Increased placental mitochondrial fusion in gestational diabetes mellitus: an adaptive mechanism to optimize feto-placental metabolic homeostasis?
Bibliographic record
Abstract
INTRODUCTION: Gestational diabetes mellitus (GDM), a common pregnancy disorder, increases the risk of fetal overgrowth and later metabolic morbidity in the offspring. The placenta likely mediates these sequelae, but the exact mechanisms remain elusive. Mitochondrial dynamics refers to the joining and division of these organelles, in attempts to maintain cellular homeostasis in stress conditions or alterations in oxygen and fuel availability. These remodeling processes are critical to optimize mitochondrial function, and their disturbances characterize diabetes and obesity. METHODS AND RESULTS: Herein we show that placental mitochondrial dynamics are tilted toward fusion in GDM, as evidenced by transmission electron microscopy and changes in the expression of key mechanochemical enzymes such as OPA1 and active phosphorylated DRP1. In vitro experiments using choriocarcinoma JEG-3 cells demonstrated that increased exposure to insulin, which typifies GDM, promotes mitochondrial fusion. As placental ceramide induces mitochondrial fission in pre-eclampsia, we also examined ceramide content in GDM and control placentae and observed a reduction in placental ceramide enrichment in GDM, likely due to an insulin-dependent increase in ceramide-degrading ASAH1 expression. CONCLUSIONS: Placental mitochondrial fusion is enhanced in GDM, possibly as a compensatory response to maternal and fetal metabolic derangements. Alterations in placental insulin exposure and sphingolipid metabolism are among potential contributing factors. Overall, our results suggest that GDM has profound impacts on placental mitochondrial dynamics and metabolism, with plausible implications for the short-term and long-term health of the offspring.
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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) | 0.001 | 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".