Comparison of Vitamin E Derivatives α-TEA and VES in Reduction of Mouse Mammary Tumor Burden and Metastasis
Bibliographic record
Abstract
A novel nonhydrolyzable ether derivative of RRR-alpha-tocopherol, RRR-alpha-tocopherol ether acetic acid analog [2,5,7,8-tetramethyl-2R-(4R,8R,12-trimethyltridecyl)chroman-6-yloxyacetic acid (alpha-TEA)], and a hydrolyzable ester derivative RRR-alpha-tocopheryl succinate (vitamin E succinate; VES) inhibited BALB/c mouse 66cl-4-GFP mammary tumor cell growth in vitro and in vivo. Treatment of 66cl-4-GFP cells in culture with alpha-TEA or VES induced dose-dependent DNA synthesis arrest and apoptosis and inhibited colony formation. Liposomal formulations of alpha-TEA delivered orally or by aerosol significantly reduced subcutaneous 66cl-4-GFP tumor burden and metastasis to lung and lymph nodes. Liposomal formulations of VES delivered by aerosol significantly reduced tumor burden and lung metastasis, but not lymph node metastasis. Unlike alpha-TEA, VES was ineffective in reducing tumor burden and metastasis to lungs and lymph nodes when administered orally. Analyses of tumor sections showed that alpha-TEA delivered by either method significantly reduced tumor cell proliferation as measured by Ki67, and increased apoptosis as measured by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick-end labeling (TUNEL), whereas VES delivered by aerosol reduced tumor cell proliferation and increased apoptosis, but not significantly. In summary, the nonhydrolyzable ether vitamin E derivative alpha-TEA was effective in reducing tumor burden and metastasis when delivered either by aerosol or orally, whereas the hydrolyzable ester vitamin E derivative VES was effective only when delivered by aerosol.
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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".