Variation of facial features among three African populations: Body height match analyses.

PubMed

Taura, M G; Adamu, L H; Gudaji, A

2017-01-01

Body height is one of the variables that show a correlation with facial craniometry. Here we seek to discriminate the three populations (Nigerians, Ugandans and Kenyans) using facial craniometry based on different categories of body height of adult males. A total of 513 individuals comprising 234 Nigerians, 169 Ugandans and 110 Kenyans with mean age of 25.27, s=5.13 (18-40 years) participated. Paired and unpaired facial features were measured using direct craniometry. Multivariate and stepwise discriminate function analyses were used for differentiation of the three populations. The result showed significant overall facial differences among the three populations in all the body height categories. Skull height, total facial height, outer canthal distance, exophthalmometry, right ear width and nasal length were significantly different among the three different populations irrespective of body height categories. Other variables were sensitive to body height. Stepwise discriminant function analyses included maximum of six variables for better discrimination between the three populations. The single best discriminator of the groups was total facial height, however, for body height >1.70m the single best discriminator was nasal length. Most of the variables were better used with function 1, hence, better discrimination than function 2. In conclusion, adult body height in addition to other factors such as age, sex, and ethnicity should be considered in making decision on facial craniometry. However, not all the facial linear dimensions were sensitive to body height. Copyright © 2016 Elsevier GmbH. All rights reserved.

Performance, physiological, and oculometer evaluation of VTOL landing displays

NASA Technical Reports Server (NTRS)

North, R. A.; Stackhouse, S. P.; Graffunder, K.

1979-01-01

A methodological approach to measuring workload was investigated for evaluation of new concepts in VTOL aircraft displays. Physiological, visual response, and conventional flight performance measures were recorded for landing approaches performed in the NASA Visual Motion Simulator (VMS). Three displays (two computer graphic and a conventional flight director), three crosswind amplitudes, and two motion base conditions (fixed vs. moving base) were tested in a factorial design. Multivariate discriminant functions were formed from flight performance and/or visual response variables. The flight performance variable discriminant showed maximum differentation between crosswind conditions. The visual response measure discriminant maximized differences between fixed vs. motion base conditions and experimental displays. Physiological variables were used to attempt to predict the discriminant function values for each subject/condition trial. The weights of the physiological variables in these equations showed agreement with previous studies. High muscle tension, light but irregular breathing patterns, and higher heart rate with low amplitude all produced higher scores on this scale and thus represent higher workload levels.

Introduction to multivariate discrimination

NASA Astrophysics Data System (ADS)

Kégl, Balázs

2013-07-01

Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either relevant to or even motivated by certain unorthodox applications of multivariate discrimination in experimental physics.

Determination of sex from radiographic measurements of the humerus by discriminant function analysis in Saudi population, Qassim region, KSA.

PubMed

Shehri, Fahad Al; Soliman, Khaled E A

2015-08-01

Diagnosis of sex from skeleton or individual bone plays an important role in identifying unknown bodies, parts of bodies or skeletal remains for forensic purposes. This study aims to examine the applicability of the measurements taken from the humerus to assess sex, and to contribute to establishing discriminant function equations for Saudi populations for medico legal applications. Archived X-ray radiographs of humerus for 387 patients (216 males & 171 females) who attended the orthopedic clinics at Suleiman Al-Habib Hospital, Qassim region, KSA in the period from January 2011 to December 2013 were reviewed and analyzed. Five dimensions, including maximum length, vertical head diameter, diameter of head+greater tubercle, right-left diameter at midshaft, and epicondylar breadth were taken and subjected to Univariate and multivariate discriminant function analysis. The studied radiographic dimensions of the humerus indicate that there are significant differences (p<0.05) between the males and females measurements while the difference between right and left measurements was not significant. The findings revealed that the proximal part of the humerus has greater diagnostic accuracy than distal and middle parts. Accuracy of correct classification varies between 68.0% (epicondylar breadth) and 90.4% (vertical head diameter) for univariate analyses. When the multivariate analyses were conducted, three functions were produced, with the accuracy of ranging between 88.4% and 94.3%. These findings suggested that the dimensions of the humerus, especially the measurements taken from the proximal parts, could be used successfully for sex diagnosis. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Multivariate pattern analysis strategies in detection of remitted major depressive disorder using resting state functional connectivity.

PubMed

Bhaumik, Runa; Jenkins, Lisanne M; Gowins, Jennifer R; Jacobs, Rachel H; Barba, Alyssa; Bhaumik, Dulal K; Langenecker, Scott A

2017-01-01

Understanding abnormal resting-state functional connectivity of distributed brain networks may aid in probing and targeting mechanisms involved in major depressive disorder (MDD). To date, few studies have used resting state functional magnetic resonance imaging (rs-fMRI) to attempt to discriminate individuals with MDD from individuals without MDD, and to our knowledge no investigations have examined a remitted (r) population. In this study, we examined the efficiency of support vector machine (SVM) classifier to successfully discriminate rMDD individuals from healthy controls (HCs) in a narrow early-adult age range. We empirically evaluated four feature selection methods including multivariate Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net feature selection algorithms. Our results showed that SVM classification with Elastic Net feature selection achieved the highest classification accuracy of 76.1% (sensitivity of 81.5% and specificity of 68.9%) by leave-one-out cross-validation across subjects from a dataset consisting of 38 rMDD individuals and 29 healthy controls. The highest discriminating functional connections were between the left amygdala, left posterior cingulate cortex, bilateral dorso-lateral prefrontal cortex, and right ventral striatum. These appear to be key nodes in the etiopathophysiology of MDD, within and between default mode, salience and cognitive control networks. This technique demonstrates early promise for using rs-fMRI connectivity as a putative neurobiological marker capable of distinguishing between individuals with and without rMDD. These methods may be extended to periods of risk prior to illness onset, thereby allowing for earlier diagnosis, prevention, and intervention.

Chemometric techniques on the analysis of Raman spectra of serum blood samples of breast cancer patients

NASA Astrophysics Data System (ADS)

Rocha-Osornio, L. N.; Pichardo-Molina, J. L.; Barbosa-Garcia, O.; Frausto-Reyes, C.; Araujo-Andrade, C.; Huerta-Franco, R.; Gutiérrez-Juárez, G.

2008-02-01

Raman spectroscopy and Multivariate methods were used to study serum blood samples of control and breast cancer patients. Blood samples were obtained from 11 patients and 12 controls from the central region of Mexico. Our results show that principal component analysis is able to discriminate serum sample of breast cancer patients from those of control group, also the loading vectors of PCA plotted as a function of Raman shift shown which bands permitted to make the maximum discrimination between both groups of samples.

Two models for evaluating landslide hazards

USGS Publications Warehouse

Davis, J.C.; Chung, C.-J.; Ohlmacher, G.C.

2006-01-01

Two alternative procedures for estimating landslide hazards were evaluated using data on topographic digital elevation models (DEMs) and bedrock lithologies in an area adjacent to the Missouri River in Atchison County, Kansas, USA. The two procedures are based on the likelihood ratio model but utilize different assumptions. The empirical likelihood ratio model is based on non-parametric empirical univariate frequency distribution functions under an assumption of conditional independence while the multivariate logistic discriminant model assumes that likelihood ratios can be expressed in terms of logistic functions. The relative hazards of occurrence of landslides were estimated by an empirical likelihood ratio model and by multivariate logistic discriminant analysis. Predictor variables consisted of grids containing topographic elevations, slope angles, and slope aspects calculated from a 30-m DEM. An integer grid of coded bedrock lithologies taken from digitized geologic maps was also used as a predictor variable. Both statistical models yield relative estimates in the form of the proportion of total map area predicted to already contain or to be the site of future landslides. The stabilities of estimates were checked by cross-validation of results from random subsamples, using each of the two procedures. Cell-by-cell comparisons of hazard maps made by the two models show that the two sets of estimates are virtually identical. This suggests that the empirical likelihood ratio and the logistic discriminant analysis models are robust with respect to the conditional independent assumption and the logistic function assumption, respectively, and that either model can be used successfully to evaluate landslide hazards. ?? 2006.

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.

Multivariate analysis of early and late nest sites of Abert's Towhees

Treesearch

Deborah M. Finch

1985-01-01

Seasonal variation in nest site selection by the Abert's towhee (Pipilo aberti) was studied in honey mesquite (Prosopis glandulosa) habitat along the lower Colorado River from March to July, 1981. Stepwise discriminant function analysis identified nest vegetation type, nest direction, and nest height as the three most important variables that characterized the...

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.

Discriminative analysis of early Alzheimer's disease based on two intrinsically anti-correlated networks with resting-state fMRI.

PubMed

Wang, Kun; Jiang, Tianzi; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Liu, Zhening

2006-01-01

In this work, we proposed a discriminative model of Alzheimer's disease (AD) on the basis of multivariate pattern classification and functional magnetic resonance imaging (fMRI). This model used the correlation/anti-correlation coefficients of two intrinsically anti-correlated networks in resting brains, which have been suggested by two recent studies, as the feature of classification. Pseudo-Fisher Linear Discriminative Analysis (pFLDA) was then performed on the feature space and a linear classifier was generated. Using leave-one-out (LOO) cross validation, our results showed a correct classification rate of 83%. We also compared the proposed model with another one based on the whole brain functional connectivity. Our proposed model outperformed the other one significantly, and this implied that the two intrinsically anti-correlated networks may be a more susceptible part of the whole brain network in the early stage of AD.

The significance and robustness of a plasma free amino acid (PFAA) profile-based multiplex function for detecting lung cancer

PubMed Central

2013-01-01

Background We have recently reported on the changes in plasma free amino acid (PFAA) profiles in lung cancer patients and the efficacy of a PFAA-based, multivariate discrimination index for the early detection of lung cancer. In this study, we aimed to verify the usefulness and robustness of PFAA profiling for detecting lung cancer using new test samples. Methods Plasma samples were collected from 171 lung cancer patients and 3849 controls without apparent cancer. PFAA levels were measured by high-performance liquid chromatography (HPLC)–electrospray ionization (ESI)–mass spectrometry (MS). Results High reproducibility was observed for both the change in the PFAA profiles in the lung cancer patients and the discriminating performance for lung cancer patients compared to previously reported results. Furthermore, multivariate discriminating functions obtained in previous studies clearly distinguished the lung cancer patients from the controls based on the area under the receiver-operator characteristics curve (AUC of ROC = 0.731 ~ 0.806), strongly suggesting the robustness of the methodology for clinical use. Moreover, the results suggested that the combinatorial use of this classifier and tumor markers improves the clinical performance of tumor markers. Conclusions These findings suggest that PFAA profiling, which involves a relatively simple plasma assay and imposes a low physical burden on subjects, has great potential for improving early detection of lung cancer. PMID:23409863

The Value of Routine Biochemical Tests in Discriminating Between Malignant and Benign Pancreatic Tumours

PubMed Central

Blind, P-J; Eriksson, S.

1991-01-01

The probability that routine hematological laboratory tests of liver and pancreatic function can discriminate between malignant and benign pancreatic tumours, incidentally detected during operation, was investigated. The records of 53 patients with a verified diagnosis of pancreatic carcinoma and 19 patients with chronic pancreatitis were reviewed with regard to preoperative total bilirubin, direct reacting bilirubin, alkaline phosphatase, glutamyltranspeptidase, aminotransferases, lactic dehydrogenase and amylase. Multivariate and discriminant analysis were performed to calculate the predictive value for cancer, using SYSTAT statistical package in a Macintosh II computer. Total and direct reacting bilirubin and glutamyltranspeptidase were significantly higher in patients with pancreatic carcinoma. However, only considerably increased levels of direct reating bilirubin were predictive of pancreatic carcinoma. PMID:1931781

Assessment of sampling stability in ecological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.

1988-01-01

A simulation study was undertaken to assess the sampling stability of the variable loadings in linear discriminant function analysis. A factorial design was used for the factors of multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. A review of 60 published studies and 142 individual analyses indicated that sample sizes in ecological studies often have met that requirement. However, individual group sample sizes frequently were very unequal, and checks of assumptions usually were not reported. The authors recommend that ecologists obtain group sample sizes that are at least three times as large as the number of variables measured.

Default mode network connectivity distinguishes chemotherapy-treated breast cancer survivors from controls

PubMed Central

Kesler, Shelli R.; Wefel, Jeffrey S.; Hosseini, S. M. Hadi; Cheung, Maria; Watson, Christa L.; Hoeft, Fumiko

2013-01-01

Breast cancer (BC) chemotherapy is associated with cognitive changes including persistent deficits in some individuals. We tested the accuracy of default mode network (DMN) resting state functional connectivity patterns in discriminating chemotherapy treated (C+) from non–chemotherapy (C−) treated BC survivors and healthy controls (HC). We also examined the relationship between DMN connectivity patterns and cognitive function. Multivariate pattern analysis was used to classify 30 C+, 27 C−, and 24 HC, which showed significant accuracy for discriminating C+ from C− (91.23%, P < 0.0001) and C+ from HC (90.74%, P < 0.0001). The C− group did not differ significantly from HC (47.06%, P = 0.60). Lower subjective memory function was correlated (P < 0.002) with greater hyperplane distance (distance from the linear decision function that optimally separates the groups). Disrupted DMN connectivity may help explain long-term cognitive difficulties following BC chemotherapy. PMID:23798392

Multivariate carbon and nitrogen stable isotope model for the reconstruction of prehistoric human diet.

PubMed

Froehle, A W; Kellner, C M; Schoeninger, M J

2012-03-01

Using a sample of published archaeological data, we expand on an earlier bivariate carbon model for diet reconstruction by adding bone collagen nitrogen stable isotope values (δ(15) N), which provide information on trophic level and consumption of terrestrial vs. marine protein. The bivariate carbon model (δ(13) C(apatite) vs. δ(13) C(collagen) ) provides detailed information on the isotopic signatures of whole diet and dietary protein, but is limited in its ability to distinguish between C(4) and marine protein. Here, using cluster analysis and discriminant function analysis, we generate a multivariate diet reconstruction model that incorporates δ(13) C(apatite) , δ(13) C(collagen) , and δ(15) N holistically. Inclusion of the δ(15) N data proves useful in resolving protein-related limitations of the bivariate carbon model, and splits the sample into five distinct dietary clusters. Two significant discriminant functions account for 98.8% of the sample variance, providing a multivariate model for diet reconstruction. Both carbon variables dominate the first function, while δ(15) N most strongly influences the second. Independent support for the functions' ability to accurately classify individuals according to diet comes from a small sample of experimental rats, which cluster as expected from their diets. The new model also provides a statistical basis for distinguishing between food sources with similar isotopic signatures, as in a previously analyzed archaeological population from Saipan (see Ambrose et al.: AJPA 104(1997) 343-361). Our model suggests that the Saipan islanders' (13) C-enriched signal derives mainly from sugarcane, not seaweed. Further development and application of this model can similarly improve dietary reconstructions in archaeological, paleontological, and primatological contexts. Copyright © 2011 Wiley Periodicals, Inc.

Selected Gray Matter Volumes and Gender but Not Basal Ganglia nor Cerebellum Gyri Discriminate Left Versus Right Cerebral Hemispheres: Multivariate Analyses in human Brains at 3T.

PubMed

Roldan-Valadez, Ernesto; Suarez-May, Marcela A; Favila, Rafael; Aguilar-Castañeda, Erika; Rios, Camilo

2015-07-01

Interest in the lateralization of the human brain is evident through a multidisciplinary number of scientific studies. Understanding volumetric brain asymmetries allows the distinction between normal development stages and behavior, as well as brain diseases. We aimed to evaluate volumetric asymmetries in order to select the best gyri able to classify right- versus left cerebral hemispheres. A cross-sectional study performed in 47 right-handed young-adults healthy volunteers. SPM-based software performed brain segmentation, automatic labeling and volumetric analyses for 54 regions involving the cerebral lobes, basal ganglia and cerebellum from each cerebral hemisphere. Multivariate discriminant analysis (DA) allowed the assembling of a predictive model. DA revealed one discriminant function that significantly differentiated left vs. right cerebral hemispheres: Wilks' λ = 0.008, χ(2) (9) = 238.837, P < 0.001. The model explained 99.20% of the variation in the grouping variable and depicted an overall predictive accuracy of 98.8%. With the influence of gender; the selected gyri able to discriminate between hemispheres were middle orbital frontal gyrus (g.), angular g., supramarginal g., middle cingulum g., inferior orbital frontal g., calcarine g., inferior parietal lobule and the pars triangularis inferior frontal g. Specific brain gyri are able to accurately classify left vs. right cerebral hemispheres by using a multivariate approach; the selected regions correspond to key brain areas involved in attention, internal thought, vision and language; our findings favored the concept that lateralization has been evolutionary favored by mental processes increasing cognitive efficiency and brain capacity. © 2015 Wiley Periodicals, Inc.

Solution identification and quantitative analysis of fiber-capacitive drop analyzer based on multivariate statistical methods

NASA Astrophysics Data System (ADS)

Chen, Zhe; Qiu, Zurong; Huo, Xinming; Fan, Yuming; Li, Xinghua

2017-03-01

A fiber-capacitive drop analyzer is an instrument which monitors a growing droplet to produce a capacitive opto-tensiotrace (COT). Each COT is an integration of fiber light intensity signals and capacitance signals and can reflect the unique physicochemical property of a liquid. In this study, we propose a solution analytical and concentration quantitative method based on multivariate statistical methods. Eight characteristic values are extracted from each COT. A series of COT characteristic values of training solutions at different concentrations compose a data library of this kind of solution. A two-stage linear discriminant analysis is applied to analyze different solution libraries and establish discriminant functions. Test solutions can be discriminated by these functions. After determining the variety of test solutions, Spearman correlation test and principal components analysis are used to filter and reduce dimensions of eight characteristic values, producing a new representative parameter. A cubic spline interpolation function is built between the parameters and concentrations, based on which we can calculate the concentration of the test solution. Methanol, ethanol, n-propanol, and saline solutions are taken as experimental subjects in this paper. For each solution, nine or ten different concentrations are chosen to be the standard library, and the other two concentrations compose the test group. By using the methods mentioned above, all eight test solutions are correctly identified and the average relative error of quantitative analysis is 1.11%. The method proposed is feasible which enlarges the applicable scope of recognizing liquids based on the COT and improves the concentration quantitative precision, as well.

Early Numeracy Intervention: Does Quantity Discrimination Really Work?

ERIC Educational Resources Information Center

Hansmann, Paul

2013-01-01

Scope and Method of Study: The current study demonstrates that a taped problem intervention is an effective tool for increasing the early numeracy skill of QD. A taped problems intervention was used with two variations of the quantity discrimination measure (triangle and traditional). A 3x2 doubly multivariate multivariate analysis of variance was…

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.

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.

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.

Fast discrimination of hydroxypropyl methyl cellulose using portable Raman spectrometer and multivariate methods

NASA Astrophysics Data System (ADS)

Song, Biao; Lu, Dan; Peng, Ming; Li, Xia; Zou, Ye; Huang, Meizhen; Lu, Feng

2017-02-01

Raman spectroscopy is developed as a fast and non-destructive method for the discrimination and classification of hydroxypropyl methyl cellulose (HPMC) samples. 44 E series and 41 K series of HPMC samples are measured by a self-developed portable Raman spectrometer (Hx-Raman) which is excited by a 785 nm diode laser and the spectrum range is 200-2700 cm-1 with a resolution (FWHM) of 6 cm-1. Multivariate analysis is applied for discrimination of E series from K series. By methods of principal components analysis (PCA) and Fisher discriminant analysis (FDA), a discrimination result with sensitivity of 90.91% and specificity of 95.12% is achieved. The corresponding receiver operating characteristic (ROC) is 0.99, indicting the accuracy of the predictive model. This result demonstrates the prospect of portable Raman spectrometer for rapid, non-destructive classification and discrimination of E series and K series samples of HPMC.

Photos for estimating fuel loadings before and after prescribed burning in the upper coastal plain of the southeast

Treesearch

Eric R. Scholl; Thomas A. Waldrop

1999-01-01

Although prescribed burning is common in the Southeastern United States, most fuel models apply to only western forests. This paper documents a fuel classification system that was developed for plantations of loblolly and longleaf pines for the Upper Coastal Plain region. Multivariate analysis of variance and discriminant function analysis were used to confirm eight...

Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

PubMed Central

Lim, Jongguk; Kim, Giyoung; Mo, Changyeun; Oh, Kyoungmin; Yoo, Hyeonchae; Ham, Hyeonheui; Kim, Moon S.

2017-01-01

The purpose of this study is to use near-infrared reflectance (NIR) spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA) was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method. PMID:28974012

Social Context of Depressive Distress in Aging Transgender Adults

PubMed Central

White Hughto, Jaclyn M.; Reisner, Sari L.

2016-01-01

This study investigates the relationship between discrimination and mental health in aging transgender adults. Survey responses from 61 transgender adults above 50 (Mage = 57.7, SD = 5.8; 77.1% male-to-female; 78.7% White non-Hispanic) were analyzed. Multivariable logistic regression models examined the relationship between gender- and age-related discrimination, number of everyday discrimination experiences, and past-week depressive distress, adjusting for social support, sociodemographics, and other forms of discrimination. The most commonly attributed reasons for experiencing discrimination were related to gender (80.3%) and age (34.4%). More than half of participants (55.5%) met criteria for past-week depressive distress. In an adjusted multivariable model, gender-related discrimination and a greater number of everyday discrimination experiences were associated with increased odds of past-week depressive distress. Additional research is needed to understand the effects of aging and gender identity on depressive symptoms and develop interventions to safeguard the mental health of this vulnerable aging population. PMID:28380703

Social Context of Depressive Distress in Aging Transgender Adults.

PubMed

White Hughto, Jaclyn M; Reisner, Sari L

2016-11-01

This study investigates the relationship between discrimination and mental health in aging transgender adults. Survey responses from 61 transgender adults above 50 ( M age = 57.7, SD = 5.8; 77.1% male-to-female; 78.7% White non-Hispanic) were analyzed. Multivariable logistic regression models examined the relationship between gender- and age-related discrimination, number of everyday discrimination experiences, and past-week depressive distress, adjusting for social support, sociodemographics, and other forms of discrimination. The most commonly attributed reasons for experiencing discrimination were related to gender (80.3%) and age (34.4%). More than half of participants (55.5%) met criteria for past-week depressive distress. In an adjusted multivariable model, gender-related discrimination and a greater number of everyday discrimination experiences were associated with increased odds of past-week depressive distress. Additional research is needed to understand the effects of aging and gender identity on depressive symptoms and develop interventions to safeguard the mental health of this vulnerable aging population.

Sex discrimination from the acetabulum in a twentieth-century skeletal sample from France using digital photogrammetry.

PubMed

Macaluso, P J

2011-02-01

Digital photogrammetric methods were used to collect diameter, area, and perimeter data of the acetabulum for a twentieth-century skeletal sample from France (Georges Olivier Collection, Musée de l'Homme, Paris) consisting of 46 males and 36 females. The measurements were then subjected to both discriminant function and logistic regression analyses in order to develop osteometric standards for sex assessment. Univariate discriminant functions and logistic regression equations yielded overall correct classification accuracy rates for both the left and the right acetabula ranging from 84.1% to 89.6%. The multivariate models developed in this study did not provide increased accuracy over those using only a single variable. Classification sex bias ratios ranged between 1.1% and 7.3% for the majority of models. The results of this study, therefore, demonstrate that metric analysis of acetabular size provides a highly accurate, and easily replicable, method of discriminating sex in this documented skeletal collection. The results further suggest that the addition of area and perimeter data derived from digital images may provide a more effective method of sex assessment than that offered by traditional linear measurements alone. Copyright © 2010 Elsevier GmbH. All rights reserved.

Characterization of Interfacial Chemistry of Adhesive/Dentin Bond Using FTIR Chemical Imaging With Univariate and Multivariate Data Processing

PubMed Central

Wang, Yong; Yao, Xiaomei; Parthasarathy, Ranganathan

2008-01-01

Fourier transform infrared (FTIR) chemical imaging can be used to investigate molecular chemical features of the adhesive/dentin interfaces. However, the information is not straightforward, and is not easily extracted. The objective of this study was to use multivariate analysis methods, principal component analysis and fuzzy c-means clustering, to analyze spectral data in comparison with univariate analysis. The spectral imaging data collected from both the adhesive/healthy dentin and adhesive/caries-affected dentin specimens were used and compared. The univariate statistical methods such as mapping of intensities of specific functional group do not always accurately identify functional group locations and concentrations due to more or less band overlapping in adhesive and dentin. Apart from the ease with which information can be extracted, multivariate methods highlight subtle and often important changes in the spectra that are difficult to observe using univariate methods. The results showed that the multivariate methods gave more satisfactory, interpretable results than univariate methods and were conclusive in showing that they can discriminate and classify differences between healthy dentin and caries-affected dentin within the interfacial regions. It is demonstrated that the multivariate FTIR imaging approaches can be used in the rapid characterization of heterogeneous, complex structure. PMID:18980198

Superiority of artificial neural networks for a genetic classification procedure.

PubMed

Sant'Anna, I C; Tomaz, R S; Silva, G N; Nascimento, M; Bhering, L L; Cruz, C D

2015-08-19

The correct classification of individuals is extremely important for the preservation of genetic variability and for maximization of yield in breeding programs using phenotypic traits and genetic markers. The Fisher and Anderson discriminant functions are commonly used multivariate statistical techniques for these situations, which allow for the allocation of an initially unknown individual to predefined groups. However, for higher levels of similarity, such as those found in backcrossed populations, these methods have proven to be inefficient. Recently, much research has been devoted to developing a new paradigm of computing known as artificial neural networks (ANNs), which can be used to solve many statistical problems, including classification problems. The aim of this study was to evaluate the feasibility of ANNs as an evaluation technique of genetic diversity by comparing their performance with that of traditional methods. The discriminant functions were equally ineffective in discriminating the populations, with error rates of 23-82%, thereby preventing the correct discrimination of individuals between populations. The ANN was effective in classifying populations with low and high differentiation, such as those derived from a genetic design established from backcrosses, even in cases of low differentiation of the data sets. The ANN appears to be a promising technique to solve classification problems, since the number of individuals classified incorrectly by the ANN was always lower than that of the discriminant functions. We envisage the potential relevant application of this improved procedure in the genomic classification of markers to distinguish between breeds and accessions.

Multivariate Profiles of Selected versus Non-Selected Elite Youth Brazilian Soccer Players

PubMed Central

Alves, Isabella S.; Padilha, Maickel B.; Casanova, Filipe; Puggina, Enrico F.; Maia, José

2017-01-01

Abstract This study determined whether a multivariate profile more effectively discriminated selected than non-selected elite youth Brazilian soccer players. This examination was carried out on 66 youth soccer players (selected, n = 28, mean age 16.3 ± 0.1; non-selected, n = 38, mean age 16.7 ± 0.4) using objective instruments. Multivariate profiles were assessed through anthropometric characteristics, biological maturation, tactical-technical skills, and motor performance. The Student’s t-test identified that selected players exhibited significantly higher values for height (t = 2.331, p = 0.02), lean body mass (t = 2.441, p = 0.01), and maturity offset (t = 4.559, p < 0.001), as well as performed better in declarative tactical knowledge (t = 10.484, p < 0.001), shooting (t = 2.188, p = 0.03), dribbling (t = 5.914, p < 0.001), speed – 30 m (t = 8.304, p < 0.001), countermovement jump (t = 2.718, p = 0.008), and peak power tests (t = 2.454, p = 0.01). Forward stepwise discriminant function analysis showed that declarative tactical knowledge, running speed –30 m, maturity offset, dribbling, height, and peak power correctly classified 97% of the selected players. These findings may have implications for a highly efficient selection process with objective measures of youth players in soccer clubs. PMID:29339991

A Statistical Discrimination Experiment for Eurasian Events Using a Twenty-Seven-Station Network

DTIC Science & Technology

1980-07-08

to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...the weight assigned to each variable whenever a new one is added. Jennrich, R. I. (1977). Stepwise discriminant analysis , in Statistical Methods for

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.

Multivariate analysis of sexual size dimorphism in local turkeys (Meleagris gallopavo) in Nigeria.

PubMed

Ajayi, Oyeyemi O; Yakubu, Abdulmojeed; Jayeola, Oluwaseun O; Imumorin, Ikhide G; Takeet, Michael I; Ozoje, Michael O; Ikeobi, Christian O N; Peters, Sunday O

2012-06-01

Sexual size dimorphism is a key evolutionary feature that can lead to important biological insights. To improve methods of sexing live birds in the field, we assessed sexual size dimorphism in Nigerian local turkeys (Meleagris gallopavo) using multivariate techniques. Measurements were taken on 125 twenty-week-old birds reared under the intensive management system. The body parameters measured were body weight, body length, breast girth, thigh length, shank length, keel length, wing length and wing span. Univariate analysis revealed that toms (males) had significantly (P < 0.05) higher mean values than hens (females) in all the measured traits. Positive phenotypic correlations between body weight and body measurements ranged from 0.445 to 0.821 in toms and 0.053-0.660 in hens, respectively. Three principal components (PC1, PC2 and PC3) were extracted in toms, each accounting for 63.70%, 19.42% and 5.72% of the total variance, respectively. However, four principal components (PC1, PC2, PC3 and PC4) were extracted in hens, which explained 54.03%, 15.29%, 11.68% and 6.95%, respectively of the generalised variance. A stepwise discriminant function analysis of the eight morphological traits indicated that body weight, body length, tail length and wing span were the most discriminating variables in separating the sexes. The single discriminant function obtained was able to correctly classify 100% of the birds into their source population. The results obtained from the present study could aid future management decisions, ecological studies and conservation of local turkeys in a developing economy.

Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

PubMed

Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

2015-07-08

When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

Depth Discrimination Using Rg-to-Sg Spectral Amplitude Ratios for Seismic Events in Utah Recorded at Local Distances

DOE PAGES

Tibi, Rigobert; Koper, Keith D.; Pankow, Kristine L.; ...

2018-03-20

Most of the commonly used seismic discrimination approaches are designed for regional data. Relatively little attention has focused on discriminants for local distances (< 200 km), the range at which the smallest events are recorded. We take advantage of the variety of seismic sources and the existence of a dense regional seismic network in the Utah region to evaluate amplitude ratio seismic discrimination at local distances. First, we explored phase-amplitude Pg-to-Sg ratios for multiple frequency bands to classify events in a dataset that comprises populations of single-shot surface explosions, shallow and deep ripple-fired mining blasts, mining-induced events, and tectonic earthquakes.more » We achieved a limited success. Then, for the same dataset, we combined the Pg-to-Sg phase-amplitude ratios with Sg-to-Rg spectral amplitude ratios in a multivariate quadratic discriminant function (QDF) approach. For two-category, pairwise classification, seven out of ten population pairs show misclassification rates of about 20% or less, with five pairs showing rates of about 10% or less. The approach performs best for the pair involving the populations of single-shot explosions and mining-induced events. By combining both Pg-to-Sg and Rg-to-Sg ratios in the multivariate QDFs, we are able to achieve an average improvement of about 4–14% in misclassification rates compared to Pg-to-Sg ratios alone. When all five event populations are considered simultaneously, as expected, the potential for misclassification increases and our QDF approach using both Pg-to-Sg and Rg-to-Sg ratios achieves an average success rate of about 74%, compared to the rate of about 86% for two-category, pairwise classification.« less

Depth Discrimination Using Rg-to-Sg Spectral Amplitude Ratios for Seismic Events in Utah Recorded at Local Distances

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

Tibi, Rigobert; Koper, Keith D.; Pankow, Kristine L.

Most of the commonly used seismic discrimination approaches are designed for regional data. Relatively little attention has focused on discriminants for local distances (< 200 km), the range at which the smallest events are recorded. We take advantage of the variety of seismic sources and the existence of a dense regional seismic network in the Utah region to evaluate amplitude ratio seismic discrimination at local distances. First, we explored phase-amplitude Pg-to-Sg ratios for multiple frequency bands to classify events in a dataset that comprises populations of single-shot surface explosions, shallow and deep ripple-fired mining blasts, mining-induced events, and tectonic earthquakes.more » We achieved a limited success. Then, for the same dataset, we combined the Pg-to-Sg phase-amplitude ratios with Sg-to-Rg spectral amplitude ratios in a multivariate quadratic discriminant function (QDF) approach. For two-category, pairwise classification, seven out of ten population pairs show misclassification rates of about 20% or less, with five pairs showing rates of about 10% or less. The approach performs best for the pair involving the populations of single-shot explosions and mining-induced events. By combining both Pg-to-Sg and Rg-to-Sg ratios in the multivariate QDFs, we are able to achieve an average improvement of about 4–14% in misclassification rates compared to Pg-to-Sg ratios alone. When all five event populations are considered simultaneously, as expected, the potential for misclassification increases and our QDF approach using both Pg-to-Sg and Rg-to-Sg ratios achieves an average success rate of about 74%, compared to the rate of about 86% for two-category, pairwise classification.« less

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.

Application of multivariate statistical techniques for differentiation of ripe banana flour based on the composition of elements.

PubMed

Alkarkhi, Abbas F M; Ramli, Saifullah Bin; Easa, Azhar Mat

2009-01-01

Major (sodium, potassium, calcium, magnesium) and minor elements (iron, copper, zinc, manganese) and one heavy metal (lead) of Cavendish banana flour and Dream banana flour were determined, and data were analyzed using multivariate statistical techniques of factor analysis and discriminant analysis. Factor analysis yielded four factors explaining more than 81% of the total variance: the first factor explained 28.73%, comprising magnesium, sodium, and iron; the second factor explained 21.47%, comprising only manganese and copper; the third factor explained 15.66%, comprising zinc and lead; while the fourth factor explained 15.50%, comprising potassium. Discriminant analysis showed that magnesium and sodium exhibited a strong contribution in discriminating the two types of banana flour, affording 100% correct assignation. This study presents the usefulness of multivariate statistical techniques for analysis and interpretation of complex mineral content data from banana flour of different varieties.

Root Cause Analysis of Quality Defects Using HPLC-MS Fingerprint Knowledgebase for Batch-to-batch Quality Control of Herbal Drugs.

PubMed

Yan, Binjun; Fang, Zhonghua; Shen, Lijuan; Qu, Haibin

2015-01-01

The batch-to-batch quality consistency of herbal drugs has always been an important issue. To propose a methodology for batch-to-batch quality control based on HPLC-MS fingerprints and process knowledgebase. The extraction process of Compound E-jiao Oral Liquid was taken as a case study. After establishing the HPLC-MS fingerprint analysis method, the fingerprints of the extract solutions produced under normal and abnormal operation conditions were obtained. Multivariate statistical models were built for fault detection and a discriminant analysis model was built using the probabilistic discriminant partial-least-squares method for fault diagnosis. Based on multivariate statistical analysis, process knowledge was acquired and the cause-effect relationship between process deviations and quality defects was revealed. The quality defects were detected successfully by multivariate statistical control charts and the type of process deviations were diagnosed correctly by discriminant analysis. This work has demonstrated the benefits of combining HPLC-MS fingerprints, process knowledge and multivariate analysis for the quality control of herbal drugs. Copyright © 2015 John Wiley & Sons, Ltd.

Perceived discrimination and self-rated health in Canada: an exploratory study.

PubMed

Du Mont, Janice; Forte, Tonia

2016-08-08

Our objective was to explore whether the link between discrimination and self-rated health status differed as a function of discrimination type, including discrimination based on ethnicity/culture, race, physical appearance (other than skin colour), religion, age, and disability. A sample of 19,422 men and women aged 15 and older was included in this study. A multivariate logistic regression analysis was used to measure the association between perceived discrimination types and self-reported health status defined as excellent/good versus fair/poor. The prevalence of experiencing any discrimination in the past five years was higher among those who rated their health as fair or poor (21.8 %) compared to those who rated their health as excellent or good (14.5 %, p < 0.0001). After controlling for all other covariates, there was a positive association between poorer self-rated health and two of the six specific discrimination variables entered into the model: perceived discrimination based on physical appearance (other than skin colour) (OR = 1.79, 95 % CI: 1.24, 2.58) and perceived discrimination based on a having a disability (OR = 1.59, 95 % CI: 1.04, 2.41). Our main findings indicate that perceived discrimination based on physical appearance and disability may have an adverse impact on health. The results highlight the need for a comprehensive approach to improving health outcomes that should include policies that are targeted against specific types of discrimination.

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

PubMed Central

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

2013-01-01

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

Ensembles of radial basis function networks for spectroscopic detection of cervical precancer

NASA Technical Reports Server (NTRS)

Tumer, K.; Ramanujam, N.; Ghosh, J.; Richards-Kortum, R.

1998-01-01

The mortality related to cervical cancer can be substantially reduced through early detection and treatment. However, current detection techniques, such as Pap smear and colposcopy, fail to achieve a concurrently high sensitivity and specificity. In vivo fluorescence spectroscopy is a technique which quickly, noninvasively and quantitatively probes the biochemical and morphological changes that occur in precancerous tissue. A multivariate statistical algorithm was used to extract clinically useful information from tissue spectra acquired from 361 cervical sites from 95 patients at 337-, 380-, and 460-nm excitation wavelengths. The multivariate statistical analysis was also employed to reduce the number of fluorescence excitation-emission wavelength pairs required to discriminate healthy tissue samples from precancerous tissue samples. The use of connectionist methods such as multilayered perceptrons, radial basis function (RBF) networks, and ensembles of such networks was investigated. RBF ensemble algorithms based on fluorescence spectra potentially provide automated and near real-time implementation of precancer detection in the hands of nonexperts. The results are more reliable, direct, and accurate than those achieved by either human experts or multivariate statistical algorithms.

Vegetation characteristics important to common songbirds in east Texas

USGS Publications Warehouse

Conner, Richard N.; Dickson, James G.; Locke, Brian A.; Segelquist, Charles A.

1983-01-01

Multivariate studies of breeding bird communities have used principal component analysis (PCA) or several-group (three or more groups) discriminant function analysis (DFA) to ordinate bird species on vegetational continua (Cody 1968, James 1971, Whitmore 1975). In community studies, high resolution of habitat requirements for individual species is not always possible with either PCA or several-group DFA. When habitat characteristics of several species are examined with a DFA the resultant axes optimally discriminate among all species simultaneously. Hence, the characteristics assigned to a particular species reflect in part the presence of other species in the analyses. A better resolution of each species' habitat requirements may be obtained from a two-group DFA, wherein habitats selected by a species are discriminated from all other available habitats. Analyses using two-group DFAs to compare habitat used by a species with habitat unused by the same species have the potential to provide an optimal frame of reference from which to examine habitat variables (Martinka 1972, Conner and Adkisson 1976, Whitmore 1981). Mathematically (DFA) it is possible to maximally separate two groups of multivariate observations with a single axis (Harner and whitmore 1977). A line drawn in three or n-dimensional space can easily be positioned to intersect two multivariate means (centroids). If three or more centroids for species are analyzed simultaneously, a single line can no longer intersect all centroids unless a perfectly linear relationship exists for the species being examined. The probability of such an occurrence is extremely low. Thus, a high degree of resolution can be realized when a two-group DFA is used to determine habitat parameters important to individual species. We have used two-group DFA to identify vegetation variable important to 12 common species of songbirds in East Texas.

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

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.

Determination of five active compounds in Artemisia princeps and A. capillaris based on UPLC-DAD and discrimination of two species with multivariate analysis.

PubMed

Yang, Heejung; Lee, Dong Young; Jeon, Minji; Suh, Youngbae; Sung, Sang Hyun

2014-05-01

Five active compounds, chlorogenic acid, 3,5-di-O-caffeoylquinic acid, 4,5-di-O-caffeoylquinic acid, jaceosidin, and eupatilin, in Artemisia princeps (Compositae) were simultaneously determined by ultra-performance liquid chromatography connected to diode array detector. The morphological resemblance between A. princeps and A. capillaris makes it difficult to properly identify species properly. It occasionally leads to misuse or misapplication in Korean traditional medicine. In the study, the discrimination between A. princeps and A. capillaris was optimally performed by the developed validation method, which resulted in definitely a difference between two species. Also, it was developed the most reliable markers contributing to the discrimination of two species by the multivariate analysis methods, such as a principal component analysis and a partial least squares discrimination analysis.

Discrimination of lichen genera and species using element concentrations

USGS Publications Warehouse

Bennett, James P.

2008-01-01

The importance of organic chemistry in the classification of lichens is well established, but inorganic chemistry has been largely overlooked. Six lichen species were studied over a period of 23 years that were growing in 11 protected areas of the northern Great Lakes ecoregion, which were not greatly influenced by anthropogenic particulates or gaseous air pollutants. The elemental data from these studies were aggregated in order to test the hypothesis that differences among species in tissue element concentrations were large enough to discriminate between taxa faithfully. Concentrations of 16 chemical elements that were found in tissue samples from Cladonia rangiferina, Evernia mesomorpha, Flavopunctelia flaventior, Hypogymnia physodes, Parmelia sulcata, and Punctelia rudecta were analyzed statistically using multivariate discriminant functions and CART analyses, as well as t-tests. Genera and species were clearly separated in element space, and elemental discriminant functions were able to classify 91-100 of the samples correctly into species. At the broadest level, a Zn concentration of 51 ppm in tissues of four of the lichen species effectively discriminated foliose from fruticose species. Similarly, a S concentration of 680 ppm discriminated C. rangiferina and E. mesomorpha, and a Ca concentration of 10 436 ppm discriminated H. physodes from P. sulcata. For the three parmelioid species, a Ca concentration >32 837 ppm discriminated Punctelia rudecta from the other two species, while a Zn concentration of 56 ppm discriminated Parmelia sulcata from F. flaventior. Foliose species also had higher concentrations than did fruticose species of all elements except Na. Elemental signatures for each of the six species were developed using standardized means. Twenty-four mechanisms explaining the differences among species are summarized. Finally, the relationships of four species based on element concentrations, using additive-trees clustering of a Euclidean-distance matrix, produced identical relationships as did analyses based on secondary product chemistry that used additive-trees clustering of a Jaccard similarity matrix. At least for these six species, element composition has taxonomic significance, and may be useful for discriminating other taxa.

Health care workplace discrimination and physician turnover.

PubMed

Nunez-Smith, Marcella; Pilgrim, Nanlesta; Wynia, Matthew; Desai, Mayur M; Bright, Cedric; Krumholz, Harlan M; Bradley, Elizabeth H

2009-12-01

To examine the association between physician race/ ethnicity, workplace discrimination, and physician job turnover. Cross-sectional, national survey conducted in 2006-2007 of practicing physicians (n = 529) randomly identified via the American Medical Association Masterfile and the National Medical Association membership roster. We assessed the relationships between career racial/ethnic discrimination at work and several career-related dependent variables, including 2 measures of physician turnover, career satisfaction, and contemplation of career change. We used standard frequency analyses, odds ratios and chi2 statistics, and multivariate logistic regression modeling to evaluate these associations. Physicians who self-identified as nonmajority were significantly more likely to have left at least 1 job because of workplace discrimination (black, 29%; Asian, 24%; other race, 21%; Hispanic/Latino, 20%; white, 9%). In multivariate models, having experienced racial/ethnic discrimination at work was associated with high job turnover (adjusted odds ratio, 2.7; 95% CI, 1.4-4.9). Among physicians who experienced workplace discrimination, only 45% of physicians were satisfied with their careers (vs 88% among those who had not experienced workplace discrimination, p value < .01), and 40% were contemplating a career change (vs 10% among those who had not experienced workplace discrimination, p value < .001). Workplace discrimination is associated with physician job turnover, career dissatisfaction, and contemplation of career change. These findings underscore the importance of monitoring for workplace discrimination and responding when opportunities for intervention and retention still exist.

The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis.

PubMed

Corvucci, Francesca; Nobili, Lara; Melucci, Dora; Grillenzoni, Francesca-Vittoria

2015-02-15

Honey traceability to food quality is required by consumers and food control institutions. Melissopalynologists traditionally use percentages of nectariferous pollens to discriminate the botanical origin and the entire pollen spectrum (presence/absence, type and quantities and association of some pollen types) to determinate the geographical origin of honeys. To improve melissopalynological routine analysis, principal components analysis (PCA) was used. A remarkable and innovative result was that the most significant pollens for the traditional discrimination of the botanical and geographical origin of honeys were the same as those individuated with the chemometric model. The reliability of assignments of samples to honey classes was estimated through explained variance (85%). This confirms that the chemometric model properly describes the melissopalynological data. With the aim to improve honey discrimination, FT-microRaman spectrography and multivariate analysis were also applied. Well performing PCA models and good agreement with known classes were achieved. Encouraging results were obtained for botanical discrimination. Copyright © 2014 Elsevier Ltd. All rights reserved.

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

Association Between Perceived Discrimination and Racial/Ethnic Disparities in Problem Behaviors Among Preadolescent Youths

PubMed Central

Elliott, Marc N.; Kanouse, David E.; Klein, David J.; Davies, Susan L.; Cuccaro, Paula M.; Banspach, Stephen W.; Peskin, Melissa F.; Schuster, Mark A.

2013-01-01

Objectives. We examined the contribution of perceived racial/ethnic discrimination to disparities in problem behaviors among preadolescent Black, Latino, and White youths. Methods. We used cross-sectional data from Healthy Passages, a 3-community study of 5119 fifth graders and their parents from August 2004 through September 2006 in Birmingham, Alabama; Los Angeles County, California; and Houston, Texas. We used multivariate regressions to examine the relationships of perceived racial/ethnic discrimination and race/ethnicity to problem behaviors. We used values from these regressions to calculate the percentage of disparities in problem behaviors associated with the discrimination effect. Results. In multivariate models, perceived discrimination was associated with greater problem behaviors among Black and Latino youths. Compared with Whites, Blacks were significantly more likely to report problem behaviors, whereas Latinos were significantly less likely (a “reverse disparity”). When we set Blacks’ and Latinos’ discrimination experiences to zero, the adjusted disparity between Blacks and Whites was reduced by an estimated one third to two thirds; the reverse adjusted disparity favoring Latinos widened by about one fifth to one half. Conclusions. Eliminating discrimination could considerably reduce mental health issues, including problem behaviors, among Black and Latino youths. PMID:23597387

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.

Discrimination of cultivation ages and cultivars of ginseng leaves using Fourier transform infrared spectroscopy combined with multivariate analysis

PubMed Central

Kwon, Yong-Kook; Ahn, Myung Suk; Park, Jong Suk; Liu, Jang Ryol; In, Dong Su; Min, Byung Whan; Kim, Suk Weon

2013-01-01

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng. PMID:24558311

Perceived Discrimination and Mental Health Symptoms among Black Men with HIV

PubMed Central

Bogart, Laura M.; Wagner, Glenn J.; Galvan, Frank H.; Landrine, Hope; Klein, David J.; Sticklor, Laurel A.

2011-01-01

Objective People living with HIV (PLWH) exhibit more severe mental health symptoms than do members of the general public (including depression and post-traumatic stress disorder/PTSD symptoms). We examined whether perceived discrimination, which has been associated with poor mental health in prior research, contributes to greater depression and PTSD symptoms among HIV-positive Black men who have sex with men (MSM), who are at high risk for discrimination from multiple stigmatized characteristics (HIV-serostatus, race/ethnicity, sexual orientation). Method A total of 181 Black MSM living with HIV completed audio computer-assisted self-interviews (ACASI) that included measures of mental health symptoms (depression, PTSD) and scales assessing perceived discrimination due to HIV-serostatus, race/ethnicity, and sexual orientation. Results In bivariate tests, all three perceived discrimination scales were significantly associated with greater symptoms of depression and PTSD (i.e., re-experiencing, avoidance, and arousal subscales) (all p-values < .05). The multivariate model for depression yielded a three-way interaction among all three discrimination types (p < .01), indicating that perceived racial discrimination was negatively associated with depression symptoms when considered in isolation from other forms of discrimination, but positively associated when all three types of discrimination were present. In multivariate tests, only perceived HIV-related discrimination was associated with PTSD symptoms (p < .05). Conclusion Findings suggest that some types of perceived discrimination contribute to poor mental health among PLWH. Researchers need to take into account intersecting stigmas when developing interventions to improve mental health among PLWH. PMID:21787061

Perceived discrimination and mental health symptoms among Black men with HIV.

PubMed

Bogart, Laura M; Wagner, Glenn J; Galvan, Frank H; Landrine, Hope; Klein, David J; Sticklor, Laurel A

2011-07-01

People living with HIV (PLWH) exhibit more severe mental health symptoms, including depression and posttraumatic stress disorder (PTSD) symptoms, than do members of the general public. We examined whether perceived discrimination, which has been associated with poor mental health in prior research, contributes to greater depression and PTSD symptoms among HIV-positive Black men who have sex with men (MSM), who are at high risk for discrimination from multiple stigmatized characteristics (HIV-serostatus, race/ethnicity, sexual orientation). A total of 181 Black MSM living with HIV completed audio computer-assisted self-interviews (ACASI) that included measures of mental health symptoms (depression, PTSD) and scales assessing perceived discrimination due to HIV-serostatus, race/ethnicity, and sexual orientation. In bivariate tests, all three perceived discrimination scales were significantly associated with greater symptoms of depression and PTSD (i.e., reexperiencing, avoidance, and arousal subscales; all p values < .05). The multivariate model for depression yielded a three-way interaction among all three discrimination types (p < .01), indicating that perceived racial discrimination was negatively associated with depression symptoms when considered in isolation from other forms of discrimination, but positively associated when all three types of discrimination were present. In multivariate tests, only perceived HIV-related discrimination was associated with PTSD symptoms (p < .05). Findings suggest that some types of perceived discrimination contribute to poor mental health among PLWH. Researchers need to take into account intersecting stigmata when developing interventions to improve mental health among PLWH.

Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Manfredi, Marcello; Robotti, Elisa; Quasso, Fabio; Mazzucco, Eleonora; Calabrese, Giorgio; Marengo, Emilio

2018-01-01

The authentication and traceability of hazelnuts is very important for both the consumer and the food industry, to safeguard the protected varieties and the food quality. This study investigates the use of a portable FTIR spectrometer coupled to multivariate statistical analysis for the classification of raw hazelnuts. The method discriminates hazelnuts from different origins/cultivars based on differences of the signal intensities of their IR spectra. The multivariate classification methods, namely principal component analysis (PCA) followed by linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA), with or without variable selection, allowed a very good discrimination among the groups, with PLS-DA coupled to variable selection providing the best results. Due to the fast analysis, high sensitivity, simplicity and no sample preparation, the proposed analytical methodology could be successfully used to verify the cultivar of hazelnuts, and the analysis can be performed quickly and directly on site.

Analysis of laser printer and photocopier toners by spectral properties and chemometrics

NASA Astrophysics Data System (ADS)

Verma, Neha; Kumar, Raj; Sharma, Vishal

2018-05-01

The use of printers to generate falsified documents has become a common practice in today's world. The examination and identification of the printed matter in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the document. In the present study, a total number of 100 black toner samples both from laser printers and photocopiers were examined using diffuse reflectance UV-Vis Spectroscopy. The present research is divided into two parts; visual discrimination and discrimination by using multivariate analysis. A comparison between qualitative and quantitative analysis showed that multivariate analysis (Principal component analysis) provides 99.59%pair-wise discriminating power for laser printer toners while 99.84% pair-wise discriminating power for photocopier toners. The overall results obtained confirm the applicability of UV-Vis spectroscopy and chemometrics, in the nondestructive analysis of toner printed documents while enhancing their evidential value for forensic applications.

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

NASA Astrophysics Data System (ADS)

Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

2015-03-01

Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

Health Care Workplace Discrimination and Physician Turnover

PubMed Central

Nunez-Smith, Marcella; Pilgrim, Nanlesta; Wynia, Matthew; Desai, Mayur M.; Bright, Cedric; Krumholz, Harlan M.; Bradley, Elizabeth H.

2013-01-01

Objective To examine the association between physician race/ethnicity, workplace discrimination, and physician job turnover. Methods Cross-sectional, national survey conducted in 2006–2007 of practicing physicians [n = 529] randomly identified via the American Medical Association Masterfile and The National Medical Association membership roster. We assessed the relationships between career racial/ethnic discrimination at work and several career-related dependent variables, including 2 measures of physician turnover, career satisfaction, and contemplation of career change. We used standard frequency analyses, odds ratios and χ2 statistics, and multivariate logistic regression modeling to evaluate these associations. Results Physicians who self-identified as nonmajority were significantly more likely to have left at least 1 job because of workplace discrimination (black, 29%; Asian, 24%; other race, 21%; Hispanic/Latino, 20%; white, 9%). In multivariate models, having experienced racial/ethnic discrimination at work was associated with high job turnover [adjusted odes ratio, 2.7; 95% CI, 1.4–4.9]. Among physicians who experienced work-place discrimination, only 45% of physicians were satisfied with their careers (vs 88% among those who had not experienced workplace discrimination, p value < .01], and 40% were con-templating a career change (vs 10% among those who had not experienced workplace discrimination, p value < .001). Conclusion Workplace discrimination is associated with physician job turnover, career dissatisfaction, and contemplation of career change. These findings underscore the importance of monitoring for workplace discrimination and responding when opportunities for intervention and retention still exist. PMID:20070016

Gap Shape Classification using Landscape Indices and Multivariate Statistics

PubMed Central

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-01-01

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks’ lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap. PMID:27901127

Gap Shape Classification using Landscape Indices and Multivariate Statistics.

PubMed

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-11-30

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks' lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap.

MEMD-enhanced multivariate fuzzy entropy for the evaluation of complexity in biomedical signals.

PubMed

Azami, Hamed; Smith, Keith; Escudero, Javier

2016-08-01

Multivariate multiscale entropy (mvMSE) has been proposed as a combination of the coarse-graining process and multivariate sample entropy (mvSE) to quantify the irregularity of multivariate signals. However, both the coarse-graining process and mvSE may not be reliable for short signals. Although the coarse-graining process can be replaced with multivariate empirical mode decomposition (MEMD), the relative instability of mvSE for short signals remains a problem. Here, we address this issue by proposing the multivariate fuzzy entropy (mvFE) with a new fuzzy membership function. The results using white Gaussian noise show that the mvFE leads to more reliable and stable results, especially for short signals, in comparison with mvSE. Accordingly, we propose MEMD-enhanced mvFE to quantify the complexity of signals. The characteristics of brain regions influenced by partial epilepsy are investigated by focal and non-focal electroencephalogram (EEG) time series. In this sense, the proposed MEMD-enhanced mvFE and mvSE are employed to discriminate focal EEG signals from non-focal ones. The results demonstrate the MEMD-enhanced mvFE values have a smaller coefficient of variation in comparison with those obtained by the MEMD-enhanced mvSE, even for long signals. The results also show that the MEMD-enhanced mvFE has better performance to quantify focal and non-focal signals compared with multivariate multiscale permutation entropy.

Application of multivariate statistics to vestibular testing: discriminating between Meniere's disease and migraine associated dizziness

NASA Technical Reports Server (NTRS)

Dimitri, P. S.; Wall, C. 3rd; Oas, J. G.; Rauch, S. D.

2001-01-01

Meniere's disease (MD) and migraine associated dizziness (MAD) are two disorders that can have similar symptomatologies, but differ vastly in treatment. Vestibular testing is sometimes used to help differentiate between these disorders, but the inefficiency of a human interpreter analyzing a multitude of variables independently decreases its utility. Our hypothesis was that we could objectively discriminate between patients with MD and those with MAD using select variables from the vestibular test battery. Sinusoidal harmonic acceleration test variables were reduced to three vestibulo-ocular reflex physiologic parameters: gain, time constant, and asymmetry. A combination of these parameters plus a measurement of reduced vestibular response from caloric testing allowed us to achieve a joint classification rate of 91%, independent quadratic classification algorithm. Data from posturography were not useful for this type of differentiation. Overall, our classification function can be used as an unbiased assistant to discriminate between MD and MAD and gave us insight into the pathophysiologic differences between the two disorders.

Discriminant analysis in wildlife research: Theory and applications

USGS Publications Warehouse

Williams, B.K.; Capen, D.E.

1981-01-01

Discriminant analysis, a method of analyzing grouped multivariate data, is often used in ecological investigations. It has both a predictive and an explanatory function, the former aiming at classification of individuals of unknown group membership. The goal of the latter function is to exhibit group separation by means of linear transforms, and the corresponding method is called canonical analysis. This discussion focuses on the application of canonical analysis in ecology. In order to clarify its meaning, a parametric approach is taken instead of the usual data-based formulation. For certain assumptions the data-based canonical variates are shown to result from maximum likelihood estimation, thus insuring consistency and asymptotic efficiency. The distorting effects of covariance heterogeneity are examined, as are certain difficulties which arise in interpreting the canonical functions. A 'distortion metric' is defined, by means of which distortions resulting from the canonical transformation can be assessed. Several sampling problems which arise in ecological applications are considered. It is concluded that the method may prove valuable for data exploration, but is of limited value as an inferential procedure.

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.

Racial and ethnic health disparities: evidence of discrimination's effects across the SEP spectrum.

PubMed

D'Anna, Laura Hoyt; Ponce, Ninez A; Siegel, Judith M

2010-04-01

Perceived discrimination is a psychosocial stressor that plays a role in explaining racial/ethnic disparities in self-reported physical and mental health. The purpose of this paper is: (1) to investigate the association between perceived discrimination in receiving healthcare and racial/ethnic disparities in self-rated health status, physical, and emotional functional limitations among a diverse sample of California adults; (2) to assess whether discrimination effects vary by racial/ethnic group and gender; and (3) to evaluate how the effects of discrimination on health are manifest across the socioeconomic position (SEP) spectrum. Data were drawn from the 2001 California Health Interview Survey adult file (n=55,428). The analytic approach employed multivariate linear and logistic regressions. Discrimination is qualitatively identified into two types: (1) discrimination due to race/ethnicity, language, or accent, and (2) other discrimination. Findings show that both types of discrimination negatively influenced self-rated health, and were associated with a two to three-fold odds of limitations in physical and emotional health. Further, these effects varied by racial/ethnic group and gender, and the effects were mixed. Most notably, for emotional health, racial/ethnic discrimination penalized Latinas more than non-Latina Whites, but for physical health, other discrimination was less detrimental to Latinas than it was to non-Latina Whites. At higher levels of SEP, the effects of racial/ethnic discrimination on self-rated health and other discriminations' effects on physical health were attenuated. Higher SEP may serve as an important mitigator, particularly when comparing the medium to the low SEP categories. It is also possible that SEP effects cannot be extracted from the relationships of interest in that SEP is an expression of social discrimination. In fact, negative health effects associated with discrimination are evident across the SEP spectrum. This study highlights the complexity of the relationships between discrimination and racial/ethnic identity, gender, and SEP.

Age, Body Mass Index, and Daytime and Nocturnal Hypoxia as Predictors of Hypertension in Patients With Obstructive Sleep Apnea.

PubMed

Natsios, Georgios; Pastaka, Chaido; Vavougios, Georgios; Zarogiannis, Sotirios G; Tsolaki, Vasiliki; Dimoulis, Andreas; Seitanidis, Georgios; Gourgoulianis, Konstantinos I

2016-02-01

A growing body of evidence links obstructive sleep apnea (OSA) with hypertension. The authors performed a retrospective cohort study using the University Hospital of Larissa Sleep Apnea Database (1501 patients) to determine predictors of in-laboratory diagnosed OSA for development of hypertension. Differences in continuous variables were assessed via independent samples t test, whereas discrete variables were compared by Pearson's chi-square test. Multivariate analysis was performed via discriminant function analysis. There were several significant differences between hypertensive and normotensive patients. Age, body mass index, comorbidity, daytime oxygen saturation, and indices of hypoxia during sleep were deemed the most accurate predictors of hypertension, whereas apnea-hypopnea index and desaturation index were not. The single derived discriminant function was statistically significant (Wilk's lambda=0.771, χ(2) =289.070, P<.0001). Daytime and nocturnal hypoxia as consequences of chronic intermittent hypoxia play a central role in OSA-related hypertension and should be further evaluated as possible severity markers in OSA. ©2015 Wiley Periodicals, Inc.

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.

Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods.

PubMed

Jiménez-Carvelo, Ana M; González-Casado, Antonio; Pérez-Castaño, Estefanía; Cuadros-Rodríguez, Luis

2017-03-01

A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Kullback-Leibler information function and the sequential selection of experiments to discriminate among several linear models

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

The error variance of the process prior multivariate normal distributions of the parameters of the models are assumed to be specified, prior probabilities of the models being correct. A rule for termination of sampling is proposed. Upon termination, the model with the largest posterior probability is chosen as correct. If sampling is not terminated, posterior probabilities of the models and posterior distributions of the parameters are computed. An experiment was chosen to maximize the expected Kullback-Leibler information function. Monte Carlo simulation experiments were performed to investigate large and small sample behavior of the sequential adaptive procedure.

Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study.

PubMed

Prabitha, Vasumathi Gopala; Suchetha, Sambasivan; Jayanthi, Jayaraj Lalitha; Baiju, Kamalasanan Vijayakumary; Rema, Prabhakaran; Anuraj, Koyippurath; Mathews, Anita; Sebastian, Paul; Subhash, Narayanan

2016-01-01

Diffuse reflectance (DR) spectroscopy is a non-invasive, real-time, and cost-effective tool for early detection of malignant changes in squamous epithelial tissues. The present study aims to evaluate the diagnostic power of diffuse reflectance spectroscopy for non-invasive discrimination of cervical lesions in vivo. A clinical trial was carried out on 48 sites in 34 patients by recording DR spectra using a point-monitoring device with white light illumination. The acquired data were analyzed and classified using multivariate statistical analysis based on principal component analysis (PCA) and linear discriminant analysis (LDA). Diagnostic accuracies were validated using random number generators. The receiver operating characteristic (ROC) curves were plotted for evaluating the discriminating power of the proposed statistical technique. An algorithm was developed and used to classify non-diseased (normal) from diseased sites (abnormal) with a sensitivity of 72 % and specificity of 87 %. While low-grade squamous intraepithelial lesion (LSIL) could be discriminated from normal with a sensitivity of 56 % and specificity of 80 %, and high-grade squamous intraepithelial lesion (HSIL) from normal with a sensitivity of 89 % and specificity of 97 %, LSIL could be discriminated from HSIL with 100 % sensitivity and specificity. The areas under the ROC curves were 0.993 (95 % confidence interval (CI) 0.0 to 1) and 1 (95 % CI 1) for the discrimination of HSIL from normal and HSIL from LSIL, respectively. The results of the study show that DR spectroscopy could be used along with multivariate analytical techniques as a non-invasive technique to monitor cervical disease status in real time.

Morphometric analysis of sex differences in contemporary Japanese pelves using multidetector computed tomography.

PubMed

Torimitsu, Suguru; Makino, Yohsuke; Saitoh, Hisako; Sakuma, Ayaka; Ishii, Namiko; Yajima, Daisuke; Inokuchi, Go; Motomura, Ayumi; Chiba, Fumiko; Yamaguchi, Rutsuko; Hashimoto, Mari; Hoshioka, Yumi; Iwase, Hirotaro

2015-12-01

Sex estimation of decomposed or skeletal remains is clearly important in forensic contexts. Recently, contemporary population-specific data has been obtained using multidetector computed tomography (MDCT) scanning. The main purpose of this study was to investigate skeletal pelvic dimorphism in a contemporary Japanese forensic sample and to quantify the accuracy of sex estimation using various pelvic measurements obtained from three-dimensional (3D) CT images. This study used a total of 208 cadavers (104 males, 104 females) of which postmortem CT scanning and subsequent forensic autopsy were conducted between December 2011 and August 2014. Eleven measurements of each pelvis were obtained from 3D CT reconstructed images that extracted only bone data. The measurements were analyzed using descriptive statistics and discriminant function analyses. All except one measurement were dimorphic in terms of sex differences. Univariate discriminant function analyses using these measurements provided sex classification accuracy rates of 62.0-98.1%. The subpubic angle was found to contribute most significantly to accurate sex estimation. Multivariate discriminant functions yielded sex prediction accuracy rates of 63.9-98.1%. In conclusion, the pelvic measurements obtained from 3D CT images of a contemporary Japanese population successfully demonstrated sexual dimorphism and may be useful for the estimation of skeletal sex in the field of forensic anthropology. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Generalized t-statistic for two-group classification.

PubMed

Komori, Osamu; Eguchi, Shinto; Copas, John B

2015-06-01

In the classic discriminant model of two multivariate normal distributions with equal variance matrices, the linear discriminant function is optimal both in terms of the log likelihood ratio and in terms of maximizing the standardized difference (the t-statistic) between the means of the two distributions. In a typical case-control study, normality may be sensible for the control sample but heterogeneity and uncertainty in diagnosis may suggest that a more flexible model is needed for the cases. We generalize the t-statistic approach by finding the linear function which maximizes a standardized difference but with data from one of the groups (the cases) filtered by a possibly nonlinear function U. We study conditions for consistency of the method and find the function U which is optimal in the sense of asymptotic efficiency. Optimality may also extend to other measures of discriminatory efficiency such as the area under the receiver operating characteristic curve. The optimal function U depends on a scalar probability density function which can be estimated non-parametrically using a standard numerical algorithm. A lasso-like version for variable selection is implemented by adding L1-regularization to the generalized t-statistic. Two microarray data sets in the study of asthma and various cancers are used as motivating examples. © 2014, The International Biometric Society.

Discrimination of lichen genera and species using element concentrations

USGS Publications Warehouse

Bennett, J.P.

2008-01-01

The importance of organic chemistry in the classification of lichens is well established, but inorganic chemistry has been largely overlooked. Six lichen species were studied over a period of 23 years that were growing in 11 protected areas of the northern Great Lakes ecoregion, which were not greatly influenced by anthropogenic particulates or gaseous air pollutants. The elemental data from these studies were aggregated in order to test the hypothesis that differences among species in tissue element concentrations were large enough to discriminate between taxa faithfully. Concentrations of 16 chemical elements that were found in tissue samples from Cladonia rangiferina, Evernia mesomorpha, Flavopunctelia flaventior, Hypogymnia physodes, Parmelia sulcata, and Punctelia rudecta were analyzed statistically using multivariate discriminant functions and CART analyses, as well as t-tests. Genera and species were clearly separated in element space, and elemental discriminant functions were able to classify 91-100 of the samples correctly into species. At the broadest level, a Zn concentration of 51 ppm in tissues of four of the lichen species effectively discriminated foliose from fruticose species. Similarly, a S concentration of 680 ppm discriminated C. rangiferina and E. mesomorpha, and a Ca concentration of 10 436 ppm discriminated H. physodes from P. sulcata. For the three parmelioid species, a Ca concentration >32 837 ppm discriminated Punctelia rudecta from the other two species, while a Zn concentration of 56 ppm discriminated Parmelia sulcata from F. flaventior. Foliose species also had higher concentrations than did fruticose species of all elements except Na. Elemental signatures for each of the six species were developed using standardized means. Twenty-four mechanisms explaining the differences among species are summarized. Finally, the relationships of four species based on element concentrations, using additive-trees clustering of a Euclidean-distance matrix, produced identical relationships as did analyses based on secondary product chemistry that used additive-trees clustering of a Jaccard similarity matrix. At least for these six species, element composition has taxonomic significance, and may be useful for discriminating other taxa. ?? 2008 British Lichen Society.

Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback

PubMed Central

Cisler, Josh M.; Bush, Keith; James, G. Andrew; Smitherman, Sonet; Kilts, Clinton D.

2015-01-01

Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD. PMID:26241958

Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback.

PubMed

Cisler, Josh M; Bush, Keith; James, G Andrew; Smitherman, Sonet; Kilts, Clinton D

2015-01-01

Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD.

[The influence of perceived discrimination on health in migrants].

PubMed

Igel, Ulrike; Brähler, Elmar; Grande, Gesine

2010-05-01

The aim of the study was to investigate the influence of racial discrimination on subjective health in migrants. The sample included 1.844 migrants from the SOEP. Discrimination was assessed by two items. Socioeconomic status, country of origin, and health behavior were included in multivariate regression models to control for effects on health. Differential models with regard to gender and origin were analysed. Migrants who experienced discrimination report a worse health status. Discrimination determines mental and physical health of migrants. There are differences in models due to gender and origin. In addition to socioeconomic factors experienced discrimination should be taken into account as a psycho-social stressor of migrants.

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes.

PubMed

Motegi, Hiromi; Tsuboi, Yuuri; Saga, Ayako; Kagami, Tomoko; Inoue, Maki; Toki, Hideaki; Minowa, Osamu; Noda, Tetsuo; Kikuchi, Jun

2015-11-04

There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance ((1)H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets.

Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

PubMed

Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

2017-07-01

Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Discrimination of irradiated MOX fuel from UOX fuel by multivariate statistical analysis of simulated activities of gamma-emitting isotopes

NASA Astrophysics Data System (ADS)

Åberg Lindell, M.; Andersson, P.; Grape, S.; Hellesen, C.; Håkansson, A.; Thulin, M.

2018-03-01

This paper investigates how concentrations of certain fission products and their related gamma-ray emissions can be used to discriminate between uranium oxide (UOX) and mixed oxide (MOX) type fuel. Discrimination of irradiated MOX fuel from irradiated UOX fuel is important in nuclear facilities and for transport of nuclear fuel, for purposes of both criticality safety and nuclear safeguards. Although facility operators keep records on the identity and properties of each fuel, tools for nuclear safeguards inspectors that enable independent verification of the fuel are critical in the recovery of continuity of knowledge, should it be lost. A discrimination methodology for classification of UOX and MOX fuel, based on passive gamma-ray spectroscopy data and multivariate analysis methods, is presented. Nuclear fuels and their gamma-ray emissions were simulated in the Monte Carlo code Serpent, and the resulting data was used as input to train seven different multivariate classification techniques. The trained classifiers were subsequently implemented and evaluated with respect to their capabilities to correctly predict the classes of unknown fuel items. The best results concerning successful discrimination of UOX and MOX-fuel were acquired when using non-linear classification techniques, such as the k nearest neighbors method and the Gaussian kernel support vector machine. For fuel with cooling times up to 20 years, when it is considered that gamma-rays from the isotope 134Cs can still be efficiently measured, success rates of 100% were obtained. A sensitivity analysis indicated that these methods were also robust.

Ties that bind: community attachment and the experience of discrimination among Black men who have sex with men

PubMed Central

Van Sluytman, Laurens; Spikes, Pilgrim; Nandi, Vijay; Van Tieu, Hong; Frye, Victoria; Patterson, Jocelyn; Koblin, Beryl

2015-01-01

In the USA, the impact of psychological distress may be greater for Black men who have sex with men given that they may experience both racial discrimination in society at large and discrimination due to sexual orientation within Black communities. Attachments to community members may play a role in addressing psychological distress for members of this vulnerable population. This analysis is based on 312 Black men who have sex with men recruited for a behavioural intervention trial in New York City. Analyses were conducted using bivariate and multivariable logistic regression to examine the relationship of discrimination and community attachment to psychological distress. Most participants (63%) reported exposure to both discrimination due to race and sexual orientation. However, a majority of participants (89%) also reported racial and/or sexual orientation community attachment. Psychological distress was significant and negatively associated with older age (40 years and above), being a high school graduate and having racial and/or sexual orientation community attachments. Psychological distress was significantly and positively associated with being HIV-positive and experiencing both racial and sexual orientation discrimination. Similar results were found in the multivariable model. Susceptibility to disparate psychological distress outcomes must be understood in relation to social membership, including its particular norms, structures and ecological milieu. PMID:25647586

Ties that bind: community attachment and the experience of discrimination among Black men who have sex with men.

PubMed

Van Sluytman, Laurens; Spikes, Pilgrim; Nandi, Vijay; Van Tieu, Hong; Frye, Victoria; Patterson, Jocelyn; Koblin, Beryl

2015-01-01

In the USA, the impact of psychological distress may be greater for Black men who have sex with men given that they may experience both racial discrimination in society at large and discrimination due to sexual orientation within Black communities. Attachments to community members may play a role in addressing psychological distress for members of this vulnerable population. This analysis is based on 312 Black men who have sex with men recruited for a behavioural intervention trial in New York City. Analyses were conducted using bivariate and multivariable logistic regression to examine the relationship of discrimination and community attachment to psychological distress. Most participants (63%) reported exposure to both discrimination due to race and sexual orientation. However, a majority of participants (89%) also reported racial and/or sexual orientation community attachment. Psychological distress was significant and negatively associated with older age (40 years and above), being a high school graduate and having racial and/or sexual orientation community attachments. Psychological distress was significantly and positively associated with being HIV-positive and experiencing both racial and sexual orientation discrimination. Similar results were found in the multivariable model. Susceptibility to disparate psychological distress outcomes must be understood in relation to social membership, including its particular norms, structures and ecological milieu.

Multivariate calibration on NIR data: development of a model for the rapid evaluation of ethanol content in bakery products.

PubMed

Bello, Alessandra; Bianchi, Federica; Careri, Maria; Giannetto, Marco; Mori, Giovanni; Musci, Marilena

2007-11-05

A new NIR method based on multivariate calibration for determination of ethanol in industrially packed wholemeal bread was developed and validated. GC-FID was used as reference method for the determination of actual ethanol concentration of different samples of wholemeal bread with proper content of added ethanol, ranging from 0 to 3.5% (w/w). Stepwise discriminant analysis was carried out on the NIR dataset, in order to reduce the number of original variables by selecting those that were able to discriminate between the samples of different ethanol concentrations. With the so selected variables a multivariate calibration model was then obtained by multiple linear regression. The prediction power of the linear model was optimized by a new "leave one out" method, so that the number of original variables resulted further reduced.

Analyzing Faculty Salaries When Statistics Fail.

ERIC Educational Resources Information Center

Simpson, William A.

The role played by nonstatistical procedures, in contrast to multivariant statistical approaches, in analyzing faculty salaries is discussed. Multivariant statistical methods are usually used to establish or defend against prima facia cases of gender and ethnic discrimination with respect to faculty salaries. These techniques are not applicable,…

Atrial Electrogram Fractionation Distribution before and after Pulmonary Vein Isolation in Human Persistent Atrial Fibrillation-A Retrospective Multivariate Statistical Analysis.

PubMed

Almeida, Tiago P; Chu, Gavin S; Li, Xin; Dastagir, Nawshin; Tuan, Jiun H; Stafford, Peter J; Schlindwein, Fernando S; Ng, G André

2017-01-01

Purpose: Complex fractionated atrial electrograms (CFAE)-guided ablation after pulmonary vein isolation (PVI) has been used for persistent atrial fibrillation (persAF) therapy. This strategy has shown suboptimal outcomes due to, among other factors, undetected changes in the atrial tissue following PVI. In the present work, we investigate CFAE distribution before and after PVI in patients with persAF using a multivariate statistical model. Methods: 207 pairs of atrial electrograms (AEGs) were collected before and after PVI respectively, from corresponding LA regions in 18 persAF patients. Twelve attributes were measured from the AEGs, before and after PVI. Statistical models based on multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) have been used to characterize the atrial regions and AEGs. Results: PVI significantly reduced CFAEs in the LA (70 vs. 40%; P < 0.0001). Four types of LA regions were identified, based on the AEGs characteristics: (i) fractionated before PVI that remained fractionated after PVI (31% of the collected points); (ii) fractionated that converted to normal (39%); (iii) normal prior to PVI that became fractionated (9%) and; (iv) normal that remained normal (21%). Individually, the attributes failed to distinguish these LA regions, but multivariate statistical models were effective in their discrimination ( P < 0.0001). Conclusion: Our results have unveiled that there are LA regions resistant to PVI, while others are affected by it. Although, traditional methods were unable to identify these different regions, the proposed multivariate statistical model discriminated LA regions resistant to PVI from those affected by it without prior ablation information.

Balance measured by the sway balance smart-device application does not discriminate between older persons with and without a fall history.

PubMed

Vincenzo, Jennifer L; Glenn, Jordan M; Gray, Stephanie M; Gray, Michelle

2016-08-01

Clinical functional assessments of balance often lack specificity and sensitivity in discriminating and predicting falls among community-dwelling older adults. We determined the feasibility of using a smart-device application measuring balance to discriminate fall status among older adults. We also evaluated differences between smart-device balance measurements when secured with or without a harness. A cross-sectional study design to determine the ability of the Sway Balance smart-device application (SWAY) to discriminate older adults based on fall history. The Berg Balance Scale (BBS) and Activities-Specific Balance Confidence Scale (ABC) were used as comparative, clinically based assessments. Community-dwelling older adults with (n = 25) and without (n = 32) a history of fall(s) participated. Multivariate analysis of variance was used to determine differences among assessments based on fall history. Logistic regression models determined the ability of each assessment to discriminate fall history. Older adults with and without a history of falls were not significantly different on SWAY (P = 0.92) but were different on BBS (P = 0.01), and ABC (P < 0.001). Similarly, SWAY did not discriminate fall history (P = 0.92), while BBS and ABC both discriminated fall history (P < 0.01). Paired t tests between SWAY scores with and without a harness indicated no differences (P ≥ 0.05). Among the older adults studied, the BBS and ABC measures discriminated groups defined by fall history, while the SWAY smart-device balance application did not. Modifications to the application may improve the discriminating ability of the measure in the recognition of fall status in older adults.

Multivariate optical element platform for compressed detection of fluorescence markers

NASA Astrophysics Data System (ADS)

Priore, Ryan J.; Swanstrom, Joseph A.

2014-05-01

The success of a commercial fluorescent diagnostic assay is dependent on the selection of a fluorescent biomarker; due to the broad nature of fluorescence biomarker emission profiles, only a small number of fluorescence biomarkers may be discriminated from each other as a function of excitation source. Multivariate Optical Elements (MOEs) are thin-film devices that encode a broad band, spectroscopic pattern allowing a simple broadband detector to generate a highly sensitive and specific detection for a target analyte. MOEs have historically been matched 1:1 to a discrete analyte or class prediction; however, MOE filter sets are capable of sensing projections of the original sparse spectroscopic space enabling a small set of MOEs to discriminate a multitude of target analytes. This optical regression can offer real-time measurements with relatively high signal-to-noise ratios that realize the advantages of multiplexed detection and pattern recognition in a simple optical instrument. The specificity advantage of MOE-based sensors allows fluorescent biomarkers that were once incapable of discrimination from one another via optical band pass filters to be employed in a common assay panel. A simplified MOE-based sensor may ultimately reduce the requirement for highly trained operators as well as move certain life science applications like disease prognostication from the laboratory to the point of care. This presentation will summarize the design and fabrication of compressed detection MOE filter sets for detecting multiple fluorescent biomarkers simultaneously with strong spectroscopic interference as well as comparing the detection performance of the MOE sensor with traditional optical band pass filter methodologies.

Mathematical Formulation of Multivariate Euclidean Models for Discrimination Methods.

ERIC Educational Resources Information Center

Mullen, Kenneth; Ennis, Daniel M.

1987-01-01

Multivariate models for the triangular and duo-trio methods are described, and theoretical methods are compared to a Monte Carlo simulation. Implications are discussed for a new theory of multidimensional scaling which challenges the traditional assumption that proximity measures and perceptual distances are monotonically related. (Author/GDC)

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

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.

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.

Multivariate analysis, mass balance techniques, and statistical tests as tools in igneous petrology: application to the Sierra de las Cruces volcanic range (Mexican Volcanic Belt).

PubMed

Velasco-Tapia, Fernando

2014-01-01

Magmatic processes have usually been identified and evaluated using qualitative or semiquantitative geochemical or isotopic tools based on a restricted number of variables. However, a more complete and quantitative view could be reached applying multivariate analysis, mass balance techniques, and statistical tests. As an example, in this work a statistical and quantitative scheme is applied to analyze the geochemical features for the Sierra de las Cruces (SC) volcanic range (Mexican Volcanic Belt). In this locality, the volcanic activity (3.7 to 0.5 Ma) was dominantly dacitic, but the presence of spheroidal andesitic enclaves and/or diverse disequilibrium features in majority of lavas confirms the operation of magma mixing/mingling. New discriminant-function-based multidimensional diagrams were used to discriminate tectonic setting. Statistical tests of discordancy and significance were applied to evaluate the influence of the subducting Cocos plate, which seems to be rather negligible for the SC magmas in relation to several major and trace elements. A cluster analysis following Ward's linkage rule was carried out to classify the SC volcanic rocks geochemical groups. Finally, two mass-balance schemes were applied for the quantitative evaluation of the proportion of the end-member components (dacitic and andesitic magmas) in the comingled lavas (binary mixtures).

Suicidal ideation in outpatients with chronic musculoskeletal pain: an exploratory study of the role of sleep onset insomnia and pain intensity.

PubMed

Smith, Michael T; Perlis, Michael L; Haythornthwaite, Jennifer A

2004-01-01

Sleep disturbance, depression, and heightened risk of suicide are among the most clinically significant sequelae of chronic pain. While sleep disturbance is associated with suicidality in patients with major depression and is a significant independent predictor of completed suicide in psychiatric patients, it is not known whether sleep disturbance is associated with suicidal behavior in chronic pain. This exploratory study evaluates the importance of insomnia in discriminating suicidal ideation in chronic pain relative to depression severity and other pain-related factors. Fifty-one outpatients with non-cancer chronic pain were recruited. Subjects completed a pain and sleep survey, the Pittsburgh Sleep Quality Index, the Beck Depression Inventory, and the Multidimensional Pain Inventory. Subjects were classified as "suicidal ideators" or "non-ideators" based on their responses to BDI-Item 9 (Suicide). Bivariate analyses and multivariate discriminant function analyses were conducted. Twenty-four percent reported suicidal ideation (without intent). Suicidal ideators endorsed higher levels of: sleep onset insomnia, pain intensity, medication usage, pain-related interference, affective distress, and depressive symptoms (P < 0.03). These 6 variables were entered into stepwise discriminant function analyses. Two variables predicted group membership: Sleep Onset Insomnia Severity and Pain Intensity, respectively. The discriminant function correctly classified 84.3% of the cases (P < 0.0001). Chronic pain patients who self-reported severe and frequent initial insomnia with concomitant daytime dysfunction and high pain intensity were more likely to report passive suicidal ideation, independent from the effects of depression severity. Future research aimed at determining whether sleep disturbance is a modifiable risk factor for suicidal ideation in chronic pain is warranted.

Metabolomics of Ulva lactuca Linnaeus (Chlorophyta) exposed to oil fuels: Fourier transform infrared spectroscopy and multivariate analysis as tools for metabolic fingerprint.

PubMed

Pilatti, Fernanda Kokowicz; Ramlov, Fernanda; Schmidt, Eder Carlos; Costa, Christopher; Oliveira, Eva Regina de; Bauer, Claudia M; Rocha, Miguel; Bouzon, Zenilda Laurita; Maraschin, Marcelo

2017-01-30

Fossil fuels, e.g. gasoline and diesel oil, account for substantial share of the pollution that affects marine ecosystems. Environmental metabolomics is an emerging field that may help unravel the effect of these xenobiotics on seaweeds and provide methodologies for biomonitoring coastal ecosystems. In the present study, FTIR and multivariate analysis were used to discriminate metabolic profiles of Ulva lactuca after in vitro exposure to diesel oil and gasoline, in combinations of concentrations (0.001%, 0.01%, 0.1%, and 1.0% - v/v) and times of exposure (30min, 1h, 12h, and 24h). PCA and HCA performed on entire mid-infrared spectral window were able to discriminate diesel oil-exposed thalli from the gasoline-exposed ones. HCA performed on spectral window related to the protein absorbance (1700-1500cm -1 ) enabled the best discrimination between gasoline-exposed samples regarding the time of exposure, and between diesel oil-exposed samples according to the concentration. The results indicate that the combination of FTIR with multivariate analysis is a simple and efficient methodology for metabolic profiling with potential use for biomonitoring strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sex determination from the mandibular ramus flexure of Koreans by discrimination function analysis using three-dimensional mandible models.

PubMed

Lin, Chenghe; Jiao, Benzheng; Liu, Shanshan; Guan, Feng; Chung, Nak-Eun; Han, Seung-Ho; Lee, U-Young

2014-03-01

It has been known that mandible ramus flexure is an important morphologic trait for sex determination. However, it will be unavailable when mandible is incomplete or fragmented. Therefore, the anthropometric analysis on incomplete or fragmented mandible becomes more important. The aim of this study is to investigate the sex-discriminant potential of mandible ramus flexure on the Korean three-dimensional (3D) mandible models with anthropometric analysis. The sample consists of 240 three dimensional mandibular models obtained from Korean population (M:F; 120:120, mean age 46.2 y), collected by The Catholic Institute for Applied Anatomy, The Catholic University of Korea. Anthropometric information about 11 metric was taken with Mimics, anthropometry libraries toolkit. These parameters were subjected to different discriminant function analyses using SPSS 17.0. Univariate analyses showed that the resubstitution accuracies for sex determination range from 50.4 to 77.1%. Mandibular flexure upper border (MFUB), maximum ramus vertical height (MRVH), and upper ramus vertical height (URVH) expressed the greatest dimorphism, 72.1 to 77.1%. Bivariate analyses indicated that the combination of MFUB and MRVH hold even higher resubstitution accuracy of 81.7%. Furthermore, the direct and stepwise discriminant analyses with the variables on the upper ramus above flexure could predict sex in 83.3 and 85.0%, respectively. When all variables of mandibular ramus flexure were input in stepwise discriminant analysis, the resubstitution accuracy arrived as high as 88.8%. Therefore, we concluded that the upper ramus above flexure hold the larger potentials than the mandibular ramus flexure itself to predict sexes, and that the equations in bivariate and multivariate analysis from our study will be helpful for sex determination on Korean population in forensic science and law. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Brain regions with abnormal network properties in severe epilepsy of Lennox-Gastaut phenotype: Multivariate analysis of task-free fMRI.

PubMed

Pedersen, Mangor; Curwood, Evan K; Archer, John S; Abbott, David F; Jackson, Graeme D

2015-11-01

Lennox-Gastaut syndrome, and the similar but less tightly defined Lennox-Gastaut phenotype, describe patients with severe epilepsy, generalized epileptic discharges, and variable intellectual disability. Our previous functional neuroimaging studies suggest that abnormal diffuse association network activity underlies the epileptic discharges of this clinical phenotype. Herein we use a data-driven multivariate approach to determine the spatial changes in local and global networks of patients with severe epilepsy of the Lennox-Gastaut phenotype. We studied 9 adult patients and 14 controls. In 20 min of task-free blood oxygen level-dependent functional magnetic resonance imaging data, two metrics of functional connectivity were studied: Regional homogeneity or local connectivity, a measure of concordance between each voxel to a focal cluster of adjacent voxels; and eigenvector centrality, a global connectivity estimate designed to detect important neural hubs. Multivariate pattern analysis of these data in a machine-learning framework was used to identify spatial features that classified disease subjects. Multivariate pattern analysis was 95.7% accurate in classifying subjects for both local and global connectivity measures (22/23 subjects correctly classified). Maximal discriminating features were the following: increased local connectivity in frontoinsular and intraparietal areas; increased global connectivity in posterior association areas; decreased local connectivity in sensory (visual and auditory) and medial frontal cortices; and decreased global connectivity in the cingulate cortex, striatum, hippocampus, and pons. Using a data-driven analysis method in task-free functional magnetic resonance imaging, we show increased connectivity in critical areas of association cortex and decreased connectivity in primary cortex. This supports previous findings of a critical role for these association cortical regions as a final common pathway in generating the Lennox-Gastaut phenotype. Abnormal function of these areas is likely to be important in explaining the intellectual problems characteristic of this disorder. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Social status correlates of reporting gender discrimination and racial discrimination among racially diverse women.

PubMed

Ro, Annie E; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in North California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design.

Discrimination of inflammatory bowel disease using Raman spectroscopy and linear discriminant analysis methods

NASA Astrophysics Data System (ADS)

Ding, Hao; Cao, Ming; DuPont, Andrew W.; Scott, Larry D.; Guha, Sushovan; Singhal, Shashideep; Younes, Mamoun; Pence, Isaac; Herline, Alan; Schwartz, David; Xu, Hua; Mahadevan-Jansen, Anita; Bi, Xiaohong

2016-03-01

Inflammatory bowel disease (IBD) is an idiopathic disease that is typically characterized by chronic inflammation of the gastrointestinal tract. Recently much effort has been devoted to the development of novel diagnostic tools that can assist physicians for fast, accurate, and automated diagnosis of the disease. Previous research based on Raman spectroscopy has shown promising results in differentiating IBD patients from normal screening cases. In the current study, we examined IBD patients in vivo through a colonoscope-coupled Raman system. Optical diagnosis for IBD discrimination was conducted based on full-range spectra using multivariate statistical methods. Further, we incorporated several feature selection methods in machine learning into the classification model. The diagnostic performance for disease differentiation was significantly improved after feature selection. Our results showed that improved IBD diagnosis can be achieved using Raman spectroscopy in combination with multivariate analysis and feature selection.

Morphometric discrimination of early life stage Lampetra tridentata and L richardsoni (Petromyzonidae) from the Columbia river basin

USGS Publications Warehouse

Meeuwig, M.H.; Bayer, J.M.; Reiche, R.A.

2006-01-01

The effectiveness of morphometric and meristic characteristics for taxonomic discrimination of Lampetra tridentata and L. richardsoni (Petromyzonidae) during embryological, prolarval, and early larval stages (i.e., age class 1) were examined. Mean chorion diameter increased with time from fertilization to hatch and was significantly greater for L. tridentata than for L. richardsoni at 1, 8, and 15 days postfertilization. Lampetra tridentata larvae had significantly more trunk myomeres than L. richardsoni; however, trunk myomere numbers were highly variable within species and deviated from previously published data. Multivariate examinations of prolarval and larval L. tridentata (7.2-11.0 mm; standard length) and L. richardsoni (6.6-10.8 mm) were conducted based on standard length and truss element lengths established from eight homologous landmarks. Principal components analysis indicated allometric relationships among the morphometric characteristics examined. Changes in body shape were indicated by groupings of morphometric characteristics associated with body regions (e.g., oral hood, branchial region, trunk region, and tail region). Discriminant function analysis using morphometric characteristics was successful in classifying a large proportion (>94.7%) of the lampreys sampled. 

A multidisciplinary selection model for youth soccer: the Ghent Youth Soccer Project

PubMed Central

Vaeyens, R; Malina, R M; Janssens, M; Van Renterghem, B; Bourgois, J; Vrijens, J; Philippaerts, R M

2006-01-01

Objectives To determine the relationships between physical and performance characteristics and level of skill in youth soccer players aged 12–16 years. Methods Anthropometry, maturity status, functional and sport‐specific parameters were assessed in elite, sub‐elite, and non‐elite youth players in four age groups: U13 (n = 117), U14 (n = 136), U15 (n = 138) and U16 (n = 99). Results Multivariate analyses of covariance by age group with maturity status as the covariate showed that elite players scored better than the non‐elite players on strength, flexibility, speed, aerobic endurance, anaerobic capacity and several technical skills (p<0.05). Stepwise discriminant analyses showed that running speed and technical skills were the most important characteristics in U13 and U14 players, while cardiorespiratory endurance was more important in U15 and U16 players. The results suggest that discriminating characteristics change with competitive age levels. Conclusions Characteristics that discriminate youth soccer players vary by age group. Talent identification models should thus be dynamic and provide opportunities for changing parameters in a long‐term developmental context. PMID:16980535

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.

Cancer, comorbidity and workplace discrimination: The US experience.

PubMed

Gehrke, Amanda K; Feuerstein, Michael

2017-09-01

Cancer survivors with comorbidities have more work-related challenges than cancer survivors without these other health problems. This study evaluated how these cancer survivors with comorbidities are faring under a newly revised workplace discrimination policy, which better accounts for the episodic nature of chronic illnesses. The sample included 18-64 year olds with a history of cancer who filed allegations of workplace discrimination in 2009-2011 (N = 1.291) in the US. Multivariable logistic regressions were used. Cancer survivors with comorbidities were more likely to file discrimination claims related to the terms of their employment (OR = 1.37, 95% CI = 1.04-1.80) than cancer survivors without comorbidities. Terms of employment-related claims were more likely to be ruled in favour of cancer survivors (versus employers), regardless of comorbidity status (OR = 1.44, 95% CI = 1.06-1.96). Despite this policy reform, alleged discrimination related to terms of employment existed at higher rates in cancer survivors with concurrent health problems. If employment is a goal in this high-risk group, replication of findings in other countries, studies on potential mechanisms and development of innovative interventions in these higher risk cases are warranted. Efforts should be made to mitigate the impact of these comorbid health problems on work-related function. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Comparison of Employer Factors in Disability and Other Employment Discrimination Charges

ERIC Educational Resources Information Center

Nazarov, Zafar E.; von Schrader, Sarah

2014-01-01

Purpose: We explore whether certain employer characteristics predict Americans with Disabilities Act (ADA) charges and whether the same characteristics predict receipt of the Age Discrimination in Employment Act and Title VII of the Civil Rights Act charges. Method: We estimate a set of multivariate regressions using the ordinary least squares…

Detection and discrimination of microorganisms on various substrates with quantum cascade laser spectroscopy

NASA Astrophysics Data System (ADS)

Padilla-Jiménez, Amira C.; Ortiz-Rivera, William; Rios-Velazquez, Carlos; Vazquez-Ayala, Iris; Hernández-Rivera, Samuel P.

2014-06-01

Investigations focusing on devising rapid and accurate methods for developing signatures for microorganisms that could be used as biological warfare agents' detection, identification, and discrimination have recently increased significantly. Quantum cascade laser (QCL)-based spectroscopic systems have revolutionized many areas of defense and security including this area of research. In this contribution, infrared spectroscopy detection based on QCL was used to obtain the mid-infrared (MIR) spectral signatures of Bacillus thuringiensis, Escherichia coli, and Staphylococcus epidermidis. These bacteria were used as microorganisms that simulate biothreats (biosimulants) very truthfully. The experiments were conducted in reflection mode with biosimulants deposited on various substrates including cardboard, glass, travel bags, wood, and stainless steel. Chemometrics multivariate statistical routines, such as principal component analysis regression and partial least squares coupled to discriminant analysis, were used to analyze the MIR spectra. Overall, the investigated infrared vibrational techniques were useful for detecting target microorganisms on the studied substrates, and the multivariate data analysis techniques proved to be very efficient for classifying the bacteria and discriminating them in the presence of highly IR-interfering media.

(13)C NMR pattern recognition techniques for the classification of Atlantic salmon (Salmo salar L.) according to their wild, farmed, and geographical origin.

PubMed

Aursand, Marit; Standal, Inger B; Praël, Angelika; McEvoy, Lesley; Irvine, Joe; Axelson, David E

2009-05-13

(13)C nuclear magnetic resonance (NMR) in combination with multivariate data analysis was used to (1) discriminate between farmed and wild Atlantic salmon ( Salmo salar L.), (2) discriminate between different geographical origins, and (3) verify the origin of market samples. Muscle lipids from 195 Atlantic salmon of known origin (wild and farmed salmon from Norway, Scotland, Canada, Iceland, Ireland, the Faroes, and Tasmania) in addition to market samples were analyzed by (13)C NMR spectroscopy and multivariate analysis. Both probabilistic neural networks (PNN) and support vector machines (SVM) provided excellent discrimination (98.5 and 100.0%, respectively) between wild and farmed salmon. Discrimination with respect to geographical origin was somewhat more difficult, with correct classification rates ranging from 82.2 to 99.3% by PNN and SVM, respectively. In the analysis of market samples, five fish labeled and purchased as wild salmon were classified as farmed salmon (indicating mislabeling), and there were also some discrepancies between the classification and the product declaration with regard to geographical origin.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis.

PubMed

Lee, Byeong-Ju; Kim, Hye-Youn; Lim, Sa Rang; Huang, Linfang; Choi, Hyung-Kyoon

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis

PubMed Central

Lim, Sa Rang; Huang, Linfang

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values. PMID:29049369

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.

Sex estimation of the tibia in modern Turkish: A computed tomography study.

PubMed

Ekizoglu, Oguzhan; Er, Ali; Bozdag, Mustafa; Akcaoglu, Mustafa; Can, Ismail Ozgur; García-Donas, Julieta G; Kranioti, Elena F

2016-11-01

The utilization of computed tomography is beneficial for the analysis of skeletal remains and it has important advantages for anthropometric studies. The present study investigated morphometry of left tibia using CT images of a contemporary Turkish population. Seven parameters were measured on 203 individuals (124 males and 79 females) within the 19-92-years age group. The first objective of this study was to provide population-specific sex estimation equations for the contemporary Turkish population based on CT images. A second objective was to test the sex estimation formulae on Southern Europeans by Kranioti and Apostol (2015). Univariate discriminant functions resulted in classification accuracy that ranged from 66 to 86%. The best single variable was found to be upper epiphyseal breadth (86%) followed by lower epiphyseal breadth (85%). Multivariate discriminant functions resulted in classification accuracy for cross-validated data ranged from 79 to 86%. Applying the multivariate sex estimation formulae on Southern Europeans (SE) by Kranioti and Apostol in our sample resulted in very high classification accuracy ranging from 81 to 88%. In addition, 35.5-47% of the total Turkish sample is correctly classified with over 95% posterior probability, which is actually higher than the one reported for the original sample (25-43%). We conclude that the tibia is a very useful bone for sex estimation in the contemporary Turkish population. Moreover, our test results support the hypothesis that the SE formulae are sufficient for the contemporary Turkish population and they can be used safely for criminal investigations when posterior probabilities are over 95%. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Offline handwritten word recognition using MQDF-HMMs

NASA Astrophysics Data System (ADS)

Ramachandrula, Sitaram; Hambarde, Mangesh; Patial, Ajay; Sahoo, Dushyant; Kochar, Shaivi

2015-01-01

We propose an improved HMM formulation for offline handwriting recognition (HWR). The main contribution of this work is using modified quadratic discriminant function (MQDF) [1] within HMM framework. In an MQDF-HMM the state observation likelihood is calculated by a weighted combination of MQDF likelihoods of individual Gaussians of GMM (Gaussian Mixture Model). The quadratic discriminant function (QDF) of a multivariate Gaussian can be rewritten by avoiding the inverse of covariance matrix by using the Eigen values and Eigen vectors of it. The MQDF is derived from QDF by substituting few of badly estimated lower-most Eigen values by an appropriate constant. The estimation errors of non-dominant Eigen vectors and Eigen values of covariance matrix for which the training data is insufficient can be controlled by this approach. MQDF has been successfully shown to improve the character recognition performance [1]. The usage of MQDF in HMM improves the computation, storage and modeling power of HMM when there is limited training data. We have got encouraging results on offline handwritten character (NIST database) and word recognition in English using MQDF HMMs.

Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data

PubMed Central

Havlicek, Martin; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

2015-01-01

Increasing interest in understanding dynamic interactions of brain neural networks leads to formulation of sophisticated connectivity analysis methods. Recent studies have applied Granger causality based on standard multivariate autoregressive (MAR) modeling to assess the brain connectivity. Nevertheless, one important flaw of this commonly proposed method is that it requires the analyzed time series to be stationary, whereas such assumption is mostly violated due to the weakly nonstationary nature of functional magnetic resonance imaging (fMRI) time series. Therefore, we propose an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data. The effectiveness and robustness of the dynamic approach was significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling. In our method, the functional networks were first detected by independent component analysis (ICA), a computational method for separating a multivariate signal into maximally independent components. Then the measure of Granger causality was evaluated using generalized partial directed coherence that is suitable for bivariate as well as multivariate data. Moreover, this metric provides identification of causal relation in frequency domain, which allows one to distinguish the frequency components related to the experimental paradigm. The procedure of evaluating Granger causality via dynamic MAR was demonstrated on simulated time series as well as on two sets of group fMRI data collected during an auditory sensorimotor (SM) or auditory oddball discrimination (AOD) tasks. Finally, a comparison with the results obtained from a standard time-invariant MAR model was provided. PMID:20561919

Relationship of plasma N-terminal pro-brain natriuretic peptide concentrations to heart failure classification and cause of respiratory distress in dogs using a 2nd generation ELISA assay.

PubMed

Fox, P R; Oyama, M A; Hezzell, M J; Rush, J E; Nguyenba, T P; DeFrancesco, T C; Lehmkuhl, L B; Kellihan, H B; Bulmer, B; Gordon, S G; Cunningham, S M; MacGregor, J; Stepien, R L; Lefbom, B; Adin, D; Lamb, K

2015-01-01

Cardiac biomarkers provide objective data that augments clinical assessment of heart disease (HD). Determine the utility of plasma N-terminal pro-brain natriuretic peptide concentration [NT-proBNP] measured by a 2nd generation canine ELISA assay to discriminate cardiac from noncardiac respiratory distress and evaluate HD severity. Client-owned dogs (n = 291). Multicenter, cross-sectional, prospective investigation. Medical history, physical examination, echocardiography, and thoracic radiography classified 113 asymptomatic dogs (group 1, n = 39 without HD; group 2, n = 74 with HD), and 178 with respiratory distress (group 3, n = 104 respiratory disease, either with or without concurrent HD; group 4, n = 74 with congestive heart failure [CHF]). HD severity was graded using International Small Animal Cardiac Health Council (ISACHC) and ACVIM Consensus (ACVIM-HD) schemes without knowledge of [NT-proBNP] results. Receiver-operating characteristic curve analysis assessed the capacity of [NT-proBNP] to discriminate between dogs with cardiac and noncardiac respiratory distress. Multivariate general linear models containing key clinical variables tested associations between [NT-proBNP] and HD severity. Plasma [NT-proBNP] (median; IQR) was higher in CHF dogs (5,110; 2,769-8,466 pmol/L) compared to those with noncardiac respiratory distress (1,287; 672-2,704 pmol/L; P < .0001). A cut-off >2,447 pmol/L discriminated CHF from noncardiac respiratory distress (81.1% sensitivity; 73.1% specificity; area under curve, 0.84). A multivariate model comprising left atrial to aortic ratio, heart rate, left ventricular diameter, end-systole, and ACVIM-HD scheme most accurately associated average plasma [NT-proBNP] with HD severity. Plasma [NT-proBNP] was useful for discriminating CHF from noncardiac respiratory distress. Average plasma [NT-BNP] increased significantly as a function of HD severity using the ACVIM-HD classification scheme. Copyright © 2014 by the American College of Veterinary Internal Medicine.

Combining Frequency Doubling Technology Perimetry and Scanning Laser Polarimetry for Glaucoma Detection.

PubMed

Mwanza, Jean-Claude; Warren, Joshua L; Hochberg, Jessica T; Budenz, Donald L; Chang, Robert T; Ramulu, Pradeep Y

2015-01-01

To determine the ability of frequency doubling technology (FDT) and scanning laser polarimetry with variable corneal compensation (GDx-VCC) to detect glaucoma when used individually and in combination. One hundred ten normal and 114 glaucomatous subjects were tested with FDT C-20-5 screening protocol and the GDx-VCC. The discriminating ability was tested for each device individually and for both devices combined using GDx-NFI, GDx-TSNIT, number of missed points of FDT, and normal or abnormal FDT. Measures of discrimination included sensitivity, specificity, area under the curve (AUC), Akaike's information criterion (AIC), and prediction confidence interval lengths. For detecting glaucoma regardless of severity, the multivariable model resulting from the combination of GDx-TSNIT, number of abnormal points on FDT (NAP-FDT), and the interaction GDx-TSNIT×NAP-FDT (AIC: 88.28, AUC: 0.959, sensitivity: 94.6%, specificity: 89.5%) outperformed the best single-variable model provided by GDx-NFI (AIC: 120.88, AUC: 0.914, sensitivity: 87.8%, specificity: 84.2%). The multivariable model combining GDx-TSNIT, NAP-FDT, and interaction GDx-TSNIT×NAP-FDT consistently provided better discriminating abilities for detecting early, moderate, and severe glaucoma than the best single-variable models. The multivariable model including GDx-TSNIT, NAP-FDT, and the interaction GDx-TSNIT×NAP-FDT provides the best glaucoma prediction compared with all other multivariable and univariable models. Combining the FDT C-20-5 screening protocol and GDx-VCC improves glaucoma detection compared with using GDx or FDT alone.

Comparative evaluation of spectroscopic models using different multivariate statistical tools in a multicancer scenario

NASA Astrophysics Data System (ADS)

Ghanate, A. D.; Kothiwale, S.; Singh, S. P.; Bertrand, Dominique; Krishna, C. Murali

2011-02-01

Cancer is now recognized as one of the major causes of morbidity and mortality. Histopathological diagnosis, the gold standard, is shown to be subjective, time consuming, prone to interobserver disagreement, and often fails to predict prognosis. Optical spectroscopic methods are being contemplated as adjuncts or alternatives to conventional cancer diagnostics. The most important aspect of these approaches is their objectivity, and multivariate statistical tools play a major role in realizing it. However, rigorous evaluation of the robustness of spectral models is a prerequisite. The utility of Raman spectroscopy in the diagnosis of cancers has been well established. Until now, the specificity and applicability of spectral models have been evaluated for specific cancer types. In this study, we have evaluated the utility of spectroscopic models representing normal and malignant tissues of the breast, cervix, colon, larynx, and oral cavity in a broader perspective, using different multivariate tests. The limit test, which was used in our earlier study, gave high sensitivity but suffered from poor specificity. The performance of other methods such as factorial discriminant analysis and partial least square discriminant analysis are at par with more complex nonlinear methods such as decision trees, but they provide very little information about the classification model. This comparative study thus demonstrates not just the efficacy of Raman spectroscopic models but also the applicability and limitations of different multivariate tools for discrimination under complex conditions such as the multicancer scenario.

Within-individual variation in bullfrog vocalizations: implications for a vocally mediated social recognition system.

PubMed

Bee, Mark A

2004-12-01

Acoustic signals provide a basis for social recognition in a wide range of animals. Few studies, however, have attempted to relate the patterns of individual variation in signals to behavioral discrimination thresholds used by receivers to discriminate among individuals. North American bullfrogs (Rana catesbeiana) discriminate among familiar and unfamiliar individuals based on individual variation in advertisement calls. The sources, patterns, and magnitudes of variation in eight acoustic properties of multiple-note advertisement calls were examined to understand how patterns of within-individual variation might either constrain, or provide additional cues for, vocal recognition. Six of eight acoustic properties exhibited significant note-to-note variation within multiple-note calls. Despite this source of within-individual variation, all call properties varied significantly among individuals, and multivariate analyses indicated that call notes were individually distinct. Fine-temporal and spectral call properties exhibited less within-individual variation compared to gross-temporal properties and contributed most toward statistically distinguishing among individuals. Among-individual differences in the patterns of within-individual variation in some properties suggest that within-individual variation could also function as a recognition cue. The distributions of among-individual and within-individual differences were used to generate hypotheses about the expected behavioral discrimination thresholds of receivers.

Discrimination and mental health problems among homeless minority young people.

PubMed

Milburn, Norweeta G; Batterham, Philip; Ayala, George; Rice, Eric; Solorio, Rosa; Desmond, Kate; Lord, Lynwood; Iribarren, Javier; Rotheram-Borus, Mary Jane

2010-01-01

We examined the associations among perceived discrimination, racial/ethnic identification, and emotional distress in newly homeless adolescents. We assessed a sample of newly homeless adolescents (n=254) in Los Angeles, California, with measures of perceived discrimination and racial/ethnic identification. We assessed emotional distress using the Brief Symptom Inventory and used multivariate linear regression modeling to gauge the impact of discrimination and racial identity on emotional distress. Controlling for race and immigration status, gender, and age, young people with a greater sense of ethnic identification experienced less emotional distress. Young people with a history of racial/ethnic discrimination experienced more emotional distress. Intervention programs that contextualize discrimination and enhance racial/ethnic identification and pride among homeless young people are needed.

Right atrial pressure predicts worsening renal function in patients with acute right ventricular myocardial infarction.

PubMed

Ivey-Miranda, Juan Betuel; Posada-Martínez, Edith Liliana; Almeida-Gutiérrez, Eduardo; Borrayo-Sánchez, Gabriela; Flores-Umanzor, Eduardo

2018-08-01

Right ventricular myocardial infarction (RVMI) is associated with serious complications in the short-term. Worsening renal function (WRF) is a frequent and dangerous complication. We investigated if right atrial pressure (RAP) predicts WRF in these patients. We prospectively studied patients with RVMI. RAP was obtained invasively at admission to coronary care unit. Blood samples were extracted from patients at baseline and every 24h for creatinine measurements for seven days. We defined WRF as an increase of 25% or 0.5mg/dl in serum creatinine during the first seven days compared to baseline creatinine. We included forty-five patients (age 68±10years, male 71%). WRF occurred in 51%. The best cut-off value of RAP for WRF prediction was 11mmHg. RAP ≥11mmHg was associated with WRF at univariate analysis (OR 5.5, 95% CI 1.27-24.3, p=0.023) and multivariate analysis (OR 6.1, 95% CI 1.07-35.4, p=0.042). RAP ≥11mmHg improved reclassification and discrimination after usual prediction with the Mehran score (net reclassification improvement 64.8%, p=0.030; integrated discrimination improvement 7.5%, p=0.037). In patients with RVMI, RAP ≥11mmHg predicted WRF and improved discrimination. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Diagnostic value of fibronectin discriminant score for predicting liver fibrosis stages in chronic hepatitis C virus patients.

PubMed

Attallah, Abdelfattah M; Abdallah, Sanaa O; Attallah, Ahmed A; Omran, Mohamed M; Farid, Khaled; Nasif, Wesam A; Shiha, Gamal E; Abdel-Aziz, Abdel-Aziz F; Rasafy, Nancy; Shaker, Yehia M

2013-01-01

Several noninvasive predictive models were developed to substitute liver biopsy for fibrosis assessment. To evaluate the diagnostic value of fibronectin which reflect extracellular matrix metabolism and standard liver functions tests which reflect alterations in hepatic functions. Chronic hepatitis C (CHC) patients (n = 145) were evaluated using ROC curves and stepwise multivariate discriminant analysis (MDA) and was validated in 180 additional patients. Liver biochemical profile including transaminases, bilirubin, alkaline phosphatase, albumin, complete blood count were estimated. Fibronectin concentration was determined using monoclonal antibody and ELISA. A novel index named fibronectin discriminant score (FDS) based on fibronectin, APRI and albumin was developed. FDS produced areas under ROC curves (AUC) of 0.91 for significant fibrosis and 0.81 for advanced fibrosis. The FDS correctly classified 79% of the significant liver fibrosis patients (F2-F4) with 87% sensitivity and 75% specificity. The relative risk [odds ratio (OR)] of having significant liver fibrosis using the cut-off values determined by ROC curve analyses were 6.1 for fibronectin, 4.9 for APRI, and 4.2 for albumin. FDS predicted liver fibrosis with an OR of 16.8 for significant fibrosis and 8.6 for advanced fibrosis. The FDS had similar AUC and OR in the validation group to the estimation group without statistically significant difference. FDS predicted liver fibrosis with high degree of accuracy, potentially decreasing the number of liver biopsy required.

Spatially invariant coding of numerical information in functionally defined subregions of human parietal cortex.

PubMed

Eger, E; Pinel, P; Dehaene, S; Kleinschmidt, A

2015-05-01

Macaque electrophysiology has revealed neurons responsive to number in lateral (LIP) and ventral (VIP) intraparietal areas. Recently, fMRI pattern recognition revealed information discriminative of individual numbers in human parietal cortex but without precisely localizing the relevant sites or testing for subregions with different response profiles. Here, we defined the human functional equivalents of LIP (feLIP) and VIP (feVIP) using neurophysiologically motivated localizers. We applied multivariate pattern recognition to investigate whether both regions represent numerical information and whether number codes are position specific or invariant. In a delayed number comparison paradigm with laterally presented numerosities, parietal cortex discriminated between numerosities better than early visual cortex, and discrimination generalized across hemifields in parietal, but not early visual cortex. Activation patterns in the 2 parietal regions of interest did not differ in the coding of position-specific or position-independent number information, but in the expression of a numerical distance effect which was more pronounced in feLIP. Thus, the representation of number in parietal cortex is at least partially position invariant. Both feLIP and feVIP contain information about individual numerosities in humans, but feLIP hosts a coarser representation of numerosity than feVIP, compatible with either broader tuning or a summation code. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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…

Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

PubMed Central

Ro, Annie E.; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in Northern California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design. PMID:19485231

Racial/Ethnic Disparities in Influenza Vaccination of Chronically Ill US Adults: The Mediating Role of Perceived Discrimination in Health Care.

PubMed

Bleser, William K; Miranda, Patricia Y; Jean-Jacques, Muriel

2016-06-01

Despite well-established programs, influenza vaccination rates in US adults are well below federal benchmarks and exhibit well-documented, persistent racial and ethnic disparities. The causes of these disparities are multifactorial and complex, though perceived racial/ethnic discrimination in health care is 1 hypothesized mechanism. To assess the role of perceived discrimination in health care in mediating influenza vaccination RACIAL/ETHNIC disparities in chronically ill US adults (at high risk for influenza-related complications). We utilized 2011-2012 data from the Aligning Forces for Quality Consumer Survey on health and health care (n=8127), nationally representative of chronically ill US adults. Logistic regression marginal effects examined the relationship between race/ethnicity and influenza vaccination, both unadjusted and in multivariate models adjusted for determinants of health service use. We then used binary mediation analysis to calculate and test the significance of the percentage of this relationship mediated by perceived discrimination in health care. Respondents reporting perceived discrimination in health care had half the uptake as those without discrimination (32% vs. 60%, P=0.009). The change in predicted probability of vaccination given perceived discrimination experiences (vs. none) was large but not significant in the fully adjusted model (-0.185; 95% CI, -0.385, 0.014). Perceived discrimination significantly mediated 16% of the unadjusted association between race/ethnicity and influenza vaccination, though this dropped to 6% and lost statistical significance in multivariate models. The causes of persistent racial/ethnic disparities are complex and a single explanation is unlikely to be sufficient. We suggest reevaluation in a larger cohort as well as potential directions for future research.

Discrimination, perceived social inequity, and mental health among rural-to-urban migrants in China.

PubMed

Lin, Danhua; Li, Xiaoming; Wang, Bo; Hong, Yan; Fang, Xiaoyi; Qin, Xiong; Stanton, Bonita

2011-04-01

Status-based discrimination and inequity have been associated with the process of migration, especially with economics-driven internal migration. However, their association with mental health among economy-driven internal migrants in developing countries is rarely assessed. This study examines discriminatory experiences and perceived social inequity in relation to mental health status among rural-to-urban migrants in China. Cross-sectional data were collected from 1,006 rural-to-urban migrants in 2004-2005 in Beijing, China. Participants reported their perceptions and experiences of being discriminated in daily life in urban destination and perceived social inequity. Mental health was measured using the symptom checklist-90 (SCL-90). Multivariate analyses using general linear model were performed to test the effect of discriminatory experience and perceived social inequity on mental health. Experience of discrimination was positively associated with male gender, being married at least once, poorer health status, shorter duration of migration, and middle range of personal income. Likewise, perceived social inequity was associated with poorer health status, higher education attainment, and lower personal income. Multivariate analyses indicate that both experience of discrimination and perceived social inequity were strongly associated with mental health problems of rural-to-urban migrants. Experience of discrimination in daily life and perceived social inequity have a significant influence on mental health among rural-to-urban migrants. The findings underscore the needs to reduce public or societal discrimination against rural-to-urban migrants, to eliminate structural barriers (i.e., dual household registrations) for migrants to fully benefit from the urban economic development, and to create a positive atmosphere to improve migrant's psychological well-being.

Significance of serum CA125 and TPS antigen levels for determination of overall survival after three chemotherapy courses in ovarian cancer patients during long-term follow-up.

PubMed

van Dalen, A; Favier, J; Hallensleben, E; Burges, A; Stieber, P; de Bruijn, H W A; Fink, D; Ferrero, A; McGing, P; Harlozinska, A; Kainz, Ch; Markowska, J; Molina, R; Sturgeon, C; Bowman, A; Einarsson, R; Goike, H

2009-01-01

To evaluate the prognostic significance for overall survival rate for the marker combination TPS and CA125 in ovarian cancer patients after three chemotherapy courses during long-term clinical follow-up. The overall survival of 212 (out of 213) ovarian cancer patients (FIGO Stages I-IV) was analyzed in a prospective multicenter study during a 10-year clinical follow-up by univariate and multivariate analysis. In patients with ovarian cancer FIGO Stage I (34 patients) or FIGO Stage II (30 patients) disease, the univariate and multivariate analysis of the 10-year overall survival data showed that CA125 and TPS serum levels were not independent prognostic factors. In the FIGO Stage III group (112 patients), the 10-year overall survival was 15.2%; while in the FIGO Stage IV group (36 patients) a 10-year overall survival of 5.6% was seen. Here, the tumor markers CA125 and TPS levels were significant prognostic factors in both univariate and multivariate analysis (p < 0.0001). In a combined FIGO Stage III + FIGO Stage IV group (60 patients with optimal debulking surgery), multivariate analysis demonstrated that CA125 and TPS levels were independent prognostic factors. For patients in this combined FIGO Stage III + IV group having both markers below respective discrimination level, 35.3% survived for more than ten years, as opposed to patients having one marker above the discrimination level where the 10-year survival was reduced to 10% of the patients. For patients showing both markers above the respective discrimination level, none of the patients survived for the 10-year follow-up time. In FIGO III and IV ovarian cancer patients, only patients with CA 125 and TPS markers below the discrimination level after three chemotherapy courses indicated a favorable prognosis. Patients with an elevated level of CA 125 or TPS or both markers after three chemotherapy courses showed unfavorable prognosis.

Statistically Correct Methodology for Compositional Data in New Discriminant Function Tectonomagmatic Diagrams and Application to Ophiolite Origin

NASA Astrophysics Data System (ADS)

Verma, Surendra P.; Pandarinath, Kailasa; Verma, Sanjeet K.

2011-07-01

In the lead presentation (invited talk) of Session SE05 (Frontiers in Geochemistry with Reference to Lithospheric Evolution and Metallogeny) of AOGS2010, we have highlighted the requirement of correct statistical treatment of geochemical data. In most diagrams used for interpreting compositional data, the basic statistical assumption of open space for all variables is violated. Among these graphic tools, discrimination diagrams have been in use for nearly 40 years to decipher tectonic setting. The newer set of five tectonomagmatic discrimination diagrams published in 2006 (based on major-elements) and two sets made available in 2008 and 2011 (both based on immobile elements) fulfill all statistical requirements for correct handling of compositional data, including the multivariate nature of compositional variables, representative sampling, and probability-based tectonic field boundaries. Additionally in the most recent proposal of 2011, samples having normally distributed, discordant-outlier free, log-ratio variables were used in linear discriminant analysis. In these three sets of five diagrams each, discrimination was successfully documented for four tectonic settings (island arc, continental rift, ocean-island, and mid-ocean ridge). The discrimination diagrams have been extensively evaluated for their performance by different workers. We exemplify these two sets of new diagrams (one set based on major-elements and the other on immobile elements) using ophiolites from Boso Peninsula, Japan. This example is included for illustration purposes only and is not meant for testing of these newer diagrams. Their evaluation and comparison with older, conventional bivariate or ternary diagrams have been reported in other papers.

Detection and characterization of glaucoma-like canine retinal tissues using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Wang, Qi; Grozdanic, Sinisa D.; Harper, Matthew M.; Hamouche, Karl; Hamouche, Nicholas; Kecova, Helga; Lazic, Tatjana; Hernandez-Merino, Elena; Yu, Chenxu

2013-06-01

Early detection of pathological changes and progression in glaucoma and other neuroretinal diseases remains a great challenge and is critical to reduce permanent structural and functional retina and optic nerve damage. Raman spectroscopy is a sensitive technique that provides rapid biochemical characterization of tissues in a nondestructive and noninvasive fashion. In this study, spectroscopic analysis was conducted on the retinal tissues of seven beagles with acute elevation of intraocular pressure (AEIOP), six beagles with compressive optic neuropathy (CON), and five healthy beagles. Spectroscopic markers were identified associated with the different neuropathic conditions. Furthermore, the Raman spectra were subjected to multivariate discriminate analysis to classify independent tissue samples into diseased/healthy categories. The multivariate discriminant model yielded an average optimal classification accuracy of 72.6% for AEIOP and 63.4% for CON with 20 principal components being used that accounted for 87% of the total variance in the data set. A strong correlation (R2>0.92) was observed between pattern electroretinography characteristics of AEIOP dogs and Raman separation distance that measures the separation of spectra of diseased tissues from normal tissues; however, the underlining mechanism of this correlation remains to be understood. Since AEIOP mimics the pathological symptoms of acute/early-stage glaucoma, it was demonstrated that Raman spectroscopic screening has the potential to become a powerful tool for the detection and characterization of early-stage disease.

Heavy metals in edible seaweeds commercialised for human consumption

NASA Astrophysics Data System (ADS)

Besada, Victoria; Andrade, José Manuel; Schultze, Fernando; González, Juan José

2009-01-01

Though seaweed consumption is growing steadily across Europe, relatively few studies have reported on the quantities of heavy metals they contain and/or their potential effects on the population's health. This study focuses on the first topic and analyses the concentrations of six typical heavy metals (Cd, Pb, Hg, Cu, Zn, total As and inorganic As) in 52 samples from 11 algae-based products commercialised in Spain for direct human consumption ( Gelidium spp.; Eisenia bicyclis; Himanthalia elongata; Hizikia fusiforme; Laminaria spp.; Ulva rigida; Chondrus crispus; Porphyra umbilicales and Undaria pinnatifida). Samples were ground, homogenised and quantified by atomic absorption spectrometry (Cu and Zn by flame AAS; Cd, Pb and total As by electrothermal AAS; total mercury by the cold vapour technique; and inorganic As by flame-hydride generation). Accuracy was assessed by participation in periodic QUASIMEME (Quality Assurance of Information in Marine Environmental Monitoring in Europe) and IAEA (International Atomic Energy Agency) intercalibration exercises. To detect any objective differences existing between the seaweeds' metal concentrations, univariate and multivariate studies (principal component analysis, cluster analysis and linear discriminant analysis) were performed. It is concluded that the Hizikia fusiforme samples contained the highest values of total and inorganic As and that most Cd concentrations exceeded the French Legislation. The two harvesting areas (Atlantic and Pacific oceans) were differentiated using both univariate studies (for Cu, total As, Hg and Zn) and a multivariate discriminant function (which includes Zn, Cu and Pb).

Investigating the sex-related geometric variation of the human cranium.

PubMed

Bertsatos, Andreas; Papageorgopoulou, Christina; Valakos, Efstratios; Chovalopoulou, Maria-Eleni

2018-01-29

Accurate sexing methods are of great importance in forensic anthropology since sex assessment is among the principal tasks when examining human skeletal remains. The present study explores a novel approach in assessing the most accurate metric traits of the human cranium for sex estimation based on 80 ectocranial landmarks from 176 modern individuals of known age and sex from the Athens Collection. The purpose of the study is to identify those distance and angle measurements that can be most effectively used in sex assessment. Three-dimensional landmark coordinates were digitized with a Microscribe 3DX and analyzed in GNU Octave. An iterative linear discriminant analysis of all possible combinations of landmarks was performed for each unique set of the 3160 distances and 246,480 angles. Cross-validated correct classification as well as multivariate DFA on top performing variables reported 13 craniometric distances with over 85% classification accuracy, 7 angles over 78%, as well as certain multivariate combinations yielding over 95%. Linear regression of these variables with the centroid size was used to assess their relation to the size of the cranium. In contrast to the use of generalized procrustes analysis (GPA) and principal component analysis (PCA), which constitute the common analytical work flow for such data, our method, although computational intensive, produced easily applicable discriminant functions of high accuracy, while at the same time explored the maximum of cranial variability.

Multivariate Analysis, Mass Balance Techniques, and Statistical Tests as Tools in Igneous Petrology: Application to the Sierra de las Cruces Volcanic Range (Mexican Volcanic Belt)

PubMed Central

Velasco-Tapia, Fernando

2014-01-01

Magmatic processes have usually been identified and evaluated using qualitative or semiquantitative geochemical or isotopic tools based on a restricted number of variables. However, a more complete and quantitative view could be reached applying multivariate analysis, mass balance techniques, and statistical tests. As an example, in this work a statistical and quantitative scheme is applied to analyze the geochemical features for the Sierra de las Cruces (SC) volcanic range (Mexican Volcanic Belt). In this locality, the volcanic activity (3.7 to 0.5 Ma) was dominantly dacitic, but the presence of spheroidal andesitic enclaves and/or diverse disequilibrium features in majority of lavas confirms the operation of magma mixing/mingling. New discriminant-function-based multidimensional diagrams were used to discriminate tectonic setting. Statistical tests of discordancy and significance were applied to evaluate the influence of the subducting Cocos plate, which seems to be rather negligible for the SC magmas in relation to several major and trace elements. A cluster analysis following Ward's linkage rule was carried out to classify the SC volcanic rocks geochemical groups. Finally, two mass-balance schemes were applied for the quantitative evaluation of the proportion of the end-member components (dacitic and andesitic magmas) in the comingled lavas (binary mixtures). PMID:24737994

Discrimination and prediction of the origin of Chinese and Korean soybeans using Fourier transform infrared spectrometry (FT-IR) with multivariate statistical analysis

PubMed Central

Lee, Byeong-Ju; Zhou, Yaoyao; Lee, Jae Soung; Shin, Byeung Kon; Seo, Jeong-Ah; Lee, Doyup; Kim, Young-Suk

2018-01-01

The ability to determine the origin of soybeans is an important issue following the inclusion of this information in the labeling of agricultural food products becoming mandatory in South Korea in 2017. This study was carried out to construct a prediction model for discriminating Chinese and Korean soybeans using Fourier-transform infrared (FT-IR) spectroscopy and multivariate statistical analysis. The optimal prediction models for discriminating soybean samples were obtained by selecting appropriate scaling methods, normalization methods, variable influence on projection (VIP) cutoff values, and wave-number regions. The factors for constructing the optimal partial-least-squares regression (PLSR) prediction model were using second derivatives, vector normalization, unit variance scaling, and the 4000–400 cm–1 region (excluding water vapor and carbon dioxide). The PLSR model for discriminating Chinese and Korean soybean samples had the best predictability when a VIP cutoff value was not applied. When Chinese soybean samples were identified, a PLSR model that has the lowest root-mean-square error of the prediction value was obtained using a VIP cutoff value of 1.5. The optimal PLSR prediction model for discriminating Korean soybean samples was also obtained using a VIP cutoff value of 1.5. This is the first study that has combined FT-IR spectroscopy with normalization methods, VIP cutoff values, and selected wave-number regions for discriminating Chinese and Korean soybeans. PMID:29689113

Stimulus familiarity modulates functional connectivity of the perirhinal cortex and anterior hippocampus during visual discrimination of faces and objects

PubMed Central

McLelland, Victoria C.; Chan, David; Ferber, Susanne; Barense, Morgan D.

2014-01-01

Recent research suggests that the medial temporal lobe (MTL) is involved in perception as well as in declarative memory. Amnesic patients with focal MTL lesions and semantic dementia patients showed perceptual deficits when discriminating faces and objects. Interestingly, these two patient groups showed different profiles of impairment for familiar and unfamiliar stimuli. For MTL amnesics, the use of familiar relative to unfamiliar stimuli improved discrimination performance. By contrast, patients with semantic dementia—a neurodegenerative condition associated with anterolateral temporal lobe damage—showed no such facilitation from familiar stimuli. Given that the two patient groups had highly overlapping patterns of damage to the perirhinal cortex, hippocampus, and temporal pole, the neuroanatomical substrates underlying their performance discrepancy were unclear. Here, we addressed this question with a multivariate reanalysis of the data presented by Barense et al. (2011), using functional connectivity to examine how stimulus familiarity affected the broader networks with which the perirhinal cortex, hippocampus, and temporal poles interact. In this study, healthy participants were scanned while they performed an odd-one-out perceptual task involving familiar and novel faces or objects. Seed-based analyses revealed that functional connectivity of the right perirhinal cortex and right anterior hippocampus was modulated by the degree of stimulus familiarity. For familiar relative to unfamiliar faces and objects, both right perirhinal cortex and right anterior hippocampus showed enhanced functional correlations with anterior/lateral temporal cortex, temporal pole, and medial/lateral parietal cortex. These findings suggest that in order to benefit from stimulus familiarity, it is necessary to engage not only the perirhinal cortex and hippocampus, but also a network of regions known to represent semantic information. PMID:24624075

Discriminative ability and predictive validity of the timed up and go test in identifying older people who fall: systematic review and meta-analysis.

PubMed

Schoene, Daniel; Wu, Sandy M-S; Mikolaizak, A Stefanie; Menant, Jasmine C; Smith, Stuart T; Delbaere, Kim; Lord, Stephen R

2013-02-01

To investigate the discriminative ability and diagnostic accuracy of the Timed Up and Go Test (TUG) as a clinical screening instrument for identifying older people at risk of falling. Systematic literature review and meta-analysis. People aged 60 and older living independently or in institutional settings. Studies were identified with searches of the PubMed, EMBASE, CINAHL, and Cochrane CENTRAL data bases. Retrospective and prospective cohort studies comparing times to complete any version of the TUG of fallers and non-fallers were included. Fifty-three studies with 12,832 participants met the inclusion criteria. The pooled mean difference between fallers and non-fallers depended on the functional status of the cohort investigated: 0.63 seconds (95% confidence (CI) = 0.14-1.12 seconds) for high-functioning to 3.59 seconds (95% CI = 2.18-4.99 seconds) for those in institutional settings. The majority of studies did not retain TUG scores in multivariate analysis. Derived cut-points varied greatly between studies, and with the exception of a few small studies, diagnostic accuracy was poor to moderate. The findings suggest that the TUG is not useful for discriminating fallers from non-fallers in healthy, high-functioning older people but is of more value in less-healthy, lower-functioning older people. Overall, the predictive ability and diagnostic accuracy of the TUG are at best moderate. No cut-point can be recommended. Quick, multifactorial fall risk screens should be considered to provide additional information for identifying older people at risk of falls. © 2013, Copyright the Authors Journal compilation © 2013, The American Geriatrics Society.

Morphological and Hemodynamic Discriminators for Rupture Status in Posterior Communicating Artery Aneurysms

PubMed Central

Karmonik, Christof; Fang, Yibin; Xu, Jinyu; Yu, Ying; Cao, Wei; Liu, Jianmin; Huang, Qinghai

2016-01-01

Background and Purpose The conflicting findings of previous morphological and hemodynamic studies on intracranial aneurysm rupture may be caused by the relatively small sample sizes and the variation in location of the patient-specific aneurysm models. We aimed to determine the discriminators for aneurysm rupture status by focusing on only posterior communicating artery (PCoA) aneurysms. Materials and Methods In 129 PCoA aneurysms (85 ruptured, 44 unruptured), clinical, morphological and hemodynamic characteristics were compared between the ruptured and unruptured cases. Multivariate logistic regression analysis was performed to determine the discriminators for rupture status of PCoA aneurysms. Results While univariate analyses showed that the size of aneurysm dome, aspect ratio (AR), size ratio (SR), dome-to-neck ratio (DN), inflow angle (IA), normalized wall shear stress (NWSS) and percentage of low wall shear stress area (LSA) were significantly associated with PCoA aneurysm rupture status. With multivariate analyses, significance was only retained for higher IA (OR = 1.539, p < 0.001) and LSA (OR = 1.393, p = 0.041). Conclusions Hemodynamics and morphology were related to rupture status of intracranial aneurysms. Higher IA and LSA were identified as discriminators for rupture status of PCoA aneurysms. PMID:26910518

Morphological and Hemodynamic Discriminators for Rupture Status in Posterior Communicating Artery Aneurysms.

PubMed

Lv, Nan; Wang, Chi; Karmonik, Christof; Fang, Yibin; Xu, Jinyu; Yu, Ying; Cao, Wei; Liu, Jianmin; Huang, Qinghai

2016-01-01

The conflicting findings of previous morphological and hemodynamic studies on intracranial aneurysm rupture may be caused by the relatively small sample sizes and the variation in location of the patient-specific aneurysm models. We aimed to determine the discriminators for aneurysm rupture status by focusing on only posterior communicating artery (PCoA) aneurysms. In 129 PCoA aneurysms (85 ruptured, 44 unruptured), clinical, morphological and hemodynamic characteristics were compared between the ruptured and unruptured cases. Multivariate logistic regression analysis was performed to determine the discriminators for rupture status of PCoA aneurysms. While univariate analyses showed that the size of aneurysm dome, aspect ratio (AR), size ratio (SR), dome-to-neck ratio (DN), inflow angle (IA), normalized wall shear stress (NWSS) and percentage of low wall shear stress area (LSA) were significantly associated with PCoA aneurysm rupture status. With multivariate analyses, significance was only retained for higher IA (OR = 1.539, p < 0.001) and LSA (OR = 1.393, p = 0.041). Hemodynamics and morphology were related to rupture status of intracranial aneurysms. Higher IA and LSA were identified as discriminators for rupture status of PCoA aneurysms.

Multivariate qualitative analysis of banned additives in food safety using surface enhanced Raman scattering spectroscopy

NASA Astrophysics Data System (ADS)

He, Shixuan; Xie, Wanyi; Zhang, Wei; Zhang, Liqun; Wang, Yunxia; Liu, Xiaoling; Liu, Yulong; Du, Chunlei

2015-02-01

A novel strategy which combines iteratively cubic spline fitting baseline correction method with discriminant partial least squares qualitative analysis is employed to analyze the surface enhanced Raman scattering (SERS) spectroscopy of banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. Multivariate qualitative analysis methods, using the combination of spectra preprocessing iteratively cubic spline fitting (ICSF) baseline correction with principal component analysis (PCA) and discriminant partial least squares (DPLS) classification respectively, are applied to investigate the effectiveness of SERS spectroscopy for predicting the class assignments of unknown banned food additives. PCA cannot be used to predict the class assignments of unknown samples. However, the DPLS classification can discriminate the class assignment of unknown banned additives using the information of differences in relative intensities. The results demonstrate that SERS spectroscopy combined with ICSF baseline correction method and exploratory analysis methodology DPLS classification can be potentially used for distinguishing the banned food additives in field of food safety.

Awareness and Acceptability of Pre-exposure HIV Prophylaxis Among Men Who have Sex with Men in Baltimore.

PubMed

Fallon, Susan A; Park, Ju Nyeong; Ogbue, Christine Powell; Flynn, Colin; German, Danielle

2017-05-01

This paper assessed characteristics associated with awareness of and willingness to take pre-exposure prophylaxis (PrEP) among Baltimore men who have sex with men (MSM). We used data from BESURE-MSM3, a venue-based cross-sectional HIV surveillance study conducted among MSM in 2011. Multivariate regression was used to identify characteristics associated with PrEP knowledge and acceptability among 399 participants. Eleven percent had heard of PrEP, 48% would be willing to use PrEP, and none had previously used it. In multivariable analysis, black race and perceived discrimination against those with HIV were significantly associated with decreased awareness, and those who perceived higher HIV discrimination reported higher acceptability of PrEP. Our findings indicate a need for further education about the potential utility of PrEP in addition to other prevention methods among MSM. HIV prevention efforts should address the link between discrimination and potential PrEP use, especially among men of color.

Combining Frequency Doubling Technology Perimetry and Scanning Laser Polarimetry for Glaucoma Detection

PubMed Central

Mwanza, Jean-Claude; Warren, Joshua L.; Hochberg, Jessica T.; Budenz, Donald L.; Chang, Robert T.; Ramulu, Pradeep Y.

2014-01-01

Purpose To determine the ability of frequency doubling technology (FDT) and scanning laser polarimetry with variable corneal compensation (GDx-VCC) to detect glaucoma when used individually and in combination. Methods One hundred and ten normal and 114 glaucomatous subjects were tested with FDT C-20-5 screening protocol and the GDx-VCC. The discriminating ability was tested for each device individually and for both devices combined using GDx-NFI, GDx-TSNIT, number of missed points of FDT, and normal or abnormal FDT. Measures of discrimination included sensitivity, specificity, area under the curve (AUC), Akaike’s information criterion (AIC), and prediction confidence interval lengths (PIL). Results For detecting glaucoma regardless of severity, the multivariable model resulting from the combination of GDX-TSNIT, number of abnormal points on FDT (NAP-FDT), and the interaction GDx-TSNIT * NAP-FDT (AIC: 88.28, AUC: 0.959, sensitivity: 94.6%, specificity: 89.5%) outperformed the best single variable model provided by GDx-NFI (AIC: 120.88, AUC: 0.914, sensitivity: 87.8%, specificity: 84.2%). The multivariable model combining GDx-TSNIT, NAPFDT, and interaction GDx-TSNIT*NAP-FDT consistently provided better discriminating abilities for detecting early, moderate and severe glaucoma than the best single variable models. Conclusions The multivariable model including GDx-TSNIT, NAP-FDT, and the interaction GDX-TSNIT * NAP-FDT provides the best glaucoma prediction compared to all other multivariable and univariable models. Combining the FDT C-20-5 screening protocol and GDx-VCC improves glaucoma detection compared to using GDx or FDT alone. PMID:24777046

Discrimination between Bacillus and Alicyclobacillus isolates in apple juice by Fourier transform infrared spectroscopy and multivariate analysis.

PubMed

Al-Holy, Murad A; Lin, Mengshi; Alhaj, Omar A; Abu-Goush, Mahmoud H

2015-02-01

Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared spectroscopy (FT-IR) was used to identify and discriminate between 4 Alicyclobacillus strains and 4 Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm(-1) reflected the most distinctive biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (for example, principal component analysis and soft independent modeling of class analogy) were used to analyze the spectral data. Distinctive separation of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus and to distinguish between species belonging to these 2 genera. © 2015 Institute of Food Technologists®

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Enlightening discriminative network functional modules behind Principal Component Analysis separation in differential-omic science studies

PubMed Central

Ciucci, Sara; Ge, Yan; Durán, Claudio; Palladini, Alessandra; Jiménez-Jiménez, Víctor; Martínez-Sánchez, Luisa María; Wang, Yuting; Sales, Susanne; Shevchenko, Andrej; Poser, Steven W.; Herbig, Maik; Otto, Oliver; Androutsellis-Theotokis, Andreas; Guck, Jochen; Gerl, Mathias J.; Cannistraci, Carlo Vittorio

2017-01-01

Omic science is rapidly growing and one of the most employed techniques to explore differential patterns in omic datasets is principal component analysis (PCA). However, a method to enlighten the network of omic features that mostly contribute to the sample separation obtained by PCA is missing. An alternative is to build correlation networks between univariately-selected significant omic features, but this neglects the multivariate unsupervised feature compression responsible for the PCA sample segregation. Biologists and medical researchers often prefer effective methods that offer an immediate interpretation to complicated algorithms that in principle promise an improvement but in practice are difficult to be applied and interpreted. Here we present PC-corr: a simple algorithm that associates to any PCA segregation a discriminative network of features. Such network can be inspected in search of functional modules useful in the definition of combinatorial and multiscale biomarkers from multifaceted omic data in systems and precision biomedicine. We offer proofs of PC-corr efficacy on lipidomic, metagenomic, developmental genomic, population genetic, cancer promoteromic and cancer stem-cell mechanomic data. Finally, PC-corr is a general functional network inference approach that can be easily adopted for big data exploration in computer science and analysis of complex systems in physics. PMID:28287094

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.

Acromegaly determination using discriminant analysis of the three-dimensional facial classification in Taiwanese.

PubMed

Wang, Ming-Hsu; Lin, Jen-Der; Chang, Chen-Nen; Chiou, Wen-Ko

2017-08-01

The aim of this study was to assess the size, angles and positional characteristics of facial anthropometry between "acromegalic" patients and control subjects. We also identify possible facial soft tissue measurements for generating discriminant functions toward acromegaly determination in males and females for acromegaly early self-awareness. This is a cross-sectional study. Subjects participating in this study included 70 patients diagnosed with acromegaly (35 females and 35 males) and 140 gender-matched control individuals. Three-dimensional facial images were collected via a camera system. Thirteen landmarks were selected. Eleven measurements from the three categories were selected and applied, including five frontal widths, three lateral depths and three lateral angular measurements. Descriptive analyses were conducted using means and standard deviations for each measurement. Univariate and multivariate discriminant function analyses were applied in order to calculate the accuracy of acromegaly detection. Patients with acromegaly exhibit soft-tissue facial enlargement and hypertrophy. Frontal widths as well as lateral depth and angle of facial changes were evident. The average accuracies of all functions for female patient detection ranged from 80.0-91.40%. The average accuracies of all functions for male patient detection were from 81.0-94.30%. The greatest anomaly observed was evidenced in the lateral angles, with greater enlargement of "nasofrontal" angles for females and greater "mentolabial" angles for males. Additionally, shapes of the lateral angles showed changes. The majority of the facial measurements proved dynamic for acromegaly patients; however, it is problematic to detect the disease with progressive body anthropometric changes. The discriminant functions of detection developed in this study could help patients, their families, medical practitioners and others to identify and track progressive facial change patterns before the possible patients go to the hospital, especially the lateral "angles" which can be calculated by relative point-to-point changes derived from 2D lateral imagery without the 3D anthropometric measurements. This study tries to provide a novel and easy method to detect acromegaly when the patients start to have awareness of abnormal appearance because of facial measurement changes, and it also suggests that undiagnosed patients be urged to go to the hospital as soon as possible for acromegaly early diagnosis.

The specter of discrimination: Fear of interpersonal racial discrimination among adolescents in Chicago.

PubMed

Herda, Daniel

2016-01-01

This analysis examines fear of interpersonal racial discrimination among Black, Hispanic, and White adolescents. The extent and correlates of these concerns are examined using survey data from the Project for Human Development in Chicago Neighborhoods. Borrowing from the fear-of-crime literature, the contact hypothesis, and group threat theory, several hypotheses are developed linking discrimination fear to direct personal experience with discrimination, indirect or vicarious experience, and environmental signals of discrimination. Results show that about half of Blacks and Hispanics have feared discrimination in the past year. Multivariate results indicate that fear is most likely if one has experienced victimization first-hand and when one's parent is affected by discrimination. Further, a larger presence neighborhood outgroups produces greater fear. Overall, discrimination fear constitutes an additional obstacle for minority adolescents as they transition to adulthood. The phenomenon warrants increased scholarly attention and represents a fruitful avenue for future research. Copyright © 2015 Elsevier Inc. All rights reserved.

Experiences of stigma, discrimination, care and support among people living with HIV: A four country study

PubMed Central

Neuman, Melissa; Obermeyer, Carla Makhlouf; Cherutich, Peter; Desclaux, Alice; Hardon, Anita; Ky-Zerbo, Odette; Namakhoma, Ireen; Wanyenze, Rhoda

2013-01-01

While it is widely agreed that HIV-related stigma may impede access to treatment and support, there is little evidence describing who is most likely to experience different forms of stigma and discrimination and how these affect disclosure and access to care. This study examined experiences of interpersonal discrimination, internalized stigma, and discrimination at health care facilities among HIV-positive adults aged 18 years and older utilizing health facilities in four countries in Sub-Saharan Africa (N=536). Prevalence of interpersonal discrimination across all countries was 34.6%, with women significantly more likely to experience interpersonal discrimination than men. Prevalences of internalized stigma varied across countries, ranging from 9.6% (Malawi) to 45.0% (Burkina Faso). Prevalence of health care discrimination was 10.4% across all countries. In multivariate analyses, we found positive, significant, and independent associations between disclosure and interpersonal discrimination and support group utilization, and positive associations between both internalized stigma and health care discrimination and referral for medications. PMID:23479002

Perceived discrimination and health among Puerto Rican and Mexican Americans: buffering effect of the Lazo matrimonial?

PubMed

Lee, Min-Ah; Ferraro, Kenneth F

2009-06-01

An emerging body of research shows that perceived discrimination adversely influences the mental health of minority populations, but is it also deleterious to physical health? If yes, can marriage buffer the effect of perceived discrimination on physical health? We address these questions with data from Puerto Rican and Mexican American residents of Chicago. Multivariate regression analyses reveal that perceived discrimination is associated with more physical health problems for both Puerto Rican and Mexican Americans. In addition, an interaction effect between marital status and perceived discrimination was observed: married Mexican Americans with higher perceived discrimination had fewer physical health problems than their unmarried counterparts even after adjusting for differential effects of marriage by nativity. The findings reveal that perceived discrimination is detrimental to the physical health of both Puerto Rican and Mexican Americans, but that the stress-buffering effect of marriage on physical health exists for Mexican Americans only.

Measurement Properties of the Scoliosis Research Society Outcomes Questionnaire in Adolescent Patients With Spondylolisthesis.

PubMed

Gutman, Gabriel; Joncas, Julie; Mac-Thiong, Jean-Marc; Beauséjour, Marie; Roy-Beaudry, Marjolaine; Labelle, Hubert; Parent, Stefan

2017-09-01

Prospective validation of the Scoliosis Research Society Outcomes Questionnaire French-Canadian version (SRS-22fv) in adolescent patients with spondylolisthesis. To determine the measurement properties of the SRS-22fv. The SRS-22 is widely used for the assessment of health-related quality of life in adolescent idiopathic scoliosis (AIS) and other spinal deformities. Spondylolisthesis has an important effect on quality of life. The instrument was previously used in this population, although its measurement properties remained unknown. We aim to determine its reliability, factorial, concurrent validity, and its discriminant capacity in an adolescent spondylolisthesis population. The SRS-22fv was tested in 479 subjects (272 patients with spondylolisthesis, 143 with AIS, and 64 controls) at a single institution. Its reliability was measured using the coefficient of internal consistency, concurrent validity by the short form-12 (SF-12v2 French version) and discriminant validity using multivariate analysis of variance, analysis of covariance, and multivariate linear regression. The SRS-22fv showed a good global internal consistency (spondylolisthesis: Cronbach α = 0.91, AIS: 0.86, and controls: 0.78) in all its domains for spondylolisthesis patients. It showed a factorial structure consistent with the original questionnaire, with 60% of explained variance under four factors. Moderate to high correlation coefficients were found for specifically corresponding domains between SRS-22fv and SF-12v2. Boys had higher scores than do girls, scores worsened with increasing age and body mass index. Analysis of covariance showed statistically significant differences between patients with spondylolisthesis, patients with AIS, and controls when controlling for age, sex, body mass index, pain, function, and self-image scores. In the spondylolisthesis group, scores on all domains and mean total scores were significantly lower in surgical candidates and in patients with high-grade spondylolisthesis. Low to moderate ceiling effects were shown in function (1.1%), self-image (10.7%), and pain (13.6%). The SRS-22fv can discriminate between healthy and spondylolisthesis subjects. It can be used in spondylolisthesis patients to assess health-related quality of life. 4.

Selective Attention in Fast and Slow Learners During Discrimination Learning in the Haptic Modality. Information and Research Report.

ERIC Educational Resources Information Center

Hunt, Dennis; And Others

Sixty-four 8-year-old children were divided into fast and slow learner groups and trained on a tactile simultaneous discrimination task. Selective attention was measured in terms of percentage contact time per trial to the relevant dimension. Inter- and intracouplings per trial were also recorded. A multivariate analysis was carried out to examine…

Fluorescent discrimination between traces of chemical warfare agents and their mimics.

PubMed

Díaz de Greñu, Borja; Moreno, Daniel; Torroba, Tomás; Berg, Alexander; Gunnars, Johan; Nilsson, Tobias; Nyman, Rasmus; Persson, Milton; Pettersson, Johannes; Eklind, Ida; Wästerby, Pär

2014-03-19

An array of fluorogenic probes is able to discriminate between nerve agents, sarin, soman, tabun, VX and their mimics, in water or organic solvent, by qualitative fluorescence patterns and quantitative multivariate analysis, thus making the system suitable for the in-the-field detection of traces of chemical warfare agents as well as to differentiate between the real nerve agents and other related compounds.

Compositional variations of ignimbrite magmas in the Central Andes over the past 26 Ma - A multivariate statistical perspective

NASA Astrophysics Data System (ADS)

Brandmeier, M.; Wörner, G.

2016-10-01

Multivariate statistical and geospatial analyses based on a compilation of 890 geochemical and 1200 geochronological data for 194 mapped ignimbrites from the Central Andes document the compositional and temporal patterns of large-volume ignimbrites (so-called "ignimbrite flare-ups") during Neogene times. Rapid advances in computational science during the past decade led to a growing pool of algorithms for multivariate statistics for large datasets with many predictor variables. This study applies cluster analysis (CA) and linear discriminant analysis (LDA) on log-ratio transformed data with the aim of (1) testing a tool for ignimbrite correlation and (2) distinguishing compositional groups that reflect different processes and sources of ignimbrite magmatism during the geodynamic evolution of the Central Andes. CA on major and trace elements allows grouping of ignimbrites according to their geochemical characteristics into rhyolitic and dacitic "end-members" and to differentiate characteristic trace element signatures with respect to Eu anomaly, depletions in middle and heavy rare earth elements (REE) and variable enrichments in light REE. To highlight these distinct compositional signatures, we applied LDA to selected ignimbrites for which comprehensive datasets were available. In comparison to traditional geochemical parameters we found that the advantage of multivariate statistics is their capability of dealing with large datasets and many variables (elements) and to take advantage of this n-dimensional space to detect subtle compositional differences contained in the data. The most important predictors for discriminating ignimbrites are La, Yb, Eu, Al2O3, K2O, P2O5, MgO, FeOt, and TiO2. However, other REE such as Gd, Pr, Tm, Sm, Dy and Er also contribute to the discrimination functions. Significant compositional differences were found between (1) the older (> 13 Ma) large-volume plateau-forming ignimbrites in northernmost Chile and southern Peru and (2) the younger (< 10 Ma) Altiplano-Puna-Volcanic-Complex (APVC) ignimbrites that are of similar volumes. Older ignimbrites are less depleted in HREE and less radiogenic in Sr isotopes, indicating smaller crustal contributions during evolution in a thinner and thermally less evolved crust. These compositional variations indicate a relation to crustal thickening with a "transition" from plagioclase to amphibole and garnet residual mineralogy between 13 and 9 Ma. Compositional and volumetric variations correlate to the N-S passage of the Juan-Fernandéz-Ridge, crustal shortening and thickening, and increased average crustal temperatures during the past 26 Ma. Table DR2 Mapped ignimbrite sheets.

Discrimination, Perceived Social Inequity, and Mental Health Among Rural-to-Urban Migrants in China

PubMed Central

Lin, Danhua; Wang, Bo; Hong, Yan; Qin, Xiong; Stanton, Bonita

2010-01-01

Status-based discrimination and inequity have been associated with the process of migration, especially with economics-driven internal migration. However, their association with mental health among economy-driven internal migrants in developing countries is rarely assessed. This study examines discriminatory experiences and perceived social inequity in relation to mental health status among rural-to-urban migrants in China. Cross-sectional data were collected from 1,006 rural-to-urban migrants in 2004–2005 in Beijing, China. Participants reported their perceptions and experiences of being discriminated in daily life in urban destination and perceived social inequity. Mental health was measured using the symptom checklist-90 (SCL-90). Multivariate analyses using general linear model were performed to test the effect of discriminatory experience and perceived social inequity on mental health. Experience of discrimination was positively associated with male gender, being married at least once, poorer health status, shorter duration of migration, and middle range of personal income. Likewise, perceived social inequity was associated with poorer health status, higher education attainment, and lower personal income. Multivariate analyses indicate that both experience of discrimination and perceived social inequity were strongly associated with mental health problems of rural-to-urban migrants. Experience of discrimination in daily life and perceived social inequity have a significant influence on mental health among rural-to-urban migrants. The findings underscore the needs to reduce public or societal discrimination against rural-to-urban migrants, to eliminate structural barriers (i.e., dual household registrations) for migrants to fully benefit from the urban economic development, and to create a positive atmosphere to improve migrant's psychological well-being. PMID:20033772

Determining sources of elevated salinity in pre-hydraulic fracturing water quality data using a multivariate discriminant analysis model

NASA Astrophysics Data System (ADS)

Lautz, L. K.; Hoke, G. D.; Lu, Z.; Siegel, D. I.

2013-12-01

Hydraulic fracturing has the potential to introduce saline water into the environment due to migration of deep formation water to shallow aquifers and/or discharge of flowback water to the environment during transport and disposal. It is challenging to definitively identify whether elevated salinity is associated with hydraulic fracturing, in part, due to the real possibility of other anthropogenic sources of salinity in the human-impacted watersheds in which drilling is taking place and some formation water present naturally in shallow groundwater aquifers. We combined new and published chemistry data for private drinking water wells sampled across five southern New York (NY) counties overlying the Marcellus Shale (Broome, Chemung, Chenango, Steuben, and Tioga). Measurements include Cl, Na, Br, I, Ca, Mg, Ba, SO4, and Sr. We compared this baseline groundwater quality data in NY, now under a moratorium on hydraulic fracturing, with published chemistry data for 6 different potential sources of elevated salinity in shallow groundwater, including Appalachian Basin formation water, road salt runoff, septic effluent, landfill leachate, animal waste, and water softeners. A multivariate random number generator was used to create a synthetic, low salinity (< 20 mg/L Cl) groundwater data set (n=1000) based on the statistical properties of the observed low salinity groundwater. The synthetic, low salinity groundwater was then artificially mixed with variable proportions of different potential sources of salinity to explore chemical differences between groundwater impacted by formation water, road salt runoff, septic effluent, landfill leachate, animal waste, and water softeners. We then trained a multivariate, discriminant analysis model on the resulting data set to classify observed high salinity groundwater (> 20 mg/L Cl) as being affected by formation water, road salt, septic effluent, landfill leachate, animal waste, or water softeners. Single elements or pairs of elements (e.g. Cl and Br) were not effective at discriminating between sources of salinity, indicating multivariate methods are needed. The discriminant analysis model classified most accurately samples affected by formation water and landfill leachate, whereas those contaminated by road salt, animal waste, and water softeners were more likely to be discriminated as contaminated by a different source. Using this approach, no shallow groundwater samples from NY appear to be affected by formation water, suggesting the source of salinity pre-hydraulic fracturing is primarily a combination of road salt, septic effluent, landfill leachate, and animal waste.

Modelling spatio-temporal heterogeneities in groundwater quality in Ghana: a multivariate chemometric approach.

PubMed

Armah, Frederick Ato; Paintsil, Arnold; Yawson, David Oscar; Adu, Michael Osei; Odoi, Justice O

2017-08-01

Chemometric techniques were applied to evaluate the spatial and temporal heterogeneities in groundwater quality data for approximately 740 goldmining and agriculture-intensive locations in Ghana. The strongest linear and monotonic relationships occurred between Mn and Fe. Sixty-nine per cent of total variance in the dataset was explained by four variance factors: physicochemical properties, bacteriological quality, natural geologic attributes and anthropogenic factors (artisanal goldmining). There was evidence of significant differences in means of all trace metals and physicochemical parameters (p < 0.001) between goldmining and non-goldmining locations. Arsenic and turbidity produced very high value F's demonstrating that 'physical properties and chalcophilic elements' was the function that most discriminated between non-goldmining and goldmining locations. Variations in Escherichia coli and total coliforms were observed between the dry and wet seasons. The overall predictive accuracy of the discriminant function showed that non-goldmining locations were classified with slightly better accuracy (89%) than goldmining areas (69.6%). There were significant differences between the underlying distributions of Cd, Mn and Pb in the wet and dry seasons. This study emphasizes the practicality of chemometrics in the assessment and elucidation of complex water quality datasets to promote effective management of groundwater resources for sustaining human health.

Combining vibrational biomolecular spectroscopy with chemometric techniques for the study of response and sensitivity of molecular structures/functional groups mainly related to lipid biopolymer to various processing applications.

PubMed

Yu, Gloria Qingyu; Yu, Peiqiang

2015-09-01

The objectives of this project were to (1) combine vibrational spectroscopy with chemometric multivariate techniques to determine the effect of processing applications on molecular structural changes of lipid biopolymer that mainly related to functional groups in green- and yellow-type Crop Development Centre (CDC) pea varieties [CDC strike (green-type) vs. CDC meadow (yellow-type)] that occurred during various processing applications; (2) relatively quantify the effect of processing applications on the antisymmetric CH3 ("CH3as") and CH2 ("CH2as") (ca. 2960 and 2923 cm(-1), respectively), symmetric CH3 ("CH3s") and CH2 ("CH2s") (ca. 2873 and 2954 cm(-1), respectively) functional groups and carbonyl C=O ester (ca. 1745 cm(-1)) spectral intensities as well as their ratios of antisymmetric CH3 to antisymmetric CH2 (ratio of CH3as to CH2as), ratios of symmetric CH3 to symmetric CH2 (ratio of CH3s to CH2s), and ratios of carbonyl C=O ester peak area to total CH peak area (ratio of C=O ester to CH); and (3) illustrate non-invasive techniques to detect the sensitivity of individual molecular functional group to the various processing applications in the recently developed different types of pea varieties. The hypothesis of this research was that processing applications modified the molecular structure profiles in the processed products as opposed to original unprocessed pea seeds. The results showed that the different processing methods had different impacts on lipid molecular functional groups. Different lipid functional groups had different sensitivity to various heat processing applications. These changes were detected by advanced molecular spectroscopy with chemometric techniques which may be highly related to lipid utilization and availability. The multivariate molecular spectral analyses, cluster analysis, and principal component analysis of original spectra (without spectral parameterization) are unable to fully distinguish the structural differences in the antisymmetric and symmetric CH3 and CH2 spectral region (ca. 3001-2799 cm(-1)) and carbonyl C=O ester band region (ca. 1771-1714 cm(-1)). This result indicated that the sensitivity to detect treatment difference by multivariate analysis of cluster analysis (CLA) and principal components analysis (PCA) might be lower compared with univariate molecular spectral analysis. In the future, other more sensitive techniques such as "discriminant analysis" could be considered for discriminating and classifying structural differences. Molecular spectroscopy can be used as non-invasive technique to study processing-induced structural changes that are related to lipid compound in legume seeds.

Longitudinal relationships between antiretroviral treatment adherence and discrimination due to HIV-serostatus, race, and sexual orientation among African-American men with HIV.

PubMed

Bogart, Laura M; Wagner, Glenn J; Galvan, Frank H; Klein, David J

2010-10-01

African-Americans show worse HIV disease outcomes compared to Whites. Health disparities may be aggravated by discrimination, which is associated with worse health and maladaptive health behaviors. We examined longitudinal effects of discrimination on antiretroviral treatment adherence among 152 HIV-positive Black men who have sex with men. We measured adherence and discrimination due to HIV-serostatus, race/ethnicity, and sexual orientation at baseline and monthly for 6 months. Hierarchical repeated-measures models tested longitudinal effects of each discrimination type on adherence. Over 6 months, participants took 60% of prescribed medications on average; substantial percentages experienced discrimination (HIV-serostatus, 38%; race/ethnicity, 40%; and sexual orientation, 33%). Greater discrimination due to all three characteristics was significantly bivariately associated with lower adherence (all p's < 0.05). In the multivariate model, only racial discrimination was significant (p < 0.05). Efforts to improve HIV treatment adherence should consider the context of multiple stigmas, especially racism.

Influence of experiences of racial discrimination and ethnic identity on prenatal smoking among urban black and Hispanic women.

PubMed

Nguyen, Kim Hanh; Subramanian, S V; Sorensen, Glorian; Tsang, Kathy; Wright, Rosalind J

2012-04-01

Although the prevalence of prenatal smoking among minority women exceeds the projected 2010 national objective, data on the determinants of prenatal smoking among minorities remain sparse. We examined associations between self-reported experiences of racial discrimination on prenatal smoking among urban black and Hispanic women aged 18-44 years (n=677). Our main independent variable was created from the Experiences of Discrimination (EOD) scale. Multivariable logistic regression models were estimated to examine the relationship between EOD (moderate EOD as the referent group) and smoking for the entire sample and then separately by race/ethnicity adjusted for sociodemographic variables. We also examined the role of ethnic identity (EI) as a buffer to racial discrimination (n=405). The prevalence of smoking was 18.1% versus 10% for black and Hispanic women, respectively (p=0.002). There were no significant differences in the level of EOD based on race. In multivariate regressions, compared to those reporting moderate EOD, women reporting high discrimination (OR 2.64, 95% CI 1.25 to 5.60) had higher odds of smoking. In stratified analyses, this relationship remained significant only in black women. Results suggest that foreign-born Hispanic women with higher EI were less likely to smoke compared to their low-EI counterparts (3.5 vs 10.1%; p=0.08). These are the first data in pregnant minority women showing an association between discrimination and increased risk of smoking particularly among black women. Ethnic identity and nativity status were also associated with smoking risk. Smoking cessation programmes should consider such factors among childbearing minority women.

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.

Intrinsic, stimulus-driven and task-dependent connectivity in human auditory cortex.

PubMed

Häkkinen, Suvi; Rinne, Teemu

2018-06-01

A hierarchical and modular organization is a central hypothesis in the current primate model of auditory cortex (AC) but lacks validation in humans. Here we investigated whether fMRI connectivity at rest and during active tasks is informative of the functional organization of human AC. Identical pitch-varying sounds were presented during a visual discrimination (i.e. no directed auditory attention), pitch discrimination, and two versions of pitch n-back memory tasks. Analysis based on fMRI connectivity at rest revealed a network structure consisting of six modules in supratemporal plane (STP), temporal lobe, and inferior parietal lobule (IPL) in both hemispheres. In line with the primate model, in which higher-order regions have more longer-range connections than primary regions, areas encircling the STP module showed the highest inter-modular connectivity. Multivariate pattern analysis indicated significant connectivity differences between the visual task and rest (driven by the presentation of sounds during the visual task), between auditory and visual tasks, and between pitch discrimination and pitch n-back tasks. Further analyses showed that these differences were particularly due to connectivity modulations between the STP and IPL modules. While the results are generally in line with the primate model, they highlight the important role of human IPL during the processing of both task-irrelevant and task-relevant auditory information. Importantly, the present study shows that fMRI connectivity at rest, during presentation of sounds, and during active listening provides novel information about the functional organization of human AC.

Functional MRI Representational Similarity Analysis Reveals a Dissociation between Discriminative and Relative Location Information in the Human Visual System.

PubMed

Roth, Zvi N

2016-01-01

Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream.

Functional MRI Representational Similarity Analysis Reveals a Dissociation between Discriminative and Relative Location Information in the Human Visual System

PubMed Central

Roth, Zvi N.

2016-01-01

Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream. PMID:27242455

Feature discrimination/identification based upon SAR return variations

NASA Technical Reports Server (NTRS)

Rasco, W. A., Sr.; Pietsch, R.

1978-01-01

A study of the statistics of The look-to-look variation statistics in the returns recorded in-flight by a digital, realtime SAR system are analyzed. The determination that the variations in the look-to-look returns from different classes do carry information content unique to the classes was illustrated by a model based on four variants derived from four look in-flight SAR data under study. The model was limited to four classes of returns: mowed grass on a athletic field, rough unmowed grass and weeds on a large vacant field, young fruit trees in a large orchard, and metal mobile homes and storage buildings in a large mobile home park. The data population in excess of 1000 returns represented over 250 individual pixels from the four classes. The multivariant discriminant model operated on the set of returns for each pixel and assigned that pixel to one of the four classes, based on the target variants and the probability distribution function of the four variants for each class.

Perceived discrimination, psychological distress, and current smoking status: results from the Behavioral Risk Factor Surveillance System Reactions to Race module, 2004-2008.

PubMed

Purnell, Jason Q; Peppone, Luke J; Alcaraz, Kassandra; McQueen, Amy; Guido, Joseph J; Carroll, Jennifer K; Shacham, Enbal; Morrow, Gary R

2012-05-01

We examined the association between perceived discrimination and smoking status and whether psychological distress mediated this relationship in a large, multiethnic sample. We used 2004 through 2008 data from the Behavioral Risk Factor Surveillance System Reactions to Race module to conduct multivariate logistic regression analyses and tests of mediation examining associations between perceived discrimination in health care and workplace settings, psychological distress, and current smoking status. Regardless of race/ethnicity, perceived discrimination was associated with increased odds of current smoking. Psychological distress was also a significant mediator of the discrimination-smoking association. Our results indicate that individuals who report discriminatory treatment in multiple domains may be more likely to smoke, in part, because of the psychological distress associated with such treatment.

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

Predicting trauma patient mortality: ICD [or ICD-10-AM] versus AIS based approaches.

PubMed

Willis, Cameron D; Gabbe, Belinda J; Jolley, Damien; Harrison, James E; Cameron, Peter A

2010-11-01

The International Classification of Diseases Injury Severity Score (ICISS) has been proposed as an International Classification of Diseases (ICD)-10-based alternative to mortality prediction tools that use Abbreviated Injury Scale (AIS) data, including the Trauma and Injury Severity Score (TRISS). To date, studies have not examined the performance of ICISS using Australian trauma registry data. This study aimed to compare the performance of ICISS with other mortality prediction tools in an Australian trauma registry. This was a retrospective review of prospectively collected data from the Victorian State Trauma Registry. A training dataset was created for model development and a validation dataset for evaluation. The multiplicative ICISS model was compared with a worst injury ICISS approach, Victorian TRISS (V-TRISS, using local coefficients), maximum AIS severity and a multivariable model including ICD-10-AM codes as predictors. Models were investigated for discrimination (C-statistic) and calibration (Hosmer-Lemeshow statistic). The multivariable approach had the highest level of discrimination (C-statistic 0.90) and calibration (H-L 7.65, P= 0.468). Worst injury ICISS, V-TRISS and maximum AIS had similar performance. The multiplicative ICISS produced the lowest level of discrimination (C-statistic 0.80) and poorest calibration (H-L 50.23, P < 0.001). The performance of ICISS may be affected by the data used to develop estimates, the ICD version employed, the methods for deriving estimates and the inclusion of covariates. In this analysis, a multivariable approach using ICD-10-AM codes was the best-performing method. A multivariable ICISS approach may therefore be a useful alternative to AIS-based methods and may have comparable predictive performance to locally derived TRISS models. © 2010 The Authors. ANZ Journal of Surgery © 2010 Royal Australasian College of Surgeons.

Multivariate Classification of Major Depressive Disorder Using the Effective Connectivity and Functional Connectivity

PubMed Central

Geng, Xiangfei; Xu, Junhai; Liu, Baolin; Shi, Yonggang

2018-01-01

Major depressive disorder (MDD) is a mental disorder characterized by at least 2 weeks of low mood, which is present across most situations. Diagnosis of MDD using rest-state functional magnetic resonance imaging (fMRI) data faces many challenges due to the high dimensionality, small samples, noisy and individual variability. To our best knowledge, no studies aim at classification with effective connectivity and functional connectivity measures between MDD patients and healthy controls. In this study, we performed a data-driving classification analysis using the whole brain connectivity measures which included the functional connectivity from two brain templates and effective connectivity measures created by the default mode network (DMN), dorsal attention network (DAN), frontal-parietal network (FPN), and silence network (SN). Effective connectivity measures were extracted using spectral Dynamic Causal Modeling (spDCM) and transformed into a vectorial feature space. Linear Support Vector Machine (linear SVM), non-linear SVM, k-Nearest Neighbor (KNN), and Logistic Regression (LR) were used as the classifiers to identify the differences between MDD patients and healthy controls. Our results showed that the highest accuracy achieved 91.67% (p < 0.0001) when using 19 effective connections and 89.36% when using 6,650 functional connections. The functional connections with high discriminative power were mainly located within or across the whole brain resting-state networks while the discriminative effective connections located in several specific regions, such as posterior cingulate cortex (PCC), ventromedial prefrontal cortex (vmPFC), dorsal cingulate cortex (dACC), and inferior parietal lobes (IPL). To further compare the discriminative power of functional connections and effective connections, a classification analysis only using the functional connections from those four networks was conducted and the highest accuracy achieved 78.33% (p < 0.0001). Our study demonstrated that the effective connectivity measures might play a more important role than functional connectivity in exploring the alterations between patients and health controls and afford a better mechanistic interpretability. Moreover, our results showed a diagnostic potential of the effective connectivity for the diagnosis of MDD patients with high accuracies allowing for earlier prevention or intervention. PMID:29515348

Discriminant analysis of cardiovascular and respiratory variables for classification of road cyclists by specialty.

PubMed

Nikolić, Biljana; Martinović, Jelena; Matić, Milan; Stefanović, Đorđe

2018-05-29

Different variables determine the performance of cyclists, which brings up the question how these parameters may help in their classification by specialty. The aim of the study was to determine differences in cardiorespiratory parameters of male cyclists according to their specialty, flat rider (N=21), hill rider (N=35) and sprinter (N=20) and obtain the multivariate model for further cyclists classification by specialties, based on selected variables. Seventeen variables were measured at submaximal and maximum load on the cycle ergometer Cosmed E 400HK (Cosmed, Rome, Italy) (initial 100W with 25W increase, 90-100 rpm). Multivariate discriminant analysis was used to determine which variables group cyclists within their specialty, and to predict which variables can direct cyclists to a particular specialty. Among nine variables that statistically contribute to the discriminant power of the model, achieved power on the anaerobic threshold and the produced CO2 had the biggest impact. The obtained discriminatory model correctly classified 91.43% of flat riders, 85.71% of hill riders, while sprinters were classified completely correct (100%), i.e. 92.10% of examinees were correctly classified, which point out the strength of the discriminatory model. Respiratory indicators mostly contribute to the discriminant power of the model, which may significantly contribute to training practice and laboratory tests in future.

Examining substance use and affective processes as multivariate risk factors associated with overweight body mass among treatment-seeking smokers.

PubMed

Farris, Samantha G; Zvolensky, Michael J; Robles, Zuzuky; Schmidt, Norman B

2015-01-01

Cigarette smoking and obesity are two major public health problems. However, factors related to the underlying risk for being overweight are not well established. Certain demographic, smoking, and psychological factors have been linked to overweight/obese body mass. The current study examined a multivariate risk model, stratified by gender, in order to better explicate the nature of overweight body mass among daily smokers. In a sample of treatment-seeking smokers (n = 395), among males and females, (1) older age, (2) stronger expectancies about the weight/appetite control effects of smoking, (3) greater smoking-based inflexibility/avoidance due to smoking-related sensations, and (4) less problematic alcohol use, were associated with being overweight. Additionally, among males, having a tobacco-related medical problem and higher tolerance for physical discomfort aided in the discriminant function model for classifying smokers as overweight. Together, numerous cognitive-affective vulnerabilities and smoking processes may be targetable and potentially inform weight-related prevention programs among smokers.

[A Feature Extraction Method for Brain Computer Interface Based on Multivariate Empirical Mode Decomposition].

PubMed

Wang, Jinjia; Liu, Yuan

2015-04-01

This paper presents a feature extraction method based on multivariate empirical mode decomposition (MEMD) combining with the power spectrum feature, and the method aims at the non-stationary electroencephalogram (EEG) or magnetoencephalogram (MEG) signal in brain-computer interface (BCI) system. Firstly, we utilized MEMD algorithm to decompose multichannel brain signals into a series of multiple intrinsic mode function (IMF), which was proximate stationary and with multi-scale. Then we extracted and reduced the power characteristic from each IMF to a lower dimensions using principal component analysis (PCA). Finally, we classified the motor imagery tasks by linear discriminant analysis classifier. The experimental verification showed that the correct recognition rates of the two-class and four-class tasks of the BCI competition III and competition IV reached 92.0% and 46.2%, respectively, which were superior to the winner of the BCI competition. The experimental proved that the proposed method was reasonably effective and stable and it would provide a new way for feature extraction.

Discriminative Ability of Plasma Branched-Chain Amino Acid Levels for Glucose Intolerance in Families At Risk for Type 2 Diabetes.

PubMed

Jainandunsing, Sjaam; Wattimena, J L Darcos; Verhoeven, Adrie J M; Langendonk, Janneke G; Rietveld, Trinet; Isaacs, Aaron J; Sijbrands, Eric J G; de Rooij, Felix W M

2016-04-01

Insulin resistance and glucose intolerance have been associated with increased plasma levels of branched-chain amino acids (BCAA). BCAA levels do not predict T2DM in the population. We determined the discriminative ability of fasting BCAA levels for glucose intolerance in nondiabetic relatives of patients with T2DM of two different ethnicities. Based on oral glucose tolerance test (OGTT), first-degree relatives of patients with T2DM were categorized as normal glucose tolerance, prediabetes, or T2DM. Included were 34, 12, and 18 Caucasian and 22, 12, and 23 Asian Indian participants, respectively. BCAA levels were measured in fasting plasma together with alanine, phenylalanine, and tyrosine. Insulin sensitivity and beta-cell function were assessed by indices derived from an extended OGTT and their relationship with plasma BCAA levels was assessed in multivariate regression analysis. The value of the amino acids for discriminating prediabetes among nondiabetic family members was determined with the area under the curve of receiver-operated characteristics (c-index). BCAA levels were higher in diabetic than in normoglycemic family members in the Caucasians (P = 0.001) but not in the Asian Indians. In both groups, BCAA levels were associated with waist-hip ratio (β = 0.31; P = 0.03 and β = 0.42; P = 0.001, respectively) but not with indices of insulin sensitivity or beta-cell function. The c-index of BCAA for discriminating prediabetes among nondiabetic participants was 0.83 and 0.74 in Caucasians and Asian Indians, respectively, which increased to 0.84 and 0.79 by also including the other amino acids. The c-index of fasting glucose for discriminating prediabetes increased from 0.91 to 0.92 in Caucasians and 0.85 to 0.97 (P = 0.04) in Asian Indians by inclusion of BCAA+alanine, phenylalanine, and tyrosine. Adding fasting plasma BCAA levels, combined with phenylalanine, tyrosine and alanine to fasting glucose improved discriminative ability for the prediabetic state within Asian Indian families at risk for T2DM. BCAA levels may serve as biomarkers for early development of glucose intolerance in these families.

The intervals method: a new approach to analyse finite element outputs using multivariate statistics

PubMed Central

De Esteban-Trivigno, Soledad; Püschel, Thomas A.; Fortuny, Josep

2017-01-01

Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches. PMID:29043107

Selective sensing of vapors of similar dielectric constants using peptide-capped gold nanoparticles on individual multivariable transducers.

PubMed

Nagraj, Nandini; Slocik, Joseph M; Phillips, David M; Kelley-Loughnane, Nancy; Naik, Rajesh R; Potyrailo, Radislav A

2013-08-07

Peptide-capped AYSSGAPPMPPF gold nanoparticles were demonstrated for highly selective chemical vapor sensing using individual multivariable inductor-capacitor-resistor (LCR) resonators. Their multivariable response was achieved by measuring their resonance impedance spectra followed by multivariate spectral analysis. Detection of model toxic vapors and chemical agent simulants, such as acetonitrile, dichloromethane and methyl salicylate, was performed. Dichloromethane (dielectric constant εr = 9.1) and methyl salicylate (εr = 9.0) were discriminated using a single sensor. These sensing materials coupled to multivariable transducers can provide numerous opportunities for tailoring the vapor response selectivity based on the diversity of the amino acid composition of the peptides, and by the modulation of the nature of peptide-nanoparticle interactions through designed combinations of hydrophobic and hydrophilic amino acids.

Multivariate qualitative analysis of banned additives in food safety using surface enhanced Raman scattering spectroscopy.

PubMed

He, Shixuan; Xie, Wanyi; Zhang, Wei; Zhang, Liqun; Wang, Yunxia; Liu, Xiaoling; Liu, Yulong; Du, Chunlei

2015-02-25

A novel strategy which combines iteratively cubic spline fitting baseline correction method with discriminant partial least squares qualitative analysis is employed to analyze the surface enhanced Raman scattering (SERS) spectroscopy of banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. Multivariate qualitative analysis methods, using the combination of spectra preprocessing iteratively cubic spline fitting (ICSF) baseline correction with principal component analysis (PCA) and discriminant partial least squares (DPLS) classification respectively, are applied to investigate the effectiveness of SERS spectroscopy for predicting the class assignments of unknown banned food additives. PCA cannot be used to predict the class assignments of unknown samples. However, the DPLS classification can discriminate the class assignment of unknown banned additives using the information of differences in relative intensities. The results demonstrate that SERS spectroscopy combined with ICSF baseline correction method and exploratory analysis methodology DPLS classification can be potentially used for distinguishing the banned food additives in field of food safety. Copyright © 2014 Elsevier B.V. All rights reserved.

fMRI-based Multivariate Pattern Analyses Reveal Imagery Modality and Imagery Content Specific Representations in Primary Somatosensory, Motor and Auditory Cortices.

PubMed

de Borst, Aline W; de Gelder, Beatrice

2017-08-01

Previous studies have shown that the early visual cortex contains content-specific representations of stimuli during visual imagery, and that these representational patterns of imagery content have a perceptual basis. To date, there is little evidence for the presence of a similar organization in the auditory and tactile domains. Using fMRI-based multivariate pattern analyses we showed that primary somatosensory, auditory, motor, and visual cortices are discriminative for imagery of touch versus sound. In the somatosensory, motor and visual cortices the imagery modality discriminative patterns were similar to perception modality discriminative patterns, suggesting that top-down modulations in these regions rely on similar neural representations as bottom-up perceptual processes. Moreover, we found evidence for content-specific representations of the stimuli during auditory imagery in the primary somatosensory and primary motor cortices. Both the imagined emotions and the imagined identities of the auditory stimuli could be successfully classified in these regions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Spectral Mining for Discriminating Blood Origins in the Presence of Substrate Interference via Attenuated Total Reflection Fourier Transform Infrared Spectroscopy: Postmortem or Antemortem Blood?

PubMed

Takamura, Ayari; Watanabe, Ken; Akutsu, Tomoko; Ikegaya, Hiroshi; Ozawa, Takeaki

2017-09-19

Often in criminal investigations, discrimination of types of body fluid evidence is crucially important to ascertain how a crime was committed. Compared to current methods using biochemical techniques, vibrational spectroscopic approaches can provide versatile applicability to identify various body fluid types without sample invasion. However, their applicability is limited to pure body fluid samples because important signals from body fluids incorporated in a substrate are affected strongly by interference from substrate signals. Herein, we describe a novel approach to recover body fluid signals that are embedded in strong substrate interferences using attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy and an innovative multivariate spectral processing. This technique supported detection of covert features of body fluid signals, and then identified origins of body fluid stains on substrates. We discriminated between ATR FT-IR spectra of postmortem blood (PB) and those of antemortem blood (AB) by creating a multivariate statistics model. From ATR FT-IR spectra of PB and AB stains on interfering substrates (polyester, cotton, and denim), blood-originated signals were extracted by a weighted linear regression approach we developed originally using principal components of both blood and substrate spectra. The blood-originated signals were finally classified by the discriminant model, demonstrating high discriminant accuracy. The present method can identify body fluid evidence independently of the substrate type, which is expected to promote the application of vibrational spectroscopic techniques in forensic body fluid analysis.

Identifying the hydrochemical characteristics of rivers and groundwater by multivariate statistical analysis in the Sanjiang Plain, China

NASA Astrophysics Data System (ADS)

Cao, Yingjie; Tang, Changyuan; Song, Xianfang; Liu, Changming; Zhang, Yinghua

2016-06-01

Two multivariate statistical technologies, factor analysis (FA) and discriminant analysis (DA), are applied to study the river and groundwater hydrochemistry and its controlling processes in the Sanjiang Plain of the northeast China. Factor analysis identifies five factors which account for 79.65 % of the total variance in the dataset. Four factors bearing specific meanings as the river and groundwater hydrochemistry controlling processes are divided into two groups, the "natural hydrochemistry evolution" group and the "pollution" group. The "natural hydrochemistry evolution" group includes the salinity factor (factor 1) caused by rock weathering and the residence time factor (factor 2) reflecting the groundwater traveling time. The "pollution" group represents the groundwater quality deterioration due to geogenic pollution caused by elevated Fe and Mn (factor 3) and elevated nitrate (NO3 -) introduced by human activities such as agriculture exploitations (factor 5). The hydrochemical difference and hydraulic connection among rivers (surface water, SW), shallow groundwater (SG) and deep groundwater (DG) group are evaluated by the factor scores obtained from FA and DA (Fisher's method). It is showed that the river water is characterized as low salinity and slight pollution, and the shallow groundwater has the highest salinity and severe pollution. The SW is well separated from SG and DG by Fisher's discriminant function, but the SG and DG can not be well separated showing their hydrochemical similarities, and emphasize hydraulic connections between SG and DG.

Estuarial fingerprinting through multidimensional fluorescence and multivariate analysis.

PubMed

Hall, Gregory J; Clow, Kerin E; Kenny, Jonathan E

2005-10-01

As part of a strategy for preventing the introduction of aquatic nuisance species (ANS) to U.S. estuaries, ballast water exchange (BWE) regulations have been imposed. Enforcing these regulations requires a reliable method for determining the port of origin of water in the ballast tanks of ships entering U.S. waters. This study shows that a three-dimensional fluorescence fingerprinting technique, excitation emission matrix (EEM) spectroscopy, holds great promise as a ballast water analysis tool. In our technique, EEMs are analyzed by multivariate classification and curve resolution methods, such as N-way partial least squares Regression-discriminant analysis (NPLS-DA) and parallel factor analysis (PARAFAC). We demonstrate that classification techniques can be used to discriminate among sampling sites less than 10 miles apart, encompassing Boston Harbor and two tributaries in the Mystic River Watershed. To our knowledge, this work is the first to use multivariate analysis to classify water as to location of origin. Furthermore, it is shown that curve resolution can show seasonal features within the multidimensional fluorescence data sets, which correlate with difficulty in classification.

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®

Perceived age discrimination in older adults.

PubMed

Rippon, Isla; Kneale, Dylan; de Oliveira, Cesar; Demakakos, Panayotes; Steptoe, Andrew

2014-05-01

to examine perceived age discrimination in a large representative sample of older adults in England. this cross-sectional study of over 7,500 individuals used data from the fifth wave of the English Longitudinal Study of Ageing (ELSA), a longitudinal cohort study of men and women aged 52 years and older in England. Wave 5 asked respondents about the frequency of five everyday discriminatory situations. Participants who attributed any experiences of discrimination to their age were treated as cases of perceived age discrimination. Multivariable logistic regression analysis was used to estimate the odds ratios of experiencing perceived age discrimination in relation to selected sociodemographic factors. approximately a third (33.3%) of all respondents experienced age discrimination, rising to 36.8% in those aged 65 and over. Perceived age discrimination was associated with older age, higher education, lower levels of household wealth and being retired or not in employment. The correlates of age discrimination across the five discriminatory situations were similar. understanding age discrimination is vital if we are to develop appropriate policies and to target future interventions effectively. These findings highlight the scale of the challenge of age discrimination for older adults in England and illustrate that those groups are particularly vulnerable to this form of discrimination.

Multivariate geometry as an approach to algal community analysis

USGS Publications Warehouse

Allen, T.F.H.; Skagen, S.

1973-01-01

Multivariate analyses are put in the context of more usual approaches to phycological investigations. The intuitive common-sense involved in methods of ordination, classification and discrimination are emphasised by simple geometric accounts which avoid jargon and matrix algebra. Warnings are given that artifacts result from technique abuses by the naive or over-enthusiastic. An analysis of a simple periphyton data set is presented as an example of the approach. Suggestions are made as to situations in phycological investigations, where the techniques could be appropriate. The discipline is reprimanded for its neglect of the multivariate approach.

A comparison of two follow-up analyses after multiple analysis of variance, analysis of variance, and descriptive discriminant analysis: A case study of the program effects on education-abroad programs

Treesearch

Alvin H. Yu; Garry Chick

2010-01-01

This study compared the utility of two different post-hoc tests after detecting significant differences within factors on multiple dependent variables using multivariate analysis of variance (MANOVA). We compared the univariate F test (the Scheffé method) to descriptive discriminant analysis (DDA) using an educational-tour survey of university study-...

Neurodevelopmental functioning in children with FAS, pFAS, and ARND.

PubMed

Chasnoff, Ira J; Wells, Anne M; Telford, Erin; Schmidt, Christine; Messer, Gwendolyn

2010-04-01

The purpose of this article is to compare the neurodevelopmental profiles of 78 foster and adopted children with fetal alcohol syndrome (FAS), partial FAS (pFAS), or alcohol-related neurodevelopmental disorder (ARND). Seventy-eight foster and adopted children underwent a comprehensive diagnostic evaluation. By using criteria more stringent than those required by current guidelines, the children were placed in 1 of 3 diagnostic categories: FAS, pFAS, or ARND. Each child was evaluated across the domains of neuropsychological functioning most frequently affected by prenatal exposure to alcohol. Multivariate analyses of variance were conducted to examine differences in neuropsychological functioning between the 3 diagnostic groups. Descriptive discriminant analyses were performed in follow-up to the multivariate analyses of variance. The children in the 3 diagnostic categories were similar for descriptive and child welfare variables. Children with FAS had significantly decreased mean weight, height, and head circumference. Children with FAS exhibited the most impaired level of general intelligence, significantly worse language-based memory compared with children with ARND, and significantly poorer functional communication skills than children with pFAS. On executive functioning, the FAS group of children performed significantly worse on sequencing and shift than either the pFAS or ARND groups. Children with pFAS and ARND were similar in all neurodevelopmental domains that were tested. The children who met tightly defined physical criteria for a diagnosis of FAS demonstrated significantly poorer neurodevelopmental functioning than children with pFAS and ARND. Children in these latter 2 groups were similar in all neurodevelopmental domains that were tested.

Multivariate analysis of volatile compounds detected by headspace solid-phase microextraction/gas chromatography: A tool for sensory classification of cork stoppers.

PubMed

Prat, Chantal; Besalú, Emili; Bañeras, Lluís; Anticó, Enriqueta

2011-06-15

The volatile fraction of aqueous cork macerates of tainted and non-tainted agglomerate cork stoppers was analysed by headspace solid-phase microextraction (HS-SPME)/gas chromatography. Twenty compounds containing terpenoids, aliphatic alcohols, lignin-related compounds and others were selected and analysed in individual corks. Cork stoppers were previously classified in six different classes according to sensory descriptions including, 2,4,6-trichloroanisole taint and other frequent, non-characteristic odours found in cork. A multivariate analysis of the chromatographic data of 20 selected chemical compounds using linear discriminant analysis models helped in the differentiation of the a priori made groups. The discriminant model selected five compounds as the best combination. Selected compounds appear in the model in the following order; 2,4,6 TCA, fenchyl alcohol, 1-octen-3-ol, benzyl alcohol and benzothiazole. Unfortunately, not all six a priori differentiated sensory classes were clearly discriminated in the model, probably indicating that no measurable differences exist in the chromatographic data for some categories. The predictive analyses of a refined model in which two sensory classes were fused together resulted in a good classification. Prediction rates of control (non-tainted), TCA, musty-earthy-vegetative, vegetative and chemical descriptions were 100%, 100%, 85%, 67.3% and 100%, respectively, when the modified model was used. The multivariate analysis of chromatographic data will help in the classification of stoppers and provide a perfect complement to sensory analyses. Copyright © 2010 Elsevier Ltd. All rights reserved.

Exploring Geographical Differentiation of the Hoelen Medicinal Mushroom, Wolfiporia extensa (Agaricomycetes), Using Fourier-Transform Infrared Spectroscopy Combined with Multivariate Analysis.

PubMed

Li, Yan; Zhang, Ji; Zhao, Yanli; Liu, Honggao; Wang, Yuanzhong; Jin, Hang

2016-01-01

In this study the geographical differentiation of dried sclerotia of the medicinal mushroom Wolfiporia extensa, obtained from different regions in Yunnan Province, China, was explored using Fourier-transform infrared (FT-IR) spectroscopy coupled with multivariate data analysis. The FT-IR spectra of 97 samples were obtained for wave numbers ranging from 4000 to 400 cm-1. Then, the fingerprint region of 1800-600 cm-1 of the FT-IR spectrum, rather than the full spectrum, was analyzed. Different pretreatments were applied on the spectra, and a discriminant analysis model based on the Mahalanobis distance was developed to select an optimal pretreatment combination. Two unsupervised pattern recognition procedures- principal component analysis and hierarchical cluster analysis-were applied to enhance the authenticity of discrimination of the specimens. The results showed that excellent classification could be obtained after optimizing spectral pretreatment. The tested samples were successfully discriminated according to their geographical locations. The chemical properties of dried sclerotia of W. extensa were clearly dependent on the mushroom's geographical origins. Furthermore, an interesting finding implied that the elevations of collection areas may have effects on the chemical components of wild W. extensa sclerotia. Overall, this study highlights the feasibility of FT-IR spectroscopy combined with multivariate data analysis in particular for exploring the distinction of different regional W. extensa sclerotia samples. This research could also serve as a basis for the exploitation and utilization of medicinal mushrooms.

Linking multimetric and multivariate approaches to assess the ecological condition of streams.

PubMed

Collier, Kevin J

2009-10-01

Few attempts have been made to combine multimetric and multivariate analyses for bioassessment despite recognition that an integrated method could yield powerful tools for bioassessment. An approach is described that integrates eight macroinvertebrate community metrics into a Principal Components Analysis to develop a Multivariate Condition Score (MCS) from a calibration dataset of 511 samples. The MCS is compared to an Index of Biotic Integrity (IBI) derived using the same metrics based on the ratio to the reference site mean. Both approaches were highly correlated although the MCS appeared to offer greater potential for discriminating a wider range of impaired conditions. Both the MCS and IBI displayed low temporal variability within reference sites, and were able to distinguish between reference conditions and low levels of catchment modification and local habitat degradation, although neither discriminated among three levels of low impact. Pseudosamples developed to test the response of the metric aggregation approaches to organic enrichment, urban, mining, pastoral and logging stressor scenarios ranked pressures in the same order, but the MCS provided a lower score for the urban scenario and a higher score for the pastoral scenario. The MCS was calculated for an independent test dataset of urban and reference sites, and yielded similar results to the IBI. Although both methods performed comparably, the MCS approach may have some advantages because it removes the subjectivity of assigning thresholds for scoring biological condition, and it appears to discriminate a wider range of degraded conditions.

Space-time patterns in ignimbrite compositions revealed by GIS and R based statistical analysis

NASA Astrophysics Data System (ADS)

Brandmeier, Melanie; Wörner, Gerhard

2017-04-01

GIS-based multivariate statistical and geospatial analysis of a compilation of 890 geochemical and ca. 1,200 geochronological data for 194 mapped ignimbrites from Central Andes documents the compositional and temporal pattern of large volume ignimbrites (so-called "ignimbrite flare-ups") during Neogene times. Rapid advances in computational sciences during the past decade lead to a growing pool of algorithms for multivariate statistics on big datasets with many predictor variables. This study uses the potential of R and ArcGIS and applies cluster (CA) and linear discriminant analysis (LDA) on log-ratio transformed spatial data. CA on major and trace element data allows to group ignimbrites according to their geochemical characteristics into rhyolitic and a dacitic "end-members" and differentiates characteristic trace element signatures with respect to Eu anomaly, depletion of MREEs and variable enrichment in LREE. To highlight these distinct compositional signatures, we applied LDA to selected ignimbrites for which comprehensive data sets were available. The most important predictors for discriminating ignimbrites are La (LREE), Yb (HREE), Eu, Al2O3, K2O, P2O5, MgO, FeOt and TiO2. However, other REEs such as Gd, Pr, Tm, Sm and Er also contribute to the discrimination functions. Significant compositional differences were found between the older (>14 Ma) large-volume plateau-forming ignimbrites in northernmost Chile and southern Peru and the younger (< 10 Ma) Altiplano-Puna-Volcanic-Complex ignimbrites that are of similar volumes. Older ignimbrites are less depleted in HREEs and less radiogenic in Sr isotopes, indicating smaller crustal contributions during evolution in thinner and thermally less evolved crust. These compositional variations indicate a relation to crustal thickening with a "transition" from plagioclase to amphibole and garnet residual mineralogy between 13 to 9 Ma. We correlate compositional and volumetric variations to the N-S passage of the Juan-Fernandéz ridge and crustal shortening and thickening during the past 26 Ma. The value of GIS and multivariate statistics in comparison to traditional geochemical parameters are highlighted working with large datasets with many predictors in a spatial and temporal context. Algorithms implemented in R allow taking advantage of an n-dimensional space and, thus, of subtle compositional differences contained in the data, while space-time patterns can be analyzed easily in GIS.

Machine Learning Classification of Cirrhotic Patients with and without Minimal Hepatic Encephalopathy Based on Regional Homogeneity of Intrinsic Brain Activity.

PubMed

Chen, Qiu-Feng; Chen, Hua-Jun; Liu, Jun; Sun, Tao; Shen, Qun-Tai

2016-01-01

Machine learning-based approaches play an important role in examining functional magnetic resonance imaging (fMRI) data in a multivariate manner and extracting features predictive of group membership. This study was performed to assess the potential for measuring brain intrinsic activity to identify minimal hepatic encephalopathy (MHE) in cirrhotic patients, using the support vector machine (SVM) method. Resting-state fMRI data were acquired in 16 cirrhotic patients with MHE and 19 cirrhotic patients without MHE. The regional homogeneity (ReHo) method was used to investigate the local synchrony of intrinsic brain activity. Psychometric Hepatic Encephalopathy Score (PHES) was used to define MHE condition. SVM-classifier was then applied using leave-one-out cross-validation, to determine the discriminative ReHo-map for MHE. The discrimination map highlights a set of regions, including the prefrontal cortex, anterior cingulate cortex, anterior insular cortex, inferior parietal lobule, precentral and postcentral gyri, superior and medial temporal cortices, and middle and inferior occipital gyri. The optimized discriminative model showed total accuracy of 82.9% and sensitivity of 81.3%. Our results suggested that a combination of the SVM approach and brain intrinsic activity measurement could be helpful for detection of MHE in cirrhotic patients.

Divergence in male cricket song and female preference functions in three allopatric sister species.

PubMed

Hennig, Ralf Matthias; Blankers, Thomas; Gray, David A

2016-05-01

Multivariate female preference functions for male sexual signals have rarely been investigated, especially in a comparative context among sister species. Here we examined male signal and female preference co-variation in three closely related, but allopatric species of Gryllus crickets and quantified male song traits as well as female preferences. We show that males differ conspicuously in either one of two relatively static song traits, carrier frequency or pulse rate; female preference functions for these traits also differed, and would in combination enhance species discrimination. In contrast, the relatively dynamic song traits, chirp rate and chirp duty cycle, show minimal divergence among species and relatively greater conservation of female preference functions. Notably, among species we demonstrate similar mechanistic rules for the integration of pulse and chirp time scales, despite divergence in pulse rate preferences. As these are allopatric taxa, selection for species recognition per se is unlikely. More likely sexual selection combined with conserved properties of preference filters enabled divergent coevolution of male song and female preferences.

The Association Between Perceived Discrimination and Obesity in a Population-Based Multiracial and Multiethnic Adult Sample

PubMed Central

Williams, David R.

2009-01-01

Objectives. We examined whether perceived chronic discrimination was related to excess body fat accumulation in a random, multiethnic, population-based sample of US adults. Methods. We used multivariate multinomial logistic regression and logistic regression analyses to examine the relationship between interpersonal experiences of perceived chronic discrimination and body mass index and high-risk waist circumference. Results. Consistent with other studies, our analyses showed that perceived unfair treatment was associated with increased abdominal obesity. Compared with Irish, Jewish, Polish, and Italian Whites who did not experience perceived chronic discrimination, Irish, Jewish, Polish, and Italian Whites who perceived chronic discrimination were 2 to 6 times more likely to have a high-risk waist circumference. No significant relationship between perceived discrimination and the obesity measures was found among the other Whites, Blacks, or Hispanics. Conclusions. These findings are not completely unsupported. White ethnic groups including Polish, Italians, Jews, and Irish have historically been discriminated against in the United States, and other recent research suggests that they experience higher levels of perceived discrimination than do other Whites and that these experiences adversely affect their health. PMID:18923119

Is Perceived Discrimination in Pregnancy Prospectively Linked to Postpartum Depression? Exploring the Role of Education.

PubMed

Stepanikova, Irena; Kukla, Lubomir

2017-08-01

Objectives The role of perceived discrimination in postpartum depression is largely unknown. We investigate whether perceived discrimination reported in pregnancy contributes to postpartum depression, and whether its impact varies by education level. Methods Prospective data are a part of European Longitudinal Study of Pregnancy and Childhood, the Czech Republic. Surveys were collected in mid-pregnancy and at 6 months after delivery. Depression was measured using Edinburgh Postnatal Depression Scale. Generalized linear models were estimated to test the effects of perceived discrimination on postpartum depression. Results Multivariate models revealed that among women with low education, discrimination in pregnancy was prospectively associated with 2.43 times higher odds of postpartum depression (p < .01), after adjusting for antenatal depression, history of earlier depression, and socio-demographic background. In contrast, perceived discrimination was not linked to postpartum depression among women with high education. Conclusions Perceived discrimination is a risk factor for postpartum depression among women with low education. Screening for discrimination and socio-economic disadvantage during pregnancy could benefit women who are at risk for mental health problems.

The impact of racial discrimination on the health of Australian Indigenous children aged 5-10 years: analysis of national longitudinal data.

PubMed

Shepherd, Carrington C J; Li, Jianghong; Cooper, Matthew N; Hopkins, Katrina D; Farrant, Brad M

2017-07-03

A growing body of literature highlights that racial discrimination has negative impacts on child health, although most studies have been limited to an examination of direct forms of racism using cross-sectional data. We aim to provide further insights on the impact of early exposure to racism on child health using longitudinal data among Indigenous children in Australia and multiple indicators of racial discrimination. We used data on 1239 Indigenous children aged 5-10 years from Waves 1-6 (2008-2013) of Footprints in Time, a longitudinal study of Indigenous children across Australia. We examined associations between three dimensions of carer-reported racial discrimination (measuring the direct experiences of children and vicarious exposure by their primary carer and family) and a range of physical and mental health outcomes. Analysis was conducted using multivariate logistic regression within a multilevel framework. Two-fifths (40%) of primary carers, 45% of families and 14% of Indigenous children aged 5-10 years were reported to have experienced racial discrimination at some point in time, with 28-40% of these experiencing it persistently (reported at multiple time points). Primary carer and child experiences of racial discrimination were each associated with poor child mental health status (high risk of clinically significant emotional or behavioural difficulties), sleep difficulties, obesity and asthma, but not with child general health or injury. Children exposed to persistent vicarious racial discrimination were more likely to have sleep difficulties and asthma in multivariate models than those with a time-limited exposure. The findings indicate that direct and persistent vicarious racial discrimination are detrimental to the physical and mental health of Indigenous children in Australia, and suggest that prolonged and more frequent exposure to racial discrimination that starts in the early lifecourse can impact on multiple domains of health in later life. Tackling and reducing racism should be an integral part of policy and intervention aimed at improving the health of Australian Indigenous children and thereby reducing health disparities between Indigenous and non-Indigenous children.

Multivariate statistical analysis of the hydrogeochemical and isotopic composition of the groundwater resources in northeastern Peloponnesus (Greece).

PubMed

Matiatos, Ioannis; Alexopoulos, Apostolos; Godelitsas, Athanasios

2014-04-01

The present study involves an integration of the hydrogeological, hydrochemical and isotopic (both stable and radiogenic) data of the groundwater samples taken from aquifers occurring in the region of northeastern Peloponnesus. Special emphasis has been given to health-related ions and isotopes in relation to the WHO and USEPA guidelines, to highlight the concentrations of compounds (e.g., As and Ba) exceeding the drinking water thresholds. Multivariate statistical analyses, i.e. two principal component analyses (PCA) and one discriminant analysis (DA), combined with conventional hydrochemical methodologies, were applied, with the aim to interpret the spatial variations in the groundwater quality and to identify the main hydrogeochemical factors and human activities responsible for the high ion concentrations and isotopic content in the groundwater analysed. The first PCA resulted in a three component model, which explained approximately 82% of the total variance of the data sets and enabled the identification of the hydrogeological processes responsible for the isotopic content i.e., δ(18)Ο, tritium and (222)Rn. The second PCA, involving the trace element presence in the water samples, revealed a four component model, which explained approximately 89% of the total variance of the data sets, giving more insight into the geochemical and anthropogenic controls on the groundwater composition (e.g., water-rock interaction, hydrothermal activity and agricultural activities). Using discriminant analysis, a four parameter (δ(18)O, (Ca+Mg)/(HCO3+SO4), EC and Cl) discriminant function concerning the (222)Rn content was derived, which favoured a classification of the samples according to the concentration of (222)Rn as (222)Rn-safe (<11 Bq·L(-1)) and (222)Rn-contaminated (>11 Bq·L(-1)). The selection of radon builds on the fact that this radiogenic isotope has been generally related to increased health risk when consumed. Copyright © 2014 Elsevier B.V. All rights reserved.

Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification

PubMed Central

Li, Yang; Wee, Chong-Yaw; Jie, Biao; Peng, Ziwen

2014-01-01

Brain connectivity network derived from functional magnetic resonance imaging (fMRI) is becoming increasingly prevalent in the researches related to cognitive and perceptual processes. The capability to detect causal or effective connectivity is highly desirable for understanding the cooperative nature of brain network, particularly when the ultimate goal is to obtain good performance of control-patient classification with biological meaningful interpretations. Understanding directed functional interactions between brain regions via brain connectivity network is a challenging task. Since many genetic and biomedical networks are intrinsically sparse, incorporating sparsity property into connectivity modeling can make the derived models more biologically plausible. Accordingly, we propose an effective connectivity modeling of resting-state fMRI data based on the multivariate autoregressive (MAR) modeling technique, which is widely used to characterize temporal information of dynamic systems. This MAR modeling technique allows for the identification of effective connectivity using the Granger causality concept and reducing the spurious causality connectivity in assessment of directed functional interaction from fMRI data. A forward orthogonal least squares (OLS) regression algorithm is further used to construct a sparse MAR model. By applying the proposed modeling to mild cognitive impairment (MCI) classification, we identify several most discriminative regions, including middle cingulate gyrus, posterior cingulate gyrus, lingual gyrus and caudate regions, in line with results reported in previous findings. A relatively high classification accuracy of 91.89 % is also achieved, with an increment of 5.4 % compared to the fully-connected, non-directional Pearson-correlation-based functional connectivity approach. PMID:24595922

Multivariate class modeling techniques applied to multielement analysis for the verification of the geographical origin of chili pepper.

PubMed

Naccarato, Attilio; Furia, Emilia; Sindona, Giovanni; Tagarelli, Antonio

2016-09-01

Four class-modeling techniques (soft independent modeling of class analogy (SIMCA), unequal dispersed classes (UNEQ), potential functions (PF), and multivariate range modeling (MRM)) were applied to multielement distribution to build chemometric models able to authenticate chili pepper samples grown in Calabria respect to those grown outside of Calabria. The multivariate techniques were applied by considering both all the variables (32 elements, Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Fe, Ga, La, Li, Mg, Mn, Na, Nd, Ni, Pb, Pr, Rb, Sc, Se, Sr, Tl, Tm, V, Y, Yb, Zn) and variables selected by means of stepwise linear discriminant analysis (S-LDA). In the first case, satisfactory and comparable results in terms of CV efficiency are obtained with the use of SIMCA and MRM (82.3 and 83.2% respectively), whereas MRM performs better than SIMCA in terms of forced model efficiency (96.5%). The selection of variables by S-LDA permitted to build models characterized, in general, by a higher efficiency. MRM provided again the best results for CV efficiency (87.7% with an effective balance of sensitivity and specificity) as well as forced model efficiency (96.5%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data

PubMed Central

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-01-01

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. PMID:26921716

Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

Player's success prediction in rugby union: From youth performance to senior level placing.

PubMed

Fontana, Federico Y; Colosio, Alessandro L; Da Lozzo, Giorgio; Pogliaghi, Silvia

2017-04-01

The study questioned if and to what extent specific anthropometric and functional characteristics measured in youth draft camps, can accurately predict subsequent career progression in rugby union. Original research. Anthropometric and functional characteristics of 531 male players (U16) were retrospectively analysed in relation to senior level team representation at age 21-24. Players were classified as International (Int: National team and international clubs) or National (Nat: 1st, 2nd and other divisions and dropout). Multivariate analysis of variance (one-way MANOVA) tested differences between Int and Nat, along a combination of anthropometric (body mass, height, body fat, fat-free mass) and functional variables (SJ, CMJ, t 15m , t 30m , VO 2max ). A discriminant function (DF) was determined to predict group assignment based on the linear combination of variables that best discriminate groups. Correct level assignment was expressed as % hit rate. A combination of anthropometric and functional characteristics reflects future level assignment (Int vs. Nat). Players' success can be accurately predicted (hit rate=81% and 77% for Int and Nat respectively) by a DF that combines anthropometric and functional variables as measured at ∼15 years of age, percent body fat and speed being the most influential predictors of group stratification. Within a group of 15 year-olds with exceptional physical characteristics, future players' success can be predicted using a linear combination of anthropometric and functional variables, among which a lower percent body fat and higher speed over a 15m sprint provide the most important predictors of the highest career success. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Assessment of derelict soil quality: Abiotic, biotic and functional approaches.

PubMed

Vincent, Quentin; Auclerc, Apolline; Beguiristain, Thierry; Leyval, Corinne

2018-02-01

The intensification and subsequent closing down of industrial activities during the last century has left behind large surfaces of derelict lands. Derelict soils have low fertility, can be contaminated, and many of them remain unused. However, with the increasing demand of soil surfaces, they might be considered as a resource, for example for non-food biomass production. The study of their physico-chemical properties and of their biodiversity and biological activity may provide indications for their potential re-use. The objective of our study was to investigate the quality of six derelict soils, considering abiotic, biotic, and functional parameters. We studied (i) the soil bacteria, fungi, meso- and macro-fauna and plant communities of six different derelict soils (two from coking plants, one from a settling pond, two constructed ones made from different substrates and remediated soil, and an inert waste storage one), and (ii) their decomposition function based on the decomposer trophic network, enzyme activities, mineralization activity, and organic pollutant degradation. Biodiversity levels in these soils were high, but all biotic parameters, except the mycorrhizal colonization level, discriminated them. Multivariate analysis showed that biotic parameters co-varied more with fertility proxies than with soil contamination parameters. Similarly, functional parameters significantly co-varied with abiotic parameters. Among functional parameters, macro-decomposer proportion, enzyme activity, average mineralization capacity, and microbial polycyclic aromatic hydrocarbon degraders were useful to discriminate the soils. We assessed their quality by combining abiotic, biotic, and functional parameters: the compost-amended constructed soil displayed the highest quality, while the settling pond soil and the contaminated constructed soil displayed the lowest. Although differences among the soils were highlighted, this study shows that derelict soils may provide a biodiversity ecosystem service and are functional for decomposition. Copyright © 2017 Elsevier B.V. All rights reserved.

Differences in Functional Fitness Among Older Adults With and Without Risk of Falling.

PubMed

Zhao, Yanan; Chung, Pak-Kwong

2016-03-01

This study aimed to identify the differences in functional fitness between older adults who were at risk of falling and those who were not. A total of 104 older adults aged 65-74 years were recruited from a local community senior center. They were independent older adults without a history of falls in the preceding 12 months. Falling risk status was assessed using the Fall Risk Test. Five dimensions of functional fitness with seven testing parameters (i.e., 30-second chair stand test, 30-second arm curl test, 2-minute step test, chair sit and reach test, back scratch test, 8-foot up and go test, and body mass index) were evaluated by the Senior Fitness Test. Only 78 participants completed all the tests, of which 48 participants were identified with risk of falling, and 30 participants were free from risk of falling. Results from multivariate analysis of variance found significant differences on the combined outcome variables, especially in the 8-foot up and go test, 2-minute step test, and 30-second arm curl test. Results from discriminant analysis found a significant discriminant function among all the seven testing parameters, where the 8-foot up and go test, and the 2-minute step test contributed most. Older adults who are at the early stage of risk of falling tend to have lower functional fitness capacities, especially in agility and dynamic balance, aerobic endurance as well as in a combined relationship among all the testing parameters. Copyright © 2016. Published by Elsevier B.V.

[Stigma and discrimination experienced by people living with HIV in Togo, in 2013].

PubMed

Saka, Bayaki; Tchounga, Boris; Ekouevi, Didier K; Sehonou, Céphas; Sewu, Essèboè; Dokla, Augustin; Maboudou, Angèle; Kassankogno, Yao; Palokinam Pitche, Vincent

2017-01-01

Stigma and discrimination experienced by people living with HIV (PLWHA) prevent and delay access to prevention and treatment services. The aim of this study was to describe the patterns of stigma and discrimination experienced by PLWHA in Togo and to identify the associated factors. A cross-sectional study was conducted in 2013 among PLWHA in Togo in order to collect data on stigma or discrimination experiences. Univariate and multivariate analyses were performed to identify associated factors. A total of 891 PLWHA were interviewed, including 848 (95.2%) receiving antiretroviral therapy. External stigma (37.9%) was the major form of stigmatization followed by internalized stigma (35.4%). The main features of external stigma were gossip (36.5%) and issues to access education (36.0%). Internalized stigma mainly consisted of a feeling of guilt (37.6%) and self-devaluation (36.0%). In univariate and multivariate analysis, female gender was significantly associated with stigma (aOR = 1.73, 95% CI [1.08-2.77]). Of the 891 PLWHA, 75 (8.4%) reported a violation of their rights. Finally 27 (4.1%) were discouraged from having children by a health professional because of their HIV status. Stigma affects more than one-third of PLWHA in Togo, more particularly females. It appears necessary to design new interventions and integrate psychosocial care in the management of PLWHA, in addition to antiretroviral therapy.

Evaluation of MELD score and Maddrey discriminant function for mortality prediction in patients with alcoholic hepatitis.

PubMed

Monsanto, Pedro; Almeida, Nuno; Lrias, Clotilde; Pina, Jos Eduardo; Sofia, Carlos

2013-01-01

Maddrey discriminant function (DF) is the traditional model for evaluating the severity and prognosis in alcoholic hepatitis (AH). However, MELD has also been used for this purpose. We aimed to determine the predictive parameters and compare the ability of Maddrey DF and MELD to predict short-term mortality in patients with AH. Retrospective study of 45 patients admitted in our department with AH between 2000 and 2010. Demographic, clinical and laboratory parameters were collected. MELD and Maddrey DF were calculated on admission. Short-term mortality was assessed at 30 and 90 days. Student t-test, χ2 test, univariate analysis, logistic regression and receiver operating characteristic curves were performed. Thirty-day and 90-day mortality was 27% and 42%, respectively. In multivariate analysis, Maddrey DF was the only independent predictor of mortality for these two periods. Receiver operating characteristic curves for Maddrey DF revealed an excellent discriminatory ability to predict 30-day and 90-day mortality for a Maddrey DF greater than 65 and 60, respectively. Discriminatory ability to predict 30-day and 90-day mortality for MELD was low. AH remains associated with a high short-term mortality. Maddrey DF is a more valuable model than MELD to predict short-term mortality in patients with AH.

Multivariate methods to visualise colour-space and colour discrimination data.

PubMed

Hastings, Gareth D; Rubin, Alan

2015-01-01

Despite most modern colour spaces treating colour as three-dimensional (3-D), colour data is usually not visualised in 3-D (and two-dimensional (2-D) projection-plane segments and multiple 2-D perspective views are used instead). The objectives of this article are firstly, to introduce a truly 3-D percept of colour space using stereo-pairs, secondly to view colour discrimination data using that platform, and thirdly to apply formal statistics and multivariate methods to analyse the data in 3-D. This is the first demonstration of the software that generated stereo-pairs of RGB colour space, as well as of a new computerised procedure that investigated colour discrimination by measuring colour just noticeable differences (JND). An initial pilot study and thorough investigation of instrument repeatability were performed. Thereafter, to demonstrate the capabilities of the software, five colour-normal and one colour-deficient subject were examined using the JND procedure and multivariate methods of data analysis. Scatter plots of responses were meaningfully examined in 3-D and were useful in evaluating multivariate normality as well as identifying outliers. The extent and direction of the difference between each JND response and the stimulus colour point was calculated and appreciated in 3-D. Ellipsoidal surfaces of constant probability density (distribution ellipsoids) were fitted to response data; the volumes of these ellipsoids appeared useful in differentiating the colour-deficient subject from the colour-normals. Hypothesis tests of variances and covariances showed many statistically significant differences between the results of the colour-deficient subject and those of the colour-normals, while far fewer differences were found when comparing within colour-normals. The 3-D visualisation of colour data using stereo-pairs, as well as the statistics and multivariate methods of analysis employed, were found to be unique and useful tools in the representation and study of colour. Many additional studies using these methods along with the JND and other procedures have been identified and will be reported in future publications. © 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists.

Perceived age discrimination in older adults

PubMed Central

Rippon, Isla; Kneale, Dylan; de Oliveira, Cesar; Demakakos, Panayotes; Steptoe, Andrew

2014-01-01

Objectives: to examine perceived age discrimination in a large representative sample of older adults in England. Methods: this cross-sectional study of over 7,500 individuals used data from the fifth wave of the English Longitudinal Study of Ageing (ELSA), a longitudinal cohort study of men and women aged 52 years and older in England. Wave 5 asked respondents about the frequency of five everyday discriminatory situations. Participants who attributed any experiences of discrimination to their age were treated as cases of perceived age discrimination. Multivariable logistic regression analysis was used to estimate the odds ratios of experiencing perceived age discrimination in relation to selected sociodemographic factors. Results: approximately a third (33.3%) of all respondents experienced age discrimination, rising to 36.8% in those aged 65 and over. Perceived age discrimination was associated with older age, higher education, lower levels of household wealth and being retired or not in employment. The correlates of age discrimination across the five discriminatory situations were similar. Conclusion: understanding age discrimination is vital if we are to develop appropriate policies and to target future interventions effectively. These findings highlight the scale of the challenge of age discrimination for older adults in England and illustrate that those groups are particularly vulnerable to this form of discrimination. PMID:24077751

The Effects of Discrimination Are Associated With Cigarette Smoking Among Black Males.

PubMed

Parker, Lauren J; Hunte, Haslyn; Ohmit, Anita; Furr-Holden, Debra; Thorpe, Roland J

2017-02-23

Previous research has demonstrated that experiencing interpersonal discrimination is associated with cigarette smoking. Few studies have examined the relationship between the effects of physical and emotional discrimination and cigarette usage, and none have examined this relationship among Black men. The aim of this study was to examine the association between the effects of physical and emotional discrimination and cigarette smoking. Data from the Indiana Black Men's Health Study, a community-based sample of adult Black men, was used to conduct multivariate logistic regression to examine the relationship between the physical and emotional effects of discrimination and smoking, net of healthcare and workplace discrimination, age, education, household income, and being married. After adjusting for having an emotional response to discrimination, health care and workplace discrimination, age, education, household income, and being married, males who had a physical response to discrimination (e.g., upset stomach or headache) had higher odds of cigarette use (odds ratio (OR): 1.95, 95% confidence interval (CI): 1.15-3.30) than men who did not have a physical response to discrimination. Findings from the study suggest that Black males may use cigarette smoking as a means to mitigate the stress associated with experiences of discrimination. Future research is needed further to explore if and how Black males use cigarette smoking to cope with unfair treatment.

Perceived Racial/Ethnic Discrimination Among Fifth-Grade Students and Its Association With Mental Health

PubMed Central

Elliott, Marc N.; Kanouse, David E.; Grunbaum, Jo Anne; Schwebel, David C.; Gilliland, M. Janice; Tortolero, Susan R.; Peskin, Melissa F.; Schuster, Mark A.

2009-01-01

Objectives. We sought to describe the prevalence, characteristics, and mental health problems of children who experience perceived racial/ethnic discrimination. Methods. We analyzed cross-sectional data from a study of 5147 fifth-grade students and their parents from public schools in 3 US metropolitan areas. We used multivariate logistic regression (overall and stratified by race/ethnicity) to examine the associations of sociodemographic factors and mental health problems with perceived racial/ethnic discrimination. Results. Fifteen percent of children reported perceived racial/ethnic discrimination, with 80% reporting that discrimination occurred at school. A greater percentage of Black (20%), Hispanic (15%), and other (16%) children reported perceived racial/ethnic discrimination compared with White (7%) children. Children who reported perceived racial/ethnic discrimination were more likely to have symptoms of each of the 4 mental health conditions included in the analysis: depression, attention deficit hyperactivity disorder, oppositional defiant disorder, and conduct disorder. An association between perceived racial/ethnic discrimination and depressive symptoms was found for Black, Hispanic, and other children but not for White children. Conclusions. Perceived racial/ethnic discrimination is not an uncommon experience among fifth-grade students and may be associated with a variety of mental health disorders. PMID:19299673

Factors Associated with Medical Doctors' Intentions to Discriminate Against Transgender Patients in Kuala Lumpur, Malaysia.

PubMed

Vijay, Aishwarya; Earnshaw, Valerie A; Tee, Ying Chew; Pillai, Veena; White Hughto, Jaclyn M; Clark, Kirsty; Kamarulzaman, Adeeba; Altice, Frederick L; Wickersham, Jeffrey A

2018-01-01

Transgender people are frequent targets of discrimination. Discrimination against transgender people in the context of healthcare can lead to poor health outcomes and facilitate the growth of health disparities. This study explores factors associated with medical doctors' intentions to discriminate against transgender people in Malaysia. A total of 436 physicians at two major university medical centers in Kuala Lumpur, Malaysia, completed an online survey. Sociodemographic characteristics, stigma-related constructs, and intentions to discriminate against transgender people were measured. Bivariate and multivariate linear regression were used to evaluate independent covariates of discrimination intent. Medical doctors who felt more fearful of transgender people and more personal shame associated with transgender people expressed greater intention to discriminate against transgender people, whereas doctors who endorsed the belief that transgender people deserve good care reported lower discrimination intent. Stigma-related constructs accounted for 42% of the variance and 8% was accounted for by sociodemographic characteristics. Constructs associated with transgender stigma play an important role in medical doctors' intentions to discriminate against transgender patients. Development of interventions to improve medical doctors' knowledge about and attitudes toward transgender people are necessary to reduce discriminatory intent in healthcare settings.

Factors Associated with Medical Doctors' Intentions to Discriminate Against Transgender Patients in Kuala Lumpur, Malaysia

PubMed Central

Vijay, Aishwarya; Earnshaw, Valerie A.; Tee, Ying Chew; Pillai, Veena; White Hughto, Jaclyn M.; Clark, Kirsty; Kamarulzaman, Adeeba; Altice, Frederick L.

2018-01-01

Abstract Purpose: Transgender people are frequent targets of discrimination. Discrimination against transgender people in the context of healthcare can lead to poor health outcomes and facilitate the growth of health disparities. This study explores factors associated with medical doctors' intentions to discriminate against transgender people in Malaysia. Methods: A total of 436 physicians at two major university medical centers in Kuala Lumpur, Malaysia, completed an online survey. Sociodemographic characteristics, stigma-related constructs, and intentions to discriminate against transgender people were measured. Bivariate and multivariate linear regression were used to evaluate independent covariates of discrimination intent. Results: Medical doctors who felt more fearful of transgender people and more personal shame associated with transgender people expressed greater intention to discriminate against transgender people, whereas doctors who endorsed the belief that transgender people deserve good care reported lower discrimination intent. Stigma-related constructs accounted for 42% of the variance and 8% was accounted for by sociodemographic characteristics. Conclusions: Constructs associated with transgender stigma play an important role in medical doctors' intentions to discriminate against transgender patients. Development of interventions to improve medical doctors' knowledge about and attitudes toward transgender people are necessary to reduce discriminatory intent in healthcare settings. PMID:29227183

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.

Enhanced attentional gain as a mechanism for generalized perceptual learning in human visual cortex.

PubMed

Byers, Anna; Serences, John T

2014-09-01

Learning to better discriminate a specific visual feature (i.e., a specific orientation in a specific region of space) has been associated with plasticity in early visual areas (sensory modulation) and with improvements in the transmission of sensory information from early visual areas to downstream sensorimotor and decision regions (enhanced readout). However, in many real-world scenarios that require perceptual expertise, observers need to efficiently process numerous exemplars from a broad stimulus class as opposed to just a single stimulus feature. Some previous data suggest that perceptual learning leads to highly specific neural modulations that support the discrimination of specific trained features. However, the extent to which perceptual learning acts to improve the discriminability of a broad class of stimuli via the modulation of sensory responses in human visual cortex remains largely unknown. Here, we used functional MRI and a multivariate analysis method to reconstruct orientation-selective response profiles based on activation patterns in the early visual cortex before and after subjects learned to discriminate small offsets in a set of grating stimuli that were rendered in one of nine possible orientations. Behavioral performance improved across 10 training sessions, and there was a training-related increase in the amplitude of orientation-selective response profiles in V1, V2, and V3 when orientation was task relevant compared with when it was task irrelevant. These results suggest that generalized perceptual learning can lead to modified responses in the early visual cortex in a manner that is suitable for supporting improved discriminability of stimuli drawn from a large set of exemplars. Copyright © 2014 the American Physiological Society.

Linear discriminant analysis of dermoscopic parameters for the differentiation of early melanomas from Clark naevi.

PubMed

Oka, Hiroshi; Tanaka, Masaru; Kobayashi, Seiichiro; Argenziano, Giuseppe; Soyer, H Peter; Nishikawa, Takeji

2004-04-01

As a first step to develop a screening system for pigmented skin lesions, we performed digital discriminant analyses between early melanomas and Clark naevi. A total of 59 cases of melanoma, including 23 melanoma in situ and 36 thin invasive melanomas (Breslow thickness < or =0.75 mm), and 188 clinically equivocal, histopathologically diagnosed Clark naevi were used in our study. After calculating 62 mathematical variables related to the colour, texture, asymmetry and circularity based on the dermoscopic findings of the pigmented skin lesions, we performed multivariate stepwise discriminant analysis using these variables to differentiate melanomas from naevi. The sensitivities and specificities of our model were 94.4 and 98.4%, respectively, for discriminating between melanomas (Breslow thickness < or =0.75 mm) and Clark naevi, and 73.9 and 85.6%, respectively, for discriminating between melanoma in situ and Clark naevi. Our algorithm accurately discriminated invasive melanomas from Clark naevi, but not melanomas in situ from Clark naevi.

The relationship between discrimination and substance use disorders among lesbian, gay, and bisexual adults in the United States.

PubMed

McCabe, Sean Esteban; Bostwick, Wendy B; Hughes, Tonda L; West, Brady T; Boyd, Carol J

2010-10-01

We examined the associations between 3 types of discrimination (sexual orientation, race, and gender) and substance use disorders in a large national sample in the United States that included 577 lesbian, gay, and bisexual (LGB) adults. Data were collected from wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions, which used structured diagnostic face-to-face interviews. More than two thirds of LGB adults reported at least 1 type of discrimination in their lifetimes. Multivariate analyses indicated that the odds of past-year substance use disorders were nearly 4 times greater among LGB adults who reported all 3 types of discrimination prior to the past year than for LGB adults who did not report discrimination (adjusted odds ratio = 3.85; 95% confidence interval = 1.71, 8.66). Health professionals should consider the role multiple types of discrimination plays in the development and treatment of substance use disorders among LGB adults.

Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury

PubMed Central

Wu, Xuehai; Zou, Qihong; Hu, Jin; Tang, Weijun; Mao, Ying; Gao, Liang; Zhu, Jianhong; Jin, Yi; Wu, Xin; Lu, Lu; Zhang, Yaojun; Zhang, Yao; Dai, Zhengjia; Gao, Jia-Hong; Weng, Xuchu; Northoff, Georg; Giacino, Joseph T.; He, Yong

2015-01-01

For accurate diagnosis and prognostic prediction of acquired brain injury (ABI), it is crucial to understand the neurobiological mechanisms underlying loss of consciousness. However, there is no consensus on which regions and networks act as biomarkers for consciousness level and recovery outcome in ABI. Using resting-state fMRI, we assessed intrinsic functional connectivity strength (FCS) of whole-brain networks in a large sample of 99 ABI patients with varying degrees of consciousness loss (including fully preserved consciousness state, minimally conscious state, unresponsive wakefulness syndrome/vegetative state, and coma) and 34 healthy control subjects. Consciousness level was evaluated using the Glasgow Coma Scale and Coma Recovery Scale-Revised on the day of fMRI scanning; recovery outcome was assessed using the Glasgow Outcome Scale 3 months after the fMRI scanning. One-way ANOVA of FCS, Spearman correlation analyses between FCS and the consciousness level and recovery outcome, and FCS-based multivariate pattern analysis were performed. We found decreased FCS with loss of consciousness primarily distributed in the posterior cingulate cortex/precuneus (PCC/PCU), medial prefrontal cortex, and lateral parietal cortex. The FCS values of these regions were significantly correlated with consciousness level and recovery outcome. Multivariate support vector machine discrimination analysis revealed that the FCS patterns predicted whether patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%, and the most discriminative region was the PCC/PCU. These findings suggest that intrinsic functional connectivity patterns of the human posteromedial cortex could serve as a potential indicator for consciousness level and recovery outcome in individuals with ABI. SIGNIFICANCE STATEMENT Varying degrees of consciousness loss and recovery are commonly observed in acquired brain injury patients, yet the underlying neurobiological mechanisms remain elusive. Using a large sample of patients with varying degrees of consciousness loss, we demonstrate that intrinsic functional connectivity strength in many brain regions, especially in the posterior cingulate cortex and precuneus, significantly correlated with consciousness level and recovery outcome. We further demonstrate that the functional connectivity pattern of these regions can predict patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%. Our study thus provides potentially important biomarkers of acquired brain injury in clinical diagnosis, prediction of recovery outcome, and decision making for treatment strategies for patients with severe loss of consciousness. PMID:26377477

Classification of adulterated honeys by multivariate analysis.

PubMed

Amiry, Saber; Esmaiili, Mohsen; Alizadeh, Mohammad

2017-06-01

In this research, honey samples were adulterated with date syrup (DS) and invert sugar syrup (IS) at three concentrations (7%, 15% and 30%). 102 adulterated samples were prepared in six batches with 17 replications for each batch. For each sample, 32 parameters including color indices, rheological, physical, and chemical parameters were determined. To classify the samples, based on type and concentrations of adulterant, a multivariate analysis was applied using principal component analysis (PCA) followed by a linear discriminant analysis (LDA). Then, 21 principal components (PCs) were selected in five sets. Approximately two-thirds were identified correctly using color indices (62.75%) or rheological properties (67.65%). A power discrimination was obtained using physical properties (97.06%), and the best separations were achieved using two sets of chemical properties (set 1: lactone, diastase activity, sucrose - 100%) (set 2: free acidity, HMF, ash - 95%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Neuropsychologic predictors of competency in Alzheimer's disease using a rational reasons legal standard.

PubMed

Marson, D C; Cody, H A; Ingram, K K; Harrell, L E

1995-10-01

To identify neuropsychologic predictors of competency performance and status in Alzheimer's disease (AD) using a specific legal standard (LS). This study is a follow-up to the competency assessment research reported in this issue of the archives. Univariate and multivariate analyses of independent neuropsychologic test measures with a dependent measure of competency to consent to treatment. University medical center. Fifteen normal older control subjects and 29 patients with probable AD. Subjects were administered a battery of neuropsychologic measures theoretically linked to competency function, as well as two clinical vignettes testing their capacity to consent to medical treatment under five different LSs. The present study focused on one specific LS: the capacity to provide "rational reasons" for a treatment choice (LS4). Neuropsychologic test scores were correlated with scores on LS4 for the normal control group and the AD group. The resulting univariate predictors were then analyzed using stepwise regression and discriminant function to identify the key multivariate predictors of competency performance and status under LS4. Measures of word fluency predicted the LS4 scores of controls (R2 = .33) and the AD group (R2 = .36). A word fluency measure also emerged as the best single predictor of competency status for the full subject sample (n = 44), correctly classifying 82% of cases. Dementia severity (Mini-Mental State Examination score) did not emerge as a multivariate predictor of competency performance or status. Interestingly, measures of verbal reasoning and memory were not strongly associated with LS4. Word fluency measures predicted the normative performance and intact competency status of older control subjects and the declining performance and compromised competency status of patients with AD on a "rational reasons" standard of competency to consent to treatment. Cognitive capacities related to frontal lobe function appear to underlie the capacity to formulate rational reasons for a treatment choice. Neuropsychologic studies of competency function have important theoretical and clinical value.

Discrimination and distress among Afghan refugees in northern California: The moderating role of pre- and post-migration factors

PubMed Central

2018-01-01

This study investigates the effect of perceived discrimination on the mental health of Afghan refugees, and secondly, tests the distress moderating effects of pre-migration traumatic experiences and post-resettlement adjustment factors. In a cross-sectional design, 259 Afghans completed surveys assessing perceived discrimination and a number of other factors using scales developed through inductive techniques. Multivariable analyses consisted of a series of hierarchical regressions testing the effect of perceived discrimination on distress, followed by a sequential analysis of moderator variables. Perceived discrimination was significantly associated with higher distress, and this relationship was stronger among those with a strong intra-ethnic identity and high pre-resettlement traumatic experiences. The expected buffering effects of civic engagement, ethnic orientation (e.g. integration), and social support were not significant. Discrimination is a significant source of stress for Afghan refugees, which may exacerbate stresses associated with other pre- and post-migration stressors. Future research is needed to tailor interventions that can help mitigate the stress associated with discrimination among this highly vulnerable group. PMID:29782531

Combination of laser-induced breakdown spectroscopy and Raman spectroscopy for multivariate classification of bacteria

NASA Astrophysics Data System (ADS)

Prochazka, D.; Mazura, M.; Samek, O.; Rebrošová, K.; Pořízka, P.; Klus, J.; Prochazková, P.; Novotný, J.; Novotný, K.; Kaiser, J.

2018-01-01

In this work, we investigate the impact of data provided by complementary laser-based spectroscopic methods on multivariate classification accuracy. Discrimination and classification of five Staphylococcus bacterial strains and one strain of Escherichia coli is presented. The technique that we used for measurements is a combination of Raman spectroscopy and Laser-Induced Breakdown Spectroscopy (LIBS). Obtained spectroscopic data were then processed using Multivariate Data Analysis algorithms. Principal Components Analysis (PCA) was selected as the most suitable technique for visualization of bacterial strains data. To classify the bacterial strains, we used Neural Networks, namely a supervised version of Kohonen's self-organizing maps (SOM). We were processing results in three different ways - separately from LIBS measurements, from Raman measurements, and we also merged data from both mentioned methods. The three types of results were then compared. By applying the PCA to Raman spectroscopy data, we observed that two bacterial strains were fully distinguished from the rest of the data set. In the case of LIBS data, three bacterial strains were fully discriminated. Using a combination of data from both methods, we achieved the complete discrimination of all bacterial strains. All the data were classified with a high success rate using SOM algorithm. The most accurate classification was obtained using a combination of data from both techniques. The classification accuracy varied, depending on specific samples and techniques. As for LIBS, the classification accuracy ranged from 45% to 100%, as for Raman Spectroscopy from 50% to 100% and in case of merged data, all samples were classified correctly. Based on the results of the experiments presented in this work, we can assume that the combination of Raman spectroscopy and LIBS significantly enhances discrimination and classification accuracy of bacterial species and strains. The reason is the complementarity in obtained chemical information while using these two methods.

Using sperm morphometry and multivariate analysis to differentiate species of gray Mazama

PubMed Central

Duarte, José Maurício Barbanti

2016-01-01

There is genetic evidence that the two species of Brazilian gray Mazama, Mazama gouazoubira and Mazama nemorivaga, belong to different genera. This study identified significant differences that separated them into distinct groups, based on characteristics of the spermatozoa and ejaculate of both species. The characteristics that most clearly differentiated between the species were ejaculate colour, white for M. gouazoubira and reddish for M. nemorivaga, and sperm head dimensions. Multivariate analysis of sperm head dimension and format data accurately discriminated three groups for species with total percentage of misclassified of 0.71. The individual analysis, by animal, and the multivariate analysis have also discriminated correctly all five animals (total percentage of misclassified of 13.95%), and the canonical plot has shown three different clusters: Cluster 1, including individuals of M. nemorivaga; Cluster 2, including two individuals of M. gouazoubira; and Cluster 3, including a single individual of M. gouazoubira. The results obtained in this work corroborate the hypothesis of the formation of new genera and species for gray Mazama. Moreover, the easily applied method described herein can be used as an auxiliary tool to identify sibling species of other taxonomic groups. PMID:28018612

The intersectionality of discrimination attributes and bullying among youth: an applied latent class analysis.

PubMed

Garnett, Bernice Raveche; Masyn, Katherine E; Austin, S Bryn; Miller, Matthew; Williams, David R; Viswanath, Kasisomayajula

2014-08-01

Discrimination is commonly experienced among adolescents. However, little is known about the intersection of multiple attributes of discrimination and bullying. We used a latent class analysis (LCA) to illustrate the intersections of discrimination attributes and bullying, and to assess the associations of LCA membership to depressive symptoms, deliberate self harm and suicidal ideation among a sample of ethnically diverse adolescents. The data come from the 2006 Boston Youth Survey where students were asked whether they had experienced discrimination based on four attributes: race/ethnicity, immigration status, perceived sexual orientation and weight. They were also asked whether they had been bullied or assaulted for these attributes. A total of 965 (78%) students contributed to the LCA analytic sample (45% Non-Hispanic Black, 29% Hispanic, 58% Female). The LCA revealed that a 4-class solution had adequate relative and absolute fit. The 4-classes were characterized as: low discrimination (51%); racial discrimination (33%); sexual orientation discrimination (7%); racial and weight discrimination with high bullying (intersectional class) (7%). In multivariate models, compared to the low discrimination class, individuals in the sexual orientation discrimination class and the intersectional class had higher odds of engaging in deliberate self-harm. Students in the intersectional class also had higher odds of suicidal ideation. All three discrimination latent classes had significantly higher depressive symptoms compared to the low discrimination class. Multiple attributes of discrimination and bullying co-occur among adolescents. Research should consider the co-occurrence of bullying and discrimination.

Spermiogram and sperm head morphometry assessed by multivariate cluster analysis results during adolescence (12-18 years) and the effect of varicocele

PubMed Central

Vásquez, Fernando; Soler, Carles; Camps, Patricia; Valverde, Anthony; García-Molina, Almudena

2016-01-01

This work evaluates sperm head morphometric characteristics in adolescents from 12 to 18 years of age, and the effect of varicocele. Volunteers between 150 and 224 months of age (mean 191, n = 87), who had reached oigarche by 12 years old, were recruited in the area of Barranquilla, Colombia. Morphometric analysis of sperm heads was performed with principal component (PC) and discriminant analysis. Combining seminal fluid and sperm parameters provided five PCs: two related to sperm morphometry, one to sperm motility, and two to seminal fluid components. Discriminant analysis on the morphometric results of varicocele and nonvaricocele groups did not provide a useful classification matrix. Of the semen-related PCs, the most explanatory (40%) was related to sperm motility. Two PCs, including sperm head elongation and size, were sufficient to evaluate sperm morphometric characteristics. Most of the morphometric variables were correlated with age, with an increase in size and decrease in the elongation of the sperm head. For head size, the entire sperm population could be divided into two morphometric subpopulations, SP1 and SP2, which did not change during adolescence. In general, for varicocele individuals, SP1 had larger and more elongated sperm heads than SP2, which had smaller and more elongated heads than in nonvaricocele men. In summary, sperm head morphometry assessed by CASA-Morph and multivariate cluster analysis provides a better comprehension of the ejaculate structure and possibly sperm function. Morphometric analysis provides much more information than data obtained from conventional semen analysis. PMID:27751986

Risk factors, sequential organ failure assessment and model for end-stage liver disease scores for predicting short term mortality in cirrhotic patients admitted to intensive care unit.

PubMed

Cholongitas, E; Senzolo, M; Patch, D; Kwong, K; Nikolopoulou, V; Leandro, G; Shaw, S; Burroughs, A K

2006-04-01

Prognostic scores in an intensive care unit (ICU) evaluate outcomes, but derive from cohorts containing few cirrhotic patients. To evaluate 6-week mortality in cirrhotic patients admitted to an ICU, and to compare general and liver-specific prognostic scores. A total of 312 consecutive cirrhotic patients (65% alcoholic; mean age 49.6 years). Multivariable logistic regression to evaluate admission factors associated with survival. Child-Pugh, Model for End-stage Liver Disease (MELD), Acute Physiology and Chronic Health Evaluation (APACHE) II and Sequential Organ Failure Assessment (SOFA) scores were compared by receiver operating characteristic curves. Major indication for admission was respiratory failure (35.6%). Median (range) Child-Pugh, APACHE II, MELD and SOFA scores were 11 (5-15), 18 (0-44), 24 (6-40) and 11 (0-21), respectively; 65% (n = 203) died. Survival improved over time (P = 0.005). Multivariate model factors: more organs failing (FOS) (<3 = 49.5%, > or =3 = 90%), higher FiO(2), lactate, urea and bilirubin; resulting in good discrimination [area under receiver operating characteristic curve (AUC) = 0.83], similar to SOFA and MELD (AUC = 0.83 and 0.81, respectively) and superior to APACHE II and Child-Pugh (AUC = 0.78 and 0.72, respectively). Cirrhotics admitted to ICU with > or =3 failing organ systems have 90% mortality. The Royal Free model discriminated well and contained key variables of organ function. SOFA and MELD were better predictors than APACHE II or Child-Pugh scores.

Temporal processing impairment in children with attention-deficit-hyperactivity disorder.

PubMed

Huang, Jia; Yang, Bin-rang; Zou, Xiao-bing; Jing, Jin; Pen, Gang; McAlonan, Gráinne M; Chan, Raymond C K

2012-01-01

The current study aimed to investigate temporal processing in Chinese children with Attention-Deficit-Hyperactivity Disorder(ADHD) using time production, time reproduction paradigm and duration discrimination tasks. A battery of tests specifically designed to measure temporal processing was administered to 94 children with ADHD and 100 demographically matched healthy children. A multivariate analysis of variance (MANOVA) and a repeated measure MANOVA indicated that children with ADHD were impaired in time processing functions. The results of pairwise comparisons showed that the probands with a family history of ADHD performed significantly worse than those without family history in the time production tasks and the time reproduction task. Logistic regression analysis showed duration discrimination had a significant role in predicting whether the children were suffering from ADHD or not, while temporal processing had a significant role in predicting whether the ADHD children had a family history or not. This study provides further support for the existence of a generic temporal processing impairment in ADHD children and suggests that abnormalities in time processing and ADHD share some common genetic factors. Copyright © 2011 Elsevier Ltd. All rights reserved.

Identifying contextual influences of community reintegration among injured servicemembers.

PubMed

Hawkins, Brent L; McGuire, Francis A; Britt, Thomas W; Linder, Sandra M

2015-01-01

Research suggests that community reintegration (CR) after injury and rehabilitation is difficult for many injured servicemembers. However, little is known about the influence of the contextual factors, both personal and environmental, that influence CR. Framed within the International Classification of Functioning, Disability and Health and Social Cognitive Theory, the quantitative portion of a larger mixed-methods study of 51 injured, community-dwelling servicemembers compared the relative contribution of contextual factors between groups of servicemembers with different levels of CR. Cluster analysis indicated three groups of servicemembers showing low, moderate, and high levels of CR. Statistical analyses identified contextual factors (e.g., personal and environmental factors) that significantly discriminated between CR clusters. Multivariate analysis of variance and discriminant analysis indicated significant contributions of general self-efficacy, services and assistance barriers, physical and structural barriers, attitudes and support barriers, perceived level of disability and/or handicap, work and school barriers, and policy barriers on CR scores. Overall, analyses indicated that injured servicemembers with lower CR scores had lower general self-efficacy scores, reported more difficulty with environmental barriers, and reported their injuries as more disabling.

Temporal Lobe and “Default” Hemodynamic Brain Modes Discriminate Between Schizophrenia and Bipolar Disorder

PubMed Central

Calhoun, Vince D.; Maciejewski, Paul K.; Pearlson, Godfrey D.; Kiehl, Kent A.

2009-01-01

Schizophrenia and bipolar disorder are currently diagnosed on the basis of psychiatric symptoms and longitudinal course. The determination of a reliable, biologically-based diagnostic indicator of these diseases (a biomarker) could provide the groundwork for developing more rigorous tools for differential diagnosis and treatment assignment. Recently, methods have been used to identify distinct sets of brain regions or “spatial modes” exhibiting temporally coherent brain activity. Using functional magnetic resonance imaging (fMRI) data and a multivariate analysis method, independent component analysis, we combined the temporal lobe and the default modes to discriminate subjects with bipolar disorder, chronic schizophrenia, and healthy controls. Temporal lobe and default mode networks were reliably identified in all participants. Classification results on an independent set of individuals revealed an average sensitivity and specificity of 90 and 95%, respectively. The use of coherent brain networks such as the temporal lobe and default mode networks may provide a more reliable measure of disease state than task-correlated fMRI activity. A combination of two such hemodynamic brain networks shows promise as a biomarker for schizophrenia and bipolar disorder. PMID:17894392

Temporal lobe and "default" hemodynamic brain modes discriminate between schizophrenia and bipolar disorder.

PubMed

Calhoun, Vince D; Maciejewski, Paul K; Pearlson, Godfrey D; Kiehl, Kent A

2008-11-01

Schizophrenia and bipolar disorder are currently diagnosed on the basis of psychiatric symptoms and longitudinal course. The determination of a reliable, biologically-based diagnostic indicator of these diseases (a biomarker) could provide the groundwork for developing more rigorous tools for differential diagnosis and treatment assignment. Recently, methods have been used to identify distinct sets of brain regions or "spatial modes" exhibiting temporally coherent brain activity. Using functional magnetic resonance imaging (fMRI) data and a multivariate analysis method, independent component analysis, we combined the temporal lobe and the default modes to discriminate subjects with bipolar disorder, chronic schizophrenia, and healthy controls. Temporal lobe and default mode networks were reliably identified in all participants. Classification results on an independent set of individuals revealed an average sensitivity and specificity of 90 and 95%, respectively. The use of coherent brain networks such as the temporal lobe and default mode networks may provide a more reliable measure of disease state than task-correlated fMRI activity. A combination of two such hemodynamic brain networks shows promise as a biomarker for schizophrenia and bipolar disorder.

Towards exaggerated emphysema stereotypes

NASA Astrophysics Data System (ADS)

Chen, C.; Sørensen, L.; Lauze, F.; Igel, C.; Loog, M.; Feragen, A.; de Bruijne, M.; Nielsen, M.

2012-03-01

Classification is widely used in the context of medical image analysis and in order to illustrate the mechanism of a classifier, we introduce the notion of an exaggerated image stereotype based on training data and trained classifier. The stereotype of some image class of interest should emphasize/exaggerate the characteristic patterns in an image class and visualize the information the employed classifier relies on. This is useful for gaining insight into the classification and serves for comparison with the biological models of disease. In this work, we build exaggerated image stereotypes by optimizing an objective function which consists of a discriminative term based on the classification accuracy, and a generative term based on the class distributions. A gradient descent method based on iterated conditional modes (ICM) is employed for optimization. We use this idea with Fisher's linear discriminant rule and assume a multivariate normal distribution for samples within a class. The proposed framework is applied to computed tomography (CT) images of lung tissue with emphysema. The synthesized stereotypes illustrate the exaggerated patterns of lung tissue with emphysema, which is underpinned by three different quantitative evaluation methods.

LANDSCAPE METRICS THAT ARE USEFUL FOR EXPLAINING ESTUARINE ECOLOGICAL RESPONSES

EPA Science Inventory

We investigated whether land use/cover characteristics of watersheds associated with estuaries exhibit a strong enough signal to make landscape metrics useful for predicting estuarine ecological condition. We used multivariate logistic regression models to discriminate between su...

A model for incomplete longitudinal multivariate ordinal data.

PubMed

Liu, Li C

2008-12-30

In studies where multiple outcome items are repeatedly measured over time, missing data often occur. A longitudinal item response theory model is proposed for analysis of multivariate ordinal outcomes that are repeatedly measured. Under the MAR assumption, this model accommodates missing data at any level (missing item at any time point and/or missing time point). It allows for multiple random subject effects and the estimation of item discrimination parameters for the multiple outcome items. The covariates in the model can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is described utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher-scoring solution, which provides standard errors for all model parameters, is used. A data set from a longitudinal prevention study is used to motivate the application of the proposed model. In this study, multiple ordinal items of health behavior are repeatedly measured over time. Because of a planned missing design, subjects answered only two-third of all items at a given point. Copyright 2008 John Wiley & Sons, Ltd.

Foreign-Born Latinos Living in Rural Areas are more likely to Experience Health Care Discrimination: Results from Proyecto de Salud para Latinos.

PubMed

López-Cevallos, Daniel F; Harvey, S Marie

2016-08-01

Health care discrimination is increasingly considered a significant barrier to accessing health services among minority populations, including Latinos. However, little is known about the role of immigration status. The purpose of this study was to examine the association between immigration status and perceived health care discrimination among Latinos living in rural areas. Interviews were conducted among 349 young-adult Latinos (ages 18 to 25) living in rural Oregon, as part of Proyecto de Salud para Latinos. Over a third of participants experienced health care discrimination (39.5 %). Discrimination was higher among foreign-born (44.9 %) rather than US-born Latinos (31.9 %). Multivariate results showed that foreign-born Latinos were significantly more likely to experience health care discrimination, even after controlling for other relevant factors (OR = 2.10, 95 % CI 1.16-3.82). This study provides evidence that health care discrimination is prevalent among young-adult Latinos living in rural areas, particularly the foreign-born. Effective approaches towards reducing discrimination in health care settings should take into consideration the need to reform our broken immigration system.

Somatosensory Representations Link the Perception of Emotional Expressions and Sensory Experience.

PubMed

Kragel, Philip A; LaBar, Kevin S

2016-01-01

Studies of human emotion perception have linked a distributed set of brain regions to the recognition of emotion in facial, vocal, and body expressions. In particular, lesions to somatosensory cortex in the right hemisphere have been shown to impair recognition of facial and vocal expressions of emotion. Although these findings suggest that somatosensory cortex represents body states associated with distinct emotions, such as a furrowed brow or gaping jaw, functional evidence directly linking somatosensory activity and subjective experience during emotion perception is critically lacking. Using functional magnetic resonance imaging and multivariate decoding techniques, we show that perceiving vocal and facial expressions of emotion yields hemodynamic activity in right somatosensory cortex that discriminates among emotion categories, exhibits somatotopic organization, and tracks self-reported sensory experience. The findings both support embodied accounts of emotion and provide mechanistic insight into how emotional expressions are capable of biasing subjective experience in those who perceive them.

What is the role of impression management in adolescent cigarette smoking?

PubMed

O'Callaghan, F; Doyle, J

2001-01-01

This study examined the role of impression management in cigarette smoking by linking the constructs of self-monitoring, perceived success in impression management, self-esteem and social anxiety among nonsmokers (NS), occasional smokers (OS), and frequent smokers (FS). High school students (N=243) in years 8-12 completed a questionnaire assessing the above-mentioned variables. Multivariate discriminant function analysis and a priori contrasts were used to analyze the data. In comparison to OS, FS and NS had the lowest levels of self-monitoring, perceived success in impression management and self-esteem, while having the highest levels of social anxiety. Cigarette use may serve an impression management function during adolescence and subsequently influences OS' level of smoking. Intervention programs need to give greater consideration to providing adolescents with alternative strategies for both social acceptance and the acquisition and maintenance of self-esteem.

Somatosensory Representations Link the Perception of Emotional Expressions and Sensory Experience123

PubMed Central

2016-01-01

Abstract Studies of human emotion perception have linked a distributed set of brain regions to the recognition of emotion in facial, vocal, and body expressions. In particular, lesions to somatosensory cortex in the right hemisphere have been shown to impair recognition of facial and vocal expressions of emotion. Although these findings suggest that somatosensory cortex represents body states associated with distinct emotions, such as a furrowed brow or gaping jaw, functional evidence directly linking somatosensory activity and subjective experience during emotion perception is critically lacking. Using functional magnetic resonance imaging and multivariate decoding techniques, we show that perceiving vocal and facial expressions of emotion yields hemodynamic activity in right somatosensory cortex that discriminates among emotion categories, exhibits somatotopic organization, and tracks self-reported sensory experience. The findings both support embodied accounts of emotion and provide mechanistic insight into how emotional expressions are capable of biasing subjective experience in those who perceive them. PMID:27280154

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

Psychosocial functioning and stress-processing of children with asthma in the school context: differences and similarities with children without asthma.

PubMed

Röder, Irma; Kroonenberg, Pieter M; Boekaerts, Monique

2003-01-01

To characterize children with asthma by their stress processing at school and their psychosocial functioning. To establish similarities and differences between children with and without asthma. Participants were 79 children with asthma and 359 children without asthma (ages 8-12). Children completed questionnaires on stress processing and their well-being at school. Parents filled in a questionnaire on behavior problems, and teachers provided data on school performance and absence rate. Children with asthma had higher scores on absence rates, teacher-rated well-being, internalizing behavior problems, occurrence of "rejection by peers," and use of aggression when coping with "problems with school work." However, using discriminant analyses, the groups could not reliably be distinguished from one another by these variables. Children with asthma are similar to other children with regard to their stress processing at school and their psychosocial functioning. The value of conducting multivariate analysis over several univariate tests is underscored.

Perceived Discrimination, Psychological Distress, and Current Smoking Status: Results From the Behavioral Risk Factor Surveillance System Reactions to Race Module, 2004–2008

PubMed Central

Peppone, Luke J.; Alcaraz, Kassandra; McQueen, Amy; Guido, Joseph J.; Carroll, Jennifer K.; Shacham, Enbal; Morrow, Gary R.

2012-01-01

Objectives. We examined the association between perceived discrimination and smoking status and whether psychological distress mediated this relationship in a large, multiethnic sample. Methods. We used 2004 through 2008 data from the Behavioral Risk Factor Surveillance System Reactions to Race module to conduct multivariate logistic regression analyses and tests of mediation examining associations between perceived discrimination in health care and workplace settings, psychological distress, and current smoking status. Results. Regardless of race/ethnicity, perceived discrimination was associated with increased odds of current smoking. Psychological distress was also a significant mediator of the discrimination–smoking association. Conclusions. Our results indicate that individuals who report discriminatory treatment in multiple domains may be more likely to smoke, in part, because of the psychological distress associated with such treatment. PMID:22420821

Discriminatory experiences associated with posttraumatic stress disorder symptoms among transgender adults

PubMed Central

Reisner, Sari L.; White Hughto, Jaclyn M.; Gamarel, Kristi E.; Keuroghlian, Alex S.; Mizock, Lauren; Pachankis, John

2016-01-01

Discrimination has been shown to disproportionately burden transgender people; however, there has been a lack of clinical attention to the mental health sequelae of discrimination, including posttraumatic stress disorder (PTSD) symptoms. Additionally, few studies contextualize discrimination alongside other traumatic stressors in predicting PTSD symptomatology. The current study sought to fill these gaps. A community-based sample of 412 transgender adults (mean age 33, SD=13; 63% female-to-male spectrum; 19% people of color; 88% sampled online) completed a cross-sectional self-report survey of everyday discrimination experiences and PTSD symptoms. Multivariable linear regression models examined the association between self-reported everyday discrimination experiences, number of attributed domains of discrimination, and PTSD symptoms, adjusting for prior trauma, sociodemographics, and psychosocial co-morbidity. The mean number of discrimination attributions endorsed was 4.8 (SD=2.4) and the five most frequently reported reasons for discrimination were: gender identity and/or expression (83%), masculine and feminine appearance (79%), sexual orientation (68%), sex (57%), and age (44%). Higher everyday discrimination scores (β=0.25; 95% CL=0.21–0.30) and greater number of attributed reasons for discrimination experiences (β=0.05; 95% CL=0.01–0.10) were independently associated with PTSD symptoms, even after adjusting for prior trauma experiences. Everyday discrimination experiences from multiple sources necessitate clinical consideration in treatment for PTSD symptoms in transgender people. PMID:26866637

Discriminatory experiences associated with posttraumatic stress disorder symptoms among transgender adults.

PubMed

Reisner, Sari L; White Hughto, Jaclyn M; Gamarel, Kristi E; Keuroghlian, Alex S; Mizock, Lauren; Pachankis, John E

2016-10-01

Discrimination has been shown to disproportionately burden transgender people; however, there has been a lack of clinical attention to the mental health sequelae of discrimination, including posttraumatic stress disorder (PTSD) symptoms. Additionally, few studies contextualize discrimination alongside other traumatic stressors in predicting PTSD symptomatology. The current study sought to fill these gaps. A community-based sample of 412 transgender adults (mean age 33, SD = 13; 63% female-to-male spectrum; 19% people of color; 88% sampled online) completed a cross-sectional self-report survey of everyday discrimination experiences and PTSD symptoms. Multivariable linear regression models examined the association between self-reported everyday discrimination experiences, number of attributed domains of discrimination, and PTSD symptoms, adjusting for prior trauma, sociodemographics, and psychosocial comorbidity. The mean number of discrimination attributions endorsed was 4.8 (SD = 2.4) and the 5 most frequently reported reasons for discrimination were: gender identity and/or expression (83%), masculine and feminine appearance (79%), sexual orientation (68%), sex (57%), and age (44%). Higher everyday discrimination scores (β = 0.25; 95% CL [0.21, 0.30]) and greater number of attributed reasons for discrimination experiences (β = 0.05; 95% CL [0.01, 0.10]) were independently associated with PTSD symptoms, even after adjusting for prior trauma experiences. Everyday discrimination experiences from multiple sources necessitate clinical consideration in treatment for PTSD symptoms in transgender people. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Relationships between Participants' International Prostate Symptom Score and BPH Impact Index Changes and Global Ratings of Change in a Trial of Phytotherapy for Men with Lower Urinary Tract Symptoms

PubMed Central

Barry, Michael J.; Cantor, Alan; Roehrborn, Claus G.

2014-01-01

Purpose To relate changes in AUA Symptom Index (AUASI) scores with bother measures and global ratings of change among men with lower urinary tract symptoms enrolled in a trial of saw palmetto. Materials and Methods To be eligible, men were ≥45 years old, had ajpeak uroflow ≥4 ml/sec, and an AUASI score ≥ 8 and ≤ 24. Participants self-administered the AUASI, IPSS quality of life item (IPSS QoL), BPH Impact Index (BII) and two global change questions at baseline and 24, 48, and 72 weeks. Results Among 357 participants, global ratings of “a little better” were associated with mean decreases in AUASI scores from 2.8 to 4.1 points, across three time points. The analogous range for mean decreases in BII scores was 1.0 to 1.7 points, and for the IPSS QoL item 0.5 to 0.8 points. At 72 weeks, for the first global change question, each change measure could discriminate between participants rating themselves at least a little better versus unchanged or worse 70-72% of the time. A multivariable model increased discrimination to 77%. For the second global change question, each change measure correctly discriminated ratings of at least a little better versus unchanged or worse 69-74% of the time, and a multivariable model increased discrimination to 79%. Conclusions Changes in AUASI scores could discriminate between participants rating themselves at least a little better versus unchanged or worse. Our findings support the practice of powering studies to detect group mean differences in AUASI scores of at least 3 points. PMID:23017510

Clinical and Radiological Discrimination of Solitary Pulmonary Lesions in Colorectal Cancer Patients.

PubMed

Ohtaki, Yoichi; Shimizu, Kimihiro; Nagashima, Toshiteru; Nakazawa, Seshiru; Obayashi, Kai; Azuma, Yoko; Iijima, Misaki; Kosaka, Takayuki; Yajima, Toshiki; Ogawa, Hiroomi; Tsutsumi, Soichi; Arai, Motohiro; Mogi, Akira; Kuwano, Hiroyuki

2018-04-01

The lung is one of the most common organs of metastasis from colorectal cancer (CRC), and we have encountered lung cancer patients with a history of CRC. There have been few studies regarding methods used to discriminate between primary lung cancer (PLC) and pulmonary metastasis from CRC (PM-CRC) based only on preoperative findings. We retrospectively investigated predictive factors discriminating between these lesions in patients with a history of CRC. Between 2006 and 2015, 117 patients with a history of CRC (44 patients with 47 PLC and 73 patients with 102 PM-CRC) underwent subsequent or concurrent resection of pulmonary lesions. We compared the clinical and radiological characteristics of 100 patients with solitary lesions (43 PLC and 57 PM-CRC). Using univariate and multivariate analyses, we examined predictive factors for discrimination of these two lesions. All tumors with findings of ground-glass opacity (GGO) were PLC (n = 19). In a multivariate analysis of 81 radiologically solid tumors, two factors were found to be significant independent predictors of PLC: a history of stage I CRC and presence of pleural indentation. All tumors in 26 patients with either GGO or both a stage I CRC history and pleural indentation were PLC, while most tumors in patients without all three factors were PM-CRC (43/44; 97.7%). The presence or absence of GGO, pathological CRC stage, and pleural indentation could be useful factors to distinguish between PLC and PM-CRC.

Geographically-based discrimination is a social determinant of mental health in a deprived or stigmatized area in Japan: a cross-sectional study.

PubMed

Tabuchi, Takahiro; Fukuhara, Hiroyuki; Iso, Hiroyasu

2012-09-01

Perceived discrimination has been shown to be associated with health. However, it is uncertain whether discrimination based on geographical place of residence (geographically-based discrimination), such as Buraku or Nishinari discrimination in Japan, is associated with health. We conducted a cross-sectional study (response rate = 52.3%) from February to March 2009 in a Buraku district of Nishinari ward in Osaka city, one of the most deprived areas in Japan. We implemented sex-stratified and education-stratified multivariate regression models to examine the association between geographically-based discrimination and two mental health outcomes (depressive symptoms and diagnosis of mental illness) with adjustment for age, socioeconomic status, social relationships and lifestyle factors. A total of 1994 persons aged 25-79 years (928 men and 1066 women) living in the district were analyzed. In the fully-adjusted model, perceived geographically-based discrimination was significantly associated with depressive symptoms and diagnosis of mental illness. It was more strongly associated among men or highly educated people than among women or among less educated people. The effect of geographically-based discrimination on mental health is independent of socioeconomic status, social relationship and lifestyle factors. Geographically-based discrimination may be one of the social determinants of mental health. Copyright © 2012. Published by Elsevier Ltd.

Racial/Ethnic Contrasts in the Relationships between Physical Disability, Perceived Discrimination, and Depressive Symptoms.

PubMed

Kilpatrick, Quentin K; Taylor, John

2018-02-13

The systematic deprivation of equal access to valued opportunities has greatly harmed the disadvantaged. Discrimination, whether it is based on gender, race, sexual orientation, or physical health exacts a high toll. This is especially true with respect to the role of race and equality in the USA today. This paper attempts to evaluate the significance of perceived discrimination among a multiethnic sample of physically disabled and non-disabled study participants. We employ survey data from a community-based multiethnic sample of study participants to assess whether physical disability increases perceptions of discrimination across racial/ethnic groups. Additionally, we assess whether physical disability impacts the relationship between discrimination and depressive symptoms and whether this relationship is consistent across race/ethnicity. Descriptive and multivariate analyses indicate that disabled whites and Hispanics report higher levels of discrimination than their non-disabled counterparts. However, this pattern was not observed among black respondents who report high levels of discrimination regardless of their disability status. OLS models indicate that among Hispanics, physical disability moderates the relationship between discrimination and depressive symptoms. Among black and white study participants, physical disability does not moderate this relationship. Taken together, the results demonstrate the continuing significance of race as a source of discrimination and a health risk.

Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models.

PubMed

Ji, Ruijun; Du, Wanliang; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Zhao, Xingquan; Wang, Yongjun

2014-11-25

Acute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS). The DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score ≤ 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration. A total of 12,026 patients were included and the median age was 67 (interquartile range: 57-75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS ≤ 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001). The DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS.

Rapid discrimination and characterization of vanilla bean extracts by attenuated total reflection infrared spectroscopy and selected ion flow tube mass spectrometry.

PubMed

Sharp, Michael D; Kocaoglu-Vurma, Nurdan A; Langford, Vaughan; Rodriguez-Saona, Luis E; Harper, W James

2012-03-01

Vanilla beans have been shown to contain over 200 compounds, which can vary in concentration depending on the region where the beans are harvested. Several compounds including vanillin, p-hydroxybenzaldehyde, guaiacol, and anise alcohol have been found to be important for the aroma profile of vanilla. Our objective was to evaluate the performance of selected ion flow tube mass spectrometry (SIFT-MS) and Fourier-transform infrared (FTIR) spectroscopy for rapid discrimination and characterization of vanilla bean extracts. Vanilla extracts were obtained from different countries including Uganda, Indonesia, Papua New Guinea, Madagascar, and India. Multivariate data analysis (soft independent modeling of class analogy, SIMCA) was utilized to determine the clustering patterns between samples. Both methods provided differentiation between samples for all vanilla bean extracts. FTIR differentiated on the basis of functional groups, whereas the SIFT-MS method provided more specific information about the chemical basis of the differentiation. SIMCA's discriminating power showed that the most important compounds responsible for the differentiation between samples by SIFT-MS were vanillin, anise alcohol, 4-methylguaiacol, p-hydroxybenzaldehyde/trimethylpyrazine, p-cresol/anisole, guaiacol, isovaleric acid, and acetic acid. ATR-IR spectroscopy analysis showed that the classification of samples was related to major bands at 1523, 1573, 1516, 1292, 1774, 1670, 1608, and 1431 cm(-1) , associated with vanillin and vanillin derivatives. © 2012 Institute of Food Technologists®

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

PubMed

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity

PubMed Central

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others’ facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition. PMID:29615882

An introduction to metabolomics and its potential application in veterinary science.

PubMed

Jones, Oliver A H; Cheung, Victoria L

2007-10-01

Metabolomics has been found to be applicable to a wide range of fields, including the study of gene function, toxicology, plant sciences, environmental analysis, clinical diagnostics, nutrition, and the discrimination of organism genotypes. This approach combines high-throughput sample analysis with computer-assisted multivariate pattern-recognition techniques. It is increasingly being deployed in toxico- and pharmacokinetic studies in the pharmaceutical industry, especially during the safety assessment of candidate drugs in human medicine. However, despite the potential of this technique to reduce both costs and the numbers of animals used for research, examples of the application of metabolomics in veterinary research are, thus far, rare. Here we give an introduction to metabolomics and discuss its potential in the field of veterinary science.

Effect of altered sensory conditions on multivariate descriptors of human postural sway

NASA Technical Reports Server (NTRS)

Kuo, A. D.; Speers, R. A.; Peterka, R. J.; Horak, F. B.; Peterson, B. W. (Principal Investigator)

1998-01-01

Multivariate descriptors of sway were used to test whether altered sensory conditions result not only in changes in amount of sway but also in postural coordination. Eigenvalues and directions of eigenvectors of the covariance of shnk and hip angles were used as a set of multivariate descriptors. These quantities were measured in 14 healthy adult subjects performing the Sensory Organization test, which disrupts visual and somatosensory information used for spatial orientation. Multivariate analysis of variance and discriminant analysis showed that resulting sway changes were at least bivariate in character, with visual and somatosensory conditions producing distinct changes in postural coordination. The most significant changes were found when somatosensory information was disrupted by sway-referencing of the support surface (P = 3.2 x 10(-10)). The resulting covariance measurements showed that subjects not only swayed more but also used increased hip motion analogous to the hip strategy. Disruption of vision, by either closing the eyes or sway-referencing the visual surround, also resulted in altered sway (P = 1.7 x 10(-10)), with proportionately more motion of the center of mass than with platform sway-referencing. As shown by discriminant analysis, an optimal univariate measure could explain at most 90% of the behavior due to altered sensory conditions. The remaining 10%, while smaller, are highly significant changes in posture control that depend on sensory conditions. The results imply that normal postural coordination of the trunk and legs requires both somatosensory and visual information and that each sensory modality makes a unique contribution to posture control. Descending postural commands are multivariate in nature, and the motion at each joint is affected uniquely by input from multiple sensors.

Patterns of Circulating Inflammatory Biomarkers in Older Persons with Varying Levels of Physical Performance: A Partial Least Squares-Discriminant Analysis Approach

PubMed Central

Marzetti, Emanuele; Landi, Francesco; Marini, Federico; Cesari, Matteo; Buford, Thomas W.; Manini, Todd M.; Onder, Graziano; Pahor, Marco; Bernabei, Roberto; Leeuwenburgh, Christiaan; Calvani, Riccardo

2014-01-01

Background: Chronic, low-grade inflammation and declining physical function are hallmarks of the aging process. However, previous attempts to correlate individual inflammatory biomarkers with physical performance in older people have produced mixed results. Given the complexity of the inflammatory response, the simultaneous analysis of an array of inflammatory mediators may provide more insights into the relationship between inflammation and age-related physical function decline. This study was designed to explore the association between a panel of inflammatory markers and physical performance in older adults through a multivariate statistical approach. Methods: Community-dwelling older persons were categorized into “normal walkers” (NWs; n = 27) or “slow walkers” (SWs; n = 11) groups using 0.8 m s−1 as the 4-m gait speed cutoff. A panel of 14 circulating inflammatory biomarkers was assayed by multiplex analysis. Partial least squares-discriminant analysis (PLS-DA) was used to identify patterns of inflammatory mediators associated with gait speed categories. Results: The optimal complexity of the PLS-DA model was found to be five latent variables. The proportion of correct classification was 88.9% for NW subjects (74.1% in cross-validation) and 90.9% for SW individuals (81.8% in cross-validation). Discriminant biomarkers in the model were interleukin 8, myeloperoxidase, and tumor necrosis factor alpha (all higher in the SW group), and P-selectin, interferon gamma, and granulocyte–macrophage colony-stimulating factor (all higher in the NW group). Conclusion: Distinct profiles of circulating inflammatory biomarkers characterize older subjects with different levels of physical performance. The dissection of these patterns may provide novel insights into the role played by inflammation in the disabling cascade and possible new targets for interventions. PMID:25593902

Perceived discrimination and physical health among HIV-positive Black and Latino men who have sex with men.

PubMed

Bogart, Laura M; Landrine, Hope; Galvan, Frank H; Wagner, Glenn J; Klein, David J

2013-05-01

We conducted the first study to examine health correlates of discrimination due to race/ethnicity, HIV-status, and sexual orientation among 348 HIV-positive Black (n = 181) and Latino (n = 167) men who have sex with men. Participants completed audio computer-assisted self-interviews. In multivariate analyses, Black participants who experienced greater racial discrimination were less likely to have a high CD4 cell count [OR = 0.7, 95 % CI = (0.5, 0.9), p = 0.02], and an undetectable viral load [OR = 0.8, 95 % CI = (0.6, 1.0), p = 0.03], and were more likely to visit the emergency department [OR = 1.3, 95 % CI = (1.0, 1.7), p = 0.04]; the combined three types of discrimination predicted greater AIDS symptoms [F (3,176) = 3.8, p < 0.01]. Among Latinos, the combined three types of discrimination predicted greater medication side effect severity [F (3,163) = 4.6, p < 0.01] and AIDS symptoms [F (3,163) = 3.1, p < 0.05]. Findings suggest that the stress of multiple types of discrimination plays a role in health outcomes.

Perceived Discrimination and Physical Health among HIV-Positive Black and Latino Men who have Sex with Men

PubMed Central

Bogart, Laura M.; Landrine, Hope; Galvan, Frank H.; Wagner, Glenn J.; Klein, David J.

2012-01-01

We conducted the first study to examine health correlates of discrimination due to race/ethnicity, HIV-status, and sexual orientation among 348 HIV-positive Black (n=181) and Latino (n=167) men who have sex with men. Participants completed audio computer-assisted self-interviews. In multivariate analyses, Black participants who experienced greater racial discrimination were less likely to have a high CD4 cell count [OR=0.7, 95%CI=(0.5, 0.9), p=.02], and an undetectable viral load [OR=0.8, 95%CI=(0.6, 1.0), p=.03], and were more likely to visit the emergency department [OR=1.3, 95%CI=(1.0, 1.7), p=.04]; the combined three types of discrimination predicted greater AIDS symptoms [F (3,176)=3.8, p<0.01]. Among Latinos, the combined three types of discrimination predicted greater medication side effect severity [F (3,163)=4.6, p<0.01] and AIDS symptoms [F (3,163)=3.1, p<0.05]. Findings suggest that the stress of multiple types of discrimination plays a role in health outcomes. PMID:23297084

An exploratory examination of the associations among racial and ethnic discrimination, racial climate, and trauma-related symptoms in a college student population.

PubMed

Pieterse, Alex L; Carter, Robert T; Evans, Sarah A; Walter, Rebecca A

2010-07-01

In this study, we examined the association among perceptions of racial and/or ethnic discrimination, racial climate, and trauma-related symptoms among 289 racially diverse college undergraduates. Study measures included the Perceived Stress Scale, the Perceived Ethnic Discrimination Questionnaire, the Posttraumatic Stress Disorder Checklist-Civilian Version, and the Racial Climate Scale. Results of a multivariate analysis of variance (MANOVA) indicated that Asian and Black students reported more frequent experiences of discrimination than did White students. Additionally, the MANOVA indicated that Black students perceived the campus racial climate as being more negative than did White and Asian students. A hierarchical regression analysis showed that when controlling for generic life stress, perceptions of discrimination contributed an additional 10% of variance in trauma-related symptoms for Black students, and racial climate contributed an additional 7% of variance in trauma symptoms for Asian students. (c) 2010 APA, all rights reserved.

Discrimination, Harassment, and Gendered Health Inequalities: Do Perceptions of Workplace Mistreatment Contribute to the Gender Gap in Self-reported Health?

PubMed

Harnois, Catherine E; Bastos, João L

2018-06-01

This study examines the extent to which discrimination and harassment contribute to gendered health disparities. Analyzing data from the 2006, 2010, and 2014 General Social Surveys ( N = 3,724), we ask the following: (1) To what extent are perceptions of workplace gender discrimination and sexual harassment associated with self-reported mental and physical health? (2) How do multiple forms of workplace mistreatment (e.g., racism, ageism, and sexism) combine to structure workers' self-assessed health? and (3) To what extent do perceptions of mistreatment contribute to the gender gap in self-assessed health? Multivariate analyses show that among women, but not men, perceptions of workplace gender discrimination are negatively associated with poor mental health, and perceptions of sexual harassment are associated with poor physical health. Among men and women, perceptions of multiple forms of mistreatment are associated with worse mental health. Gender discrimination partially explains the gender gap in self-reported mental health.

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data.

PubMed

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-05-15

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Greater Perceived Age Discrimination in England than the United States: Results from HRS and ELSA

PubMed Central

Zaninotto, Paola; Steptoe, Andrew

2015-01-01

Objectives. We examined cross-national differences in perceptions of age discrimination in England and the United States. Under the premise that the United States has had age discrimination legislation in place for considerably longer than England, we hypothesized that perceptions of age discrimination would be lower in the United States. Methods. We analyzed data from two nationally representative studies of aging, the U.S. Health and Retirement Study (n = 4,818) and the English Longitudinal Study of Ageing (n = 7,478). Respondents aged 52 years and older who attributed any experiences of discrimination to their age were treated as cases of perceived age discrimination. We used multivariable logistic regression to estimate the odds ratios of experiencing perceived age discrimination in relation to selected sociodemographic factors. Results. Perceptions of age discrimination were significantly higher in England than the United States, with 34.8% of men and women in England reporting age discrimination compared with 29.1% in the United States. Associations between perceived age discrimination and older age and lower levels of household wealth were observed in both countries, but we found differences between England and the United States in the relationship between perceived age discrimination and education. Discussion. Our study revealed that levels of perceived age discrimination are lower in the United States than England and are less socially patterned. This suggests that differing social and political circumstances in the two countries may have an important role to play. PMID:26224759

Racial discrimination associated with higher diastolic blood pressure in a sample of American Indian adults

PubMed Central

Thayer, Zaneta M.; Blair, Irene V.; Buchwald, Dedra S.; Manson, Spero M.

2017-01-01

Objectives Hypertension prevalence is high among American Indians (AIs). AIs experience a substantial burden of interpersonal racial discrimination, which in other populations has been associated with higher blood pressure. The purpose of this study is to understand whether racial discrimination experiences are associated with higher blood pressure in AIs. Materials and Methods We used the Everyday Discrimination Scale to evaluate the relationship between discrimination and measured blood pressure among 77 AIs from two reservation communities in the Northern Plains. We used multivariate linear regression to evaluate the association of racial discrimination with systolic and diastolic blood pressure, respectively. Racial discrimination, systolic blood pressure, and diastolic blood pressure were analyzed as continuous variables. All analyses adjusted for sex, waist circumference, age, posttraumatic stress disorder status, and education. Results We found that 61% of participants experienced discrimination that they attributed to their race or ancestry. Racial discrimination was associated with significantly higher diastolic blood pressure (β = 0.22, SE = 0.09, P = 0.02), and with a similar non-significant trend toward higher systolic blood pressure (β = 0.25, SE = 0.15, P = 0.09). Conclusion The results of this analysis suggest that racial discrimination may contribute to higher diastolic blood pressure within Native communities. These findings highlight one pathway through which the social environment can shape patterns of biology and health in AI and other socially and politically marginalized groups. PMID:28198537

Perceived discrimination and stigma toward children affected by HIV/AIDS and their HIV-positive caregivers in central Haiti

PubMed Central

Surkan, Pamela J.; Mukherjee, Joia S.; Williams, David R.; Eustache, Eddy; Louis, Ermaze; Jean-Paul, Thierry; Lambert, Wesler; Scanlan, Fiona C.; Oswald, Catherine M.; Fawzi, Mary C. Smith

2010-01-01

In many settings worldwide, HIV-positive individuals have experienced a significant level of stigma and discrimination. This discrimination may also impact other family members affected by the disease, including children. The aim of our study was to identify factors associated with stigma and/or discrimination among HIV-affected youth and their HIV-positive caregivers in central Haiti. Recruitment of HIV-positive patients with children aged 10–17 years was conducted in 2006–2007. Data on HIV-related stigma and/or discrimination were based on interviews with 451 youth and 292 caregivers. Thirty-two percent of caregivers reported that children were discriminated against because of HIV/AIDS. Commune of residence was associated with discrimination against children affected by HIV/AIDS and HIV-related stigma among HIV-positive caregivers, suggesting variability across communities. Multivariable regression models showed that lacking social support, being an orphan, and caregiver HIV-related stigma were associated with discrimination in HIV-affected children. Caregiver HIV-related stigma demonstrated a strong association with depressive symptoms. The results could inform strategies for potential interventions to reduce HIV-related stigma and discrimination. These may include increasing social and caregiver support of children affected by HIV, enhancing support of caregivers to reduce burden of depressive symptoms, and promoting reduction of HIV-related stigma and discrimination at the community-level. PMID:20635244

Racial Discrimination and HIV-related Risk Behaviors in Southeast Louisiana

PubMed Central

Kaplan, Kathryn C.; Hormes, Julia M.; Wallace, Maeve; Rountree, Michele; Theall, Katherine P.

2016-01-01

Objectives We examined the relationship between cumulative experiences of racial discrimination and HIV-related risk taking, and whether these relationships are mediated through alcohol use among African Americans in semi-rural southeast Louisiana. Methods Participants (N = 214) reported on experiences of discrimination, HIV sexual risk-taking, history of sexually transmitted infection (STI), and health behaviors including alcohol use in the previous 90 days. Experiences of discrimination (scaled both by frequency of occurrence and situational counts) as a predictor of a sexual risk composite score as well as a history of STI was assessed using multivariate linear and logistic regression, respectively, including tests for mediation by alcohol use. Results Discrimination was common in this cohort, with respondents confirming their experience on average 7 of the 9 potential situations and on more than 34 separate occasions. After adjustment, discrimination was significantly associated with increasing sexual risk-taking and lifetime history of STI when measured either by frequency of occurrence or number of situations, although there was no evidence that these relationships were mediated through alcohol use. Conclusions Cumulative experiences of discrimination may play a significant role in sexual risk behavior and consequently increase vulnerability to HIV and other STIs. PMID:26685822

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Comparison of the prognostic value of pretreatment measurements of systemic inflammatory response in patients undergoing curative resection of clear cell renal cell carcinoma.

PubMed

Lucca, Ilaria; de Martino, Michela; Hofbauer, Sebastian L; Zamani, Nura; Shariat, Shahrokh F; Klatte, Tobias

2015-12-01

Pretreatment measurements of systemic inflammatory response, including the Glasgow prognostic score (GPS), the neutrophil-to-lymphocyte ratio (NLR), the monocyte-to-lymphocyte ratio (MLR), the platelet-to-lymphocyte ratio (PLR) and the prognostic nutritional index (PNI) have been recognized as prognostic factors in clear cell renal cell carcinoma (CCRCC), but there is at present no study that compared these markers. We evaluated the pretreatment GPS, NLR, MLR, PLR and PNI in 430 patients, who underwent surgery for clinically localized CCRCC (pT1-3N0M0). Associations with disease-free survival were assessed with Cox models. Discrimination was measured with the C-index, and a decision curve analysis was used to evaluate the clinical net benefit. On multivariable analyses, all measures of systemic inflammatory response were significant prognostic factors. The increase in discrimination compared with the stage, size, grade and necrosis (SSIGN) score alone was 5.8 % for the GPS, 1.1-1.4 % for the NLR, 2.9-3.4 % for the MLR, 2.0-3.3 % for the PLR and 1.4-3.0 % for the PNI. On the simultaneous multivariable analysis of all candidate measures, the final multivariable model contained the SSIGN score (HR 1.40, P < 0.001), the GPS (HR 2.32, P < 0.001) and the MLR (HR 5.78, P = 0.003) as significant variables. Adding both the GPS and the MLR increased the discrimination of the SSIGN score by 6.2 % and improved the clinical net benefit. In patients with clinically localized CCRCC, the GPS and the MLR appear to be the most relevant prognostic measures of systemic inflammatory response. They may be used as an adjunct for patient counseling, tailoring management and clinical trial design.

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

Classification of edible oils by employing 31P and 1H NMR spectroscopy in combination with multivariate statistical analysis. A proposal for the detection of seed oil adulteration in virgin olive oils.

PubMed

Vigli, Georgia; Philippidis, Angelos; Spyros, Apostolos; Dais, Photis

2003-09-10

A combination of (1)H NMR and (31)P NMR spectroscopy and multivariate statistical analysis was used to classify 192 samples from 13 types of vegetable oils, namely, hazelnut, sunflower, corn, soybean, sesame, walnut, rapeseed, almond, palm, groundnut, safflower, coconut, and virgin olive oils from various regions of Greece. 1,2-Diglycerides, 1,3-diglycerides, the ratio of 1,2-diglycerides to total diglycerides, acidity, iodine value, and fatty acid composition determined upon analysis of the respective (1)H NMR and (31)P NMR spectra were selected as variables to establish a classification/prediction model by employing discriminant analysis. This model, obtained from the training set of 128 samples, resulted in a significant discrimination among the different classes of oils, whereas 100% of correct validated assignments for 64 samples were obtained. Different artificial mixtures of olive-hazelnut, olive-corn, olive-sunflower, and olive-soybean oils were prepared and analyzed by (1)H NMR and (31)P NMR spectroscopy. Subsequent discriminant analysis of the data allowed detection of adulteration as low as 5% w/w, provided that fresh virgin olive oil samples were used, as reflected by their high 1,2-diglycerides to total diglycerides ratio (D > or = 0.90).

Nomogram Prediction of Overall Survival After Curative Irradiation for Uterine Cervical Cancer

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

Seo, YoungSeok; Yoo, Seong Yul; Kim, Mi-Sook

Purpose: The purpose of this study was to develop a nomogram capable of predicting the probability of 5-year survival after radical radiotherapy (RT) without chemotherapy for uterine cervical cancer. Methods and Materials: We retrospectively analyzed 549 patients that underwent radical RT for uterine cervical cancer between March 1994 and April 2002 at our institution. Multivariate analysis using Cox proportional hazards regression was performed and this Cox model was used as the basis for the devised nomogram. The model was internally validated for discrimination and calibration by bootstrap resampling. Results: By multivariate regression analysis, the model showed that age, hemoglobin levelmore » before RT, Federation Internationale de Gynecologie Obstetrique (FIGO) stage, maximal tumor diameter, lymph node status, and RT dose at Point A significantly predicted overall survival. The survival prediction model demonstrated good calibration and discrimination. The bootstrap-corrected concordance index was 0.67. The predictive ability of the nomogram proved to be superior to FIGO stage (p = 0.01). Conclusions: The devised nomogram offers a significantly better level of discrimination than the FIGO staging system. In particular, it improves predictions of survival probability and could be useful for counseling patients, choosing treatment modalities and schedules, and designing clinical trials. However, before this nomogram is used clinically, it should be externally validated.« less

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.

Metabolic profiling of Angelica acutiloba roots utilizing gas chromatography-time-of-flight-mass spectrometry for quality assessment based on cultivation area and cultivar via multivariate pattern recognition.

PubMed

Tianniam, Sukanda; Tarachiwin, Lucksanaporn; Bamba, Takeshi; Kobayashi, Akio; Fukusaki, Eiichiro

2008-06-01

Gas chromatography time-of-flight mass spectrometry was applied to elucidate the profiling of primary metabolites and to evaluate the differences between quality differences in Angelica acutiloba (or Yamato-toki) roots through the utilization of multivariate pattern recognition-principal component analysis (PCA). Twenty-two metabolites consisting of sugars, amino and organic acids were identified. PCA analysis successfully discriminated the good, the moderate and the bad quality Yamato-toki roots in accordance to their cultivation areas. The results signified two reducing sugars, fructose and glucose being the most accumulated in the bad quality, whereas higher quantity of phosphoric acid, proline, malic acid and citric acid were found in the good and the moderate quality toki roots. PCA was also effective in discriminating samples derive from different cultivars. Yamato-toki roots with the moderate quality were compared by means of PCA, and the results illustrated good discrimination which was influenced most by malic acid. Overall, this study demonstrated that metabolomics technique is accurate and efficient in determining the quality differences in Yamato-toki roots, and has a potential to be a superior and suitable method to assess the quality of this medicinal plant.

Does tip-of-the-tongue for proper names discriminate amnestic mild cognitive impairment?

PubMed

Juncos-Rabadán, Onésimo; Facal, David; Lojo-Seoane, Cristina; Pereiro, Arturo X

2013-04-01

Difficulty in retrieving people's names is very common in the early stages of Alzheimer's disease and mild cognitive impairment. Such difficulty is often observed as the tip-of-the-tongue (TOT) phenomenon. The main aim of this study was to explore whether a famous people's naming task that elicited the TOT state can be used to discriminate between amnestic mild cognitive impairment (aMCI) patients and normal controls. Eighty-four patients with aMCI and 106 normal controls aged over 50 years performed a task involving naming 50 famous people shown in pictures. Univariate and multivariate regression analyses were used to study the relationships between aMCI and semantic and phonological measures in the TOT paradigm. Univariate regression analyses revealed that all TOT measures significantly predicted aMCI. Multivariate analysis of all these measures correctly classified 70% of controls (specificity) and 71.6% of aMCI patients (sensitivity), with an AUC (area under curve ROC) value of 0.74, but only the phonological measure remained significant. This classification value was similar to that obtained with the Semantic verbal fluency test. TOTs for proper names may effectively discriminate aMCI patients from normal controls through measures that represent one of the naming processes affected, that is, phonological access.

Morphological analysis of Trichomycterus areolatus Valenciennes, 1846 from southern Chilean rivers using a truss-based system (Siluriformes, Trichomycteridae).

PubMed

Colihueque, Nelson; Corrales, Olga; Yáñez, Miguel

2017-01-01

Trichomycterus areolatus Valenciennes, 1846 is a small endemic catfish inhabiting the Andean river basins of Chile. In this study, the morphological variability of three T. areolatus populations, collected in two river basins from southern Chile, was assessed with multivariate analyses, including principal component analysis (PCA) and discriminant function analysis (DFA). It is hypothesized that populations must segregate morphologically from each other based on the river basin that they were sampled from, since each basin presents relatively particular hydrological characteristics. Significant morphological differences among the three populations were found with PCA (ANOSIM test, r = 0.552, p < 0.0001) and DFA (Wilks's λ = 0.036, p < 0.01). PCA accounted for a total variation of 56.16% by the first two principal components. The first Principal Component (PC1) and PC2 explained 34.72 and 21.44% of the total variation, respectively. The scatter-plot of the first two discriminant functions (DF1 on DF2) also validated the existence of three different populations. In group classification using DFA, 93.3% of the specimens were correctly-classified into their original populations. Of the total of 22 transformed truss measurements, 17 exhibited highly significant ( p < 0.01) differences among populations. The data support the existence of T. areolatus morphological variation across different rivers in southern Chile, likely reflecting the geographic isolation underlying population structure of the species.

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

NASA Astrophysics Data System (ADS)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

Discrimination of whisky brands and counterfeit identification by UV-Vis spectroscopy and multivariate data analysis.

PubMed

Martins, Angélica Rocha; Talhavini, Márcio; Vieira, Maurício Leite; Zacca, Jorge Jardim; Braga, Jez Willian Batista

2017-08-15

The discrimination of whisky brands and counterfeit identification were performed by UV-Vis spectroscopy combined with partial least squares for discriminant analysis (PLS-DA). In the proposed method all spectra were obtained with no sample preparation. The discrimination models were built with the employment of seven whisky brands: Red Label, Black Label, White Horse, Chivas Regal (12years), Ballantine's Finest, Old Parr and Natu Nobilis. The method was validated with an independent test set of authentic samples belonging to the seven selected brands and another eleven brands not included in the training samples. Furthermore, seventy-three counterfeit samples were also used to validate the method. Results showed correct classification rates for genuine and false samples over 98.6% and 93.1%, respectively, indicating that the method can be helpful for the forensic analysis of whisky samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

A quality function deployment framework for the service quality of health information websites.

PubMed

Chang, Hyejung; Kim, Dohoon

2010-03-01

This research was conducted to identify both the users' service requirements on health information websites (HIWs) and the key functional elements for running HIWs. With the quality function deployment framework, the derived service attributes (SAs) are mapped into the suppliers' functional characteristics (FCs) to derive the most critical FCs for the users' satisfaction. Using the survey data from 228 respondents, the SAs, FCs and their relationships were analyzed using various multivariate statistical methods such as principal component factor analysis, discriminant analysis, correlation analysis, etc. Simple and compound FC priorities were derived by matrix calculation. Nine factors of SAs and five key features of FCs were identified, and these served as the basis for the house of quality model. Based on the compound FC priorities, the functional elements pertaining to security and privacy, and usage support should receive top priority in the course of enhancing HIWs. The quality function deployment framework can improve the FCs of the HIWs in an effective, structured manner, and it can also be utilized for critical success factors together with their strategic implications for enhancing the service quality of HIWs. Therefore, website managers could efficiently improve website operations by considering this study's results.

Multivariate Analysis of Combined Fourier Transform Near-Infrared Spectrometry (FT-NIR) and Raman Datasets for Improved Discrimination of Drying Oils.

PubMed

Carlesi, Serena; Ricci, Marilena; Cucci, Costanza; La Nasa, Jacopo; Lofrumento, Cristiana; Picollo, Marcello; Becucci, Maurizio

2015-07-01

This work explores the application of chemometric techniques to the analysis of lipidic paint binders (i.e., drying oils) by means of Raman and near-infrared spectroscopy. These binders have been widely used by artists throughout history, both individually and in mixtures. We prepared various model samples of the pure binders (linseed, poppy seed, and walnut oils) obtained from different manufacturers. These model samples were left to dry and then characterized by Raman and reflectance near-infrared spectroscopy. Multivariate analysis was performed by applying principal component analysis (PCA) on the first derivative of the corresponding Raman spectra (1800-750 cm(-1)), near-infrared spectra (6000-3900 cm(-1)), and their combination to test whether spectral differences could enable samples to be distinguished on the basis of their composition. The vibrational bands we found most useful to discriminate between the different products we studied are the fundamental ν(C=C) stretching and methylenic stretching and bending combination bands. The results of the multivariate analysis demonstrated the potential of chemometric approaches for characterizing and identifying drying oils, and also for gaining a deeper insight into the aging process. Comparison with high-performance liquid chromatography data was conducted to check the PCA results.

Molecular monitoring of epithelial-to-mesenchymal transition in breast cancer cells by means of Raman spectroscopy.

PubMed

Marro, M; Nieva, C; Sanz-Pamplona, R; Sierra, A

2014-09-01

In breast cancer the presence of cells undergoing the epithelial-to-mesenchymal transition is indicative of metastasis progression. Since metabolic features of breast tumour cells are critical in cancer progression and drug resistance, we hypothesized that the lipid content of malignant cells might be a useful indirect measure of cancer progression. In this study Multivariate Curve Resolution was applied to cellular Raman spectra to assess the metabolic composition of breast cancer cells undergoing the epithelial to mesenchymal transition. Multivariate Curve Resolution analysis led to the conclusion that this transition affects the lipid profile of cells, increasing tryptophan but maintaining a low fatty acid content in comparison with highly metastatic cells. Supporting those results, a Partial Least Square-Discriminant analysis was performed to test the ability of Raman spectroscopy to discriminate the initial steps of epithelial to mesenchymal transition in breast cancer cells. We achieved a high level of sensitivity and specificity, 94% and 100%, respectively. In conclusion, Raman microspectroscopy coupled with Multivariate Curve Resolution enables deconvolution and tracking of the molecular content of cancer cells during a biochemical process, being a powerful, rapid, reagent-free and non-invasive tool for identifying metabolic features of breast cancer cell aggressiveness at first stages of malignancy. Copyright © 2014 Elsevier B.V. All rights reserved.

Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America.

PubMed

Puhl, R M; Andreyeva, T; Brownell, K D

2008-06-01

Limited data are available on the prevalence and patterns of body weight discrimination from representative samples. This study examined experiences of weight/height discrimination in a nationally representative sample of US adults and compared their prevalence and patterns with discrimination experiences based on race and gender. Data were from the National Survey of Midlife Development in the United States, a 1995-1996 community-based survey of English-speaking adults aged 25-74 (N=2290). Reported experiences of weight/height discrimination included a variety of institutional settings and interpersonal relationships. Multivariate regression analyses were used to predict weight/height discrimination controlling for sociodemographic characteristics and body weight status. The prevalence of weight/height discrimination ranged from 5% among men to 10% among women, but these average percentages obscure the much higher risk of weight discrimination among heavier individuals (40% for adults with body mass index (BMI) of 35 and above). Younger individuals with a higher BMI had a particularly high risk of weight/height discrimination regardless of their race, education and weight status. Women were at greater risk for weight/height discrimination than men, especially women with a BMI of 30-35 who were three times more likely to report weight/height discrimination compared to male peers of a similar weight. Weight/height discrimination is prevalent in American society and is relatively close to reported rates of racial discrimination, particularly among women. Both institutional forms of weight/height discrimination (for example, in employment settings) and interpersonal mistreatment due to weight/height (for example, being called names) were common, and in some cases were even more prevalent than discrimination due to gender and race.

Association of discrimination-related trauma with sexual risk among HIV-positive African American men who have sex with men.

PubMed

Fields, Errol L; Bogart, Laura M; Galvan, Frank H; Wagner, Glenn J; Klein, David J; Schuster, Mark A

2013-05-01

We investigated whether 1 form of traumatic stress, discrimination-related trauma (e.g., physical assault because of race), was associated with unprotected anal intercourse, especially when compared with non-discrimination-related trauma, among African American men who have sex with men. A convenience sample of 131 HIV-positive African American men who have sex with men receiving antiretroviral treatment completed audio computer-assisted self-interviews that covered unprotected anal intercourse, interpersonal trauma, and whether trauma was because of discrimination on the basis of race/ethnicity, HIV serostatus, or sexual orientation. Sixty percent reported at least 1 interpersonal trauma; they attributed at least 1 trauma to being gay (47%), African American (17%), or HIV positive (9%). In a multivariate regression, experiencing discrimination-related trauma was significantly associated with unprotected anal intercourse (adjusted odds ratio [AOR] = 2.4; 95% confidence interval [CI] = 1.0, 5.7; P = .04), whereas experiencing non-discrimination-related trauma was not (AOR = 1.3; 95% CI = 0.6, 3.1; P = .53). HIV-positive African American men who have sex with men experience high levels of discrimination-related trauma, a stressor associated with greater risk taking. HIV prevention interventions should consider the potential damaging effects of discrimination in the context of trauma.

Inverse associations between perceived racism and coronary artery calcification.

PubMed

Everage, Nicholas J; Gjelsvik, Annie; McGarvey, Stephen T; Linkletter, Crystal D; Loucks, Eric B

2012-03-01

To evaluate whether racial discrimination is associated with coronary artery calcification (CAC) in African-American participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. The study included American Black men (n = 571) and women (n = 791) aged 33 to 45 years in the CARDIA study. Perceived racial discrimination was assessed based on the Experiences of Discrimination scale (range, 1-35). CAC was evaluated using computed tomography. Primary analyses assessed associations between perceived racial discrimination and presence of CAC using multivariable-adjusted logistic regression analysis, adjusted for age, gender, socioeconomic position (SEP), psychosocial variables, and coronary heart disease (CHD) risk factors. In age- and gender-adjusted logistic regression models, odds of CAC decreased as the perceived racial discrimination score increased (odds ratio [OR], 0.94; 95% confidence interval [CI], 0.90-0.98 per 1-unit increase in Experiences of Discrimination scale). The relationship did not markedly change after further adjustment for SEP, psychosocial variables, or CHD risk factors (OR, 0.93; 95% CI, 0.87-0.99). Perceived racial discrimination was negatively associated with CAC in this study. Estimation of more forms of racial discrimination as well as replication of analyses in other samples will help to confirm or refute these findings. Copyright © 2012 Elsevier Inc. All rights reserved.

Perceived Discrimination and Health among Immigrants in Europe According to National Integration Policies.

PubMed

Borrell, Carme; Palència, Laia; Bartoll, Xavier; Ikram, Umar; Malmusi, Davide

2015-08-31

Discrimination harms immigrants' health. The objective of this study was to analyze the association between perceived discrimination and health outcomes among first and second generation immigrants from low-income countries living in Europe, while accounting for sex and the national policy on immigration. Cross-sectional study including immigrants from low-income countries aged ≥15 years in 18 European countries (European Social Survey, 2012) (sample of 1271 men and 1335 women). The dependent variables were self-reported health, symptoms of depression, and limitation of activity. The independent variables were perceived group discrimination, immigrant background and national immigrant integration policy. We tested for association between perceived group discrimination and health outcomes by fitting robust Poisson regression models. We only observed significant associations between perceived group discrimination and health outcomes in first generation immigrants. For example, depression was associated with discrimination among both men and women (Prevalence Ratio-, 1.55 (95% CI: 1.16-2.07) and 1.47 (95% CI: 1.15-1.89) in the multivariate model, respectively), and mainly in countries with assimilationist immigrant integration policies. Perceived group discrimination is associated with poor health outcomes in first generation immigrants from low-income countries who live in European countries, but not among their descendants. These associations are more important in assimilationist countries.

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.

Evaluation of drinking quality of groundwater through multivariate techniques in urban area.

PubMed

Das, Madhumita; Kumar, A; Mohapatra, M; Muduli, S D

2010-07-01

Groundwater is a major source of drinking water in urban areas. Because of the growing threat of debasing water quality due to urbanization and development, monitoring water quality is a prerequisite to ensure its suitability for use in drinking. But analysis of a large number of properties and parameter to parameter basis evaluation of water quality is not feasible in a regular interval. Multivariate techniques could streamline the data without much loss of information to a reasonably manageable data set. In this study, using principal component analysis, 11 relevant properties of 58 water samples were grouped into three statistical factors. Discriminant analysis identified "pH influence" as the most distinguished factor and pH, Fe, and NO₃⁻ as the most discriminating variables and could be treated as water quality indicators. These were utilized to classify the sampling sites into homogeneous clusters that reflect location-wise importance of specific indicator/s for use to monitor drinking water quality in the whole study area.

Microwave-Assisted Extraction of Phenolic Compounds from Almond Skin Byproducts (Prunus amygdalus): A Multivariate Analysis Approach.

PubMed

Valdés, Arantzazu; Vidal, Lorena; Beltrán, Ana; Canals, Antonio; Garrigós, María Carmen

2015-06-10

A microwave-assisted extraction (MAE) procedure to isolate phenolic compounds from almond skin byproducts was optimized. A three-level, three-factor Box-Behnken design was used to evaluate the effect of almond skin weight, microwave power, and irradiation time on total phenolic content (TPC) and antioxidant activity (DPPH). Almond skin weight was the most important parameter in the studied responses. The best extraction was achieved using 4 g, 60 s, 100 W, and 60 mL of 70% (v/v) ethanol. TPC, antioxidant activity (DPPH, FRAP), and chemical composition (HPLC-DAD-ESI-MS/MS) were determined by using the optimized method from seven different almond cultivars. Successful discrimination was obtained for all cultivars by using multivariate linear discriminant analysis (LDA), suggesting the influence of cultivar type on polyphenol content and antioxidant activity. The results show the potential of almond skin as a natural source of phenolics and the effectiveness of MAE for the reutilization of these byproducts.

Detection of Leukemia with Blood Samples Using Raman Spectroscopy and Multivariate Analysis

NASA Astrophysics Data System (ADS)

Martínez-Espinosa, J. C.; González-Solís, J. L.; Frausto-Reyes, C.; Miranda-Beltrán, M. L.; Soria-Fregoso, C.; Medina-Valtierra, J.

2009-06-01

The use of Raman spectroscopy to analyze blood biochemistry and hence distinguish between normal and abnormal blood was investigated. Blood samples were obtained from 6 patients who were clinically diagnosed with leukemia and 6 healthy volunteers. The imprint was put under the microscope and several points were chosen for Raman measurement. All the spectra were collected by a confocal Raman micro-spectroscopy (Renishaw) with a NIR 830 nm laser. It is shown that the serum samples from patients with leukemia and from the control group can be discriminated when the multivariate statistical methods of principal component analysis (PCA) and linear discriminated analysis (LDA) are applied to their Raman spectra. The ratios of some band intensities were analyzed and some band ratios were significant and corresponded to proteins, phospholipids, and polysaccharides. The preliminary results suggest that Raman Spectroscopy could be a new technique to study the degree of damage to the bone marrow using just blood samples instead of biopsies, treatment very painful for patients.

Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches.

PubMed

Yang, Jun-Ho; Yoh, Jack J

2018-01-01

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis.

PubMed

Choi, Young Hae; Sertic, Sarah; Kim, Hye Kyong; Wilson, Erica G; Michopoulos, Filippos; Lefeber, Alfons W M; Erkelens, Cornelis; Prat Kricun, Sergio D; Verpoorte, Robert

2005-02-23

The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.

Sugar and acid content of Citrus prediction modeling using FT-IR fingerprinting in combination with multivariate statistical analysis.

PubMed

Song, Seung Yeob; Lee, Young Koung; Kim, In-Jung

2016-01-01

A high-throughput screening system for Citrus lines were established with higher sugar and acid contents using Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. FT-IR spectra confirmed typical spectral differences between the frequency regions of 950-1100 cm(-1), 1300-1500 cm(-1), and 1500-1700 cm(-1). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate five Citrus lines into three separate clusters corresponding to their taxonomic relationships. The quantitative predictive modeling of sugar and acid contents from Citrus fruits was established using partial least square regression algorithms from FT-IR spectra. The regression coefficients (R(2)) between predicted values and estimated sugar and acid content values were 0.99. These results demonstrate that by using FT-IR spectra and applying quantitative prediction modeling to Citrus sugar and acid contents, excellent Citrus lines can be early detected with greater accuracy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Trauma exposure, discrimination, and romantic relationship functioning: A longitudinal investigation among LGB young adults

PubMed Central

Sullivan, Timothy J.; Feinstein, Brian A.; Marshall, Amy D.; Mustanski, Brian

2017-01-01

Sexual orientation-related discrimination is common among sexual minority individuals, but its influence on romantic relationship functioning remains unclear. Further, exposure to potentially traumatic events may influence the association between discrimination and relationship functioning, but this has not been tested among sexual minority couples to date. The current study examines breadth of lifetime trauma exposure as a moderator of the associations between recent discrimination and changes in relationship functioning (satisfaction, commitment, and trust) over twelve months among 86 racially/ethnically diverse sexual minority young adults in relationships. For those with low trauma exposure, discrimination was associated with increases in satisfaction and commitment, but not trust. In contrast, for those with high trauma exposure, discrimination was not associated with changes in relationship functioning. Thus, some partnered sexual minority young adults may experience resilience in the face of discrimination, such that discrimination may promote positive relationship functioning. However, this does not appear to extend to those with more extensive trauma exposure histories. With an eye toward informing interventions, these findings call for additional research on individual differences in responses to discrimination, such as support seeking and dyadic coping. PMID:29527540

Advanced qualification of pharmaceutical excipient suppliers by multiple analytics and multivariate analysis combined.

PubMed

Hertrampf, A; Müller, H; Menezes, J C; Herdling, T

2015-11-10

Pharmaceutical excipients have different functions within a drug formulation, consequently they can influence the manufacturability and/or performance of medicinal products. Therefore, critical to quality attributes should be kept constant. Sometimes it may be necessary to qualify a second supplier, but its product will not be completely equal to the first supplier product. To minimize risks of not detecting small non-similarities between suppliers and to detect lot-to-lot variability for each supplier, multivariate data analysis (MVA) can be used as a more powerful alternative to classical quality control that uses one-parameter-at-a-time monitoring. Such approach is capable of supporting the requirements of a new guideline by the European Parliament and Council (2015/C-95/02) demanding appropriate quality control strategies for excipients based on their criticality and supplier risks in ensuring quality, safety and function. This study compares calcium hydrogen phosphate from two suppliers. It can be assumed that both suppliers use different manufacturing processes. Therefore, possible chemical and physical differences were investigated by using Raman spectroscopy, laser diffraction and X-ray powder diffraction. Afterwards MVA was used to extract relevant information from each analytical technique. Both CaHPO4 could be discriminated by their supplier. The gained knowledge allowed to specify an enhanced strategy for second supplier qualification. Copyright © 2015 Elsevier B.V. All rights reserved.

Stigma, discrimination and HIV outcomes among people living with HIV in Rio de Janeiro, Brazil: The intersection of multiple social inequalities.

PubMed

Kerrigan, Deanna; Vazzano, Andrea; Bertoni, Neilane; Malta, Monica; Bastos, Francisco Inacio

2017-02-01

Limited research has examined the social context surrounding stigma and discrimination and HIV outcomes among people living with HIV (PLHIV). We surveyed 900 PLHIV in Brazil and examined the relationship between stigma, discrimination and HIV outcomes utilising multivariable logistic regression. HIV stigma and discrimination were inversely associated with age (AOR Stigma 0.65, 95% CI 0.49-0.88; AOR Discrimination 0.72, 95% CI 0.54-0.95) and income (AOR Stigma 0.74, 95% CI 0.55-0.99; AOR Discrimination 0.62, 95% CI 0.46-0.82). Stigma was inversely associated with education (AOR 0.71, 95% CI 0.52-0.96) and no history of sex work (AOR 0.56, 95% CI 0.35-0.90), and positively associated with having children (AOR 1.71, 95% CI 1.18-2.48). Discrimination was inversely associated with no history of drug use (AOR 0.63, 95% CI 0.42-0.95). Stigma and discrimination were found to be inversely associated with overall health (AOR Stigma 0.54, 95% CI 0.40-0.74; AOR Discrimination 0.71, 95% CI 0.52-0.97). Discrimination was associated with having a sexually transmitted infection since HIV diagnosis (AOR 1.63, 95% CI 1.14-2.32). Findings suggest that future interventions should address multiple social inequalities faced by PLHIV to reduce HIV stigma and discrimination and improve health and HIV outcomes.

Discrimination, Mental Health, and Substance Use Disorders Among Sexual Minority Populations.

PubMed

Lee, Ji Hyun; Gamarel, Kristi E; Bryant, Kendall J; Zaller, Nickolas D; Operario, Don

2016-08-01

Sexual minority (lesbian, gay, bisexual) populations have a higher prevalence of mental health and substance use disorders compared to their heterosexual counterparts. Such disparities have been attributed, in part, to minority stressors, including distal stressors such as discrimination. However, few studies have examined associations between discrimination, mental health, and substance use disorders by gender among sexual minority populations. We analyzed data from 577 adult men and women who self-identified as lesbian, gay, or bisexual and participated in Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Six questions assessed discrimination due to sexual orientation. Weighted multivariable logistic regression examined associations between experiences of sexual orientation discrimination and both mental health and substance use disorders. Analyses were conducted separately for sexual minority men and women, adjusting for sociodemographic covariates. Sexual minority men who ever experienced discrimination (57.4%) reported higher odds of any lifetime drug use disorder and cannabis use disorder compared to sexual minority men who never experienced discrimination. Sexual minority women who ever experienced discrimination (42.9%) reported higher odds of any lifetime mood disorder and any lifetime anxiety disorder compared to sexual minority women who never experienced discrimination. The findings suggest that discrimination is differentially associated with internalizing (mental health) and externalizing (substance use) disorders for sexual minority men and women. These findings indicate a need to consider how homophobia and heteronormative discrimination may contribute to distinct health outcomes for lesbian and bisexual women compared with gay and bisexual men.

False alarm reduction by the And-ing of multiple multivariate Gaussian classifiers

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2003-09-01

The high-resolution sonar is one of the principal sensors used by the Navy to detect and classify sea mines in minehunting operations. For such sonar systems, substantial effort has been devoted to the development of automated detection and classification (D/C) algorithms. These have been spurred by several factors including (1) aids for operators to reduce work overload, (2) more optimal use of all available data, and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and man-made clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while still maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms have been studied. We refer to this as Algorithm Fusion. The results have been remarkable, including reliable robustness to new environments. This paper describes a method for training several multivariate Gaussian classifiers such that their And-ing dramatically reduces false alarms while maintaining a high probability of classification. This training approach is referred to as the Focused- Training method. This work extends our 2001-2002 work where the Focused-Training method was used with three other types of classifiers: the Attractor-based K-Nearest Neighbor Neural Network (a type of radial-basis, probabilistic neural network), the Optimal Discrimination Filter Classifier (based linear discrimination theory), and the Quadratic Penalty Function Support Vector Machine (QPFSVM). Although our experience has been gained in the area of sea mine detection and classification, the principles described herein are general and can be applied to a wide range of pattern recognition and automatic target recognition (ATR) problems.

Perceived discrimination and mental health disorders: The South African Stress and Health study

PubMed Central

Moomal, Hashim; Jackson, Pamela B; Stein, Dan J; Herman, Allen; Myer, Landon; Seedat, Soraya; Madela-Mntla, Edith; Williams, David R

2011-01-01

Objectives To describe the demographic correlates of perceived discrimination and explore the association between perceived discrimination and psychiatric disorders. Design A national household survey was conducted between 2002 and 2004 using the World Health Organization Composite International Diagnostic Interview (CIDI) to generate diagnoses of psychiatric disorders. Additional instruments provided data on perceived discrimination and related variables. Setting A nationally representative sample of adults in South Africa. Subjects 4 351 individuals aged 18 years and older. Outcomes 12-month and lifetime mood, anxiety and substance use disorders. Results In the multivariate analyses, acute and chronic racial discrimination were associated with an elevated risk of any 12-month DSM-IV disorder when adjusted for socio-demographic factors, but this association was no longer statistically significant when adjusted for other sources of social stress. In fully adjusted models, acute racial discrimination was associated with an elevated risk of lifetime substance use disorders. Acute and chronic non-racial discrimination were associated with an elevated risk of 12-month and lifetime rates of any disorder, even after adjustment for other stressors and potentially confounding psychological factors. The association of chronic non-racial discrimination and 12-month and lifetime disorder was evident across mood, anxiety, and substance use disorders in the fully adjusted models. Conclusion The risk of psychiatric disorders is elevated among persons who report experiences of discrimination. These associations are more robust for chronic than for acute discrimination and for non-racial than for racial discrimination. Perceived discrimination constitutes an important stressor that should be taken into account in the aetiology of psychiatric disorders. PMID:19588802

Greater Perceived Age Discrimination in England than the United States: Results from HRS and ELSA.

PubMed

Rippon, Isla; Zaninotto, Paola; Steptoe, Andrew

2015-11-01

We examined cross-national differences in perceptions of age discrimination in England and the United States. Under the premise that the United States has had age discrimination legislation in place for considerably longer than England, we hypothesized that perceptions of age discrimination would be lower in the United States. We analyzed data from two nationally representative studies of aging, the U.S. Health and Retirement Study (n = 4,818) and the English Longitudinal Study of Ageing (n = 7,478). Respondents aged 52 years and older who attributed any experiences of discrimination to their age were treated as cases of perceived age discrimination. We used multivariable logistic regression to estimate the odds ratios of experiencing perceived age discrimination in relation to selected sociodemographic factors. Perceptions of age discrimination were significantly higher in England than the United States, with 34.8% of men and women in England reporting age discrimination compared with 29.1% in the United States. Associations between perceived age discrimination and older age and lower levels of household wealth were observed in both countries, but we found differences between England and the United States in the relationship between perceived age discrimination and education. Our study revealed that levels of perceived age discrimination are lower in the United States than England and are less socially patterned. This suggests that differing social and political circumstances in the two countries may have an important role to play. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America.

Predicting the Naturalistic Course of Major Depressive Disorder Using Clinical and Multimodal Neuroimaging Information: A Multivariate Pattern Recognition Study.

PubMed

Schmaal, Lianne; Marquand, Andre F; Rhebergen, Didi; van Tol, Marie-José; Ruhé, Henricus G; van der Wee, Nic J A; Veltman, Dick J; Penninx, Brenda W J H

2015-08-15

A chronic course of major depressive disorder (MDD) is associated with profound alterations in brain volumes and emotional and cognitive processing. However, no neurobiological markers have been identified that prospectively predict MDD course trajectories. This study evaluated the prognostic value of different neuroimaging modalities, clinical characteristics, and their combination to classify MDD course trajectories. One hundred eighteen MDD patients underwent structural and functional magnetic resonance imaging (MRI) (emotional facial expressions and executive functioning) and were clinically followed-up at 2 years. Three MDD trajectories (chronic n = 23, gradual improving n = 36, and fast remission n = 59) were identified based on Life Chart Interview measuring the presence of symptoms each month. Gaussian process classifiers were employed to evaluate prognostic value of neuroimaging data and clinical characteristics (including baseline severity, duration, and comorbidity). Chronic patients could be discriminated from patients with more favorable trajectories from neural responses to various emotional faces (up to 73% accuracy) but not from structural MRI and functional MRI related to executive functioning. Chronic patients could also be discriminated from remitted patients based on clinical characteristics (accuracy 69%) but not when age differences between the groups were taken into account. Combining different task contrasts or data sources increased prediction accuracies in some but not all cases. Our findings provide evidence that the prediction of naturalistic course of depression over 2 years is improved by considering neuroimaging data especially derived from neural responses to emotional facial expressions. Neural responses to emotional salient faces more accurately predicted outcome than clinical data. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Screening for Frailty in Older Patients With Early-Stage Solid Tumors: A Prospective Longitudinal Evaluation of Three Different Geriatric Tools.

PubMed

Biganzoli, Laura; Mislang, Anna Rachelle; Di Donato, Samantha; Becheri, Dimitri; Biagioni, Chiara; Vitale, Stefania; Sanna, Giuseppina; Zafarana, Elena; Gabellini, Stefano; Del Monte, Francesca; Mori, Elena; Pozzessere, Daniele; Brunello, Antonella; Luciani, Andrea; Laera, Letizia; Boni, Luca; Di Leo, Angelo; Mottino, Giuseppe

2017-07-01

Frailty increases the risk of adverse health outcomes and/or dying when exposed to a stressor, and routine frailty assessment is recommended to guide treatment decision. The Balducci frailty criteria (BFC) and Fried frailty criteria (FFC) are commonly used, but these are time consuming. Vulnerable Elders Survey-13 (VES-13) score of ≥7, a simple and resource conserving function-based scoring system, may be used instead. This prospective study evaluates the performance of VES-13 in parallel with BFC and FFC, to identify frailty in elderly patients with early-stage cancer. Patients aged ≥70 years with early-stage solid tumors were classified as frail/nonfrail based on BFC (≥1 criteria), FFC (≥3 criteria), and VES-13 (score ≥ 7). All patients were assessed for functional decline and death. We evaluated 185 patients. FFC had a 17% frailty rate, whereas BFC and VES-13 both had 25%, with poor concordance seen between the three geriatric tools. FFC (hazard ratio = 1.99, p = .003) and VES-13 (hazard ratio = 2.81, p < .001) strongly discriminated for functional decline, whereas BFC (hazard ratio = 3.29, p < .001) had the highest discriminatory rate for deaths. BFC and VES-13 remained prognostic for overall survival in multivariate analysis correcting for age, tumor type, stage, and systemic treatment. A VES-13 score of ≥7 is a valuable discriminating tool for predicting functional decline or death and can be used as a frailty-screening tool among older cancer patients in centers with limited resources to conduct a comprehensive geriatric assessment. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Experimental variability and data pre-processing as factors affecting the discrimination power of some chemometric approaches (PCA, CA and a new algorithm based on linear regression) applied to (+/-)ESI/MS and RPLC/UV data: Application on green tea extracts.

PubMed

Iorgulescu, E; Voicu, V A; Sârbu, C; Tache, F; Albu, F; Medvedovici, A

2016-08-01

The influence of the experimental variability (instrumental repeatability, instrumental intermediate precision and sample preparation variability) and data pre-processing (normalization, peak alignment, background subtraction) on the discrimination power of multivariate data analysis methods (Principal Component Analysis -PCA- and Cluster Analysis -CA-) as well as a new algorithm based on linear regression was studied. Data used in the study were obtained through positive or negative ion monitoring electrospray mass spectrometry (+/-ESI/MS) and reversed phase liquid chromatography/UV spectrometric detection (RPLC/UV) applied to green tea extracts. Extractions in ethanol and heated water infusion were used as sample preparation procedures. The multivariate methods were directly applied to mass spectra and chromatograms, involving strictly a holistic comparison of shapes, without assignment of any structural identity to compounds. An alternative data interpretation based on linear regression analysis mutually applied to data series is also discussed. Slopes, intercepts and correlation coefficients produced by the linear regression analysis applied on pairs of very large experimental data series successfully retain information resulting from high frequency instrumental acquisition rates, obviously better defining the profiles being compared. Consequently, each type of sample or comparison between samples produces in the Cartesian space an ellipsoidal volume defined by the normal variation intervals of the slope, intercept and correlation coefficient. Distances between volumes graphically illustrates (dis)similarities between compared data. The instrumental intermediate precision had the major effect on the discrimination power of the multivariate data analysis methods. Mass spectra produced through ionization from liquid state in atmospheric pressure conditions of bulk complex mixtures resulting from extracted materials of natural origins provided an excellent data basis for multivariate analysis methods, equivalent to data resulting from chromatographic separations. The alternative evaluation of very large data series based on linear regression analysis produced information equivalent to results obtained through application of PCA an CA. Copyright © 2016 Elsevier B.V. All rights reserved.

Parasites as biological tags of fish stocks: a meta-analysis of their discriminatory power.

PubMed

Poulin, Robert; Kamiya, Tsukushi

2015-01-01

The use of parasites as biological tags to discriminate among marine fish stocks has become a widely accepted method in fisheries management. Here, we first link this approach to its unstated ecological foundation, the decay in the similarity of the species composition of assemblages as a function of increasing distance between them, a phenomenon almost universal in nature. We explain how distance decay of similarity can influence the use of parasites as biological tags. Then, we perform a meta-analysis of 61 uses of parasites as tags of marine fish populations in multivariate discriminant analyses, obtained from 29 articles. Our main finding is that across all studies, the observed overall probability of correct classification of fish based on parasite data was about 71%. This corresponds to a two-fold improvement over the rate of correct classification expected by chance alone, and the average effect size (Zr = 0·463) computed from the original values was also indicative of a medium-to-large effect. However, none of the moderator variables included in the meta-analysis had a significant effect on the proportion of correct classification; these moderators included the total number of fish sampled, the number of parasite species used in the discriminant analysis, the number of localities from which fish were sampled, the minimum and maximum distance between any pair of sampling localities, etc. Therefore, there are no clear-cut situations in which the use of parasites as tags is more useful than others. Finally, we provide recommendations for the future usage of parasites as tags for stock discrimination, to ensure that future applications of the method achieve statistical rigour and a high discriminatory power.

Characteristic fingerprinting based on macamides for discrimination of maca (Lepidium meyenii) by LC/MS/MS and multivariate statistical analysis.

PubMed

Pan, Yu; Zhang, Ji; Li, Hong; Wang, Yuan-Zhong; Li, Wan-Yi

2016-10-01

Macamides with a benzylalkylamide nucleus are characteristic and major bioactive compounds in the functional food maca (Lepidium meyenii Walp). The aim of this study was to explore variations in macamide content among maca from China and Peru. Twenty-seven batches of maca hypocotyls with different phenotypes, sampled from different geographical origins, were extracted and profiled by liquid chromatography with ultraviolet detection/tandem mass spectrometry (LC-UV/MS/MS). Twelve macamides were identified by MS operated in multiple scanning modes. Similarity analysis showed that maca samples differed significantly in their macamide fingerprinting. Partial least squares discriminant analysis (PLS-DA) was used to differentiate samples according to their geographical origin and to identify the most relevant variables in the classification model. The prediction accuracy for raw maca was 91% and five macamides were selected and considered as chemical markers for sample classification. When combined with a PLS-DA model, characteristic fingerprinting based on macamides could be recommended for labelling for the authentication of maca from different geographical origins. The results provided potential evidence for the relationships between environmental or other factors and distribution of macamides. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Racial discrimination associated with higher diastolic blood pressure in a sample of American Indian adults.

PubMed

Thayer, Zaneta M; Blair, Irene V; Buchwald, Dedra S; Manson, Spero M

2017-05-01

Hypertension prevalence is high among American Indians (AIs). AIs experience a substantial burden of interpersonal racial discrimination, which in other populations has been associated with higher blood pressure. The purpose of this study is to understand whether racial discrimination experiences are associated with higher blood pressure in AIs. We used the Everyday Discrimination Scale to evaluate the relationship between discrimination and measured blood pressure among 77 AIs from two reservation communities in the Northern Plains. We used multivariate linear regression to evaluate the association of racial discrimination with systolic and diastolic blood pressure, respectively. Racial discrimination, systolic blood pressure, and diastolic blood pressure were analyzed as continuous variables. All analyses adjusted for sex, waist circumference, age, posttraumatic stress disorder status, and education. We found that 61% of participants experienced discrimination that they attributed to their race or ancestry. Racial discrimination was associated with significantly higher diastolic blood pressure (β = 0.22, SE = 0.09, p = .02), and with a similar non-significant trend toward higher systolic blood pressure (β = 0.25, SE = 0.15, p = .09). The results of this analysis suggest that racial discrimination may contribute to higher diastolic blood pressure within Native communities. These findings highlight one pathway through which the social environment can shape patterns of biology and health in AI and other socially and politically marginalized groups. © 2017 Wiley Periodicals, Inc.

Functional and effective brain connectivity for discrimination between Alzheimer's patients and healthy individuals: A study on resting state EEG rhythms.

PubMed

Blinowska, Katarzyna J; Rakowski, Franciszek; Kaminski, Maciej; De Vico Fallani, Fabrizio; Del Percio, Claudio; Lizio, Roberta; Babiloni, Claudio

2017-04-01

This exploratory study provided a proof of concept of a new procedure using multivariate electroencephalographic (EEG) topographic markers of cortical connectivity to discriminate normal elderly (Nold) and Alzheimer's disease (AD) individuals. The new procedure was tested on an existing database formed by resting state eyes-closed EEG data (19 exploring electrodes of 10-20 system referenced to linked-ear reference electrodes) recorded in 42 AD patients with dementia (age: 65.9years±8.5 standard deviation, SD) and 42 Nold non-consanguineous caregivers (age: 70.6years±8.5 SD). In this procedure, spectral EEG coherence estimated reciprocal functional connectivity while non-normalized directed transfer function (NDTF) estimated effective connectivity. Principal component analysis and computation of Mahalanobis distance integrated and combined these EEG topographic markers of cortical connectivity. The area under receiver operating curve (AUC) indexed the classification accuracy. A good classification of Nold and AD individuals was obtained by combining the EEG markers derived from NDTF and coherence (AUC=86%, sensitivity=0.85, specificity=0.70). These encouraging results motivate a cross-validation study of the new procedure in age- and education-matched Nold, stable and progressing mild cognitive impairment individuals, and de novo AD patients with dementia. If cross-validated, the new procedure will provide cheap, broadly available, repeatable over time, and entirely non-invasive EEG topographic markers reflecting abnormal cortical connectivity in AD patients diagnosed by direct or indirect measurement of cerebral amyloid β and hyperphosphorylated tau peptides. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Metabolomic Biomarkers in Urine of Cushing's Syndrome Patients.

PubMed

Kotłowska, Alicja; Puzyn, Tomasz; Sworczak, Krzysztof; Stepnowski, Piotr; Szefer, Piotr

2017-01-29

Cushing's syndrome (CS) is a disease which results from excessive levels of cortisol in the human body. The disorder is associated with various signs and symptoms which are also common for the general population not suffering from compound hypersecretion. Thus, more sensitive and selective methods are required for the diagnosis of CS. This follow-up study was conducted to determine which steroid metabolites could serve as potential indicators of CS and possible subclinical hypercortisolism in patients diagnosed with so called non-functioning adrenal incidentalomas (AIs). Urine samples from negative controls ( n = 37), patients with CS characterized by hypercortisolism and excluding iatrogenic CS ( n = 16), and patients with non-functioning AIs with possible subclinical Cushing's syndrome ( n = 25) were analyzed using gas chromatography-mass spectrometry (GC/MS) and gas chromatograph equipped with flame ionization detector (GC/FID). Statistical and multivariate methods were applied to investigate the profile differences between examined individuals. The analyses revealed hormonal differences between patients with CS and the rest of examined individuals. The concentrations of selected metabolites of cortisol, androgens, and pregnenetriol were elevated whereas the levels of tetrahydrocortisone were decreased for CS when opposed to the rest of the study population. Moreover, after analysis of potential confounding factors, it was also possible to distinguish six steroid hormones which discriminated CS patients from other study subjects. The obtained discriminant functions enabled classification of CS patients and AI group characterized by mild hypersecretion of cortisol metabolites. It can be concluded that steroid hormones selected by applying urinary profiling may serve the role of potential biomarkers of CS and can aid in its early diagnosis.

Metabolomic Biomarkers in Urine of Cushing’s Syndrome Patients

PubMed Central

Kotłowska, Alicja; Puzyn, Tomasz; Sworczak, Krzysztof; Stepnowski, Piotr; Szefer, Piotr

2017-01-01

Cushing’s syndrome (CS) is a disease which results from excessive levels of cortisol in the human body. The disorder is associated with various signs and symptoms which are also common for the general population not suffering from compound hypersecretion. Thus, more sensitive and selective methods are required for the diagnosis of CS. This follow-up study was conducted to determine which steroid metabolites could serve as potential indicators of CS and possible subclinical hypercortisolism in patients diagnosed with so called non-functioning adrenal incidentalomas (AIs). Urine samples from negative controls (n = 37), patients with CS characterized by hypercortisolism and excluding iatrogenic CS (n = 16), and patients with non-functioning AIs with possible subclinical Cushing’s syndrome (n = 25) were analyzed using gas chromatography-mass spectrometry (GC/MS) and gas chromatograph equipped with flame ionization detector (GC/FID). Statistical and multivariate methods were applied to investigate the profile differences between examined individuals. The analyses revealed hormonal differences between patients with CS and the rest of examined individuals. The concentrations of selected metabolites of cortisol, androgens, and pregnenetriol were elevated whereas the levels of tetrahydrocortisone were decreased for CS when opposed to the rest of the study population. Moreover, after analysis of potential confounding factors, it was also possible to distinguish six steroid hormones which discriminated CS patients from other study subjects. The obtained discriminant functions enabled classification of CS patients and AI group characterized by mild hypersecretion of cortisol metabolites. It can be concluded that steroid hormones selected by applying urinary profiling may serve the role of potential biomarkers of CS and can aid in its early diagnosis. PMID:28146078

Experiences of transgender-related discrimination and implications for health: results from the Virginia Transgender Health Initiative Study.

PubMed

Bradford, Judith; Reisner, Sari L; Honnold, Julie A; Xavier, Jessica

2013-10-01

We examined relationships between social determinants of health and experiences of transgender-related discrimination reported by transgender people in Virginia. In 2005 through 2006, 387 self-identified transgender people completed a statewide health needs assessment; 350 who completed eligibility questions were included in this examination of factors associated with experiences of discrimination in health care, employment, or housing. We fit multivariate logistic regression models using generalized estimating equations to adjust for survey modality (online vs paper). Of participants, 41% (n = 143) reported experiences of transgender-related discrimination. Factors associated with transgender-related discrimination were geographic context, gender (female-to male spectrum vs male-to-female spectrum), low socioeconomic status, being a racial/ethnic minority, not having health insurance, gender transition indicators (younger age at first transgender awareness), health care needed but unable to be obtained (hormone therapy and mental health services), history of violence (sexual and physical), substance use health behaviors (tobacco and alcohol), and interpersonal factors (family support and community connectedness). Findings suggest that transgender Virginians experience widespread discrimination in health care, employment, and housing. Multilevel interventions are needed for transgender populations, including legal protections and training for health care providers.

The neural basis of visual word form processing: a multivariate investigation.

PubMed

Nestor, Adrian; Behrmann, Marlene; Plaut, David C

2013-07-01

Current research on the neurobiological bases of reading points to the privileged role of a ventral cortical network in visual word processing. However, the properties of this network and, in particular, its selectivity for orthographic stimuli such as words and pseudowords remain topics of significant debate. Here, we approached this issue from a novel perspective by applying pattern-based analyses to functional magnetic resonance imaging data. Specifically, we examined whether, where and how, orthographic stimuli elicit distinct patterns of activation in the human cortex. First, at the category level, multivariate mapping found extensive sensitivity throughout the ventral cortex for words relative to false-font strings. Secondly, at the identity level, the multi-voxel pattern classification provided direct evidence that different pseudowords are encoded by distinct neural patterns. Thirdly, a comparison of pseudoword and face identification revealed that both stimulus types exploit common neural resources within the ventral cortical network. These results provide novel evidence regarding the involvement of the left ventral cortex in orthographic stimulus processing and shed light on its selectivity and discriminability profile. In particular, our findings support the existence of sublexical orthographic representations within the left ventral cortex while arguing for the continuity of reading with other visual recognition skills.

Multivariate statistical techniques for the evaluation of surface water quality of the Himalayan foothills streams, Pakistan

NASA Astrophysics Data System (ADS)

Malik, Riffat Naseem; Hashmi, Muhammad Zaffar

2017-10-01

Himalayan foothills streams, Pakistan play an important role in living water supply and irrigation of farmlands; thus, the water quality is closely related to public health. Multivariate techniques were applied to check spatial and seasonal trends, and metals contamination sources of the Himalayan foothills streams, Pakistan. Grab surface water samples were collected from different sites (5-15 cm water depth) in pre-washed polyethylene containers. Fast Sequential Atomic Absorption Spectrophotometer (Varian FSAA-240) was used to measure the metals concentration. Concentrations of Ni, Cu, and Mn were high in pre-monsoon season than the post-monsoon season. Cluster analysis identified impaired, moderately impaired and least impaired clusters based on water parameters. Discriminant function analysis indicated spatial variability in water was due to temperature, electrical conductivity, nitrates, iron and lead whereas seasonal variations were correlated with 16 physicochemical parameters. Factor analysis identified municipal and poultry waste, automobile activities, surface runoff, and soil weathering as major sources of contamination. Levels of Mn, Cr, Fe, Pb, Cd, Zn and alkalinity were above the WHO and USEPA standards for surface water. The results of present study will help to higher authorities for the management of the Himalayan foothills streams.

Evolution of the Max and Mlx networks in animals.

PubMed

McFerrin, Lisa G; Atchley, William R

2011-01-01

Transcription factors (TFs) are essential for the regulation of gene expression and often form emergent complexes to perform vital roles in cellular processes. In this paper, we focus on the parallel Max and Mlx networks of TFs because of their critical involvement in cell cycle regulation, proliferation, growth, metabolism, and apoptosis. A basic-helix-loop-helix-zipper (bHLHZ) domain mediates the competitive protein dimerization and DNA binding among Max and Mlx network members to form a complex system of cell regulation. To understand the importance of these network interactions, we identified the bHLHZ domain of Max and Mlx network proteins across the animal kingdom and carried out several multivariate statistical analyses. The presence and conservation of Max and Mlx network proteins in animal lineages stemming from the divergence of Metazoa indicate that these networks have ancient and essential functions. Phylogenetic analysis of the bHLHZ domain identified clear relationships among protein families with distinct points of radiation and divergence. Multivariate discriminant analysis further isolated specific amino acid changes within the bHLHZ domain that classify proteins, families, and network configurations. These analyses on Max and Mlx network members provide a model for characterizing the evolution of TFs involved in essential networks.

Discriminating Nonpareil marketing group almond cultivars through multivariate analyses

USDA-ARS?s Scientific Manuscript database

The California almond industry produces over 80% of the world’s almonds with nearly 2 billion pounds harvested in 2011. Several dozen cultivars are grown, but the Nonpareil cultivar is dominant in both acreage and tonnage. Almond cultivars are categorized into defined marketing groups based on ker...

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

ERIC Educational Resources Information Center

Mavridis, Dimitris; Moustaki, Irini

2008-01-01

In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…

Identifying cognitive impairment in type 2 diabetes with functional connectivity: a multivariate pattern analysis of resting state fMRI data

NASA Astrophysics Data System (ADS)

Liu, Zhenyu; Cui, Xingwei; Tang, Zhenchao; Dong, Di; Zang, Yali; Tian, Jie

2017-03-01

Previous researches have shown that type 2 diabetes mellitus (T2DM) is associated with an increased risk of cognitive impairment. Early detection of brain abnormalities at the preclinical stage can be useful for developing preventive interventions to abate cognitive decline. We aimed to investigate the whole-brain resting-state functional connectivity (RSFC) patterns of T2DM patients between 90 regions of interest (ROIs) based on the RS-fMRI data, which can be used to test the feasibility of identifying T2DM patients with cognitive impairment from other T2DM patients. 74 patients were recruited in this study and multivariate pattern analysis was utilized to assess the prediction performance. Elastic net was firstly used to select the key features for prediction, and then a linear discrimination model was constructed. 23 RSFCs were selected and it achieved the performance with classification accuracy of 90.54% and areas under the receiver operating characteristic curve (AUC) of 0.944 using ten-fold cross-validation. The results provide strong evidence that functional interactions of brain regions undergo notable alterations between T2DM patients with cognitive impairment or not. By analyzing the RSFCs that were selected as key features, we found that most of them involved the frontal or temporal. We speculated that cognitive impairment in T2DM patients mainly impacted these two lobes. Overall, the present study indicated that RSFCs undergo notable alterations associated with the cognitive impairment in T2DM patients, and it is possible to predicted cognitive impairment early with RSFCs.

Relationships between discrimination in health care and health care outcomes among four race/ethnic groups.

PubMed

Benjamins, Maureen R; Whitman, Steven

2014-06-01

Discrimination has been found to be detrimental to health, but less is known about the influence of discrimination in health care. To address this, the current study (1) compared levels of racial/ethnic discrimination in health care among four race/ethnic groups; (2) determined associations between this type of discrimination and health care outcomes; and (3) assessed potential mediators and moderators as suggested by previous studies. Multivariate logistic regression models were used within a population-based sample of 1,699 White, African American, Mexican, and Puerto Rican respondents. Overall, 23% of the sample reported discrimination in health care, with levels varying substantially by race/ethnicity. In adjusted models, this type of discrimination was associated with an increased likelihood of having unmet health care needs (OR = 2.48, CI = 1.57-3.90) and lower odds of perceiving excellent quality of care (OR = 0.43, CI = 0.28-0.66), but not with the use of a physician when not sick or use of alternative medicine. The mediating role of mental health factors was inconsistently observed and the relationships were not moderated by race/ethnicity. These findings expand the literature and provide preliminary evidence that can eventually inform the development of interventions and the training of health care providers.

Spectral discrimination of serum from liver cancer and liver cirrhosis using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Tianyue; Li, Xiaozhou; Yu, Ting; Sun, Ruomin; Li, Siqi

2011-07-01

In this paper, Raman spectra of human serum were measured using Raman spectroscopy, then the spectra was analyzed by multivariate statistical methods of principal component analysis (PCA). Then linear discriminant analysis (LDA) was utilized to differentiate the loading score of different diseases as the diagnosing algorithm. Artificial neural network (ANN) was used for cross-validation. The diagnosis sensitivity and specificity by PCA-LDA are 88% and 79%, while that of the PCA-ANN are 89% and 95%. It can be seen that modern analyzing method is a useful tool for the analysis of serum spectra for diagnosing diseases.

Perceived discrimination In Primary Healthcare in Europe: evidence from the cross-sectional QUALICOPC study.

PubMed

Hanssens, Lise G M; Detollenaere, Jens D J; Van Pottelberge, Amelie; Baert, Stijn; Willems, Sara J T

2017-03-01

Recent figures show that discrimination in healthcare is still persistent in the European Union. Research has confirmed these results but focused mainly on the outcomes of perceived discrimination. Studies that take into account socioeconomic determinants of discrimination limit themselves to either ethnicity, income or education. This article explores the influence of several socioeconomic indicators (e.g. gender, age, income, education and ethnicity) on perceived discrimination in 30 European countries. Data from the QUALICOPC study were used. These data were collected between October 2011 and December 2013 in the participating countries. In total, 7183 GPs (general practitioners) and 61932 patients participated in the study, which had an average response rate of 74.1%. Data collection was co-ordinated by NIVEL (Dutch Institute for Research of Health Care). Bivariate binomial logistic regressions were used to estimate the impact of each socioeconomic indicator on perceived discrimination. Multivariate logistic regressions were used to estimate the unique effect of each indicator. Results indicate that in Europe, overall 7% of the respondents felt discriminated, ranging between 1.4% and 12.8% at the country level. With regard to socioeconomic determinants in perceived discrimination, income and age are both important indicators, with lower income groups and younger people having a higher chance to feel discriminated. In addition, we find significant influences of education, gender, age and ethnicity in several countries. In most countries, higher educated people, older people, women and the indigenous population appeared to feel less discriminated. In conclusion, perceived discrimination in healthcare is reported in almost all European countries, but there is large variation between European countries. A high prevalence of perceived discrimination within a country also does not imply a correlation between socioeconomic indicators and perceived discrimination. © 2016 John Wiley & Sons Ltd.

Fully optimized discrimination of physiological responses to auditory stimuli

PubMed Central

Kruglikov, Stepan Y; Chari, Sharmila; Rapp, Paul E; Weinstein, Steven L; Given, Barbara K; Schiff, Steven J

2008-01-01

The use of multivariate measurements to characterize brain activity (electrical, magnetic, optical) is widespread. The most common approaches to reduce the complexity of such observations include principal and independent component analyses (PCA and ICA), which are not well suited for discrimination tasks. We addressed two questions: first, how do the neurophysiological responses to elongated phonemes relate to tone and phoneme responses in normal children, and, second, how discriminable are these responses. We employed fully optimized linear discrimination analysis to maximally separate the multi-electrode responses to tones and phonemes, and classified the response to elongated phonemes. We find that discrimination between tones and phonemes is dependent upon responses from associative regions of the brain apparently distinct from the primary sensory cortices typically emphasized by PCA or ICA, and that the neuronal correlates corresponding to elongated phonemes are highly variable in normal children (about half respond with neural correlates of tones and half as phonemes). Our approach is made feasible by the increase in computational power of ordinary personal computers and has significant advantages for a wide range of neuronal imaging modalities. PMID:18430975

Racism, other discriminations and effects on health.

PubMed

Gil-González, Diana; Vives-Cases, Carmen; Borrell, Carme; Agudelo-Suárez, Andrés A; Davó-Blanes, Mari Carmen; Miralles, Juanjo; Álvarez-Dardet, Carlos

2014-04-01

We study the probability of perceived racism/other forms of discrimination on immigrant and Spanish populations within different public spheres and show their effect on the health of immigrants using a cross-sectional design (ENS-06). perceived racism/other forms of discrimination (exposure), socio-demographic (explicative), health indicators (dependent). Frequencies, prevalences, and bivariate/multivariate analysis were conducted separately for men (M) and women (W). We estimated the health problems attributable to racism through the population attributable proportion (PAP). Immigrants perceived more racism than Spaniards in workplace (ORM = 48.1; 95% CI 28.2-82.2), and receiving health care (ORW = 48.3; 95% CI 24.7-94.4). Racism and other forms of discrimination were associated with poor mental health (ORM = 5.6; 95% CI 3.9-8.2; ORW = 7.3; 95% CI 4.1-13.0) and injury (ORW = 30.6; 95% CI 13.6-68.7). It is attributed to perceived racism the 80.1% of consumption of psychotropics (M), and to racism with other forms of discrimination the 52.3% of cases of injury (W). Racism plays a role as a health determinant.

Screening analysis of biodiesel feedstock using UV-vis, NIR and synchronous fluorescence spectrometries and the successive projections algorithm.

PubMed

Insausti, Matías; Gomes, Adriano A; Cruz, Fernanda V; Pistonesi, Marcelo F; Araujo, Mario C U; Galvão, Roberto K H; Pereira, Claudete F; Band, Beatriz S F

2012-08-15

This paper investigates the use of UV-vis, near infrared (NIR) and synchronous fluorescence (SF) spectrometries coupled with multivariate classification methods to discriminate biodiesel samples with respect to the base oil employed in their production. More specifically, the present work extends previous studies by investigating the discrimination of corn-based biodiesel from two other biodiesel types (sunflower and soybean). Two classification methods are compared, namely full-spectrum SIMCA (soft independent modelling of class analogies) and SPA-LDA (linear discriminant analysis with variables selected by the successive projections algorithm). Regardless of the spectrometric technique employed, full-spectrum SIMCA did not provide an appropriate discrimination of the three biodiesel types. In contrast, all samples were correctly classified on the basis of a reduced number of wavelengths selected by SPA-LDA. It can be concluded that UV-vis, NIR and SF spectrometries can be successfully employed to discriminate corn-based biodiesel from the two other biodiesel types, but wavelength selection by SPA-LDA is key to the proper separation of the classes. Copyright © 2012 Elsevier B.V. All rights reserved.

Perceived discrimination, family functioning, and depressive symptoms among immigrant women in Taiwan.

PubMed

Yang, Hao-Jan; Wu, Jyun-Yi; Huang, Sheng-Shiung; Lien, Mei-Huei; Lee, Tony Szu-Hsien

2014-10-01

This study examined the moderating effect of family functioning on the relationship between perceived discrimination and depressive symptoms in immigrant women. A total of 239 immigrant women were selected from four administrative regions in Central Taiwan. Questionnaires concerning perceived discrimination, family functioning (including family cohesion and family adaptability), depressive symptoms, and demographic characteristics were completed by either women themselves (N = 120) or their husbands (N = 119). The moderating effect of family functioning on the relationship between perceived discrimination and depression symptoms was analyzed using multiple regression analysis. Findings showed that a higher level of perceived discrimination among immigrant women is associated with more severe depressive symptoms. Family functioning serves as a moderator between the relationship of perceived discrimination and depressive symptoms, but the moderating effect of family adaptability was evident only in data reported by immigrant women. The results indicate that perceived discrimination has negative mental health implications, and also point to the importance of family functioning for depression. Findings suggest that providers should consider addressing immigrant women's mental health needs through declining their psychosocial distress at multiple ecological levels.

The association between discrimination and PTSD in African Americans: exploring the role of gender.

PubMed

Brooks Holliday, Stephanie; Dubowitz, Tamara; Haas, Ann; Ghosh-Dastidar, Bonnie; DeSantis, Amy; Troxel, Wendy M

2018-02-28

Research has demonstrated the adverse impact that discrimination has on physical and mental health. However, few studies have examined the association between discrimination and symptoms of posttraumatic stress disorder (PTSD). There is evidence that African Americans experience higher rates of PTSD and are more likely to develop PTSD following trauma exposure than Whites, and discrimination may be one reason for this disparity. To examine the association between discrimination and PTSD among a cross-sectional sample largely comprising African American women, controlling for other psychosocial stressors (psychological distress, neighborhood safety, crime). A sample of 806 participants was recruited from two low-income predominantly African American neighborhoods. Participants completed self-report measures of PTSD symptoms, perceived discrimination, perceived safety, and psychological distress. Information on neighborhood crime was obtained through data requested from the city. Multivariate linear regression models were estimated to assess adjusted relationships between PTSD symptoms and discrimination. Discrimination was significantly associated with PTSD symptoms with a small effect size, controlling for relevant sociodemographic variables. This association remained consistent after controlling for psychological distress, perceived safety, and total neighborhood crime. There was no evidence of a gender by discrimination interaction. Participants who experienced any discrimination were significantly more likely to screen positive for PTSD. Discrimination may contribute to the disparate rates of PTSD experienced by African Americans. PTSD is associated with a range of negative consequences, including poorer physical health, mental health, and quality of life. These results suggest the importance of finding ways to promote resilience in this at-risk population.

Discrimination, Mental Health, and Substance Use Disorders Among Sexual Minority Populations

PubMed Central

Lee, Ji Hyun; Gamarel, Kristi E.; Bryant, Kendall J.; Zaller, Nickolas D.

2016-01-01

Abstract Purpose: Sexual minority (lesbian, gay, bisexual) populations have a higher prevalence of mental health and substance use disorders compared to their heterosexual counterparts. Such disparities have been attributed, in part, to minority stressors, including distal stressors such as discrimination. However, few studies have examined associations between discrimination, mental health, and substance use disorders by gender among sexual minority populations. Methods: We analyzed data from 577 adult men and women who self-identified as lesbian, gay, or bisexual and participated in Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Six questions assessed discrimination due to sexual orientation. Weighted multivariable logistic regression examined associations between experiences of sexual orientation discrimination and both mental health and substance use disorders. Analyses were conducted separately for sexual minority men and women, adjusting for sociodemographic covariates. Results: Sexual minority men who ever experienced discrimination (57.4%) reported higher odds of any lifetime drug use disorder and cannabis use disorder compared to sexual minority men who never experienced discrimination. Sexual minority women who ever experienced discrimination (42.9%) reported higher odds of any lifetime mood disorder and any lifetime anxiety disorder compared to sexual minority women who never experienced discrimination. Conclusion: The findings suggest that discrimination is differentially associated with internalizing (mental health) and externalizing (substance use) disorders for sexual minority men and women. These findings indicate a need to consider how homophobia and heteronormative discrimination may contribute to distinct health outcomes for lesbian and bisexual women compared with gay and bisexual men. PMID:27383512

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.

Perceived Discrimination and Health among Immigrants in Europe According to National Integration Policies

PubMed Central

Borrell, Carme; Palència, Laia; Bartoll, Xavier; Ikram, Umar; Malmusi, Davide

2015-01-01

Background: Discrimination harms immigrants’ health. The objective of this study was to analyze the association between perceived discrimination and health outcomes among first and second generation immigrants from low-income countries living in Europe, while accounting for sex and the national policy on immigration. Methods: Cross-sectional study including immigrants from low-income countries aged ≥15 years in 18 European countries (European Social Survey, 2012) (sample of 1271 men and 1335 women). The dependent variables were self-reported health, symptoms of depression, and limitation of activity. The independent variables were perceived group discrimination, immigrant background and national immigrant integration policy. We tested for association between perceived group discrimination and health outcomes by fitting robust Poisson regression models. Results: We only observed significant associations between perceived group discrimination and health outcomes in first generation immigrants. For example, depression was associated with discrimination among both men and women (Prevalence Ratio-, 1.55 (95% CI: 1.16–2.07) and 1.47 (95% CI: 1.15–1.89) in the multivariate model, respectively), and mainly in countries with assimilationist immigrant integration policies. Conclusion: Perceived group discrimination is associated with poor health outcomes in first generation immigrants from low-income countries who live in European countries, but not among their descendants. These associations are more important in assimilationist countries. PMID:26334284

The Link Between Everyday Discrimination, Healthcare Utilization, and Health Status Among a National Sample of Women.

PubMed

Fazeli Dehkordy, Soudabeh; Hall, Kelli S; Dalton, Vanessa K; Carlos, Ruth C

2016-10-01

Research has not adequately examined the potential negative effects of perceiving routine discrimination on general healthcare utilization or health status, especially among reproductive-aged women. We sought to evaluate the association between everyday discrimination, health service use, and perceived health among a national sample of women in the United States. Data were drawn from the Women's Healthcare Experiences and Preferences survey, a randomly selected, national probability sample of 1078 U.S. women aged 18-55 years. We examined associations between everyday discrimination (via a standardized scale) on frequency of health service utilization and perceived general health status using chi-square and multivariable logistic regression modeling. Compared with women who reported healthcare visits every 3 years or less (reference group), each one-point increase in discrimination score was associated with higher odds of having healthcare visits annually or more often (odds ratio [OR] = 1.36, confidence interval [95% CI] = 1.01-1.83). Additionally, each one-point increase in discrimination score was significantly associated with lower odds of having excellent/very good perceived health (OR = 0.65; 95% CI = 0.54-0.80). Perceived discrimination was associated with increased exposure to the healthcare setting among this national sample of women. Perceived discrimination was also inversely associated with excellent/very good perceived health status.

Predictors of experiences of discrimination and positive treatment in people with mental health problems: findings from an Australian national survey.

PubMed

Reavley, Nicola J; Morgan, Amy J; Jorm, Anthony F

2017-03-01

The aim of the study was to assess the factors predicting experiences of avoidance, discrimination and positive treatment in people with mental health problems. In 2014, telephone interviews were carried out with 5220 Australians aged 18+, 1381 of whom reported a mental health problem or scored highly on a symptom screening questionnaire. Questions covered experiences of avoidance, discrimination and positive treatment by friends, spouse, other family, workplace, educational institution and others in the community; as well as disclosure of mental health problems. Avoidance, discrimination and positive treatment scores were calculated by counting the number of domains in which each occurred. Predictors of avoidance, discrimination and positive treatment were modelled with negative binomial regression analyses. After adjusting for the effects of other predictors in multivariate analyses, symptom severity and a diagnosis of 'any other disorder' (most commonly psychotic disorders or eating disorders) predicted experiences of both avoidance and discrimination but not positive treatment. Disclosing a mental health problem in more settings was also associated with higher rates of avoidance and discrimination, but also with positive treatment. Disclosure of mental health problems to others may increases experiences of discrimination, but may also increase experiences of positive treatment. These findings can help to inform decision making by people with mental health problems about disclosure, particularly in the case of more severe or low-prevalence disorders.

Racial discrimination and relationship functioning among African American couples.

PubMed

Lavner, Justin A; Barton, Allen W; Bryant, Chalandra M; Beach, Steven R H

2018-05-21

Racial discrimination is a common stressor for African Americans, with negative consequences for mental and physical well-being. It is likely that these effects extend into the family, but little research has examined the association between racial discrimination and couple functioning. This study used dyadic data from 344 rural, predominantly low-income heterosexual African American couples with an early adolescent child to examine associations between self-reported racial discrimination, psychological and physical aggression, and relationship satisfaction and instability. Experiences of discrimination were common among men and women and were negatively associated with relationship functioning. Specifically, men reported higher levels of psychological aggression and relationship instability if they experienced higher levels of racial discrimination, and women reported higher levels of physical aggression if they experienced higher levels of racial discrimination. All results replicated when controlling for financial hardship, indicating unique effects for discrimination. Findings suggest that racial discrimination may be negatively associated with relationship functioning among African Americans and call for further research on the processes underlying these associations and their long-term consequences. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A multivariate study of mangrove morphology (Rhizophora mangle) using both above and below-water plant architecture

USGS Publications Warehouse

Brooks, R.A.; Bell, S.S.

2005-01-01

A descriptive study of the architecture of the red mangrove, Rhizophora mangle L., habitat of Tampa Bay, FL, was conducted to assess if plant architecture could be used to discriminate overwash from fringing forest type. Seven above-water (e.g., tree height, diameter at breast height, and leaf area) and 10 below-water (e.g., root density, root complexity, and maximum root order) architectural features were measured in eight mangrove stands. A multivariate technique (discriminant analysis) was used to test the ability of different models comprising above-water, below-water, or whole tree architecture to classify forest type. Root architectural features appear to be better than classical forestry measurements at discriminating between fringing and overwash forests but, regardless of the features loaded into the model, misclassification rates were high as forest type was only correctly classified in 66% of the cases. Based upon habitat architecture, the results of this study do not support a sharp distinction between overwash and fringing red mangrove forests in Tampa Bay but rather indicate that the two are architecturally undistinguishable. Therefore, within this northern portion of the geographic range of red mangroves, a more appropriate classification system based upon architecture may be one in which overwash and fringing forest types are combined into a single, "tide dominated" category. ?? 2005 Elsevier Ltd. All rights reserved.

Physical victimization, gender identity and suicide risk among transgender men and women.

PubMed

Barboza, Gia Elise; Dominguez, Silvia; Chance, Elena

2016-12-01

We investigated whether being attacked physically due to one's gender identity or expression was associated with suicide risk among trans men and women living in Virginia. The sample consisted of 350 transgender men and women who participated in the Virginia Transgender Health Initiative Survey (THIS). Multivariate multinomial logistic regression was used to explore the competing outcomes associated with suicidal risk. Thirty-seven percent of trans men and women experienced at least one physical attack since the age of 13. On average, individuals experienced 3.97 (SD = 2.86) physical attacks; among these about half were attributed to one's gender identity or expression (mean = 2.08, SD = 1.96). In the multivariate multinomial regression, compared to those with no risk, being physically attacked increased the odds of both attempting and contemplating suicide regardless of gender attribution. Nevertheless, the relative impact of physical victimization on suicidal behavior was higher among those who were targeted on the basis of their gender identity or expression. Finally, no significant association was found between multiple measures of institutional discrimination and suicide risk once discriminatory and non-discriminatory physical victimization was taken into account. Trans men and women experience high levels of physical abuse and face multiple forms of discrimination. They are also at an increased risk for suicidal tendencies. Interventions that help transindividuals cope with discrimination and physical victimization simultaneously may be more effective in saving lives.

Esophageal cancer detection based on tissue surface-enhanced Raman spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Chen, Weisheng; Wang, Yue; Chen, Rong; Zeng, Haishan

2013-01-01

The capability of using silver nanoparticle based near-infrared surface enhanced Raman scattering (SERS) spectroscopy combined with principal component analysis (PCA) and linear discriminate analysis (LDA) to differentiate esophageal cancer tissue from normal tissue was presented. Significant differences in Raman intensities of prominent SERS bands were observed between normal and cancer tissues. PCA-LDA multivariate analysis of the measured tissue SERS spectra achieved diagnostic sensitivity of 90.9% and specificity of 97.8%. This exploratory study demonstrated great potential for developing label-free tissue SERS analysis into a clinical tool for esophageal cancer detection.

[Effect of angiotensin II depot administration on bioelectric functional processes of the central nervous system].

PubMed

Martin, G; Baumann, H; Grieger, F

1976-01-01

Using the average evoked potential technique, angiotensin-II depot effects (1 mg implantate = 3--4 mg/kg body weight angiotensin-II) were studied neuroelectrophysiologically in reticular, hippocampal and neocrotical structures of albino rats. A multivariate variance and discriminance analysis program revealed differentiated changes of the bioelectrical processing data of the CNS. Evidence was obtained for a varying structural sensitivity of central-nervous substructures under depot administration of angiotensin-II. In later phases of angiotensin-II action, the hippocampus was characterized by an electrographic synchronization phenomenon with high-amplitude average evoked potentials. The reticular formation, and to a lesser extent the visual cortex, showed an angiotensin-induced diminution of bioelectrical excitation. However, the intensity of the change in functional CNS patterns did not always correlate with maximal blood pressure rises. The described changes of afference processing to standardized sensory stimuli, especially in hippocampal and reticular structures of the CNS foll owing angiotensin depot action, point to a central-nervous action mechanism of angiotensin-II.

Two traditional maize inbred lines of contrasting technological abilities are discriminated by the seed flour proteome.

PubMed

Pinheiro, Carla; Sergeant, Kjell; Machado, Cátia M; Renaut, Jenny; Ricardo, Cândido P

2013-07-05

The seed proteome of two traditional maize inbred lines (pb269 and pb369) contrasting in grain hardness and in preferable use for bread-making was evaluated. The pb269 seeds, of flint type (i.e., hard endosperm), are preferably used by manufacturers, while pb369 (dent, soft endosperm) is rejected. The hypothesis that the content and relative amounts of specific proteins in the maize flour are relevant for such discrimination of the inbred lines was tested. The flour proteins were sequentially extracted following the Osborne fractionation (selective solubilization), and the four Osborne fractions were submitted to two-dimensional electrophoresis (2DE). The total amount of protein extracted from the seeds was not significantly different, but pb369 flour exhibited significantly higher proportions of salt-extracted proteins (globulins) and ethanol-extracted proteins (alcohol-soluble prolamins). The proteome analysis allowed discrimination between the two inbred lines, with pb269 demonstrating higher heterogeneity than pb369. From the 967 spots (358 common to both lines, 208 specific to pb269, and 401 specific to pb369), 588 were submitted to mass spectrometry (MS). Through the combined use of trypsin and chymotrypsin it was possible to identify proteins in 436 spots. The functional categorization in combination with multivariate analysis highlighted the most discriminant biological processes (carbohydrate metabolic process, response to stress, chitin catabolic process, oxidation-reduction process) and molecular function (nutrient reservoir activity). The inbred lines exhibited quantitative and qualitative differences in these categories. Differences were also revealed in the amounts, proportions, and distribution of several groups of storage proteins, which can have an impact on the organization of the protein body and endosperm hardness. For some proteins (granule-bound starch synthase-1, cyclophilin, zeamatin), a change in the protein solubility rather than in the total amount extracted was observed, which reveals distinct in vivo associations and/or changes in binding strength between the inbred lines. Our approach produced information that relates protein content, relative protein content, and specific protein types to endosperm hardness and to the preferable use for "broa" bread-making.

Multivariate Analyses of Rotator Cuff Pathologies in Shoulder Disability

PubMed Central

Henseler, Jan F.; Raz, Yotam; Nagels, Jochem; van Zwet, Erik W.; Raz, Vered; Nelissen, Rob G. H. H.

2015-01-01

Background Disability of the shoulder joint is often caused by a tear in the rotator cuff (RC) muscles. Four RC muscles coordinate shoulder movement and stability, among them the supraspinatus and infraspinatus muscle which are predominantly torn. The contribution of each RC muscle to tear pathology is not fully understood. We hypothesized that muscle atrophy and fatty infiltration, features of RC muscle degeneration, are predictive of superior humeral head translation and shoulder functional disability. Methods Shoulder features, including RC muscle surface area and fatty infiltration, superior humeral translation and RC tear size were obtained from a consecutive series of Magnetic Resonance Imaging with arthrography (MRA). We investigated patients with superior (supraspinatus, n = 39) and posterosuperior (supraspinatus and infraspinatus, n = 30) RC tears, and patients with an intact RC (n = 52) as controls. The individual or combinatorial contribution of RC measures to superior humeral translation, as a sign of RC dysfunction, was investigated with univariate or multivariate models, respectively. Results Using the univariate model the infraspinatus surface area and fatty infiltration in both the supraspinatus and infraspinatus had a significant contribution to RC dysfunction. With the multivariate model, however, the infraspinatus surface area only affected superior humeral translation (p<0.001) and discriminated between superior and posterosuperior tears. In contrast neither tear size nor fatty infiltration of the supraspinatus or infraspinatus contributed to superior humeral translation. Conclusion Our study reveals that infraspinatus atrophy has the strongest contribution to RC tear pathologies. This suggests a pivotal role for the infraspinatus in preventing shoulder disability. PMID:25710703

Relations between Cardiac and Visual Phenotypes in Diabetes: A Multivariate Approach.

PubMed

Oliveiros, Bárbara; Sanches, Mafalda; Quendera, Bruno; Graça, Bruno; Guelho, Daniela; Gomes, Leonor; Carrilho, Francisco; Caseiro-Alves, Filipe; Castelo-Branco, Miguel

2016-01-01

Cardiovascular disease and diabetes represent a major public health concern. The former is the most frequent cause of death and disability in patients with type 2 diabetes, where left ventricular dysfunction is highly prevalent. Moreover, diabetic retinopathy is becoming a dominant cause of visual impairment and blindness. The complex relation between cardiovascular disease and diabetic retinopathy as a function of ageing, obesity and hypertension remains to be clarified. Here, we investigated such relations in patients with diabetes type 2, in subjects with neither overt heart disease nor advanced proliferative diabetic retinopathy. We studied 47 patients and 50 controls, aged between 45 and 65 years, equally distributed according to gender. From the 36 measures regarding visual structure and function, and the 11 measures concerning left ventricle function, we performed data reduction to obtain eight new derived variables, seven of which related to the eye, adjusted for age, gender, body mass index and high blood pressure using both discriminant analysis (DA) and logistic regression (LR). We found moderate to strong correlation between left ventricle function and the eye constructs: minimum correlation was found for psychophysical motion thresholds (DA: 0.734; LR: 0.666), while the maximum correlation was achieved with structural volume density in the neural retina (DA: 0.786; LR: 0.788). Controlling the effect of pairwise correlated visual constructs, the parameters that were most correlated to left ventricle function were volume density in retina and thickness of the retinal nerve fiber layers (adjusted multiple R2 is 0.819 and 0.730 for DA and LR), with additional contribution of psychophysical loss in achromatic contrast discrimination. We conclude that visual structural and functional changes in type 2 diabetes are related to heart dysfunction, when the effects of clinical, demographic and associated risk factors are taken into account, revealing a genuine relation between cardiac and retinal diabetic phenotypes.

Association between kidney function and genetic polymorphisms in atherosclerotic and chronic kidney diseases: A cross-sectional study in Japanese male workers

PubMed Central

Nakatochi, Masahiro; Yasuda, Yoshinari; Honda, Hiroyuki; Kuwatsuka, Yachiyo; Kato, Sawako; Kikuchi, Kyoko; Kondo, Takaaki; Iwata, Masamitsu; Nakashima, Toru; Yasui, Hiroshi; Takamatsu, Hideki; Okajima, Hiroshi; Yoshida, Yasuko; Maruyama, Shoichi

2017-01-01

Background Several single nucleotide polymorphisms (SNPs) have been implicated in the predisposition to chronic kidney disease (CKD). Atherosclerotic disease is deeply involved in the incidence of CKD; however, whether SNPs related to arteriosclerosis are involved in CKD remains unclear. This study aimed to identify SNPs associated with CKD and to examine whether risk allele accumulation is associated with CKD. Methods We conducted a cross-sectional study using data of 4814 male workers to examine the association between estimated glomerular filtration rate (eGFR) and 59 candidate polymorphisms (17 CKD, 42 atherosclerotic diseases). We defined the genetic risk score (GRS) as the total number of risk alleles that showed a significant association in this analysis and examined the relationship with CKD (eGFR < 60 ml/min/1.73m2). Multivariate logistic regression, discrimination by area under the receiver operating characteristic curve, integrated discrimination improvement (IDI), and category-free net reclassification improvement (cNRI) were evaluated. Results In total, 432 participants were categorized as having CKD. We found eight candidate SNPs with P value < 0.05 (CX3CR1 rs3732379, SHROOM3 rs17319721, MTP rs1800591, PIP5K1B rs4744712, APOA5 rs662799, BRAP rs3782886, SPATA5L1 rs2467853, and MCP1 rs1024611) in the multivariate linear regression adjusted for age, body mass index, systolic blood pressure, and fasting blood glucose. Among these eight SNPs, BRAP rs3782886 and SPATA5L1 rs2467853 were significantly associated with eGFR (false discovery rate < 0.05). GRS was significantly associated with CKD (odds ratio, 1.17; 95% confidence interval, 1.09–1.26). C-statisics improved from 0.775 to 0.780 but showed no statistical significance. However, adding GRS significantly improved IDI and cNRI (0.0057, P = 0.0028, and 0.212, P < 0.001, respectively). Conclusions After adjustment for clinical factors, kidney function was associated with BRAP rs3782886 and SPATA5L1 rs2467853 and the GRS for CKD that we developed was associated CKD. PMID:29016630

Association between kidney function and genetic polymorphisms in atherosclerotic and chronic kidney diseases: A cross-sectional study in Japanese male workers.

PubMed

Kubo, Yoko; Imaizumi, Takahiro; Ando, Masahiko; Nakatochi, Masahiro; Yasuda, Yoshinari; Honda, Hiroyuki; Kuwatsuka, Yachiyo; Kato, Sawako; Kikuchi, Kyoko; Kondo, Takaaki; Iwata, Masamitsu; Nakashima, Toru; Yasui, Hiroshi; Takamatsu, Hideki; Okajima, Hiroshi; Yoshida, Yasuko; Maruyama, Shoichi

2017-01-01

Several single nucleotide polymorphisms (SNPs) have been implicated in the predisposition to chronic kidney disease (CKD). Atherosclerotic disease is deeply involved in the incidence of CKD; however, whether SNPs related to arteriosclerosis are involved in CKD remains unclear. This study aimed to identify SNPs associated with CKD and to examine whether risk allele accumulation is associated with CKD. We conducted a cross-sectional study using data of 4814 male workers to examine the association between estimated glomerular filtration rate (eGFR) and 59 candidate polymorphisms (17 CKD, 42 atherosclerotic diseases). We defined the genetic risk score (GRS) as the total number of risk alleles that showed a significant association in this analysis and examined the relationship with CKD (eGFR < 60 ml/min/1.73m2). Multivariate logistic regression, discrimination by area under the receiver operating characteristic curve, integrated discrimination improvement (IDI), and category-free net reclassification improvement (cNRI) were evaluated. In total, 432 participants were categorized as having CKD. We found eight candidate SNPs with P value < 0.05 (CX3CR1 rs3732379, SHROOM3 rs17319721, MTP rs1800591, PIP5K1B rs4744712, APOA5 rs662799, BRAP rs3782886, SPATA5L1 rs2467853, and MCP1 rs1024611) in the multivariate linear regression adjusted for age, body mass index, systolic blood pressure, and fasting blood glucose. Among these eight SNPs, BRAP rs3782886 and SPATA5L1 rs2467853 were significantly associated with eGFR (false discovery rate < 0.05). GRS was significantly associated with CKD (odds ratio, 1.17; 95% confidence interval, 1.09-1.26). C-statisics improved from 0.775 to 0.780 but showed no statistical significance. However, adding GRS significantly improved IDI and cNRI (0.0057, P = 0.0028, and 0.212, P < 0.001, respectively). After adjustment for clinical factors, kidney function was associated with BRAP rs3782886 and SPATA5L1 rs2467853 and the GRS for CKD that we developed was associated CKD.

Perceived discrimination in health care and health status in a racially diverse sample.

PubMed

Hausmann, Leslie R M; Jeong, Kwonho; Bost, James E; Ibrahim, Said A

2008-09-01

Despite the surge of recent research on the association between perceived discrimination and health-related outcomes, few studies have focused on race-based discrimination encountered in health care settings. This study examined the prevalence of such discrimination, and its association with health status, for the 3 largest race/ethnic groups in the United States. Data were drawn from the 2004 Behavioral Risk Factor Surveillance System survey. The primary variables were perceived racial discrimination in health care and self-reported health status. Multivariable logistic regression was used to compare the prevalence of perceived discrimination for whites, African Americans, and Hispanics, and to examine the association between perceived discrimination and health status, controlling for sex, age, income, education, health care coverage, affordability of medical care, racial salience, and state. Perceived discrimination was reported by 2%, 5.2%, and 10.9% of whites, Hispanics, and African Americans, respectively. Only the difference between African Americans and whites remained significant in adjusted analyses [odds ratio (OR) = 3.22, 95% confidence interval (CI) = 2.46-4.21]. Racial/ethnic differences in perceived discrimination depended on income, education, health care coverage, and affordability of medical care. Perceived discrimination was associated with worse health status for the overall sample (OR = 1.71, 95% CI = 1.35-2.16). Stratified analyses revealed that this relationship was significant for whites (OR = 2.00, 95% CI = 1.45-2.77) and African Americans (OR = 1.95, 95% CI = 1.39-2.73), but not for Hispanics (OR = 0.55, 95% CI = 0.24-1.22). Perceived racial discrimination in health care is much more prevalent for African Americans than for whites or Hispanics. Furthermore, such discrimination is associated with worse health both for African Americans and for whites.

Racial/Ethnic Workplace Discrimination

PubMed Central

Chavez, Laura J.; Ornelas, India J.; Lyles, Courtney R.; Williams, Emily C.

2014-01-01

Background Experiences of discrimination are associated with tobacco and alcohol use, and work is a common setting where individuals experience racial/ethnic discrimination. Few studies have evaluated the association between workplace discrimination and these behaviors, and none have described associations across race/ethnicity. Purpose To examine the association between workplace discrimination and tobacco and alcohol use in a large, multistate sample of U.S. adult respondents to the Behavioral Risk Factor Surveillance System survey Reactions to Race Module (2004–2010). Methods Multivariable logistic regression analyses evaluated cross-sectional associations between self-reported workplace discrimination and tobacco (current and daily smoking) and alcohol use (any and heavy use, and binge drinking) among all participants and stratified by race/ethnicity, adjusting for relevant covariates. Data were analyzed in 2013. Results Among respondents, 70,080 completed the workplace discrimination measure. Discrimination was more common among black non-Hispanic (21%), Hispanic (12%), and other race respondents (11%) than white non-Hispanics (4%) (p<0.001). In the total sample, discrimination was associated with current smoking (risk ratio [RR]=1.32, 95% CI=1.19, 1.47), daily smoking (RR=1.41, 95% CI=1.24, 1.61), and heavy drinking (RR=1.11, 95% CI=1.01, 1.22), but not binge or any drinking. Among Hispanics, workplace discrimination was associated with increased heavy and binge drinking, but not any alcohol use or smoking. Workplace discrimination among black non-Hispanics and white Non-Hispanics was associated with increased current and daily smoking, but not alcohol outcomes. Conclusions Workplace discrimination is common, associated with smoking and alcohol use, and merits further policy attention given the impact of these behaviors on morbidity and mortality. PMID:25441232

Racial/ethnic workplace discrimination: association with tobacco and alcohol use.

PubMed

Chavez, Laura J; Ornelas, India J; Lyles, Courtney R; Williams, Emily C

2015-01-01

Experiences of discrimination are associated with tobacco and alcohol use, and work is a common setting where individuals experience racial/ethnic discrimination. Few studies have evaluated the association between workplace discrimination and these behaviors, and none have described associations across race/ethnicity. To examine the association between workplace discrimination and tobacco and alcohol use in a large, multistate sample of U.S. adult respondents to the Behavioral Risk Factor Surveillance System survey Reactions to Race Module (2004-2010). Multivariable logistic regression analyses evaluated cross-sectional associations between self-reported workplace discrimination and tobacco (current and daily smoking) and alcohol use (any and heavy use, and binge drinking) among all participants and stratified by race/ethnicity, adjusting for relevant covariates. Data were analyzed in 2013. Among respondents, 70,080 completed the workplace discrimination measure. Discrimination was more common among black non-Hispanic (21%), Hispanic (12%), and other race respondents (11%) than white non-Hispanics (4%) (p<0.001). In the total sample, discrimination was associated with current smoking (risk ratio [RR]=1.32, 95% CI=1.19, 1.47), daily smoking (RR=1.41, 95% CI=1.24, 1.61), and heavy drinking (RR=1.11, 95% CI=1.01, 1.22), but not binge or any drinking. Among Hispanics, workplace discrimination was associated with increased heavy and binge drinking, but not any alcohol use or smoking. Workplace discrimination among black non-Hispanics and white Non-Hispanics was associated with increased current and daily smoking, but not alcohol outcomes. Workplace discrimination is common, associated with smoking and alcohol use, and merits further policy attention, given the impact of these behaviors on morbidity and mortality. Copyright © 2015 American Journal of Preventive Medicine. All rights reserved.

Different faces of discrimination: perceived discrimination among homeless adults with mental illness in healthcare settings.

PubMed

Skosireva, Anna; O'Campo, Patricia; Zerger, Suzanne; Chambers, Catharine; Gapka, Susan; Stergiopoulos, Vicky

2014-09-07

Research on discrimination in healthcare settings has primarily focused on health implications of race-based discrimination among ethno-racial minority groups. Little is known about discrimination experiences of other marginalized populations, particularly groups facing multiple disadvantages who may be subjected to other/multiple forms of discrimination. (1) To examine the prevalence of perceived discrimination due to homelessness/poverty, mental illness/alcohol/drug related problems, and race/ethnicity/skin color while seeking healthcare in the past year among racially diverse homeless adults with mental illness; (2) To identify whether perceiving certain types of discrimination is associated with increased likelihood of perceiving other kinds of discrimination; and (3) To examine association of these perceived discrimination experiences with socio-demographic characteristics, self-reported measures of psychiatric symptomatology and substance use, and Emergency Department utilization. We used baseline data from the Toronto site of the At Home/Chez Soi randomized controlled trial of Housing First for homeless adults with mental illness (n = 550). Bivariate statistics and multivariable logistic regression models were used for the analysis. Perceived discrimination related to homelessness/poverty (30.4%) and mental illness/alcohol/substance use (32.5%) is prevalent among ethnically diverse homeless adults with mental illness in healthcare settings. Only 15% of the total participants reported discrimination due to race/ethnicity/skin color. After controlling for relevant confounders and presence of psychosis, all types of discrimination in healthcare settings were associated with more frequent ED use, a greater - 3 - severity of lifetime substance abuse, and mental health problems. Perceiving discrimination of one type was associated with increased likelihood of perceiving other kinds of discrimination. Understanding the experience of discrimination in healthcare settings and associated healthcare utilization is the first step towards designing policies and interventions to address health disparities among vulnerable populations. This study contributes to the knowledge base in this important area. This study has been registered with the International Standard Randomized Control Trial Number Register and assigned ISRCTN42520374.

Discrimination of high-Z materials in concrete-filled containers using muon scattering tomography

NASA Astrophysics Data System (ADS)

Frazão, L.; Velthuis, J.; Thomay, C.; Steer, C.

2016-07-01

An analysis method of identifying materials using muon scattering tomography is presented, which uses previous knowledge of the position of high-Z objects inside a container and distinguishes them from similar materials. In particular, simulations were performed in order to distinguish a block of Uranium from blocks of Lead and Tungsten of the same size, inside a concrete-filled drum. The results show that, knowing the shape and position from previous analysis, it is possible to distinguish 5 × 5 × 5 cm3 blocks of these materials with about 4h of muon exposure, down to 2 × 2 × 2 cm3 blocks with 70h of data using multivariate analysis (MVA). MVA uses several variables, but it does not benefit the discrimination over a simpler method using only the scatter angles. This indicates that the majority of discrimination is provided by the angular information. Momentum information is shown to provide no benefits in material discrimination.

Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics.

PubMed

Melucci, Dora; Bendini, Alessandra; Tesini, Federica; Barbieri, Sara; Zappi, Alessandro; Vichi, Stefania; Conte, Lanfranco; Gallina Toschi, Tullia

2016-08-01

At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between "100% Italian" and "non-100% Italian" oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined. Copyright © 2016. Published by Elsevier Ltd.

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.

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Gulgundi, Mohammad Shahid; Shetty, Amba

2018-03-01

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

Multivariate and Cladistic Analyses of Isolated Teeth Reveal Sympatry of Theropod Dinosaurs in the Late Jurassic of Northern Germany.

PubMed

Gerke, Oliver; Wings, Oliver

2016-01-01

Remains of theropod dinosaurs are very rare in Northern Germany because the area was repeatedly submerged by a shallow epicontinental sea during the Mesozoic. Here, 80 Late Jurassic theropod teeth are described of which the majority were collected over decades from marine carbonates in nowadays abandoned and backfilled quarries of the 19th century. Eighteen different morphotypes (A-R) could be distinguished and 3D models based on micro-CT scans of the best examples of all morphotypes are included as supplements. The teeth were identified with the assistance of discriminant function analysis and cladistic analysis based on updated datamatrices. The results show that a large variety of theropod groups were present in the Late Jurassic of northern Germany. Identified specimens comprise basal Tyrannosauroidea, as well as Allosauroidea, Megalosauroidea cf. Marshosaurus, Megalosauridae cf. Torvosaurus and probably Ceratosauria. The formerly reported presence of Dromaeosauridae in the Late Jurassic of northern Germany could not be confirmed. Some teeth of this study resemble specimens described as pertaining to Carcharodontosauria (morphotype A) and Abelisauridae (morphotype K). This interpretation is however, not supported by discriminant function analysis and cladistic analysis. Two smaller morphotypes (N and Q) differ only in some probably size-related characteristics from larger morphotypes (B and C) and could well represent juveniles of adult specimens. The similarity of the northern German theropods with groups from contemporaneous localities suggests faunal exchange via land-connections in the Late Jurassic between Germany, Portugal and North America.

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses.

PubMed

Bisele, Maria; Bencsik, Martin; Lewis, Martin G C; Barnett, Cleveland T

2017-01-01

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors' knowledge, this is the first study to optimise the development of a machine learning algorithm.

Morphological analysis of Trichomycterus areolatus Valenciennes, 1846 from southern Chilean rivers using a truss-based system (Siluriformes, Trichomycteridae)

PubMed Central

Colihueque, Nelson; Corrales, Olga; Yáñez, Miguel

2017-01-01

Abstract Trichomycterus areolatus Valenciennes, 1846 is a small endemic catfish inhabiting the Andean river basins of Chile. In this study, the morphological variability of three T. areolatus populations, collected in two river basins from southern Chile, was assessed with multivariate analyses, including principal component analysis (PCA) and discriminant function analysis (DFA). It is hypothesized that populations must segregate morphologically from each other based on the river basin that they were sampled from, since each basin presents relatively particular hydrological characteristics. Significant morphological differences among the three populations were found with PCA (ANOSIM test, r = 0.552, p < 0.0001) and DFA (Wilks’s λ = 0.036, p < 0.01). PCA accounted for a total variation of 56.16% by the first two principal components. The first Principal Component (PC1) and PC2 explained 34.72 and 21.44% of the total variation, respectively. The scatter-plot of the first two discriminant functions (DF1 on DF2) also validated the existence of three different populations. In group classification using DFA, 93.3% of the specimens were correctly-classified into their original populations. Of the total of 22 transformed truss measurements, 17 exhibited highly significant (p < 0.01) differences among populations. The data support the existence of T. areolatus morphological variation across different rivers in southern Chile, likely reflecting the geographic isolation underlying population structure of the species. PMID:29134012

Should Schools Expect Poor Physical and Mental Health, Social Adjustment, and Participation Outcomes in Students with Disability?

PubMed Central

Vaz, Sharmila; Cordier, Reinie; Falkmer, Marita; Ciccarelli, Marina; Parsons, Richard; McAuliffe, Tomomi; Falkmer, Torbjorn

2015-01-01

The literature on whether students with disabilities have worse physical and mental health, social adjustment, and participation outcomes when compared to their peers without disabilities is largely inconclusive. While the majority of case control studies showed significantly worse outcomes for students with disabilities; the proportion of variance accounted for is rarely reported. The current study used a population cross-sectional approach to determine the classification ability of commonly used screening and outcome measures in determining the disability status. Furthermore, the study aimed to identify the variables, if any, that best predicted the presence of disability. Results of univariate discriminant function analyses suggest that across the board, the sensitivity of the outcome/screening tools to correctly identify students with a disability was 31.9% higher than the related Positive Predictive Value (PPV). The lower PPV and Positive Likelihood Ratio (LR+) scores suggest that the included measures had limited discriminant ability (17.6% to 40.3%) in accurately identifying students at-risk for further assessment. Results of multivariate analyses suggested that poor health and hyperactivity increased the odds of having a disability about two to three times, while poor close perceived friendship and academic competences predicted disability with roughly the same magnitude. Overall, the findings of the current study highlight the need for researchers and clinicians to familiarize themselves with the psychometric properties of measures, and be cautious in matching the function of the measures with their research and clinical needs. PMID:25965845

Should schools expect poor physical and mental health, social adjustment, and participation outcomes in students with disability?

PubMed

Vaz, Sharmila; Cordier, Reinie; Falkmer, Marita; Ciccarelli, Marina; Parsons, Richard; McAuliffe, Tomomi; Falkmer, Torbjorn

2015-01-01

The literature on whether students with disabilities have worse physical and mental health, social adjustment, and participation outcomes when compared to their peers without disabilities is largely inconclusive. While the majority of case control studies showed significantly worse outcomes for students with disabilities; the proportion of variance accounted for is rarely reported. The current study used a population cross-sectional approach to determine the classification ability of commonly used screening and outcome measures in determining the disability status. Furthermore, the study aimed to identify the variables, if any, that best predicted the presence of disability. Results of univariate discriminant function analyses suggest that across the board, the sensitivity of the outcome/screening tools to correctly identify students with a disability was 31.9% higher than the related Positive Predictive Value (PPV). The lower PPV and Positive Likelihood Ratio (LR+) scores suggest that the included measures had limited discriminant ability (17.6% to 40.3%) in accurately identifying students at-risk for further assessment. Results of multivariate analyses suggested that poor health and hyperactivity increased the odds of having a disability about two to three times, while poor close perceived friendship and academic competences predicted disability with roughly the same magnitude. Overall, the findings of the current study highlight the need for researchers and clinicians to familiarize themselves with the psychometric properties of measures, and be cautious in matching the function of the measures with their research and clinical needs.

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses

PubMed Central

Bisele, Maria; Bencsik, Martin; Lewis, Martin G. C.

2017-01-01

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors’ knowledge, this is the first study to optimise the development of a machine learning algorithm. PMID:28886059

Default network connectivity decodes brain states with simulated microgravity.

PubMed

Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

2016-04-01

With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity.

A Quality Function Deployment Framework for the Service Quality of Health Information Websites

PubMed Central

Kim, Dohoon

2010-01-01

Objectives This research was conducted to identify both the users' service requirements on health information websites (HIWs) and the key functional elements for running HIWs. With the quality function deployment framework, the derived service attributes (SAs) are mapped into the suppliers' functional characteristics (FCs) to derive the most critical FCs for the users' satisfaction. Methods Using the survey data from 228 respondents, the SAs, FCs and their relationships were analyzed using various multivariate statistical methods such as principal component factor analysis, discriminant analysis, correlation analysis, etc. Simple and compound FC priorities were derived by matrix calculation. Results Nine factors of SAs and five key features of FCs were identified, and these served as the basis for the house of quality model. Based on the compound FC priorities, the functional elements pertaining to security and privacy, and usage support should receive top priority in the course of enhancing HIWs. Conclusions The quality function deployment framework can improve the FCs of the HIWs in an effective, structured manner, and it can also be utilized for critical success factors together with their strategic implications for enhancing the service quality of HIWs. Therefore, website managers could efficiently improve website operations by considering this study's results. PMID:21818418

Joint Entropy for Space and Spatial Frequency Domains Estimated from Psychometric Functions of Achromatic Discrimination

PubMed Central

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised. PMID:24466158

Joint entropy for space and spatial frequency domains estimated from psychometric functions of achromatic discrimination.

PubMed

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised.

Predicting Community College and University Student Success: A Test of the Triadic Reciprocal Model for Two Populations

ERIC Educational Resources Information Center

Heller, Monica L.; Cassady, Jerrell C.

2017-01-01

The current study explored the differential influences that behavioral learning strategies (i.e., cognitive-metacognitive, resource management), motivational profiles, and academic anxiety appraisals have on college-level learners in two unique learning contexts. Using multivariate analysis of variance and discriminant analysis, the study first…

Recoding Numerics to Geometrics for Complex Discrimination Tasks; A Feasibility Study of Coding Strategy.

ERIC Educational Resources Information Center

Simpkins, John D.

Processing complex multivariate information effectively when relational properties of information sub-groups are ambiguous is difficult for man and man-machine systems. However, the information processing task is made easier through code study, cybernetic planning, and accurate display mechanisms. An exploratory laboratory study designed for the…

Barriers to Gender Transition-Related Healthcare: Identifying Underserved Transgender Adults in Massachusetts

PubMed Central

White Hughto, Jaclyn M.; Rose, Adam J.; Pachankis, John E.; Reisner, Sari L.

2017-01-01

Abstract Purpose: The present study sought to examine whether individual (e.g., age, gender), interpersonal (e.g., healthcare provider discrimination), and structural (e.g., lack of insurance coverage) factors are associated with access to transition-related care in a statewide sample of transgender adults. Method: In 2013, 364 transgender residents of Massachusetts completed an electronic web-based survey online (87.1%) or in person (12.9%). A multivariable logistic regression model tested whether individual, interpersonal, and structural factors were associated with access to transition-related care. Results: Overall, 23.6% reported being unable to access transition-related care in the past 12 months. In a multivariable model, younger age, low income, low educational attainment, private insurance coverage, and healthcare discrimination were significantly associated with being unable to access transition-related care (all p<0.05). Discussion: Despite state nondiscrimination policies and universal access to healthcare, many of the Massachusetts transgender residents sampled were unable to access transition-related care. Multilevel interventions are needed, including supportive policies and policy enforcement, to ensure that underserved transgender adults can access medically necessary transition-related care. PMID:29082331

[Quality evaluation of American ginseng using UPLC coupled with multivariate analysis].

PubMed

Tang, Yan; Yan, Shu-Mo; Wang, Jing-Jing; Yuan, Yuan; Yang, Bin

2016-05-01

An ultra performance liquid chromatography (UPLC)method combined with multivariate data analysis was developed to evaluate the quality of American ginseng by simultaneously determining the concentrations of six ginsenosides (Rg₁, Re, Rb₁, Rc, Ro and Rd)in the samples. For UPLC, acetonitrile with 0.01% formic acid and water with 0.01% formic acid were used as the mobile phase with gradient elution. Under the established chromatographic conditions, the six ginsenosides could be well separated and the results of linearity, stability, precision, repeatability, and recovery rate all reached the requirement of quantification analysis, respectively. The total contents of Rg₁, Re, and Rb₁ in 57 samples all reached the requirement of the 2015 edition of Chinese Pharmacopoeia. At the same time, the experimental data were analyzed by principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The crude drugs and the decoction pieces can be discriminated by a PCA method and the samples with different age can be distinguished by a PLS-DA method. Copyright© by the Chinese Pharmaceutical Association.

Multielement geochemistry identifies the spatial pattern of soil and sediment contamination in an urban parkland, Western Australia.

PubMed

Rate, Andrew W

2018-06-15

Urban environments are dynamic and highly heterogeneous, and multiple additions of potential contaminants are likely on timescales which are short relative to natural processes. The likely sources and location of soil or sediment contamination in urban environment should therefore be detectable using multielement geochemical composition combined with rigorously applied multivariate statistical techniques. Soil, wetland sediment, and street dust was sampled along intersecting transects in Robertson Park in metropolitan Perth, Western Australia. Samples were analysed for near-total concentrations of multiple elements (including Cd, Ce, Co, Cr, Cu, Fe, Gd, La, Mn, Nd, Ni, Pb, Y, and Zn), as well as pH, and electrical conductivity. Samples at some locations within Robertson Park had high concentrations of potentially toxic elements (Pb above Health Investigation Limits; As, Ba, Cu, Mn, Ni, Pb, V, and Zn above Ecological Investigation Limits). However, these concentrations carry low risk due to the main land use as recreational open space, the low proportion of samples exceeding guideline values, and a tendency for the highest concentrations to be located within the less accessible wetland basin. The different spatial distributions of different groups of contaminants was consistent with different inputs of contaminants related to changes in land use and technology over the history of the site. Multivariate statistical analyses reinforced the spatial information, with principal component analysis identifying geochemical associations of elements which were also spatially related. A multivariate linear discriminant model was able to discriminate samples into a-priori types, and could predict sample type with 84% accuracy based on multielement composition. The findings suggest substantial advantages of characterising a site using multielement and multivariate analyses, an approach which could benefit investigations of other sites of concern. Copyright © 2018 Elsevier B.V. All rights reserved.

Racial Identity Matters: The Relationship between Racial Discrimination and Psychological Functioning in African American Adolescents

ERIC Educational Resources Information Center

Sellers, Robert M.; Copeland-Linder, Nikeea; Martin, Pamela P.; Lewis, R. L'Heureux

2006-01-01

This study examines the interrelationships among racial discrimination, racial identity, and psychological functioning in a sample of 314 African American adolescents. Racial discrimination was associated with lower levels of psychological functioning as measured by perceived stress, depressive symptomatology, and psychological well-being.…

Inflammatory biomarkers for persistent fatigue in breast cancer survivors.

PubMed

Collado-Hidalgo, Alicia; Bower, Julienne E; Ganz, Patricia A; Cole, Steve W; Irwin, Michael R

2006-05-01

This study seeks to define immunologic and inflammatory variables associated with persistent post-treatment fatigue in breast cancer survivors. Leukocyte subsets, plasma inflammatory markers, and ex vivo proinflammatory cytokine production were assessed in 50 fatigued and nonfatigued breast cancer survivors recruited > or = 2 years after successful primary therapy. Multivariate statistical analyses were used to define a composite immunologic biomarker of fatigue risk. Fatigued breast cancer survivors were distinguished from nonfatigued survivors by increased ex vivo monocyte production of interleukin (IL)-6 and tumor necrosis factor-alpha following lipopolysaccharide stimulation, elevated plasma IL-1ra and soluble IL-6 receptor (sIL-6R/CD126), decreased monocyte cell-surface IL-6R, and decreased frequencies of activated T lymphocytes and myeloid dendritic cells in peripheral blood (all P < 0.05). An inverse correlation between sIL-6R and cell-surface IL-6R was consistent with inflammation-mediated shedding of IL-6R, and in vitro studies confirmed that proinflammatory cytokines induced such shedding. Multivariate linear discriminant function analysis identified two immunologic markers, the ratio of sIL-6R to monocyte-associated IL-6R and decreased circulating CD69+ T lymphocytes, as highly diagnostic of fatigue (P = 0.0005), with cross-validation estimates indicating 87% classification accuracy (sensitivity = 0.83; specificity = 0.83). These results extend links between fatigue and inflammatory markers to show a functional alteration in proinflammatory cytokine response to lipopolysaccharide and define a prognostic biomarker of behavioral fatigue.

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.

Medical mistrust, perceived discrimination, and satisfaction with health care among young-adult rural latinos.

PubMed

López-Cevallos, Daniel F; Harvey, S Marie; Warren, Jocelyn T

2014-01-01

Little research has analyzed mistrust and discrimination influencing receipt of health care services among Latinos, particularly those living in rural areas. This study examined the associations between medical mistrust, perceived discrimination, and satisfaction with health care among young-adult rural Latinos. This cross-sectional study analyzed data from 387 young-adult Latinos (ages 18-25) living in rural Oregon. The Behavioral Model of Vulnerable Populations was utilized as the theoretical framework. Correlations were run to assess bivariate associations among variables included in the study. Ordered logistic regression models evaluated the associations between medical mistrust, perceived discrimination, and satisfaction with health care. On average, participants used health services 4 times in the past year. Almost half of the participants had health insurance (46%). The majority reported that they were moderately (32%) or very satisfied (41%) with health care services used in the previous year. In multivariable models, medical mistrust and perceived discrimination were significantly associated with satisfaction with health care. Medical mistrust and perceived discrimination were significant contributors to lower satisfaction with health care among young-adult Latinos living in rural Oregon. Health care reform implementation, currently under way, provides a unique opportunity for developing evaluation systems and interventions toward monitoring and reducing rural Latino health care disparities. © 2014 National Rural Health Association.

PERCEIVED WEIGHT DISCRIMINATION AMPLIFIES THE LINK BETWEEN CENTRAL ADIPOSITY AND NONDIABETIC GLYCEMIC CONTROL (HBA1C)

PubMed Central

Tsenkova, Vera K.; Carr, Deborah; Schoeller, Dale A.; Ryff, Carol D.

2010-01-01

Background While the preclinical development of type 2 diabetes is partly explained by obesity and central adiposity, psychosocial research has shown that chronic stressors such as discrimination have health consequences as well. Purpose We investigated the extent to which the well-established effects of obesity and central adiposity on nondiabetic glycemic control (indexed by HbA1c) were moderated by a targeted psychosocial stressor linked to weight: perceived weight discrimination. Methods Data came from the nondiabetic subsample (n=938) of the Midlife in the United States (MIDUS II) survey. Results Body mass index (BMI), waist-to-hip ratio, and waist circumference were linked to significantly higher HbA1c (p < .001). Multivariate-adjusted models showed that weight discrimination exacerbated the effects of waist-to-hip ratio on HbA1c ( p < .05), such that people who had higher WHR and reported weight discrimination had the highest HbA1c levels. Conclusions Understanding how biological and psychosocial factors interact at nondiabetic levels to increase vulnerability could have important implications for public health and education strategies. Effective strategies may include targeting sources of discrimination, rather than solely targeting health behaviors and practices of overweight and obese persons. PMID:21136227

Experiences of Transgender-Related Discrimination and Implications for Health: Results From the Virginia Transgender Health Initiative Study

PubMed Central

Reisner, Sari L.; Honnold, Julie A.; Xavier, Jessica

2013-01-01

Objectives. We examined relationships between social determinants of health and experiences of transgender-related discrimination reported by transgender people in Virginia. Methods. In 2005 through 2006, 387 self-identified transgender people completed a statewide health needs assessment; 350 who completed eligibility questions were included in this examination of factors associated with experiences of discrimination in health care, employment, or housing. We fit multivariate logistic regression models using generalized estimating equations to adjust for survey modality (online vs paper). Results. Of participants, 41% (n = 143) reported experiences of transgender-related discrimination. Factors associated with transgender-related discrimination were geographic context, gender (female-to male spectrum vs male-to-female spectrum), low socioeconomic status, being a racial/ethnic minority, not having health insurance, gender transition indicators (younger age at first transgender awareness), health care needed but unable to be obtained (hormone therapy and mental health services), history of violence (sexual and physical), substance use health behaviors (tobacco and alcohol), and interpersonal factors (family support and community connectedness). Conclusions. Findings suggest that transgender Virginians experience widespread discrimination in health care, employment, and housing. Multilevel interventions are needed for transgender populations, including legal protections and training for health care providers. PMID:23153142

Proof of Principle for a Real-Time Pathogen Isolation Media Diagnostic: The Use of Laser-Induced Breakdown Spectroscopy to Discriminate Bacterial Pathogens and Antimicrobial-Resistant Staphylococcus aureus Strains Grown on Blood Agar

PubMed Central

Multari, Rosalie A.; Cremers, David A.; Bostian, Melissa L.; Dupre, Joanne M.

2013-01-01

Laser-Induced Breakdown Spectroscopy (LIBS) is a rapid, in situ, diagnostic technique in which light emissions from a laser plasma formed on the sample are used for analysis allowing automated analysis results to be available in seconds to minutes. This speed of analysis coupled with little or no sample preparation makes LIBS an attractive detection tool. In this study, it is demonstrated that LIBS can be utilized to discriminate both the bacterial species and strains of bacterial colonies grown on blood agar. A discrimination algorithm was created based on multivariate regression analysis of spectral data. The algorithm was deployed on a simulated LIBS instrument system to demonstrate discrimination capability using 6 species. Genetically altered Staphylococcus aureus strains grown on BA, including isogenic sets that differed only by the acquisition of mutations that increase fusidic acid or vancomycin resistance, were also discriminated. The algorithm successfully identified all thirteen cultures used in this study in a time period of 2 minutes. This work provides proof of principle for a LIBS instrumentation system that could be developed for the rapid discrimination of bacterial species and strains demonstrating relatively minor genomic alterations using data collected directly from pathogen isolation media. PMID:24109513

Experiences of racial discrimination and relation to sexual risk for HIV among a sample of urban black and African American men.

PubMed

Reed, E; Santana, M C; Bowleg, L; Welles, S L; Horsburgh, C R; Raj, A

2013-04-01

This study aimed to examine racial discrimination and relation to sexual risk for HIV among a sample of urban black and African American men. Participants of this cross-sectional study were black and African American men (N = 703) between the ages of 18 and 65 years, recruited from four urban clinical sites in the northeast. Multivariate logistic regression models were used to analyze the relation of reported racial discrimination to the following: (1) sex trade involvement, (2) recent unprotected sex, and (3) reporting a number of sex partners in the past 12 months greater than the sample average. The majority of the sample (96%) reported racial discrimination. In adjusted analyses, men reporting high levels of discrimination were significantly more likely to report recent sex trade involvement (buying and/or selling) (adjusted odds ratio (AOR) range = 1.7-2.3), having recent unprotected vaginal sex with a female partner (AOR = 1.4, 95% confidence interval (CI), 1.1-2.0), and reporting more than four sex partners in the past year (AOR = 1.4, 95% CI, 1.1-1.9). Findings highlight the link between experiences of racial discrimination and men's sexual risk for HIV.

Sex assessment using clavicle measurements: inter- and intra-population comparisons.

PubMed

Králík, Miroslav; Urbanová, Petra; Wagenknechtová, Martina

2014-01-01

We studied sexual dimorphism of the human clavicle in order to describe size variation and create population-specific discriminant tools for morphometric sex assessment. The studied sample consisted of 200 skeletons of adult individuals obtained from the University of Athens Human Skeletal Reference Collection, Athens, Greece. The specimens were well-documented and represented a modern population from cemeteries in the Athens area. Six dimensions typically used for clavicle measurements were recorded. For sexing clavicles, we used both traditional univariate (limiting, demarking and sectioning points) and multivariate discriminant function analysis. The accuracy of the best five classification equations/functions ranged from 91.62% to 92.55% of correctly assigned specimens. By testing new and previously published sexing functions (Greeks, Polynesians, Guatemalans) on four available population samples (English, Indians from Amritsar, Indians from Varanasi, and data from the present study) we found that, for some combinations of tested and reference samples, the accuracy of the sex assessment may decrease even below the probability given by random sex assignment. Therefore, measurements of the clavicle should not be used for sex assessment of individual cases (both forensic and archeological) whose population origin is unknown. However, significant metric differences were also recorded among three different Greek samples (i.e. within a population). As a consequence, application of a sexing method generated from one Greek sample and applied to another Greek sample led to negligible reduction in the success of sex assessment, despite general similarities in ethnic origin (Greeks), generation structure and presumed social background of the samples. Therefore, we believe that future studies should focus on understanding the nature of the differences among within-population reference samples. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

[Development of the Spanish brief-version of the University of California Performance Skills Assessment (Sp-UPSA-Brief) in patients with schizophrenia and bipolar disorder].

PubMed

Garcia-Portilla, María Paz; Gomar, Jesús; Bobes-Bascaran, María Teresa; Menendez-Miranda, Isabel; Saiz, Pilar Alejandra; Muñiz, José; Arango, Celso; Patterson, Thomas; Harvey, Philip; Bobes, Julio; Goldberg, Terry

2014-01-01

In patients with severe mental disorders outcome measurement should include symptoms, cognition, functioning and quality of life at least. Shorter and efficient instruments have greater potential for pragmatic and valid clinical utility. Our aim was to develop the Spanish UPSA Brief scale (Sp-UPSA-Brief). Naturalistic, 6-month follow-up, multicentre study. 139 patients with schizophrenia, 57 with bipolar disorder and 31 controls were evaluated using the Sp-UPSA, CGI-S, GAF, and PSP. We conducted a multivariate linear regression model to identify candidate subscales for the Sp-UPSA-Brief. The stepwise regression model for patients with schizophrenia showed that communication and transportation Sp-UPSA subscales entered first and second at p<0.0001 (R(2)=0.88, model df=2, F=395.05). In patients with bipolar disorder transportation and communication Sp-UPSA subscales entered first and second at p<0.0001 (R(2)=0.87, model df=2, F=132.32). Cronbach's alpha was 0.78 in schizophrenia and 0.64 in bipolar patients. Test-retest was 0.66 and 0.64 (p<0.0001) respectively. Pearson correlation coefficients between Sp-UPSA and Sp-UPSA-Brief were 0.93 for schizophrenia and 0.92 for bipolar patients (p<0.0001).The Sp-UPSA-Brief discriminated between patients and controls. In schizophrenia patients it also discriminated among different levels of illness severity according to CGI-S scores. The Sp-UPSA-Brief is an alternate instrument to evaluate functional capacity that is valid and reliable. Having a shorter instrument makes it more feasible to assess functional capacity in patients with severe mental disorders, especially in everyday clinical practice. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Requiring collaboration: Hippocampal-prefrontal networks needed in spatial working memory and ageing. A multivariate analysis approach.

PubMed

Zancada-Menendez, C; Alvarez-Suarez, P; Sampedro-Piquero, P; Cuesta, M; Begega, A

2017-04-01

Ageing is characterized by a decline in the processes of retention and storage of spatial information. We have examined the behavioural performance of adult rats (3months old) and aged rats (18months old) in a spatial complex task (delayed match to sample). The spatial task was performed in the Morris water maze and consisted of three sessions per day over a period of three consecutive days. Each session consisted of two trials (one sample and retention) and inter-session intervals of 5min. Behavioural results showed that the spatial task was difficult for middle aged group. This worse execution could be associated with impairments of processing speed and spatial information retention. We examined the changes in the neuronal metabolic activity of different brain regions through cytochrome C oxidase histochemistry. Then, we performed MANOVA and Discriminant Function Analyses to determine the functional profile of the brain networks that are involved in the spatial learning of the adult and middle-aged groups. This multivariate analysis showed two principal functional networks that necessarily participate in this spatial learning. The first network was composed of the supramammillary nucleus, medial mammillary nucleus, CA3, and CA1. The second one included the anterior cingulate, prelimbic, and infralimbic areas of the prefrontal cortex, dentate gyrus, and amygdala complex (basolateral l and central subregions). There was a reduction in the hippocampal-supramammilar network in both learning groups, whilst there was an overactivation in the executive network, especially in the aged group. This response could be due to a higher requirement of the executive control in a complex spatial memory task in older animals. Copyright © 2017 Elsevier Inc. All rights reserved.

Functional hyperconnectivity vanishes in children with developmental dyscalculia after numerical intervention.

PubMed

Michels, Lars; O'Gorman, Ruth; Kucian, Karin

2018-04-01

Developmental dyscalculia (DD) is a developmental learning disability associated with deficits in processing numerical and mathematical information. Although behavioural training can reduce these deficits, it is unclear which neuronal resources show a functional reorganization due to training. We examined typically developing (TD) children (N=16, mean age: 9.5 years) and age-, gender-, and handedness-matched children with DD (N=15, mean age: 9.5 years) during the performance of a numerical order task with fMRI and functional connectivity before and after 5-weeks of number line training. Using the intraparietal sulcus (IPS) as seed region, DD showed hyperconnectivity in parietal, frontal, visual, and temporal regions before the training controlling for age and IQ. Hyperconnectivity disappeared after training, whereas math abilities improved. Multivariate classification analysis of task-related fMRI data corroborated the connectivity results as the same group of TD could be discriminated from DD before but not after number line training (86.4 vs. 38.9%, respectively). Our results indicate that abnormally high functional connectivity in DD can be normalized on the neuronal level by intensive number line training. As functional connectivity in DD was indistinguishable to TD's connectivity after training, we conclude that training lead to a re-organization of inter-regional task engagement. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Chemical discrimination of lubricant marketing types using direct analysis in real time time-of-flight mass spectrometry.

PubMed

Maric, Mark; Harvey, Lauren; Tomcsak, Maren; Solano, Angelique; Bridge, Candice

2017-06-30

In comparison to other violent crimes, sexual assaults suffer from very low prosecution and conviction rates especially in the absence of DNA evidence. As a result, the forensic community needs to utilize other forms of trace contact evidence, like lubricant evidence, in order to provide a link between the victim and the assailant. In this study, 90 personal bottled and condom lubricants from the three main marketing types, silicone-based, water-based and condoms, were characterized by direct analysis in real time time of flight mass spectrometry (DART-TOFMS). The instrumental data was analyzed by multivariate statistics including hierarchal cluster analysis, principal component analysis, and linear discriminant analysis. By interpreting the mass spectral data with multivariate statistics, 12 discrete groupings were identified, indicating inherent chemical diversity not only between but within the three main marketing groups. A number of unique chemical markers, both major and minor, were identified, other than the three main chemical components (i.e. PEG, PDMS and nonoxynol-9) currently used for lubricant classification. The data was validated by a stratified 20% withheld cross-validation which demonstrated that there was minimal overlap between the groupings. Based on the groupings identified and unique features of each group, a highly discriminating statistical model was then developed that aims to provide the foundation for the development of a forensic lubricant database that may eventually be applied to casework. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

PubMed

Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

2017-05-01

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

The Advantages of Using Planned Comparisons over Post Hoc Tests.

ERIC Educational Resources Information Center

Kuehne, Carolyn C.

There are advantages to using a priori or planned comparisons rather than omnibus multivariate analysis of variance (MANOVA) tests followed by post hoc or a posteriori testing. A small heuristic data set is used to illustrate these advantages. An omnibus MANOVA test was performed on the data followed by a post hoc test (discriminant analysis). A…

[Change settings for visual analyzer of child users of mobile communication: longitudinal study].

PubMed

Khorseva, N I; Grigor'ev, Iu G; Gorbunova, N V

2014-01-01

The paper represents theresults of longitudinal monitoring of the changes in the parameters of simple visual-motor reaction, the visual acuity and the rate of the visual discrimination in the child users of mobile communication, which indicate the multivariability of the possible effects of radiation from mobile phones on the auditory system of children.

NIRS Identification of Swietenia Macrophylla is Robust Across Specimens from 27 Countries

Treesearch

Maria C.J. Bergo; Tereza C.M. Pastore; Vera T.R. Coradin; Alex C. Wiedenhoeft; Jez W.B. Braga

2016-01-01

Big-leaf mahogany is the world’s most valuable widely traded tropical timber species and Near Infrared Spectroscopy (NIRS) has been applied as a tool for discriminating its wood from similar species using multivariate analysis. In this study four look-alike timbers of Swietenia macrophylla (mahogany or big-leaf mahogany), Carapa...

HIV-related discrimination among grade six students in nine Southern African countries.

PubMed

Maughan-Brown, Brendan; Spaull, Nicholas

2014-01-01

HIV-related stigmatisation and discrimination by young children towards their peers have important consequences at the individual level and for our response to the epidemic, yet research on this area is limited. We used nationally representative data to examine discrimination of HIV-positive children by grade six students (n = 39,664) across nine countries in Southern Africa: Botswana, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Zambia and Zimbabwe. Descriptive statistics are used to compare discrimination by country, gender, geographic location and socioeconomic status. Multivariate logistic regression is employed to assess potential determinants of discrimination. The levels and determinants of discrimination varied significantly between the nine countries. While one in ten students in Botswana, Malawi, South Africa and Swaziland would "avoid or shun" an HIV positive friend, the proportions in Lesotho, Mozambique, Zambia and Zimbabwe were twice as high (approximately 20%). A large proportion of students believed that HIV positive children should not be allowed to continue to attend school, particularly in Zambia (33%), Lesotho (37%) and Zimbabwe (42%). The corresponding figures for Malawi and Swaziland were significantly lower at 13% and 12% respectively. Small differences were found by gender. Children from rural areas and poorer schools were much more likely to discriminate than those from urban areas and wealthier schools. Importantly, we identified factors consistently associated with discrimination across the region: students with greater exposure to HIV information, better general HIV knowledge and fewer misconceptions about transmission of HIV via casual contact were less likely to report discrimination. Our study points toward the need for early interventions (grade six or before) to reduce stigma and discrimination among children, especially in schools situated in rural areas and poorer communities. In particular, interventions should focus on correcting misconceptions that HIV can be transmitted via casual contact.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

A discriminant function model as an alternative method to spirometry for COPD screening in primary care settings in China.

PubMed

Cui, Jiangyu; Zhou, Yumin; Tian, Jia; Wang, Xinwang; Zheng, Jingping; Zhong, Nanshan; Ran, Pixin

2012-12-01

COPD is often underdiagnosed in a primary care setting where the spirometry is unavailable. This study was aimed to develop a simple, economical and applicable model for COPD screening in those settings. First we established a discriminant function model based on Bayes' Rule by stepwise discriminant analysis, using the data from 243 COPD patients and 112 non-COPD subjects from our COPD survey in urban and rural communities and local primary care settings in Guangdong Province, China. We then used this model to discriminate COPD in additional 150 subjects (50 non-COPD and 100 COPD ones) who had been recruited by the same methods as used to have established the model. All participants completed pre- and post-bronchodilator spirometry and questionnaires. COPD was diagnosed according to the Global Initiative for Chronic Obstructive Lung Disease criteria. The sensitivity and specificity of the discriminant function model was assessed. THE ESTABLISHED DISCRIMINANT FUNCTION MODEL INCLUDED NINE VARIABLES: age, gender, smoking index, body mass index, occupational exposure, living environment, wheezing, cough and dyspnoea. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, accuracy and error rate of the function model to discriminate COPD were 89.00%, 82.00%, 4.94, 0.13, 86.66% and 13.34%, respectively. The accuracy and Kappa value of the function model to predict COPD stages were 70% and 0.61 (95% CI, 0.50 to 0.71). This discriminant function model may be used for COPD screening in primary care settings in China as an alternative option instead of spirometry.

Mobility measures differentiate falls risk status in persons with multiple sclerosis: An exploratory study.

PubMed

Sebastião, Emerson; Learmonth, Yvonne C; Motl, Robert W

2017-01-01

Falls are of great concern among persons with multiple sclerosis (MS). To examine differences in metrics of mobility, postural control, and cognition in persons with MS with distinct fall risk status; and to investigate predictors of fall risk group membership using discriminant analysis. Forty-seven persons with MS completed the Activities-Balance Confidence (ABC) Scale and underwent a battery of assessments of mobility, balance, and cognition. Participants further wore an accelerometer for 7 days as an assessment of steps/day. Participants were allocated into fall risk groups based on ABC scale scores (increased fall risk (IFR); and normal fall risk (NFR)). We examined univariate differences between groups using ANOVA, and discriminant function analysis (DFA) identified the significant multivariate predictors of FR status. After controlling for disability level, the IFR group had significantly (p < 0.05) worse scores on measures of mobility (i.e., MSWS-12, 6 MW, and steps/day) compared to the NFR group. DFA identified MSWS-12 and 6 MW scores as significant (p < 0.05) predictors of fall risk group membership. Those two variables collectively explained 55% of variance in fall risk grouping. The findings suggest that mobility should be the focus of rehabilitation programs in persons with MS, especially for those at IFR.

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.

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.

Comprehensive Chemical Fingerprinting of High-Quality Cocoa at Early Stages of Processing: Effectiveness of Combined Untargeted and Targeted Approaches for Classification and Discrimination.

PubMed

Magagna, Federico; Guglielmetti, Alessandro; Liberto, Erica; Reichenbach, Stephen E; Allegrucci, Elena; Gobino, Guido; Bicchi, Carlo; Cordero, Chiara

2017-08-02

This study investigates chemical information of volatile fractions of high-quality cocoa (Theobroma cacao L. Malvaceae) from different origins (Mexico, Ecuador, Venezuela, Columbia, Java, Trinidad, and Sao Tomè) produced for fine chocolate. This study explores the evolution of the entire pattern of volatiles in relation to cocoa processing (raw, roasted, steamed, and ground beans). Advanced chemical fingerprinting (e.g., combined untargeted and targeted fingerprinting) with comprehensive two-dimensional gas chromatography coupled with mass spectrometry allows advanced pattern recognition for classification, discrimination, and sensory-quality characterization. The entire data set is analyzed for 595 reliable two-dimensional peak regions, including 130 known analytes and 13 potent odorants. Multivariate analysis with unsupervised exploration (principal component analysis) and simple supervised discrimination methods (Fisher ratios and linear regression trees) reveal informative patterns of similarities and differences and identify characteristic compounds related to sample origin and manufacturing step.

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.

Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques.

PubMed

Tahir, Haroon Elrasheid; Xiaobo, Zou; Xiaowei, Huang; Jiyong, Shi; Mariod, Abdalbasit Adam

2016-09-01

Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography-mass spectrometry (GC-MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

Differentiating clinical groups using the serial color-word test (S-CWT).

PubMed

Hentschel, Uwe; Rubino, I Alex; Bijleveld, Catrien

2011-04-01

The present study attempted to differentiate 11 diagnostic groups by means of the Serial Color-Word Test (S-CWT), using multivariate discriminant analysis. Two alternative scoring systems of the S-CWT were outlined. Asample of 514 individuals who had clinical diagnoses of various types and 397 controls who had no diagnostic findings comprised the sample. The first discriminant analysis failed to differentiate the groups adequately. The groups were consequently reduced to four (schizophrenia, bipolar disorders, temporo-mandibular joint pain dysfunction syndrome, and eating disturbances), which gave better reclassification findings for a clinical application of the test. This classification gave over 55% correct assignments. The final four groups had a statistically significant discrimination on the test, which remained stable also in a bootstrap procedure. Implications for treatment indications and outcomes as well as strategies for further studies using the S-CWT are discussed.

Multivariate Classification of Structural MRI Data Detects Chronic Low Back Pain

PubMed Central

Ung, Hoameng; Brown, Justin E.; Johnson, Kevin A.; Younger, Jarred; Hush, Julia; Mackey, Sean

2014-01-01

Chronic low back pain (cLBP) has a tremendous personal and socioeconomic impact, yet the underlying pathology remains a mystery in the majority of cases. An objective measure of this condition, that augments self-report of pain, could have profound implications for diagnostic characterization and therapeutic development. Contemporary research indicates that cLBP is associated with abnormal brain structure and function. Multivariate analyses have shown potential to detect a number of neurological diseases based on structural neuroimaging. Therefore, we aimed to empirically evaluate such an approach in the detection of cLBP, with a goal to also explore the relevant neuroanatomy. We extracted brain gray matter (GM) density from magnetic resonance imaging scans of 47 patients with cLBP and 47 healthy controls. cLBP was classified with an accuracy of 76% by support vector machine analysis. Primary drivers of the classification included areas of the somatosensory, motor, and prefrontal cortices—all areas implicated in the pain experience. Differences in areas of the temporal lobe, including bordering the amygdala, medial orbital gyrus, cerebellum, and visual cortex, were also useful for the classification. Our findings suggest that cLBP is characterized by a pattern of GM changes that can have discriminative power and reflect relevant pathological brain morphology. PMID:23246778

Delineation of estuarine management areas using multivariate geostatistics: the case of Sado Estuary.

PubMed

Caeiro, Sandra; Goovaerts, Pierre; Painho, Marco; Costa, M Helena

2003-09-15

The Sado Estuary is a coastal zone located in the south of Portugal where conflicts between conservation and development exist because of its location near industrialized urban zones and its designation as a natural reserve. The aim of this paper is to evaluate a set of multivariate geostatistical approaches to delineate spatially contiguous regions of sediment structure for Sado Estuary. These areas will be the supporting infrastructure of an environmental management system for this estuary. The boundaries of each homogeneous area were derived from three sediment characterization attributes through three different approaches: (1) cluster analysis of dissimilarity matrix function of geographical separation followed by indicator kriging of the cluster data, (2) discriminant analysis of kriged values of the three sediment attributes, and (3) a combination of methods 1 and 2. Final maximum likelihood classification was integrated into a geographical information system. All methods generated fairly spatially contiguous management areas that reproduce well the environment of the estuary. Map comparison techniques based on kappa statistics showed thatthe resultant three maps are similar, supporting the choice of any of the methods as appropriate for management of the Sado Estuary. However, the results of method 1 seem to be in better agreement with estuary behavior, assessment of contamination sources, and previous work conducted at this site.

A stress ecology framework for comprehensive risk assessment of diffuse pollution.

PubMed

van Straalen, Nico M; van Gestel, Cornelis A M

2008-12-01

Environmental pollution is traditionally classified as either localized or diffuse. Local pollution comes from a point source that emits a well-defined cocktail of chemicals, distributed in the environment in the form of a gradient around the source. Diffuse pollution comes from many sources, small and large, that cause an erratic distribution of chemicals, interacting with those from other sources into a complex mixture of low to moderate concentrations over a large area. There is no good method for ecological risk assessment of such types of pollution. We argue that effects of diffuse contamination in the field must be analysed in the wider framework of stress ecology. A multivariate approach can be applied to filter effects of contaminants from the many interacting factors at the ecosystem level. Four case studies are discussed (1) functional and structural properties of terrestrial model ecosystems, (2) physiological profiles of microbial communities, (3) detritivores in reedfield litter, and (4) benthic invertebrates in canal sediment. In each of these cases the data were analysed by multivariate statistics and associations between ecological variables and the levels of contamination were established. We argue that the stress ecology framework is an appropriate assessment instrument for discriminating effects of pollution from other anthropogenic disturbances and naturally varying factors.

Legal Protections in Public Accommodations Settings: A Critical Public Health Issue for Transgender and Gender-Nonconforming People

PubMed Central

Reisner, Sari L; Hughto, Jaclyn M White; Dunham, Emilia E; Heflin, Katherine J; Begenyi, Jesse Blue Glass; Coffey-Esquivel, Julia; Cahill, Sean

2015-01-01

Context Gender minority people who are transgender or gender nonconforming experience widespread discrimination and health inequities. Since 2012, Massachusetts law has provided protections against discrimination on the basis of gender identity in employment, housing, credit, public education, and hate crimes. The law does not, however, protect against discrimination in public accommodations (eg, hospitals, health centers, transportation, nursing homes, supermarkets, retail establishments). For this article, we examined the frequency and health correlates of public accommodations discrimination among gender minority adults in Massachusetts, with attention to discrimination in health care settings. Methods In 2013, we recruited a community-based sample (n = 452) both online and in person. The respondents completed a 1-time, electronic survey assessing demographics, health, health care utilization, and discrimination in public accommodations venues in the past 12 months. Using adjusted multivariable logistic regression models, we examined whether experiencing public accommodations discrimination in health care was independently associated with adverse self-reported health, adjusting for discrimination in other public accommodations settings. Findings Overall, 65% of respondents reported public accommodations discrimination in the past 12 months. The 5 most prevalent discrimination settings were transportation (36%), retail (28%), restaurants (26%), public gatherings (25%), and health care (24%). Public accommodations discrimination in the past 12 months in health care settings was independently associated with a 31% to 81% increased risk of adverse emotional and physical symptoms and a 2-fold to 3-fold increased risk of postponement of needed care when sick or injured and of preventive or routine health care, adjusting for discrimination in other public accommodations settings (which also conferred an additional 20% to 77% risk per discrimination setting endorsed). Conclusions Discrimination in public accommodations is common and is associated with adverse health outcomes among transgender and gender-nonconforming adults in Massachusetts. Discrimination in health care settings creates a unique health risk for gender minority people. The passage and enforcement of transgender rights laws that include protections against discrimination in public accommodations—inclusive of health care—are a public health policy approach critically needed to address transgender health inequities. PMID:26219197

Pretransplantation recipient regulatory T cell suppressive function predicts delayed and slow graft function after kidney transplantation.

PubMed

Nguyen, Minh-Tri J P; Fryml, Elise; Sahakian, Sossy K; Liu, Shuqing; Michel, Rene P; Lipman, Mark L; Mucsi, Istvan; Cantarovich, Marcelo; Tchervenkov, Jean I; Paraskevas, Steven

2014-10-15

Delayed graft function (DGF) and slow graft function (SGF) are a continuous spectrum of ischemia-reperfusion-related acute kidney injury (AKI) that increases the risk for acute rejection and graft loss after kidney transplantation. Regulatory T cells (Tregs) are critical in transplant tolerance and attenuate murine AKI. In this prospective observational cohort study, we evaluated whether pretransplantation peripheral blood recipient Treg frequency and suppressive function are predictors of DGF and SGF after kidney transplantation. Deceased donor kidney transplant recipients (n=53) were divided into AKI (n=37; DGF, n=10; SGF, n=27) and immediate graft function (n=16) groups. Pretransplantation peripheral blood CD4CD25FoxP3 Treg frequency was quantified by flow cytometry. Regulatory T-cell suppressive function was measured by suppression of autologous effector T-cell proliferation by Treg in co-culture. Pretransplantation Treg suppressive function, but not frequency, was decreased in AKI recipients (P<0.01). In univariate and multivariate analyses accounting for the effects of cold ischemic time and donor age, Treg suppressive function discriminated DGF from immediate graft function recipients in multinomial logistic regression (odds ratio, 0.77; P<0.01), accurately predicted AKI in receiver operating characteristic curve (area under the curve, 0.82; P<0.01), and predicted 14-day estimated glomerular filtration rate in linear regression (P<0.01). Our results indicate that recipient peripheral blood Treg suppressive function is a potential independent pretransplantation predictor of DGF and SGF.

Capital market based warning indicators of bank runs

NASA Astrophysics Data System (ADS)

Vakhtina, Elena; Wosnitza, Jan Henrik

2015-01-01

In this investigation, we examine the univariate as well as the multivariate capabilities of the log-periodic [super-exponential] power law (LPPL) for the prediction of bank runs. The research is built upon daily CDS spreads of 40 international banks for the period from June 2007 to March 2010, i.e. at the heart of the global financial crisis. For this time period, 20 of the financial institutions received federal bailouts and are labeled as defaults while the remaining institutions are categorized as non-defaults. The employed multivariate pattern recognition approach represents a modification of the CORA3 algorithm. The approach is found to be robust regardless of reasonable changes of its inputs. Despite the fact that distinct alarm indices for banks do not clearly demonstrate predictive capabilities of the LPPL, the synchronized alarm indices confirm the multivariate discriminative power of LPPL patterns in CDS spread developments acknowledged by bootstrap intervals with 70% confidence level.

Authentication of Trappist beers by LC-MS fingerprints and multivariate data analysis.

PubMed

Mattarucchi, Elia; Stocchero, Matteo; Moreno-Rojas, José Manuel; Giordano, Giuseppe; Reniero, Fabiano; Guillou, Claude

2010-12-08

The aim of this study was to asses the applicability of LC-MS profiling to authenticate a selected Trappist beer as part of a program on traceability funded by the European Commission. A total of 232 beers were fingerprinted and classified through multivariate data analysis. The selected beer was clearly distinguished from beers of different brands, while only 3 samples (3.5% of the test set) were wrongly classified when compared with other types of beer of the same Trappist brewery. The fingerprints were further analyzed to extract the most discriminating variables, which proved to be sufficient for classification, even using a simplified unsupervised model. This reduced fingerprint allowed us to study the influence of batch-to-batch variability on the classification model. Our results can easily be applied to different matrices and they confirmed the effectiveness of LC-MS profiling in combination with multivariate data analysis for the characterization of food products.

Differentiation of Chinese rice wines from different wineries based on mineral elemental fingerprinting.

PubMed

Shen, Fei; Wu, Jian; Ying, Yibin; Li, Bobin; Jiang, Tao

2013-12-15

Discrimination of Chinese rice wines from three well-known wineries ("Guyuelongshan", "Kuaijishan", and "Pagoda") in China has been carried out according to mineral element contents in this study. Nineteen macro and trace mineral elements (Na, Mg, Al, K, Ca, Mn, Fe, Cu, Zn, V, Cr, Co, Ni, As, Se, Mo, Cd, Ba and Pb) were determined by inductively coupled plasma mass spectrometry (ICP-MS) in 117 samples. Then the experimental data were subjected to analysis of variance (ANOVA) and principal component analysis (PCA) to reveal significant differences and potential patterns between samples. Stepwise linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA) were applied to develop classification models and achieved correct classified rates of 100% and 97.4% for the prediction sample set, respectively. The discrimination could be attributed to different raw materials (mainly water) and elaboration processes employed. The results indicate that the element compositions combined with multivariate analysis can be used as fingerprinting techniques to protect prestigious wineries and enable the authenticity of Chinese rice wine. Copyright © 2013 Elsevier Ltd. All rights reserved.

Metabolomic Approach for Discrimination of Four- and Six-Year-Old Red Ginseng (Panax ginseng) Using UPLC-QToF-MS.

PubMed

Shin, Jung-Sub; Park, Hee-Won; In, Gyo; Seo, Hyun Kyu; Won, Tae Hyung; Jang, Kyoung Hwa; Cho, Byung-Goo; Han, Chang Kyun; Shin, Jongheon

2016-09-01

Panax ginseng C.A. MEYER is one of the most popular medicinal herbs in Asia and the chemical constituents are changed by processing methods such as steaming or sun drying. Metabolomic analysis was performed to distinguish age discrimination of four- and six-year-old red ginseng using ultra-performance liquid chromatography quadruple time of flight mass spectrometry (UPLC-QToF-MS) with multivariate statistical analysis. Principal component analysis (PCA) showed clear discrimination between extracts of red ginseng of different ages and suggest totally six discrimination markers (two for four-year-old and four for six-year-old red ginseng). Among these, one marker was isolated and the structure determined by NMR spectroscopic analysis was 13-cis-docosenamide (marker 6-1) from six-year-old red ginseng. This is the first report of a metabolomic study regarding the age differentiation of red ginseng using UPLC-QToF-MS and determination of the structure of the marker. These results will contribute to the quality control and standardization as well as provide a scientific basis for pharmacological research on red ginseng.

¹H NMR spectroscopy reveals the effect of genotype and growth conditions on composition of sea buckthorn (Hippophaë rhamnoides L.) berries.

PubMed

Kortesniemi, Maaria; Sinkkonen, Jari; Yang, Baoru; Kallio, Heikki

2014-03-15

¹H NMR spectroscopy and multivariate data analysis were applied to the metabolic profiling and discrimination of wild sea buckthorn (Hippophaë rhamnoides L.) berries from different locations in Finland (subspecies (ssp.) rhamnoides) and China (ssp. sinensis). Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) showed discrimination of the two subspecies and different growth sites. The discrimination of ssp. rhamnoides was mainly associated with typically higher temperature, radiation and humidity and lower precipitation in the south, yielding higher levels of O-ethyl β-d-glucopyranoside and d-glucose, and lower levels of malic, quinic and ascorbic acids. Significant metabolic differences (p<0.05) in genetically identical berries were observed between latitudes 60° and 67° north in Finland. High altitudes (> 2,000 m) correlated with greater levels of malic and ascorbic acids in ssp. sinensis. The NMR metabolomics approach applied here is effective for identification of metabolites, geographical origin and subspecies of sea buckthorn berries. Copyright © 2013 Elsevier Ltd. All rights reserved.

Geographical origin discrimination of lentils (Lens culinaris Medik.) using 1H NMR fingerprinting and multivariate statistical analyses.

PubMed

Longobardi, Francesco; Innamorato, Valentina; Di Gioia, Annalisa; Ventrella, Andrea; Lippolis, Vincenzo; Logrieco, Antonio F; Catucci, Lucia; Agostiano, Angela

2017-12-15

Lentil samples coming from two different countries, i.e. Italy and Canada, were analysed using untargeted 1 H NMR fingerprinting in combination with chemometrics in order to build models able to classify them according to their geographical origin. For such aim, Soft Independent Modelling of Class Analogy (SIMCA), k-Nearest Neighbor (k-NN), Principal Component Analysis followed by Linear Discriminant Analysis (PCA-LDA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were applied to the NMR data and the results were compared. The best combination of average recognition (100%) and cross-validation prediction abilities (96.7%) was obtained for the PCA-LDA. All the statistical models were validated both by using a test set and by carrying out a Monte Carlo Cross Validation: the obtained performances were found to be satisfying for all the models, with prediction abilities higher than 95% demonstrating the suitability of the developed methods. Finally, the metabolites that mostly contributed to the lentil discrimination were indicated. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Discrimination between Alzheimer's Disease and Late Onset Bipolar Disorder Using Multivariate Analysis.

PubMed

Besga, Ariadna; Gonzalez, Itxaso; Echeburua, Enrique; Savio, Alexandre; Ayerdi, Borja; Chyzhyk, Darya; Madrigal, Jose L M; Leza, Juan C; Graña, Manuel; Gonzalez-Pinto, Ana Maria

2015-01-01

Late onset bipolar disorder (LOBD) is often difficult to distinguish from degenerative dementias, such as Alzheimer disease (AD), due to comorbidities and common cognitive symptoms. Moreover, LOBD prevalence in the elder population is not negligible and it is increasing. Both pathologies share pathophysiological neuroinflammation features. Improvements in differential diagnosis of LOBD and AD will help to select the best personalized treatment. The aim of this study is to assess the relative significance of clinical observations, neuropsychological tests, and specific blood plasma biomarkers (inflammatory and neurotrophic), separately and combined, in the differential diagnosis of LOBD versus AD. It was carried out evaluating the accuracy achieved by classification-based computer-aided diagnosis (CAD) systems based on these variables. A sample of healthy controls (HC) (n = 26), AD patients (n = 37), and LOBD patients (n = 32) was recruited at the Alava University Hospital. Clinical observations, neuropsychological tests, and plasma biomarkers were measured at recruitment time. We applied multivariate machine learning classification methods to discriminate subjects from HC, AD, and LOBD populations in the study. We analyzed, for each classification contrast, feature sets combining clinical observations, neuropsychological measures, and biological markers, including inflammation biomarkers. Furthermore, we analyzed reduced feature sets containing variables with significative differences determined by a Welch's t-test. Furthermore, a battery of classifier architectures were applied, encompassing linear and non-linear Support Vector Machines (SVM), Random Forests (RF), Classification and regression trees (CART), and their performance was evaluated in a leave-one-out (LOO) cross-validation scheme. Post hoc analysis of Gini index in CART classifiers provided a measure of each variable importance. Welch's t-test found one biomarker (Malondialdehyde) with significative differences (p < 0.001) in LOBD vs. AD contrast. Classification results with the best features are as follows: discrimination of HC vs. AD patients reaches accuracy 97.21% and AUC 98.17%. Discrimination of LOBD vs. AD patients reaches accuracy 90.26% and AUC 89.57%. Discrimination of HC vs LOBD patients achieves accuracy 95.76% and AUC 88.46%. It is feasible to build CAD systems for differential diagnosis of LOBD and AD on the basis of a reduced set of clinical variables. Clinical observations provide the greatest discrimination. Neuropsychological tests are improved by the addition of biomarkers, and both contribute significantly to improve the overall predictive performance.

Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

PubMed

Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

2014-02-01

Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhu, Ying; Tan, Tuck Lee

2016-04-01

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.

Discrimination and Delayed Health Care Among Transgender Women and Men: Implications for Improving Medical Education and Health Care Delivery.

PubMed

Jaffee, Kim D; Shires, Deirdre A; Stroumsa, Daphna

2016-11-01

The transgender community experiences health care discrimination and approximately 1 in 4 transgender people were denied equal treatment in health care settings. Discrimination is one of the many factors significantly associated with health care utilization and delayed care. We assessed factors associated with delayed medical care due to discrimination among transgender patients, and evaluated the relationship between perceived provider knowledge and delayed care using Anderson's behavioral model of health services utilization. Multivariable logistic regression analysis was used to test whether predisposing, enabling, and health system factors were associated with delaying needed care for transgender women and transgender men. A sample of 3486 transgender participants who took part in the National Transgender Discrimination Survey in 2008 and 2009. Predisposing, enabling, and health system environment factors, and delayed needed health care. Overall, 30.8% of transgender participants delayed or did not seek needed health care due to discrimination. Respondents who had to teach health care providers about transgender people were 4 times more likely to delay needed health care due to discrimination. Transgender patients who need to teach their providers about transgender people are significantly more likely to postpone or not seek needed care. Systemic changes in provider education and training, along with health care system adaptations to ensure appropriate, safe, and respectful care, are necessary to close the knowledge and treatment gaps and prevent delayed care with its ensuing long-term health implications.

Health care barriers, racism, and intersectionality in Australia.

PubMed

Bastos, João L; Harnois, Catherine E; Paradies, Yin C

2018-02-01

While racism has been shown to negatively affect health care quality, little is known about the extent to which racial discrimination works with and through gender, class, and sexuality to predict barriers to health care (e.g., perceived difficulty accessing health services). Additionally, most existing studies focus on racial disparities in the U.S. context, with few examining marginalized groups in other countries. To address these knowledge gaps, we analyze data from the 2014 Australian General Social Survey, a nationally representative survey of individuals aged 15 and older living in 12,932 private dwellings. Following an intersectional perspective, we estimate a series of multivariable logit regression models to assess three hypotheses: racial discrimination will be positively associated with perceived barriers to health care (H1); the effect of perceived racial discrimination will be particularly severe for women, sexual minorities, and low socio-economic status individuals (H2); and, in addition to racial discrimination, other forms of perceived discrimination will negatively impact perceived barriers to health care (H3). Findings show that perceptions of racial discrimination are significantly associated with perceived barriers to health care, though this relationship is not significantly stronger for low status groups. In addition, our analyses reveal that perceived racism and other forms of discrimination combine to predict perceived barriers to health care. Taken together, these results speak to the benefits of an intersectional approach for examining racial inequalities in perceived access to health care. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Association Between Racial and Gender Discrimination and Body Mass Index Among Residents Living in Lower-income Housing

PubMed Central

Shelton, Rachel C.; Puleo, Elaine; Bennett, Gary G.; McNeill, Lorna H.; Sorensen, Glorian; Emmons, Karen M.

2010-01-01

Background Research on the association between self-reported racial or gender discrimination and body mass index (BMI) has been limited and inconclusive to date, particularly among lower-income populations. Objectives The aim of the current study was to examine the association between self-reported racial and gender discrimination and BMI among a sample of adult residents living in 12 urban lower-income housing sites in Boston, Masschusetts (USA). Methods Baseline survey data were collected among 1,307 (weighted N=1907) study participants. For analyses, linear regression models with a cluster design were conducted using SUDAAN and SAS statistical software. Results Our sample was predominately Black (weighted n=956) and Hispanic (weighted n=857), and female (weighted n=1420), with a mean age of 49.3 (SE: .40) and mean BMI of 30.2 kg m−2 (SE: .19). Nearly 47% of participants reported ever experiencing racial discrimination, and 24.8% reported ever experiencing gender discrimination. In bivariate and multivariable linear regression models, no main effect association was found between either racial or gender discrimination and BMI. Conclusions While our findings suggest that self-reported discrimination is not a key determinant of BMI among lower-income housing residents, these results should be considered in light of study limitations. Future researchers may want to investigate this association among other relevant samples, and other social contextual and cultural factors should be explored to understand how they contribute to disparities. PMID:19769005

The association between racial and gender discrimination and body mass index among residents living in lower-income housing.

PubMed

Shelton, Rachel C; Puleo, Elaine; Bennett, Gary G; McNeill, Lorna H; Sorensen, Glorian; Emmons, Karen M

2009-01-01

Research on the association between self-reported racial or gender discrimination and body mass index (BMI) has been limited and inconclusive to date, particularly among lower-income populations. The aim of the current study was to examine the association between self-reported racial and gender discrimination and BMI among a sample of adult residents living in 12 urban lower-income housing sites in Boston, Masschusetts (USA). Baseline survey data were collected among 1,307 (weighted N = 1907) study participants. For analyses, linear regression models with a cluster design were conducted using SUDAAN and SAS statistical software. Our sample was predominately Black (weighted n = 956) and Hispanic (weighted n = 857), and female (weighted n = 1420), with a mean age of 49.3 (SE: .40) and mean BMI of 30.2 kg m(-2) (SE: .19). Nearly 47% of participants reported ever experiencing racial discrimination, and 24.8% reported ever experiencing gender discrimination. In bivariate and multivariable linear regression models, no main effect association was found between either racial or gender discrimination and BMI. While our findings suggest that self-reported discrimination is not a key determinant of BMI among lower-income housing residents, these results should be considered in light of study limitations. Future researchers may want to investigate this association among other relevant samples, and other social contextual and cultural factors should be explored to understand how they contribute to disparities.

Feature selection and recognition from nonspecific volatile profiles for discrimination of apple juices according to variety and geographical origin.

PubMed

Guo, Jing; Yue, Tianli; Yuan, Yahong

2012-10-01

Apple juice is a complex mixture of volatile and nonvolatile components. To develop discrimination models on the basis of the volatile composition for an efficient classification of apple juices according to apple variety and geographical origin, chromatography volatile profiles of 50 apple juice samples belonging to 6 varieties and from 5 counties of Shaanxi (China) were obtained by headspace solid-phase microextraction coupled with gas chromatography. The volatile profiles were processed as continuous and nonspecific signals through multivariate analysis techniques. Different preprocessing methods were applied to raw chromatographic data. The blind chemometric analysis of the preprocessed chromatographic profiles was carried out. Stepwise linear discriminant analysis (SLDA) revealed satisfactory discriminations of apple juices according to variety and geographical origin, provided respectively 100% and 89.8% success rate in terms of prediction ability. Finally, the discriminant volatile compounds selected by SLDA were identified by gas chromatography-mass spectrometry. The proposed strategy was able to verify the variety and geographical origin of apple juices involving only a reduced number of discriminate retention times selected by the stepwise procedure. This result encourages the similar procedures to be considered in quality control of apple juices. This work presented a method for an efficient discrimination of apple juices according to apple variety and geographical origin using HS-SPME-GC-MS together with chemometric tools. Discrimination models developed could help to achieve greater control over the quality of the juice and to detect possible adulteration of the product. © 2012 Institute of Food Technologists®

Transdiagnostic Factors and Mediation of the Relationship Between Perceived Racial Discrimination and Mental Disorders.

PubMed

Rodriguez-Seijas, Craig; Stohl, Malki; Hasin, Deborah S; Eaton, Nicholas R

2015-07-01

Multivariable comorbidity research indicates that many common mental disorders are manifestations of 2 latent transdiagnostic factors, internalizing and externalizing. Environmental stressors are known to increase the risk for experiencing particular mental disorders, but their relationships with transdiagnostic disorder constructs are unknown. The present study investigated one such stressor, perceived racial discrimination, which is robustly associated with a variety of mental disorders. To examine the direct and indirect associations between perceived racial discrimination and common forms of psychopathology. Quantitative analysis of 12 common diagnoses that were previously assessed in a nationally representative sample (N = 5191) of African American and Afro-Caribbean adults in the United States, taken from the National Survey of American Life, and used to test the possibility that transdiagnostic factors mediate the effects of discrimination on disorders. The data were obtained from February 2001 to March 2003. Latent variable measurement models, including factor analysis, and indirect effect models were used in the study. Mental health diagnoses from reliable and valid structured interviews and perceived race-based discrimination. While perceived discrimination was positively associated with all examined forms of psychopathology and substance use disorders, latent variable indirect effects modeling revealed that almost all of these associations were significantly mediated by the transdiagnostic factors. For social anxiety disorder and attention-deficit/hyperactivity disorder, complete mediation was found. The pathways linking perceived discrimination to psychiatric disorders were not direct but indirect (via transdiagnostic factors). Therefore, perceived discrimination may be associated with risk for myriad psychiatric disorders due to its association with transdiagnostic factors.

Cultural and social determinants of health among indigenous Mexican migrants in the United States.

PubMed

Lee, Junghee; Donlan, William; Cardoso, Edgar Ezequiel Orea; Paz, Juan Jesus

2013-01-01

Despite growing numbers, indigenous Mexican migrants are relatively invisible to health practitioners who group them with nonindigenous, mestizo Mexican-origin populations. Associations between indigenous and mestizo cultural identifications with psychosocial characteristics and health indicators among indigenous Mexican migrants were examined. Results revealed gender differences in cultural identifications, perceived discrimination, self-esteem, self-efficacy, and various health indicators including depression severity, culture-bound syndromes, and self-rated health. Multivariate regression and structural equation path modeling demonstrated how indigenous cultural identification and perceived discrimination affects health. Findings suggest that interventions should utilize indigenous community-based activities designed to promote self-esteem and the value of indigenous culture, with a focus on females.

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.

Homeostatic signature of anabolic steroids in cattle using 1H-13C HMBC NMR metabonomics.

PubMed

Dumas, Marc-Emmanuel; Canlet, Cécile; Vercauteren, Joseph; André, François; Paris, Alain

2005-01-01

We used metabonomics to discriminate the urinary signature of different anabolic steroid treatments in cattle having different physiological backgrounds (age, sex, and race). (1)H-(13)C heteronuclear multiple bonding connectivity NMR spectroscopy and multivariate statistical methods reveal that metabolites such as trimethylamine-N-oxide, dimethylamine, hippurate, creatine, creatinine, and citrate characterize the biological fingerprint of anabolic treatment. These urinary biomarkers suggest an overall homeostatic adaptation in nitrogen and energy metabolism. From results obtained in this study, it is now possible to consider metabonomics as a complementary method usable to improve doping control strategies to detect fraudulent anabolic treatment in cattle since the oriented global metabolic response provides helpful discrimination.

Accuracy of metric sex analysis of skeletal remains using Fordisc based on a recent skull collection.

PubMed

Ramsthaler, F; Kreutz, K; Verhoff, M A

2007-11-01

It has been generally accepted in skeletal sex determination that the use of metric methods is limited due to the population dependence of the multivariate algorithms. The aim of the study was to verify the applicability of software-based sex estimations outside the reference population group for which discriminant equations have been developed. We examined 98 skulls from recent forensic cases of known age, sex, and Caucasian ancestry from cranium collections in Frankfurt and Mainz (Germany) to determine the accuracy of sex determination using the statistical software solution Fordisc which derives its database and functions from the US American Forensic Database. In a comparison between metric analysis using Fordisc and morphological determination of sex, average accuracy for both sexes was 86 vs 94%, respectively, and males were identified more accurately than females. The ratio of the true test result rate to the false test result rate was not statistically different for the two methodological approaches at a significance level of 0.05 but was statistically different at a level of 0.10 (p=0.06). Possible explanations for this difference comprise different ancestry, age distribution, and socio-economic status compared to the Fordisc reference sample. It is likely that a discriminant function analysis on the basis of more similar European reference samples will lead to more valid and reliable sexing results. The use of Fordisc as a single method for the estimation of sex of recent skeletal remains in Europe cannot be recommended without additional morphological assessment and without a built-in software update based on modern European reference samples.

Relationships among participant international prostate symptom score, benign prostatic hyperplasia impact index changes and global ratings of change in a trial of phytotherapy in men with lower urinary tract symptoms.

PubMed

Barry, Michael J; Cantor, Alan; Roehrborn, Claus G

2013-03-01

We related changes in American Urological Association symptom index scores with bother measures and global ratings of change in men with lower urinary tract symptoms who were enrolled in a saw palmetto trial. To be eligible for study men were 45 years old or older, and had a peak uroflow of 4 ml per second or greater and an American Urological Association symptom index score of 8 to 24. Participants self-administered the American Urological Association symptom index, International Prostate Symptom Score quality of life item, Benign Prostatic Hyperplasia Impact Index and 2 global change questions at baseline, and at 24, 48 and 72 weeks. In 357 participants global ratings of a little better were associated with a mean decrease in American Urological Association symptom index scores from 2.8 to 4.1 points across 3 time points. The analogous range for mean decreases in Benign Prostatic Hyperplasia Impact Index scores was 1.0 to 1.7 points and for the International Prostate Symptom Score quality of life item it was 0.5 to 0.8 points. At 72 weeks for the first global change question each change measure discriminated between participants who rated themselves at least a little better vs unchanged or worse 70% to 72% of the time. A multivariate model increased discrimination to 77%. For the second global change question each change measure correctly discriminated ratings of at least a little better vs unchanged or worse 69% to 74% of the time and a multivariate model increased discrimination to 79%. Changes in American Urological Association symptom index scores could discriminate between participants rating themselves at least a little better vs unchanged or worse. Our findings support the practice of powering studies to detect group mean differences in American Urological Association symptom index scores of at least 3 points. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Discriminating Talent Identified Junior Australian Footballers Using a Fundamental Gross Athletic Movement Assessment.

PubMed

Woods, Carl T; Banyard, Harry G; McKeown, Ian; Fransen, Job; Robertson, Sam

2016-09-01

Talent identification (TID) is a pertinent component of the sports sciences, affording practitioners the opportunity to target developmental interventions to a select few; optimising financial investments. However, TID is multi-componential, requiring the recognition of immediate and prospective performance. The measurement of athletic movement skill may afford practitioners insight into the latter component given its augmented relationship with functional sport specific qualities. It is currently unknown whether athletic movement skill is a discriminant quality in junior Australian football (AF). This study aimed to discriminate talent identified junior AF players from their non-talent identified counterparts using a fundamental gross athletic movement assessment. From a total of 50 under 18 (U18) AF players; two groups were classified a priori based on selection level; talent identified (n = 25; state academy representatives) and non-talent identified (n = 25; state-based competition representatives). Players performed a fundamental gross athletic movement assessment based on the Athletic Ability Assessment (AAA), consisting of an overhead squat, double lunge (left and right legs), single leg Romanian deadlift (left and right legs), and a push up (six movement criterions). Movements were scored across three assessment points using a three-point scale (resulting in a possible score of nine for each movement). A multivariate analysis of variance revealed significant between group effects on four of the six movement criterions (d = 0.56 - 0.87; p = 0.01 - 0.02). Binary logistic regression models and a receiver operating characteristic curve inspection revealed that the overhead squat score provided the greatest group discrimination (β(SE) = -0.89(0.44); p < 0.05), with a score of 4.5 classifying 64% and 88% of the talent identified and non-talent identified groups, respectively. Results support the integration of this assessment into contemporary talent identification approaches in junior AF, as it may provide coaches with insight into a juniors developmental potential.

Diversity and association of phenotypic and metabolomic traits in the close model grasses Brachypodium distachyon, B. stacei and B. hybridum

PubMed Central

López-Álvarez, Diana; Zubair, Hassan; Beckmann, Manfred; Draper, John

2017-01-01

Abstract Background and Aims Morphological traits in combination with metabolite fingerprinting were used to investigate inter- and intraspecies diversity within the model annual grasses Brachypodium distachyon, Brachypodium stacei and Brachypodium hybridum. Methods Phenotypic variation of 15 morphological characters and 2219 nominal mass (m/z) signals generated using flow infusion electrospray ionization–mass spectrometry (FIE–MS) were evaluated in individuals from a total of 174 wild populations and six inbred lines, and 12 lines, of the three species, respectively. Basic statistics and multivariate principal component analysis and discriminant analysis were used to differentiate inter- and intraspecific variability of the two types of variable, and their association was assayed with the rcorr function. Key Results Basic statistics and analysis of variance detected eight phenotypic characters [(stomata) leaf guard cell length, pollen grain length, (plant) height, second leaf width, inflorescence length, number of spikelets per inflorescence, lemma length, awn length] and 434 tentatively annotated metabolite signals that significantly discriminated the three species. Three phenotypic traits (pollen grain length, spikelet length, number of flowers per inflorescence) might be genetically fixed. The three species showed different metabolomic profiles. Discriminant analysis significantly discriminated the three taxa with both morphometric and metabolome traits and the intraspecific phenotypic diversity within B. distachyon and B. stacei. The populations of B. hybridum were considerably less differentiated. Conclusions Highly explanatory metabolite signals together with morphological characters revealed concordant patterns of differentiation of the three taxa. Intraspecific phenotypic diversity was observed between northern and southern Iberian populations of B. distachyon and between eastern Mediterranean/south-western Asian and western Mediterranean populations of B. stacei. Significant association was found for pollen grain length and lemma length and ten and six metabolomic signals, respectively. These results would guide the selection of new germplasm lines of the three model grasses in ongoing genome-wide association studies. PMID:28040672

Resolving human object recognition in space and time

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2014-01-01

A comprehensive picture of object processing in the human brain requires combining both spatial and temporal information about brain activity. Here, we acquired human magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) responses to 92 object images. Multivariate pattern classification applied to MEG revealed the time course of object processing: whereas individual images were discriminated by visual representations early, ordinate and superordinate category levels emerged relatively later. Using representational similarity analysis, we combine human fMRI and MEG to show content-specific correspondence between early MEG responses and primary visual cortex (V1), and later MEG responses and inferior temporal (IT) cortex. We identified transient and persistent neural activities during object processing, with sources in V1 and IT., Finally, human MEG signals were correlated to single-unit responses in monkey IT. Together, our findings provide an integrated space- and time-resolved view of human object categorization during the first few hundred milliseconds of vision. PMID:24464044

An empirical study of innovation-performance linkage in the paper industry

NASA Astrophysics Data System (ADS)

Farooquie, Parveen; Gani, Abdul; Zuberi, Arsalanullah K.; Hashmi, Imran

2012-10-01

To enter new markets and remain competitive in the existing markets, companies need to shift their focus from traditional means and ways to some innovative approaches. Though the paper industry in India has improved remarkably on its technological and environmental issues, yet it shows a low rate of innovation. The present paper attempts to review the industry in the perspective of technological innovations and investigates empirically the role of innovations in performance improvement and pollution control. Multivariate analysis of variance and discriminant function analysis are applied for data processing. The findings reveal that the mean scores on the factors, such as sales, quality, and flexibility, are higher for the good innovators than those for the poor innovators. Conversely, the factors which are likely to be reduced as a result of innovations, such as time, cost, emissions, and disposal of waste, have shown higher means for the poor innovators.

Charges of human immunodeficiency virus discrimination in the workplace: the Americans with Disabilities Act in action.

PubMed

Studdert, David M

2002-08-01

Congress enacted the Americans with Disabilities Act (ADA) to provide persons living with the human immunodeficiency virus (HIV) and other vulnerable populations with legal means of redress against discrimination, yet virtually nothing is known about how the intended beneficiaries have used these protections. This study aimed to describe the epidemiology of ADA charges alleging employment-related discrimination due to HIV and to investigate the charge-filing behavior of workers with HIV. Using a national database of all HIV discrimination charges filed since the inception of the ADA in 1991, the author described respondent employers, issues in dispute, and outcomes of charges. Next, he used multivariate regression analyses to compare the sociodemographic characteristics of charge filers with those of a nationally representative baseline sample of workers with HIV. Of the 3,520 HIV discrimination charges filed through 1999, 18.0% had merit and 14.1% received monetary compensation. Workers who were female (odds ratio (OR) = 0.79, p < 0.01), aged less than 25 years (OR = 0.36, p < 0.01), and aged 25-34 years (OR = 0.77, p < 0.01) filed disproportionately fewer charges. Controlling for underlying rates of discrimination in the baseline population magnified this "underclaiming" among young workers. The findings should help to target dissemination and support activities, designed to help workers take advantage of antidiscrimination protections, at the subgroups of workers who need them most.

Exploring intentions to discriminate against patients living with HIV/AIDS among future healthcare providers in Malaysia

PubMed Central

Earnshaw, Valerie A.; Jin, Harry; Wickersham, Jeffrey; Kamarulzaman, Adeeba; John, Jacob; Altice, Frederick L.

2015-01-01

OBJECTIVES Stigma towards people living with HIV/AIDS (PLWHA) is strong in Malaysia. Although stigma has been understudied, it may be a barrier to treating the approximately 81 000 Malaysian PLWHA. The current study explores correlates of intentions to discriminate against PLWHA among medical and dental students, the future healthcare providers of Malaysia. METHODS An online, cross-sectional survey of 1296 medical and dental students was conducted in 2012 at seven Malaysian universities; 1165 (89.9%) completed the survey and were analysed. Sociodemographic characteristics, stigma-related constructs and intentions to discriminate against PLWHA were measured. Linear mixed models were conducted, controlling for clustering by university. RESULTS The final multivariate model demonstrated that students who intended to discriminate more against PLWHA were female, less advanced in their training, and studying dentistry. They further endorsed more negative attitudes towards PLWHA, internalised greater HIV-related shame, reported more HIV-related fear and disagreed more strongly that PLWHA deserve good care. The final model accounted for 38% of the variance in discrimination intent, with 10% accounted for by sociodemographic characteristics and 28% accounted for by stigma-related constructs. CONCLUSIONS It is critical to reduce stigma among medical and dental students to eliminate intentions to discriminate and achieve equitable care for Malaysian PLWHA. Stigma-reduction interventions should be multipronged, addressing attitudes, internalised shame, fear and perceptions of deservingness of care. PMID:24666546

Health Care Engagement and Follow-up After Perceived Discrimination in Maternity Care.

PubMed

Attanasio, Laura; Kozhimannil, Katy B

2017-09-01

Negative experiences in the health care system, including perceived discrimination, can result in patient disengagement from health care. Four million US women give birth each year, and the perinatal period is a time of sustained interaction with the health care system, but potential consequences of negative experiences have not been examined in this context. We assessed whether perceived discrimination during the birth hospitalization were associated with postpartum follow-up care. Data were from the Listening to Mothers III survey, a nationally drawn sample of 2400 women with singleton births in US hospitals in 2011-2012. We used multivariate logistic regression to estimate adjusted odds of having a postpartum visit in the 8 weeks following birth by perceptions of discrimination due to (1) race/ethnicity; (2) insurance type; and (3) a difference of opinion with a provider about care. Women who experienced any of the 3 types of perceived discrimination had more than twice the odds of postpartum visit nonattendance (adjusted odds ratio=2.28, P=0.001), after adjusting for socioeconomic and medical characteristics. The postpartum visit is an opportunity for a patient and clinician to address continuing health problems following birth, discuss contraception, and screen for chronic disease. Forgoing this care may have negative health effects. The findings from this study underscore the need to reduce discrimination and improve maternity care experiences.

Exploring intentions to discriminate against patients living with HIV/AIDS among future healthcare providers in Malaysia.

PubMed

Earnshaw, Valerie A; Jin, Harry; Wickersham, Jeffrey; Kamarulzaman, Adeeba; John, Jacob; Altice, Frederick L

2014-06-01

Stigma towards people living with HIV/AIDS (PLWHA) is strong in Malaysia. Although stigma has been understudied, it may be a barrier to treating the approximately 81 000 Malaysian PLWHA. The current study explores correlates of intentions to discriminate against PLWHA among medical and dental students, the future healthcare providers of Malaysia. An online, cross-sectional survey of 1296 medical and dental students was conducted in 2012 at seven Malaysian universities; 1165 (89.9%) completed the survey and were analysed. Socio-demographic characteristics, stigma-related constructs and intentions to discriminate against PLWHA were measured. Linear mixed models were conducted, controlling for clustering by university. The final multivariate model demonstrated that students who intended to discriminate more against PLWHA were female, less advanced in their training, and studying dentistry. They further endorsed more negative attitudes towards PLWHA, internalised greater HIV-related shame, reported more HIV-related fear and disagreed more strongly that PLWHA deserve good care. The final model accounted for 38% of the variance in discrimination intent, with 10% accounted for by socio-demographic characteristics and 28% accounted for by stigma-related constructs. It is critical to reduce stigma among medical and dental students to eliminate intentions to discriminate and achieve equitable care for Malaysian PLWHA. Stigma-reduction interventions should be multipronged, addressing attitudes, internalised shame, fear and perceptions of deservingness of care. © 2014 John Wiley & Sons Ltd.

Development of Raman microspectroscopy for automated detection and imaging of basal cell carcinoma

NASA Astrophysics Data System (ADS)

Larraona-Puy, Marta; Ghita, Adrian; Zoladek, Alina; Perkins, William; Varma, Sandeep; Leach, Iain H.; Koloydenko, Alexey A.; Williams, Hywel; Notingher, Ioan

2009-09-01

We investigate the potential of Raman microspectroscopy (RMS) for automated evaluation of excised skin tissue during Mohs micrographic surgery (MMS). The main aim is to develop an automated method for imaging and diagnosis of basal cell carcinoma (BCC) regions. Selected Raman bands responsible for the largest spectral differences between BCC and normal skin regions and linear discriminant analysis (LDA) are used to build a multivariate supervised classification model. The model is based on 329 Raman spectra measured on skin tissue obtained from 20 patients. BCC is discriminated from healthy tissue with 90+/-9% sensitivity and 85+/-9% specificity in a 70% to 30% split cross-validation algorithm. This multivariate model is then applied on tissue sections from new patients to image tumor regions. The RMS images show excellent correlation with the gold standard of histopathology sections, BCC being detected in all positive sections. We demonstrate the potential of RMS as an automated objective method for tumor evaluation during MMS. The replacement of current histopathology during MMS by a ``generalization'' of the proposed technique may improve the feasibility and efficacy of MMS, leading to a wider use according to clinical need.

Near-infrared confocal micro-Raman spectroscopy combined with PCA-LDA multivariate analysis for detection of esophageal cancer

NASA Astrophysics Data System (ADS)

Chen, Long; Wang, Yue; Liu, Nenrong; Lin, Duo; Weng, Cuncheng; Zhang, Jixue; Zhu, Lihuan; Chen, Weisheng; Chen, Rong; Feng, Shangyuan

2013-06-01

The diagnostic capability of using tissue intrinsic micro-Raman signals to obtain biochemical information from human esophageal tissue is presented in this paper. Near-infrared micro-Raman spectroscopy combined with multivariate analysis was applied for discrimination of esophageal cancer tissue from normal tissue samples. Micro-Raman spectroscopy measurements were performed on 54 esophageal cancer tissues and 55 normal tissues in the 400-1750 cm-1 range. The mean Raman spectra showed significant differences between the two groups. Tentative assignments of the Raman bands in the measured tissue spectra suggested some changes in protein structure, a decrease in the relative amount of lactose, and increases in the percentages of tryptophan, collagen and phenylalanine content in esophageal cancer tissue as compared to those of a normal subject. The diagnostic algorithms based on principal component analysis (PCA) and linear discriminate analysis (LDA) achieved a diagnostic sensitivity of 87.0% and specificity of 70.9% for separating cancer from normal esophageal tissue samples. The result demonstrated that near-infrared micro-Raman spectroscopy combined with PCA-LDA analysis could be an effective and sensitive tool for identification of esophageal cancer.

Implementation of physicochemical and sensory analysis in conjunction with multivariate analysis towards assessing olive oil authentication/adulteration.

PubMed

Arvanitoyannis, Ioannis S; Vlachos, Antonios

2007-01-01

The authenticity of products labeled as olive oils, and in particular as virgin olive oils, stands for a very important issue both in terms of its health and commercial aspects. In view of the continuously increasing interest in virgin olive oil therapeutic properties, the traditional methods of characterization and physical and sensory analysis were further enriched with more advanced and sophisticated methods such as HPLC-MS, HPLC-GC/C/IRMS, RPLC-GC, DEPT, and CSIA among others. The results of both traditional and "novel" methods were treated both by means of classical multivariate analysis (cluster, principal component, correspondence, canonical, and discriminant) and artificial intelligence methods showing that nowadays the adulteration of virgin olive oil with seed oil is detectable at very low percentages, sometimes even at less than 1%. Furthermore, the detection of geographical origin of olive oil is equally feasible and much more accurate in countries like Italy and Spain where databases of physical/chemical properties exist. However, this geographical origin classification can also be accomplished in the absence of such databases provided that an adequate number of oil samples are used and the parameters studied have "discriminating power."

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.

Caregiver Experiences of Discrimination and African American Adolescents' Psychological Health over Time

ERIC Educational Resources Information Center

Ford, Kahlil R.; Hurd, Noelle M.; Jagers, Robert J.; Sellers, Robert M.

2013-01-01

The present study examined the effect of caregivers' experiences of racial discrimination on their adolescent children's psychological functioning among a sample of 264 African American dyads. Potential relations between caregiver discrimination experiences and a number of indicators of adolescents' (aged 12-17) psychological functioning over time…

Imagine All the People: How the Brain Creates and Uses Personality Models to Predict Behavior

PubMed Central

Hassabis, Demis; Spreng, R. Nathan; Rusu, Andrei A.; Robbins, Clifford A.; Mar, Raymond A.; Schacter, Daniel L.

2014-01-01

The behaviors of other people are often central to envisioning the future. The ability to accurately predict the thoughts and actions of others is essential for successful social interactions, with far-reaching consequences. Despite its importance, little is known about how the brain represents people in order to predict behavior. In this functional magnetic resonance imaging study, participants learned the unique personality of 4 protagonists and imagined how each would behave in different scenarios. The protagonists' personalities were composed of 2 traits: Agreeableness and Extraversion. Which protagonist was being imagined was accurately inferred based solely on activity patterns in the medial prefrontal cortex using multivariate pattern classification, providing novel evidence that brain activity can reveal whom someone is thinking about. Lateral temporal and posterior cingulate cortex discriminated between different degrees of agreeableness and extraversion, respectively. Functional connectivity analysis confirmed that regions associated with trait-processing and individual identities were functionally coupled. Activity during the imagination task, and revealed by functional connectivity, was consistent with the default network. Our results suggest that distinct regions code for personality traits, and that the brain combines these traits to represent individuals. The brain then uses this “personality model” to predict the behavior of others in novel situations. PMID:23463340

Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization

PubMed Central

Cavagnaro, Daniel R.; Pitt, Mark A.; Gonzalez, Richard; Myung, Jay I.

2014-01-01

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models. PMID:24453406

Statistical classification techniques for engineering and climatic data samples

NASA Technical Reports Server (NTRS)

Temple, E. C.; Shipman, J. R.

1981-01-01

Fisher's sample linear discriminant function is modified through an appropriate alteration of the common sample variance-covariance matrix. The alteration consists of adding nonnegative values to the eigenvalues of the sample variance covariance matrix. The desired results of this modification is to increase the number of correct classifications by the new linear discriminant function over Fisher's function. This study is limited to the two-group discriminant problem.

FUNCTIONAL LIMITATION AND DEPRESSIVE SYMPTOMATOLOGY: CONSIDERING PERCEIVED STIGMA AND DISCRIMINATION WITHIN A STRESS AND COPING FRAMEWORK

PubMed Central

Brown, Robyn Lewis

2016-01-01

This study examines whether perceived stigma and discrimination moderate the associations between functional limitation, psychosocial coping resources, and depressive symptoms among people with physical disabilities. Using two waves of data from a large community study including a representative sample of persons with physical disabilities (N=417), an SEM-based moderated mediation analysis was performed. Mediation tests demonstrate that mastery significantly mediates the association between functional limitation and depressive symptoms over the study period. Moderated mediation tests reveal that the linkage between functional limitation and mastery varies as a function of perceived stigma and experiences of major discrimination and day-to-day discrimination, however. The implications of these findings are discussed in the context of the stress and coping literature. PMID:28497112

Classification of debtor credit status and determination amount of credit risk by using linier discriminant function

NASA Astrophysics Data System (ADS)

Aidi, Muhammad Nur; Sari, Resty Indah

2012-05-01

A decision of credit that given by bank or another creditur must have a risk and it called credit risk. Credit risk is an investor's risk of loss arising from a borrower who does not make payments as promised. The substantial of credit risk can lead to losses for the banks and the debtor. To minimize this problem need a further study to identify a potential new customer before the decision given. Identification of debtor can using various approaches analysis, one of them is by using discriminant analysis. Discriminant analysis in this study are used to classify whether belonging to the debtor's good credit or bad credit. The result of this study are two discriminant functions that can identify new debtor. Before step built the discriminant function, selection of explanatory variables should be done. Purpose of selection independent variable is to choose the variable that can discriminate the group maximally. Selection variables in this study using different test, for categoric variable selection of variable using proportion chi-square test, and stepwise discriminant for numeric variable. The result of this study are two discriminant functions that can identify new debtor. The selected variables that can discriminating two groups of debtor maximally are status of existing checking account, credit history, credit amount, installment rate in percentage of disposable income, sex, age in year, other installment plans, and number of people being liable to provide maintenance. This classification produce a classification accuracy rate is good enough, that is equal to 74,70%. Debtor classification using discriminant analysis has risk level that is small enough, and it ranged beetwen 14,992% and 17,608%. Based on that credit risk rate, using discriminant analysis on the classification of credit status can be used effectively.

Trained Musical Performers' and Musically Untrained College Students' Ability to Discriminate Music Instrument Timbre as a Function of Duration.

NASA Astrophysics Data System (ADS)

Johnston, Dennis Alan

The purpose of this study was to investigate the ability of trained musicians and musically untrained college students to discriminate music instrument timbre as a function of duration. Specific factors investigated were the thresholds for timbre discrimination as a function of duration, musical ensemble participation as training, and the relative discrimination abilities of vocalists and instrumentalists. The subjects (N = 126) were volunteer college students from intact classes from various disciplines separated into musically untrained college students (N = 43) who had not participated in musical ensembles and trained musicians (N = 83) who had. The musicians were further divided into instrumentalists (N = 51) and vocalists (N = 32). The Method of Constant Stimuli, using a same-different response procedure with 120 randomized, counterbalanced timbre pairs comprised of trumpet, clarinet, or violin, presented in durations of 20 to 100 milliseconds in a sequence of pitches, in two blocks was used for data collection. Complete, complex musical timbres were recorded digitally and presented in a sequence of changing pitches to more closely approximate an actual music listening experience. Under the conditions of this study, it can be concluded that the threshold for timbre discrimination as a function of duration is at or below 20 ms. Even though trained musicians tended to discriminate timbre better than musically untrained college students, musicians cannot discriminate timbre significantly better then those subjects who have not participated in musical ensembles. Additionally, instrumentalists tended to discriminate timbre better than vocalists, but the discrimination is not significantly different. Recommendations for further research include suggestions for a timbre discrimination measurement tool that takes into consideration the multidimensionality of timbre and the relationship of timbre discrimination to timbre source, duration, pitch, and loudness.

Characterizing populations and searching for diagnostics via elastic registration of MRI images

NASA Astrophysics Data System (ADS)

Pettey, David; Gee, James C.

2001-07-01

Given image data from two distinct populations and a family of functions, we find the scalar discriminant function which best discriminates between the populations. The goals are two-fold: first, to construct a discriminant function which can accurately and reliably classify subjects via the image data. Second, the best discriminant allows us to see which features in the images distinguish between the populations; these features can guide us to finding characteristic differences between the two groups even if these differences are not sufficient to perform classification. We apply our method to mid-sagittal MRI sections of the corpus callosum from 34 males and 52 females. While we are not certain of the ability of the derived discriminant function to perform sex classification, we find that regions in the anterior of the corpus callosum do appear to be more important for the discriminant function than other regions. This indicates there may be significant differences in the relative size of the splenium in males and females, as has been reported elsewhere. More notably, we applied previous methods which support this view on our larger data set, but found that these methods no longer show statistically significant differences between the male and female splenium.

Discrimination and Psychological Distress: Gender Differences among Arab Americans.

PubMed

Assari, Shervin; Lankarani, Maryam Moghani

2017-01-01

Despite the existing knowledge on the association between discrimination and poor mental health, very few studies have explored gender differences in this association in Arab Americans. The current study aimed to investigate whether gender moderates the association between the experience of discrimination and psychological distress in a representative sample of Arab Americans in Michigan. Using data from the Detroit Arab American Study (DAAS), 2003, this study recruited Arab Americans (337 males, 385 females) living in Michigan, United States. The main independent variable was discrimination. The main outcome was psychological distress. Covariates included demographic factors (age), socioeconomic status (education, employment, and income), and immigration characteristics (nativity and years living in United States). Gender was the focal moderator. We used multivariable regression with and without discrimination × gender interaction term. In the pooled sample, discrimination was positively associated with psychological distress [ B  = 0.62, 95% confidence interval (CI) = 0.22-1.03, p  = 0.003]. We found a significant gender × discrimination interaction in the pooled sample ( B  = 0.79, 95% CI = 0.01-1.59, p  = 0.050), suggesting a stronger association in males than females. In our gender-specific model, higher discrimination was associated with higher psychological distress among male ( B  = 0.87, 95% CI = 0.33-1.42, p  = 0.002) but not female ( B  = 0.18, 95% CI = -0.43 to 0.78, p  = 0.567) Arab Americans. While discrimination is associated with poor mental health, a stronger link between discrimination and psychological symptoms may exist in male compared to female Arab Americans. While efforts should be made to universally reduce discrimination, screening for discrimination may be a more salient component of mental health care for male than female Arab Americans.

Testing for Statistical Discrimination by Race/Ethnicity in Panel Data for Depression Treatment in Primary Care

PubMed Central

McGuire, Thomas G; Ayanian, John Z; Ford, Daniel E; Henke, Rachel E M; Rost, Kathryn M; Zaslavsky, Alan M

2008-01-01

Objective To test for discrimination by race/ethnicity arising from clinical uncertainty in treatment for depression, also known as “statistical discrimination.” Data Sources We used survey data from 1,321 African-American, Hispanic, and white adults identified with depression in primary care. Surveys were administered every six months for two years in the Quality Improvement for Depression (QID) studies. Study Design To examine whether and how change in depression severity affects change in treatment intensity by race/ethnicity, we used multivariate cross-sectional and change models that difference out unobserved time-invariant patient characteristics potentially correlated with race/ethnicity. Data Collection/Extraction Methods Treatment intensity was operationalized as expenditures on drugs, primary care, and specialty services, weighted by national prices from the Medical Expenditure Panel Survey. Patient race/ethnicity was collected at baseline by self-report. Principal Findings Change in depression severity is less associated with change in treatment intensity in minority patients than in whites, consistent with the hypothesis of statistical discrimination. The differential effect by racial/ethnic group was accounted for by use of mental health specialists. Conclusions Enhanced physician–patient communication and use of standardized depression instruments may reduce statistical discrimination arising from clinical uncertainty and be useful in reducing racial/ethnic inequities in depression treatment. PMID:18370966

Facial patterns in a tropical social wasp correlate with colony membership

NASA Astrophysics Data System (ADS)

Baracchi, David; Turillazzi, Stefano; Chittka, Lars

2016-10-01

Social insects excel in discriminating nestmates from intruders, typically relying on colony odours. Remarkably, some wasp species achieve such discrimination using visual information. However, while it is universally accepted that odours mediate a group level recognition, the ability to recognise colony members visually has been considered possible only via individual recognition by which wasps discriminate `friends' and `foes'. Using geometric morphometric analysis, which is a technique based on a rigorous statistical theory of shape allowing quantitative multivariate analyses on structure shapes, we first quantified facial marking variation of Liostenogaster flavolineata wasps. We then compared this facial variation with that of chemical profiles (generated by cuticular hydrocarbons) within and between colonies. Principal component analysis and discriminant analysis applied to sets of variables containing pure shape information showed that despite appreciable intra-colony variation, the faces of females belonging to the same colony resemble one another more than those of outsiders. This colony-specific variation in facial patterns was on a par with that observed for odours. While the occurrence of face discrimination at the colony level remains to be tested by behavioural experiments, overall our results suggest that, in this species, wasp faces display adequate information that might be potentially perceived and used by wasps for colony level recognition.

Comprehensive analysis of Polygoni Multiflori Radix of different geographical origins using ultra-high-performance liquid chromatography fingerprints and multivariate chemometric methods.

PubMed

Sun, Li-Li; Wang, Meng; Zhang, Hui-Jie; Liu, Ya-Nan; Ren, Xiao-Liang; Deng, Yan-Ru; Qi, Ai-Di

2018-01-01

Polygoni Multiflori Radix (PMR) is increasingly being used not just as a traditional herbal medicine but also as a popular functional food. In this study, multivariate chemometric methods and mass spectrometry were combined to analyze the ultra-high-performance liquid chromatograph (UPLC) fingerprints of PMR from six different geographical origins. A chemometric strategy based on multivariate curve resolution-alternating least squares (MCR-ALS) and three classification methods is proposed to analyze the UPLC fingerprints obtained. Common chromatographic problems, including the background contribution, baseline contribution, and peak overlap, were handled by the established MCR-ALS model. A total of 22 components were resolved. Moreover, relative species concentrations were obtained from the MCR-ALS model, which was used for multivariate classification analysis. Principal component analysis (PCA) and Ward's method have been applied to classify 72 PMR samples from six different geographical regions. The PCA score plot showed that the PMR samples fell into four clusters, which related to the geographical location and climate of the source areas. The results were then corroborated by Ward's method. In addition, according to the variance-weighted distance between cluster centers obtained from Ward's method, five components were identified as the most significant variables (chemical markers) for cluster discrimination. A counter-propagation artificial neural network has been applied to confirm and predict the effects of chemical markers on different samples. Finally, the five chemical markers were identified by UPLC-quadrupole time-of-flight mass spectrometer. Components 3, 12, 16, 18, and 19 were identified as 2,3,5,4'-tetrahydroxy-stilbene-2-O-β-d-glucoside, emodin-8-O-β-d-glucopyranoside, emodin-8-O-(6'-O-acetyl)-β-d-glucopyranoside, emodin, and physcion, respectively. In conclusion, the proposed method can be applied for the comprehensive analysis of natural samples. Copyright © 2016. Published by Elsevier B.V.

Parasites as Biological Tags for Stock Discrimination of Beaked Redfish (Sebastes mentella): Parasite Infra-Communities vs. Limited Resolution of Cytochrome Markers

PubMed Central

Klapper, Regina; Kochmann, Judith; O’Hara, Robert B.; Karl, Horst; Kuhn, Thomas

2016-01-01

The use of parasites as biological tags for discrimination of fish stocks has become a commonly used approach in fisheries management. Metazoan parasite community analysis and anisakid nematode population genetics based on a mitochondrial cytochrome marker were applied in order to assess the usefulness of the two parasitological methods for stock discrimination of beaked redfish Sebastes mentella of three fishing grounds in the North East Atlantic. Multivariate, model-based approaches demonstrated that the metazoan parasite fauna of beaked redfish from East Greenland differed from Tampen, northern North Sea, and Bear Island, Barents Sea. A joint model (latent variable model) was used to estimate the effects of covariates on parasite species and identified four parasite species as main source of differences among fishing grounds; namely Chondracanthus nodosus, Anisakis simplex s.s., Hysterothylacium aduncum, and Bothriocephalus scorpii. Due to its high abundance and differences between fishing grounds, Anisakis simplex s.s. was considered as a major biological tag for host stock differentiation. Whilst the sole examination of Anisakis simplex s.s. on a population genetic level is only of limited use, anisakid nematodes (in particular, A. simplex s.s.) can serve as biological tags on a parasite community level. This study confirmed the use of multivariate analyses as a tool to evaluate parasite infra-communities and to identify parasite species that might serve as biological tags. The present study suggests that S. mentella in the northern North Sea and Barents Sea is not sub-structured. PMID:27104735

Quantifying surgical complexity with machine learning: looking beyond patient factors to improve surgical models.

PubMed

Van Esbroeck, Alexander; Rubinfeld, Ilan; Hall, Bruce; Syed, Zeeshan

2014-11-01

To investigate the use of machine learning to empirically determine the risk of individual surgical procedures and to improve surgical models with this information. American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) data from 2005 to 2009 were used to train support vector machine (SVM) classifiers to learn the relationship between textual constructs in current procedural terminology (CPT) descriptions and mortality, morbidity, Clavien 4 complications, and surgical-site infections (SSI) within 30 days of surgery. The procedural risk scores produced by the SVM classifiers were validated on data from 2010 in univariate and multivariate analyses. The procedural risk scores produced by the SVM classifiers achieved moderate-to-high levels of discrimination in univariate analyses (area under receiver operating characteristic curve: 0.871 for mortality, 0.789 for morbidity, 0.791 for SSI, 0.845 for Clavien 4 complications). Addition of these scores also substantially improved multivariate models comprising patient factors and previously proposed correlates of procedural risk (net reclassification improvement and integrated discrimination improvement: 0.54 and 0.001 for mortality, 0.46 and 0.011 for morbidity, 0.68 and 0.022 for SSI, 0.44 and 0.001 for Clavien 4 complications; P < .05 for all comparisons). Similar improvements were noted in discrimination and calibration for other statistical measures, and in subcohorts comprising patients with general or vascular surgery. Machine learning provides clinically useful estimates of surgical risk for individual procedures. This information can be measured in an entirely data-driven manner and substantially improves multifactorial models to predict postoperative complications. Copyright © 2014 Elsevier Inc. All rights reserved.

Prevalence and correlates of substance use among trans*female youth ages 16–24 years in the San Francisco Bay Area

PubMed Central

Rowe, Chris; Santos, Glenn-Milo; McFarland, Willi; Wilson, Erin C.

2014-01-01

Background Substance use is highly prevalent among transgender (trans*) females and has been associated with negative health outcomes, including HIV infection. Little is known about psychosocial risk factors that may influence the onset of substance use among trans*female youth, which can contribute to health disparities during adulthood. Methods We conducted a secondary data analysis of a study on HIV risk and resilience among trans*female youth (N=292). Prevalence of substance use was assessed and multivariable logistic regression models were used to examine the relationship between posttraumatic stress disorder (PTSD), psychological distress, gender-related discrimination, parental drug or alcohol problems (PDAP) and multiple substance use outcomes. Results Most (69%) of the trans*female youth reported recent drug use. In multivariable analyses, those with PTSD had increased odds of drug use [AOR=1.94 (95%CI=1.09–3.44)]. Those who experienced gender-related discrimination had increased odds of drug use [AOR=2.28 (95%CI=1.17–4.44)], drug use concurrent with sex [AOR=2.35 (95%CI=1.11–4.98)] and use of multiple drugs [AOR=3.24 (95%CI=1.52–6.88)]. Those with psychological distress had increased odds of using multiple heavy drugs [AOR=2.27 (95%CI=1.01–5.12)]. Those with PDAP had increased odds of drugs use [AOR=2.62 (95%CI=1.43–4.82)], drug use concurrent with sex [AOR=2.01 (95%CI, 1.15–3.51)] and use of multiple drugs [AOR=2.10 (95%CI=1.22–3.62)]. Conclusions Substance use is highly prevalent among trans*female youth and was significantly associated with psychosocial risk factors. In order to effectively address substance use among trans*female youth, efforts must address coping related to gender-based discrimination and trauma. Furthermore, structural level interventions aiming to reduce stigma and gender-identity discrimination might also be effective. PMID:25548025

Discrimination of Gastrodia elata from Different Geographical Origin for Quality Evaluation Using Newly-Build Near Infrared Spectrum Coupled with Multivariate Analysis.

PubMed

Zuo, Yamin; Deng, Xuehua; Wu, Qing

2018-05-04

Discrimination of Gastrodia elata ( G. elata ) geographical origin is of great importance to pharmaceutical companies and consumers in China. this paper focuses on the feasibility of near infrared spectrum (NIRS) combined multivariate analysis as a rapid and non-destructive method to prove its fit for this purpose. Firstly, 16 batches of G. elata samples from four main-cultivation regions in China were quantified by traditional HPLC method. It showed that samples from different origins could not be efficiently differentiated by the contents of four phenolic compounds in this study. Secondly, the raw near infrared (NIR) spectra of those samples were acquired and two different pattern recognition techniques were used to classify the geographical origins. The results showed that with spectral transformation optimized, discriminant analysis (DA) provided 97% and 99% correct classification for the calibration and validation sets of samples from discriminating of four different main-cultivation regions, and provided 98% and 99% correct classifications for the calibration and validation sets of samples from eight different cities, respectively, which all performed better than the principal component analysis (PCA) method. Thirdly, as phenolic compounds content (PCC) is highly related with the quality of G. elata , synergy interval partial least squares (Si-PLS) was applied to build the PCC prediction model. The coefficient of determination for prediction (R p ²) of the Si-PLS model was 0.9209, and root mean square error for prediction (RMSEP) was 0.338. The two regions (4800 cm −1 ⁻5200 cm −1 , and 5600 cm −1 ⁻6000 cm −1 ) selected by Si-PLS corresponded to the absorptions of aromatic ring in the basic phenolic structure. It can be concluded that NIR spectroscopy combined with PCA, DA and Si-PLS would be a potential tool to provide a reference for the quality control of G. elata.

Prevalence and correlates of substance use among trans female youth ages 16-24 years in the San Francisco Bay Area.

PubMed

Rowe, Chris; Santos, Glenn-Milo; McFarland, Willi; Wilson, Erin C

2015-02-01

Substance use is highly prevalent among transgender (trans*) females and has been associated with negative health outcomes, including HIV infection. Little is known about psychosocial risk factors that may influence the onset of substance use among trans*female youth, which can contribute to health disparities during adulthood. We conducted a secondary data analysis of a study on HIV risk and resilience among trans*female youth (N=292). Prevalence of substance use was assessed and multivariable logistic regression models were used to examine the relationship between posttraumatic stress disorder (PTSD), psychological distress, gender-related discrimination, parental drug or alcohol problems (PDAP) and multiple substance use outcomes. Most (69%) of the trans*female youth reported recent drug use. In multivariable analyses, those with PTSD had increased odds of drug use [AOR=1.94 (95% CI=1.09-3.44)]. Those who experienced gender-related discrimination had increased odds of drug use [AOR=2.28 (95% CI=1.17-4.44)], drug use concurrent with sex [AOR=2.35 (95% CI=1.11-4.98)] and use of multiple drugs [AOR=3.24 (95% CI=1.52-6.88)]. Those with psychological distress had increased odds of using multiple heavy drugs [AOR=2.27 (95% CI=1.01-5.12)]. Those with PDAP had increased odds of drugs use [AOR=2.62 (95% CI=1.43-4.82)], drug use concurrent with sex [AOR=2.01 (95% CI, 1.15-3.51)] and use of multiple drugs [AOR=2.10 (95% CI=1.22-3.62)]. Substance use is highly prevalent among trans*female youth and was significantly associated with psychosocial risk factors. In order to effectively address substance use among trans*female youth, efforts must address coping related to gender-based discrimination and trauma. Furthermore, structural level interventions aiming to reduce stigma and gender-identity discrimination might also be effective. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Hypertensive heart disease versus hypertrophic cardiomyopathy: multi-parametric cardiovascular magnetic resonance discriminators when end-diastolic wall thickness ≥ 15 mm.

PubMed

Rodrigues, Jonathan C L; Rohan, Stephen; Ghosh Dastidar, Amardeep; Harries, Iwan; Lawton, Christopher B; Ratcliffe, Laura E; Burchell, Amy E; Hart, Emma C; Hamilton, Mark C K; Paton, Julian F R; Nightingale, Angus K; Manghat, Nathan E

2017-03-01

European guidelines state left ventricular (LV) end-diastolic wall thickness (EDWT) ≥15mm suggests hypertrophic cardiomyopathy (HCM), but distinguishing from hypertensive heart disease (HHD) is challenging. We identify cardiovascular magnetic resonance (CMR) predictors of HHD over HCM when EDWT ≥15mm. 2481 consecutive clinical CMRs between 2014 and 2015 were reviewed. 464 segments from 29 HCM subjects with EDWT ≥15mm but without other cardiac abnormality, hypertension or renal impairment were analyzed. 432 segments from 27 HHD subjects with EDWT ≥15mm but without concomitant cardiac pathology were analyzed. Magnitude and location of maximal EDWT, presence of late gadolinium enhancement (LGE), LV asymmetry (>1.5-fold opposing segment) and systolic anterior motion of the mitral valve (SAM) were measured. Multivariate logistic regression was performed. Significance was defined as p<0.05. HHD and HCM cohorts were age-/gender-matched. HHD had significantly increased indexed LV mass (110±27g/m 2 vs. 91±31g/m 2 , p=0.016) but no difference in site or magnitude of maximal EDWT. Mid-wall LGE was significantly more prevalent in HCM. Elevated indexed LVM, mid-wall LGE and absence of SAM were significant multivariate predictors of HHD, but LV asymmetry was not. Increased indexed LV mass, absence of mid-wall LGE and absence of SAM are better CMR discriminators of HHD from HCM than EDWT ≥15mm. • Hypertrophic cardiomyopathy (HCM) is often diagnosed with end-diastolic wall thickness ≥15mm. • Hypertensive heart disease (HHD) can be difficult to distinguish from HCM. • Retrospective case-control study showed that location and magnitude of EDWT are poor discriminators. • Increased left ventricular mass and midwall fibrosis are independent predictors of HHD. • Cardiovascular magnetic resonance parameters facilitate a better discrimination between HHD and HCM.

Frequency discriminator/phase detector

NASA Technical Reports Server (NTRS)

Crow, R. B.

1974-01-01

Circuit provides dual function of frequency discriminator/phase detector which reduces frequency acquisition time without adding to circuit complexity. Both frequency discriminators, in evaluated frequency discriminator/phase detector circuits, are effective two decades above and below center frequency.

Apolipoprotein E4 serum concentration for increased sensitivity and specificity of diagnosis of drug treated Alzheimer's disease patients vs. drug treated parkinson's disease patients vs. age-matched normal controls.

PubMed

Goldknopf, Ira L; Park, Helen R; Sabbagh, Marwan

2012-12-01

Inasmuch as Alzheimer's disease (AD) is difficult to diagnose, patients with suspected dementias are often given FDA approved medications, including donepezil, rivastigmine, memantine HCl, or a combination, prior to diagnosis, and some respond with improved cognition. The present study demonstrates how concentrations of a select group of serum protein biomarkers can provide the basis for sensitive and specific differential diagnosis of AD in drug treated patients. Optimization is addressed by taking into account whether the patients and controls have or do not have increased risk of AD die to the presence or absence of Apolipoprotein E4. For differential diagnosis of AD, prospectively collected newly drawn blood serum samples were obtained from drug treated Alzheimer's disease and Parkinson's disease patients from a first (39 drug treated DTAD, and 31 age matched normal controls) and second medical center (56 drug treated DTPD, 47 age-matched normal controls). Analytically validated quantitative 2D gel electrophoresis (%CV ≤ 20%; LOD ≥ 0.5 ng/spot, 300 μg/ml of blood serum) was employed with patient and control sera for differential diagnosis of AD. Protein quantitation was subjected to statistical analysis by single variable Dot, Box and Whiskers and Receiver Operator Characteristics (ROC) plots for individual biomarker performance, and multivariate linear discriminant analysis for joint performance of groups of biomarkers. Protein spots were identified and characterized by LC MS/MS of in-gel trypsin digests, amino acid sequence spans of the identified peptides, and the protein spot molecular weights and isoelectric points. The single variable statistical profiles of 58 individual protein biomarker concentrations of the DTAD patient group differed from those of the normal and/or the disease control groups. Multivariate linear discriminant analysis of blood serum concentrations of the 58 proteins distinguished drug treated Alzheimer's disease (DTAD) patients from drug treated Parkinson's disease (DTPD) patients and age matched normal controls (collectively not-DTAD, DTAD Sensitivity 87.2%, Not-DTAD Specificity 87.2). Moreover, when the patients and controls were stratified into carriers or non-carriers of Alzheimer's high risk Apolipoprotein E 4 allele and/or the Apolipoprotein E4 protein, the DTAD, DTPD and control Apo E4 (+) profiles were more divergent from one another than the corresponding Apo E4 (-) profiles. Multivariate stepwise linear discriminant analysis selected 17 of the 58 biomarkers as optimal and complimentary for distinguishing Apo E4 (+) DTAD patients from Apo E4 (+) DTPD and Apo E4 (+) controls (collectively Apo E4 (+) not-DTAD, DTAD Sensitivity 100%, not-DTAD Specificity 100%) and 22 of the 58 biomarkers for distinguishing Apo E4 (-) DTAD patients from Apo E4 (-) DTPD and Apo E4 (-) controls (collectively Apo E4 (-) not-DTAD, DTAD Sensitivity 94.4%, not- DTAD Specificity 94.4%). Only 6 of the selected proteins were common to both the Apo E4 (+) and the Apo E4 (-) discriminant functions. Recombining of the results of Apo E4 (+) and Apo E4 (-) discriminations provided overall sensitivity for total DTAD of 97.4% and specificity for total not-DTAD of 95.7%. These results can form the basis of a blood test for differential diagnosis of Alzheimer's disease patients already under treatment (DTAD) by anti dementia drugs, including donepezil, rivastigmine, memantine HCl, or a combination thereof. Also, the profile differences and the rise in specificity and sensitivity obtained by handling the Apo E4 (+) and Apo E4 (-) groups separately supports the concept that they are different patient and control populations in terms of the "normal" physiology, the pathophysiology of disease, and the response to drug treatment. Taking that into account enables increased sensitivity and specificity of differential diagnosis of Alzheimer's disease.

Establishing Pragmatic Discriminations among the Communicative Functions of Requesting, Rejecting, and Commenting in an Adolescent.

ERIC Educational Resources Information Center

Reichle, Joe; And Others

1984-01-01

A 15-year-old with severe handicaps who exhibited minimal intentional communicative behavior was taught to discriminately encode three classes of communicative functions. Results suggest that pragmatic discriminations can be established early in a sequence of communication intervention. The S used requesting and rejecting spontaneously in other…

Moving Beyond Univariate Post-Hoc Testing in Exercise Science: A Primer on Descriptive Discriminate Analysis.

PubMed

Barton, Mitch; Yeatts, Paul E; Henson, Robin K; Martin, Scott B

2016-12-01

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 variables. However, this univariate approach decreases power, increases the risk for Type 1 error, and contradicts the rationale for conducting multivariate tests in the first place. The purpose of this study was to provide a user-friendly primer on conducting descriptive discriminant analysis (DDA), which is a post-hoc strategy to MANOVA that takes into account the complex relationships among multiple dependent variables. A real-world example using the Statistical Package for the Social Sciences syntax and data from 1,095 middle school students on their body composition and body image are provided to explain and interpret the results from DDA. While univariate post hocs increased the risk for Type 1 error to 76%, the DDA identified which dependent variables contributed to group differences and which groups were different from each other. For example, students in the very lean and Healthy Fitness Zone categories for body mass index experienced less pressure to lose weight, more satisfaction with their body, and higher physical self-concept than the Needs Improvement Zone groups. However, perceived pressure to gain weight did not contribute to group differences because it was a suppressor variable. Researchers are encouraged to use DDA when investigating group differences on multiple correlated dependent variables to determine which variables contributed to group differences.

Socio-Demographic and Clinical Characteristics are Not Clinically Useful Predictors of Refill Adherence in Patients with Hypertension

PubMed Central

Steiner, John F.; Ho, P. Michael; Beaty, Brenda L.; Dickinson, L. Miriam; Hanratty, Rebecca; Zeng, Chan; Tavel, Heather M.; Havranek, Edward P.; Davidson, Arthur J.; Magid, David J.; Estacio, Raymond O.

2009-01-01

Background Although many studies have identified patient characteristics or chronic diseases associated with medication adherence, the clinical utility of such predictors has rarely been assessed. We attempted to develop clinical prediction rules for adherence with antihypertensive medications in two health care delivery systems. Methods and Results Retrospective cohort studies of hypertension registries in an inner-city health care delivery system (N = 17176) and a health maintenance organization (N = 94297) in Denver, Colorado. Adherence was defined by acquisition of 80% or more of antihypertensive medications. A multivariable model in the inner-city system found that adherent patients (36.3% of the total) were more likely than non-adherent patients to be older, white, married, and acculturated in US society, to have diabetes or cerebrovascular disease, not to abuse alcohol or controlled substances, and to be prescribed less than three antihypertensive medications. Although statistically significant, all multivariate odds ratios were 1.7 or less, and the model did not accurately discriminate adherent from non-adherent patients (C-statistic = 0.606). In the health maintenance organization, where 72.1% of patients were adherent, significant but weak associations existed between adherence and older age, white race, the lack of alcohol abuse, and fewer antihypertensive medications. The multivariate model again failed to accurately discriminate adherent from non-adherent individuals (C-statistic = 0.576). Conclusions Although certain socio-demographic characteristics or clinical diagnoses are statistically associated with adherence to refills of antihypertensive medications, a combination of these characteristics is not sufficiently accurate to allow clinicians to predict whether their patients will be adherent with treatment. PMID:20031876

Toward a neurologic model of competency: Cognitive predictors of capacity to consent in Alzheimer's disease using three different legal standards.

PubMed

Marson, D C; Chatterjee, A; Ingram, K K; Harrell, L E

1996-03-01

To identify cognitive predictors of competency performance and status in Alzheimer's disease (AD) using three differentially stringent legal standards for capacity to consent. Univariate and multivariate analyses of independent neuropsychological test measures with three dependent measures of competency to consent to treatment. University medical center. 15 normal older controls and 29 patients with probably AD (15 mild and 14 moderate). Subjects were administered a batter of neuropsychological measures theoretically linked to competency function, as well as two clinical vignettes testing capacity to consent to medical treatment under five legal standards (LSs). The present study focused on three differentially stringent LSs: the capacity simply to "evidence a treatment of choice" (LS1), which is a minimal standard; the capacity to "appreciate the consequences" of a treatment of choice (LS3), a moderately stringent standard; and the capacity to "understand the treatment situation and choices" (LS5), the most stringent standard. Control subject and AD patient neuropsychological test scores were correlated with scores on the three LSs. The resulting univariate correlates were than analyzed using stepwise regression and discriminant function to identify key multivariate predictors of competency performance and status under each LS. No neuropsychological measures predicted control group performance on the LSs. For the AD group, a measure of simple auditory comprehension predicted LS1 performance (r(2)=0.44, p < 0.0001), a word fluency measure predicted LS3 performance (r(2)=0.58, p < 0.0001), and measures of conceptualization and confrontation naming together predicted LS5 performance (r(2)=0.81, p < 0.0001). Under discriminant function analysis, confrontation naming was the best single predictor of LS1 competency status for all subjects, correctly classifying 96% of cases (42/44). Measures of visumotor tracking and confrontation naming were the best single predictors, respectively, of competency status under LS3 (91% [39/43]) and LS5 (98% [43/44]). Multiple cognitive functions are associated with loss of competency in AD. Deficits in conceptualization, semantic memory, and probably verbal recall are associated with the declining capacity of mild AD patients to understand a treatment situation and choices (LS5); executive dysfunction with the declining capacity of mild to moderate AD patients to identify the consequences of treatment choice (LS3); and receptive aphasia and severe dysnomia with the declining capacity of advanced AD patients to evidence a simple treatment choice (LS1). The results offer insight into the relationship between different legal thresholds of competency and the progressive cognitive changes characteristic of AD, and represent an initial step toward a neurologic model of competency.

Identification of Uranium Minerals in Natural U-Bearing Rocks Using Infrared Reflectance Spectroscopy.

PubMed

Beiswenger, Toya N; Gallagher, Neal B; Myers, Tanya L; Szecsody, James E; Tonkyn, Russell G; Su, Yin-Fong; Sweet, Lucas E; Lewallen, Tricia A; Johnson, Timothy J

2018-02-01

The identification of minerals, including uranium-bearing species, is often a labor-intensive process using X-ray diffraction (XRD), fluorescence, or other solid-phase or wet chemical techniques. While handheld XRD and fluorescence instruments can aid in field applications, handheld infrared (IR) reflectance spectrometers can now also be used in industrial or field environments, with rapid, nondestructive identification possible via analysis of the solid's reflectance spectrum providing information not found in other techniques. In this paper, we report the use of laboratory methods that measure the IR hemispherical reflectance of solids using an integrating sphere and have applied it to the identification of mineral mixtures (i.e., rocks), with widely varying percentages of uranium mineral content. We then apply classical least squares (CLS) and multivariate curve resolution (MCR) methods to better discriminate the minerals (along with two pure uranium chemicals U 3 O 8 and UO 2 ) against many common natural and anthropogenic background materials (e.g., silica sand, asphalt, calcite, K-feldspar) with good success. Ground truth as to mineral content was attained primarily by XRD. Identification is facile and specific, both for samples that are pure or are partially composed of uranium (e.g., boltwoodite, tyuyamunite, etc.) or non-uranium minerals. The characteristic IR bands generate unique (or class-specific) bands, typically arising from similar chemical moieties or functional groups in the minerals: uranyls, phosphates, silicates, etc. In some cases, the chemical groups that provide spectral discrimination in the longwave IR reflectance by generating upward-going (reststrahlen) bands can provide discrimination in the midwave and shortwave IR via downward-going absorption features, i.e., weaker overtone or combination bands arising from the same chemical moieties.

The Role of Perceived Discrimination in Obesity Among African Americans.

PubMed

Stepanikova, Irena; Baker, Elizabeth H; Simoni, Zachary R; Zhu, Aowen; Rutland, Sarah B; Sims, Mario; Wilkinson, Larrell L

2017-01-01

African Americans, especially those in the South, suffer a disproportionate burden of obesity and are at high risk for perceived discrimination (PD). This study investigates the association between PD and weight status among African Americans and clarifies the role of perceived stress and health behaviors in this relationship. Data came from the Jackson Heart Study, Examination 1 (2000-2004; analyses conducted in 2016 using Stata, version 14). African Americans from Jackson, Mississippi, aged 21-95 years were recruited (N=5,301). Weight status was measured using anthropometric data with BMI; waist circumference (in centimeters); and obesity class (I, II, III). Survey instruments were used to measure PD, perceived global stress, and health behaviors. Multivariate regression was used to model weight status outcomes as a function of PD, perceived stress, and health behaviors. After controlling for sociodemographic factors and health status, perceived everyday discrimination was associated with higher BMI (b=0.33, p<0.01); higher waist circumference (b=0.70, p<0.01); and higher relative risk of Class III obesity versus non-obesity (relative risk ratio, 1.18; p<0.001). Global perceived stress was linked to higher BMI (b=0.42, p<0.05) and higher waist circumference (b=1.18; p<0.01) and partially mediated the relationships between PD and these weight status outcomes. Health behaviors led to suppression rather than mediation between PD and weight status and between stress and weight status. PD and perceived stress are potential risk factors for higher weight status. They should be considered as a part of a comprehensive approach to reduce obesity among African Americans. Published by Elsevier Inc.

Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.

PubMed

Yourganov, Grigori; Schmah, Tanya; Churchill, Nathan W; Berman, Marc G; Grady, Cheryl L; Strother, Stephen C

2014-08-01

The field of fMRI data analysis is rapidly growing in sophistication, particularly in the domain of multivariate pattern classification. However, the interaction between the properties of the analytical model and the parameters of the BOLD signal (e.g. signal magnitude, temporal variance and functional connectivity) is still an open problem. We addressed this problem by evaluating a set of pattern classification algorithms on simulated and experimental block-design fMRI data. The set of classifiers consisted of linear and quadratic discriminants, linear support vector machine, and linear and nonlinear Gaussian naive Bayes classifiers. For linear discriminant, we used two methods of regularization: principal component analysis, and ridge regularization. The classifiers were used (1) to classify the volumes according to the behavioral task that was performed by the subject, and (2) to construct spatial maps that indicated the relative contribution of each voxel to classification. Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps. In simulated data sets, we performed an additional evaluation of spatial maps with ROC analysis. We varied the magnitude, temporal variance and connectivity of simulated fMRI signal and identified the optimal classifier for each simulated environment. Overall, the best performers were linear and quadratic discriminants (operating on principal components of the data matrix) and, in some rare situations, a nonlinear Gaussian naïve Bayes classifier. The results from the simulated data were supported by within-subject analysis of experimental fMRI data, collected in a study of aging. This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI. Copyright © 2014 Elsevier Inc. All rights reserved.

NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics.

PubMed

Kumar, Deepak; Gupta, Ashish; Mandhani, Anil; Sankhwar, Satya Narain

2016-09-01

To address the shortcomings of digital rectal examinations (DRE), serum prostate-specific antigen (PSA), and trans-rectal ultrasound (TRUS) for precise determination of prostate cancer (PC) and differentiation from benign prostatic hyperplasia (BPH), we applied (1) H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate tactic for probing and prediction of PC and BPH. The study comprises 210 filtered sera from suspected PC, BPH, and a healthy subjects' cohort (HC). The filtered serum approach delineates to identify and quantify 52 metabolites using (1) H NMR spectroscopy. All subjects had undergone clinical evaluations (DRE, PSA, and TRUS) followed by biopsy for Gleason score, if needed. NMR-measured metabolites and clinical evaluation data were examined separately using linear multivariate discriminant function analysis (DFA) to probe the signature descriptors for each cohort. DFA indicated that glycine, sarcosine, alanine, creatine, xanthine, and hypoxanthine were able to determine abnormal prostate (BPH + PC). DFA-based classification presented high precision (86.2% by NMR and 68.1% by clinical laboratory method) in discriminating HC from BPH + PC. DFA reveals that alanine, sarcosine, creatinine, glycine, and citrate were able to discriminate PC from BPH. DFA-based categorization exhibited high accuracy (88.3% by NMR and 75.2% by clinical laboratory method) to differentiate PC from BPH. (1) H NMR-based metabolic profiling of filtered-serum sample appears to be assuring, swift, and least-invasive for probing and prediction of PC and BPH with its signature metabolic profile. This novel technique is not only on a par with histopathological evaluation of PC determination but is also comparable to liquid chromatography-based mass spectrometry to identify the metabolites. Prostate 76:1106-1119, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Differentiation between pine woods according to species and growing location using FTIR-ATR.

PubMed

Traoré, Mohamed; Kaal, Joeri; Martínez Cortizas, Antonio

2018-01-01

Attenuated total reflectance-Fourier transform infrared (FTIR-ATR) spectroscopy was applied to 120 samples of heartwood rings from eight individual pine trees from different locations in Spain. Pinus sylvestris cores were collected at the Artikutza natural park (Ps-ART). Pinus nigra cores were collected in Sierra de Cazorla (Pn-LIN) and in La Sagra Mountain (Pn-LSA). Three discriminant analysis tests were performed using all bands (DF T ), lignin bands only (DF L ) and polysaccharides bands only (DF P ), to explore the ability of FTIR-ATR to separate between species and growing location. The DF L model enabled a good separation between pine species, whereas the DF P model enabled differentiation for both species and growing location. The DF T model enabled virtually perfect separation, based on two functions involving twelve FTIR bands. Discrimination between species was related to bands at 860 and 1655 cm -1 , which were more intense in P. sylvestris samples, and bands at 1425 and 1635 cm -1 , more intense in P. nigra samples. These vibrations were related to differences in lignin structure and polysaccharide linear chains. Discrimination between growing locations was mainly related to polysaccharide absorptions: at 900, 1085 and 1335 cm -1 more representative of Pn-LIN samples, and at 1105 and 1315 cm -1 mostly associated to Pn-LSA samples. These absorptions are related to β-glycosidic linkages (900 cm -1 ), cellulose and hemicellulose (C-O bonds, 1085 and 1105 cm -1 ) and content in amorphous/crystalline cellulose (1315 and 1335 cm -1 ). These results show that FTIR-ATR in combination with multivariate statistics can be a useful tool for species identification and provenancing for pine wood samples of unknown origin.

Problems of stock definition in estimating relative contributions of Atlantic striped bass to the coastal fishery

USGS Publications Warehouse

Waldman, John R.; Fabrizio, Mary C.

1994-01-01

Stock contribution studies of mixed-stock fisheries rely on the application of classification algorithms to samples of unknown origin. Although the performance of these algorithms can be assessed, there are no guidelines regarding decisions about including minor stocks, pooling stocks into regional groups, or sampling discrete substocks to adequately characterize a stock. We examined these questions for striped bass Morone saxatilis of the U.S. Atlantic coast by applying linear discriminant functions to meristic and morphometric data from fish collected from spawning areas. Some of our samples were from the Hudson and Roanoke rivers and four tributaries of the Chesapeake Bay. We also collected fish of mixed-stock origin from the Atlantic Ocean near Montauk, New York. Inclusion of the minor stock from the Roanoke River in the classification algorithm decreased the correct-classification rate, whereas grouping of the Roanoke River and Chesapeake Bay stock into a regional (''southern'') group increased the overall resolution. The increased resolution was offset by our inability to obtain separate contribution estimates of the groups that were pooled. Although multivariate analysis of variance indicated significant differences among Chesapeake Bay substocks, increasing the number of substocks in the discriminant analysis decreased the overall correct-classification rate. Although the inclusion of one, two, three, or four substocks in the classification algorithm did not greatly affect the overall correct-classification rates, the specific combination of substocks significantly affected the relative contribution estimates derived from the mixed-stock sample. Future studies of this kind must balance the costs and benefits of including minor stocks and would profit from examination of the variation in discriminant characters among all Chesapeake Bay substocks.

Identifying States along the Hematopoietic Stem Cell Differentiation Hierarchy with Single Cell Specificity via Raman Spectroscopy.

PubMed

Ilin, Yelena; Choi, Ji Sun; Harley, Brendan A C; Kraft, Mary L

2015-11-17

A major challenge for expanding specific types of hematopoietic cells ex vivo for the treatment of blood cell pathologies is identifying the combinations of cellular and matrix cues that direct hematopoietic stem cells (HSC) to self-renew or differentiate into cell populations ex vivo. Microscale screening platforms enable minimizing the number of rare HSCs required to screen the effects of numerous cues on HSC fate decisions. These platforms create a strong demand for label-free methods that accurately identify the fate decisions of individual hematopoietic cells at specific locations on the platform. We demonstrate the capacity to identify discrete cells along the HSC differentiation hierarchy via multivariate analysis of Raman spectra. Notably, cell state identification is accurate for individual cells and independent of the biophysical properties of the functionalized polyacrylamide gels upon which these cells are cultured. We report partial least-squares discriminant analysis (PLS-DA) models of single cell Raman spectra enable identifying four dissimilar hematopoietic cell populations across the HSC lineage specification. Successful discrimination was obtained for a population enriched for long-term repopulating HSCs (LT-HSCs) versus their more differentiated progeny, including closely related short-term repopulating HSCs (ST-HSCs) and fully differentiated lymphoid (B cells) and myeloid (granulocytes) cells. The lineage-specific differentiation states of cells from these four subpopulations were accurately identified independent of the stiffness of the underlying biomaterial substrate, indicating subtle spectral variations that discriminated these populations were not masked by features from the culture substrate. This approach enables identifying the lineage-specific differentiation stages of hematopoietic cells on biomaterial substrates of differing composition and may facilitate correlating hematopoietic cell fate decisions with the extrinsic cues that elicited them.

Comparing classification methods for diffuse reflectance spectra to improve tissue specific laser surgery.

PubMed

Engelhardt, Alexander; Kanawade, Rajesh; Knipfer, Christian; Schmid, Matthias; Stelzle, Florian; Adler, Werner

2014-07-16

In the field of oral and maxillofacial surgery, newly developed laser scalpels have multiple advantages over traditional metal scalpels. However, they lack haptic feedback. This is dangerous near e.g. nerve tissue, which has to be preserved during surgery. One solution to this problem is to train an algorithm that analyzes the reflected light spectra during surgery and can classify these spectra into different tissue types, in order to ultimately send a warning or temporarily switch off the laser when critical tissue is about to be ablated. Various machine learning algorithms are available for this task, but a detailed analysis is needed to assess the most appropriate algorithm. In this study, a small data set is used to simulate many larger data sets according to a multivariate Gaussian distribution. Various machine learning algorithms are then trained and evaluated on these data sets. The algorithms' performance is subsequently evaluated and compared by averaged confusion matrices and ultimately by boxplots of misclassification rates. The results are validated on the smaller, experimental data set. Most classifiers have a median misclassification rate below 0.25 in the simulated data. The most notable performance was observed for the Penalized Discriminant Analysis, with a misclassifiaction rate of 0.00 in the simulated data, and an average misclassification rate of 0.02 in a 10-fold cross validation on the original data. The results suggest a Penalized Discriminant Analysis is the most promising approach, most probably because it considers the functional, correlated nature of the reflectance spectra.The results of this study improve the accuracy of real-time tissue discrimination and are an essential step towards improving the safety of oral laser surgery.

Perceived Discrimination and Longitudinal Change in Kidney Function Among Urban Adults.

PubMed

Beydoun, May A; Poggi-Burke, Angedith; Zonderman, Alan B; Rostant, Ola S; Evans, Michele K; Crews, Deidra C

2017-09-01

Perceived discrimination has been associated with psychosocial distress and adverse health outcomes. We examined associations of perceived discrimination measures with changes in kidney function in a prospective cohort study, the Healthy Aging in Neighborhoods of Diversity across the Life Span. Our study included 1620 participants with preserved baseline kidney function (estimated glomerular filtration rate [eGFR] ≥ 60 mL/min/1.73 m) (662 whites and 958 African Americans, aged 30-64 years). Self-reported perceived racial discrimination and perceived gender discrimination (PGD) and a general measure of experience of discrimination (EOD) ("medium versus low," "high versus low") were examined in relation to baseline, follow-up, and annual rate of change in eGFR using multiple mixed-effects regression (γbase, γrate) and ordinary least square models (γfollow). Perceived gender discrimination "high versus low PGD" was associated with a lower baseline eGFR in all models (γbase = -3.51 (1.34), p = .009 for total sample). Among white women, high EOD was associated with lower baseline eGFR, an effect that was strengthened in the full model (γbase = -5.86 [2.52], p = .020). Overall, "high versus low" PGD was associated with lower follow-up eGFR (γfollow = -3.03 [1.45], p = .036). Among African American women, both perceived racial discrimination and PGD were linked to lower follow-up kidney function, an effect that was attenuated with covariate adjustment, indicating mediation through health-related, psychosocial, and lifestyle factors. In contrast, EOD was not linked to follow-up eGFR in any of the sex by race groups. Perceived racial and gender discrimination are associated with lower kidney function assessed by glomerular filtration rate and the strength of associations differ by sex and race groups. Perceived discrimination deserves further investigation as a psychosocial risk factors for kidney disease.

Discrimination in Healthcare Settings is Associated with Disability in Older Adults: Health and Retirement Study, 2008-2012.

PubMed

Rogers, Stephanie E; Thrasher, Angela D; Miao, Yinghui; Boscardin, W John; Smith, Alexander K

2015-10-01

As our society ages, improving medical care for an older population will be crucial. Discrimination in healthcare may contribute to substandard experiences with the healthcare system, increasing the burden of poor health in older adults. Few studies have focused on the presence of healthcare discrimination and its effects on older adults. We aimed to examine the relationship between healthcare discrimination and new or worsened disability. This was a longitudinal analysis of data from the nationally representative Health and Retirement Study administered in 2008 with follow-up through 2012. Six thousand and seventeen adults over the age of 50 years (mean age 67 years, 56.3 % female, 83.1 % white) were included in this study. Healthcare discrimination assessed by a 2008 report of receiving poorer service or treatment than other people by doctors or hospitals (never, less than a year=infrequent; more than once a year=frequent). Outcome was self-report of new or worsened disability by 2012 (difficulty or dependence in any of six activities of daily living). We used a Cox proportional hazards model adjusting for age, race/ethnicity, gender, net worth, education, depression, high blood pressure, diabetes, cancer, lung disease, heart disease, stroke, and healthcare utilization in the past 2 years. In all, 12.6 % experienced discrimination infrequently and 5.9 % frequently. Almost one-third of participants (29 %) reporting frequent healthcare discrimination developed new or worsened disability over 4 years, compared to 16.8 % of those who infrequently and 14.7 % of those who never experienced healthcare discrimination (p < 0.001). In multivariate analyses, compared to no discrimination, frequent healthcare discrimination was associated with new or worsened disability over 4 years (aHR = 1.63, 95 % CI 1.16-2.27). One out of five adults over the age of 50 years experiences discrimination in healthcare settings. One in 17 experience frequent healthcare discrimination, and this is associated with new or worsened disability by 4 years. Future research should focus on the mechanisms by which healthcare discrimination influences disability in older adults to promote better health outcomes for an aging population.

Observational difference between gamma and X-ray properties of optically dark and bright GRBs

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

Balazs, L. G.; Horvath, I.; Bagoly, Zs.

2008-05-22

Using the discriminant analysis of the multivariate statistical analysis we compared the distribution of the physical quantities of the optically dark and bright GRBs, detected by the BAT and XRT on board of the Swift Satellite. We found that the GRBs having detected optical transients (OT) have systematically higher peak fluxes and lower HI column densities than those without OT.

Reliable Early Classification on Multivariate Time Series with Numerical and Categorical Attributes

DTIC Science & Technology

2015-05-22

design a procedure of feature extraction in REACT named MEG (Mining Equivalence classes with shapelet Generators) based on the concept of...Equivalence Classes Mining [12, 15]. MEG can efficiently and effectively generate the discriminative features. In addition, several strategies are proposed...technique of parallel computing [4] to propose a process of pa- rallel MEG for substantially reducing the computational overhead of discovering shapelet

Study of the questionnaire of the Polytechnic University of Valencia (UPV) teaching staff, using students opinion survey. Statistical treatment

NASA Astrophysics Data System (ADS)

Martinez Gomez, Monica

Quality improvement of university institutions represents the most important challenge in the next years, and the potential tool to achieve it is based on the institutional evaluation in general, and specially the evaluation of the teaching performance. The opinion questionnaire from the students is the most generalised tool used to evaluate the teaching performance at Spanish universities. The general objective of this thesis is to develop a statistical methodology suitable to extract, analyse and interpret the information contained in the Questionnaire of Teaching Evaluation from Student Opinion (CEDA) of the UPV, aimed at optimising its practical use. The study is centred in the application of different multivariate techniques and has been structured in three parts: (1) Evaluation of the reliability, validity and dimensionality of the tool. The multivariate method used for this purpose is the Factorial Analysis. (2) Determination of the capacity of the questionnaire to identify different profiles of lecturers based on the quality perceived by students. This target is conducted with different multivariate classification techniques: hierarchical cluster analysis, non-hierarchical and two-stage analysis. Moreover, those items that best discriminate among the teaching typologies obtained are identified in the questionnaire. (3) Identification of the teaching typologies according to different descriptive characteristics referent to the subject and lecturer, with the use of decision trees. Once identified these typologies, a new discriminant analysis is conducted aimed at identifying those items that best characterise each typology. Finally, a study is carried out with the classification method SIMCA (Soft Independent Modelling of Class Analogy) in order to determine the discriminant loading of every item among the identified teaching typologies, allowing the identification of those that best distinguish the different classes obtained. With the combined use of the proposed techniques, it is expected to optimise the use of CEDA as a measuring tool and an indicator of the teaching quality at the university, that would allow the introduction of actions for the continuous improvement in the teaching processes of the UPV.

Social capital, anticipated ethnic discrimination and self-reported psychological health: a population-based study.

PubMed

Lindström, Martin

2008-01-01

This study investigates the association between anticipated ethnic discrimination and self-reported psychological health, taking generalized trust in other people into consideration. The 2004 Public Health Survey in Skåne, Sweden, is a cross-sectional postal questionnaire study including a total of 27,757 respondents aged 18-80 with a 59% response rate. Multivariate analyses of anticipated discrimination and self-reported psychological health were performed using logistic regressions in order to investigate the importance of possible confounders (age, country of origin, education and horizontal trust). Poor psychological health was reported by 13.0% of men and 18.9% of women, and 44.8% and 44.7%, respectively, reported that 50% or more of employers would discriminate according to race, colour of skin, religion, or cultural background. Respondents in younger age groups, born abroad, with high education, low trust and high levels of self-reported anticipated discrimination, had significantly higher levels of poor self-reported psychological health. There was a significant association between anticipated discrimination and low horizontal trust. After multiple adjustments for age, country of origin and education, the addition of trust in the model reduced the odds ratio of poor self-reported psychological health in the "most employers" category from 1.8 (1.4-2.1) to 1.5 (1.3-1.9) among men and from 2.2 (1.8-2.6) to 1.8 (1.5-2.2) among women. Generalized trust in other people may be a confounder of the association between anticipated discrimination and poor psychological health. Anticipated discrimination may have effects on the mental health of not only the affected minorities, but also on the mental health of the general population.

Discrimination against HIV-Infected People and the Spread of HIV: Some Evidence from France

PubMed Central

Peretti-Watel, Patrick; Spire, Bruno; Obadia, Yolande; Moatti, Jean-Paul

2007-01-01

Background Many people living with HIV/AIDS (PLWHA) suffer from stigma and discrimination. There is an ongoing debate, however, about whether stigma, fear and discrimination actually fuel the persisting spread of HIV, or slow it down by reducing contacts between the whole population and high-risk minorities. To contribute to this debate, we analysed the relationship between perceived discrimination and unsafe sex in a large sample of French PLWHAs. Methodology/Principal Findings In 2003, we conducted a national cross-sectional survey among a random sample of HIV-infected patients. The analysis was restricted to sexually active respondents (N = 2,136). Unsafe sex was defined as sexual intercourse without a condom with a seronegative/unknown serostatus partner during the prior 12 months. Separate analyses were performed for each transmission group (injecting drug use (IDU), homosexual contact, heterosexual contact). Overall, 24% of respondents reported experiences of discrimination in their close social environment (relatives, friends and colleagues) and 18% reported unsafe sex during the previous 12 months. Both prevalences were higher in the IDU group (32% for perceived discrimination, 23% for unsafe sex). In multivariate analyses, experience of discrimination in the close social environment was associated with an increase in unsafe sex for both PLWHAs infected through IDU and heterosexual contact (OR = 1.65 and 1.80 respectively). Conclusions Our study clearly confirms a relationship between discrimination and unsafe sex among PLWHAs infected through either IDU or heterosexual contact. This relationship was especially strong in the heterosexual group that has become the main vector of HIV transmission in France, and who is the more likely of sexual mixing with the general population. These results seriously question the hypothesis that HIV-stigma has no effect or could even reduce the infection spread of HIV. PMID:17476333

Age Group Differences in Perceived Age Discrimination: Associations With Self-Perceptions of Aging.

PubMed

Giasson, Hannah L; Queen, Tara L; Larkina, Marina; Smith, Jacqui

2017-08-01

From midlife onwards, age stereotypes increasingly underlie social judgments and contribute to age-based discrimination. Whereas many studies compare differences between young and older adults in reports of age discrimination or sensitivity to age stereotypes, few consider age group differences among adults over 50. We form subgroups corresponding to social age group membership (early midlife, late midlife, young old, oldest old) and examine differences in reported experiences of everyday age discrimination and associations with self-perceptions of aging. Using cross-sectional and longitudinal data from the Health and Retirement Study (HRS: N = 15,071; M Age = 68, range 50-101), multivariate logistic regression was used to examine experiences of everyday discrimination attributed to age, and associations between age discrimination and self-perceptions of aging, in four age groups: early midlife, late midlife, young old, oldest old. People in the early midlife group (aged 50-59) reported more experiences of unfair treatment than the older age groups but were less likely to attribute their experiences to age discrimination. After controlling for covariates, individuals in all age groups who perceived their own aging positively were less likely to report experiences of age discrimination. The magnitude of this effect, however, was greatest in the early midlife group. Findings support proposals that midlife is a pivotal life period when individuals adjust to life events and social role transitions. Future longitudinal studies will provide further insight into whether positive self-perceptions of aging are especially important in this phase of the life course. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Perceived discrimination and cancer screening behaviors in US Hispanics: the Hispanic Community Health Study/Study of Latinos Sociocultural Ancillary Study.

PubMed

Valdovinos, Cristina; Penedo, Frank J; Isasi, Carmen R; Jung, Molly; Kaplan, Robert C; Giacinto, Rebeca Espinoza; Gonzalez, Patricia; Malcarne, Vanessa L; Perreira, Krista; Salgado, Hugo; Simon, Melissa A; Wruck, Lisa M; Greenlee, Heather A

2016-01-01

Perceived discrimination has been associated with lower adherence to cancer screening guidelines. We examined whether perceived discrimination was associated with adherence to breast, cervical, colorectal, and prostate cancer screening guidelines in US Hispanic/Latino adults. Data were obtained from the Hispanic Community Health Study/Study of Latinos Sociocultural Ancillary Study, including 5,313 Hispanic adults aged 18–74 from Bronx, NY, Chicago, IL, Miami, FL, and San Diego, CA, and those who were within appropriate age ranges for specific screening tests were included in the analysis. Cancer screening behaviors were assessed via self-report. Perceived discrimination was measured using the Perceived Ethnic Discrimination Questionnaire. Confounder-adjusted multivariable polytomous logistic regression models assessed the association between perceived discrimination and adherence to cancer screening guidelines. Among women eligible for screening, 72.1 % were adherent to cervical cancer screening guidelines and 71.3 %were adherent to breast cancer screening guidelines. In participants aged 50–74, 24.6 % of women and 27.0 % of men were adherent to fecal occult blood test guidelines; 43.5 % of women and 34.8 % of men were adherent to colonoscopy/sigmoidoscopy guidelines; 41.0 % of men were adherent to prostate-specific antigen screening guidelines. Health insurance coverage, rather than perceived ethnic discrimination,was the variable most associated with receiving breast, cervical,colorectal, or prostate cancer screening. The influence of discrimination as a barrier to cancer screening may be modest among Hispanics/Latinos in urban US regions. Having health insurance facilitates cancer screening in this population. Efforts to increase cancer screening in Hispanics/Latinos should focus on increasing access to these services, especially among the uninsured.

Functional sensibility of the hand in leprosy patients.

PubMed

van Brakel, W H; Kets, C M; van Leerdam, M E; Khawas, I B; Gurung, K S

1997-03-01

The aims of this cross-sectional comparative study was to compare the results of Semmes-Weinstein monofilament testing (SWM) and moving 2-point discrimination (M2PD) with four tests of functional sensibility: recognition of objects, discrimination of size and texture and detection of dots. Ninety-eight leprosy in- and outpatients at Green Pastures Hospital in Pokhara, Nepal were tested with each of the above tests and the results were compared to see how well they agreed. Using the tests of functional sensibility as reference points, we examined the validity of the SWM and M2PD as predictors of functional sensibility. There was definite, but only moderate correlation between thresholds of monofilaments and M2PD and functional sensibility of the hand. A normal result with the SWM and/or M2PD had a good predictive value for normal functional sensibility. Sensitivity was reasonable against recognition of objects and discrimination of textures as reference tests (80-90% and 88-93%), but poor against discrimination of size and detection of dots (50-75% and 43-65%). Specificity was high for most combinations of SWM or M2PD with any of the tests of functional sensibility (85-99%). Above a monofilament threshold of 2 g, the predictive value of an abnormal test was 100% for dot detection and 83-92% for textural discrimination. This indicates that impairment of touch sensibility at this level correlates well with loss of dot detection and textural discrimination in patients with leprous neuropathy. For M2PD the pattern was very similar. Above a threshold of 5 mm, 95-100% of affected hands had loss of dot detection and 73-80% had loss of textural discrimination. Monofilament testing and M2PD did not seem suitable as proxy measures of functional sensibility of the hand in leprosy patients. However, a normal threshold with monofilaments and/or M2PD had a good predictive value for normal functional sensibility. Above a monofilament threshold of 2 g and/or a M2PD threshold of 5 mm, textural discrimination was abnormal in most hands.

How discriminating are discriminative instruments?

PubMed

Hankins, Matthew

2008-05-27

The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy.

PubMed

Zhu, Ying; Tan, Tuck Lee

2016-04-15

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects. Copyright © 2016 Elsevier B.V. All rights reserved.

Discrimination and depressive symptoms among sexual minority youth: is gay-affirming religious affiliation a protective factor?

PubMed

Gattis, Maurice N; Woodford, Michael R; Han, Yoonsun

2014-11-01

Researchers have examined perceived discrimination as a risk factor for depression among sexual minorities; however, the role of religion as a protective factor is under-investigated, especially among sexual minority youth. Drawing on a cross-sectional study investigating campus climate at a large public university in the U.S. midwest, we examined the role of affiliation with a gay-affirming denomination (i.e., endorsing same-sex marriage) as a moderating factor in the discrimination-depression relationship among self-identified sexual minority (n = 393) and heterosexual youth (n = 1,727). Using multivariate linear regression analysis, religious affiliation was found to moderate the discrimination-depression relationship among sexual minorities. Specifically, the results indicated that the harmful effects of discrimination among sexual minority youth affiliated with denominations that endorsed same-sex marriage were significantly less than those among peers who affiliated with denominations opposing same-sex marriage or who identified as secular. In contrast, religious affiliation with gay-affirming denominations did not moderate the discrimination-depression relationship among heterosexual participants. The findings suggest that, although religion and same-sex sexuality are often seen as incompatible topics, it is important when working with sexual minority clients for clinicians to assess religious affiliation, as it could be either a risk or a protective factor, depending on the religious group's stance toward same-sex sexuality. To promote the well-being of sexual minority youth affiliated with denominations opposed to same-sex marriage, the results suggest these faith communities may be encouraged to reconsider their position and/or identify ways to foster youth's resilience to interpersonal discrimination.

The weight of racism: Vigilance and racial inequalities in weight-related measures

PubMed Central

Hicken, Margaret T.; Lee, Hedwig; Hing, Anna K.

2017-01-01

In the United States, racial/ethnic inequalities in obesity are well-documented, particularly among women. Using the Chicago Community Adult Health Study, a probability-based sample in 2001–2003 (N=3,105), we examined the roles of discrimination and vigilance in racial inequalities in two weight-related measures, body mass index (BMI) and waist circumference (WC), viewed through a cultural racism lens. Cultural racism creates a social environment in which Black Americans bear the stigma burden of their racial group while White Americans are allowed to view themselves as individuals. We propose that in this context, interpersonal discrimination holds a different meaning for Blacks and Whites, while vigilance captures the coping style for Blacks who carry the stigma burden of the racial group. By placing discrimination and vigilance within the context of cultural racism, we operationalize existing survey measures and utilize statistical models to clarify the ambiguous associations between discrimination and weight-related inequalities in the extant literature. Multivariate models were estimated for BMI and WC separately and were stratified by gender. Black women had higher mean BMI and WC than any other group, as well as highest levels of vigilance. White women did not show an association between vigilance and WC but did show a strong positive association between discrimination and WC. Conversely, Black women displayed an association between vigilance and WC, but not between discrimination and WC. These results demonstrate that vigilance and discrimination may hold different meanings for obesity by ethnoracial group that are concealed when all women are examined together and viewed without considering a cultural racism lens. PMID:28372829

Perceived Discrimination, Social Support, and Quality of Life in Gender Dysphoria.

PubMed

Başar, Koray; Öz, Gökhan; Karakaya, Jale

2016-07-01

Transgender individuals experience discrimination in all domains of their personal and social life. Discrimination is believed to be associated with worse quality of life (QoL). To investigate the relation between QoL and perceived levels of discrimination and social support in individuals with gender dysphoria (GD). Individuals with GD who attended a psychiatry clinic from January 2012 through December 2014 were recruited. Demographic, social, and medical transition features were collected with standardized forms. Self-report measurements of QoL (Turkish version of the World Health Organization's Quality of Life-BREF) that included physical, psychological, social, and environmental domains, perceived discrimination with personal and group subscales (Perceived Discrimination Scale [PDS]), and social support (Multidimensional Scale of Perceived Social Support) were completed. Ninety-four participants (76.6% trans men) adequately completed the study measurements. Regression models with each QoL domain score as a dependent variable indicated a significant predictor value of personal PDS in social and environmental QoL. Social support from family was associated with better QoL in psychological QoL, whereas perceived support from friends significantly predicted all other domains of QoL. There was a tendency for group PDS to be rated higher than personal PDS, suggesting personal vs group discrimination discrepancy. However, group PDS was not found to be a predictor of QoL in the multivariate model. Perceived personal discrimination and social support from different sources predicted domains of QoL with a non-uniform pattern in individuals with GD. Social support and discrimination were found to have opposing contributions to QoL in GD. The present findings emphasize the necessity of addressing discrimination and social support in clinical work with GD. Moreover, strategies to improve and strengthen friend and family support for individuals with GD should be explored by clinicians. Further research with larger and community-based samples is required. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

HIV-Related Discrimination among Grade Six Students in Nine Southern African Countries

PubMed Central

Maughan-Brown, Brendan; Spaull, Nicholas

2014-01-01

Background HIV-related stigmatisation and discrimination by young children towards their peers have important consequences at the individual level and for our response to the epidemic, yet research on this area is limited. Methods We used nationally representative data to examine discrimination of HIV-positive children by grade six students (n = 39,664) across nine countries in Southern Africa: Botswana, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Zambia and Zimbabwe. Descriptive statistics are used to compare discrimination by country, gender, geographic location and socioeconomic status. Multivariate logistic regression is employed to assess potential determinants of discrimination. Results The levels and determinants of discrimination varied significantly between the nine countries. While one in ten students in Botswana, Malawi, South Africa and Swaziland would “avoid or shun” an HIV positive friend, the proportions in Lesotho, Mozambique, Zambia and Zimbabwe were twice as high (approximately 20%). A large proportion of students believed that HIV positive children should not be allowed to continue to attend school, particularly in Zambia (33%), Lesotho (37%) and Zimbabwe (42%). The corresponding figures for Malawi and Swaziland were significantly lower at 13% and 12% respectively. Small differences were found by gender. Children from rural areas and poorer schools were much more likely to discriminate than those from urban areas and wealthier schools. Importantly, we identified factors consistently associated with discrimination across the region: students with greater exposure to HIV information, better general HIV knowledge and fewer misconceptions about transmission of HIV via casual contact were less likely to report discrimination. Conclusions Our study points toward the need for early interventions (grade six or before) to reduce stigma and discrimination among children, especially in schools situated in rural areas and poorer communities. In particular, interventions should focus on correcting misconceptions that HIV can be transmitted via casual contact. PMID:25105728

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

PubMed Central

Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W.

2015-01-01

Background and Aims Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. Methods and Results We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Conclusions Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. Significance of the Study The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach. PMID:26658757

PROM and Labour Effects on Urinary Metabolome: A Pilot Study

PubMed Central

Meloni, Alessandra; Palmas, Francesco; Mereu, Rossella; Deiana, Sara Francesca; Fais, Maria Francesca; Mussap, Michele; Ragusa, Antonio; Pintus, Roberta; Fanos, Vassilios; Melis, Gian Benedetto

2018-01-01

Since pathologies and complications occurring during pregnancy and/or during labour may cause adverse outcomes for both newborns and mothers, there is a growing interest in metabolomic applications on pregnancy investigation. In fact, metabolomics has proved to be an efficient strategy for the description of several perinatal conditions. In particular, this study focuses on premature rupture of membranes (PROM) in pregnancy at term. For this project, urine samples were collected at three different clinical conditions: out of labour before PROM occurrence (Ph1), out of labour with PROM (Ph2), and during labour with PROM (Ph3). GC-MS analysis, followed by univariate and multivariate statistical analysis, was able to discriminate among the different classes, highlighting the metabolites most involved in the discrimination. PMID:29511388

Tailoring a psychophysical discrimination experiment upon assessment of the psychometric function: Predictions and results

NASA Astrophysics Data System (ADS)

Vilardi, Andrea; Tabarelli, Davide; Ricci, Leonardo

2015-02-01

Decision making is a widespread research topic and plays a crucial role in neuroscience as well as in other research and application fields of, for example, biology, medicine and economics. The most basic implementation of decision making, namely binary discrimination, is successfully interpreted by means of signal detection theory (SDT), a statistical model that is deeply linked to physics. An additional, widespread tool to investigate discrimination ability is the psychometric function, which measures the probability of a given response as a function of the magnitude of a physical quantity underlying the stimulus. However, the link between psychometric functions and binary discrimination experiments is often neglected or misinterpreted. Aim of the present paper is to provide a detailed description of an experimental investigation on a prototypical discrimination task and to discuss the results in terms of SDT. To this purpose, we provide an outline of the theory and describe the implementation of two behavioural experiments in the visual modality: upon the assessment of the so-called psychometric function, we show how to tailor a binary discrimination experiment on performance and decisional bias, and to measure these quantities on a statistical base. Attention is devoted to the evaluation of uncertainties, an aspect which is also often overlooked in the scientific literature.

[Application of Bayes Probability Model in Differentiation of Yin and Yang Jaundice Syndromes in Neonates].

PubMed

Mu, Chun-sun; Zhang, Ping; Kong, Chun-yan; Li, Yang-ning

2015-09-01

To study the application of Bayes probability model in differentiating yin and yang jaundice syndromes in neonates. Totally 107 jaundice neonates who admitted to hospital within 10 days after birth were assigned to two groups according to syndrome differentiation, 68 in the yang jaundice syndrome group and 39 in the yin jaundice syndrome group. Data collected for neonates were factors related to jaundice before, during and after birth. Blood routines, liver and renal functions, and myocardial enzymes were tested on the admission day or the next day. Logistic regression model and Bayes discriminating analysis were used to screen factors important for yin and yang jaundice syndrome differentiation. Finally, Bayes probability model for yin and yang jaundice syndromes was established and assessed. Factors important for yin and yang jaundice syndrome differentiation screened by Logistic regression model and Bayes discriminating analysis included mothers' age, mother with gestational diabetes mellitus (GDM), gestational age, asphyxia, or ABO hemolytic diseases, red blood cell distribution width (RDW-SD), platelet-large cell ratio (P-LCR), serum direct bilirubin (DBIL), alkaline phosphatase (ALP), cholinesterase (CHE). Bayes discriminating analysis was performed by SPSS to obtain Bayes discriminant function coefficient. Bayes discriminant function was established according to discriminant function coefficients. Yang jaundice syndrome: y1= -21. 701 +2. 589 x mother's age + 1. 037 x GDM-17. 175 x asphyxia + 13. 876 x gestational age + 6. 303 x ABO hemolytic disease + 2.116 x RDW-SD + 0. 831 x DBIL + 0. 012 x ALP + 1. 697 x LCR + 0. 001 x CHE; Yin jaundice syndrome: y2= -33. 511 + 2.991 x mother's age + 3.960 x GDM-12. 877 x asphyxia + 11. 848 x gestational age + 1. 820 x ABO hemolytic disease +2. 231 x RDW-SD +0. 999 x DBIL +0. 023 x ALP +1. 916 x LCR +0. 002 x CHE. Bayes discriminant function was hypothesis tested and got Wilks' λ =0. 393 (P =0. 000). So Bayes discriminant function was proved to be with statistical difference. To check Bayes probability model in discriminating yin and yang jaundice syndromes, coincidence rates for yin and yang jaundice syndromes were both 90% plus. Yin and yang jaundice syndromes in neonates could be accurately judged by Bayesian discriminating functions.

Rapid characterization of transgenic and non-transgenic soybean oils by chemometric methods using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Luna, Aderval S.; da Silva, Arnaldo P.; Pinho, Jéssica S. A.; Ferré, Joan; Boqué, Ricard

Near infrared (NIR) spectroscopy and multivariate classification were applied to discriminate soybean oil samples into non-transgenic and transgenic. Principal Component Analysis (PCA) was applied to extract relevant features from the spectral data and to remove the anomalous samples. The best results were obtained when with Support Vectors Machine-Discriminant Analysis (SVM-DA) and Partial Least Squares-Discriminant Analysis (PLS-DA) after mean centering plus multiplicative scatter correction. For SVM-DA the percentage of successful classification was 100% for the training group and 100% and 90% in validation group for non transgenic and transgenic soybean oil samples respectively. For PLS-DA the percentage of successful classification was 95% and 100% in training group for non transgenic and transgenic soybean oil samples respectively and 100% and 80% in validation group for non transgenic and transgenic respectively. The results demonstrate that NIR spectroscopy can provide a rapid, nondestructive and reliable method to distinguish non-transgenic and transgenic soybean oils.

Identification of the geographical origins of sea cucumber (Apostichopus japonicus) in northern China by using stable isotope ratios and fatty acid profiles.

PubMed

Zhang, Xufeng; Liu, Yu; Li, Ying; Zhao, Xinda

2017-03-01

Geographic traceability is an important issue for food quality and safety control of seafood. In this study,δ 13 C and δ 15 N values, as well as fatty acid (FA) content of 133 samples of A. japonicus from seven sampling points in northern China Sea were determined to evaluate their applicability in the origin traceability of A. japonicus. Principal component analysis (PCA) and discriminant analysis (DA) were applied to different data sets in order to evaluate their performance in terms of classification or predictive ability. δ 13 C and δ 15 N values could effectively discriminate between different origins of A. japonicus. Significant differences in the FA compositions showed the effectiveness of FA composition as a tool for distinguishing between different origins of A. japonicus. The two technologies, combined with multivariate statistical analysis, can be promising methods to discriminate A. japonicus from different geographical areas. Copyright © 2016. Published by Elsevier Ltd.

Geographic authentication of Asian rice (Oryza sativa L.) using multi-elemental and stable isotopic data combined with multivariate analysis.

PubMed

Chung, Ill-Min; Kim, Jae-Kwang; Lee, Kyoung-Jin; Park, Sung-Kyu; Lee, Ji-Hee; Son, Na-Young; Jin, Yong-Ik; Kim, Seung-Hyun

2018-02-01

Rice (Oryza sativa L.) is the world's third largest food crop after wheat and corn. Geographic authentication of rice has recently emerged asan important issue for enhancing human health via food safety and quality assurance. Here, we aimed to discriminate rice of six Asian countries through geographic authentication using combinations of elemental/isotopic composition analysis and chemometric techniques. Principal components analysis could distinguish samples cultivated from most countries, except for those cultivated in the Philippines and Japan. Furthermore, orthogonal projection to latent structure-discriminant analysis provided clear discrimination between rice cultivated in Korea and other countries. The major common variables responsible for differentiation in these models were δ 34 S, Mn, and Mg. Our findings contribute to understanding the variations of elemental and isotopic compositions in rice depending on geographic origins, and offer valuable insight into the control of fraudulent labeling regarding the geographic origins of rice traded among Asian countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

Authentication of animal origin of heparin and low molecular weight heparin including ovine, porcine and bovine species using 1D NMR spectroscopy and chemometric tools.

PubMed

Monakhova, Yulia B; Diehl, Bernd W K; Fareed, Jawed

2018-02-05

High resolution (600MHz) nuclear magnetic resonance (NMR) spectroscopy is used to distinguish heparin and low-molecular weight heparins (LMWHs) produced from porcine, bovine and ovine mucosal tissues as well as their blends. For multivariate analysis several statistical methods such as principal component analysis (PCA), factor discriminant analysis (FDA), partial least squares - discriminant analysis (PLS-DA), linear discriminant analysis (LDA) were utilized for the modeling of NMR data of more than 100 authentic samples. Heparin and LMWH samples from the independent test set (n=15) were 100% correctly classified according to its animal origin. Moreover, by using 1 H NMR coupled with chemometrics and several batches of bovine heparins from two producers were differentiated. Thus, NMR spectroscopy combined with chemometrics is an efficient tool for simultaneous identification of animal origin and process based manufacturing difference in heparin products. Copyright © 2017 Elsevier B.V. All rights reserved.

Discrimination and Cumulative Disease Damage Among African American Women With Systemic Lupus Erythematosus.

PubMed

Chae, David H; Drenkard, Cristina M; Lewis, Tené T; Lim, S Sam

2015-10-01

We examined associations between unfair treatment, attributions of unfair treatment to racial discrimination, and cumulative disease damage among African American women with systemic lupus erythematosus (SLE). We used multivariable regression models to examine SLE damage among 578 African American women in metropolitan Atlanta, Georgia, recruited to the Georgians Organized Against Lupus cohort. When we controlled for demographic, socioeconomic, and health-related covariates, reporting any unfair treatment was associated with greater SLE damage compared with reporting no unfair treatment (b = 0.55; 95% confidence interval = 0.14, 0.97). In general, unfair treatment attributed to nonracial factors was more strongly associated with SLE damage than was unfair treatment attributed to racial discrimination, although the difference was not statistically significant. Unfair treatment may contribute to worse disease outcomes among African American women with SLE. Unfair treatment attributed to nonracial causes may have a more pronounced negative effect on SLE damage. Future research may further examine possible differences in the effect of unfair treatment by attribution.

Traceability of 'Limone di Siracusa PGI' by a multidisciplinary analytical and chemometric approach.

PubMed

Amenta, M; Fabroni, S; Costa, C; Rapisarda, P

2016-11-15

Food traceability is increasingly relevant with respect to safety, quality and typicality issues. Lemon fruits grown in a typical lemon-growing area of southern Italy (Siracusa), have been awarded the PGI (Protected Geographical Indication) recognition as 'Limone di Siracusa'. Due to its peculiarity, consumers have an increasing interest about this product. The detection of potential fraud could be improved by using the tools linking the composition of this production to its typical features. This study used a wide range of analytical techniques, including conventional techniques and analytical approaches, such as spectral (NIR spectra), multi-elemental (Fe, Zn, Mn, Cu, Li, Sr) and isotopic ((13)C/(12)C, (18)O/(16)O) marker investigations, joined with multivariate statistical analysis, such as PLS-DA (Partial Least Squares Discriminant Analysis) and LDA (Linear Discriminant Analysis), to implement a traceability system to verify the authenticity of 'Limone di Siracusa' production. The results demonstrated a very good geographical discrimination rate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of offal adulteration in beef by laser induced breakdown spectroscopy (LIBS).

PubMed

Velioglu, Hasan Murat; Sezer, Banu; Bilge, Gonca; Baytur, Süleyman Efe; Boyaci, Ismail Hakki

2018-04-01

Minced meat is the major ingredient in sausages, beef burgers, and similar products; and thus it is the main product subjected to adulteration with meat offal. Determination of this kind of meat adulteration is crucial due to religious, economic and ethical concerns. The aim of the present study is to discriminate the beef meat and offal samples by using laser induced breakdown spectroscopy (LIBS). To this end, LIBS and multivariate data analysis were used to discriminate pure beef and offal samples qualitatively and to determine the offal mixture adulteration quantitatively. In this analysis, meat samples were frozen and LIBS analysis were performed. The results indicate that by using principal component analysis (PCA), discrimination of pure offal and offal mixture adulterated beef samples can be achieved successfully. Besides, adulteration ratio can be determined using partial least square analysis method (PLS) with 0.947 coefficient of determination (R 2 ) and 3.8% of limit of detection (LOD) values for offal mixture adulterated beef samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Determinants of Job Satisfaction and Turnover Intent in Home Health Workers: The Role of Job Demands and Resources.

PubMed

Jang, Yuri; Lee, Ahyoung A; Zadrozny, Michelle; Bae, Sung-Heui; Kim, Miyong T; Marti, Nathan C

2017-01-01

Based on the job demands-resources (JD-R) model, this study explored the impact of job demands (physical injury and racial/ethnic discrimination) and resources (self-confidence in job performance and recognition by supervisor/organization/society) on home health workers' employee outcomes (job satisfaction and turnover intent). Using data from the National Home Health Aide Survey (N = 3,354), multivariate models of job satisfaction and turnover intent were explored. In both models, the negative impact of demands (physical injury and racial/ethnic discrimination) and the positive impact of resources (self-confidence in job performance and recognition by supervisor and organization) were observed. The overall findings suggest that physical injury and discrimination should be prioritized in prevention and intervention efforts to improve home health workers' safety and well-being. Attention also needs to be paid to ways to bolster work-related efficacy and to promote an organizational culture of appreciation and respect. © The Author(s) 2015.

Control of oenological products: discrimination between different botanical sources of L-tartaric acid by isotope ratio mass spectrometry.

PubMed

Moreno Rojas, Jose Manuel; Cosofret, Sorin; Reniero, Fabiano; Guillou, Claude; Serra, Francesca

2007-01-01

Following previous studies on counterfeit of wines with synthetic ingredients, the possibility of frauds by natural external L-tartaric acid has also been investigated. The aim of this research was to map the stable isotope ratios of L-tartaric acid coming from botanical species containing large amounts of this compound: grape and tamarind. Samples of L-tartaric acid were extracted from the pulp of tamarind fruits originating from several countries and from grape must. delta(13)C and delta(18)O were measured for all samples. Additional delta(2)H measurements were performed as a complementary analysis to help discrimination of the botanical origin. Different isotopic patterns were observed for the different botanical origins. The multivariate statistical analysis of the data shows clear discrimination among the different botanical and synthetic sources. This approach could be a complementary tool for the control of L-tartaric acid used in oenology. Copyright (c) 2007 John Wiley & Sons, Ltd.

Whole-brain functional connectivity identification of functional dyspepsia.

PubMed

Nan, Jiaofen; Liu, Jixin; Li, Guoying; Xiong, Shiwei; Yan, Xuemei; Yin, Qing; Zeng, Fang; von Deneen, Karen M; Liang, Fanrong; Gong, Qiyong; Qin, Wei; Tian, Jie

2013-01-01

Recent neuroimaging studies have shown local brain aberrations in functional dyspepsia (FD) patients, yet little attention has been paid to the whole-brain resting-state functional network abnormalities. The purpose of this study was to investigate whether FD disrupts the patterns of whole-brain networks and the abnormal functional connectivity could reflect the severity of the disease. The dysfunctional interactions between brain regions at rest were investigated in FD patients as compared with 40 age- and gender- matched healthy controls. Multivariate pattern analysis was used to evaluate the discriminative power of our results for classifying patients from controls. In our findings, the abnormal brain functional connections were mainly situated within or across the limbic/paralimbic system, the prefrontal cortex, the tempo-parietal areas and the visual cortex. About 96% of the subjects among the original dataset were correctly classified by a leave one-out cross-validation approach, and 88% accuracy was also validated in a replication dataset. The classification features were significantly associated with the patients' dyspepsia symptoms, the self-rating depression scale and self-rating anxiety scale, but it was not correlated with duration of FD patients (p>0.05). Our results may indicate the effectiveness of the altered brain functional connections reflecting the disease pathophysiology underling FD. These dysfunctional connections may be the epiphenomena or causative agents of FD, which may be affected by clinical severity and its related emotional dimension of the disease rather than the clinical course.