DAPT Enhances the Apoptosis of Human Tongue Carcinoma Cells
Bibliographic record
Abstract
AIM: To investigate the effect of DAPT (gamma-secretase inhibitor) on the growth of human tongue carcinoma cells and to determine the molecular mechanism to enable the potential application of DAPT to the treatment of tongue carcinoma. METHODOLOGY: Human tongue carcinoma Tca8113 cells were cultured with DAPT. Cell growth was determined using Indigotic Reduction method. The cell cycle and apoptosis were analyzed by flow cytometry. Real-time PCR and Immuno-Fluorescence (IF) were employed to determine the intracellular expression levels. RESULTS: DAPT inhibited the growth of human tongue carcinoma Tca8113 cells by inducing G0-G1 cell cycle arrest and apoptosis. The mRNA levels of Hairy/Enhancer of Split-1 (Hes-1), a target of Notch activation, were reduced by DAPT in a dose-dependent manner. Coincident with this observation, DAPT induced a dose-dependent promotion of constitutive Caspase-3 in Tca8113 cells. CONCLUSION: DAPT may have a therapeutic value for human tongue carcinoma. Moreover, the effects of DAPT in tumor inhibition may arise partly via the modulation of Notch-1 and Caspase-3.
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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 | 0.000 |
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".