A Validated RP-HPLC Method for the Determination of Telmisartan In Bulk and Pharmaceutical Dosage Form

A RP-HPLC method has been developed and validated for the estimation of telmisartan in bulk and pharmaceutical dosage form. A RP-HPLC isocratic separation was achieved on C18 column (250.6 mm i.d., 5m) utilizing a mobile phase comprising of methanol and acetonitrile in the ratio of 90: 10(v/v) and the eluents from the column were detected using a variable wavelength detector at 237nm. The proposed method has permitted the quantification of telmisartan in the linearity range of 20-100g/ml and the flow rate was maintained at 1ml/min. The column was maintained at ambient temperature and the complete separation was achieved for telmisartan in an overall analytical run time of approximately 10 minutes. The retention time of telmisartan was found to be 3.3 minutes. The limit of detection and limit of quantification were found to be 2.82 and 8.54 ?g/ml, respectively. The percentage recovery was found to be in between 87.3 to 103.18%. The method was found to be suitable for the routine quality control analysis of telmisartan in bulk drug and formulation. The method was validated as per ICH guidelines

Prevalence and Factors Associated With Mental Health Symptoms in Adults Undergoing Covid-19 Testing

BACKGROUND AND OBJECTIVE: Understanding the mental health impact of the COVID-19 pandemic on persons receiving COVID-19 testing will help guide mental health interventions. We aimed to determine the association between sociodemographic factors and mental health symptoms at 8 weeks (baseline) after a COVID-19 test, and compare prevalence of mental health symptoms at baseline to those at 16-week follow-up. MATERIALS AND METHODS: Prospective cohort study of adults who received outpatient COVID-19 testing at primary care clinics. Logistic regression analyses were used to assess the association between sociodemographic characteristics and COVID-19 test results with mental health symptoms. Mental health symptoms reported at baseline were compared to symptoms at 16 weeks follow-up using conditional logistic regression analyses. RESULTS: At baseline, a total of 124 (47.51%) participants reported at least mild depressive symptoms, 110 (42.15%) participants endorsed at least mild anxiety symptoms, and 94 participants (35.21%) endorsed hazardous use of alcohol. Females compared to males were at increased risk of at least mild depressive symptoms at baseline (Adjusted Odds Ratio (AOR): 2.08; 95% CI: 1.14-3.79). The odds of at least mild depressive symptoms was significantly lower among those residing in zip codes within the highest quartile compared to lowest quartile of household income (AOR: 0.37; 95% CI: 0.17-0.81). Also, non-Hispanic Whites had significantly higher odds of reporting hazardous alcohol use compared to non-Whites at baseline (AOR: 1.94; 95% CI: 1.05-3.57). The prevalence of mental health symptoms remained elevated after 16 weeks. CONCLUSION AND RELEVANCE: We found a high burden of symptoms of depression and anxiety as well as hazardous alcohol use in a diverse population who received testing for COVID-19 in the primary care setting. Primary care providers need to remain vigilant in screening for symptoms of mental health disorders in patients tested for COVID-19 well after initial testing

Centrality evolution of the charged-particle pseudorapidity density over a broad pseudorapidity range in Pb-Pb collisions at root s(NN)=2.76TeV

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Not AvailableCOVID-19 is the deadliest pandemic, with over 18.2 million people infected with the SARS-CoV-2 virus by August 2, 2021 resulting in human deaths and economic losses. A number of countries have formulated control measures in order to prevent the spread of the virus. However, it is unknown when the outbreak will subside in different countries around the world. The role of predicting the COVID-19 trend is extremely difficult. Indian government has made disease outbreak analysis a priority in order to implement necessary healthcare measures to reduce the impact of this deadly pandemic on human health and country’s economics. The time series data for COVID-19 disease was collected from the website www.covid19india.org and were analyzed using a periodic regression model using the data from 22nd Janaury March 2020 to 01st Febraury 2021 the estimated number of cases until 27 July, 2021 was predicted to develop a stochastic model using periodic regression and were documented in top 10 highly infected states in India. The analysis revealed a increasing pattern for the number of reporting cases in the early days of prediction and decreasing trend for the number of reporting cases in the later days of prediction, which could decrease in future days in Karnataka, West Bengal, Uttar Pradesh, Telangana, Bihar and Haryana states. However, in Madhya Pradesh, Andhra Pradesh, Maharashtra and Tamil Nadu states showed a rapid phase of rise in disease incidence, which is likely to infect a larger population and suggests the disease's pandemic existence over a duration. Our model emphasizes the importance of ongoing and continuous efforts that are in place in all states to minimize occurrence of new cases of infections, so as to potentially improving India's economic wealth with the available resourcesNot Availabl