Metformin regulates TRPM6, a potential explanation for magnesium imbalance in type 2 diabetes patients
Bibliographic record
Abstract
Metformin therapy is associated with lower serum magnesium (Mg2+) levels in type 2 diabetes patients. The TRPM6 channel determines the fine-tuning of Mg2+ (re)absorption in intestine and kidney. Therefore, we aimed to investigate the short- and long-term effects of metformin on TRPM6. Patch clamp recordings and biotinylation assays were performed upon 1 h of incubation with metformin in TRPM6-transfected HEK293 cells. Additionally, 24 h of treatment of mDCT15 kidney and hCaco-2 colon cells with metformin was applied to measure the effects on endogenous TRPM6 expression by quantitative real-time PCR. To assess Mg2+ absorption, 25Mg2+ uptake measurements were performed using inductively coupled plasma mass spectrometry. Short-term effects of metformin significantly increased TRPM6 activity and its cell surface trafficking. In contrast, long-term effects significantly decreased TRPM6 mRNA expression and 25Mg2+ uptake. Metformin lowered TRPM6 mRNA levels independently of insulin- and AMPK-mediated pathways. Moreover, in type 2 diabetes patients, metformin therapy was associated with lower plasma Mg2+ concentrations and fractional excretion of Mg2+. Thereby, short-term metformin treatment increases TRPM6 activity explained by enhanced cell surface expression. Conversely, long-term metformin treatment results in downregulation of TRPM6 gene expression in intestine and kidney cells. This long-term effect translated in an inverse correlation between metformin and plasma Mg2+ concentration in type 2 diabetes patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".