Bioterrorism

Clinical and immunological significance of FOXO1 as a biomarker of improved response to immune checkpoint plus tyrosine kinase inhibitor therapy in metastatic renal cell carcinoma.

BACKGROUND: Predicting response to immune checkpoint inhibitor plus tyrosine kinase inhibitor (IO+TKI) therapy in metastatic renal cell carcinoma (mRCC) remains challenging. Forkhead box protein O1 (FOXO1) is a key transcription factor regulating tumor suppression and T cell immunity, but its clinical and immunological significance in RCC is unclear. METHODS: FOXO1 expression was analyzed in TCGA-...

Models Integrating Disease Heterogeneity and MPA Exposure Predict Systemic and Renal Efficacy of Mycophenolate in Pediatric Lupus Nephritis.

OBJECTIVES: This study aimed to develop and validate integrated prediction models for pediatric lupus nephritis (LN) treated with a mycophenolate mofetil (MMF)-based induction regimen (combined with glucocorticoids and hydroxychloroquine), incorporating both disease heterogeneity and pharmacokinetic variability. The primary model predicts the achievement of low disease activity (Systemic Lupus Ery...

Advanced Control of Continuous Pharmaceutical Manufacturing Processes: A Case Study on the Application of Artificial Neural Network for Predictive Control of a CDC Line.

The adoption of continuous pharmaceutical manufacturing has driven increased use of modeling, simulation, and advanced process control strategies. Art...

The Mediating Role of Artificial Intelligence Anxiety in The Effect of Nurses' Attitudes Toward Health Technologies on Their Readiness for Medical Artificial Intelligence.

AIM: This study aims to evaluate the mediating role of artificial intelligence (AI) anxiety in the effect of nurses' attitudes toward health technolog...

AI-assessed sarcopenia as an independent predictor of neoadjuvant chemotherapy outcomes in muscle-invasive bladder cancer.

PURPOSE: Sarcopenia has already been widely investigated as a potential indicator of negative outcomes in oncology patients. Our aim was to evaluate t...

[Machine learning and radiomics-based model for predicting response to lenvatinib combined with TACE in patients with unresectable hepatocellular carcinoma].

Objective: To evaluate the predictive value of machine learning combined with radiomics for treatment response to lenvatinib combined with transarteri...

What's new on the market? Combining internet traces and pretrained language models to recognize emerging drug names.

Posts and comments published by users in online forum discussions provide valuable insights and might contain the earliest traces of new substances em...

Machine learning and probabilistic approaches for forecasting infectious disease transmission and cases.

OBJECTIVES: Forecasting the effective reproductive number (Rt) and infection case counts is critical for guiding public health responses. We developed...

Impact of an Immersive AI Simulation on Nursing Student Attitudes Toward Mental Illness.

There is simultaneously a global shortage of mental health professionals and a rising demand for mental health services. Nurses provide the largest sh...

AI-guided multi-omics analysis identifies NPC1-modulated susceptibility to SARS-CoV-2 infection under PM2.5 exposure.

Exposure to airborne fine particulate matter (PM2.5) has been linked to increased risk of the severe acute respiratory syndrome coronavirus 2 (SARS-Co...

Development and validation of a highly accurate multigene gene expression biomarker to predict chemotherapy response in primary triple-negative breast cancer.

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive subtype lacking estrogen and progesterone receptors and HER2 amplification. Representin...

Optimising pandemic response through vaccination strategies using neural networks.

Epidemic risk assessment poses inherent challenges, with traditional approaches often failing to balance health outcomes and economic constraints. Thi...

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

A systems view on DNA damage response kinetics in Tetrahymena.

A tightly regulated DNA damage response is critical to the overall integrity of the genome. Here, we combine transcriptomics and proteomics to study D...

When seconds matter - introducing a surgical salvage strategy by emergency robotic surgery: a review.

Robotic surgery has expanded minimally invasive options but introduces specific vulnerabilities during intraoperative emergencies. The physical separa...

A programmable matrix-robust plasmonic MetaRing biosensor for rapid SERS-based chemotherapeutic response profiling.

Rapid assessment of chemotherapeutic response is essential for precision oncology but remains hindered by tumor heterogeneity and complex biological m...

Feasibility of short-term hospital mask demand forecasting using a backpropagation neural network under data scarcity.

Early-stage infectious disease outbreaks impose acute pressure on hospital supply systems, particularly for essential protective materials such as med...

Genomic evolution of SARS-CoV-2 delta variants pre- and post-omicron emergence using alignment-free machine learning models.

The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutatio...

Reimagining Recovery: How Extended Ambulatory Models and Patient Hotels are Changing the Outpatient Surgical Paradigm.

Ambulatory extended recovery facilities, designed for 1-night stays, provide an alternative care setting for more complex patients and procedures than...

A Scoping Review of Machine Learning Applications for Diagnosis, Classification, and Prognosis in Lupus Nephritis.

BACKGROUND: Over the past decade, machine learning (ML) has transformed histopathology, yet its application in lupus nephritis (LN) remains underexplo...