The effect of novel second generation prebiotics (levan of β‐[2,6]‐glycosidic linkages) on the cardiovascular system in obesity
Bibliographic record
Abstract
Objectives Bacteria dysbiosis is very well documented in obesity and is known to regulate the cardiovascular system. Recovering the bacteria composition is a key element in improving the cardiovascular function during obesity. Hypothesis In this study we investigate the effect of levan, a novel second generation of prebiotic (β‐[2,6]‐linkages, on the cardiovascular system in obesity. Methods Eight‐week‐old C57/b6 mice were fed with high fat diet (HFD) for 12 weeks in the presence and absence of levan (β‐[2,6]‐linkages). Treatment was administered by gavage (250 mg/kg) for the last 30 days of HFD feeding. Body weight, blood glucose, body composition and lipid profile were determined. Vascular function and endothelial function markers were studied in aorta and mesenteric resistance arteries (MRA). Results Levan (β‐[2,6]‐linkages) treatment reduced the body weight in obese mice. Blood glucose, % of fat mass, total cholesterol, and LDL levels were significantly reduced and the % of lean mass was significantly increased after Levan (β‐[2,6]‐linkages) treatment. Aortic and mesenteric arteries vascular response to sodium nitroprusside (SNP) was similar among groups. However, the vascular response to acetylcholine (Ach) was improved in the treated group. Conclusions Treatment with Levan (β‐[2,6]‐linkages) attenuated the increase in body weight in obese mice and restored the lipid profile and the vascular function.
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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".