Fructose, pregnancy and later life impacts
Bibliographic record
Abstract
Fructose is an increasingly common constituent of the Westernized diet due to cost and production efficiencies. Although an integral component of our pre-industrial revolution diet, over the past two decades human and animal studies have highlighted that excessive fructose intake appears to be associated with adverse metabolic effects. Excessive intake of fructose is the combined result of increased total energy consumption and increased portion sizes of foods, which often incorporate the fructose-containing sugars sucrose and high-fructose corn-syrup (HFCS). The adverse metabolic effects following excessive fructose consumption have become a hot topic in mainstream media and there is now rigorous scientific debate regarding periods of exposure, dosage levels, interactive effects with other sugars and fats and mechanisms underlying the actions of fructose. There is still a degree of controversy regarding the extent to which sugars such as sucrose and HFCS have contributed to the current epidemic of obesity and diabetes. Furthermore, an increasing number of infants are being exposed to sugar-sweetened food and beverages before birth and during early postnatal life, highlighting the importance of determining the long-term effects of this perinatal exposure on the developing offspring. There are limited human observational and controlled studies identifying associations of excessive sweetened food and beverage consumption with poor pregnancy outcomes. Animal research has demonstrated an increased incidence of gestational diabetes as well as altered maternal, fetal and offspring metabolic function, although the long-term effects and the mechanism underlying these perturbations are ill defined. This review aims to understand the role of early life fructose exposure in modifying postnatal risk of disease in the offspring, focusing on fructose intake during pregnancy and in early postnatal life.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".