Evasion of Neutrophil Extracellular Traps by Respiratory Pathogens
Bibliographic record
Abstract
The release of neutrophil extracellular traps (NETs) is a major immune mechanism intended to capture pathogens. These histone- and protease-coated DNA structures are released by neutrophils in response to a variety of stimuli, including respiratory pathogens, and have been identified in the airways of patients with respiratory infection, cystic fibrosis, acute lung injury, primary graft dysfunction, and chronic obstructive pulmonary disease. NET production has been demonstrated in the lungs of mice infected with Staphylococcus aureus, Klebsiella pneumoniae, and Aspergillus fumigatus. Since the discovery of NETs over a decade ago, evidence that "NET evasion" might act as an immune protection strategy among respiratory pathogens, including group A Streptococcus, Bordetella pertussis, and Haemophilus influenzae, has been growing, with the majority of these studies being published in the past 2 years. Evasion strategies fall into three main categories: inhibition of NET release by down-regulating host inflammatory responses; degradation of NETs using pathogen-derived DNases; and resistance to the microbicidal components of NETs, which involves a variety of mechanisms, including encapsulation. Hence, the evasion of NETs appears to be a widespread strategy to allow pathogen proliferation and dissemination, and is currently a topic of intense research interest. This article outlines the evidence supporting the three main strategies of NET evasion-inhibition, degradation, and resistance-with particular reference to common respiratory pathogens.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".