Pondering neutrophil extracellular traps with healthy skepticism
Bibliographic record
Abstract
The authors engage in a dialogue that evaluates critically the state of the study of neutrophil extracellular traps (NETs), a phenomenon currently the object of considerable interest, with the goal of identifying those aspects that merit clarification in order to assign the process its proper place in our current understanding of cell biology. Since the seminal observations in the Zychlinsky laboratory that described the extrusion of filaments of nuclear DNA associated with histones and granule proteins from neutrophils stimulated in vitro, many investigators have examined the phenomenon of NET formation in numerous and diverse settings. However, an overview of work in this rapidly growing field prompts several fundamental questions about NETs, including their precise composition, the mechanisms by which they arise, their clinical relevance, and the interrelationship of those observed in vitro and in vivo. In this discussion, the authors challenge interpretation of data from some experimental settings and provide recommendations for specific studies that would address the concerns raised, improve understanding of the biological relevance of NETs, and strengthen the field.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.016 |
| 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".