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At least 433 records · Page 24Linked to original sources
PubMed1979

Medically-related absenteeism: random or motivated behavior?

The present study examined alternative measures of absence proneness related to organizationally-defined measures of absenteeism. A typical distinction among various types of absences is to separate medically-related absences from other types, since medically-related absences are believed to reflect random or unsystematic causes of behavior rather than voluntary choice behavior of the employee. The present study defined absence proneness as the degree to which individuals repeat their behavior. Three years of absence data for a sample of employees from one company were examined to discover the degree of absence proneness present in organizationally-defined forms of medically-related and voluntary absenteeism. In addition, a survey was administered to the sample to measure employee perceptions of work and non-work-related factors which were believed to be motivational determinants of absenteeism. A multiple discriminant analysis was developed in an attempt to classify employees to a survey designed to measure motivational determinants of absenteeism. The classification results supported the view that medically-related absenteeism has motivational determinants related to employee work and non-work preferences. Implications for management are discussed.

Absenteeism↗
PubMed1994

[Analysis of risk factors in postinfarction angina].

The clinical and echocardiographic variables related to postinfarction angina were evaluated in 54 patients with acute myocardial infarction. All patients underwent 2D echocardiography at 2-3 weeks after infarction. Wall motion analysis was quantified with a wall motion score index (WMSI) based on 16 left ventricular wall segments. Among the 54 patients with acute myocardial infarction 23 (42.6%) had early postinfarction angina. Multiple regression analysis demonstrated no significant difference between the patients with and without postinfarction angina in age, sex, location of infarction, Killip classification, previous angina, hypertension, hyperlipidemia, diabetes mellitus, creatine kinase level and left ventricular ejection fraction. In comparison with patients without postinfarction angina, patients with postinfarction angina had higher WMSI. It indicates that postinfarction angina appears to be related more to myocardial ischemia rather than to the infarct of myocardium.

Adult↗
PubMed2001

Rapid prototyping of an EEG-based brain-computer interface (BCI).

The electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g., late stage of amyotrophic lateral sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEG-based brain-computer interface (BCI). This paper describes a new type of BCI system that uses rapid prototyping to enable a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. Rapid prototyping is possible by using Matlab, Simulink, and the Real-Time Workshop. It is shown how to automate real-time experiments and perform the interplay between on-line experiments and offline analysis. The system is able to process multiple EEG channels on-line and operates under Windows 95 in real-time on a standard PC without an additional digital signal processor (DSP) board. The BCI can be controlled over the Internet, LAN or modem. This BCI was tested on 3 subjects whose task it was to imagine either left or right hand movement. A classification accuracy between 70% and 95% could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive (AAR) model and linear discriminant analysis (LDA).

Adolescent↗
PubMed2005

Sequence and comparative genomic analysis of actin-related proteins.

Actin-related proteins (ARPs) are key players in cytoskeleton activities and nuclear functions. Two complexes, ARP2/3 and ARP1/11, also known as dynactin, are implicated in actin dynamics and in microtubule-based trafficking, respectively. ARP4 to ARP9 are components of many chromatin-modulating complexes. Conventional actins and ARPs codefine a large family of homologous proteins, the actin superfamily, with a tertiary structure known as the actin fold. Because ARPs and actin share high sequence conservation, clear family definition requires distinct features to easily and systematically identify each subfamily. In this study we performed an in depth sequence and comparative genomic analysis of ARP subfamilies. A high-quality multiple alignment of approximately 700 complete protein sequences homologous to actin, including 148 ARP sequences, allowed us to extend the ARP classification to new organisms. Sequence alignments revealed conserved residues, motifs, and inserted sequence signatures to define each ARP subfamily. These discriminative characteristics allowed us to develop ARPAnno (http://bips.u-strasbg.fr/ARPAnno), a new web server dedicated to the annotation of ARP sequences. Analyses of sequence conservation among actins and ARPs highlight part of the actin fold and suggest interactions between ARPs and actin-binding proteins. Finally, analysis of ARP distribution across eukaryotic phyla emphasizes the central importance of nuclear ARPs, particularly the multifunctional ARP4.

Actins↗
PubMed1997

Predictive factors of restenosis after coronary stent placement.

OBJECTIVES: The objective of this study was to identify clinical, lesional and procedural factors that can predict restenosis after coronary stent placement. BACKGROUND: Coronary stent placement reduces the restenosis rate compared with that after percutaneous transluminal coronary angioplasty (PTCA). However, restenosis remains an unresolved issue, and identification of its predictive factors may allow further insight into the underlying process. METHODS: All patients with successful coronary stent placement were eligible for this study unless they had had a major adverse cardiac event during the 1st 30 days after the procedure. Of the 1,349 eligible patients (1,753 lesions), follow-up angiography at 6 months was performed in 80.4% (1,084 patients, 1,399 lesions). Demographic, clinical, lesional and procedural data were prospectively recorded and analyzed for any predictive power for the occurrence of late restenosis after stenting. Restenosis was evaluated by using three outcomes at follow-up: binary restenosis as a diameter stenosis > or =50%, late lumen loss as lumen diameter reduction and target lesion revascularization (TLR) as any repeat PTCA or coronary artery bypass surgery involving the stented lesion. RESULTS: Multivariate analysis demonstrated that diabetes mellitus, placement of multiple stents and minimal lumen diameter (MLD) immediately after stenting were the strongest predictors of restenosis. Diabetes increased the risk of binary restenosis with an odds ratio (OR) [95% confidence interval] of 1.86 [1.56 to 2.16] and the risk of TLR with an OR of 1.45 [1.11 to 1.80]. Multiple stents increased the risk of binary restenosis with an OR of 1.81 [1.55 to 2.06] and that of TLR with an OR of 1.94 [1.66 to 2.22]. An MLD <3 mm at the end of the procedure augmented the risk of binary restenosis with an OR of 1.81 [1.55 to 2.06] and that of TLR with an OR of 2.05 [1.77 to 2.34]. Classification and regression tree analysis demonstrated that the incidence of restenosis may be as low as 16% for a lesion without any of these risk factors and as high as 59% for a lesion with a combination of these risk factors. CONCLUSIONS: Diabetes, multiple stents and smaller final MLD are strong predictors of restenosis after coronary stent placement. Achieving an optimal result with a minimal number of stents during the procedure may significantly reduce this risk even in patients with adverse clinical characteristics such as diabetes.

Aged↗
PubMed2006

Automated classification of evoked quantal events.

We provide both theoretical and computational improvements to the analysis of synaptic transmission data. Theoretically, we demonstrate the correlation structure of observations within evoked postsynaptic potentials (EPSP) are consistent with multiple random draws from a common autoregressive moving-average (ARMA) process of order (2, 2). We use this observation and standard time series results to construct a statistical hypothesis testing procedure for determining whether a given trace is an EPSP. Computationally, we implement this method in R, a freeware statistical language, which reduces the amount of time required for the investigator to classify traces into EPSPs or non-EPSPs and eliminates investigator subjectivity from this classification. In addition, we provide a computational method for calculating common functionals of EPSPs (peak amplitude, decay rate, etc.). The methodology is freely available over the internet. The automated procedure to index the quantal characteristics greatly facilitates determining if any one or multiple parameters are changing due to experimental conditions. In our experience, the software reduces the time required to perform these analyses from hours to minutes.

Animals↗
PubMed2006

ROKU: a novel method for identification of tissue-specific genes.

BACKGROUND: One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. RESULTS: We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. CONCLUSION: ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes.

Algorithms↗
PubMedDate not supplied

Cellular process classification of human papillomavirus-16-positive SiHa cervical carcinoma cell using Gene Ontology.

This study utilized mRNA differential display and the Gene Ontology (GO) analysis to characterize the multiple interactions of a number of genes involved in human papillomavirus (HPV)-16-induced cervical carcinogenesis. We used HPV-16-positive cervical cancer cell line (SiHa) and normal human keratinocyte cell line (HaCaT) as a control. Each gene has several biological functions in the GO, and hence, we chosen the several functions for each gene. and then, the specific functions were correlated with gene expression patterns. The results showed that 157 genes were up- or down-regulated above two-fold and organized into mutually dependent subfunction sets depending on the cervical cancer pathway, suggesting the potentially significant genes of unknown function. The GO analysis suggested that cervical cancer cells underwent repression of cancer-specific cell-adhesive properties. Also, genes belonging to DNA metabolism such as DNA repair and replication were strongly down-regulated, whereas significant increases were shown in protein degradation and in protein synthesis. The GO analysis can overcome the complexity of the gene expression profile of the HPV-16-associated pathway and identify several cancer-specific cellular processes as well as genes of unknown function. Also, it can become a major competing platform for the genome-wide characterization of carcinogenesis.

Carcinoma, Squamous Cell↗
PubMed2001

Behavior and severity of adjuvant arthritis in four rat strains.

Previous research has suggested that behavioral traits of the histocompatible Lewis and Fischer strains of rats could be related to the difference in their susceptibility to adjuvant arthritis (AA). In the present study, the predictive value of behavioral markers in susceptibility to AA was investigated in nonhistocompatible inbred DA, Lewis, Albino Oxford (AO), and outbred Wistar strain. Behavioral profiles (open filed test and forced swim test) were determined prior to immunization with a single intradermal injection of complete Freund's adjuvant. Animals were daily scored for clinical signs of AA. The occurrence of certain behaviors and clinical indices of AA was significantly associated with strain membership. Discriminant analysis identified strain-related behavioral and illness profiles with very few overlaps among the phenotypes. Discriminant classification significantly exceeded the proportion of cases, which could have been correctly classified on the basis of chance. Open field behavior, in particular, exploration and grooming, differentiated among AA-susceptible and AA-resistant strains. Multiple regression analysis indicated that severity of AA (maximum clinical sign) can be predicted by the latency time and grooming behavior in the open field independently of strain membership. No clear distinction between AA-susceptible and AA-resistant strains was found with respect to forced swim test immobility. It was concluded that (a) strain-related genetic predisposition is important for the expression of certain behavioral traits and for susceptibility to AA and (b) open field behaviors, particularly grooming and latency, predict susceptibility to AA across different rat strains.

Animals↗
PubMed2003

MBGD: microbial genome database for comparative analysis.

MBGD is a workbench system for comparative analysis of completely sequenced microbial genomes. The central function of MBGD is to create an orthologous gene classification table using precomputed all-against-all similarity relationships among genes in multiple genomes. In MBGD, an automated classification algorithm has been implemented so that users can create their own classification table by specifying a set of organisms and parameters. This feature is especially useful when the user's interest is focused on some taxonomically related organisms. The created classification table is stored into the database and can be explored combining with the data of individual genomes as well as similarity relationships among genomes. Using these data, users can carry out comparative analyses from various points of view, such as phylogenetic pattern analysis, gene order comparison and detailed gene structure comparison. MBGD is accessible at http://mbgd.genome.ad.jp/.

Algorithms↗
PubMed2001

A new prognosis factor analysis based on nonhomogeneous Markov description.

To evaluate prognosis factors, Cox's proportional hazard model has been used. But it was found that the analytical ability was not sufficient. So we propose a new evaluation method combining Markov chain model and multiple logistic regression analysis to estimate the prognosis factors. Stage II breast cancer was chosen as the subject. The data was retrospective data gathered in National Cancer Center Central Hospital. As first step, a simple Markov chain model was constructed to describe the state transition of a breast cancer. Then the multiple property of each state transition was investigated in detail. And the patients who had gotten a recurrence for the first two and a half years were discriminated as the poor prognosis group by a nonparametric test (p < 0.05). And the result proved to corresponding with the clinical experience. As second step, three factors (n classification of pathological diagnosis, ductal spread, and estrogen receptor) were selected as the prognosis factors for the early death in Stage II breast cancer by a multiple logistic regression analysis. This new prognosis factor analysis could find out some scientific evidences. Especially, it was found to be remarkable efficient in proving clinically experienced observation.

Breast Neoplasms↗
PubMed2004

Molecular dynamics of protein complexes from four-dimensional cryo-electron microscopy.

Cryo-electron microscopy of single particles offers a unique opportunity to detect and quantify conformational variation of protein complexes. Different conformers may, in principle, be distinguished by classification of individual projections in which image differences arising from viewing geometry are disentangled from variability in the underlying structures by "multiple particle analysis"--MPA. If the various conformers represent dynamically related states of the same complex, MPA has the potential to visualize transition states, and eventually to yield movies of the dynamic process. Ordering the various conformers into a time series is facilitated if cryo-EM data are taken at successive times from a system that is known to be developing in time. Virus maturation represents a relatively tractable dynamic process because the changes are large and irreversible and the rate of the natural process may be conveniently slowed in vitro by adjusting the environmental conditions. We describe the strategy employed in a recent analysis of herpes simplex virus procapsid maturation (Nat. Struct. Biol. 10 (2003) 334-341), compare it with previous work on the maturation of bacteriophage HK97 procapsid, and discuss various factors that impinge on the feasibility of performing similar experimental analyses of molecular dynamics in the general case.

Bacteriophages↗
PubMed2005

A study on several machine-learning methods for classification of malignant and benign clustered microcalcifications.

In this paper, we investigate several state-of-the-art machine-learning methods for automated classification of clustered microcalcifications (MCs). The classifier is part of a computer-aided diagnosis (CADx) scheme that is aimed to assisting radiologists in making more accurate diagnoses of breast cancer on mammograms. The methods we considered were: support vector machine (SVM), kernel Fisher discriminant (KFD), relevance vector machine (RVM), and committee machines (ensemble averaging and AdaBoost), of which most have been developed recently in statistical learning theory. We formulated differentiation of malignant from benign MCs as a supervised learning problem, and applied these learning methods to develop the classification algorithm. As input, these methods used image features automatically extracted from clustered MCs. We tested these methods using a database of 697 clinical mammograms from 386 cases, which included a wide spectrum of difficult-to-classify cases. We analyzed the distribution of the cases in this database using the multidimensional scaling technique, which reveals that in the feature space the malignant cases are not trivially separable from the benign ones. We used receiver operating characteristic (ROC) analysis to evaluate and to compare classification performance by the different methods. In addition, we also investigated how to combine information from multiple-view mammograms of the same case so that the best decision can be made by a classifier. In our experiments, the kernel-based methods (i.e., SVM, KFD, and RVM) yielded the best performance (Az = 0.85, SVM), significantly outperforming a well-established, clinically-proven CADx approach that is based on neural network (Az = 0.80).

Algorithms↗
PubMed2006

VANTED: a system for advanced data analysis and visualization in the context of biological networks.

BACKGROUND: Recent advances with high-throughput methods in life-science research have increased the need for automatized data analysis and visual exploration techniques. Sophisticated bioinformatics tools are essential to deduct biologically meaningful interpretations from the large amount of experimental data, and help to understand biological processes. RESULTS: We present VANTED, a tool for the visualization and analysis of networks with related experimental data. Data from large-scale biochemical experiments is uploaded into the software via a Microsoft Excel-based form. Then it can be mapped on a network that is either drawn with the tool itself, downloaded from the KEGG Pathway database, or imported using standard network exchange formats. Transcript, enzyme, and metabolite data can be presented in the context of their underlying networks, e. g. metabolic pathways or classification hierarchies. Visualization and navigation methods support the visual exploration of the data-enriched networks. Statistical methods allow analysis and comparison of multiple data sets such as different developmental stages or genetically different lines. Correlation networks can be automatically generated from the data and substances can be clustered according to similar behavior over time. As examples, metabolite profiling and enzyme activity data sets have been visualized in different metabolic maps, correlation networks have been generated and similar time patterns detected. Some relationships between different metabolites were discovered which are in close accordance with the literature. CONCLUSION: VANTED greatly helps researchers in the analysis and interpretation of biochemical data, and thus is a useful tool for modern biological research. VANTED as a Java Web Start Application including a user guide and example data sets is available free of charge at http://vanted.ipk-gatersleben.de.

Algorithms↗
PubMed2006

[C-reactive protein and interleukin-6 serum levels increase as Chagas disease progresses towards cardiac failure].

INTRODUCTION AND OBJECTIVES: Chagas disease is the most common cause of myocarditis in Latin America, including Venezuela. Some 25% of patients progress to chronic chagasic cardiomyopathy, which is characterized by heart failure and arrhythmias. The serum levels of C-reactive protein (CRP) and interleukin-6 (IL-6) have prognostic value in non-chagasic cardiopathy. The goal of this study was to investigate the relationship between the serum levels of CRP and IL-6 and the developmental stage of Chagas disease. PATIENTS AND METHOD: The study included 64 Chagas disease patients (34 female and 30 male; age 62.2 [1.7] years) and 20 healthy individuals (10 of each sex; age 50.4 [2.7] years). Clinical investigations included echocardiography and measurement of CRP and IL-6 serum levels using ELISAs. Chagas disease patients were graded according to Carrasco et al 1994 classification. Patients with ischemic cardiopathy, liver disease, autoimmune disease, a systemic inflammatory condition, immunosuppression, cancer, pericarditis, or endocarditis were excluded. RESULTS: Multiple regression analysis demonstrated an association between Chagas disease developmental stage and the serum IL-6 level. The serum CRP level increased during only the most advanced phase of the disease. In addition, a high left ventricular mass index was associated with a high IL-6 level and male sex. CONCLUSIONS: IL-6 and CRP serum levels could be of prognostic value in assessing Chagas disease progression because there are significant correlations between elevated levels and the deterioration of cardiac function.

C-Reactive Protein↗
PubMed2004

[Immunophenotype analysis in 121 patients with lymphoproliferative diseases by flow cytometry].

BACKGROUND & OBJECTIVE: Multiple parameter immunophenotype analysis by flow cytometry (FCM) could improve the accuracy of diagnosis in lymphoproliferative diseases. This study was to analyze the immunophenotype of 135 samples, including lymph nodes, blood, bone marrow, and cerebrospinal fluid samples, from 121 patients with suspected lymphoid malignancies, to evaluate its role in diagnosis. METHODS: All samples were tested by routine morphological, pathological, and immunohistochemical methods, and analyzed by FCM in suspended single cells, to compare the accuracy of different diagnostic methods. RESULTS: (1) Three of 23 lymph nodes, which failed to be diagnosed by routine methods, were determined by flow cytometric immunophenotype analysis. (2) According to new WHO classification, 96 of 97 blood or bone marrow aspiration samples were diagnosed by flow cytometric immunophenotype analysis, while 88 of 97 samples were diagnosed by routine immunohistochemical method. (3) Multiple parameter immunophenotype analysis in cerebrospinal fluid samples by FCM improved the diagnostic accuracy of leukemia or lymphoma involvement of central nervous system. CONCLUSIONS: Multiple parameter immunophenotype analysis by FCM improves the accuracy of diagnosis in lymphoid malignancies, and can be used in diagnosis, differentiated diagnosis, and detection of minimal residue in lymphoproliferative diseases.

Adolescent↗
PubMed1995

[Familial hyperparathyroidism].

Recently, not only the multiple endocrine adenomatosis (MEN)-associated type but also the type which can be isolated from MEN syndrome have been widely accepted in the classification of familial hyperparathyroidism. Analysis of gene markers specific to MEN syndrome contributed markedly to the establishment of isolated familial hyperparathyroidism. We attempted an analysis of 15 pedigrees in the report of familial hyperparathyroidism in which MEN syndrome was actively ruled out. In 7 pedigrees, adenoma alone was seen while in 2 pedigrees was hyperplasia alone seen. In 6 pedigrees parathyroid carcinoma was also admitted (other members of the pedigree were affected with parathyroid adenoma or hyperplasia). There were 5 pedigrees in which cementifying fibroma or ossifying fibroma of the jaw was associated with familial hyperparathyroidism. The association of parathyroid carcinomas or benign jaw tumors should be paid attention.

Fibroma↗