Modulation of Glucose Transporter Protein by Dietary Flavonoids in Type 2 Diabetes Mellitus

Diabetes mellitus (DM) is a metabolic diseases characterized by hyperglycemia due to insufficient or inefficient insulin secretory response. This chronic disease is a global problem and there is a need for greater emphasis on therapeutic strategies in the health system. Phytochemicals such as flavonoids have recently attracted attention as source materials for the development of new antidiabetic drugs or alternative therapy for the management of diabetes and its related complications. The antidiabetic potential of flavonoids are mainly through their modulatory effects on glucose transporter by enhancing GLUT-2 expression in pancreatic β cells and increasing expression and promoting translocation of GLUT-4 via PI3K/AKT, CAP/Cb1/TC10 and AMPK pathways. This review highlights the recent findings on beneficial effects of flavonoids in the management of diabetes with particular emphasis on the investigations that explore the role of these compounds in modulating glucose transporter proteins at cellular and molecular level.     

Fluoride Stress-Mediated Regulation of Tricarboxylic Acid Cycle and Sugar Metabolism in Rice Seedlings in Absence and Presence of Exogenous Calcium

Journal of Plant Growth Regulation - The aim of the current study was to investigate the regulation of tricarboxylic acid (TCA) cycle and sugar metabolism in the seedlings of the rice variety,...     

High Defibrillation Threshold: The Science,Signs and Solutions

Defibrillation threshold (DFT) testing has traditionally been an integral part of implantable cardioverter defibrillator (ICD) implantation. With the increasing number of patients receiving ICDs, physicians are encountering high DFT more often than before. Tackling the problem of high DFT, warrants an in-depth understanding of the science of defibrillation including the key electrophysiological concepts and the underlying molecular mechanisms. Numerous factors have been implicated in the causation of high DFT. Due consideration to the past medical history, pharmacotherapy, laboratory data and cardiac imaging, help in assessing the pre-procedural risk for occurrence of high DFT. Drugs, procedural changes, type and location of ICD lead system are some of the key players in predicting DFT during implantation. In the event of encountering an unacceptably high DFT, we recommend to follow a step-wise algorithm. Ruling out procedural complications like pneumothorax and tamponade is imperative before embarking on a search for potentially reversible clinical or metabolic derangements. Finally, if these attempts fail, the electrophysiologist must choose from a wide range of options for device adjustment and system modification. Although this review article is meant to be a treatise on the science, signs and solutions for high DFT, it is bound by limitations of space and scope of the article.     

A machine-learning approach to calibrate generic Raman models for real-time monitoring of cell culture processes

The manufacture of biotherapeutic proteins consists of complex upstream unit operations requiring multiple raw materials, analytical techniques, and control strategies to produce safe and consistent products for patients. Raman spectroscopy is a ubiquitous multipurpose analytical technique in biopharmaceutical manufacturing for real-time predictions of critical parameters in cell culture processes. The accuracy of Raman spectroscopy relies on chemometric models that need to be carefully calibrated. The existing calibration procedure is nontrivial to implement as it necessitates executing multiple carefully designed experiments for generating relevant calibration sets. Further, existing procedure yields calibration models that are reliable only in operating conditions they were calibrated in. This creates a unique challenge in clinical manufacturing where products have limited production history. In this paper, a novel machine-learning procedure based on just-in-time learning (JITL) is proposed to calibrate Raman models. Unlike traditional techniques, JITL-based generic Raman models can be reliably used for different modalities, cell lines, culture media, and operating conditions. The accuracy of JITL-based generic models is demonstrated on several validation studies involving real-time predictions of critical cell culture performance parameters, such as glucose, glutamate, glutamine, ammonium, lactate, sodium, calcium, viability, and viable cell density. The proposed JITL framework introduces a paradigm shift in the way industrial Raman models are calibrated, which to the best of authors’ knowledge have not been done before.     

Preparation of Monodomain Liquid Crystal Elastomers and Liquid Crystal Elastomer Nanocomposites

LCEs are shape-responsive materials with fully reversible shape change and potential applications in medicine, tissue engineering, artificial muscles, and as soft robots. Here, we demonstrate the preparation of shape-responsive liquid crystal elastomers (LCEs) and LCE nanocomposites along with characterization of their shape-responsiveness, mechanical properties, and microstructure. Two types of LCEs — polysiloxane-based and epoxy-based — are synthesized, aligned, and characterized. Polysiloxane-based LCEs are prepared through two crosslinking steps, the second under an applied load, resulting in monodomain LCEs. Polysiloxane LCE nanocomposites are prepared through the addition of conductive carbon black nanoparticles, both throughout the bulk of the LCE and to the LCE surface. Epoxy-based LCEs are prepared through a reversible esterification reaction. Epoxy-based LCEs are aligned through the application of a uniaxial load at elevated (160 °C) temperatures. Aligned LCEs and LCE nanocomposites are characterized with respect to reversible strain, mechanical stiffness, and liquid crystal ordering using a combination of imaging, two-dimensional X-ray diffraction measurements, differential scanning calorimetry, and dynamic mechanical analysis. LCEs and LCE nanocomposites can be stimulated with heat and/or electrical potential to controllably generate strains in cell culture media, and we demonstrate the application of LCEs as shape-responsive substrates for cell culture using a custom-made apparatus.     

Identification of key genes involved in root development of tomato using expressed sequence tag analysis

Root system of plants are actually fascinating structures, not only critical for plant development, but also important for storage and conduction. Due to its agronomic importance, identification of genes involved in root development has been a subject of intense study. Tomato is the one of the most consumed vegetables in the world. Tomato has been used as model system for dicot plants because of its small genome, well-established transformation techniques and well-constructed physical map. The present study is targeted to identify of root specific genes expressed temporally and also gene(s) involved in lateral root and profuse root development. A total of 890 ESTs were identified from five EST libraries constructed using SSH approach which included temporal gene regulation (early and late) and genes involved in morphogenetic traits (lateral and profuse rooting). One hundred sixty-one unique ESTs identified from various libraries were categorized based on their putative functions and deposited in NCBI-dbEST database. In addition, 36 ESTs were selected for validation of their expression by RT-PCR. The present findings will help in shedding light to the unexplored developmental process of root growth in tomato and plant in general.     

A Stoichiometry Driven Universal Spatial Organization of Backbones of Folded Proteins: Are there Chargaff's Rules for Protein Folding?

Abstract

Protein folding is at least a six decade old problem, since the times of Pauling and Anfinsen. However, rules of protein folding remain elusive till date. In this work, rigorous analyses of several thousand crystal structures of folded proteins reveal a surprisingly simple unifying principle of backbone organization in protein folding. We find that protein folding is a direct consequence of a narrow band of stoichiometric occurrences of amino-acids in primary sequences, regardless of the size and the fold of a protein. We observe that “preferential interactions” between amino-acids do not drive protein folding, contrary to all prevalent views. We dedicate our discovery to the seminal contribution of Chargaff which was one of the major keys to elucidation of the stoichiometry-driven spatially organized double helical structure of DNA.     

Testing the efficacy of hyperspectral (AVIRIS-NG), multispectral (Sentinel-2) and radar (Sentinel-1) remote sensing images to detect native and invasive non-native trees

Biological Invasions - Invasive alien species threaten tropical grasslands and native biodiversity across the globe, including in the natural mosaic of native grasslands and forests in the Shola...