TRAIL-Induced Apoptosis in Human Vascular Endothelium Is Regulated by Phosphatidylinositol 3-Kinase/Akt through the Short Form of Cellular FLIP and Bcl-2
Bibliographic record
Abstract
BACKGROUND: Apoptosis of vascular endothelial cells plays a central role in angiogenesis and atherosclerosis. This study investigates the molecular mechanisms of endothelial apoptosis induced by tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) following inhibition of phosphatidylinositol 3-kinase (PI3K). It examines downstream regulation and activation of the extrinsic and intrinsic pathways. METHODS AND RESULTS: By flow cytometry, TRAIL receptors 2 and 3 were present to a greater extent than receptors 1 and 4. TRAIL reduced cell numbers in combination with the PI3K inhibitor LY 294002. TRAIL (100 ng/ml) with LY 294002 (20 micromol/l) activated the extrinsic pathway, causing progressive cleavage of caspase-8 and caspase-3. Activation of the intrinsic pathway proceeded by release of mitochondrial factors Smac/DIABLO and cytochrome c, and caspase-9 cleavage. LY 294002 reduced phosphorylated Akt (p-Akt), with early loss of the short form of cellular FLIP (c-FLIP(S)) and concurrent reduction of Bcl-2. Treatment with small interfering RNA against PI3K also reduced c-FLIP(S) and Bcl-2, and cotreatment with TRAIL triggered caspase-3 cleavage. CONCLUSIONS: This study details the molecular regulation of TRAIL-induced apoptosis in vascular endothelium. Inhibition of PI3K reduces p-Akt, with concurrent reductions in c-FLIP(S) and Bcl-2, and so renders endothelium sensitive to TRAIL-induced apoptosis through the extrinsic and intrinsic 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 | 0.000 |
| 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".