Hemoglobin’s β-subunit is primed to synergize oxygen delivery with nitric oxide-mediated increased blood flow
Bibliographic record
Abstract
Hemoglobin (Hb) undergoes a well-documented R[Formula: see text]T quaternary transition from a high [Formula: see text] affinity R state to a low [Formula: see text] affinity T state to optimize [Formula: see text] delivery to tissues. Also, red blood cells (RBCs) release a nitrovasodilator that increases blood flow to boost [Formula: see text] delivery. Hb’s R[Formula: see text]T transition coordinates its [Formula: see text] desaturation and RBC nitrovasodilator release by much-debated mechanisms. Here we investigate the allosterically controlled [Formula: see text]-nitrosation of Hb at its conserved βCys93 (i.e., SNO-Hb formation) for nitrovasodilator release. First, we examined NO[Formula: see text]/deoxyHb (HbFeII) incubations following aeration to mimic RBC NO production by the nitrite reductase activity of HbFeII and trapping of the nascent NO by βCys93 to give SNO-Hb on HbFeII conversion to oxyHb (HbFeO2). We confirmed SNO-Hb formation in the incubations with yields modulated by RBC antioxidant enzymes and [Formula: see text] but not CO. Since FeO2 hemes scavenge free NO, we hypothesized NO channeling within Hb and found by molecular dynamics simulations that most unligated NO molecules placed in the β-distal heme pocket (βDP) rapidly diffuse into a wide β-tunnel connecting the βDP to Hb’s central cavity and βCys93. Contraction of the central cavity brings NO closer to βCys93 in R-state plus βPhe71 and βTyr145 adopt conformations favorable to thiol access and SNO-Hb formation. In T-state, the SNO group is surface-exposed and destabilized to extrude NO. Thus, its structure, dynamics and conserved reactive thiol (βCys93) suggest that the β-subunit evolved to synergize [Formula: see text] and nitrovasoactivity delivery to tissues as a function of Hb [Formula: see text] saturation.
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) | 0.001 | 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".