Selenomethionine increases proliferation and reduces apoptosis in bovine mammary epithelial cells under oxidative stress
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The decline in mammary epithelial cell number as lactation progresses may be due, in part, to oxidative stress. Selenium is an integral component of several antioxidant enzymes. The present study was conducted to examine the effect of oxidative stress and selenomethionine (SeMet) on morphology, viability, apoptosis, and proliferation of bovine mammary epithelial cells (BMEC) in primary culture. Cells were isolated from mammary glands of lactating dairy cows and grown for 3 d in a low-serum gel system containing lactogenic hormones and 0 or 100 μM H2O2 with 0, 10, 20, or 50 nM SeMet. Hydrogen peroxide stress increased intracellular H2O2 to 3 times control concentrations and induced a loss of cuboidal morphology, cell-cell contact, and viability of BMEC by 25%. Apoptotic cell number more than doubled during oxidative stress, but proliferating cell number was not affected. Supplementation with SeMet increased glutathione peroxidase activity 2-fold and restored intracellular H2O2 to control levels with a concomitant return of morphology and viability to normal. Apoptotic BMEC number was decreased 76% below control levels by SeMet and proliferating cell number was increased 4.2-fold. These findings suggest that SeMet modulated apoptosis and proliferation independently of a selenoprotein-mediated reduction of H2O2. In conclusion, SeMet supplementation protects BMEC from H2O2-induced apoptosis and increased proliferation and cell viability under conditions of oxidative stress.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it