The effects of nitroglycerine on the redox status of rat erythrocytes and reticulocytes
Bibliographic record
Abstract
The effects of nitroglycerine (NTG) are mediated by liberated nitric oxide (NO) after NTG enzymatic bio-transformation in cells. The aim of this study was to evaluate some products of NTG bio-transformation and their consequences on the redox status of rat erythrocytes and reticulocytes, considering the absence and presence of functional mitochondria in these cells, respectively. Rat erythrocyte and 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 NTG (0.1, 0.25, 0.5, 1.0 and 1.5 mM). In rat erythrocytes, NTG did not elevate the concentrations of any reactive nitrogen species (RNS). However, NTG robustly increased concentration of methemoglobin (MetHb), suggesting that NTG bio-transformation was primarily connected with hemoglobin (Hb). NTG-induced MetHb formation was followed by the induction of lipid peroxidation. In rat reticulocytes, NTG caused an increase in the levels of nitrite, peroxinitrite, hydrogen peroxide, MetHb and lipid peroxide levels, but it decreased the level of the superoxide anion radical. Millimolar concentrations of NTG caused oxidative damage of both erythrocytes and reticulocytes. These data indicate that two pathways of NTG bio-transformation exist in reticulocytes: one generating RNS and the other connected with Hb (as in erythrocytes). In conclusion, NTG bio-transformation is different in erythrocytes and reticulocytes due to the presence of mitochondria in the latter.
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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 | 0.000 |
| 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 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".