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Jing, Su et al. analyze global trends in congenital heart disease and non-congenital cardiovascular diseases (NC-CVD) among individuals under 20 years from 1992-2021 using GBD 2021 data. They find declining mortality but rising NC-CVD incidence and prevalence, with persistent disparities across socio-demographic index levels.

Elgendi and Markov et al. systematically review 26 studies on wearable devices that use physiological signals such as heart activity, breathing, skin responses, and blood flow to detect anxiety. They find that combining multiple signals improves accuracy over single-signal methods, highlighting the potential of wearables for anxiety detection.

Sobkowiak et al., present a comprehensive genomic epidemiology of SARS-CoV-2 in Peru from 2020 to 2024, highlighting the emergence and spread of key variants including Lambda and Gamma P.1.12. The work provides valuable insights into regional viral transmission dynamics in a high-burden, middle-income setting, emphasizing the importance of sustained genomic surveillance.

Akodad et al. map nearly four decades of FDA approvals to identify how authorised medicines acquire new therapeutic uses. The study shows that repurposing follows consistent regulatory and industrial patterns, highlighting its growing role in pharmaceutical innovation.

Kimura, Tanaka et al. perform exome and RNA sequencing in Japanese melanoma patients to investigate genomic and transcriptomic factors associated with clinical efficacy of immune checkpoint inhibitors. Findings reveal the characteristic genomic features and potential biomarkers of melanoma in Japanese patients.

Gubela et al. calibrate an adaptive agent-based model with intra-host dynamics to investigate the 2022 Mpox outbreak dynamics in Berlin. Behavioral change and infection-induced immunity are the main reasons for outbreak decline, while the effect of vaccination is marginal.

Werwath, Lawn et al. conduct a large trans-ancestry genome-wide association study (GWAS) of hot flashes among post-menopausal women age 35-88. The findings reveal a locus on chromosome 4 and multiple genes linked to hot flashes, suggesting potential mechanisms and treatment targets.

Buttar et al. explore a contactless method for screening five respiratory diseases using 6G Integrated Sensing And Communication Orthogonal Frequency Division Multiplexing (ISAC OFDM) signals from software-defined radios. Using deep learning, the approach enables accurate, real-time screening for Asthma, Chronic Obstructive Pulmonary Disease, Interstitial Lung Disease, Pneumonia and Tuberculosis.

Yaw et al. assess the association between cumulative radiation exposure from CT imaging during trauma hospitalization and subsequent risk of developing malignant neoplasms and cancer-related mortality. Related radiation exposure is associated with a dose-dependent increase in the risk of subsequent cancer incidence and mortality.

Lösel, Relle et al. present a biomechanical approach and visualisation tool for incisional hernia repair using two CT scans, one at rest and one during a Valsalva manoeuvre, to assess abdominal wall instability and guide surgical planning. In 31 patients treated with this method, all remained pain-free and had no hernia recurrence after three years.

Kopal et al. analyze MRI data from a Parkinson’s Disease cohort to assess how LRRK2 gene variants shape brain structure. They find that LRRK2-associated Parkinson’s Disease shows a milder and anatomically distinct pattern of neurodegeneration compared to non LRRK2-associated Parkinson’s Disease.

Shi, Yu et al. examine the associations of abdominal obesity and plasma fatty acids with microvascular diseases risk in the UK Biobank cohort. Authors find that n-3 polyunsaturated fatty acids are associated with a lower risk, whereas saturated- and monounsaturated- fatty acids are associated with an increased risk.

Chua et al., discuss how artificial intelligence is transforming breast cancer care by improving detection, diagnosis, prognosis, treatment planning, and patient recovery through advanced machine learning and deep learning applications. They emphasise that widespread adoption faces challenges such as data diversity, reproducibility, regulatory hurdles, infrastructure limitations, and ethical concerns around transparency and bias.

Jayavelu, Samaha et al., apply machine learning models on hospital admission data, including antibody titers and viral load, to identify patients at high risk for Long COVID. Low antibody levels, high viral loads, chronic diseases, and female sex are key predictors, supporting early, targeted interventions.

Valero-Muñoz, Saw et al. apply a translational model in which adult cardiac myocytes are exposed to serum from people with HIV before and after initiation of ART. The authors identify distinct molecular signatures, indicating that HIV infection and antiretroviral therapy engage separate biological pathways that may precede diastolic dysfunction and the development of HFpEF.

Sánchez-Valle et al. analyze gene expression data from over 100 diseases to explore differences in comorbidity occurrence between sexes. They find that men and women share distinct molecular mechanisms driving disease co-occurrence and distinct drug associations with comorbidities.

Anneberg et al. investigate associations between data-driven maternal dietary patterns during pregnancy and offspring’s risk of inflammatory bowel disease (IBD). Based on 56,097 mother-child pairs followed over 18 years, they show that a diverse dietary pattern may protect offspring against IBD development compared to a Western dietary pattern.

Kim, D’Anniballe et al. examined olfactory tissue from individuals with Long COVID-related anosmia and conducted a randomised pilot trial of topical steroid therapy. They found no persistent viral presence, identified clonally expanded inflammatory T cells, and confirmed the therapy’s safety, supporting the need for larger trials.