The development of retinotectal maps: A review of models based on molecular gradients

Information about the world is often represented in the brain in the form of topographic maps. A paradigm example is the topographic representation of the visual world in the optic tectum/superior colliculus. This map initially forms during neural development using activity-independent molecular cues, most notably some type of chemospecific matching between molecular gradients in the retina and corresponding gradients in the tectum/superior colliculus. Exactly how this process might work has been studied both experimentally and theoretically for several decades. This review discusses the experimental data briefly, and then in more detail the theoretical models proposed. The principal conclusions are that (1) theoretical models have helped clarify several important ideas in the field, (2) earlier models were often more sophisticated than more recent models, and (3) substantial revisions to current modelling approaches are probably required to account for more than isolated subsets of the experimental data.

A phase I biological and pharmacologic study of the heparanase inhibitor PI-88 in patients with advanced solid tumors

Purpose: PI-88 is a mixture of highly sulfated oligosaccharides that inhibits heparanase, an extracellular matrix endoglycosidase, and the binding of angiogenic growth factors to heparan sulfate. This agent showed potent inhibition of placental blood vessel angiogenesis as well as growth inhibition in multiple xenograft models, thus forming the basis for this study. Experimental Design: This study evaluated the toxicity and pharmacokinetics of PI-88 (80-315 mg) when administered s.c. daily for 4 consecutive days bimonthly (part 1) or weekly (part 2). Results: Forty-two patients [median age, 53 years (range, 19-78 years); median performance status, 1] with a range of advanced solid tumors received a total of 232 courses. The maximum tolerated dose was 250 mg/d. Dose-limiting toxicity consisted of thrombocytopenia and pulmonary embolism. Other toxicity was generally mild and included prolongation of the activated partial thromboplastin time and injection site echymosis. The pharmacokinetics were linear with dose. Intrapatient variability was low and interpatient variability was moderate. Both AUC and C-max correlated with the percent increase in activated partial thromboplastin time, showing that this pharmacodynamic end point can be used as a surrogate for drug exposure, No association between PI-88 administration and vascular endothelial growth factor or basic fibroblast growth factor levels was observed. One patient with melanoma had a partial response, which was maintained for >50 months, and 9 patients had stable disease for >= 6 months. Conclusion: The recommended dose of PI-88 administered for 4 consecutive days bimonthly or weekly is 250 mg/d. PI-88 was generally well tolerated. Evidence of efficacy in melanoma supports further evaluation of PI-88 in phase II trials.

Applicability of experience from laboratory reactors with biological phosphorus removal in full-scale plants

Enhanced biological phosphorus removal (EBPR) has been used at many wastewater treatment plants all over the world for many years. In this study a full-scale sludge with good EBPR was tested with P-release batch tests and combined FISH/MAR (fluorescence in situ hybridisation and microautoradiography). Proposed models of PAOs and GAOs (polyphosphate- and glycogen-accumulating organisms) and microbial methods suggested from studies of laboratory reactors were found to be applicable also on sludge from full-scale plants. Dependency of pH and the uptake of both acetate and propionate were studied and used for calculations for verifying the models and results from microbial methods. All rates found from the batch tests with acetate were higher than in the batch tests with propionate, which was explained by the finding that only those parts of the bacterial community that were able to take up acetate anaerobically were able to take up propionate anaerobically.

Construction and analysis of a metagenomic library from an enhanced biological phosphorus removal biomass

The enhanced biological phosphorus removal (EBPR) process is regularly used for the treatment of wastewater, but suffers from erratic performance. Successful EBPR relies on the growth of bacteria called polyphosphate-accumulating organisms (PAOs), which store phosphorus intracellularly as polyphosphate, thus removing it from wastewater. Metabolic models have been proposed which describe the measured chemical transformations, however genetic evidence is lacking to confirm these hypotheses. The aim of this research was to generate a metagenomic library from biomass enriched in PAOs as determined by phenotypic data and fluorescence in situ hybridisation (FISH) using probes specific for the only described PAO to date, Candidatus Accumulibacter phosphatis. DNA extraction methods were optimised and two fosmid libraries were constructed which contained 93 million base pairs of metagenomic data. Initial screening of the library for 16S rRNA genes revealed fosmids originating from a range of non-pure-cultured wastewater bacteria. The metagenomic libraries constructed will provide the ability to link phylogenetic and metabolic data for bacteria involved in nutrient removal from wastewater. Keywords DNA extraction; EBPR; metagenomic library; 16S rRNA gene.

Enhancement of drug affinity for cell membranes by conjugation with lipoamino acids II. Experimental and computational evidence using biomembrane models

Lipoamino acids (LAAs) are promoieties able to enhance the amphiphilicity of drugs, facilitating their interaction with cell membranes. Experimental and computational studies were carried out on two series of lipophilic amide conjugates between a model drug (tranylcypromine, TCP) and LAA or alkanoic acids containing a short, medium or long alkyl side chain (C-4 to C-16). The effects of these compounds were evaluated by monolayer surface tension analysis and differential scanning calorimetry using dimyristoylphosphatidylcholine nnonolayers and liposomes as biomembrane models. The experimental results were related to independent calculations to determine partition coefficient and blood-brain partitioning. The comparison of TCP-LAA conjugates with the related series of TCP alkanoyl amides confirmed that the ability to interact with the biomembrane models is not due to the mere increase of lipophilicity, but mainly to the amphipatic nature and the kind of LAA residue. (C) 2005 Elsevier B.V. All rights reserved.

Metagenomic analysis of two enhanced biological phosphorus removal (EBPR) sludge communities

Enhanced biological phosphorus removal (EBPR) is one of the best-studied microbially mediated industrial processes because of its ecological and economic relevance. Despite this, it is not well understood at the metabolic level. Here we present a metagenomic analysis of two lab-scale EBPR sludges dominated by the uncultured bacterium, Candidatus Accumulibacter phosphatis.'' The analysis sheds light on several controversies in EBPR metabolic models and provides hypotheses explaining the dominance of A. phosphatis in this habitat, its lifestyle outside EBPR and probable cultivation requirements. Comparison of the same species from different EBPR sludges highlights recent evolutionary dynamics in the A. phosphatis genome that could be linked to mechanisms for environmental adaptation. In spite of an apparent lack of phylogenetic overlap in the flanking communities of the two sludges studied, common functional themes were found, at least one of them complementary to the inferred metabolism of the dominant organism. The present study provides a much needed blueprint for a systems-level understanding of EBPR and illustrates that metagenomics enables detailed, often novel, insights into even well-studied biological systems.

Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures

Background: The structure of proteins may change as a result of the inherent flexibility of some protein regions. We develop and explore probabilistic machine learning methods for predicting a continuum secondary structure, i.e. assigning probabilities to the conformational states of a residue. We train our methods using data derived from high-quality NMR models. Results: Several probabilistic models not only successfully estimate the continuum secondary structure, but also provide a categorical output on par with models directly trained on categorical data. Importantly, models trained on the continuum secondary structure are also better than their categorical counterparts at identifying the conformational state for structurally ambivalent residues. Conclusion: Cascaded probabilistic neural networks trained on the continuum secondary structure exhibit better accuracy in structurally ambivalent regions of proteins, while sustaining an overall classification accuracy on par with standard, categorical prediction methods.

Predicting population dynamics of weed biological control agents: science or gazing into crystal balls?

Various factors can influence the population dynamics of phytophages post introduction, of which climate is fundamental. Here we present an approach, using a mechanistic modelling package (CLIMEX), that at least enables one to make predictions of likely dynamics based on climate alone. As biological control programs will have minimal funding for basic work (particularly on population dynamics), we show how predictions can be made using a species geographical distribution, relative abundance across its range, seasonal phenology and laboratory rearing data. Many of these data sets are more likely to be available than long-term population data, and some can be incorporated into the exploratory phase of a biocontrol program. Although models are likely to be more robust the more information is available, useful models can be developed using information on species distribution alone. The fitted model estimates a species average response to climate, and can be used to predict likely geographical distribution if introduced, where the agent is likely to be more abundant (i.e. good locations) and more importantly for interpretation of release success, the likely variation in abundance over time due to intra- and inter-year climate variability. The latter will be useful in predicting both the seasonal and long-term impacts of the potential biocontrol agent on the target weed. We believe this tool may not only aid in the agent selection process, but also in the design of release strategies, and for interpretation of post-introduction dynamics and impacts. More importantly we are making testable predictions. If biological control is to become more of a science making and testing such hypothesis will be a key component.

Stochastic models for regulatory networks of the genetic toggle switch

Bistability arises within a wide range of biological systems from the A phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. in this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

Mixture models for detecting differentially expressed genes in microarrays

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

On parameter estimation in population models

We describe methods for estimating the parameters of Markovian population processes in continuous time, thus increasing their utility in modelling real biological systems. A general approach, applicable to any finite-state continuous-time Markovian model, is presented, and this is specialised to a computationally more efficient method applicable to a class of models called density-dependent Markov population processes. We illustrate the versatility of both approaches by estimating the parameters of the stochastic SIS logistic model from simulated data. This model is also fitted to data from a population of Bay checkerspot butterfly (Euphydryas editha bayensis), allowing us to assess the viability of this population. (c) 2006 Elsevier Inc. All rights reserved.

Evaluation of different models to describe egg and pupal development of Xyleborus fornicatus Eichh. (Coleoptera: Scolytidae), the shot-hole borer of tea in Sri Lanka

Abstract Development data of eggs and pupae of Xyleborus fornicatus Eichh. (Coleoptera: Scolytidae), the shot-hole borer of tea in Sri Lanka, at constant temperatures were used to evaluate a linear and seven nonlinear models for insect development. Model evaluation was based on fit to data (residual sum of squares and coefficient of determination or coefficient of nonlinear regression), number of measurable parameters, the biological value of the fitted coefficients and accuracy in the estimation of thresholds. Of the nonlinear models, the Lactin model fitted experimental data well and along with the linear model, can be used to describe the temperature-dependent development of this species.