The Potential Anti-Diabetic Effects of Saskatoon Berry in Experimental Mouse Models
Bibliographic record
Abstract
We previously reported that Saskatoon-Berry-Powder (SBP) might have beneficial effects on vascular inflammation and endoplasmic reticulum stress in experimental animals.In a pilot study, we tested various oral doses of SBP and learned that the 5% (w/w) dose seems to have the best effects.This study investigated the impact of dietary intake of SBP at 5% (w/w) on several biochemical factors pertaining to body weight gain, glucose metabolism; lipids, inflammation and organ function over a 4-week study period.The db/db mouse model of type 2 diabetes and their wild-type counterparts (C57BL/6J mice) were used.Body weight, food-intake, whole blood glucose, and plasma total cholesterol levels were significantly higher in the db/db mice as compared with those in C57BL/6J mice.Consumption of SBP did not change the animals' body weight gain rates or food consumption in either animal model over the experimental course.The SBP-treated db/db mice showed approximately 30% reductions in their blood and urine glucose levels as compared to those in nontreated db/db mice over 4 weeks of experiment.Furthermore, the db/db mice show a different inflammatory-marker profile as compared to that in C57BL/6J mice; treatment with SBP was associated with changes in such profiles mainly in db/db mice.It is not clear which component(s) of SBP is responsible for the effects observed in this study.Future studies warrant identification of such functional components of SBP.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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".