Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

A prospective comparison of two models of cannabis use and psychotic relapse in early psychosis

No abstract

Virtual models of the HLA class I antigen processing pathway

Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class 1 binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify H LA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. (C) 2004 Elsevier Inc. All rights reserved.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Dermaseptin 01 as antimicrobial peptide with rich biotechnological potential: study of peptide interaction with membranes containing Leishmania amazonensis lipid-rich extract and membrane models

This article addresses the interactions of the synthetic antimicrobial peptide dermaseptin 01 (GLWSTIKQKGKEAAIAAA-KAAGQAALGAL-NH(2), DS 01) with phospholipid (PL) monolayers comprising (i) a lipid-rich extract of Leishmania amazonensis (LRE-La), (ii) zwitterionic PL (dipalmitoylphosphatidylcholine, DPPC), and (iii) negatively charged PL (dipalmitoylphosphatidylglycerol, DPPG). The degree of interaction of DS 01 with the different biomembrane models was quantified from equilibrium and dynamic liquid-air interface parameters. At low peptide concentrations, interactions between DS 01 and zwitterionic PL, as well as with the LRE-La monolayers were very weak, whereas with negatively charged PLs the interactions were stronger. For peptide concentrations above 1 mu g/ml, a considerable expansion of negatively charged monolayers occurred. In the case of DPPC, it was possible to return to the original lipid area in the condensed phase, suggesting that the peptide was expelled from the monolayer. However, in the case of DPPG, the average area per lipid molecule in the presence of DS 01 was higher than pure PLs even at high surface pressures, suggesting that at least part of DS 01 remained incorporated in the monolayer. For the LRE-La monolayers, DS 01 also remained in the monolayer. This is the first report on the antiparasitic activity of AMPs using Langmuir monolayers of a natural lipid extract from L. amazonensis. Copyright (C) 2011 European Peptide Society and John Wiley & Sons, Ltd.

Attentional modulation of neural responses to action observation: Implications for models of the human 'mirror' system

In primates, the observation of meaningful, goaldirected actions engages a network of cortical areas located within the premotor and inferior parietal lobules. Current models suggest that activity within these regions arises relatively automatically during passive action observation without the need for topdown control. Here we used functional magnetic resonance imaging to determine whether cortical activit)' associated with action observation is modulated by the strategic allocation of selective attention. Normal observers viewed movie clips of reach-to-grasp actions while performing an easy or difficult visual discrimination at the fovea. A wholebrain analysis was performed to determine the effects of attentional load on neural responses to observed hand actions. Our results suggest that cortical areas involved in action observation are significantiy modulated by attentional load. These findings have important implications for recent attempts to link the human action-observation system to response properties of "mirror neurons" in monkeys.

Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models

We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.

Drinfeld twists and symmetric Bethe vectors of supersymmetric fermion models

We construct the Drinfeld twists ( factorizing F-matrices) of the gl(m-n)-invariant fermion model. Completely symmetric representation of the pseudo-particle creation operators of the model are obtained in the basis provided by the F-matrix ( the F-basis). We resolve the hierarchy of the nested Bethe vectors in the F-basis for the gl(m-n) supersymmetric model.

The effects of predator odors in mammalian prey species: A review of field and laboratory studies

wPrey species show specific adaptations that allow recognition, avoidance and defense against predators. For many mammalian species this includes sensitivity towards predator-derived odors. The typical sources of such odors include predator skin and fur, urine, feces and anal gland secretions. Avoidance of predator odors has been observed in many mammalian prey species including rats, mice, voles, deer, rabbits, gophers, hedgehogs, possums and sheep. Field and laboratory studies show that predator odors have distinctive behavioral effects which include (1) inhibition of activity, (2) suppression of non-defensive behaviors such as foraging, feeding and grooming, and (3) shifts to habitats or secure locations where such odors are not present. The repellent effect of predator odors in the field may sometimes be of practical use in the protection of crops and natural resources, although not all attempts at this have been successful. The failure of some studies to obtain repellent effects with predator odors may relate to (1) mismatches between the predator odors and prey species employed, (2) strain and individual differences in sensitivity to predator odors, and (3) the use of predator odors that have low efficacy. In this regard, a small number of recent studies have suggested that skin and fur-derived predator odors may have a more profound lasting effect on prey species than those derived from urine or feces. Predator odors can have powerful effects on the endocrine system including a suppression of testosterone and increased levels of stress hormones such as corticosterone and ACTH. Inhibitory effects of predator odors on reproductive behavior have been demonstrated, and these are particularly prevalent in female rodent species. Pregnant female rodents exposed to predator odors may give birth to smaller litters while exposure to predator odors during early life can hinder normal development. Recent research is starting to uncover the neural circuitry activated by predator odors, leading to hypotheses about how such activation leads to observable effects on reproduction, foraging and feeding. (c) 2005 Elsevier Ltd. All rights reserved.

Special issue on methods and learning in functional MRI: Introductory remarks

This special issue represents a further exploration of some issues raised at a symposium entitled “Functional magnetic resonance imaging: From methods to madness” presented during the 15th annual Theoretical and Experimental Neuropsychology (TENNET XV) meeting in Montreal, Canada in June, 2004. The special issue’s theme is methods and learning in functional magnetic resonance imaging (fMRI), and it comprises 6 articles (3 reviews and 3 empirical studies). The first (Amaro and Barker) provides a beginners guide to fMRI and the BOLD effect (perhaps an alternative title might have been “fMRI for dummies”). While fMRI is now commonplace, there are still researchers who have yet to employ it as an experimental method and need some basic questions answered before they venture into new territory. This article should serve them well. A key issue of interest at the symposium was how fMRI could be used to elucidate cerebral mechanisms responsible for new learning. The next 4 articles address this directly, with the first (Little and Thulborn) an overview of data from fMRI studies of category-learning, and the second from the same laboratory (Little, Shin, Siscol, and Thulborn) an empirical investigation of changes in brain activity occurring across different stages of learning. While a role for medial temporal lobe (MTL) structures in episodic memory encoding has been acknowledged for some time, the different experimental tasks and stimuli employed across neuroimaging studies have not surprisingly produced conflicting data in terms of the precise subregion(s) involved. The next paper (Parsons, Haut, Lemieux, Moran, and Leach) addresses this by examining effects of stimulus modality during verbal memory encoding. Typically, BOLD fMRI studies of learning are conducted over short time scales, however, the fourth paper in this series (Olson, Rao, Moore, Wang, Detre, and Aguirre) describes an empirical investigation of learning occurring over a longer than usual period, achieving this by employing a relatively novel technique called perfusion fMRI. This technique shows considerable promise for future studies. The final article in this special issue (de Zubicaray) represents a departure from the more familiar cognitive neuroscience applications of fMRI, instead describing how neuroimaging studies might be conducted to both inform and constrain information processing models of cognition.

Effects of immunosuppressants on hepatocyte cell mitosis during liver regeneration in growing animal models of partial hepatectomy

Objective. We sought to evaluate the effects of immunosuppressant drugs (corticosteroid, cyclosporine [CsA], and tacrolimus [Tac]) on liver regeneration in growing animals submitted to 70% hepatectomy. Materials and Methods. Newborn and weaning rats were submitted to 70% hepatectomy receiving separately methylprednisolone, CsA, or Tac. All animals were sacrificed 24 hours after the procedure. The remnant liver lobes were subjected to histomorphometric analyses with determination of hepatocyte mitotic index. Results., Administration of immunosuppressants did not change the mitotic index of the regenerating liver in newborn animals. In weaning rats, methylprednisolone reduced the mitotic index (P = .01) and Tac caused a greater increase in this rate (P = .001). CsA had no effect on mitotic index. The number of hepatocyte mitoses in newborn animal livers was greater than that in weaning animal livers (P = .001). Conclusion. In situations in which intense, fast processes of liver regeneration are crucial, the advantages of the use of Tac must be considered, such as in pediatric transplant patients.

Influence of gender on the clinical and laboratory spectra of patients with primary antiphospholipid syndrome

The objectives of this cross-sectional study were to evaluate the differences between males and females in the clinical and biochemical manifestations of primary antiphospholipid antibody syndrome (PAPS). The method involved 49 patients (38 premenopausal females and 11 males) diagnosed with PAPS (according to the Sapporo criteria) and their demographic data, clinical data, medications used and antiphospholipid antibodies were analyzed. The results of this study are as follows. Both the groups of patients were statistically similar regarding age, race, weight and body mass index. However, males were significantly taller than females (172 +/- A 8.9 vs. 159.2 +/- A 6.2 cm, p < 0.0001). The duration of disease was similar for females and males. The prevalence of pulmonary thromboembolism was higher in females than in males (34.2 vs. 0.0%, p = 0.024). Regarding other PAPS manifestations (arterial events, venous events, deep venous thrombosis, thrombocytopenia, acute myocardial infarction, angina, cerebrovascular accidents and Sneddon syndrome), comorbidities (arterial hypertension and dyslipidemia), lifestyle (physical activity, previous smoking and current smoking) and the use of medications (current and previous use of corticosteroids, as well as the use of statins or chloroquine), both groups were statistically similar (p > 0.05). More females than males tested positive for IgM anticardiolipin antibodies (76.3 vs. 36.4%, p = 0.025) or for at least one of the antiphospholipid antibodies tested (either IgM anticardiolipin or IgG anticardiolipin 84.2 vs. 45.5%, p = 0.016). However, both groups were similar regarding the frequency of positivity for lupus anticoagulant and isolated IgG anticardiolipin, as well as regarding mean levels of IgG and IgM anticardiolipin (p > 0.05). We concluded that, among PAPS patients, the frequency of pulmonary thromboembolism and of positivity for IgM anticardiolipin is higher in females than in males. Our findings show that there are gender differences in PAPS, differences that might be related to alterations in sex hormones.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd