Systems modelling predicts chronic inflammation and genomic instability prevent effective mitochondrial regulation during biological ageing

The regulation of mitochondrial turnover under conditions of stress occurs partly through the AMPK-NAD+-PGC1α-SIRT1 signalling pathway. This pathway can be affected by both genomic instability and chronic inflammation since these will result in an increased rate of NAD+ degradation through PARP1 and CD38 respectively. In this work we develop a computational model of this signalling pathway, calibrating and validating it against experimental data. The computational model is used to study mitochondrial turnover under conditions of stress and how it is affected by genomic instability, chronic inflammation and biological ageing in general. We report that the AMPK-NAD+-PGC1α-SIRT1 signalling pathway becomes less responsive with age and that this can prime for the accumulation of dysfunctional mitochondria

Rev1 deficiency induces a metabolic shift in MEFs that can be manipulated by the NAD plus precursor nicotinamide riboside

Replication stress, caused by Rev1 deficiency, is associated with mitochondrial dysfunction, and metabolic stress. However, the overall metabolic alterations and possible interventions to rescue the deficits due to Rev1 loss remain unclear. Here, we report that loss of Rev1 leads to intense changes in metabolites and that this can be manipulated by NAD + supplementation. Autophagy decreases in Rev1-/- mouse embryonic fibroblasts (MEFs) and can be restored by supplementing the NAD+ precursor nicotinamide riboside (NR). The abnormal mitochondrial morphology in Rev1-/-MEFs can be partially reversed by NR supplementation, which also protects the mito-chondrial cristae from rotenone-induced degeneration. In nematodes rev-1 deficiency causes sensitivity to oxidative stress but this cannot be rescued by NR supplementation. In conclusion, Rev1 deficiency leads to metabolic dysregulation of especially lipid and nucleotide metabolism, impaired autophagy, and mitochondrial anomalies, and all of these phenotypes can be improved by NR replenishment in MEFs.Genome Instability and Cance

Genetic Affinities of the Central Indian Tribal Populations

Background: The central Indian state Madhya Pradesh is often called as ‘heart of India ’ and has always been an important region functioning as a trinexus belt for three major language families (Indo-European, Dravidian and Austroasiatic). There are less detailed genetic studies on the populations inhabited in this region. Therefore, this study is an attempt for extensive characterization of genetic ancestries of three tribal populations, namely; Bharia, Bhil and Sahariya, inhabiting this region using haploid and diploid DNA markers. Methodology/Principal Findings: Mitochondrial DNA analysis showed high diversity, including some of the older sublineages of M haplogroup and prominent R lineages in all the three tribes. Y-chromosomal biallelic markers revealed high frequency of Austroasiatic-specific M95-O2a haplogroup in Bharia and Sahariya, M82-H1a in Bhil and M17-R1a in Bhil and Sahariya. The results obtained by haploid as well as diploid genetic markers revealed strong genetic affinity of Bharia (a Dravidian speaking tribe) with the Austroasiatic (Munda) group. The gene flow from Austroasiatic group is further confirmed by their Y-STRs haplotype sharing analysis, where we determined their founder haplotype from the North Munda speaking tribe, while, autosomal analysis was largely in concordant with the haploid DNA results. Conclusions/Significance: Bhil exhibited largely Indo-European specific ancestry, while Sahariya and Bharia showed admixed genetic package of Indo-European and Austroasiatic populations. Hence, in a landscape like India, linguistic labe

Deep Reinforcement Learning Based Control of a Grid Connected Inverter With LCL-Filter for Renewable Solar Applications

This research paper presents a novel approach to current control in Grid-Connected Inverters (GCI) using Deep Reinforcement Learning (DRL) based Twin Delayed Deep Deterministic Policy Gradient (TD3) method. The study focuses on addressing the limitations of traditional control techniques and state of the art techniques, particularly Proportional-Integral (PI) control and Model Predictive Control (MPC), by leveraging the adaptive and autonomous learning capabilities of DRL. The proposed novel modified TD3-based DRL method learns an optimal control policy directly from raw data, enabling the controller to adapt and improve its performance in real-time. The research includes a comprehensive analysis of the implementation and validation of the modified TD3-based DRL control in a grid-connected three phase three level Neutral Point Clamped (NPC) inverter system with Inductor-Capacitor-Inductor (LCL) filter. Real-time validation experiments are conducted to evaluate the control performance, power transfer capability in grid compliance. Furthermore, a detailed comparison is presented with experimentation, highlighting the advantages of the TD3-based DRL control over PI and MPC control techniques. Robustness checking is performed under various operating conditions, including parameter variations and dynamic conditions in the grid. The results analysis demonstrates that the TD3-based DRL control outperforms traditional PI control techniques in terms of static, dynamic response, and robustness. Additionally, The DRL based grid connected inverter current control method is validated in Renewable Energy Source (RES) solar PV grid integration application

Association of Subjective and Objective Sleep Duration as well as Sleep Quality with Non-Invasive Markers of Sub-Clinical Cardiovascular Disease (CVD): A Systematic Review

Aim: Abnormal daily sleep duration and quality have been linked to hypertension, diabetes, stroke, and overall cardiovascular disease (CVD) morbidity& mortality. However, the relationship between daily sleep duration and quality with subclinical measures of CVD remains less well studied. This systematic review evaluated how daily sleep duration and quality affect burden of subclinical CVD in subjects free of symptomatic CVD. Methods: Literature search was done via MEDLINE, EMBASE, Web of Science until June 2016 and 32 studies met the inclusion criteria. Sleep duration and quality were measured either via subjective methods, as self-reported questionnaires or Pittsburg Sleep Quality Index (PSQI) or via objective methods, as actigraphy or polysomnography or by both. Among subclinical CVD measures, coronary artery calcium (CAC) was measured by electron beam computed tomography, Carotid intima-media thickness (CIMT) measured by high-resolution B-mode ultrasound on carotid arteries, endothelial/microvascular function measured by flow mediated dilation (FMD) or peripheral arterial tone (PAT) or iontophoresis or nailfold capillaroscopy, and arterial stiffness measured by pulse wave velocity (PWV) or ankle brachial index (ABI). Results: Subjective short sleep duration was associated with CAC and CIMT, but variably associated with endothelial dysfunction (ED) and arterial stiffness; however, subjective long sleep duration was associated with CAC, CIMT and arterial stiffness, but variably associated with ED. Objective short sleep duration was positively associated with CIMT and variably with CAC but not associated with ED. Objective long sleep duration was variably associated with CAC and CIMT but not associated with ED. Poor subjective sleep quality was significantly associated with ED and arterial stiffness but variably associated with CAC and CIMT. Poor objective sleep quality was significantly associated with CIMT, and ED but variably associated with CAC. Conclusions: Overall, our review provided mixed results, which is generally in line with published literature, with most of the studies showing a significant relationship with subclinical CVD, but only some studies failed to demonstrate such an association. Although such mechanistic relationship needs further evaluation in order to determine appropriate screening strategies in vulnerable populations, this review strongly suggested the existence of a relationship between abnormal sleep duration and quality with increased subclinical CVD burden

Genome-wide analysis correlates Ayurveda Prakriti

The practice of Ayurveda, the traditional medicine of India, is based on the concept of three major constitutional types (Vata, Pitta and Kapha) defined as ``Prakriti''. To the best of our knowledge, no study has convincingly correlated genomic variations with the classification of Prakriti. In the present study, we performed genome-wide SNP (single nucleotide polymorphism) analysis (Affymetrix, 6.0) of 262 well-classified male individuals (after screening 3416 subjects) belonging to three Prakritis. We found 52 SNPs (p <= 1 x 10(-5)) were significantly different between Prakritis, without any confounding effect of stratification, after 10(6) permutations. Principal component analysis (PCA) of these SNPs classified 262 individuals into their respective groups (Vata, Pitta and Kapha) irrespective of their ancestry, which represent its power in categorization. We further validated our finding with 297 Indian population samples with known ancestry. Subsequently, we found that PGM1 correlates with phenotype of Pitta as described in the ancient text of Caraka Samhita, suggesting that the phenotypic classification of India's traditional medicine has a genetic basis; and its Prakriti-based practice in vogue for many centuries resonates with personalized medicine