Orchestration of Neutrophil Extracellular Traps (Nets), a Unique Innate Immune Function during Chronic Obstructive Pulmonary Disease (COPD) Development
Bibliographic record
Abstract
Morbidity, mortality and economic burden caused by chronic obstructive pulmonary disease (COPD) is a significant global concern. Surprisingly, COPD is already the third leading cause of death worldwide, something that WHO had not predicted to occur until 2030. It is characterized by persistent respiratory symptoms and airway limitation due to airway and/or alveolar abnormalities usually caused by significant exposure to noxious particles of gases. Neutrophil is one of the key infiltrated innate immune cells in the lung during the pathogenesis of COPD. Neutrophils during pathogenic attack or injury decide to undergo for a suicidal death by releasing decondensed chromatin entangled with antimicrobial peptides to trap and ensnare pathogens. Casting neutrophil extracellular traps (NETs) has been widely demonstrated to be an effective mechanism against invading microorganisms thus controlling overwhelming infections. However, aberrant and massive NETs formation has been reported in several pulmonary diseases, including chronic obstructive pulmonary disease. Moreover, NETs can directly induce epithelial and endothelial cell death resulting in impairing pulmonary function and accelerating the progression of the disease. Therefore, understanding the regulatory mechanism of NET formation is the need of the hour in order to use NETs for beneficial purpose and controlling their involvement in disease exacerbation. For example, DNA neutralization of NET proteins using protease inhibitors and disintegration with recombinant human DNase would be helpful in controlling excess NETs. Targeting CXC chemokine receptor 2 (CXCR2) would also reduce neutrophilic inflammation, mucus production and neutrophil-proteinase mediated tissue destruction in lung. In this review, we discuss the interplay of NETs in the development and pathophysiology of COPD and how these NETs associated therapies could be leveraged to disrupt NETopathic inflammation as observed in COPD, for better management of the disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".