Role of T Regulatory Lymphocytes in the Pathogenesis of High-Fructose Diet–Induced Metabolic Syndrome
Bibliographic record
Abstract
We recently showed that T regulatory lymphocytes (Treg), which are immune suppressors of inflammatory responses, play a role blunting the development of hypertension-induced injury. Treg are unchanged or decreased in children with metabolic syndrome, and therefore, their role in metabolic syndrome remains unclear. We hypothesized that Treg number or function would be depressed in a high-fructose diet-induced metabolic syndrome-like model in rats. Sprague-Dawley rats were fed normal chow or a high-fructose diet for 5 weeks. The high-fructose diet-induced a 3.8-fold increase in plasma triglycerides and a 14% reduction in high-density lipoprotein cholesterol (P<0.001). The high-fructose diet increased reactive oxygen species in aorta and periaortic adipose tissue 2.8-fold (P<0.05), and reduced nicotinamide adenine dinucleotide phosphate oxidase activity 1.9-fold in aorta, and 2.5-fold in the heart (P<0.05). It also increased plasma nitric oxide metabolite levels 6.4-fold (P<0.001). Western blots showed that the high-fructose diet increased ≥2.3-fold vascular and in platelet endothelial cell adhesion molecule 1 in aorta (P<0.01). It did not affect monocyte/macrophage aortic infiltration but caused a 2.4-fold increase in collagen deposition in the aortic media (P<0.01). No change in plasma interleukin-10 was detected. The percentage of spleen CD4+ CD25- and Treg (CD4+ CD25(high)) cells was unaltered by the high-fructose diet. However, cultured Treg from high-fructose diet-fed rats secreted 62% less interleukin-10 than control cells (P<0.05), suggesting a decreased Treg function, which could play a role in the development of cardiovascular complications of the metabolic syndrome.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".