Cobalt ions induce a cellular senescence secretory phenotype in human synovial fibroblast-like cells that may be an early event in the development of adverse local tissue reactions to hip implants
Bibliographic record
Abstract
Objectives: Total hip arthroplasty is a successful procedure for treating advanced osteoarthritis (OA). Metal bearing surfaces remain one of the most widely implanted prosthesis, however approximately 10% of patients develop adverse local tissue reactions (ALTRs), namely lymphocytic predominant soft tissue reaction with or without necrosis and osteolysis resulting in high revision rates. The mechanism(s) for these reactions remains unclear although T lymphocyte mediated type IV hypersensitivity to cobalt (Co) and chromium (Cr) ions have been described. The purpose of this study was to determine the prolonged effects of Co and Cr metal ions on synovial fibroblasts to better understand the impact of the synovial membrane in the development of ALTRs. Methods: Human synovial fibroblast-like cells were isolated from donors undergoing arthroplasty. DNA content and Alamar blue assay were used to determine cellular viability against exposure to Co and Cr. A beta-galactosidase assay was used to determine the development of cellular senescence. Western blotting and RT-qPCR were employed to determine changes in senescent associated secretory factors, signaling and anti-oxidant enzyme expression. A fluorescent assay was used to measure accumulation of hydrogen peroxide. Results: We demonstrate that prolonged cobalt exposure results in a downregulation of the enzyme catalase resulting in cytosolic accumulation of hydrogen peroxide, decreased Akt activity and cellular senescence. Senescent fibroblasts demonstrated upregulation of proinflammatory cytokines IL-1β and TNFα in addition to the neurotrophic factor NGF. Conclusion: Our results provide evidence that metal ions induce a senescent associated secretory phenotype in synovial fibroblasts that could contribute to the development of adverse local tissue reactions.
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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".