Hypothalamic AMP-Activated Protein Kinase Regulates Glucose Production
Bibliographic record
Abstract
OBJECTIVE: The fuel sensor AMP-activated protein kinase (AMPK) in the hypothalamus regulates energy homeostasis by sensing nutritional and hormonal signals. However, the role of hypothalamic AMPK in glucose production regulation remains to be elucidated. We hypothesize that bidirectional changes in hypothalamic AMPK activity alter glucose production. RESEARCH DESIGN AND METHODS: To introduce bidirectional changes in hypothalamic AMPK activity in vivo, we first knocked down hypothalamic AMPK activity in male Sprague-Dawley rats by either injecting an adenovirus expressing the dominant-negative form of AMPK (Ad-DN AMPKα2 [D(157)A]) or infusing AMPK inhibitor compound C directly into the mediobasal hypothalamus. Next, we independently activated hypothalamic AMPK by delivering either an adenovirus expressing the constitutive active form of AMPK (Ad-CA AMPKα1(312) [T172D]) or the AMPK activator AICAR. The pancreatic (basal insulin)-euglycemic clamp technique in combination with the tracer-dilution methodology was used to assess the impact of alternations in hypothalamic AMPK activity on changes in glucose kinetics in vivo. RESULTS: Injection of Ad-DN AMPK into the hypothalamus knocked down hypothalamic AMPK activity and led to a significant suppression of glucose production with no changes in peripheral glucose uptake during the clamps. In parallel, hypothalamic infusion of AMPK inhibitor compound C lowered glucose production as well. Conversely, molecular and pharmacological activation of hypothalamic AMPK negated the ability of hypothalamic nutrients to lower glucose production. CONCLUSIONS: These data indicate that changes in hypothalamic AMPK activity are sufficient and necessary for hypothalamic nutrient-sensing mechanisms to alter glucose production in vivo.
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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".