Spontaneous up‐regulation of SIRT1 during osteogenesis contributes to stem cells’ resistance to oxidative stress
Bibliographic record
Abstract
Abstract Osteogenic differentiation of bone marrow‐derived mesenchymal stem cells (BM‐MSCs) is a central event in bone formation. However, oxidative stress has a deleterious impact on BM‐MSC osteogenesis. In this study, we hypothesized that oxidative stress influenced BM‐MSC osteogenesis differently in the early or late stages, in which silent information regulator type 1 (SIRT1) played a critical role. A continuous exposure to sublethal concentrations of hydrogen peroxide (H2O2), ranging from 25 to 100 µM for 21 days, resulted in the complete inhibition of BM‐MSC osteogenesis. We found that a 7‐day treatment with H2O2 inhibited the lineage commitment of BM‐MSCs toward osteoblasts, as evidenced by a significant reduction of alkaline phosphatase activity (a typical marker for early osteogenesis). However, moderate oxidative stress did not affect late‐differentiated BM‐MSCs, as there were comparable levels of matrix mineralization (a typical marker for late osteogenesis). In addition, we observed a spontaneous up‐regulation of SIRT1 and intracellular antioxidant enzymes such as superoxide dismutase 2, catalase, and glutathione peroxidase 1, which accounted for the enhanced resistance to oxidative stress upon osteogenic differentiation. Activation of SIRT1 by resveratrol rescued the effect of H2O2 on early‐differentiated BM‐MSCs and inhibition of SIRT1 by nicotinamide intensified the effect of H2O2 on late‐differentiated BM‐MSCs, indicating that the SIRT1‐mediated pathway was actively involved in MSC osteogenesis and antioxidant mechanisms. Our findings uncovered the relationship between SIRT1 and resistance to H2O2‐induced oxidative stress during BM‐MSC osteogenesis, which could provide a new strategy for protecting MSCs from extracellular oxidative stress.
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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 | 0.001 |
| 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 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".