Differential effects of type 2 diabetes and gestational diabetes on maternal and cord blood adipokines and newborn weight
Bibliographic record
Abstract
BACKGROUND: Dysregulated adipokine levels are associated with type 2 diabetes and gestational diabetes. Adiponectin and leptin are involved in nutrient transport, thereby affecting fetal growth and metabolism. We aimed to determine whether type 2 diabetes and gestational diabetes were associated different levels of serum and cord blood adiponectin, leptin, insulin and offspring birthweight. METHODS: Serum, cord blood, gestational age and birthweight were collected for First Nations mothers and infants who were enrolled in the Next Generation Cohort Study. A total of 173 maternal and 188 neonatal samples were available for analysis. Of those, 136 were matched maternal infant dyads that we used for paired mother-infant analyses. Pairs were sorted into groups based on maternal diagnoses of pre-existing type 2 diabetes, gestational diabetes or no diabetes (control). Adiponectin and leptin were measured by enzyme linked immunosorbent assay. RESULTS: Mothers with gestational diabetes had lower serum adiponectin (6.48 ± 3.64 µg/mL) in the third trimester relative to mothers with type 2 diabetes (8.55 ± 5.24 µg/mL, p < 0.05) or no diabetes (7.73 ± 3.47 µg/mL). However, cord blood adiponectin was lower only in normal weight pregnancies complicated by type 2 diabetes. Cord blood glucose, insulin and leptin were increased in infants of type 2 diabetes mothers and increased leptin was positively correlated with maternal leptin and birth weight. Female infants exposed to pregestational type 2 diabetes had a significantly higher birthweight z-score than female control infants. CONCLUSIONS: In this study, exposure to type 2 diabetes, but not gestational diabetes, impacted cord blood levels of glucose, insulin and leptin and birthweight. Collectively, these factors may contribute to the greater impact of pregestational type 2 diabetes exposure on offspring health relative to gestational diabetes.
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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) | 0.000 | 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".