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PubMed1998

Statistical modelling and phylogenetic analysis of a deaminase domain.

Deamination reactions are catalyzed by a variety of enzymes including those involved in nucleoside/nucleotide metabolism and cytosine to uracil (C-->U) and adenosine to inosine (A-->I) mRNA editing. The active site of the deaminase (DM) domain in these enzymes contains a conserved histidine (or rarely cysteine), two cysteines and a glutamate proposed to act as a proton shuttle during deamination. Here, a statistical model, a hidden Markov model (HMM), of the DM domain has been created which identifies currently known DM domains and suggests new DM domains in viral, bacterial and eucaryotic proteins. However, no DM domains were identified in the currently predicted proteins from the archaeon Methanococcus jannaschii and possible causes for, and a potential means to ameliorate this situation are discussed. In some of the newly identified DM domains, the glutamate is changed to a residue that could not function as a proton shuttle and in one instance (Mus musculus spermatid protein TENR) the cysteines are also changed to lysine and serine. These may be non-competent DM domains able to bind but not act upon their substrate. Phylogenetic analysis using an HMM-generated alignment of DM domains reveals three branches with clear substructure in each branch. The results suggest DM domains that are candidates for yeast, platyhelminth, plant and mammalian C-->U and A-->I mRNA editing enzymes. Some bacterial and eucaryotic DM domains form distinct branches in the phylogenetic tree suggesting the existence of common, novel substrates.

Amino Acid Sequence↗
PubMed1994

Statistical models for PET and SPECT data.

This article outlines the statistical developments that have taken place in emission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data and define the additive Poisson regression model. This leads to the use of the method of maximum likelihood as a means of estimating the underlying isotope concentration within a given region of a patient's body, and to the use of the EM algorithm to compute the reconstruction. The need for the regulation of the maximum likelihood solution is tackled using Bayesian techniques. A number of algorithms for the computation of regularized solutions are outlined. The issue of parameter estimation is discussed and some open issues are mentioned.

Algorithms↗
PubMed2001

An efficient and robust statistical modeling approach to discover differentially expressed genes using genomic expression profiles.

We have developed a statistical regression modeling approach to discover genes that are differentially expressed between two predefined sample groups in DNA microarray experiments. Our model is based on well-defined assumptions, uses rigorous and well-characterized statistical measures, and accounts for the heterogeneity and genomic complexity of the data. In contrast to cluster analysis, which attempts to define groups of genes and/or samples that share common overall expression profiles, our modeling approach uses known sample group membership to focus on expression profiles of individual genes in a sensitive and robust manner. Further, this approach can be used to test statistical hypotheses about gene expression. To demonstrate this methodology, we compared the expression profiles of 11 acute myeloid leukemia (AML) and 27 acute lymphoblastic leukemia (ALL) samples from a previous study (Golub et al. 1999) and found 141 genes differentially expressed between AML and ALL with a 1% significance at the genomic level. Using this modeling approach to compare different sample groups within the AML samples, we identified a group of genes whose expression profiles correlated with that of thrombopoietin and found that genes whose expression associated with AML treatment outcome lie in recurrent chromosomal locations. Our results are compared with those obtained using t-tests or Wilcoxon rank sum statistics.

Acute Disease↗
PubMed2004

Mixed-model statistical analysis of fuel, equipment, mileage, and driving schedule effects on particulate matter emissions from heavy diesel-powered vehicles.

An extensive experimental program has been conducted to evaluate the comparative effects of California Air Resources Board diesel fuel and an ultra-low-sulfur (S) diesel (with and without aftermarket passive filtering devices) on mass emissions of particulate matter (PM) in heavy vehicles. Tests have been performed on 20 Class 8 trucks at two high-mileage levels using two different driving schedules. The design of the test program facilitates the use of mixed-model statistical analysis, which allows more appropriate treatment of the explanatory variables than normally achieved. The analysis suggests that the ultra-low-S diesel fuel yields extremely low mean PM emissions when used in conjunction with a particulate filter, even at high mileage, but that the estimates are highly variable. The high degree of uncertainty, caused at least in part by large vehicle-to-vehicle variation, may obscure the true PM response and adversely impact attainment of increasingly more stringent diesel PM emissions standards in the United States.

Air Pollutants↗
PubMed2004

PCR-probe capture hybridization assay and statistical model for SEN virus prevalence estimation.

SEN viruses (SENV) are newly discovered blood-borne single-stranded circular DNA viruses that may play a role in liver disease. To date, no serologic assays are available for the detection of SENV antigens or antibodies. We report on a rapid and sensitive molecular assay for the detection of four SENV strains (SENV-A, -C, -D, -H). This method uses PCR with universal primers and microwell capture hybridization with type-specific probes. Cut-off points to define "infected" based on chemiluminescence readings were determined from a statistical mixture model applied to samples from 300 injection drug users (IDUs) in San Francisco. Based on the estimated cut-off points, we examined the prevalence of SENV infection among 232 healthy US blood donors and assessed sensitivity and specificity of the assay in a small validation sample of infected individuals with partial sequence information.

Base Sequence↗
PubMed2002

Risk factors for the formation of a steinstrasse after extracorporeal shock wave lithotripsy: a statistical model.

PURPOSE: We studied the various stone, renal and therapy factors that could affect steinstrasse formation after extracorporeal shock wave lithotripsy (ESWL), Dornier Medical Systems Inc., Marietta, Georgia to define the predictive factors for its formation. Thus, steinstrasse could be anticipated and prophylactically avoided. MATERIALS AND METHODS: Between February 1989 and May 1999, 4,634 patients were treated with a Dornier MFL 5000 lithotriptor (Dornier Med Tech, GmbH, Germany). Renal stones were encountered in 3,403 patients and ureteral stones in 1,231. Steinstrasse were recorded in 184 patients, of whom 74 required intervention and formed the "complicated group." All patient data, stone and renal characteristics, and data of ESWL were reviewed. Univariate and multivariate statistical analyses of patients, stones and therapy characteristics in correlation with the incidence of steinstrasse formation were performed to assign the factors that had a significant impact on steinstrasse formation. RESULTS: The overall incidence of steinstrasse was 3.97%. The steinstrasse was in the pelvic ureter in 74% of the cases, lumbar ureter in 21.7% and iliac ureter in 4.3%. Steinstrasse incidence significantly correlated with stone size and site, the power level (kV.) used during therapy and radiological renal features. Steinstrasse was more common with renal stones more than 2 cm. in diameter in a dilated system, especially with the use of high power (greater than 22 kV.) for disintegration. A statistical model was constructed to estimate the risk of steinstrasse formation accurately. CONCLUSIONS: Stone size and site, renal morphology and shock wave energy are the significant predictive factors controlling steinstrasse formation. If a patient has a high probability of steinstrasse formation, close followup with early intervention or prophylactic pre-ESWL ureteral stenting is indicated.

Adolescent↗
PubMed1996

Prognostic indicators for intrauterine insemination (IUI): statistical model for IUI success.

A retrospective analysis of 260 completed intrauterine insemination (IUI) cycles was used in an attempt to identify significant variables predictive of treatment success. Couples received a maximum of three IUI cycles for the treatment of anovulation, cervical factors or unexplained infertility. Male factor problems were largely excluded by pretreatment screening. The overall pregnancy rate was 19.6% per completed cycle, the miscarriage rate 15.6%, the multiple pregnancy rate 23.5% and the cancellation rate 19%. Logistic regression identified four significant IUI variables [follicle number (P < 0.005), endometrial thickness (P < 0.005), duration of infertility (P < 0.01) and progressive motility (P < 0.05)] which were the most predictive of IUI success. The chance of conceiving when only one follicle was produced was only 7.6%, whereas with two follicles this chance increased to 26%. These variables were incorporated into a statistical model to allow the prediction of the chance of success in subsequent cycles. We conclude that careful patient selection criteria coupled with successful ovarian stimulation is the model for IUI success.

Adult↗
PubMed1994

Survey of methods and statistical models used in the analysis of occupational cohort studies.

OBJECTIVES: This survey was conducted to determine the frequency with which different data analysis techniques are being used in occupational cohort studies. Of particular interest was the relative use of external and internal comparison groups, and the choice of multivariable model. METHODS: Occupational cohort studies published in 1990-91 were located with Medline and Index Medicus, and the contents of several relevant journals were systematically reviewed. Each study was categorised by the methods of external or internal comparisons performed. RESULTS: Of 200 occupational cohort studies identified, 104 (52%) conducted only external comparisons, 46 (23%) conducted only internal, and 50 (25%) presented both. Of those that used an external referent population, about two thirds used a national standard. 40 of the studies that performed internal comparisons fitted multivariable models, with use divided about equally between proportional hazards regression, Poisson regression, and logistic regression. DISCUSSION: The finding that logistic regression is used quite commonly, even though it does not directly model time dependent data of the type frequently encountered in occupational cohort studies, was suprising. The reasons why investigators choose from among the available statistical and modelling techniques are likely to include familiarity, ease of use, restrictions in study population characteristics, especially study size, and others. Authors should be encouraged to be more explicit about the statistical methods used in the analysis of occupational cohort studies, as well as whether important assumptions about their data have been evaluated.

Cohort Studies↗
PubMed1996

Fibrosis and other histological features in chronic hepatitis C virus infection: a statistical model.

AIMS: To study the inter-relation between hepatic fibrosis and other histological features of chronic hepatitis C virus (HCV) infection. METHODS: Liver biopsy specimens from 200 consecutive patients with chronic HCV infection were graded and staged separately for necro-inflammatory activity and for fibrosis. The interaction between fibrosis and other histological features was evaluated by univariate and multivariate analysis, followed by hierarchical log linear modelling. RESULTS: The most striking feature was the presence of portal tract inflammation in 177 (89%) of 200 samples. Lymphoid aggregates/follicles were observed either alone or as part of the general inflammatory infiltration of the portal tracts in 120 (60%) of 200 samples. Fatty change (macro- and microvesicular steatosis) was observed in 76 (38%) samples: mild to moderate in 60 (30%) and diffuse in 16 (8%). Bile duct damage was found in 30 (15%) of 200 specimens. Lobular activity was found in 154 (77%) of 200 samples and was significant in 44; piecemeal necrosis was present in 79 (40%). Thirty one (16%) patients had stage 0 liver fibrosis, 27 (14%) had stage 1, 69 (35%) had stage 2, 43 (22%) had stage 3, 16 (8%) had stage 4, and 12 (6%) had stage 5. On log linear analysis, piecemeal necrosis, lobular inflammation and steatosis were linked directly with fibrosis. Portal tract inflammation was linked directly and indirectly via piecemeal necrosis and lobular inflammation with fibrosis. The presence of lymphoid aggregates was associated with bile duct damage. CONCLUSIONS: Portal tract inflammation with lymphoid aggregates or follicles, together with fatty change, bile duct damage and/or lobular activity, are characteristic of chronic HCV infection, confirming previous reports. Piecemeal necrosis, lobular inflammation, portal inflammation, and steatosis are linked directly with fibrosis in this statistical model, suggesting a close inter-relation in the development of fibrosis/cirrhosis.

Adolescent↗
PubMed1998

Statistical model of the hippocampal CA3 region. I. The single-cell module: bursting model of the pyramidal cell.

A model with intermediate complexity is introduced to reproduce the basic firing modes of the CA3 pyramidal cell. Our model consists of a single compartment, has two variables (membrane potential and internal calcium concentration), and involves two separate stages for interspike mechanisms and firing. Interspike dynamics is governed by voltage- and calcium-dependent ionic channels but no channel kinetics are provided. This model is suitable to be included in our statistical population model (Part II, following paper). Bifurcation analysis reveals that interspike dynamics rather than sodium firing has the dominant role in the control of bursting/nonbursting behavior.

Action Potentials↗
PubMed1984

Statistical modelling and diagnostic aids.

This paper considers the problems involved in constructing operational aids for diagnosis. A collaborative approach is proposed which involves utilisation of the expertise of clinician and statistician, working jointly on the analysis of hard data for a particular diagnostic application. The application of this approach to a problem involving cerebral disease diagnosis based on CT scan data is described.

Bayes Theorem↗
PubMed2001

Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization.

Interferometric radar techniques often necessitate two-dimensional (2-D) phase unwrapping, defined here as the estimation of unambiguous phase data from a 2-D array known only modulo 2pi rad. We develop a maximum a posteriori probability (MAP) estimation approach for this problem, and we derive an algorithm that approximately maximizes the conditional probability of its phase-unwrapped solution given observable quantities such as wrapped phase, image intensity, and interferogram coherence. Examining topographic and differential interferometry separately, we derive simple, working models for the joint statistics of the estimated and the observed signals. We use generalized, nonlinear cost functions to reflect these probability relationships, and we employ nonlinear network-flow techniques to approximate MAP solutions. We apply our algorithm both to a topographic interferogram exhibiting rough terrain and layover and to a differential interferogram measuring the deformation from a large earthquake. The MAP solutions are complete and are more accurate than those of other tested algorithms.

Journal Article↗