Bibliographic record
Abstract
Neutrophils are short-lived innate immune cells. These cells respond quickly to stimuli, and die within minutes to hours; the relevance of DNA transcription in dying neutrophils remains an enigma for several decades. Here we show that the transcriptional activity reflects the degree of DNA decondensation occurring in both NADPH oxidase 2 (Nox)-dependent and Nox-independent neutrophil extracellular trap (NET) formation or NETosis. Transcriptomics analyses show that transcription starts at multiple loci in all chromosomes earlier in the rapid Nox-independent NETosis (induced by calcium ionophore A23187) than Nox-dependent NETosis (induced by PMA). NETosis-specific kinase cascades differentially activate transcription of different sets of genes. Inhibitors of transcription, but not translation, suppress both types of NETosis. In particular, promoter melting step is important to drive NETosis (induced by PMA, E. coli LPS, A23187, Streptomyces conglobatus ionomycin). Extensive citrullination of histones in multiple loci occurs only during calcium-mediated NETosis, suggesting that citrullination of histone contributes to the rapid DNA decondensation seen in Nox-independent NETosis. Furthermore, blocking transcription suppresses both types of NETosis, without affecting the reactive oxygen species production that is necessary for antimicrobial functions. Therefore, we assign a new function for transcription in neutrophils: Transcriptional firing, regulated by NETosis-specific kinases, helps to drive NETosis.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".