Regulation of platelet-activating factor-mediated protein tyrosine phosphatase 1B activation by a Janus kinase 2/calpain pathway
Bibliographic record
Abstract
Atherosclerosis is a pro-inflammatory condition underlying many cardiovascular diseases. Platelet-activating factor (PAF) and interleukin 6 (IL-6) are actively involved in the onset and progression of atherosclerotic plaques. The involvement of monocyte-derived macrophages is well characterized in the installation of inflammatory conditions in the plaque, but less is known about the contribution of monocyte-derived dendritic cells (Mo-DCs). In the same way, the involvement of calcium, phospholipase C and A2 in PAF-induced IL-6 production, in different cells types, has been shown; however, the importance of the Jak/STAT pathway and its regulation by protein-tyrosine phosphatases in this response have not been addressed. In this study, we report that PAF stimulates PTP1B activity via Jak2, thereby modulating PAF-induced IL-6 production. Using HEK 293 cells stably transfected with the PAF receptor in order to discriminate the pathway components, our results suggest that Jak2 modulates PAF-induced IL-6 production via both positive and negative pathways. Jak2 kinase activity was necessary for maximal transactivation of the IL-6 promoter, as seen by luciferase assays, whereas the same kinase also downregulated this promoter transactivation through the activation of a calcium/calpain/PTP1B pathway. The same pathways were operational in monocyte-derived dendritic cells, since PAF-induced PTP1B activation negatively regulated PAF-induced IL-6 mRNA production and, in addition, Jak2 activated calpain, one of the components involved in PAF-induced PTP1B activation. Results obtained in this study indicate that Jak2 activation is important for maximal IL-6 promoter transactivation by PAF and that PTP1B is involved in the negative regulation of this transactivation. However, PTP1B does not directly regulate Jak2 activation, but rather Jak2 regulates PAF-induced PTP1B activation.
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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 | 0.000 |
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".