Dietary Enrichment with Blueberry and/or Probiotics Does Not Alter Blood Pressure Variability Compared to Control Diet in Hypertensive Rats
Bibliographic record
Abstract
Variability in blood pressure (BP) is a risk factor for cardiovascular events independent of mean BP. Recently we showed that feeding polyphenol‐rich wild blueberries (BB) or probiotics (PRO) to hypertensive rats reduced the characteristic rise in BP over time. Here we report the effect of these diets on BP variability. Groups (n=8 each) of male spontaneously hypertensive rats were fed one of four AIN93G‐based diets for 8 weeks: Control; 3% freeze‐dried wild BB; 1% probiotic bacteria (PRO); or 3% BB + 1% PRO. BP was measured biweekly by the tail‐cuff method. The standard deviation (SD) and coefficient of variation (CV) of diastolic and systolic BP were compared across groups using 2‐way ANOVA with repeated measures. Results Separate diet enrichment with BB or PRO did not have a significant effect on BP variability (p>0.10). However, the interaction of enrichment with BB and PRO had a significant effect on diastolic BP SD (p=0.016) and CV (p=0.007), with post‐hoc comparisons showing lower variability in the BB+PRO vs. BB group (p<0.05). BP variability was not different from control for any enriched diet. Conclusion Diet enrichment with separate or combined BB and PRO does not affect BP variability compared to control diet in hypertensive rats. Adding PRO to BB‐enriched diets might alter BP variability. Support or Funding Information Wild Blueberry Association of North America
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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) | 0.002 | 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".