Mass Spectra and Ion Collision Cross Sections of Hemoglobin
Bibliographic record
Abstract
Mass spectra of commercially obtained hemoglobin (Hb) show higher levels of monomer and dimer ions, heme-deficient dimer ions, and apo-monomer ions than hemoglobin freshly prepared from blood. This has previously been attributed to oxidation of commercial Hb. Further, it has been reported that that dimer ions from commercial bovine Hb have lower collision cross sections than low charge state monomer ions. To investigate these effects further, we have recorded mass spectra of fresh human Hb, commercial human and bovine Hb, fresh human Hb oxidized with H(2)O(2), lyophilized fresh human Hb, fresh human Hb both lyophilized and chemically oxidized, and commercial human Hb oxidized with H(2)O(2). Masses of α-monomer ions of all hemoglobins agree with the masses expected from the sequences within 3 Da or better. Mass spectra of the β chains of commercial Hb and oxidized fresh human Hb show a peak or shoulder on the high mass side, consistent with oxidation of the protein. Both commercial proteins and oxidized fresh human Hb produce heme-deficient dimers with masses 32 Da greater than expected and higher levels of monomer and dimer ions than fresh Hb. Lyophilization or oxidation of Hb both produce higher levels of monomer and dimer ions in mass spectra. Fresh human Hb, commercial human Hb, commercial bovine Hb, and oxidized commercial human Hb all give dimer ions with cross sections greater than monomer ions. Thus, neither oxidation of Hb or the difference in sequence between human and bovine Hb make substantial differences to cross sections of ions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 0.001 |
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".