The JAK‐STAT pathway regulation of endothelial cell migration and differentiation
Bibliographic record
Abstract
Cell migration and differentiation are both fundamental processes in angiogenesis. We investigated the role of the Janus kinase (JAK)‐signal transducer and activator of transcription (STAT) pathway in endothelial migration and differentiation. Matrigel tube formation assays were used to examine endothelial differentiation following stimulation with vascular endothelial growth factor (VEGF) or sphingosine 1‐phosphate (S1P), a lipid activator of angiogenesis. VEGF receptor 2 inhibitors blocked tube formation induction by both S1P and VEGF, supporting a transactivation mechanism. These inhibitors also blocked JAK activation, demonstrating the involvement of S1P‐induced transactivation of the VEGF receptor 2. A JAK inhibitor blocked differentiation induced by either ligand, implicating the JAK‐STAT pathway in regulation of the process. STAT5 inhibition significantly inhibited differentiation. Signalling pathways involve the ERK cascade, Src and NF‐κB were also found to play important roles differentiation. The migration of endothelial cells was studied using a modified Boyden chamber assay and the inhibition of the JAK‐STAT pathway blocked migration. The STAT3 and STAT5 pathways were both found to play important roles in migration. Angiogenic processes induced by both VEGF and S1P require activation of multiple signalling pathways, including JAK‐STAT 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 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".