Das and colleagues develop and evaluate a parallel discriminator generative adversarial network (P-GAN) for improved in-vivo imaging of retinal cellular structures. The P-GAN network improves retinal pigment epithelium contrast 3.5-fold and the overall throughput 99-fold.

Felton et al. conduct a systematic review to determine the utility of islet autoantibodies as biomarkers of type 1 diabetes heterogeneity. They find that islet autoantibodies are most likely to be useful for patient stratification prior to clinical diagnosis.

Esposito et al. investigate the genetic basis of response to BNT162b2 mRNA COVID-19 vaccine in 1351 Italian subjects. They find variants in the human leukocyte antigen locus significantly associate with serum anti-SARS-CoV-2 antibody levels, after vaccination.

Fredolini et al. present a proteomics analysis of home-sampled dried blood spots taken from the general population in Stockholm during the COVID-19 pandemic. The study provides insights into the molecular effects of SARS-CoV-2 infection in non-hospitalized individuals and demonstrates the compatibility of self-sampled blood spots with proteomics.

Kruper et al. investigate the impact of glaucoma on brain tissue by comparing MRI data from 856 people with glaucoma to matched controls without glaucoma. They find that neural networks using tissue properties from visual brain connections more accurately detect glaucoma than those trained on non-visual brain connections.

Kolbinger, Veldhuizen et al. systematically review reporting guidelines for artificial intelligence (AI) methods in clinical research. They identify several essential, commonly recommended items on study design and model performance, while other items are specific to particular fields and research stages.

Das and colleagues develop and evaluate a parallel discriminator generative adversarial network (P-GAN) for improved in-vivo imaging of retinal cellular structures. The P-GAN network improves retinal pigment epithelium contrast 3.5-fold and the overall throughput 99-fold.

Holm et al. present a SARS-CoV-2 surveillance model linking hospitalization, seroprevalence, and wastewater concentrations. They fit this model to epidemic data from Kentucky, USA, to generate counterfactual scenarios highlighting the plausible effects of vaccination and changes in dynamics due to emergence of new variants.

Nunez et al. investigate the use of natural language processing to predict which patients with cancer will see a psychiatrist or counselling using the initial oncology consultation document. Their study supports the use of such techniques with widely-available medical documents to better address the psychosocial needs of cancer patients.

Fola et al. perform a nationwide genomic surveillance study of P. falciparum parasites across Zambia from samples collected in 2018 and report key genetic metrics informing transmission intensity, genetic relatedness, and selection. These genomic surveillance data highlight the need to strengthen malaria control and surveillance of drug resistance.

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.

Dr. Kamilla Kamaruddin is a general practitioner in Transgender Health Care and Clinical Lead at the East of England Gender Service, Cambridge, UK. She is also a board member for sexual health and wellbeing organisation Spectra-London, trustee at LGBTQ+ cancer charity Live Through This, and health advisor for trans community organisation TransActual UK. In this Q&A, we ask Dr. Kamaruddin a series of questions on the difficulties transgender people face in accessing quality healthcare, with a particular focus on the UK.