Benzimidazole derivative small-molecule 991 enhances AMPK activity and glucose uptake induced by AICAR or contraction in skeletal muscle
Bibliographic record
Abstract
AMP-activated protein kinase (AMPK) plays diverse roles and coordinates complex metabolic pathways for maintenance of energy homeostasis. This could be explained by the fact that AMPK exists as multiple heterotrimer complexes comprising a catalytic α-subunit (α1 and α2) and regulatory β (β1 and β2)- and γ (γ1, γ2, γ3)-subunits, which are uniquely distributed across different cell types. There has been keen interest in developing specific and isoform-selective AMPK-activating drugs for therapeutic use and also as research tools. Moreover, establishing ways of enhancing cellular AMPK activity would be beneficial for both purposes. Here, we investigated if a recently described potent AMPK activator called 991, in combination with the commonly used activator 5-aminoimidazole-4-carboxamide riboside or contraction, further enhances AMPK activity and glucose transport in mouse skeletal muscle ex vivo. Given that the γ3-subunit is exclusively expressed in skeletal muscle and has been implicated in contraction-induced glucose transport, we measured the activity of AMPKγ3 as well as ubiquitously expressed γ1-containing complexes. We initially validated the specificity of the antibodies for the assessment of isoform-specific AMPK activity using AMPK-deficient mouse models. We observed that a low dose of 991 (5 μM) stimulated a modest or negligible activity of both γ1- and γ3-containing AMPK complexes. Strikingly, dual treatment with 991 and 5-aminoimidazole-4-carboxamide riboside or 991 and contraction profoundly enhanced AMPKγ1/γ3 complex activation and glucose transport compared with any of the single treatments. The study demonstrates the utility of a dual activator approach to achieve a greater activation of AMPK and downstream physiological responses in various cell types, including skeletal muscle.
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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 | 0.000 |
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".