Fibrinogen-Induced<i>Streptococcus mutans</i>Biofilm Formation and Adherence to Endothelial Cells
Bibliographic record
Abstract
Streptococcus mutans, the predominant bacterial species associated with dental caries, can enter the bloodstream and cause infective endocarditis. The aim of this study was to investigate S. mutans biofilm formation and adherence to endothelial cells induced by human fibrinogen. The putative mechanism by which biofilm formation is induced as well as the impact of fibrinogen on S. mutans resistance to penicillin was also evaluated. Bovine plasma dose dependently induced biofilm formation by S. mutans. Of the various plasma proteins tested, only fibrinogen promoted the formation of biofilm in a dose-dependent manner. Scanning electron microscopy observations revealed the presence of complex aggregates of bacterial cells firmly attached to the polystyrene support. S. mutans in biofilms induced by the presence of fibrinogen was markedly resistant to the bactericidal effect of penicillin. Fibrinogen also significantly increased the adherence of S. mutans to endothelial cells. Neither S. mutans cells nor culture supernatants converted fibrinogen into fibrin. However, fibrinogen is specifically bound to the cell surface of S. mutans and may act as a bridging molecule to mediate biofilm formation. In conclusion, our study identified a new mechanism promoting S. mutans biofilm formation and adherence to endothelial cells which may contribute to infective endocarditis.
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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) | 0.000 | 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 | 0.000 |
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".