Metal Ions and Electrolytes Regulate the Dissociation of Heme from Human Hemopexin at Physiological pH
Bibliographic record
Abstract
The stability of the hemopexin-heme (Hx-heme) complex to dissociation of the heme prosthetic group has been examined in bicarbonate buffers in the presence and absence of various divalent metal ions. In NH(4)HCO(3) buffer (pH 7.4, 20 mm, 25 degrees C) containing Zn(2+) (100 microm), 14% of the heme dissociates from this complex (4.5 microm) within 10 min, and 50% dissociates within 2 h. In the absence of metal ions, the rate of dissociation of this complex is far lower, is decreased further in KHCO(3) solution, and is minimal in NaHCO(3). In NH(4)HCO(3) buffer, dissociation of the Hx-heme complex is accelerated by addition of divalent metals with decreasing efficiency in the order Zn(2+) > Cu(2+) >> Ni(2+) > Co(2+)>>Mn(2+). Addition of Ca(2+) prior to addition of Zn(2+) stabilizes the Hx-heme complex to dissociation of the heme group, and addition of Ca(2+) after Zn(2+)-induced dissociation of the Hx-heme complex results in re-formation of the Hx-heme complex. These effects are greatly accelerated at 37 degrees C and diminished in other buffers. Overall, the solution conditions that promote formation of the Hx-heme complex are similar to those found in blood plasma, and conditions that promote release of heme are similar to those that the Hx-heme complex should encounter in endosomes following endocytosis of the complex formed with its hepatic receptor.
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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 | 0.000 | 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) | 0.000 | 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 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".