Kamal Raj Pardasani

Brief Communication: Ambush hypothesis revisited: Evidences for phylogenetic trends

Recoding events occur in competition with standard readout of the transcript, and are site-specific. Recoding is the reprogramming of mRNA translation by localized alterations in the standard translational rules. Frame-shifting is one class of recoding and defined as protein translations that start not at the first, but either at the second (+1 frame-shift) or the third (-1 frame-shift) nucleotide of the codon. Coding sequences lack stop codons, but frame-shifted sequences contain many stop codons, termed off-frame stops or hidden stops. These hidden stops terminate frame-shifted translation, potentially decreasing energy, and resource waste on non-functional proteins. Our results support this putative ancient adaptive event for the selection of codons that can be part of hidden stop codons. All taxonomic groups represent positive correlation between codon usage frequencies and contribution of codons to hidden stops in off-frame context. Our analysis on nuclear and mitochondrial genomic data revealed phylogenomic selection of ambush mechanism. Strongest impact of this event was found in viruses and bacteria. It has been suggested that this mechanism has occurred and been utilized in the early stages of evolution.

FINITE ELEMENT MODEL TO STUDY THERMAL EFFECT OF UNIFORMLY PERFUSED TUMOR IN DERMAL LAYERS OF ELLIPTICAL SHAPED HUMAN LIMB

In this paper, a two-dimensional finite element model has been developed to study thermal disturbances in elliptical shaped human limbs involving uniformly perfused tumor. The model incorporates the effect of important physiological parameters like blood mass flow rate, self-controlled metabolic activity and thermal conductivity in dermal regions. For tumor regions the uncontrolled rate of metabolic activity and abnormal rate of blood flow have been incorporated. The outer surface of the limb is exposed to the environment where heat loss takes place via the conduction, convection, radiation and evaporation. Appropriate boundary conditions have been framed. The model has been simulated using MATLAB 7.5 to obtain numerical results.

Finite element model to study calcium distribution in oocytes involving voltage gated Ca2+ channel, ryanodine receptor and buffers

Abstract Calcium is one of the most important signalling ions in cell biology performing numerous functions with high specificity. A calcium wave triggers life at fertilization but also can cause cell death. The means by which this single ion can be both highly specific and universal is believed to lie in its spatiotemporal dynamics mediated by ion channels, pumps, receptors and calcium buffers. During oocyte maturation the calcium signalling machinery undergoes differentiation which results in distinctly different calcium release patterns on all organizational scales from puffs to waves. The calcium concentration patterns required during different stages of oocyte maturation are still not completely known. Also the mechanisms involved in calcium dynamics in oocyte cell are still not well understood. In view of above a two dimensional model has been proposed to study calcium dynamics in an oocyte cell. The parameters such as buffers, ryanodine receptor and voltage gated calcium channel are incorporated in the model. Based on the biophysical conditions the initial and boundary conditions have been framed. The model is transformed into variational form and Ritz finite element method has been employed to obtain the solution. A program has been developed in MATLAB 7.10 for the entire problem and executed to obtain numerical results. The numerical results have been used to study the effect of buffers, RyR and VGCC on calcium distribution in oocyte. The results indicate that buffers can significantly decrease the calcium concentration and RyR & VGCC can significantly raise the calcium concentration level in the oocyte cell in order to initiate, sustain and terminate specific activities in the cell. The information generated from the model can be useful to biomedical scientists for clinical and biomedical applications.

One Dimensional Finite Element Method Approach to Study Effect of Ryanodine Receptor and Serca Pump on Calcium Distribution in Oocytes

Oocyte is a female gametocyte or germ cell involved in reproduction. Calcium ions (Ca2+) impact nearly all aspects of cellular life as they play an important role in a variety of cellular functions. Calcium ions contributes to egg activation upon fertilization. Since it is the internal stores which provide most of the calcium signal, much attention has been focused on the intracellular channels. There are mainly two types of calcium channels which release calcium from the internal stores to the cytoplasm in many cell types. These channels are IP3-Receptor and Ryanodine Receptor (RyR). Further it is essential to maintain low cytosolic calcium concentration, the cell engages the Serco/Endoplasmic reticulum Ca2+ ATPases (SERCA) present on the ER or SR membrane for the re-uptake of cytosolic calcium at the expense of ATP hydrolysis. In view of above an attempt has been made to study the effect of the Ryanodine receptor (RyR) and the SERCA pump on the calcium distribution in oocytes. The main aim of this paper is to study the calcium concentration in absence and presence of these parameters. The FEM is used to solve the proposed Mathematical model under appreciate initial and boundary conditions. The program has been developed in MATLAB 7.10 for the entire problem to get numerical results.

Decision Tree Classifier for Classification of Plant and Animal Micro RNA’s

Gene expression is regulated by miRNAs or micro RNAs which can be 21-23 nucleotide in length. They are non coding RNAs which control gene expression either by translation repression or mRNA degradation. Plants and animals both contain miRNAs which have been classified by wet lab techniques. These techniques are highly expensive, labour intensive and time consuming. Hence faster and economical computational approaches are needed. In view of above a machine learning model has been developed for classification of plant and animal miRNAs using decision tree classifier. The model has been tested on available data and it gives results with 91% accuracy.

Modelling the transition from simple to complex Ca2+oscillations in pancreatic acinar cells

A mathematical model is proposed which systematically investigates complex calcium oscillations in pancreatic acinar cells. This model is based on calcium-induced calcium release via inositol trisphosphate receptors (IPR) and ryanodine receptors (RyR) and includes calcium modulation of inositol (1,4,5) trisphosphate (IP3) levels through feedback regulation of degradation and production. In our model, the apical and the basal regions are separated by a region containing mitochondria, which is capable of restricting Ca2+ responses to the apical region. We were able to reproduce the observed oscillatory patterns, from baseline spikes to sinusoidal oscillations. The model predicts that calcium-dependent production and degradation of IP3 is a key mechanism for complex calcium oscillations in pancreatic acinar cells. A partial bifurcation analysis is performed which explores the dynamic behaviour of the model in both apical and basal regions.

Modelling mechanism of calcium oscillations in pancreatic acinar cells

We present a simple model for calcium oscillations in the pancreatic acinar cells. This model is based on the calcium release from two receptors, inositol trisphosphate receptors (IPR) and ryanodine receptors (RyR) through the process of calcium induced calcium release (CICR). In pancreatic acinar cells, when the Ca2+ concentration increases, the mitochondria uptake it very fast to restrict Ca2+ response in the cell. Afterwards, a much slower release of Ca2+ from the mitochondria serves as a calcium supply in the cytosol which causes calcium oscillations. In this paper we discuss a possible mechanism for calcium oscillations based on the interplay among the three calcium stores in the cell: the endoplasmic reticulum (ER), mitochondria and cytosol. Our model predicts that calcium shuttling between ER and mitochondria is a pacemaker role in the generation of Ca2+oscillations. We also consider the calcium dependent production and degradation of (1,4,5) inositol-trisphosphate (IP3), which is a key source of intracellular calcium oscillations in pancreatic acinar cells. In this study we are able to predict the different patterns of calcium oscillations in the cell from sinusoidal to raised-baseline, high frequency and low-frequency baseline spiking.

Three-dimensional finite element model to study calcium distribution in oocytes

Abstract Calcium is the most universal second messenger in cells and plays an important role in initiation, sustenance and termination of various activities in cells required for maintaining the structure and function of the cell. Calcium signal at fertilization is necessary for egg activation and exhibits specialized spatial and temporal dynamics. The specific calcium concentration distribution patterns in oocytes required for various activities such as egg fertilization and maturation are not well understood. In this paper, a three-dimensional finite element model is proposed to study the spatio-temporal calcium distribution in oocyte. The parameters such as buffers, SERCA pump, RyR calcium channel, point source and line source of calcium are incorporated in the model. The appropriate initial and boundary conditions have been framed on the basis of physical condition of the problem. A program is developed in MATLAB for simulation. The results have been used to study the effect of source geometry, RyR calcium channel, SERCA pump and buffers on cytosolic calcium concentration distribution in oocyte.

Mining amino acid association patterns in class B GPCRs

Class B GPCR family is a small group of receptors which are activated by peptides of intermediate length that range from 30 to 40 amino acid residues including hormones, neuropeptides and autocrine factors that mediate diverse physiological functions. They are involved in physiological processes like glucose homeostasis (glucagon and glucagon-like peptide-1), calcium homeostasis and bone turnover (parathyroid hormone and calcitonin), and control of the stress axis (corticotropin-releasing factor). Most of the GPCR structures and their functions are still unknown. Thus, the study of amino acid association patterns can be useful in prediction of their structure and functions. In view of above, in this paper, an attempt has been made to explore amino acid association patterns in class B GPCRs and their relationships with secondary structures and physiochemical properties. The fuzzy association rule mining is employed to take care of uncertainty due to variation in length of sequences. The association rules have been generated with the help of patterns discovered in the sequences.

Naïve Bayes Classifier for Classification of Plant and Animal miRNA

MicroRNAs (miRNA) are single-stranded RNA molecules of about 21-23 nucleotides in length. MicroRNAs (miRNAs) constitute a large family of non coding RNAs that function to regulate gene expression. Till today wet lab experiments have been used to classify the miRNA of plants and animals. The wet lab techniques are highly expensive, labour intensive and time consuming. Thus there arises a need for computational approach for classification of plants and animal miRNA. These computational approaches are fast and economical as compared to wet lab techniques. In view of above a machine learning models has been developed for classification of plant and animal miRNA using Naive Bayes classifier. The model has been tested on available data and it gives results with 85.71% accuracy.