P. K. Mohanty

CSF proteomics of secondary phase spinal cord injury in human subjects: perturbed molecular pathways post injury.

Recovery of sensory and motor functions following traumatic spinal cord injury (SCI) is dependent on injury severity. Here we identified 49 proteins from cerebrospinal fluid (CSF) of SCI patients, eight of which were differentially abundant among two severity groups of SCI. It was observed that the abundance profiles of these proteins change over a time period of days to months post SCI. Statistical analysis revealed that these proteins take part in several molecular pathways including DNA repair, protein phosphorylation, tRNA transcription, iron transport, mRNA metabolism, immune response and lipid and ATP catabolism. These pathways reflect a set of mechanisms that the system may adopt to cope up with the assault depending on the injury severity, thus leading to observed physiological responses. Apart from putting forward a picture of the molecular scenario at the injury site in a human study, this finding further delineates consequent pathways and molecules that may be altered by external intervention to restrict neural degeneration.

Active-absorbing-state phase transition beyond directed percolation: a class of exactly solvable models.

We introduce and solve a model of hardcore particles on a one-dimensional periodic lattice which undergoes an active-absorbing-state phase transition at finite density. In this model, an occupied site is defined to be active if its left neighbor is occupied and the right neighbor is vacant. Particles from such active sites hop stochastically to their right. We show that both the density of active sites and the survival probability vanish as the particle density is decreased below half. The critical exponents and spatial correlations of the model are calculated exactly using the matrix product ansatz. Exact analytical study of several variations of the model reveals that these nonequilibrium phase transitions belong to a new universality class different from the generic active-absorbing-state phase transition, namely, directed percolation.

Energy diffusion in hard-point systems

Abstract.We investigate the diffusive properties of energy fluctuations in a none-dimensional diatomic chain of hard-point particles interacting through ansquare-well potential. The evolution of initially localized infinitesimal andnfinite perturbations is numerically investigated for different density values.nAll cases belong to the same universality class which can be also interpretednas a Levy walk of the energy with scaling exponent γ=3/5. Thenzero-pressure limit is nevertheless exceptional in that normal diffusionnis found in tangent space and yet anomalous diffusion with a different ratenfor perturbations of finite amplitude. The different behaviour of the twonclasses of perturbations is traced back to the “stable chaos type of dynamicsnexhibited by this model. Finally, the effect of an additional internal degree ofnfreedom is investigated, finding that it does not modify the overall scenario.

Comparison of Modules of Wild Type and Mutant Huntingtin and TP53 Protein Interaction Networks: Implications in Biological Processes and Functions

Disease-causing mutations usually change the interacting partners of mutant proteins. In this article, we propose that the biological consequences of mutation are directly related to the alteration of corresponding protein protein interaction networks (PPIN). Mutation of Huntingtin (HTT) which causes Huntingtons disease (HD) and mutations to TP53 which is associated with different cancers are studied as two example cases. We construct the PPIN of wild type and mutant proteins separately and identify the structural modules of each of the networks. The functional role of these modules are then assessed by Gene Ontology (GO) enrichment analysis for biological processes (BPs). We find that a large number of significantly enriched () GO terms in mutant PPIN were absent in the wild type PPIN indicating the gain of BPs due to mutation. Similarly some of the GO terms enriched in wild type PPIN cease to exist in the modules of mutant PPIN, representing the loss. GO terms common in modules of mutant and wild type networks indicate both loss and gain of BPs. We further assign relevant biological function(s) to each module by classifying the enriched GO terms associated with it. It turns out that most of these biological functions in HTT networks are already known to be altered in HD and those of TP53 networks are altered in cancers. We argue that gain of BPs, and the corresponding biological functions, are due to new interacting partners acquired by mutant proteins. The methodology we adopt here could be applied to genetic diseases where mutations alter the ability of the protein to interact with other proteins.

Spatial correlations in exclusion models corresponding to the zero-range process

We show that the steady state weights of all one-dimensional exclusion models which are mapped to the zero-range process (ZRP) can be written in a matrix product form, where the required matrices depend only on the steady state weights of the ZRP. An infinite-dimensional representation of these matrices which works for generic systems has also been provided. This is in contrast to the case for the usual matrix product ansatz which does not always guarantee a solution for the dynamics dependent algebra that the matrices need to satisfy. The formulation helps us study the spatial correlations of these exclusion processes which are unfeasibly difficult to obtain directly from their ZRP correspondence. To illustrate this method we reproduce certain known results, and then investigate unexplored correlations in some other model systems.

Driven k-mers: correlations in space and time

Steady-state properties of hard objects with exclusion interaction and a driven motion along a one-dimensional periodic lattice are investigated. The process is a generalization of the asymmetric simple exclusion process (ASEP) to particles of length k, and is called the k-ASEP. Here, we analyze both static and dynamic properties of the k-ASEP. Density correlations are found to display interesting features, such as pronounced oscillations in both space and time, as a consequence of the extended length of the particles. At long times, the density autocorrelation decays exponentially in time, except at a special k-dependent density when it decays as a power law. In the limit of large k at a finite density of occupied sites, the appropriately scaled system reduces to a nonequilibrium generalization of the Tonks gas describing the motion of hard rods along a continuous line. This allows us to obtain in a simple way the known two-particle distribution for the Tonks gas. For large but finite k, we also obtain the leading-order correction to the Tonks result.

Distribution of microRNA co-targets exhibit universality across a wide class of species

MicroRNAs (miRNAs) are small non-coding RNAs which regulate gene expression by binding to the UTR of the corresponding messenger RNAs. We construct miRNA co-target networks for a wide class of species (22 in total) using a target prediction database, MicroCosm Targets. For each species, miRNA pairs having one or more common target genes are connected and the number of co-targets are assigned as the weight of these links. We show that the link-weight distributions of all the species collapse remarkably onto each other when scaled suitably —the scale-factor turns out to be a measure of complexity of the species. A simple model, where targets are chosen randomly by miRNAs, could provide the correct scaling function and suggest that the increase of species complexity is related to the increase of the fraction of genes typically targeted by their miRNAs.

Restricted exclusion processes without particle conservation flows to directed percolation

Absorbing phase transitions in restricted exclusion processes are characterized by simple integer exponents. We show that this critical behaviour flows to the directed percolation (DP) universality class when particle conservation is broken suitably. The same transition, when studied using the average density as the controlling parameter, yields critical exponents quite different from DP; we argue that these exponents are actually related to DP by a scaling factor 1/ β DP . These conclusions also apply to conserved lattice gas in one dimension.

Increased expression of ApoA1 after neuronal injury may be beneficial for healing.

ApoA1 is a player in reverse cholesterol transport that initiates multiple cellular pathways on binding to its receptor ABCA1. Its relation to neuronal injury is however unclear. We found ApoA1 to be increasingly abundant at a later time point in the secondary phase of traumatic spinal cord injury. In a cellular injury model of neuroblastoma, ApoA1 showed an initial diminished expression after infliction of injury, which sharply increased thereafter. Subsequently, ApoA1 was shown to alter wound healing dynamics in neuroblastoma injury model. It was observed that an initial lag in scratch wound closure was followed by rapid healing in the ApoA1 treatment group. Activation of ERK pathway and Actin polymerisation by ApoA1 corroborated its role in healing after neuronal injury. We propose that ApoA1 is increasingly expressed and secreted as a delayed response to neuronal injury, and this is a self-protecting mechanism of the injured system.

Conserved mass models with stickiness and chipping

We study a chipping model in a one-dimensional periodic lattice with continuous mass, where a fixed fraction of the mass is chipped off from a site and distributed randomly among the departure site and its neighbours; the remaining mass sticks to the site. In the asymmetric version the chipped off mass is distributed among the site and the right neighbour, whereas in the symmetric version the redistribution occurs among the two neighbours. The steady state mass distribution of the model is obtained using a perturbation method for both parallel and random sequential updates. In most cases, this perturbation theory provides a steady state distribution with reasonable accuracy.