3-Hydroxy-3-Methylglutaryl-CoA Reductase (HMGR) Enzyme of the Sterol Biosynthetic Pathway: A Potential Target against Visceral Leishmaniasis

Sterol biosynthetic pathway is explored for its therapeutic potential for Visceral Leishmaniasis. In Leishmania, this pathway produces ergosterol which is absent in host and therefore is a promising strategy to combat proliferation of both extracellular and intracellular forms of the parasite with minimal host toxicity. The present chapter focuses on 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) enzyme which is the rate-limiting enzyme of the ergosterol biosynthesis. HMGR gene of L. donovani was biochemically and biophysically characterized for the first time. HMGR over expressing transgenic parasites were generated to evaluate its role in parasite growth and infection ability. A series of statins like atorvastatin, simvastatin and mevastatin were evaluated for its therapeutic efficacy and mode of action elucidated. Atorvastatin and mevastatin were found to be killing both the promastigote and amastigote forms of the parasite without exhibiting host cytotoxicity. Besides, non-statin class of molecules like resveratrol and glycyrrhizic acid were also analyzed for antileishmanial potential. Two antidepressants, ketanserin and mianserin were found to kill both L. donovani promastigotes and intracellular amastigotes with no apparent toxicity to the host cells. Since targeting of the sterol biosynthetic pathway enzymes may be useful therapeutically, the present work may have implications in treatment of Leishmaniasis

The Effect of Taxpayers Attitudes towards the Legal System and Government on Tax Morale (With Reference to Selected Assesses in Addis Ababa, Ethiopia)

The overall purpose of this study was to assess the effect of taxpayers’ attitudes towards the legal system and government on tax morale. The researchers used survey method for the study. Data for the survey study were collected from the target populations by means of self administered questionnaire. From the populations the sample was select by using stratified sampling to obtain a representative sample from taxpayers of business organization. An ordered probit model is employed to analyze the effect of taxpayers’ attitudes towards the legal system and government on tax morale. The results showed that tax morale (dependent variable) is correlated at 0.4982 with attitude of taxpayers towards government and legal system at 5 percent significance level and there is a significant relationship between taxpayer attitude towards the legal system and government, and tax morale at a p value of 0.001 and 0.000 and has a significant positive effect on tax morale, with higher marginal effects. They have a statistically significant positive effect on tax morale. Therefore, governance quality seems to be a key component in the understanding of tax morale. Hence, governments are called to create confidence in their credibility and their capacity to deliver promised returns for taxes. The government should build trustworthy institutions; much weight should be put on developing a trustworthy ground so that taxpayers feel comfortable with paying taxes. Keywords: Tax morale, Legal System, Governmen

Deciphering Customer Perceived Value a Comparative Study using Holbrook's Typology across Brands in Visakhapatnam

This study explores the intricate landscape of customer perceived value through a comprehensive examination of theoretical frameworks and empirical analyses. Drawing on model named Holbrook's Typology, the research investigates the multifaceted dimensions that shape consumers' assessments of value with a sample size of 168 in Visakhapatnam city. Statistical analyses, including Chi-Square Tests and the Kaiser-Meyer-Olkin Measure, affirm the robustness of the study, revealing significant associations within constructs such as Extrinsic Value Assessment, Intrinsic Value Assessment, Self-oriented Value Assessment, Other-oriented Value Assessment, Active Value Engagement, and Reactive Value Assessment. The nuanced interpretation of the findings, acknowledging instances of rejected null hypotheses, provides actionable insights for brand marketers. The study suggests strategies for marketers to enhance customer perceived value, ranging from elevating intrinsic value through user experience to tailoring offerings based on self-oriented and other-oriented values. Emphasis is placed on active engagement, positive word-of-mouth, and strategic partnerships, offering a roadmap for creating meaningful connections with consumers. This research contributes not only to theoretical understandings of customer perceived value but also provides practical guidance for marketers navigating the complex landscape of consumer preferences. By aligning strategies with the identified dimensions of perceived value, brand marketers can cultivate dynamic relationships, foster loyalty, and navigate the evolving market with strategic precision

RP-HPLC (STABILITY-INDICATING) BASED ASSAY METHOD FOR THE SIMULTANEOUS ESTIMATION OF DORAVIRINE, TENOFOVIR DISOPROXIL FUMARATE AND LAMIVUDINE

Objective: In this study, a RP-HPLC (stability-indicating) based assay method for the estimation of doravirine (DRV), tenofovir disoproxil fumarate (TFF) and lamivudine (LMV) simultaneously in the tablets was described. Methods: The simultaneous analysis of DRV, TFF and LMV was done with HPLC system (Agilent 1100 series) and Luna Phenomenex C18 (250 mm × 4.6 mm × 5 μ) column with isocratic mobile phase (35% volume ratio of methanol and 65% volume ratio of 20 mmol ammonium formate, pH 5). Validation of assay method was done on sensitivity, linearity, accuracy, selectivity, precision, robustness and specificity. Results: The calibration curves were linear through the range of 25-200 µg/ml for DRV and 75-600 µg/ml for TFF and LMV. The percent relative standard deviation for intraday variation/precision, interday variation/precision, intermediate precision/ruggedness and robustness were lower than 2%. The recovery of LMV (99.09-99.76%), TFF (99.10-99.41%) and DRV (98.65-99.28%) confirmed the good accuracy. The stability of LMV, TFF and DRV in 0.1N NaOH, 3% peroxide, 0.1 N HCl, UV light and dry heat of 60 °C was determined. Conclusion: The results have allowed the method to be implemented in the tablets to quantify DRV, TFF, and LMV

THE IMPACT OF SHARE PRICES BEFORE AND AFTER THE DIVIDEND ANNOUNCEMENT WITH REGARD TO BANK NIFTY COMPANIES

The purpose of this paper is to examine the relationship between dividend announcement and shareholders value. According to the dividend signalling theory, a company decides to announce its dividend pay-out policy to signal the market that the firm is now processing future prospects, which will result in changing its stock prices

EEG Signal Classification Automation using Novel Modified Random Forest Approach

Digitalization and automation are the two aspects in the medical industry that define compliance with industry 4.0. Automation is essential for speeding up the diagnosis process, while digitalization leads to smart medicine and efficient diagnosis. Epilepsy is one such disease that can use these automation techniques. The automatic monitoring of epilepsy EEG is of great significance in clinical medicine. Aiming at the non-stationary characteristics of EEG signals, the classification of EEG signals is based on the combination of overall empirical mode. It is proposed using the random forest method. The EEG signal data set has an epileptic interval over 200 single-channel signals with a seizure period. A total of 819,400 data are used as samples. First, the overall epileptic EEG signal modal is decomposed into multiple intrinsic modal functions. The effective features are extracted from the first-order intrinsic modal function. Finally, random forest and Least Square SVM (LS-SVM) are considered to classify the EEG signals characteristics. The correct recognition rate of random forest and LS-SVM is compared. The results show that random forest classification method has an ideal classification effect on epilepsy EEG signals during and between seizures. The recognition accuracy is 99% and 60%, which is higher than the accuracy of the LS-SVM. The proposed method improves clinical epilepsy. The efficiency of EEG signals analysis

Curcumin-Loaded Apotransferrin Nanoparticles Provide Efficient Cellular Uptake and Effectively Inhibit HIV-1 Replication In Vitro

Curcumin (diferuloylmethane) shows significant activity across a wide spectrum of conditions, but its usefulness is rather limited because of its low bioavailability. Use of nanoparticle formulations to enhance curcumin bioavailability is an emerging area of research.In the present study, curcumin-loaded apotransferrin nanoparticles (nano-curcumin) prepared by sol-oil chemistry and were characterized by electron and atomic force microscopy. Confocal studies and fluorimetric analysis revealed that these particles enter T cells through transferrin-mediated endocytosis. Nano-curcumin releases significant quantities of drug gradually over a fairly long period, ∼50% of curcumin still remaining at 6 h of time. In contrast, intracellular soluble curcumin (sol-curcumin) reaches a maximum at 2 h followed by its complete elimination by 4 h. While sol-curcumin (GI(50) = 15.6 µM) is twice more toxic than nano-curcumin (GI(50) = 32.5 µM), nano-curcumin (IC(50)<1.75 µM) shows a higher anti-HIV activity compared to sol-curcumin (IC(50) = 5.1 µM). Studies in vitro showed that nano-curcumin prominently inhibited the HIV-1 induced expression of Topo II α, IL-1β and COX-2, an effect not seen with sol-curcumin. Nano-curcumin did not affect the expression of Topoisomerase II β and TNF α. This point out that nano-curcumin affects the HIV-1 induced inflammatory responses through pathways downstream or independent of TNF α. Furthermore, nano-curcumin completely blocks the synthesis of viral cDNA in the gag region suggesting that the nano-curcumin mediated inhibition of HIV-1 replication is targeted to viral cDNA synthesis.Curcumin-loaded apotransferrin nanoparticles are highly efficacious inhibitors of HIV-1 replication in vitro and promise a high potential for clinical usefulness

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic