Bibliographic record
Abstract
Neutrophils are critical inflammatory cells that cause tissue damage in a range of diseases and disorders. Being bone marrow-derived white blood cells, they migrate from the bloodstream to sites of tissue inflammation in response to chemotactic signals and induce inflammation by undergoing receptor-mediated respiratory burst and degranulation. Degranulation from neutrophils has been implicated as a major causative factor in pulmonary disorders, including severe asphyxic episodes of asthma. However, the mechanisms that control neutrophil degranulation are not well understood. Recent observations indicate that granule release from neutrophils depends on activation of intracellular signalling pathways, including beta-arrestins, the Rho guanosine triphosphatase Rac2, soluble NSF attachment protein (SNAP) receptors, the src family of tyrosine kinases, and the tyrosine phosphatase MEG2. Some of these observations suggest that degranulation from neutrophils is selective and depends on nonredundant signalling pathways. This review focuses on new findings from the literature on the mechanisms that control the release of granule-derived mediators from neutrophils.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".