Effects of a highly palatable diet on lipid and glucose parameters, nitric oxide, and ectonucleotidases activity
Bibliographic record
Abstract
Obesity has reached epidemic proportions worldwide and is stimulated by the ready availability of food rich in fat and sugar (highly palatable diet). This type of diet increases the risks of obesity-associated pathologies, such as insulin resistance and cardiovascular disease. Nitric oxide, a potent endogenous vasodilator, is decreased in these pathologies, mostly as a result of insulin resistance. Ectonucleotidases are ecto and soluble enzymes that regulate the availability of the nucleotides ATP, ADP, and AMP and the nucleoside adenosine in the vascular system, thereby affecting vasoconstriction, vasodilatation, and platelet aggregation homeostasis. The aim of this study was to evaluate the effects of a highly palatable diet on serum lipid and glucose parameters, nitric oxide, and ectonucleotidase activity. Forty male Wistar rats were fed 1 of 2 diets for either 45 days or 4 months: standard chow (SC, n = 10) or a highly palatable diet enriched with sucrose (HP, n = 10). Body mass, visceral fat mass, glucose tolerance, cholesterol (total, high-density lipoprotein (HDL) and non-HDL), serum triacylglycerol, liver triacylglycerol, and free glycerol were increased in the HP group after 45 days and after 4 months, whereas insulin levels were not different between the groups at either time. Furthermore, levels of nitric oxide metabolites and ATP, ADP, and AMP hydrolysis were significantly lower in the HP group (p < 0.05) after 4 months. In conclusion, the consumption of the HP diet for 4 months induced overall corporal and metabolic changes, and decreased nitric oxide metabolites and ectonucleotidase activity, thereby promoting an appropriate environment for the development of cardiovascular diseases, without apparent changes in insulin levels.
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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) | 0.000 | 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 | 0.001 |
| 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".