Endothelial TMEM16F lipid scramblase regulates angiogenesis
Bibliographic record
Abstract
Abstract Dynamic loss of lipid asymmetry through the activation of TMEM16 Ca 2+ -activated lipid scramblases (CaPLSases) has been increasingly recognized as an essential membrane event in a wide range of physiological and pathological processes, including blood coagulation, microparticle release, bone development, pain sensation, cell-cell fusion, and viral infection. Despite the recent implications of TMEM16F CaPLSase in vascular development and endothelial cell-mediated coagulation, its signaling role in endothelial biology remains to be established. Here, we show that endothelial TMEM16F regulates in vitro and in vivo angiogenesis through intracellular signaling. Developmental retinal angiogenesis is significantly impaired in TMEM16F deficient mice, as evidenced by fewer vascular loops and larger loop areas. Consistent with our in vivo observation, TMEM16F siRNA knockdown in human umbilical vein endothelial cells compromises angiogenesis in vitro . We further discovered that TMEM16F knockdown enhances VE-cadherin phosphorylation and reduces its expression. Moreover, TMEM16F knockdown also promotes Src kinase phosphorylation at tyrosine 416, which may be responsible for downregulating VE-cadherin expression. Our study thus uncovers a new biological function of TMEM16F in angiogenesis and provides a potential mechanism for how the CaPLSase regulates angiogenesis through intracellular signaling.
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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) | 0.002 | 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".