Investigation of trends in basin-scale temperature variables

This research paper presents an analysis of temperature variables over the West Banas basin in order to detect the presence of underlying trends employing historical temperature data for three points viz., Abu Road, Mount Abu and Pindwara obtained for a period of 40 years (1981 – 2020) from MERRA-2 database. The study aims to investigate the long-term changes in temperature trends and identify any significant patterns or anomalies in mean, maximum and minimum temperatures at monthly, seasonal and annual timescales at the three locations amounting to a total of 162 series. The trends were evaluated using the Mann-Kendall test, a popular and powerful statistical technique formulated for analysing abnormal distributions. Prior to the application of the trend test, autocorrelated time series were identified and the trend test was modified using a variance correction approach to incorporate the influence of autocorrelations upon the resultant trends. The findings of autocorrelation analysis revealed that 11 of the 162 series were autocorrelated, a majority of which were associated with the temperature series at Abu Road. The results of the trend test showed that 27 out of the 162 series possessed significant trends with the mean and maximum monsoon temperatures in most of the series exhibiting a reducing trend while the minimum temperature appeared to be rising. Overall, the research highlights the importance of monitoring temperature trends, particularly in regions that may be more vulnerable to the impacts of climate change. The findings of this study can inform future climate adaptation strategies and support decision-making processes aimed at mitigating the effects of global warming on the natural and built environment

DEVELOPMENT AND EVALUATION OF BILAYERED GASTRO-RETENTIVE TABLET CONTAINING METFORMINHCL SR AND PIOGLITAZONEHCL IR

To get advantage of novel drug delivery in treatment of diabetes mellitus is centered aim of this work.Bi-layered gastro-retentive tablet containing MetforminHCl and PioglitazoneHCl for treatment of type-II diabetes mellitus has been formulated . To make the system more effective, combination of immediate layer, PioglitazoneHCl 15mg and sustained release layer of MetforminHCl 500mg were prepared. The core tablet of MetforminHCl was prepared by using different swellable polymers like HPMC E15, HPMC K100 and carbopol by wet granulation method and evaluated for swelling index, total floating time and floating lag time. In vitro release studies were carried out with 0.1N HCl using USP dissolution apparatus 2 (paddle). Tablet thus formulated using HPMC K100M and E15 provided sustained release of Metformin HCl over a period of 10 hours. The immediate release layer of PioglitazoneHCl was prepared by using crosspovidone,a super disintegrant  by direct compression method and evaluated for disintegration time and dissolution also. Then bilayered tablet was prepared with the selected core tablet batch of MetforminHCl followed by compression coating with the selected immediate release layer of PioglitazoneHCl. The present study concluded that bilayered tablet can be a good way to treat diabetic patients with combination therapy

Simultaneous Estimation of Phenylephrine HCl, Doxylamine Succinate and Dextromethorphan HBr in Soft Gelatin Capsule (Cough and Cold Preparation) by RP-HPLC

ABSTRACT A RP-HPLC methods were developed and validated for simultaneous estimation of Phenylephrine HCl (PE), Doxylamine Succinate (DOX) and Dextromethorphan HBr (DEX). The separation was achieved on a Princestone ODS C18 (250mm X 4.6 mm i.d., 10 μm particle size) with an Isocratic system of Phosphate Buffer (10 mM) : Methanol : Acetonitrile (pH 4) in the ratio of 70:25:5 v/v/v. The retention time for PE, DOX and DEX was obtained as 5.125 min, 10.419 min and 2.661 min respectively with a flow rate of 1.0 ml/min at detection wavelength 215 nm. The linearity of the proposed method was investigated in the range of 25 -125 μg/ml, 31.25 -156.25 µg/ml and 50 -250 μg/ml for PE, DOX and DEX respectively. The developed method was validated as per ICH guideline and found to be satisfactory

Understanding of colistin usage in food animals and available detection techniques: a review

Progress in the medical profession is determined by the achievements and effectiveness of new antibiotics in the treatment of microbial infections. However, the development of multiple-drug resistance in numerous bacteria, especially Gram-negative bacteria, has limited the treatment options. Due to this resistance, the resurgence of cyclic polypeptide drugs like colistin remains the only option. The drug, colistin, is a well-known growth inhibitor of Gram-negative bacteria like Acinetobacter baumanni, Enterobacter cloacae, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Technological advancements have uncovered the role of the mcr-1(mobilized colistin resistance) gene, which is responsible for the development of resistance in Gram-negative bacteria, which make them distinct from other bacteria without this gene. Additionally, food animals have been determined to be the reservoir for colistin resistance microbes, from which they spread to other hosts. Due to the adverse effects of colistin, many developed countries have prohibited its usage in animal foods, but developing countries are still using colistin in animal food production, thereby imposing a major risk to the public health. Therefore, there is a need for implementation of sustainable measures in livestock farms to prevent microbial infection. This review highlights the negative effects (increased resistance) of colistin consumption and emphasizes the different approaches used for detecting colistin in animal-based foods as well as the challenges associated with its detectio

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019.

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.Funding/Support: The Institute for Health Metrics and Evaluation received funding from the Bill & Melinda Gates Foundation and the American Lebanese Syrian Associated Charities. Dr Aljunid acknowledges the Department of Health Policy and Management of Kuwait University and the International Centre for Casemix and Clinical Coding, National University of Malaysia for the approval and support to participate in this research project. Dr Bhaskar acknowledges institutional support from the NSW Ministry of Health and NSW Health Pathology. Dr Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, which is funded by the German Federal Ministry of Education and Research. Dr Braithwaite acknowledges funding from the National Institutes of Health/ National Cancer Institute. Dr Conde acknowledges financial support from the European Research Council ERC Starting Grant agreement No 848325. Dr Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia, IP under the Norma Transitória grant DL57/2016/CP1334/CT0006. Dr Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). Dr Glasbey is supported by a National Institute of Health Research Doctoral Research Fellowship. Dr Vivek Kumar Gupta acknowledges funding support from National Health and Medical Research Council Australia. Dr Haque thanks Jazan University, Saudi Arabia for providing access to the Saudi Digital Library for this research study. Drs Herteliu, Pana, and Ausloos are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Dr Hugo received support from the Higher Education Improvement Coordination of the Brazilian Ministry of Education for a sabbatical period at the Institute for Health Metrics and Evaluation, between September 2019 and August 2020. Dr Sheikh Mohammed Shariful Islam acknowledges funding by a National Heart Foundation of Australia Fellowship and National Health and Medical Research Council Emerging Leadership Fellowship. Dr Jakovljevic acknowledges support through grant OI 175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Dr Katikireddi acknowledges funding from a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). Dr Md Nuruzzaman Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Dr Yun Jin Kim was supported by the Research Management Centre, Xiamen University Malaysia (XMUMRF/2020-C6/ITCM/0004). Dr Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education. Dr Landires is a member of the Sistema Nacional de Investigación, which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación. Dr Loureiro was supported by national funds through Fundação para a Ciência e Tecnologia under the Scientific Employment Stimulus–Institutional Call (CEECINST/00049/2018). Dr Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. Dr Moosavi appreciates NIGEB's support. Dr Pati acknowledges support from the SIAN Institute, Association for Biodiversity Conservation & Research. Dr Rakovac acknowledges a grant from the government of the Russian Federation in the context of World Health Organization Noncommunicable Diseases Office. Dr Samy was supported by a fellowship from the Egyptian Fulbright Mission Program. Dr Sheikh acknowledges support from Health Data Research UK. Drs Adithi Shetty and Unnikrishnan acknowledge support given by Kasturba Medical College, Mangalore, Manipal Academy of Higher Education. Dr Pavanchand H. Shetty acknowledges Manipal Academy of Higher Education for their research support. Dr Diego Augusto Santos Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil Finance Code 001 and is supported in part by CNPq (302028/2018-8). Dr Zhu acknowledges the Cancer Prevention and Research Institute of Texas grant RP210042

An Open Labelled, Parallel Arm Interventional Clinical Assessment of Vasa (Justicia Adhatoda L.) in Dadru Kushtha (Fungal Skin Infection)

Vasa is a prime drug of respiratory disorders in Ayurveda. Seers of Ayurveda have also prescribed it as a single drug in Kushtha Roga in various dosage forms. It possesses Tikta Rasa Pradhana–Kashaya Anurasa, Sheeta Virya, Laghu Guna and Kapha-Pitta Hara properties. Many experimental studies like antitussive, bronchodilator activity, anti-asthmatic activities and clinical study were conducted to evaluate its Kasahara, Shwasahara, Raktapittahara Karma. But till date not a single study conducted to evaluate its Kushthaghna effect. Hence, an attempt was made to clinically compare Vasa with standard drug Nimba for its Kushthghna Karma. Aim: To clinically assess the effect of Vasa in Dadru Kushtha. Settings and Design: Interventional, Open labeled, Randomized, Parallel arm. Methods and Material: Fresh leaves of Vasa were collected from periphery of Rajpipla, Gujarat. The patients were selected from Government Ayurved College & Hospital, Vadodara and grading analogue scale, general & physical examination was done as a screening. Statistical analysis used: Data were calculated by student ‘t’ test for parametric data using Sigma stat 3.2. Results: Vasa showed statistically significant (p<0.001) results in all symptoms of Dadru Kushtha. Group A- (Nimba) showed 75.83% and Group B- (Vasa) showed 78.54% improvement in all symptoms of Dadru. The chief complaint of Dadru Kushtha i.e., Kandu was better relieved by Vasa on the basis of percentage of relief i.e. 97.92% in comparison to Nimba i.e., 89.58. Conclusion: Vasa is effective in all the symptoms of Dadru Kushtha. Current study suggests that it can be effectively used in Kapha pitta pradhana Kushtharoga

Potential Therapeutic Role of Mesenchymal-Derived Stem Cells as an Alternative Therapy to Combat COVID-19 through Cytokines Storm

Medical health systems continue to be challenged due to newly emerging COVID-19, and there is an urgent need for alternative approaches for treatment. An increasing number of clinical observations indicate cytokine storms to be associated with COVID-19 severity and also to be a significant cause of death among COVID-19 patients. Cytokine storm involves the extensive proliferative and hyperactive activity of T and macrophage cells and the overproduction of pro-inflammatory cytokines. Stem cells are the type of cell having self-renewal properties and giving rise to differentiated cells. Currently, stem cell therapy is an exciting and promising therapeutic approach that can treat several diseases that were considered incurable in the past. It may be possible to develop novel methods to treat various diseases by identifying stem cells’ growth and differentiation factors. Treatment with mesenchymal stem cells (MSCs) in medicine is anticipated to be highly effective. The present review article is organized to put forward the positive arguments and implications in support of mesenchymal stem cell therapy as an alternative therapy to cytokine storms, to combat COVID-19. Using the immunomodulatory potential of the MSCs, it is possible to fight against COVID-19 and counterbalance the cytokine storm

Groundwater quality characterization using an integrated water quality index and multivariate statistical techniques.

This study attempts to characterize and interpret the groundwater quality (GWQ) using a GIS environment and multivariate statistical approach (MSA) for the Jakham River Basin (JRB) in Southern Rajasthan. In this paper, analysis of various statistical indicators such as the Water Quality Index (WQI) and multivariate statistical methods, i.e., principal component analysis and correspondence analysis (PCA and CA), were implemented on the pre and post-monsoon water quality datasets. All these methods help identify the most critical factor in controlling GWQ for potable water. In pre-monsoon (PRM) and post-monsoon (POM) seasons, the computed value of WQI has ranged between 28.28 to 116.74 and from 29.49 to 111.98, respectively. As per the GIS-based WQI findings, 63.42 percent of the groundwater samples during the PRM season and 42.02 percent during the POM were classed as 'good' and could be consumed for drinking. The Principal component analysis (PCA) is a suitable tool for simplification of the evaluation process in water quality analysis. The PCA correlation matrix defines the relation among the water quality parameters, which helps to detect the natural or anthropogenic influence on sub-surface water. The finding of PCA's factor analysis shows the impact of geological and human intervention, as increased levels of EC, TDS, Na+, Cl-, HCO3-, F-, and SO42- on potable water. In this study, hierarchical cluster analysis (HCA) was used to categories the WQ parameters for PRM and POR seasons using the Ward technique. The research outcomes of this study can be used as baseline data for GWQ development activities and protect human health from water-borne diseases in the southern region of Rajasthan