Distinct Intracellular Signaling in Tumor Necrosis Factor-related Apoptosis-inducing Ligand- and CD95 Ligand-mediated Apoptosis
Bibliographic record
Abstract
Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a potent inducer of apoptosis in tumor cells but not in healthy cells. Similar to CD95 ligand (CD95L), TRAIL signaling requires ligand-receptor interaction; the downstream signaling molecules, such as Fas-associated death domain and caspase-8, also seem similar. Using cells stably expressing TRAIL and CD95L, we show that both TRAIL and CD95L induce apoptosis in the rat colon carcinoma cell line CC531. The mitochondrial damage (loss of mitochondrial membrane potential (MMP) and release of cytochrome c) observed after co-incubation with TRAIL-expressing cells occurs much earlier than that observed with CD95L-expressing cells. The decrease in MMP induced by both ligands was caspase-8-mediated; no difference in caspase-8 activation by TRAIL and CD95L was found. TRAIL, but not CD95L, induced activation of caspase-10. bcl-2 overexpression could not prevent TRAIL-induced mitochondrial dysfunction, whereas it completely prevented CD95L-mediated loss of MMP and cytochrome c release. The selective effect of TRAIL on tumor cells and the apparent inability of bcl-2 to block TRAIL-induced apoptosis suggest that TRAIL may offer a lead for cancer therapy in the future.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".