Sepsis

Machine learning prediction of functional cure to pegylated interferon-alpha therapy in two HBV populations: Advantaged populations and HBeAg-negative patients.

Despite advances in antiviral therapy, the rate of functional cure for chronic hepatitis B (CHB) remains unsatisfactory, and developing an applicable prediction model is pivotal to improving it. Thus, we aimed to identify key predictive factors and develop prognostic models for functional cure in HBeAg-negative patients and the advantaged populations. This retrospective study included 202 HBeAg-ne...

TFAP2A transcriptionally regulates B3GALT2 to affect gouty arthritis progression through pyroptosis: a study based on machine learning and multi-omics integration analysis.

BACKGROUND: Gouty arthritis (GA) is an inflammatory joint disease driven by monosodium urate (MSU) crystal deposition. The NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome-mediated pyroptosis is central to GA pathogenesis, yet potential regulatory targets remain limited. The role of β-1,3-galactosyltransferase 2 (B3GALT2), a glycosyltransferase, is entirely unknow...

Current perspectives in cardiogenic shock.

Cardiogenic shock (CS) remains a leading cause of death in intensive cardiac care. Outcomes are limited by delayed recognition of hypoperfusion, heter...

Development of a rapid metal oxide semiconductor-based sensory system for noninvasive neonatal sepsis detection.

Systemic immune-inflammation (SII) index as a novel prognostic biomarker in critically ill patients with sepsis: analysis of the MIMIC-IV cohort and predictive modeling based on machine learning.

Application of machine learning for the diagnosis and prognosis of sepsis-induced acute respiratory distress syndrome: a systematic review and meta-analysis.

AMP-CapsNet: a multi-view feature fusion approach for antimicrobial peptide prediction using capsule networks.

Antimicrobial peptides (AMPs) are universally found in both intracellular and extracellular settings and have significant antibiotic-resistant bacteri...

Machine learning model predicts prognosis in SARS-CoV-2-infected autoimmune encephalitis patients.

OBJECTIVE: To assess the neurological prognosis of patients with autoimmune encephalitis (AE) after severe acute respiratory syndrome coronavirus 2 (S...

Multiple neural networks from cognition to motivation of prosocial behaviour in rodents: Potential mechanism between empathy and autism spectrum disorder.

Prosocial behaviour, as a facet of social behaviour across species, entails voluntary actions that benefit others, including helping and comforting be...

A machine learning model for predicting 28-day mortality in patients with alcoholic cirrhosis and sepsis: a study based on the MIMIC-IV database.

OBJECTIVE: To develop and validate the best machine learning model for predicting 28-day mortality in septic patients with alcoholic cirrhosis (AC), l...

Auditory and Vestibular Recovery in Otosclerosis Surgery: Clinical Efficacy and Predictive Modeling of Intraoperative Corticosteroid Use.

OBJECTIVE: To evaluate the effect of intraoperative local corticosteroid application on hearing, tinnitus, and dizziness outcomes after stapes surgery...

Microvascular phenotypes in pediatric sepsis identified by machine learning: prognostic implications for organ dysfunction and mortality.

Factors influencing long-term outcomes in lung transplantation: effective monitoring and comprehensive intervention.

PURPOSE OF REVIEW: Achieving long-term survival after lung transplantation remains a major challenge. Outcome determinants have expanded beyond pathop...

Synergistic impact of Gram-negative bacterial co-infection on invasive pulmonary aspergillosis in non-neutropenic patients: a machine learning-based risk stratification approach.

BACKGROUND: Invasive pulmonary aspergillosis (IPA) is increasingly recognized in non-neutropenic patients, where coexisting bacterial infections, part...

Revitalizing actinobacteria research: an urgent response to the antimicrobial resistance crisis.

The crisis of antimicrobial resistance (AMR) is escalating while the antibiotic pipeline remains stagnant. Our bibliometric analysis of eight decades ...

Next-generation advanced surface plasmon resonance biosensor for dopamine detection with ZnO-ag multilayer design: Machine learning optimization for high sensitivity.

The individual's physiological system needs to function effectively for a person to maintain life in good health. Deficiency of vitamins and minerals ...

Iatrogenic plasticizer Di(2-ethylhexyl) phthalate (DEHP) exposure increases Sepsis mortality risk: Machine learning implicates monocyte-driven immune dysregulation.

Sepsis poses a significant global health burden, and ICU patients are disproportionately exposed to di(2-ethylhexyl) phthalate (DEHP), an immunotoxic ...

Advances in multi-omics for esophageal squamous cell carcinoma: Diagnostic, prognostic, and therapeutic perspectives.

Esophageal squamous cell carcinoma (ESCC) remains a major health burden, particularly in Asia, with poor patient prognosis despite advancements in rad...

Explainable machine learning model for predicting short-term outcomes in sepsis- induced coagulopathy.

BACKGROUND: Sepsis-Induced coagulopathy (SIC) is not only a common complication in the development process of sepsis but also related to poor prognosi...

Association of lactate-to-albumin ratio with 28-day mortality in elderly sepsis patients: a retrospective MIMIC-IV database analysis.

BACKGROUND: The lactate-to-albumin ratio (LAR) is correlated with mortality in critically ill patients; however, its predictive value for sepsis in th...