Prenatal fruit juice exposure enhances memory consolidation in male post-weanling Sprague-Dawley rats
Bibliographic record
Abstract
OBJECTIVES: Nutritional intake during gestation is known to impact health outcomes for progeny. Correlational evidence in humans suggests that increased fruit consumption of pregnant mothers enhances infant cognitive development. Moreover, wild-type Drosophila supplemented with a combination of orange and tomato juice showed robust enhancements in performance on an associative olfactory memory task. The current study aimed to experimentally test the effects of prenatal fruit juice exposure in a non-human, mammalian model of learning and memory. METHODS: Across three separate birth cohorts, pregnant rats were given access to diluted tomato and orange juice (N = 2 per cohort), with control rats (N = 2 per cohort) receiving only water, in addition to standard rodent chow, throughout the duration of gestation, ending at parturition. Following weaning, male offspring were tested for learning and memory in a spatial version of the circular water maze and an auditory-cued fear-conditioning task. RESULTS: All pregnant rats increased fluid and food intake over the gestational period. Fruit juice-fed pregnant rats had increased fluid intake compared to control pregnant rats. When testing progeny, there were no effects of prenatal fruit juice on spatial learning, while it appeared to impair learning in fear conditioning relative to controls. However, we measured significant enhancements in both spatial memory and conditioned fear memory in the prenatal fruit-juice group compared to controls. Measures of vigilance, in response to the conditioned cue, were increased in prenatal fruit rats compared to controls, suggesting less generalized, and more adaptive, anxiety behaviours. DISCUSSION: Our results corroborate the human and Drosophila findings of prenatal fruit effects on behaviour, specifically that prenatal fruit juice exposure may be beneficial for early-life memory consolidation in rats.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".