Sepsis

Applying prior knowledge of regulatory signaling to investigate macrophage cAMP dynamics during Mycobacterium tuberculosis infection.

Mycobacterium tuberculosis (Mtb), the causative agent of Tuberculosis, resides in host lung macrophages and has evolved unique processes to hijack host signaling pathways to facilitate its survival and propagation within macrophages. Notably, Mtb exports cyclic AMP (cAMP), a key regulatory signaling molecule, during infection. As can often be the case, experimental data exploring immune modulation...

A machine learning-driven multitask framework for antibiotic resistance prediction in Escherichia coli, Klebsiella pneumoniae, and Enterobacter cloacae bloodstream infections among hematological malignancy patients.

BACKGROUND: Inappropriate empirical antimicrobial therapy (IEAT) significantly increases mortality in patients with resistant Gram-negative bacteremia. We developed a multitask machine learning framework to predict carbapenem resistance (CR), β-lactam/β-lactamase inhibitor combinations resistance (BL/BLI-R), and third-/fourth-generation cephalosporins resistance (3GC/4GC-R) in HM patients with mon...

A 2004-2025 Bibliometric Study of Genetic Variation and Multiomics Biomarkers in Sepsis Based on 940 Publications.

Sepsis is a highly heterogeneous syndrome, and conventional clinical indicators and single biomarkers often fail to capture its biological complexity ...

Bioinformatics analysis reveals the association of bile acid metabolism-related genes with sepsis.

BACKGROUND: Sepsis, is a life-threatening syndrome triggered by infection. Bile acid metabolism may be involved in the pathogenesis of sepsis, the und...

Brain network correlates of fatigue, depression, and anxiety in patients with Crohn's Disease in different disease states.

BACKGROUND: Symptoms of fatigue, depression or anxiety are frequent in Crohn's Disease (CD) and may relate to disturbed brain-gut interactions. While ...

Identification of key genes associated with T cell exhaustion in HIV infection based on transcriptomic data.

BACKGROUND: Human immunodeficiency virus (HIV) is a lentivirus belonging to the retrovirus subclass. HIV specifically targets and infects human CD4 + ...

Pepholin, a bacteriophage holin-derived antimicrobial peptide with membrane-disruptive activity and therapeutic efficacy in MDR Pseudomonas aeruginosa burn wounds.

The emergence of multidrug-resistant (MDR) Pseudomonas aeruginosa poses a serious threat to burn wound healing, necessitating the development of alter...

Antibiotic residue detection based on SERS technology: enhancement mechanisms, material innovations, and challenges in on-site applications.

In the face of the serious threat of antibiotic residues in food to human health, it is urgent to develop efficient and sensitive detection techniques...

Correction: Enterocutaneous Fistula-Associated Sepsis and Mortality: Development and Validation of a Multimodal Artificial Intelligence Prediction Model.

[This corrects the article DOI: 10.2196/79985.].

Infection prevention and control measures for Ebola and Marburg disease: a series of rapid reviews.

OBJECTIVES: An evidence synthesis informed the 2023 WHO infection prevention and control (IPC) guideline for Ebola disease (EBOD) and Marburg disease ...

A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD.

BACKGROUND: Blood gas parameters are associated with sepsis prognosis. This study aimed to develop an assessment model based on blood gas parameters f...

Development and validation of a novel multimodal deep neural network model based on CBC digit parameters and scattergrams for rapid hematolymphoid malignancy classification: a multicenter cohort study.

BACKGROUND: Rapid screening of hematolymphoid malignancies (HMs) by complete blood cell count (CBC) is crucial for choosing the next appropriate worku...

Reporting follow-up budgets for diagnostic and predictive AI.

OBJECTIVE: To argue that diagnostic and predictive AI should be evaluated by both classification performance and the downstream work their outputs cre...

Prediction of the toxicity of complex antibiotic mixtures with hormetic effects by an interpretable machine learning model.

Hormesis, a phenomenon frequently found in some low-dose chemical mixtures and their individual components in the environment, remains a formidable ch...

Mining the code of life for new antibiotics.

Antimicrobial resistance (AMR) is outpacing antibiotic development, creating an urgent need for discovery strategies that are faster, broader, and mor...

The hidden infectious disease-related sepsis risk of wildfire-specific PM2.5.

Wildfire smoke is a major source of fine particulate matter (PM2.5) and may increase vulnerability to severe infectious outcomes such as sepsis, a con...

Explainable machine learning for the early differentiation of pediatric bronchopneumonia using routine laboratory parameters.

OBJECTIVE: Early differentiation of pediatric acute respiratory infections in outpatient and emergency settings is often hindered by nonspecific clini...

Bioactive Peptides for Oral Diseases: Biomaterial-Assisted Therapeutics and Translational Applications.

Dental caries, periodontitis, oral mucosal inflammation, peri-implant infections, and oral tissue defects remain major clinical burdens. Conventional ...

scVAEAT: An Integrative Attention-Augmented Variational Autoencoder for Predicting Single-Cell Perturbation Responses.

Understanding how individual cells respond to genetic or environmental perturbations is crucial for deciphering disease mechanisms and advancing preci...

Seamless human electronics interfacing through advanced skin attachable and implantable sensor technologies.

The transition from episodic clinical assessment to continuous physiological monitoring represents a transformative shift in biomedical engineering. T...