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PubMed1994

Principal Components Analysis of the General Purpose Abbreviated Battery of the Stanford-Binet, Fourth Edition, for Young Children

With increased emphasis on preschool assessment, the technology and theoretical basis of intelligence measures suitable for this age group is of increasing importance. One method of examining the appropriateness of preschool measures involves verification of the factor structure of the measure as an indication of construct validity. Factor analytic studies of the Binet 4 have not resulted in consistent findings, and more specifically, the number of factors identified have demonstrated variability across age levels. In that many clinicians use abbreviated forms of the Binet 4, this study conducted a principal component analysis of the General Purpose Abbreviated Battery (GPAB) for a sample of 107 children (ages 2-7 years) who were referred for evaluation to a community-based pediatric psychoeducational outpatient clinic. The structure of the GPAB resulted in a single general intelligence component that mitigates against Binet Area Score interpretation for this age group when the GPAB is used. Implications of previous research as well as the results of this study are discussed relative to the interpretation and utility of the GPAB with preschool and young children.

Journal Article↗
PubMed1995

Use of principal component analysis for the evaluation of the retention behaviour of monoamine oxidase inhibitory drugs on beta-cyclodextrin column.

The retention of 17 monoamine oxidase inhibitory drugs (proparlgylamine derivatives) were determined on a beta-cyclodextrin polymer (beta CDP)-coated silica column using ethanol-0.05 M K2HPO4 (6:4 v/v) as the eluent. The relative strength of interaction between the drugs and a water soluble beta-cyclodextrin polymer was determined by charge-transfer chromatography carried out on reversed-phase TLC layers. The relationship between capacity factors, physicochemical parameters and inclusion complex forming capacity of the monoamine oxidase inhibitory drugs were evaluated by stepwise regression analysis and by principal component analysis (PCA) followed by two-dimensional nonlinear mapping and varimax rotation. Calculations indicated that the retention of monoamine oxidase inhibitory drugs on beta CDP column is mainly governed by their steric and lipophylic parameters. Significant linear correlations were found between the corresponding coordinates of varimax rotation and two-dimensional nonlinear maps proving the suitability of both methods for the reduction of dimensionality of complicated data matrices.

Chemical Phenomena↗
PubMed2002

Molecular diversity sample generation on the basis of quantum-mechanical computations and principal component analysis.

The present study introduces a new strategy of selection of a maximum diversity sample of n compounds from N available in a molecular database. This strategy can be useful in pharmacological screening, combinatorial chemistry or parallel synthesis planning. It consists of first describing the compounds by means of parameters derived from quantum mechanical computations (water solvation deltaG, benzene solvation deltaG, octanol solvation deltaG, dipolar moment), as well as standard molecular parameters such as solvent-accessible surface area and molecular weight. Solvation parameters are used because of the importance of this phenomenon in the pharmacological behaviour. Redundant information in the description of the compounds is eliminated by using principal components (PC) instead of the original descriptors. Based on the similarity between the N compounds in the PC space, they are classified into n groups by k-means cluster analysis. The compounds that are nearest to the centroid of each cluster constituted the maximum diversity sample. When practical difficulties exist for the use of one of the proposed compounds, another also close to the cluster centroid can substitute for it. This strategy has been tested in the selection of a sample of 50 amines from the 923 available in the Aldrich catalogue. The results have been contrasted with those obtained from an optimal, distance-based experimental design, resulting in an 86% of agreement between both approaches. An R(2)-like diversity coefficient has been used to assess the quality of the proposed solutions.

Amines↗
PubMed1989

[Metrical study on teeth and mandible in Macaca fuscata fuscata. 2. Principal component analysis].

Metrical investigation on teeth and mandible together was performed to understand the morphological relationship between these two components in Macaca fuscata fuscata. Measurements are 9 items from the mandible, 2 items from dental arch, and 8 mesiodistal diameters from teeth. Correlation matrix composed of 19 items, in total, was examined in males and females, respectively. Significant correlation coefficients were frequently seen among mandibular measurements and also among tooth measurements, but rarely seen between mandibular and tooth measurements. The only exception was a mesiodistal diameter of P3 which has a few significant correlations with mandibular measurements. Principal component analysis was also carried out based on the correlation matrix of 19 measurements. The first component was a size factor in which factor loadings were all positive. The second component was thought to be a factor of the mandibular size in which factor loadings were highly positive on the mandibular measurements and contrarily low on the dental measurements. It is concluded that there is no obvious correlation between general sizes of the mandible and the teeth in Macaca fuscata fuscata.

Animals↗
PubMed2002

A new whole-mouth gustatory test procedure. 1. Thresholds and principal components analysis in healthy men and women.

Gustatory testing using the whole-mouth method was performed in 123 healthy young male and female subjects. The average thresholds for detection and recognition of the four basic tastes were not greatly different from the normal thresholds previously reported in Japan: a 0.0165 M solution of sucrose for sweet taste, a 0.0316 M solution of table salt for salty taste, a 0.000743 M solution of tartaric acid for sour taste and a 0.0000203 M solution of quinine hydrochloride for bitter taste. These results indicate that the whole-mouth gustatory test procedure employed in this study may be useful for evaluating gustatory function clinically. Principal components analysis confirmed that sweet, salty, sour and bitter are indeed the four basic tastes and revealed that the sensation of taste is detected before the specific taste is recognized, regardless of the specific taste tested.

Adolescent↗
PubMed2025

Matching Heterogeneous Cohorts by Projected Principal Components Reveals Two Novel Alzheimer's Disease-Associated Genes in the Hispanic Population.

Alzheimer's disease (AD) is the most common form of dementia in elderly, affecting 6.9 million individuals in the United States. Some studies have suggested the prevalence of AD is greater in individuals who self-identify as Hispanic. Focused results are relevant for personalized and equitable clinical interventions. Ethnicity as a stratifying tool in genetic studies is often accompanied by genomic inflation due to heterogeneity. In this study, we report GWAS and meta-analyses conducted among NIAGADS subjects who self-identified as Hispanic and All of Us (AoU) sub-cohorts matched to that cohort, using projected genetically-derived principal components, with and without age and sex. In Hispanic NIAGADS subjects, we identified a common variant in PIEZO2 that was protective for AD with a p-value just beyond genome-wide significance (p = 5.4*10-8). Meta-analyses with genetically-matched AoU participants yielded three (two novel) genome-wide significant AD-associated loci based on rare lead variants: rs374043832 (RGS6/PSEN1), rs192423465 (ASPSCR1), and rs935208076 (GDAP2), which were also nominally significant in AoU sub-cohorts. We thus demonstrate an efficient way to select subjects from large heterogeneous biobank cohorts who are genetically similar to a smaller disease-specific cohort, yielding novel disease-relevant findings.

Journal Article↗
PubMed1997

Identification of mitochondrial deficiency using principal component analysis.

The mitochondrial pathologies are a heterogeneous group of metabolic disorders that are characterized by anomalies of oxidative phosphorylation, especially in the respiratory chain. The diagnosis of these pathologies involves many investigations among which biochemical study is at present the main tool. However, the analysis of the results obtained during such study remains complex and often does not make it possible to conclude clearly if a patient is affected or not by a biochemical and/or bioenergetic deficiency. This arises from two main problems: 1. The determination of control values from the whole set of variable values (affected and unaffected people). 2. The small size of the population studied and the large number of variables collected which present a rather large variability. To cope with these problems, the principal component analysis method is applied to the results obtained during our biochemical studies. This analysis makes it possible for each respiratory chain complex, to distinguish clearly two subsets of the whole population (affected and unaffected people) as well as to detect the variables which are the most discriminative.

Adolescent↗
PubMed2004

Orientations of the principal components of electric field gradients and internal motions in dihydrogen ligands from the 2H T1 NMR relaxation data in solution.

The deuterium spin-lattice relaxation times in (D2) ligands of W, Ru and Os complexes are reviewed and analyzed in terms of the fast internal (D2) motions: free rotation, librations and 180 degrees jumps. The analysis was performed using quadrupolar coupling constant (DQCC) parameters taken from the solid-state 2H NMR spectra and density function theory calculations. It is shown that the calculated DQCC values can be corrected for further use in interpretations of deuterium relaxation times for Ru and Os dihydrogen complexes. The resulting data led to a criterion for using the relaxation data to distinguish fast-spinning dihydrogen ligands. It is shown that the principal components of electric field gradient tensors at D in the dihydrogen ligands are oriented closer to M-D directions.

Databases as Topic↗
PubMed2004

Improvement of comparative model accuracy by free-energy optimization along principal components of natural structural variation.

Accurate high-resolution refinement of protein structure models is a formidable challenge because of the delicate balance of forces in the native state, the difficulty in sampling the very large number of alternative tightly packed conformations, and the inaccuracies in current force fields. Indeed, energy-based refinement of comparative models generally leads to degradation rather than improvement in model quality, and, hence, most current comparative modeling procedures omit physically based refinement. However, despite their inaccuracies, current force fields do contain information that is orthogonal to the evolutionary information on which comparative models are based, and, hence, refinement might be able to improve comparative models if the space that is sampled is restricted sufficiently so that false attractors are avoided. Here, we use the principal components of the variation of backbone structures within a homologous family to define a small number of evolutionarily favored sampling directions and show that model quality can be improved by energy-based optimization along these directions.

Models, Molecular↗
PubMed2002

Time-frequency and principal-component methods for the analysis of EMGs recorded during a mildly fatiguing exercise on a cycle ergometer.

Electromyographic signals contain the information on muscle activity and have to be frequently averaged, compared, classified or details need to be extracted. A time-frequency analysis, based on wavelets, was previously presented. The analysis transformed an EMG signal into an EMG-intensity-pattern showing the intensities at any point in time for the frequencies filtered out by the wavelets. The purpose of the present study was:to define and apply a new EMG-pattern-space for the analysis of EMG-intensity-patterns; and to determine the variation of EMG-intensity-patterns while getting mildly fatigued by cycling on a cycle-ergometer. The coordinates spanning the pattern space were principal components of the measured EMG-intensity-patterns. A point in pattern-space thus represented an EMG-intensity-pattern. Fatigue resulted in points moving along a line in pattern space. The line was characterized by an intercept at time 0 and a slope. Thus mild fatigue caused a shift from an initial intensity-pattern representing the intercept to a final intensity-pattern adding gradually larger amounts of the pattern representing the slope. The intensity-pattern of the slope revealed the physiologically important individual strategies for coping with mild fatigue. Changes were observed at different times and at different frequencies during the cycling movement.

Adult↗
PubMed1985

Subclassification of neurons in the ventrobasal complex of the dog: quantitative Golgi study using principal components analysis.

The neuronal architecture of the ventrobasal complex (VB) in dog is examined in coronal and horizontal brain sections processed by Golgi- and Nissl-staining methods. Presumed projection and intrinsic neurons are identified by differences in soma size and shape, dendritic branch pattern, the morphology and distribution of appendages, and the appearance of axons. Forty-five projection neurons are examined by quantifying (1) soma cross-sectional area, (2) dendritic field extent and shape, (3) appendages on the soma, primary dendrites, and in a defined major dendritic branch zone, and (4) location in the VB. When considered independently, each variable offers little evidence for separation into morphological classes. However, several of the variables have wide ranges and show significant correlation with other parameters. Using the multivariate descriptive methods of principal components analysis and cluster analysis, a separation of the projection neurons into three morphological classes designated as large, medium, and small neurons is indicated. The features most critical in distinguishing between the groups are, in descending order of importance: (1) dendritic field extent; (2) number of primary dendrites; (3) soma cross-sectional area; (4) number of appendages per major branch point (MBP); (5) number of appendages on the soma; and, (6) number of appendages on the primary dendrites. Dendritic field shape and neuron location have little influence in determining classification.

Analysis of Variance↗
PubMed1994

Principal component analysis, using the measurements during running and swimming test, in thoroughbred horses.

To investigate whether the running exercise fitness of individual horses could be assessed by a standardized swimming exercise test, the results of multivariate analysis of the exercise parameters measured during incremental running and swimming tests were compared. Ten thoroughbred horses were subjected to different types of exercise tests on a track or in a pool, and the maximum heart rate during and the blood lactate concentration immediately after the exercise were examined. Serial exercise parameters (VLA2, VLA4, LA0, V150, V200, HRS, HRLA2, HRLA4) referred to as the indices related to the adaptation of cardiovascular or metabolic systems were computed using the relationships between these measurements and velocity during each test, and were analyzed by a multivariate procedure, i.e. the principal component analysis. The correlation diagram between the exercise parameters on the first two component axes in running were similar to that in swimming. When the exercise fitness in each horse was compared between running and swimming, three horses trained by short-term endurance exercise were statistically distinguished in both tests and differed as a group from the other horses. Therefore, it is thought that evaluation of the exercise fitness in swimming using the multivariate analysis is useful for predicting poor performing horses on a track.

Animals↗
PubMed2005

Enhancing the signal-to-noise ratio of X-ray diffraction profiles by smoothed principal component analysis.

X-ray diffraction is one of the most widely applied methodologies for the in situ analysis of kinetic processes involving crystalline solids. However, due to its relatively high detection limit, it has only limited application in the context of crystallizations from liquids. Methods that can improve the detection limit of X-ray diffraction are therefore highly desirable. Signal processing approaches such as Savitzky-Golay, maximum likelihood, stochastic resonance, and wavelet transforms have been used previously to preprocess X-ray diffraction data. Since all these methods only utilize the frequency information contained in the single X-ray diffraction profile being processed to discriminate between the signals and the noise, they may not successfully identify very weak but important peaks especially when these weak signals are masked by severe noise. Smoothed principal component analysis (SPCA), which takes advantage of both the frequency information and the common variation within a set of profiles, is proposed as a methodology for the preprocessing of the X-ray diffraction data. Two X-ray diffraction data sets are used to demonstrate the effectiveness of the proposed approach. The first was obtained from mannitol-methanol suspensions, and the second data set was generated from slurries of L-glutamic acid (GA) in methanol. The results showed that SPCA can significantly improve the signal-to-noise ratio and hence lower the detection limits (approximately 0.389% g/mL for mannitol-methanol suspensions and 0.4 wt % for beta-form GA in GA-methanol slurries comprising mixtures of both alpha- and beta-forms of GA) thereby providing an important contribution to crystallization process performance monitoring.

Crystallization↗
PubMed1993

Differential diagnosis in dementia. Principal components analysis of clinical data from a population survey.

OBJECTIVE: To reduce all the clinical data, collected from an unselected group of subjects, to a small set of factors and to see how these factors correspond to standard clinical diagnosis of dementing disorders. DESIGN: Population survey. SETTING: General community: elderly older than 74 years, from an area in Stockholm, Sweden. SUBJECTS: Population-based sample including (1) all the screened positive subjects using the Mini-Mental State examination; and (2) a random sample of the screened negative subjects, matched by age and sex. A clinical examination and an informant interview were carried out. Cases were identified using Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition diagnostic criteria for Alzheimer's disease (AD) and other dementias. MAIN OUTCOME MEASURE: Independently from the clinical diagnosis, a principal components factor analysis was carried out to investigate groupings among the clinical data (factors). Factor scores, calculated as a weighted sum of the symptom variables and converted to a standard score form. RESULTS: Four major factors were found: cognitive impairment, cerebrovascular disease, disturbed behavior, and depressive symptoms. The comparison of these factors with the clinical diagnoses showed that (1) the cognitive impairment factor discriminated demented cases from nondemented; (2) the cerebrovascular disease factor discriminated vascular dementia from AD cases and nondemented; (3) the disturbed behavior factor discriminated AD cases from vascular dementia cases and nondemented, indicating behavioral changes characteristic of AD. CONCLUSIONS: This finding, if replicated, would have implications for the construction of diagnostic criteria for AD.

Aged↗
PubMed1995

Link between emotional memory and anxiety states: a study by principal component analysis.

Numerous theoretical as well as pharmacological arguments lead to the assumption that anxiety and memory are two closely linked concepts. Nevertheless, the study of this relationship is full of complexities because neither memory nor anxiety are unitary phenomena. Indeed, the term memory covers a large number of concepts, and anxiety has been divided in two main classes, "state" and "trait" anxiety. Recently the neophobic responses exhibited by Balb/c mice confronted to the free exploratory paradigm have been proposed as a "trait anxiety" model while response exhibited in the light/dark choice procedure as a "state anxiety" one. The aim of this study was to further clarify the link between these two anxiety types and memory of emotional events assessed in the passive avoidance test. The relationship between the variables measured in these three tests were assessed by a principal component analysis that confirmed that the behavior recorded in the two anxiety tests does not reflect the same psychological state, and showed that emotional memory is linked to "state" but not "trait" anxiety.

Animals↗
PubMed2000

Statistical analysis of mitochondrial pathologies in childhood: identification of deficiencies using principal component analysis.

Mitochondrial pathologies are a heterogeneous group of metabolic disorders that are frequently characterized by anomalies of oxidative phosphorylation, especially in the respiratory chain. The identification of these anomalies may involve many investigations, and biochemistry is a main tool. However, considering the whole set of biochemical data, the interpretation of the results by the traditionally used statistical methods remains complex and does not always lead to an unequivocal conclusion about the presence or absence of a respiratory chain defect. This arises from three main problems: (a) the absence of an a priori-defined control population, because the determination of the control values are derived from the whole set of investigated patients, (b) the small size of the population studied, (c) the large number of variables collected, each of which creates a wide variability. To cope with these problems, the principal component analysis (PCA) has been applied to the biochemical data obtained from 35 muscle biopsies of children suspected of having a mitochondrial disease. This analysis makes it possible for each respiratory chain complex to distinguish between different subsets within the whole population (normal, deficient, and, in between, borderline subgroups of patients) and to detect the most discriminating variables. PCA of the data of all complexes together showed that mitochondrial diseases in this population were mainly caused by multiple deficits in respiratory chain complexes. This analysis allows the definition of a new subgroup of newborns, which have high respiratory chain complex activity values. Our results show that the PCA method, which simultaneously takes into account all of the concerned variables, allows the separation of patients into subgroups, which may help clinicians make their diagnoses.

Adolescent↗
PubMed2000

Statistical validation of reproducibility of HPLC peptide mapping for the identity of an investigational drug compound based on principal component analysis.

Peptide mapping is a key analytical method for studying the primary structure of proteins. The sensitivity of the peptide map to even the smallest change in the covalent structure of the protein makes it a valuable "fingerprint" for identity testing and process monitoring. We recently conducted a full method validation study of an optimized reverse-phase high-performance liquid chromatography (RP-HPLC) tryptic map of a therapeutic anti-CD4 monoclonal antibody. We have used this method routinely for over a year to test production lots for clinical trials and to support bioprocess development. One of the difficulties in the validation of the peptide mapping method is the lack of proper quantitative measures of its reproducibility. A reproducibility study may include method and system precision study, ruggedness study, and robustness study. In this paper, we discuss the use of principal component analysis (PCA) to quantitate peptide maps properly using its projected scores on the reduced dimensions. This approach allowed us not only to summarize the reproducibility study properly, but also to use the method as a diagnostic tool to investigate any troubles in the reproducibility validation process.

Antibodies, Monoclonal↗
PubMed1992

Use of principal components analysis for mutation detection with two-dimensional electrophoresis protein separations.

The application of two-dimensional electrophoresis (2-DE) to mutation detection requires the capability to monitor each protein in a 2-DE pattern for significant changes in abundance indicative of a mutation event. Previously, mutation searches were done using a univariate outlier detection method in which each protein spot was considered independently in a classical outlier search. An alternative approach to analysis of 2-DE patterns for quantitative changes is a multivariate procedure which takes advantage of the observation that protein spots in a 2-DE pattern often represent correlated rather than independent measurements. We have compared the efficiency of univariate and multivariate procedures for mutation detection using data from the Argonne National Laboratory 2-DE database of mouse liver proteins. Analyses involving a total of over 1500 gels were performed to compare the performance of a multivariate method based on principal components analysis (PCA) with the univariate method. Up to 279 spots from each pattern were used for PCA. First, a simulation was performed to assess the detection efficiency of PCA for single protein spots decreased in abundance by 50%. Then, the ability to detect actual mutations was tested using eight confirmed mutations. Results show that, compared to a univariate approach to analysis of data from the mouse model system, the multivariate method increases the number of protein spots on each 2-DE pattern that can be monitored for quantitative changes indicative of mutations by compensating for variables that contribute to the background quantitative variability of protein spots.

Animals↗