Evasion of Neutrophil Extracellular Traps by Respiratory Pathogens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it