Understanding Reactive Sulfur Species Storage from Hybrid S/N Crosstalk Species: Perthionitrite (SSNO<sup>–</sup>) and Thionitrite (SNO<sup>–</sup>) Activation by a Mononuclear Nonheme Fe<sup>II</sup> Complex
Bibliographic record
Abstract
S/N hybrid species, such as perthionitrite (SSNO – ) and thionitrite (SNO – ), play intricate roles in nitric oxide (NO • ) and hydrogen sulfide (H 2 S) biological signaling and transport pathways. Despite this emerging significance, the fundamental reactivities of these species remain largely unexplored. In particular, a significant gap remains in understanding how these S/N hybrid species react with redox active metal centers. Building from this gap, we report here the reactivity of SSNO – and SNO – toward tripodal Fe 2+ complex [Fe( 3 CF 3 -baTren)] − ( 1 ) and examine the associated reactive nitrogen and sulfur species output pathways from these reactions using both spectroscopic and chemical trapping techniques. Specifically, we observe that complex 1 facilitates S–N bond homolysis of SSNO – to give {Fe–NO} 7 complex [Fe( 3 CF 3 -baTren)(NO)] − ( 2 ) and polysulfide radicals, whereas SNO – reacts with 1 to undergo S-centered reduction to give S 2– and NO • . Taken together, these results advance our understanding of how small molecule S/N hybrids react with redox active metal centers and may contribute to metal nitrosyl formation.
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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) | 0.001 | 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".