Knapen et al. apply consensus-independent transcriptional component analysis to dissect transcriptomes into statistically independent transcriptional components in early colorectal cancer. Their findings identify 43 biological processes associated with disease-free survival which enables stratification of patients into different subgroups.

Takele et al. conduct a systematic review and meta-analysis of the effects of intervention characteristics on preventing gestational diabetes. Group or healthcare facility-based physical activity interventions are found to be more effective in preventing gestational diabetes than community-based interventions.

Iwadare et al. investigate the value of serum autotaxin levels in predicting liver-related events within a retrospective cohort of 309 biopsy-proven NAFLD patients. Multivariate Cox proportional hazards models identify autotaxin levels and advanced fibrosis as independent predictive factors.

Van der Zalm et al. apply Ridge regression analysis to RNA-seq data from esophageal cancer samples to predict mesenchymal transitions occurring in patients. Expression of NANOG in pre-treatment biopsies is associated with poor response to neoadjuvant chemoradiation, recurrence, and median overall survival in patients with esophageal adenocarcinoma.

Yan, Liang, Zhang et al. propose a domain knowledge-based interpretable deep learning system to improve breast cancer risk prediction from multimodal ultrasound images. Its inherent interpretability enables effective human-machine collaboration and thus may aid clinical decision-making.

Zhang et al. demonstrate that plasma sampling for a VHL-PROTAC does not represent the tissue concentrations necessary for efficacy; the tissue uptake/retention can be used to guide their therapeutic potential in target organs.

Wever et al. explore the use of different types of patient-friendly material, including urine, for the detection of ovarian cancer by methylation and copy number analysis. Upon continued development, DNA-based testing in cervical scrapes and urine could aid ovarian cancer diagnosis.

James et al. compare mitochondrial function in fibroblast cell lines from disease carriers of spinal muscular atrophy (SMA) and control individuals. They report altered mitochondrial activity in SMA carriers, suggesting that carriers have a subclinical mitochondrial phenotype.

Huo, Ong et al. present a comprehensive workflow to try to overcome key limitations in prior approaches for artificial intelligence (AI)-assisted prostate cancer Gleason grading. Their approach incorporates automated quality control, efficient annotation and visualization, and pathologist-AI interaction.

Chisholm-Burns et al. discuss the substantial shortage of organs available for transplantation, with disparities in access amongst some racial and ethnic groups. The authors suggest that while xenotransplantation can potentially increase organ availability, it also has the potential to further embed inequities in transplant care.

Thirunavukkarasu et al. discuss how standard lifestyle interventions prove ineffective in preventing type 2 diabetes in individuals with isolated impaired fasting glucose, a highly prevalent prediabetes phenotype globally. They propose low-calorie diets as a promising strategy for diabetes prevention in this high-risk population.

Zhang et al. discuss how artificial intelligence (AI) can be used to optimize clinical trial design and potentially boost the success rate of clinical trials. AI has unparalleled potential to leverage real-world data and unlock valuable insights for innovative trial design.

Ivancovsky-Wajcman et al. outline the need for a holistic preventive hepatology approach, involving social nutrition and social prescribing, to address the public health threat of metabolic dysfunction-associated steatotic liver disease (MASLD). They argue that this will facilitate individuals’ engagement in behavioural modifications to treat MASLD.

Macharia et al. discuss a Communications Medicine article on global healthcare accessibility and the impact of the COVID-19 pandemic. They outline strengths in the comprehensive approach taken to studying revealed versus potential spatial accessibility, plus some limitations and wider context with which the results can be interpreted.

Pallett et al. discuss the impact of human conflict on development of antimicrobial resistance. They overview approaches to limit the spread of antimicrobial resistance, using the ongoing conflict in Ukraine as an example of the challenges and opportunities.