Heme Nitrosylation of Deoxyhemoglobin byS-Nitrosoglutathione Requires Copper
Bibliographic record
Abstract
NO reactions with hemoglobin (Hb) likely play a role in blood pressure regulation. For example, NO exchange between Hb and S-nitrosoglutathione (GSNO) has been reported in vitro. Here we examine the reaction between GSNO and deoxyHb (HbFe(II)) in the presence of both Cu(I) (2,9-dimethyl-1, 10-phenanthroline (neocuproine)) and Cu(II) (diethylenetriamine-N,N,N',N",N"-pentaacetic acid) chelators using a copper-depleted Hb solution. Spectroscopic analysis of deoxyHb (HbFe(II))/GSNO incubates shows prompt formation (<5 min) of approximately 100% heme-nitrosylated Hb (HbFe(II)NO) in the absence of chelators, 46% in the presence of diethylenetriamine-N,N,N',N",N"-pentaacetic acid, and 25% in the presence of neocuproine. Negligible (<2%) HbFe(II)NO was detected when neocuproine was added to copper-depleted HbFe(II)/GSNO incubates. Thus, HbFe(II)NO formation via a mechanism involving free NO generated by Cu(I) catalysis of GSNO breakdown is proposed. GSH is a source of reducing equivalents because extensive GSSG was detected in HbFe(II)/GSNO incubates in the absence of metal chelators. No S-nitrosation of HbFe(II) was detected under any conditions. In contrast, the NO released from GSNO is directed to Cysbeta(93) of oxyHb in the absence of chelators, but only metHb formation is observed in the presence of chelators. Our findings reveal that the reactions of GSNO and Hb are controlled by copper and that metal chelators do not fully inhibit NO release from GSNO in Hb-containing solutions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".