Bioterrorism

Real-Time Gas Identification at Room Temperature Using UV-Modulated Sb-Doped SnO Sensors via Machine Learning.

This study presents a novel approach for real-time gas identification at room temperature. We use UV-modulated Sb-doped SnO sensors combined with machine learning. Our method exclusively employs the gas response () as the sole metric. This eliminates the need for time-dependent parameters such as response and recovery times. By modulating the UV light intensity at five distinct levels (5, 10, 15, ...

Deep molecular profiling of synovial biopsies in the STRAP trial identifies signatures predictive of treatment response to biologic therapies in rheumatoid arthritis.

Approximately 40% of patients with rheumatoid arthritis do not respond to individual biologic therapies, while biomarkers predictive of treatment response are lacking. Here we analyse RNA-sequencing (RNA-Seq) of pre-treatment synovial tissue from the biopsy-based, precision-medicine STRAP trial (n = 208), to identify gene response signatures to the randomised therapies: etanercept (TNF-inhibitor),...

Management and prediction of river flood utilizing optimization approach of artificial intelligence evolutionary algorithms.

Flooding is a devastating natural disaster that causes fatalities and property damage worldwide. Effective flood susceptibility mapping (FSM) has beco...

Treatment Response Evaluation in Prostate Cancer Using PSMA PET/CT.

In recent years, there has been a headlong rush into the use of prostate-specific membrane antigen (PSMA)-targeted PET for the staging and restaging o...

Predicting cisplatin response in cholangiocarcinoma patients using chromosome pattern and related gene expression.

Cholangiocarcinoma (CCA) is a prevalent bile duct cancer with limited treatment options. Cisplatin-based chemotherapy is a common approach, but respon...

Machine learning model for predicting tertiary lymphoid structures and treatment response in triple-negative breast cancer.

This study developed a machine learning model for predicting the presence of tertiary lymphoid structures (TLSs) and treatment response to neoadjuvant...

Mapping global risk of bat and rodent borne disease outbreaks to anticipate emerging threats.

Future epidemics and/or pandemics may likely arise from zoonotic viruses with bat- and rodent-borne pathogens being among the prime candidates. To imp...

The impact of an AI-focused ethics education program on nursing students' ethical awareness, moral sensitivity, attitudes, and generative AI adoption intention: a quasi-experimental study.

BACKGROUND: The integration of Generative artificial intelligence (GAI) into healthcare is rapidly evolving, necessitating ethical preparedness among ...

Insights into the relationship between anxiety and attitudes toward artificial intelligence among nursing students.

BACKGROUND: Artificial Intelligence (AI) integration in healthcare education represents a critical technological advancement that requires careful exa...

Enhancing out-of-hospital cardiac arrest survival in China through the 5-minute social rescue circle implementation.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) survival in China remains critically low due to limited bystander cardiopulmonary resuscitation (CPR...

Metabolic Phenotypes, Genotypes, and Gut Microbiome Signatures in Obesity: Implications for Precision Nutrition Strategies in Type 2 Diabetes Prevention.

The worldwide prevalence of overweight and obesity has increased rapidly in the last decades. This rise has led to a surge in comorbidities such as ty...

Radiomic Model Associated with Tumor Microenvironment Predicts Immunotherapy Response and Prognosis in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma.

No robust biomarkers have been identified to predict the efficacy of programmed cell death protein 1 (PD-1) inhibitors in patients with locoregionall...

Physiological Response of Tissue-Engineered Vascular Grafts to Vasoactive Agents in an Ovine Model.

Tissue-engineered vascular grafts (TEVGs) are emerging as promising alternatives to synthetic grafts, particularly in pediatric cardiovascular surgery...

Emergency radiology: roadmap for radiology departments.

Emergency radiology has evolved into a significant subspecialty over the past 2 decades, facing unique challenges including escalating imaging volumes...

Droplet microfluidics integrated with machine learning reveals how adipose-derived stem cells modulate endocrine response and tumor heterogeneity in ER breast cancer.

Approximately 70% of breast cancer (BC) diagnoses are estrogen receptor positive (ER) with ∼40% of ER BC patients presenting resistance to endocrine ...

HAPIR: a refined Hallmark gene set-based machine learning approach for predicting immunotherapy response in cancer patients.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet the response rate remains limited, with only about 30% of solid tumor pa...

Melioidosis molecular diagnostics: An update.

Melioidosis, a fatal tropical disease, presents a wide array of clinical manifestations, including abscesses, pneumonia, septic shock, bacteraemia, os...

Stereotactic Body Radiation Therapy for Primary Renal Cancer and Genetic Markers of Response: A Phase 2 Trial.

Controlled outcome assessment of radiotherapy for primary renal cell carcinoma (RCC) remains limited, particularly regarding its impact on ipsilateral...

Geospatial analysis of short sleep duration and cognitive disability in US adults: a multi-state study using machine learning techniques.

BACKGROUND: There is evidence of increased risk of cognitive disability due to short sleep duration and adverse Social Determinants of Health (SDoH). ...

Multiscale-fusion models with genomic, topological and pathomic features to predict response to radiation therapy for non-small cell lung cancer patients.

Artificial intelligence models with biomarkers to predict treatment responses to radiation would be necessary to maximise the treatment outcomes of in...