SEARCH · PubMed Health

Results for “principal component analysis”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57Linked to original sources

PubMed2006

The dimensions of responsiveness of a health system: a Taiwanese perspective.

BACKGROUND: Responsiveness is an indicator used to measure how well a health system performs relative to non-health aspects. This study assessed whether seven dimensions proposed by the World Health Organization (WHO) to measure responsiveness (dignity, autonomy, confidentiality, prompt attention, social support, basic amenities, and choices of providers) are applicable in evaluating the health system of Taiwan. METHODS: A key informant survey and focus group research were used in this study. The translated WHO proposed questionnaire was sent to 205 nominated key informants by mail, and 132 (64.4%) were returned. We used principal component analysis to extract factors. Linear regression analysis was used to assess the relationship between the total score and the extracted factors. A qualitative content analysis was also carried out in focus group research. RESULTS: Principal component analysis produced five factors (respect, access, confidentiality, basic amenities, and social support) that explained 63.5% of the total variances. These five factors demonstrated acceptable internal consistency and four of them (except social support) were significantly correlated with the total responsiveness score. The focus group interviews revealed health providers' communication ability and medical ethics were also highly appraised by Taiwanese. CONCLUSION: When the performance of a health system is to be evaluated, elements of responsiveness proposed by WHO may have to be tailored to fit different cultural backgrounds. Four key features illustrate the uniqueness of Taiwanese perspectives: the idea of autonomy may not be conceptualized, prompt attention and choice of providers are on the same track, social support during care is trivially correlated to the total responsiveness score, and accountability of health providers is deemed essential to a health system.

Adult↗

PubMed2002

Classification of disease subgroup and correlation with disease severity using magnetic resonance imaging whole-brain histograms: application to magnetization transfer ratios and multiple sclerosis.

This paper presents a new approach to characterize subtle diffuse changes in multiple sclerosis (MS) using histograms derived from magnetization transfer ratio (MTR) images. Two major parts dominate our histogram analysis; 1) Classification of MTR histograms into control and MS subgroups; 2) Correlation with current disability, as measured by the EDSS scale (a measure of disease severity). Two data reduction schemes are used to reduce the complexity of the analysis: linear discriminant analysis (LDA) and principal component analysis (PCA). LDA is better for the classification of MTR histograms as it takes into account the between-class variation. By using LDA, the space of MTR histograms is transformed to the optimal discriminant space for a nearest mean classifier. In contrast, PCA is useful for correlation with current disability as it takes into account the variation within each subgroup in its process. A multiple regression analysis is used to evaluate the multiple correlation of those principal components with the degree of disability in MS. This is the first application of such classification and correlation techniques to magnetic resonance imaging histogram data. Our MTR histogram analysis approach give improved classification success and improved correlation compared with methods that use traditional histogram features such as peak height and peak location.

Adult↗

PubMed2004

Direct estimation of genetic principal components: simplified analysis of complex phenotypes.

Estimating the genetic and environmental variances for multivariate and function-valued phenotypes poses problems for estimation and interpretation. Even when the phenotype of interest has a large number of dimensions, most variation is typically associated with a small number of principal components (eigen-vectors or eigenfunctions). We propose an approach that directly estimates these leading principal components; these then give estimates for the covariance matrices (or functions). Direct estimation of the principal components reduces the number of parameters to be estimated, uses the data efficiently, and provides the basis for new estimation algorithms. We develop these concepts for both multivariate and function-valued phenotypes and illustrate their application in the restricted maximum-likelihood framework.

Algorithms↗

PubMed2003

Potential for improving description of bovine udder health status by combined analysis of milk parameters.

The objective of this study was to assess the potential of a stepwise multivariate procedure to quantify cow-level udder health based on eight milk parameters: milk yield, protein percentage, fat percentage, lactose percentage, citrate percentage, somatic cell count (SCC), and two electrical conductivity parameters. The data were collected in one research herd and included 821 cow-level observations. In addition to milk parameters, disease recordings and bacteriology on quarter milk samples every eighth week throughout lactation were included. A multivariate mixed model was applied to the milk parameters in a healthy subset to adjust for the following systematic factors: total mixed ration (TMR) energy density, breed-line combination, parity, stage of lactation, and season. The proportion of variance accounted for by the mixed model ranged from 0.14 to 0.82 depending on milk parameter. The adjustments estimated in the healthy subset were applied to the whole dataset, including observations pertaining to nonhealthy cows. Combined description of the adjusted variation in the milk parameters was performed with a principal component analysis. The first principal component (Prin1) described 30% of the adjusted variation and was interpreted as being the main consequences of mastitis. Finally, cluster analysis based on Prin1 separated the observations into nine clusters, which were strongly associated with udder health in terms of increasing clinical and subclinical mastitis with increasing level of Prin1. It was concluded that a multivariate approach to assess udder health from milk parameters has the potential to substantially improve description of udder health.

Analysis of Variance↗

PubMed2002

UV-VIS spectroscopy of 2,4,6-trinitrotoluene-hydroxide reaction.

Contamination of groundwater, surface water and soil by explosives has occurred at military sites throughout the world as a result of manufacture of explosive compounds, assembly of munitions, and deployment of explosives containing devices. Due to the adverse effects of explosives on humans and other natural receptors, a low cost means of decontaminating these areas of contamination is needed. Base-induced transformation of explosives has shown promise as a rapid, low cost, and minimally resource-intensive technology for detoxifying explosives in soil and water. In order to understand the reaction mechanism, a reaction mixture of 2:1:1 (water:2,4,6-trinitrotoluene (TNT):1 N KOH) was analyzed by UV/VIS spectrometry from 190 to 1,100 nm. Time course measurements were conducted at 25, 20, 15, and 12 degrees C. A factor analysis program was used to analyze the spectral data. Principal component analysis indicated that six principal components explained the spectra to within experimental error, with four factors explaining the majority of the variance. Test spectral vectors for four components were developed, including TNT, two intermediates, and the final product, and were tested against the abstract vectors. Two possible reaction mechanisms were suggested and tested to explain the spectral data.

Hydroxides↗

PubMedDate not supplied

Perceived benefits and barriers of increased fruit and vegetable consumption: validation of a decisional balance scale.

OBJECTIVE: To develop and validate scales to assess perceived benefits and barriers (decisional balance) for increasing fruit and vegetable consumption. DESIGN: A cross-sectional mail and telephone survey was conducted. SUBJECTS/SETTINGS: A total of 1200 Chinese households were randomly selected from the Singapore residential telephone listings, and 71% responded to the mail survey; 390 males and 406 females participated (mean age = 39.3). MAIN OUTCOME MEASURES: Decisional balance, stage of change, and fruit and vegetable consumption were measured. STATISTICAL ANALYSES PERFORMED: Using a split-half sample approach, developmental sample responses were analyzed by principal-components analysis and validation sample responses by confirmatory factor analysis. Analyses of variance were used to examine stage differences in decisional balance. RESULTS: Principal-components analysis indicated two components representing benefits (or pros) (Cronbach's alpha = 0.86) and barriers (or cons) (alpha 0.79) of change. Confirmatory factor analysis strongly supported the two-component structure (Goodness of Fit Index = 0.97). There was a shift from cons to pros being more important across the stages. The increase in pros across the stages of change (p < 0.0001) corresponded to a medium effect size, and the decrease in cons (p < 0.01) corresponded to a small effect size. IMPLICATIONS: Decisional balance scales may be used to guide interventions to influence fruit and vegetable consumption.

Adult↗

PubMed2005

Molecular alterations in primary prostate cancer after androgen ablation therapy.

PURPOSE: After an initial response to androgen ablation, most prostate tumors recur, ultimately progressing to highly aggressive androgen-independent cancer. The molecular mechanisms underlying progression are not well known in part due to the rarity of androgen-independent samples from primary and metastatic sites. EXPERIMENTAL DESIGN: We compared the gene expression profiles of 10 androgen-independent primary prostate tumor biopsies with 10 primary, untreated androgen-dependent tumors. Samples were laser capture microdissected, the RNA was amplified, and gene expression was assessed using Affymetrix Human Genome U133A GeneChip. Differential expression was examined with principal component analysis, hierarchical clustering, and Student's t testing. Analysis of gene ontology was done with Expression Analysis Systematic Explorer and gene expression data were integrated with genomic alterations with Differential Gene Locus Mapping. RESULTS: Unsupervised principal component analysis showed that the androgen-dependent and androgen-independent tumors segregated from one another. After filtering the data, 239 differentially expressed genes were identified. Two main gene ontologies were found discordant between androgen-independent and androgen-dependent tumors: macromolecule biosynthesis was down-regulated and cell adhesion was up-regulated in androgen-independent tumors. Other differentially expressed genes were related to interleukin-6 signaling as well as angiogenesis, cell adhesion, apoptosis, oxidative stress, and hormone response. The Differential Gene Locus Mapping analysis identified nine regions of potential chromosomal deletion in the androgen-independent tumors, including 1p36, 3p21, 6p21, 8p21, 11p15, 11q12, 12q23, 16q12, and 16q21. CONCLUSIONS: Taken together, these data identify several unique characteristics of androgen-independent prostate cancer that may hold potential for the development of targeted therapeutic intervention.

Aged↗

PubMed2006

Selection of background electrolyte for CZE analysis by a chemometric approach. Part I. Separation of a mixture of acidic non-steroidal anti-inflammatory drugs.

This paper is the first part of the presentation of a chemometric approach for the rapid selection of a suitable background electrolyte (BGE) in CZE analysis of small drug molecules. The strategy is based on principal component analysis and experimental design. In this first section, the approach is applied to the analysis of a mixture of six arylpropionic anti-inflammatory drugs. Initially, 222 possible aqueous background electrolytes (objects) were characterized using as descriptors pH, conductivity, ionic strength and relative viscosity. In order to allow the dissociation of the acidic analytes, this original data set was reduced to 154 background electrolytes with pH values higher than or equal to 5. Principal component analysis made it possible to graphically represent the new set of objects, described by the four variables, in a two-dimensional space. Among these electrolytes, Kennard-Stone algorithm selected ten objects to be tested by CZE, covering homogeneously principal component space. CZE analyses were carried out with the selected electrolytes, and 0.1 M borax was identified as the most suitable one for the specified application. Finally, the characteristics of the analysis were finely tuned by means of a response surface study, which allowed the best conditions to be determined: borax concentration, 0.09 M; methanol, 6% (v/v); temperature, 24 degrees C, voltage, 20 kV. Applying these conditions, a baseline resolution among the six compounds was obtained in less than 10 min.

Anti-Inflammatory Agents, Non-Steroidal↗

PubMed2002

Exploratory fMRI analysis by autocorrelation maximization.

A novel and computationally efficient method for exploratory analysis of functional MRI data is presented. The basic idea is to reveal underlying components in the fMRI data that have maximum autocorrelation. The tool for accomplishing this task is Canonical Correlation Analysis. The relation to Principal Component Analysis and Independent Component Analysis is discussed and the performance of the methods is compared using both simulated and real data.

Brain↗

PubMed2005

Genome-wide association study in esophageal cancer using GeneChip mapping 10K array.

Whole genome association studies of complex human diseases represent a new paradigm in the postgenomic era. In this study, we report application of the Affymetrix, Inc. (Santa Clara, CA) high-density single nucleotide polymorphism (SNP) array containing 11,555 SNPs in a pilot case-control study of esophageal squamous cell carcinoma (ESCC) that included the analysis of germ line samples from 50 ESCC patients and 50 matched controls. The average genotyping call rate for the 100 samples analyzed was 96%. Using the generalized linear model (GLM) with adjustment for potential confounders and multiple comparisons, we identified 37 SNPs associated with disease, assuming a recessive mode of transmission; similarly, 48 SNPs were identified assuming a dominant mode and 53 SNPs in a continuous mode. When the 37 SNPs identified from the GLM recessive mode were used in a principal components analysis, the first principal component correctly predicted 46 of 50 cases and 47 of 50 controls. Among all the SNPs selected from GLMs for the three modes of transmission, 39 could be mapped to 1 of 33 genes. Many of these genes are involved in various cancers, including GASC1, shown previously to be amplified in ESCCs, and EPHB1 and PIK3C3. In conclusion, we have shown the feasibility of the Affymetrix 10K SNP array in genome-wide association studies of common cancers and identified new candidate loci to study in ESCC.

Carcinoma, Squamous Cell↗

PubMed1995

Modified neonatal growth assessment score: a multivariate approach to the detection of intrauterine growth retardation in the neonate.

The objective of this investigation was the development of a modified Neonatal Growth Assessment Score (mNGAS) for use in the evaluation of neonatal growth status. The growth of 74 fetuses at risk for intrauterine growth retardation (IUGR) was followed longitudinally, beginning in the first or early second trimester. Rossavik growth models derived from data obtained in the second trimester were used to predict the weight (WT), crown-heel length (CHL) and head (HC), abdominal (AC) and thigh circumferences (ThC) at birth, which were then actually measured within 24 h after delivery. These measurements were compared to age-specific size curves and used to calculate sets of five growth potential index (GPRIi) values, which in turn were used to calculate five-variable Neonatal Growth Assessment Scores (NGAS5). Neonates were initially classified as normal or IUGR on the basis of NGAS5, GPRIi, and anatomic measurements. A final classification based on principal component analysis and linear discriminant analysis was carried out. The score obtained using the first principal component function was defined to be mNGAS51. The effectiveness of mNGASij values, determined from 1-4 GPRIi values, in separating normal and IUGR neonates was also evaluated. Neonates initially considered to be normal had very few abnormal GPRI values or anatomic measurements, whereas the frequency of these abnormalities in IUGR neonates was significantly increased. However, no single anatomic variable was 100% normal in the normal neonates and 100% abnormal in IUGR neonates. Only 40% of IUGR neonates were small for gestational age. Classification of these neonates using principal component analysis and linear discriminant analysis was essentially the same (98.6%) as that made initially after reclassification of two IUGR neonates as normal. The characteristics of the initial and final normal and IUGR groups were very similar and the mNGAS51 was strongly correlated with the NGAS5 in the IUGR group. The effectiveness of mNGASij in separating normal and IUGR neonates increased with the number of GPRIi values included and the types used. GPRIThC and GPRIWT were the most important, followed by GPRIAC. GPRICHL and GPRIHC were much less important and in some cases detrimental. These findings support the concepts of a decrease in soft tissue mass as the initial step in the development of IUGR and the protection of head growth (brain-sparing). The characteristics of mNGAS51, particularly its comprehensiveness, its independence of differences in growth potential, its weighting of GPRIi values according to their importance in the detection of IUGR and its ability to detect different manifestations of IUGR in different individuals, indicate that this should be a most effective parameter for separating normal and IUGR neonates.

Embryonic and Fetal Development↗

PubMed1999

[A physical performance battery assessing low/high extremity functional fitness in older Japanese women].

The aim of this study was to establish a physical performance test battery to assess the wide variation of functional fitness in older Japanese women. The criteria for sampling low/high extremity functional fitness were the amount of physical activities that older women perform on a regular basis and the distance they could move by foot. Seventeen tests related to the activities parallel to daily living (APDL) were completed for 178 women, aged 60 to 91 years. Principal component analysis of the 17 performance tests in the reference group (n = 140) yielded 5 components accounting for 63.5% of the total variance. Fourteen test items were heavily loaded on the 1st principal component, so that 31.4% of the total variance was accounted for by this component. Considering these results as well as test-retest reliability, kurtosis, and skewness of each item, the following four items were selected as a combination of test battery: (X1) repetition of the bicipital flexion/extension, (X2) walking around two cones and sitting on a chair, (X3) moving beans with chopsticks, and (X4) functional reach. Principal component analysis was again applied to these four variables so as to obtain the first principal component score of each person. As a result, the following equation was drawn: the first principal component score = 0.063X1 - 0.055X2 + 0.098X3 + 0.042X4 - 2.65. The scores averaged 0.68 +/- 0.27 for the exercise group (n = 19) (those who played croquet or other similar sports activities consistently twice or more a week); and -0.76 +/- 0.55 for the sedentary group (n = 19) (those who did no exercise and confined their activities to the home). Biserial correlation coefficient as an index of criterion-related validity was 0.67 (P < 0.05) between the scores in the exercise and sedentary groups. These results indicate that a wide range of functional fitness among older Japanese women can be assessed by the four tests.

Aged↗

PubMed2003

Profiling phenolic metabolites in transgenic alfalfa modified in lignin biosynthesis.

Soluble phenolics, wall-bound phenolics and soluble and core lignin were analyzed in transgenic alfalfa with genetically down-regulated O-methyltransferase genes involved in lignin biosynthesis. High performance liquid chromatography and principal component analysis were used to distinguish metabolic phenotypes of different transgenic alfalfa genotypes growing under standard greenhouse conditions. Principal component analysis of HPLC chromatograms did not resolve differences in leaf metabolite profiles between wild-type and transgenic plants of the same genetic background, although stem phenolic profiles were clearly different between wild-type and transgenic plants. However, the analytical methods clearly differentiated two non-transgenic alfalfa cultivars based on either leaf or stem profiles. Metabolic profiling provides a useful approach to monitoring the broader biochemical phenotypes of transgenic plants with altered expression of lignin pathway enzymes.

Cell Wall↗

PubMed1989

Doubts on the adequacy of the principal component varimax analysis for the identification of event-related brain potential components: a commentary on Glaser and Ruchkin, and Donchin and Heffley.

Glaser and Ruchkin (1976) as well as Donchin and Heffley (1978) have proposed principal component varimax analysis (PCVA) for identification of event-related potential (ERP) components. In the present commentary, the assumptions on the ERP data structure of this procedure are considered. They are formalized and compared with a simpler and more restrictive hypothesized ERP data structure containing autoregressive properties. Referring to the principle of parsimony, the comparison of the two models shows the superiority of the hypothesized autoregressive structure: to fit a set of ERP data equally well, the autoregressive structure does so with considerably more parsimonious assumptions, i.e. with fewer parameters to be estimated, than the structure induced by PCVA. It is concluded that an appropriate model for the ERP data structure should take the autocorrelated nature of the ERP into account.

Contingent Negative Variation↗

PubMed1992

Multivariate quantitative structure-toxicity relationships in a series of dopamine mimetics.

The techniques of principal components analysis and non-linear mapping are routinely used by computer chemists at SmithKline Beecham Pharmaceuticals in the process of drug development by relating the structure of a compound to its chemical activity. To our knowledge these techniques had not previously been applied to the association between the structure of a compound and its toxicological properties. Using a series of 12 structurally related compounds (11 were active dopamine mimetics and one was inactive), of which five were known to be teratogenic and seven were non-teratogenic, it was possible to demonstrate that molecular modelling techniques could be applied to differentiate toxicological data. The structure/property relationships of these compounds were investigated using calculated physicochemical properties, molecular modelling and multivariate statistical techniques. A data set of 56 molecular descriptors was used to represent this series of compounds. Analysis of the data set using principal components analysis and non-linear mapping suggested that teratogenicity was associated with four molecular properties. Moreover, the electronic nature of the 4-phenyl group appeared to be an important determinant of the teratogenesis.

Abnormalities, Drug-Induced↗

PubMed2001

Ablation spectra of the human cornea.

Ablation of human corneal tissue with 193 nm excimer laser energy generates fluorescence in the near ultraviolet and visible regions of the spectrum. The fluorescence spectra from five human corneas were collected during ablation in vitro. We find that the fluorescence spectrum changes continuously as the cornea is ablated from the epithelial surface towards the endothelium. We reduced the dimensionality of the large data set resulting from each cornea by a principal components analysis. The three most significant principal component eigenvectors suffice to describe the observed spectral evolution, and independent analysis of each tissue sample produces a similar set of eigenvectors. The evolution of the calculated eigenvector weighting factors during ablation then corresponds to the observed spectral evolution. In fact, this evolution is qualitatively consistent between corneas. We suggest that this spectral evolution offers promise as a real-time surgical feedback tool.

Algorithms↗

PubMed2001

Analysis of galvanic skin responses with principal components and clustering techniques.

An advanced method for analyzing the patterning of successive galvanic skin responses (GSR) is presented. The proposed method is based on principal component analysis in which the vector containing the measured signal is presented as a weighted sum of orthogonal basis vectors. The method is tested using measurements from 20 healthy controls and 13 psychotic patients. For each subject, 11 surprising auditory stimuli were delivered to right ear at irregular intervals and evoked GSRs were recorded from the hand. For most of the healthy controls, there was a clear pattern in successive GSRs, whereas within psychotic patients the lack of time-locking of GSRs seemed to be characteristical. These between group differences can be revealed by the proposed method. With application to clustering a significant discrimination, with overall correct ratings of 82%, of healthy controls and psychotic patients is achieved. A significant fact is that all patients were ranked correctly giving the proposed method a sensitivity of 100%.

Case-Control Studies↗

PubMed1985

Third trochanter incidence and metric trait covariation in the human femur.

The relationship between third trochanter incidence and femoral metric trait covariation has been investigated in a group of 60 left human femora. The experimental sample was constructed so that one group consisted of 15 male and 15 female femora which displayed a third trochanter and a second group consisted of an equal number of sexed long bones which lacked this trait. A battery of ten femoral measurements was sorted according to main effects and interactions and respective covariance matrices were tested for equivalence. Covariance matrices of sorted variables determined not to be significantly different were initially subjected to both ANOVA and MANOVA and subsequently to a principal component analysis. Covariance matrices determined to be significantly different were subjected to a principal component analysis separately. Results of this study indicate that third trochanter incidence is associated with short femora displaying robust proximal diaphyses. The gluteus maximus muscle may act as a primary factor governing third trochanter expression. Further, this infracranial discrete trait appears well suited for human taxonomy studies.

Analysis of Variance↗