 0.001). On portal images, WD-HCCs tended to show iso- or high SI (n = 21), whereas DNs showed low SI (n = 29) (P < 0.001). Multivariate analysis revealed that a subjective degree of enhancement on AP images and SI on post-SPIO and pre-Gd T1W GRE images were the 2 variables that independently differentiated WD-HCCs from DNs. The use of DC-MRI is helpful in the differentiation of WD HCCs and DNs. More specifically, a subjective degree of enhancement on AP images and SI on post-SPIO and pre-Gd T1W GRE images are the 2 variables that independently differentiate WD-HCCs from DNs.

Two-sample tests and one-way MANOVA for multivariate biomarker data with nondetects.

PubMed

Thulin, M

2016-09-10

Testing whether the mean vector of a multivariate set of biomarkers differs between several populations is an increasingly common problem in medical research. Biomarker data is often left censored because some measurements fall below the laboratory's detection limit. We investigate how such censoring affects multivariate two-sample and one-way multivariate analysis of variance tests. Type I error rates, power and robustness to increasing censoring are studied, under both normality and non-normality. Parametric tests are found to perform better than non-parametric alternatives, indicating that the current recommendations for analysis of censored multivariate data may have to be revised. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A non-iterative extension of the multivariate random effects meta-analysis.

PubMed

Makambi, Kepher H; Seung, Hyunuk

2015-01-01

Multivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative, have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.

Determinants of holmium:yttrium-aluminum-garnet laser time and energy during ureteroscopic laser lithotripsy.

PubMed

Molina, Wilson R; Marchini, Giovanni S; Pompeo, Alexandre; Sehrt, David; Kim, Fernando J; Monga, Manoj

2014-04-01

To evaluate the association of preoperative noncontrast computed tomography stone characteristics, laser settings, and stone composition with cumulative holmium:yttrium-aluminum-garnet (Ho:YAG) laser time/energy. We retrospectively reviewed patients who underwent semirigid/flexible ureteroscopy and Ho:YAG laser lithotripsy (200 or 365 μm laser fiber; 0.8-1.0 J energy; and 8-10 Hz rate) at 2 tertiary care centers (April 2010-May 2012). Studied parameters were as follows: patient's characteristics; stone characteristics (location, burden, hardness, and composition); total laser time and energy; and surgical outcomes. One hundred patients met our inclusion criteria. Mean stone size was 1.01 ± 0.42 cm and volume 0.33 ± 0.04 cm(3). Mean stone radiodensity was 990 ± 296 HU, and Hounsfield units density 13.8 ± 6.0 HU/mm. All patients were considered stone free. Stone size and volume had a significant positive correlation with laser energy (R = 0.516, P <.001; R = 0.621, P <.001) and laser time (R = 0.477, P <.001; R = 0.567, P <.001). When controlling for stone size, only the correlation between HU and laser time was significant (R = 0.262, P = .011). In the multivariate analysis, with exception of stone composition (P = .103), all parameters significantly increased laser energy (R(2) = 0.524). Multivariate analysis revealed a positive significant association of laser time with stone volume (P <.001) and Hounsfield units density (P <.001; R(2) = 0.512). In multivariate analysis for laser energy, only calcium phosphate stones required less energy to fragment compared with uric acid stones. No significant differences were found in the multivariate laser time model. Ho:YAG laser cumulative energy and total time are significantly affected by stone dimensions, hardness location, fiber size, and power. Kidney location, laser fiber size, and laser power have more influence on the final laser energy than on the total laser time. Calcium phosphate stones require less laser energy to fragment. Copyright © 2014 Elsevier Inc. All rights reserved.

Economic Impact of Increased Utilization of Multivariate Assay Testing to Guide the Treatment of Ovarian Cancer: Implications for Payers.

PubMed

Brodsky, Burton S; Owens, Gary M; Scotti, Dennis J; Needham, Keith A; Cool, Christina L

2017-10-01

Ovarian cancer is the eighth most common cancer among women, but ranks fifth in cancer-related causes of death, the majority of which are detected in late stages, after the cancer has metastasized. The CA125 test is the standard of care for assessing suspicious pelvic masses. However, the primary use of CA125 is to monitor treatment progress rather than to screen for disease, and its sensitivity is exceedingly low, unlike the multivariate assay OVA1. A cost-effective treatment of ovarian cancer requires early and accurate diagnosis of pelvic masses and reduced referrals of patients with benign tumors to a gynecologic oncologist. To analyze the economic impact of increased utilization of a multivariate assay, such as OVA1, to guide the treatment of ovarian cancer. The study population was drawn from Medicare and commercial health plan claims data. A budget impact model was constructed to estimate the economic consequences of substituting the multivariate assay OVA1 to replace the single biomarker assay CA125 to assess the likelihood of pelvic mass malignancy in premenopausal and/or postmenopausal women. All patients selected for the analysis had CA125 testing before surgical intervention. A total of 92,843 health plan members were included for analysis, comprising 48,113 commercially insured members and 44,730 Medicare beneficiaries. Estimates of future health plan expenditures, which were calculated from base-case assumptions, projected overall savings of $0.05 per-member per-month (PMPM) for commercially insured members and $0.01 PMPM for Medicare beneficiaries as a result of increased utilization of OVA1. Sensitivity analysis revealed potential savings of up to $0.17 PMPM for commercially insured patients and up to $0.05 for Medicare beneficiaries. The results of the budget impact model support the use of OVA1 instead of CA125 by indicating that modest cost-savings can be achieved, while reaping the clinical benefits of improved diagnostic accuracy, early disease detection, and reductions in multiple, and possibly unnecessary, referrals to gynecologic oncologists.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

A refined method for multivariate meta-analysis and meta-regression.

PubMed

Jackson, Daniel; Riley, Richard D

2014-02-20

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects' standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. Copyright © 2013 John Wiley & Sons, Ltd.

Merging metagenomics and geochemistry reveals environmental controls on biological diversity and evolution.

PubMed

Alsop, Eric B; Boyd, Eric S; Raymond, Jason

2014-05-28

The metabolic strategies employed by microbes inhabiting natural systems are, in large part, dictated by the physical and geochemical properties of the environment. This study sheds light onto the complex relationship between biology and environmental geochemistry using forty-three metagenomes collected from geochemically diverse and globally distributed natural systems. It is widely hypothesized that many uncommonly measured geochemical parameters affect community dynamics and this study leverages the development and application of multidimensional biogeochemical metrics to study correlations between geochemistry and microbial ecology. Analysis techniques such as a Markov cluster-based measure of the evolutionary distance between whole communities and a principal component analysis (PCA) of the geochemical gradients between environments allows for the determination of correlations between microbial community dynamics and environmental geochemistry and provides insight into which geochemical parameters most strongly influence microbial biodiversity. By progressively building from samples taken along well defined geochemical gradients to samples widely dispersed in geochemical space this study reveals strong links between the extent of taxonomic and functional diversification of resident communities and environmental geochemistry and reveals temperature and pH as the primary factors that have shaped the evolution of these communities. Moreover, the inclusion of extensive geochemical data into analyses reveals new links between geochemical parameters (e.g. oxygen and trace element availability) and the distribution and taxonomic diversification of communities at the functional level. Further, an overall geochemical gradient (from multivariate analyses) between natural systems provides one of the most complete predictions of microbial taxonomic and functional composition. Clustering based on the frequency in which orthologous proteins occur among metagenomes facilitated accurate prediction of the ordering of community functional composition along geochemical gradients, despite a lack of geochemical input. The consistency in the results obtained from the application of Markov clustering and multivariate methods to distinct natural systems underscore their utility in predicting the functional potential of microbial communities within a natural system based on system geochemistry alone, allowing geochemical measurements to be used to predict purely biological metrics such as microbial community composition and metabolism.

Terminally differentiated CD8+ T cells and CD57−FOXP3+CD8+ T cells are highly associated with the efficacy of immunotherapy using activated autologous lymphocytes

PubMed Central

Akagi, Junji; Baba, Hideo; Sekine, Teruaki; Ogawa, Kenji

2018-01-01

Treatment with activated autologous lymphocytes (AALs) has demonstrated mixed results for cancer treatment. Preliminary results revealed that the proportion of cluster of differentiation (CD)8+CD57+ T cells is significantly increased in AALs, indicating that they are able to determine treatment outcome. Therefore, the role of CD8+CD57+ T cells in AAL efficacy was investigated. T lymphocytes were isolated from 35 patients with stage IV gastric carcinomas (17 men and 18 women; aged 41–84 years) receiving immunotherapy using AALs (IAAL). Using fluorescence activated cell sorting, CD8, CD27, CD57, and forkhead box protein 3 (FOXP3) expression was investigated on CD8+ T cell populations in CD8+ T cell differentiation prior to and following in vitro culture. The association between these populations and progression-free survival (PFS) was analyzed using Cox univariate, and multivariate analyses and Kaplan-Meier survival analysis. CD57 expression was negative in early-differentiated CD8+ T cells (CD27+CD8+CD57−), and positive in intermediate- (CD27+CD8+CD57+) and terminal- (CD27−CD8+CD57+) differentiated CD8+ T cells. Univariate analysis revealed a significant association between terminal-CD8+ T cells and longer PFS times (P=0.035), whereas CD57−FOXP3+CD8+ T cells were associated with shorter PFS times. Multivariate analysis revealed that CD57−FOXP3+CD8+ T cells was an independent poor prognostic factor, whereas CD57+FOXP3+CD8+ T cells were not associated with PFS. Although IAAL increased the proportion of terminal-CD8+ T cells relative to the pre-culture proportions, patients with a high CD57−FOXP3+CD8+ T cell percentage exhibited repressed terminal-CD8+ T cell induction, leading to poor patient prognosis. Terminally differentiated CD27−CD8+CD57+ T cells were responsible for the effectiveness of AALs; however, CD57−FOXP3+CD8+ T cells abrogated their efficacy, possibly by inhibiting their induction.

Sensitivity of human auditory cortex to rapid frequency modulation revealed by multivariate representational similarity analysis.

PubMed

Joanisse, Marc F; DeSouza, Diedre D

2014-01-01

Functional Magnetic Resonance Imaging (fMRI) was used to investigate the extent, magnitude, and pattern of brain activity in response to rapid frequency-modulated sounds. We examined this by manipulating the direction (rise vs. fall) and the rate (fast vs. slow) of the apparent pitch of iterated rippled noise (IRN) bursts. Acoustic parameters were selected to capture features used in phoneme contrasts, however the stimuli themselves were not perceived as speech per se. Participants were scanned as they passively listened to sounds in an event-related paradigm. Univariate analyses revealed a greater level and extent of activation in bilateral auditory cortex in response to frequency-modulated sweeps compared to steady-state sounds. This effect was stronger in the left hemisphere. However, no regions showed selectivity for either rate or direction of frequency modulation. In contrast, multivoxel pattern analysis (MVPA) revealed feature-specific encoding for direction of modulation in auditory cortex bilaterally. Moreover, this effect was strongest when analyses were restricted to anatomical regions lying outside Heschl's gyrus. We found no support for feature-specific encoding of frequency modulation rate. Differential findings of modulation rate and direction of modulation are discussed with respect to their relevance to phonetic discrimination.

Sex hormones and quantitative ultrasound parameters at the heel in men and women from the general population.

PubMed

Pätzug, Konrad; Friedrich, Nele; Kische, Hanna; Hannemann, Anke; Völzke, Henry; Nauck, Matthias; Keevil, Brian G; Haring, Robin

2017-12-01

The present study investigates potential associations between liquid chromatography-mass spectrometry (LC-MS) measured sex hormones, dehydroepiandrosterone sulphate, sex hormone-binding globulin (SHBG) and bone ultrasound parameters at the heel in men and women from the general population. Data from 502 women and 425 men from the population-based Study of Health in Pomerania (SHIP-TREND) were used. Cross-sectional associations of sex hormones including testosterone (TT), calculated free testosterone (FT), dehydroepiandrosterone sulphate (DHEAS), androstenedione (ASD), estrone (E1) and SHBG with quantitative ultrasound (QUS) parameters at the heel, including broadband ultrasound attenuation (BUA), speed of sound (SOS) and stiffness index (SI) were examined by analysis of variance (ANOVA) and multivariable quantile regression models. Multivariable regression analysis showed a sex-specific inverse association of DHEAS with SI in men (Beta per SI unit = - 3.08, standard error (SE) = 0.88), but not in women (Beta = - 0.01, SE = 2.09). Furthermore, FT was positively associated with BUA in men (Beta per BUA unit = 29.0, SE = 10.1). None of the other sex hormones (ASD, E1) or SHBG was associated with QUS parameters after multivariable adjustment. This cross-sectional population-based study revealed independent associations of DHEAS and FT with QUS parameters in men, suggesting a potential influence on male bone metabolism. The predictive role of DHEAS and FT as a marker for osteoporosis in men warrants further investigation in clinical trials and large-scale observational studies.

Multivariate missing data in hydrology - Review and applications

NASA Astrophysics Data System (ADS)

Ben Aissia, Mohamed-Aymen; Chebana, Fateh; Ouarda, Taha B. M. J.

2017-12-01

Water resources planning and management require complete data sets of a number of hydrological variables, such as flood peaks and volumes. However, hydrologists are often faced with the problem of missing data (MD) in hydrological databases. Several methods are used to deal with the imputation of MD. During the last decade, multivariate approaches have gained popularity in the field of hydrology, especially in hydrological frequency analysis (HFA). However, treating the MD remains neglected in the multivariate HFA literature whereas the focus has been mainly on the modeling component. For a complete analysis and in order to optimize the use of data, MD should also be treated in the multivariate setting prior to modeling and inference. Imputation of MD in the multivariate hydrological framework can have direct implications on the quality of the estimation. Indeed, the dependence between the series represents important additional information that can be included in the imputation process. The objective of the present paper is to highlight the importance of treating MD in multivariate hydrological frequency analysis by reviewing and applying multivariate imputation methods and by comparing univariate and multivariate imputation methods. An application is carried out for multiple flood attributes on three sites in order to evaluate the performance of the different methods based on the leave-one-out procedure. The results indicate that, the performance of imputation methods can be improved by adopting the multivariate setting, compared to mean substitution and interpolation methods, especially when using the copula-based approach.

Use of an operating microscope during spine surgery is associated with minor increases in operating room times and no increased risk of infection.

PubMed

Basques, Bryce A; Golinvaux, Nicholas S; Bohl, Daniel D; Yacob, Alem; Toy, Jason O; Varthi, Arya G; Grauer, Jonathan N

2014-10-15

Retrospective database review. To evaluate whether microscope use during spine procedures is associated with increased operating room times or increased risk of infection. Operating microscopes are commonly used in spine procedures. It is debated whether the use of an operating microscope increases operating room time or confers increased risk of infection. The American College of Surgeons National Surgical Quality Improvement Program database, which includes data from more than 370 participating hospitals, was used to identify patients undergoing elective spinal procedures with and without the use of an operating microscope for the years 2011 and 2012. Bivariate and multivariate linear regressions were used to test the association between microscope use and operating room times. Bivariate and multivariate logistic regressions were similarly conducted to test the association between microscope use and infection occurrence within 30 days of surgery. A total of 23,670 elective spine procedures were identified, of which 2226 (9.4%) used an operating microscope. The average patient age was 55.1±14.4 years. The average operative time (incision to closure) was 125.7±82.0 minutes.Microscope use was associated with minor increases in preoperative room time (+2.9 min, P=0.013), operative time (+13.2 min, P<0.001), and total room time (+18.6 min, P<0.001) on multivariate analysis.A total of 328 (1.4%) patients had an infection within 30 days of surgery. Multivariate analysis revealed no significant difference between the microscope and nonmicroscope groups for occurrence of any infection, superficial surgical site infection, deep surgical site infection, organ space infection, or sepsis/septic shock, regardless of surgery type. We did not find operating room times or infection risk to be significant deterrents for use of an operating microscope during spine surgery. 3.

Use of an operating microscope during spine surgery is associated with minor increases in operating room times and no increased risk of infection

PubMed Central

Basques, Bryce A.; Golinvaux, Nicholas S.; Bohl, Daniel D.; Yacob, Alem; Toy, Jason O.; Varthi, Arya G.; Grauer, Jonathan N.

2014-01-01

Study Design Retrospective database review. Objective To evaluate whether microscope use during spine procedures is associated with increased operating room times or increased risk of infection. Summary of Background Data Operating microscopes are commonly used in spine procedures. It is debated whether the use of an operating microscope increases operating room time or confers increased risk of infection. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, which includes data from over 370 participating hospitals, was used to identify patients undergoing elective spinal procedures with and without an operating microscope for the years 2011 and 2012. Bivariate and multivariate linear regressions were used to test the association between microscope use and operating room times. Bivariate and multivariate logistic regressions were similarly conducted to test the association between microscope use and infection occurrence within 30 days of surgery. Results A total of 23,670 elective spine procedures were identified, of which 2,226 (9.4%) used an operating microscope. The average patient age was 55.1 ± 14.4 years. The average operative time (incision to closure) was 125.7 ± 82.0 minutes. Microscope use was associated with minor increases in preoperative room time (+2.9 minutes, p=0.013), operative time (+13.2 minutes, p<0.001), and total room time (+18.6 minutes, p<0.001) on multivariate analysis. A total of 328 (1.4%) patients had an infection within 30 days of surgery. Multivariate analysis revealed no significant difference between the microscope and non-microscope groups for occurrence of any infection, superficial surgical site infection (SSI), deep SSI, organ space infection, or sepsis/septic shock, regardless of surgery type. Conclusions We did not find operating room times or infection risk to be significant deterrents for use of an operating microscope during spine surgery. PMID:25188600

Development of Pattern Recognition Techniques for the Evaluation of Toxicant Impacts to Multispecies Systems

DTIC Science & Technology

1993-06-18

the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and clustering methods...rule rather than the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and...experiments using two microcosm protocols. We use nonmetric clustering, a multivariate pattern recognition technique developed by Matthews and Heame (1991

System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism.

PubMed

Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram

2017-01-01

Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed similarities to Concord grape and indicates the strong effect of genetic background on metabolic partitioning in primary and secondary metabolism.

System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism

PubMed Central

Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram

2017-01-01

Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed similarities to Concord grape and indicates the strong effect of genetic background on metabolic partitioning in primary and secondary metabolism. PMID:28713396

Multivariate analysis for scanning tunneling spectroscopy data

NASA Astrophysics Data System (ADS)

Yamanishi, Junsuke; Iwase, Shigeru; Ishida, Nobuyuki; Fujita, Daisuke

2018-01-01

We applied principal component analysis (PCA) to two-dimensional tunneling spectroscopy (2DTS) data obtained on a Si(111)-(7 × 7) surface to explore the effectiveness of multivariate analysis for interpreting 2DTS data. We demonstrated that several components that originated mainly from specific atoms at the Si(111)-(7 × 7) surface can be extracted by PCA. Furthermore, we showed that hidden components in the tunneling spectra can be decomposed (peak separation), which is difficult to achieve with normal 2DTS analysis without the support of theoretical calculations. Our analysis showed that multivariate analysis can be an additional powerful way to analyze 2DTS data and extract hidden information from a large amount of spectroscopic data.

The return period analysis of natural disasters with statistical modeling of bivariate joint probability distribution.

PubMed

Li, Ning; Liu, Xueqin; Xie, Wei; Wu, Jidong; Zhang, Peng

2013-01-01

New features of natural disasters have been observed over the last several years. The factors that influence the disasters' formation mechanisms, regularity of occurrence and main characteristics have been revealed to be more complicated and diverse in nature than previously thought. As the uncertainty involved increases, the variables need to be examined further. This article discusses the importance and the shortage of multivariate analysis of natural disasters and presents a method to estimate the joint probability of the return periods and perform a risk analysis. Severe dust storms from 1990 to 2008 in Inner Mongolia were used as a case study to test this new methodology, as they are normal and recurring climatic phenomena on Earth. Based on the 79 investigated events and according to the dust storm definition with bivariate, the joint probability distribution of severe dust storms was established using the observed data of maximum wind speed and duration. The joint return periods of severe dust storms were calculated, and the relevant risk was analyzed according to the joint probability. The copula function is able to simulate severe dust storm disasters accurately. The joint return periods generated are closer to those observed in reality than the univariate return periods and thus have more value in severe dust storm disaster mitigation, strategy making, program design, and improvement of risk management. This research may prove useful in risk-based decision making. The exploration of multivariate analysis methods can also lay the foundation for further applications in natural disaster risk analysis. © 2012 Society for Risk Analysis.

Personality traits of a group of young adults from different family structures.

PubMed

Du Toit, J; Nel, E M; Steel, H R

1992-07-01

The impact of parental divorce and remarriage and young adults' gender on second-order personality traits, such as extraversion, anxiety, tough poise and independence, was examined. The responses of 227 young adults on the Sixteen Personality Factor Questionnaire (16PF; Cattell, Eber, & Tatsuoka, 1970) were subjected to a parametric multivariate analysis of variance. Results revealed significant differences between the anxiety scores of the young men and women as well as between those of the three different family-structure groups, but divorce and remarriage was not associated with either positive or negative personality development in this sample.

Nuclear magnetic resonance (NMR) study of the effect of cisplatin on the metabolic profile of MG-63 osteosarcoma cells.

PubMed

Duarte, Iola F; Lamego, Ines; Marques, Joana; Marques, M Paula M; Blaise, Benjamin J; Gil, Ana M

2010-11-05

In the present study, (1)H HRMAS NMR spectroscopy was used to assess the changes in the intracellular metabolic profile of MG-63 human osteosarcoma (OS) cells induced by the chemotherapy agent cisplatin (CDDP) at different times of exposure. Multivariate analysis was applied to the cells spectra, enabling consistent variation patterns to be detected and drug-specific metabolic effects to be identified. Statistical recoupling of variables (SRV) analysis and spectral integration enabled the most relevant spectral changes to be evaluated, revealing significant time-dependent alterations in lipids, choline-containing compounds, some amino acids, polyalcohols, and nitrogenated bases. The metabolic relevance of these compounds in the response of MG-63 cells to CDDP treatment is discussed.

Quantitative analysis of virgin coconut oil in cream cosmetics preparations using fourier transform infrared (FTIR) spectroscopy.

PubMed

Rohman, A; Man, Yb Che; Sismindari

2009-10-01

Today, virgin coconut oil (VCO) is becoming valuable oil and is receiving an attractive topic for researchers because of its several biological activities. In cosmetics industry, VCO is excellent material which functions as a skin moisturizer and softener. Therefore, it is important to develop a quantitative analytical method offering a fast and reliable technique. Fourier transform infrared (FTIR) spectroscopy with sample handling technique of attenuated total reflectance (ATR) can be successfully used to analyze VCO quantitatively in cream cosmetic preparations. A multivariate analysis using calibration of partial least square (PLS) model revealed the good relationship between actual value and FTIR-predicted value of VCO with coefficient of determination (R2) of 0.998.

Multivariate Analysis of Schools and Educational Policy.

ERIC Educational Resources Information Center

Kiesling, Herbert J.

This report describes a multivariate analysis technique that approaches the problems of educational production function analysis by (1) using comparable measures of output across large experiments, (2) accounting systematically for differences in socioeconomic background, and (3) treating the school as a complete system in which different…

Long-term outcome of pronation-external rotation ankle fractures treated with syndesmotic screws only.

PubMed

Lambers, Kaj T A; van den Bekerom, Michel P J; Doornberg, Job N; Stufkens, Sjoerd A S; van Dijk, C Niek; Kloen, Peter

2013-09-04

There is sparse information in the literature on the outcome of Maisonneuve-type pronation-external rotation ankle fractures treated with syndesmotic screws. The primary aim of this study was to determine the long-term results of such treatment of these fractures as indicated by standardized patient-based and physician-based outcome measures. The secondary aim was to identify predictors of the outcome with use of bivariate and multivariate statistical analysis. Fifty patients with pronation-external rotation (predominantly Maisonneuve) fractures were treated with open reduction and internal fixation of the syndesmosis utilizing only one or two screws. The results were evaluated at a mean of twenty-one years after the fracture utilizing three standardized outcomes instruments: (1) the Foot and Ankle Ability Measure (FAAM), (2) the American Orthopaedic Foot & Ankle Society (AOFAS) ankle-hindfoot scale, and (3) the Center for Epidemiologic Studies-Depression (CES-D) Scale. Osteoarthritis was graded according to the van Dijk and revised Takakura radiographic scoring systems. Bivariate and multivariate analyses were performed to identify predictors of long-term outcome. Forty-four (92%) of forty-eighty patients had good or excellent AOFAS scores, and forty-four (90%) of forty-nine had good or excellent FAAM scores. Arthrodesis for severe osteoarthritis was performed in two patients. Radiographic evidence of osteoarthritis was observed in twenty-four (49%) of forty-nine patients. Multivariate analysis identified pain as the most important independent predictor of long-term ankle function as indicated by the AOFAS and FAAM scores, explaining 91% and 53% of the variation in scores, respectively. Analysis of pain as the dependent variable in bivariate analyses revealed that depression, ankle range of motion, and a subsequent surgery were significantly correlated with higher pain scores. No firm conclusions could be drawn after multivariate analysis of predictors of pain. Long-term functional outcomes at a mean of twenty-one years after pronation-external rotation ankle fractures treated with one or two syndesmotic screws were good to excellent in the great majority of patients despite substantial radiographic evidence of osteoarthritis in one-half of the patients. The most important predictor of long-term functional outcome was patient-reported pain rather than physician-reported function or posttraumatic osteoarthritis. There was no significant association between radiographic signs of posttraumatic osteoarthritis and perceived pain in the present series.

Multivariate statistical analysis: Principles and applications to coorbital streams of meteorite falls

NASA Technical Reports Server (NTRS)

Wolf, S. F.; Lipschutz, M. E.

1993-01-01

Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.

Determination of Diethyl Phthalate and Polyhexamethylene Guanidine in Surrogate Alcohol from Russia

PubMed Central

Monakhova, Yulia B.; Kuballa, Thomas; Leitz, Jenny; Lachenmeier, Dirk W.

2011-01-01

Analytical methods based on spectroscopic techniques were developed and validated for the determination of diethyl phthalate (DEP) and polyhexamethylene guanidine (PHMG), which may occur in unrecorded alcohol. Analysis for PHMG was based on UV-VIS spectrophotometry after derivatization with Eosin Y and 1H NMR spectroscopy of the DMSO extract. Analysis of DEP was performed with direct UV-VIS and 1H NMR methods. Multivariate curve resolution and spectra computation methods were used to confirm the presence of PHMG and DEP in the investigated beverages. Of 22 analysed alcohol samples, two contained DEP or PHMG. 1H NMR analysis also revealed the presence of signals of hawthorn extract in three medicinal alcohols used as surrogate alcohol. The simple and cheap UV-VIS methods can be used for rapid screening of surrogate alcohol samples for impurities, while 1H NMR is recommended for specific confirmatory analysis if required. PMID:21647285

Determination of diethyl phthalate and polyhexamethylene guanidine in surrogate alcohol from Russia.

PubMed

Monakhova, Yulia B; Kuballa, Thomas; Leitz, Jenny; Lachenmeier, Dirk W

2011-01-01

Analytical methods based on spectroscopic techniques were developed and validated for the determination of diethyl phthalate (DEP) and polyhexamethylene guanidine (PHMG), which may occur in unrecorded alcohol. Analysis for PHMG was based on UV-VIS spectrophotometry after derivatization with Eosin Y and (1)H NMR spectroscopy of the DMSO extract. Analysis of DEP was performed with direct UV-VIS and (1)H NMR methods. Multivariate curve resolution and spectra computation methods were used to confirm the presence of PHMG and DEP in the investigated beverages. Of 22 analysed alcohol samples, two contained DEP or PHMG. (1)H NMR analysis also revealed the presence of signals of hawthorn extract in three medicinal alcohols used as surrogate alcohol. The simple and cheap UV-VIS methods can be used for rapid screening of surrogate alcohol samples for impurities, while (1)H NMR is recommended for specific confirmatory analysis if required.

Pretreatment and integrated analysis of spectral data reveal seaweed similarities based on chemical diversity.

PubMed

Wei, Feifei; Ito, Kengo; Sakata, Kenji; Date, Yasuhiro; Kikuchi, Jun

2015-03-03

Extracting useful information from high dimensionality and large data sets is a major challenge for data-driven approaches. The present study was aimed at developing novel integrated analytical strategies for comprehensively characterizing seaweed similarities based on chemical diversity. The chemical compositions of 107 seaweed and 2 seagrass samples were analyzed using multiple techniques, including Fourier transform infrared (FT-IR) and solid- and solution-state nuclear magnetic resonance (NMR) spectroscopy, thermogravimetry-differential thermal analysis (TG-DTA), inductively coupled plasma-optical emission spectrometry (ICP-OES), CHNS/O total elemental analysis, and isotope ratio mass spectrometry (IR-MS). The spectral data were preprocessed using non-negative matrix factorization (NMF) and NMF combined with multivariate curve resolution-alternating least-squares (MCR-ALS) methods in order to separate individual component information from the overlapping and/or broad spectral peaks. Integrated analysis of the preprocessed chemical data demonstrated distinct discrimination of differential seaweed species. Further network analysis revealed a close correlation between the heavy metal elements and characteristic components of brown algae, such as cellulose, alginic acid, and sulfated mucopolysaccharides, providing a componential basis for its metal-sorbing potential. These results suggest that this integrated analytical strategy is useful for extracting and identifying the chemical characteristics of diverse seaweeds based on large chemical data sets, particularly complicated overlapping spectral data.

Outcome and prognostic factors in single brain metastases from small-cell lung cancer.

PubMed

Bernhardt, Denise; Adeberg, Sebastian; Bozorgmehr, Farastuk; Opfermann, Nils; Hörner-Rieber, Juliane; König, Laila; Kappes, Jutta; Thomas, Michael; Unterberg, Andreas; Herth, Felix; Heußel, Claus Peter; Warth, Arne; Debus, Jürgen; Steins, Martin; Rieken, Stefan

2018-02-01

Whole brain radiation therapy (WBRT) is historically the standard of care for patients with brain metastases (BM) from small-cell lung cancer (SCLC), although locally ablative treatments are the standard of care for patients with 1-4 BM from other solid tumors. The objective of this analysis was to find prognostic factors influencing overall survival (OS) and intracranial progression-free survival (iPFS) in SCLC patients with single BM (SBM) treated with WBRT. A total of 52 patients were identified in the authors' cancer center database with histologically confirmed SCLC and contrast-enhanced magnet resonance imaging (MRI) or computed tomography (CT), which confirmed SBM between 2006 and 2015 and were therefore treated with WBRT. A Kaplan-Meier survival analysis was performed for OS analyses. The log-rank (Mantel-Cox) test was used to compare survival curves. Univariate Cox proportional-hazards ratios (HRs) were used to assess the influence of cofactors on OS and iPFS. The median OS after WBRT was 5 months and the median iPFS after WBRT 16 months. Patients that received surgery prior to WBRT had a significantly longer median OS of 19 months compared to 5 months in the group receiving only WBRT (p = 0.03; HR 2.24; 95% confidence interval [CI] 1.06-4.73). Patients with synchronous disease had a significantly longer OS compared to patients with metachronous BM (6 months vs. 3 months, p = 0.005; HR 0.27; 95% CI 0.11-0.68). Univariate analysis for OS revealed a statistically significant effect for metachronous disease (HR 2.25; 95% CI 1.14-4.46; p = 0.019), initial response to first-line chemotherapy (HR 0.58; 95% CI 0.35-0.97; p = 0.04), and surgical resection (HR 0.36; 95% CI 0.15-0.88; p = 0.026). OS was significantly affected by metachronous disease in multivariate analysis (HR 2.20; 95% CI 1.09-4.45; p = 0.028). Univariate analysis revealed that surgery followed by WBRT can improve OS in patients with SBM in SCLC. Furthermore, synchronous disease and response to initial chemotherapy appeared to be major prognostic factors. Multivariate analysis revealed metachronous disease as a significantly negative prognostic factor on OS. The value of WBRT, stereotactic radiosurgery (SRS), or surgery alone or in combination for patients with a limited number of BM in SCLC should be evaluated in further prospective clinical trials.

Conditional survival estimates improve over time for patients with advanced melanoma: results from a population-based analysis.

PubMed

Xing, Yan; Chang, George J; Hu, Chung-Yuan; Askew, Robert L; Ross, Merrick I; Gershenwald, Jeffrey E; Lee, Jeffrey E; Mansfield, Paul F; Lucci, Anthony; Cormier, Janice N

2010-05-01

Conditional survival (CS) has emerged as a clinically relevant measure of prognosis for cancer survivors. The objective of this analysis was to provide melanoma-specific CS estimates to help clinicians promote more informed patient decision making. Patients with melanoma and at least 5 years of follow-up were identified from the Surveillance Epidemiology and End Results registry (1988-2000). By using the methods of Kaplan and Meier, stage-specific, 5-year CS estimates were independently calculated for survivors for each year after diagnosis. Stage-specific multivariate Cox regression models including baseline survivor functions were used to calculate adjusted melanoma-specific CS for different subgroups of patients further stratified by age, gender, race, marital status, anatomic tumor location, and tumor histology. Five-year CS estimates for patients with stage I disease remained constant at 97% annually, while for patients with stages II, III, and IV disease, 5-year CS estimates from time 0 (diagnosis) to 5 years improved from 72% to 86%, 51% to 87%, and 19% to 84%, respectively. Multivariate CS analysis revealed that differences in stages II through IV CS based on age, gender, and race decreased over time. Five-year melanoma-specific CS estimates improve dramatically over time for survivors with advanced stages of disease. These prognostic data are critical to patients for both treatment and nontreatment related life decisions. (c) 2010 American Cancer Society.

Influence of caregiver personality on the burden of family caregivers of terminally ill cancer patients.

PubMed

Kim, Ha-Hyun; Kim, Seon-Young; Kim, Jae-Min; Kim, Sung-Wan; Shin, Il-Seon; Shim, Hyun-Jeong; Hwang, Jun-Eul; Chung, Ik-Joo; Yoon, Jin-Sang

2016-02-01

To determine the influence of caregiver personality and other factors on the burden of family caregivers of terminally ill cancer patients. We investigated a wide range of factors related to the patient-family caregiver dyad in a palliative care setting using a cross-sectional design. Caregiver burden was assessed using the seven-item short version of the Zarit Burden Interview (ZBI-7). Caregiver personality was assessed using the 10-item short version of the Big Five Inventory (BFI-10), which measures the following five personality dimensions: extroversion, agreeableness, conscientiousness, neuroticism, and openness. Patient- and caregiver-related sociodemographic and psychological factors were included in the analysis because of their potential association with caregiver burden. Clinical patient data were obtained from medical charts or by using other measures. Multivariate linear regression analysis was performed to identify the independent factors associated with caregiver burden. We analyzed 227 patient-family caregiver dyads. The multivariate analysis revealed that caregiver extroversion was protective against caregiver burden, whereas depressive symptoms in caregivers were related to increased burden. Neuroticism was positively correlated with caregiver burden, but this relationship was nonsignificant following adjustment for depressive symptoms. Patient-related factors were not significantly associated with caregiver burden. Evaluating caregiver personality traits could facilitate identification of individuals at greater risk of high burden. Furthermore, depression screening and treatment programs for caregivers in palliative care settings are required to decrease caregiver burden.

Robust tumor morphometry in multispectral fluorescence microscopy

NASA Astrophysics Data System (ADS)

Tabesh, Ali; Vengrenyuk, Yevgen; Teverovskiy, Mikhail; Khan, Faisal M.; Sapir, Marina; Powell, Douglas; Mesa-Tejada, Ricardo; Donovan, Michael J.; Fernandez, Gerardo

2009-02-01

Morphological and architectural characteristics of primary tissue compartments, such as epithelial nuclei (EN) and cytoplasm, provide important cues for cancer diagnosis, prognosis, and therapeutic response prediction. We propose two feature sets for the robust quantification of these characteristics in multiplex immunofluorescence (IF) microscopy images of prostate biopsy specimens. To enable feature extraction, EN and cytoplasm regions were first segmented from the IF images. Then, feature sets consisting of the characteristics of the minimum spanning tree (MST) connecting the EN and the fractal dimension (FD) of gland boundaries were obtained from the segmented compartments. We demonstrated the utility of the proposed features in prostate cancer recurrence prediction on a multi-institution cohort of 1027 patients. Univariate analysis revealed that both FD and one of the MST features were highly effective for predicting cancer recurrence (p <= 0.0001). In multivariate analysis, an MST feature was selected for a model incorporating clinical and image features. The model achieved a concordance index (CI) of 0.73 on the validation set, which was significantly higher than the CI of 0.69 for the standard multivariate model based solely on clinical features currently used in clinical practice (p < 0.0001). The contributions of this work are twofold. First, it is the first demonstration of the utility of the proposed features in morphometric analysis of IF images. Second, this is the largest scale study of the efficacy and robustness of the proposed features in prostate cancer prognosis.

Elevated red cell distribution width contributes to a poor prognosis in patients with esophageal carcinoma.

PubMed

Wan, Guo-Xing; Chen, Ping; Cai, Xiao-Jun; Li, Lin-Jun; Yu, Xiong-Jie; Pan, Dong-Feng; Wang, Xian-He; Wang, Xuan-Bin; Cao, Feng-Jun

2016-01-15

The red cell distribution width (RDW) has also been reported to reliably reflect the inflammation and nutrition status and predict the prognosis across several types of cancer, however, the prognostic value of RDW in esophageal carcinoma has seldom been studied. A retrospective study was performed to assess the prognostic value of RDW in patients with esophageal carcinoma by the Kaplan-Meier analysis and multivariate Cox regression proportional hazard model. All enrolled patients were divided into high RDW group (≧15%) and low RDW group (<15%) according to the detected RDW values. Clinical and laboratory data from a total of 179 patients with esophageal carcinoma were retrieved. With a median follow-up of 21months, the high RDW group exhibited a shorter disease-free survival (DFS) (p<0.001) and an unfavorable overall survival (OS) (p<0.001) in the univariate analysis. The multivariate analysis revealed that elevated RDW at diagnosis was an independent prognostic factor for shorter PFS (p=0.043, HR=1.907, 95% CI=1.020-3.565) and poor OS (p=0.042, HR=1.895, 95% CI=1.023-3.508) after adjustment with other cancer-related prognostic factors. The present study suggests that elevated preoperative RDW(≧15%) at the diagnosis may independently predict poorer disease-free and overall survival among patients with esophageal carcinoma. Copyright © 2015 Elsevier B.V. All rights reserved.

Factors predictive of the onset and duration of action of local anesthesia in mandibular third-molar surgery: a prospective study.

PubMed

Al-Shayyab, Mohammad H; Baqain, Zaid H

2018-04-01

The aim of this study was to assess the influence of patients' and surgical variables on the onset and duration of action of local anesthesia (LA) in mandibular third-molar (M3) surgery. Patients scheduled for mandibular M3 surgery were considered for inclusion in this prospective cohort study. Patients' and surgical variables were recorded. Two per cent (2%) lidocaine with 1:100,000 epinephrine was used to block the nerves for extraction of mandibular M3. Then, the onset of action and duration of LA were monitored. Univariate analysis and multivariate regression analysis were used to analyze the data. The final cohort included 88 subjects (32 men and 56 women; mean age ± SD = 29.3 ± 12.3 yr). With univariate analysis, age, gender, body mass index (BMI), smoking quantity and duration, operation time, and 'volume of local anesthetic needed' significantly influenced the onset of action and duration of LA. Multivariate regression revealed that age and smoking quantity were the only statistically significant predictors of the onset of action of LA, whereas age, smoking quantity, and 'volume of local anesthetic needed' were the only statistically significant predictors of duration of LA. Further studies are recommended to uncover other predictors of the onset of action and duration of LA. © 2018 Eur J Oral Sci.

Can the new RCP R0/R1 classification predict the clinical outcome in ductal adenocarcinoma of the pancreatic head?

PubMed

Janot, M S; Kersting, S; Belyaev, O; Matuschek, A; Chromik, A M; Suelberg, D; Uhl, W; Tannapfel, A; Bergmann, U

2012-08-01

According to the International Union Against Cancer (UICC), R1 is defined as the microscopic presence of tumor cells at the surface of the resection margin (RM). In contrast, the Royal College of Pathologists (RCP) suggested to declare R1 already when tumor cells are found within 1 mm of the RM. The aim of this study was to determine the significance of the RM concerning the prognosis of pancreatic ductal adenocarcinoma (PDAC). From 2007 to 2009, 62 patients underwent a curative operation for PDAC of the pancreatic head. The relevance of R status on cumulative overall survival (OS) was assessed on univariate and multivariate analysis for both the classic R classification (UICC) and the suggestion of the RCP. Following the UICC criteria, a positive RM was detected in 8 %. Along with grading and lymph node ratio, R status revealed a significant impact on OS on univariate and multivariate analysis. Applying the suggestion of the RCP, R1 rate rose to 26 % resulting in no significant impact on OS in univariate analysis. Our study has shown that the RCP suggestion for R status has no impact on the prognosis of PDAC. In contrast, our data confirmed the UICC R classification of RM as well as N category, grading, and lymph node ratio as significant prognostic factors.

Cross-sectional survey of workload and burnout among Japanese physicians working in stroke care: the nationwide survey of acute stroke care capacity for proper designation of comprehensive stroke center in Japan (J-ASPECT) study.

PubMed

Nishimura, Kunihiro; Nakamura, Fumiaki; Takegami, Misa; Fukuhara, Schunichi; Nakagawara, Jyoji; Ogasawara, Kuniaki; Ono, Junichi; Shiokawa, Yoshiaki; Miyachi, Shigeru; Nagata, Izumi; Toyoda, Kazunori; Matsuda, Shinya; Kataoka, Hiroharu; Miyamoto, Yoshihiro; Kitaoka, Kazuyo; Kada, Akiko; Iihara, Koji

2014-05-01

Burnout is common among physicians and affects the quality of care. We aimed to determine the prevalence of burnout among Japanese physicians working in stroke care and evaluate personal and professional characteristics associated with burnout. A cross-sectional design was used to develop and distribute a survey to 11 211 physicians. Physician burnout was assessed using the Maslach Burnout Inventory General Survey. The predictors of burnout and the relationships among them were identified by multivariable logistic regression analysis. A total of 2724 (25.3%) physicians returned the surveys. After excluding those who were not working in stroke care or did not complete the survey appropriately, 2564 surveys were analyzed. Analysis of the participants' scores revealed that 41.1% were burned out. Multivariable analysis indicated that number of hours worked per week is positively associated with burnout. Hours slept per night, day-offs per week, years of experience, as well as income, are inversely associated with burnout. Short Form 36 mental health subscale was also inversely associated with burnout. The primary risk factors for burnout are heavy workload, short sleep duration, relatively little experience, and low mental quality of life. Prospective research is required to confirm these findings and develop programs for preventing burnout. © 2014 American Heart Association, Inc.

The role of adjuvant treatment in early-stage oral cavity squamous cell carcinoma: An international collaborative study.

PubMed

Fridman, Eran; Na'ara, Shorook; Agarwal, Jaiprakash; Amit, Moran; Bachar, Gideon; Villaret, Andrea Bolzoni; Brandao, Jose; Cernea, Claudio R; Chaturvedi, Pankaj; Clark, Jonathan; Ebrahimi, Ardalan; Fliss, Dan M; Jonnalagadda, Sashikanth; Kohler, Hugo F; Kowalski, Luiz P; Kreppel, Matthias; Liao, Chun-Ta; Patel, Snehal G; Patel, Raj P; Robbins, K Thomas; Shah, Jatin P; Shpitzer, Thomas; Yen, Tzu-Chen; Zöller, Joachim E; Gil, Ziv

2018-05-14

Up to half of patients with oral cavity squamous cell carcinoma (OCSCC) have stage I to II disease. When adequate resection is attained, no further treatment is needed; however, re-resection or radiotherapy may be indicated for patients with positive or close margins. This multicenter study evaluated the outcomes and role of adjuvant treatment in patients with stage I to II OCSCC. Overall survival (OS), disease-specific survival, local-free survival, and disease-free survival rates were calculated with Kaplan-Meier analysis. Of 1257 patients with T1-2N0M0 disease, 33 (2.6%) had positive margins, and 205 (16.3%) had close margins. The 5-year OS rate was 80% for patients with clear margins, 52% for patients with close margins, and 63% for patients with positive margins (P < .0001). In a multivariate analysis, age, depth of invasion, and margins were independent predictors of outcome. Close margins were associated with a >2-fold increase in the risk of recurrence (P < .0001). The multivariate analysis revealed that adjuvant treatment significantly improved the outcomes of patients with close/positive margins (P = .002 to .03). Patients with stage I to II OCSCC and positive/close margins have poor long-term outcomes. For this population, adjuvant treatment may be associated with improved survival. Cancer 2018. © 2018 American Cancer Society. © 2018 American Cancer Society.

Craniofacial morphometric analysis of mandibular prognathism.

PubMed

Chang, H P; Liu, P H; Yang, Y H; Lin, H C; Chang, C H

2006-03-01

The purpose of this study was to provide more information about the morphological characteristics of the craniofacial complex in mandibular prognathism. Forty young adult males having mandibular prognathism were compared with 40 having normal occlusion. This was conducted to carry out geometric morphometric assessments to localize alterations, using Procrustes analysis and thin-plate spline analysis, in addition to conventional cephalometric techniques. Procrustes analysis indicated that the mean craniofacial, midfacial and mandibular morphology was significantly different in prognathic subjects compared with normal controls. This finding was corroborated by the multivariate Hotelling T(2)-test of cephalometric variables. Mandibular prognathism demonstrated a shorter and slightly retropositioned maxilla, a greater total length and anterior positioning of the mandible. Thin-plate spline analysis revealed a developmental diminution of the palatomaxillary region anteroposteriorly and a developmental elongation of the mandible anteroposteriorly, leading to the appearance of a prognathic mandibular profile. In conclusion, thin-plate spline analysis seems to provide a valuable supplement for conventional cephalometric analysis because the complex patterns of craniofacial shape change are visualized suggestive by means of grid deformations.

Multivariate analysis in the pharmaceutical industry: enabling process understanding and improvement in the PAT and QbD era.

PubMed

Ferreira, Ana P; Tobyn, Mike

2015-01-01

In the pharmaceutical industry, chemometrics is rapidly establishing itself as a tool that can be used at every step of product development and beyond: from early development to commercialization. This set of multivariate analysis methods allows the extraction of information contained in large, complex data sets thus contributing to increase product and process understanding which is at the core of the Food and Drug Administration's Process Analytical Tools (PAT) Guidance for Industry and the International Conference on Harmonisation's Pharmaceutical Development guideline (Q8). This review is aimed at providing pharmaceutical industry professionals an introduction to multivariate analysis and how it is being adopted and implemented by companies in the transition from "quality-by-testing" to "quality-by-design". It starts with an introduction to multivariate analysis and the two methods most commonly used: principal component analysis and partial least squares regression, their advantages, common pitfalls and requirements for their effective use. That is followed with an overview of the diverse areas of application of multivariate analysis in the pharmaceutical industry: from the development of real-time analytical methods to definition of the design space and control strategy, from formulation optimization during development to the application of quality-by-design principles to improve manufacture of existing commercial products.

Clinical analysis of urinary tract infection in patients undergoing transurethral resection of the prostate.

PubMed

Li, Y-H; Li, G-Q; Guo, S-M; Che, Y-N; Wang, X; Cheng, F-T

2017-10-01

To analyze the related influencing factors of urinary tract infection in patients undergoing transurethral resection of the prostate (TURP). A total of 343 patients with benign prostatic hyperplasia admitted to this hospital from January 2013 to December 2016, were selected and treated by TURP. Patients were divided into infection group and non-infection group according to the occurrence of urinary tract infection after operation. The possible influencing factors were collected to perform univariate and multivariate logistic regression analysis. There were 53 cases with urinary tract infection after operation among 343 patients with benign prostatic hyperplasia, accounting for 15.5%. The univariate analysis displayed that the occurrence of urinary tract infection in patients undergoing TURP was closely associated with patient's age ≥ 65 years old, complicated diabetes, catheterization for urinary retention before operation, no use of antibiotics before operation and postoperative indwelling catheter duration ≥ 5 d (p < 0.05). Multivariate logistic regression analysis revealed that age ≥ 65 years old, complicated diabetes, catheterization before operation, indwelling catheter duration ≥ 5 d and no use of antibiotics before operation were risk factors of urinary tract infection in patients receiving TURP (p < 0.05). The patient's age ≥ 65 years old, catheterization before operation, complicated diabetes and long-term indwelling catheter after operation, can increase the occurrence of urinary tract infection after TURP, while preoperative prophylactic utilization of anti-infective drugs can reduce the occurrence of postoperative urinary tract infection.

Metabolomic Analysis of Overactive Bladder in Male Patients: Identification of Potential Metabolite Biomarkers.

PubMed

Shimura, Hiroshi; Mitsui, Takahiko; Kira, Satoru; Ihara, Tatsuya; Sawada, Norifumi; Nakagomi, Hiroshi; Miyamoto, Tatsuya; Tsuchiya, Sachiko; Kanda, Mie; Takeda, Masayuki

2018-05-09

To identify metabolites that are associated with an overactive bladder (OAB) using metabolomics. A total of 58 male patients without apparent neurologic disease completed 24-hour bladder diaries of their micturition behavior and International Prostate Symptom Score (IPSS) for the assessment of micturition behavior and lower urinary tract symptoms. Urgency was defined as an IPSS urgency score of ≥2 (OAB group), and patients with IPSS urgency scores of ≤1 belonged to the control group. A comprehensive study of plasma metabolites was also conducted using capillary electrophoresis time-of-flight mass spectrometry. Metabolite levels were compared between the control and OAB groups using the Mann-Whitney U test. Potential metabolite biomarkers were selected using multivariate logistic regression analysis. Of the 58 subjects, the control and OAB groups consisted of 32 and 26 male patients, respectively. Nocturnal urinary volume, 24-hour micturition frequency, nocturnal micturition frequency, and the nocturia index were significantly higher in the OAB group. Metabolomic analysis revealed 60 metabolites in the subjects' plasma. The levels of 11 metabolites differed between the control and OAB groups. Multivariate analysis showed that an increased glutamate level and reduced arginine, glutamine, and inosine monophosphate levels are significantly associated with OAB in male patients. Reduced levels of asparagine and hydroxyproline could also be associated with OAB. Urgency is associated with abnormal metabolism. Analyses of amino acid profiles might aid the search for new treatment targets for OAB. Copyright © 2018 Elsevier Inc. All rights reserved.

Multivariate statistical analysis of radiological data of building materials used in Tiruvannamalai, Tamilnadu, India.

PubMed

Ravisankar, R; Vanasundari, K; Suganya, M; Raghu, Y; Rajalakshmi, A; Chandrasekaran, A; Sivakumar, S; Chandramohan, J; Vijayagopal, P; Venkatraman, B

2014-02-01

Using γ spectrometry, the concentration of the naturally occurring radionuclides (226)Ra, (232)Th and (40)K has been measured in soil, sand, cement, clay and bricks, which are used as building materials in Tiruvannamalai, Tamilnadu, India. The radium equivalent activity (Raeq), the criterion formula (CF), indoor gamma absorbed dose rate (DR), annual effective dose (HR), activity utilization index (AUI), alpha index (Iα), gamma index (Iγ), external radiation hazard index (Hex), internal radiation hazard index (Hin), representative level index (RLI), excess lifetime cancer risk (ELCR) and annual gonadal dose equivalent (AGDE) associated with the natural radionuclides are calculated to assess the radiation hazard of the natural radioactivity in the building materials. From the analysis, it is found that these materials used for the construction of dwellings are safe for the inhabitants. The radiological data were processed using multivariate statistical methods to determine the similarities and correlation among the various samples. The frequency distributions for all radionuclides were analyzed. The data set consisted of 15 measured variables. The Pearson correlation coefficient reveals that the (226)Ra distribution in building materials is controlled by the variation of the (40)K concentration. Principal component analysis (PCA) yields a two-component representation of the acquired data from the building materials in Tiruvannamalai, wherein 94.9% of the total variance is explained. The resulting dendrogram of hierarchical cluster analysis (HCA) classified the 30 building materials into four major groups using 15 variables. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases.

PubMed

Hirata, Makoto; Kamatani, Yoichiro; Nagai, Akiko; Kiyohara, Yutaka; Ninomiya, Toshiharu; Tamakoshi, Akiko; Yamagata, Zentaro; Kubo, Michiaki; Muto, Kaori; Mushiroda, Taisei; Murakami, Yoshinori; Yuji, Koichiro; Furukawa, Yoichi; Zembutsu, Hitoshi; Tanaka, Toshihiro; Ohnishi, Yozo; Nakamura, Yusuke; Matsuda, Koichi

2017-03-01

To implement personalized medicine, we established a large-scale patient cohort, BioBank Japan, in 2003. BioBank Japan contains DNA, serum, and clinical information derived from approximately 200,000 patients with 47 diseases. Serum and clinical information were collected annually until 2012. We analyzed clinical information of participants at enrollment, including age, sex, body mass index, hypertension, and smoking and drinking status, across 47 diseases, and compared the results with the Japanese database on Patient Survey and National Health and Nutrition Survey. We conducted multivariate logistic regression analysis, adjusting for sex and age, to assess the association between family history and disease development. Distribution of age at enrollment reflected the typical age of disease onset. Analysis of the clinical information revealed strong associations between smoking and chronic obstructive pulmonary disease, drinking and esophageal cancer, high body mass index and metabolic disease, and hypertension and cardiovascular disease. Logistic regression analysis showed that individuals with a family history of keloid exhibited a higher odds ratio than those without a family history, highlighting the strong impact of host genetic factor(s) on disease onset. Cross-sectional analysis of the clinical information of participants at enrollment revealed characteristics of the present cohort. Analysis of family history revealed the impact of host genetic factors on each disease. BioBank Japan, by publicly distributing DNA, serum, and clinical information, could be a fundamental infrastructure for the implementation of personalized medicine. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

A Look Inside HIV Resistance through Retroviral Protease Interaction Maps

PubMed Central

Kontijevskis, Aleksejs; Prusis, Peteris; Petrovska, Ramona; Yahorava, Sviatlana; Mutulis, Felikss; Mutule, Ilze; Komorowski, Jan; Wikberg, Jarl E. S

2007-01-01

Retroviruses affect a large number of species, from fish and birds to mammals and humans, with global socioeconomic negative impacts. Here the authors report and experimentally validate a novel approach for the analysis of the molecular networks that are involved in the recognition of substrates by retroviral proteases. Using multivariate analysis of the sequence-based physiochemical descriptions of 61 retroviral proteases comprising wild-type proteases, natural mutants, and drug-resistant forms of proteases from nine different viral species in relation to their ability to cleave 299 substrates, the authors mapped the physicochemical properties and cross-dependencies of the amino acids of the proteases and their substrates, which revealed a complex molecular interaction network of substrate recognition and cleavage. The approach allowed a detailed analysis of the molecular–chemical mechanisms involved in substrate cleavage by retroviral proteases. PMID:17352531

Epidemiological analysis of methicillin-resistant Staphylococcus aureus carriage among veterinary staff of companion animals in Japan.

PubMed

Ishihara, Kanako; Saito, Mieko; Shimokubo, Natsumi; Muramatsu, Yasukazu; Maetani, Shigeki; Tamura, Yutaka

2014-12-01

Veterinary staff carrying methicillin-resistant Staphylococcus aureus(MRSA) can be a source of MRSA infection in animals. To identify risk factors of MRSA carriage among veterinary staff, MRSA carriage and epidemiological information (sex, career, contact with MRSA-identified animal patients and others) were analyzed from 96 veterinarians and 70 veterinary technicians working at 71 private veterinary clinics in Japan. Univariate analysis determined sex (percentage of MRSA carriage, male (29.2%) vs. female (10%); P=0.002) and career (veterinarians (22.9%) vs. veterinary technicians (10%); P=0.030) as risk factors. Multivariable analysis revealed that sex was independently associated with MRSA carriage (adjusted odds ratio, 3.717; 95% confidence interval, 1.555-8.889; P=0.003). Therefore, male veterinary staff had a higher risk of MRSA carriage than female staff.

Calorimetric analysis points out the physical-chemistry of organic olive oils and reveals the geographical origin

NASA Astrophysics Data System (ADS)

Mallamace, Domenico; Vasi, Sebastiano; Corsaro, Carmelo; Naccari, Clara; Clodoveo, Maria Lisa; Dugo, Giacomo; Cicero, Nicola

2017-11-01

The thermal properties of many organic extra Virgin Olive Oils (eVOOs) coming from different countries of the world were investigated by Differential Scanning Calorimetry (DSC). This technique, through a series of heating and cooling cycles, provides a specific curve, i.e., a thermogram, which represents the fingerprint of each eVOO sample. In fact, variations due to the different cultivars, geographical origin or chemical composition can be highlighted because they produce changes in the corresponding thermogram. In particular, in this work, we show the results of an unsupervised multivariate statistical analysis applied to the DSC thermograms of many organic eVOOs. This analysis allows us to discriminate the geographical origin of the different studied samples in terms of the peculiar features shown by the melting profiles of the triacylglycerol moieties.

A multivariate test of disease risk reveals conditions leading to disease amplification.

PubMed

Halliday, Fletcher W; Heckman, Robert W; Wilfahrt, Peter A; Mitchell, Charles E

2017-10-25

Theory predicts that increasing biodiversity will dilute the risk of infectious diseases under certain conditions and will amplify disease risk under others. Yet, few empirical studies demonstrate amplification. This contrast may occur because few studies have considered the multivariate nature of disease risk, which includes richness and abundance of parasites with different transmission modes. By combining a multivariate statistical model developed for biodiversity-ecosystem-multifunctionality with an extensive field manipulation of host (plant) richness, composition and resource supply to hosts, we reveal that (i) host richness alone could not explain most changes in disease risk, and (ii) shifting host composition allowed disease amplification, depending on parasite transmission mode. Specifically, as predicted from theory, the effect of host diversity on parasite abundance differed for microbes (more density-dependent transmission) and insects (more frequency-dependent transmission). Host diversity did not influence microbial parasite abundance, but nearly doubled insect parasite abundance, and this amplification effect was attributable to variation in host composition. Parasite richness was reduced by resource addition, but only in species-rich host communities. Overall, this study demonstrates that multiple drivers, related to both host community and parasite characteristics, can influence disease risk. Furthermore, it provides a framework for evaluating multivariate disease risk in other systems. © 2017 The Author(s).

Quantitative methods for analysing cumulative effects on fish migration success: a review.

PubMed

Johnson, J E; Patterson, D A; Martins, E G; Cooke, S J; Hinch, S G

2012-07-01

It is often recognized, but seldom addressed, that a quantitative assessment of the cumulative effects, both additive and non-additive, of multiple stressors on fish survival would provide a more realistic representation of the factors that influence fish migration. This review presents a compilation of analytical methods applied to a well-studied fish migration, a more general review of quantitative multivariable methods, and a synthesis on how to apply new analytical techniques in fish migration studies. A compilation of adult migration papers from Fraser River sockeye salmon Oncorhynchus nerka revealed a limited number of multivariable methods being applied and the sub-optimal reliance on univariable methods for multivariable problems. The literature review of fisheries science, general biology and medicine identified a large number of alternative methods for dealing with cumulative effects, with a limited number of techniques being used in fish migration studies. An evaluation of the different methods revealed that certain classes of multivariable analyses will probably prove useful in future assessments of cumulative effects on fish migration. This overview and evaluation of quantitative methods gathered from the disparate fields should serve as a primer for anyone seeking to quantify cumulative effects on fish migration survival. © 2012 The Authors. Journal of Fish Biology © 2012 The Fisheries Society of the British Isles.

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.

PubMed

Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao

2016-11-30

Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.

Smoking is a risk factor for pulmonary metastasis in colorectal cancer.

PubMed

Yahagi, M; Tsuruta, M; Hasegawa, H; Okabayashi, K; Toyoda, N; Iwama, N; Morita, S; Kitagawa, Y

2017-09-01

The hepatic microenvironment, which may include chronic inflammation and fibrosis, is considered to contribute to the pathogenesis of liver metastases of colorectal cancer. A similar mechanism is anticipated for pulmonary metastases, although no reports are available. Smoking causes pulmonary inflammation and fibrosis. Thus, we hypothesized that smokers would be especially affected by pulmonary metastases of colorectal cancer. In this study, we attempted to clarify the impact of smoking on pulmonary metastasis of colorectal cancer. Between September 2005 and December 2010 we reviewed 567 patients with pathological Stage I, II or III colorectal cancer, whose clinicopathological background included a preoperative smoking history, pack-year history from medical records. Univariate and multivariate analyses using the Cox proportional hazard model were performed to determine the independent prognostic factors for pulmonary metastasis-free survival. Pulmonary metastases occurred in 39 (6.9%) patients. The smoking histories revealed 355 never smokers, 119 former smokers and 93 current smokers among the subjects. Multivariate analysis revealed that being a current smoker (hazard ratio = 2.72, 95% CI 1.18-6.25; P = 0.02) was an independent risk factor for pulmonary metastases. Smoking may be a risk factor for pulmonary metastasis of colorectal cancer. Cessation of smoking should be recommended to prevent pulmonary metastasis, although further basic and clinical studies are required. Colorectal Disease © 2017 The Association of Coloproctology of Great Britain and Ireland.

Multivariate pattern classification reveals autonomic and experiential representations of discrete emotions.

PubMed

Kragel, Philip A; Labar, Kevin S

2013-08-01

Defining the structural organization of emotions is a central unresolved question in affective science. In particular, the extent to which autonomic nervous system activity signifies distinct affective states remains controversial. Most prior research on this topic has used univariate statistical approaches in attempts to classify emotions from psychophysiological data. In the present study, electrodermal, cardiac, respiratory, and gastric activity, as well as self-report measures were taken from healthy subjects during the experience of fear, anger, sadness, surprise, contentment, and amusement in response to film and music clips. Information pertaining to affective states present in these response patterns was analyzed using multivariate pattern classification techniques. Overall accuracy for classifying distinct affective states was 58.0% for autonomic measures and 88.2% for self-report measures, both of which were significantly above chance. Further, examining the error distribution of classifiers revealed that the dimensions of valence and arousal selectively contributed to decoding emotional states from self-report, whereas a categorical configuration of affective space was evident in both self-report and autonomic measures. Taken together, these findings extend recent multivariate approaches to study emotion and indicate that pattern classification tools may improve upon univariate approaches to reveal the underlying structure of emotional experience and physiological expression. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Multivariate Pattern Classification Reveals Autonomic and Experiential Representations of Discrete Emotions

PubMed Central

Kragel, Philip A.; LaBar, Kevin S.

2013-01-01

Defining the structural organization of emotions is a central unresolved question in affective science. In particular, the extent to which autonomic nervous system activity signifies distinct affective states remains controversial. Most prior research on this topic has used univariate statistical approaches in attempts to classify emotions from psychophysiological data. In the present study, electrodermal, cardiac, respiratory, and gastric activity, as well as self-report measures were taken from healthy subjects during the experience of fear, anger, sadness, surprise, contentment, and amusement in response to film and music clips. Information pertaining to affective states present in these response patterns was analyzed using multivariate pattern classification techniques. Overall accuracy for classifying distinct affective states was 58.0% for autonomic measures and 88.2% for self-report measures, both of which were significantly above chance. Further, examining the error distribution of classifiers revealed that the dimensions of valence and arousal selectively contributed to decoding emotional states from self-report, whereas a categorical configuration of affective space was evident in both self-report and autonomic measures. Taken together, these findings extend recent multivariate approaches to study emotion and indicate that pattern classification tools may improve upon univariate approaches to reveal the underlying structure of emotional experience and physiological expression. PMID:23527508

Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

NASA Astrophysics Data System (ADS)

Glascock, M. D.; Neff, H.; Vaughn, K. J.

2004-06-01

The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Reconstructing multi-mode networks from multivariate time series

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Yang, Yu-Xuan; Dang, Wei-Dong; Cai, Qing; Wang, Zhen; Marwan, Norbert; Boccaletti, Stefano; Kurths, Jürgen

2017-09-01

Unveiling the dynamics hidden in multivariate time series is a task of the utmost importance in a broad variety of areas in physics. We here propose a method that leads to the construction of a novel functional network, a multi-mode weighted graph combined with an empirical mode decomposition, and to the realization of multi-information fusion of multivariate time series. The method is illustrated in a couple of successful applications (a multi-phase flow and an epileptic electro-encephalogram), which demonstrate its powerfulness in revealing the dynamical behaviors underlying the transitions of different flow patterns, and enabling to differentiate brain states of seizure and non-seizure.

Localization of genes involved in the metabolic syndrome using multivariate linkage analysis.

PubMed

Olswold, Curtis; de Andrade, Mariza

2003-12-31

There are no well accepted criteria for the diagnosis of the metabolic syndrome. However, the metabolic syndrome is identified clinically by the presence of three or more of these five variables: larger waist circumference, higher triglyceride levels, lower HDL-cholesterol concentrations, hypertension, and impaired fasting glucose. We use sets of two or three variables, which are available in the Framingham Heart Study data set, to localize genes responsible for this syndrome using multivariate quantitative linkage analysis. This analysis demonstrates the applicability of using multivariate linkage analysis and how its use increases the power to detect linkage when genes are involved in the same disease mechanism.

Discrimination of cherry wines based on their sensory properties and aromatic fingerprinting using HS-SPME-GC-MS and multivariate analysis.

PubMed

Xiao, Zuobing; Liu, Shengjiang; Gu, Yongbo; Xu, Na; Shang, Yi; Zhu, Jiancai

2014-03-01

Volatiles of cherry wines were extracted by headspace solid phase microextraction (HS-SPME) and analyzed by gas chromatography mass spectrometry (GC-MS), multivariate statistical techniques (such as principal component analysis (PCA) and cluster analysis (CA) and correlation analysis) to differentiate sensory attributes of 3 groups of the wines through characterization of volatiles of cherry wine. Seventy-five volatiles were identified in 9 samples, including 29 esters, 22 alcohols, 8 acids, 3 ketones, 5 aldehydes, and 8 miscellaneous compounds. The PCA results showed that the cherry wines were mainly differentiated by 8 sensory attributes. The samples W2, W4, and W7 were grouped around sweet aromatic and the samples W1, W5, and W9 were highly associated with the sweet, esters, green, bitter, and fermented. Nevertheless, the samples W3, W6, and W8 were located close to the sour, alcoholic, and fruity. The final result of correlation analysis was in conformity with the conclusion of PCA. The CA results showed that the group of W2, W4, and W7, and the group of W1, W5, and W9 had less difference than the group of W3, W6, and W8. The reason should be that esterification reactions and fermentation process during the ageing period was more extended. The results of analyzing revealed that HS-SPME-GC-MS coupled with chemometrics could give an appropriate way of characterizing and classifying the cherry wines. Attributes that represent and discriminate among cherry wines might be made use of a better comprehending of the wines and for being utilized in future work. In addition, several chemometrics were used to classify the type of wines and try to install the relationship between volatiles and sensory property. Especially, PCA clearly revealed that the most contributing compounds for sensory attributes of cherry wines, CA was a more applicable way to distinguish types of cherry wines. Therefore, a feasible method that would be helpful to promote the quality of the wines by improving the winemaking process and analyzing aromatic characteristics of wines. © 2014 Institute of Food Technologists®

Computational pathology of pre-treatment biopsies identifies lymphocyte density as a predictor of response to neoadjuvant chemotherapy in breast cancer.

PubMed

Ali, H Raza; Dariush, Aliakbar; Provenzano, Elena; Bardwell, Helen; Abraham, Jean E; Iddawela, Mahesh; Vallier, Anne-Laure; Hiller, Louise; Dunn, Janet A; Bowden, Sarah J; Hickish, Tamas; McAdam, Karen; Houston, Stephen; Irwin, Mike J; Pharoah, Paul D P; Brenton, James D; Walton, Nicholas A; Earl, Helena M; Caldas, Carlos

2016-02-16

There is a need to improve prediction of response to chemotherapy in breast cancer in order to improve clinical management and this may be achieved by harnessing computational metrics of tissue pathology. We investigated the association between quantitative image metrics derived from computational analysis of digital pathology slides and response to chemotherapy in women with breast cancer who received neoadjuvant chemotherapy. We digitised tissue sections of both diagnostic and surgical samples of breast tumours from 768 patients enrolled in the Neo-tAnGo randomized controlled trial. We subjected digital images to systematic analysis optimised for detection of single cells. Machine-learning methods were used to classify cells as cancer, stromal or lymphocyte and we computed estimates of absolute numbers, relative fractions and cell densities using these data. Pathological complete response (pCR), a histological indicator of chemotherapy response, was the primary endpoint. Fifteen image metrics were tested for their association with pCR using univariate and multivariate logistic regression. Median lymphocyte density proved most strongly associated with pCR on univariate analysis (OR 4.46, 95 % CI 2.34-8.50, p < 0.0001; observations = 614) and on multivariate analysis (OR 2.42, 95 % CI 1.08-5.40, p = 0.03; observations = 406) after adjustment for clinical factors. Further exploratory analyses revealed that in approximately one quarter of cases there was an increase in lymphocyte density in the tumour removed at surgery compared to diagnostic biopsies. A reduction in lymphocyte density at surgery was strongly associated with pCR (OR 0.28, 95 % CI 0.17-0.47, p < 0.0001; observations = 553). A data-driven analysis of computational pathology reveals lymphocyte density as an independent predictor of pCR. Paradoxically an increase in lymphocyte density, following exposure to chemotherapy, is associated with a lack of pCR. Computational pathology can provide objective, quantitative and reproducible tissue metrics and represents a viable means of outcome prediction in breast cancer. ClinicalTrials.gov NCT00070278 ; 03/10/2003.

Multivariate frequency domain analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Fuchigami, Sotaro; Kidera, Akinori

2009-03-01

Multivariate frequency domain analysis (MFDA) is proposed to characterize collective vibrational dynamics of protein obtained by a molecular dynamics (MD) simulation. MFDA performs principal component analysis (PCA) for a bandpass filtered multivariate time series using the multitaper method of spectral estimation. By applying MFDA to MD trajectories of bovine pancreatic trypsin inhibitor, we determined the collective vibrational modes in the frequency domain, which were identified by their vibrational frequencies and eigenvectors. At near zero temperature, the vibrational modes determined by MFDA agreed well with those calculated by normal mode analysis. At 300 K, the vibrational modes exhibited characteristic features that were considerably different from the principal modes of the static distribution given by the standard PCA. The influences of aqueous environments were discussed based on two different sets of vibrational modes, one derived from a MD simulation in water and the other from a simulation in vacuum. Using the varimax rotation, an algorithm of the multivariate statistical analysis, the representative orthogonal set of eigenmodes was determined at each vibrational frequency.

Imaging of polysaccharides in the tomato cell wall with Raman microspectroscopy

PubMed Central

2014-01-01

Background The primary cell wall of fruits and vegetables is a structure mainly composed of polysaccharides (pectins, hemicelluloses, cellulose). Polysaccharides are assembled into a network and linked together. It is thought that the percentage of components and of plant cell wall has an important influence on mechanical properties of fruits and vegetables. Results In this study the Raman microspectroscopy technique was introduced to the visualization of the distribution of polysaccharides in cell wall of fruit. The methodology of the sample preparation, the measurement using Raman microscope and multivariate image analysis are discussed. Single band imaging (for preliminary analysis) and multivariate image analysis methods (principal component analysis and multivariate curve resolution) were used for the identification and localization of the components in the primary cell wall. Conclusions Raman microspectroscopy supported by multivariate image analysis methods is useful in distinguishing cellulose and pectins in the cell wall in tomatoes. It presents how the localization of biopolymers was possible with minimally prepared samples. PMID:24917885

A refined method for multivariate meta-analysis and meta-regression

PubMed Central

Jackson, Daniel; Riley, Richard D

2014-01-01

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects’ standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:23996351

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis.

PubMed

Till, Kevin; Jones, Ben L; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B

2016-01-01

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

PubMed

Hu, Yi-Juan; Berndt, Sonja I; Gustafsson, Stefan; Ganna, Andrea; Hirschhorn, Joel; North, Kari E; Ingelsson, Erik; Lin, Dan-Yu

2013-08-08

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis

PubMed Central

Till, Kevin; Jones, Ben L.; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B.

2016-01-01

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification. PMID:27224653

Radiotherapy alone or combined with chemotherapy as definitive treatment for squamous cell carcinoma of the tonsil.

PubMed

Kennedy, William R; Herman, Michael P; Deraniyagala, Rohan L; Amdur, Robert J; Werning, John W; Dziegielewski, Peter; Kirwan, Jessica; Morris, Christopher G; Mendenhall, William M

2016-08-01

This study is aimed at updating our institution's experience with definitive radiotherapy (RT) for squamous cell carcinoma of the tonsil. We reviewed 531 patients treated between 1983 and 2012 with definitive RT for squamous cell carcinoma of the tonsil. Of these, 179 patients were treated with either induction (n = 19) or concomitant (n = 160) chemotherapy. Planned neck dissection was performed on 217 patients: unilaterally in 199 and bilaterally in 18 patients. Median follow-up was 5.2 years for all patients (range 0.1-31.6 years) and 8.2 years for living patients (range 1.9-31.6 years). The 5-year local control rates by T stage were as follows: T1, 94 %; T2, 87 %; T3 79 %; T4, 70 %; and overall, 83 %. Multivariate analysis revealed that local control was significantly influenced by T stage and neck dissection. The 5-year cause-specific survival rates by overall stage were as follows: I, 94 %; II, 88 %; III, 87 %; IVA, 75 %; IVB, 52 %; and overall, 78 %. Multivariate analysis revealed that cause-specific survival was significantly influenced by T stage, N stage, overall stage, fractionation, neck dissection, sex, and ethnicity. Of 77 patients treated with ipsilateral fields only, contralateral neck failure occurred in 1 %. The rate of severe complications was 12 %. Definitive RT for patients with tonsillar squamous cell carcinoma provides control rates equivalent to other modalities with a comparatively low incidence of late complications. Patients with anterior tonsillar pillar or tonsillar fossa primaries that are well lateralized with no base of tongue or soft palate extension may be treated with ipsilateral fields.

Multivariate pattern analysis of obsessive-compulsive disorder using structural neuroanatomy.

PubMed

Hu, Xinyu; Liu, Qi; Li, Bin; Tang, Wanjie; Sun, Huaiqiang; Li, Fei; Yang, Yanchun; Gong, Qiyong; Huang, Xiaoqi

2016-02-01

Magnetic resonance imaging (MRI) studies have revealed brain structural abnormalities in obsessive-compulsive disorder (OCD) patients, involving both gray matter (GM) and white matter (WM). However, the results of previous publications were based on average differences between groups, which limited their usages in clinical practice. Therefore, the aim of this study was to examine whether the application of multivariate pattern analysis (MVPA) to high-dimensional structural images would allow accurate discrimination between OCD patients and healthy control subjects (HCS). High-resolution T1-weighted images were acquired from 33 OCD patients and 33 demographically matched HCS in a 3.0 T scanner. Differences in GM and WM volume between OCD and HCS were examined using two types of well-established MVPA techniques: support vector machine (SVM) and Gaussian process classifier (GPC). We also drew a receiver operating characteristic (ROC) curve to evaluate the performance of each classifier. The classification accuracies for both classifiers using GM and WM anatomy were all above 75%. The highest classification accuracy (81.82%, P<0.001) was achieved with the SVM classifier using WM information. Regional brain anomalies with high discriminative power were based on three distributed networks including the fronto-striatal circuit, the temporo-parieto-occipital junction and the cerebellum. Our study illustrated that both GM and WM anatomical features may be useful in differentiating OCD patients from HCS. WM volume using the SVM approach showed the highest accuracy in our population for revealing group differences, which suggested its potential diagnostic role in detecting highly enriched OCD patients at the level of the individual. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

Role of Key TYMS Polymorphisms on Methotrexate Therapeutic Outcome in Portuguese Rheumatoid Arthritis Patients

PubMed Central

Lima, Aurea; Seabra, Vítor; Bernardes, Miguel; Azevedo, Rita; Sousa, Hugo; Medeiros, Rui

2014-01-01

Background Therapeutic outcome of rheumatoid arthritis (RA) patients treated with methotrexate (MTX) can be modulated by thymidylate synthase (TS) levels, which may be altered by genetic polymorphisms in TS gene (TYMS). This study aims to elucidate the influence of TYMS polymorphisms in MTX therapeutic outcome (regarding both clinical response and toxicity) in Portuguese RA patients. Methods Clinicopathological data from 233 Caucasian RA patients treated with MTX were collected, outcomes were defined and patients were genotyped for the following TYMS polymorphisms: 1) 28 base pairs (bp) variable number tandem repeat (rs34743033); 2) single nucleotide polymorphism C>G (rs2853542); and 3) 6 bp sequence deletion (1494del6, rs34489327). Chi-square and binary logistic regression analyses were performed, using genotype and haplotype-based approaches. Results Considering TYMS genotypes, 3R3R (p = 0.005, OR = 2.34), 3RC3RG (p = 0.016, OR = 3.52) and 6bp− carriers (p = 0.011, OR = 1.96) were associated with non-response to MTX. Multivariate analysis confirmed the increased risk for non-response to MTX in 6bp− carriers (p = 0.016, OR = 2.74). Data demonstrated that TYMS polymorphisms were in linkage disequilibrium (p<0.00001). Haplotype multivariate analysis revealed that haplotypes harboring both 3R and 6bp− alleles were associated with non-response to MTX. Regarding MTX-related toxicity, no statistically significant differences were observed in relation to TYMS genotypes and haplotypes. Conclusion Our study reveals that TYMS polymorphisms could be important to help predicting clinical response to MTX in RA patients. Despite the potential of these findings, translation into clinical practice needs larger studies to confirm these evidences. PMID:25279663

The double-edged sword of electronic health records: implications for patient disclosure.

PubMed

Campos-Castillo, Celeste; Anthony, Denise L

2015-04-01

Electronic health record (EHR) systems are linked to improvements in quality of care, yet also privacy and security risks. Results from research studies are mixed about whether patients withhold personal information from their providers to protect against the perceived EHR privacy and security risks. This study seeks to reconcile the mixed findings by focusing on whether accounting for patients' global ratings of care reveals a relationship between EHR provider-use and patient non-disclosure. A nationally representative sample from the 2012 Health Information National Trends Survey was analyzed using bivariate and multivariable logit regressions to examine whether global ratings of care suppress the relationship between EHR provider-use and patient non-disclosure. 13% of respondents reported having ever withheld information from a provider because of privacy/security concerns. Bivariate analysis showed that withholding information was unrelated to whether respondents' providers used an EHR. Multivariable analysis showed that accounting for respondents' global ratings of care revealed a positive relationship between having a provider who uses an EHR and withholding information. After accounting for global ratings of care, findings suggest that patients may non-disclose to providers to protect against the perceived EHR privacy and security risks. Despite evidence that EHRs inhibit patient disclosure, their advantages for promoting quality of care may outweigh the drawbacks. Clinicians should leverage the EHR's value in quality of care and discuss patients' privacy concerns during clinic visits, while policy makers should consider how to address the real and perceived privacy and security risks of EHRs. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Ratio of serum levels of AGEs to soluble form of RAGE is a predictor of endothelial function.

PubMed

Kajikawa, Masato; Nakashima, Ayumu; Fujimura, Noritaka; Maruhashi, Tatsuya; Iwamoto, Yumiko; Iwamoto, Akimichi; Matsumoto, Takeshi; Oda, Nozomu; Hidaka, Takayuki; Kihara, Yasuki; Chayama, Kazuaki; Goto, Chikara; Aibara, Yoshiki; Noma, Kensuke; Takeuchi, Masayoshi; Matsui, Takanori; Yamagishi, Sho-Ichi; Higashi, Yukihito

2015-01-01

Advanced glycation end products (AGEs) and their specific receptor, the receptor for AGEs (RAGE), play an important role in atherosclerosis. Recently, a soluble form of RAGE (sRAGE) has been identified in human serum. However, the role of sRAGE in cardiovascular disease is still controversial. There is no information on the association between simultaneous measurements of AGEs and sRAGE and vascular function. In this study, we evaluated the associations between serum levels of AGEs and sRAGE, ratio of AGEs to sRAGE, and vascular function. We measured serum levels of AGEs and sRAGE and assessed vascular function by measurement of flow-mediated vasodilation (FMD) and nitroglycerine-induced vasodilation in 110 subjects who underwent health examinations. Multivariate regression analyses were performed to identify factors associated with vascular function. Univariate regression analysis revealed that FMD correlated with age, BMI, systolic blood pressure, diastolic blood pressure, heart rate, triglycerides, HDL cholesterol, glucose, smoking pack-years, nitroglycerine-induced vasodilation, serum levels of AGEs and sRAGE, and ratio of AGEs to sRAGE. Multivariate analysis revealed that the ratio of AGEs to sRAGE remained an independent predictor of FMD, while serum level of AGEs alone or sRAGE alone was not associated with FMD. These findings suggest that sRAGE may have a counterregulatory mechanism that is activated to counteract the vasotoxic effect of the AGE-RAGE axis. The ratio of AGEs to sRAGE may be a new chemical biomarker of endothelial function. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Primary and Central Hypothyroidism After Radiotherapy for Head-and-Neck Tumors

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

Bhandare, Niranjan; Kennedy, Laurence; Malyapa, Robert S.

Purpose: To investigate the incidence of radiotherapy (RT)-induced central and primary hypothyroidism regarding total dose, fractionation, and adjuvant chemotherapy. Methods and Materials: We retrospectively reviewed the data from 312 patients treated with RT for extracranial head-and-neck tumors between 1964 and 2000. The cervical lymph nodes were irradiated in 197 patients. The radiation doses to the thyroid gland and hypothalamic-pituitary axis were estimated by reconstructing the treatment plans. Results: Clinical central hypothyroidism (CH) was observed in 17 patients (5.4%); the median clinical latency was 4.8 years. Clinical primary hypothyroidism (PH) was observed in 40 patients (20.3%); the median clinical latency wasmore » 3.1 years. Multivariate analysis of clinical CH revealed that fractionation, adjuvant chemotherapy, and total dose to the pituitary were not significant. Multivariate analysis of clinical PH revealed that the total dose to the thyroid (p = 0.043) was significant, but adjuvant chemotherapy, age, and gender were not. Of the patients tested for hypopituitarism, 14 (20.3%) of 69 demonstrated subclinical CH and 17 (27.4%) of 62 demonstrated subclinical PH. The 5-year and 10-year rates of freedom from clinical CH and PH were 97% and 87% and 68% and 67%, respectively. Of the patients tested, the 5-year and 10-year rates of freedom from subclinical CH and PH were 91% and 78% and 71% and 71%, respectively. Conclusion: Clinical and subclinical manifestations of late radiation toxicity were observed in the thyroid and hypothalamic-pituitary axis. Although CH did not indicate a dependence on fractionation, adjuvant chemotherapy, or total dose to the pituitary, PH showed a dependence on the total dose to the thyroid gland.« less

Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

PubMed

Fang, Peng; An, Jie; Zeng, Ling-Li; Shen, Hui; Chen, Fanglin; Wang, Wensheng; Qiu, Shijun; Hu, Dewen

2015-01-01

Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE), but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right) mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for each subject, multivariate pattern analysis was applied to classify the left mTLE from the right mTLE and extract the anatomical connectivity differences between the left and right mTLE patients. The classification results reveal 93.0% accuracy for the left mTLE versus the right mTLE, 93.4% accuracy for the left mTLE versus controls and 90.0% accuracy for the right mTLE versus controls. Compared with the right mTLE, the left mTLE exhibited a different connectivity pattern in the cortical-limbic network and cerebellum. The majority of the most discriminating anatomical connections were located within or across the cortical-limbic network and cerebellum, thereby indicating that these disease-related anatomical network alterations may give rise to a portion of the complex of emotional and memory deficit between the left and right mTLE. Moreover, the orbitofrontal gyrus, cingulate cortex, hippocampus and parahippocampal gyrus, which exhibit high discriminative power in classification, may play critical roles in the pathophysiology of mTLE. The current study demonstrated that anatomical connectivity differences between the left mTLE and the right mTLE may have the potential to serve as a neuroimaging biomarker to guide personalized diagnosis of the left and right mTLE.

Trajectories of caregiver burden in families of adult cystic fibrosis patients.

PubMed

Wojtaszczyk, Ann; Glajchen, Myra; Portenoy, Russell K; Berdella, Maria; Walker, Patricia; Barrett, Malcolm; Chen, Jack; Plachta, Amy; Balzano, Julie; Fresenius, Ashley; Wilder, Kenya; Langfelder-Schwind, Elinor; Dhingra, Lara

2017-10-17

Little is known about the experience of family caregivers of adults with cystic fibrosis (CF). This information is important for the identification of caregivers at risk for burden. This was a longitudinal analysis of survey data obtained from caregivers of adult CF patients participating in an early intervention palliative care trial. Caregivers completed the validated Brief Assessment Scale for Caregivers (BASC) repeatedly over a 28-month period. Mixed-effects modeling evaluated multivariate associations with positive and negative caregiver perceptions over time. Of the 54 caregivers, 47.9% were spouses. The mean age was 50.9 years (SD = 13.2); 72.2% were women; 75.9% were married; and 63.0% were employed. At baseline, the BASC revealed large variations in positive and negative perceptions of caregiving. Although average scores over time were unchanging, variation was greater across caregivers than within caregivers (0.49 vs. 0.27, respectively). At baseline, the positive impact of caregiving in the sample was higher than the negative impact. Multivariate analysis revealed that patients' baseline pulmonary function and their full-time employment status predicted caregiver burden over time. Caregivers of CF patients varied in their positive and negative caregiving experiences, although burden levels in individual caregivers were stable over time. When the disease was advanced, caregivers of CF patients experienced more overall burden but also more positive impact. This suggests that the role of caregivers may become more meaningful as disease severity worsens. In addition, full-time patient employment was associated with lower caregiver burden regardless of disease severity. This suggests that burden in CF caregivers may be predicted by financial strain or benefits conferred by patient employment. These associations require further investigation to determine whether highly burdened caregivers can be identified and assisted using tailored interventions.

Predictors of radio-cephalic arteriovenous fistulae patency in an Asian population.

PubMed

Joseph Lo, Zhiwen; Tay, Wee Ming; Lee, Qinyi; Chua, Jia Long; Tan, Glenn Wei Leong; Chandrasekar, Sadhana; Narayanan, Sriram

2016-09-21

To identify predictors of arteriovenous fistula (AVF) patency in Asian patients with autogenous radio-cephalic arteriovenous fistula (RCAVF). Retrospective review of 436 RCAVFs created between 2009 and 2013. Predictors of patency were identified with univariate and multivariate analysis. Kaplan-Meier survival analysis and log-rank test were used to calculate patency rates. Overall secondary patency rate was 72% at 12 months, 69% at 24 months, 58% at 36 months, 57% at 48 months, 56% at 60 months and 54% at 72 months. Univariate analysis showed that factors which predict for patency include male gender (p = 0.003), good diabetic control (p = 0.025), aspirin use (p = 0.031), pre-dialysis status (p = 0.037), radial artery diameter (p = 0.029) and non-calcified radial arteries (p = 0.002). Age (p = 0.866), cephalic vein diameter (p = 0.630) and surgeon grade (p = 0.472) did not predict for primary AVF failure. Multivariate analysis revealed the male gender to be an independent predictor for patency (odds ratio 1.99, p = 0.01). Subset analysis showed a significantly larger average radial artery diameter of 2.3 mm amongst males, as compared to 1.9 mm amongst females (p = 0.001) and no statistical difference in the average cephalic vein diameter. Within our Asian study population, 12-month patency rate of RCAVF is 72%, 69% at 24 months, 58% at 36 months, 57% at 48 months, 56% at 60 months and 54% at 72 months. Male gender is an independent predictor for RCAVF patency. In females or patients with calcified radial arteries, a more proximal AVF should be considered.

Factors associated with postoperative C5 palsy after expansive open-door laminoplasty: retrospective cohort study using multivariable analysis.

PubMed

Tsuji, Takashi; Matsumoto, Morio; Nakamura, Masaya; Ishii, Ken; Fujita, Nobuyuki; Chiba, Kazuhiro; Watanabe, Kota

2017-09-01

The aim of the present study was to investigate the factors associated with C5 palsy by focusing on radiological parameters using multivariable analysis. The authors retrospectively assessed 190 patients with cervical spondylotic myelopathy treated by open-door laminoplasty. Four radiographic parameters-the number of expanded lamina, C3-C7 angle, lamina open angle and space anterior to the spinal cord-were evaluated to clarify the factors associated with C5 palsy. Of the 190 patients, 11 developed C5 palsy, giving an overall incidence of 5.8%. Although the number of expanded lamina, lamina open angle and space anterior to the spinal cord were significantly larger in C5 palsy group than those in non-palsy group, a multiple logistic regression analysis revealed that only the space anterior to the spinal cord (odds ratio 2.60) was a significant independent factor associated with C5 palsy. A multiple linear regression analysis indicated that the lamina open angle was associated with the space anterior to the spinal cord and the analysis identified the following equation: space anterior to the spinal cord (mm) = 1.54 + 0.09 × lamina open angle (degree). A cut-off value of 53.5° for the lamina open angle predicted the development of C5 palsy with a sensitivity of 72.7% and a specificity of 83.2%. The larger postoperative space anterior to the spinal cord, which was associated with the lamina open angle, was positively correlated with the higher incidence of C5 palsy.

Analysis of Prognostic Factors and Patterns of Recurrence in Patients With Pathologic Stage III Endometrial Cancer

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

Patel, Samir; Portelance, Lorraine; Gilbert, Lucy

2007-08-01

Purpose: To retrospectively assess prognostic factors and patterns of recurrence in patients with pathologic Stage III endometrial cancer. Methods and Materials: Between 1989 and 2003, 107 patients with pathologic International Federation of Gynecology and Obstetrics Stage III endometrial adenocarcinoma confined to the pelvis were treated at our institution. Adjuvant radiotherapy (RT) was delivered to 68 patients (64%). The influence of multiple patient- and treatment-related factors on pelvic and distant control and overall survival (OS) was evaluated. Results: Median follow-up for patients at risk was 41 months. Five-year actuarial OS was significantly improved in patients treated with adjuvant RT (68%) comparedmore » with those with resection alone (50%; p = 0.029). Age, histology, grade, uterine serosal invasion, adnexal involvement, number of extrauterine sites, and treatment with adjuvant RT predicted for improved survival in univariate analysis. Multivariate analysis revealed that grade, uterine serosal invasion, and treatment with adjuvant RT were independent predictors of survival. Five-year actuarial pelvic control was improved significantly with the delivery of adjuvant RT (74% vs. 49%; p = 0.011). Depth of myometrial invasion and treatment with adjuvant RT were independent predictors of pelvic control in multivariate analysis. Conclusions: Multiple prognostic factors predicting for the outcome of pathologic Stage III endometrial cancer patients were identified in this analysis. In particular, delivery of adjuvant RT seems to be a significant independent predictor for improved survival and pelvic control, suggesting that pelvic RT should be routinely considered in the management of these patients.« less

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

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

Principal component analysis and analysis of variance on the effects of Entellan New on the Raman spectra of fibers.

PubMed

Yu, Marcia M L; Sandercock, P Mark L

2012-01-01

During the forensic examination of textile fibers, fibers are usually mounted on glass slides for visual inspection and identification under the microscope. One method that has the capability to accurately identify single textile fibers without subsequent demounting is Raman microspectroscopy. The effect of the mountant Entellan New on the Raman spectra of fibers was investigated to determine if it is suitable for fiber analysis. Raman spectra of synthetic fibers mounted in three different ways were collected and subjected to multivariate analysis. Principal component analysis score plots revealed that while spectra from different fiber classes formed distinct groups, fibers of the same class formed a single group regardless of the mounting method. The spectra of bare fibers and those mounted in Entellan New were found to be statistically indistinguishable by analysis of variance calculations. These results demonstrate that fibers mounted in Entellan New may be identified directly by Raman microspectroscopy without further sample preparation. © 2011 American Academy of Forensic Sciences.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Postoperative Radiotherapy Patterns of Care and Survival Implications for Medulloblastoma in Young Children.

PubMed

Kann, Benjamin H; Park, Henry S; Lester-Coll, Nataniel H; Yeboa, Debra N; Benitez, Viviana; Khan, Atif J; Bindra, Ranjit S; Marks, Asher M; Roberts, Kenneth B

2016-12-01

Postoperative radiotherapy to the craniospinal axis is standard-of-care for pediatric medulloblastoma but is associated with long-term morbidity, particularly in young children. With the advent of modern adjuvant chemotherapy strategies, postoperative radiotherapy deferral has gained acceptance in children younger than 3 years, although it remains controversial in older children. To analyze recent postoperative radiotherapy national treatment patterns and implications for overall survival in patients with medulloblastoma ages 3 to 8 years. Using the National Cancer Data Base, patients ages 3 to 8 years diagnosed as having histologically confirmed medulloblastoma in 2004 to 2012, without distant metastases, who underwent surgery and adjuvant chemotherapy with or without postoperative radiotherapy at facilities nationwide accredited by the Commission on Cancer were identified. Patients were designated as having "postoperative radiotherapy upfront" if they received radiotherapy within 90 days of surgery or "postoperative radiotherapy deferred" otherwise. Factors associated with postoperative radiotherapy deferral were identified using multivariable logistic regression. Overall survival (OS) was compared using Kaplan-Meier analysis with log-rank tests and multivariable Cox regression. Statistical tests were 2-sided. Postoperative radiotherapy utilization and overall survival. Among 816 patients, 123 (15.1%) had postoperative radiotherapy deferred, and 693 (84.9%) had postoperative radiotherapy upfront; 36.8% of 3-year-olds and 4.1% of 8-year-olds had postoperative radiotherapy deferred (P < .001). On multivariable logistic regression, variables associated with postoperative radiotherapy deferral were age (odds ratio [OR], 0.57 per year; 95% CI, 0.49-0.67 per year) and year of diagnosis (OR, 1.18 per year; 95% CI, 1.08-1.29 per year). On survival analysis, with median follow-up of 4.8 years, OS was improved for those receiving postoperative radiotherapy upfront vs postoperative radiotherapy deferred (5-year OS: 82.0% vs 63.4%; P < .001). On multivariable analysis, variables associated with poorer OS were postoperative radiotherapy deferral (hazards ratio [HR], 1.95; 95% CI, 1.15-3.31); stage M1-3 disease (HR, 1.86; 95% CI, 1.10-3.16), and low facility volume (HR, 1.75; 95% CI, 1.04-2.94). Our national database analysis reveals a higher-than-expected and increasing rate of postoperative radiotherapy deferral in children with medulloblastoma ages 3 to 8 years. The analysis suggests that postoperative radiotherapy deferral is associated with worse survival in this age group, even in the modern era of chemotherapy.

Multivariate Time Series Decomposition into Oscillation Components.

PubMed

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

Multivariate statistical data analysis methods for detecting baroclinic wave interactions in the thermally driven rotating annulus

NASA Astrophysics Data System (ADS)

von Larcher, Thomas; Harlander, Uwe; Alexandrov, Kiril; Wang, Yongtai

2010-05-01

Experiments on baroclinic wave instabilities in a rotating cylindrical gap have been long performed, e.g., to unhide regular waves of different zonal wave number, to better understand the transition to the quasi-chaotic regime, and to reveal the underlying dynamical processes of complex wave flows. We present the application of appropriate multivariate data analysis methods on time series data sets acquired by the use of non-intrusive measurement techniques of a quite different nature. While the high accurate Laser-Doppler-Velocimetry (LDV ) is used for measurements of the radial velocity component at equidistant azimuthal positions, a high sensitive thermographic camera measures the surface temperature field. The measurements are performed at particular parameter points, where our former studies show that kinds of complex wave patterns occur [1, 2]. Obviously, the temperature data set has much more information content as the velocity data set due to the particular measurement techniques. Both sets of time series data are analyzed by using multivariate statistical techniques. While the LDV data sets are studied by applying the Multi-Channel Singular Spectrum Analysis (M - SSA), the temperature data sets are analyzed by applying the Empirical Orthogonal Functions (EOF ). Our goal is (a) to verify the results yielded with the analysis of the velocity data and (b) to compare the data analysis methods. Therefor, the temperature data are processed in a way to become comparable to the LDV data, i.e. reducing the size of the data set in such a manner that the temperature measurements would imaginary be performed at equidistant azimuthal positions only. This approach initially results in a great loss of information. But applying the M - SSA to the reduced temperature data sets enable us to compare the methods. [1] Th. von Larcher and C. Egbers, Experiments on transitions of baroclinic waves in a differentially heated rotating annulus, Nonlinear Processes in Geophysics, 2005, 12, 1033-1041, NPG Print: ISSN 1023-5809, NPG Online: ISSN 1607-7946 [2] U. Harlander, Th. von Larcher, Y. Wang and C. Egbers, PIV- and LDV-measurements of baroclinic wave interactions in a thermally driven rotating annulus, Experiments in Fluids, 2009, DOI: 10.1007/s00348-009-0792-5

Male gender and renal dysfunction are predictors of adverse outcome in nonpostoperative ischemic colitis patients.

PubMed

Lee, Tsung-Chun; Wang, Hsiu-Po; Chiu, Han-Mo; Lien, Wan-Ching; Chen, Mei-Jyh; Yu, Linda C H; Sun, Chia-Tung; Lin, Jaw-Town; Wu, Ming-Shiang

2010-01-01

Ischemic colitis (IC) spans a broad spectrum from self-limiting illness to intestinal gangrene and mortality. Prognostic factors specifically for nonpostoperative IC were not fully characterized. We aim to focus on nonpostoperative IC in patients with renal dysfunction and try to identify prognostic factors for adverse outcomes. We conducted a retrospective analysis at a university-affiliated tertiary medical center in Taiwan. From January 2003 to August 2008, 25 men and 52 women (mean age: 66 y) had colonoscopic biopsy-proven IC without prior culprit surgery. We estimated glomerular filtration rate with simplified Modification of Diet in Renal Disease equation. Nine patients with glomerular filtration rate below 30 mL per minute per 1.73 m were classified as renal dysfunction group (including 7 dialysis patients). Adverse outcomes were defined as need for surgery and mortality. Predictors for adverse outcomes were captured by univariate and multivariate analysis. Research ethical committee approved the study protocol. Patients with renal dysfunction more often had: diabetes mellitus (56% vs. 16%, P=0.02), prolonged symptoms (6.8 d vs. 3.5 d, P=0.01), lower hemoglobin (11.1 g/dL vs. 13.4 g/dL, P=0.01), and more often right colonic involvement (56% vs. 19%, P=0.03). Renal dysfunction patients also had longer hospitalization days (median 15 d vs. 4 d, P=0.045). However, there was no statistical significance in the rate of either surgery or mortality between these 2 groups (P>0.05). Univariate analysis showed that renal dysfunction, sex, emergency department referral, presentation with abdominal pain were significant for adverse outcome (P<0.1). Multivariate analysis revealed that male sex conveyed 9.5-fold risk (P=0.01) and renal dysfunction conveyed 8.5-fold risk (P=0.03) for adverse outcomes. Nonpostoperative IC patients with concurrent renal dysfunction had distinct clinical profiles. Multivariate analysis showed that male patients had 9.5-fold and renal dysfunction patients had 8.5-fold increased risk for adverse outcomes. Although IC is often self-limited, our data warrants special attention and aggressive therapy in treating these patients.

Multivariate statistical and lead isotopic analyses approach to identify heavy metal sources in topsoil from the industrial zone of Beijing Capital Iron and Steel Factory.

PubMed

Zhu, Guangxu; Guo, Qingjun; Xiao, Huayun; Chen, Tongbin; Yang, Jun

2017-06-01

Heavy metals are considered toxic to humans and ecosystems. In the present study, heavy metal concentration in soil was investigated using the single pollution index (PIi), the integrated Nemerow pollution index (PIN), and the geoaccumulation index (Igeo) to determine metal accumulation and its pollution status at the abandoned site of the Capital Iron and Steel Factory in Beijing and its surrounding area. Multivariate statistical (principal component analysis and correlation analysis), geostatistical analysis (ArcGIS tool), combined with stable Pb isotopic ratios, were applied to explore the characteristics of heavy metal pollution and the possible sources of pollutants. The results indicated that heavy metal elements show different degrees of accumulation in the study area, the observed trend of the enrichment factors, and the geoaccumulation index was Hg > Cd > Zn > Cr > Pb > Cu ≈ As > Ni. Hg, Cd, Zn, and Cr were the dominant elements that influenced soil quality in the study area. The Nemerow index method indicated that all of the heavy metals caused serious pollution except Ni. Multivariate statistical analysis indicated that Cd, Zn, Cu, and Pb show obvious correlation and have higher loads on the same principal component, suggesting that they had the same sources, which are related to industrial activities and vehicle emissions. The spatial distribution maps based on ordinary kriging showed that high concentrations of heavy metals were located in the local factory area and in the southeast-northwest part of the study region, corresponding with the predominant wind directions. Analyses of lead isotopes confirmed that Pb in the study soils is predominantly derived from three Pb sources: dust generated during steel production, coal combustion, and the natural background. Moreover, the ternary mixture model based on lead isotope analysis indicates that lead in the study soils originates mainly from anthropogenic sources, which contribute much more than the natural sources. Our study could not only reveal the overall situation of heavy metal contamination, but also identify the specific pollution sources.

Multivariate time series analysis of neuroscience data: some challenges and opportunities.

PubMed

Pourahmadi, Mohsen; Noorbaloochi, Siamak

2016-04-01

Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced. Copyright © 2015 Elsevier Ltd. All rights reserved.

High Cost of Hospitalization for Colonic Diverticular Bleeding Depended on Repeated Bleeding and Blood Transfusion: Analysis with Diagnosis Procedure Combination Data in Japan.

PubMed

Ito, Yoichiro; Sakata, Yasuhisa; Yoshida, Hisako; Nonaka, Sayuri; Fujii, Susumu; Tanaka, Yuichiro; Shirai, Shimpei; Takeshita, Eri; Akutagawa, Takashi; Kawakubo, Hiroharu; Yamamoto, Koji; Tsuruoka, Nanae; Shimoda, Ryo; Iwakiri, Ryuichi; Fujimoto, Kazuma

2017-01-01

Bleeding from a colonic diverticulum is serious in aged patients. The aim of this study was to determine the risk factors for high-cost hospitalization of colonic diverticular bleeding using the diagnosis procedure combination (DPC) data. From January 2009 to December 2015, 78 patients with colonic diverticular bleeding were identified by DPC data in Saga Medical School Hospital. All patients underwent colonic endoscopy within 3 days. The patients were divided into 2 groups: the low-cost group (DPC cost of <500,000 yen) and the high-cost group (DPC cost of >500,000 yen). Univariate analysis revealed that aging, hypertension, rebleeding, a low hemoglobin concentration at admission, and blood transfusion were risk factors for high hospitalization cost. Multivariate analysis revealed that rebleeding (OR 5.3; 95% CI 1.3-21.3; p = 0.017) and blood transfusion (OR 3.8; 95% CI 1.01-14.2; p = 0.048) were definite risk factors for high hospitalization cost. Rebleeding and blood transfusion were related to high hospitalization cost for colonic diverticular bleeding. © 2017 S. Karger AG, Basel.

Increased plasma proline concentrations are associated with sarcopenia in the elderly

PubMed Central

Adachi, Yusuke; Imaizumi, Akira; Hakamada, Tomomi; Abe, Yasuko; Kaneko, Eiji; Takahashi, Soiciro; Shimokado, Kentaro

2017-01-01

Background and purpose Metabolome analyses have shown that plasma amino acid profiles reflect various pathological conditions, such as cancer and diabetes mellitus. It remains unclear, however, whether plasma amino acid profiles change in patients with sarcopenia. This study therefore aimed to investigate whether sarcopenia-specific changes occur in plasma amino acid profiles. Methods A total of 153 community-dwelling and seven institutionalized elderly individuals (56 men, 104 women; mean age, 77.7±7.0 years) were recruited for this cross-sectional analysis. We performed a comprehensive geriatric assessment, which included an evaluation of hand grip strength, gait speed, muscle mass and blood chemistry, including the concentration of 18 amino acids. Results Twenty-eight of the 160 participants met the criteria for sarcopenia established by the Asian Working Group on Sarcopenia in Older People. Univariate analysis revealed associations between the presence of sarcopenia and a higher plasma concentration of proline and glutamine, lower concentrations of histidine and tryptophan. Multivariable analysis revealed that a higher concentration of proline was the only variable independently associated with sarcopenia. Conclusions The plasma concentration of proline may be useful for understanding the underlying pathophysiology of sarcopenia. PMID:28934309

Default and Executive Network Coupling Supports Creative Idea Production

PubMed Central

Beaty, Roger E.; Benedek, Mathias; Barry Kaufman, Scott; Silvia, Paul J.

2015-01-01

The role of attention in creative cognition remains controversial. Neuroimaging studies have reported activation of brain regions linked to both cognitive control and spontaneous imaginative processes, raising questions about how these regions interact to support creative thought. Using functional magnetic resonance imaging (fMRI), we explored this question by examining dynamic interactions between brain regions during a divergent thinking task. Multivariate pattern analysis revealed a distributed network associated with divergent thinking, including several core hubs of the default (posterior cingulate) and executive (dorsolateral prefrontal cortex) networks. The resting-state network affiliation of these regions was confirmed using data from an independent sample of participants. Graph theory analysis assessed global efficiency of the divergent thinking network, and network efficiency was found to increase as a function of individual differences in divergent thinking ability. Moreover, temporal connectivity analysis revealed increased coupling between default and salience network regions (bilateral insula) at the beginning of the task, followed by increased coupling between default and executive network regions at later stages. Such dynamic coupling suggests that divergent thinking involves cooperation between brain networks linked to cognitive control and spontaneous thought, which may reflect focused internal attention and the top-down control of spontaneous cognition during creative idea production. PMID:26084037

Analysis of threats to research validity introduced by audio recording clinic visits: Selection bias, Hawthorne effect, both, or neither?

PubMed Central

Henry, Stephen G.; Jerant, Anthony; Iosif, Ana-Maria; Feldman, Mitchell D.; Cipri, Camille; Kravitz, Richard L.

2015-01-01

Objective To identify factors associated with participant consent to record visits; to estimate effects of recording on patient-clinician interactions Methods Secondary analysis of data from a randomized trial studying communication about depression; participants were asked for optional consent to audio record study visits. Multiple logistic regression was used to model likelihood of patient and clinician consent. Multivariable regression and propensity score analyses were used to estimate effects of audio recording on 6 dependent variables: discussion of depressive symptoms, preventive health, and depression diagnosis; depression treatment recommendations; visit length; visit difficulty. Results Of 867 visits involving 135 primary care clinicians, 39% were recorded. For clinicians, only working in academic settings (P=0.003) and having worked longer at their current practice (P=0.02) were associated with increased likelihood of consent. For patients, white race (P=0.002) and diabetes (P=0.03) were associated with increased likelihood of consent. Neither multivariable regression nor propensity score analyses revealed any significant effects of recording on the variables examined. Conclusion Few clinician or patient characteristics were significantly associated with consent. Audio recording had no significant effect on any dependent variables. Practice Implications Benefits of recording clinic visits likely outweigh the risks of bias in this setting. PMID:25837372

Exploring Raman spectroscopy for the evaluation of glaucomatous retinal changes

NASA Astrophysics Data System (ADS)

Wang, Qi; Grozdanic, Sinisa D.; Harper, Matthew M.; Hamouche, Nicolas; Kecova, Helga; Lazic, Tatjana; Yu, Chenxu

2011-10-01

Glaucoma is a chronic neurodegenerative disease characterized by apoptosis of retinal ganglion cells and subsequent loss of visual function. Early detection of glaucoma is critical for the prevention of permanent structural damage and irreversible vision loss. Raman spectroscopy is a technique that provides rapid biochemical characterization of tissues in a nondestructive and noninvasive fashion. In this study, we explored the potential of using Raman spectroscopy for detection of glaucomatous changes in vitro. Raman spectroscopic imaging was conducted on retinal tissues of dogs with hereditary glaucoma and healthy control dogs. The Raman spectra were subjected to multivariate discriminant analysis with a support vector machine algorithm, and a classification model was developed to differentiate disease tissues versus healthy tissues. Spectroscopic analysis of 105 retinal ganglion cells (RGCs) from glaucomatous dogs and 267 RGCs from healthy dogs revealed spectroscopic markers that differentiated glaucomatous specimens from healthy controls. Furthermore, the multivariate discriminant model differentiated healthy samples and glaucomatous samples with good accuracy [healthy 89.5% and glaucomatous 97.6% for the same breed (Basset Hounds); and healthy 85.0% and glaucomatous 85.5% for different breeds (Beagles versus Basset Hounds)]. Raman spectroscopic screening can be used for in vitro detection of glaucomatous changes in retinal tissue with a high specificity.

Nanoscale structural and electronic characterization of α-RuCl3 layered compound

NASA Astrophysics Data System (ADS)

Ziatdinov, Maxim; Maksov, Artem; Banerjee, Arnab; Zhou, Wu; Berlijn, Tom; Yan, Jiaqiang; Nagler, Stephen; Mandrus, David; Baddorf, Arthur; Kalinin, Sergei

The exceptional interplay of spin-orbit effects, Coulomb interaction, and electron-lattice coupling is expected to produce an elaborate phase space of α-RuCl3 layered compound, which to date remains largely unexplored. Here we employ a combination of scanning transmission electron microscopy (STEM) and scanning tunneling microscopy (STM) for detailed evaluation of the system's microscopic structural and electronic orders with a sub-nanometer precision. The STM and STEM measurements are further supported by neutron scattering, X-Ray diffraction, density functional theory (DFT), and multivariate statistical analysis. Our results show a trigonal distortion of Cl octahedral ligand cage along the C3 symmetry axes in each RuCl3 layer. The lattice distortion is limited mainly to the Cl subsystem leaving the Ru honeycomb lattice nearly intact. The STM topographic and spectroscopic characterization reveals an intra unit cell electronic symmetry breaking in a spin-orbit coupled Mott insulating phase on the Cl-terminated surface of α-RuCl3. The associated long-range charge order (CO) pattern is linked to a surface component of Cl cage distortion. We finally discuss a fine structure of CO and its potential relation to variations of average unit cell geometries found in multivariate analysis of STEM data. The research was sponsored by the U.S. Department of Energy.

Impact of preoperative antithrombotic therapy on blood management after implantation of primary total knee arthroplasty

PubMed Central

Leitner, Lukas; Musser, Ewald; Kastner, Norbert; Friesenbichler, Jörg; Hirzberger, Daniela; Radl, Roman; Leithner, Andreas; Sadoghi, Patrick

2016-01-01

Red blood cell concentrates (RCC) substitution after total knee arthroplasty (TKA) is correlated with multifold of complications and an independent predictor for higher postoperative mortality. TKA is mainly performed in elderly patients with pre-existing polymorbidity, often requiring permanent preoperative antithrombotic therapy (PAT). The aim of this retrospective analysis was to investigate the impact of demand for PAT on inpatient blood management in patients undergoing TKA. In this study 200 patients were retrospectively evaluated after TKA for differences between PAT and non-PAT regarding demographic parameters, preoperative ASA score > 2, duration of operation, pre-, and intraoperative hemoglobin level, and postoperative parameters including amount of wound drainage, RCC requirement, and inpatient time. In a multivariate logistic regression analysis the independent influences of PAT, demographic parameters, ASA score > 2, and duration of the operation on RCC demand following TKA were analyzed. Patients with PAT were significantly older, more often had an ASA > 2 at surgery, needed a higher number of RCCs units and more frequently and had lower perioperative hemoglobin levels. Multivariate logistic regression revealed PAT was an independent predictor for RCC requirement. PAT patients are more likely to require RCC following TKA and should be accurately monitored with respect to postoperative blood loss. PMID:27488941

Impact of preoperative antithrombotic therapy on blood management after implantation of primary total knee arthroplasty.

PubMed

Leitner, Lukas; Musser, Ewald; Kastner, Norbert; Friesenbichler, Jörg; Hirzberger, Daniela; Radl, Roman; Leithner, Andreas; Sadoghi, Patrick

2016-08-04

Red blood cell concentrates (RCC) substitution after total knee arthroplasty (TKA) is correlated with multifold of complications and an independent predictor for higher postoperative mortality. TKA is mainly performed in elderly patients with pre-existing polymorbidity, often requiring permanent preoperative antithrombotic therapy (PAT). The aim of this retrospective analysis was to investigate the impact of demand for PAT on inpatient blood management in patients undergoing TKA. In this study 200 patients were retrospectively evaluated after TKA for differences between PAT and non-PAT regarding demographic parameters, preoperative ASA score > 2, duration of operation, pre-, and intraoperative hemoglobin level, and postoperative parameters including amount of wound drainage, RCC requirement, and inpatient time. In a multivariate logistic regression analysis the independent influences of PAT, demographic parameters, ASA score > 2, and duration of the operation on RCC demand following TKA were analyzed. Patients with PAT were significantly older, more often had an ASA > 2 at surgery, needed a higher number of RCCs units and more frequently and had lower perioperative hemoglobin levels. Multivariate logistic regression revealed PAT was an independent predictor for RCC requirement. PAT patients are more likely to require RCC following TKA and should be accurately monitored with respect to postoperative blood loss.

Longitudinal analysis of physical activity, fluid intake, and graft function among kidney transplant recipients

PubMed Central

Gordon, Elisa J.; Prohaska, Thomas R.; Gallant, Mary P.; Sehgal, Ashwini R.; Strogatz, David; Yucel, Recai; Conti, David; Siminoff, Laura A.

2010-01-01

Summary Self-care is recommended to kidney transplant recipients as a vital component to maintain long-term graft function. However, little is known about the effects of physical activity, fluid intake, and smoking history on graft function. This longitudinal study examined the relationship between self-care practices on graft function among 88 new kidney transplant recipients in Chicago, IL and Albany, NY between 2005 and 2008. Participants were interviewed, completed surveys, and medical charts were abstracted. Physical activity, fluid intake, and smoking history at baseline were compared with changes in estimated glomerular filtration rate (eGFR) (every 6 months up to 1 year) using bivariate and multivariate regression analysis, while controlling for sociodemographic and clinical transplant variables. Multivariate analyses revealed that greater physical activity was significantly (P < 0.05) associated with improvement in GFR at 6 months; while greater physical activity, absence of smoking history, and nonwhite ethnicity were significant (P < 0.05) predictors of improvement in GFR at 12 months. These results suggest that increasing physical activity levels in kidney recipients may be an effective behavioral measure to help ensure graft functioning. Our findings suggest the need for a randomized controlled trial of exercise, fluid intake, and smoking history on GFR beyond 12 months. PMID:19619168

Longitudinal analysis of physical activity, fluid intake, and graft function among kidney transplant recipients.

PubMed

Gordon, Elisa J; Prohaska, Thomas R; Gallant, Mary P; Sehgal, Ashwini R; Strogatz, David; Yucel, Recai; Conti, David; Siminoff, Laura A

2009-10-01

Self-care is recommended to kidney transplant recipients as a vital component to maintain long-term graft function. However, little is known about the effects of physical activity, fluid intake, and smoking history on graft function. This longitudinal study examined the relationship between self-care practices on graft function among 88 new kidney transplant recipients in Chicago, IL and Albany, NY between 2005 and 2008. Participants were interviewed, completed surveys, and medical charts were abstracted. Physical activity, fluid intake, and smoking history at baseline were compared with changes in estimated glomerular filtration rate (eGFR) (every 6 months up to 1 year) using bivariate and multivariate regression analysis, while controlling for sociodemographic and clinical transplant variables. Multivariate analyses revealed that greater physical activity was significantly (P < 0.05) associated with improvement in GFR at 6 months; while greater physical activity, absence of smoking history, and nonwhite ethnicity were significant (P < 0.05) predictors of improvement in GFR at 12 months. These results suggest that increasing physical activity levels in kidney recipients may be an effective behavioral measure to help ensure graft functioning. Our findings suggest the need for a randomized controlled trial of exercise, fluid intake, and smoking history on GFR beyond 12 months.

Exploring Raman spectroscopy for the evaluation of glaucomatous retinal changes.

PubMed

Wang, Qi; Grozdanic, Sinisa D; Harper, Matthew M; Hamouche, Nicolas; Kecova, Helga; Lazic, Tatjana; Yu, Chenxu

2011-10-01

Glaucoma is a chronic neurodegenerative disease characterized by apoptosis of retinal ganglion cells and subsequent loss of visual function. Early detection of glaucoma is critical for the prevention of permanent structural damage and irreversible vision loss. Raman spectroscopy is a technique that provides rapid biochemical characterization of tissues in a nondestructive and noninvasive fashion. In this study, we explored the potential of using Raman spectroscopy for detection of glaucomatous changes in vitro. Raman spectroscopic imaging was conducted on retinal tissues of dogs with hereditary glaucoma and healthy control dogs. The Raman spectra were subjected to multivariate discriminant analysis with a support vector machine algorithm, and a classification model was developed to differentiate disease tissues versus healthy tissues. Spectroscopic analysis of 105 retinal ganglion cells (RGCs) from glaucomatous dogs and 267 RGCs from healthy dogs revealed spectroscopic markers that differentiated glaucomatous specimens from healthy controls. Furthermore, the multivariate discriminant model differentiated healthy samples and glaucomatous samples with good accuracy [healthy 89.5% and glaucomatous 97.6% for the same breed (Basset Hounds); and healthy 85.0% and glaucomatous 85.5% for different breeds (Beagles versus Basset Hounds)]. Raman spectroscopic screening can be used for in vitro detection of glaucomatous changes in retinal tissue with a high specificity.

Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariate chemometric analysis

PubMed Central

Myakalwar, Ashwin Kumar; Sreedhar, S.; Barman, Ishan; Dingari, Narahara Chari; Rao, S. Venugopal; Kiran, P. Prem; Tewari, Surya P.; Kumar, G. Manoj

2012-01-01

We report the effectiveness of laser-induced breakdown spectroscopy (LIBS) in probing the content of pharmaceutical tablets and also investigate its feasibility for routine classification. This method is particularly beneficial in applications where its exquisite chemical specificity and suitability for remote and on site characterization significantly improves the speed and accuracy of quality control and assurance process. Our experiments reveal that in addition to the presence of carbon, hydrogen, nitrogen and oxygen, which can be primarily attributed to the active pharmaceutical ingredients, specific inorganic atoms were also present in all the tablets. Initial attempts at classification by a ratiometric approach using oxygen to nitrogen compositional values yielded an optimal value (at 746.83 nm) with the least relative standard deviation but nevertheless failed to provide an acceptable classification. To overcome this bottleneck in the detection process, two chemometric algorithms, i.e. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA), were implemented to exploit the multivariate nature of the LIBS data demonstrating that LIBS has the potential to differentiate and discriminate among pharmaceutical tablets. We report excellent prospective classification accuracy using supervised classification via the SIMCA algorithm, demonstrating its potential for future applications in process analytical technology, especially for fast on-line process control monitoring applications in the pharmaceutical industry. PMID:22099648

Characterization of heavy-metal-contaminated sediment by using unsupervised multivariate techniques and health risk assessment.

PubMed

Wang, Yeuh-Bin; Liu, Chen-Wuing; Wang, Sheng-Wei

2015-03-01

This study characterized the sediment quality of the severely contaminated Erjen River in Taiwan by using multivariate analysis methods-including factor analysis (FA), self-organizing maps (SOMs), and positive matrix factorization (PMF)-and health risk assessment. The SOMs classified the dataset with similar heavy-metal-contaminated sediment into five groups. FA extracted three major factors-traditional electroplating and metal-surface processing factor, nontraditional heavy-metal-industry factor, and natural geological factor-which accounted for 80.8% of the variance. The SOMs and FA revealed the heavy-metal-contaminated-sediment hotspots in the middle and upper reaches of the major tributary in the dry season. The hazardous index value for health risk via ingestion was 0.302. PMF further qualified the source apportionment, indicating that traditional electroplating and metal-surface-processing industries comprised 47% of the health risk posed by heavy-metal-contaminated sediment. Contaminants discharged from traditional electroplating and metal-surface-processing industries in the middle and upper reaches of the major tributary must be eliminated first to improve the sediment quality in Erjen River. The proposed assessment framework for heavy-metal-contaminated sediment can be applied to contaminated-sediment river sites in other regions. Copyright © 2014 Elsevier Inc. All rights reserved.

Factors Predictive Of Alcohol Consumption Among Elderly People In A Rural Community: A Case Study In Phayao Province Thailand.

PubMed

Hongthong, Donnapa; Somrongthong, Ratana; Wongchaiya, Pimpimon; Kumar, Ramesh

2016-01-01

Alcohol consumption is recognized as a public health issue. Study objectives were to identify factors predictive of alcohol consumption among elderly people in Phayao province Thailand, where there was high prevalence of alcohol consumption. This was a cross-sectional study. Four hundred elderly people participated in a survey. Data was collected by face-to-face interviews. Chi-square and multivariate logistic regression were used to determine the factors predictive of alcohol consumption among the study subjects. One thirds of elderly (31.7%) had consumed alcohol in their lifetime, and (15.7%) of them were current drinkers. Following univariate analysis, seven factors included gender, working, sickness, smoking, quality of life (QOL), daily activities and economic recession - were identified as being significantly associated with drinking (p<0.05). Multivariate analysis revealed four factors to be predictive of alcohol among elderly people: gender (OR=6.02, 95% CI=3.58-10.13), smoking (OR=4.34, 95% CI=2.57-7.34), economic recession (OR=2.79, 95%, CI=1.66-4.71), and QOL (OR=1.86, 95%, CI=1.09-3.16). Gender (male) and smoking were strongly predictive factors of elderly alcohol consumption. Hence, an effort to reduce alcohol consumption should be placed on male elderly and those who smoke.

Long-term changes in fish communities of the Ria Formosa coastal lagoon (southern Portugal) based on two studies made 20 years apart

NASA Astrophysics Data System (ADS)

Ribeiro, Joaquim; Monteiro, Carlos C.; Monteiro, Pedro; Bentes, Luis; Coelho, Rui; Gonçalves, Jorge M. S.; Lino, Pedro G.; Erzini, Karim

2008-01-01

Fish communities of the Ria Formosa coastal lagoon (south Portugal) were sampled on a monthly basis with a beach seine at 4 sites, during two different time periods: 1980-1986 and 2001-2002. Community indices, species ranking and multivariate analysis were used in order to identify changes in the fish community between the two time periods. A total of 153,511 fish representing 57 taxa were recorded. Although species composition was very similar for both sampling periods, multivariate analysis performed on annual species abundance in number and weight revealed differences in fish community structure between the two periods. Structural changes in fish community were related mostly to a sharp decrease in the abundance of Mugilidae from 1980-1986 to 2001-2002. These changes were probably associated to a decrease in organic matter contents and nutrients concentrations due to improvements in sewage treatment and better water circulation inside the lagoon. The changes in fish community structure are more evident in the inner areas of the lagoon than near the inlet. The association between changes in sewage patterns and changes in the ichthyofaunal community structure reinforces the importance of fish communities as a biological indicator of human induced changes in marine systems.

Predicting worsening asthma control following the common cold

PubMed Central

Walter, Michael J.; Castro, Mario; Kunselman, Susan J.; Chinchilli, Vernon M; Reno, Melissa; Ramkumar, Thiruvamoor P.; Avila, Pedro C.; Boushey, Homer A.; Ameredes, Bill T.; Bleecker, Eugene R.; Calhoun, William J.; Cherniack, Reuben M.; Craig, Timothy J.; Denlinger, Loren C.; Israel, Elliot; Fahy, John V.; Jarjour, Nizar N.; Kraft, Monica; Lazarus, Stephen C.; Lemanske, Robert F.; Martin, Richard J.; Peters, Stephen P.; Ramsdell, Joe W.; Sorkness, Christine A.; Rand Sutherland, E.; Szefler, Stanley J.; Wasserman, Stephen I.; Wechsler, Michael E.

2008-01-01

The asthmatic response to the common cold is highly variable and early characteristics that predict worsening of asthma control following a cold have not been identified. In this prospective multi-center cohort study of 413 adult subjects with asthma, we used the mini-Asthma Control Questionnaire (mini-ACQ) to quantify changes in asthma control and the Wisconsin Upper Respiratory Symptom Survey-21 (WURSS-21) to measure cold severity. Univariate and multivariable models examined demographic, physiologic, serologic, and cold-related characteristics for their relationship to changes in asthma control following a cold. We observed a clinically significant worsening of asthma control following a cold (increase in mini-ACQ of 0.69 ± 0.93). Univariate analysis demonstrated season, center location, cold length, and cold severity measurements all associated with a change in asthma control. Multivariable analysis of the covariates available within the first 2 days of cold onset revealed the day 2 and the cumulative sum of the day 1 and 2 WURSS-21 scores were significant predictors for the subsequent changes in asthma control. In asthmatic subjects the cold severity measured within the first 2 days can be used to predict subsequent changes in asthma control. This information may help clinicians prevent deterioration in asthma control following a cold. PMID:18768579

A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration.

PubMed

Goovaerts, P; Albuquerque, Teresa; Antunes, Margarida

2016-11-01

This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded the application of traditional interpolation techniques, such as cokriging. The analysis could, however, capitalize on 376 stream sediment samples that were analyzed for twenty two elements. Gold (Au) was first predicted at all 376 locations using linear regression (R 2 =0.798) and four metals (Fe, As, Sn and W), which are known to be mostly associated with the local gold's paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential indicator simulation and a soft indicator coding of regression estimates, to supplement the hard indicator coding of gold measurements. Each simulated map then underwent a local cluster analysis to identify significant aggregates of low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated probability of occurrence. Examining the distribution of the hot-spots and cold-spots reveals a clear enrichment in Au along the Erges River downstream from the old sedimentary mineralization.

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

Safety and effectiveness of olanzapine in monotherapy: a multivariate analysis of a naturalistic study.

PubMed

Ciudad, Antonio; Gutiérrez, Miguel; Cañas, Fernando; Gibert, Juan; Gascón, Josep; Carrasco, José-Luis; Bobes, Julio; Gómez, Juan-Carlos; Alvarez, Enrique

2005-07-01

This study investigated safety and effectiveness of olanzapine in monotherapy compared with conventional antipsychotics in treatment of acute inpatients with schizophrenia. This was a prospective, comparative, nonrandomized, open-label, multisite, observational study of Spanish inpatients with an acute episode of schizophrenia. Data included safety assessments with an extrapyramidal symptoms (EPS) questionnaire and the report of spontaneous adverse events, plus clinical assessments with the Brief Psychiatric Rating Scale (BPRS) and the Clinical Global Impressions-Severity of Illness (CGI-S). A multivariate methodology was used to more adequately determine which factors can influence safety and effectiveness of olanzapine in monotherapy. 339 patients treated with olanzapine in monotherapy (OGm) and 385 patients treated with conventional antipsychotics (CG) were included in the analysis. Treatment-emergent EPS were significantly higher in the CG (p<0.0001). Response rate was significantly higher in the OGm (p=0.005). Logistic regression analyses revealed that the only variable significantly correlated with treatment-emergent EPS and clinical response was treatment strategy, with patients in OGm having 1.5 times the probability of obtaining a clinical response and patients in CG having 5 times the risk of developing EPS. In this naturalistic study olanzapine in monotherapy was better-tolerated and at least as effective as conventional antipsychotics.

The Impact of ART on the Economic Outcomes of People Living with HIV/AIDS.

PubMed

Nannungi, Annet; Wagner, Glenn; Ghosh-Dastidar, Bonnie

2013-01-01

Background. Clinical benefits of ART are well documented, but less is known about its effects on economic outcomes such as work status and income in sub-Saharan Africa. Methods. Data were examined from 482 adult clients entering HIV care (257 starting ART; 225 not yet eligible for ART) in Kampala, Uganda. Self-reported data on work status and income were assessed at baseline, months 6 and 12. Multivariate analysis examined the effects of ART over time, controlling for change in physical health functioning and baseline covariates. Results. Fewer ART patients worked at baseline compared to non-ART patients (25.5% versus 34.2%); 48.8% of those not working at baseline were now working at month 6, and 50% at month 12, with similar improvement in both the ART and non-ART groups. However, multivariate analysis revealed that the ART group experienced greater improvement over time. Average weekly income did not differ between the groups at baseline nor change significantly over time, among those who were working; being male gender and having any secondary education were predictive of higher income. Conclusions. ART was associated with greater improvement in work status, even after controlling for change in physical health functioning, suggesting other factors associated with ART may influence work.

Determinants of outcomes in patients with simple gastroschisis.

PubMed

Youssef, Fouad; Laberge, Jean-Martin; Puligandla, Pramod; Emil, Sherif

2017-05-01

We analyzed the determinants of outcomes in simple gastroschisis (GS) not complicated by intestinal atresia, perforation, or necrosis. All simple GS patients enrolled in a national prospective registry from 2005 to 2013 were studied. Patients below the median for total parenteral nutrition (TPN) duration (26days) and hospital stay (34days) were compared to those above. Univariate and multivariate logistic and linear regression analyses were employed using maternal, patient, postnatal, and treatment variables. Of 700 patients with simple GS, representing 76.8% of all GS patients, 690 (98.6%) survived. TPN was used in 352 (51.6%) and 330 (48.4%) patients for ≤26 and >26days, respectively. Hospital stay for 356 (51.9%) and 330 (48.1%) infants was ≤34 and >34days, respectively. Univariate analysis revealed significant differences in several patient, treatment, and postnatal factors. On multivariate analysis, prenatal sonographic bowel dilation, older age at closure, necrotizing enterocolitis, longer mechanical ventilation, and central-line associated blood stream infection (CLABSI) were independently associated with longer TPN duration and hospital stay, with CLABSI being the strongest predictor. Prenatal bowel dilation is associated with increased morbidity in simple GS. CLABSI is the strongest predictor of outcomes. Bowel matting is not an independent risk factor. 2c. Copyright © 2017 Elsevier Inc. All rights reserved.

Using video and theater to increase knowledge and change attitudes-Why are gorillas important to the world and to Congo?

PubMed

Breuer, Thomas; Mavinga, Franck Barrel; Evans, Ron; Lukas, Kristen E

2017-10-01

Applying environmental education in primate range countries is an important long-term activity to stimulate pro-conservation behavior. Within captive settings, mega-charismatic species, such as great apes are often used to increase knowledge and positively influence attitudes of visitors. Here, we evaluate the effectiveness of a short-term video and theater program developed for a Western audience and adapted to rural people living in two villages around Nouabalé-Ndoki National Park, Republic of Congo. We assessed the knowledge gain and attitude change using oral evaluation in the local language (N = 111). Overall pre-program knowledge about Western gorillas (Gorilla gorilla) was high. Detailed multivariate analysis of pre-program knowledge revealed differences in knowledge between two villages and people with different jobs while attitudes largely were similar between groups. The short-term education program was successful in raising knowledge, particularly of those people with less pre-program knowledge. We also noted an overall significant attitude improvement. Our data indicate short-term education programs are useful in quickly raising knowledge as well improving attitudes. Furthermore, education messages need to be clearly adapted to the daily livelihood realities of the audience, and multi-variate analysis can help to identify potential target groups for education programs. © 2017 Wiley Periodicals, Inc.

Data analysis techniques

NASA Technical Reports Server (NTRS)

Park, Steve

1990-01-01

A large and diverse number of computational techniques are routinely used to process and analyze remotely sensed data. These techniques include: univariate statistics; multivariate statistics; principal component analysis; pattern recognition and classification; other multivariate techniques; geometric correction; registration and resampling; radiometric correction; enhancement; restoration; Fourier analysis; and filtering. Each of these techniques will be considered, in order.

Chemical structure of wood charcoal by infrared spectroscopy and multivariate analysis

Treesearch

Nicole Labbe; David Harper; Timothy Rials; Thomas Elder

2006-01-01

In this work, the effect of temperature on charcoal structure and chemical composition is investigated for four tree species. Wood charcoal carbonized at various temperatures is analyzed by mid infrared spectroscopy coupled with multivariate analysis and by thermogravimetric analysis to characterize the chemical composition during the carbonization process. The...

Circulating interleukin-8 and tumor necrosis factor-α are associated with hot flashes in healthy postmenopausal women.

PubMed

Huang, Wan-Yu; Hsin, I-Lun; Chen, Dar-Ren; Chang, Chia-Chu; Kor, Chew-Teng; Chen, Ting-Yu; Wu, Hung-Ming

2017-01-01

Hot flashes have been postulated to be linked to systemic inflammation. This study aimed to investigate the relationship between hot flashes, pro-inflammatory factors, and leukocytes in healthy, non-obese postmenopausal women. In this cross-sectional study, a total of 202 women aged 45-60 years were stratified into one of four groups according to their hot-flash status: never experienced hot flashes (Group N), mild hot flashes (Group m), moderate hot flashes (Group M), and severe hot flashes (Group S). Variables measured in this study included clinical parameters, hot flash experience, leukocytes, and fasting plasma levels of nine circulating cytokines/chemokines measured by using multiplex assays. Multiple linear regression analysis was used to evaluate the associations of hot flashes with these pro-inflammatory factors. The study was performed in a hospital medical center. The mean values of leukocyte number were not different between these four groups. The hot flash status had a positive tendency toward increased levels of circulating IL-6 (P-trend = 0.049), IL-8 (P-trend < 0.001), TNF-α (P-trend = 0.008), and MIP1β (P-trend = 0.04). Multivariate linear regression analysis revealed that hot-flash severity was significantly associated with IL-8 (P-trend < 0.001) and TNFα (P-trend = 0.007) among these nine cytokines/chemokines after adjustment for age, menopausal duration, BMI and FSH. Multivariate analysis further revealed that severe hot flashes were strongly associated with a higher IL-8 (% difference, 37.19%; 95% confidence interval, 14.98,63.69; P < 0.001) and TNFα (51.27%; 6.64,114.57; P < 0.05). The present study provides evidence that hot flashes are associated with circulating IL-8 and TNF-α in healthy postmenopausal women. It suggests that hot flashes might be related to low-grade systemic inflammation.

Surgery for Infective Endocarditis: Outcomes and Predictors of Mortality in 360 Consecutive Patients

PubMed Central

Farag, Mina; Borst, Tobias; Sabashnikov, Anton; Zeriouh, Mohamed; Schmack, Bastian; Arif, Rawa; Beller, Carsten J.; Popov, Aron-Frederik; Kallenbach, Klaus; Ruhparwar, Arjang; Dohmen, Pascal M.; Szabó, Gábor; Karck, Matthias; Weymann, Alexander

2017-01-01

Background A retrospective analysis was conducted of the early and long-term outcomes after surgery for infective endocarditis (IE). Material/Methods We included 360 patients with IE operated upon between 1993 and 2012. The primary endpoint was overall cumulative postoperative survival at 30 days. Secondary endpoints were early postoperative outcomes and complication rates. Factors associated with 30-day mortality were analyzed. Results Mean age was 58.7±14.7 years and 26.9% (n=97) were female. The mean follow-up was 4.41±4.53 years. Postoperative survival was 81.7% at 30 days, 69.4% at 1 year, 63.3% at 5 years, and 63.3% at 10 years. Non-survivors were significantly older (p=0.014), with higher NYHA Class (p=0.002), had higher rates of preoperative diabetes mellitus (p=0.005), renal failure (p=0.001), and hepatic disease (p=0.002). Furthermore, non-survivors had higher baseline alanine aminotransferase (ALT, p=0.048), aspartate transaminase (AST, p=0.027), bilirubin (p=0.013), white cell count (WCC, p=0.034), and CRP (p=0.049). Factors associated with 30-day mortality were longer duration of surgery, CPB, and aortic cross-clamping times (p<0.001, p<0.001, and p=0.003, respectively), as well as higher RBC, FFP, and platelet transfusion requirements (p<0.001, p=0.005, and p<0.001, respectively). Multivariate logistic regression analysis revealed liver cirrhosis (OR 4.583, 95-CI: 1.096–19.170, p=0.037) and longer CPB time (OR 1.025, 95-CI 1.008–1.042, p=0.004) as independent predictors of 30-day mortality. Conclusions Surgical treatment of IE shows satisfactory early, midterm, and long-term results. Multivariate logistic regression analysis revealed cirrhosis and longer CPB time as independent predictors of 30-day mortality. PMID:28740070

Treatment of salivary gland neoplasms with fast neutron radiotherapy.

PubMed

Douglas, James G; Koh, Wui-jin; Austin-Seymour, Mary; Laramore, George E

2003-09-01

To evaluate the efficacy of fast neutron radiotherapy for the treatment of salivary gland neoplasms. Retrospective analysis. University of Washington Cancer Center, Neutron Facility, Seattle. The medical records of 279 patients treated with curative intent using fast neutron radiotherapy at the University of Washington Cancer Center were reviewed. Of the 279 patients, 263 had evidence of gross residual disease at the time of treatment (16 had no evidence of gross residual disease), 141 had tumors of a major salivary gland, and 138 had tumors of minor salivary glands. The median follow-up period was 36 months (range, 1-142 months). Local-regional control, cause-specific survival, and freedom from metastasis. The 6-year actuarial cause-specific survival rate was 67%. Multivariate analysis revealed that low group stage (I-II) disease, minor salivary sites, lack of skull base invasion, and primary disease were associated with a statistically significant improvement in cause-specific survival. The 6-year actuarial local-regional control rate was 59%. Multivariate analysis revealed size 4 cm or smaller, lack of base of skull invasion, prior surgical resection, and no previous radiotherapy to have a statistically significant improved local-regional control. Sixteen patients without evidence of gross residual disease had a 100% 6-year actuarial local-regional control. The 6-year actuarial freedom from metastasis rate was 64%. Factors associated with decreased development of systemic metastases included negative lymph nodes at the time of treatment and lack of base of skull involvement. The 6-year actuarial rate of development of grade 3 or 4 long-term toxicity (using the Radiation Therapy Oncology Group and European Organization for Research on the Treatment of Cancer criteria) was 10%. No patient experienced grade 5 toxic effects. Neuron radiotherapy is an effective treatment for patients with salivary gland neoplasms who have gross residual disease and achieves excellent local-regional control in patients without evidence of gross disease.

Circulating interleukin-8 and tumor necrosis factor-α are associated with hot flashes in healthy postmenopausal women

PubMed Central

Huang, Wan-Yu; Hsin, I-Lun; Chen, Dar-Ren; Chang, Chia-Chu; Kor, Chew-Teng; Chen, Ting-Yu

2017-01-01

Introduction Hot flashes have been postulated to be linked to systemic inflammation. This study aimed to investigate the relationship between hot flashes, pro-inflammatory factors, and leukocytes in healthy, non-obese postmenopausal women. Participants and design In this cross-sectional study, a total of 202 women aged 45–60 years were stratified into one of four groups according to their hot-flash status: never experienced hot flashes (Group N), mild hot flashes (Group m), moderate hot flashes (Group M), and severe hot flashes (Group S). Variables measured in this study included clinical parameters, hot flash experience, leukocytes, and fasting plasma levels of nine circulating cytokines/chemokines measured by using multiplex assays. Multiple linear regression analysis was used to evaluate the associations of hot flashes with these pro-inflammatory factors. Settings The study was performed in a hospital medical center. Results The mean values of leukocyte number were not different between these four groups. The hot flash status had a positive tendency toward increased levels of circulating IL-6 (P-trend = 0.049), IL-8 (P-trend < 0.001), TNF-α (P-trend = 0.008), and MIP1β (P-trend = 0.04). Multivariate linear regression analysis revealed that hot-flash severity was significantly associated with IL-8 (P-trend < 0.001) and TNFα (P-trend = 0.007) among these nine cytokines/chemokines after adjustment for age, menopausal duration, BMI and FSH. Multivariate analysis further revealed that severe hot flashes were strongly associated with a higher IL-8 (% difference, 37.19%; 95% confidence interval, 14.98,63.69; P < 0.001) and TNFα (51.27%; 6.64,114.57; P < 0.05). Conclusion The present study provides evidence that hot flashes are associated with circulating IL-8 and TNF-α in healthy postmenopausal women. It suggests that hot flashes might be related to low-grade systemic inflammation. PMID:28846735

Socioeconomic and sociocultural determinants of psychological distress and quality of life among patients with psoriasis in a selected multi-ethnic Malaysian population.

PubMed

Kwan, Zhenli; Bong, Yii Bonn; Tan, Leng Leng; Lim, Shu Xian; Yong, Adrian Sze Wai; Ch'ng, Chin Chwen; Tan, Maw Pin; Thevarajah, Suganthi; Ismail, Rokiah

2017-02-01

Patients with psoriasis may have increased risk of psychological comorbidities. This cross-sectional study aimed at determining associations between sociocultural and socioeconomic factors with the Depression Anxiety Stress Scale (DASS) scores and the Dermatology Life Quality Index (DLQI) scores. Adult patients with psoriasis were recruited from a Dermatology outpatient clinic via convenience sampling. Interviews were conducted regarding socio-demographic factors and willing subjects were requested to complete the DASS and DLQI questionnaires. The Pearson χ 2 test, Fisher's exact test and multivariate logistic regression were used for statistical analysis to determine independent predictors of depression, anxiety, stress and severe impairment of quality of life. Unadjusted analysis revealed that depression was associated with Indian ethnicity (p = .041) and severe impairment of quality of life was associated with Indian ethnicity (p = .032), higher education (p = .013), higher income (p = .042), and employment status (p = .014). Multivariate analysis revealed that Indian ethnicity was a predictor of depression (p = .024). For stress, tertiary level of education (p = .020) was an independent risk factor while a higher monthly income was a protective factor (p = .042). The ethnic Indians and Malays were significantly more likely than the ethnic Chinese to suffer reduced quality of life (p = .001 and p = .006 respectively) and subjects with tertiary education were more likely to have severe impairment of quality of life (p = .002). Our study was unique in determining sociocultural influences on psychological complications of psoriasis in a South East Asian population. This has provided invaluable insight into factors predictive of adverse effects of psoriasis on psychological distress and quality of life in our patient population. Future studies should devise interventions to specifically target at risk groups in the development of strategies to reduce morbidity associated with psoriasis.

Multivariate analysis: greater insights into complex systems

USDA-ARS?s Scientific Manuscript database

Many agronomic researchers measure and collect multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate (MV) statistical methods encompass the simultaneous analysis of all random variables (RV) measured on each experimental or sampling ...

Multivariate analysis of progressive thermal desorption coupled gas chromatography-mass spectrometry.

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

Van Benthem, Mark Hilary; Mowry, Curtis Dale; Kotula, Paul Gabriel

Thermal decomposition of poly dimethyl siloxane compounds, Sylgard{reg_sign} 184 and 186, were examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a method of producing multiway data using a stepped thermal desorption. The technique involves sequentially heating a sample of the material of interest with subsequent analysis in a commercial GC/MS system. The decomposition chromatograms were analyzed using multivariate analysis tools including principal component analysis (PCA), factor rotation employing the varimax criterion, and multivariate curve resolution. The results of the analysis show seven components related to offgassing of various fractions of siloxanes that varymore » as a function of temperature. Thermal desorption coupled with gas chromatography-mass spectrometry (TD/GC-MS) is a powerful analytical technique for analyzing chemical mixtures. It has great potential in numerous analytic areas including materials analysis, sports medicine, in the detection of designer drugs; and biological research for metabolomics. Data analysis is complicated, far from automated and can result in high false positive or false negative rates. We have demonstrated a step-wise TD/GC-MS technique that removes more volatile compounds from a sample before extracting the less volatile compounds. This creates an additional dimension of separation before the GC column, while simultaneously generating three-way data. Sandia's proven multivariate analysis methods, when applied to these data, have several advantages over current commercial options. It also has demonstrated potential for success in finding and enabling identification of trace compounds. Several challenges remain, however, including understanding the sources of noise in the data, outlier detection, improving the data pretreatment and analysis methods, developing a software tool for ease of use by the chemist, and demonstrating our belief that this multivariate analysis will enable superior differentiation capabilities. In addition, noise and system artifacts challenge the analysis of GC-MS data collected on lower cost equipment, ubiquitous in commercial laboratories. This research has the potential to affect many areas of analytical chemistry including materials analysis, medical testing, and environmental surveillance. It could also provide a method to measure adsorption parameters for chemical interactions on various surfaces by measuring desorption as a function of temperature for mixtures. We have presented results of a novel method for examining offgas products of a common PDMS material. Our method involves utilizing a stepped TD/GC-MS data acquisition scheme that may be almost totally automated, coupled with multivariate analysis schemes. This method of data generation and analysis can be applied to a number of materials aging and thermal degradation studies.« less

Prospective inverse associations of sex hormone concentrations in men with biomarkers of inflammation and oxidative stress.

PubMed

Haring, Robin; Baumeister, Sebastian E; Völzke, Henry; Dörr, Marcus; Kocher, Thomas; Nauck, Matthias; Wallaschofski, Henri

2012-01-01

The suggested associations between sex hormone concentrations and inflammatory biomarkers in men originate from cross-sectional studies and small-scale clinical trials. But prior studies have not investigated longitudinal associations. Overall, 1344 men aged 20-79 years from the population-based cohort Study of Health in Pomerania were followed up for 5.0 (median) years. We used multivariable regression models to analyze cross-sectional and longitudinal associations of serum sex hormone concentrations (total testosterone [TT], sex hormone-binding globulin [SHBG], calculated free testosterone [free T], and dehydroepiandrosterone sulfate [DHEAS]) with biomarkers of inflammation (fibrinogen, high-sensitive C-reactive protein [hsCRP], and white blood cell count [WBC]) and oxidative stress (γ-glutamyl transferase [GGT]) using ordinary least square regression and generalized estimating equation models, respectively. Cross-sectional models revealed borderline associations of sex hormone concentrations with hsCRP, WBC, and GGT levels that were not retained after multivariable adjustment. Longitudinal multivariable analyses revealed an inverse association of baseline TT, free T, and DHEAS concentrations with change in fibrinogen levels (per SD decrement in TT, 0.25 [95% confidence interval, 0.04-0.45]; in free T, 0.30 [0.09-0.51]; and in DHEAS, 0.23 [0.11-0.36]). Furthermore, baseline DHEAS concentrations were inversely associated with change in WBC levels (per SD decrement, 0.53 [0.24-0.82]). Baseline TT, SHBG, free T, and DHEAS concentrations were also inversely associated with change in GGT after multivariable adjustment. The present study is the first to demonstrate prospective inverse associations between sex hormone concentrations and markers of inflammation and oxidative stress in men. Additional studies are warranted to elucidate potential mechanisms underlying the revealed associations.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

Olejarczyk, Elzbieta; Marzetti, Laura; Pizzella, Vittorio; Zappasodi, Filippo

2017-06-01

Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

Combined Metabolomic Analysis of Plasma and Urine Reveals AHBA, Tryptophan and Serotonin Metabolism as Potential Risk Factors in Gestational Diabetes Mellitus (GDM)

PubMed Central

Leitner, Miriam; Fragner, Lena; Danner, Sarah; Holeschofsky, Nastassja; Leitner, Karoline; Tischler, Sonja; Doerfler, Hannes; Bachmann, Gert; Sun, Xiaoliang; Jaeger, Walter; Kautzky-Willer, Alexandra; Weckwerth, Wolfram

2017-01-01

Gestational diabetes mellitus during pregnancy has severe implications for the health of the mother and the fetus. Therefore, early prediction and an understanding of the physiology are an important part of prenatal care. Metabolite profiling is a long established method for the analysis and prediction of metabolic diseases. Here, we applied untargeted and targeted metabolomic protocols to analyze plasma and urine samples of pregnant women with and without GDM. Univariate and multivariate statistical analyses of metabolomic profiles revealed markers such as 2-hydroxybutanoic acid (AHBA), 3-hydroxybutanoic acid (BHBA), amino acids valine and alanine, the glucose-alanine-cycle, but also plant-derived compounds like sitosterin as different between control and GDM patients. PLS-DA and VIP analysis revealed tryptophan as a strong variable separating control and GDM. As tryptophan is biotransformed to serotonin we hypothesized whether serotonin metabolism might also be altered in GDM. To test this hypothesis we applied a method for the analysis of serotonin, metabolic intermediates and dopamine in urine by stable isotope dilution direct infusion electrospray ionization mass spectrometry (SID-MS). Indeed, serotonin and related metabolites differ significantly between control and GDM patients confirming the involvement of serotonin metabolism in GDM. Clustered correlation coefficient visualization of metabolite correlation networks revealed the different metabolic signatures between control and GDM patients. Eventually, the combination of selected blood plasma and urine sample metabolites improved the AUC prediction accuracy to 0.99. The detected GDM candidate biomarkers and the related systemic metabolic signatures are discussed in their pathophysiological context. Further studies with larger cohorts are necessary to underpin these observations. PMID:29312952

Insights to Galaxy Evolution Utilizing a Multivariate Comparison of Circumgalactic OVI and MgII

NASA Astrophysics Data System (ADS)

Lewis, James; Churchill, Christopher; Nielsen, Nikole; Kacprzak, Glenn; Muzahid, Sowgat; Charlton, Jane

2018-01-01

We present a promising multivariate method to categorize inter-related astronomical data in meaningful ways. We use data from the MAGIICAT and "Multiphase Galaxy Halos" surveys and limit our sample to those galaxies which are imaged with the Hubble Space Telescope and for which the Circumgalactic Medium (CGM) is measured using high-resolution quasar spectra (HIRES/COS). Utilizing the method to categorize data about the CGM and its host galaxy yields distinct categories of CGM-galaxy pairs that imply a common fate for the outflows of MgII and OVI in redder galaxies. The analysis reveals a lack of circumgalactic OVI in lower mass, bluer (younger) galaxies, and that as the blue galaxies gain mass and age along the green valley strong OVI appears in the CGM predominately along the minor axes. But as the galaxies continue to gain mass and age into the red sequence strong OVI gas is found primarily along the major axes. Furthermore, we find a population of low mass red galaxies in which only weak, uniform, circumgalactic OVI is found. Incorporating our multivariate results for circumgalactic MgII, including evidence for quenching of star formation via weak circumgalactic MgII preferentially found along the minor axes of redder galaxies, and invoking the similarity of OVI column densities and kinematic spreads along the major and minor axes, we infer that OVI is ancient gas in the CGM.

Correlates of opium use: retrospective analysis of a survey of tribal communities in Arunachal Pradesh, India

PubMed Central

2013-01-01

Background Household survey data of Changlang district, Arunachal Pradesh, were used in the present study to assess the prevalence of opium use among different tribes, and to examine the association between sociodemographic factors and opium use. Methods A sample of 3421 individuals (1795 men and 1626 women) aged 15 years and older was analyzed using a multivariate logistic regression model to determine factors associated with opium use. Sociodemographic information such as age, education, occupation, religion, ethnicity and marital status were included in the analysis. Results The prevalence of opium use was significantly higher (10.6%) among men than among women (2.1%). It varied according to age, educational level, occupation, marital status and religion of the respondents. In both sexes, opium use was significantly higher among Singpho and Khamti tribes compared with other tribes. Multivariate logistic regression indicated that opium use was significantly associated with age, occupation, ethnicity, religion and marital status of the respondents of both sexes. Multivariate rate ratios (MRR) for opium use were significantly higher (4–6 times) among older age groups (≥35 years) and male respondents. In males, the MRR was also significantly higher in respondents of Buddhist and Indigenous religion, while in females, the MRR was significantly higher in Buddhists. Most of the female opium users had taken opium for more than 5 years and were introduced to it by their husbands after marriage. Use of other substances among opium users comprised mainly tobacco (76%) and alcohol (44%). Conclusions The study reveals the sociodemographic factors, such as age, sex, ethnicity, religion and occupation, which are associated with opium use. Such information is useful for institution of intervention measures to reduce opium use. PMID:23575143

Energy Drink and Alcohol mixed Energy Drink use among high school adolescents: Association with risk taking behavior, social characteristics.

PubMed

Scalese, Marco; Denoth, Francesca; Siciliano, Valeria; Bastiani, Luca; Cotichini, Rodolfo; Cutilli, Arianna; Molinaro, Sabrina

2017-09-01

The aims of the study were to: a) examine the prevalence of energy drink (ED) and alcohol mixed with energy drink (AmED) consumption; b) investigate the relationships between ED and AmED with alcohol, binge drinking and drugs accounting for at risk behaviors among a representative sample of Italian adolescents. A representative sample of 30,588 Italian high school students, aged 15-19years, was studied. Binary and multivariate logistic regression analyses were performed to determine the independent association of the potential predictors' characteristics with the ED and AmED drinking during the last year. Respectively 41.4% and 23.2% of respondents reported drinking EDs and AmEDs in the last year. Multivariate analysis revealed that consumption of EDs and AmEDs during the last year were significantly associated with daily smoking, binge drinking, use of cannabis and other psychotropic drugs. Among life habits and risky behaviors the following were positively associated: going out with friends for fun, participating in sports, experiencing physical fights/accidents or injury, engaging in sexual intercourse without protection and being involved in accidents while driving. This study demonstrates the popularity of ED and AmED consumption among the Italian school population aged 15-19years old: 4 out of 10 students consumed EDs in the last year and 2 out of 10 AmED. Multivariate analysis highlighted the association with illicit drug consumption and harming behaviors, confirming that consumption of EDs and AmEDs is a compelling issue especially during adolescence, as it can effect health as well as risk taking behaviors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Leuconostoc strains isolated from dairy products: Response against food stress conditions.

PubMed

D'Angelo, Luisa; Cicotello, Joaquín; Zago, Miriam; Guglielmotti, Daniela; Quiberoni, Andrea; Suárez, Viviana

2017-09-01

A systematic study about the intrinsic resistance of 29 strains (26 autochthonous and 3 commercial ones), belonging to Leuconostoc genus, against diverse stress factors (thermal, acidic, alkaline, osmotic and oxidative) commonly present at industrial or conservation processes were evaluated. Exhaustive result processing was made by applying one-way ANOVA, Student's test (t), multivariate analysis by Principal Component Analysis (PCA) and Matrix Hierarchical Cluster Analysis. In addition, heat adaptation on 4 strains carefully selected based on previous data analysis was assayed. The strains revealed wide diversity of resistance to stress factors and, in general, a clear relationship between resistance and Leuconostoc species was established. In this sense, the highest resistance was shown by Leuconostoc lactis followed by Leuconostoc mesenteroides strains, while Leuconostoc pseudomesenteroides and Leuconostoc citreum strains revealed the lowest resistance to the stress factors applied. Heat adaptation improved thermal cell survival and resulted in a cross-resistance against the acidic factor. However, all adapted cells showed diminished their oxidative resistance. According to our knowledge, this is the first study regarding response of Leuconostoc strains against technological stress factors and could establish the basis for the selection of "more robust" strains and propose the possibility of improving their performance during industrial processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters.

PubMed

de Menezes, Alexandre B; Prendergast-Miller, Miranda T; Richardson, Alan E; Toscas, Peter; Farrell, Mark; Macdonald, Lynne M; Baker, Geoff; Wark, Tim; Thrall, Peter H

2015-08-01

Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co-correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of Landsat digital data. [mapping of hydrothermally altered volcanic rocks

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed using Johnson's HICLUS program. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

Combined DNA methylation and gene expression profiling in gastrointestinal stromal tumors reveals hypomethylation of SPP1 as an independent prognostic factor.

PubMed

Haller, Florian; Zhang, Jitao David; Moskalev, Evgeny A; Braun, Alexander; Otto, Claudia; Geddert, Helene; Riazalhosseini, Yasser; Ward, Aoife; Balwierz, Aleksandra; Schaefer, Inga-Marie; Cameron, Silke; Ghadimi, B Michael; Agaimy, Abbas; Fletcher, Jonathan A; Hoheisel, Jörg; Hartmann, Arndt; Werner, Martin; Wiemann, Stefan; Sahin, Ozgür

2015-03-01

Gastrointestinal stromal tumors (GISTs) have distinct gene expression patterns according to localization, genotype and aggressiveness. DNA methylation at CpG dinucleotides is an important mechanism for regulation of gene expression. We performed targeted DNA methylation analysis of 1.505 CpG loci in 807 cancer-related genes in a cohort of 76 GISTs, combined with genome-wide mRNA expression analysis in 22 GISTs, to identify signatures associated with clinicopathological parameters and prognosis. Principal component analysis revealed distinct DNA methylation patterns associated with anatomical localization, genotype, mitotic counts and clinical follow-up. Methylation of a single CpG dinucleotide in the non-CpG island promoter of SPP1 was significantly correlated with shorter disease-free survival. Hypomethylation of this CpG was an independent prognostic parameter in a multivariate analysis compared to anatomical localization, genotype, tumor size and mitotic counts in a cohort of 141 GISTs with clinical follow-up. The epigenetic regulation of SPP1 was confirmed in vitro, and the functional impact of SPP1 protein on tumorigenesis-related signaling pathways was demonstrated. In summary, SPP1 promoter methylation is a novel and independent prognostic parameter in GISTs, and might be helpful in estimating the aggressiveness of GISTs from the intermediate-risk category. © 2014 UICC.

MULTIVARIATE CURVE RESOLUTION OF NMR SPECTROSCOPY METABONOMIC DATA

EPA Science Inventory

Sandia National Laboratories is working with the EPA to evaluate and develop mathematical tools for analysis of the collected NMR spectroscopy data. Initially, we have focused on the use of Multivariate Curve Resolution (MCR) also known as molecular factor analysis (MFA), a tech...

New evidence for involvement of ESR1 gene in susceptibility to Chinese migraine.

PubMed

An, Xingkai; Fang, Jie; Lin, Qing; Lu, Congxia; Ma, Qilin; Qu, Hongli

2017-01-01

Migraine is a common and disabling nervous system disease with a significant genetic predisposition. The sex hormones play an important role in the pathogenesis of migraine. However, the conclusions of the previous genetic relation studies are conflicting. The aim of this study is to determine whether variants in genes involved in estrogen receptor and estrogen hormone metabolism are related to Chinese migraine. By employing a case-control approach, 8 SNPs in the ESR1, ESR2, and CYP19A1 genes are studied in a cohort of 494 migraine cases and 533 controls. In addition, genotyping is performed using Sequenom MALDI-TOF mass spectrometry iPLEX platform. Univariate and multivariate analyses are carried out by logistic regression. The corresponding haplotypes are studied with the Haploview software and gene-gene interaction is assessed using the Generalized Multifactor Dimensionality Reduction (GMDR) analysis. There are significant differences in allelic distributions for rs2234693 and rs9340799 in ESR1 gene between patients with migraine and control subjects. Univariate logistic analysis shows that rs2234693 and rs9340799 are risk factors for migraine, but multivariate analysis reveals that only rs2234693 is significant associated with migraine. In the subgroup analysis, rs2234693 in ESR1 gene is found associated with menstrually related migraine. Further haplotypic analysis shows that rs2234693-rs9340799 TA haplotype serves as risk haplotype for migraine. The GMDR analysis identifies rs2234693 in ESR1 alone to be a crucial candidate in migraine susceptibility. This study is in agreement with the previous studies that variants in the ESR1 gene are associated with migraine suggesting that it plays a role in the migraine process.

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Metabolomics Reveals that Momordica charantia Attenuates Metabolic Changes in Experimental Obesity.

PubMed

Gong, Zhi-Gang; Zhang, Jianbing; Xu, Yong-Jiang

2017-02-01

Momordica charantia L., also known as bitter melon, has been shown to ameliorate obesity and insulin resistance. However, metabolic changes regulated by M. charantia in obesity are not clearly understood. In this study, serums obtained from obese and M. charantia-treated mice were analyzed by using gas and liquid chromatography-mass spectrometry, and multivariate statistical analysis was performed by Orthogonal partial least squares discriminant analysis. The results from this study indicated that body weight fat and insulin levels of obese mice are dramatically suppressed by 8 weeks of dietary supplementation of M. charantia. Metabolomic data revealed that overproductions of energy and nutrient metabolism in obese mice were restored by M. charantia treatment. The antiinflammatory and inhibition of insulin resistance effect of M. charantia in obesity was illustrated with the restoration of free fatty acids and eicosanoids. The findings achieved in this study further strengthen the therapeutic value of using M. charantia to treat obesity. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Differential Adjustment Among Rural Adolescents Exposed to Family Violence.

PubMed

Sianko, Natallia; Hedge, Jasmine M; McDonell, James R

2016-04-22

This study examines differences in psychological adjustment in a sample of rural adolescents who have been exposed to family violence. Self-report questionnaires were administered to 580 adolescents and their primary caregivers. The results revealed that over two thirds of the study participants (68.8%) had been exposed to violence in their families. As hypothesized, cluster analysis identified several profiles among adolescents, distinguished by their psychological and emotional functioning: well adjusted (46.2%), moderately adjusted (44.3%), and struggling (9.5%). Discriminant function analysis confirmed the groupings and revealed that family functioning was among the most influential factors explaining adjustment differences. Multivariate analyses of variance (MANOVAs) further showed that adolescents from each of the three adjustment profiles reported significantly different levels of family social support, parental involvement, and perceived neighborhood safety. Overall, the results confirm heterogeneity of adolescent adaptation in the aftermath of family violence and provide insights into family and neighborhood factors that account for variability in adolescents' reactions to violence. Implications for future research and practical interventions are discussed. © The Author(s) 2016.

Risk Assessment of Heavy Metals Pollution in Agricultural Soils of Siling Reservoir Watershed in Zhejiang Province, China

PubMed Central

Naveedullah; Hashmi, Muhammad Zaffar; Yu, Chunna; Shen, Hui; Duan, Dechao; Lou, Liping; Chen, Yingxu

2013-01-01

Presence of heavy metals in agriculture soils above the permissible limit poses threats to public health. In this study, concentrations of seven metals were determined in agricultural soils from Yuhang county, Zhejiang, China. Multivariate statistical approaches were used to study the variation of metals in soils during summer and winter seasons. Contamination of soils was evaluated on the basis of enrichment factor (EF), geoaccumulation index (I geo), contamination factor (C f), and degree of contamination (C deg). Heavy metal concentrations were observed higher in winter as compared to summer season. Cr and Cd revealed random distribution with diverse correlations in both seasons. Principal component analysis and cluster analysis showed significant anthropogenic intrusions of Zn, Cd, Pb, Cr, and Cu in the soils. Enrichment factor revealed significant enrichment (EF > 5) of Zn, Cd, and Pb, whereas geoaccumulation index and contamination factor exhibited moderate to high contamination for Zn, Cr, Cd, and Pb. In light of the studied parameters, permissible limit to very high degree of contamination (C deg > 16) was observed in both seasons. PMID:24151611

Virtual surgical planning in endoscopic skull base surgery.

PubMed

Haerle, Stephan K; Daly, Michael J; Chan, Harley H L; Vescan, Allan; Kucharczyk, Walter; Irish, Jonathan C

2013-12-01

Skull base surgery (SBS) involves operative tasks in close proximity to critical structures in a complex three-dimensional (3D) anatomy. The aim was to investigate the value of virtual planning (VP) based on preoperative magnetic resonance imaging (MRI) for surgical planning in SBS and to compare the effects of virtual planning with 3D contours between the expert and the surgeon in training. Retrospective analysis. Twelve patients with manually segmented anatomical structures based on preoperative MRI were evaluated by eight surgeons in a randomized order using a validated National Aeronautics and Space Administration Task Load Index (NASA-TLX) questionnaire. Multivariate analysis revealed significant reduction of workload when using VP (P<.0001) compared to standard planning. Further, it showed that the experience level of the surgeon had a significant effect on the NASA-TLX differences (P<.05). Additional subanalysis did not reveal any significant findings regarding which type of surgeon benefits the most (P>.05). Preoperative anatomical segmentation with virtual surgical planning using contours in endoscopic SBS significantly reduces the workload for the expert and the surgeon in training. Copyright © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

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

Students' perceptions of the interprofessional team in practice through the application of servant leadership principles.

PubMed

Neill, Mark; Hayward, Karen S; Peterson, Teri

2007-08-01

This study examined students' perceptions of interprofessional practice within a framework of servant leadership principles, applied in the care of rural older adults utilizing a service learning model. Mobile wellness services were provided through the Idaho State University Senior Health Mobile project in a collaborative team approach in the community-based setting. Students from varied health professional programs were placed in teams for the provision of wellness care, with communication among team members facilitated by a health professions faculty member serving as field coordinator. The Interdisciplinary Education Perception Scale (IEPS) was used to measure students' perceptions of interprofessional practice using a pretest post-test research design. Multivariate analysis was performed revealing a significant pretest to post-test effect on students' perceptions as measured by factors inherent in the IEPS and deemed essential to effective interprofessional practice. Univariate analysis revealed a significant change in students' perception of professional competence and autonomy, actual cooperation and resource sharing within and across professions, and an understanding of the value and contributions of other professionals from pretest to post-test.

Multivariate functions for predicting the sorption of 2,4,6-trinitrotoluene (TNT) and 1,3,5-trinitro-1,3,5-tricyclohexane (RDX) among taxonomically distinct soils.

PubMed

Katseanes, Chelsea K; Chappell, Mark A; Hopkins, Bryan G; Durham, Brian D; Price, Cynthia L; Porter, Beth E; Miller, Lesley F

2016-11-01

After nearly a century of use in numerous munition platforms, TNT and RDX contamination has turned up largely in the environment due to ammunition manufacturing or as part of releases from low-order detonations during training activities. Although the basic knowledge governing the environmental fate of TNT and RDX are known, accurate predictions of TNT and RDX persistence in soil remain elusive, particularly given the universal heterogeneity of pedomorphic soil types. In this work, we proposed a new solution for modeling the sorption and persistence of these munition constituents as multivariate mathematical functions correlating soil attribute data over a variety of taxonomically distinct soil types to contaminant behavior, instead of a single constant or parameter of a specific absolute value. To test this idea, we conducted experiments measuring the sorption of TNT and RDX on taxonomically different soil types that were extensively physical and chemically characterized. Statistical decomposition of the log-transformed, and auto-scaled soil characterization data using the dimension-reduction technique PCA (principal component analysis) revealed a strong latent structure based in the multiple pairwise correlations among the soil properties. TNT and RDX sorption partitioning coefficients (KD-TNT and KD-RDX) were regressed against this latent structure using partial least squares regression (PLSR), generating a 3-factor, multivariate linear functions. Here, PLSR models predicted KD-TNT and KD-RDX values based on attributes contributing to endogenous alkaline/calcareous and soil fertility criteria, respectively, exhibited among the different soil types: We hypothesized that the latent structure arising from the strong covariance of full multivariate geochemical matrix describing taxonomically distinguished soil types may provide the means for potentially predicting complex phenomena in soils. The development of predictive multivariate models tuned to a local soil's taxonomic designation would have direct benefit to military range managers seeking to anticipate the environmental risks of training activities on impact sites. Published by Elsevier Ltd.

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

PubMed

Hurtado Rúa, Sandra M; Mazumdar, Madhu; Strawderman, Robert L

2015-12-30

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

PubMed Central

Hebart, Martin N.; Görgen, Kai; Haynes, John-Dylan

2015-01-01

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns. PMID:25610393

Obstetric attending physician characteristics and their impact on vacuum and forceps delivery rates: University of California at San Francisco experience from 1977 to 1999.

PubMed

Chang, Anne Lynn S; Noah, Melinda Scully; Laros, Russell K

2002-06-01

The objective of our study was to determine the impact of obstetric attending physician characteristics (eg, region of previous residency training, sex, year of graduation from residency) on the rates of vacuum and forceps delivery at our institution. The analysis was based on 19,897 vaginal deliveries that were performed by 171 attending physicians and 160 resident physicians between 1977 and 1999 at the University of California at San Francisco Medical Center. Z -tests and multivariate logistic regression were performed on a perinatal database that contained standard obstetric variables. Male attending physicians had a higher percentage of forceps deliveries compared with female attending physicians (11.1% vs 6.6%; P <.001); female attending physicians had a higher percentage of vacuum deliveries compared with male attending physicians (9.8% vs 5.1%; P <.001). However, multivariate regression analysis revealed that only the year in which the procedure was performed affected both the forceps and vacuum delivery rates (P <.041). The region of previous residency training of the attending physician affected the vacuum delivery rate (P <.0001) but not the forceps delivery rate (P >.06) in multivariate logistic regression analysis. Factors such as the sex of the obstetric attending physician, the sex of the resident, and the year of graduation from residency for the obstetric attending physician did not have a significant impact on the forceps or vacuum delivery rates (all P >.05). Our study is the first to report that the apparent gender differences in forceps and vacuum delivery rates among obstetric attending physicians was due to the year in which the procedure was performed and not due to sex per se. We also found that the region of previous residency training for the obstetric attending physician significantly influenced the vacuum delivery rate.

Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City.

PubMed

Chau, Tang-Tat; Wang, Kuo-Ying

2016-01-01

An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007-2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0-15 years old). Middle-aged people (16-65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8-1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place.

Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City

PubMed Central

Chau, Tang-Tat; Wang, Kuo-Ying

2016-01-01

An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007–2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0–15 years old). Middle-aged people (16–65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8–1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place. PMID:26815039

Vitamin-A deficiency and its determinants among preschool children: a community based cross-sectional study in Ethiopia.

PubMed

Tariku, Amare; Fekadu, Abel; Ferede, Ayanaw Tsega; Mekonnen Abebe, Solomon; Adane, Akilew Awoke

2016-06-24

Vitamin A deficiency is the leading cause of preventable visual impairments in children. It is also an underlying cause for nearly one-fourth of global child mortality associated with measles, diarrhea, and malaria. The limited literature available in Ethiopia shows severe public health significance of vitamin-A deficiency. Hence the aim of the current study was to assess the prevalence and factors determining vitamin-A deficiency among preschool children in Dembia District, northwest Ethiopia. A community-based cross-sectional study was conducted among preschool children of Dembia District from January to February, 2015. A multi-stage sampling, followed by a systematic sampling technique was employed to select study participants. A structured interviewer-administered questionnaire was used to collect data. Using a binary logistic regression model, multivariable analysis was fitted to identify the associated factors of vitamin-A deficiency. The adjusted odds ratio (AOR) with a 95 % confidence interval was computed to assess the strength of the association, and variables with a p value of <0.05 in multivariable analysis were considered as statistically significant. Six hundred eighty-one preschool children were included in the study, giving a response rate of 96.5 %. The overall prevalence of xerophthalmia was 8.6 %. The result of the multivariable analysis revealed that nonattendance at the antenatal care clinic [AOR 2.65,95 % CI (1.39,5.07)], being male [AOR 1.81, 95 % CI (1.01,3.24)], and in the age group of 49-59 months [AOR 3.00, 95 % CI (1.49,6.02)] were significantly associated with vitamin-A deficiency. Vitamin-A deficiency is a severe public health problem in the study area. Further strengthening antenatal care utilization and giving emphasis to preschool children will help to mitigate vitamin-A deficiency in the study area.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis.

PubMed

Flores, X; Comas, J; Roda, I R; Jiménez, L; Gernaey, K V

2007-01-01

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

Science Learning Outcomes in Alignment with Learning Environment Preferences

NASA Astrophysics Data System (ADS)

Chang, Chun-Yen; Hsiao, Chien-Hua; Chang, Yueh-Hsia

2011-04-01

This study investigated students' learning environment preferences and compared the relative effectiveness of instructional approaches on students' learning outcomes in achievement and attitude among 10th grade earth science classes in Taiwan. Data collection instruments include the Earth Science Classroom Learning Environment Inventory and Earth Science Learning Outcomes Inventory. The results showed that most students preferred learning in a classroom environment where student-centered and teacher-centered instructional approaches coexisted over a teacher-centered learning environment. A multivariate analysis of covariance also revealed that the STBIM students' cognitive achievement and attitude toward earth science were enhanced when the learning environment was congruent with their learning environment preference.

Sleep and nutritional deprivation and performance of house officers.

PubMed

Hawkins, M R; Vichick, D A; Silsby, H D; Kruzich, D J; Butler, R

1985-07-01

A study was conducted by the authors to compare cognitive functioning in acutely and chronically sleep-deprived house officers. A multivariate analysis of variance revealed significant deficits in primary mental tasks involving basic rote memory, language, and numeric skills as well as in tasks requiring high-order cognitive functioning and traditional intellective abilities. These deficits existed only for the acutely sleep-deprived group. The finding of deficits in individuals who reported five hours or less of sleep in a 24-hour period suggests that the minimum standard of four hours that has been considered by some to be adequate for satisfactory performance may be insufficient for more complex cognitive functioning.

Arsenic distribution and valence state variation studied by fast hierarchical length-scale morphological, compositional, and speciation imaging at the Nanoscopium, Synchrotron Soleil

NASA Astrophysics Data System (ADS)

Somogyi, Andrea; Medjoubi, Kadda; Sancho-Tomas, Maria; Visscher, P. T.; Baranton, Gil; Philippot, Pascal

2017-09-01

The understanding of real complex geological, environmental and geo-biological processes depends increasingly on in-depth non-invasive study of chemical composition and morphology. In this paper we used scanning hard X-ray nanoprobe techniques in order to study the elemental composition, morphology and As speciation in complex highly heterogeneous geological samples. Multivariate statistical analytical techniques, such as principal component analysis and clustering were used for data interpretation. These measurements revealed the quantitative and valance state inhomogeneity of As and its relation to the total compositional and morphological variation of the sample at sub-μm scales.

Metabolomics reveals mycoplasma contamination interferes with the metabolism of PANC-1 cells.

PubMed

Yu, Tao; Wang, Yongtao; Zhang, Huizhen; Johnson, Caroline H; Jiang, Yiming; Li, Xiangjun; Wu, Zeming; Liu, Tian; Krausz, Kristopher W; Yu, Aiming; Gonzalez, Frank J; Huang, Min; Bi, Huichang

2016-06-01

Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells.

Moving beyond Univariate Post-Hoc Testing in Exercise Science: A Primer on Descriptive Discriminate Analysis

ERIC Educational Resources Information Center

Barton, Mitch; Yeatts, Paul E.; Henson, Robin K.; Martin, Scott B.

2016-01-01

There has been a recent call to improve data reporting in kinesiology journals, including the appropriate use of univariate and multivariate analysis techniques. For example, a multivariate analysis of variance (MANOVA) with univariate post hocs and a Bonferroni correction is frequently used to investigate group differences on multiple dependent…

Understanding exercise behavior among Korean adults: a test of the transtheoretical model.

PubMed

Kim, YoungHo; Cardinal, Bradley J; Lee, JongYoung

2006-01-01

The purpose of this study was to examine the theorized association of Transtheoretical Model (TTM) of behavior change constructs by stage of change for exercise behavior among Korean adults. A total of 1,335 Korean adults were recruited and surveyed from the Nowon district, geographically located in northern Seoul. Four Korean-version questionnaires were used to identify the stage of exercise behavior and psychological attributes of adolescents. Data were analyzed by frequency analysis, MANOVA, correlation analysis, and discriminant analysis. Multivariate F tests indicated that behavioral and cognitive processes of change, exercise efficacy, and pros differentiated participants across the stages of exercise behavior. Furthermore, the findings revealed that adults' exercise behavior was significantly correlated with the TTM constructs and that overall classification accuracy across the stages of change was 50.6%. This study supports the internal and external validity of the TTM for explaining exercise behavior.

Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging.

PubMed

Bilenko, Natalia Y; Gallant, Jack L

2016-01-01

In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.

Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging

PubMed Central

Bilenko, Natalia Y.; Gallant, Jack L.

2016-01-01

In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model. PMID:27920675

Comprehensive NMR analysis of compositional changes of black garlic during thermal processing.

PubMed

Liang, Tingfu; Wei, Feifei; Lu, Yi; Kodani, Yoshinori; Nakada, Mitsuhiko; Miyakawa, Takuya; Tanokura, Masaru

2015-01-21

Black garlic is a processed food product obtained by subjecting whole raw garlic to thermal processing that causes chemical reactions, such as the Maillard reaction, which change the composition of the garlic. In this paper, we report a nuclear magnetic resonance (NMR)-based comprehensive analysis of raw garlic and black garlic extracts to determine the compositional changes resulting from thermal processing. (1)H NMR spectra with a detailed signal assignment showed that 38 components were altered by thermal processing of raw garlic. For example, the contents of 11 l-amino acids increased during the first step of thermal processing over 5 days and then decreased. Multivariate data analysis revealed changes in the contents of fructose, glucose, acetic acid, formic acid, pyroglutamic acid, cycloalliin, and 5-(hydroxymethyl)furfural (5-HMF). Our results provide comprehensive information on changes in NMR-detectable components during thermal processing of whole garlic.

Untargeted Identification of Wood Type-Specific Markers in Particulate Matter from Wood Combustion.

PubMed

Weggler, Benedikt A; Ly-Verdu, Saray; Jennerwein, Maximilian; Sippula, Olli; Reda, Ahmed A; Orasche, Jürgen; Gröger, Thomas; Jokiniemi, Jorma; Zimmermann, Ralf

2016-09-20

Residential wood combustion emissions are one of the major global sources of particulate and gaseous organic pollutants. However, the detailed chemical compositions of these emissions are poorly characterized due to their highly complex molecular compositions, nonideal combustion conditions, and sample preparation steps. In this study, the particulate organic emissions from a masonry heater using three types of wood logs, namely, beech, birch, and spruce, were chemically characterized using thermal desorption in situ derivatization coupled to a GCxGC-ToF/MS system. Untargeted data analyses were performed using the comprehensive measurements. Univariate and multivariate chemometric tools, such as analysis of variance (ANOVA), principal component analysis (PCA), and ANOVA simultaneous component analysis (ASCA), were used to reduce the data to highly significant and wood type-specific features. This study reveals substances not previously considered in the literature as meaningful markers for differentiation among wood types.

NMR-based metabolomic analysis of spatial variation in soft corals.

PubMed

He, Qing; Sun, Ruiqi; Liu, Huijuan; Geng, Zhufeng; Chen, Dawei; Li, Yinping; Han, Jiao; Lin, Wenhan; Du, Shushan; Deng, Zhiwei

2014-03-28

Soft corals are common marine organisms that inhabit tropical and subtropical oceans. They are shown to be rich source of secondary metabolites with biological activities. In this work, soft corals from two geographical locations were investigated using ¹H-NMR spectroscopy coupled with multivariate statistical analysis at the metabolic level. A partial least-squares discriminant analysis showed clear separation among extracts of soft corals grown in Sanya Bay and Weizhou Island. The specific markers that contributed to discrimination between soft corals in two origins belonged to terpenes, sterols and N-containing compounds. The satisfied precision of classification obtained indicates this approach using combined ¹H-NMR and chemometrics is effective to discriminate soft corals collected in different geographical locations. The results revealed that metabolites of soft corals evidently depended on living environmental condition, which would provide valuable information for further relevant coastal marine environment evaluation.

Multi-element fingerprinting as a tool in origin authentication of four east China marine species.

PubMed

Guo, Lipan; Gong, Like; Yu, Yanlei; Zhang, Hong

2013-12-01

The contents of 25 elements in 4 types of commercial marine species from the East China Sea were determined by inductively coupled plasma mass spectrometry and atomic absorption spectrometry. The elemental composition was used to differentiate marine species according to geographical origin by multivariate statistical analysis. The results showed that principal component analysis could distinguish samples from different areas and reveal the elements which played the most important role in origin diversity. The established models by partial least squares discriminant analysis (PLS-DA) and by probabilistic neural network (PNN) can both precisely predict the origin of the marine species. Further study indicated that PLS-DA and PNN were efficacious in regional discrimination. The models from these 2 statistical methods, with an accuracy of 97.92% and 100%, respectively, could both distinguish samples from different areas without the need for species differentiation. © 2013 Institute of Food Technologists®

A combined planning and self-efficacy intervention to promote physical activity: a multiple mediation analysis.

PubMed

Koring, Milena; Richert, Jana; Parschau, Linda; Ernsting, Anna; Lippke, Sonia; Schwarzer, Ralf

2012-01-01

Many individuals are motivated to improve their physical activity levels, but often fail to act upon their intention. Interventions fostering volitional strategies, such as action planning, coping planning, and self-efficacy beliefs, can help to translate intentions into behavior. This study examines the effectiveness and the mechanisms of a combined planning and self-efficacy intervention to promote physical activity among motivated individuals. Participants (N = 883) were randomly assigned to the intervention or to a waiting-list control condition. Multivariate analysis of variance revealed that the intervention resulted in significantly more physical activity, higher levels of action planning, coping planning, and volitional self-efficacy beliefs (p < 0.01). In addition, multiple mediation analysis showed that action planning, coping planning, and volitional self-efficacy mediate between the intervention and physical activity. The study shows that the intervention successfully fostered physical activity and unfolds the underlying self-regulatory mechanisms of the intervention's effectiveness.

Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.).

PubMed

Zhen, Shoumin; Dong, Kun; Deng, Xiong; Zhou, Jiaxing; Xu, Xuexin; Han, Caixia; Zhang, Wenying; Xu, Yanhao; Wang, Zhimin; Yan, Yueming

2016-08-01

Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to humans. These metabolites are important to human health. However, the metabolome of the grain during the development of bread wheat has not been studied so far. In this work the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175 was analyzed, using non-targeted gas chromatography/mass spectrometry (GC/MS) for metabolite profiling. In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids was interrelated. An integrated metabolic map revealed a distinct regulatory profile. The results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality. The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Explaining public support for space exploration funding in America: A multivariate analysis

NASA Astrophysics Data System (ADS)

Nadeau, François

2013-05-01

Recent studies have identified the need to understand what shapes public attitudes toward space policy. I address this gap in the literature by developing a multivariate regression model explaining why many Americans support government spending on space exploration. Using pooled data from the 2006 and 2008 General Social Surveys, the study reveals that spending preferences on space exploration are largely apolitical and associated instead with knowledge and opinions about science. In particular, the odds of wanting to increase funding for space exploration are significantly higher for white, male Babyboomers with a higher socio-economic status, a fondness for organized science, and a post-secondary science education. As such, I argue that public support for NASA's spending epitomizes what Launius termed "Apollo Nostalgia" in American culture. That is, Americans benefitting most from the old social order of the 1960s developed a greater fondness for science that makes them more likely to lament the glory days of space exploration. The article concludes with suggestions for how to elaborate on these findings in future studies.

Metabolome based volatiles profiling in 13 date palm fruit varieties from Egypt via SPME GC-MS and chemometrics.

PubMed

Khalil, Mohammed N A; Fekry, Mostafa I; Farag, Mohamed A

2017-02-15

Dates (Phoenix dactylifera L.) are distributed worldwide as major food complement providing a source of sugars and dietary fiber as well as macro- and micronutrients. Although phytochemical analyses of date fruit non-volatile metabolites have been reported, much less is known about the aroma given off by the fruit, which is critical for dissecting sensory properties and quality traits. Volatile constituents from 13 date varieties grown in Egypt were profiled using SPME-GCMS coupled to multivariate data analysis to explore date fruit aroma composition and investigate potential future uses by food industry. A total of 89 volatiles were identified where lipid-derived volatiles and phenylpropanoid derivatives were the major components of date fruit aroma. Multivariate data analyses revealed that 2,3-butanediol, hexanal, hexanol and cinnamaldehyde contributed the most to classification of different varieties. This study provides the most complete map of volatiles in Egyptian date fruit, with Siwi and Sheshi varieties exhibiting the most distinct aroma among studied date varieties. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multivariate relationships between groundwater chemistry and toxicity in an urban aquifer.

PubMed

Dewhurst, Rachel E; Wells, N Claire; Crane, Mark; Callaghan, Amanda; Connon, Richard; Mather, John D

2003-11-01

Multivariate statistical methods were used to investigate the causes of toxicity and controls on groundwater chemistry from 274 boreholes in an urban area (London) of the United Kingdom. The groundwater was alkaline to neutral, and chemistry was dominated by calcium, sodium, and sulfate. Contaminants included fuels, solvents, and organic compounds derived from landfill material. The presence of organic material in the aquifer caused decreases in dissolved oxygen, sulfate and nitrate concentrations, and increases in ferrous iron and ammoniacal nitrogen concentrations. Pearson correlations between toxicity results and the concentration of individual analytes indicated that concentrations of ammoniacal nitrogen, dissolved oxygen, ferrous iron, and hydrocarbons were important where present. However, principal component and regression analysis suggested no significant correlation between toxicity and chemistry over the whole area. Multidimensional scaling was used to investigate differences in sites caused by historical use, landfill gas status, or position within the sample area. Significant differences were observed between sites with different historical land use and those with different gas status. Examination of the principal component matrix revealed that these differences are related to changes in the importance of reduced chemical species.

Antibody-Mediated Rejection of the Kidney after Simultaneous Pancreas-Kidney Transplantation

PubMed Central

Pascual, Julio; Samaniego, Milagros D.; Torrealba, José R.; Odorico, Jon S.; Djamali, Arjang; Becker, Yolanda T.; Voss, Barbara; Leverson, Glen E.; Knechtle, Stuart J.; Sollinger, Hans W.; Pirsch, John D.

2008-01-01

The prevalence, risk factors, and outcome of antibody-mediated rejection (AMR) of the kidney after simultaneous pancreas-kidney transplantation are unknown. In 136 simultaneous pancreas-kidney recipients who were followed for an average of 3.1 yr, 21 episodes of AMR of the kidney allograft were identified. Eight episodes occurred early (≤90 d) after transplantation, and 13 occurred later. Histologic evidence of concomitant acute cellular rejection was noted in 12 cases; the other nine had evidence only of humoral rejection. In 13 cases, clinical rejection of the pancreas was diagnosed simultaneously, and two of these were biopsy proven and were positive for C4d immunostaining. Multivariate analysis identified only one significant risk factor: Female patients were three times more likely to experience AMR. Nearly all early episodes resolved with treatment and did not predict graft loss, but multivariate Cox models revealed that late AMR episodes more than tripled the risk for kidney and pancreas graft loss; therefore, new strategies are needed to prevent and to treat late AMR in simultaneous pancreas-kidney transplant recipients. PMID:18235091

Assessing the impacts of socio-economic and hydrological factors on urban water demand: A multivariate statistical approach

NASA Astrophysics Data System (ADS)

Panagopoulos, George P.

2014-10-01

The multivariate statistical techniques conducted on quarterly water consumption data in Mytilene reveal valuable tools that could help the local authorities in assigning strategies aimed at the sustainable development of urban water resources. The proposed methodology is an innovative approach, applied for the first time in the international literature, to handling urban water consumption data in order to analyze statistically the interrelationships among the determinants of urban water use. Factor analysis of demographic, socio-economic and hydrological variables shows that total water consumption in Mytilene is the combined result of increases in (a) income, (b) population, (c) connections and (d) climate parameters. On the other hand, the per connection water demand is influenced by variations in water prices but with different consequences in each consumption class. Increases in water prices are faced by large consumers; they then reduce their consumption rates and transfer to lower consumption blocks. These shifts are responsible for the increase in the average consumption values in the lower blocks despite the increase in the marginal prices.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Resilience and tipping points of an exploited fish population over six decades.

PubMed

Vasilakopoulos, Paraskevas; Marshall, C Tara

2015-05-01

Complex natural systems with eroded resilience, such as populations, ecosystems and socio-ecological systems, respond to small perturbations with abrupt, discontinuous state shifts, or critical transitions. Theory of critical transitions suggests that such systems exhibit fold bifurcations featuring folded response curves, tipping points and alternate attractors. However, there is little empirical evidence of fold bifurcations occurring in actual complex natural systems impacted by multiple stressors. Moreover, resilience of complex systems to change currently lacks clear operational measures with generic application. Here, we provide empirical evidence for the occurrence of a fold bifurcation in an exploited fish population and introduce a generic measure of ecological resilience based on the observed fold bifurcation attributes. We analyse the multivariate development of Barents Sea cod (Gadus morhua), which is currently the world's largest cod stock, over six decades (1949-2009), and identify a population state shift in 1981. By plotting a multivariate population index against a multivariate stressor index, the shift mechanism was revealed suggesting that the observed population shift was a nonlinear response to the combined effects of overfishing and climate change. Annual resilience values were estimated based on the position of each year in relation to the fitted attractors and assumed tipping points of the fold bifurcation. By interpolating the annual resilience values, a folded stability landscape was fit, which was shaped as predicted by theory. The resilience assessment suggested that the population may be close to another tipping point. This study illustrates how a multivariate analysis, supported by theory of critical transitions and accompanied by a quantitative resilience assessment, can clarify shift mechanisms in data-rich complex natural systems. © 2014 John Wiley & Sons Ltd.

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Power analysis for multivariate and repeated measures designs: a flexible approach using the SPSS MANOVA procedure.

PubMed

D'Amico, E J; Neilands, T B; Zambarano, R

2001-11-01

Although power analysis is an important component in the planning and implementation of research designs, it is often ignored. Computer programs for performing power analysis are available, but most have limitations, particularly for complex multivariate designs. An SPSS procedure is presented that can be used for calculating power for univariate, multivariate, and repeated measures models with and without time-varying and time-constant covariates. Three examples provide a framework for calculating power via this method: an ANCOVA, a MANOVA, and a repeated measures ANOVA with two or more groups. The benefits and limitations of this procedure are discussed.

Multi-Sample Cluster Analysis Using Akaike’s Information Criterion.

DTIC Science & Technology

1982-12-20

of Likelihood Criteria for I)fferent Hypotheses," in P. A. Krishnaiah (Ed.), Multivariate Analysis-Il, New York: Academic Press. [5] Fisher, R. A...Methods of Simultaneous Inference in MANOVA," in P. R. Krishnaiah (Ed.), rultivariate Analysis-Il, New York: Academic Press. [8) Kendall, M. G. (1966...1982), Applied Multivariate Statisti- cal-Analysis, Englewood Cliffs: Prentice-Mall, Inc. [1U] Krishnaiah , P. R. (1969), "Simultaneous Test

Longitudinal study of factors affecting taste sense decline in old-old individuals.

PubMed

Ogawa, T; Uota, M; Ikebe, K; Arai, Y; Kamide, K; Gondo, Y; Masui, Y; Ishizaki, T; Inomata, C; Takeshita, H; Mihara, Y; Hatta, K; Maeda, Y

2017-01-01

The sense of taste plays a pivotal role for personal assessment of the nutritional value, safety and quality of foods. Although it is commonly recognised that taste sensitivity decreases with age, alterations in that sensitivity over time in an old-old population have not been previously reported. Furthermore, no known studies utilised comprehensive variables regarding taste changes and related factors for assessments. Here, we report novel findings from a 3-year longitudinal study model aimed to elucidate taste sensitivity decline and its related factors in old-old individuals. We utilised 621 subjects aged 79-81 years who participated in the Septuagenarians, Octogenarians, Nonagenarians Investigation with Centenarians Study for baseline assessments performed in 2011 and 2012, and then conducted follow-up assessments 3 years later in 328 of those. Assessment of general health, an oral examination and determination of taste sensitivity were performed for each. We also evaluated cognitive function using Montreal Cognitive Assessment findings, then excluded from analysis those with a score lower than 20 in order to secure the validity and reliability of the subjects' answers. Contributing variables were selected using univariate analysis, then analysed with multivariate logistic regression analysis. We found that males showed significantly greater declines in taste sensitivity for sweet and sour tastes than females. Additionally, subjects with lower cognitive scores showed a significantly greater taste decrease for salty in multivariate analysis. In conclusion, our longitudinal study revealed that gender and cognitive status are major factors affecting taste sensitivity in geriatric individuals. © 2016 John Wiley & Sons Ltd.

The preoperative plasma fibrinogen level is an independent prognostic factor for overall survival of breast cancer patients who underwent surgical treatment.

PubMed

Wen, Jiahuai; Yang, Yanning; Ye, Feng; Huang, Xiaojia; Li, Shuaijie; Wang, Qiong; Xie, Xiaoming

2015-12-01

Previous studies have suggested that plasma fibrinogen contributes to tumor cell proliferation, progression and metastasis. The current study was performed to evaluate the prognostic relevance of preoperative plasma fibrinogen in breast cancer patients. Data of 2073 consecutive breast cancer patients, who underwent surgery between January 2002 and December 2008 at the Sun Yat-sen University Cancer Center, were retrospectively evaluated. Plasma fibrinogen levels were routinely measured before surgeries. Participants were grouped by the cutoff value estimated by the receiver operating characteristic (ROC) curve analysis. Overall survival (OS) was assessed using Kaplan-Meier analysis, and multivariate Cox proportional hazards regression model was performed to evaluate the independent prognostic value of plasma fibrinogen level. The optimal cutoff value of preoperative plasma fibrinogen was determined to be 2.83 g/L. The Kaplan-Meier analysis showed that patients with high fibrinogen levels had shorter OS than patients with low fibrinogen levels (p < 0.001). Multivariate analysis suggested preoperative plasma fibrinogen as an independent prognostic factor for OS in breast cancer patients (HR = 1.475, 95% confidence interval (CI): 1.177-1.848, p = 0.001). Subgroup analyses revealed that plasma fibrinogen level was an unfavorable prognostic parameter in stage II-III, Luminal subtypes and triple-negative breast cancer patients. Elevated preoperative plasma fibrinogen was independently associated with poor prognosis in breast cancer patients and may serve as a valuable parameter for risk assessment in breast cancer patients. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Dental students' perceived sources of stress: a multi-country study.

PubMed

Polychronopoulou, Argy; Divaris, Kimon

2009-05-01

The aim of this study was to identify dental students' self-reported sources of stress and to explore the role of specific curricular and institutional differences in the variation of perceived stressors among dental students in Greece, Ireland, Slovenia, Sweden, Spain, and Croatia. A thirty-item modified version of the Dental Environment Stress (DES) questionnaire was administered to all undergraduate students enrolled at six European dental schools selected to reflect geographical, curricular, and professional environment diversity: Athens, Greece; Dublin, Ireland; Ljubljana, Slovenia; Malmö, Sweden; Santiago de Compostela, Spain; and Zagreb, Croatia. Participation varied from 93 percent in Athens to 65 percent in Dublin. A total of 1,492 questionnaires were available for analysis. Univariate analysis and multivariate modelling were used for data analysis. Performance pressure, workload, and self-efficacy beliefs constituted the students' main concerns. In the univariate analysis, student responses differed by country: Swedish students provided the lowestst scores in five out of six DES factors, Spanish students were the most concerned about "clinical training" and "performance pressure," whereas Greek students were the most concerned about "patient treatment." Multivariate modelling revealed that problem-based learning (PBL) was inversely associated with perceived stress for "self-efficacy beliefs" OR (95% CI): 0.66 (0.52, 0.84), "workload" OR (95% CI): 0.58 (0.41, 0.80); and "clinical training" OR (95% CI): 0.69 (0.50, 0.95) when compared to traditional curricula. Students' perceived stressors differed greatly among the six institutions and were associated with both individual (gender, study level) and educational/institutional (curriculum type, class size, educational costs) parameters.

A Review of Arteriovenous Fistulae Creation in Octogenarians.

PubMed

Diandra, Jennifer Clarissa; Lo, Zhiwen Joseph; Ang, Wei-Wen; Feng, Jue Fei; Narayanan, Sriram; Tan, Glenn Wei Leong; Chandrasekar, Sadhana

2018-01-01

To analyze the outcomes of arteriovenous fistulae (AVFs) creation in octogenarians. A retrospective study of 47 AVFs created in patients aged 80 years and above from 2008 to 2014. Patient and AVF characteristics and outcomes were evaluated. Predictors of patency were analyzed with multivariate analysis and Kaplan-Meier patency, and survival analysis was performed. Forty-seven of 1,259 AVFs created were for octogenarians (4%). Mean age was 83 years old (range: 80-91 years), with 27 male (57%) and 35 with tunneled dialysis catheters in situ (75%). There were a total of 15 (32%) radiocephalic AVFs, 30 (64%) brachial-cephalic AVFs, and 2 (4%) brachial-basilic transposition AVFs. At 12 months, assisted primary patency rate was 28% (13 patients) while primary failure rate was 72% (34 patients). Subset analysis showed brachial-cephalic AVFs to have the highest assisted primary patency rate at 33%. Within 24 months, tunneled dialysis catheter-related sepsis rate was 31% (11 patients). Multivariate analysis did not reveal any factor to be statistically significant in predicting AVF patency. Kaplan-Meier survival curve showed a 50% survival rate at 63 months after AVF creation. In view of high AVF primary failure rate and relatively low tunneled dialysis catheter bacteremia rate, long-term tunneled dialysis catheters as the main form of hemodialysis renal access may be a viable option. However, with 50% of end-stage renal failure patients surviving up to 63 months after AVF creation, the risks and benefits of long-term tunneled dialysis catheters must be balanced against those of AVF creation. Copyright © 2017 Elsevier Inc. All rights reserved.

Gastric cancer, nutritional status, and outcome.

PubMed

Liu, Xuechao; Qiu, Haibo; Kong, Pengfei; Zhou, Zhiwei; Sun, Xiaowei

2017-01-01

We aim to investigate the prognostic value of several nutrition-based indices, including the prognostic nutritional index (PNI), performance status, body mass index, serum albumin, and preoperative body weight loss in patients with gastric cancer (GC). We retrospectively analyzed the records of 1,330 consecutive patients with GC undergoing curative surgery between October 2000 and September 2012. The relationship between nutrition-based indices and overall survival (OS) was examined using Kaplan-Meier analysis and Cox regression model. Following multivariate analysis, the PNI and preoperative body weight loss were the only nutritional-based indices independently associated with OS (hazard ratio [HR]: 1.356, 95% confidence interval [CI]: 1.051-1.748, P =0.019; HR: 1.152, 95% CI: 1.014-1.310, P =0.030, retrospectively). In stage-stratified analysis, multivariate analysis revealed that preoperative body weight loss was identified as an independent prognostic factor only in patients with stage III GC (HR: 1.223, 95% CI: 1.065-1.405, P =0.004), while the prognostic significance of PNI was not significant (all P >0.05). In patients with stage III GC, preoperative body weight loss stratified 5-year OS from 41.1% to 26.5%. When stratified by adjuvant chemotherapy, the prognostic significance of preoperative body weight loss was maintained in patients treated with surgery plus adjuvant chemotherapy and in patients treated with surgery alone ( P <0.001; P =0.003). Preoperative body weight loss is an independent prognostic factor for OS in patients with GC, especially in stage III disease. Preoperative body weight loss appears to be a superior predictor of outcome compared with other established nutrition-based indices.

Predictors of mistimed, and unwanted pregnancies among women of childbearing age in Rufiji, Kilombero, and Ulanga districts of Tanzania.

PubMed

Exavery, Amon; Kanté, Almamy Malick; Njozi, Mustafa; Tani, Kassimu; Doctor, Henry V; Hingora, Ahmed; Phillips, James F

2014-08-08

While unintended pregnancies pose a serious threat to the health and well-being of families globally, characteristics of Tanzanian women who conceive unintentionally are rarely documented. This analysis identifies factors associated with unintended pregnancies-both mistimed and unwanted-in three rural districts of Tanzania. A cross-sectional survey of 2,183 random households was conducted in three Tanzanian districts of Rufiji, Kilombero, and Ulanga in 2011 to assess women's health behavior and service utilization patterns. These households produced 3,127 women age 15+ years from which 2,199 gravid women aged 15-49 were selected for the current analysis. Unintended pregnancies were identified as either mistimed (wanted later) or unwanted (not wanted at all). Correlates of mistimed, and unwanted pregnancies were identified through Chi-squared tests to assess associations and multinomial logistic regression for multivariate analysis. Mean age of the participants was 32.1 years. While 54.1% of the participants reported that their most recent pregnancy was intended, 32.5% indicated their most recent pregnancy as mistimed and 13.4% as unwanted. Multivariate analysis revealed that young age (<20 years), and single marital status were significant predictors of both mistimed and unwanted pregnancies. Lack of inter-partner communication about family planning increased the risk of mistimed pregnancy significantly, and multi-gravidity was shown to significantly increase the risk of unwanted pregnancy. About one half of women in Rufiji, Kilombero, and Ulanga districts of Tanzania conceive unintentionally. Women, especially the most vulnerable should be empowered to avoid pregnancy at their own will and discretion.

Predictive factors for bleeding during treatment with rivaroxaban and warfarin in Japanese patients with atrial fibrillation - Subgroup analysis of J-ROCKET AF.

PubMed

Hori, Masatsugu; Matsumoto, Masayasu; Tanahashi, Norio; Momomura, Shin-Ichi; Uchiyama, Shinichiro; Goto, Shinya; Izumi, Tohru; Koretsune, Yukihiro; Kajikawa, Mariko; Kato, Masaharu; Cavaliere, Mary; Iekushi, Kazuma; Yamanaka, Satoshi

2016-12-01

Results from the J-ROCKET AF study revealed that rivaroxaban was non-inferior to warfarin with respect to the principal safety outcomes in patients with non-valvular atrial fibrillation. This subgroup analysis evaluated whether non-major clinically relevant bleeding (NMCRB) could be a predictive factor for major bleeding (MB). Other predictive factors for MB were also obtained in both rivaroxaban and warfarin treatment groups. The temporal incidence of MB was compared between the rivaroxaban and warfarin treatment groups. Assessment was made whether MB events were often preceded by NMCRB. Univariate and multivariate analyses were carried out to identify any independent predictive factors for MB in both treatment groups. The incidences of MB and NMCRB were 18.04% (138/639 patients) in the rivaroxaban arm, and 16.42% in the warfarin arm (124/639 patients). NMCRB preceded MB in only four patients in each treatment group (rivaroxaban: 4/117 and warfarin: 4/98). Multivariate analysis identified predictive factors for bleeding events: anemia with warfarin treatment and concomitant use of antiplatelet agents with rivaroxaban treatment. Results from this subgroup analysis, particularly the fact that there was no repeated or sequential pattern between NMCRB and MB occurrences in both treatment groups, suggests that NMCRB might not be a predictive factor for MB. On the contrary, anemia and concomitant use of antiplatelet therapy were likely predictive factors for bleeding with warfarin and rivaroxaban treatment, respectively. Copyright © 2016 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis

NASA Astrophysics Data System (ADS)

Almerico, Anna Maria; Tutone, Marco; Lauria, Antonino

2008-05-01

In this paper we describe a comparative analysis between multivariate and docking methods in the study of the drug resistance to the reverse transcriptase and the protease inhibitors. In our early papers we developed a simple but efficient method to evaluate the features of compounds that are less likely to trigger resistance or are effective against mutant HIV strains, using the multivariate statistical procedures PCA and DA. In the attempt to create a more solid background for the prediction of susceptibility or resistance, we carried out a comparative analysis between our previous multivariate approach and molecular docking study. The intent of this paper is not only to find further support to the results obtained by the combined use of PCA and DA, but also to evidence the structural features, in terms of molecular descriptors, similarity, and energetic contributions, derived from docking, which can account for the arising of drug-resistance against mutant strains.

SUGGESTIONS FOR OPTIMIZED PLANNING OF MULTIVARIATE MONITORING OF ATMOSPHERIC POLLUTION

EPA Science Inventory

Recent work in factor analysis of multivariate data sets has shown that variables with little signal should not be included in the factor analysis. Work also shows that rotational ambiguity is reduced if sources impacting a receptor have both large and small contributions. Thes...

Multivariate Meta-Analysis Using Individual Participant Data

ERIC Educational Resources Information Center

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2015-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

Spatial and spectral resolution of carbonaceous material from hematite (α-Fe2O3) using multivariate curve resolution-alternating least squares (MCR-ALS) with Raman microspectroscopic mapping: implications for the search for life on Mars.

PubMed

Smith, Joseph P; Smith, Frank C; Booksh, Karl S

2017-08-21

The search for evidence of extant or past life on Mars is a primary objective of both the upcoming Mars 2020 rover (NASA) and ExoMars 2020 rover (ESA/Roscosmos) missions. This search will involve the detection and identification of organic molecules and/or carbonaceous material within the Martian surface environment. For the first time on a mission to Mars, the scientific payload for each rover will include a Raman spectrometer, an instrument well-suited for this search. Hematite (α-Fe 2 O 3 ) is a widespread mineral on the Martian surface. The 2LO Raman band of hematite and the Raman D-band of carbonaceous material show spectral overlap, leading to the potential misidentification of hematite as carbonaceous material. Here we report the ability to spatially and spectrally differentiate carbonaceous material from hematite using multivariate curve resolution-alternating least squares (MCR-ALS) applied to Raman microspectroscopic mapping under both 532 nm and 785 nm excitation. For this study, a sample comprised of hematite, carbonaceous material, and substrate-adhesive epoxy in spatially distinct domains was constructed. Principal component analysis (PCA) reveals that both 532 nm and 785 nm excitation produce representative three-phase systems of hematite, carbonaceous material, and substrate-adhesive epoxy in the analyzed sample. MCR-ALS with Raman microspectroscopic mapping using both 532 nm and 785 nm excitation was able to resolve hematite, carbonaceous material, and substrate-adhesive epoxy by generating spatially-resolved chemical maps and corresponding Raman spectra of these spatially distinct chemical species. Moreover, MCR-ALS applied to the combinatorial data sets of 532 nm and 785 nm excitation, which contain hematite and carbonaceous material within the same locations, was able to resolve hematite, carbonaceous material, and substrate-adhesive epoxy. Using multivariate analysis with Raman microspectroscopic mapping, 785 nm excitation more effectively resolved hematite, carbonaceous material, and substrate-adhesive epoxy as compared to 532 nm excitation. To our knowledge, this is the first report of multivariate analysis methods, namely MCR-ALS, with Raman microspectroscopic mapping being employed to differentiate carbonaceous material from hematite. We have therefore provided an analytical methodology useful for the search for extant or past life on the surface of Mars.