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PubMed1999

Relation between activation sequence fluctuation and arrhythmogenicity in sodium-channel blockades.

To examine the correlation between activation sequence fluctuation and arrhythmogenicity, we investigated temporal changes in the activation sequence by measuring activation times [negative first derivative of voltage over time (-dV/dt) in QRS] from the entire heart in 18 dogs. The heart was paced by constant atrial stimulation. The character of the activation sequence fluctuation was established by a principal component analysis, in which the first principal component was defined as a stable component of the sequence and the second or third component as a fluctuated component. Steady state contained 2.2 +/- 0.6% (percent total principal component, mean +/- SD) of fluctuated components, which appeared in a beat-by-beat manner (activation sequence alternans). Activation sequence alternans was observed only during flecainide administration and not during lidocaine or disopyramide administration. Fluctuated components at a high dose of flecainide significantly increased (3.3 +/- 0.8%). Ventricular fibrillation ensued in all dogs (n = 6) exposed to flecainide after an increase in activation sequence alternans. In conclusion, flecainide evoked local activation sequence alternans. This phenomenon correlated with the occurrence of ventricular fibrillation.

Animals↗
PubMed2004

On-line multisensor monitoring of yogurt and filmjölk fermentations on production scale.

Near-infrared (NIR) spectrometry and electronic nose (EN) data were used for on-line monitoring of yogurt and filmjölk (a Swedish yogurt-like sour milk) fermentations under industrial conditions. The NIR and EN signals were selected by evaluation of principal component analysis loading vectors and further analyzed by studying the variability of the selected principal components. First principal components for the NIR and the EN signals were used for on-line generation of a process trajectory plot visualizing the actual state of fermentation. The NIR signals were also used to set up empirical partial least-squares (PLS) models for prediction of the cultures' pH and titratable acidity (expressed as Thorner degrees, degrees T). By using five or six PLS factors the models yielded acceptable predictions that could be further improved by increasing the number of reliable and precise calibration data. The presented results demonstrate that the fusion of the NIR and EN signals has a potential for rapid on-line monitoring and assessment of process quality of yogurt fermentation.

Cultured Milk Products↗
PubMed2006

Source apportionment of PM2.5 in urban area of Hong Kong.

A monitoring program for PM(2.5) had been performed at two urban monitoring stations in Hong Kong from November 2000 to February 2001 and June 2001 to August 2001. PM(2.5) samples were collected once every 6 days at PolyU and KT stations with the sampling duration of 24-h. A sum of 25 chemical species in PM(2.5) were determined and selected for receptor models. Enrichment factors relative to earth crust abundances were evaluated and it was noted that most crustal elements including Al, Ti, Mg, Ca and K have small enrichment factors. Correlation and multivariate analysis technique, such as principal components analysis (PCA)/absolute principal components analysis (APCA) and cluster analysis (CA) are used for source apportionment to identify the possible sources of PM(2.5) and to determine their contribution. Six factors at each site were isolated by using PCA/APCA and cluster analysis. Similar sources (crustal matter, automobile emission, diesel emission, secondary aerosols, tire wear, and non-ferrous smelter) are identified by the PCA/APCA and cluster analysis.

Aerosols↗
PubMed2006

Metabolic profiling as a tool for revealing Saccharomyces interactions during wine fermentation.

The multi-yeast strain composition of wine fermentations has been well established. However, the effect of multiple strains of Saccharomyces spp. on wine flavour is unknown. Here, we demonstrate that multiple strains of Saccharomyces grown together in grape juice can affect the profile of aroma compounds that accumulate during fermentation. A metabolic footprint of each yeast in monoculture, mixed cultures or blended wines was derived by gas chromatography - mass spectrometry measurement of volatiles accumulated during fermentation. The resultant ion spectrograms were transformed and compared by principal-component analysis. The principal-component analysis showed that the profiles of compounds present in wines made by mixed-culture fermentation were different from those where yeasts were grown in monoculture fermentation, and these differences could not be produced by blending wines. Blending of monoculture wines to mimic the population composition of mixed-culture wines showed that yeast metabolic interactions could account for these differences. Additionally, the yeast strain contribution of volatiles to a mixed fermentation cannot be predicted by the population of that yeast. This study provides a novel way to measure the population status of wine fermentations by metabolic footprinting.

Culture Media↗
PubMed1987

[Type A behavior pattern in health education].

A cross-sectional study was conducted to clarify the relationship between type A behavior pattern and life styles on 669 male and 60 female workers belonging to a financing company. A self-administered questionnaire was used to collect information on type A behavior pattern (including 11 questions), medical parameters and recent well-being. Principal component analysis was made to select the three major components concerning type A behavior pattern. The first component score represented overall irritability, the second score relaxation, and the third score etiology of irritability. After these component scores were adjusted to age, the following findings were observed. Smoking habits and heavy alcohol intake showed a significant correlation with a high score in the first principal component. General feeling during the past month and fatigability were related to the first and second principal component scores, respectively. Discouragement, bad arousal, little worth of living and apathy were negatively related to the second principal component score. Total cholesterol showed a positive correlation with the second principal component score (r = 0.140, p less than 0.01) in males and obesity index had a positive correlation with the second component score (r = 0.259, p less than 0.01) in females. Other medical parameters including high density lipoprotein, systolic and diastolic blood pressure did not demonstrate any significant correlation with principal component scores. It is important that recognition of type A behavior pattern may be applied to health education programs.

Adult↗
PubMed1990

[Quality of life in gastrointestinal cancer chemotherapy--from the standpoint of cancer chemotherapy].

Changes with time in quality of life (QOL) in patients who had undergone chemotherapy for various types of inoperable gastrointestinal diseases were investigated. The items studied included appetite, general feeling, sleep, fatigue, pain, familial understanding and cooperation, association with friends and colleagues, anxiety concerning the disease, expectations concerning treatment and daily life activities. These 10 items were recorded by the patients for 2-4 weeks in five grades by a combination of the analog scale and category scale methods, with the exception of association with friends and colleagues, which showed few entries, the following relations with antitumor effects were seen at the following average QOL values in the total scores for the nine items: In PR cases (n = 7), 15.6 before treatment, 19.7 during treatment and 14.8 after treatment; in NC cases (n = 11), 19.4 before treatment, 20 during treatment and 19.1 after treatment; and in PD cases (n = 4), 17.0 before treatment, 22.8 during treatment, and 22.8 after treatment. The above 10 items were surveyed simultaneously with a face scale (Arthritis and Rheumatism, Vol. 29, No,7, 906-909, 1986). Five faces considered appropriate for a five-stage evaluation were used, and the Spearman coefficient of correlation was calculated with a combination of all of the above 10 items. The face scale showed correlation in the sequence of general feeling sleep greater than activities of daily life greater than anxiety concerning the disease greater than fatigue. As a result of a nonmetric type component analysis, the data could be reduced to four dimensions with appetite, fatigue, activities of daily life, general feeling and face as the first principal component; expectations concerning treatment, understanding and cooperation of family and association with friends as the second principal component; anxiety concerning the disease and sleep as the third principal component; and pain as the fourth principal component (cumulative contribution rate: 82.38). The first principal component was investigated using a logistic regression model. As a result, the face scale could be explained by the general feeling and the daily life activities. The weight was general feeling 3 and daily life activities 1. Therefore, it appears possible to utilize sufficiently the face scale in QOL surveys of cancer patients.

Aged↗
PubMedDate not supplied

[The individual typological characteristics of the habitus of young children and the principles of somatotyping].

The nature of individual differences in early childhood was investigated by the principal component analysis of 22 absolute anthropological measures. The first principal component accounted for 45% of variability; it may be referred to as a general body-size factor, the same as in the studies of senior children and adults. The second principal component accounted for 14% of differences in habitus of children. Sex differences were inconsiderable. The concordance of the topology based on the values of two first principal components and on the V. G. Shtefko and A. D. Ostrovskiĭ classifying system was lower than 50%.

Anthropometry↗
PubMed2004

Chemometric correction of drift effects in optical spectra.

All quantitative data evaluation techniques applied to spectroscopy are based on the assumption that the baseline is stable in time. If this prerequisite is violated, major concentration errors can result since drifts are evaluated along with true spectroscopic features. For handling baseline drifts two improved principal component regression (PCR) methods are presented and compared to conventional Savitzky-Golay preprocessing followed by conventional PCR. The proposed drift-correction methods take advantage of baseline drifts being rather broad compared to the absorption features. The only assumption made is that drift effects can be modeled sufficiently by polynomials of user-selectable order. One correction method modifies principal components such that drifts of polynomial shape are orthogonal to the calibration model and thus cannot influence the concentration result. The second method extends the calibration model by synthetic so-called pseudo-principal components. While the principal components model the true spectral features, the pseudo-principal components describe drifts simultaneously and independently. Hence, drifts are explicitly included into the calibration and cannot cause erroneous concentration results. It is demonstrated that both correction methods are equivalently as powerful as the conventional PCR in the absence of drifts and superior if drifts are present. The overall performance--in the absence and presence of baseline drifts--of the novel methods makes them more versatile and reliable than the conventional Savitzky-Golay data preprocessing. In almost all investigated cases, the average concentration errors were significantly smaller than those obtained by Savitzky-Golay preprocessing. Furthermore, polyPCR and pPCR do not need laborious optimizations as Savitzky-Golay does for preventing suppression of relevant signal components. polyPCR demands less computation expense than Savitzky-Golay, and pPCR extracts the drift spectrum as additional qualitative information not provided by Savitzky-Golay.

Algorithms↗
PubMed2002

Fluorescence spectral imaging for characterization of tissue based on multivariate statistical analysis.

A novel spectral imaging method for the classification of light-induced autofluorescence spectra based on principal component analysis (PCA), a multivariate statistical analysis technique commonly used for studying the statistical characteristics of spectral data, is proposed and investigated. A set of optical spectral filters related to the diagnostically relevant principal components is proposed to process autofluorescence signals optically and generate principal component score images of the examined tissue simultaneously. A diagnostic image is then formed on the basis of an algorithm that relates the principal component scores to tissue pathology. With autofluorescence spectral data collected from nasopharyngeal tissue in vivo, a set of principal component filters was designed to process the autofluorescence signal, and the PCA-based diagnostic algorithms were developed to classify the spectral signal. Simulation results demonstrate that the proposed spectral imaging system can differentiate carcinoma lesions from normal tissue with a sensitivity of 95% and specificity of 93%. The optimal design of principal filters and the optimal selection of PCA-based algorithms were investigated to improve the diagnostic accuracy. The robustness of the spectral imaging method against noise in the autofluorescence signal was studied as well.

Algorithms↗
PubMed2005

Biogeneric tooth: a new mathematical representation for tooth morphology in lower first molars.

A mathematical representation of tooth morphology may help to improve and automate restorative computer-aided design processes, virtual dental education, and parametric morphology. However, to date, no quantitative formulation has been identified for the description of dental features. The aim of this study was to establish and to validate a mathematical process for describing the morphology of first lower molars. Stone replicas of 170 caries-free first lower molars from young patients were measured three-dimensionally with a resolution of about 100,000 points. First, the average tooth was computed, which captures the common features of the molar's surface quantitatively. For this, the crucial step was to establish a dense point-to-point correspondence between all teeth. The algorithm did not involve any prior knowledge about teeth. In a second step, principal component analysis was carried out. Repeated for 3 different reference teeth, the procedure yielded average teeth that were nearly independent of the reference (less than +/- 40 microm). Additionally, the results indicate that only a few principal components determine a high percentage of the three-dimensional shape variability of first lower molars (e.g. the first five principal components describe 52% of the total variance, the first 10 principal components 72% and the first 20 principal components 83%). With the novel approach presented in this paper, surfaces of teeth can be described efficiently in terms of only a few parameters. This mathematical representation is called the 'biogeneric tooth'.

Algorithms↗
PubMed2004

Time series analysis of collective motions in proteins.

The dynamics of alpha-amylase inhibitor tendamistat around its native state is investigated using time series analysis of the principal components of the C(alpha) atomic displacements obtained from molecular dynamics trajectories. Collective motion along a principal component is modeled as a homogeneous nonstationary process, which is the result of the damped oscillations in local minima superimposed on a random walk. The motion in local minima is described by a stationary autoregressive moving average model, consisting of the frequency, damping factor, moving average parameters and random shock terms. Frequencies for the first 50 principal components are found to be in the 3-25 cm(-1) range, which are well correlated with the principal component indices and also with atomistic normal mode analysis results. Damping factors, though their correlation is less pronounced, decrease as principal component indices increase, indicating that low frequency motions are less affected by friction. The existence of a positive moving average parameter indicates that the stochastic force term is likely to disturb the mode in opposite directions for two successive sampling times, showing the modes tendency to stay close to minimum. All these four parameters affect the mean square fluctuations of a principal mode within a single minimum. The inter-minima transitions are described by a random walk model, which is driven by a random shock term considerably smaller than that for the intra-minimum motion. The principal modes are classified into three subspaces based on their dynamics: essential, semiconstrained, and constrained, at least in partial consistency with previous studies. The Gaussian-type distributions of the intermediate modes, called "semiconstrained" modes, are explained by asserting that this random walk behavior is not completely free but between energy barriers.

Binding Sites↗
PubMed2006

Multidimensional structures of comprehensive accessibility of community support for people with mental disorders in Japan: a nationwide investigation.

The purpose of this study was to define the concept of comprehensive accessibility of community support for people with mental disorders and to clarify the multidimensional structures of comprehensive accessibility. We developed a self-administered questionnaire consisting of 47 items. A complete list of the municipalities in Japan was prepared, and the questionnaire was mailed to 3310 municipalities. Principal component analyses were applied to valid data in order to analyse the index and multidimensional structures of comprehensive accessibility. As a result, 14 principal components of community support for people with mental disorders were extracted. These principal components were interpreted as the scales for the evaluation of comprehensive accessibility. The two first principal component scores were interpreted as the index indicating the level of comprehensive accessibility. The other 12 principal components were interpreted as the scales constituting the multidimensional space of comprehensive accessibility.

Attitude of Health Personnel↗
PubMed1999

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

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

Aged↗
PubMed2004

The application of independent component analysis to the multi-channel surface electromyographic signals for separation of motor unit action potential trains: part I-measuring techniques.

The purpose of this study is to examine whether or not the application of independent component analysis (ICA) is useful for separation of motor unit action potential trains (MUAPTs) from the multi-channel surface EMG (sEMG) signals. In this study, the eight-channel sEMG signals were recorded from tibialis anterior muscles during isometric dorsi-flexions at 5%, 10%, 15% and 20% maximal voluntary contraction. Recording MUAP waveforms with little time delay mounted between the channels were obtained by vertical sEMG channel arrangements to muscle fibers. The independent components estimated by FastICA were compared with the sEMG signals and the principal components calculated by principal component analysis (PCA). From our results, it was shown that FastICA could separate groups of similar MUAP waveforms of the sEMG signals separated into each independent component while PCA could not sufficiently separate the groups into the principal components. A greater reduction of interferences between different MUAP waveforms was demonstrated by the use of FastICA. Therefore, it is suggested that FastICA could provide much better discrimination of the properties of MUAPTs for sEMG signal decomposition, i.e. waveforms, discharge intervals, etc., than not only PCA but also the original sEMG signals.

Action Potentials↗
PubMed1977

Congenital defects of the upper lateral incisors: multivariate analysis of measurements of the other teeth, the superior arch, head and face.

The survey of a French male population allowed us to ascertain 75 propositi with one or two missing ULI, 59 propositi with one or two reduced ULI and 99 controls on whom measurements (mesiodistal and buccolingual diameters) of all of teeth of the superior arch are available. Principal Component Analysis gave a first estimated principal component highly correlated with each of the dental measurements of arch measurements. This size factor was eliminated by observing the plane of the second and third principal components. Strikingly different clusters of MD diameters or BL diameters were observed for the controls, the propositi missing one or two fo the ULI and the propositi with reduced ULI. For the controls, the arch length is correlated with the MD molar diameters and the MD incisor diameter, the arch width being isolated from the other measurements. For the propositi with missing ULI, among the dental measurements the MD and BL diameters cluster, the arch length is isolated as are the arch widths. For the propositi with reduced ULI, the rich length is closer to the dental measurements while the widths, especially the first one, are isolated. The best discriminant measurements are the diameters of the first premolars and the canine, the first arch width and the arch length. Among controls, the arch is narrowed and shorter for the propositi with absence and wider for the propositi with reduction. Teeth measurements are always smaller in propositi.

Adolescent↗
PubMed2004

Resolving neurotransmitters detected by fast-scan cyclic voltammetry.

Carbon-fiber microelectrodes are frequently used as chemical sensors in biological preparations. In this work, we evaluated the ability of cyclic voltammograms recorded at fast-scan rates to resolve neurochemicals when analyzed by principal component regression. A calibration set of 30 cyclic voltammograms was constructed from 9 different substances at a variety of concentrations. The set was reduced by principal component analysis, and it was found that 99.5% of the variance in the data could be captured with five principal components. This set was used to evaluate cyclic voltammograms obtained with one or two compounds present in solution. In most cases, satisfactory predictions of the identity and concentration of analytes were obtained. Chemical dynamics were also resolved from a set of fast-scan cyclic voltammograms obtained with the electrode implanted in a region of a brain slice that contains dopaminergic terminals. Following stimulation, principal component regression of the data resolved the changes in dopamine and pH that were evoked. In a second test of the method, vesicular release was measured from adrenal medullary cells and the data were evaluated with a calibration set composed of epinephrine and norepinephrine. Cells that secreted one or the other were identified. Overall, the results show that principal component regression with appropriate calibration data allows resolution of substances that give overlapping cyclic voltammograms.

Animals↗
PubMedDate not supplied

Genetic variance in age-related changes in running performance and growth during adolescence: a longitudinal twin study.

The purpose of this study was to assess an effect of genotype on the patterns of age-related changes in running performance and physical growth during adolescence. The total sample was 14 pairs of male and 25 pairs of female monozygotic (MZ) twins and 19 pairs of male and 15 pairs of female dizygotic (DZ) twins. Performance on the 50-m dash and endurance run (1,500 m for boys and 1,000 m for girls, respectively) and stature and body mass were measured at yearly intervals from 12 to 17 years of age. A principal component analysis was applied to the longitudinal data, and within-pair resemblance in the scores on the first, the second, and the third principal components was compared between MZ and DZ twins. The analysis was conducted with both sexes pooled because of the limited number of twin pairs. The first two principal components explained at least 87% of the total variance, while the third principal component (PC3) explained a smaller portion of the total variance (more than 5%) in the dash and the endurance run. However, the total variance was explained almost entirely (more than 96%) by the first two components in height and mass. The first principal component (PC1), which explained 67-84% of the total variance, was a good indicator of average performance/body size of individuals during the period of observation. The second (PC2) and the third components (PC3) could be considered as indicators of the "shape" of developmental/growth curves, which were not related to inter-individual differences in the average performance/body size. Intraclass correlations (ri) of the scores on PC1 were consistently higher for MZ than for DZ twins, and estimated genetic variance was significant in endurance run, stature and body mass. The situation was the same for the scores on PC2 and/or PC3. However, such a between-genotype difference in ri and a significant genetic variance were not observed in the dash. It was concluded that MZ twins are more similar in the patterns of age-related changes in the performance of endurance run and physical growth during adolescence than DZ twins, suggesting a genetic contribution, while there was no evidence of a genetic contribution in the dash.

Adolescent↗
PubMed2006

Application of two-dimensional nuclear magnetic resonance spectroscopy to quality control of ginseng commercial products.

Ginseng has been used as a powder or a crude extract of the plant roots. The quality control of commercial ginseng preparations is difficult due to the diverse compounds present. Most previous quality control methods using TLC or HPLC-UV (or -MS) cannot be expected to cover a wide range of compounds in the commercial ginseng preparations. In this study, the metabolic fingerprinting of ginseng preparations was performed by (1)H-NMR spectroscopy. Although (1)H-NMR spectroscopy could provide information about the total profile of the compounds present, low resolution and overlapping signals make it difficult for further identification of each compound. For overcoming the problem two-dimensional J-resolved NMR spectra and multivariate data analysis techniques was applied for the analysis. Principal component analysis (PCA) of projected J-resolved NMR spectra shows a clear discrimination among those samples by principal component 1 and principal component 3. The loading plot of PC values obtained from all NMR signals indicates that alanine, arginine, choline, fumaric acid, inositol, sucrose as well as ginsenosides are important metabolites to differentiate the preparations from each other. This method allows an efficient discrimination of a ginseng preparation in less than 15 minutes without any pre-purification steps.

Humans↗