<i>Porphyromonas gingivalis</i> Vesicles Enhance Attachment, and the Leucine-Rich Repeat BspA Protein Is Required for Invasion of Epithelial Cells by “ <i>Tannerella forsythia</i> ”
Bibliographic record
Abstract
The human oral cavity harbors more than 500 species of bacteria. Periodontitis, a bacterially induced inflammatory disease that leads to tooth loss, is believed to result from infection by a select group of gram-negative periodontopathogens that includes Porphyromonas gingivalis, Treponema denticola, and "Tannerella forsythia" (opinion on name change from Tannerella forsythensis pending; formerly Bacteroides forsythus). Epithelial cell invasion by periodontopathogens is considered to be an important virulence mechanism for evasion of the host defense responses. Further, the epithelial cells with invading bacteria also serve as reservoirs important in recurrent infections. The present study was therefore undertaken to address the epithelial cell adherence and invasion properties of T. forsythia and the role of the cell surface-associated protein BspA in these processes. Further, we were interested in determining if P. gingivalis, one of the pathogens frequently found associated in disease, or its outer membrane vesicles (OMVs) could modulate the epithelial cell adherence and invasion abilities of T. forsythia. Here we show that epithelial cell attachment and invasion by T. forsythia are dependent on the BspA protein. In addition, P. gingivalis or its OMVs enhance the attachment and invasion of T. forsythia to epithelial cells. Thus, interactions between these two bacteria may play important roles in virulence by promoting host cell attachment and invasion.
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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".