Dietary lipids modify the age-associated changes in intestinal uptake of fructose in rats
Bibliographic record
Abstract
Because reduced nutrient absorption may contribute to malnourishment in the elderly, age and diet modulate fructose uptake in mice, and alterations in fructose uptake may be paralleled by changes in the abundance of fructose transporters, the objectives of this study were to determine 1) the effects of aging on fructose absorption in rats, 2) the effect of feeding diets enriched with saturated fatty acids (SFA) vs. polyunsaturated fatty acids (PUFA), and 3) the mechanisms of these age-and diet-associated changes. Male Fischer 344 rats aged 1, 9, and 24 mo received isocaloric diets enriched with SFA or PUFA. The uptake of (14)C-labeled D-fructose was determined in vitro using the intestinal sheet method. Northern and Western blot analyses and immunohistochemistry were used to determine the abundance of sodium-independent glucose and fructose transporters (GLUT)2 and GLUT5. When expressed on the basis of mucosal surface area, jejunal fructose uptake was increased in 9 and 24 mo compared with 1-mo-old animals fed SFA. PUFA-fed animals demonstrated increased fructose uptake at 24 mo compared with younger animals. Ileal fructose uptake was increased with SFA vs. PUFA in 9-mo-old rats but was reduced with SFA in 1- and 24-mo-old rats. Variations in GLUT2 and GLUT5 abundance did not parallel changes in uptake. These results indicate that 1) age increases fructose uptake when expressed on the basis of mucosal surface area, 2) age influences the adaptive response to dietary lipid modifications, and 3) alterations in fructose uptake are not explained by variations in GLUT2 or GLUT5.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".