Elevated Serum Growth Differentiation Factor 15 Levels as a Potential Biomarker of the Efficacy of Imeglimin in Individuals With Type 2 Diabetes Mellitus: An Exploratory Study
Bibliographic record
Abstract
Background: The aim of the present study was to conduct a prospective observational study to explore the effects of imeglimin on systemic energy metabolism/body composition and to identify potential mitochondria-related biomarkers of the efficacy of the drug in clinical settings. Methods: In this prospective observational study, 16 participants with type 2 diabetes mellitus in the diabetes clinic of Kyoto University Hospital were enrolled. Individuals were started on imeglimin as monotherapy or add-on therapy. Results: After 3 months under imeglimin treatment, there was no significant change in basal metabolism or body composition. However, serum levels of growth differentiation factor 15 (GDF15) were higher while those of serum fibroblast growth factor 21 and urine 8-hydroxy-2′-deoxyguanosine were not changed. Additional in vitro examination revealed that imeglimin induces GDF15 protein release from human hepatocytes. Conclusions: Three-month imeglimin treatment increased serum GDF15 levels in clinical type 2 diabetes mellitus patients along with little change in basal metabolism or body composition, suggesting GDF15 as a potential marker for the efficacy of imeglimin.
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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 | 0.001 | 0.001 |
| 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".