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Single patient (n-of-1) trials with binary treatment preference.

The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment 'preference' is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub-group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios.

Amitriptyline↗

Estimation of pulmonary diffusion resistance and shunt in an oxygen status model.

A compartment model of the transport of oxygen from the alveoli to the tissues is described. In patients with both pulmonary shunt and alveolar resistance to diffusion of oxygen, the model is used to simulate their response to variations in the inspired oxygen fraction. These simulation results are compared to the responses from a patient with respiratory malfunction, indicating that the method can identify patients where not only a pulmonary shunt but also a high alveolar resistance to diffusion of oxygen is clinically significant. Estimation of pulmonary shunt and oxygen diffusion resistance can be done in two different implementations of the model. In the first implementation the estimates are generated by numerical solution of the equations of the compartment model. In the second implementation the equations have been used to construct a causal probabilistic net where biological uncertainties and uncertainties in the measurements can be represented.

Airway Resistance↗

Time dependence of breakdown in a global fiber-bundle model with continuous damage.

A time-dependent global fiber-bundle model of fracture with continuous damage is formulated in terms of a set of coupled nonlinear differential equations. A first integral of this set is analytically obtained. The time evolution of the system is studied by applying a discrete probabilistic method. Several results are discussed emphasizing their differences with the standard time-dependent model. The results obtained show that with this simple model a variety of experimental observations can be qualitatively reproduced.

Journal Article↗

Delineating a recharge area for a spring using numerical modeling, Monte Carlo techniques, and geochemical investigation.

Recharge areas of spring systems can be hard to identify, but they can be critically important for protection of a spring resource. A recharge area for a spring complex in southern Wisconsin was delineated using a variety of complementary techniques. A telescopic mesh refinement (TMR) model was constructed from an existing regional-scale ground water flow model. This TMR model was formally optimized using parameter estimation techniques; the optimized "best fit" to measured heads and fluxes was obtained by using a horizontal hydraulic conductivity 200% larger than the original regional model for the upper bedrock aquifer and 80% smaller for the lower bedrock aquifer. The uncertainty in hydraulic conductivity was formally considered using a stochastic Monte Carlo approach. Two-hundred model runs used uniformly distributed, randomly sampled, horizontal hydraulic conductivity values within the range given by the TMR optimized values and the previously constructed regional model. A probability distribution of particles captured by the spring, or a "probabilistic capture zone," was calculated from the realistic Monte Carlo results (136 runs of 200). In addition to portions of the local surface watershed, the capture zone encompassed areas outside of the watershed--demonstrating that the ground watershed and surface watershed do not coincide. Analysis of water collected from the site identified relatively large contrasts in chemistry, even for springs within 15 m of one another. The differences showed a distinct gradation from Ordovician-carbonate-dominated water in western spring vents to Cambrian-sandstone-influenced water in eastern spring vents. The difference in chemistry was attributed to distinctive bedrock geology as demonstrated by overlaying the capture zone derived from numerical modeling over a bedrock geology map for the area. This finding gives additional confidence to the capture zone calculated by modeling.

Geological Phenomena↗

Transport and fate of radionuclides in aquatic environments--the use of ecosystem modelling for exposure assessments of nuclear facilities.

In safety assessments of nuclear facilities, a wide range of radioactive isotopes and their potential hazard to a large assortment of organisms and ecosystem types over long time scales need to be considered. Models used for these purposes have typically employed approaches based on generic reference organisms, stylised environments and transfer functions for biological uptake exclusively based on bioconcentration factors (BCFs). These models are of non-mechanistic nature and involve no understanding of uptake and transport processes in the environment, which is a severe limitation when assessing real ecosystems. In this paper, ecosystem models are suggested as a method to include site-specific data and to facilitate the modelling of dynamic systems. An aquatic ecosystem model for the environmental transport of radionuclides is presented and discussed. With this model, driven and constrained by site-specific carbon dynamics and three radionuclide specific mechanisms: (i) radionuclide uptake by plants, (ii) excretion by animals, and (iii) adsorption to organic surfaces, it was possible to estimate the radionuclide concentrations in all components of the modelled ecosystem with only two radionuclide specific input parameters (BCF for plants and Kd). The importance of radionuclide specific mechanisms for the exposure to organisms was examined, and probabilistic and sensitivity analyses to assess the uncertainties related to ecosystem input parameters were performed. Verification of the model suggests that this model produces analogous results to empirically derived data for more than 20 different radionuclides.

Adsorption↗

Probabilistic design analysis of the influence of material property on the human cervical spine.

Studies reported previously in the literature have described the importance of material variation on the cervical responses and have examined some effects by varying the material properties, but there is no systematic approach using statistical methods to understand the influence of material variation on a cervical spine model under a full range of loading conditions, especially under compression and anterior and posterior shear. A probabilistic design system based on Monte Carlo simulation methods using Latin hypercube sampling techniques is used to analyze the material sensitivity of a C4-C6 cervical spine model involving 13 uncertain input parameters on the biomechanical responses and disc annulus stresses under compression, anterior shear, posterior shear, flexion, extension, lateral bending, and axial rotation. The loading types and range of values were as follows: compression, 0-1 mm; anterior shear, 0-2 mm; posterior shear, 0-3.5 mm; flexion, extension, lateral bending, and axial rotation. 0-1.8 Nm with 73.6-N preload. For each case, the load-deflection and key stress values at various spinal components were captured after each load step. The model was also validated under the same conditions. The minimum and maximum predicted responses were within the range of the experimental data. Ignoring compression loading, the combined effects on the biomechanical responses of the cervical ligaments under the remaining loads are enormous. Their total impacts are almost equal to or slightly less than the influence of disc annulus. Results show that the fiber mechanical properties did not have a significant effect on the compressive stiffness. This study reveals important features that help us identify the critical input parameters and enable us to reduce the development time of a patient-specific biomechanical model.

Biomechanical Phenomena↗

[Conformation of gamma-aminobutyric acid and its receptors].

The preferable conformations of the inhibitory transmitter gamma-aminobutyric acid (GABA) and its specific inhibitor bicuculline are due to the occupation of the GABAreceptor by a part of the bicuculline molecule that is isosteric with the biologically active conformation of GABA. In the present review are described characteristics of sodium-independence receptor sites and evaluated the regional distribution of postsynaptic receptor binding for GABA in the central nervous system. The postsynaptic GABA receptor has been labeled by direct binding of 3H-GABA. The structural analogues and antagonists of GABA were investigated for inhibition of GABA binding. The developmental changes in the activity of glutamic acid decarboxylase, the GABA uptake mechanism and GABA receptor binding in embryo brain were examined. Different models for the GABA-receptor interaction are considered. Data of the stoichiometry of GABA-receptor interactions indicate that the interaction is probabilistic and that 3 molecules of GABA are needed to activate the receptor probabilistically. It was found that 1 molecule of picrotoxin was capable of blocking the interaction with 3 GABA molecules. The hypothetical model of cooperative action of GABA-recepto-inophore complexes involving membrane mobility is also discussed. The transitive complex GABA with ligand binding of Na+, Cl- and the conformational changes of GABA-receptor is proposed.

Aminobutyrates↗

Generalized Poisson distribution: the property of mixture of Poisson and comparison with negative binomial distribution.

We prove that the generalized Poisson distribution GP(theta, eta) (eta > or = 0) is a mixture of Poisson distributions; this is a new property for a distribution which is the topic of the book by Consul (1989). Because we find that the fits to count data of the generalized Poisson and negative binomial distributions are often similar, to understand their differences, we compare the probability mass functions and skewnesses of the generalized Poisson and negative binomial distributions with the first two moments fixed. They have slight differences in many situations, but their zero-inflated distributions, with masses at zero, means and variances fixed, can differ more. These probabilistic comparisons are helpful in selecting a better fitting distribution for modelling count data with long right tails. Through a real example of count data with large zero fraction, we illustrate how the generalized Poisson and negative binomial distributions as well as their zero-inflated distributions can be discriminated.

Binomial Distribution↗

A spatially-evaluated methodology for assessing risk to a population from contaminated land.

A methodology is proposed which combines quantitative probabilistic human health risk assessment and spatial statistical methods (geostatistics) to produce an assessment of risks to human health from exposure to contaminated land, in a manner which preserves the spatial distribution of risks and provides a measure of uncertainty in the assessment. Maps of soil contaminant levels, which incorporate uncertainty, are produced from sparse sample data using sequential indicator simulation. A real, age-stratified population is mapped across the contaminated area, and intake of soil contaminants by individuals is calculated probabilistically using an adaptation of the Contaminated Land Exposure Assessment (CLEA) model. An abundance of information is contained in results which can be interrogated at the population and individual level, and mapped to provide a powerful visual tool for risk managers, enabling efficient targeting of risk reduction measures to different locations.

Environmental Exposure↗

Familial sinistrality: the utility of calculating exact genotype probabilities for individuals.

Measures of familial sinistrality are frequently used in neuropsychological research. However they suffer from the problem that they are essentially a global measure of phenotypes in the family, whereas they are interpreted as an indicator of the genotype of the individual concerned. In this paper it is shown how to calculate a precise probabilistic estimate of a proband's genotype, given a particular genetic model of handedness, using all of the information available in a family tree. Example calculations are provided for a range of families with one or two sinistral relatives. Genotype probabilities are also calculated for a large population data set (the National Childhood Encephalopathy Study) and it is shown that familial sinistrality does not account for all of the variability present in the genotype probabilities, and that genotype probabilities provide an additional prediction of individual sinistrality after taking familial sinistrality into account, whereas all of the information in familial sinistrality is accounted for by the genotype probabilities. Finally it is shown how genotype probabilities can be used to assess whether there is heterozygote advantage for a characteristic, and using this method it is suggested that there is no support for heterozygotes having higher intellectual ability than homozygotes.

Family↗

Retrospective and current risks of mercury to panthers in the Florida Everglades.

Florida panthers are an endangered species inhabiting south Florida. Hg has been suggested as a causative factor for low populations and some reported panther deaths, but a quantitative assessment of risks has never been performed. This study quantitatively evaluated retrospective (pre-1992) and current (2002) risks of chronic dietary Hg exposures to panthers in the Florida Everglades. A probabilistic assessment of Hg risks was performed using a dietary exposure model and Latin Hypercube sampling that incorporated the variability and uncertainty in ingestion rate, diet, body weight, and mercury exposure of panthers. Hazard quotients (HQs) for retrospective risks ranged from less than 0.1-20, with a 46% probability of exceeding chronic dietary thresholds for methylmercury. Retrospective risks of developing clinical symptoms, including ataxia and convulsions, had an HQ range of <0.1-5.4 with a 17% probability of exceeding an HQ of 1. Current risks were substantially lower (4% probability of exceedences; HQ range <0.1-3.5) because of an estimated 70-90% decline in Hg exposure to panthers over the last decade. Under worst case conditions of panthers consuming only raccoons from the most contaminated area of the Everglades, current risks of developing clinical symptoms that may lead to death was 4.6%. Current risks of mercury poisoning of panthers with a diversified diet was 0.1% (HQ range of <0.1-1.4). The results of this assessment indicate that past Hg exposures likely adversely affected panthers in the Everglades, but current risks of Hg are low.

Animals↗

Comparative accuracy of methods for protein sequence similarity search.

MOTIVATION: Searching a protein sequence database for homologs is a powerful tool for discovering the structure and function of a sequence. Two new methods for searching sequence databases have recently been described: Probabilistic Smith-Waterman (PSW), which is based on Hidden Markov models for a single sequence using a standard scoring matrix, and a new version of BLAST (WU-BLAST2), which uses Sum statistics for gapped alignments. RESULTS: This paper compares and contrasts the effectiveness of these methods with three older methods (Smith-Waterman: SSEARCH, FASTA and BLASTP). The analysis indicates that the new methods are useful, and often offer improved accuracy. These tools are compared using a curated (by Bill Pearson) version of the annotated portion of PIR 39. Three different statistical criteria are utilized: equivalence number, minimum errors and the receiver operating characteristic. For complete-length protein query sequences from large families, PSW's accuracy is superior to that of the other methods, but its accuracy is poor when used with partial-length query sequences. False negatives are twice as common as false positives irrespective of the search methods if a family-specific threshold score that minimizes the total number of errors (i.e. the most favorable threshold score possible) is used. Thus, sensitivity, not selectivity, is the major problem. Among the analyzed methods using default parameters, the best accuracy was obtained from SSEARCH and PSW for complete-length proteins, and the two BLAST programs, plus SSEARCH, for partial-length proteins.

Databases, Factual↗

A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes.

MOTIVATION: DNA microarrays are now capable of providing genome-wide patterns of gene expression across many different conditions. The first level of analysis of these patterns requires determining whether observed differences in expression are significant or not. Current methods are unsatisfactory due to the lack of a systematic framework that can accommodate noise, variability, and low replication often typical of microarray data. RESULTS: We develop a Bayesian probabilistic framework for microarray data analysis. At the simplest level, we model log-expression values by independent normal distributions, parameterized by corresponding means and variances with hierarchical prior distributions. We derive point estimates for both parameters and hyperparameters, and regularized expressions for the variance of each gene by combining the empirical variance with a local background variance associated with neighboring genes. An additional hyperparameter, inversely related to the number of empirical observations, determines the strength of the background variance. Simulations show that these point estimates, combined with a t -test, provide a systematic inference approach that compares favorably with simple t -test or fold methods, and partly compensate for the lack of replication.

Bayes Theorem↗

Designer invariants for large phylogenies.

The Cavender-Felsenstein edge-length invariants for binary characters on 4-trees provide the starting point for the development of "customized" invariants for evaluating and comparing phylogenetic hypotheses. The binary character invariants may be generalized to k-valued characters without losing the quadratic nature of the invariants as functions of the theoretical frequencies f(UVXY) of observable character configurations (U at organism 1, V at 2, etc.). The key to the approach is that certain sets of these configurations constitute events which are probabilistically independent from other such sets, under the symmetric Markov change models studied. By introducing more complex sets of configurations, we find the quadratic invariants for 5-trees in the binary model and for individual edges in 6-trees or, indeed, in any size tree. The same technique allows us to formulate invariants for entire trees, but these are cubic functions for 6-trees and are higher-degree polynomials for larger trees. With k-valued characters and, especially, with large trees, the types of configuration sets (events) used in the simpler examples are too rare (i.e., their predicted frequencies are too low) to be useful, and the construction of meaningful pairs of independent events becomes an important and nontrivial task in designing invariants suited to testing specific hypotheses. In a very natural way, this approach fits in with well-known statistical methodology for contingency tables. We explore use of events such as "only transitions occur for character i (i.e., position i in a nucleic acid sequence) in subtree a" in analyzing a set of data on ribosomal RNA in the context of the controversy over the origins of archaebacteria, eubacteria, and eukaryotes.

Archaea↗

Phylogenetic Invariants for Metazoan Mitochondrial Genome Evolution.

The method of phylogenetic invariants was developed to apply to aligned sequence data generated, according to a stochastic substitution model, for N species related through an unknown phylogenetic tree. The invariants are functions of the probabilities of the observable N-tuples, which are identically zero, over all choices of branch length, for some trees. Evaluating the invariants associated with all possible trees, using observed N-tuple frequencies over all sequence positions, enables us to rapidly infer the generating tree. An aspect of evolution at the genomic level much studied recently is the rearrangements of gene order along the chromosome from one species to another. Instead of the substitutions responsible for sequence evolution, we examine the non-local processes responsible for genome rearrangements such as inversion of arbitrarily long segments of chromosomes. By treating the potential adjacency of each possible pair of genes as a position", an appropriate substitution" model can be recognized as governing the rearrangement process, and a probabilistically principled phylogenetic inference can be set up. We calculate the invariants for this process for N=5, and apply them to mitochondrial genome data from coelomate metazoans, showing how they resolve key aspects of branching order.

Journal Article↗