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PubMed2003

Characterization and propagation of uncertainty in diffusion-weighted MR imaging.

A fully probabilistic framework is presented for estimating local probability density functions on parameters of interest in a model of diffusion. This technique is applied to the estimation of parameters in the diffusion tensor model, and also to a simple partial volume model of diffusion. In both cases the parameters of interest include parameters defining local fiber direction. A technique is then presented for using these density functions to estimate global connectivity (i.e., the probability of the existence of a connection through the data field, between any two distant points), allowing for the quantification of belief in tractography results. This technique is then applied to the estimation of the cortical connectivity of the human thalamus. The resulting connectivity distributions correspond well with predictions from invasive tracer methods in nonhuman primate.

Algorithms↗
PubMed2006

Assessing genetic diversity and population structure in a citrus germplasm collection utilizing simple sequence repeat markers (SSRs).

Twenty-four simple sequence repeat (SSR) markers were used to detect molecular polymorphisms among 370 mostly sexually derived Citrus accessions from the collection of citrus germplasm maintained at the University of California, Riverside. A total of 275 alleles were detected with an average of 11.5 alleles per locus and an average polymorphism information content of 0.625. Genetic diversity statistics were calculated for each individual SSR marker, the entire population, and for specified Citrus groups. Phylogenetic relationships among all citrus accessions and putative non-hybrid Citrus accessions were determined by constructing neighbor-joining trees. There was strong support for monophyly at the species level when hybrid taxa were removed from the data set. Both of these trees indicate that Fortunella clusters within the genus Citrus but Poncirus is a sister genus to Citrus. Additionally, Citrus accessions were probabilistically assigned to populations or multiple populations if their genotype indicated an admixture by a model-based clustering approach. This approach identified five populations in this data set. These separate analyses (distance and model based) both support the hypothesis that there are only a few naturally occurring species of Citrus and most other types of Citrus arose through various hybridization events between these naturally occurring forms.

Alleles↗
PubMed2005

A pharmacoeconomic evaluation of escitalopram versus citalopram in the treatment of severe depression in the United Kingdom.

BACKGROUND: Severe depression can increase the risk of psychiatric hospitalization, as well as inpatient and outpatient care; it may also lead to long-term absenteeism from work. However, the cost-effectiveness of antidepressant therapy for severe depression has been little studied. OBJECTIVE: The aim of this work was to investigate the cost-effectiveness of escitalopram compared with citalopram in patients with severe depression (Montgomery-Asberg Depression Rating Scale [MADRS] total score > or = 30) in the United Kingdom. METHODS: A probabilistic decision tree with a 6-month time horizon was adapted to the UK setting. The model incorporated clinical data, resource use directly related with care of severe depression, and lost productivity costs due to absenteeism. Primary results were remission (MADRS < or = 12) and costs (in year-2003 British pounds [1.00 British pound = 0.62 US dollars in January 2003]) of treatment calculated from the perspectives of UK society and the National Health Service (NHS). Secondary outcome was first-line success of treatment (ie, remission [MADRS < or = 12] without switch of drug). Remission, discontinuation, and response rates were derived from a meta-analysis of 506 patients with severe depression and extrapolated to 6 months. Standard UK price lists and literature were used to identify costs of resources. Societal costs of lost productivity were calculated using the human capital approach. RESULTS: Treatment of patients with escitalopram instead of citalopram rendered a higher overall remission rate (relative difference, 10.3%) and first-line success rate (relative difference, 35.4%). The mean cost per successfully treated patient was 15.7% (146 British pounds) lower for escitalopram (786 British pounds [range, 702-876 British pounds]) compared with citalopram (932 British pounds [range, 843-1028 British pounds]) from the NHS perspective and 15.6% (238 British pounds) lower for escitalopram (1283 British pounds [range, 1157-1419 British pounds]) than for citalopram (1521 British pounds [range, 1383-1675 British pounds]) from the societal perspective. The mean cost per severely depressed patient treated (overall study group) was 32 British pounds lower for escitalopram (422 British pounds [range, 404-441 British pounds]) than citalopram (454 British pounds [range, 436-471 British pounds]) from an NHS perspective and 50 British pounds lower for escitalopram (690 British pounds [range, 665-714 British pounds]) than citalopram (740 British pounds [range, 715-767 British pounds]) from the societal perspective. Using multivariate sensitivity analyses, we found that, in 99.8% of the cases, escitalopram was dominant from both perspectives at all ranges of probabilities tested. A sensitivity analysis on the acquisition cost of citalopram verified that, from the societal perspective, escitalopram remained the dominant strategy, even at a cost of 0.00 British pounds for citalopram. CONCLUSIONS: These results suggest that escitalopram is a cost-saving alternative to citalopram for the treatment of severe depression in the United Kingdom from the perspectives of both the NHS and society. Therefore, a possible advantage may exist at the population level in the treatment of severe depression with escitalopram in the United Kingdom.

Antidepressive Agents, Second-Generation↗
PubMed2003

Quantum-like formalism for cognitive measurements.

We develop a quantum formalism (Hilbert space probabilistic calculus) for measurements performed over cognitive systems. In particular, this formalism is used for mathematical modelling of the functioning of consciousness as a self-measuring quantum-like system. By using this formalism, we could predict averages of cognitive observables. Reflecting the basic idea of neurophysiological and psychological studies on a hierarchic structure of cognitive processes, we use p-adic hierarchic trees as a mathematical model of a mental space. We also briefly discuss the general problem of the choice of an adequate mental geometry.

Cognition↗
PubMed2004

The advantage of timely intervention.

Can people learn causal structure more effectively through intervention rather than observation? Four studies used a trial-based learning paradigm in which participants obtained probabilistic data about a causal chain through either observation or intervention and then selected the causal model most likely to have generated the data. Experiment 1 demonstrated that interveners made more correct model choices than did observers, and Experiments 2 and 3 ruled out explanations for this advantage in terms of informational differences between the 2 conditions. Experiment 4 tested the hypothesis that the advantage was driven by a temporal signal; interveners may exploit the cue that their interventions are the most likely causes of any subsequent changes. Results supported this temporal cue hypothesis.

Cues↗
PubMed2003

Design, development and validation of software for modelling dietary exposure to food chemicals and nutrients.

The Monte Carlo computational system for stochastic modelling of dietary exposure to food chemicals and nutrients is presented. This system was developed through a European Commission-funded research project. It is accessible as a Web-based application service. The system allows and supports very significant complexity in the data sets used as the model input, but provides a simple, general purpose, linear kernel for model evaluation. Specific features of the system include the ability to enter (arbitrarily) complex mathematical or probabilistic expressions at each and every input data field, automatic bootstrapping on subjects and on subject food intake diaries, and custom kernels to apply brand information such as market share and loyalty to the calculation of food and chemical intake.

Diet↗
PubMed2006

Automated extraction of fine features of kinetochore microtubules and plus-ends from electron tomography volume.

Kinetochore microtubules (KMTs) and the associated plus-ends have been areas of intense investigation in both cell biology and molecular medicine. Though electron tomography opens up new possibilities in understanding their function by imaging their high-resolution structures, the interpretation of the acquired data remains an obstacle because of the complex and cluttered cellular environment. As a result, practical segmentation of the electron tomography data has been dominated by manual operation, which is time consuming and subjective. In this paper, we propose a model-based automated approach to extracting KMTs and the associated plus-ends with a coarse-to-fine scale scheme consisting of volume preprocessing, microtubule segmentation and plus-end tracing. In volume preprocessing, we first apply an anisotropic invariant wavelet transform and a tube-enhancing filter to enhance the microtubules at coarse level for localization. This is followed with a surface-enhancing filter to accentuate the fine microtubule boundary features. The microtubule body is then segmented using a modified active shape model method. Starting from the segmented microtubule body, the plus-ends are extracted with a probabilistic tracing method improved with rectangular window based feature detection and the integration of multiple cues. Experimental results demonstrate that our automated method produces results comparable to manual segmentation but using only a fraction of the manual segmentation time.

Algorithms↗
PubMedDate not supplied

Use of a probabilistic neural network to estimate the risk of mortality after cardiac surgery.

OBJECTIVE: To develop a probabilistic neural network (PNN) to estimate mortality risk following cardiac surgery. DESIGN AND SETTING: The PNN model was created using an institutional database obtained as part of routine quality assurance activity. Patient records (from 1991 to 1993) were randomly divided into training (n = 732) and validation (n = 380) sets. The model uses seven variables, each obtainable during routine clinical patient care. After completion of the initial validation phase, newer data (1994) became available and were used as an independent source of validation (n = 365). PATIENTS: 1,477 consecutive cardiac surgery patients operated on in a teaching hospital during a four-year period (1991-94). RESULTS: The overall accuracy of the neural network was 91.5% in the training set; it was 92.3% in the validation set. The model was well calibrated (p = 0.21 for the Hosmer-Lemeshow goodness-of-fit test) and discriminated well (areas under the ROC curves were 0.72 and 0.81 for the training and validation sets). The trained network also performed well on the 1994 data (ROC = 0.74, p = 0.19 for the Hosmer-Lemeshow test), albeit with a slight decrement in overall accuracy (88.2%). CONCLUSION: A neural network may be implemented to estimate mortality risk following cardiac surgery. Implementation is relatively rapid, and it is an alternative to standard statistical approaches.

Adult↗
PubMed2004

If I were Dean: a challenge to new medical students.

If I were Dean I would welcome new students by explaining that they will be trained to become humane, compassionate scientists, and that our medical sciences are based on classical Greek science and medicine, with its first aphorism "Life is short, but art and skill are long." Science involves the conception and construction of refutable hypotheses, and their testing by repeatable experiments, followed by publication of the results. Thus, science is uncertain, tentative, probabilistic and universal. Our students will learn compassion both from our bioethicists and from faculty role models. I would warn the students that, unfortunately, much of the general public has little understanding of science, does not accept our medical model, and is increasingly seeking alternative, pre-scientific, non-scientific and even pseudo-scientific models of care, not necessarily from lack of intelligence, but perhaps more from scientific illiteracy and innumeracy. And the public fruitlessly demands safe and effective drugs, free from side effects, for all ailments, but they often fail to take drugs when prescribed, and/or take alternative medicines instead.

Empathy↗
PubMedDate not supplied

The power of focused tests to detect disease clustering.

Statistical tests have been proposed for determining whether incident cases of adverse health effects are 'clustered' together. Several procedures, termed 'focused', specifically analyse disease surveillance data around pre-specified putative sources of environmental hazard. Little has been done to compare the performance of various proposed methods on actual models of clustering. Analytic power functions are derived for three tests of focused clustering. These functions are based on the probabilistic structure of the clustering tests and do not require simulation. The three tests are compared with respect to statistical power on hypothetical data where monotone multiplicative increases in disease risk near a putative hazard define disease clusters of varying intensity.

Cluster Analysis↗
PubMed2006

Probabilistic dietary exposure assessment taking into account variability in both amount and frequency of consumption.

Probabilistic dietary exposure assessments that are fully based on Monte Carlo sampling from the raw intake data may not be appropriate. This paper shows that the data should first be analysed by using a statistical model that is able to take the various dimensions of food consumption patterns into account. A (parametric) model is discussed that takes into account the interindividual variation in (daily) consumption frequencies, as well as in amounts consumed. Further, the model can be used to include covariates, such as age, sex, or other individual attributes. Some illustrative examples show how this model may be used to estimate the probability of exceeding an (acute or chronic) exposure limit. These results are compared with the results based on directly counting the fraction of observed intakes exceeding the limit value. This comparison shows that the latter method is not adequate, in particular for the acute exposure situation. A two-step approach for probabilistic (acute) exposure assessment is proposed: first analyse the consumption data by a (parametric) statistical model as discussed in this paper, and then use Monte Carlo techniques for combining the variation in concentrations with the variation in consumption (by sampling from the statistical model). This approach results in an estimate of the fraction of the population as a function of the fraction of days at which the exposure limit is exceeded by the individual.

Adolescent↗
PubMed2026

transfactor: transcription factor activity estimation via probabilistic gene expression deconvolution.

Gene expression is a primary modality being studied to differentiate between biological cells. Contemporary single-cell studies simultaneously measure genome-wide transcription levels for thousands of individual cells in a single experiment. While the characterization of cell population differences has often occurred through differential gene expression analysis, tiny effect sizes become statistically significant when thousands of cells are available for each population, compromising biological interpretation. Moreover, these large studies have spurred the development of methods to infer gene regulatory networks (GRNs) directly from the data, and GRN databases are becoming more comprehensive. In this work, we propose a statistical model for gene expression measures and an inference method that leverage GRNs to deconvolve transcription factor (TF) activity from gene expression, by probabilistically assigning mRNA molecules to TFs. This shifts the paradigm from investigating gene expression differences to regulatory differences at the level of TF activity, aiding interpretation and allowing prioritization of a limited number of TFs responsible for significant contributions to the observed gene expression differences. The inferred TF activities result in intuitive prioritization of TFs in terms of the (difference in) estimated number of molecules they produce, in contrast to other widely used methods relying on arbitrary enrichment scores. Our model allows the incorporation of prior information on the regulatory potential between each TF and target gene and is able to deal with both repressing and activating interactions. We compare our approach to other TF activity estimation methods using two simulation experiments and two case studies. Single-cell RNA-sequencing; TF activity; bioinformatics; GRN.

Transcription Factors↗
PubMed2001

Probabilistic risk assessment of cotton pyrethroids: V. Combining landscape-level exposures and ecotoxicological effects data to characterize risks.

Since their introduction, synthetic pyrethroid insecticides have generated regulatory concerns regarding their toxicity to fish and aquatic invertebrates. In this paper we assess the potential for risks to aquatic ecosystems in cotton-growing areas, focusing on cypermethrin as a suitable representative of the pyrethroid class and static water bodies (ponds and lakes) as worst-case water bodies because of low levels of dilution. Reviews of cypermethrin effects under laboratory and field conditions have characterized the potential aquatic effects of the chemical. Also, a landscape-level exposure characterization has been conducted in a worst-case cotton-growing county, Yazoo County, Mississippi, USA, to provide a more realistic exposure characterization than is possible using standard model scenarios. Risks were characterized using the standard tier I and II approaches of the U.S. Environmental Protection Agency. In addition, a probabilistic risk assessment was conducted by comparing landscape-level exposure calculations for ponds and lakes in Yazoo County (modified tier II analysis) with distributions of laboratory effect concentrations and with data from field studies. Risk characterization using tier I and tier II models demonstrated a level of concern for certain aquatic organisms. However, modified tier II analysis showed that exposure concentrations are unlikely to exceed concentrations that might cause ecologically significant effects. Indeed, in the vast majority of cases, concentrations in the modified tier II analysis were several orders of magnitude lower than those at which effects would be predicted on the basis of laboratory and field data. The conclusion of minimal potential for adverse ecological effects was also supported by field studies, which showed that impacts on aquatic systems were negligible, even at concentrations many times higher than the modified tier II exposure concentrations.

Animals↗
PubMed2006

Impact of correlation between pesticide parameters on estimates of environmental exposure.

Monte Carlo techniques are increasingly used in pesticide exposure modelling to evaluate the uncertainty in predictions arising from uncertainty in input parameters and to estimate the confidence that should be assigned to modelling results. The approach typically involves running a deterministic model repeatedly for a large number of input values sampled from statistical distributions. A key decision in setting up a probabilistic analysis is whether there is correlation between any of the inputs to the analysis. Pesticide properties are often the most sensitive in exposure assessment. Analysis of the literature demonstrated that there are examples of both positive and negative correlation between the sorption and degradation behaviour of a pesticide, but that general trends are not apparent at present. The inclusion of even weak correlation between sorption and degradation was found to greatly influence a probabilistic analysis of leaching through soil. Correlation will reduce the predicted extent of leaching for pesticides, and it is recommended to set the correlation to zero unless the experimental data support an alternative assumption (i.e. where the correlation is statistically significant (P <or= 0.05) and experimental artefacts can be excluded).

Environmental Exposure↗
PubMed2006

Cost-effectiveness of alternative treatments for women with osteoporosis in Canada.

BACKGROUND: During the years following menopause, estrogen levels decline leading to accelerated bone loss and an increased risk of osteoporosis and osteoporosis-related fractures. METHODS: Using a Markov model and decision analytic techniques, the long-term costs and outcomes of five treatment and secondary prevention strategies for osteoporosis were compared: 'no intervention', alendronate, etidronate, risedronate, and raloxifene. The base case analysis examined postmenopausal (65 year old) osteoporotic women without prior fracture. Probabilistic sensitivity analysis (PSA) was used to incorporate the impact of parameter uncertainty, and deterministic sensitivity analysis (DSA) was used to compare alternative patient populations and modeling assumptions. Life years and Quality Adjusted Life Years (QALYs) were used as measures of effectiveness. RESULTS: In the base case analysis, risedronate was dominated by etidronate and alendronate. Alendronate and etidronate were projected to have similar costs and QALYs, and the efficiency frontier was represented by 'no intervention', etidronate, alendronate, and raloxifene (Can$32 571, Can$38 623 and Can$114 070 per QALY respectively). Alternative assumptions of raloxifene's impact on CHD and breast cancer, alternative discount rates and alternative patient risk factors (e.g., starting age of therapy, CHD risk, and prior fracture risk) had significant impacts on the overall cost-effectiveness results for both the bisphosphonates and raloxifene. DISCUSSION: Using conventionally quoted benchmarks and compared to no therapy, alendronate, etidronate, and raloxifene would all be considered cost-effective alternatives for treating women with osteoporosis. Potential limitations of this study include the usual caveats and cautions associated with long-term projection models and the fact that not all inputs into the model are Canadian data sources.

Aged↗
PubMed2002

Generalized Taylor-Aris dispersion in discrete spatially periodic networks: microfluidic applications.

A theory is presented for the lumped parameter, convective-diffusive transport of individual, noninteracting Brownian solute particles ("macromolecules") moving within spatially periodic, solvent-filled networks--the latter representing models of chip-based microfluidic chromatographic separation devices, as well as porous media. Using graph-theoretical techniques, the composite medium is conceptually decomposed into a network of channels (the edges) through which the solute is transported by a combination of molecular diffusion and either "piggyback" entrainment within a flowing solvent or an externally applied force field acting upon the solute molecules. A probabilistic choice of egress channel for a solute particle exiting the intersection (vertex) of the channels is furnished by an imperfect mixing model. A spatially periodic, Taylor-Aris-like "method-of-moments" scheme is applied to this transport model, leading to discrete matrix equations for computing the network-scale particle velocity vector U(*) and dispersivity dyadic D(*) in terms of the prescribed microscale transport parameters and network geometry characterizing the basic unit cell of which the spatially periodic device is comprised. The ensuing algebraic equations governing the vertex-based, discrete unit-cell "fields" P(0)(infinity)(i) and B(i) (i=1,2,...,n), whose paradigmatic summations yield U(*) and D(*), constitute discrete analogs of classical continuous macrotransport phenomenological parameters, P(0)(infinity)(r) and B(r), with r a continuous position vector defined within the unit cell. The ease with which these discrete calculations can be performed for complex networks renders feasible parametric studies of potential microfluidic chip designs, particularly those pertinent to biomolecular separation schemes. Application of this discrete theory to the dispersion analysis of pressure-driven flow in spatially periodic serpentine microchannels is shown to accord with existing results previously derived using classical continuous macrotransport theory.

Journal Article↗
PubMed2005

Discussion of the paper "Cost effective policies for alternative distributions of stochastic water pollution" by Gren, Destouni and Tempone.

This discussion addresses some aspects of a recent paper appearing in this journal which investigates cost effective coastal water management based on different assumptions of the probability distributions (normal and log-normal) of pollutant transport. We also suggest an alternative approach to overcome the technical problems of using the theoretical correct distribution for characterising environmental data (log-normal) within a probabilistic programming framework.

Data Interpretation, Statistical↗
PubMed1992

Schematic methods for probabilistic enzyme kinetics.

The theory of steady-state enzyme processes which avoids using the mass action law of chemical kinetics and consistently describes catalytic mechanisms by probabilistic concepts has recently been proposed (Mazur, 1991, J. theor. Biol. 148, 229-242). To facilitate the analysis of complex reaction graphs by this theory the possibility of constructing schematic rules similar to those used in classical kinetics is studied. It is found that due to the similarity of algebraic procedures the popular method of King & Altman can be applied in probabilistic kinetics in addition to the earlier proposed rule based on enumeration of cycles of the reaction graph. This similarity also allows one to adapt many other shortcut methods of classical kinetics for probabilistic reaction graphs. The paper considers separately the possibility of transforming reaction mechanisms so that the initial graph is replaced by a simpler but equivalent one. It is shown that there are few cases when a group of states can be replaced by one united state, with earlier known rules such as the rule of Cha for equilibrium stages being particular cases of a more general procedure. In addition a novel method is proposed which performs step-by-step reduction of any reaction graph. All the new methods can be adapted for traditional kinetics as well. The results obtained demonstrate that many schematic rules of classical kinetics are of probabilistic origin.

Enzymes↗