Sepsis

Algorithmic dopamine economies: emerging psychiatric challenges in an artificial-intelligence-mediated attention ecology.

Acute deep neck infection MRI: deep learning segmentation and clinical relevance of retropharyngeal edema volume.

OBJECTIVE: Retropharyngeal edema (RPE) on MRI in patients with acute neck infection is associated wi...

Flexible Organic Clip as an Adapter to Enhance Host-Guest Nanopore Single-Molecule Sensing.

The host-guest nanopore analysis method provided an avenue for hydrophobic analytes detection. Howev...

A novel framework integrating a coupled mixing rule with deep learning for toxicity prediction and environmental risk assessment of antibiotic mixtures.

Co-exposure of multiple antibiotics in the environment is widespread, and accurate prediction of ant...

Development and validation of a machine learning-based nomogram model integrating LASSO regression and multiple evaluation methods for predicting early sepsis risk in acute abdomen.

BACKGROUND: Sepsis secondary to acute abdomen is a critical driver of clinical deterioration and mor...

From machine learning to causal insight: a robust 12-gene signature to distinguish sepsis risk from systemic inflammatory response syndrome.

BACKGROUND: Sepsis, a life-threatening condition driven by a dysregulated host response, poses signi...

Lactate metabolism-driven tumor heterogeneity and molecular signatures in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive liver malignancy with limit...

Emerging trends and converging evidence in tumor evolution: A comprehensive review.

BACKGROUND: Tumor evolution is a spatiotemporal dynamic process orchestrated by the interplay of gen...

Immunotherapy in Triple-Negative Breast Cancer: From Molecular Mechanisms to Precision Medicine-Overcoming Resistance and Optimizing Clinical Outcomes.

Triple-negative breast cancer (TNBC) is the most violent type of breast cancer, in which estrogen re...

Metabolic factor-based machine learning model for mortality prediction in acute hepatitis E: Development and validation from a dual-center cohort.

BACKGROUND: Hepatitis E virus (HEV) infection remains a major cause of liver failure with high short...

Antimicrobial resistance gene diversity, prevalence, and mobility within four landfills.

Antibiotics in landfills create selection pressures on the microorganisms present, selecting for ant...

Hierarchical Distribution of Reward Representation in the Cortical and Hippocampal Regions.

Dopaminergic inputs to various brain regions, such as the striatum, orbitofrontal cortex, and amygda...

Generation of machine-learning derived cancer vulnerability indicator to determine the spatial burden of cancer outcomes.

BACKGROUND: Due to the difficulty of obtaining population-based individual-level data, ecological st...

A Unified Machine Learning Model for Relapse Prediction in Clinical Stage I Testicular Cancer.

BACKGROUND: Approximately one-fourth of patients with clinical stage I testicular cancer relapse. Fo...

Post-treatment infection prediction in CLL using domain adaptation of lymphoma electronic health records.

BACKGROUND AND PURPOSE: Infections are the leading cause of morbidity and mortality in patients with...

Real-time holographic monitoring of insect cell morphology during baculovirus coinfection for adeno-associated virus vector production using machine learning-based classification models.

The baculovirus expression vector system (BEVS) is a scalable platform used to produce recombinant a...

Green in-situ photoreduction synthesis of SERS substrates based on violet phosphorus arrays/silver nanoparticles for ultrasensitive detection and accurate identification of UTI bacteria.

Surface-enhanced Raman spectroscopy (SERS) holds significant promise for identifying urinary tract i...

Cross-modal attention deep learning reveals how transformation products inherit life-cycle risks from parent antibiotics: Insights for environmental, ecological, health, and AMR risks.

The environmental, ecological, antimicrobial resistance (AMR), and human health risks of antibiotic ...

Predicting the active sites of quinolone antibiotics interacting with organisms by deep learning and molecular docking.

Quinolones (QNs) antibiotics have become one of the most commonly used antibacterial drugs for human...

Sepsis Diagnostics via Biosensors: Engineering Platforms, Artificial Intelligence Integration, and Clinical Translation.

Sepsis remains one of the most diagnostically challenging syndromes due to its clinical heterogeneit...

De novo design of GPCR exoframe modulators.

G-protein-coupled receptors (GPCRs) are important therapeutic targets and have been targeted mainly ...