Methotrexate Promotes Glucose Uptake and Lipid Oxidation in Skeletal Muscle via AMPK Activation
Bibliographic record
Abstract
Methotrexate (MTX) is a widely used anticancer and antirheumatic drug that has been postulated to protect against metabolic risk factors associated with type 2 diabetes, although the mechanism remains unknown. MTX inhibits 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/inosine monophosphate cyclohydrolase (ATIC) and thereby slows the metabolism of 5-aminoimidazole-4-carboxamide-1-β-D-ribofuranosyl-5'-monophosphate (ZMP) and its precursor AICAR, which is a pharmacological AMPK activator. We explored whether MTX promotes AMPK activation in cultured myotubes and isolated skeletal muscle. We found MTX markedly reduced the threshold for AICAR-induced AMPK activation and potentiated glucose uptake and lipid oxidation. Gene silencing of the MTX target ATIC activated AMPK and stimulated lipid oxidation in cultured myotubes. Furthermore, MTX activated AMPK in wild-type HEK-293 cells. These effects were abolished in skeletal muscle lacking the muscle-specific, ZMP-sensitive AMPK-γ3 subunit and in HEK-293 cells expressing a ZMP-insensitive mutant AMPK-γ2 subunit. Collectively, our findings underscore a role for AMPK as a direct molecular link between MTX and energy metabolism in skeletal muscle. Cotherapy with AICAR and MTX could represent a novel strategy to treat metabolic disorders and overcome current limitations of AICAR monotherapy.
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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".