Efeitos da N-acetilcisteína no precondicionamento isquêmico: estudo em corações isolados de ratos
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to assess if N-Acetylcysteine (NAC) changes the Ischemic Preconditioning (IP) in isolated rat hearts using only one cycle of IP. METHODS: Heart Rate (HR), Coronary Flow (CF) and Myocardial Contractility (dP/dt) were registered in 30 Wistar rat's hearts. After anesthesia the hearts were removed and perfused with Krebes-Hensleit equilibrated solution with 95% of O2 and 5% of CO2 according Langendorff's method. GI: Control (n=6); GII: 20 min. ischemia (n=6); GIII: IP (n=6); GIV 50 microg/ml/min NAC before IP (n =6); GV: 100 microg/ ml/min NAC before IP (n=6). Parameters were measured after 15 min. of stabilization (T 0) and T3, T5, T10, T15, T20, T25 and T30 min. after reperfusion. Statistical significance was considered when P<0.05. RESULTS: There were changes on HR comparing GI with GII at T20 and T25 and comparing GI with GIII, GIV with GV at T10 and T20 (P<0.05). CF was different comparing GI with GII at T3 and T5, GI with GIV at T10 and GI with GV at T10 and T25 (P<0.05). Myocardial Contractility was similar comparing GIII with GI and GV. GIII had higher dP/dt than GIV but without statistical difference (P>0.05). dP/dt was higher in GV than GIV but with statistically significant difference only at T30. CONCLUSION: dP/dt was better in preconditioned hearts and was changed if using NAC in GIV. The use of NAC didn't change the effects of preconditioning on myocardial contractility in GV.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".