Mechanisms involved in Korean mistletoe lectin-induced apoptosis of cancer cells
Bibliographic record
Abstract
AIM: To investigate the anti-cancer mechanisms of Korean mistletoe lectin (Viscum album coloratum agglutinin, VCA) using a human colon cancer cell line (COLO). METHODS: Cytotoxic effects of VCA on COLO cells were determined by 3- (4, 5-dimethylthiazol-2-yl) -2, 5-diphenyltetrazolium bromide (MTT) assay in vitro and tumor-killing effects in vivo. To study the mechanisms involved, the expression of various pro-caspases, anti-apoptotic proteins, and death receptors was determined by western blot. To determine which death receptor is involved in VCA-induced apoptosis of COLO cells, cytotoxicity was examined by MTT assay after treatment with agonists or antagonists of death receptors. RESULTS: VCA killed COLO cells in a time- and dose-dependent manner and induced complete regression of tumors in nude mice transplanted with COLO cells. Treatment of COLO cells with VCA activated caspase-2, -3, -8, and -9 and decreased expression of anti-apoptotic molecules including receptor interacting protein, nuclear factor-kappaB, X-linked inhibitor of apoptosis protein, and Akt/protein kinase B. We then examined the involvement of death receptors in VCA-induced apoptosis. Only tumor necrosis factor receptor 1, among the death receptors examined, was involved in apoptosis of COLO cells, evidenced by inhibition of VCA-induced apoptosis and decreased activation of caspases, particularly caspase-8, by tumor necrosis factor receptor 1 antagonizing antibody. CONCLUSION: VCA-induced apoptotic COLO cell death is due to the activation of caspases and inhibition of anti-apoptotic proteins, in part through the tumor necrosis factor receptor 1 signaling pathway.
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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".