Bioterrorism

Resting-state fMRI-based machine learning for predicting SSRI treatment response in major depressive disorder.

BACKGROUND: Major Depressive Disorder (MDD) is a prevalent mental health condition with significant societal impact. Although prior research has highlighted the brain changes modulated by antidepressant therapy, their efficacy and effectiveness are debated. The low rates of treatment response still existed in the pharmacological therapy of MDD. Exploring an optimal neurological predictor of sympto...

Seven Pillars for a Community-Led AI-POCUS Future - A WINFOCUS Manifesto.

The rapid integration of Artificial Intelligence (AI) into Point-of-Care Ultrasound (POCUS) represents a transformative shift, offering the potential to democratize diagnostic expertise while simultaneously presenting significant risks regarding clinical validation, workforce preparedness, and health equity. Informed by a recent global survey indicating that while 81% of practitioners are optimist...

Engineering Organoid Platforms for Pathogenesis Research.

Emerging and re-emerging infectious diseases ranging from the 1918 H1N1 influenza pandemic to the recent SARS-CoV-2 and monkeypox virus outbreaks cont...

Systems biology integration of miR-mRNA profiles identifies steroid refractoriness mechanisms and biomarker candidates in ulcerative colitis.

Approximately 60% of patients with ulcerative colitis (UC) show steroid resistance or dependence, underscoring the need for biomarkers predicting ther...

Peripheral blood profiles reflecting progenitor lineage balance are associated with molecular response in chronic myeloid leukemia.

Early achievement of deep remission improves patients' outcome in chronic myeloid leukemia (CML) treatment, highlighting the need for predictive indic...

Impact of neoadjuvant chemotherapy on breast tissue density and its correlation with pathologic response: a retrospective artificial intelligence-enhanced radiological study.

OBJECTIVES: This study evaluates the impact of neoadjuvant chemotherapy (NAT) on breast tissue density and examines the correlation between density ch...

Machine Learning Predicts Treatment Response and Prognostic Pathways From Whole-Blood Transcriptome in Primary Biliary Cholangitis.

BACKGROUND AND AIMS: Prognostic biomarkers that link disease progression and/or responses to therapeutic interventions in patients with primary biliar...

Risk Stratification for Postpartum Hemorrhage in Vaginal Delivery: A Nationwide Cohort Study of Predelivery and Intrapartum Risk Assessment.

AIM: To develop and validate machine learning models for clinically applicable risk stratification of postpartum hemorrhage (PPH) in vaginal delivery,...

Educators' Perspectives on Generative AI Use in Nursing Education: Friend or Foe?

AIM: This study explores nursing educators' perspectives on the challenges and benefits of integrating generative artificial intelligence (AI) into nu...

Psychoneuroimmunology-informed strategies for early detection of biological threat exposure: Insights from experimental rodent models.

The growing frequency of emerging infectious diseases, antimicrobial resistance, and accidental or deliberate biological threat releases underscores t...

Impact of image reconstruction algorithms on histogram analysis of iodine concentration for assessing chemotherapy response in pancreatic ductal adenocarcinoma.

PURPOSE: To evaluate the impact of image reconstruction algorithms on histogram analysis of iodine concentration (IC) derived from dual-energy CT (DEC...

Assessing the proinflammatory potential of sterile fecal microbiome filtrate from ulcerative colitis patients using an intestine-on-chip platform and automated image analysis.

BACKGROUND AND AIMS: Ulcerative colitis (UC) is characterized by disruptions of the gut microbiome and an exaggerated mucosal immune response in genet...

Forecasting and Capacity Planning in Prehospital Emergency Medical Services: The Case of Ankara.

OBJECTIVE: Time savings in prehospital emergency medical services are vital for human life. Ensuring that these services can meet potential demands is...

ViralMap: predicting features in viral proteins from primary sequence.

Modern viral vaccines are designed to elicit an immune response against viral proteins that mediate infection, making those proteins important targets...

The Role of Pharmacists in Tackling Mpox: Challenges and Future Prospects: A Narrative Review.

BACKGROUND AND AIMS: Pharmacists play a key role in managing and mitigating mpox through clinical care, pharmacovigilance, vaccine management, and res...

Sex differences in microvascular patterns associated with low- and high-risk for cardiovascular disease.

BACKGROUND: The role of the microcirculation in cardiovascular health in males and females is not fully understood. Skin microvascular function can be...

Why bother with controlled-environment phenotyping when field phenomics is already up and running?

Plant phenomics has undergone rapid development over the past two decades, driven by advances in imaging, robotics, artificial intelligence and data a...

Development and validation of a machine learning-based hierarchical classification model for predicting the early therapeutic response to initial 131I therapy in papillary thyroid carcinoma.

OBJECTIVE: Personalized tools for accurately predicting papillary thyroid carcinoma (PTC) patients' response to initial 131I therapy are lacking. This...

Interpretable dynamic quantitative vascular morphometry features using SHAP for anti-angiogenic therapy response prediction.

Anti-angiogenic therapy benefits vary, with response rates of 40 to 70%, highlighting the need for early biomarkers to identify responders. We develop...

Initial-Visit Specialty Triage in Rare Diseases Using Large Language Models: Retrospective Benchmarking Study.

BACKGROUND: Specialty triage at first contact is an overlooked step in early diagnostic pathways for rare diseases. Patients often present with overla...