An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae

Corynebacterium diphtheriae (Cd) is a Gram-positive human pathogen responsible for diphtheria infection and once regarded for high mortalities worldwide. The fatality gradually decreased with improved living standards and further alleviated when many immunization programs were introduced. However, numerous drug-resistant strains emerged recently that consequently decreased the efficacy of current therapeutics and vaccines, thereby obliging the scientific community to start investigating new therapeutic targets in pathogenic microorganisms. In this study, our contributions include the prediction of modelome of 13 C. diphtheriae strains, using the MHOLline workflow. A set of 463 conserved proteins were identified by combining the results of pangenomics based core-genome and core-modelome analyses. Further, using subtractive proteomics and modelomics approaches for target identification, a set of 23 proteins was selected as essential for the bacteria. Considering human as a host, eight of these proteins (glpX, nusB, rpsH, hisE, smpB, bioB, DIP1084, and DIP0983) were considered as essential and non-host homologs, and have been subjected to virtual screening using four different compound libraries (extracted from the ZINC database, plant-derived natural compounds and Di-terpenoid Iso-steviol derivatives). The proposed ligand molecules showed favorable interactions, lowered energy values and high complementarity with the predicted targets. Our proposed approach expedites the selection of C. diphtheriaeputative proteins for broad-spectrum development of novel drugs and vaccines, owing to the fact that some of these targets have already been identified and validated in other organisms

CMRegNet-An interspecies reference database for corynebacterial and mycobacterial regulatory networks

BACKGROUND: Organisms utilize a multitude of mechanisms for responding to changing environmental conditions, maintaining their functional homeostasis and to overcome stress situations. One of the most important mechanisms is transcriptional gene regulation. In-depth study of the transcriptional gene regulatory network can lead to various practical applications, creating a greater understanding of how organisms control their cellular behavior. DESCRIPTION: In this work, we present a new database, CMRegNet for the gene regulatory networks of Corynebacterium glutamicum ATCC 13032 and Mycobacterium tuberculosis H37Rv. We furthermore transferred the known networks of these model organisms to 18 other non-model but phylogenetically close species (target organisms) of the CMNR group. In comparison to other network transfers, for the first time we utilized two model organisms resulting into a more diverse and complete network of the target organisms. CONCLUSION: CMRegNet provides easy access to a total of 3,103 known regulations in C. glutamicum ATCC 13032 and M. tuberculosis H37Rv and to 38,940 evolutionary conserved interactions for 18 non-model species of the CMNR group. This makes CMRegNet to date the most comprehensive database of regulatory interactions of CMNR bacteria. The content of CMRegNet is publicly available online via a web interface found at http://lgcm.icb.ufmg.br/cmregnet

Assessment of age-based variations in physiological and anthropometric metrics in Kashmiri men

Background: This study investigates age-related variations in physiological and anthropometric metrics among Kashmiri men aged 60-70 years, focusing on cardiovascular and body composition parameters across two age groups (60-65 and 66-70 years). Methods: Conducted under ethical approval from the university of Delhi, the study included 200 physically active participants, evenly divided into two age groups. Physiological metrics-systolic blood pressure (SBP), diastolic blood pressure (DBP), resting heart rate (RHR), body mass index (BMI), body fat percentage (BFP), waist-to-hip ratio (WHR), and basal metabolic rate (BMR)-were measured using validated tools. Data were analysed using descriptive statistics, independent t-tests, and Pearson’s correlation analysis, with significance set at p<0.05. Results: Significant differences were observed in RHR and BMR between the age groups. Participants aged 66-70 exhibited higher RHR (82.33±3.71 bm⁻¹) compared to those aged 60-65 (80.88±3.46 bm⁻¹, p=0.01). Conversely, the 60-65 group showed a higher BMR (1555.19±184.65 kcal/day) than the 66-70 group (1487.42±165.96 kcal/day, p=0.01). Non-significant differences were noted for SBP, DBP, BMI, BFP, and WHR, though BFP approached significance (p=0.06). Correlation analysis revealed strong interrelations among BMI, BFP, and BMR, with weaker associations between blood pressure metrics and WHR. Conclusions: Age-related changes in RHR and BMR highlight physiological adaptations among older Kashmiri men. These findings underscore the need for tailored health interventions addressing cardiovascular and metabolic risks in this demographic

Optimizing dual modal biometric authentication: hybrid HPO-ANFIS and HPO-CNN framework

In the realm of secure data access, biometric authentication frameworks are vital. This work proposes a hybrid model, with a 90% confidence interval, that combines "hyperparameter optimization-adaptive neuro-fuzzy inference system (HPO-ANFIS)" parallel and "hyperparameter optimization-convolutional neural network (HPO-CNN)" sequential techniques. This approach addresses challenges in feature selection, hyperparameter optimization (HPO), and classification in dual multimodal biometric authentication. HPO-ANFIS optimizes feature selection, enhancing discriminative abilities, resulting in improved accuracy and reduced false acceptance and rejection rates in the parallel modal architecture. Meanwhile, HPO-CNN focuses on optimizing network designs and parameters in the sequential modal architecture. The hybrid model's 90% confidence interval ensures accurate and statistically significant performance evaluation, enhancing overall system accuracy, precision, recall, F1 score, and specificity. Through rigorous analysis and comparison, the hybrid model surpasses existing approaches across critical criteria, providing an advanced solution for secure and accurate biometric authentication

miRegulome: a knowledge-base of miRNA regulomics and analysis

miRNAs regulate post transcriptional gene expression by targeting multiple mRNAs and hence can modulate multiple signalling pathways, biological processes, and patho-physiologies. Therefore, understanding of miRNA regulatory networks is essential in order to modulate the functions of a miRNA. The focus of several existing databases is to provide information on specific aspects of miRNA regulation. However, an integrated resource on the miRNA regulome is currently not available to facilitate the exploration and understanding of miRNA regulomics. miRegulome attempts to bridge this gap. The current version of miRegulome v1.0 provides details on the entire regulatory modules of miRNAs altered in response to chemical treatments and transcription factors, based on validated data manually curated from published literature. Modules of miRegulome (upstream regulators, downstream targets, miRNA regulated pathways, functions, diseases, etc) are hyperlinked to an appropriate external resource and are displayed visually to provide a comprehensive understanding. Four analysis tools are incorporated to identify relationships among different modules based on user specified datasets. miRegulome and its tools are helpful in understanding the biology of miRNAs and will also facilitate the discovery of biomarkers and therapeutics. With added features in upcoming releases, miRegulome will be an essential resource to the scientific community. Availability:http://bnet.egr.vcu.edu/miRegulome

TANMANA BHOJANGATAH CHITAH (PSCHYE AND FOOD)

Three million ago of the south Asian region, India had his own traditional system of medicine which known as Ayurveda. It explains the Rasa, Guna, Virya, and Vipaka of the Dravyas (Medicinal as well as food materials). It gives us some unique concepts to take the food (Asta ahar vidhi Visheshayatana) and its effect on body and mind. Ayurveda is science of wellness which primarily deals in food and behavioural aspects. Food and psychology has a good relation in Ayurveda. Emotions and psychological state has a very profound role in the proper digestion and metabolism of food. Ayurveda explains different psychological and emotional state of digestion, and establishment of ground rule that we should have food with psychological relaxation without any mental disturbance. As well as impact of occupational stress and weight conscious diet on digestion according to modern medical science is discussed. Ayurveda already have many references in many places of different Samhitas especially in Charak, Sushrut and Astang. They clearly told that we have to follow the rules of Asht-Aharvidhi Visheshayatana and they coded that, food has his own properties which helps to enhance the physical factors as well as mental factors of the body. Balanced food habits complete the both Prayojana of the Ayurveda which is “Swasthasya Swastha Rakshanam and Aturasya Vikara Prashamanm Cha”. Emotional status of the person at the food taking time also plays an important role of its digestion and metabolism in the body. A big question arise here that whether first psychology effect in digestion of food or food affecting the psychology of the person