Bioavailability enhancers of herbal origin:An overview

Recently,the use of herbal medicines has been increased all over the world due to their therapeutic effects and fewer adverse effects as compared to the modern medicines.However,many herbal drugs and herbal extracts despite of their impressive in-vitro findings demonstrates less or negligible in-vivo activity due to their poor lipid solubility or improper molecular size,resulting in poor absorption and hence poor bioavailability.Nowadays with the advancement in the technology,novel drug delivery systems open the door towards the development of enhancing bioavailability of herbal drug delivery systems.For last one decade many novel carriers such as liposomes,microspheres,nanoparticles,transferosomes,ethosomes,lipid based systems etc.have been reported for successful modified delivery of various herbal drugs.Many herbal compounds including quercetin,genistein,naringin,sinomenine,pipeline,glycvrrhizin and nitrile glycoside have demonstrated capability to enhance the bioavailability.The objective of this review is to summarize various available novel drug delivery technologies which have been developed for delivery of drugs(herbal),and to achieve better therapeutic response.An attempt has also been made to compile a profile on bioavailability enhancers of herbal origin with the mechanism of action(wherever reported)and studies on improvement in drug bioavailability,exhibited particularly by natural compounds.

Role of mental health professionals in dealing with the stigma attached to COVID-19

The stigma associated with the disease may be as subtle as avoidance,or dramatic as physical aggression.COVID-19 has begun to cause social disruption by growing disease-related stigma and xenophobia against some cultural,national,racial or religious groups worldwide.1 People of East Asian origin and those with facial features like them,or those with a travel history to areas affected by the outbreak,are especially being subjected to xenophobia in personal contact and online threats.COVID-19 has arisen as an unknown and newly emerged highly contagious infection that has spread rapidly across the globe and is associated with high mortality,leading to fear of encountering those infected.2 Leaders across the world have taken strict measures such as lockdowns and shutdown of various vital services that have caused chaos in people’s lives and increased concerns about the disease.3 Box 1 lists the factors leading to stigmatisation towards those infected with COVID-19.

Ethnobotanical and phytopharmacological review of Scindapsus officinalis(“Gajapippali”)

Scindapsus of ficinalis(S. officinalis) holds a reputed position in Ayurvedic system of medicine. It has been ethanobotanically used to treat diarrhea("atisara"), worm infestation("krmiroga"), and as antipyretic. Literature survey on S. officinalis was carried out via electronic search in Pub Med, Sci Finder, Scirus, Google Scholar, Agricola and Web of Science and a library search. Results revealed that a very specific botanical description of the plant is still not available. The plant is mistaken within the hybrids and other plants of genus Scindapsus and family Araceae. Since ethnobotanically the plant is of much importance, chemistry of the plant yet needs to be fully explored. Thus the need of the hour is to comprehend the fragmented information available on the botany, traditional uses, phytochemistry and pharmacology of S. officinalis which could help in the correct identification of the sample and avoid adulteration due to mistaken identity.

ARIMA and NAR based prediction model for time series analysis of COVID-19 cases in India

In this paper,we have applied the univariate time series model to predict the number of COVID-19 infected cases that can be expected in upcoming days in India.We adopted an Auto-Regressive Integrated Moving Average(ARIMA)model on the data collected from 31st January 2020 to 25th March 2020 and verified it using the data collected from 26th March 2020 to 04th April 2020.A nonlinear autoregressive(NAR)neural network was developed to compare the accuracy of predicted models.The model has been used for daily prediction of COVID-19 cases for next 50 days without any additional intervention.Statistics from various sources,including the Ministry of Health and Family Welfare(MoHFW)and http://covid19india.org/are used for the study.The results showed an increasing trend in the actual and forecasted numbers of COVID-19 cases with approximately 1500 cases per day,based on available data as on 04th April 2020.The appropriate ARIMA(1,1,0)model was selected based on the Bayesian Information Criteria(BIC)values and the overall highest R 2 values of 0.95.The NAR model architecture constitutes ten neurons,which was optimized using the Levenberg-Marquardt optimization training algorithm(LM)with the overall highest R 2 values of 0.97.

Projecting the criticality of COVID-19 transmission in India using GIS and machine learning methods

There is a new public health catastrophe forbidding the world.With the advent and spread of 2019 novel coro-navirus(2019-nCoV).Learning from the experiences of various countries and the World Health Organization(WHO)guidelines,social distancing,use of sanitizers,thermal screening,quarantining,and provision of lock-down in the cities being the effective measure that can contain the spread of the pandemic.Though complete lockdown helps in containing the spread,it generates complexity by breaking the economic activity chain.Besides,laborers,farmers,and workers may lose their daily earnings.Owing to these detrimental effects,the government has to open the lockdown strategically.Prediction of the COVID-19 spread and analyzing when the cases would stop increasing helps in developing a strategy.An attempt is made in this paper to predict the time after which the number of new cases stops rising,considering the strong implementation of lockdown conditions using three different techniques such as Decision Tree,Support Vector Machine,and Gaussian Process Regression algorithm are used to project the number of cases.Thus,the projections are used in identifying inflection points,which would help in planning the easing of lockdown in a few of the areas strategically.The criticality in a region is evaluated using the criticality index(CI),which is proposed by authors in one of the past of research works.This research work is made available in a dashboard to enable the decision-makers to combat the pandemic.