The effects of escitalopram on myocardial apoptosis and the expression of Bax and Bcl-2 during myocardial ischemia/reperfusion in a model of rats with depression

BackgroundMajor depressive disorder (MDD) is an independent risk factor for coronary heart disease (CHD), and influences the occurrence and prognosis of cardiovascular events. Although there is evidence that antidepressants may be cardioprotective after acute myocardial infarction (AMI) comorbid with MDD, the operative pathophysiological mechanisms remain unclear. Our aim was therefore to explore the molecular mechanisms of escitalopram on myocardial apoptosis and the expression of Bax and Bcl-2 in a rat model of depression during myocardial ischemia/reperfusion (I/R).MethodsRats were divided randomly into 3 groups (n = 8): D group (depression), DI/R group (depression with myocardial I/R) and escitalopram + DI/R group. The rats in all three groups underwent the same chronic mild stress and separation for 21 days, at the same time, in the escitalopram + DI/R group, rats were administered escitalopram by gavage (10 mg/kg/day). Ligation of the rat¿s left anterior descending branch was done in the myocardial I/R model. Following which behavioral tests were done. The size of the myocardial infarction was detected using 1.5% TTC dye. The Tunel method was used to detect apoptotic myocardial cells, and both the Rt-PCR method and immunohistochemical techniques were used to detect the expression of Bcl¿2 and Bax.ResultsCompared with the D and DI/R groups, rats in Escitalopram + DI/R group showed significantly increased movements and sucrose consumption (P < .01). Compared with the DI/R group, the myocardial infarct size in the escitalopram + DI/R group was significantly decreased (P < .01). Compared with the D group, there were significantly increased apoptotic myocardial cells in the DI/R and escitalopram + DI/R groups (P < .01); however compared with the DI/R group, apoptotic myocardial cell numbers in the escitalopram + DI/R group were significantly decreased (P < .01). Compared with the DI/R group, there was a down-regulated Bax:Bcl-2 ratio in the escitalopram + DI/R group (P < .01).ConclusionsThese results suggest that in patients with AMI comorbid with MDD, there is an increase in pro-apoptotic pathways that is reversed by escitalopram. This suggests that clinically escitalopram may have a direct cardioprotective after acute myocardial infarction.

Efficient simulations of the aqueous bio-interface of graphitic nanostructures with a polarisable model.

To fully harness the enormous potential offered by interfaces between graphitic nanostructures and biomolecules, detailed connections between adsorbed conformations and adsorption behaviour are needed. To elucidate these links, a key approach, in partnership with experimental techniques, is molecular simulation. For this, a force-field (FF) that can appropriately capture the relevant physics and chemistry of these complex bio-interfaces, while allowing extensive conformational sampling, and also supporting inter-operability with known biological FFs, is a pivotal requirement. Here, we present and apply such a force-field, GRAPPA, designed to work with the CHARMM FF. GRAPPA is an efficiently implemented polarisable force-field, informed by extensive plane-wave DFT calculations using the revPBE-vdW-DF functional. GRAPPA adequately recovers the spatial and orientational structuring of the aqueous interface of graphene and carbon nanotubes, compared with more sophisticated approaches. We apply GRAPPA to determine the free energy of adsorption for a range of amino acids, identifying Trp, Tyr and Arg to have the strongest binding affinity and Asp to be a weak binder. The GRAPPA FF can be readily incorporated into mainstream simulation packages, and will enable large-scale polarisable biointerfacial simulations at graphitic interfaces, that will aid the development of biomolecule-mediated, solution-based graphene processing and self-assembly strategies.

Molecular dynamics study of response of liquid N,N-dimethylformamide to externally applied electric field using a polarizable force field

The behavior of Liquid N,N-dimethylformamide subjected to a wide range of externally applied electric fields (from 0.001 V/nm to 1 V/nm) has been investigated through molecular dynamics simulation. To approach the objective the AMOEBA polarizable force field was extended to include the interaction of the external electric field with atomic partial charges and the contribution to the atomic polarization. The simulation results were evaluated with quantum mechanical calculations. The results from the present force field for the liquid at normal conditions were compared with the experimental and molecular dynamics results with non-polarizable and other polarizable force fields. The uniform external electric fields of higher than 0.01 V/nm have a significant effect on the structure of the liquid, which exhibits a variation in numerous properties, including molecular polarization, local cluster structure, rotation, alignment, energetics, and bulk thermodynamic and structural properties.

Distinct kinetics of molecular gelation in a confined space and its relation to the structure and property of thin gel films

Thin films of molecular gels formed in a confined space have potential applications in transdermal delivery, artificial skin, molecular electronics, etc. The microstructures and properties of thin gel films can be significantly different from those of their bulk counterparts. However, so far a comprehensive understanding of the effects of spatial confinement on the molecular gelation kinetics, fiber network structure and related mechanical properties is still lacking. In this work, using rheological techniques, we investigated the effect of one-dimensional confinement on the formation kinetics of fiber networks in the molecular gelation process. Fractal analyses of the kinetic information in terms of an extended Dickinson model enabled us to describe quantitatively the distinct kinetic signature of molecular gelation. The structural features derived from gelation kinetics support well the fractal patterns of the fiber networks acquired by optical and electron microscopy. With the kinetics-structure correlation, we can gain an in-depth understanding of the confinement-induced differences in the structure and consequently the mechanical properties of a model molecular gelling system. Particularly, the confinement induced structural transition, from a three-dimensional, dense and compact spherulitic network composed of highly branched fibers to a quasi-two-dimensional sparse spherulitic network composed of less branched fibers and entangled fibrils at the boundary areas, renders a gel film to become less stiff but more ductile. Our study suggests here a new strategy of engineering the fiber network microstructure to achieve functional gel films with unusual but useful properties.

Molecular targets in arthritis and recent trends in nanotherapy

Due to its severity and increasing epidemiology, arthritis needs no description. There are various forms of arthritis most of which are disabling, very painful, and common. In spite of breakthroughs in the field of drug discovery, there is no cure for arthritis that can eliminate the disease permanently and ease the pain. The present review focuses on some of the most successful drugs in arthritis therapy and their side effects. Potential new targets in arthritis therapy such as interleukin-1β, interleukin-17A, tumor necrosis factor alpha, osteopontin, and several others have been discussed here, which can lead to refinement of current therapeutic modalities. Mechanisms for different forms of arthritis have been discussed along with the molecules that act as potential biomarkers for arthritis. Due to the difficulty in monitoring the disease progression to detect the advanced manifestations of the diseases, drug-induced cytotoxicity, and problems with drug delivery; nanoparticle therapy has gained the attention of the researchers. The unique properties of nanoparticles make them highly attractive for the design of novel therapeutics or diagnostic agents for arthritis. The review also focuses on the recent trends in nanoformulation development used for arthritis therapy. This review is, therefore, important because it describes the relevance and need for more arthritis research, it brings forth a critical discussion of successful drugs in arthritis and analyses the key molecular targets. The review also identifies several knowledge gaps in the published research so far along with the proposal of new ideas and future directions in arthritis therapy.

Expected shannon entropy and shannon differentiation between subpopulations for neutral genes under the finite island model

Shannon entropy H and related measures are increasingly used in molecular ecology and population genetics because (1) unlike measures based on heterozygosity or allele number, these measures weigh alleles in proportion to their population fraction, thus capturing a previously-ignored aspect of allele frequency distributions that may be important in many applications; (2) these measures connect directly to the rich predictive mathematics of information theory; (3) Shannon entropy is completely additive and has an explicitly hierarchical nature; and (4) Shannon entropy-based differentiation measures obey strong monotonicity properties that heterozygosity-based measures lack. We derive simple new expressions for the expected values of the Shannon entropy of the equilibrium allele distribution at a neutral locus in a single isolated population under two models of mutation: the infinite allele model and the stepwise mutation model. Surprisingly, this complex stochastic system for each model has an entropy expressable as a simple combination of well-known mathematical functions. Moreover, entropy- and heterozygosity-based measures for each model are linked by simple relationships that are shown by simulations to be approximately valid even far from equilibrium. We also identify a bridge between the two models of mutation. We apply our approach to subdivided populations which follow the finite island model, obtaining the Shannon entropy of the equilibrium allele distributions of the subpopulations and of the total population. We also derive the expected mutual information and normalized mutual information ("Shannon differentiation") between subpopulations at equilibrium, and identify the model parameters that determine them. We apply our measures to data from the common starling (Sturnus vulgaris) in Australia. Our measures provide a test for neutrality that is robust to violations of equilibrium assumptions, as verified on real world data from starlings.

EpCAM aptamer-mediated survivin silencing sensitized cancer stem cells to doxorubicin in a breast cancer model

Understanding the molecular basis of drug resistance and utilising this information to overcome chemoresistance remains a key challenge in oncology. Here we report that survivin, a key protein implicated in drug resistance, is overexpressed in cancer stem cell pool of doxorubicin-resistant breast cancer cells. Moreover, by utilising an active targeting system consisting of an RNA aptamer targeted against the epithelial cell adhesion molecule and a Dicer substrate survivin siRNA, we could deliver a high dose of the siRNA to cancer stem cells in xenograft tumours. Importantly, silencing of survivin with this aptamer-siRNA chimera in cancer stem cell population led to the reversal of chemoresistance, such that combined treatment with low dose of doxorubicin inhibited stemness, eliminated cancer stem cells via apoptosis, suppressed tumour growth, and prolonged survival in mice bearing chemoresistant tumours. This strategy for in vivo cancer stem cell targeting has wide application for future effective silencing of anti-death genes and in fact any dysregulated genes involved in chemoresistance and tumour relapse.

Testing the transferability of a coarse-grained model to intrinsically disordered proteins

The intermediate-resolution coarse-grained protein model PLUM [T. Bereau and M. Deserno, J. Chem. Phys., 2009, 130, 235106] is used to simulate small systems of intrinsically disordered proteins involved in biomineralisation. With minor adjustments to reduce bias toward stable secondary structure, the model generates conformational ensembles conforming to structural predictions from atomistic simulation. Without additional structural information as input, the model distinguishes regions of the chain by predicted degree of disorder, manifestation of structure, and involvement in chain dimerisation. The model is also able to distinguish dimerisation behaviour between one intrinsically disordered peptide and a closely related mutant. We contrast this against the poor ability of PLUM to model the S1 quartz-binding peptide.

Polymer architecture effect on sodium ion transport in PSTFSI-based ionomers: a molecular dynamics study

In this study, we investigated the effect of polymer architecture on the ion dynamics and local structure to understand the factors that might lead to the design of highly conductive and mechanically robust polyelectrolytes. Molecular dynamic simulations were undertaken on the sodium poly[(4-styrenesulfonyl) (trifluoromethanesulfonyl) imide] P(STFSINa) homopolymer and its copolymers with either ether or styrene spacer groups to investigate the spacer length and polarity dependence of Na-ion transport. Using a scaled charge model, we observed a continuous ion aggregate network in the homopolymer, which facilitates the fast ion dynamics despite the rigid polymer matrix. The longest spacer groups disrupt this percolating ionic network differently, with the ether group being more disruptive than the styrene group, and leading to more discrete ionic aggregates. The copolymer with the ether spacer was also found to result in an alternative Na-ion diffusion mechanism.