Effet radiosensibilisateur de l'acide linoléique conjugué chez les cellules cancéreuses du sein MCF-7 et MDA-MB-231
Bibliographic record
Abstract
Apoptotic pathways in breast cancer cells are frequently altered, reducing the efficiency of radiotherapy. Conjugated linoleic acid (CLA), known to trigger apoptosis, was tested as radiosensitizer in breast cancer cells MCF-7 and MDA-MB-231. The CLA-mix, made up of the isomers CLA-9cis 11trans and CLA-10trans 12cis, was compared to three purified isomers, i.e., the CLA-9cis 11cis, CLA-9cis 11trans, and CLA-10trans 12cis. Using the apoptotic marker YO-PRO-1, the CLA-9cis 11cis at 50 micro mol/L turned out to be the best apoptotic inducer leading to a 10-fold increase in MCF-7 cells and a 2,5-fold increase in MDA-MB-231 cells, comparatively to the CLA-mix. Contrary to previous studies on colorectal and prostate cancer cells, CLA-10trans 12cis does not lead to an apoptotic response on breast cancer cell lines MCF-7 and MDA-MB-231. Our results also suggest that the main components of the CLA-mix (CLA-9cis 11trans and CLA-10trans 12cis) are not involved in the induction of apoptosis in the breast cancer cells studied. A dose of 5 Gy did not induce apoptosis in MCF-7 and MDA-MB-231 cells. The addition of CLA-9cis 11cis or CLA-mix has allowed us to observe a radiation-induced apoptosis, with the CLA-9cis 11cis being about 8-fold better than the CLA-mix. CLA-9cis 11cis turned out to be the best radiosensitizer, although the isomers CLA-9cis 11trans and CLA-10trans 12cis have also reduced the cell survival following irradiation, but using a mechanism not related to apoptosis. In conclusion, the radiosensitizing property of CLA-9cis 11cis supports its potential as an agent to improve radiotherapy against breast carcinoma.
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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".