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PubMed1995

Trandolapril decreases prevalence of ventricular ectopic activity in middle-aged SHR.

BACKGROUND: Although severe arrhythmias are still a major problem in patients with left ventricular hypertrophy (LVH), the relationship between ventricular remodeling and its regression or prevention, and the prevalence of ventricular premature beats (VPB) or more sustained arrhythmias are still poorly explored in hypertensive heart disease. METHODS AND RESULTS: Holter monitoring was used to quantify supraventricular premature beats and VPB and heart rate (HR) in middle-aged spontaneously hypertensive rats (SHR) and Wistar rats treated for 3 months with trandolapril (ACE inhibitor, 0.3 mg/kg per day). Hypertrophy and fibrosis were morphometrically determined. Statistical analysis was performed with the use of simple regression and multivariate data analysis (cluster and correspondence analysis). SHR have higher cardiac mass and fibrosis, more VPB, and a decreased HR. Cluster analysis demonstrated that trandolapril was only effective in SHR. Trandolapril significantly reduced cardiac hypertrophy, fibrosis, and VPB incidence and increased the HR. Simple regression analysis showed that VPB incidence correlated to both hypertrophy and fibrosis. Correspondence analysis evidenced a strong correlation between hypertrophy, fibrosis, and VPB, but only for severe hypertrophy, and the correlation disappeared for moderate hypertrophy. CONCLUSIONS: After trandolapril treatment, the regression of VPB incidence not only is linked to hypertrophy and fibrosis, but additional causal factors also are involved including the myocardial phenotype and new calcium metabolism. Our model of Holter monitoring in conscious middle-aged SHR and multivariate data analysis might be useful in correlating myocardial structural modifications and ectopic activity.

Aging↗

PubMed2005

Multispecies and monoculture rhizoremediation of polycyclic aromatic hydrocarbons (PAHs) from the soil.

In this study, we investigated the potential of multispecies rhizoremediation and monoculture rhizoremediation in decontaminating polycyclic aromatic hydrocarbon (PAH) contaminated soil Plant-mediated PAH dissipation was evaluated using monoplanted soil microcosms and soil microcosms vegetated with several different grass species (Brachiaria serrata and Eleusine corocana). The dissipation of naphthalene and fluorene was higher in the "multispecies" vegetated soil compared to the monoplanted and nonplanted control soil. The concentration of naphthalene was undetectable in the multispecies vegetated treatment compared to 96% removal efficiencies in the monoplanted treatments and 63% in the nonplanted control after 10 wk of incubation. Similar removal efficiencies were obtained for fluorene. However, there was no significant difference in the dissipation of pyrene in both the mono- and multispecies vegetated treatments. There also was no significant difference between the dissipation of PAHs in the monoplanted treatments with different grass species. Principle component analysis (PCA) and cluster analysis were used to evaluate functional diversity of the different treatments during phytoremediation of PAHs. Both PCA and cluster analysis revealed differences in the metabolic fingerprints of the PAH contaminated and noncontaminated soils. However, the differences in metabolic diversity between the multispecies vegetated and monoplanted treatments were not clearly revealed. The results suggest that multispecies rhizoremediation using tolerant plant species rather than monoculture rhizoremediation have the potential to enhance pollutant removal in moderately contaminated soils.

Biodegradation, Environmental↗

PubMed1993

Cluster arousal analysis in chronic pain-disturbed sleep.

A new cluster arousal analysis system was developed to quantify microdisturbances in the sleep architecture. The system was evaluated in 10 healthy volunteers and the sleep of 23 outpatients with chronic low back pain was investigated before and after a special rehabilitative training. The comparison of sleep parameters before and after the treatment showed a significant reduction of the cluster disturbed sleep (CDS), whereas sleep efficiency and the number of stage shifts remained unchanged. The reduction of the CDS correlated with a reduction of depression scale. This cluster arousal analysis appears to be a sensitive tool for evaluating alterations in the sleep microstructure.

Journal Article↗

PubMed1997

Validity of using non-pilot subjects to represent pilots in a sustained acceleration environment.

BACKGROUND: A preliminary study determined the similarities between the personality of military pilots (transport and fighter) and centrifuge subjects using the Edwards Personal Preference Schedule (EPPS). Past, similar personality studies have shown differences between military fighter vs. transport pilots, and general population vs. male and female general aviators. To use subjects in lieu of pilots in the centrifuge, they must represent the pilot characteristics of interest, for both ethical and scientific reasons. With the increase in measuring performance metrics (e.g., reaction time, tracking tasks, missile evasion) during centrifuge testing, any factor effecting performance must be explored. It is unknown whether personality effects performance. METHODS: Cluster analysis of 36 pilot and subject personality tests consisted of the Partitioning Around Medoids (PAM) program by Leonard Kaufman and Peter Rousseeuw (10) and Ward's method/K-MEANS clustering (CSS:STATISTICA). RESULTS: The clusters generated by the 36 pilots and subjects did not match the Retzlaff and Gibertini (21) clusters. Two clusters were preferred over three, and while the values of the personality variables Dominance, Exhibition, and Aggression (DOM, EXH, AGG) were similar, the pilot membership did not coincide. Subjects had basically the same cluster characteristics as pilots and did not alter the pilot cluster composition characteristics when clustered together. Females did not appear to differ from the males in the cluster analysis. Clustering did not differentiate between fighter and transport pilots using the chosen variables. CONCLUSION: These preliminary results support the hypothesis that there are no major differences in personality between fighter pilots, transport pilots, or centrifuge subjects using the EPPS.

Acceleration↗

PubMed2004

Metabolite profiling using (1)H NMR spectroscopy for quality assessment of green tea, Camellia sinensis (L.).

A set of 191 green teas from different countries was collected and analyzed by (1)H NMR. It was proposed to establish if the teas could be discriminated according to the country of origin or with respect to quality. Both principal component analysis (PCA) and cluster analysis were applied to the data. Some separation of Chinese and non-Chinese teas was observed. The present results did not allow allocation of samples to individual countries, but cluster analysis suggested that it might be possible with an augmented sample set. The PCA did show a separation between the Longjing type (highest quality Chinese tea) and most other Chinese teas and indicated some metabolites that could be responsible for the difference. Longjing teas showed higher levels of theanine, gallic acid, caffeine, epigallocatechin gallate, and epicatechin gallate and lower levels of epigallocatechin when compared with other teas. These compounds have been mentioned previously in connection with quality, but it was also shown that higher levels of theogallin (5-galloyl quinic acid), theobromine, 2-O-(beta-l-arabinopyranosyl)-myo-inositol and some minor sugar-containing compounds were found in Longjing teas while higher levels of fatty acids and sucrose were found in the other teas. These new markers could prove to be useful for the authentication of bulk tea.

Camellia sinensis↗

PubMed2005

Cluster analysis-based physiological classification and morphological properties of inhibitory neurons in layers 2-3 of monkey dorsolateral prefrontal cortex.

In primates, little is known about intrinsic electrophysiological properties of neocortical neurons and their morphological correlates. To classify inhibitory cells (interneurons) in layers 2-3 of monkey dorsolateral prefrontal cortex we used whole cell voltage recordings and intracellular labeling in slice preparation with subsequent morphological reconstructions. Regular spiking pyramidal cells have been also included in the sample. Neurons were successfully segregated into three physiological clusters: regular-, intermediate-, and fast-spiking cells using cluster analysis as a multivariate exploratory technique. When morphological types of neurons were mapped on the physiological clusters, the cluster of regular spiking cells contained all pyramidal cells, whereas the intermediate- and fast-spiking clusters consisted exclusively of interneurons. The cluster of fast-spiking cells contained all of the chandelier cells and the majority of local, medium, and wide arbor (basket) interneurons. The cluster of intermediate spiking cells predominantly consisted of cells with the morphology of neurogliaform or vertically oriented (double-bouquet) interneurons. Thus a quantitative approach enabled us to demonstrate that intrinsic electrophysiological properties of neurons in the monkey prefrontal cortex define distinct cell types, which also display distinct morphologies.

Action Potentials↗

PubMed2001

Bayesian methods of analysis for cluster randomized trials with binary outcome data.

We explore the potential of Bayesian hierarchical modelling for the analysis of cluster randomized trials with binary outcome data, and apply the methods to a trial randomized by general practice. An approximate relationship is derived between the intracluster correlation coefficient (ICC) and the between-cluster variance used in a hierarchical logistic regression model. By constructing an informative prior for the ICC on the basis of available information, we are thus able implicitly to specify an informative prior for the between-cluster variance. The approach also provides us with a credible interval for the ICC for binary outcome data. Several approaches to constructing informative priors from empirical ICC values are described. We investigate the sensitivity of results to the prior specified and find that the estimate of intervention effect changes very little in this data set, while its interval estimate is more sensitive. The Bayesian approach allows us to assume distributions other than normality for the random effects used to model the clustering. This enables us to gain insight into the robustness of our parameter estimates to the classical normality assumption. In a model with a more complex variance structure, Bayesian methods can provide credible intervals for a difference between two variance components, in order for example to investigate whether the effect of intervention varies across clusters. We compare our results with those obtained from classical estimation, discuss the relative merits of the Bayesian framework, and conclude that the flexibility of the Bayesian approach offers some substantial advantages, although selection of prior distributions is not straightforward.

Bayes Theorem↗

PubMed2003

On the relation between seasonal synoptic circulation types and spatial air quality characteristics in Athens, Greece.

The impact of weather on air pollution was examined and evaluated for the city of Athens, Greece. We used an objectively defined synoptic classification scheme consisting of six summer and eight winter circulation types. This scheme was established using a combination of both factor and cluster analysis during 1954-1999. Surface and isobaric levels of 850 hPa data were used. Factor analysis combined with cluster analysis was used to derive circulation types based on surface meteorological data for the period 1954-1999 in Athens and on surface pressure grid data. The city was divided into three sectors according to the financial and social activities of the residents. To examine the spatial characteristics of pollutant concentrations over Athens for each synoptic type, the synoptic circulation types were then correlated with both gaseous and particulate pollutant concentrations measured in each sector between 1983 and 1999. Finally, extreme and severe episodic events were studied in terms of their meteorological and synoptic characteristics.

Air Movements↗

PubMed2001

Principal component analysis for clustering gene expression data.

MOTIVATION: There is a great need to develop analytical methodology to analyze and to exploit the information contained in gene expression data. Because of the large number of genes and the complexity of biological networks, clustering is a useful exploratory technique for analysis of gene expression data. Other classical techniques, such as principal component analysis (PCA), have also been applied to analyze gene expression data. Using different data analysis techniques and different clustering algorithms to analyze the same data set can lead to very different conclusions. Our goal is to study the effectiveness of principal components (PCs) in capturing cluster structure. Specifically, using both real and synthetic gene expression data sets, we compared the quality of clusters obtained from the original data to the quality of clusters obtained after projecting onto subsets of the principal component axes. RESULTS: Our empirical study showed that clustering with the PCs instead of the original variables does not necessarily improve, and often degrades, cluster quality. In particular, the first few PCs (which contain most of the variation in the data) do not necessarily capture most of the cluster structure. We also showed that clustering with PCs has different impact on different algorithms and different similarity metrics. Overall, we would not recommend PCA before clustering except in special circumstances.

Algorithms↗

PubMedDate not supplied

Analysis of tear-protein patterns as a diagnostic tool for the detection of dry eyes.

PURPOSE: To analyze the electrophoretic patterns of tear proteins from diabetic (DIDRY) and non-diabetic (DRY) patients with dry-eye disease in comparison with the patterns in healthy subjects (CTRL). The patterns were classified using multivariate statistical methods. METHODS: A total of 119 eyes were examined in this study (50 DIDRY, 39 DRY, 30 CTRL). The patients were primarily grouped according to the results of the basic secretory test (BST) and subjective symptoms (burning, foreign body sensations, tearing, "dryness" of the eyes). Patients with values < or = 10/5' plus subjective symptoms were classified as dry-eye patients. Tear proteins were separated by sodium-dodecyl-sulfate poly-acrylamide gel electrophoresis (SDS-PAGE). Digital image analysis was done using the ScanPacK (Biometra, Gottingen, Germany). A data set was created from each electrophoretic pattern. The data were analyzed by multivariate analysis of discriminance, k-means cluster analysis and with a factor analysis before k-means cluster analysis as a data reduction tool. RESULTS: The protein patterns of the three groups were significantly different (Wilks' lambda: 0.1425; P < 0.01): P < 0.05 (CTRL-DRY), P < 0.00005 (CTRL-DIDRY), and P < 0.0005 (DIDRY-DRY). There were more peaks/electrophoretic lane in the DRY and DIDRY groups (P < 0.05) than CTRL. Classification of all samples as DRY and CTRL gave the following results: known patterns 97% correct; unknown patterns 71.4% correct. Classification in DIDRY, DRY or CTRL was 92% correct for known patterns and 43% for unknown patterns. Using k-means cluster analysis, 72% of patients previously classified as "dry-eye" according to the BST value were classified as "dry-eye" based on their electrophoretic data too. CONCLUSIONS: Analysis of protein patterns and statistical evaluation are suitable for the detection of dry eyes. Tear-protein pattern analysis can provide more information on the pathogenesis of the disease. Thus, this new method might be more reliable than the BST value for both diagnostic and therapeutic purposes.

Diabetes Complications↗

PubMed2005

Prevalence and socioeconomic impact of upper gastrointestinal disorders in the United States: results of the US Upper Gastrointestinal Study.

BACKGROUND & AIMS: This study examined the prevalence of upper gastrointestinal (GI) symptoms and symptom groupings and determined impact on disability days in a nationally representative US sample. METHODS: A telephone survey of 21,128 adults was conducted including questions about the presence of upper GI symptoms during the past 3 months. Respondents were categorized as symptomatic (ie, reported GI symptoms once per month) or asymptomatic. The survey included questions about missed work, leisure activity, or household activity days. Symptom groupings were identified by using factor analysis, and cluster analysis was used to assign respondents into distinct groups on the basis of these symptom groupings. RESULTS: The prevalence of an average of 1 or more upper GI symptoms during the past 3 months was 44.9%. The most common symptoms experienced during the past 3 months were early satiety, heartburn, and postprandial fullness. Factor analysis identified 4 symptom groupings: (1) heartburn/regurgitation; (2) nausea/vomiting; (3) bloating/abdominal pain; and (4) early satiety/loss of appetite. Five respondent clusters were identified; the largest clusters were primarily early satiety/fullness (44%) and gastroesophageal reflux disease-like symptoms (28%). Two small clusters reflected nausea and vomiting (7%) and a heterogeneous symptom profile (4%). Symptomatic respondents reported significantly more missed work, leisure, and household activity days than asymptomatic respondents (all P < .0001). CONCLUSIONS: Factor analysis separated GI symptoms into groupings reflecting gastroesophageal reflux disease and dyspepsia: early satiety, postprandial fullness, and loss of appetite; bloating and abdominal pain/discomfort; and nausea and vomiting. These upper GI symptoms were associated with significant loss of work and activity days.

Adolescent↗

PubMed2006

Multivariate statistical evaluation of trace elements in groundwater in a coastal area in Shenzhen, China.

Multivariate statistical techniques are efficient ways to display complex relationships among many objects. An attempt was made to study the data of trace elements in groundwater using multivariate statistical techniques such as principal component analysis (PCA), Q-mode factor analysis and cluster analysis. The original matrix consisted of 17 trace elements estimated from 55 groundwater samples colleted in 27 wells located in a coastal area in Shenzhen, China. PCA results show that trace elements of V, Cr, As, Mo, W, and U with greatest positive loadings typically occur as soluble oxyanions in oxidizing waters, while Mn and Co with greatest negative loadings are generally more soluble within oxygen depleted groundwater. Cluster analyses demonstrate that most groundwater samples collected from the same well in the study area during summer and winter still fall into the same group. This study also demonstrates the usefulness of multivariate statistical analysis in hydrochemical studies.

Anions↗

PubMed2000

Comprehensive gene expression profile of the adult human renal cortex: analysis by cDNA array hybridization.

BACKGROUND: Profiling of gene expression in healthy and diseased renal tissue is important for elucidating the pathogenesis of renal diseases. Comprehensive information about the genes expressed in renal tissue is unavailable. The recently developed cDNA array hybridization methodology allows simultaneous monitoring of thousands of genes expressed renal tissue. METHODS: Complex [alpha-33P]-labeled cDNA probes were prepared from histopathologically uninvolved remnants of nine renal tissues obtained by nephrectomy. Each probe was hybridized to a high-density array of 18,326 paired target genes. The radioactive hybridization signals by phosphorimager screens were quantitated by special software. Bioinformatics from public genomic databases were used to assign a chromosomal location of each expressed transcript and gene function. Cluster analysis was used to arrange genes according to the similarity in pattern of gene expression. RESULTS: A total of 7563 different gene transcripts was detected in the nine tissue samples. Approximately 870 of these genes were full-length mRNA human transcripts (HT), and the remaining 6693 were expressed sequence tags (ESTs). The full-length transcripts were classified by function of the gene product and were listed with information of their chromosomal positions. To allow a comparison between gene expression in clinical and experimental studies, the mouse genes with known similar function to the human counterpart were included in the bioinformatics analysis. Cluster analysis of 502 full-length genes that are expressed in four or more renal tissues revealed more than 110 genes that are highly expressed in all the renal specimens. CONCLUSIONS: The presented data constitute a comprehensive preliminary transcriptional map of the adult human renal cortex. The information may serve as a resource for speeding up the discovery of genes underlying human renal disease. The integrated listing of the full-length expressed human and mouse genes is available through e-mail (Abdalla_Rifai@Brown.edu).

Adult↗

PubMed2003

An evaluation of methods for the stratified analysis of clustered binary data in community intervention trials.

A simulation study is conducted in a community intervention setting. Several methods of stratified analysis of clustered binary data are compared in terms of empirical significance and empirical power levels. They are the Mantel-Haenszel test statistic (chi(2) (MH)), the adjusted Mantel-Haenszel test statistic of Donald-Donner (chi(2) (DD)), Rao-Scott (chi(2) (RSN) and chi(2) (RSP)), and Zhang-Boos (chi(2) (ZBN) and chi(2) (ZBP)), Wald (chi(2) (W)), robust Wald (chi(2) (RW)), score (chi(2) (S)), robust score (chi(2) (RS)), and the test statistic based on generalized linear mixed model (GLMM) (chi(2) (GLMM)). When rho not equal 0, chi(2) (MH) has inflated type I error, and it should not be used when observations are correlated. The results also warn of the use of chi(2) (RSN) and chi(2) (RW) due to their poor performance in terms of empirical significance level. chi(2) (ZBP) and chi(2) (GLMM) have better empirical significance levels as compared to other statistics; however, chi(2) (ZBP) tends to have lower empirical powers than other statistics when the number of clusters (N) is less than 24. chi(2) (RSP) provides the highest empirical powers when rho > or = 0.1 and N < or = 12. When rho < or = 0.01, we recommend the use of chi(2) (RS) and chi(2) (GLMM) since they have better overall performance in terms of empirical significance levels and empirical power levels.

Adolescent↗

PubMed2004

Immediate gene expression changes after the first course of neoadjuvant chemotherapy in patients with primary breast cancer disease.

PURPOSE: Our goal was to identify genes undergoing expressional changes shortly after the beginning of neoadjuvant chemotherapy for primary breast cancer. EXPERIMENTAL DESIGN: The biopsies were taken from patients with primary breast cancer prior to any treatment and 24 hours after the beginning of the neoadjuvant chemotherapy. Expression analyses from matched pair samples representing 25 patients were carried out with Clontech filter arrays. A subcohort of those 25 paired samples were additionally analyzed with the Affymetrix GeneChip platform. All of the transcripts from both platforms were queried for expressional changes. RESULTS: Performing hierarchical cluster analysis, we clustered pre- and posttreatment samples from individual patients more closely to each other than the samples taken from different patients. This reflects the rather low number of transcripts responding directly to the drugs used. Although transcriptional drug response occurring during therapy differed between individual patients, two genes (p21(WAF1/CIP1) and MIC-1) were up-regulated in posttreatment samples. This could be validated by semiquantitative and real-time reverse transcription-PCR. Partial least- discriminant analysis based on approximately 25 genes independently identified by either Clontech or Affymetrix platforms could clearly discriminate pre- and posttreatment samples. However, correlation of certain gene expression levels as well as of differential patterns and clusters as determined by a different platform was not always satisfying. CONCLUSIONS: This study has demonstrated the potential of monitoring posttreatment changes in gene expression as a measure of the pharmacodynamics of drugs. As a clinical laboratory model, it can be useful to identify patients with sensitive and reactive tumors and to help for optimized choice for sequential therapy and obviously improve relapse- free and overall survival.

Adult↗

PubMed1995

Psychological long-term coping with experience of disease and treatment in childhood cancer survivors.

Childhood cancer, although cured, may have long-term psychological consequences for the adult survivor. The outcome of patients' coping with the illness and treatment experience was assessed in relation to a theoretical model describing optimal long-term coping with a potential psychic trauma of this nature. Thirty young adult childhood cancer survivors were studied. The average age at diagnosis was 8 years, and at evaluation 22 years. The average time since diagnosis was 13 years. The evaluations of coping were carried out independently by two psychologists, who rated material from semistructured in-depth interviews. By statistical cluster analysis three clusters were produced that could be interpreted as exhibiting "good," "intermediate" and "poor" coping, containing 40, 33, and 27%, respectively, of the total group. Overall cluster differences were statistically significant. Profile analysis revealed statistical stability and internal homogeneity in the good coping cluster and the poor coping cluster.

Adaptation, Psychological↗

PubMed1997

Primate sense of taste: behavioral and single chorda tympani and glossopharyngeal nerve fiber recordings in the rhesus monkey, Macaca mulatta.

The responses of 51 chorda tympani proper (CT) and 33 glossopharyngeal (NG) neural taste units from the rhesus monkey (Macaca mulatta) were recorded during stimulation of either the anterior (CT) or posterior (NG) part of the tongue with 26 stimuli that taste salty, umami, sour, bitter, and sweet to humans. In the CT, hierarchical cluster analysis separated four major clusters. The N and S clusters were most populous, followed by the H cluster and a small Q cluster. NaCl, monosodium glutamate (MSG), and MSG with guanosine 5'-monophosphate were the best stimuli in the N cluster. Amiloride suppressed responses to NaCl. KCl did not stimulate fibers from this cluster. S cluster fibers were characterized by strong responses to all sweeteners. The H cluster responded best to acids but also to some of the sweeteners such as xylitol, fructose, and sucrose. Q fibers responded well to quinine hydrochloride (QHCl) and caffeine, but not to denatonium benzoate. In the NG, hierarchical cluster analysis separated three major clusters. Q fibers formed the largest cluster. QHCl, caffeine, and sucrose octa-acetate but not denatonium benzoate elicited very strong responses in these fibers. S fibers formed a second cluster. Although most of the sweeteners stimulated the S fibers, their responses were not so pronounced as in CT S fibers. The small M cluster was formed by fibers that responded best to MSG. They also responded to NaCl and acids. Two bottle preference tests showed a positive relationship between a sweetener's ability to stimulate the taste fibers and the animals' consumption. Thus the most-liked sweeteners stimulated the S cluster fibers of CT best, whereas less-liked sweeteners such as D-phenylalanine elicited a response in Q fibers and sodium cyclamate stimulated N fibers. The results show that both CT and NG taste fibers of M. mulatta group according to the human concepts of taste qualities.

Animals↗

PubMed1999

A cluster-analytical approach toward physical activity and other health related behaviors.

PURPOSE: The purpose of our study was to investigate, on the basis of cluster analysis, whether healthy behavior clusters in a healthy or unhealthy way, whether physical activity can discriminate among those clusters, and whether the groups identified could be characterized by demographic variables. METHODS: The relationships between physical activity and other health related behaviors were studied in three age groups, ages 16-25, 35-45, and 50-65. Almost 2400 subjects from a medium-sized Belgian town were interviewed at home to assess their level of physical activity in the past year and to obtain information on other healthy behaviors. RESULTS: The two-cluster solution was found to be most reliable in all three age groups. Smoking discriminated most among the clusters. Cluster analysis divided each age group into a healthy and a more unhealthy subgroup, in which the healthy subgroup is larger than the unhealthy one. Sex differences were found in all three age groups, with more men in the unhealthy cluster. Socio-economic differences are especially strong in the two youngest samples. CONCLUSIONS: The hypothesis that leisure time physical activity had discriminating power between healthy and unhealthy subgroups was not confirmed. Physical activity seems to be a unique factor in contrast to other health related behaviors. In the future, specific intervention directed at the promotion of physical activity in the population is necessary.

Adolescent↗