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Air pollution is a major risk factor for global health, with 3 million deaths annually being attributed to fine particulate matter ambient pollution (PM2.5).The primary source of information for estimating population exposures to air pollution has been measurements from ground monitoring networks but, although coverage is increasing, regions remain in which monitoring is limited. The data integration model for air quality supplements ground monitoring data with information from other sources, such as satellite retrievals of aerosol optical depth and chemical transport models. Set within a Bayesian hierarchical modelling framework, the model allows spatially varying relationships between ground measurements and other factors that estimate air quality. The model is used to estimate exposures, together with associated measures of uncertainty, on a high resolution grid covering the entire world from which it is estimated that 92% of the world's population reside in areas exceeding the World Health Organization's air quality guidelines.

Global assessments of air quality and health require comprehensive estimates of the exposures to air pollution that are experienced by populations in every country. However, there are many countries in which measurements from ground-based monitoring are sparse or non-existent, with quality-control and representativeness providing additional challenges. While ground-based monitoring provides a far from complete picture of global air quality, there are other sources of information that provide comprehensive coverage across the globe. The World Health Organization developed the Data Integration Model for Air Quality (DIMAQ) to combine information from ground measurements with that from other sources, such as atmospheric chemical transport models and estimates from remote sensing satellites in order to produce the information that is required for health burden assessment and the calculation of air pollution-related Sustainable Development Goals indicators. Here, we show an example of the use of DIMAQ with the Copernicus Atmosphere Monitoring Service Re-Analysis (CAMSRA) of atmospheric composition, which represents the best practices in meteorology and climate monitoring that were developed under the World Meteorological Organization’s Global Atmosphere Watch programme. Estimates of PM2.5 from CAMSRA are integrated within the DIMAQ framework in order to produce high-resolution estimates of air pollution exposure that can be aggregated in a coherent fashion to produce country-level assessments of exposures.

Background Voluntary medical male circumcision (VMMC) reduces the risk of male HIV acquisition by 60%. Programmes to provide VMMCs for HIV prevention have been introduced in sub-Saharan African countries with high HIV burden. Traditional circumcision is also a long-standing male coming-of-age ritual, but practices vary considerably across populations. Accurate estimates of circumcision coverage by age, type, and time at subnational levels are required for planning and delivering VMMCs to meet targets and evaluating their impacts on HIV incidence. Methods We developed a Bayesian competing risks time-to-event model to produce region-age-time-type specific probabilities and coverage of male circumcision with probabilistic uncertainty. The model jointly synthesises data from household surveys and health system data on the number of VMMCs conducted. We demonstrated the model using data from five household surveys and VMMC programme data to produce estimates of circumcision coverage for 52 districts in South Africa between 2008 and 2019. Results Nationally, in 2008, 24.1% (95% CI: 23.4–24.8%) of men aged 15–49 were traditionally circumcised and 19.4% (18.9–20.0%) were medically circumcised. Between 2010 and 2019, 4.25 million VMMCs were conducted. Circumcision coverage among men aged 15–49 increased to 64.0% (63.2–64.9%) and medical circumcision coverage to 42% (41.3–43.0%). Circumcision coverage varied widely across districts, ranging from 13.4 to 86.3%. The average age of traditional circumcision ranged between 13 and 19 years, depending on local cultural practices. Conclusion South Africa has made substantial, but heterogeneous, progress towards increasing medical circumcision coverage. Detailed subnational information on coverage and practices can guide programmes to identify unmet need to achieve national and international targets. Plain language summary Voluntary medical male circumcision reduces the risk of male HIV acquisition. Programmes to provide circumcisions for HIV prevention have been introduced in sub-Saharan African countries with high HIV burden. Estimates of circumcision coverage are needed for planning and delivering circumcisions to meet targets and evaluate their impacts on HIV incidence. We developed a model to integrate date from both household surveys and health systems on the number of circumcisions conducted, and applied it to understand how the practices and coverage of circumcision are changing in South Africa. National circumcision coverage increased considerably between 2008 and 2019, however, there remains a substantial subnational variation across districts and age groups. Further progress is needed to reach national and international targets. Thomas et al. present a model that integrates household survey and health system data to estimate subnational circumcision coverage in South Africa during scale-up for HIV prevention. Results show considerable, but heterogenous, progress towards increasing circumcision coverage, identifying priority ages and districts to reach national targets.

Transmembrane protein tyrosine phosphatases, such as CD45, can act as both positive and negative regulators of cellular signaling. CD45 positively modulates T cell receptor (TCR) signaling by constitutively priming p561ck through the dephosphorylation of the C-terminal negative regulatory phosphotyrosine site. However, CD45 can also exert negative effects on cellular processes, including events triggered by integrin-mediated adhesion. To better understand these opposing actions of tyrosine phosphatases, the subcellular compartmentalization of CD45 was imaged by using laser scanning confocal microscopy during functional TCR signaling of live T lymphocytes. On antigen engagement, CD45 was first excluded from the central region of the interface between the T cell and the antigen-presenting surface where CD45 would inhibit integrin activation. Subsequently, CD45 was recruited back to the center of the contact to an area adjacent to the site of sustained TCR engagement. Thus, CD45 is well positioned within a supramolecular assembly in the vicinity of the engaged TCR, where CD45 would be able to maintain src-kinase activity for the duration of TCR engagement.

Introduction Several HIV risk scores have been developed to identify individuals for prioritized HIV prevention in sub‐Saharan Africa. We systematically reviewed HIV risk scores to: (1) identify factors that consistently predicted incident HIV infection, (2) review inclusion of community‐level HIV risk in predictive models and (3) examine predictive performance. Methods We searched nine databases from inception until 15 February 2021 for studies developing and/or validating HIV risk scores among the heterosexual adult population in sub‐Saharan Africa. Studies not prospectively observing seroconversion or recruiting only key populations were excluded. Record screening, data extraction and critical appraisal were conducted in duplicate. We used random‐effects meta‐analysis to summarize hazard ratios and the area under the receiver‐operating characteristic curve (AUC‐ROC). Results From 1563 initial search records, we identified 14 risk scores in 13 studies. Seven studies were among sexually active women using contraceptives enrolled in randomized‐controlled trials, three among adolescent girls and young women (AGYW) and three among cohorts enrolling both men and women. Consistently identified HIV prognostic factors among women were younger age (pooled adjusted hazard ratio: 1.62 [95% confidence interval: 1.17, 2.23], compared to above 25), single/not cohabiting with primary partners (2.33 [1.73, 3.13]) and having sexually transmitted infections (STIs) at baseline (HSV‐2: 1.67 [1.34, 2.09]; curable STIs: 1.45 [1.17; 1.79]). Among AGYW, only STIs were consistently associated with higher incidence, but studies were limited (n = 3). Community‐level HIV prevalence or unsuppressed viral load strongly predicted incidence but was only considered in 3 of 11 multi‐site studies. The AUC‐ROC ranged from 0.56 to 0.79 on the model development sets. Only the VOICE score was externally validated by multiple studies, with pooled AUC‐ROC 0.626 [0.588, 0.663] (I2: 64.02%). Conclusions Younger age, non‐cohabiting and recent STIs were consistently identified as predicting future HIV infection. Both community HIV burden and individual factors should be considered to quantify HIV risk. However, HIV risk scores had only low‐to‐moderate discriminatory ability and uncertain generalizability, limiting their programmatic utility. Further evidence on the relative value of specific risk factors, studies populations not restricted to “at‐risk” individuals and data outside South Africa will improve the evidence base for risk differentiation in HIV prevention programmes. PROSPERO Number CRD42021236367

CD22 is a membrane immunoglobulin (mlg)-associated protein of B cells. CD22 is tyrosine-phosphorylated when mlg is ligated. Tyrosine-phosphorylated CD22 binds and activates SHP, a protein tyrosine phosphatase known to negatively regulate signaling through mlg. Ligation of CD22 to prevent its coaggregation with mlg lowers the threshold at which mlg activates the B cell by a factor of 100. In secondary lymphoid organs, CD22 may be sequestered away from mlg through interactions with counterreceptors on T cells. Thus, CD22 is a molecular switch for SHP that may bias mlg signaling to anatomic sites rich in T cells.

Introduction HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small‐area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five‐year age groups. Methods Small‐area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district‐level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016–2018. Results Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty‐eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city. Conclusions The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.

At the invitation of the Rwandan Government, Team Heart, a team of American healthcare professionals, performs volunteer rheumatic heart disease (RHD) surgery in Rwanda every year, and confronts ethical concerns that call for cultural sensitivity. This article describes how five standard bioethical precepts are applied in practice in medical volunteerism related to RHD surgery in Rwanda. The content for the applied precepts stems from semiscripted, transcribed conversations with the authors, two Rwandan cardiologists, a Rwandan nurse and a Rwandan premedical student. The conversations revealed that the criteria for RHD surgical selection in Rwanda are analogous to the patient-selection process involving material scarcity in the USA. Rwandan notions of benefit and harm focus more attention on structural issues, such as shared benefit, national reputation and expansion of expertise, than traditional Western notions. Harm caused by inadequate patient follow-up remains a critical concern. Gender disparities regarding biological and social implications of surgical valve choices impact considerations of justice. Individual agency remains important, but not central to Rwandan concepts of justice, transparency and respect, particularly regarding women. The Rwandan understanding of standard bioethical precepts is substantively similar to the traditionally recognised interpretation with important contextual differences. The communal importance of improving the health of a small number of individuals may be underestimated in previous literature. Moreover, openness and the incorporation of Rwandan stakeholders in difficult ethical choices and long-term contributions to indigenous medical capacity appear to be valued by Rwandans. These descriptions of applied precepts are applicable to different medical missions in other emerging nations following a similar process of inclusion.

Atopy is characterized by the formation of IgE antibody in persons with a genetic predisposition, who respond with immediate hypersensitivity on exposure to specific allergens. Atopy is common, affecting up to 40 percent of populations of Western societies, 1 – 3 and it underlies the development of allergic diseases in susceptible persons. Although environmental factors such as exposure to antigens have an important role in the development of allergic diseases, 4 – 6 there is a strong genetic predisposition. 7 , 8 Recently, a number of atopy susceptibility genes have been identified. Some of these, such as those for interleukin-4 9 – 11 and several HLA class II . . .