Cord Blood Fetuin-B, Fetal Growth Factors, and Lipids in Gestational Diabetes Mellitus
Bibliographic record
Abstract
CONTEXT: Fetuin-B is a hepatokine/adipokine implicated in glucose homeostasis and lipid metabolism. OBJECTIVE: We sought to assess whether cord blood fetuin-B levels are altered in gestational diabetes mellitus (GDM) and the association with fetal growth factors and lipids. METHODS: In a nested, case-control study of 153 pairs of neonates of mothers with GDM and euglycemic pregnancies in the Shanghai Birth Cohort, we assessed cord blood fetuin-B in relation to fetal growth factors and lipids (high-density lipoprotein, low-density lipoprotein [LDL], total cholesterol [TC], and triglycerides). RESULTS: Cord blood fetuin-B concentrations were higher in the newborns of GDM vs euglycemic mothers (mean ± SD: 2.35 ± 0.96 vs 2.05 ± 0.73 mg/L; P = .012), and were positively correlated with LDL (r = 0.239; P < .0001), TC (r = 0.230; P = .0001), insulin-like growth factor-Ⅰ (IGF-Ⅰ) (r = 0.137; P = .023) and IGF-Ⅱ (r = 0.148; P = .014) concentrations. Similar associations were observed adjusting for maternal and neonatal characteristics. CONCLUSION: The study is the first to demonstrate that fetuin-B levels are elevated in fetal life in GDM, and that fetuin-B affects lipid metabolic health during fetal life in humans. The secretion of fetuin-B appears to be related to the secretion of IGF-Ⅰ and IGF-Ⅱ.
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 | 0.000 | 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".