Cx43 Promotes Endothelial Cell Migration and Angiogenesis via the Tyrosine Phosphatase SHP-2
Bibliographic record
Abstract
The gap junction protein connexin 43 (Cx43) is associated with increased cell migration and to related changes of the actin cytoskeleton, which is mediated via its C-terminal cytoplasmic tail and is independent of its channel function. Cx43 has been shown to possess an angiogenic potential, however, the role of Cx43 in endothelial cell migration has not yet been investigated. Here, we found that the knock-down of Cx43 by siRNA in human microvascular endothelial cells (HMEC) reduces migration, as assessed by a wound assay in vitro and impaired aortic vessel sprouting ex vivo. Immunoprecipitation of Cx43 revealed an interaction with the tyrosine phosphatase SHP-2, which enhanced its phosphatase activity, as observed in Cx43 expressing HeLa cells compared to cells treated with an empty vector. Interestingly, the expression of a dominant negative substrate trapping mutant SHP-2 (CS) in HMEC, via lentiviral transduction, also impaired endothelial migration to a similar extent as Cx43 siRNA compared to SHP-2 WT. Moreover, the reduction in endothelial migration upon Cx43 siRNA could not be rescued by the introduction of a constitutively active SHP-2 construct (EA). Our data demonstrate that Cx43 and SHP-2 mediate endothelial cell migration, revealing a novel interaction between Cx43 and SHP-2, which is essential for this process.
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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 | 0.000 |
| 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".