A five-drug class model using routinely available clinical features to optimise prescribing in type 2 diabetes: a prediction model development and validation study.

Background: Data to support individualised choice of optimal glucose-lowering therapy are scarce for people with type 2 diabetes. We aimed to establish whether routinely available clinical features can be used to predict the relative glycaemic effectiveness of five glucose-lowering drug classes.

Methods: We developed and validated a five-drug class model to predict the relative glycaemic effectiveness, in terms of absolute 12-month glycated haemoglobin (HbA), for initiating dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists, sodium-glucose co-transporter-2 inhibitors, sulfonylureas, and thiazolidinediones.

The transformative terrain: An in-depth analysis of trends in self-managed abortion in India using NFHS-5 national data.

In 2022, the World Health Organization endorsed self-managed abortion (SMA) with medical abortion pills as a safe abortion method. This study utilises India's National Family Health Survey Round 5 (2019-2021) data from 724,115 women to estimate state-level self-managed abortion (SMA). It examines SMA characteristics, trends over time, and self-reported complications in India using descriptive and multivariate analysis.

A Retrospective Cohort Study of Tranexamic Acid Administration for the Treatment of Angiotensin-Converting Enzyme Inhibitor-Induced Angioedema in the Emergency Department.

Background: Treatment options for angiotensin-converting enzyme inhibitor-induced angioedema (ACEi-AE) are primarily limited to airway monitoring and protection with intubation. The efficacy of tranexamic acid (TXA) in this context remains poorly understood.

Objective: Examine outcomes among patients treated with and without TXA for ACEi-AE.

Building ADMISSION - A research collaborative to transform understanding of multiple long-term conditions for people admitted to hospital.

Background: Multiple long-term conditions (MLTCs; commonly referred to as multimorbidity) are highly prevalent among people admitted to hospital and are therefore of critical importance to hospital-based healthcare systems. To date, most research on MLTCs has been conducted in primary care or the general population with comparatively little work undertaken in the hospital setting.

Purpose: To describe the rationale and content of ADMISSION: a four-year UK Research and Innovation and National Institute of Health and Care Research funded interdisciplinary programme that seeks, in partnership with public contributors, to transform care for people living with MLTCs admitted to hospital.

Understanding the unique role of community-based para-professionals delivering early childhood development in low-resource contexts: a Delphi study.

Background: Community-based para-professionals are trained or untrained professionals who assist in the delivery of health-related care in communities where they live. The role of community-based para-professionals in supporting early childhood development (ECD) supports has attracted increased attention recently, particularly in the context of severe constraints in the global health workforce. However, these practitioners face challenges associated with low status and poor working conditions.

Exploring the potential role of C-peptide in type 2 diabetes management.

Type 2 diabetes (T2D) is a complex condition characterised by the interaction between insulin resistance and beta cell dysfunction. C-peptide, a key biomarker of endogenous insulin secretion, has a role in diagnosing type 1 diabetes (T1D). However, its utility in T2D has not been extensively studied.

Genome-wide association study of varenicline-aided smoking cessation.

Introduction: Varenicline is an α4β2 nicotinic acetylcholine receptor partial agonist with the highest therapeutic efficacy of any pharmacological smoking cessation aid and a 12-month cessation rate of 26%. Genetic variation may be associated with varenicline response, but to date no genome-wide association studies of varenicline response have been published.

Methods: In this study, we investigated the genetic contribution to varenicline effectiveness using two electronic health record-derived phenotypes.

Diagnosis and management of antiphospholipid syndrome.

Antiphospholipid syndrome is an autoimmune disease characterised by thrombotic and/or obstetric manifestations with persistent antiphospholipid antibodies. Diagnosis involves confirming the persistence of antiphospholipid antibodies in symptomatic patients, using validated classification criteria as a guide. The likelihood of obtaining false-positive or false-negative test results in certain settings, and the lack of standardisation between laboratory methods, are important considerations.

Deep-learning prediction of cardiovascular outcomes from routine retinal images in individuals with type 2 diabetes.

Background: Prior studies have demonstrated an association between retinal vascular features and cardiovascular disease (CVD), however most studies have only evaluated a few simple parameters at a time. Our aim was to determine whether a deep-learning artificial intelligence (AI) model could be used to predict CVD outcomes from routinely obtained diabetic retinal screening photographs and to compare its performance to a traditional clinical CVD risk score.

Methods: We included 6127 individuals with type 2 diabetes without myocardial infarction or stroke prior to study entry.

Hypoglycaemic stimulation of macrophage cytokine release is suppressed by AMP-activated protein kinase activation.

Aims: Acute hypoglycaemia promotes pro-inflammatory cytokine production, increasing the risk for cardiovascular events in diabetes. AMP-activated protein kinase (AMPK) is regulated by and influences the production of pro-inflammatory cytokines. We sought to examine the mechanistic role of AMPK in low glucose-induced changes in the pro-inflammatory cytokine macrophage migration inhibitory factor (MIF), which is elevated in people with diabetes.

iDiabetes platform-enhanced phenotyping of patients with diabetes for precision diagnosis, prognosis and treatment: study protocol for a cluster-randomised controlled study in Tayside, Scotland.

Introduction And Aim: Diabetes is a global health emergency with increasing prevalence and diabetes-associated morbidity and mortality. One of the challenges in optimising diabetes care is translating research advances in this heterogeneous disease into clinical care. A potential solution is the introduction of precision medicine approaches into diabetes care.

Routine measurement of cardiometabolic disease risk factors in primary care in England before, during, and after the COVID-19 pandemic: A population-based cohort study.

Background: This study estimated to what extent the number of measurements of cardiometabolic risk factors (e.g., blood pressure, cholesterol, glycated haemoglobin) were impacted by the COVID-19 pandemic and whether these have recovered to expected levels.

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV.

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.

Concurrent Zoster Sine Herpete and Hepatosplenic Fungal Infection in a Cancer Patient: A Case Report.

In patients undergoing treatment for hematological cancers, like hairy cell leukemia (HCL), appropriate management of infections is of utmost importance. This paper describes the successful treatment of an HCL patient who had both visceral zoster sine herpete (ZSH) and hepatosplenic fungal infection, possibly caused by . To our knowledge, this is the first such case to appear in the literature, as these are rare conditions associated with states of immunosuppression, similar to those observed in hematological malignancy.

A radiation therapy platform to enable upright cone beam computed tomography and future upright treatment on existing photon therapy machines.

Background: The conventional lying down position for radiation therapy can be challenging for patients due to pain, swallowing or breathing issues. To provide an alternative upright treatment position for these patients, we have developed a portable rotating radiation therapy platform which integrates with conventional photon treatment machines. The device enables cone-beam computed tomography (CBCT) imaging of patients in an upright position, and the future delivery of therapeutic radiation.

Self-Assembly of Microstructured Protein Coatings with Programmable Functionality for Fluorescent Biosensors.

Proteins, as genetically programmable functional macromolecules, hold immense potential as biocompatible self-assembling building blocks, owing to their versatility in building coating materials and programming their functionality genetically. In this study, we demonstrate a modular self-assembly of protein coatings that are genetically programmable for a biosensor application. We designed and produced recombinant fusion protein building blocks to form microstructured coatings on diverse substrates, such as glass or polymers, through thermally triggered liquid-liquid phase separation and an orthogonal high-affinity coiled-coil interaction.

Search for the Z Boson Decay to ττμμ in Proton-Proton Collisions at sqrt[s]=13 TeV.

The first search for the Z boson decay to ττμμ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 138  fb^{-1}. The data are compatible with the predicted background. For the first time, an upper limit at the 95% confidence level of 6.

Subclassification of obesity for precision prediction of cardiometabolic diseases.

Obesity and cardiometabolic disease often, but not always, coincide. Distinguishing subpopulations within which cardiometabolic risk diverges from the risk expected for a given body mass index (BMI) may facilitate precision prevention of cardiometabolic diseases. Accordingly, we performed unsupervised clustering in four European population-based cohorts (N ≈ 173,000).