Platelet Activating Factor (PAF): A Mediator of Inflammation
Bibliographic record
Abstract
Platelet-activating factor (PAF) is a phospholipid-derived mediator with an established role in multiple inflammatory states. PAF is synthesized and secreted by multiple cell types and is then rapidly hydrolyzed and degraded to an inactive metabolite, lyso-PAF, by the enzyme PAF acetylhydrolase. In addition to its role in platelet aggregation and activation, PAF contributes to allergic and nonallergic inflammatory diseases such as anaphylaxis, sepsis, cardiovascular disease, neurological disease, and malignancy as demonstrated in multiple animal models and, increasingly, in human disease states. Recent research has demonstrated the importance of the PAF pathway in multiple conditions including the prediction of severe pediatric anaphylaxis, effects on blood-brain barrier permeability, effects on reproduction, ocular diseases, and further understanding of its role in cardiovascular risk. Investigation of PAF as both a biomarker and a therapeutic target continues because of the need for directed management of inflammation. Collectively, studies have shown that therapies focused on the PAF pathway have the potential to provide targeted and effective treatments for multiple inflammatory conditions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".