Effect of aging and obesity on GLUT12 expression in small intestine, adipose tissue, muscle, and kidney and its regulation by docosahexaenoic acid and exercise in mice
Bibliographic record
Abstract
Obesity is characterized by excessive fat accumulation and inflammation. Aging has also been characterized as an inflammatory condition, frequently accompanied by accumulation of visceral fat. Beneficial effects of exercise and n-3 long-chain polyunsaturated fatty acids in metabolic disorders have been described. Glucose transporter 12 (GLUT12) is one of the less investigated members of the GLUT family. Glucose, insulin, and tumor necrosis factor alpha (TNF-α) induce GLUT12 translocation to the membrane in muscle, adipose tissue, and intestine. We aimed to investigate GLUT12 expression in obesity and aging, and under diet supplementation with docosahexaenoic acid (DHA) alone or in combination with physical exercise in mice. Aging increased GLUT12 expression in intestine, kidney, and adipose tissue, whereas obesity reduced it. No changes on the transporter occurred in skeletal muscle. In obese 18-month-old mice, DHA further decreased GLUT12 in the 4 organs. Aerobic exercise alone did not modify GLUT12, but the changes triggered by exercise were able to prevent the DHA-diminishing effect, and almost restored GLUT12 basal levels. In conclusion, the downregulation of metabolism in aging would be a stimulus to upregulate GLUT12 expression. Contrary, obesity, an excessive energy condition, would induce GLUT12 downregulation. The combination of exercise and DHA would contribute to restore basal function of GLUT12. Novelty In small intestine, kidney and adipose tissue aging increases GLUT12 protein expression whereas obesity reduces it. Dietary DHA decreases GLUT12 in small intestine, kidney, adipose tissue and skeletal muscle. Exercise alone does not modify GLUT12 expression, nevertheless exercise prevents the DHA-diminishing effect on GLUT12.
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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 | 0.001 |
| 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) | 0.002 | 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".