Bibliographic record
Abstract
This review presents a summary of signalling events related to the activation of human polymorphonuclear neutrophils by a variety of soluble and particulate agonists. It is not intended as a comprehensive review of this vast field or as a presentation of the multiple new aspects of neutrophil functions that are being documented at an ever faster rate. Its aim is rather to focus on multiple aspects of major signalling pathways that, in the view of this reviewer, are currently shadowed by present trends and to provide the core evidence for their implication and the limitations of our present knowledge. More specifically, this review starts with cell surface receptors and some of their functional and biological properties and then moves on to downstream transducers (G proteins) and effectors (the phosphoinositide, tyrosine kinases, and cyclic nucleotide pathways). Classical second messengers (calcium, protein kinase C, polyphosphoinositides, and cyclic nucleotides) are emphasized. It is hoped that this presentation will not only remind present-day investigators of the central role these pathways play in the regulation of the functional responsiveness of neutrophils, but that it will also highlight some of the areas deserving additional investigation.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".