A cellular automaton model to find the risk of developing autism through gut-mediated effects.

BACKGROUND: One of the risk factors for the development of Autism Spectrum Disorder (ASD) is hypothesized to be an imbalance in the gut microbiome. Alterations in the relative numbers of gut microbiota may contribute to such a disruption in normal bacterial diversity. It is assumed that this process may be adequately mirrored for the purpose of the current paper by modeling the dynamic shifts in the numbers of three bacterial species, namely Clostridium, Desulfovibrio, and Bifidobacterium. Such imbalances in the gut microbiome are thought to promote the development of increased gut permeability (the so-called "leaky gut") which in turn is a potential risk factor for the development of ASD. METHODS: We constructed a mathematical model using 2-D Cellular Automata to simulate the growth rates and interactions of three bacterial species, namely Bifidobacterium, Clostridium and Desulfovibrio, with each other and with available nutrients in the gut, and particularly following the introduction of lysozyme into the gut. RESULTS: It was observed from the modeled simulation that increasing or decreasing the population of Clostridium in the gut produces key shifts in the gut microbiome which could potentially increase or decrease the risk of ASD. CONCLUSION: Simulations using our cellular automaton model suggest that it could be useful in predicting the effects produced by alterations to key components of the gut microbiome. In particular, the model demonstrated that the introduction of lysozyme in the gut results in steep reductions in Clostridium growth rate, which in turn could potentially alter the gut microbiome population in such a way as to significantly reduce the risk of developing ASD.

Genome-wide pathway analysis and visualization using gene expression data.

Visualization of results for high performance computing pose special problems due to the complexity and the volume of data these systems manipulate. We present an approach for visualization of c-DNA microarray gene expression data in metabolic and regulatory pathways using multi-resolution animation at different levels of detail. We describe three scoring functions to characterize pathways at the transcriptional level based on gene expression, coregulation and cascade effect. We also assess the significance of each pathway score on the basis of their biological connotation.

Confirmation of parathion, methyl parathion and fenitrothion in biological material on thin-layer plates.

The present work describes a confirmatory procedure for the organophosphorus insecticides having a nitro group. These insecticides are reduced to corresponding amino derivatives on thin-layer plates, and the reduction product as well as the parent compound are resolved and identified by thin-layer chromatography.

Rapid method for extracting aldrin, dieldrin, and endrin from visceral material.

A simple method is described for purifying aldrin, dieldrin, and endrin from visceral material by using a Celite column. Celite retains all interfering materials including Lipids whereas the chlorinated Insecticides are eluted from the column with n-hexane. This extract can be used directly for gas chromatographic analysis.