Evidence That Peroxynitrite Affects Human Osteoblast Proliferation and Differentiation
Bibliographic record
Abstract
Peroxynitrite (PN), a nitric oxide (NO*)-derived anion, has been associated with NO* damage in various cell types. We examined the effects of adding PN to cultured human osteoblast-like (hOB) cells obtained after hip arthroplasty. Exposure to PN (0.1-0.4 mM) decreased both hOB proliferation and differentiation, measured by [3H]thymidine uptake and alkaline phosphatase production, respectively. Incubation with 3-morpholinosydnonimine (SIN-1; 0.25-1 mM), an NO* and O2- donor that leads to PN release, also reduced both hOB proliferation and differentiation. Coincubation with both superoxide dismutase (SOD; 100 U/ml) and catalase (CAT; 50 U/ml), rendering SIN-1 a pure NO* donor, reversed its effects on hOB proliferation and differentiation. However, SIN-1-induced NO* production, measured by nitrite release to the hOB medium, was not altered by cotreatment with SOD and CAT. Expression of nitrotyrosine by hOB, a marker of PN action, was significantly increased after SIN-1 addition, as compared with untreated cells, as revealed by Western blot analysis. Interleukin-1alpha (IL-1alpha) and interferon gamma (IFN-gamma) but not tumor necrosis factor alpha (TNF-alpha) also significantly increased nitrotyrosine expression in these cells. These data show that PN is at least partially responsible for osteoblast derangement by NO* and that cytokines released during inflammatory arthropathies can induce PN production in hOB cells.
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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".