Sepsis

From decay to discovery: A new antimicrobial peptide from Chrysomya megacephala (Diptera: Calliphoridae) larvae.

The larvae of Chrysomya megacephala (Diptera: Calliphoridae) thrive in environments rich in decaying organic matter and dead animals, which are often colonized by bacteria. This adaptation suggests the larvae possess antimicrobial substances that provide them with a defense against bacterial infection. The hemolymph from around 200 C. megacephala larvae previously exposed to methicillin-resistant ...

Deep Learning Algorithm-Guided Raman Spectroscopy for Real-Time Correlation of Critical Process Parameters and Titers in Lentiviral Vector.

Manufacturing scalability and cost efficiency of Lentiviral vector (LV) production for gene therapy are hampered by slow offline detection of critical parameters and viral titer. To enable real-time monitoring, this study proposes a process analytical technology (PAT) based on Raman spectroscopy and an innovative deep learning algorithm to achieve real-time prediction of glucose, lactate, viable c...

Recent advancements in artificial intelligence applications for the mitigation of antimicrobial resistance: challenges and opportunities.

Antimicrobial resistance (AMR) poses a significant global public health threat, and efforts to mitigate it have been aided by artificial intelligence ...

From bedside queries to complex care: AI for decision-making in infectious diseases.

BACKGROUND: Infectious Diseases require rapid decisions based on heterogeneous and evolving clinical data. At the same time, the shortage of infectiou...

An update on biofilms in acute and chronic wounds: Incidence, clinical evidence, diagnosis, prevention, and treatment.

Pathogenic biofilms are a critical barrier to wound healing, driving infection persistence, delayed tissue repair, and antimicrobial resistance (AMR) ...

Privacy-Preserving Framework for Multi-Institutional Medical Time-Series Analysis via Homomorphic Encryption: Design and Development Study.

BACKGROUND: The development of robust medical AI for knowledge discovery and decision support commonly necessitates large-scale datasets from multiple...

Automated CT Volumetry of Peripancreatic Collections for Risk Stratification in Acute Pancreatitis: A Multicenter Retrospective Study.

RATIONALE AND OBJECTIVES: Extrapancreatic necrosis volume is an established prognostic marker in acute necrotizing pancreatitis, yet early diagnosis r...

Reimagining antimicrobial resistance: AI-driven predictive epidemiology and the C-AMRE framework for next-generation antibiotic discovery.

Antimicrobial Resistance (AMR) has evolved from a clinically observed phenomenon into a complex, dynamic, and partially predictable evolutionary proce...

Modelling the impact of awareness campaigns on HPV transmission dynamics: a neural network-enhanced mathematical model.

HPV is the most common sexually transmitted infection; most sexually active individuals are exposed to HPV at some point in their lives, and the major...

Clinical Research on Microecological Landscape for Infection Risk Stratification in Newly Diagnosed Patients with Hematological Conditions.

INTRODUCTION: Infection is a common and potentially fatal complication during the treatment of hematological diseases, particularly in the context of ...

Identifying GADD45A as a potential R-loop regulator in sepsis via machine-learning and multi-omics analysis.

BACKGROUND: Sepsis is a life-threatening syndrome characterized by dysregulated immune responses, while the molecular basis of immune dysfunction rema...

C1R suppresses hepatocellular carcinoma cell aggressiveness through promoting HIF-1α degradation and modulating cuproptosis-related protein expression.

BACKGROUND: Hepatocellular carcinoma (HCC) frequently develops in the setting of chronic hepatitis B virus (HBV) infection, yet the molecular events s...

Practical applications of artificial intelligence in infectious disease surveillance and control: opportunities, challenges, and ethical considerations.

BACKGROUND: Artificial intelligence (AI) has been increasingly recognized as a public health tool with applications ranging from epidemiology, pandemi...

Interpretable Machine Learning Models for Mortality Prediction in Critically Ill Patients with Intra-Aortic Balloon Pump Therapy: Development and Evaluation.

BACKGROUND: This study aims to develop and validate predictive models to assess mortality risk among patients undergoing intra-aortic balloon pump (IA...

Admission photoplethysmography-based mortality prediction in hospitalized Ugandan children with suspected or confirmed infection: A feasibility study.

Sepsis remains a major cause of preventable pediatric hospital deaths in developing countries, with progress hindered by the lack of effective risk id...

An explainable machine learning model for predicting in-hospital infection in patients with systemic lupus erythematosus.

Infection is a leading cause of mortality in patients with systemic lupus erythematosus (SLE), yet effective tools for early identification of high-ri...

AI-driven Identification of Zika Virus Inhibitors.

Research engaged with AI has dramatically increased due to a huge improvement of technologies in terms of cost and time-effectiveness as well as decre...

Deep Learning Improves Robustness of Voxelwise Kinetic Modeling for Hyperpolarized Carbon-13 MRI.

PURPOSE: To evaluate whether deep learning improves the robustness of voxelwise kinetic parameter estimation from hyperpolarized (HP) 13C MRI compared...

Large Language Model-Based Clinical Decision Support for Antibiotic Selection and Dose Recommendation in Hospitalized Patients With Pneumonia: Multicenter Retrospective Study.

BACKGROUND: Pneumonia is a common infectious disease, and antibiotic treatment in hospitalized patients must balance efficacy, safety, and resistance ...

Exploration of Hepatitis B Virus Infection Dynamics through Physics-Informed Deep Learning Approach.

Accurate forecasting of viral disease outbreaks is crucial for guiding public health responses and preventing widespread loss of life. Recently, Physi...