Methyl succinate antagonises biguanide‐induced AMPK‐activation and death of pancreatic <i>β</i>‐cells through restoration of mitochondrial electron transfer
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Two mechanisms have been proposed to explain the insulin-sensitising properties of metformin in peripheral tissues: (a) inhibition of electron transport chain complex I, and (b) activation of the AMP activated protein kinase (AMPK). However the relationship between these mechanisms and their contribution to beta-cell death and dysfunction in vitro, are currently unclear. EXPERIMENTAL APPROACH: The effects of biguanides (metformin and phenformin) were tested on MIN6 beta-cells and primary FACS-purified rat beta-cells. Cell metabolism was assessed biochemically and by FACS analysis, and correlated with AMPK phosphorylation state and cell viability, with or without fuel substrates. KEY RESULTS: In MIN6 cells, metformin reduced mitochondrial complex I activity by up to 44% and a 25% net reduction in mitochondrial reducing potential. In rat beta-cells, metformin caused NAD(P)H accumulation above maximal glucose-inducible levels, mimicking the effect of rotenone. Drug exposure caused phosphorylation of AMPK on Thr(172) in MIN6 cell extracts, indicative of kinase activation. Methyl succinate, a complex II substrate, appeared to bypass metformin blockade of complex I. This resulted in reduced phosphorylation of AMPK, establishing a link between biguanide-induced mitochondrial inhibition and AMPK activation. Corresponding assessment of cell death indicated that methyl succinate decreased biguanide toxicity to beta-cells in vitro. CONCLUSIONS AND IMPLICATIONS: AMPK activation can partly be attributed to metformin's inhibitory action on mitochondrial complex I. Anaplerotic fuel metabolism via complex II rescued beta-cells from metformin-associated toxicity. We propose that utilisation of anaplerotic nutrients may reconcile in vitro and in vivo effects of metformin on the pancreatic beta-cell.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Pharmacology experiment on biguanide-induced AMPK activation in beta-cells; the object is cell metabolism.
The study investigates metformin effects on pancreatic beta cells.
Biomedical pharmacology of biguanides on pancreatic beta cells.
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) | 0.000 | 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".