Lipoproteins are an important bacterial component responsible for bone destruction through the induction of osteoclast differentiation and activation
Bibliographic record
Abstract
Bacterial infection can cause inflammatory bone diseases accompanied by the bone destruction resulting from excess generation of osteoclasts. Although lipoproteins are one of the major immunostimulating components of bacteria, little is known about their effects on bone metabolism. In this study, we investigated the role of lipoproteins in bacteria-induced bone destruction using Staphylococcus aureus wild type, its lipoprotein-deficient mutant, and synthetic lipopeptides Pam2CSK4 and Pam3CSK4 known to mimic bacterial lipoproteins. Formaldehyde-inactivated S. aureus or the synthetic lipopeptides induced severe bone loss in the femurs of mice after intraperitoneal administration and in a calvarial bone implantation model, whereas the lipoprotein-deficient S. aureus did not show such effects. Mechanism studies further identified three action mechanisms for the lipopeptide-induced osteoclast differentiation and bone resorption via (i) enhancement of osteoclast differentiation through Toll-like receptor 2 and MyD88-dependent signaling pathways; (ii) induction of pro-inflammatory cytokines, TNF-α and IL-6; and (iii) upregulation of RANKL expression with downregulation of osteoprotegerin expression in osteoblasts. Taken together, these results suggest that lipoprotein might be an important bacterial component responsible for bone destruction during bacterial infections through augmentation of osteoclast differentiation and activation.
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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) | 0.000 | 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) | 0.000 | 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".