A deep learning network can classify cardiac myocytes into drug-free and drugged categories and predict the impact of electrophysiological perturbation across the continuum of aging.

A multi-species chemical screening platform reveals a conserved role for p38 inhibition in modulating ryanodine receptor-related phenotypes and is adaptable to a range of neuromuscular disorders.

A genetically diverse panel of subject-specific induced pluripotent stem cells models the in vitro susceptibility of cardiac cells to develop a cardiotoxic drug response.

Libraries of patient-derived tumor organoids are a reliable and scalable model system that can help identify and optimize targeted therapies in a pre-clinical setting.

A novel bioengineered human skeletal muscle model with accurate physiological and pharmacological responses may provide a useful tool for preclinical testing.

The oral carbapenem 'Tebipenem' has high level antibacterial activity against highly drug-resistant Shigella, and its mode of action and pharmacokinetics make it suitable for the treatment of severe diarrhoea caused by highly drug-resistant bacteria.

A computer model of human cardiomyocyte was produced and validated on independent datasets, overcoming shortcomings of its predecessors, also yielding broadly relevant insights and results on major ionic currents.

Genetic data revealed existing drugs that could be repurposed to improve lung function, with evidence that compounds which control blood glucose could be particularly useful for respiratory impairment.

A deep learning-based pipeline was developed for extracting cellular signals flexibly from moving cells in 3D time lapse images, and it outperformed previous methods under different imaging conditions.