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Assessment of intake from the diet.

Exposure assessment is one of the key parts of the risk assessment process. Only intake of toxicologically significant amounts can lead to adverse health effects even for a relatively toxic substance. In the case of chemicals in foods this is based on three major aspects: (i) how to determine quantitatively the presence of a chemical in individual foods and diets, including its fate during the processes within the food production chain; (ii) how to determine the consumption patterns of the individual foods containing the relevant chemicals; (iii) how to integrate both the likelihood of consumers eating large amounts of the given foods and of the relevant chemical being present in these foods at high levels. The techniques used for the evaluation of these three aspects have been critically reviewed in this paper to determine those areas where the current approaches provide a solid basis for assessments and those areas where improvements are needed or desirable. For those latter areas, options for improvements are being suggested, including, for example, the development of a pan-European food composition database, activities to understand better effects of processing on individual food chemicals, harmonisation of food consumption survey methods with the option of a regular pan-European survey, evaluation of probabilistic models and the development of models to assess exposure to food allergens. In all three areas, the limitations of the approaches currently used lead to uncertainties which can either cause an over- or underestimation of real intakes and thus risks. Given these imprecisions, risk assessors tend to build in additional uncertainty factors to avoid health-relevant underestimates. This is partly done by using screening methods designed to look for "worst case" situations. Such worse case assumptions lead to intake estimates that are higher than reality. These screening methods are used to screen all those chemicals with a safe intake distribution. For chemicals with a potential risk, more information is needed to allow more refined screening or even the most accurate estimation. More information and more refined methods however, require more resources. The ultimate aims are: (1) to obtain appropriate estimations for the presence and quantity of a given chemical in a food and in the diet in general; (2) to assess the consumption patterns for the foods containing these substances, including especially those parts of the population with high consumption and thus potentially high intakes; and (3) to develop and apply tools to predict reliably the likelihood of high end consumption with the presence of high levels of the relevant substances. It has thus been demonstrated that a tiered approach at all three steps can be helpful to optimise the use of the available resources: if relatively crude tools - designed to provide a "worst case" estimate - do not suggest a toxicologically significant exposure (or a relevant deficit of a particular nutrient) it may not be necessary to use more sophisticated tools. These will be needed if initially high intakes are indicated for at least parts of the population. Existing pragmatic approaches are a first crude step to model food chemical intake. It is recommended to extend, refine and validate this approach in the near future. This has to result in a cost-effective exposure assessment system to be used for existing and potential categories of chemicals. This system of knowledge (with information on sensitivities, accuracy, etc.) will guide future data collection.

Animals↗

DNA evidence, probabilistic evaluation and collaborative tests.

Forensic scientists working in 12 state or private laboratories participated in collaborative tests to improve the reliability of the presentation of DNA data at trial. These tests were motivated in response to the growing criticism of the power of DNA evidence. The experts' conclusions in the tests are presented and discussed in the context of the Bayesian approach to interpretation. The use of a Bayesian approach and subjective probabilities in trace evaluation permits, in an easy and intuitive manner, the integration into the decision procedure of any revision of the measure of uncertainty in the light of new information. Such an integration is especially useful with forensic evidence. Furthermore, we believe that this probabilistic model is a useful tool (a) to assist scientists in the assessment of the value of scientific evidence, (b) to help jurists in the interpretation of judicial facts and (c) to clarify the respective roles of scientists and of members of the court. Respondents to the survey were reluctant to apply this methodology in the assessment of DNA evidence.

Alleles↗

[Cost-effectiveness of colorectal cancer screening].

Colorectal cancer (CRC) screening in France is based on a faecal occult blood test every two years in average risk subjects 50-74 years of age while other endoscopic or non-endoscopic screening methods are used in Europe and in the USA. Beside the reduced incidence of and mortality from CRC found in available studies, cost-effectiveness data need to be taken into account. Because of the delay between randomized controlled trials and clinical results, transitional probabilistic models of screening programs are useful for public health policy makers. The aim of the present review was to promote the implementation of cost-effectiveness studies, to provide a guide to analyze cost-effectiveness studies on CRC screening and, to propose a French cost effectiveness study comparing CRC screening strategies. Most of these trials were performed by US or UK authors and demonstrate that the incremental cost-effectiveness ratio varies between 5 000 and 15 000 US dollars/one year life gained, with wide variations: these results were highly dependent on the unit costs of the different devices as well as the predictive values of the screening tests. Although CRC screening programs have been implemented in several administrative districts of France since 2002, and the results of these randomized controlled trials using fecal occult blood have been updated, cost-effectiveness criteria need to be integrated; especially since the results of screening campaigns based on other tools such as flexible sigmoidoscopy should be available in 2007.

Aged↗

A technique for single-channel MR brain tissue segmentation: application to a pediatric sample.

A segmentation method is presented for gray matter, white matter, and cerebrospinal fluid (CSF) in thin-sliced single-channel brain magnetic resonance (MR) scans. The method is based on probabilistic modeling of intensity distributions and on a region growing technique. Interrater and intrarater reliabilities for the method were high, and comparison with phantom studies and hand-traced results from an experienced rater indicated good validity. The method was designed to account for spatially dependent image intensity inhomogeneities. Segmentation of MR brain scans of 105 (56 male and 49 female) healthy children and adolescents showed that although the total brain volume was stable over age 4-18, white matter increased and gray matter decreased significantly. There were no sex differences in total gray and white matter growth after correction for total brain volume. White matter volume increased the most in superior and posterior regions and laterality effects were seen in hemisphere tissue volumes. These findings are consistent with other reports, and further validate the segmentation technique.

Adolescent↗

Test characteristics and decision rules.

We have demonstrated using several examples how different test characteristics can be used to assist clinicians in making better decisions for their patients. These probabilistic models may seem confusing and difficult to implement. Some general rules may help, such as SnNout and SpPin. Clinicians should know the test characteristics and decision rules for the acute problems they may face. For chronic conditions, advanced planning may be helpful. Electronic medical record systems may be able to incorporate these at the user interface. The improvements in hand-held computers may bring clinical decision-support systems directly to the point of service. We may also begin to see laboratories report test characteristics for important conditions as likelihood ratios (we already see estimates of the risk of heart disease corresponding to different lipid ratios). We also suspect that the medical literature will report likelihood ratios more frequently. As practice networks develop more sophisticated disease-tracking mechanisms, clinicians will be able to obtain estimates of disease prevalence more appropriate to their practice. Ultimately, for physicians to make better decisions, appropriate data are needed, including accurate estimates of test characteristics and of disease probability.

Clinical Laboratory Techniques↗

An Efficient EM-based Training Algorithm for Feedforward Neural Networks.

A fast training algorithm is developed for two-layer feedforward neural networks based on a probabilistic model for hidden representations and the EM algorithm. The algorithm decomposes training the original two-layer networks into training a set of single neurons. The individual neurons are then trained via a linear weighted regression algorithm. Significant improvement on training speed has been made using this algorithm for several bench-mark problems. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.

Journal Article↗

DIAVAL, a Bayesian expert system for echocardiography.

DIAVAL is an expert system for the diagnosis of heart diseases, including several kinds of data, mainly from echocardiography. The first part of this paper is devoted to the causal probabilistic model which constitutes the knowledge base of the expert system in the form of a Bayesian network, emphasizing the importance of the OR gate. The second part deals with the process of diagnosis, which consists of computing the a posteriori probabilities, selecting the most probable and most relevant diagnoses, and generating a written report. It also describes the results of the evaluation of the program.

Artificial Intelligence↗

Avoiding premature closure in sequential diagnosis.

An important aspect of diagnostic reasoning is the ability to recognise when there is sufficient evidence to enable a working diagnosis to be made and thus avoid the unnecessary risks and costs of further testing. On the other hand, the reasoner must be careful to avoid the error, known as premature closure, of accepting a diagnosis before it is fully verified. In the absence of a more rigorous approach to verification, a pragmatic approach adopted in many programs for sequential diagnosis is to discontinue testing when the probability of the leading hypothesis reaches an arbitrary threshold. Experimental results are presented to illustrate the potential unreliability of this approach. A more reliable way to avoid premature closure is to discontinue testing only when the lower bound for the probability of the leading hypothesis reaches an acceptably high level. For example, a lower bound of 70% means that its probability can never be less than 70% regardless of any evidence that further testing may reveal. Another reason to discontinue testing may be that further evidence can at best increase the probability of the leading hypothesis by a small amount. For example, if the probability of the leading hypothesis is 72%, with a lower bound of 65% and an upper bound of 75%, further testing may be difficult to justify. As these examples illustrate, a termination strategy informed by upper and lower bounds for the probability of the leading hypothesis may help to avoid both premature closure and undue prolongation of the testing process. Finding upper and lower bounds for the probability of a diagnostic hypothesis as each new piece of evidence is obtained is feasible by existing techniques only when the number of remaining tests is small. However, new techniques are presented which can often produce a dramatic reduction in the computational effort required to find the upper and lower bounds. Based on the independence Bayesian framework, the theory presented extends a probabilistic model of hypothetico-deductive reasoning designed to enable programs for sequential diagnosis in medicine to emulate the reasoning processes of human diagnosticians.

Abdomen, Acute↗

Computational identification of noncoding RNAs in E. coli by comparative genomics.

Some genes produce noncoding transcripts that function directly as structural, regulatory, or even catalytic RNAs [1, 2]. Unlike protein-coding genes, which can be detected as open reading frames with distinctive statistical biases, noncoding RNA (ncRNA) gene sequences have no obvious inherent statistical biases [3]. Thus, genome sequence analyses reveal novel protein-coding genes, but any novel ncRNA genes remain invisible. Here, we describe a computational comparative genomic screen for ncRNA genes. The key idea is to distinguish conserved RNA secondary structures from a background of other conserved sequences using probabilistic models of expected mutational patterns in pairwise sequence alignments. We report the first whole-genome screen for ncRNA genes done with this method, in which we applied it to the "intergenic" spacers of Escherichia coli using comparative sequence data from four related bacteria. Starting from >23,000 conserved interspecies pairwise alignments, the screen predicted 275 candidate structural RNA loci. A sample of 49 candidate loci was assayed experimentally. At least 11 loci expressed small, apparently noncoding RNA transcripts of unknown function. Our computational approach may be used to discover structural ncRNA genes in any genome for which appropriate comparative genome sequence data are available.

Animals↗

IMP-8 observations of the spectra, composition, and variability of solar heavy ions at high energies relevant to manned space missions.

In more than 25 years of almost continuous observations, the University of Chicago's Cosmic Ray Telescope (CRT) on IMP-8 has amassed a unique database on high-energy solar heavy ions of potential relevance to manned spaceflight. In the very largest particle events, IMP-8/CRT has even observed solar Fe ions above the Galactic cosmic ray background up to approximately 800 MeV/nucleon, an energy sufficiently high to penetrate nearly 25 g/cm2 of shielding. IMP-8/CRT observations show that high-energy heavy-ion spectra are often surprisingly hard power laws, without the exponential roll-offs suggested by stochastic acceleration fits to lower energy measurements alone. Also, in many solar particle events the Fe/O ratio grows with increasing energy, contrary to the notion that ions with higher mass-to-charge ratios should be less abundant at higher energies. Previous studies of radiation hazards for manned spaceflight have often assumed heavy-ion composition and steeply-falling energy spectra inconsistent with these observations. Conclusions based on such studies should therefore be re-assessed. The significant event-to-event variability observed in the high-energy solar heavy ions also has important implications for strategies in building probabilistic models of solar particle radiation hazards.

Astronomy↗

Genomics and computational molecular biology.

There has been a dramatic increase in the number of completely sequenced bacterial genomes during the past two years as a result of the efforts both of public genome agencies and the pharmaceutical industry. The availability of completely sequenced genomes permits more systematic analyses of genes, evolution and genome function than was otherwise possible. Using computational methods - which are used to identify genes and their functions including statistics, sequence similarity, motifs, profiles, protein folds and probabilistic models - it is possible to develop characteristic genome signatures, assign functions to genes, identify pathogenic genes, identify metabolic pathways, develop diagnostic probes and discover potential drug-binding sites. All of these directions are critical to understanding bacterial growth, pathogenicity and host-pathogen interactions.

Bacterial Proteins↗

Estimating the number of multiple-species geohelminth infections in human communities.

Infections with Ascaris lumbricoides, Trichuris trichiura and the hookworm species are often found in the same communities and individuals. Hosts infected by more than one species are potentially at risk of morbidity associated with each infection. This paper describes the use of a probabilistic model to predict the prevalence of multiple-species infections in communities for which only overall prevalence data exist. The model is tested against field data, using log-linear analysis, and is found to be more effective at estimating the numbers of multiple infections involving hookworms than those involving only A. lumbicoides and T. trichiura. This latter combination of infections is found, in half the communities examined, to be more common than expected by chance. An age-stratified analysis reveals that the degree of interaction between these two infections does not alter significantly with age in the child age classes of a Malaysian population.

Adolescent↗

Prediction of posttranslational modifications using intact-protein mass spectrometric data.

We present a Web-based application that uses whole-protein masses determined by mass spectrometry to identify putative co- and posttranslational proteolytic cleavages and chemical modifications. The protein cleavage and modification engine (PROCLAME) requires as input an intact mass measurement and a precursor identification based on peptide mass fingerprinting or tandem mass spectrometry. This approach predicts mass-modifying events using a depth-first tree search, bounded by a set of rules controlled by a custom-built fuzzy logic engine, to explore a large number of possible combinations of modifications accounting for the experimental mass. Candidates are saved during a search if they are within a user-specified instrument mass accuracy; the total number of possible candidates searched is based on a specified fuzzy cutoff score. Candidates are scored and ranked using a simple probabilistic model. There is generally not enough information in an intact mass measurement to determine a single unique protein characterization; however, the program provides utility by expediting the identification of sets of putative events consistent with the mass data and ranking them for further investigation. This approach uses a simple, intuitive rule base and lends itself to discovery of unannotated posttranslational events. We have assessed the program with both in silico-generated test data and with published data from an analysis of large ribosomal subunit proteins, both from the yeast S. cerevisiae. Results indicate a high degree of sensitivity and specificity in characterizing proteins whose masses resulted from reasonable proteolysis and covalent modification scenarios. The application is available on the web at http://proclame.unc.edu.

Computational Biology↗

Potential sources of pesticides, PCBs, and PAHs to the atmosphere of the Great Lakes.

A probabilistic model called the potential source contribution function (PSCF) has been used to estimate atmospheric source regions of polycyclic aromatic hydrocarbons (PAHs), chlorinated pesticides, and polychlorinated biphenyls (PCBs) to the Great Lakes. This model allows us to map each compound's source region on a 0.5 degrees x 0.5 degrees latitude/longitude grid centered over the Great Lakes basin. PCBs primarily have urban sources, the strengths of which vary. Like PCBs, PAHs show a strong urban signature, but these compounds also seem to come from rural sites. The source regions of PAH become less distinct as the molecular weight of the compound increases. Since reactivity increases with PAH size, this diminishing trend may be an indication that atmospheric degradation plays a large role in PAH transport. The pesticides have the strongest source regions and are typically transported the farthest, often from areas distant from the Great Lakes basin.

Air Movements↗

Estimating potential environmental loadings of Cryptosporidium spp. and Campylobacter spp. from livestock in the Grand River Watershed, Ontario, Canada.

Exposure to waterborne pathogens in recreational or drinking water is a serious public health concern. Thus, it is important to determine the sources of pathogens in a watershed and to quantify their environmental loadings. The natural variability of potentially pathogenic microorganisms in the environment from anthropogenic, natural, and livestock sources is large and has been difficult to quantify. A first step in characterizing the risk of nonpoint source contamination from pathogens of livestock origin is to determine the potential environmental loading based on animal prevalence and fecal shedding intensity. This study developed a probabilistic model for estimating the production of Cryptosporidium spp. and Campylobacter spp. from livestock sources within a watershed. Probability density functions representing daily pathogen production rates from livestock were simulated for the Grand River Watershed in southwestern Ontario. The prevalence of pathogenic microorganisms in animals was modeled as a mixture of beta-distributions with parameters drawn from published studies. Similarly, gamma-distributions were generated to describe animal pathogen shedding intensity. Results demonstrate that although cattle are responsible for the largest amount of manure produced, other domesticated farm animals contribute large numbers of the two pathogenic microorganisms studied. Daily pathogen production rates are highly sensitive to the parameters of the gamma-distributions, illustrating the need for reliable data on animal shedding intensity. The methodology may be used for identifying source terms for pathogen fate and transport modeling and for defining and targeting regions that are most vulnerable to water contamination from pathogenic sources.

Animals↗

Population characteristics of biological systems influenced by multicomponent random and uniform variation.

The total variability associated with the pharmacokinetic disposition of seven therapeutic agents was decomposed into its source components. After differentiating and isolating random components from fixed uniform components of variance, the proportional contribution of random intersubject and intrasubject variance was evaluated. Statistical analysis utilized a mixed-effects probabilistic model which incorporated both random effects and fixed day-to-day effects. In some cases, time-within-day diurnal effects were also incorporated. While significant intersubject effects were found for all seven drugs studied, three of them were characterized by predominant intrasubject variance. Since intrasubject variance represents a measure of the stability of drug disposition, characterization of its relative magnitude is fundamentally important in assessing the therapeutic consequences of a given treatment at any given time. Significant diurnal effects were found which were strikingly invariant.

Adult↗

One frog, two frog, red frog, blue frog: factors affecting children's syntactic choices in production and comprehension.

Two experiments are reported which examine children's ability to use referential context when making syntactic choices in language production and comprehension. In a recent on-line study of auditory comprehension, Trueswell, Sekerina, Hill, and Logrip (1999) examined children's and adults' abilities to resolve temporary syntactic ambiguities involving prepositional phrases (e.g., "Put the frog on the napkin into..."). Although adults and older children used the referential context to guide their initial analysis (pursuing a destination interpretation in a one-frog context and a modifier interpretation in a two-frog context), 4 to 5-year olds' initial and ultimate analysis was one of destination, regardless of context. The present studies examined whether these differences were attributable to the comprehension process itself or to other sources, such as possible differences in how children perceive the scene and referential situation. In both experiments, children were given a language generation task designed to elicit and test children's ability to refer to a member of a set through restrictive modification. This task was immediately followed by the "put" comprehension task. The findings showed that, in response to a question about a member of a set (e.g., "Which frog went to Mrs. Squid's house?"), 4- to 5-year-olds frequently produced a definite NP with a restrictive prepositional modifier (e.g., "The one on the napkin"). These same children, however, continued to misanalyze put instructions, showing a strong avoidance of restrictive modification during comprehension. Experiment 2 showed that an increase in the salience of the platforms that distinguished the two referents increased overall performance, but still showed the strong asymmetry between production and comprehension. Eye movements were also recorded in Experiment 2, revealing on-line parsing patterns similar to Trueswell et al.: an initial preference for a destination analysis and a failure to revise early referential commitments. These experiments indicate that child-adult differences in parsing preferences arise, in part, from developmental changes in the comprehension process itself and not from a general insensitivity to referential properties of the scene. The findings are consistent with a probabilistic model for uncovering the structure of the input during comprehension, in which more reliable linguistic and discourse-related cues are learned first, followed by a gradually developing ability to take into account other more uncertain (or more difficult to learn) cues to structure.

Child↗

Finding useful questions: on Bayesian diagnosticity, probability, impact, and information gain.

Several norms for how people should assess a question's usefulness have been proposed, notably Bayesian diagnosticity, information gain (mutual information), Kullback-Liebler distance, probability gain (error minimization), and impact (absolute change). Several probabilistic models of previous experiments on categorization, covariation assessment, medical diagnosis, and the selection task are shown to not discriminate among these norms as descriptive models of human intuitions and behavior. Computational optimization found situations in which information gain, probability gain, and impact strongly contradict Bayesian diagnosticity. In these situations, diagnosticity's claims are normatively inferior. Results of a new experiment strongly contradict the predictions of Bayesian diagnosticity. Normative theoretical concerns also argue against use of diagnosticity. It is concluded that Bayesian diagnosticity is normatively flawed and empirically unjustified.

Bayes Theorem↗