Efficacy of MEDI0618, a pH-dependent monoclonal antibody targeting PAR2, in preclinical models of migraine.

Protease activated receptor 2 (PAR2) is a G-protein coupled receptor expressed in meningeal neurons, fibroblasts and mast cells that may be targeted to treat migraine. MEDI0618, a fully humanized PAR2 monoclonal antibody, engineered to enhance FcRn-dependent recycling and currently in clinical development, was evaluated in human and rodent in vitro assays, in multiple murine in vivo migraine models and in a model of post-traumatic headache. MEDI0618 bound specifically and with high affinity to cells expressing human PAR2 (hPAR2) and prevented matriptase-induced increase in cytosolic calcium.

Survey of healthcare-associated sink infrastructure, and sink trap antibiotic residues and biochemistry, in 29 UK hospitals.

Background: Hospital sinks are linked to healthcare-associated infections. Antibiotics and chemicals in sink traps can select for pathogens and antimicrobial resistance (AMR). Optimising sink design and usage can mitigate sink-to-patient dissemination of pathogens, but large-scale surveys of hospital sink infrastructure are lacking.

Safety reporting in neonatal clinical trials: reflections towards optimal, globally relevant approaches.

Adverse event (AE) collection is a key part of evidence generation in clinical trials and an integral element of safety reporting. AE assessment and documentation is particularly challenging in neonates who are a heterogeneous population with high rates of co-morbidities. Neonatal research is finally gaining the attention of regulators regarding drug development and the need for optimal dosing specific to this population.

Developing a framework for tracking antimicrobial resistance gene movement in a persistent environmental reservoir.

Mobile genetic elements are key to the global emergence of antibiotic resistance. We successfully reconstructed the complete bacterial genome and plasmid assemblies of isolates sharing the same carbapenemase gene to understand evolution over time in six confined hospital drains over five years. From 82 isolates we identified 14 unique strains from 10 species with 113 carrying plasmids across 16 distinct replicon types.

Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections.

Background: Patients with Gram-negative bloodstream infections are at risk of serious adverse outcomes without active treatment, but identifying who has antimicrobial resistance (AMR) to target empirical treatment is challenging.

Methods: We used XGBoost machine learning models to predict antimicrobial resistance to seven antibiotics in patients with Enterobacterales bloodstream infection. Models were trained using hospital and community data from Oxfordshire, UK, for patients with positive blood cultures between 01-January-2017 and 31-December-2021.

Addition of macrolide antibiotics for hospital treatment of community-acquired pneumonia.

Background: Current guidelines recommend combining a macrolide with a β-lactam antibiotic for the empirical treatment of moderate-to-high severity community-acquired pneumonia (CAP); however macrolide use is associated with potential adverse events and antimicrobial resistance.

Methods: We analysed electronic health data from 8,872 adults in Oxfordshire, UK, hospitalised with CAP between 01-January-2016 and 19-March-2024, who received either amoxicillin or co-amoxiclav as initial treatment. We examined the effects of adjunctive macrolides on 30-day all-cause mortality, time to hospital discharge, and changes in Sequential Organ Failure Assessment (SOFA) score, using inverse probability treatment weighting to address confounding by baseline severity.

Robust self-supervised denoising of voltage imaging data using CellMincer.

Voltage imaging is a powerful technique for studying neuronal activity, but its effectiveness is often constrained by low signal-to-noise ratios (SNR). Traditional denoising methods, such as matrix factorization, impose rigid assumptions about noise and signal structures, while existing deep learning approaches fail to fully capture the rapid dynamics and complex dependencies inherent in voltage imaging data. Here, we introduce CellMincer, a novel self-supervised deep learning method specifically developed for denoising voltage imaging datasets.

Yatakemycin biosynthesis requires two deoxyribonucleases for toxin self-resistance.

The highly active natural product yatakemycin (YTM) from sp. TP-A0356 is a potent DNA damaging agent with antimicrobial and antitumor properties. The YTM biosynthesis gene cluster () contains several toxin self-resistance genes.

Determining Targets for Antiretroviral Drug Concentrations: A Causal Framework Illustrated With Pediatric Efavirenz Data From the CHAPAS-3 Trial.

Background: Determining a therapeutic window for maintaining antiretroviral drug concentrations within an appropriate range is required for identifying effective dosing regimens. The limits of this window are typically calculated using predictive models. We propose that target concentrations should instead be calculated based on counterfactual probabilities of relevant outcomes and describe a counterfactual framework for this.

Predicting individual patient and hospital-level discharge using machine learning.

Background: Accurately predicting hospital discharge events could help improve patient flow and the efficiency of healthcare delivery. However, using machine learning and diverse electronic health record (EHR) data for this task remains incompletely explored.

Methods: We used EHR data from February-2017 to January-2020 from Oxfordshire, UK to predict hospital discharges in the next 24 h.

Azithromycin in severe malaria bacterial co-infection in African children (TABS-PKPD): a phase II randomised controlled trial.

Background: African children with severe malaria are at increased risk of non-typhoidal salmonellae co-infection. Broad-spectrum antibiotics are recommended by guidelines but the optimal class and dose have not been established. We investigated the optimal dose of oral dispersible azithromycin and whether simple clinical criteria and point-of-care biomarkers could target antibiotics to those at greatest risk of bacterial co-infection.

Primed for Discovery.

Antibiotics are essential components of current medical practice, but their effectiveness is being eroded by the increasing emergence of antimicrobial-resistant infections. At the same time, the rate of antibiotic discovery has slowed, and our future ability to treat infections is threatened. Among Christopher T.

Functional Redundancy and Dual Function of a Hypothetical Protein in the Biosynthesis of Eunicellane-Type Diterpenoids.

Many complex terpenoids, predominantly isolated from plants and fungi, show drug-like physicochemical properties. Recent advances in genome mining revealed actinobacteria as an almost untouched treasure trove of terpene biosynthetic gene clusters (BGCs). In this study, we characterized a terpene BGC with an unusual architecture.

How, why and when are delayed (back-up) antibiotic prescriptions used in primary care? A realist review integrating concepts of uncertainty in healthcare.

Background: Antimicrobial resistance is a global patient safety priority and inappropriate antimicrobial use is a key contributing factor. Evidence have shown that delayed (back-up) antibiotic prescriptions (DP) are an effective and safe strategy for reducing unnecessary antibiotic consumption but its use is controversial.

Methods: We conducted a realist review to ask why, how, and in what contexts general practitioners (GPs) use DP.

Statistical Coupling Analysis Predicts Correlated Motions in Dihydrofolate Reductase.

Dihydrofolate reductase (DHFR), due to its universality and the depth with which it has been studied, is a model system in the study of protein dynamics. Myriad previous works have identified networks of residues in positions near to and remote from the active site that are involved in the dynamics. For example, specific mutations on the Met20 loop in DHFR (N23PP/S148A) are known to disrupt millisecond-time scale motions as well as reduce catalytic activity.

Exploring uncatalogued genetic variation in antimicrobial resistance gene families in Escherichia coli: an observational analysis.

Background: Antimicrobial resistance (AMR) in Escherichia coli is a global problem associated with substantial morbidity and mortality. AMR-associated genes are typically annotated based on similarity to variants in a curated reference database, with the implicit assumption that uncatalogued genetic variation within these is phenotypically unimportant. In this study, we evaluated the performance of the AMRFinder tool and, subsequently, the potential for discovering new AMR-associated gene families and characterising variation within existing ones to improve genotype-to-susceptibility phenotype predictions in E coli.

Exploration, expansion and definition of the atropopeptide family of ribosomally synthesized and posttranslationally modified peptides.

Ribosomally synthesized and posttranslationally modified peptides (RiPPs) constitute a diverse class of natural products. Atropopeptides are a recent addition to the class. Here we developed AtropoFinder, a genome mining algorithm to chart the biosynthetic landscape of the atropopeptides.

Analysis of EGFR binding hotspots for design of new EGFR inhibitory biologics.

The epidermal growth factor (EGF) receptor (EGFR) is activated by the binding of one of seven EGF-like ligands to its ectodomain. Ligand binding results in EGFR dimerization and stabilization of the active receptor conformation subsequently leading to activation of downstream signaling. Aberrant activation of EGFR contributes to cancer progression through EGFR overexpression/amplification, modulation of its positive and negative regulators, and/or activating mutations within EGFR.

Stop antibiotics when you feel better? Opportunities, challenges and research directions.

Shortening standard antibiotic courses and stopping antibiotics when patients feel better are two ways to reduce exposure to antibiotics in the community, and decrease the risks of antimicrobial resistance and antibiotic side effects. While evidence shows that shorter antibiotic treatments are non-inferior to longer ones for infections that benefit from antibiotics, shorter courses still represent average treatment durations that might be suboptimal for some. In contrast, stopping antibiotics based on improvement or resolution of symptoms might help personalize antibiotic treatment to individual patients and help reduce unnecessary exposure.

Genomic epidemiology and longitudinal sampling of ward wastewater environments and patients reveals complexity of the transmission dynamics of -carbapenemase-producing Enterobacterales in a hospital setting.

Background: Healthcare-associated wastewater and asymptomatic patient reservoirs colonized by carbapenemase-producing Enterobacterales (CPE) contribute to nosocomial CPE dissemination, but the characteristics and dynamics of this remain unclear.

Methods: We systematically sampled wastewater sites ( = 4488 samples; 349 sites) and patients ( = 1247) across six wards over 6-12 months to understand bla-associated CPE (KPC-E) diversity within these reservoirs and transmission in a healthcare setting. Up to five KPC-E-positive isolates per sample were sequenced (Illumina).

A Phase I trial of Non-invasive Ventilation and seizure prophylaxis with levetiracetam In Children with Cerebral Malaria Trial (NOVICE-M Trial).

Background: African children with cerebral malaria and seizures caused are at greater risk of poor outcomes including death and neurological sequelae. The agonal events are severe hypoventilation and respiratory arrest often triggered by seizures. We hypothesised that prophylactic anti-seizure medication (ASM) could avert 'spikes' of intracranial pressure during or following seizures and that adequate ventilation could be supported by biphasic Cuirass Ventilation (BCV) which requires no intubation.