Evaluation of chitosan nanoformulations as potent anti-HIV therapeutic systems

Background: Antiretroviral Therapy (ART) is currently the major therapeutic intervention in the treatment of AIDS. ART, however, is severely limited due to poor availability, high cytotoxicity, and enhanced metabolism and clearance of the drug molecules by the renal system. The use of nanocarriers encapsulating the antiretroviral drugs may provide a solution to the aforementioned problems. Importantly, the application of mildly immunogenic polymeric carrier confers the advantage of making the nanoparticles more visible to the immune system leading to their efficient uptake by the phagocytes. Methods: The saquinavir-loaded chitosan nanopartides were characterized by transmission electron microscopy and differential scanning calorimetry and analyzed for the encapsulation efficiency, swelling characteristics, particle size properties, and the zeta potential. Furthermore, cellular uptake of the chitosan nanocarriers was evaluated using confocal microscopy and Flow cytometry. The antiviral efficacy was quantified using viral infection of the target cells. Results: Using novel chitosan carriers loaded with saquinavir, a protease inhibitor, we demonstrate a drug encapsulation efficiency of 75% and cell targeting efficiency greater than 92%. As compared to the soluble drug control, the saquinavir-loaded chitosan carriers caused superior control of the viral proliferation as measured by using two different viral strains, NL4-3 and Indie-C1, and two different target T-cells, Jurkat and CEM-CCR5. Conclusion: Chitosan nanoparticles loaded with saquinavir were characterized and they demonstrated superior drug loading potential with greater cell targeting efficiency leading to efficient control of the viral proliferation in target T-cells. General significance: Our data ascertain the potential of chitosan nanocarriers as novel vehicles for HIV-1 therapeutics. (C) 2013 Elsevier B.V. All rights reserved.

Cooperative Communication of UAV to Perform Multi-task Using Nature Inspired Techniques

In this paper, the approach for assigning cooperative communication of Uninhabited Aerial Vehicles (UAV) to perform multiple tasks on multiple targets is posed as a combinatorial optimization problem. The multiple task such as classification, attack and verification of target using UAV is employed using nature inspired techniques such as Artificial Immune System (AIS), Particle Swarm Optimization (PSO) and Virtual Bee Algorithm (VBA). The nature inspired techniques have an advantage over classical combinatorial optimization methods like prohibitive computational complexity to solve this NP-hard problem. Using the algorithms we find the best sequence in which to attack and destroy the targets while minimizing the total distance traveled or the maximum distance traveled by an UAV. The performance analysis of the UAV to classify, attack and verify the target is evaluated using AIS, PSO and VBA.

A Stochastic Chemical Dynamic Approach to Correlate Autoimmunity and Optimal Vitamin-D Range

Motivated by several recent experimental observations that vitamin-D could interact with antigen presenting cells (APCs) and T-lymphocyte cells (T-cells) to promote and to regulate different stages of immune response, we developed a coarse grained but general kinetic model in an attempt to capture the role of vitamin-D in immunomodulatory responses. Our kinetic model, developed using the ideas of chemical network theory, leads to a system of nine coupled equations that we solve both by direct and by stochastic (Gillespie) methods. Both the analyses consistently provide detail information on the dependence of immune response to the variation of critical rate parameters. We find that although vitamin-D plays a negligible role in the initial immune response, it exerts a profound influence in the long term, especially in helping the system to achieve a new, stable steady state. The study explores the role of vitamin-D in preserving an observed bistability in the phase diagram (spanned by system parameters) of immune regulation, thus allowing the response to tolerate a wide range of pathogenic stimulation which could help in resisting autoimmune diseases. We also study how vitamin-D affects the time dependent population of dendritic cells that connect between innate and adaptive immune responses. Variations in dose dependent response of anti-inflammatory and pro-inflammatory T-cell populations to vitamin-D correlate well with recent experimental results. Our kinetic model allows for an estimation of the range of optimum level of vitamin-D required for smooth functioning of the immune system and for control of both hyper-regulation and inflammation. Most importantly, the present study reveals that an overdose or toxic level of vitamin-D or any steroid analogue could give rise to too large a tolerant response, leading to an inefficacy in adaptive immune function.

Multimodal therapy for complete regression of malignant melanoma using constrained nonlinear optimal dynamic inversion

Using a realistic nonlinear mathematical model for melanoma dynamics and the technique of optimal dynamic inversion (exact feedback linearization with static optimization), a multimodal automatic drug dosage strategy is proposed in this paper for complete regression of melanoma cancer in humans. The proposed strategy computes different drug dosages and gives a nonlinear state feedback solution for driving the number of cancer cells to zero. However, it is observed that when tumor is regressed to certain value, then there is no need of external drug dosages as immune system and other therapeutic states are able to regress tumor at a sufficiently fast rate which is more than exponential rate. As model has three different drug dosages, after applying dynamic inversion philosophy, drug dosages can be selected in optimized manner without crossing their toxicity limits. The combination of drug dosages is decided by appropriately selecting the control design parameter values based on physical constraints. The process is automated for all possible combinations of the chemotherapy and immunotherapy drug dosages with preferential emphasis of having maximum possible variety of drug inputs at any given point of time. Simulation study with a standard patient model shows that tumor cells are regressed from 2 x 107 to order of 105 cells because of external drug dosages in 36.93 days. After this no external drug dosages are required as immune system and other therapeutic states are able to regress tumor at greater than exponential rate and hence, tumor goes to zero (less than 0.01) in 48.77 days and healthy immune system of the patient is restored. Study with different chemotherapy drug resistance value is also carried out. (C) 2014 Elsevier Ltd. All rights reserved.

Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: multi-scale approach

Human Leukocyte Antigen (HLA) plays an important role, in presenting foreign pathogens to our immune system, there by eliciting early immune responses. HLA genes are highly polymorphic, giving rise to diverse antigen presentation capability. An important factor contributing to enormous variations in individual responses to diseases is differences in their HLA profiles. The heterogeneity in allele specific disease responses decides the overall disease epidemiological outcome. Here we propose an agent based computational framework, capable of incorporating allele specific information, to analyze disease epidemiology. This framework assumes a SIR model to estimate average disease transmission and recovery rate. Using epitope prediction tool, it performs sequence based epitope detection for a given the pathogenic genome and derives an allele specific disease susceptibility index depending on the epitope detection efficiency. The allele specific disease transmission rate, that follows, is then fed to the agent based epidemiology model, to analyze the disease outcome. The methodology presented here has a potential use in understanding how a disease spreads and effective measures to control the disease.

Comparative proteomic analysis of primordial follicles from ovaries of immature and aged rats

Age related decline in reproductive performance in women is well documented and apoptosis has been considered as one of the reasons for the decline of primordial follicle reserve. Recently we observed a decline in the efficiency of DNA repair ability in aged rat primordial follicles as demonstrated by decreased mRNA levels of DNA repair genes BRCA1 and H2AX. In the present study, a two-dimensional electrophoresis (2DE) proteomic approach was employed to identify differentially expressed proteins in primordial follicles isolated from ovaries of immature (approximate to 20 days) and aged (approximate to 400-450 days) rats. Using MALDI-TOF/TOF MS, we identified 13 differentially expressed proteins (p<0.05) which included seven up-regulated and six down-regulated proteins in aged primordial follicles. These proteins are involved in a wide range of biological functions including apoptosis, DNA repair, and the immune system. Interestingly, the differentially expressed proteins such as FIGNL1 (DNA repair) and BOK (apoptotic protein) have not been previously reported in the rat primordial follicles and these proteins can be related to some common features of ovarian aging such as loss of follicle reserve and genome integrity. The quantitative differences of two important proteins BOK and FIGNL1 observed by the proteomic analysis were correlated with the transcript levels, as determined by semi-quantitative RT-PCR. Our results improve the current knowledge about protein factors associated with molecular changes in rat primordial follicles as a function of aging and our understanding of the proteomic processes involved in degenerative changes observed in aging primordial follicles.

Characterization of type I interferon pathway during hepatic differentiation of human pluripotent stem cells and hepatitis C virus infection

Pluripotent stem cells are being actively studied as a cell source for regenerating damaged liver. For long-term survival of engrafting cells in the body, not only do the cells have to execute liver-specific function but also withstand the physical strains and invading pathogens. The cellular innate immune system orchestrated by the interferon (IFN) pathway provides the first line of defense against pathogens. The objective of this study is to assess the innate immune function as well as to systematically profile the IFN-induced genes during hepatic differentiation of pluripotent stem cells. To address this objective, we derived endodermal cells (day 5 post-differentiation), hepatoblast (day 15) and hepatocyte-like cells (day 21) from human embryonic stem cells (hESCs). Day 5, 15 and 21 cells were stimulated with IFN-alpha and subjected to IFN pathway analysis. Transcriptome analysis was carried out by RNA sequencing. The results showed that the IFN-alpha treatment activated STAT-JAK pathway in differentiating cells. Transcriptome analysis indicated stage specific expression of classical and non-classical IFN-stimulated genes (ISGs). Subsequent validation confirmed the expression of novel ISGs including RASGRP3, CLMP and TRANK1 by differentiated hepatic cells upon IFN treatment. Hepatitis C virus replication in hESC-derived hepatic cells induced the expression of ISGs - LAMP3, ETV7, RASGRP3, and TRANK1. The hESC-derived hepatic cells contain intact innate system and can recognize invading pathogens. Besides assessing the tissue-specific functions for cell therapy applications, it may also be important to test the innate immune function of engrafting cells to ensure adequate defense against infections and improve graft survival. (C) 2015 The Authors. Published by Elsevier B.V.