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At least 649 records · Page 36Linked to original sources
PubMed2000

Classification of chili powders by thin-layer chromatography and principal component analysis.

Silica gel, aluminium oxide, diatomaceous earth, polyamide, cyano, diol and amino plates have been tested for their capacity to separate the color pigments of six chili powders of different origin by both adsorption and reversed-phase thin-layer chromatography. The plates were evaluated at 340 and 440 nm wavelengths. Best separation of color pigments was obtained on impregnated diatomaceous earth layer using acetone-water 17:3 v/v eluent. It was found that the pigment composition of chili powders showed marked differences. Principal component analysis employed for the classification of the chili powders according to their pigment composition indicated that these differences can be used for the determination of the similarity or dissimilarity of the chili powders.

Capsicum↗
PubMed1998

Short column gas chromatography-mass spectrometry and principal component analysis for the identification of coeluted substances in doping control analysis.

The identification of four doping control substances in an artificial mixture, using short column gas chromatography-mass spectrometry (GC-MS) analysis was examined. Two chromatographic peaks were recorded in the chromatogram, using a short capillary column (1.8 m) at an oven temperature of 180 degrees C. The first peak was associated with a mixture of a solvent derivative and an artifact. The second one corresponded to the mixture of four control substances. Principal component analysis was applied on a selected GC-MS data set of the latter peak to determine clear full spectra of pure substances from mixture spectra. The time of GC-MS analysis was significantly reduced to less than 1 min from 30 min which is a typical GC-MS analysis time, using standard methods of doping control analysis.

Cocaine↗
PubMed1997

Recognition of patient anaesthetic levels: neural network systems, principal components analysis, and canonical discriminant variates.

The goal of this study was to examine the ability of Neural Networks to recognise the levels of anaesthetic state of a patient. Data obtained under different levels of anaesthesia have been modelled for the purpose. It is shown that inferential parameters can be used to recognise the levels of anaesthesia. In addition to demonstrating the ability of neural networks for classification we were interested in understanding the classification strategy discovered by the neural networks. Multivariate data analysis techniques, namely Principal Components Analysis and Canonical Discriminant Variates, were applied to analyse the resultant networks.

Anesthesia↗
PubMed1992

Depression in Benin: an assessment using the Comprehensive Psychopathological Rating Scale and the principal component analysis.

Ninety two major depressed outpatients were rated with the Comprehensive Psychopathological Rating Scale (CPRS) in Cotonou, in Benin (West-Africa). Patients satisfied modified DSM III major depression criteria and were French-speaking. Men, civil servants, and city dwellers were over-represented in the population sample. The examination of item frequency yielded rather 'western-like' clinical features of depression: with differences described previously: a lower frequency of suicidal thoughts and guilt feelings, a higher frequency of somatic complaints and ideas of persecution. Principal component analysis reinforced 'western-like' aspects. The relationship between the so-called 'western culture-bound symptoms' and the so-called 'African ones' is discussed.

Adult↗
PubMed2005

Distinctiveness, typicality, and recollective experience in face recognition: a principal components analysis.

In this study, participants rated previously unseen faces on six dimensions: familiarity, distinctiveness, attractiveness, memorability, typicality, and resemblance to a familiar person. The faces were then presented again in a recognition test in which participants assigned their positive recognition decisions to either remember (R), know (K), or guess categories. On all dimensions except typicality, faces that were categorized as R responses were associated with significantly higher ratings than were faces categorized as K responses. Study ratings for R and K responses were then subjected to a principal components analysis. The factor loadings suggested that R responses were influenced primarily by the distinctiveness of faces, but K responses were influenced by moderate ratings on all six dimensions. These findings indicate that the structural features of a face influence the subjective experience of recognition.

Face↗
PubMed2005

Analysis of glass fragments by laser ablation-inductively coupled plasma-mass spectrometry and principal component analysis.

Laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) is used to differentiate glass samples with similar optical and physical properties based on trace elemental composition. Laser ablation increases the number of elements that can be used for differentiation by eliminating problems commonly associated with dissolution and contamination. In this study, standard residential window and tempered glass samples that could not be differentiated by refractive index or density were successfully differentiated by LA-ICP-MS. The primary analysis approach used is Principal Component Analysis (PCA) of the complete mass spectrum. PCA, a multivariate analysis technique, provides rapid analysis of samples without time-consuming pair-wise comparison of calibrated analyses or prior knowledge of the elements present in the samples. Probabilities for positive association of the individual samples are derived from PCA. Utilization of the Q-statistic with PCA allowed us to distinguish all samples within the set to a certainty greater than the 99% confidence interval.

Journal Article↗
PubMed2006

Principal component analysis of urine metabolites detected by NMR and DESI-MS in patients with inborn errors of metabolism.

Urine metabolic profiles of patients with inborn errors of metabolism were examined with nuclear magnetic resonance (NMR) and desorption electrospray ionization mass spectrometry (DESI-MS) methods. Spectra obtained from the study of urine samples from individual patients with argininosuccinic aciduria (ASA), classic homocystinuria (HCY), classic methylmalonic acidemia (MMA), maple syrup urine disease (MSUD), phenylketonuria (PKU) and type II tyrosinemia (TYRO) were compared with six control patient urine samples using principal component analysis (PCA). Target molecule spectra were identified from the loading plots of PCA output and compared with known metabolic profiles from the literature and metabolite databases. Results obtained from the two techniques were then correlated to obtain a common list of molecules associated with the different diseases and metabolic pathways. The combined approach discussed here may prove useful in the rapid screening of biological fluids from sick patients and may help to improve the understanding of these rare diseases.

Case-Control Studies↗
PubMed1989

Principal components analyses of behavior problems in Jamaican clinic-referred children: teacher reports for ages 6-17.

Factor analyses of child behavior problems have often yielded two broad-band syndromes, Overcontrolled (e.g., worrying, fearfulness, withdrawal) and Undercontrolled (e.g., restlessness, fighting, disobedience). We explored whether these two broad-band syndromes might be identified for youngsters in Jamaica. We obtained teacher reports for 320 clinic-referred Jamaican youngsters on a 24-item problem checklist designed by Jamaican clinicians for the assessment of child behavior problems and subjected these to principal components analyses. Regardless of whether the sample was split according to age or sex, the analyses revealed factors similar to the Over- and Undercontrolled syndromes most often found in other cultures. The analyses also revealed school absence factors in each age and sex group; school avoidance was correlated with crying in children (aged 6-11) but with conduct problems in adolescents (aged 12-17). The findings suggest important similarities and possible differences between the factor structures of child behavior problems in Jamaica and the United States.

Adolescent↗
PubMed2002

Comparison of male adolescent-report of attention-deficit/hyperactivity disorder (ADHD) symptoms across two cultures using latent class and principal components analysis.

BACKGROUND: The goal of this study is to gauge the consistency of Attention Deficit/Hyperactivity Disorder (ADHD) latent class models that are generated by different informants such as adolescents and parents. The consistency of adolescent-derived latent classes from two different samples was assessed and these results were then compared to the class structure generated by parent-report ADHD information. METHODS: Self-reported DSM-IV Criterion A ADHD symptoms of 497 adolescent males from a population-based twin study in the state of Missouri (USA) were subjected to principal components and latent class analysis, and findings were compared to previous results obtained from identical analyses using an adolescent sample from Porto Alegre, Brazil (N = 483). RESULTS: The bi-dimensional structure of self-reported ADHD symptoms was similar for both male adolescent groups, but explained less than 40% of the symptom variance in either sample. Two factors, one with loadings on inattention symptoms only and the other with loadings on hyperactive-impulsive symptoms only, were identified in the Missouri sample. Specific ADHD latent classes did not replicate well across the Missouri and Brazilian samples, and both groups were characterized by the presence of several combined symptom classes but few inattentive or hyperactive-impulsive classes. CONCLUSIONS: While adolescent-report information across two different cultures can at least in part reproduce the two-factor structure of ADHD, results from latent class analysis suggest that adolescent reporting on their own symptoms is markedly different from the type of information parents provide about ADHD symptoms in their offspring. The current findings indicate that if male adolescents endorse any ADHD symptoms there is a tendency for them to report combined type problems.

Adolescent↗
PubMed2005

Scoring of visual field measured through Humphrey perimetry: principal component varimax rotation followed by validated cluster analysis.

PURPOSE: To extract unidimensional, well-separated latent scores that are anatomically and clinically valid from 52 standardized variables collected by Humphrey visual field (VF) perimetry (Carl Zeiss Meditec, Dublin, CA). METHODS: Visual field data of 437 patients were collected and classified by a glaucoma specialist into seven clinical groups: irregularities of VF (IVF), nasal step (NaS), arcuate scotoma (AC), paracentral scotoma (PCS), blind-spot enlargement (BSE), diffuse deficit (DD), and advanced deficit (AD). The number and content of constituent variable scores were identified by principal components analysis followed by Varimax Rotation and simple clustering, taking spatial distribution homogeneity and visual system anatomy into account. Unidimensionality was checked by a stepwise Cronbach alpha curve. Clinical predictability of the derived scores was checked by comparing clinical groups (ANOVA). RESULTS: Patients older than 60 years comprised 53.3% of the sample. The average mean deviation was -9.2 dB and pattern standard deviation was 6.5 dB. Six scores were identified: four peripheral scores (nasal superior, NS; nasal inferior, NI; temporal superior, TS; and temporal inferior, TI) and two paracentral scores (PCSs; superior, PCSS; and inferior, PCSI). Cronbach alpha was always >0.90. The six scores decreased sequentially from IVF to DD to AD. Scores of AC were lower in NS, NI, and TS; PCSS was less in PCS; BSE scores were less in TS and TI; NaS scores were less in NS and NI. CONCLUSIONS: Six well-separated, optimal scores were obtained from the Humphrey perimetry matrix. Internal reliability was good. It was possible to discriminate between clinical subgroups. Further analyses, based on longitudinal data, must be performed to confirm these findings.

Cluster Analysis↗
PubMed1999

Disease-specific changes in equine ground reaction force data documented by use of principal component analysis.

OBJECTIVE: To assess the force plate as a diagnostic aid in equine locomotor abnormalities, particularly for abnormalities such as navicular disease that do not have specific diagnostic criteria. ANIMALS: 17 Thoroughbreds without observable locomotor abnormalities (group A), 6 Thoroughbreds with superficial digital flexor tendon injury (group B), and 8 Thoroughbreds with navicular disease (group C). PROCEDURE: Using a force plate, ground reaction force patterns were recorded at the trot. Peak limb vertical force and force/time curve parameters were derived from 4 identifiable points at the beginning and end of vertical and craniocaudal horizontal plots. Principal component analysis (PCA) of group-A data was undertaken on beginning and end of stride data, and the first 2 components were represented graphically. The PCA rotation matrices were applied to equivalent data for horses of groups B and C. RESULTS: Asymmetry of peak vertical force (PVF) could not be differentiated among groups A, B, and C. Values for group-B horses, however, were significantly outside mean group-A values on the PCA plot for beginning of stride phase variables. Group-B data were within the group-A range for end of stride phase variables. Values for group-C horses were significantly outside the group-A range for beginning of stride phase variables and were outside mean group-A values for end of stride phase variables. CONCLUSIONS: PCA of force/time data provides a sensitive method to evaluate the force/time curve associated with 2 specific injury/disease processes. CLINICAL RELEVANCE: Horses alter weight-bearing in biomechanically distinct ways, thus creating potential for the force plate to become an important diagnostic and prognostic tool.

Animals↗
PubMedDate not supplied

The symptoms of hyperglycaemia in people with insulin-treated diabetes: classification using principal components analysis.

BACKGROUND AND AIMS: People with insulin-treated diabetes commonly experience symptoms of hyperglycaemia, but the nature of these symptoms and their origins are poorly understood. The aims of this study were (1) to identify and classify the symptoms of hyperglycaemia experienced by people with insulin-treated diabetes and (2) to identify patient characteristics associated with intensity of, and glycaemic threshold for, glycaemic symptoms. METHODS: Common hyperglycaemic symptoms were identified from preliminary interviews. Eighteen symptoms were used in a questionnaire. Four hundred participants estimated the intensities with which they experienced these symptoms during hyperglycaemia. Principal components analysis (PCA) was used to examine correlations between symptoms. Associations between symptom intensity, glycaemic threshold, and other characteristics were examined with multiple regression. RESULTS: In total, 361 participants (90.2%) reported experiencing hyperglycaemic symptoms. PCA suggested four symptom groupings: (1) feeling tense, irritability, restlessness, poor concentration (agitation) (2) thirst, dry mouth, need to urinate, not feeling right, sweet/funny taste, weakness (osmotic) (3) dizziness, blurred vision, light-headedness, weakness (neurological) (4) headache, nausea (malaise). Mean symptom intensity was associated with younger age. The median (range) estimated blood glucose threshold for symptom onset was 15 (8-30) mmol/L; there was a weak tendency for this threshold to be elevated in people who had impaired hypoglycaemia awareness. CONCLUSIONS: People with insulin-treated diabetes commonly reported symptoms associated with hyperglycaemia. PCA separated these into four groups. Osmotic symptoms appear to be specific to hyperglycaemia; symptoms in the other groups may suggest underlying physiological mechanisms, but are relatively non-specific. Symptoms are more intense in younger people and may be reported at lower blood glucose concentrations in people with normal awareness of hypoglycaemia.

Adolescent↗
PubMed1997

Principal Component Analysis of the Absorption Spectra of the Dye Thiacyanine in the Presence of the Surfactant AOT: Precise Identification of the Dye-Surfactant Aggregates

Spectral change of a cationic dye 3,3'-diethylthiacyanine iodide (THIA) in the presence of an anionic surfactant AOT has been presented. The THIA-AOT system exhibits blue-shifted metachromasia at AOT concentrations below its critical micellar concentration (CMC) and is thought to be due to the aggregation of electrostatically bound dye-AOT complex (DS). Metachromasia is gradually reversed to the monomeric band (peak at 425 nm) by AOT above its CMC. Principal component analysis (PCA) method has been applied for spectral analysis; the results show that the metachromatic peaks at 377 and 366 nm originate, respectively, from trimer and hexamer of the dye associated with AOT. From PCA, the molar absorption coefficient spectra of the individual absorbing components and the equilibrium constants for the systems, monomer right harpoon over left harpoon trimer and hexamer right harpoon over left harpoon monomer below and above CMC of AOT, respectively, have also been obtained. The micellar aggregation number of AOT obtained from PCA is found to be 16 which is in good agreement with the literature value.

Journal Article↗
PubMed1983

Principal component analysis of Motokawa's data on wavelength dependence of retinal processes.

Electric excitability of the human eye as determined by measuring the threshold for a sensation of phosphene in response to electric stimulation of the eye was found by Koiti Motokawa to increase temporarily after a brief illumination (J. Neurophysiol., 1949, 112, 475-488). While changing the wavelength of illuminating light widely, he found that the time course of the variation in the eye's electric excitability after illumination differed characteristically according to the wavelength. His data on this point (Tohoku J. exp. Med., 1949, 51, 197-205) were subjected to the principal component analysis. Three components were found necessary and sufficient for their linear combinations to reproduce time courses of the excitability enhancement after illumination with lights of varying wavelengths; one of the three components makes a great contribution to the excitability enhancement by green lights, the other to the one by red lights and the remainder to the one by blue lights. This is in support of Motokawa's view that his data are interpretable as summation effects of the three retinal processes which are excited preferentially by red, green and blue lights, respectively.

Electric Stimulation↗
PubMed2000

Principal component analysis and blind separation of sources for optical imaging of intrinsic signals.

The analysis of data sets from optical imaging of intrinsic signals requires the separation of signals, which accurately reflect stimulated neuronal activity (mapping signal), from signals related to background activity. Here we show that blind separation of sources by extended spatial decorrelation (ESD) is a powerful method for the extraction of the mapping signal from the total recorded signal. ESD is based on the assumptions (i) that each signal component varies smoothly across space and (ii) that every component has zero cross-correlation functions with the other components. In contrast to the standard analysis of optical imaging data, the proposed method (i) is applicable to nonorthogonal stimulus-conditions, (ii) can remove the global signal, blood-vessel patterns, and movement artifacts, (iii) works without ad hoc assumptions about the data structure in the frequency domain, and (iv) provides a confidence measure for the signals (Z score). We first demonstrate on orientation maps from cat and ferret visual cortex, that principal component analysis, which acts as a preprocessing step to ESD, can already remove global signals from image stacks, as long as data stacks for at least two-not necessarily orthogonal-stimulus conditions are available. We then show that the full ESD analysis can further reduce global signal components and-finally-concentrate the mapping signal within a single component both for differential image stacks and for image stacks recorded during presentation of a single stimulus.

Animals↗
PubMedDate not supplied

Assessment of depression in Kuwait by principal component analysis.

One hundred depressed inpatients were examined by the WHO schedule for Standardized Assessment of Depressive Disorders (SADD). A common core of symptoms is shared with patients in other studies from Western, Middle-Eastern and international studies. However, pathoplastic cultural influences are manifest in a number of symptoms, notable among which are metaphorical descriptions of symptom intensity by the overwhelmed patient, infrequency of feelings of hopelessness and suicidal attempts, masking of guilt feelings by a front of somatization and a linkage of body weight and sexual functions to health in general. Evidence is provided for a continuum-type unimodal distribution of the principal components studied.

Adult↗
PubMed2004

Analysis of gene expression data using functional principal components.

The large amount of data involved in DNA microarrays implies the development of efficient computer algorithms to analyze the gene expressions, and thus to study the transcriptome. Numerous techniques already exist and we propose a new method based on the key idea that gene profiles may be considered as continuous curves. The analysis of the set of curves stemming from the DNA microarray may be then performed using a functional analysis which can exhibit the main modes of variations in this set, gather genes with similar variations and extract characteristic parameters of gene profiles. We aim here at introducing this method, called the Functional Principal Component Analysis. A prospective study has been performed on two available datasets, concerning on the one hand the sporulation data of the Saccharomyces cerevisiae, and on the other hand data of tumor cell lines. Results are very promising: the method is able to extract characteristic parameters from the datasets, to extract significant modes of variations in the set of gene profiles, and to link these variations to biological processes already studied in literature.

Algorithms↗
PubMed2000

Open field locomotion and neurotransmission in mice evaluated by principal component factor analysis-effects of housing condition, individual activity disposition and psychotropic drugs.

Effects of housing condition and individual disposition on dopaminergically and GABAergically influenced open field locomotion and neurochemistry were studied in mice. Mice characterized as high active (HAM) and low active (LAM) by a running-wheel test were housed in groups or isolated for 1 day, 1 week, 3, 6, 12 or 18 weeks before an open field test was performed with saline, apomorphine (0.75 mg/kg) or diazepam (1.00 mg/kg) administration. Immediately afterwards animals were decapitated and brain sections were frozen for subsequent HPLC-analysis of dopaminergic and serotonergic transmitter metabolism. Principal component factor analysis (PCA) of locomotion variables provided three factors explaining 78.5% of total variance. Variables related to the amount of locomotion loaded highly on Factor 1 (F1-Activity), variables related to place utilization loaded highly on Factor 2 (F2-Exploration) and variables related to immobility and place preference loaded highly on Factor 3 (F3-Irritation). Apomorphine decreased F1-Activity with smaller effects in HAM and without changes in F2-Exploration and F3-Irritation independent on housing conditions. Diazepam exerted a decrease in F2-Exploration with a small increase in FI-Activity and no effects in F3-Irritation. Diazepam induced changes depended on housing conditions and were especially pronounced in isolated HAM. PCA of considerable locomotion and neurochemical data revealed interrelationships between striatal dopamine metabolism and F1-Activity, between cortical dopamine and serotonin metabolism and F2-Exploration as well as between cerebellar, hippocampal and striatal serotonin metabolism and F3-Irritation. The authors concluded that the application of PCA is a useful method to provide functionally relevant characteristics of behaviors and functionally relevant descriptions of interrrelationships between behavior and appropriate central nervous mechanisms. Furthermore the received behavioral characteristics (F1, F2, F3) of open field locomotion were sensitive to reveal housing and drug effects.

Animals↗