Cognitive Enhancement in Infants Associated with Increased Maternal Fruit Intake During Pregnancy: Results from a Birth Cohort Study with Validation in an Animal Model
Bibliographic record
Abstract
In-utero nutrition is an under-studied aspect of cognitive development. Fruit has been an important dietary constituent for early hominins and humans. Among 808 eligible CHILD-Edmonton sub-cohort subjects, 688 (85%) had 1-year cognitive outcome data. We found that each maternal daily serving of fruit (sum of fruit plus 100% fruit juice) consumed during pregnancy was associated with a 2.38 point increase in 1-year cognitive development (95% CI 0.39, 4.37; p<0.05). Consistent with this, we found 30% higher learning Performance index (PI) scores in Drosophila offspring from parents who consumed 30% fruit juice supplementation prenatally (PI: 85.7; SE 1.8; p<0.05) compared to the offspring of standard diet parents (PI: 65.0 SE 3.4). Using the Drosophila model, we also show that the cyclic adenylate monophosphate (cAMP) pathway may be a major regulator of this effect, as prenatal fruit associated cognitive enhancement was blocked in Drosophila rutabaga mutants with reduced Ca(2+)-Calmodulin-dependent adenylyl cyclase. Moreover, gestation is a critical time for this effect as postnatal fruit intake did not enhance cognitive performance in either humans or Drosophila. Our study supports increased fruit consumption during pregnancy with significant increases in infant cognitive performance. Validation in Drosophila helps control for potential participant bias or unmeasured confounders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".