Sepsis

Development and Clinical Evaluation of a Mpox Antigen-detecting Rapid Diagnostic Test.

To address the global emergence of mpox after the 2022 epidemic, a rapid and accurate diagnostic tool is needed at the point of care to identify individuals infected with mpox virus (MPXV) to prevent and control the spread of the virus. We designed an antigen-detecting rapid diagnostic test that exclusively detects MPXV without cross-reacting with the vaccinia virus by developing monoclonal antibo...

Revolutionizing biosensing with wearable microneedle patches: innovations and applications.

Wearable microneedle (MN) patches have emerged as a transformative platform for biosensing, offering a minimally invasive and user-friendly approach to real-time health monitoring and disease diagnosis. Primarily designed to access interstitial fluid (ISF) through shallow skin penetration, MNs enable precise and continuous sampling of biomarkers such as glucose, lactate, and electrolytes. Addition...

Tailored pharmacotherapy monitoring in Parkinson's disease and Schizophrenia using a rapid and sensitive α-Synuclein assay.

BACKGROUND: While Parkinson's disease is a low dopamine neurodegenerative disorder, Schizophrenia is considered a high dopamine psychiatric disorder. ...

Serum Vitamin D and the Risk of SARS-CoV-2 and Seasonal Influenza Infection During the Twindemic Period.

BACKGROUND & AIMS: The association between circulating vitamin D levels and the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) o...

Machine learning-based text mining for cutaneous myiasis and potential value of an accidental maggot therapy for complicated skin and soft tissue infection with sepsis.

BACKGROUND: Cutaneous myiasis, one of the most frequently diagnosed myiasis types, is defined as skin or soft tissue on a living host infested by dipt...

Functions and Mechanisms of Secreted Proteinaceous Effectors of Broad-Host-Range Necrotrophic Fungal Pathogens.

This review focuses on the intricate interaction mechanisms between necrotrophic fungal pathogens and their host plants, emphasizing the pivotal role ...

Identification of pyroptosis-related gene S100A12 as a potential diagnostic biomarker for sepsis through bioinformatics analysis and machine learning.

Sepsis is a non-discriminatory inflammatory reaction that can result in a diverse array of organ dysfunctions, which can be fatal. Pyroptosis is a pro...

ADT²R: Adaptive Decision Transformer for Dynamic Treatment Regimes in Sepsis.

Dynamic treatment regimes (DTRs), which comprise a series of decisions taken to select adequate treatments, have attracted considerable attention in t...

The application of machine learning in clinical microbiology and infectious diseases.

With the development of artificial intelligence(AI) in computer science and statistics, it has been further applied to the medical field. These applic...

GBE1 alleviates MPTP-induced PD symptoms in mice by enhancing glycolysis and oxidative phosphorylation.

In Parkinson's disease (PD), the disturbance of energy metabolism due to glucose metabolic reprogramming may be a critical factor contributing to neur...

The future of HIV diagnostics: an exemplar in infectious diseases.

Over the past 40 years, diagnostics have become the backbone of HIV prevention, treatment, and retention in care, and are central to the achievement o...

Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study.

BACKGROUND: Persistent sepsis-associated acute kidney injury (SA-AKI) shows poor clinical outcomes and remains a therapeutic challenge for clinicians....

Deep learning for fetal inflammatory response diagnosis in the umbilical cord.

INTRODUCTION: Inflammation of the umbilical cord can be seen as a result of ascending intrauterine infection or other inflammatory stimuli. Acute feta...

Integrating bioinformatics and machine learning to discover sumoylation associated signatures in sepsis.

Small Ubiquitin-like MOdifier-mediated modification (SUMOylation) is associated with sepsis; however, its molecular mechanism remains unclear. Herein,...

Integrating AI for infectious disease prediction: A hybrid ANN-XGBoost model for leishmaniasis in Pakistan.

Addressing leishmaniasis infection remains a substantial challenge in KP-Pakistan due to the increased infection prevalence. Understanding its spreadi...

Interpretable machine learning model for predicting delirium in patients with sepsis: a study based on the MIMIC data.

OBJECTIVE: The aim of this study was to construct interpretable machine learning models to predict the risk of developing delirium in patients with se...

Host Biomarkers and Antibiotic Tissue Penetration in Sepsis: Insights from Moxifloxacin.

BACKGROUND AND OBJECTIVE: Sepsis-induced pathophysiological changes may lead to pharmacokinetic variability which alters antibiotic concentrations at ...

Association between the (neutrophil + monocyte)/albumin ratio and all-cause mortality in sepsis patients: a retrospective cohort study and predictive model establishment according to machine learning.

INTRODUCTION: Sepsis is a life-threatening condition characterized by widespread inflammatory response syndrome in the body resulting from infection. ...

A comparative study on TB incidence and HIVTB coinfection using machine learning models on WHO global TB dataset.

Tuberculosis, a deadly and contagious disease caused by Mycobacterium tuberculosis, remains a significant global public health threat. HIV co-infectio...

A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication associated with a high mortality rate in patients with sepsis. Early i...