Dark Matter and Galactic Collisions, gravitational lensing and the apparatus of wimps under consideration

During the last century many observations have been made to peep into the dark matter in the universe and many astonishing behaviors of Galaxy clusters have been found which do not fit to any theories formulated before. However, Optical Spectroscopic observation has been initially used to measure the rotational velocity of the Andromeda Galaxy as a function of distance found in contrast to the Law of Gravitation.Due to the expansion of space, electromagnetic radiation emitted in the distant Universe is redshifted on its path towards us which can be used to determine the distances of astronomical objects.Comment: 15 pages, 22 figure

MELK Promotes Melanoma Growth by Stimulating the NF-kappaB Pathway

Melanoma accounts for more than 80% of skin cancer-related deaths, and current therapies provide only short-term benefit to patients. Here, we show in melanoma cells that maternal embryonic leucine zipper kinase (MELK) is transcriptionally upregulated by the MAPK pathway via transcription factor E2F1. MELK knockdown or pharmacological inhibition blocked melanoma growth and enhanced the effectiveness of BRAFV600E inhibitor against melanoma cells. To identify mediators of MELK function, we performed stable isotope labeling with amino acids in cell culture (SILAC) and identified 469 proteins that had downregulated phosphorylation after MELK inhibition. Of these proteins, 139 were previously reported as substrates of BRAF or MEK, demonstrating that MELK is an important downstream mediator of the MAPK pathway. Furthermore, we show that MELK promotes melanoma growth by activating NF-kappaB pathway activity via Sequestosome 1 (SQSTM1/p62). Altogether, these results underpin an important role for MELK in melanoma growth downstream of the MAPK pathway

Sustainable green campus in Nepal: 3E analysis

In today's world, where global warming is one of the greatest human challenges, sustainable energy generation is becoming increasingly relevant. The use of green and clean energy sources is the best way to minimize CO2, CO, NOX and other emissions of conventional energy usage. Solar photovoltaic (PV) systems are more beneficial and an exciting application to set up an eco-friendly green educational campus. In this regard, the potential sites within Tribhuvan University, Institute of Engineering, Purwanchal Campus, Dharan city, Nepal are analysed for grid-tied solar PV power plant installation to meet the 100% energy demand of the campus using energy, economic and environment-friendly analysis. The daily, monthly and annual load and solar irradiance data of past years of the campus have been analysed to estimate the solar PV plant's capacity and system performance using PVSYST V7.0 software analysis tools. The simulation results show that 110 kWp of solar PV power plant will be sufficient for the entire campus to qualify for the first fully green-powered campus in Nepal, which corresponds to fulfill 66.4 MWh/year daytime energy demand out of total 161 MWh/year energy consumption of the campus with a capacity to generate a total of 181.5 MWh/year energy from the designed solar PV system. The result also shows that 115.1 MWh/year of surplus energy produced from the PV power plant can be injected into the utility grid to yield considerable savings in utility cost. On the basis of these results, campus authorities and stakeholders may commit to investing and implementing of this project to ensure that the campus is completely green

Prevalence and risk of hepatitis e virus infection in the HIV population of Nepal

Background: Infection with the hepatitis E virus (HEV) can cause acute hepatitis in endemic areas in immune-competent hosts, as well as chronic infection in immune-compromised subjects in non-endemic areas. Most studies assessing HEV infection in HIV-infected populations have been performed in developed countries that are usually affected by HEV genotype 3. The objective of this study is to measure the prevalence and risk of acquiring HEV among HIV-infected individuals in Nepal. Methods: We prospectively evaluated 459 Human Immunodeficiency Virus (HIV)-positive individuals from Nepal, an endemic country for HEV, for seroprevalence of HEV and assessed risk factors associated with HEV infection. All individuals were on antiretroviral therapy and healthy blood donors were used as controls. Results: We found a high prevalence of HEV IgG (39.4%) and HEV IgM (15.3%) in HIV-positive subjects when compared to healthy HIV-negative controls: 9.5% and 4.4%, respectively (OR: 6.17, 95% CI 4.42-8.61, p < 0.001 and OR: 3.7, 95% CI 2.35-5.92, p < 0.001, respectively). Individuals residing in the Kathmandu area showed a significantly higher HEV IgG seroprevalance compared to individuals residing outside of Kathmandu (76.8% vs 11.1%, OR: 30.33, 95% CI 18.02-51.04, p = 0.001). Mean CD4 counts, HIV viral load and presence of hepatitis B surface antigen correlated with higher HEV IgM rate, while presence of hepatitis C antibody correlated with higher rate of HEV IgG in serum. Overall, individuals with HEV IgM positivity had higher levels of alanine aminotransferase (ALT) than IgM negative subjects, suggesting active acute infection. However, no specific symptoms for hepatitis were identified. Conclusions: HIV-positive subjects living in Kathmandu are at higher risk of acquiring HEV infection as compared to the general population and to HIV-positive subjects living outside Kathmandu

A quantitative mass spectrometry-based approach to monitor the dynamics of endogenous chromatin-associated protein complexes.

Understanding the dynamics of endogenous protein-protein interactions in complex networks is pivotal in deciphering disease mechanisms. To enable the in-depth analysis of protein interactions in chromatin-associated protein complexes, we have previously developed a method termed RIME (Rapid Immunoprecipitation Mass spectrometry of Endogenous proteins). Here, we present a quantitative multiplexed method (qPLEX-RIME), which integrates RIME with isobaric labelling and tribrid mass spectrometry for the study of protein interactome dynamics in a quantitative fashion with increased sensitivity. Using the qPLEX-RIME method, we delineate the temporal changes of the Estrogen Receptor alpha (ERα) interactome in breast cancer cells treated with 4-hydroxytamoxifen. Furthermore, we identify endogenous ERα-associated proteins in human Patient-Derived Xenograft tumours and in primary human breast cancer clinical tissue. Our results demonstrate that the combination of RIME with isobaric labelling offers a powerful tool for the in-depth and quantitative characterisation of protein interactome dynamics, which is applicable to clinical samples

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere