Calcifediol Decreases Interleukin-6 Secretion by Cultured Human Trophoblasts From GDM Pregnancies
Bibliographic record
Abstract
Abstract Gestational diabetes mellitus (GDM) is often characterized by low maternal calcifediol (25OHD) and high inflammation levels. This study aimed to determine whether placental protein expressions of CYP27B1, vitamin D receptor (VDR), and CYP24A1 are impaired in GDM and to investigate the effect of a 25OHD treatment on IL-6 secretion by GDM trophoblasts compared with normoglycemic (NG) trophoblasts. Placental tissue samples were harvested to determine protein expression of CYP27B1, VDR, and CYP24A1 by immunoblots. Isolated trophoblasts were stimulated with 25OHD concentrations (25 to 2000 nM) once a day for 3 days and IL-6 secretion was quantified (ELISA). We recruited 17 NG women, 19 women with GDM treated with diet and exercise alone (GDM-d) and 9 women with GDM who necessitated insulin therapy (GDM-i). Protein expressions of CYP27B1 and VDR were significantly higher in placental tissue from GDM-d women compared with NG women (both P = 0.02), whereas no differences were detected between GDM-i and NG placental tissues. In cultured trophoblasts (two groups; n = 5 NG and n = 5 GDM-d), exposure to increasing 25OHD concentrations significantly decreased IL-6 secretion in the GDM-d group only (P = 0.006). After treatment with 25OHD (2000 nM), IL-6 secretion was lower in the GDM-d group compared with the NG group (P = 0.03). Our results suggest an upregulation of the VDR-1,25(OH)2D complex bioavailability in GDM-d placentas, possibly reflecting a compensatory mechanism aiming to ensure that vitamin D can exert its genomic and nongenomic effects in the target cells of the placental-fetal unit. Our findings support an anti-inflammatory effect of vitamin D at the feto-maternal interface in GDM-d pregnancies.
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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 | 0.000 |
| 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".