AIMC Topic: Female

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Identification of ferroptosis- and mitochondrial metabolism-related biomarkers and the potential molecular mechanisms of poor ovarian response.

Journal of ovarian research
BACKGROUND: Ferroptosis and mitochondrial metabolism are closely associated with the pathological processes of various diseases. However, the role of ferroptosis-related genes (FRGs) and mitochondrial metabolism-related genes (MMRGs) in poor ovarian ...

Machine learning-based screening and validation of pyroptosis-associated prognostic genes and potential drugs in cervical cancer.

BMC medical genomics
Pyroptosis is a newly discovered form of programmed cell death, but its mechanism in the development of cervical cancer has not been elucidated. Cervical cancer differentially expressed pyroptosis-related genes were identified via bioinformatic analy...

Precision integrated identification of predictive first-trimester metabolomics signatures for early detection of gestational diabetes mellitus.

Cardiovascular diabetology
BACKGROUND AND AIM: Gestational diabetes mellitus (GDM), a common pregnancy-related metabolic disorder, often goes undiagnosed until the second trimester, limiting early intervention opportunities. Given the higher prevalence of GDM in India, there i...

Development of a consensus molecular classifier for pancreatic ductal adenocarcinoma.

Genome medicine
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) presents a significant challenge, with a 5-year survival rate of approximately 10%. Tumor heterogeneity contributes to the limited effectiveness of treatments. Several tumor and stroma molecular cla...

Precision medicine exploration of postpartum rectus abdominis muscle separation: from basic research to clinical practice.

BMC surgery
Postpartum diastasis recti abdominis (PDRA), characterized by pathological separation of the rectus abdominis muscles, affects 30%-60% of women, with many cases persisting beyond 6 months postpartum and having significant impacts on musculoskeletal f...

Prediction of uterine cavity conception environment using two-dimensional transvaginal ultrasound imaging semantic feature-based machine learning: a case-control study.

BMC pregnancy and childbirth
BACKGROUND: Independently investigating the association between pregnancy outcomes and the uterine cavity conception environment (UCCE) is challenging. Therefore, this study aimed to employ a range of machine learning algorithms to systematically ana...

Explainable machine learning for predicting clinical outcomes in HIV/TB co-infection: a comparative retrospective study.

BMC infectious diseases
BACKGROUND: HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identifying high-risk pat...

PTA-DFS study: design of a randomised controlled trial assessing the effects of early percutaneous transluminal angioplasty on the healing of diabetic foot ulcers in persons with type 2 diabetes.

BMC cardiovascular disorders
BACKGROUND: Peripheral arterial disease (PAD) and local infections increase the risk of non-healing diabetic foot ulcers (DFU) and limb amputations but are treatable by percutaneous transluminal angioplasty (PTA), local wound care and antibiotic ther...

Non-invasive identification of mesenchymal glioblastoma using quantitative radiomic features from advanced diffusion MRI: a preclinical-to-clinical transfer learning strategy.

European radiology experimental
BACKGROUND: Glioblastoma (GBM) is no longer regarded as a single disease, as distinct molecular subgroups exist, with the mesenchymal (MES) having the worst prognosis. As such, there is a critical need for noninvasive methods to determine GBM molecul...