Effects of supplemental cystine or methionine on growth and lifespan of stroke-prone spontaneously hypertensive rats
Bibliographic record
Abstract
Stroke-prone spontaneously hypertensive (SHRSP) rats are considered a suitable model for studying the effects of dietary and other environmental factors on human essential hypertension and haemorrhagic stroke. To investigate the suitability of a control diet for this strain of rats, we studied the effects of supplementing casein and soya protein isolate (SPI) with two sulphur amino acids (methionine and cystine) on the growth and lifespan of SHRSP rats. The source of dietary protein and the type of supplemental sulphur amino acid had significant (P < 0.05) effects on food intake and weight gain measured after 31 d of the feeding study, while only the type of supplemental sulphur amino acid had significant effects on mean survival times and the survival rates. On average, the casein groups had higher food intake and weight gain compared with the SPI groups. The methionine-supplemented groups had lower food intake but higher weight gain than the cystine-supplemented groups. Similarly, the methionine-supplemented groups had higher mean survival times and survival rates compared with the cystine-supplemented groups. The data would suggest that a control diet based on cystine-supplemented casein (as recommended for normal healthy rats by the American Institute of Nutrition), may not meet the sulphur amino acid requirements for SHRSP rats, and that the methionine-supplemented casein would be an appropriate control diet for this animal model.
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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".