Sesamol Induces Apoptosis by Altering Expression of Bcl-2 and Bax Proteins and Modifies Skin Tumor Development in Balb/c Mice
Bibliographic record
Abstract
BACKGROUND: Chemoprevention using natural agents has emerged as a new and promising strategy for reducing cancer burden. Sesamol, a water soluble lignin, is a potent antioxidant with potential anticancer activities. Its small size (molecular weight: 138.34g) coupled with easy permeability (log P: 1.29) results in its excessive systemic loss therefore, compromising local bioavailability. Furthermore, irritant nature of sesamol limits its application on skin per se. OBJECTIVE: Present study aims to evaluate chemopreventive efficacy of free and encapsulated (SLNs) sesamol, at gross and molecular level, in DMBA induced skin cancer animal model. METHODS: Evaluation is done in terms of tumor burden quantification, histological evaluation of skin, determination of oxidative stress, and quantification of apoptotic proteins, bcl-2 and bax, using both western blot analysis and immunofluorescence studies. RESULTS: Sesamol administration (both in free and encapsulated form) significantly decreased the tumor burden and lipid peroxidation level and increased anti-oxidant levels, thereby hampering the development and promotion of skin tumors. Further, downregulation of bcl-2 and stimulation of bax protein expression on treatment with both free and encapsulated sesamol was responsible for the induction of apoptosis in tumor cells. Encapsulating sesamol into SLNs not only reduced its irritant nature which limits its direct topical application but also improved its local targeting to skin. CONCLUSION: Both free and encapsulated sesamol demonstrated the inhibition of tumor progression by inducing skin cell apoptosis via bcl-2/bax mediated 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".