Osteoblasts Are Rapidly Ablated by Virus-Induced Systemic Inflammation following Lymphocytic Choriomeningitis Virus or Pneumonia Virus of Mice Infection in Mice
Bibliographic record
Abstract
Abstract A link between inflammatory disease and bone loss is now recognized. However, limited data exist on the impact of virus infection on bone loss and regeneration. Bone loss results from an imbalance in remodeling, the physiological process whereby the skeleton undergoes continual cycles of formation and resorption. The specific molecular and cellular mechanisms linking virus-induced inflammation to bone loss remain unclear. In the current study, we provide evidence that infection of mice with either lymphocytic choriomeningitis virus (LCMV) or pneumonia virus of mice (PVM) resulted in rapid and substantial loss of osteoblasts from the bone surface. Osteoblast ablation was associated with elevated levels of circulating inflammatory cytokines, including TNF-α, IFN-γ, IL-6, and CCL2. Both LCMV and PVM infections resulted in reduced osteoblast-specific gene expression in bone, loss of osteoblasts, and reduced serum markers of bone formation, including osteocalcin and procollagen type 1 N propeptide. Infection of Rag-1–deficient mice (which lack adaptive immune cells) or specific depletion of CD8+ T lymphocytes limited osteoblast loss associated with LCMV infection. By contrast, CD8+ T cell depletion had no apparent impact on osteoblast ablation in association with PVM infection. In summary, our data demonstrate dramatic loss of osteoblasts in response to virus infection and associated systemic inflammation. Further, the inflammatory mechanisms mediating viral infection-induced bone loss depend on the specific inflammatory condition.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".