Fibroblast Growth Factor 19 in Gestational Diabetes Mellitus and Fetal Growth
Bibliographic record
Abstract
Fibroblast growth factor 19 (FGF19) has been implicated in glucose homeostasis. Gestational diabetes mellitus (GDM) enhances fetal insulin secretion and fetal growth. Girls weigh less and are more insulin resistant than boys at birth. We sought to assess whether FGF19 is associated with GDM and fetal growth and explore potential sex dimorphic associations. This was a nested case-control study in the Shanghai Birth Cohort, including 153 pairs of newborns of GDM versus euglycemic mothers matched by infant's sex and gestational age at birth. Cord plasma FGF19, insulin, C-peptide, proinsulin, IGF-I and IGF-II concentrations were measured. Cord plasma FGF19 concentrations were similar in GDM versus euglycemic pregnancies (mean ± SD: 43.5 ± 28.2 versus 44.5 ± 30.2 pg/mL, P=0.38). FGF19 was not correlated with IGF-I or IGF-II. FGF19 concentrations were positively correlated with birth weight (r=0.23, P=0.01) and length (r=0.21, P=0.02) z scores, C-peptide (r=0.27, P=0.002) and proinsulin (r=0.27, P=0.002) concentrations in females. Each SD increment in cord plasma FGF19 was associated with a 0.25 (0.07-0.43) increase in birth weight z score in females. In contrast, FGF19 was not correlated with birth weight or length in males. These sex dimorphic associations remained after adjusting for maternal and neonatal characteristics. The study is the first to demonstrate that GDM does not matter for cord blood FGF19 concentrations. The female specific positive correlation between FGF19 and birth weight is suggestive of a sex-dimorphic role of FGF19 in fetal growth. The observations call for more studies to validate the novel findings and elucidate the underlying mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".