RANTES Activates Jak2 and Jak3 to Regulate Engagement of Multiple Signaling Pathways in T Cells
Bibliographic record
Abstract
The chemokine RANTES (regulated on activation normal T cell expressed and secreted) and its cognate receptor CC chemokine receptor 5 (CCR5) have been implicated in regulating immune cell function. Previously we reported that in T cells, RANTES activation of CCR5 results in Stat1 and Stat3 phosphorylation-activation, leading to Stat1:1 and Stat1:3 dimers that exhibit DNA binding activity and the transcriptional induction of a Stat-inducible gene, c-fos. Given that RANTES and CCR5 have been implicated in T cell activation, we have studied RANTES-induced signaling events in a CCR5-expressing T cell line, PM1. RANTES treatment of PM1 T cells results in the rapid phosphorylation-activation of CCR5, Jak2, and Jak3. RANTES-inducible Jak phosphorylation is insensitive to pertussis toxin inhibition, indicating that RANTES-CCR5-mediated tyrosine phosphorylation events are not coupled directly to Galpha(i) protein-mediated events. In addition to Jaks, several other proteins are rapidly phosphorylated on tyrosine residues in a RANTES-dependent manner, including the Src kinase p56(lck), which associates with Jak3. Additionally our data confirm that the amino-terminally modified RANTES proteins, aminooxypentane-RANTES and Met-RANTES, are agonists for CCR5 and induce early tyrosine phosphorylation events that are indistinguishable from those inducible by RANTES with similar kinetics. Our data also demonstrate that RANTES activates the p38 mitogen-activated protein (MAP) kinase pathway. This is evidenced by the rapid RANTES-dependent phosphorylation and activation of p38 MAP kinase as well as the activation of the downstream effector of p38, MAP kinase-activated protein (MAPKAP) kinase-2. Pharmacological inhibition of RANTES-dependent p38 MAP kinase activation blocks MAPKAP kinase-2 activity. Thus, activation of Jak kinases and p38 MAP kinase by RANTES regulates the engagement of multiple signaling pathways.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".