Role of Altered Expression,Activity and Sub-cellular Distribution of Various Histone Deacetylases (HDACs) in Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis

Cellular and Molecular Neurobiology - Histone deacetylases (HDACs) have been described to have both neurotoxic and neuroprotective roles, and partly, depend on its sub-cellular distribution. HDAC...     

Biophysical characterization of mycobacterial model membranes and their interaction with rifabutin: Towards lipid-guided drug screening in tuberculosis

Lipid structure critically dictates the molecular interactions of drugs with membranes influencing passive diffusion, drug partitioning and accumulation, thereby underpinning a lipid-composition specific interplay. Spurring selective passive drug diffusion and uptake through membranes is an obvious solution to combat growing antibiotic resistance with minimized toxicities. However, the spectrum of complex mycobacterial lipids and lack thereof of suitable membrane platforms limits the understanding of mechanisms underlying drug-membrane interactions in tuberculosis. Herein, we developed membrane scaffolds specific to mycobacterial outer membrane and demonstrate them as improvised research platforms for investigating anti-tubercular drug interactions. Combined spectroscopy and microscopy results reveal an enhanced partitioning of model drug Rifabutin in trehalose dimycolate-containing mycobacterial membrane systems. These effects are apportioned to specific changes in membrane structure, order and fluidity leading to enhanced drug interaction. These findings on the membrane biophysical consequences of drug interactions will offer valuable insights for guiding the design of more effective antibiotic drugs coupled with tuned toxicity profiles.     

Independent and combined abiotic stresses affect the physiology and expression patterns of DREB genes differently in stress‐susceptible and resistant genotypes of banana

In tropics, combined stresses of drought and heat often reduce crop productivity in plants like Musa acuminata L. We compared responses of two contrasting banana genotypes, namely the drought‐sensitive Grand Nain (GN; AAA genome) and drought tolerant Hill banana (HB; AAB genome) to individual drought, heat and their combination under controlled and field conditions. Drought and combined drought and heat treatments caused greater reduction in leaf relative water content and greater increase in ion leakage and H₂O₂ content in GN plants, especially in early stages, while the responses were more pronounced in HB at later stages. A combination of drought and heat increased the severity of responses. Real‐time expression patterns of the A‐1 and A‐2 group DEHYDRATION‐RESPONSIVE ELEMENT BINDING (DREB) genes revealed greater changes in expression in leaves of HB plants for both the individual stresses under controlled conditions compared to GN plants. A combination of heat and drought, however, activated most DREB genes in GN but surprisingly suppressed their expression in HB in controlled and field conditions. Its response seems correlated to a better stomatal control over transpiration in HB and a DREB‐independent pathway for the more severe combined stresses unlike in GN. Most of the DREB genes had abscisic acid (ABA)‐responsive elements in their promoters and were also activated by ABA suggesting at least partial dependence on ABA. This study provides valuable information on physiological and molecular responses of the two genotypes to individual and combined drought and heat stresses.     

Leveraging high-throughput screening data,deep neural networks,and conditional generative adversarial networks to advance predictive toxicology

There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) and computational methods are vital. As part of one such HTS effort, embryonic zebrafish were used to examine a suite of morphological and mortality endpoints at six concentrations from over 1,000 unique chemicals found in the ToxCast library (phase 1 and 2). We hypothesized that by using a conditional generative adversarial network (cGAN) or deep neural networks (DNN), and leveraging this large set of toxicity data we could efficiently predict toxic outcomes of untested chemicals. Utilizing a novel method in this space, we converted the 3D structural information into a weighted set of points while retaining all information about the structure. In vivo toxicity and chemical data were used to train two neural network generators. The first was a DNN (Go-ZT) while the second utilized cGAN architecture (GAN-ZT) to train generators to produce toxicity data. Our results showed that Go-ZT significantly outperformed the cGAN, support vector machine, random forest and multilayer perceptron models in cross-validation, and when tested against an external test dataset. By combining both Go-ZT and GAN-ZT, our consensus model improved the SE, SP, PPV, and Kappa, to 71.4%, 95.9%, 71.4% and 0.673, respectively, resulting in an area under the receiver operating characteristic (AUROC) of 0.837. Considering their potential use as prescreening tools, these models could provide in vivo toxicity predictions and insight into the hundreds of thousands of untested chemicals to prioritize compounds for HT testing.     

Characterization and Fungal Inhibition Activity of Siderophore from Wheat Rhizosphere Associated Acinetobacter calcoaceticus Strain HIRFA32

Acinetobacter calcoaceticus HIRFA32 from wheat rhizosphere produced catecholate type of siderophore with optimum siderophore (ca. 92 % siderophore units) in succinic acid medium without FeSO₄ at 28 °C and 24 h of incubation. HPLC purified siderophore appeared as pale yellow crystals with molecular weight [M⁺¹] m/z 347.18 estimated by LCMS. The structure elucidated by ¹H NMR, ¹³C NMR, HMQC, HMBC, NOESY and decoupling studies, revealed that siderophore composed of 2,3-dihydroxybenzoic acid with hydroxyhistamine and threonine as amino acid subunits. In vitro study demonstrated siderophore mediated mycelium growth inhibition (ca. 46.87 ± 0.5 %) of Fusarium oxysporum. This study accounts to first report on biosynthesis of acinetobactin-like siderophore by the rhizospheric strain of A. calcoaceticus and its significance in inhibition of F. oxysporum.     

Gender-dimorphic regulation of liver proteins in Streptozotocin-induced diabetic rats

To address the issue of gender importance in development of diabetes, in the present study, we performed two-dimensional gel electrophoresis (2-DE)-based proteomic study in Streptozotocin (STZ)-induced diabetic rats by investigating gender-dimorphic differential regulation patterns of liver proteins. Animal experiments revealed that females have greater susceptibility towards developing diabetes due to lower insulin secretion, greater severity of liver damage, more impaired regulation of sex hormones as well as lower glucose tolerance and higher blood glucose levels as compared to male diabetic rats when exposed to STZ. Proteomic analysis detected about 730 hepatic protein spots, ranging from 6 to 240 kDa mass between pH 3 ～ 10, of which 45 identified proteins showed gender-dimorphic regulation. Most interesting is that our gender-specific proteome comparison showed that male and female rats displayed different regulations of hepatic proteins involved in lipid metabolism, methionine and citric acid cycles, as well as antioxidative and stress defense system. We for the first time identified chaperonin 10 and D-dopachrome tautomerase showing gender-dependent differential regulation between healthy control and diabetic rats, which have not been reported to date with respect to diabetes pathophysiology. In conclusion, current proteomic study revealed that more severely impaired hepatic protein regulation in female diabetic rats was influential on greater susceptibility of females to STZ-induced diabetes. We expect that the present proteomic data can provide valuable information for evidence-based gender-specific treatment of diabetes.     

Effectiveness of Spray Congealing to Obtain Physically Stabilized Amorphous Dispersions of a Poorly Soluble Thermosensitive API

An amorphous phase produced by micronization up to the molecular or colloidal level of a poorly soluble drug having low lipophilicity can distinctly enhance its solubility characteristics. However, though dispersing the molten mass of a poorly water-soluble drug within polymeric matrix has been found to be most effective in formation of molecular dispersions, the drug molecules which melt at high temperature also accompanied by decomposition, such as acetazolamide, are difficult to formulate as molecular dispersions. Hence, a method is proposed to obtain molecular dispersions of acetazolamide with poloxamer-237 by spray congealing under optimal heat treatment. Uniform molecular and/or colloidal dispersions of the drug were achieved with instantaneous solvent evaporation by mixing a drug solution with molten mass of the plasticizer matrix. Immobilization of dispersed drug molecules was effected subsequently through rapid solidification by spray congealing. Initial characterization of 1:1, 1:1.5, and 1:2 ratios of solid dispersions and devitrification study of an optimized (1:2) ratio ensured efficacy of the proposed method in formation of physically stabilized amorphous systems without thermal degradation and hence resulted in more than ninefold rise in solubility and more than 90% dissolution within initial 10 min. With 1:2 ratio, molecular dispersions could be achieved by initial solvent evaporation stage, which when subjected to spray congealing produced physically stable amorphous systems, without signs of thermal degradation. This study also proposes an opportunity for selection of those polymers with which the drug is immiscible in their fluid state, yet obtaining molecular dispersions.KEY WORDS: low molecular lipophilicity, melt with decomposition, rapid solidification, solid solutions     

FCDD: A Database for Fruit Crops Diseases

Fruit Crops Diseases Database (FCDD) requires a number of biotechnology and bioinformatics tools. The FCDD is a unique bioinformatics resource that compiles information about 162 details on fruit crops diseases, diseases type, its causal organism, images, symptoms and their control. The FCDD contains 171 phytochemicals from 25 fruits, their 2D images and their 20 possible sequences. This information has been manually extracted and manually verified from numerous sources, including other electronic databases, textbooks and scientific journals. FCDD is fully searchable and supports extensive text search. The main focus of the FCDD is on providing possible information of fruit crops diseases, which will help in discovery of potential drugs from one of the common bioresource-fruits. The database was developed using MySQL. The database interface is developed in PHP, HTML and JAVA. FCDD is freely available.

Availability

http://www.fruitcropsdd.com/