Long-term effects of gestational diabetes on offspring health are more pronounced in skeletal growth than body composition and glucose tolerance
Bibliographic record
Abstract
Infants of diabetic mothers may have low arachidonic acid (AA) and develop obesity and insulin resistance in adulthood. The present study tested the effect of maternal diabetes and AA supplementation on offspring body composition, bone mass and glucose tolerance from 4 to 12 weeks. Rat dams were randomised into six groups using a 3 × 2 design. The rat dams were treated using the following treatments: saline-placebo, streptozotocin-induced diabetes (STZ) with glucose controlled at < 13 mmol/l (STZ/GC) or poorly controlled at 13-20 mmol/l (STZ/PC) using insulin, and fed either a control or an AA (0.5 % of fat) diet throughout reproduction. Weaned offspring were fed regular chow. Measurements included offspring body composition, bone and oral glucose tolerance testing (OGTT) plus liver fatty acids of dam and offspring. Comparable to saline-placebo offspring, the STZ/GC offspring had greater (P < 0.03) whole body and regional bone area than STZ/PC offspring. Maternal glucose negatively correlated (P < 0.05) with offspring whole body bone area and mineral content at 4 weeks in all offspring, and with tibia area in males at 12 weeks. Maternal liver DHA negatively (P < 0.03) correlated with femur and tibia mineral content and tibia mineral density of female offspring at 12 weeks. Offspring from AA-supplemented dams had higher (P = 0.004) liver AA at 4 weeks. Liver AA at 4 weeks positively (P = 0.05) correlated with lumbar spine mineral density in males. OGTT was not affected by maternal treatment or diet. These results suggest that maternal glucose control has long-term consequences to bone health of adult offspring. Skeletal growth appears more sensitive to maternal hyperglycaemia than glucose tolerance.
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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 | 0.000 |
| 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 | 0.001 |
| 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".