Can early-life high fructose exposure induce long-term depression and anxiety-like behaviours? – A preclinical systematic review
Bibliographic record
Abstract
Early-life environmental factors, such as maternal diet or early-life nutrition, have been described as significant risk factors for anxiety and depression later in life. With the rising intake of fructose since the 1960 s, several adverse effects have been described, but little is known about the impact of early-life high fructose exposure on the risk of developing depression and anxiety later in life. Since animal models provide ways to test this hypothesis longitudinally in an experimental and controlled environment, we performed a systematic review to investigate whether high fructose exposure during early life influences the risk of developing depression or anxiety-like behaviours in animals. We adopted a high-sensitivity strategy to find potential studies. We included 1805 papers for screening, but only found nine eligible studies that tested only high fructose exposure during development, all conducted in rats. Data extraction and analysis revealed that 6 studies found evidence indicating that fructose exposure in early life increases the risk of anxiety or depression. The remaining 3 studies found no altered behavior after fructose exposure. The discrepancies may be caused by multiple factors, such as time of diet exposure, animal strain, behavioural testing differences, and fructose's metabolic influence. Due to weak and contradictory evidence, we could not conclude if early-life fructose exposure influences the risk of anxiety or depression-like behaviors. We propose future directions and suggestions for future studies to strengthen their findings.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".