Induced senescence of healthy nucleus pulposus cells is mediated by paracrine signaling from TNF‐α–activated cells
Bibliographic record
Abstract
Intervertebral disc degeneration is an irreversible process associated with accumulation of senescent nucleus pulposus (NP) cells. This study investigates the hypothesis that Tumor necrosis factor-α (TNF-α)-treated senescent NP cells propagate senescence of neighboring healthy cells via a paracrine effect that involves p-Stat3 signaling and the cytokine interleukin-6 (IL-6). NP cells isolated from bovine caudal intervertebral disc (IVD) were treated with TNF-α to induce senescence which was confirmed by demonstrating upregulation of senescence-associated β-galactosidase and p16. This was correlated with downregulation of NP-associated markers, Aggrecan, Col2A1, and Sox9. Direct contact and non-contact co-culture of healthy and senescent cells showed that TNF-α-treated cells increased the senescence in healthy cells via a paracrine effect. The senescent cells have a secretory phenotype as indicated by increased gene and protein levels of IL-6. Phosphorylated Signal Transducer and Activator of Transcription 3 (pStat3) levels were also high in treated cells and appeared to upregulate IL-6 as inhibition of Stat3 phosphorylation by StatticV downregulated IL-6 mRNA expression in cells and protein levels in the culture media. All trans retinoic acid, an IL-6 inhibitor, also decreased the secretion of IL-6 and reduced the paracrine effect of senescent cells on healthy cells. Decreased pStat3 levels and inhibition of IL-6 secretion did not fully restore NP gene expression of Col2A1 but importantly, appeared to cause senescent cells to undergo apoptosis and cell death. This study demonstrated the paracrine effect of senescent NP cells which involves Stat3 and IL-6 and may explain why senescent NP cells accumulate in IVD with age. The role of pSTAT3 and IL-6 in mediating NP senescence requires further study as it may be a novel strategy for modulating the senescent-inducing effects of TNF-α.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".