Bibliographic record
Abstract
Hemoglobin (Hb) (α(2)β(2)) is a tetrameric protein-protein complex. Collision cross sections, hydrogen exchange levels, and tandem mass spectrometry have been used to investigate the properties of gas-phase monomer, dimer, and tetramer ions of adult human hemoglobin (Hb A, α(2)β(2)), and two variant hemoglobins: fetal hemoglobin (Hb F, α(2)γ(2)) and sickle hemoglobin (Hb S, α(2)β(2), E6V[β]). All three proteins give similar mass spectra. Monomers of Hb S and Hb F have similar cross sections, ca. 10% greater than those of Hb A. Cross sections of dimer ions of Hb S are 11% greater than those of Hb A and 6% greater than those of Hb F. Tetramers of Hb S are 13% larger than tetramers of Hb A or Hb F. Monomers and dimers of all three Hb have similar hydrogen-deuterium exchange (HDX) levels. Tetramers of Hb S exchange 16% more hydrogens than Hb A and Hb F. In tandem mass spectrometry, monomers of Hb S and Hb F require ca. 10% greater internal energy for heme loss than Hb A. Dimers (+11) of Hb A and Hb S dissociate to monomers with asymmetrical charge division; dimers of Hb F (+11) dissociate with nearly equal charge division. Tetramer ions dissociate to monomers and trimers, unlike solution Hb, which dissociates to dimers. The most stable dimers are from Hb S; the most stable tetramers from Hb F. The results with Hb S show that a single mutation in the β chain can change the physical properties of this gas-phase protein-protein complex.
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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 | 0.001 | 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) | 0.002 | 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".