Mechanisms of oral bacteria-induced platelet activation
Bibliographic record
Abstract
The oral cavity is inhabited by over 500 different bacterial species that normally exist in ecological balance both with each other and with the host. When this equilibrium is disturbed, an overgrowth of individual organisms can occur, which, in turn, can lead to the onset of pathological processes, notably dental caries and periodontitis. Generally, bacteraemias occur more frequently in individuals with periodontal disease, and these bacteraemias have been implicated in the development of a range of systemic diseases, including atherothrombotic disorders. The mechanism underlying this relationship remains to be precisely defined, although studies have shown a link between bacteria of oral origin and platelet activation. Several orally derived species of bacteria interact with platelets, including those of the Streptococcus (Streptococcus sanguinis, Streptococcus mutans, Streptococcus agalactiae, Streptococcus pyogenes, Streptococcus gordonii, Streptococcus pneumoniae, Streptococcus mitis) and Staphylococcus (Staphylococcus epidermidis, Staphylococcus capitis) genera, as well as Pseudomonas aeruginosa and Porphyromonas gingivalis. In addition, some members of both the Streptococcus and the Staphylococcus genera, as well as Porphyromonas gingivalis, can activate platelets in vitro. The current review describes the heterogeneous mechanisms of platelet activation employed by individual bacterial species. The pathological and clinical implications of platelet activation by orally derived bacteria are discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".