Type 2 diabetic neuropathy with special reference to mitochondrial role and its effective management

Diabetic neuropathy denotes to a group of nerve disorders caused by diabetes. It may occur in both type 1 and type 2 diabetes patients. Mitochondria are essential for energy production as well as intermediary metabolism and equally important in the action of insulin on its targeted tissue. Recently, mitochondrial dysfunctions have been recognized as a cause of diabetes. Hyperglycemia enhances the activity of mitochondrial electron transport chain, leading to mitochondrial hyperpolarisation and elevates the reactive oxygen species (ROS) production. Increased electron availability causes partial reduction of oxygen to superoxide in the proximal electron transport chain which subsequently induces neurodegeneration in diabetes. Currently there is no satisfactory pharmacotherapy for painful diabetic neuropathy. This review summarizes mitochondrial role in type 2 diabetic neuropathy, diagnostic challenges, general treatments and benefits of alternative approach for effective management

Using Signal Processing in Tandem With Adapted Mixture Models for Classifying Genomic Signals

Genomic signal processing has been used successfully in bioinformatics to analyze biomolecular sequences and gain varied insights into DNA structure, gene organization, protein binding, sequence evolution, etc. But challenges remain in finding the appropriate spectral representation of a biomolecular sequence, especially when multiple variable-length sequences need to be handled consistently. In this study, we address this challenge in the context of the well-studied problem of classifying genomic sequences into different taxonomic units (strain, phyla, order, etc.). We propose a novel technique that employs signal processing in tandem with Gaussian mixture models to improve the spectral representation of a sequence and subsequently the taxonomic classification accuracies. The sequences are first transformed into spectra, and projected to a subspace, where sequences belonging to different taxons are better distinguishable. Our method outperforms a similar state-of-the-art method on established benchmark datasets by an absolute margin of 6.06% accuracy

Investigation of new actinobacteria for the biodesulphurisation of diesel fuel

Biodesulphurisation (BDS) is an emerging technology that utilises microorganisms for the removal of sulphur from fossil fuels. Commercial-scale BDS needs the development of highly active bacterial strains which allow easier downstream processing. In this research, a collection of actinobacteria that originated from oil-contaminated soils in Russia were investigated to establish their phylogenetic positions and biodesulphurisation capabilities.The eleven test strains were confirmed as members of the genus Rhodococcus based on 16S rRNA and gyrB gene sequence analysis. Two organisms namely strain F and IEGM 248, confirmed as members of the species R. qingshengii and R. opacus, respectively based on the wholegenome sequence based OrthoANIu values, exhibited robust biodesulphurisation of dibenzothiophene (DBT) and benzothiophene (BT), respectively. R. qingshengii strain F was found to convert DBT to hydroxybiphenyl (2-HBP) with DBTO and DBTO2 as intermediates. The DBT desulphurisation genes of strain F occur as a cluster and share high sequence similarity with the dsz operon of R. erythropolis IGTS8. Rhodococcus opacus IEGM 248 could convert BT into benzofuran. The BDS reaction of both strains follows the well-known 4S pathway of desulphurisation of DBT and BT.When cultured directly in a biphasic growth medium containing 10% (v/v) oil (n-hexadecane or diesel) containing 300 ppm sulphur, strain F formed a stable oil-liquid emulsion, making it unsuitable for direct industrial application despite the strong desulphurisation activity. Whereas the strain 248 formed distinct oil, biomass and aqueous phases which enabled easy extraction of the desulphurised oil with more than 80% reduction in total sulphur content, making it a potential candidate strain for the development of a robust BDS biocatalyst to upgrade crude oils and refinery streams at industrial scale.Whole-genome analysis of these strains also revealed the presence of a high copy number of various monooxygenases and sulphur metabolism related genes that occurred in clusters. These genes offer potential target sites for future mutation strategies to forestall sulphate induced repression of the desulphurisation genes which warrants future investigation

Isolation, characterization of Vibrio and Pseudomonas spp from infected fresh water ornamental fishes and evaluation of potential agents for its control

The present work aims at comparing the antibacterial effect of probiotics, plant extracts of Vitex negundo and Clitoria ternatae and antibiotics against the disease causing bacteria isolated from infected ornamental fishes. The molecular characterization of isolated pathogens was performed by randomly amplified polymorphic DNA (RAPD) technique. The antibacterial effects of probiotic and plant extracts were analyzed by well diffusion method and antibiotic disc was performed by disc diffusion method. Isolated probiotics such as Bacillus sp. showed maximum antibacterial activity of 18 mm and 16 mm zone against Vibrio  sp (V2) and Pseudomonas sp (Ps1) respectively. Leaf extract of Vitex negundo displayed zone of inhibition of 20 mm on Pseudomonas sp (Ps3) and 16 mm on Vibrio sp (V1). Among the antibiotics,  chloramphenicol and ampicillin showed maximum inhibitory activity against Vibrio sp (V3) (25mm) and Pseudomonas sp (Ps2) (25mm) respectively. Even though, antibiotics showed higher inhibitory activity  than the isolated Bacillus bacteria and plant extract (V. negundo and C. ternatae). This study concluded that the use of probiotics as an alternative strategy to the use of antibiotics because of its effective  antibacterial activity and growing concern in violence of disinfectants and antibacterial agents

Do Primitive Neuroectodermal Tumors of the Kidney Have a Predilection for Inferior Vena Cava Involvement? A Case Series and Review of the Literature

The primitive neuroectodermal tumor (PNET) of the kidney is an extremely rare neoplasm, the diagnosis of which mainly depends upon histopathology, immunohistochemistry (IHC), and cytogenetics. A handful of cases reported in the literature mention about aggressive features of this neoplasm. The purpose of our study was to review our experience in not only the diagnosis and management of the patients with renal PNET but also to highlight its propensity to involve inferior vena cava (IVC) and also present a rare occurrence of Ewing’s sarcoma (ES)/PNET of the renal pelvis. The clinical, operative, and histopathology records of four patients of renal PNET treated between January 2017 and December 2019 were reviewed and data analyzed concerning the available literature. Out of the four patients treated, two had level III and IV IVC thrombus, and one had dense desmoplastic adhesions with the IVC wall. One of the cases had a rare presentation of ES/PNET of the renal pelvis. All patients were managed surgically, while only one patient received adjuvant chemotherapy and following up with remission for the last 2 years and 4 months. On IHC, cluster of differentiation-99 (CD-99) was positive in all patients, and three were positive for Friend leukemia integration-1. PNET of the kidney is primarily an immunohistopathological diagnosis. This neoplasm has an increased propensity for the local invasion of surrounding structures. A multimodality approach with surgery, chemotherapy, and radiotherapy could offer better outcomes, although the prognosis of these tumors remains poor

Meta-analysis of Inter-species Liver Co-expression Networks Elucidates Traits Associated with Common Human Diseases

Co-expression networks are routinely used to study human diseases like obesity and diabetes. Systematic comparison of these networks between species has the potential to elucidate common mechanisms that are conserved between human and rodent species, as well as those that are species-specific characterizing evolutionary plasticity. We developed a semi-parametric meta-analysis approach for combining gene-gene co-expression relationships across expression profile datasets from multiple species. The simulation results showed that the semi-parametric method is robust against noise. When applied to human, mouse, and rat liver co-expression networks, our method out-performed existing methods in identifying gene pairs with coherent biological functions. We identified a network conserved across species that highlighted cell-cell signaling, cell-adhesion and sterol biosynthesis as main biological processes represented in genome-wide association study candidate gene sets for blood lipid levels. We further developed a heterogeneity statistic to test for network differences among multiple datasets, and demonstrated that genes with species-specific interactions tend to be under positive selection throughout evolution. Finally, we identified a human-specific sub-network regulated by RXRG, which has been validated to play a different role in hyperlipidemia and Type 2 diabetes between human and mouse. Taken together, our approach represents a novel step forward in integrating gene co-expression networks from multiple large scale datasets to leverage not only common information but also differences that are dataset-specific