A DIETARY PHASE 2 ENZYME INDUCER IN ANIMAL MODEL OF ESSENTIAL HYPERTENSION: PP.29.158
Bibliographic record
Abstract
Numerous studies have demonstrated the health benefits of fruits, vegetables, spices and herbs. For instance, consuming a clove of garlic (or equivalent) decreases cholesterol levels and attenuates hypertension. Previous studies in our laboratory have shown that broccoli sprouts rich in glucoraphanin, a precursor of a potent phase 2 protein inducing isothiocyanate sulforaphane, decreases oxidative stress and ameliorates hypertension. The question this study addressed was the importance of a food matrix in causing these beneficial effects, i.e., can one see the same effects by administration of sulforaphane alone? Sulforaphane (5, 10 and 20 μMoles/Kg) was administered by daily gavage to 5-wk old Spontaneously Hypertensive Stroke Prone rats (SHRsp) for 4 months. Blood pressure was measured weekly by tail cuff and at the end of the experiment by an external catheter inserted into the carotid artery in anesthetized animals. For comparison, age-matched normotensive Sprague Dawley (SD) rats were treated in the same manner. SHRsp control rats had significantly higher Systolic Blood Pressure (SBP) (179.9 ± 4.3 mm Hg) than control SD rats (83.98 ± 1.69). Sulforaphane treatment significantly lowered SHRsp blood pressure to 157.7 ± .21. There was no effect of sulforaphane treatment on SD rat SBP (93.9 ± 4.26). We conclude that the health benefit previously demonstrated in our laboratory is due to sulforaphane.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".