Sepsis

Explainable MRI radiomics of the basal ganglia and ventral midbrain distinguishes Parkinson's disease, SWEDD, and healthy controls.

Distinguishing scans without evidence of dopaminergic deficit (SWEDD) from Parkinson's disease (PD) remains challenging on routine MRI. We extracted 1,285 radiomic features from T1- and T2-weighted MRI within six a priori subcortical regions of interest in the PPMI cohort. A nested cross-validation framework (inner: univariate ANOVA or Kruskal-Wallis with BH-FDR correction, mRMR, and LASSO; outer:...

Clinically Confirmed Cohort Reveals Antioxidant Genetic Polymorphisms as Potential Susceptibility Factors for Long COVID After Mild or Asymptomatic COVID-19.

Although the COVID-19 pandemic has now been down-graded, long COVID (LC) presents an ongoing risk of long-term disease for a significant percentage of the population, even after mild or no symptoms upon infection. LC post-viral effects have been associated with oxidative stress (OS), impacting canonical cell function. The aim of this study was to investigate the association of eight OS-related sin...

Advanced neuroimaging for central nervous system infections: when, where, how, and why?

PURPOSE OF REVIEW: Central nervous system (CNS) infections remain a major cause of morbidity and mortality worldwide, particularly in children, older ...

Machine learning predicts sepsis deterioration trajectories.

Sepsis has heterogeneous clinical trajectories, but conventional severity scores offer only static risk estimates. Timely, dynamic prediction could en...

Impact of region-based shape alterations in MRI as indicators of Parkinson's Disease.

BACKGROUND: Parkinson's Disease (PD) is a neuro-degenerative condition that progressively impairs movement, resulting from the loss of dopamine-produc...

Personalized prediction of initial valproic acid dose in children with epilepsy using machine learning techniques.

INTRODUCTION: Valproic acid (VPA) is widely prescribed antiepileptic drug in children because of its broad-spectrum efficacy. However, marked inter-in...

Metagenomic analysis of the gut microbiota in Cryptosporidium-infected Tibetan sheep.

Cryptosporidium are important causative parasitic protozoa that cause gastrointestinal discomfort and diarrhea in humans and animals, posing a huge th...

Improving severity grading of chemotherapy-induced myelosuppression in AML via data-driven and model-based deep learning.

Chemotherapy-induced myelosuppression in acute myeloid leukemia (AML) frequently leads to life-threatening complications, yet current assessment stand...

Integrated analysis of the gut mycobiota and plasma metabolome reveals mortality and age-specific characteristics in sepsis.

Antimicrobial discovery from underexplored environments: unlocking specialized metabolism.

The discovery of antibiotics transformed modern medicine and extended the average human lifespan by decades. However, the initial golden era of antibi...

Nanogels for the targeted delivery of antibiotic and antimicrobial drugs.

Nanoparticle-based drug delivery systems represent a promising platform for advancing biomedical therapies. Among them, nanogels - three‑dimensional, ...

The Impact of Evaluation Strategy on Sepsis Prediction Model Performance Metrics in Intensive Care Data: Retrospective Cohort Study.

BACKGROUND: The prediction of the onset of sepsis, a life-threatening condition resulting from a dysregulated response to an infection, is one of the ...

Differential Factors Associated With the Presence of Persistent Symptoms in Individuals Diagnosed With Long COVID: Protocol for a Longitudinal Matched Case-Control Study.

BACKGROUND: Long COVID (postacute sequelae of SARS-CoV-2 infection) is a heterogeneous condition with persistent multisystem symptoms and substantial ...

Integration of Systemic Immune-Inflammation Index and Lactate for diagnostic and early risk stratification in pediatric sepsis.

The role of digital tools and artificial intelligence in supporting antimicrobial stewardship: Study protocol for a systematic review.

INTRODUCTION: Since the post-antibiotic era, there has been significant difficulty in treating infectious diseases due to the increase in antimicrobia...

Linguistic, Orthographic, and Typographical Errors in Science (LOTS): A Growing Threat to Academic Integrity.

Biomedical engineers produce knowledge and artifacts. Across the life cycle of an idea, errors can creep in. In this letter, we propose the term lingu...

Identification and experimental validation of biomarkers associated with integrated stress response in sepsis.

BACKGROUND: Strategies that specifically target the integrated stress response (ISR) as a therapeutic approach in sepsis remain largely unexplored. Th...

Explainable Artificial Intelligence for Predicting Length of Stay and Treatment Response in Pediatric Asthma and Allergic Rhinitis: An Irregular Fuzzy Cellular Automata Approach Across Pre- and During-COVID-19 Periods.

OBJECTIVE: The COVID-19 pandemic significantly altered treatment strategies and healthcare utilization patterns in pediatric respiratory diseases. Giv...

Early-Stage Quality - Late-Stage Confidence: Neural Induction Quality Control as a Key to Reproducible MEA-based Neurotoxicity Assays.

Human induced pluripotent stem cell (hiPSC)-derived neural models combined with microelectrode array (MEA)-based readouts are increasingly used in nex...

TCB-Kla: a hybrid deep learning model for predicting human lysine lactylation sites by incorporating transformer encoder and multi-scale CNN.

Lysine lactylation as a newly discovered post-translational modification of proteins, plays a key role in various cellular processes. It can be stimul...