Effectiveness of participatory women’s groups scaled up by the public health system to improve birth outcomes in Jharkhand, eastern India: a pragmatic cluster non-randomised controlled trial

INTRODUCTION: The WHO recommends community mobilisation with women’s groups practising participatory learning and action (PLA) to improve neonatal survival in high-mortality settings. This intervention has not been evaluated at scale with government frontline workers. METHODS: We did a pragmatic cluster non-randomised controlled trial of women’s groups practising PLA scaled up by government front-line workers in Jharkhand, eastern India. Groups prioritised maternal and newborn health problems, identified strategies to address them, implemented the strategies and evaluated progress. Intervention coverage and quality were tracked state-wide. Births and deaths to women of reproductive age were monitored in six of Jharkhand’s 24 districts: three purposively allocated to an early intervention start (2017) and three to a delayed start (2019). We monitored vital events prospectively in 100 purposively selected units of 10 000 population each, during baseline (1 March 2017–31 August 2017) and evaluation periods (1 September 2017–31 August 2019). The primary outcome was neonatal mortality. RESULTS: We identified 51 949 deliveries and conducted interviews for 48 589 (93.5%). At baseline, neonatal mortality rates (NMR) were 36.9 per 1000 livebirths in the early arm and 39.2 in the delayed arm. Over 24 months of intervention, the NMR was 29.1 in the early arm and 39.2 in the delayed arm, corresponding to a 24% reduction in neonatal mortality (adjusted OR (AOR) 0.76, 95% CI 0.59 to 0.98), including 26% among the most deprived (AOR 0.74, 95% CI 0.57 to 0.95). Twenty of Jharkhand’s 24 districts achieved adequate meeting coverage and quality. In these 20 districts, the intervention saved an estimated 11 803 newborn lives (min: 1026–max: 20 527) over 42 months, and cost 41 international dollars per life year saved. CONCLUSION: Participatory women’s groups scaled up by the Indian public health system reduced neonatal mortality equitably in a largely rural state and were highly cost-effective, warranting scale-up in other high-mortality rural settings. TRIAL REGISTRATION: ISRCTN99422435

Artificial intelligence in biological activity prediction

Artificial intelligence has become an indispensable resource in chemoinformatics. Numerous machine learning algorithms for activity prediction recently emerged, becoming an indispensable approach to mine chemical information from large compound datasets. These approaches enable the automation of compound discovery to find biologically active molecules with important properties. Here, we present a review of some of the main machine learning studies in biological activity prediction of compounds, in particular for sweetness prediction. We discuss some of the most used compound featurization techniques and the major databases of chemical compounds relevant to these tasks.This study was supported by the European Commission through project SHIKIFACTORY100 - Modular cell factories for the production of 100 compounds from the shikimate pathway (Reference 814408), and by the Portuguese FCT under the scope of the strategic funding of UID/BIO/04469/2019 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020.info:eu-repo/semantics/publishedVersio

Recent Advances in Cardiac Tissue Engineering for the Management of Myocardium Infarction

Myocardium Infarction (MI) is one of the foremost cardiovascular diseases (CVDs) causing death worldwide, and its case numbers are expected to continuously increase in the coming years. Pharmacological interventions have not been at the forefront in ameliorating MI-related morbidity and mortality. Stem cell-based tissue engineering approaches have been extensively explored for their regenerative potential in the infarcted myocardium. Recent studies on microfluidic devices employing stem cells under laboratory set-up have revealed meticulous events pertaining to the pathophysiology of MI occurring at the infarcted site. This discovery also underpins the appropriate conditions in the niche for differentiating stem cells into mature cardiomyocyte-like cells and leads to engineering of the scaffold via mimicking of native cardiac physiological conditions. However, the mode of stem cell-loaded engineered scaffolds delivered to the site of infarction is still a challenging mission, and yet to be translated to the clinical setting. In this review, we have elucidated the various strategies developed using a hydrogel-based system both as encapsulated stem cells and as biocompatible patches loaded with cells and applied at the site of infarction.</jats:p

Discovery of potent, novel, non-toxic anti-malarial compounds via quantum modelling, virtual screening and in vitro experimental validation

<p>Abstract</p> <p>Background</p> <p>Developing resistance towards existing anti-malarial therapies emphasize the urgent need for new therapeutic options. Additionally, many malaria drugs in use today have high toxicity and low therapeutic indices. Gradient Biomodeling, LLC has developed a quantum-model search technology that uses quantum similarity and does not depend explicitly on chemical structure, as molecules are rigorously described in fundamental quantum attributes related to individual pharmacological properties. Therapeutic activity, as well as toxicity and other essential properties can be analysed and optimized simultaneously, independently of one another. Such methodology is suitable for a search of novel, non-toxic, active anti-malarial compounds.</p> <p>Methods</p> <p>A set of innovative algorithms is used for the fast calculation and interpretation of electron-density attributes of molecular structures at the quantum level for rapid discovery of prospective pharmaceuticals. Potency and efficacy, as well as additional physicochemical, metabolic, pharmacokinetic, safety, permeability and other properties were characterized by the procedure. Once quantum models are developed and experimentally validated, the methodology provides a straightforward implementation for lead discovery, compound optimizzation and <it>de novo </it>molecular design.</p> <p>Results</p> <p>Starting with a diverse training set of 26 well-known anti-malarial agents combined with 1730 moderately active and inactive molecules, novel compounds that have strong anti-malarial activity, low cytotoxicity and structural dissimilarity from the training set were discovered and experimentally validated. Twelve compounds were identified <it>in silico </it>and tested <it>in vitro</it>; eight of them showed anti-malarial activity (IC50 ≤ 10 μM), with six being very effective (IC50 ≤ 1 μM), and four exhibiting low nanomolar potency. The most active compounds were also tested for mammalian cytotoxicity and found to be non-toxic, with a therapeutic index of more than 6,900 for the most active compound.</p> <p>Conclusions</p> <p>Gradient's metric modelling approach and electron-density molecular representations can be powerful tools in the discovery and design of novel anti-malarial compounds. Since the quantum models are agnostic of the particular biological target, the technology can account for different mechanisms of action and be used for <it>de novo </it>design of small molecules with activity against not only the asexual phase of the malaria parasite, but also against the liver stage of the parasite development, which may lead to true causal prophylaxis.</p

Mammalian microRNA: an important modulator of host-pathogen interactions in human viral infections

MicroRNAs (miRNAs), which are small non-coding RNAs expressed by almost all metazoans, have key roles in the regulation of cell differentiation, organism development and gene expression. Thousands of miRNAs regulating approximately 60æ% of the total human genome have been identified. They regulate genetic expression either by direct cleavage or by translational repression of the target mRNAs recognized through partial complementary base pairing. The active and functional unit of miRNA is its complex with Argonaute proteins known as the microRNA-induced silencing complex (miRISC). De-regulated miRNA expression in the human cell may contribute to a diverse group of disorders including cancer, cardiovascular dysfunctions, liver damage, immunological dysfunction, metabolic syndromes and pathogenic infections. Current day studies have revealed that miRNAs are indeed a pivotal component of host-pathogen interactions and host immune responses toward microorganisms. miRNA is emerging as a tool for genetic study, therapeutic development and diagnosis for human pathogenic infections caused by viruses, bacteria, parasites and fungi. Many pathogens can exploit the host miRNA system for their own benefit such as surviving inside the host cell, replication, pathogenesis and bypassing some host immune barriers, while some express pathogen-encoded miRNA inside the host contributing to their replication, survival and/or latency. In this review, we discuss the role and significance of miRNA in relation to some pathogenic viruses

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Parameter estimation of beta distribution for unit hydrograph derivation

Traditionally used methods for developing a synthetic unit hydrograph (SUH) are well known for their limitations. In last few decades, use of probability distribution functions in developing SUHs has received much attention. In this study, the potentials of a three-parameter beta distribution are explored. Using a analogy between the three-parameter beta-distribution shape and the SUH shape, approaches are developed to evaluate the unknown parameters. Based on nondimensional analysis and optimization, a simple accurate relation is introduced to estimate the three parameters of the beta distribution that is useful for unit hydrograph derivation. The relation yields results closer to those obtained by an available trial and error procedure. The unit hydrographs from the proposed method fit observed hydrographs better than those from the widely used two-parameter gamma distribution. The potential of the approach is demonstrated using data from different catchments lying within and outside India. The methodology is found to work consistently better in most cases

Investigation of crystallization kinetic of SrO-La(2)O(3)-Al(2)O(3)-B(2)O(3)-SiO(2) glass and its suitability for SOFC sealant

Strontium-lanthanum-aluminoborosilicate (SrO-La(2)O(3)-Al(2)O(3)-B(2)O(3)-SiO(2)) (SLABS) glass was prepared for sealant material in planar Solid Oxide Fuel Cells (pSOFC). Differential Thermal Analysis of the glass showed the formation of two crystalline phases, first one 807 degrees C and the second phase at 1021 degrees C. Crystallization kinetic of the first crystalline phase was investigated by differential thermal analysis (DTA) and using the JMA-kinetic model. The activation energy for crystallization was calculated to be 114.04 kJ/mol with frequency factor 5.9 x 10(3). Coefficient of Thermal Expansion (CTE) of the glass was measured to be 9.72 x 10(-6)/degrees C. Optical band gap of the glass was measured to be 3.07 eV. Conductivity measured by Impedance spectroscopy found to be 5.68 x 10(-7) S cm(-1) at 600 degrees C and it increased with temperature to 2.68 x 10(-6) S cm(-1) at 800 degrees C. Activation energy for electrical conduction was measured to be 66.12 kJ/mol. Wetting behavior of the glass on a ferritic steel substrate was investigated under hot stage microscopy. It showed initial deformation temperature (IDT) 754 degrees C, softening temperature (ST) 840 degrees C, hemispherical temperature (HT) 1108 degrees C and flow temperature (FT) 1279 degrees C. Copyright (C) 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved

Nanocrystalline yttria stabilized zirconia by metal-PVA complexation

Nanocrystalline 8 mol% yttria stabilized zirconia (YSZ) powder was synthesized using polyvinyl alcohol (PVA) as organic precursor and acidic solutions of yttrium oxynitrite and zirconium nitrate. Complex formation was established using Fourier transform infrared (FTIR) spectroscopy and solid state (13)C nuclear magnetic resonance (NMR) spectroscopy. Thermal stability of the complex was investigated by thermogravimetric analysis (TGA). X-ray diffractometry (XRD) revealed formation of cubic phase YSZ at a temperature as low as 600 degrees C. The lattice parameter and average crystallite size were calculated from the XRD data. Particle size of the YSZ powder was investigated through transmission electron microscopy (TEM). The band gap of the sintered YSZ pellet was measured by UV-Vis-diffused reflectance spectroscopy (DRS). AC electrical conductivity was measured in air at 1 kHz frequency using a programmable RCL meter. The activation energy was calculated from the conductivity data at different temperatures using the standard Arrhenius equation. (C) 2009 Elsevier Ltd and Techna Group S.r.l.