miRNA Profiles in Extracellular Vesicles From Serum Early in Pregnancies Complicated by Gestational Diabetes Mellitus
Bibliographic record
Abstract
CONTEXT: Underlying mechanisms leading to gestational diabetes mellitus (GDM) are still under investigation, and it is unclear whether the placenta plays a role in triggering glucose intolerance or if its functions are modified in response to the hyperglycemia. Circulating miRNAs are involved in placental development and function and are encapsulated in extracellular vesicles (EVs). OBJECTIVE: To compare differential expression of miRNAs in circulating EVs in pregnancies complicated by GDM vs controls. METHODS: This was a case-control study nested in a prospective pregnancy cohort including 23 women with GDM and 46 matched controls. The presence of serum EVs in early pregnancy was validated by transmission electron microscopy. Placental dimensions were assessed at 11 to 13 weeks of gestation. Differential expression of 17 miRNAs encapsulated in EVs (miR‒122-5p, miR‒132-3p, miR-1323, miR‒182-3p, miR‒210-3p, miR‒29a-3p, miR‒29b-3p, miR‒342-3p, miR‒517-5p, miR‒517a-3p, miR‒518b, miR-520h, miR‒525-5p, miR‒136-5p, miR‒342-3p, miR‒376c-5p, and miR‒494-3p) was assessed using quantitative reverse transcription PCR. RESULTS: EVs were present in the early phase of placentation (6 to 15 weeks of gestation) in both cases and controls. No differences were observed for placental dimensions and estimated placental volume between GDM and control groups. Ten miRNAs (miR‒122-5p; miR‒132-3p; miR‒1323; miR‒136-5p; miR‒182-3p; miR‒210-3p; miR‒29a-3p; miR‒29b-3p; miR‒342-3p, and miR-520h) showed significantly higher levels in GDM cases than in controls (P ≤ 0.05). Bioinformatics analysis showed that these miRNAs are involved in trophoblast proliferation/differentiation as well as in insulin secretion/regulation and glucose transport in pregnant women. CONCLUSION: The miRNA content of blood EVs may be a promising avenue for studying the early effect of impaired glucose metabolism on placental development.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".