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Results for “Likelihood Functions”

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PubMedDate not supplied

A randomized clinical trial of a care recommendation letter intervention for somatization in primary care.

PURPOSE: This paper describes the impact of a care recommendation (CR) letter intervention on patients with multisomatoform disorder (MSD) and analysis of patient factors that affect the response to the intervention. METHODS: One hundred eighty-eight patients from 3 family practices, identified through screening of 2,902 consecutive patients, were classified using somatization diagnoses based on the number of unexplained physical symptoms from a standardized mental health interview. In a controlled, single-crossover trial, patients were randomized to have their primary care physician receive the CR letter either immediately following enrollment or 12 months after enrollment. The CR letter notified the physician of the patient's somatization status and provided recommendations for the patient's care. Patients were followed for 24 months with assessments of functional status at baseline, 12, and 24 months. RESULTS: Longitudinal analysis revealed a 12-month intervention effect for patients with multisomatoform disorder (MSD) of 5.5 points (P < .001) on the physical functioning (PCS) scale of the SF-36. Analysis of scores on the MCS scale of the SF-36 found no significant effect on mental functioning. The intervention was more effective for patients with 1 or more comorbid chronic physical diseases (P = .01). CONCLUSIONS: The CR letter has a favorable impact on physical impairment of primary care patients with MSD, especially for patients with comorbid chronic physical disease. Multisomatoform disorder appears to be a useful diagnostic classification for managing and studying somatization in primary care patients.

Alabama↗

PubMed2001

Mitochondrial versus nuclear gene sequences in deep-level mammalian phylogeny reconstruction.

Both mitochondrial and nuclear gene sequences have been employed in efforts to reconstruct deep-level phylogenetic relationships. A fundamental question in molecular systematics concerns the efficacy of different types of sequences in recovering clades at different taxonomic levels. We compared the performance of four mitochondrial data sets (cytochrome b, cytochrome oxidase II, NADH dehydrogenase subunit I, 12S rRNA-tRNA-16S rRNA) and eight nuclear data sets (exonic regions of alpha-2B adrenergic receptor, aquaporin, ss-casein, gamma-fibrinogen, interphotoreceptor retinoid binding protein, kappa-casein, protamine, von Willebrand Factor) in recovering deep-level mammalian clades. We employed parsimony and minimum-evolution with a variety of distance corrections for superimposed substitutions. In 32 different pairwise comparisons between these mitochondrial and nuclear data sets, we used the maximum set of overlapping taxa. In each case, the variable-length bootstrap was used to resample at the size of the smaller data set. The nuclear exons consistently performed better than mitochondrial protein and rRNA-tRNA coding genes on a per-residue basis in recovering benchmark clades. We also concatenated nuclear genes for overlapping taxa and made comparisons with concatenated mitochondrial protein-coding genes from complete mitochondrial genomes. The variable-length bootstrap was used to score the recovery of benchmark clades as a function of the number of resampled base pairs. In every case, the nuclear concatenations were more efficient than the mitochondrial concatenations in recovering benchmark clades. Among genes included in our study, the nuclear genes were much less affected by superimposed substitutions. Nuclear genes having appropriate rates of substitution should receive strong consideration in efforts to reconstruct deep-level phylogenetic relationships.

Animals↗

PubMedDate not supplied

A new model for category-scaling data with an application to the development of health-status measures.

Category rating is used to assess patient, family-member, provider, and societal preferences for health outcomes. Often, it is of interest to compare ratings obtained from different groups. Standard methods for making comparisons, such as regressions, correlations, and multiple t-tests, do not account for the dependency among ratings. The authors propose a new model for category ratings that does consider their relative dependency. This model provides a profile of ratings for a single group and facilitates comparisons across groups. It was applied to category ratings for four levels of Bending and Lifting function as defined by the recently developed Functional Capacity Index (FCI). Differences in ratings were observed across groups with different personal experiences of functional limitations and across groups with different degrees of clinical knowledge. These differences were not observed when standard methods were used. Thus, ignoring the relative nature of category ratings can lead to different conclusions about group preferences for health outcomes. When the ratings are being used to scale a health-status measure, this discrepancy has implications for the application of the measure in resource allocation.

Activities of Daily Living↗

PubMed2004

Structural characterization of genomes by large scale sequence-structure threading: application of reliability analysis in structural genomics.

BACKGROUND: We establish that the occurrence of protein folds among genomes can be accurately described with a Weibull function. Systems which exhibit Weibull character can be interpreted with reliability theory commonly used in engineering analysis. For instance, Weibull distributions are widely used in reliability, maintainability and safety work to model time-to-failure of mechanical devices, mechanisms, building constructions and equipment. RESULTS: We have found that the Weibull function describes protein fold distribution within and among genomes more accurately than conventional power functions which have been used in a number of structural genomic studies reported to date. It has also been found that the Weibull reliability parameter beta for protein fold distributions varies between genomes and may reflect differences in rates of gene duplication in evolutionary history of organisms. CONCLUSIONS: The results of this work demonstrate that reliability analysis can provide useful insights and testable predictions in the fields of comparative and structural genomics.

Computational Biology↗

PubMed1998

Probabilistic analysis of functional magnetic resonance imaging data.

Probability theory is applied to the analysis of fMRI data. The posterior distribution of the parameters is shown to incorporate all the information available from the data, the hypotheses, and the prior information. Under appropriate simplifying conditions, the theory reduces to the standard statistical test, including the general linear model. The theory is particularly suited to handle the spatial variations in the noise present in fMRI, allowing the comparison of activated voxels that have different, and unknown, noise. The theory also explicitly includes prior information, which is shown to be critical in the attainment of reliable activation maps.

Humans↗

PubMed2006

Statistical inference in a stochastic epidemic SEIR model with control intervention: Ebola as a case study.

A stochastic discrete-time susceptible-exposed-infectious-recovered (SEIR) model for infectious diseases is developed with the aim of estimating parameters from daily incidence and mortality time series for an outbreak of Ebola in the Democratic Republic of Congo in 1995. The incidence time series exhibit many low integers as well as zero counts requiring an intrinsically stochastic modeling approach. In order to capture the stochastic nature of the transitions between the compartmental populations in such a model we specify appropriate conditional binomial distributions. In addition, a relatively simple temporally varying transmission rate function is introduced that allows for the effect of control interventions. We develop Markov chain Monte Carlo methods for inference that are used to explore the posterior distribution of the parameters. The algorithm is further extended to integrate numerically over state variables of the model, which are unobserved. This provides a realistic stochastic model that can be used by epidemiologists to study the dynamics of the disease and the effect of control interventions.

Algorithms↗

PubMed1998

Customer satisfaction and self-reported treatment outcomes among psychiatric inpatients.

OBJECTIVE: Relationships among different dimensions of patient satisfaction and selected demographic, clinical, and outcome variables were explored in a sample of severely ill people receiving inpatient psychiatric services. METHOD: The sample consisted of 81 patients admitted to and discharged from an inpatient psychiatric unit at a midwestern Veterans Affairs medical center. Stepwise multiple regression was used to examine the relationship between patient satisfaction and self-reported changes in quality of life, symptomatology, and level of functioning as measured by the Treatment Outcome Profile. Other variables such as diagnosis, length of stay, employment, living situation, and prior psychiatric and substance abuse treatment were also considered. A subsample of the most satisfied and dissatisfied patients was chosen to further explore variables contributing to satisfaction with services. RESULTS: Patient satisfaction was related to initial level of functioning, certain diagnoses, and treatment gains. Clinicians were highly accurate in identifying patients who were satisfied, based on blind chart reviews. CONCLUSIONS: This study underscores the significant relationships between patient satisfaction, psychiatric diagnosis, and other outcome measures, and argues for the validity and utility of patient satisfaction measures in assessing the efficacy of inpatient care.

Attitude to Health↗

PubMed2003

A social network analysis of communication about hereditary nonpolyposis colorectal cancer genetic testing and family functioning.

Hereditary cancers are relational diseases. A primary focus of research in the past has been the biological relations that exist within the families and how genes are passed along family lines. However, hereditary cancers are relational in a psychosocial sense, as well. They can impact communication relationships within a family, as well as support relationships among family members. Furthermore, the familial culture can affect an individual's participation in genetic counseling and testing endeavors. Our aims are (a) to describe the composition of familial networks, (b) to characterize the patterns of family functioning within families, (c) to analyze how these patterns relate to communications about genetic counseling and testing among family members, and (d) to identify influential family members. Specifically, we asked how the relationship between mutation status, kinship ties, and family functioning constructs, e.g., communication, cohesion, affective involvement, leadership, and conflict, was associated with discussions about genetic counseling and testing. We used social network analysis and random graph techniques to examine 783 dyadic relationships in 36 members of 5 hereditary nonpolyposis colorectal cancer (HNPCC) families interviewed from 1999-2000. Results suggest that in these five HNPCC families, two family members are more likely to discuss genetic counseling and testing if either one carries the mutation, if either one is a spouse or a first-degree relative of the other, or if the relationship is defined by positive cohesion, leadership, or lack of conflict. Furthermore, the family functioning patterns suggest that mothers tend to be the most influential persons in the family network. Results of this study suggest encouraging family members who act in the mother role to take a "team approach" with the family proband when discussing HNPCC risks and management with family members.

Adult↗

PubMed1995

Gaussian models for degradation processes-Part I: Methods for the analysis of biomarker data.

We present two stochastic models that describe the relationship between biomarker process values at random time points, event times, and a vector of covariates. In both models the biomarker processes are degradation processes that represent the decay of systems over time. In the first model the biomarker process is a Wiener process whose drift is a function of the covariate vector. In the second model the biomarker process is taken to be the difference between a stationary Gaussian process and a time drift whose drift parameter is a function of the covariates. For both models we present statistical methods for estimation of the regression coefficients. The first model is useful for predicting the residual time from study entry to the time a critical boundary is reached while the second model is useful for predicting the latency time from the infection until the time the presence of the infection is detected. We present our methods principally in the context of conducting inference in a population of HIV infected individuals.

Biomarkers↗

PubMed1996

Sequence of a malic enzyme gene of Giardia lamblia.

The nucleotide sequence and predicted amino acid sequence of malate dehydrogenase (decarboxylating) or malic enzyme (EC 1.1.1.40) of the amitochondriate protist Giardia lamblia were determined. The overall amino acid identity with malic enzyme sequences from other eukaryotes was between 34 and 39%. Functional domains previously defined in other malic enzymes, the malate-, the ADP- and the NAD(P)-binding domains, were present also in the G. lamblia sequence. In phylogenetic reconstructions, the G. lamblia sequence is part of the eukaryotic clade, but its relative position versus the other early branches of the eukaryotic tree (Trichomonas vaginalis hydrogenosome and plant mitochondria) cannot be firmly established. The results indicate, however, a long, independent evolutionary past of this enzyme.

Amino Acid Sequence↗

PubMed2006

Assessing 1-h plasma glucose and shape of the glucose curve during oral glucose tolerance test.

OBJECTIVE: To assess the cutoff values at different time points for impaired glucose regulation (IGR) and diabetes, the glucose curve and isolated 1-h hyperglycemia were monitored during an oral glucose tolerance test (OGTT). METHODS: Two thousand eight hundred and eighty-six subjects (1300 men and 1586 women) were recruited to have an OGTT. Plasma was collected at 0, 30, 60, 120, and 180 min to analyze glucose and insulin. The diagnosis of impaired fasting glucose, impaired glucose tolerance, and diabetes was based on World Health Organization and American Diabetes Association's criteria. Those with fasting plasma glucose (FPG) < 5.6 and 2-h plasma glucose (PG) < 7.8, but 1-h PG > or = 7.8 and < 11.1 mmol/l were defined as 1h-High7.8, and those with FPG < 7.0 and 2-h PG < 11.1, but 1-h PG > or =11.1 mmol/l as 1h-High11.1. The cutoff values were calculated by receiver operating characteristic (ROC) curve. The correlation between beta-cell function and the area under the curve of glucose (AUCg) and the shape index was analyzed with linear regression. RESULTS: The cutoff values for IGR were 5.6, 9.7, 10.1, 7.8 and 6.1 mmol/l for blood glucose at 0, 30, 60, 120 and 180 min, 24 for AUCg and 1.3 mmol/l for the shape index. The cutoff values for diabetes were 6.8, 11.2, 13, 11.1 and 7 mmol/l for 0, 30, 60, 120 and 180 min, 30.9 for AUCg and 2 mmol/l for the shape index. Both AUCg and the shape index were inversely related to beta-cell function. The profiles of glucose and insulin in the subgroup with isolated 1-h hyperglycemia were very different from those seen in subjects with normal glucose tolerance or IGR. CONCLUSIONS: The present study provides new information on measures other than the fasting and 2-h PG to evaluate glucose metabolism in vivo and stimulates further research aimed at assessing the value of the OGTT 1-h PG concentration prospectively.

Adult↗

PubMed1998

Phylogenetic inference in protein superfamilies: analysis of SH2 domains.

This work focuses on the inference of evolutionary relationships in protein superfamilies, and the uses of these relationships to identify key positions in the structure, to infer attributes on the basis of evolutionary distance, and to identify potential errors in sequence annotations. Relative entropy, a distance metric from information theory, is used in combination with Dirichlet mixture priors to estimate a phylogenetic tree for a set of proteins. This method infers key structural or functional positions in the molecule, and guides the tree topology to preserve these important positions within subtrees. Minimum-description-length principles are used to determine a cut of the tree into subtrees, to identify the subfamilies in the data. This method is demonstrated on SH2-domain containing proteins, resulting in a new subfamily assignment for Src2-drome and a suggested evolutionary relationship between Nck_human and Drk_drome, Sem5_caeel, Grb2_human and Grb2_chick.

Amino Acid Sequence↗

PubMed2005

A semi-Markov model based on generalized Weibull distribution with an illustration for HIV disease.

Multi-state stochastic models are useful tools for studying complex dynamics such as chronic diseases. Semi-Markov models explicitly define distributions of waiting times, giving an extension of continuous time and homogeneous Markov models based implicitly on exponential distributions. This paper develops a parametric model adapted to complex medical processes. (i) We introduced a hazard function of waiting times with a U or inverse U shape. (ii) These distributions were specifically selected for each transition. (iii) The vector of covariates was also selected for each transition. We applied this method to the evolution of HIV infected patients. We used a sample of 1244 patients followed up at the hospital in Nice, France.

Adult↗

PubMed2001

Measuring the genetic influence in modulating the human life span: gene-environment interaction and the sex-specific genetic effect.

New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene-environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic and demographic information in the estimation of the genetic influence on life spans. Based on Cox's proportional hazard assumption, the model measures the risks for each gene as well as for gene-environment and gene-sex interactions, while controlling for confounding factors. A two-step MLE is introduced to obtain a non-parametric form of the baseline hazard function. The model is applied to genotypic data from Italian centenarian studies to estimate relative risks of candidate genes, risks due to interactions and initial frequencies of different genes in the population. Results from models that either do or do not take into consideration individual heterogeneity are compared. It is shown that ignoring the existence of heterogeneity can lead to a systematic underestimation of genetic effects and effects due to interactions.

Alleles↗

PubMed2003

Highly heterogeneous rates of evolution in the SKP1 gene family in plants and animals: functional and evolutionary implications.

Skp1 (S-phase kinase-associated protein 1) is a core component of SCF ubiquitin ligases and mediates protein degradation, thereby regulating eukaryotic fundamental processes such as cell cycle progression, transcriptional regulation, and signal transduction. Among the four components of the SCF complexes, Rbx1 and Cullin form a core catalytic complex, an F-box protein acts as a receptor for target proteins, and Skp1 is an adaptor between one of the variable F-box proteins and Cullin. Whereas protists, fungi, and some vertebrates have a single SKP1 gene, many animal and plant species possess multiple SKP1 homologs. It has been shown that the same Skp1 homolog can interact with two or more F-box proteins, and different Skp1 homologs from the same species sometimes can interact with the same F-box protein. In this paper, we demonstrate that multiple Skp1 homologs from the same species have evolved at highly heterogeneous rates. Parametric bootstrap analyses suggested that the differences in evolutionary rate are so large that true phylogenies were not recoverable from the full data set. Only when the original data set were partitioned into sets of genes with slow, medium, and rapid rates of evolution and analyzed separately, better-resolved relationships were observed. The slowly evolving Skp1 homologs, which are relatively highly conserved in sequence and expressed widely and/or at high levels, usually have very low d(N)/d(S) values, suggesting that they have evolved under functional constraint and serve the most fundamental function(s). On the other hand, the rapidly evolving members are structurally more diverse and usually have limited expression patterns and higher d(N)/d(S) values, suggesting that they may have evolved under relaxed or altered constraint, or even under positive selection. Some rapidly evolving members may have lost their original function(s) and/or acquired new function(s) or become pseudogenes, as suggested by their expression patterns, d(N)/d(S) values, and amino acid changes at key positions. In addition, our analyses revealed several monophyletic groups within the SKP1 gene family, one for each of protists, fungi, animals, and plants, as well as nematodes, arthropods, and angiosperms, suggesting that the extant SKP1 genes within each of these eukaryote groups shared only one common ancestor.

Amino Acid Sequence↗

PubMed2006

Concentration maximization and local basis expansions (LBEX) for linear inverse problems.

Linear inverse problems arise in biomedicine electroencephalography and magnetoencephalography (EEG and MEG) and geophysics. The kernels relating sensors to the unknown sources are Green's functions of some partial differential equation. This knowledge is obscured when treating the discretized kernels simply as matrices. Consequently, physical understanding of the fundamental resolution limits has been lacking. We relate the inverse problem to spatial Fourier analysis, and the resolution limits to uncertainty principles, providing conceptual links to underlying physics. Motivated by the spectral concentration problem and multitaper spectral analysis, our approach constructs local basis sets using maximally concentrated linear combinations of the measurement kernels.

Algorithms↗

PubMed2003

Inferring nonneutral evolution from human-chimp-mouse orthologous gene trios.

Even though human and chimpanzee gene sequences are nearly 99% identical, sequence comparisons can nevertheless be highly informative in identifying biologically important changes that have occurred since our ancestral lineages diverged. We analyzed alignments of 7645 chimpanzee gene sequences to their human and mouse orthologs. These three-species sequence alignments allowed us to identify genes undergoing natural selection along the human and chimp lineage by fitting models that include parameters specifying rates of synonymous and nonsynonymous nucleotide substitution. This evolutionary approach revealed an informative set of genes with significantly different patterns of substitution on the human lineage compared with the chimpanzee and mouse lineages. Partitions of genes into inferred biological classes identified accelerated evolution in several functional classes, including olfaction and nuclear transport. In addition to suggesting adaptive physiological differences between chimps and humans, human-accelerated genes are significantly more likely to underlie major known Mendelian disorders.

Active Transport, Cell Nucleus↗

PubMed2003

Exposure to traumatic events and experiences: aetiological relationships with personality function.

Empirical research has shown that the odds of experiencing traumatic events are influenced by genetic factors and the heritability of trauma exposure varies with the type of trauma. Traumatic events per se are unlikely to be heritable; more likely to be inherited are factors such as personality that influence the person's risk for entering into, or creating, potentially hazardous situations. With data from 406 twin pairs (222 monozygotic and 184 dizygotic twin pairs) from the urban general population, the present study used multiple regression analysis to identify personality variables associated with exposure to trauma, and estimated the degree to which these relationships were mediated by genetic factors. The experience of violent assaultive traumatic events was predicted by antisocial personality traits, specifically juvenile antisocial behavior, self-harming behavior, Psychoticism (e.g. adult antisocial behavior and substance misuse), and being open to new ideas and experiences. Genetic factors were found to partially mediate these relationships as indexed by the genetic correlation coefficient. The values of the genetic correlations were statistically significant and ranged from 0.14 to 0.36, accounting for 5-11% of the observed correlation between personality and trauma exposure. These findings suggest that heritable personality characteristics explain part of the variance in the likelihood of exposure to some classes of traumatic events.

Adolescent↗