Sepsis

Evaluation of a machine learning system for genomic antimicrobial susceptibility determination on a clinically representative test set.

UNLABELLED: Next-generation sequencing is anticipated to transform infectious disease treatment by enabling faster diagnosis, yet a clinical-grade method for genomic AST determination is still lacking. We assessed the accuracy of Keynome gAST, a k-mer based machine learning system for genomic AST, on 956 clinical bacterial isolates. We compared 7,801 predictions of susceptible (S), intermediate (I...

HCAR1 antagonist screening based on boundary-selected negative sampling strategy and multi-level graph neural network.

BACKGROUND AND OBJECTIVE: Hydroxycarboxylic acid receptor 1 (HCAR1), also known as the lactate receptor, is closely associated with tumorigenesis and cancer progression due to its aberrant activation, making it an attractive therapeutic target for cancer treatment. Accurate prediction of HCAR1 antagonists is therefore crucial for tumor immunotherapy. However, traditional drug screening suffers fro...

Insights into red sea bream iridovirus pathogenesis: Unveiling host-pathogen interactions using membrane yeast two-hybrid and molecular dynamics.

Red sea bream iridovirus (RSIV), a member of the genus Megalocytivirus, poses a substantial threat to global aquaculture through its infection of mari...

Tegmental kappa-opioid receptor neurons modulate opioid withdrawal via the periaqueductal gray.

Opioid withdrawal is a common and distressing manifestation of opioid dependence which, if left untreated, frequently results in relapse, accidental o...

The escalating threat of multidrug-resistant organisms: COVID-19 impact, global burden, and the Taiwanese experience.

INTRODUCTION: The COVID-19 pandemic has intensified global health challenges, including a silent but escalating crisis: multidrug-resistant organisms ...

Infection-targeted innovations in anastomotic leak management: endoscopic advances, antimicrobial biomaterials, and precision strategies.

Anastomotic leakage (AL) is a devastating complication of gastrointestinal surgery and a critical source of hospital-acquired infections. This review ...

Flavor molecules regulate appetite through the gut-brain Axis: An emerging perspective.

Bioactive flavor molecules (e.g., eugenol, cinnamaldehyde, capsaicin) regulate appetite and energy metabolism via the gut-brain axis, yet their multi-...

Leveraging a large language model to support expansion of surveillance activities to include cardiovascular implantable device infections in a large, integrated national healthcare system.

BACKGROUND: Surveillance activities are emerging as exemplar use cases for large language models (LLMs) in health care. The aim of this study was to e...

Confidence-based prediction of antibiotic resistance at the patient level.

Rapid and accurate diagnostics of bacterial infections are necessary for efficient treatment of antibiotic-resistant pathogens. Cultivation-based meth...

Prediction of renal cell carcinoma: Development and validation of machine learning model.

Renal cell carcinoma (RCC) is the leading cause of urinary system morbidity and mortality. Early identification is crucial for improving RCC patient o...

Engineered Supramolecular Therapeutics in Development for Combating Antibiotic-Resistant Bacterial Infections.

The emergence of antibiotic-resistant bacteria has rendered conventional antibiotic treatments ineffective, necessitating the development of antibacte...

Identification of Chlamydia pneumoniae and NLRP3 inflammasome activation in Alzheimer's disease retina.

Chlamydia pneumoniae is an intracellular bacterium implicated in Alzheimer's disease (AD), but its role in retinal pathology and disease progression i...

A machine learning-based prediction model for poor prognosis in sepsis using lymphocyte count: a national, multicenter prospective cohort.

Sepsis-induced immunosuppression leads to poor prognosis. Circulating lymphocyte count (LC), as an easily accessible clinical marker, closely reflects...

Assessing in-hospital mortality risk in ICU lung cancer patients using machine learning: An analysis based on the MIMIC-IV database.

BACKGROUND: Patients with advanced lung cancer admitted to the intensive care unit (ICU) face a substantially elevated risk of in-hospital mortality. ...

Integrative analysis identifies lactylation-related biomarkers in sepsis via bioinformatics and machine learning.

BACKGROUND: Protein lactylation is a novel post-translational modification driven by lactate and has emerged as a critical link between cellular metab...

The Contribution of the Locus Ceruleus-Norepinephrine System to the Coupling between Pupil-Linked Arousal and Cortical State.

Understanding how pupil-linked arousal couples with cortical state is crucial for uncovering the neural mechanisms underlying brain state-dependent co...

Machine Learning Model Predicts Recurrent Clostridioides difficile Infection in Patients With Inflammatory Bowel Disease (Recur CDI-IBD).

INTRODUCTION: Clostridioides difficile infection (CDI) present a significant challenge in patients with inflammatory bowel disease (IBD), with high re...

A Smartphone-Read, Machine Learning-Enhanced Lanthanide Hydrogel Sensor for Multimodal and On-Site Detection of Kanamycin in Food Safety.

Residual kanamycin from veterinary use poses a persistent threat to environmental safety and public health, as its accumulation in water systems and a...

Vancomycin resistance in gram-positive infections: evolutionary strategies of survival.

Vancomycin is a critical glycopeptide antibiotic for treating severe infections caused by Gram-positive bacteria, particularly MRSA and Clostridioides...

Machine learning-driven prediction model for successful weaning of patients from mechanical ventilation in ICU.

BACKGROUND: Mechanical ventilation is a critical life support technology in the intensive care unit. However, the weaning process remains complex, mak...