Ligand Growing Experiments Suggested 4-amino and 4-ureido pyridazin-3(2H)-one as Novel Scaffold for FABP4 Inhibition

Fatty acid binding protein (FABP4) inhibitors are of synthetic and therapeutic interest and ongoing clinical studies indicate that they may be a promise for the treatment of cancer, as well as other diseases. As part of a broader research effort to develop more effective FABP4 inhibitors, we sought to identify new structures through a two-step computing assisted molecular design based on the established scaffold of a co-crystallized ligand. Novel and potent FABP4 inhibitors have been developed using this approach and herein we report the synthesis, biological evaluation and molecular docking of the 4-amino and 4-ureido pyridazinone-based series

Scope, Nutritional Importance and Value Addition in Palmyrah (<em>Borassus flabellifer L.</em>): An Under Exploited Crop

Palmyrah palm has great economic potential and every part of the palm is useful in one way or the other is considered as ‘kalpaga tharu’. The palm is found growing widely in southern states of India. As the value addition in palmyrah is not standardized, the palmyrah products viz. tender fruit endosperm (nungu), neera, jaggery and tuber flour are not commercialized so far. Even though palmyrah is an economically important palm for its nutritional aspects, it has not received proper attention from the agricultural research workers, probably on account of the fact that it is very slow growing palm and mostly found in the wild state. In this context, knowing the physico-chemical properties and development of value added products and popularizing the same is essential

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

This article contains supporting information online at http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2113561119/-/DCSupplemental.Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Integrative Biolog

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Phytochemical analysis, synthesis, antitumor and antimicrobial activity of Silver Nanoparticles using flower extracts of Ixora coccinea

Abstract: This study aims to analyse aqueous, ethanolic and methanolic extracts of flowers of Ixora coccinea for the presence of various phytochemicals and synthesised silver nanoparticles using the aqueous extract of Ixora coccinea flowers and also checked the antimicrobial activity, TLC studies using both the extracts. The presence of various phytochemicals viz., alkaloids, tannins, carbohydrates, flavonoids, terpenes and glycosides were analysed by standard biochemical screening methods. The synthesised silver nanoparticles (SNPs) were characterised by using UV-Vis Spectroscopy, FTIR, XRD, SEM, TEM The synthesised nanoparticles were found to be spherical in shape with average size in the range of 5-10 nm and also showed inhibitory zones to the bacterial cultures. The results revealed that the aqueous extract of Ixora coccinea flowers is a very good bioreductant for the synthesis of silver nanoparticles

HYPOCHOLESTEROLEMIC EFFECT OF THE ANOXYGENIC PHOTOTROPHIC BACTERIUM RHOPSEUDOMONAS PALUSTRIS MGU001 IN HEN LAYING EGGS.

ABSTRACT: The study was designed to investigate the effects of dietary Rhodopseudomonas palustris on the laying hen. The values were recorded after about a period of 60 days. Dietary supplementation of four day old cultures of R.palustris at 0.08 % reduced cholesterol and triglycerides concentration in serum by 15.34 % and 6.19 % respectively. The hen egg-yolk recorded a reduction of about 17.18 % in cholesterol concentration. Also, supplementation of R.palustris in diets increased high-density lipoprotein cholesterol level and decreased atherogenic index in serum. Reduction in the levels of cholesterol was also observed in liver, breast and thigh muscles. Diets fed with R.palustris may lead to the development of chicken and eggs containing less cholesterol. Significance of the above results with respect to the existing literature are discussed in this communication