SHP-1–Pyk2–Src Protein Complex and p38 MAPK Pathways Independently Regulate IL-10 Production in Lipopolysaccharide-Stimulated Macrophages
Bibliographic record
Abstract
The role of tyrosine phosphatase Src homology region 2 domain-containing phosphatase (SHP)-1 in LPS-activated cytokine production and inflammation was investigated by determining TNF-α and IL-10 production in splenic macrophages employing SHP-1-null (me/me) mouse model. LPS-stimulated me/me splenic macrophages secreted significantly less IL-10 with concomitantly elevated levels of TNF-α compared with wild-type (WT) macrophages irrespective of LPS dose and duration of stimulation. IL-10 significantly inhibited LPS-induced TNF-α production in both me/me and WT macrophages. The critical requirement for SHP-1 in regulating LPS-induced IL-10 and TNF-α production was confirmed by interfering with SHP-1 expression in WT macrophages and by reconstituting me/me macrophages with the SHP-1 gene. To delineate the role of SHP-1 in positive regulation of LPS-induced IL-10 production, signaling proteins representing SHP-1 targets were examined. The results reveal that tyrosine kinases Src and proline-rich tyrosine kinase 2 (Pyk2) regulate SHP-1-dependent LPS-induced IL-10 production and infer that optimal LPS-induced IL-10 production requires an assembly of a protein complex consisting of SHP-1-Pyk2-Src proteins. Moreover, LPS-induced IL-10 production also requires activation of the p38 MAPK independent of SHP-1 function. Overall, to our knowledge our results show for the first time that SHP-1 acts as a positive regulator of LPS-induced IL-10 production in splenic macrophages through two distinct and independent SHP-1-Pyk2-Src and p38 MAPK pathways.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".