Effects of lysine and methionine on mRNA expression of candidate transcription factors by primary bovine mammary epithelial cells
Bibliographic record
Abstract
Abstract It has been established that essential amino acids (EAA) regulate protein synthesis in mammary epithelial cells by rapidly altering the phosphorylation state of translation factors. However, the long-term transcriptional response to EAA supply has been investigated much less. Eight transcription factors were selected as candidate mediators of EAA effects on mammary cell function via the amino acid response ( ATF4 , ATF6 ), mitogen-activated protein kinase ( JUN , FOS , EGR1 ), and mechanistic target of rapamycin complex 1 ( MYC , HIF1A , SREBF1 ). The objective was to determine if and when expression of these candidate genes was affected in primary cultures of bovine mammary epithelial cells more than 24 h after imposing an EAA deficiency, and to evaluate effects of EAA deficiency on protein synthesis, endoplasmic reticulum size, cell proliferation, and lipogenesis. Differentiated cells were cultured in 1 of 3 treatment media representing normal physiological concentrations of all amino acids (CTL), low lysine (LK), or low methionine (LM) for 24, 40, 48, or 60 h. Both LK and LM suppressed protein synthesis and activated ATF4 expression, indicating the classic amino acid response pathway had been triggered. However, there was no effect of LK or LM on endoplasmic reticulum size, possibly related to elevated ATF6 expression on LM. Expression of early response genes JUN , FOS , EGR1 and MYC was not elevated by EAA deficiency but LM decreased EGR1 expression. LM also increased expression of HIF1A . The EGR1 and HIF1A expression results are consistent with the decrease in cell proliferation rate observed. Variable responses in SREBF1 expression to LK and LM at different timepoints may have contributed to a lack of effect on lipogenesis rates. These findings indicate that EAA deficiency may inhibit mammary protein synthesis and cell proliferation through transcription factors.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".