Production of transferrin receptors by<i>Histophilus ovis</i>: three of five strains require two signals
Bibliographic record
Abstract
Five strains of Histophilus ovis (9L, 642A, 714, 5688T, and 3384Y) were investigated with respect to iron acquisition. All strains used ovine, bovine, and goat transferrins (Tfs), but not porcine or human Tfs, as iron sources for growth. In solid phase binding assays, total membranes from only two (9L and 642A) of the five strains, grown under iron-restricted conditions, were able to bind Tfs (ovine, bovine, and goat, but not porcine or human). However, when the organisms were grown under iron-restricted conditions in the presence of bovine transferrin (Tf), total membranes from all strains exhibited Tf binding (as above); competition experiments demonstrated that all three Tfs (ovine, bovine, and goat) were bound by the same receptor(s). Membranes from organisms grown under iron-replete conditions in the presence or absence of bovine Tf failed to bind any of the test Tfs. An affinity-isolation procedure allowed the isolation of two putative Tf-binding polypeptides (78 and 66 kDa) from total membranes of strains 9L and 642A grown under iron-restricted conditions, and from membranes of all strains if the growth medium also contained Tf. It is concluded that all strains tested acquire Tf-bound iron by means of siderophore-independent mechanisms involving surface receptors analogous to the Tf-binding proteins (TbpA and TbpB) found in comparable organisms; although iron restriction alone is sufficient to promote the expression of these proteins by strains 9L and 642A, their production by strains 714, 5688T, and 3384Y appears to require two signals, iron restriction and the presence of Tf.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".