Formation, Signaling and Occurrence of Specialized Pro-Resolving Lipid Mediators—What is the Evidence so far?
Bibliographic record
Abstract
Formation of specialized pro-resolving lipid mediators (SPMs) such as lipoxins or resolvins usually involves arachidonic acid 5-lipoxygenase (5-LO, ALOX5) and different types of arachidonic acid 12- and 15-lipoxygenating paralogues (15-LO1, ALOX15; 15-LO2, ALOX15B; 12-LO, ALOX12). Typically, SPMs are thought to be formed via consecutive steps of oxidation of polyenoic fatty acids such as arachidonic acid, eicosapentaenoic acid or docosahexaenoic acid. One hallmark of SPM formation is that reported levels of these lipid mediators are much lower than typical pro-inflammatory mediators including the monohydroxylated fatty acid derivatives (e.g., 5-HETE), leukotrienes or certain cyclooxygenase-derived prostaglandins. Thus, reliable detection and quantification of these metabolites is challenging. This paper is aimed at critically evaluating i) the proposed biosynthetic pathways of SPM formation, ii) the current knowledge on SPM receptors and their signaling cascades and iii) the analytical methods used to quantify these pro-resolving mediators in the context of their instability and their low concentrations. Based on current literature it can be concluded that i) there is at most, a low biosynthetic capacity for SPMs in human leukocytes. ii) The identity and the signaling of the proposed G-protein-coupled SPM receptors have not been supported by studies in knock-out mice and remain to be validated. iii) In humans, SPM levels were neither related to dietary supplementation with their ω-3 polyunsaturated fatty acid precursors nor were they formed during the resolution phase of an evoked inflammatory response. iv) The reported low SPM levels cannot be reliably quantified by means of the most commonly reported methodology. Overall, these questions regarding formation, signaling and occurrence of SPMs challenge their role as endogenous mediators of the resolution of inflammation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".