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At least 613 records · Page 34Linked to original sources
PubMed2003

Chromatographic classification and comparison of commercially available reversed-phase liquid chromatographic columns using principal component analysis.

A total of 135 commercially available alkyl, cyano, phenyl, perfluorinated, polar embedded, enhanced polar selectivity (i.e., polar/hydrophilic endcapped), "Aqua type" and a variety of novel phases including some non-silica based stationary phases have been characterised in terms of their surface coverage, hydrophobic selectivity, shape selectivity, hydrogen bonding capacity and ion-exchange capacity at pH 2.7 and 7.6. Principal component analysis has been used to provide a simple graphical comparison of the differences/similarities between columns in the entire database and differing subsets such as "Aqua type"/enhanced polar selectivity phases. The PCA has been correlated to the phase's ability to analyse a range of hydrophilic bases.

Chromatography, Liquid↗
PubMed1979

Principal component analysis of four health indicators and construction of a global health index in the aged.

The health status of 1025 urban senior citizens in a Montreal metropolitan area was determined by a questionnaire based on the subjects' view of physical, mental, and general well-being, and of dependence (indicators of Belloc et al., Berkman, Grogono and Woodgate, and Linn). A principal component analysis was made of these health indicators and two factors were retained. The first factor, which can be called a global health index, was used to compare the sexes and the age strata; it was thus found that men (those who survive) are generally healthier than the women, and that subjects from the lower-age strata are healthier than their older counterparts. The second factor is described as opposing physical health and dependence to mental health, the results of which were similar for both sexes, bur differed according to the various age strata compared.

Age Factors↗
PubMed1993

Conformational characterization of nucleosomes by principal component analysis of their electron micrographs.

Optimized fixation conditions were determined for protein-protein and protein-DNA crosslinking within calf-thymus nucleosomes in low monovalent salt concentrations. Nucleosomes were examined without heavy-atom staining by darkfield electron microscopy. The dimensions of these macromolecular complexes and those of HeLa core particles optimally fixed in divalent salt were analysed using principal component analysis. According to this analysis the structure of the calf-thymus nucleosomes was best presented by a prolate ellipsoid. Particle images had average major and minor axis lengths of 14.1 and 10.5 nm, respectively. In contrast, the HeLa nucleosomes were best modelled by an oblate ellipsoid from the analysis of their images, which had average major and minor axes of 13.3 and 11.5 nm. The applicability of this multivariate statistical analysis to the interpretation of macromolecular images is illustrated and discussed.

Animals↗
PubMed2002

Genetics of colitis susceptibility in IL-10-deficient mice: backcross versus F2 results contrasted by principal component analysis.

Interleukin-10-deficient (Il10(-/-)) mice on a C3H/HeJBir genetic background develop more severe colitis than those on a C57BL/6J background. We performed genome screens for quantitative trait loci (QTLs) regulating colitis susceptibility in this model system using two first backcross populations derived from these two strains. To reduce the complexity of this analysis, the information from numerous histologic phenotypes was summarized by principal component analysis. A similar approach was applied to previously published data from an F2 intercross (involving the same progenitor strains), which allowed us to ascertain all six previously reported cytokine-deficiency-induced colitis susceptibility loci (Cdcs1-6) with main and/or interacting effects on chromosomes 3, 1, 2, 8, 17, and 18. The colitogenic effect of Cdcs1 was confirmed in the backcross to C3H/HeJBir-Il10(-/-). Its effect was epistatically modified by another locus on chromosome 12. In addition, three main effect QTLs on chromosomes 4, 5, and 12 were identified in the backcross to C57BL/6J-Il10(-/-). Analyses of the modes of inheritance in these crosses revealed colitogenic contributions by both parental genomes. These findings show the complexity of inheritance underlying susceptibility to colitis and illustrate why detection of human inflammatory bowel disease loci has proven to be so difficult.

Animals↗
PubMed2001

Studies on the structure of water using two-dimensional near-infrared correlation spectroscopy and principal component analysis.

The structure of water molecules in the pure liquid state has been subjected to extensive research for several decades. Questions still remain unanswered, however, and no single model has been found capable of explaining all the anomalies of water. In the present study, near-infrared spectra of water in the temperature region 6-80 degrees C have been analyzed by use of principal component analysis and two-dimensional correlation spectroscopy in order to study the dynamic behavior of a band centered around 1,450 nm at room temperature, which is due to the combination of symmetric and antisymmetric O-H stretching modes (first overtone) of water. It has been found that the wavelengths 1,412 and 1,491 nm account for more than 99% of the spectral variation, representing two major water species with weaker and stronger hydrogen bonds, respectively. A third species located at 1438 nm, whose concentration was relatively constant as a function of temperature, is also indicated. A somewhat distorted two-state structural model for water is suggested.

Journal Article↗
PubMed2002

Fast formation of statistically reliable FDG parametric images based on clustering and principal components.

Formation of parametric images requires voxel-by-voxel estimation of rate constants, a process sensitive to noise and computationally demanding. A model-based clustering method for a two-parameter model (CAKS) was extended to the FDG three-parameter model. The concept was to average voxels with similar kinetic signatures to reduce noise. Voxel kinetics were categorized by the first two principal components of the tissue time-activity curves for all voxels. k2 and k3 were estimated cluster-by-cluster, and K1 was estimated voxel-by-voxel within clusters. When CAKS was applied to simulated images with noise levels similar to brain FDG scans, estimation bias was well suppressed, and estimation errors were substantially smaller--1.3 times for Ki and 1.5 times for k3-than those of conventional voxel-based estimation. The statistical reliability of voxel-level estimation by CAKS was comparable with ROI analysis including 100 voxels. CAKS was applied to clinical cases with Alzheimer's disease (ALZ) and cortico basal degeneration (CBD). In ALZ, the affected regions had low Ki (K1k3/(k2 +k3)) and k3. In CBD, Ki was low, but k3 was preserved. These results were consistent with ROI-based kinetic analysis. Because CAKS decreased the number of invoked estimations, the calculation time was reduced substantially. In conclusion, CAKS has been extended to allow parametric imaging of a three-compartment model. The method is computationally efficient. with low bias and excellent noise properties.

Algorithms↗
PubMed1996

Use of principal component analysis for the study of the retention behaviour of anticancer drugs on a beta-cyclodextrin polymer-coated silica column.

The retention parameters of eighteen commercial anticancer drugs were determined on a beta-cyclodextrin polymer-coated silica support (beta CDP) using methanol-water mixtures as eluent and the relationship between the retention behaviour and physico-chemical parameters was elucidated by principal component analysis (PCA) followed by two-dimensional non-linear mapping. No significant linear correlation was found between the retention behaviour of drugs on octadecylsilica and beta CDP silica columns, indicating that the retention capacity and selectivity of the columns are considerably different. The results of PCA indicated that hydrophobic and electronic interactions and steric conditions govern the retention of anticancer drugs on beta CDP column, suggesting a mixed retention mechanism.

Antineoplastic Agents↗
PubMed2005

Applications of hierarchical cluster analysis (CLA) and principal component analysis (PCA) in feed structure and feed molecular chemistry research, using synchrotron-based Fourier transform infrared (FTIR) microspectroscopy.

Synchrotron technology based Fourier transform infrared microspectroscopy (S-FTIR) is a recently emerging bioanalytical microprobe capable of exploring the molecular chemistry within microstructures of feed tissues at a cellular or subcellular level. To date there has been very little application of hierarchical cluster analysis (CLA) and principal component analysis (PCA) to the study of feed inherent microstructures and feed molecular chemistry between feeds and/or between different structures within a feed, in relation to feed quality and nutrient availability using S-FTIR. In this paper, multivariate statistical methods--CLA and PCA--were used to analyze synchrotron-based FTIR individual spectra obtained from feed inherent microstructures within intact tissues by using the S-FTIR as a novel approach. The S-FTIR spectral data of three feed inherent structures (strucutre 1, feed pericarp; structure 2, feed aleurone; structure 3, feed endosperm) and different varieties of feeds within cellular dimensions were collected at the National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory (BNL), U.S. Department of Energy (NSLS-BNL, New York). Both PCA and CLA methods gave satisfactory analytical results and are conclusive in showing that they can discriminate and classify inherent structures and molecular chemistry between and among the feed tissues. They also can be used to identify whether differences exist between the varieties. These statistical analyses place synchrotron-based FTIR microspectroscopy at the forefront of those new potential techniques that could be used in rapid, nondestructive, and noninvasive screening of feed intrinsic microstructures and feed molecular chemistry in relation to the quality and nutritive value of feeds.

Analysis of Variance↗
PubMed1996

Differentiation of resin-modified paints by pyrolysis-gas chromatography/mass spectrometry and principal component analysis.

The combination of pyrolysis (Py) with gas chromatography/mass spectrometry (GC/MS) is already well established for polymer analysis. A first approach is reported using this method for detailed quality monitoring of a complex technical polymer system. Six similar solvent-based paints (one standard and five modifications) have been used for evaluation. The major pyrolysis products were identified and qualitative and quantitative modifications were detected and specified. Principal component analysis (PCA) was applied for visualization of differences and similarities.

Journal Article↗
PubMed1985

Subclassification of neurons in the subthalamic nucleus of the lesser bushbaby (Galago senegalensis): a quantitative Golgi study using principal components analysis.

The morphology of neurons in the subthalamic nucleus (STN) of the lesser bushbaby (Galago senegalensis) is described in coronal brain sections processed by Golgi- and Nissl-staining techniques. Quantitative and statistical methods are used to evaluate (1) soma size and shape, (2) dendritic field size, shape, and branch frequency, (3) the number of dendritic and somatic spines per neuron, and (4) neuron location within the STN. Principal components analysis of these variables suggests that three classes of neurons are present. Two of these classes are considered to be projection cells, referred to as elongate-fusiform and radiate neurons, respectively. Elongatefusiform neurons have somata and dendritic fields which are large in diameter, extremely fusiform in shape, and give rise to few appendages. Somata and dendritic fields of radiate neurons are smaller in diameter, more rounded in shape, and support more spines than the elongate-fusiform neurons. The third class of cells in Galago STN is tentatively identified as consisting of interneurons on the basis of small soma and dendritic field size, thin and varicose dendritic morphology, and the presence of multilobulated dendritic appendages.

Animals↗
PubMed2000

Determination of the major dimensions of femoral implants using morphometrical data and principal component analysis.

This paper describes the work that leads to the establishment of a set of major parameters for the design of symmetrical prosthetic implants for the Asian population. In the study, 62 sets of femurs harvested from cadavers were used. The morphometrical data obtained are compared with known results and found to be in good agreement with Asian knees. Subsequently, the data are treated and analysed using the principal component analysis, a statistical technique for analysing multivariate data. The analysis has resulted in the establishment of the major design parameters for six different sizes of femoral implants. Details of the analysis are presented. The major parameters obtained in this work are compared with those of existing implants. Results of the comparison are presented. The relationship between the anterio-posterior and medio-lateral dimensions is also examined and reported.

Aged↗
PubMed2002

Principal component method for assessing structural heterogeneity across multiple alignment media.

The recent availability of residual dipolar coupling measurements in a variety of different alignment media raises the question to what extent biomolecular structure and dynamics are differentially affected by their presence. A computational method is presented that allows the sensitive assessment of such changes using dipolar couplings measured in six or more alignment media. The method is based on a principal component analysis of the covariance matrix of the dipolar couplings. It does not require a priori structural or dynamic information nor knowledge of the alignment tensors and their orientations. In the absence of experimental errors, the covariance matrix has at most five nonzero eigenvalues if the structure and dynamics of the biomolecule is the same in all media. In contrast, differential structural and dynamic changes lead to additional nonzero eigenvalues. Characteristic features of the eigenvalue distribution in the absence and presence of noise are discussed using dipolar coupling data calculated from conformational ensembles taken from a molecular dynamics trajectory of native ubiquitin.

Computational Biology↗
PubMed1987

Principal components analysis for source localization of VEPs in man.

This study defines and compares the topologies of the visual evoked potentials to various stimuli such as pattern onset/offset, pattern reversal, pattern motion and high frequency luminance flicker. The responses recorded from 24 occipital derivations were examined using a three sphere conductance model to represent the head, with the assumption that activity from an underlying cortical source is equivalent to a single dipole. Principal components analysis was used to find the dimensionality of the data space. From this analysis could be concluded that all stimuli evoked responses in the primary visual cortex. Only pattern onset, and to a lesser degree pattern offset and pattern reversal, yielded activity in higher visual areas. In particular it has been shown that the CI, CII interval of the pattern onset response has its origins in two different cortical regions. A fast positive (CI)-negative (part of the CII) component arises from area 18 (or 19), a slower negative (initial part of CII) component comes from area 17.

Evoked Potentials, Visual↗
PubMed1998

Determination of lipophilicity of some non-steroidal anti-inflammatory agents and their relationships by using principal component analysis based on thin-layer chromatographic retention data.

The relative lipophilicity of ten non-steroidal anti-inflammatory agents have been determined by reversed-phase thin layer chromatography using different reversed-phase high-performance thin-layer chromatography plates and water-methanol mixtures as eluents. The compounds studied showed regular retention behavior, their RM values decreasing linearly with increasing concentration of methanol in the eluent. Principal component analysis allowed a more rational and objective estimation and comparison of lipophilicity determined by reversed-phase thin-layer chromatography. It also affords a useful graphical tool, since scatterplots of the scores onto the plane described by the first two components will have the effect of separating compounds from each other most effectively, thus obtaining "congeneric lipophilicity chart".

Anti-Inflammatory Agents, Non-Steroidal↗
PubMed1975

Calcitonin treatment of post-menopausal osteoporosis. Evaluation of efficacy by principal components analysis.

The efficacy of long term treatment of senile osteoporosis by low doses of calcitonin was established using five parameters of calcium kinetics and a quantitative pain scale. Under treatment the calcium balance improved, due predominantly to a decrease in bone resorption associated with an increase in bone accretion and intestinal absorption of calcium. In addition, the hormone had a marked analgesic effect, which increased with the length of the treatment. Principal components analysis enables to establish the value of a therapeutic agent for the management of a progressive disease with period of regression like osteoporosis, for which the eficacy of previously advocated treatments had never been proven.

Aging↗
PubMedDate not supplied

Effective dimensionality of large-scale expression data using principal component analysis.

Large-scale expression data are today measured for thousands of genes simultaneously. This development is followed by an exploration of theoretical tools to get as much information out of these data as possible. One line is to try to extract the underlying regulatory network. The models used thus far, however, contain many parameters, and a careful investigation is necessary in order not to over-fit the models. We employ principal component analysis to show how, in the context of linear additive models, one can get a rough estimate of the effective dimensionality (the number of information-carrying dimensions) of large-scale gene expression datasets. We treat both the lack of independence of different measurements in a time series and the fact that that measurements are subject to some level of noise, both of which reduce the effective dimensionality and thereby constrain the complexity of models which can be built from the data.

Gene Expression Profiling↗
PubMed2000

Chromosome identification using hidden Markov models: comparison with neural networks, singular value decomposition, principal components analysis, and Fisher discriminant analysis.

The analysis of G-banded chromosomes remains the most important tool available to the clinical cytogeneticist. The analysis is laborious when performed manually, and the utility of automated chromosome identification algorithms has been limited by the fact that classification accuracy of these methods seldom exceeds about 80% in routine practice. In this study, we use four new approaches to automated chromosome identification--singular value decomposition (SVD), principal components analysis (PCA), Fisher discriminant analysis (FDA), and hidden Markov models (HMM)--to classify three well-known chromosome data sets (Philadelphia, Edinburgh, and Copenhagen), comparing these approaches with the use of neural networks (NN). We show that the HMM is a particularly robust approach to identification that attains classification accuracies of up to 97% for normal chromosomes and retains classification accuracies of up to 95% when chromosome telomeres are truncated or small portions of the chromosome are inverted. This represents a substantial improvement of the classification accuracy for normal chromosomes, and a doubling in classification accuracy for truncated chromosomes and those with inversions, as compared with NN-based methods. HMMs thus appear to be a promising approach for the automated identification of both normal and abnormal G-banded chromosomes.

Chromosome Mapping↗
PubMed2001

The principal components of response strength.

As Skinner (1938) described it, response strength is the "state of the reflex with respect to all its static properties" (p. 15), which include response rate, latency, probability, and persistence. The relations of those measures to one another was analyzed by probabilistically reinforcing, satiating, and extinguishing pigeons' key pecking in a trials paradigm. Reinforcement was scheduled according to variable-interval, variable-ratio, and fixed-interval contingencies. Principal components analysis permitted description in terms of a single latent variable, strength, and this was validated with confirmatory factor analyses. Overall response rate was an excellent predictor of this state variable.

Animals↗