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PubMed2002

Influence of physico-chemical parameters of some barbituric acid derivatives on their retention on an amide embedded RP silica column.

Retention parameters of 45 different barbituric acid derivatives were determined on an amide embedded RP silica column (Discovery RP-AmideC16) using non-buffered water-acetonitrile eluent systems. Linear correlation were calculated between the logarithm of the capacity factor and the acetonitrile concentration in the eluent. To determine the retention behavior of barbituric acid derivatives, stepwise regression analysis (SRA) and principal component analysis (PCA) followed by two-dimensional nonlinear and modified nonlinear mapping was used. It can be concluded, the retention of barbituric acid derivatives are governed mainly by the steric parameters of the substituents. Principal component analysis indicated that the barbituric acid derivatives have mixed retention on this amide embedded RP silica column in water-acetonitrile eluent.

Barbiturates↗
PubMed2001

A minimum data set and empirical model for population health status assessment.

BACKGROUND: The need to assess the health status of American communities in a comprehensive and systematic manner has been widely acknowledged. This study attempts to empirically derive a minimum core data set of indicators, in order to produce a uniform parsimonious model for population health status monitoring. METHODS: Five years of secondary data (1992-1996) for 113 indicators of community health for each of Florida's 67 counties were organized into 11 conceptual groups. Principal component analysis with orthogonal rotation was conducted separately on each group of indicators for each year. The component scores were converted to standard scores to further study the relationships among the conceptual groups measuring community health. A causal model was hypothesized and tested using ordinary least-squares path analysis. RESULTS: Nineteen principal components composed of 78 indicators were identified. The model demonstrated a large difference in the ability to explain variance in adult mortality (56%) compared with variance associated with adverse birth outcomes (13%). Both demographic and socioenvironmental factors have a direct effect on adult mortality. Socioeconomic factors, on the other hand, influence adult mortality indirectly through adequacy of primary care and other available resources. CONCLUSIONS: Minimum core data sets of indicators drawn from extant databases can be used to uniformly describe and explain variation in adult mortality. This research suggests caution in regard to the creation of integrated indices that combine mortality, morbidity, and other concepts such as quality of life into a single measure of community health. Further validation research employing a national sample of counties is recommended.

Adolescent↗
PubMed1995

Artificial neural networks for multicomponent kinetic determinations.

An artificial neural network (ANN) procedure that uses the scores of a principal component model as input data was tested for calibration in the resolution of binary mixtures from kinetic measurements. The results thus obtained are compared with those provided by partial least-squares (PLS) regression and principal component regression (PCR). The ANN was first applied to simulated single wavelength kinetic curves. The effect of experimental variability was considered by assuming rate constants to fit a normal distribution curve. An amount of instrumental noise was also added to the simulated curves. Both linear and nonlinear systems were tested. Non-linearity was assumed to result from interactions between analytes and modeled by introducing a multiplicative term in the rate equation. The results provided by the three methods on linear systems were comparable; in the presence of interactions between analytes, however, the ANN method clearly outperformed the other two. The ANN method was also used to resolve mixtures of Fe(III), Co(II), and Zn(II) by displacement from their EGTA complexes with 4-(2-pyridylazo)resorcinol (PAR) using a stopped-flow injection assembly including a diode array detector. Preliminary experiments revealed the Co(II) and Zn(II) displacement reactions to be pseudo-first-order and that of Fe(III) to be a multistep process that departed from the linear behavior of the other two. Again, the results obtained with ANN were better than those provided by PCR and PLS.

Calibration↗
PubMedDate not supplied

Spectral pattern recognition using self-organizing MAPS.

A Kohonen neural network is an iterative technique used to map multivariate data. The network is able to learn and display the topology of the data. Self-organizing maps have advantages as well as drawbacks when compared to principal component plots. One advantage is that data preprocessing is usually minimal. Another is that an outlier will only affect one map unit and its neighborhood. However, outliers can have a drastic and disproportionate effect on principal component plots. Removing them does not always solve the problem for as soon as the worst outliers are deleted, other data points may appear in this role. The advantage of using self-organizing maps for spectral pattern recognition is demonstrated by way of two studies recently completed in our laboratory. In the first study, Raman spectroscopy and self-organizing maps were used to differentiate six common household plastics by type for recycling purposes. The second study involves the development of a potential method to differentiate acceptable lots from unacceptable lots of avicel using diffuse reflectance near-infrared spectroscopy and self-organizing maps.

Journal Article↗
PubMed1994

Quantitative analysis of human movement synergies: constructive pattern analysis for gait.

To record three-dimensional coordinates of the joints from normal human subjects during locomotion, we used a digital motion analysis system (ELITE). Recordings were obtained under several different conditions, which included normal walking and stepping over obstacles. Principal component analysis was used to analyze coordinate data after conversion of the data to segmental angles. This technique gave a stable summary of the redundancy in gait kinematic data in the form of reduced variables (principal components). By modeling the shapes of the phase plots of reduced variables (distortion analysis) and using a limited number of model parameters, good resolution was obtained between subtly different conditions. Hence, it was possible to accurately resolve small distributed changes in gait patterns within subjects. These methods seem particularly suited to longitudinal studies in which relevant movement features are not known a priori. Assumptions and neurophysiological applications are discussed.

Journal Article↗
PubMed1998

Brain networks affected by synchronized sleep visualized by positron emission tomography.

Nineteen lightly sleep-deprived healthy volunteers were examined with H2(15)O and positron emission tomography (PET). Scanning was performed during wakefulness and after the subjects had fallen asleep. Sleep stage was graded retrospectively from electroencephalogram (EEG) recordings, and scans were divided into two groups: wakefulness or synchronized sleep. Global flow was quantified, revealing no difference between sleep and wakefulness. A pixel-by-pixel-blocked one-way analysis of variance (ANOVA) was performed after correcting for differences in anatomy and global flow. The sum of squares of the z-score distribution showed a highly significant (P < 0.00001) omnibus difference between sleep and wakefulness. The z-score images indicated decreased flow in the thalamus and the frontal and parietal association cortices and increased flow in the cerebellum during sleep. A principal component (PC) analysis was performed on data after correction for global flow and block effects, and a multivariate analysis of variance (MANOVA) on all PC scores revealed significant (P = 0.00004) differences between sleep and wakefulness. Principal component's 2 and 5 correlated to sleep and revealed distinct networks consisting of PC 2, cerebellum and frontal and parietal association cortices, and PC 5, thalamus.

Analysis of Variance↗
PubMedDate not supplied

Neonatal status: an objective scoring method for identifying infants at risk for poor outcome.

The likelihood of sustaining neurological, sensory or cognitive deficits is considerably greater for very low birthweight (VLBW) infants who require intensive care in early postnatal life than those without major neonatal illness. Identifying which, if any, medical events are responsible for an adverse outcome is most difficult in the face of multiple concurrent complications. In this research, a principal components analysis was performed in order to arrive at a set of orthogonal variables which succinctly described clinical involvement in the nursery. With this procedure, a single hypothetical factor depicting neonatal status (NS) was computed. Principal component scores were then generated for NS and assigned to 252 VLBW (less than 1500 g) infants. These subjects were followed prospectively from birth to 4 years of age. Standardized measures of neurological, sensory and intellectual function were regularly administered. Neonatal status was shown to be significantly correlated with the various test results and predictive of long-term development. When subjects were divided into quartiles with respect to NS, a specific subgroup was identified as "at high risk" for poor outcome. Those subjects falling into the lower quartile incurred more neurological abnormalities persisting beyond the first year. They also suffered a higher incidence of intracranial hemorrhage and sensori-neural hearing loss. In addition, the lower 25%, as a group, scored well below all others on traditional tests of mental ability. These differences were sustained throughout infancy and early childhood and could not be attributed to a number of demographic variables including sex, gestational age, birthweight, Apgar scores or parental educational level.

Child Development↗
PubMed2004

Regional dissociated heterochrony in multivariate analysis.

Heterochrony, the classic framework to study ontogeny and phylogeny, in essence relies on a univariate concept of shape. Though principal component plots of multivariate shape data seem to resemble classical bivariate allometric plots, the language of heterochrony cannot be translated directly into general multivariate methodology. We simulate idealized multivariate ontogenetic trajectories and demonstrate their behavior in principal component plots in shape space and in size-shape space. The concept of "dissociation", which is conventionally regarded as a change in the relationship between shape change and size change, appears to be algebraically the same as regional dissociation - the variation of apparent heterochrony by region. Only if the trajectories of two related species lie along exactly the same path in shape space can the classic terminology of heterochrony apply so that pure dissociation of size change against shape change can be detected. We demonstrate a geometric morphometric approach to these issues using adult and subadult crania of 48 Pan paniscus and 47 P. troglodytes. On each specimen we digitized 47 landmarks and 144 semilandmarks on ridge curves and the external neurocranial surface. The relation between these two species' growth trajectories is too complex for a simple summary in terms of global heterochrony.

Aging↗
PubMed2005

Multivariate analysis of FTIR and ion chromatographic data for the quality control of tequila.

Principal component analysis (PCA) was applied to the chromatographic and spectroscopic data of authentic Mexican tequilas (n = 14) and commercially available samples purchased in Mexico and Germany (n = 24). The scores scatter plot of the first two principal components (PC) of the anions chloride, nitrate, sulfate, acetate, and oxalate accounting for 78% of the variability allowed a classification between tequilas bottled in Mexico and overseas; however, no discrimination between tequila categories was possible. Mexican products had a significantly (p = 0.0014) lower inorganic anion concentration (range = 1.5-5.1 mg/L; mean = 2.5 mg/L) than the products bottled in the importing countries (range = 3.3-62.6 mg/L; mean = 26.3 mg/L). FTIR allowed a rapid screening of density and ethanol as well as the volatile compounds methanol, ethyl acetate, propanol-1, isobutanol, and 2-/3-methyl-1-butanol using partial least-squares regression (precisions = 5.3-29.3%). Using PCA of the volatile compounds, a differentiation between tequila derived from "100% agave" (Agave tequilana Weber var. azul, Agavaceae) and tequila produced with other fermentable sugars ("mixed"tequila) was possible. The first two PCs describe 89% of the total variability of the data. Methanol and isobutanol influenced the variability in PC1, which led to discrimination. The concentrations of methanol and isobutanol were significantly higher (methanol, p = 0.004; isobutanol, p = 0.005) in the 100% agave (methanol, 297.9 +/- 49.5; isobutanol, 251.3 +/- 34.9) than in the mixed tequilas (methanol, 197.8 +/- 118.5; isobutanol, 151.4 +/- 52.8).

Agave↗
PubMed1996

Internal representation of two-dimensional shape.

The psychological space of shapes has been studied in many experiments. However, how shapes are represented in the brain has not been a major issue in psychological literature. Here, the characteristics of internal representation and how it was formed have been considered and an attempt has been made to explain the results of experiments in a unified manner. First, the data of similarity of alphabetic characters and random-dot patterns were reexamined. Multivariate analysis suggested that those patterns were represented by the combination of global features. Second, three-layer neural networks were trained to perform categorization or identity transformation of the same sets of patterns as used in psychological experiments, and activation patterns of the hidden units were analyzed. When the network learned categorization of the patterns, its internal representation was not similar to the representation suggested by psychological experiments. But a network which learned identity transformation of the patterns could acquire such an internal representation. The transformation performed by this kind of network is similar to principal-component analysis in that it projects the input image onto a lower-dimensional space. From these results it is proposed that two-dimensional shapes are represented in human brain by a process like principal-component analysis. This idea is compatible with the findings in neurophysiological studies about higher visual areas.

Animals↗
PubMed2005

The interpersonal circumplex as a model of interpersonal capabilities.

In this study, we sought to challenge the existing conceptualization of interpersonal capabilities as a distinct construct from interpersonal traits by explicitly taking into account the general factor inherent within most models of circumplexes. A sample of 206 college students completed a battery of measures including the Battery of Interpersonal Capabilities (BIC; Paulhus & Martin, 1987). Principal components analysis and the randomization test of hypothesized order relations demonstrated that contrary to previous findings, the BIC adhered to a circular ordering. Joint analysis of the BIC with the Interpersonal Adjective Scale (Wiggins, 1995) using principal components analysis and structural equation modeling demonstrated that the 2 measures represented similar constructs. Furthermore, the general factor in the BIC was not correlated with measures of general self-competence, satisfaction with life, or general pathology.

Adolescent↗
PubMed1993

[Multivariate analysis of mandibular morphology with fetal growth by means of the soft standardized radiographs].

Mandibular growth of the fetus is a great matter of importance to anatomy, anthropology and also oral and Maxillofacial surgery. The postnatal changes of the mandible that have occurred with growth have been reported by numerous investigators. However, a few researchers have investigated the prenatal growth of the mandible. The purposes of this study were discussed how to change in size and shape of the mandible during the fetal period. The materials consisted of 162 human fetuses from the body length (BL) of 95 mm, to 500 mm. They were divided into four groups: 95-199 mm (BL1, N = 40), 200-299 mm (BL2, N = 76), 300-399 mm (BL3, N = 26), 400-500 mm (BL4, N = 20). All specimens were stored in formalin, and only those free from gross deformation were selected for study. The heads were removed by decapitation at the level of the hyoid bone. The soft standardized radiographs were taken of the frontal, lateral, basal aspects. They were used for tracing and angular and linear measurements (total thirty). The data were used to evaluate the mandibular form by multivariate analysis. They were supported the univariate analysis. The findings leads to the following conclusions: 1) Cluster analysis and principal component analysis were applied to the data to make clear the correlation between 30 variables. Four clusters were constructed at the level ninety similarities in cluster analysis. They were corresponded to four factors were obtained in principal component analysis. 2) The data were subjected to a stepwise discriminant function analysis using the seventeen of original 30 variables. Nine variables, mandibular length (Go-Me), mandibular ramus height (Col-Go), Symphyseal height (Id-Me), mandibular body height (Kr'-beta), gonial angle (< Co2, Go, Me), mental angle (< Id, Pog, Go), gonial width (BGo), alveolar width (BKr'), basal angle of mandible (< RGo, Me, LGo), were selected as the best discriminators. The incidence of correctly classified cases 88.68%. 3) As a result of the first discriminant function of the discriminant analysis and one-way analysis of variance (ANOVA) and t-test, mandibular length (Go-Me), gonial width (BGo), alveolar width (BKr'), Symphyseal height (Id-Me) were longer in tall group that short group (BL4 > BL3 > BL2 > BL1). Therefore, the first discriminant function was accounted for the size factor. 4) In consequence of the second discriminant function of the discriminant analysis and regression analysis, gonial width (BGo) was grown broader than alveolar width (BKr') from BL1 to BL2.(ABSTRACT TRUNCATED AT 400 WORDS)

Anthropometry↗
PubMed1996

Anthropometric and motor characteristics of Senegalese children with different nutritional histories.

The effects of Protein Energy Malnutrition (PEM) on the motor performance of 4.5-6.5-year-old Senegalese children were studied. Body dimensions included weight, lengths, circumferences, and four skinfolds. Motor performance tests included a 3-min endurance run, 4 x 10 m shuttle-run, distance throw, standing long jump and grip strength. The sample consisted of 147 children: 52 children who were hospitalized for severe undernutrition (severe UN group) during infancy but who had been nutritionally rehabilitated; 63 children who were never severely malnourished but who were chronically exposed to mild-to-moderate undernutrition up to the time of study (chronic UN group); and 32 well nourished children (well nourished group) from well-off households. After adjusting for sex and age, the well nourished group performed better than the severe UN and chronic UN groups. Principal components analysis resulted in two factors which explained 65% of the variance in anthropometry and motor performance. One was related to body size and the second to body composition. The three nutritional groups differed significantly in principal component scores for the two factors; chronic UN and severe UN children also differed for the second factor. Body composition, especially low fat mass appeared to be an important feature for motor performance in chronically undernourished children.

Anthropometry↗
PubMedDate not supplied

[Physical anhedonia and depression: distinct concepts? Study of the construct validity of these dimensions in a group of 224 normal subjects].

The aim of the study was to precise the relationship between physical anhedonia and depression in healthy subjects. The construct validity of these two dimensions were determined using a principal components analysis. 224 normal subjects were recruited for the study. They filled out the abrigded version of the Beck Depression Inventory (BDI) and a physical pleasure scale (Fawcett Clark Pleasure Capacity Scale--FCPCS-PP). A principal components analyses following by a varimax rotation was done. The correlation matrix comprising items from both the BDI and the FCPCS-PP yielded a three-factor solution (two "pleasure" factors and one "depression factor") with no overlap of the significant factor loading for the items from each scale. The findings support the view that physical anhedonia is a construct that is distinct and separate from depression.

Adult↗
PubMed2002

Volatile components of peel and leaf oils of lemon and lime species.

Peel and leaf oils of 43 taxa of lemons and limes were obtained from fruits and leaves collected from trees submitted to the same pedoclimatic and cultural conditions. Their chemical composition was investigated by capillary GC, GC-MS, and (13)C NMR, and the results were submitted to principal component analysis to check for chemical variability. Three major chemotypes were distinguished for lemon peel oils: limonene; limonene/beta-pinene/gamma-terpinene; and limonene/linalyl acetate/linalool. Two chemotypes were identified for lemon leaf oils: limonene/beta-pinene/geranial/neral and linalool/linalyl acetate/alpha-terpineol. In lime peel oils, four chemotypes were distinguished: limonene; limonene/gamma-terpinene; limonene/beta-pinene/gamma-terpinene; and limonene/gamma-terpinene/beta-pinene/oxygenated products. Four others were identified for lime leaf oils: beta-pinene/limonene; limonene/geranial/neral; limonene/linalool/citronellal; and limonene/sabinene/citronellal/linalool. These results were interpreted using principal component analysis.

Acyclic Monoterpenes↗
PubMed1996

The evolution of optical signals in human and rodent cortex.

The time course of optical intrinsic signals was examined in order to characterize the evolution of response in human and rodent cortex. Both subtraction/ratio and principal component analyses were used to construct time-course curves. The time course began at a prestimulus baseline, responded with a finite delay, overcompensated, reduced to a maintenance level, and then disappeared. The magnitude, spatial involvement, and principal components demonstrated similar time-course curves both in human and in rodent. For acute stimuli, peak response was reached between 2 and 3 s and returned to baseline by 6 s poststimulation. The shape of the time-course curve is consistent with the need to satisfy neuronal demand and the contributions of vascular smooth muscle properties to the response behavior. The temporal delays and nonlinear phenomena observed in the time-course curves are consistent with a hydraulic model of neurovascular supply/demand behavior.

Animals↗
PubMed2000

A statistically derived index for classifying East Coast fever reactions in cattle challenged with Theileria parva under experimental conditions.

A statistically derived disease reaction index based on parasitological, clinical and haematological measurements observed in 309 5 to 8-month-old Boran cattle following laboratory challenge with Theileria parva is described. Principal component analysis was applied to 13 measures including first appearance of schizonts, first appearance of piroplasms and first occurrence of pyrexia, together with the duration and severity of these symptoms, and white blood cell count. The first principal component, which was based on approximately equal contributions of the 13 variables, provided the definition for the disease reaction index, defined on a scale of 0-10. As well as providing a more objective measure of the severity of the reaction, the continuous nature of the index score enables more powerful statistical analysis of the data compared with that which has been previously possible through clinically derived categories of non-, mild, moderate and severe reactions.

Animals↗
PubMed2004

Separation and structural analysis of lipoprotein in a lipopolysaccharide preparation from Porphyromonas gingivalis.

Lipopolysaccharide (LPS) preparations from the periodontopathic bacterium Porphyromonas gingivalis (Pg-LPS) are thought to require Toll-like receptor (TLR)2 rather than TLR4, a receptor of Escherichia coli LPS (Ec-LPS), for activation of immune cells. However, we previously reported that P. gingivalis lipid A, an immunostimulatory principal component of LPS, and its synthetic counterpart activate cells through a TLR4-dependent pathway but not via TLR2. In the present study, a lipoprotein from Pg-LPS (Pg-LP) was shown to be a principal component for TLR2-mediated cell activation. Pg-LP was separated by hydrophobic interaction chromatography followed by preparative electrophoresis and identified by internal peptide sequencing as PG1828, a putative lipoprotein encoded in the P. gingivalis genome. The N-terminal structure was characterized as a triacylated lipopeptide using mass spectrometry. Pg-LP, as well as Ec-LPS, was potent in inducing IL-8 production in human gingival fibroblasts. From our results, we propose that Pg-LP is a powerful inflammatory factor of P. gingivalis.

Amino Acid Sequence↗