Bibliographic record
Abstract
PURPOSE OF REVIEW: Fructose, a naturally found sugar in many fruits, is now commonly used as an industrial sweetener and is excessively consumed in Western diets. High fructose intake is increasingly recognized as causative in development of prediabetes and metabolic syndrome. The mechanisms underlying fructose-induced metabolic disturbances are unclear but are beginning to be unravelled. This review presents recent findings in this field and an overall mechanistic insight into the metabolic effects of dietary fructose and its role in metabolic syndrome. RECENT FINDINGS: Recent animal studies have confirmed the link between fructose feeding and increased plasma uric acid, a potentially causative factor in metabolic syndrome. Advanced glycation end products are also implicated because of their direct protein modifications and indirect effects on inflammation and oxidative stress. Human studies have demonstrated fructose's ability to change metabolic hormonal response, possibly contributing to decreased satiety. SUMMARY: There is much evidence from both animal models and human studies supporting the notion that fructose is a highly lipogenic nutrient that, when consumed in high quantities, contributes to tissue insulin insensitivity, metabolic defects, and the development of a prediabetic state. Recently evidence has helped to decipher the mechanisms involved in these metabolic changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".