Mice with Whole-Body Disruption of AMPK-Glycogen Binding Have Increased Adiposity, Reduced Fat Oxidation and Altered Tissue Glycogen Dynamics
Bibliographic record
Abstract
The AMP-activated protein kinase (AMPK), a central regulator of cellular energy balance and metabolism, binds glycogen via its β subunit. However, the physiological effects of disrupting AMPK-glycogen interactions remain incompletely understood. To chronically disrupt AMPK-glycogen binding, AMPK β double knock-in (DKI) mice were generated with mutations in residues critical for glycogen binding in both the β1 (W100A) and β2 (W98A) subunit isoforms. We examined the effects of this DKI mutation on whole-body substrate utilization, glucose homeostasis, and tissue glycogen dynamics. Body composition, metabolic caging, glucose and insulin tolerance, serum hormone and lipid profiles, and tissue glycogen and protein content were analyzed in chow-fed male DKI and age-matched wild-type (WT) mice. DKI mice displayed increased whole-body fat mass and glucose intolerance associated with reduced fat oxidation relative to WT. DKI mice had reduced liver glycogen content in the fed state concomitant with increased utilization and no repletion of skeletal muscle glycogen in response to fasting and refeeding, respectively, despite similar glycogen-associated protein content relative to WT. DKI liver and skeletal muscle displayed reductions in AMPK protein content versus WT. These findings identify phenotypic effects of the AMPK DKI mutation on whole-body metabolism and tissue AMPK content and glycogen dynamics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".