PSXII-20 AMPK senses energy substrate availability to regulate glucose metabolism in bovine mammary epithelial cells.
Bibliographic record
Abstract
The objective of this study was to assess the role of 5’ adenosine monophosphate-activated protein kinase (AMPK) in glucose metabolism in response to energy substrates in bovine mammary epithelial cells (BMEC). Primary BMEC were isolated from lactating mammary tissue of 3 independent cows. The cells were induced to differentiate by incubation in DMEM/F12 supplemented with lactogenic hormones (5 µg/mL each of insulin, prolactin and hydrocortisone) for 4 d. Site-specific phosphorylation was measured by immunoblotting. Relative mRNA transcript abundance was measured by qPCR. Data were analyzed using a randomized complete block design using PROC MIXED in SAS. Treatment differences were considered significant when p<0.05. To assess the regulation of AMPK by energy availability in BMEC, cells were incubated in control medium containing 4 mmol/L glucose and 1 mmol/L sodium acetate, or medium lacking glucose or acetate for 4 h. Deprivation of glucose or acetate significantly promoted phosphorylation of AMPKα at Thr172 by 84 or 58 %, respectively. To define the sensitivity of AMPK to glucose levels, BMEC were treated with 4, 2, 1 or 0 mmol/L glucose for 4 h. The phosphorylation of AMPKα and its downstream target, ACC at Ser79, was increased by 81% when glucose concentration in medium was reduced by half and 250% in cells culture in medium completely devoid of glucose (p<0.05). To define the role of AMPK on glucose uptake and oxidation, BMEC were treated with 100 μmol/L A769662, an allosteric activator of AMPK, or vehicle control for 16 h. Activation of AMPK increased expression of the key glycolytic enzyme PGK1 by 35%, but did not change the expression of SLC2A1, which encodes for GLUT1. These results demonstrate that AMPK senses cellular energy status in BMEC and may be implicated in the control of glycolysis in BMEC, but the latter will require confirmation by direct measurement.
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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) | 0.002 | 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".