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PubMedDate not supplied

Fitness for work: the SIMLII Health Surveillance Guidelines.

Italian legislation on prevention in occupational hygiene and safety, which is based largely on European Union Directives, requires health surveillance when risk assessment has identified a risk for workers' health. Health surveillance must be carried out by the occupational physician and concludes with the issue of a fitness for work certificate for the specific job. The guidelines produced by the "Italian Society of Occupational Medicine and Industrial Hygiene" (SIMLII), through the "Consortium for Accreditation and Updating in Occupational Medicine" founded by the "S. Maugeri Foundation of Pavia", Italy, focus firstly on the definition of judgment of fitness for a specific job. They outline the theoretical basis of the medico-legal terminology for fitness for work, which is founded on the concepts of suitability, fitness, capacity, ability, representing successive degrees of qualification and specific potential that the worker may attain during accomplishment of the tasks involved in the job. To assess fitness for a specific job, the occupational physician must consider whether the worker possesses the psycho-physical requisites normally needed to do the job, not the top levels of such requisites. The intrinsic characteristics of any judgment of fitness for work, namely its individual, probabilistic and time-dependent nature, are illustrated. The operative methodological model for making a judgment must include: assessment of the job and work environment, assessment of the worker through health surveillance, comparison and correlation of the two terms of the equation: human subject-work environment, the judgment thus made and the choice of any necessary measures and/or intervention. The methods for conducting the assessment process culminating in a judgement are presented, as stipulated in the pertinent legislation, and include the following conclusions: fitness, partial or total unfitness, temporary unfitness, fitness provided suitable prescriptions are observed,fitness provided some conditions are met. These definitions are analyzed in greater depth, especially the possible confusion between partial unfitness and fitness provided suitable prescriptions are observed. The employer or worker may lodge an appeal with the local health service inspection service against certain judgments of unfitness for work. Finally, as health surveillance is governed by different legal norms, the contents of which appear to be to some extent contradictory, even though aimed at safeguarding the dignity and freedom of the worker, the reasons why the occupational physician should take into account diseases apart from those of the organs exposed to specific risk are discussed. These should be borne in mind when issuing the specific fitness for work certificate at the end of preventive and periodical medical examinations.

Humans↗
PubMed2005

Feature detection using spikes: the greedy approach.

A goal of low-level neural processes is to build an efficient code extracting the relevant information from the sensory input. It is believed that this is implemented in cortical areas by elementary inferential computations dynamically extracting the most likely parameters corresponding to the sensory signal. We explore here a neuro-mimetic feed-forward model of the primary visual area (VI) solving this problem in the case where the signal may be described by a robust linear generative model. This model uses an over-complete dictionary of primitives which provides a distributed probabilistic representation of input features. Relying on an efficiency criterion, we derive an algorithm as an approximate solution which uses incremental greedy inference processes. This algorithm is similar to 'Matching Pursuit' and mimics the parallel architecture of neural computations. We propose here a simple implementation using a network of spiking integrate-and-fire neurons which communicate using lateral interactions. Numerical simulations show that this Sparse Spike Coding strategy provides an efficient model for representing visual data from a set of natural images. Even though it is simplistic, this transformation of spatial data into a spatio-temporal pattern of binary events provides an accurate description of some complex neural patterns observed in the spiking activity of biological neural networks.

Action Potentials↗
PubMed2001

Identifying influences on model uncertainty: an application using a forest carbon budget model.

Uncertainty is an important consideration for both developers and users of environmental simulation models. Establishing quantitative estimates of uncertainty for deterministic models can be difficult when the underlying bases for such information are scarce. We demonstrate an application of probabilistic uncertainty analysis that provides for refinements in quantifying input uncertainty even with little information. Uncertainties in forest carbon budget projections were examined with Monte Carlo analyses of the model FORCARB. We identified model sensitivity to range, shape, and covariability among model probability density functions, even under conditions of limited initial information. Distributional forms of probabilities were not as important as covariability or ranges of values. Covariability among FORCARB model parameters emerged as a very influential component of uncertainty, especially for estimates of average annual carbon flux.

Carbon↗
PubMed1986

Cell growth and division: a deterministic/probabilistic model of the cell cycle.

A model of the cell cycle, incorporating a deterministic cell-size monitor and a probabilistic component, is investigated. Steady-state distributions for cell size and generation time are calculated and shown to be globally asymptotically stable. These distributions are used to calculate various statistical quantities, which are then compared to known experimental data. Finally, the results are compared to distributions calculated from a Monte-Carlo simulation of the model.

Cell Cycle↗
PubMed2003

Directional sensitivity of neurons in the primary auditory (AI) cortex: effects of sound-source intensity level.

Transient sounds were delivered from different directions in virtual acoustic space while recording from single neurons in primary auditory cortex (AI) of cats under general anesthesia. The intensity level of the sound source was varied parametrically to determine the operating characteristics of the spatial receptive field. The spatial receptive field was constructed from the onset latency of the response to a sound at each sampled direction. Spatial gradients of response latency composing a receptive field are due partially to a systematic co-dependence on sound-source direction and intensity level. Typically, at any given intensity level, the distribution of response latency within the receptive field was unimodal with a range of approximately 3-4 ms, although for some cells and some levels, the spread could be as much as 20 or as little as 2 ms. Response latency, averaged across directions, differed among neurons for the same intensity level, and also differed among intensity levels for the same neuron. Generally, increases in intensity level resulted in decreases in the mean and variance, which follows an inverse Gaussian distribution. Receptive field models, based on response latency, are developed using multiple parameters (azimuth, elevation, intensity), validated with Monte Carlo simulation, and their spatial filtering described using spherical harmonic analysis. Observations from an ensemble of modeled receptive fields are obtained by linking the inverse Gaussian density to the probabilistic inverse problem of estimating sound-source direction and intensity. Upper bounds on acuity is derived from the ensemble using Fisher information, and the predicted patterns of estimation errors are related to psychophysical performance.

Acoustic Stimulation↗
PubMed2003

Predicting the genotoxicity of thiophene derivatives from molecular structure.

We report several binary classification models that directly link the genetic toxicity of a series of 140 thiophene derivatives with information derived from the compounds' molecular structure. Genetic toxicity was measured using an SOS Chromotest. IMAX (maximal SOS induction factor) values were recorded for each of the 140 compounds both in the presence and in the absence of S9 rat liver homogenate. Compounds were classified as genotoxic if IMAX >or= 1.5 in either test or nongenotoxic if IMAX < 1.5 for both tests. The molecular structures were represented by numerical descriptors that encoded the topological, geometric, electronic, and polar surface area properties of the thiophene derivatives. The classification models used were linear discriminant analysis (LDA), k-nearest neighbor classification (k-NN), and the probabilistic neural network (PNN). These were used in conjunction with either a genetic algorithm or a generalized simulated annealing to find optimal subsets of descriptors for each classifier. The quality of the resulting models was determined by the number of misclassified compounds, with preference given to models that produced fewer false negative classifications. Model sizes ranged from seven descriptors for LDA to three descriptors for k-NN and PNN. Very good classification results were obtained with all three classifiers. Classification rates for the LDA, k-NN, and PNN models were 80, 85, and 85%, respectively, for the prediction set compounds. Additionally, a consensus model was generated that incorporated all three of the basic model types. This consensus model correctly predicted the genotoxicity of 95% of the prediction set compounds.

DNA Damage↗
PubMed2003

A new model for simulating 3-d crystal growth and its application to the study of antifreeze proteins.

A novel computational technique for modeling crystal formation has been developed that combines three-dimensional (3-D) molecular representation and detailed energetics calculations of molecular mechanics techniques with the less-sophisticated probabilistic approach used by statistical techniques to study systems containing millions of molecules undergoing billions of interactions. Because our model incorporates both the structure of and the interaction energies between participating molecules, it enables the 3-D shape and surface properties of these molecules to directly affect crystal formation. This increase in model complexity has been achieved while simultaneously increasing the number of molecules in simulations by several orders of magnitude over previous statistical models. We have applied this technique to study the inhibitory effects of antifreeze proteins (AFPs) on ice-crystal formation. Modeling involving both fish and insect AFPs has produced results consistent with experimental observations, including the replication of ice-etching patterns, ice-growth inhibition, and specific AFP-induced ice morphologies. Our work suggests that the degree of AFP activity results more from AFP ice-binding orientation than from AFP ice-binding strength. This technique could readily be adapted to study other crystal and crystal inhibitor systems, or to study other noncrystal systems that exhibit regularity in the structuring of their component molecules, such as those associated with the new nanotechnologies.

Antifreeze Proteins↗
PubMed2002

Variability in thermal response of primed and non-primed seeds of squirreltail [Elymus elymoides (Raf.) Swezey and Elymus multisetus (J. G. Smith) M. E. Jones].

Bottlebrush squirreltail [Elymus elymoides (Raf.) Swezey = Sitanion hystrix (Nutt.) J. G. Smith] and big squirrel-tail [Elymus multisetus (J. G. Smith) M. E. Jones = Sitanion jubatum (J. G. Smith)] have a broad geographical distribution and have been identified as high priority species for restoration of degraded rangelands in the western United States. These rangelands exhibit high annual and seasonal variability in seedbed microclimate. The objective of this study was to examine variability in thermal response of both primed and non-primed seeds of these species in the context of field-variable temperature regimes. Seed priming treatments were selected to optimize germination rate in a low-temperature test environment. Primed and non-primed seeds were evaluated for laboratory germination response under 12 constant temperature treatments between 3 and 36 degrees C. Thermal time and base temperature were estimated by regression analysis of germination rate as a function of temperature in the sub-optimal temperature range. The thermal germination model and 6 years of field temperature data were used to simulate the potential germination response under different field planting scenarios. Seed priming reduced the total germination percentage of some seedlots, especially at higher germination temperatures. Seed priming increased the germination rate (reduced the number of days to 50 % germination) by 3.8-8.4 d at 6 degrees C with a mean germination advancement of 6.9 +/- 0.6 d. Maximum germination advancement in the model simulations was 5-10 d for planting dates between I March and 15 May. Model simulations can be used to expand germination analysis beyond simple treatment comparisons, to include a probabilistic description of potential germination response under historical or potential future conditions of seedbed microclimate.

Germination↗
PubMed2005

Prediction of protein interdomain linker regions by a hidden Markov model.

MOTIVATION: Our aim was to predict protein interdomain linker regions using sequence alone, without requiring known homology. Identifying linker regions will delineate domain boundaries, and can be used to computationally dissect proteins into domains prior to clustering them into families. We developed a hidden Markov model of linker/non-linker sequence regions using a linker index derived from amino acid propensity. We employed an efficient Bayesian estimation of the model using Markov Chain Monte Carlo, Gibbs sampling in particular, to simulate parameters from the posteriors. Our model recognizes sequence data to be continuous rather than categorical, and generates a probabilistic output. RESULTS: We applied our method to a dataset of protein sequences in which domains and interdomain linkers had been delineated using the Pfam-A database. The prediction results are superior to a simpler method that also uses linker index.

Algorithms↗
PubMedDate not supplied

Phylogenetic invariants for genome rearrangements.

We review the combinatorial optimization problems in calculating edit distances between genomes and phylogenetic inference based on minimizing gene order changes. With a view to avoiding the computational cost and the "long branches attract" artifact of some tree-building methods, we explore the probabilization of genome rearrangement models prior to developing a methodology based on branch-length invariants. We characterize probabilistically the evolution of the structure of the gene adjacency set for reversals on unsigned circular genomes and, using a nontrivial recurrence relation, reversals on signed genomes. Concepts from the theory of invariants developed for the phylogenetics of homologous gene sequences can be used to derive a complete set of linear invariants for unsigned reversals, as well as for a mixed rearrangement model for signed genomes, though not for pure transposition or pure signed reversal models. The invariants are based on an extended Jukes-Cantor semigroup. We illustrate the use of these invariants to relate mitochondrial genomes from a number of invertebrate animals.

Algorithms↗
PubMed1999

Stochastic models of telomere shortening.

Shortening of chromosome ends, known as telomeres, is one of the supposed mechanisms of cellular aging and death. We provide a probabilistic analysis of the process of loss of telomere ends. The first work concerned with that issue is the paper by Levy et al. [J. Molec. Biol. 225 (1992) 951-960]. Their deterministic model reproduced the observed frequencies of viable cells in the in vitro experiments. Arino et al. [J. Theor. Biol. 177 (1995) 45-57] reformulated the model of Levy et al. (1992) in the terms of branching processes with denumerable type space. In the present paper, the mathematical results of Arino et al. (1995) are extended to the case in which cell death is present, in cells with telomeres above and below the critical threshold of length, generally with differing probabilities. Both exact and asymptotic results are provided, as well as a discussion of biological relevance of the results.

Cell Death↗
PubMed1980

The structure of competence in health professions.

The past decade has seen widespread research on systematic evaluation of the competence of health professionals. Such activity usually has been carried out in accordance with the prevailing psychological paradigms, in which competence is represented as a trait, or as an intrapsychic factor. However, even when competence has been delimited as problem-solving, the research generally identified a strong situational influence on performance. In this article are assembled a set of diverse but complementary arguments for dispensing with the conventional representations of professional competence. In their place is proposed a relational model in which competence in health professions is seen as the aggregated adaptations of practitioners to the set of special social circumstances that obtain within the situational boundaries of their profession. It is argued that a thorough understanding of the content of professional situations is a necessary prerequisite for successful evaluation of professional competence, since competent behavior is lodged in a network of probabilistic relationships with the surroundings. Also discussed are selected procedural implications of this new model for the conduct of investigations of professional situations.

Evaluation Studies as Topic↗
PubMed2004

Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes.

Humans and other animals demonstrate the ability to perceive and respond to temporally relevant information with characteristic behavioral properties. For example, the response time distributions in peak-interval timing tasks are well described by Gaussian functions, and superimpose when scaled by the criterion duration. This superimposition has been referred to as the scalar property and results from the fact that the standard deviation of a temporal estimate is proportional to the duration being timed. Various psychological models have been proposed to account for such responding. These models vary in their success in predicting the temporal control of behavior as well as in the neurobiological feasibility of the mechanisms they postulate. A review of the major interval timing models reveals that no current model is successful on both counts. The neurobiological properties of the basal ganglia, an area known to be necessary for interval timing and motor control, suggests that this set of structures act as a coincidence detector of cortical and thalamic input. The hypothesized functioning of the basal ganglia is similar to the mechanisms proposed in the beat frequency timing model [R.C. Miall, Neural Computation 1 (1989) 359-371], leading to a reevaluation of its capabilities in terms of behavioral prediction. By implementing a probabilistic firing rule, a dynamic response threshold, and adding variance to a number of its components, simulations of the striatal beat frequency model were able to produce output that is functionally equivalent to the expected behavioral response form of peak-interval timing procedures.

Animals↗
PubMed1981

Improved interpretation of a continuous variable in diagnostic testing: probabilistic analysis of scintigraphic rest and exercise left ventricular ejection fractions for coronary disease detection.

The interpretation of a diagnostic modality requires consideration of the entire distribution of potential responses in both the normal and diseases population to extract the maximum available information from the test. Accordingly, we developed a probabilistic format for interpretation of scintigraphic left ventricular ejection fraction (LVEF) in the diagnosis of coronary artery disease (CAD). This format is distinguished (1) by accurate assessment of CAD likelihood based upon age, sex, and symptom classification using a logistical regression model (mean r = 0.9991, mean SEE = 0.008) and (2) by consideration of LVEF as a continuous probabilistic variable which obeys beta frequency distribution. This format allows assessment of the probability of CAD in an individual patient, according to Bayes' theorem of conditional probability of disease, given combinations of LVEF at rest and/or with exercise, and thereby is designed to provide more information than conventional categorical classification of "normal" or "abnormal" test observations.

Adult↗
PubMed2001

Determining the Dimensionality of Multidimensional Scaling Representations for Cognitive Modeling.

Multidimensional scaling models of stimulus domains are widely used as a representational basis for cognitive modeling. These representations associate stimuli with points in a coordinate space that has some predetermined number of dimensions. Although the choice of dimensionality can significantly influence cognitive modeling, it is often made on the basis of unsatisfactory heuristics. To address this problem, a Bayesian approach to dimensionality determination, based on the Bayesian Information Criterion (BIC), is developed using a probabilistic formulation of multidimensional scaling. The BIC approach formalizes the trade-off between data-fit and model complexity implicit in the problem of dimensionality determination and allows for the explicit introduction of information regarding data precision. Monte Carlo simulations are presented that indicate, by using this approach, the determined dimensionality is likely to be accurate if either a significant number of stimuli are considered or a reasonable estimate of precision is available. The approach is demonstrated using an established data set involving the judged pairwise similarities between a set of geometric stimuli. Copyright 2001 Academic Press.

Journal Article↗
PubMed2003

Reconstruction of extended cortical sources for EEG and MEG based on a Monte-Carlo-Markov-chain estimator.

A new procedure to model extended cortical sources from EEG and MEG recordings based on a probabilistic approach is presented. The method (SPMECS) was implemented within the framework of maximum likelihood estimators. Neuronal activity generating EEG or MEG signals was characterized by the number of sources and their location and extension. Based on the noise distribution of the measured data, source configurations were associated with the according value of the likelihood function. To find the most likely source, i.e., the maximum likelihood estimator, and its level of confidence, a stochastic solver (Metropolis algorithm) was applied. The method presented supports the incorporation of virtually any constraint, e.g., based on physiological and anatomical a priori knowledge. Thus, ambiguity of the ill-posed inverse problem was reduced considerably by confining sources to the cortical surface extracted from individual MR images. The influence of different levels and types of noise on the outcome was investigated by means of simulations. Somatosensory evoked magnetic fields analyzed by the method presented suggest that larger extended cortical areas are involved in the processing of combined finger stimulation as compared to single finger stimulation.

Algorithms↗
PubMed1999

Use of in vitro gas production models in ruminal kinetics.

Physiological systems models for ruminant animals are used to predict the extent of ruminal carbohydrate digestion, based on rates of intake, digestion, and passage to the lower tract. Digestion of feed carbohydrates is described in these models by a first-order rate constant. Recently, an in vitro gas production technique has been developed to determine the digestion kinetics in batch fermentation, and nonlinear mathematical models have been fitted to the cumulative gas production data from these experiments. In this paper, we present an analysis that converts these gas production models to an effective first-order rate constant that can be used directly in rumen systems models. The analysis considers the digestion of an incremental mass of substrate entering the rumen. The occurrence of passage is represented probabilistically, and integration through time gives the total mass of substrate and total rate of digestion in the rumen. To demonstrate the analysis, several gas production models are fitted to a sample data set for corn silage, and the effective first-order rate constants are calculated. The rate constants for digestion depend on ruminal passage rate, an interaction that arises from the nonlinearity of the gas production models.

Animals↗
PubMed1994

Automated transformation of probabilistic knowledge for a medical diagnostic system.

Iliad is a large medical diagnostic system that covers more than 2000 diagnoses and 9000 findings. Due to the size and the complexity of this system, a robust knowledge representation is essential to consistently and efficiently model the medical knowledge involved. In this paper, we describe the knowledge representation currently used in Iliad and a probabilistic representation based on the Bayesian network formalism which can be derived using the information that the Iliad knowledge base contains.

Algorithms↗