A comparative study of the effects of molsidomine and 3‐morpholinosydnonimine on the redox status of rat erythrocytes and reticulocytes
Bibliographic record
Abstract
After enzymic biotransformation, molsidomine (MO) acts via the metabolite 3-morpholinosydnonimine (SIN-1) through spontaneous liberation of nitric oxide (NO) and superoxide (O(2)(.-)). The aim of this study was to compare the effects of MO and its active metabolite SIN-1 on the redox status of rat erythrocytes and reticulocytes. Rat erythrocyte as well as reticulocyte-rich red blood cell (RBC) suspensions were aerobically incubated (2 h, 37 degrees C) without (control) or in the presence of different concentrations of MO or SIN-1. In rat erythrocytes, biotransformation of MO resulted in the production of NO and nitroxyl (NO(-)). Endogenous superoxide anion (O(2)(.-)) participated in peroxynitrite generation. SIN-1 simultaneously liberated NO and O(2)(.-), which formed peroxynitrite (at least in part), but the liberated NO predominantly reacted with haemoglobin, forming methaemoglobin in erythrocytes. In reticulocytes, MO and SIN-1 caused an increase in the levels of both nitrite and 3-nitrotyrosine (an indicator of peroxynitrite), whereas they decreased the level of O(2)(.-). In reticulocytes, MO was metabolized into SIN-1 which led to the generation of NO, which reacted with O(2)(.-) (endogenous or exogenous) forming reactive nitrogen species. In conclusion, there are two metabolic pathways for MO biotransformation: one causing NO and NO(-) generation predominantly in erythrocytes and the other, via SIN-1 metabolism, in reticulocytes. The main difference between the action of MO and SIN-1 was that the latter caused oxidative damage in RBCs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".