Dynamics of the amino acid composition of the medium during cultivation of isolated organs by the directed perfusion method]

The dynamics of the amino acid composition of the medium under conditions of adequate perfusion of the isolated organs of a dog (sternum, kidney and liver) was studied. It was found that after a 6-hour perfusion of the complex of organs the amount in the perfusion medium of such amino acids as histidine, lysine, alanine, considerably increased, whereas the amount of arginine, serine, aspartic acid, threonine with glutamine, isoleucine, proline, leucine and valine decreased as compared with their initial concentration. The dynamics of the amino acid medium composition during a 4-hour perfusion was studied in experiments with the isolated sternum. The concentration of alanine, lysine and histidine increased in the medium. At the same time there was seen a decrease in the concentration of serine, aspartic acid, isoleucine, tyrosine and phenyl-alanine.     

Growth and luminescence of luminous bacteria promoted by agents of microbial origin

The examination of four species of luminous bacteria Photobacterium leiognathi, Photobacterium phosphoreum, Vibrio fischeri and Vibrio harveyi has enabled us to reveal some nutrient medium components effecting growth, luminescence intensity and luciferase synthesis. These agents are nucleic components (nucleotides, nucleosides and amine bases), amino acids and vitamins, which are part of hydrolysates from the biomass of various lithotrophic microorganisms, hydrogen-oxidizing, ironoxidizing and carboxydobacteria. The effect of promoting agents essentially alters the physiological state and ultrastructure of the cells of luminous bacteria and increases luciferase biosynthesis two- to three-fold compared to a control.     

Prediction of the three-dimensional structure of aflatoxin of Aspergillus flavus by homology modelling

Aflatoxins are polyketide-derived secondary metabolites produced by Aspergillus spp. The toxic effects of aflatoxins have adverse consequences for human health and agricultural economics. The aflR gene, a regulatory gene for aflatoxin biosynthesis, encodes a protein containing a zinc-finger DNA-binding motif. AFLR-Protein three-dimensional model was generated using Robetta server. The modeled AFLR-Protein was further optimization and validation using Rampage. In the simulations, we monitored the backbone atoms and the C-α-helix of the modeled protein. The low RMSD and the simulation time indicate that, as expected, the 3D structural model of AFLR-protein represents a stable folding conformation. This study paves the way for generating computer molecular models for proteins whose crystal structures are not available and which would aid in detailed molecular mechanism of inhibition of aflatoxin.     

Classification of large microarray datasets using fast random forest construction

Random forest is an ensemble classification algorithm. It performs well when most predictive variables are noisy and can be used when the number of variables is much larger than the number of observations. The use of bootstrap samples and restricted subsets of attributes makes it more powerful than simple ensembles of trees. The main advantage of a random forest classifier is its explanatory power: it measures variable importance or impact of each factor on a predicted class label. These characteristics make the algorithm ideal for microarray data. It was shown to build models with high accuracy when tested on high-dimensional microarray datasets. Current implementations of random forest in the machine learning and statistics community, however, limit its usability for mining over large datasets, as they require that the entire dataset remains permanently in memory. We propose a new framework, an optimized implementation of a random forest classifier, which addresses specific properties of microarray data, takes computational complexity of a decision tree algorithm into consideration, and shows excellent computing performance while preserving predictive accuracy. The implementation is based on reducing overlapping computations and eliminating dependency on the size of main memory. The implementation's excellent computational performance makes the algorithm useful for interactive data analyses and data mining.     

Mapping the amino acid properties of constituent nucleoporins onto the yeast nuclear pore complex

Visualization of molecular structures aids in the understanding of structural and functional roles of biological macromolecules. Macromolecular transport between the cell nucleus and cytoplasm is facilitated by the nuclear pore complex (NPC). The ring structure of the NPC is large and contains several distinct proteins (nucleoporins) which function as a selective gate for the passage of certain molecules into and out of the nucleus. In this note we demonstrate the utility of a python code that allows direct mapping of the physiochemical properties of the constituent nucleoporins on the scaffold of the yeast NPC׳s cytoplasmic view. We expect this tool to be useful for researchers to visualize the NPC based on their physiochemical properties and how it alters when specific mutations are introduced in one or more of the nucleoporins. The code developed using Python is available freely from the authors.