Evidence for S-nitrosothiol-dependent changes in fibrinogen that do not involve transnitrosation or thiolation.
Bibliographic record
Abstract
S-nitrosoglutathione (GSNO, 50 microM) inhibited the initial rate of thrombin-catalyzed human and bovine fibrinogen polymerization by approximately 50% to 68% respectively. Inhibition was also observed with other structurally varied S-nitrosothiols (RSNOs) including sugar derivatives of S-nitroso-N-acetylpenicillamine (SNAP). The fact that the same concentration of GSNO had no effect on thrombin-dependent hydrolysis of tosylglycylprolylarginine-4-nitroanilide acetate suggested that this inhibition was due to GSNO-induced changes in fibrinogen structure. This result was confirmed by CD spectroscopy where GSNO or S-nitrosohomocysteine increased the alpha-helical content of fibrinogen by approximately 15% and 11%, respectively. S-carboxymethylamido derivatives of glutathione or homocysteine had no effect on the fibrinogen secondary structure. The GSNO-dependent secondary structural effects were reversed on gel filtration chromatography, suggesting that the effects were allosteric. Further evidence for fibrinogen-GSNO interactions was obtained from GSNO-dependent quenching of the intrinsic fibrinogen Trp fluorescence and the perturbation of the GSNO circular dichroic absorbance as a function of [fibrinogen]. The K(d)s of 3 to 10 microM for fibrinogen-GSNO interactions with a stoichiometry of 2:1 (GSNO:fibrinogen) were estimated from isothermal titration calorimetry and fluorescence quenching, respectively. These results suggest that RSNOs induce changes to fibrinogen structure by interacting at specific aromatic rich domains. Three such putative RSNO-binding domains have been identified in the unordered, aromatic residue-rich C-termini of the alpha-chains of fibrinogen.
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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 | 0.001 |
| Open science | 0.001 | 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".