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PubMed2006

Cluster analysis for the extraction of sagittal gait patterns in children with cerebral palsy.

Classification of gait disorders would facilitate standardisation of gait management and communication across professional boundaries. In the past, such classification was undertaken using a variety of approaches with often unclear methodology and validation procedures. This study describes the application of hierarchical cluster analysis on sagittal kinematic gait data derived from 56 children with cerebral palsy and 11 neurologically intact children in order to define existing clusters of gait patterns in the children's data. A structured rationale was developed to seek and validate the optimal number of homogenous gait types within the data resulting in 13 different gait clusters that were organised into 'crouch gait type', 'equinus gait type' and 'other gait type'. Applying cluster analysis in combination with visual assessment of gait data and a structured protocol, we have been able to define valid gait groupings.

Adolescent↗
PubMed1998

Cluster analysis and display of genome-wide expression patterns.

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

Cluster Analysis↗
PubMed1994

Cluster analysis of MCMI and MCMI-II on chronic PTSD victims.

A cluster analysis was used to identify groups of inpatients with confirmed post-traumatic stress disorder (PTSD) due to combat. In Study 1 the MCMI was administered to 256 subjects, in addition to the MMPI, PTSD measures, and background variables. Three clusters resulted: a Traumatic Personality (8-2), Schizoid Influence (8-2-1), and Antisocial Influence (8-6). Comparison on the MCMI symptom scales, MMPI, and PTSD scales showed that the Antisocial Influence cluster was "healthier" on all measures. The Schizoid Influence was most psychopathological. In Study 2 the MCMI-II was administered to 136 new subjects who met the same criteria as in Study 1. Four clusters resulted: Global (1-2-6A-6B-8A-8B), Subclinical (1), Aggressive (6A-6B-8A), and Detached/Self-defeating (1-2-8A-8B).

Adult↗
PubMed2005

The application of cluster analysis in the intercomparison of loop structures in RNA.

We have developed a computational approach for the comparison and classification of RNA loop structures. Hairpin or interior loops identified in atomic resolution RNA structures were intercompared by conformational matching. The root-mean-square deviation (RMSD) values between all pairs of RNA fragments of interest, even if from different molecules, are calculated. Subsequently, cluster analysis is performed on the resulting matrix of RMSD distances using the unweighted pair group method with arithmetic mean (UPGMA). The cluster analysis objectively reveals groups of folds that resemble one another. To demonstrate the utility of the approach, a comprehensive analysis of all the terminal hairpin tetraloops that have been observed in 15 RNA structures that have been determined by X-ray crystallography was undertaken. The method found major clusters corresponding to the well-known GNRA and UNCG types. In addition, two tetraloops with the unusual primary sequence UMAC (M is A or C) were successfully assigned to the GNRA cluster. Larger loop structures were also examined and the clustering results confirmed the occurrence of variations of the GNRA and UNCG tetraloops in these loops and provided a systematic means for locating them. Nineteen examples of larger loops that closely resemble either the GNRA or UNCG tetraloop were found in the large ribosomal RNAs. When the clustering approach was extended to include all structures in the SCOR database, novel relationships were detected including one between the ANYA motif and a less common folding of the GAAA tetraloop sequence.

Cluster Analysis↗
PubMed2005

[cDNA microarray and cluster analysis to identify the significance of immune genes associated with benzene poisoning].

OBJECTIVE: To delineate the immune regulatory pathway of benzene poisoning by using gene expression profile analysis. METHODS: Peripheral white blood cell gene expression profile of 7 benzene poisoning patients, including one aplastic anemia, was determined by microarray. Seven chips from normal workers were served as controls. Cluster analysis of gene expression profile was performed. Differentially expressed immune genes associated with benzene poisoning were determined. RESULTS: Among the 2 779 target genes, 38 genes differentially expressed were identified, including 10 up-regulated genes such as CD59, TRA@, MCP etc, and 14 down-regulated genes such as HLA-DMB, HLA-DQA1, HLA-DPB1, ITGB2, PFC etc. Cluster analysis showed that the expression profiles of 38 genes were associated with benzene poisoning. CONCLUSION: Differentially expressed immune genes may play an important role in the pathogenesis of benzene poisoning.

Benzene↗
PubMed1995

Impact of sampling technique on appraisal of pulsatile insulin secretion by deconvolution and cluster analysis.

Little is known about the optimal experimental conditions for assessing pulsatile insulin secretion in vivo. To address this, we employed a recently validated canine model (n = 12) to determine the consequences of 1) sampling from the systemic circulation (SC) vs. the portal vein (PV), 2) sampling intensity and duration, and 3) deconvolution vs. cluster analysis on assessing pulsatile insulin secretion. PV vs. SC sampling resulted in a approximately 40% higher pulse frequency by deconvolution (9.0 +/- 0.5 vs. 6.6 +/- 0.9 pulses/h, P < 0.02) and cluster analysis (7.5 +/- 0.3 vs. 5.6 +/- 0.6 pulses/h, P < 0.01) due to a higher signal-to-noise ratio (19 +/- 4.8 PV vs. 12 +/- 1.8 SC). PV sampling also disclosed a higher calculated contribution of the pulsatile vs. nonpulsatile mode of delivery to total insulin secretion (57 +/- 4 vs. 28 +/- 5%, P < 0.001). Analysis of the relevance of sampling intensity revealed that 1-min data yielded a markedly higher estimate of pulse frequency with PV sampling than 2-min data (9.0 +/- 0.5 vs. 5.4 +/- 0.5, P < 0.02, deconvolution; 7.5 +/- 0.3 vs. 4.3 +/- 0.6 pulses/h, P < 0.001, cluster). Optimal sampling duration was shown to be 40 min or more. We conclude that the resolving power of the analytical tool, the anatomic site of blood withdrawal, the frequency of blood sampling, and the duration of the total observation interval all significantly influence estimated insulin secretory pulse frequency and the fraction of insulin secreted in pulses. With the assumption that PV 1-min insulin data constitute the "gold standard," our in vivo inferences of 7.5-9.0 insulin pulses/h closely recapitulate in vitro islet secretory activity.

Animals↗
PubMed1986

Metastatic behavior of prostate cancer. Cluster analysis of patterns with respect to estrogen treatment.

The responsiveness of prostate cancer to treatment with estrogen has been recognized for over 40 years, but whether the effect is mediated by diminished tumor growth or reduction in metastatic spread is not known. To answer this question the authors reviewed the clinical and pathologic features of 89 patients with metastatic prostate cancer after autopsy. Sixty-three percent of the patients studied were black. Patients treated with estrogen survived somewhat longer (0.05 less than P less than 0.10), but they had significantly greater numbers of metastatic sites (P less than 0.001) and greater overall tumor burden (P less than 0.001), with significantly increased frequencies of metastases to the liver, adrenal gland, bone, lymph nodes, large bowel, lungs, serosal surfaces, ureters, and central nervous system (CNS) (all P less than 0.05 or lower) compared with patients who had not been treated with estrogen. However, patients not treated with estrogen more frequently died from other causes (P less than 0.001). When the patients who died from other causes were excluded from the data analysis, there were no significant differences in the number of metastatic sites between patients who received estrogen therapy and those who did not, and the only remaining significant difference in the distribution of metastases was that patients who received estrogen treatment had more frequent metastases to the adrenal cortex and CNS (P less than 0.05). These observations were corroborated by cluster analysis of the metastatic patterns. Cluster analysis also identified a subset of predominantly (67%) black patients who developed distant metastases without much local spread of tumor. This suggests that tumor behavior in this group was less predictable than for the other patients in whom disease appeared to progress from Stage A to Stage D as expected. The authors conclude that estrogen therapy may prolong survival by slowing the rate of tumor growth rather than by inhibiting the metastatic progression of prostate cancer or destroying selective populations of tumor cells.

Adenocarcinoma↗
PubMed2006

The hierarchical cluster analysis of oral health attitudes and behaviour using the Hiroshima University--Dental Behavioural Inventory (HU-DBI) among final year dental students in 17 countries.

OBJECTIVE: To explore and describe international oral health attitudes/ behaviours among final year dental students. METHODS: Validated translated versions of the Hiroshima University-Dental Behavioural Inventory (HU-DBI) questionnaire were administered to 1,096 final-year dental students in 17 countries. Hierarchical cluster analysis was conducted within the data to detect patterns and groupings. RESULTS: The overall response rate was 72%. The cluster analysis identified two main groups among the countries. Group 1 consisted of twelve countries: one Oceanic (Australia), one Middle-Eastern (Israel), seven European (Northern Ireland, England, Finland, Greece, Germany, Italy, and France) and three Asian (Korea, Thailand and Malaysia) countries. Group 2 consisted of five countries: one South American (Brazil), one European (Belgium) and three Asian (China, Indonesia and Japan) countries. The percentages of 'agree' responses in three HU-DBI questionnaire items were significantly higher in Group 2 than in Group 1. They include: "I worry about the colour of my teeth."; "I have noticed some white sticky deposits on my teeth."; and "I am bothered by the colour of my gums." CONCLUSION: Grouping the countries into international clusters yielded useful information for dentistry and dental education.

Asia↗
PubMed2005

Cluster analysis of p-glycoprotein, c-erb-B2 and P53 in relation to tumor histology strongly indicates prognosis in patients with operable non-small cell lung cancer.

BACKGROUND: Various biomarkers have prognostic value in non-small cell lung cancer (NSCLC). We aimed to identify the roles of P53, c-erb- B2 and p-glycoprotein (pgp) as prognostic factors, independently or in conjunction with each other, in operable NSCLC. MATERIAL/METHODS: Seventy operable NSCLC cases were retrospectively evaluated for P53, c-erb-B2 and pgp expression patterns by immunohistochemistry. An unsupervised hierarchical cluster analysis of the 3 biomarkers was conducted. Univariate and multivariate survival analyses were made in relation to cluster affiliation. RESULTS: Cluster analysis yielded two distinct subgroups; group A of high biomarker expressors (n=26, 37%), and group B (n=44, 63%) of low expressors. Cluster affiliation with regard to tumor histology (interaction term) was independently associated with Recurrence- free survival (RFS) and Overall survival (OAS) with a Hazard Ratio (HR) of 5.88, P=0.003, and HR=4.68, P=0.012, respectively. The median OAS times for cluster A and B in the squamous cell carcinoma subgroup were 328 and 596 days, whereas the corresponding figures in the non-squamous cell carcinoma subgroup were non-measurable and 298 days. CONCLUSIONS: In operable NSCLC there may be different relationships of P53, c-erb-B2 and pgp with patient outcome for different tumor histologies. The prognostic utility of cluster affiliation with regard to these biomarkers, and in relation to tumor histology, deserves further testing.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2003

Iterative temporal clustering analysis for the detection of multiple response peaks in fMRI.

The temporal clustering analysis (TCA) is a novel and effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown. Performing the TCA method once can only detect the largest peak of the activation time windows well, if multiple response peaks at the same location of the brain occur. However, this limitation can be removed by using a TCA method in an iterative way in order for the smaller peaks to be detected. Our in vivo fMRI experiments with event-related visual tasks have demonstrated this ability.

Brain Mapping↗
PubMed2006

An improved temporal clustering analysis method applied to whole-brain data in fMRI study.

Temporal clustering analysis (TCA) has been proposed as a method to detect the brain responses of an fMRI time series when the time and location of the activation are completely unknown. But TCA is still incompetent in dealing with the time series of the whole brain due to the existence of many inactive pixels. If only active pixels are considered, the sensitivity of TCA will be improved greatly and it could be applied to the whole brain. In this study, some modifications were made to TCA to remove inactive pixels, and the applicability of the modified TCA to the whole brain was validated with a set of visual fMRI data. Based on the time series of the modified TCA, activations of the whole brain corresponding to the visual stimulation were detected. Compared with the previous TCA, the modified TCA method shows a significant improvement in the sensitivity to detect activation peaks of the whole brain.

Brain↗
PubMed2003

DNA microarray cluster analysis reveals tissue similarity and potential neuron-specific genes expressed in cranial sensory ganglia.

Each of four cranial sensory ganglia, trigeminal, geniculate, petrosal, and nodose ganglia, contains multiple kinds of sensory neurons with different cell morphologies and neuronal properties that transmit information about sensory stimuli received peripherally. Here we analyze the complex properties of these neurons from the viewpoint of gene expression using DNA microarrays by cluster analysis. From a total of 8,740 genes, 498 genes were selected as showing tissue-dependent expression on the microarray by hierarchical cluster analysis, and their profiles indicated that, among the four sensory ganglia, the petrosal and trigeminal ganglia are intimately related. Tissue trees of 37 subclusters containing the 498 genes showed that the profiles of gene expression and the subclusters were classified into a smaller number of groups (18 groups) when information on the amounts of expression was added. In situ hybridization analysis of 21 genes selected from 13 different groups was carried out, and the gene expression patterns were classified into eight categories. The putative profiles postulated from the microarray data were essentially consistent with the patterns of expression at the cellular level as shown by in situ hybridization. In conclusion, from the overall analyses of gene expression by DNA microarray, we can identify a number of candidate genes showing neuron type-specific expression in the peripheral ganglia.

Animals↗
PubMed1995

Cluster analysis of Helicobacter pylori genomic DNA fingerprints suggests gastroduodenal disease-specific associations.

BACKGROUND: Helicobacter pylori infection is now accepted as the most common cause of chronic active gastritis and peptic ulcer disease. The etiologies of many infectious diseases have been attributed to specific or clonal strains of bacterial pathogens. Polymerase chain reaction (PCR) amplification of DNA between repetitive DNA sequences, REP elements (REP-PCR), has been utilized to generate DNA fingerprints to examine similarity among strains within a bacterial species. METHODS: Genomic DNA from H. pylori isolates obtained from 70 individuals (39 duodenal ulcers and 31 simple gastritis) was PCR-amplified using consensus probes to repetitive DNA elements. The H. pylori DNA fingerprints were analyzed for similarity and correlated with disease presentation using the NTSYS-pc computer program. RESULTS: Each H. pylori strain had a distinct DNA fingerprint except for two pairs. Single-colony DNA fingerprints of H. pylori from the same patient were identical, suggesting that each patient harbors a single strain. Computer-assisted cluster analysis of the REP-PCR DNA fingerprints showed two large clusters of isolates, one associated with simple gastritis and the other with duodenal ulcer disease. CONCLUSIONS: Cluster analysis of REP-PCR DNA fingerprints of H. pylori strains suggests that duodenal ulcer isolates, as a group, are more similar to one another and different from gastritis isolates. These results suggest that disease-specific strains may exist.

Adult↗
PubMed2002

Studies on genetics of heat tolerance in dairy cattle with reduced weather information via cluster analysis.

The objective of this study was to explore the possibility of reducing the number of weather stations for studies on genetics of heat tolerance in dairy cattle. The similarity of information from 21 Georgia weather stations was analyzed by cluster analysis. Two major clusters have been found, separating Georgia along the NE and SW line. One weather station was selected for each of the clusters based on the minimal distance to all the remaining weather stations and on completeness of the weather information. The production dataset consisted of 114,751 first-parity test-day records for milk on 14,297 Holsteins from 120 herds in Georgia. Analyses using a model for daily milk yield with temperature-humidity index classes and several other fixed effects showed no increase in error sum of squares when using only two weather stations. The threshold of heat stress was different for each of the two regions but the rate of decline after the threshold was similar. After accounting for different thresholds, the genetic component of heat tolerance for milk was higher with the two-station model. Genetic studies on or evaluation for heat tolerance based on information from a few carefully selected weather stations can be as accurate as those based on information from numerous such stations.

Animals↗
PubMed2004

Dietary patterns in middle-aged Irish men and women defined by cluster analysis.

OBJECTIVES: To identify and characterise dietary patterns in a middle-aged Irish population sample and study associations between these patterns, sociodemographic and anthropometric variables and major risk factors for cardiovascular disease. DESIGN: A cross-sectional study. SUBJECTS AND METHODS: A group of 1473 men and women were sampled from 17 general practice lists in the South of Ireland. A total of 1018 attended for screening, with a response rate of 69%. Participants completed a detailed health and lifestyle questionnaire and provided a fasting blood sample for glucose, lipids and homocysteine. Dietary intake was assessed using a standard food-frequency questionnaire adapted for use in the Irish population. The food-frequency questionnaire was a modification of that used in the UK arm of the European Prospective Investigation into Cancer study, which was based on that used in the US Nurses' Health Study. Dietary patterns were assessed primarily by K-means cluster analysis, following initial principal components analysis to identify the seeds. RESULTS: Three dietary patterns were identified. These clusters corresponded to a traditional Irish diet, a prudent diet and a diet characterised by high consumption of alcoholic drinks and convenience foods. Cluster 1 (Traditional Diet) had the highest intakes of saturated fat (SFA), monounsaturated fat (MUFA) and percentage of total energy from fat, and the lowest polyunsaturated fat (PUFA) intake and ratio of polyunsaturated to saturated fat (P:S). Cluster 2 (Prudent Diet) was characterised by significantly higher intakes of fibre, PUFA, P:S ratio and antioxidant vitamins (vitamins C and E), and lower intakes of total fat, MUFA, SFA and cholesterol. Cluster 3 (Alcohol & Convenience Foods) had the highest intakes of alcohol, protein, cholesterol, vitamin B(12), vitamin B(6), folate, iron, phosphorus, selenium and zinc, and the lowest intakes of PUFA, vitamin A and antioxidant vitamins (vitamins C and E). There were significant differences between clusters in gender distribution, smoking status, physical activity, body mass index, waist circumference and serum homocysteine concentrations. CONCLUSION: In this general population sample, cluster analysis methods yielded two major dietary patterns: prudent and traditional. The prudent dietary pattern is associated with other health-seeking behaviours. Study of dietary patterns will help elucidate links between diet and disease and contribute to the development of healthy eating guidelines for health promotion.

Alcohol Drinking↗
PubMed2000

Prognosis of functional recovery 1 year after hip fracture: typical patient profiles through cluster analysis.

BACKGROUND: Many investigators have identified distinct medical, demographic and psychosocial prefracture conditions that influence the functional outcome of patients surgically treated for a fracture of the hip. However, to design efficient intervention care programs addressing the needs of these patients, at optimal economic and social costs, more information is required on the typical combinations of prognostic determinants actually encountered. METHODS: Data on specific descriptors of the prefracture status and on mobility and functioning 1 year after surgical intervention were collected by interview from 253 consecutive patients hospitalized for a fracture of the proximal femur. Cluster analysis was used to form homogeneous groups of patients with similar profiles in terms of the 13 predictive variables and the 7 outcome variables significantly interrelated. The modeling procedure generated four clusters of patients with a typical profile sharply contrasted by their structure. RESULTS: Subjects of two clusters could walk without difficulty and were functionally independent prior to their hip fracture. One year later, however, mobility and functioning were only fully recovered by the members of one cluster. The majority of predictors were of less favorable prognostic value for the members of the second cluster. The other two clusters regrouped patients with impaired prefracture mobility that were either unaltered or even aggravated 1 year later. CONCLUSIONS. Cluster analysis identified typical profiles of elderly hip fracture patients. Close scrutiny of their respective global structure, in terms of combined prognostic determinants and outcomes, may help to develop specific management strategies that are more efficiently adapted to these different groups of patients.

Activities of Daily Living↗
PubMed2003

Cluster analysis of Delhi's ambient air quality data.

The purpose of this study was to study the spatial patterns of ambient air quality in Delhi in the absence of extensive datasets needed for space-time modeling. A spatial classification was attempted on the basis of ambient air quality data of nine years (1998 is latest year for which published data were available) for three criteria pollutants--nitrogen dioxide, sulfur dioxide, and suspended particulate matter. Monitoring stations take 24-hour samples twice a week. Published monthly average concentration data were used in this study. A hierarchical agglomerative algorithm using the average linkage between groups method and the Euclidean distance metric was used. Cluster analysis indicated that till 1998, by and large, two distinct classes existed. The results of cluster analysis prompted an investigation of systematic biases in the monitored data. No statistically significant differences in the mean concentration of all pollutants were observed between stations belonging to different land-use types (residential and industrial). This fact would be useful, if and when the authorities consider modifying the network or expanding it in Delhi. The results also support the recommendation that Delhi have a uniform standard across all areas. This study has provided a methodology for Indian researchers and practitioners to do an exploratory study of spatial patterns of air pollution and data quality issues in Indian cities using the National Ambient Air Quality Monitoring System data.

Air Pollutants↗