Fetuin-A in Infants Born Small- or Large-for-Gestational-Age
Bibliographic record
Abstract
Fetuin-A is a multifunctional glycoprotein that has been implicated in insulin resistance and bone metabolism. We assessed whether fetuin-A is associated with poor or excessive fetal growth. In the Shanghai Birth Cohort, we conducted a nested case-control study of 60 trios of small-for-gestational-age (SGA, birth weight <10th percentile), optimal-for-gestational-age (OGA, 25-75th, the reference) and large-for-gestational-age (LGA, >90th percentile) infants matched by sex and gestational age. Cord plasma concentrations of fetuin-A and fetal growth factors [insulin, proinsulin, insulin-like growth factor (IGF)-I and IGF-II] were measured. Cord plasma fetuin-A concentrations were higher in SGA (809.4±306.9 μg/ml, P=0.026) and LGA (924.2±375.9 μg/ml, P<0.001) relative to OGA (680.7±262.1 μg/ml) newborns, and were not correlated to insulin, proinsulin, IGF-I and IGF-II (all P>0.2). Higher fetuin-A concentrations were associated with increased risks of SGA [OR=1.67 (1.08-2.58) per SD increment, P=0.024] and LGA [OR=2.36 (1.53-3.66), P<0.001]. Adjusting for maternal and neonatal characteristics and fetal growth factors, the elevated risk changed little for LGA [adjusted OR=2.28 (1.29-4.01), P=0.005], but became non-significant for SGA (P=0.202). Our study is the first to demonstrate that fetuin-A may be involved in excessive fetal growth. This association is independent of fetal growth factors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".