Cord blood myostatin concentrations by gestational diabetes mellitus and fetal sex
Bibliographic record
Abstract
Introduction Myostatin is a member of the transforming growth factor β superfamily, and is mainly secreted from skeletal muscle. Animal studies have demonstrated that deficiency in myostatin promotes muscle growth and protects against insulin resistance. In humans, gestational diabetes mellitus (GDM) affects fetal insulin sensitivity. Females are more insulin resistant and weigh less than males at birth. We sought to assess whether cord blood myostatin concentrations vary by GDM and fetal sex, and the associations with fetal growth factors. Methods In a study of 44 GDM and 66 euglycemic mother-newborn dyads, myostatin, insulin, proinsulin, insulin-like growth factor (IGF)-1, IGF-2 and testosterone were measured in cord blood samples. Results Cord blood myostatin concentrations were similar in GDM vs. euglycemic pregnancies (mean ± SD: 5.5 ± 1.4 vs. 5.8 ± 1.4 ng/mL, P=0.28), and were higher in males vs. females (6.1 ± 1.6 vs. 5.3 ± 1.0 ng/mL, P=0.006). Adjusting for gestational age, myostatin was negatively correlated with IGF-2 (r=-0.23, P=0.02), but not correlated with IGF-1 (P=0.60) or birth weight (P=0.23). Myostatin was strongly correlated with testosterone in males (r=0.56, P<0.001), but not in females (r=-0.08, P=0.58) (test for difference in r, P<0.001). Testosterone concentrations were higher in males vs. females (9.5 ± 6.4 vs. 7.1 ± 4.0 nmol/L, P=0.017), and could explain 30.0% (P=0.039) of sex differences in myostatin concentrations. Discussion The study is the first to demonstrate that GDM does not impact cord blood myostatin concentration, but fetal sex does. The higher myostatin concentrations in males appear to be partly mediated by higher testosterone concentrations. These findings shed novel insight on developmental sex differences in insulin sensitivity regulation relevant molecules.
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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 | 0.001 |
| 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) | 0.002 | 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".