AIMC Topic: Extracellular Traps

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Identification of neutrophil extracellular trap-related biomarkers in non-alcoholic fatty liver disease through machine learning and single-cell analysis.

Scientific reports
Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increas...

Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning.

Inflammation
Neutrophil extracellular trap (NET) is released by neutrophils to trap invading pathogens and can lead to dysregulation of immune responses and disease pathogenesis. However, systematic evaluation of NET-related genes (NETRGs) for the diagnosis of pe...

Machine learning framework develops neutrophil extracellular traps model for clinical outcome and immunotherapy response in lung adenocarcinoma.

Apoptosis : an international journal on programmed cell death
Neutrophil extracellular traps (NETs) are novel inflammatory cell death in neutrophils. Emerging studies demonstrated NETs contributed to cancer progression and metastases in multiple ways. This study intends to provide a prognostic NETs signature an...

Development of a prognostic Neutrophil Extracellular Traps related lncRNA signature for soft tissue sarcoma using machine learning.

Frontiers in immunology
BACKGROUND: Soft tissue sarcoma (STS) is a highly heterogeneous musculoskeletal tumor with a significant impact on human health due to its high incidence and malignancy. Long non-coding RNA (lncRNA) and Neutrophil Extracellular Traps (NETs) have cruc...

Circulating Neutrophil Extracellular Traps Signature for Identifying Organ Involvement and Response to Glucocorticoid in Adult-Onset Still's Disease: A Machine Learning Study.

Frontiers in immunology
Adult-onset Still's disease (AOSD) is an autoinflammatory disease with multisystem involvement. Early identification of patients with severe complications and those refractory to glucocorticoid is crucial to improve therapeutic strategy in AOSD. Exag...

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis.

Journal of visualized experiments : JoVE
Glomerular cell death is a pathological feature of myeloperoxidase anti neutrophil cytoplasmic antibody associated vasculitis (MPO-AAV). Extracellular deoxyribonucleic acid (ecDNA) is released during different forms of cell death including apoptosis,...

Convolutional Neural Networks-Based Image Analysis for the Detection and Quantification of Neutrophil Extracellular Traps.

Cells
Over a decade ago, the formation of neutrophil extracellular traps (NETs) was described as a novel mechanism employed by neutrophils to tackle infections. Currently applied methods for NETs release quantification are often limited by the use of unspe...

Machine Learning to Quantitate Neutrophil NETosis.

Scientific reports
We introduce machine learning (ML) to perform classification and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate...

Azithromycin and Chloramphenicol Diminish Neutrophil Extracellular Traps (NETs) Release.

International journal of molecular sciences
Neutrophils are one of the first cells to arrive at the site of infection, where they apply several strategies to kill pathogens: degranulation, respiratory burst, phagocytosis, and release of neutrophil extracellular traps (NETs). Antibiotics have a...

The effect of Intravenous Immunoglobulin (IVIG) on \textit{ex vivo} activation of human leukocytes.

Human antibodies
INTRODUCTION: Intravenous immunoglobulin (IVIG) has been widely used to treat various conditions, including inflammatory and autoimmune diseases. IVIG has been shown to have a direct influence on neutrophils, eosinophils and lymphocytes. However, man...