Cardioprotective Effects of Cysteine Alone or in Combination With Taurine in Diabetes
Bibliographic record
Abstract
This study was undertaken to examine the effects of dietary supplementation of cysteine and taurine in rats with diabetes induced with streptozotocin (STZ, 65 mg/kg body weight). Experimental animals were treated orally (by gavage) with cysteine (200 mg/kg) and taurine (400 mg/kg), alone or in combination, daily for 8 weeks. In one group, rats were also pretreated 3 weeks before the induction of diabetes (prevention arm) whereas in the other, the treatment was started 3 days after the induction of diabetes (reversal arm). Diabetes increased heart weight/body weight (HW/BW) ratio, plasma glucose, triglyceride and cholesterol levels as well as depressed heart rate (HR), blood pressure, left ventricular systolic pressure (LVSP), rate of contraction (+dP/dt), rate of relaxation (-dP/dt), fractional shortening (FS) and cardiac output (CO). The left ventricular internal diameter in systole (LViDs) was increased whereas that in diastole (LViDd) was decreased. In the prevention arm, treatment of the diabetic animals with cysteine or taurine decreased HW/BW ratio and improved HR, FS, +dP/dt and -dP/dt, as well as normalized LViDs, without altering the increase in glucose level. Cysteine decreased plasma triglyceride and cholesterol levels and improved LVSP whereas CO was improved by taurine. In the reversal arm, cysteine alone or with taurine did not correct the changes in hemodynamic parameters, FS and plasma triglycerides. Diabetes-induced cardiac dysfunction and increases in plasma triglycerides can be prevented, but not reversed, by dietary cysteine alone or in combination with taurine.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".