The Capacity of Porphyromonas gingivalis to Multiply Under Iron-limiting Conditions Correlates with its Pathogenicity in an Animal Model
Bibliographic record
Abstract
Isolates of Porphyromonas gingivalis have various abilities to induce infections in an animal model. The hypothesis of this study was that pathogenic strains of P. gingivalis could multiply under iron-limiting conditions, while non-pathogenic strains could not. Three pathogenic strains (W50, W83, and ATCC 49417) grew to a final optical density (660 nm) > 2 in horse serum, while the growth of the 3 non-pathogenic strains (ATCC 33277, LB13D-2, and HW24D-1) was negligible. When an excess of hemin or ferric chloride was added to the serum, significant growth of the non-pathogenic strains occurred. Under iron-limiting conditions, the pathogenic strains of P. gingivalis had a much lower requirement for human iron-loaded transferrin and hemin than the non-pathogenic strains. Proteolytic degradation of transferrin, which may be associated with the release of iron, was not markedly different for pathogenic and non-pathogenic strains. In addition, no relationship could be established between the level of 55Fe uptake from 55Fe-transferrin and the pathogenicity of strains. Our study provided evidence that the ability of P. gingivalis to multiply in vitro under iron-limiting conditions may be correlated with its ability to induce infections in an animal model. Isolates of P. gingivalis possessing a low requirement for iron are likely to have a higher potential for initiating periodontal infections.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".