Pregnancy

RNA-based cancer immunotherapy: Harnessing the power of RNA nanoparticles for melanoma treatment.

RNA-based cancer immunotherapy has emerged as a next-generation strategy in oncology, harnessing the versatile properties of RNA molecules to activate and modulate antitumor immunity. In melanoma, a highly immunogenic yet evasive malignancy, RNA therapeutics offer promising avenues for overcoming immune resistance, tumor heterogeneity, and treatment failure. Messenger RNA (mRNA) vaccines have led ...

Thrombosis at the crossroads of inflammation, coagulation, and vascular biology: Recent advances and emerging therapeutic strategies.

Thrombosis is a multifaceted pathological process involving intravascular clot formation that drives a range of cardiovascular and cerebrovascular diseases, including myocardial infarction, ischemic stroke, venous thromboembolism, and cancer-associated thrombosis. Despite major advances in anticoagulation and thrombolytic therapies, clinical outcomes remain limited by bleeding risk, incomplete clo...

Advanced intelligent drug-device combination systems: regulatory landscapes, technological foundations, and clinical translation.

Drug-device combinations (DDCs) have evolved from simple drug-coated implants into sophisticated intelligent platforms capable of real-time sensing, a...

Prostate Cancer Detection on Micro-Ultrasound Raw Data Using a Deep Learning Neural Network.

BACKGROUND: Micro-ultrasound (micro-US) is a clinically available novel high-resolution imaging technology for guiding prostate biopsies. However, cli...

Deep learning model for noninvasive prediction of Ki-67 expression and prognostic stratification in breast cancer: a multicenter retrospective study.

OBJECTIVE: Ki-67 correlates with prognosis for patients with breast cancer. However, the evaluation of Ki-67expression relies on pathological analysis...

The application of Artificial Intelligence in the ultrasound-based diagnosis of liver disease: current status, hurdles, and prospects.

Over the past decade, there has been marked progress in artificial intelligence (AI) and its application in medicine. In the field of hepatology, AI c...

Determinants and disparities in skilled birth attendants during childbirth in Bangladesh: A study of machine learning and decomposition analysis.

This study delves into the determinants and socioeconomic disparities influencing the utilization of Skilled Birth Attendants (SBAs) for childbirth in...

Prevalence and determinants of sacroiliac joint bone marrow oedema in the general population in Germany: a population-based cross-sectional study.

BACKGROUND: MRI-detected bone marrow oedema in sacroiliac joints is central to diagnosing axial spondyloarthritis, influencing treatment decisions inc...

Advances in neuropharmacology: Innovative drug strategies targeting synaptic plasticity, neuroinflammation, and ion channel regulation for future CNS treatments.

As our understanding of the molecular and cellular mechanisms underlying central nervous system (CNS) disorders expands, neuropharmacology is undergoi...

Real-time artificial intelligence-based needle tracking for ultrasound-guided regional anesthesia training: a pilot prospective randomized controlled trial.

BACKGROUND: Proper needle visualization is a major technical challenge for novices learning ultrasound-guided regional anesthesia (UGRA). We developed...

Development and validation of a risk prediction model for dysglycaemia at 6-12 weeks postpartum in Chinese women with gestational diabetes: a retrospective cohort study.

BACKGROUND: Compared with normoglycaemic pregnancies, gestational diabetes mellitus (GDM) confers a markedly elevated risk of dysglycaemia at 6-12 wee...

Deep Learning-Based Segmentation of Fetal Anatomical Structures in the First Trimester.

OBJECTIVES: To develop and evaluate an artificial intelligence (AI) system that automatically identifies and classifies the fetal structures in the fi...

The Pathophysiology of Spontaneous Preterm Birth: Emerging Mechanisms Reviewed by the Preterm Birth International Collaborative.

Around 10% of global births are preterm (before 37 weeks of gestation), posing a significant challenge to maternal and neonatal health. Preterm infant...

Applying Machine Learning to Fetal Echocardiograms: A Novel Method for Predicting Critical Coarctation of the Aorta.

BACKGROUND: Current fetal echocardiographic metrics are inadequate for confident prediction of neonatal critical coarctation of the aorta due to low s...

Prenatal behavioral contagion through maternal yawning and fetal resonance.

Yawning is a phylogenetically preserved and highly stereotyped behavior observed across vertebrates.1 In humans, it emerges early in development, as i...

Diuretic Ultrasound Evaluation of Surgical Necessity in Pediatric Ureteropelvic Junction Obstruction.

RATIONALE AND OBJECTIVES: This study aimed to develop an interpretable machine learning (ML) model using diuretic ultrasonography to predict the neces...

Focused Ultrasound in Brain Tumors: Mechanisms, Imaging Guidance, and Emerging Clinical Applications.

Focused ultrasound (FUS) is an emerging therapeutic and diagnostic technology in neuro-oncology, offering new strategies for molecular diagnosis, drug...

Feasibility and Acceptability of a Prevention-Focused Screener for Perinatal Depression Risk: Mixed Methods Cohort Study.

BACKGROUND: More than 20% of perinatal women experience depression, with suicide being a leading cause of maternal death in the United States. Profess...

Machine learning for the prediction of three-year survival in locally advanced breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound imaging.

Locally Advanced Breast Cancer (LABC) is a serious type of cancer with a poor prognosis despite advances in cancer treatment. As the disease is often ...

A hybrid deep-learning-architecture for identifying cotton content in fabric materials.

Recycling plays a crucial role in achieving sustainable production. In particular, automating sorting processes holds great promise for enhancing both...