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PubMedDate not supplied

Statistical andrology: standard semen analysis and computer-assisted sperm motility analysis.

Results are reported of a statistical evaluation of the variables obtained by standard microscopic semen analysis and by computer-assisted sperm motility analysis. Descriptive statistical analysis and cluster analysis were carried out on both sets of data. A contingency table was created to compare the classifications obtained by the two clustering procedures. A canonical correlation analysis was performed to evaluate the classification power of the variables obtained by the two semen analyses. The results show that the two techniques of semen analysis are complementary and not substitutive and that the correlated variables "percentage forward motility" and "sperm velocity" are the most discriminating.

Humans↗

PubMed1999

Stages of change and the intake of dietary fat in African-American women: improving stage assignment using the Eating Styles Questionnaire.

OBJECTIVE: To develop an algorithm for determining the stage of change for dietary fat intake in African-American women. DESIGN: We examined the relationships between stage of change, dietary fat intake, and associated eating behaviors and developed an assessment tool for placing subjects in their appropriate stage of change. SUBJECTS: Working class and middle-income African-American women in Nashville, Tenn; 174 in study 1 and 208 in study 2. STATISTICAL ANALYSES: Fat and fiber intake by stage of change was examined using multivariate analysis of variance. Hierarchical cluster analysis was performed using Ward's method. RESULTS: A significant difference in fat intake was noted between women trying to change their intake and those not trying to change in study 1 (P < .001) and study 2 (P < .03). Of those trying to change, only 34% (study 1) and 9% (study 2) of subjects reported fat intakes below the Healthy People 2000 goal of 30% of energy from fat. In study 1, cluster analysis identified 14 groups of foods that significantly separated subjects into not trying, noncompliant, and compliant categories. Compliant subjects ate out less; ate fewer snack foods and less chicken, meat, and fat; and ate more fruits, vegetables, breakfast foods, and low-fat products. These results led to development of the Eating Styles Questionnaire (study 2), which facilitated more appropriate placement of the noncompliant group in stages of change for dietary fat intake. APPLICATIONS/CONCLUSIONS: These data support the stage construct of the Transtheoretical Model for dietary fat reduction in African-American women. Moreover, the Eating Styles Questionnaire (ESQ) can improve determination of stage of change for this group of women. The ESQ can be used to diagnose the eating styles that contribute to a high-fat intake and help in the design of interventions to lower fat intakes.

Adult↗

PubMed2006

Segmentation of VOI from multidimensional dynamic PET images by integrating spatial and temporal features.

Segmentation of multidimensional dynamic positron emission tomography (PET) images into volumes of interest (VOIs) exhibiting similar temporal behavior and spatial features is a challenging task due to inherently poor signal-to-noise ratio and spatial resolution. In this study, we propose VOI segmentation of dynamic PET images by utilizing both the three-dimensional (3-D) spatial and temporal domain information in a hybrid technique that integrates two independent segmentation techniques of cluster analysis and region growing. The proposed technique starts with a cluster analysis that partitions the image based on temporal similarities. The resulting temporal partitions, together with the 3-D spatial information are utilized in the region growing segmentation. The technique was evaluated with dynamic 2-[18F] fluoro-2-deoxy-D-glucose PET simulations and clinical studies of the human brain and compared with the k-means and fuzzy c-means cluster analysis segmentation methods. The quantitative evaluation with simulated images demonstrated that the proposed technique can segment the dynamic PET images into VOIs of different kinetic structures and outperforms the cluster analysis approaches with notable improvements in the smoothness of the segmented VOIs with fewer disconnected or spurious segmentation clusters. In clinical studies, the hybrid technique was only superior to the other techniques in segmenting the white matter. In the gray matter segmentation, the other technique tended to perform slightly better than the hybrid technique, but the differences did not reach significance. The hybrid technique generally formed smoother VOIs with better separation of the background. Overall, the proposed technique demonstrated potential usefulness in the diagnosis and evaluation of dynamic PET neurological imaging studies.

Algorithms↗

PubMed2003

Analysis of clustered matched-pair data.

Evaluation of the performance of a new diagnostic procedure with respect to a standard procedure arises frequently in practice. The response of interest, often in a dichotomous form, is measured twice, once with each procedure. The two procedures are administered to either two matched individuals, or when practical, to the same individual. A large sample test for matched-pair data is the McNemar test. The main assumption of this test is independent paired responses; however, when more than one outcome from an individual is measured by each procedure, the data are clustered. Examples of such cases can be seen in dental and ophthalmology studies. Variance adjustment methods for the analysis of clustered matched-pair data have been proposed; however, because of unequal cluster sizes, variability of correlation structures within a cluster (within paired responses in a cluster as well as between paired responses in a cluster), and unequal success probabilities among the clusters, the performances of some available methods are not consistent. This research proposes a simple adjustment to the McNemar test for the analysis of clustered matched-pair data. Method of moments is used to calculate a consistent variance estimator. Using Monte Carlo simulation, the size and power of the proposed test are compared to those of two currently available methods. To illustrate practical application, clustered matched-pair data from two clinical studies are analysed.

Clinical Trials as Topic↗

PubMed1983

Analysis of a short test battery for children.

Explored the hierarchical structure of mental abilities by comparing principal component analysis with a hierarchical cluster analysis algorithm on a short test battery for children. This short test battery included the Wechsler Intelligence Scale for Children-Revised (WISC-R), the Peabody Individual Achievement Test (PIAT), the Beery Developmental Test of Visual-Motor Integration (VMI) and the Peabody Picture Vocabulary Test (PPVT). Scores from 182 children (116 boys and 66 girls) with a mean age of 10.83 were analyzed. The structure of the test battery included general intelligence, attention, academic achievement and perceptual-motor eye-hand coordination. Both the linear principal component analysis and the nonlinear hierarchical clustering analysis confirmed the hierarchical organization of mental abilities.

Achievement↗

PubMed1996

Identifying subtypes of schizophrenia by cluster analyses.

The existence of two subtypes of schizophrenia (positive and negative) is well established. The evidence in favor of other subtypes, particularly a disorganized subtype, is still the subject of some debate. The aim of the study reported in this article is to investigate the possibility of further subtypes of schizophrenia by applying a particular method of cluster analysis to a particular set of data. Ward's method of cluster analysis was applied to the Positive and Negative syndrome Scale (PANSS) scores of 138 patients, defined as having schizophrenia by one of four diagnostic criteria. The validity of the cluster solution was assessed both by examining differences between clusters on a number of clinical characteristics recorded for each patient and by comparing the results obtained from the PANSS with those derived from a cluster analysis using two other instruments (the Scale for the Assessment of Negative Symptoms and the Scale for the Assessment of Positive Symptoms). Results from the cluster analysis suggest the existence of at least four subtypes of schizophrenia: positive, negative, mixed, and disorganized. A fifth subtype includes patients with few symptoms, suggesting the simple schizophrenia named by Bleuler. Evidence for the validity of these subtypes was provided by the differences observed between the clusters on a number of clinical characteristics and by the similarity of the cluster solution obtained from the different instruments. In conclusion, the negative-positive dichotomy in schizophrenia is an oversimplification, and the existence of a more complex structure needs to be taken into account in future research.

Adult↗

PubMed2001

Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters.

MOTIVATION: Cluster analysis of genome-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and samples. In the present paper, we focus on several important issues related to clustering algorithms that have not yet been fully studied. RESULTS: We describe a simple and robust algorithm for the clustering of temporal gene expression profiles that is based on the simulated annealing procedure. In general, this algorithm guarantees to eventually find the globally optimal distribution of genes over clusters. We introduce an iterative scheme that serves to evaluate quantitatively the optimal number of clusters for each specific data set. The scheme is based on standard approaches used in regular statistical tests. The basic idea is to organize the search of the optimal number of clusters simultaneously with the optimization of the distribution of genes over clusters. The efficiency of the proposed algorithm has been evaluated by means of a reverse engineering experiment, that is, a situation in which the correct distribution of genes over clusters is known a priori. The employment of this statistically rigorous test has shown that our algorithm places greater than 90% genes into correct clusters. Finally, the algorithm has been tested on real gene expression data (expression changes during yeast cell cycle) for which the fundamental patterns of gene expression and the assignment of genes to clusters are well understood from numerous previous studies.

Algorithms↗

PubMed2025

Genetic targets related to aging for the treatment of coronary artery disease.

BACKGROUND: Coronary Artery Disease (CAD) is the most common cardiovascular disease worldwide, threatening human health, quality of life and longevity. Aging is a dominant risk factor for CAD. This study aims to investigate the potential mechanisms of aging-related genes and CAD, and to make molecular drug predictions that will contribute to the diagnosis and treatment. METHODS: We downloaded the gene expression profile of circulating leukocytes in CAD patients (GSE12288) from Gene Expression Omnibus database, obtained differentially expressed aging genes through "limma" package and GenaCards database, and tested their biological functions. Further screening of aging related characteristic genes (ARCGs) using least absolute shrinkage and selection operator and random forest, generating nomogram charts and ROC curves for evaluating diagnostic efficacy. Immune cells were estimated by ssGSEA, and then combine ARCGs with immune cells and clinical indicators based on Pearson correlation analysis. Unsupervised cluster analysis was used to construct molecular clusters based on ARCGs and to assess functional characteristics between clusters. The DSigDB database was employed to explore the potential targeted drugs of ARCGs, and the molecular docking was carried out through Autodock Vina. Finally, single-cell data (GSE159677) of arterial intima was used to further explore the expression of aging signature genes in different cell subpopulations. RESULTS: We identified 8 ARCGs associated with CAD, in which HIF1A and FGFR3 were up while NOX4, TCF7L2, HK3, CDK18, TFAP4, and ITPK1 were down in CAD patients. Based on this, CAD patients can be divided into two molecular clusters, among which cluster A mainly involves functional pathways such as ECM receptor interaction and focal adhesion; cluster B mainly involves functional pathways such as amimo sugar and nucleotide sugar metabolism and pyrimidine metabolism. In addition, the molecular docking results showed that retinoic acid and resveratrol had good binding affinity with targets genes. Further single-cell analysis results showed that NOX4, TCF7L2, ITPK1, and HIF1A were specifically expressed in different types of cells in atherosclerotic tissues. CONCLUSION: Our study identified several ARCGs that may be involved in the pathogenesis and progression of CAD. Further, retinoic acid and resveratrol were potential candidate molecule drugs for inhibiting these targets.

Humans↗

PubMed1994

Lifestyle and accidents among young drivers.

This study covers the lifestyle component of the problems related to young drivers' accident risk. The purpose of the study is to measure the relationship between lifestyle and accident risk, and to identify specific high-risk and low-risk groups. Lifestyle is measured through a questionnaire, where 20-year-olds describe themselves and how often they deal with a large number of different activities, like sports, music, movies, reading, cars and driving, political engagement, etc. They also report their involvement in traffic accidents. With a principal component analysis followed by a cluster analysis, lifestyle profiles are defined. These profiles are finally correlated to accidents, which makes it possible to define high-risk and low-risk groups. The cluster analysis defined 15 clusters including four high-risk groups with an average overrisk of 150% and two low-risk groups with an average underrisk of 75%. The results are discussed from two perspectives. The first is the importance of theoretical understanding of the contribution of lifestyle factors to young drivers' high accident risk. The second is how the findings could be used in practical road safety measures, like education, campaigns, etc.

Accidents, Traffic↗

PubMed1999

The relationship between personality and attainment in 16-19-year-old students in a sixth form college: II: Self-perception, gender and attainment.

BACKGROUND: A related paper (Summerfield & Youngman, 1999) has described the development of a scale, the Student Self-Perception Scale (SSPS) designed to explore the relationship between academic self-concept, attainment and personality in sixth form college students. AIMS: The study aimed to identify groups of students exhibiting varying patterns of relationship using a range of measures including the SSPS. Issues of gender and also examined. SAMPLES: The samples comprised a pilot sample of 152 students (aged 16-17 years from two sixth form colleges) and a main sample of 364 students (mean age, 16 yrs 10 mths range 16:0 to 18:6 years, from one sixth form college). The main sample included similar numbers of male and female students (46% male, 54% female) and ethnic minority students comprised 14% of this sample. METHOD: Data comprised responses to two personality measures (the SSPS, Summerfield, 1995, and the Nowicki-Strickland Locus of Control Scale, Nowicki & Strickland, 1973), various student and tutor estimates of success, and performance data from college records. Students were classified using relocation cluster analysis and cluster differences verified using discriminant function analysis. Thirty outcome models were tested using covariance regression analysis. RESULTS: Eight distinct and interpretable groups, consistent with other research, were identified but the hypothesis of a positive, linear relationship between mastery and academic attainment was not sustained without qualification. Previous attainment was the major determinant of final performance. Gender variations were detected on the personality measures, particularly Confidence of outcomes, Prediction discrepancy, Passivity, Mastery, Dependency and Locus of control, and these were implicated in the cluster characteristics. CONCLUSIONS: The results suggest that a non-linear methodology may be required to isolate relationships between self-concept, personality and attainment, especially where gender effects may exist.

Achievement↗

PubMed2006

The Personality Assessment Inventory in individuals with traumatic brain injury.

This study examined the Personality Assessment Inventory (PAI) in 95 individuals who had suffered a traumatic brain injury (TBI). Participants were recruited from a rehabilitation hospital (n=60) and a military hospital (n=35); despite differences in demographics and injury characteristics groups did not differ on any of the clinical scales and were thus combined. In the combined group, the highest mean clinical scale elevations were on Somatic Complaints, Depression, and Borderline Features and the most common configural profiles, based on cluster analysis, were Cluster 1 (no prominent elevations), Cluster 6 (social isolation and confused thinking), and Cluster 2 (depression and withdrawal). Factor analysis indicated a robust three-factor solution that accounted for 74.86 percent of the variance and was similar to findings from the psychiatric and non-psychiatric populations in the standardization sample. The above findings are compared with the previous literature on psychopathology in TBI, particularly in regards to the Minnesota Multiphasic Personality Inventory-2 (MMPI-2), as well as previous psychometric research on the PAI.

Adult↗

PubMed2006

An automated image-processing strategy to analyze dynamic arterial spin labeling perfusion studies. Application to human skeletal muscle under stress.

Arterial spin labeling (ASL) perfusion measurements allow the follow-up of muscle perfusion with high temporal resolution during a stress test. Automated image processing is proposed to estimate perfusion maps from ASL images. It is based on two successive analyses: at first, automated rejection of the image pairs between which a large displacement is detected is performed, followed by factor analysis of the dynamic data and cluster analysis to classify pixels with large signal variation characteristic of vessels. Then, after masking these "vascular" pixels, factor analysis and cluster analysis are further applied to separate the different muscles between low or high perfusion increase, yielding a functional map of the leg. Data from 10 subjects (five normal volunteers and five elite sportsmen) had been analyzed. Resulting time perfusion curves from a region of interest (ROI) in active muscles show a good accordance whether extracted with automated processing or with manual processing. This method of functional segmentation allows automated suppression of vessels and fast visualization of muscles with high, medium or low perfusion, without any a priori knowledge.

Adult↗

PubMed2006

Cluster-based analysis of FMRI data.

We propose a method for the statistical analysis of fMRI data that tests cluster units rather than voxel units for activation. The advantages of this analysis over previous ones are both conceptual and statistical. Recognizing that the fundamental units of interest are the spatially contiguous clusters of voxels that are activated together, we set out to approximate these cluster units from the data by a clustering algorithm especially tailored for fMRI data. Testing the cluster units has a two-fold statistical advantage over testing each voxel separately: the signal to noise ratio within the unit tested is higher, and the number of hypotheses tests compared is smaller. We suggest controlling FDR on clusters, i.e., the proportion of clusters rejected erroneously out of all clusters rejected and explain the meaning of controlling this error rate. We introduce the powerful adaptive procedure to control the FDR on clusters. We apply our cluster-based analysis (CBA) to both an event-related and a block design fMRI vision experiment and demonstrate its increased power over voxel-by-voxel analysis in these examples as well as in simulations.

Algorithms↗

PubMed1985

Hypomethylation of DNA derived from purified human erythroid cells correlates with gene activity of the beta-globin cluster.

Analysis of methylation at the beta-globin gene cluster was carried out on DNA derived from nucleated RBCs (orthochromatic normoblasts) isolated from peripheral blood of patients with beta-thalassemia major or other congenital hemolytic anemia after splenectomy. A procedure to separate these normoblasts from the other nucleated cells of the peripheral blood was developed, providing us with a convenient source of DNA for investigating parameters related to human erythroid differentiation. Blood samples were obtained from six adult patients who express their gamma-globin genes at different levels. Inverse correlation between methylation and gene activity was consistently observed for five of the eight sites analyzed. A site 3' to the beta gene was always unmethylated, two sites flanking the epsilon gene were always found to be methylated, and two sites 5' to the two gamma genes, G gamma and A gamma, were hypomethylated in correlation with gamma gene activity of the individual patients. A site 5' to the delta gene was unmethylated in normoblasts as well as in WBC. No apparent relation between hypomethylation and gene activity was observed for two additional sites. The results suggest that methylation at specific chromosomal locations participate in genetic regulation of the beta-like globin genes in humans.

DNA↗

PubMed1984

Detection of a novel DNA polymorphism in the beta-globin gene cluster.

Analysis of DNA from the beta-globin gene cluster in an Albanian family identified a novel RsaI site approximately 550 base pairs 5' to the beta-globin gene. In this family, two chromosomes carrying otherwise identical beta-globin haplotypes were found to differ at the RsaI site. Population screening demonstrated the presence and absence of the site in DNA from individuals of northern European, Mediterranean, Middle Eastern, Southeast Asian, African, and Asian Indian descent, indicating that this site is a DNA polymorphism common in many ethnic groups. The polymorphism is also present in DNA from individuals carrying different beta-globin alleles. Additional nucleotide sequence changes identified in an RsaI (+) genomic clone in the region immediately 3' to the RsaI site suggest a mechanism for the randomization of the site with respect to haplotype.

Alleles↗

PubMed1998

Track structure in radiation biology: theory and applications.

PURPOSE: A brief review is presented of the basic concepts in track structure and the relative merit of various theoretical approaches adopted in Monte-Carlo track-structure codes are examined. In the second part of the paper, a formal cluster analysis is introduced to calculate cluster-distance distributions. METHOD: Total experimental ionization cross-sections were least-square fitted and compared with the calculation by various theoretical methods. Monte-Carlo track-structure code Kurbuc was used to examine and compare the spectrum of the secondary electrons generated by using functions given by Born-Bethe, Jain-Khare, Gryzinsky, Kim-Rudd, Mott and Vriens' theories. The cluster analysis in track structure was carried out using the k-means method and Hartigan algorithm. RESULTS: Data are presented on experimental and calculated total ionization cross-sections: inverse mean free path (IMFP) as a function of electron energy used in Monte-Carlo track-structure codes; the spectrum of secondary electrons generated by different functions for 500 eV primary electrons; cluster analysis for 4 MeV and 20 MeV alpha-particles in terms of the frequency of total cluster energy to the root-mean-square (rms) radius of the cluster and differential distance distributions for a pair of clusters; and finally relative frequency distribution for energy deposited in DNA, single-strand break and double-strand breaks for 10MeV/u protons, alpha-particles and carbon ions. CONCLUSIONS: There are a number of Monte-Carlo track-structure codes that have been developed independently and the bench-marking presented in this paper allows a better choice of the theoretical method adopted in a track-structure code to be made. A systematic bench-marking of cross-sections and spectra of the secondary electrons shows differences between the codes at atomic level, but such differences are not significant in biophysical modelling at the macromolecular level. Clustered-damage evaluation shows: that a substantial proportion of dose ( 30%) is deposited by low-energy electrons; the majority of DNA damage lesions are of simple type; the complexity of damage increases with increased LET, while the total yield of strand breaks remains constant; and at high LET values nearly 70% of all double-strand breaks are of complex type.

Alpha Particles↗

PubMed1996

The use of cluster significance analysis to identify asymmetric QSAR data sets in toxicology. An example with eye irritation data.

Cluster significance analysis is a tool that allows the identification of "embedded clusters' in QSAR datasets. It is successfully applied to an eye irritation data set to show that these data are indeed asymmetric. The method identifies five parameters that form an embedded cluster of eye irritants amongst non irritants, although full separation is not achieved. This method has considerable potential to identify potential non-linearity in toxicology data sets and for parameter reduction. It is shown also that this can be obtained relatively quickly with an analysis performed on 100,000 subsets containing the same information as an analysis on 1,000,000 subsets.

Cluster Analysis↗

PubMed2004

Cluster size analysis of two-dimensional order in colloidal gold nanoparticle arrays.

A protocol for cluster size distribution analysis was developed in order to parametrize local two-dimensional (2D) order in a quantitative manner, using mean cluster sizes and fractional hcp cluster formation (fhcp). Cluster size analysis was performed on 2D arrays of Au nanoparticles encapsulated in resorcinarene tetrathiol, which were organized into close-packed films at aqueous interfaces. The degree of monolayer formation and 2D order within the self-assembled nanoparticle arrays was observed to be strongly dependent on the amount and type of electrolyte (chloride and/or citrate) adsorbed on the nanoparticle surface, prior to encapsulation and extraction to the solvent interface. Increasing the concentration of adsorbed electrolyte could promote monoparticulate film formation but had a variable effect on local 2D order.

Cluster Analysis↗