The bacterial receptor protein, transferrin-binding protein B, does not independently facilitate the release of metal ion from human transferrin
Bibliographic record
Abstract
Pathogenic Gram-negative bacteria of the Pasteurellaceae and Neisseriaceae acquire iron for growth from host transferrin through the action of specific surface receptors. Iron is removed from transferrin by the receptor at the cell surface and is transported across the outer membrane to the periplasm. A periplasmic binding protein-dependent pathway subsequently transports iron into the cell. The transferrin receptor is composed of a largely surface-exposed lipoprotein, transferrin binding protein B, and a TonB-dependent integral outer membrane protein, transferrin binding protein A. To examine the role of transferrin binding protein B in the iron removal process, complexes of recombinant transferrin binding protein B and transferrin were prepared and compared with transferrin in metal-binding and -removal experiments. A polyhistidine-tagged form of recombinant transferrin binding protein B was able to purify a complex with transferrin that was largely monodisperse by dynamic light scattering analysis. Gallium was used instead of iron in the metal-binding studies, since it resulted in increased stability of recombinant transferrin binding protein B in the complex. Difference absorption spectra were used to monitor removal of gallium by nitrilotriacetic acid. Kinetic and equilibrium binding studies indicated that transferrin binds gallium more tightly in the presence of transferrin binding protein B. Thus, transferrin binding protein B does not facilitate metal ion removal and additional components are required for this process.
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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) | 0.001 | 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".