Full UPF3B function is critical for neuronal differentiation of neural stem cells

Acknowledgments We thank Fred H Gage (Salk Institute, La Jolla, CA, USA) for HCN-A94 cells and Niels Gehring (University of Cologne, Germany) for constructs. We gratefully acknowledge Tenovus Scotland (Project Grant G11-06), Moonlight Prowl (FS) and the Saudi Arabian Ministry of Higher Education via King Abdullah Program for Scholarships for support (TA). JA is supported by a PhD studentship from Medical Research Scotland (PhD-654-2012) and Dundee Cell Products.Peer reviewedPublisher PD

Antiretroviral resistance in HIV-1 patients at a tertiary medical institute in Saudi Arabia: a retrospective study and analysis

Abstract Background Since the early 90’s antiretroviral drugs have been available at King Faisal Specialist Hospital and Research Centre (KFSH&RC), a referral hospital in Riyadh, Saudi Arabia, for the treatment of both adults and children infected with HIV-1. However, up to date, there are no genetic profiling data for the resistance-causing mutations in HIV-1 virus in patients on antiretroviral drugs therapy. This paper presents an initial report and a profiling survey of drug resistance-associated mutations of 103 HIV-1 patients seen at KFSH&RC. Methods This is a retrospective study on Patients treated at KFSH&RC since 2003 up to 2016. The analysis was done on the drug resistance mutations profiles of 103 patients who were undergoing highly active antiretroviral therapy protocols. Results Our analysis shows that the drug resistance mutations reported in our treatment cohort of HIV-infected adults patients is similar what is internationally reported to some extent. Additionally, we have identified novel drug resistance causing mutations. Furthermore, different profile of drug resistance causing mutations was also observed. Conclusion Patients showed both similar and new drug resistant causing mutations, early identification of these mutations is crucial to guide and avoid failure future therapy

Association of Child Growth Failure Indicators With Household Sanitation Practices in India (1998-2021): Spatiotemporal Observational Study

BackgroundUndernutrition among children younger than 5 years is a subtle indicator of a country’s health and economic status. Despite substantial macroeconomic progress in India, undernutrition remains a significant burden with geographical variations, compounded by poor access to water, sanitation, and hygiene services. ObjectiveThis study aimed to explore the spatial trends of child growth failure (CGF) indicators and their association with household sanitation practices in India. MethodsWe used data from the Indian Demographic and Health Surveys spanning 1998-2021. District-level CGF indicators (stunting, wasting, and underweight) were cross-referenced with sanitation and sociodemographic characteristics. Global Moran I and Local Indicator of Spatial Association were used to detect spatial clustering of the indicators. Spatial regression models were used to evaluate the significant determinants of CGF indicators. ResultsOur study showed a decreasing trend in stunting (44.9%-38.4%) and underweight (46.7%-35.7%) but an increasing prevalence of wasting (15.7%-21.0%) over 15 years. The positive values of Moran I between 1998 and 2021 indicate the presence of spatial autocorrelation. Geographic clustering was consistently observed in the states of Madhya Pradesh, Jharkhand, Odisha, Uttar Pradesh, Chhattisgarh, West Bengal, Rajasthan, Bihar, and Gujarat. Improved sanitation facilities, a higher wealth index, and advanced maternal education status showed a significant association in reducing stunting. Relative risk maps identified hotspots of CGF health outcomes, which could be targeted for future interventions. ConclusionsDespite numerous policies and programs, malnutrition remains a concern. Its multifaceted causes demand coordinated and sustained interventions that go above and beyond the usual. Identifying hotspot locations will aid in developing control methods for achieving objectives in target areas