<i>Porphyromonas gingivalis</i> lipopolysaccharide activates platelet Cdc42 and promotes platelet spreading and thrombosis
Bibliographic record
Abstract
BACKGROUND: Periodontitis confers an increased risk for cardiovascular diseases, including thrombosis. However, the molecular mechanisms that potentially link periodontitis with thrombosis are undefined. Here we test the hypothesis that Gram-negative periodontal infection promotes pathological platelet activation and amplifies shape change. We focus specifically on lipopolysaccharide (LPS) signaling to platelets. METHODS: Platelets were isolated from blood samples and allowed to spread on coverslips in the presence or absence of LPS purified from the periodontal pathogen Porphyromonas gingivalis. Platelets were fixed and stained with Alexa-488-phalloidin to label the actin cytoskeleton. The degree of platelet spreading and shape change was quantified by confocal microscopy. In a translational pilot study, blood samples were obtained from human subjects exhibiting generalized severe periodontitis (SP) or healthy periodontium (HP). Rotational thromboelastometry was used to quantify the rate of clot formation via the intrinsic coagulation pathway. RESULTS: LPS-treated platelets exhibited significantly (P < 0.05) greater spreading and higher numbers of actin-rich filopodia (cell extensions) than controls. We also found that LPS stimulation of platelets promoted the activation of Cdc42, the small GTPase responsible for filopodia formation. Exposure of whole blood samples to LPS significantly (P < 0.05) reduced clotting times. Blood from SP patients clotted significantly (P < 0.05) more rapidly and exhibited shorter partial thromboplastin times compared with HP controls. CONCLUSIONS: This is the first study to suggest a mechanism by which LPS stimulation drives Cdc42 activation and platelet spreading. These data are consistent with the notion that periodontitis promotes accelerated clot formation and an increased risk of thrombosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".