The Effects of Morinda citrifolia (Noni) Fruit Juice on the Prevention of Stroke by Promoting Production of Nitric Oxide through the Brain of the Spontaneously Hypertensive Stroke Prone (SHRSP) Rats
Bibliographic record
Abstract
Morinda citrifolia (Noni) is a traditional folk medicinal plant and has a long history of use as a food and medicine. In order to reveal the effects of Noni fruit juice (NFJ) on stroke prevention, we performed experiments using spontaneously hypertensive stroke prone (SHRSP) rats. NFJ did not change rat body weight, food intake, and water intake. However, both systolic blood pressure (SBP) and diastolic blood pressure (DBP) were significantly decreased after NFJ treatment in SHRSP rats. Furthermore, NFJ significantly increased the survival rate, urinary nitric oxide (NO) concentration was significantly higher in the NFJ group, and endothelial NO synthase (eNOS) phosphorylation levels increased in the brain after NFJ treatment. Two pathways regulate eNOS phosphorylation: the insulin-dependent pathway and the insulin-independent pathway. For the insulin-dependent pathway, phosphorylation of insulin receptor substrate 1 (IRS1) and protein kinase B (Akt) did not change in the NFJ group. For the insulin-independent pathway, expression of adenosine monophosphate-activated protein kinase (AMPK) phosphorylation, liver kinase B 1 (LKB1), and silent information regulator 1 (Sirt1) significantly increased in the brain of SHRSP rats after NFJ treatment. These data suggested that NFJ prevented stroke by improved blood circulation, increased NO production, and elevated eNOS phosphorylation by stimulating the insulin-independent pathway (Sirt1-LKB1-AMPK-eNOS).
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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 | 0.001 |
| 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".