Contrasting effects of transforming growth factor β1 on programmed cell death of bovine mammary epithelial cell lines MAC-T and BME-UV1
Bibliographic record
Abstract
A previous study in the bovine mammary epithelial cell line BME-UV1 demonstrated that suppression of the phosphatidylinositol-4,5-biphosphate 3 kinase (PI3K)/AKT (somatotropic) signaling pathway was required for transforming growth factor β1 (TGFβ1)-induced programmed cell death (PCD). To investigate whether this is a universal mechanism for TGFβ1 to induce PCD in bovine mammary epithelium, we compared TGFβ1 modulation of PI3K/AKT and its role in PCD in 2 bovine mammary epithelial cell lines: MAC-T and BME-UV1. In MAC-T cells, TGFβ1 promoted cell survival, and this paralleled a reduction in PI3K/AKT activity, rather than an increase. In BME-UV1 cells, TGFβ1 induced PCD, and this was accompanied by a time-dependent effect on PI3K/AKT activity, including an initial significant increase in the phosphorylation of AKT at 3 h, followed by a reduction between 12 and 24 h, and then an increase at 48 h. Inhibition of AKT activity enhanced TGFβ1-induced PCD in BME-UV1 cells but had no effect on MAC-T cells, suggesting that TGFβ1 mediates PCD in BME-UV1 cells through suppression of AKT activity. Inhibition of TGFβ receptor type I (TβRI) kinase activity completely abrogated TGFβ1-induced PCD in BME-UV1 cells but had no effect on TGFβ1-induced suppression of PCD in MAC-T cells, demonstrating that TGFβ1-induced PCD in BME-UV1 cells is dependent on TβRI/SMAD signaling. These and previous observations suggest that the different effects of TGFβ1 on PCD in these cell lines might involve noncanonical signaling pathways other than PI3K/AKT, and may reflect their different lineages. Future studies should address this finding, taking into consideration the effect that different culture conditions might have on cell phenotype.
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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 | 0.001 |
| 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".