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CD4+ T cell immunity against cutaneous melanoma encompasses multifaceted MHC II-dependent responses

Whereas CD4+ T cells conventionally mediate antitumor immunity by providing help to CD8+ T cells, recent clinical studies have implied an important role for cytotoxic CD4+ T cells in cancer immunity. Using an orthotopic melanoma model, we provide a detailed account of antitumoral CD4+ T cell responses and their regulation by major histocompatibility complex class II (MHC II) in the skin.

A blueprint for a multi-disease, multi-domain Bayesian adaptive platform trial incorporating adult and paediatric subgroups: the Staphylococcus aureus Network Adaptive Platform trial

The Staphylococcus aureus Network Adaptive Platform (SNAP) trial is a multifactorial Bayesian adaptive platform trial that aims to improve the way that S. aureus bloodstream infection, a globally common and severe infectious disease, is treated. In a world first, the SNAP trial will simultaneously investigate the effects of multiple intervention modalities within multiple groups of participants with different forms of S. aureus bloodstream infection.

Respiratory syncytial virus in children: epidemiology and clinical impact post-COVID-19

Respiratory syncytial virus (RSV) remains a leading cause of mortality and morbidity worldwide. RSV seasonality was disrupted by COVID-19-associated nonpharmaceutical interventions (NPIs). We review RSV seasonality, molecular epidemiology, clinical manifestations, and community awareness to inform future prevention strategies. 

A Maximum Entropy Model of the Distribution of Dengue Serotype in Mexico

Pathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling.

Protocol for a nested case-control study design for omics investigations in the Environmental Determinants of Islet Autoimmunity cohort

The Environmental Determinants of Islet Autoimmunity (ENDIA) pregnancy-birth cohort investigates the developmental origins of type 1 diabetes (T1D), with recruitment between 2013 and 2019. ENDIA is the first study in the world with comprehensive data and biospecimen collection during pregnancy, at birth and through childhood from at-risk children who have a first-degree relative with T1D.

Developing type 1 diabetes resources: a qualitative study to identify resources needed to upskill and support community sport coaches

Community sport coaches in Western Australia lack an understanding, the confidence, and knowledge in supporting young people with Type 1 diabetes (T1D). This study aims to identify what T1D educational resources are required to upskill coaches in Western Australia. 

Inflammation risk before cardiac surgery and the treatment effect of intraoperative dexamethasone

Patients who exhibit high systemic inflammation after cardiac surgery may benefit most from pre-emptive anti-inflammatory treatments. In this secondary analysis of the randomised, double-blind Intraoperative High-Dose Dexamethasone for Cardiac Surgery trial, we set out to develop an inflammation risk prediction model and assess whether patients at higher risk benefit from a single intraoperative dose of dexamethasone.

Spatio-temporal mapping of stunting and wasting in Nigerian children: A bivariate mixture modeling

Studies have shown that stunting and wasting indicators are strongly correlated among children, with the potential of concurrently affecting their physical and cognitive development. However, the identification of subpopulations of children with varying risks of stunting and wasting could be valuable for targeted intervention.

CRISPR-Cas9-generated PTCHD1 2489T>G stem cells recapitulate patient phenotype when undergoing neural induction

An estimated 3.5%-5.9% of the global population live with rare diseases, and approximately 80% of these diseases have a genetic cause. Rare genetic diseases are difficult to diagnose, with some affected individuals experiencing diagnostic delays of 5-30 years. Next-generation sequencing has improved clinical diagnostic rates to 33%-48%. In a majority of cases, novel variants potentially causing the disease are discovered.