Maternal arachidonic acid supplement improved neurodevelopment of offspring of diabetic dams in poor glucose control
Bibliographic record
Abstract
It has been suggested that diabetic teratogenesis is mediated by a functional deficiency of arachidonic acid (AA) at a critical stage of organogenesis. This study was conducted in pups of control and diabetic dams to determine the effect of maternal dietary AA supplement on offspring neurodevelopment. 30 female Sprague Dawley rats were randomized to 6 groups; 2 groups were control and 4 groups were diabetic; half of the diabetic groups were in good glucose control (<13 mmol/L) and the other in poor control (13‐20 mmol/L). Half of each treatment was fed an AA diet (5%) and the other half a control diet from 1 wk prior to conception to weaning. Offspring were assessed on postnatal d3 for righting response, d7 for geotaxis, d14 for wire hanging, d18 for rota rod performance, and d28 for Morris water maze. For righting response, a diet by sex interaction yielded quicker responses in male pups fed AA (17.9 vs 10.4 s, P=0.007). For negative geotaxis (21.7 vs 33.4 vs 51.7 s, P<0.02) and rota rod (5.8 vs 4.5 vs 3.3 s, P<0.05), offspring of diabetic dams performed worse than control but the AA diet improved performance in pups from dams in poorly controlled diabetes groups (geotaxis: 61.1 vs 42.3 s, P<0.0006; rota rod: 2.4 vs 4.2 P<0.03). For the water maze test, no effects of treatment (P=0.77) or diet (P=0.16) were observed. In conclusion, offspring of diabetic dams in good glucose control are smaller but have neurologic development similar to control pups. Pups from dams with poor glucose control benefited from the dietary AA suggesting a potential intervention suitable for use in human infants of diabetic mothers with poor glycemic control in pregnancy. (CIHR)
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".