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PubMed1987

Helminth parasites of the coyote (Canis latrans) in Tennessee.

From 1980 to 1984, 267 coyotes (Canis latrans) from Tennessee were examined for helminth parasites. Hearts were examined for the presence of Dirofilaria immitis, diaphragms for Trichinella spiralis, and digestive tracts for other helminths. Six species were found including 5 nematodes (D. immitis, Physaloptera rara, Trichuris vulpis, Ancylostoma caninum, and Toxascaris leonina) and 1 cestode (Taenia pisiformis). Univariate and multivariate statistical techniques were used to assess parasite prevalence and intensity. For prevalence data, a matrix of correlation among characters was computed, and the first 3 principal components were extracted from the original distance matrix. These accounted for 93.7% of the variation in the character set. Three-dimensional projections of localities showed spatial variability on each component. Significant relationships were found between principal component I and longitude, component II and latitude and mean January temperature, and component III and mean July precipitation and mean January actual evapotranspiration. For intensity data, no spatial variability was determined.

Animals↗
PubMed1998

[Relationship between dietary fiber intake and food intake patterns of the general population, evaluated by a regional nutrition survey].

This study was performed to estimate the dietary fiber intake calculated using individual food intake data and the dietary fiber tables, and to ascertain the relationship between food intake patterns and dietary fiber intake of the general population. The 805 subjects over 15 years old were obtained from the Tottori Prefecture Nutrition Survey. The results are summarized as follows: 1. The average dietary fiber intake per capita per day was 18.19 g; 18.67 g in men, and 17.81 g in women. Dietary fiber intake per energy was different among sexes and ages: women had more dietary fiber than men and the aged had more than the young. Those who had high fiber intake per energy took green vegetables, fruits, milk, soybean products, seaweed and potatoes more frequently, and did not take oil so frequently. 2. Total dietary fiber intake from 20 food-group sources was analyzed by Multiple Regression Analysis. For both men and women fruits, vegetables and soybean products mostly influenced dietary fiber intake. 3. Based on the intake of the 20 food-groups obtained from 356 men and 449 women, the correlation matrix among these foods was calculated. The correlation matrix was also submitted to a Principal Component Analysis. The result of the Principal Component Analysis told that food intake patterns were different among the levels of dietary fiber intake. Food intake patterns of men and women who had high fiber intake per energy had an eating pattern characterized by relatively more non-processed vegetable food, bread and milk. 4. The level of blood pressure was significantly related to dietary fiber intake per energy in men over 60 years old. In the hypertensive men over 60 years old, 23.3% were in the low fiber intake group, 37.2% in the middle group, and 39.5% in the high group. But in the normal blood pressure men over 60 years old, 50.0% were in the low fiber intake group, 8.3% in the middle group, and 41.7% in the high group.

Adolescent↗
PubMed2003

Quality control and peak finding for proteomics data collected from nipple aspirate fluid by surface-enhanced laser desorption and ionization.

BACKGROUND: Recently, researchers have been using mass spectroscopy to study cancer. For use of proteomics spectra in a clinical setting, stringent quality-control procedures will be needed. METHODS: We pooled samples of nipple aspirate fluid from healthy breasts and breasts with cancer to prepare a control sample. Aliquots of the control sample were used on two spots on each of three IMAC ProteinChip arrays (Ciphergen Biosystems, Inc.) on 4 successive days to generate 24 SELDI spectra. In 36 subsequent experiments, the control sample was applied to two spots of each ProteinChip array, and the resulting spectra were analyzed to determine how closely they agreed with the original 24 spectra. RESULTS: We describe novel algorithms that (a) locate peaks in unprocessed proteomics spectra and (b) iteratively combine peak detection with baseline correction. These algorithms detected approximately 200 peaks per spectrum, 68 of which are detected in all 24 original spectra. The peaks were highly correlated across samples. Moreover, we could explain 80% of the variance, using only six principal components. Using a criterion that rejects a chip if the Mahalanobis distance from both control spectra to the center of the six-dimensional principal component space exceeds the 95% confidence limit threshold, we rejected 5 of the 36 chips. CONCLUSIONS: Mahalanobis distance in principal component space provides a method for assessing the reproducibility of proteomics spectra that is robust, effective, easily computed, and statistically sound.

Algorithms↗
PubMed2005

Chemical fingerprinting of petroleum biomarkers using time warping and PCA.

A new method for chemical fingerprinting of petroleum biomakers is described. The method consists of GC-MS analysis, preprocessing of GC-MS chromatograms, and principal component analysis (PCA) of selected regions. The preprocessing consists of baseline removal by derivatization, normalization, and alignment using correlation optimized warping. The method was applied to chromatograms of m/z 217 (tricyclic and tetracyclic steranes) of oil spill samples and source oils. Oil spill samples collected from the coastal environment in the weeks after the Baltic Carrier oil spill were clustered in principal components 1 to 4 with oil samples from the tank of the Baltic Carrier (source oil). The discriminative power of PCA was enhanced by deselecting the most uncertain variables or scaling them according to their uncertainty, using a weighted least squares criterion. The four principal components were interpreted as follows: boiling point range (PC1), clay content (PC2), carbon number distribution of sterols in the source rock (PC3), and thermal maturity of the oil (PC4). In summary, the method allows for analyses of chromatograms using a fast and objective procedure and with more comprehensive data usage compared to other fingerprinting methods.

Accidents↗
PubMed2001

[Estimating cardiovascular age of civil flying personnel by means of heart rate and blood pressure variability analysis].

Objective. To estimate the cardiovascular age of civil flying personnel by means of heart rate and blood pressure variability analysis and to evaluate its significance in aviation medicine. Method. First, heart rate variability (HRV), blood pressure variability (BPV) and spontaneous baroreflex sensitivity (BRS) were analyzed among 89 healthy civil flying personnel by using conventional AR spectral analysis and sequence method respectively. Then, principal component analysis was conducted over original and derived variables of HRV and BPV spectral and BRS data. Finally, by the use of multiple regression in which the chronological age acted as the dependent variable and the components significantly related to age were used as the regressors, the equation for estimating the cardiovascular age was established. Result. Only seven principal components can exactly reflect the same information of autonomic regulatory function which was embodied in the 17 variables of HRV and BPV spectral and BRS parameters. Among the seven principal components, the PC2orig, PC4orig and PC2deri were negatively correlated with chronological age (P<0.05), whereas the PC3orig was positively correlated with the chronological age (P<0.01). The cardiovascular age derived from the equation was significantly correlated with the chronological age of the civil flying personnel (r= 0.73, P<0.01). Conclusion. The cardiovascular age estimated by means of a multi-variate analysis of HRV, BPV and BRS can be treated as a comprehensive indicator reflecting the age dependency of autonomic regulatory function of cardiovascular system in healthy civil flying personnel, and its interpretation and significance in application are surely worthy of further and fully dedicated efforts.

Adult↗
PubMed2001

Facial growth: separating shape from size.

Optical surface scanning technologies produce dense three-dimensional (3D) data sets, which allow detailed analysis of surface morphology. This paper describes a method of analysing change in facial shape independently of change in size. The 3D data from three male subjects from the age of 6-21 years were recorded using an optical surface scanner. A series of 22 conventional landmarks were located with the aid of horizontal and vertical profiles across the face, and were analysed using geometric morphometrics. The 3D landmark co-ordinates were scaled and aligned using Generalized Procrustes Analysis (GPA) and analysed by Principal Component Analysis (PCA) to determine the shape change over the growth period for each individual. The results show that the centroid size reaches a steady value at different times for each of the subjects. When analysing shape versus age, highly significant correlations were found with principal component 1 (PC-1), but not with other principal components. PC-1 encompassed 40 per cent of the total variance for each subject. The movement of facial landmarks with time that is represented by PC-1 in each of the individuals is described. The use of these techniques has enabled the individual characteristics of facial growth to be identified and also has revealed the subtle changes in shape that continue after change in size has ceased.

Adolescent↗
PubMed1993

[A quantitative pharmaco-EEG study on psychotropic properties of cerebral metabolic enhancers: comparison between young and elderly healthy volunteers].

In order to investigate psychotropic properties of cerebral metabolic enhancers (CMEs), the author carried out two identical quantitative pharmaco-EEG studies in different age groups of healthy volunteers; the young group (group-Y) consisted of six males between the ages of 21-26 years and elderly group (group-E) consisted of six males between the ages of 60-66 years. The drugs tested were five CMEs, dihydroergotoxine mesylate (DHE), propentofylline (PPF), nicergoline (NCG), lisuride maleate (LIS) and ibudilast (IDL). Each volunteer received either of the five test drugs or inert placebo in six one-day weekly sessions' according to single-blind, randomized crossover design. In each session, a single oral dose, equivalent to the clinically recommended daily dose, of either drug or placebo was administered and EEGs were recorded before and 1.3 and 6 hours after the drug administration. Firstly, the background EEGs before the drug administration were compared between the two groups. Group-E showed less slow activities and more alpha and fast activities than group -Y. This difference in background EEG profiles between two groups are considered to be due to physiological aging process. Secondly, drug effects on EEGs in two groups were compared. There were discrepancies in drug-induced EEG changes between the groups. In group-Y, any of the five tested CMEs did not induce EEG changes that were significantly different from placebo, whereas, in group-E, drug-induced EEG changes were more apparent. In group-E, DHE and PPF induced similar EEG changes, which were characterized by a decrease of alpha activity associated with marked decreases of slow and fast activities, the EEG profile similar to thymoleptics with sedative effects. LIS and IDL induced a decrease of alpha activity and an increase of fast activities, the profile close to thymoleptics with mood-elevating (stimulant) effects. NCG induced an increase of slow activities, the profile close to central depressants. These results in this study coincided with the experimental and subjective classification of the clinical effects of CMEs. Further analysis of EEG profiles based on principal component analysis indicated that there were two major components in background EEGs. There were discrepancies in the response to CMEs between two groups. In group-Y, CME-induced changes were seen mainly in the second principal component, while in group-E, the changes were seen mainly in the first principal component. These results suggested CMEs provoked thymoleptic effects by affecting the essential component of the EEG basic rhythm.(ABSTRACT TRUNCATED AT 400 WORDS)

Adult↗
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↗
PubMed2005

Influence of yeast strain and aging time on free amino acid changes in sparkling ciders.

An analytical method for the determination of free amino acids in ciders is reported. It is based on high-performance liquid chromatography with an automatic precolumn derivatization with o-phthaldehyde and 3-mercaptopropionic acid and diode array detection. The method was applied to monitor the amino acids during second fermentation of sparkling ciders. This paper reports the influence of yeast strains and aging time on the amino acid composition of sparkling ciders. The application of principal component analysis enables the ciders to be differentiated on the basis of the two factors considered (yeast strain and aging time). The first principal component, which accounts for 58% of the total variance, achieved the separation according to aging time with serine, glycine, alanine, valine, ornithine, leucine, and lysine as the most important variables. The second principal component, accounting for 28% of the explained variance, is closely related to aspartic acid and asparagine and separates the samples according to the yeast strain.

Amino Acids↗
PubMed2000

The psychophysics of informal covariation assessment: perceiving relatedness against a background of dispersion.

The goal of 2 studies was to develop a psychophysical model of informal covariation assessment. The results of Experiment 1 suggest that mean covariation estimates are a function of the ratio of the lengths of the major and minor principal-components axes of correlated bivariate data. In Experiment 2, multidimensional scaling showed that observers perceived (a) the lengths of the major and minor principal-components axes and (b) the slope and dispersion of correlated data. The focal stimulus for mean covariation estimates was the ratio of the major and minor principal-components axes. Moreover, dispersion constituted a background context that lowered estimates somewhat. These results suggested a model of covariation assessment in which mean estimates were mapped onto a product of power transformations of the axis ratio and dispersion of correlated data. This model accounted for 96% of the variability in mean covariation estimates.

Cues↗
PubMed2005

[A proposal of new indices for hospital management].

BACKGROUND: Diagnosis related groups (DRGs) are the most reliable patient classification system in hospital management. When this information is unavailable, other reliable classification system must be used. AIM: To obtain useful indices for hospital management, based on descriptive multivariate techniques. MATERIAL AND METHODS: Data on admissions to a University Hospital during 2003 were analyzed. Number of discharges, lethality rate, re-admission rate, number of outpatient consultations, length of hospital stay and surgical complexity index were analyzed, using information obtained by the Operations Management Department. The Principal Components Analysis (PCA) technique was applied and the R correlation matrix was used. RESULTS: A total of 24,345 discharges were analyzed. The first two principal components were selected, accounting cumulatively for 76% of data variability (47% for the first and 29% for the second). CONCLUSIONS: The first component may be assimilated to a new index representing the difficulty of the attended cases, which we have termed Case Complexity. The second principal component would explain the number of attended persons, which we have termed Case Load. These two indices allow us to classify hospital services.

Chile↗
PubMedDate not supplied

Admixture estimates for Churuguara, a Venezuelan town in the State of Falcón.

BACKGROUND: The present Venezuelan population is the admixture product of Amerindians, Europeans and Africans, a process which was not homogeneous over the country. Blood groups, STRs and VNTRs, specifically D1S80, have been used successfully in admixture studies, but few have been made in Venezuela. AIM: This study aims to estimate the admixture components of Churuguara, Venezuela, and to evaluate the genetic relationship of this population with other Venezuelan as well as worldwide populations through principal component analysis and the study of dendrograms based on genetic distances. SUBJECTS AND METHODS: Gene frequencies of blood groups ABO and Rh (only anti D), of STRs VWA, F13A01, FES/FPS and VNTR D1S80 were studied in a sample of 60 individuals born in Churuguara, a Venezuelan town of admixed ancestry in the State of Falc6n. Admixture was estimated with Chakraborty's gene identity method, and Nei's standard genetic distance was used to build two dendrograms with the neighbour-joining approach, one based on the three STRs and the other based only on D1S80. Principal component analyses with the gene frequencies of these markers were also performed. RESULTS: The frequency of allele ABO*O was 0.788, of ABO*A was 0.187 and of RH*D was 0.74. D1S80 showed 16 different alleles with a heterozygosity of 0.880, whilst the three STRs showed only eight different alleles and heterozygosities between 0.733 and 0.797. The estimates of admixture obtained in this analysis were 52.5% for the Spanish parental group, 27.6% for the African and 19.9% for the Amerindian. Comparison of Churuguara with other Latin American populations shows that its African component is not as high as that observed in Colombian Choco, but it is higher than that observed in other samples from Colombia, Chile and Maracaibo (Venezuela). CONCLUSIONS: Results of the admixture analysis are consistent with those obtained with two dendrograms and principal component analyses, suggesting that the strong initial Amerindian component of 500 years ago has been diluted by the continuous flow of European genes, mainly Spanish, to this region.

ABO Blood-Group System↗
PubMed2001

[Structural analysis for psychosocial factors including health locus of control (HLC) and sense of coherence (SOC) associated with lifestyle-related diseases].

The purpose of this study was to clarify psychosocial characteristics associated with preventive health behavior for lifestyle-related diseases. The author performed objective health examinations and gave questionnaires to 289 men (39.7 +/- 11.8 years, mean +/- SD) and 80 women (32.8 +/- 10.4 years) engaged in office work. Psychosocial factors included lifestyle and perceived stress, as well as the health locus of control (HLC) and sense of coherence (SOC) as newly developed indicators for health behavior. The principal component analysis for men did not extract lifestyle from the psychosocial structures. Multiple regression analysis showed that internal HLC (IHLC), chance HLC (CHLC), professional HLC (PHLC) and stress significantly contributed to SOC. Principal component analysis using psychosocial factors in women showed two psychosocial structures, i.e. the second principal (high SOC, high lifestyle, and low stress) and the 4th principal components (high supernatural HLC, and high PHLC). Both components were negatively correlated with systolic blood pressure. SOC was recognized to be negatively associated with age, stress, and total cholesterol, and positively with IHLC, FHLC, lifestyle, and gamma-GTP using multiple regression analysis for women. These results indicated a distinguishable sex difference regarding the involvement of psychosocial factors including HLC and SOC in objective health. SOC seems likely to be involved not in objective health, but closely with stress, suggesting a direct influence on mental health. Lifestyle should be divided into more detailed categories such as smoking and salt intake. Structural analysis of women suggests that SOC is involved directly or indirectly through lifestyle in objective health, different from men. To further clarify causal relationships between psychosocial factors and risk factors for lifestyle-related diseases, a longitudinal study is necessary based on these results.

Adult↗
PubMed2004

Spectral deconvolution of chemical mixtures by covariance NMR.

A method is presented for the deconvolution of the NMR spectrum of a chemical mixture without requiring physical separation of its components. The method, which is termed "Demix", is based on a principal component analysis of a series of one-dimensional (1D) spectra that are statistically modulated during preparation and TOCSY mixing periods. The largest principal components correspond to the 1D NMR spectra of the scalar J-coupled spin networks of the individual components of the mixture. The method is demonstrated for aqueous mixtures of the amino acids Glu, Leu, Lys, and Val.

Amino Acids↗
PubMed2003

River system in Japan from a landscape ecological aspect.

The objective of this study was to elucidate characteristics associated with rivers by classification of major rivers in Japan into several types based on riparian conditions. As the results of principal component analysis (PCA) with use of parameters reflecting form and artificial alterations of respective rivers, four major components such as "comprehensive riparian size", "intactness of water front", "continuity of streams" and "simplicity of landform in river basin" were extracted. Subsequently, cluster analysis was performed based on principal component scores, leading to successful classification of major rivers into 6 types. These findings disclosed that (1) the extracted principal components provide effective viewpoint for classification of rivers; (2) distribution of respective classes indicates area properties; and (3) the employed quantitative procedures were found effective for classification of major rivers.

Data Collection↗
PubMedDate not supplied

Pharmacokinetically based mapping device for chemical space navigation.

ChemGPS, the chemical global positioning system, is a tool that combines rules (equivalent to dimensions) and objects (chemical structures) to provide a consistent chemical space map (Oprea, T. I.; Gottfries, J. J. Comb. Chem. 2001, 3, 157-166.). Rules included, initially, general properties such as size, lipophilicity, and hydrogen bond capacity, while objects include "satellites", intentionally placed outside the druglike space, as well as "core" objects, mostly orally available drugs. ChemGPS molecules (objects) were used in conjunction with the VolSurf (http://www.moldiscovery.com) descriptors (rules), which are relevant for ADME (absorption, distribution, metabolism, and excretion) properties. The combination of ChemGPS and VolSurf, GPSVS, was investigated with respect to the biopharmaceutics classification system, which is recommended by the Food and Drug Administration (FDA) (http://www.fda.gov/cder/OPS/BCS_guidance.htm), in particular with respect to permeability and solubility. The first GPSVS principal component correlates, with no further training, to passive transcellular permeability, as illustrated for the Caco-2, ghost erythrocyte, and blood-brain barrier datasets, respectively. The second GPSVS principal component correlates, without prior training, to solubility, as shown for the octanol-water partition and intrinsic solubility datasets, respectively. Although derived from principal component analysis, the two property axes rotate and form an angle of approximately 43 degrees, thus being no longer orthogonal. GPSVS can be used to map the chemical space with respect to permeability and solubility, as recommended by FDA's biopharmaceutics classification system.

Journal Article↗
PubMed2001

Multivariate evaluation of doxorubicin surface-enhanced Raman spectra.

Multivariate evaluation of surface-enhanced Raman spectra of doxorubicin in plasma was performed. In a principal component analysis (PCA) all spectral features were modelled into three principal components. The major variation of the data was shown to be the variation of doxorubicin Raman signal together with the doxorubicin fluorescence, whereas the variation due to plasma was of minor importance. It was also shown that the surface-enhanced Raman scattering (SERS) measurements were independent on such factors as measurement occasion and silver colloids. The presented results show that with some improvements, quantification of doxorubicin directly in plasma could be possible.

Animals↗
PubMed2001

Discrimination between orange juice and pulp wash by (1)H Nuclear Magnetic Resonance spectroscopy: identification of marker compounds.

The potential of NMR spectroscopy and multivariate analysis methods to detect the adulteration of orange juice with pulp wash is demonstrated. Principal component analysis has been applied to (1)H NMR spectra of >300 orange and pulp wash juices, and stepwise linear discriminant analysis was used to classify the samples. A model with six principal components gave a high success rate of classification (94%) for both training and validation sets. An important principal component loading showed that dimethylproline played a key role in the discrimination between the two types of juice, with higher levels in pulp wash. Dimethylproline was not previously known as a marker compound for orange juice adulteration. An ANOVA test revealed at least 21 other NMR signals that differed significantly between the authentic and pulp wash groups. The compounds they represent could be seen as potential marker compounds in addition to dimethylproline. This makes NMR with chemometrics an attractive screening tool with advantages in terms of rapidity, simplicity, and diversity of information provided.

Amino Acids↗