High mechanical strain of primary intervertebral disc cells promotes secretion of inflammatory factors associated with disc degeneration and pain
Bibliographic record
Abstract
INTRODUCTION: Excessive mechanical loading of intervertebral discs (IVDs) is thought to alter matrix properties and influence disc cell metabolism, contributing to degenerative disc disease and development of discogenic pain. However, little is known about how mechanical strain induces these changes. This study investigated the cellular and molecular changes as well as which inflammatory receptors and cytokines were upregulated in human intervertebral disc cells exposed to high mechanical strain (HMS) at low frequency. The impact of these metabolic changes on neuronal differentiation was also explored to determine a role in the development of disc degeneration and discogenic pain. METHODS: Isolated human annulus fibrosus (AF) and nucleus pulposus (NP) cells were exposed to HMS (20% cyclical stretch at 0.001 Hz) on high-extension silicone rubber dishes coupled to a mechanical stretching apparatus and compared to static control cultures. Gene expression of Toll-like receptors (TLRs), neuronal growth factor (NGF) and tumour necrosis factor α (TNFα) was assessed. Collected conditioned media were analysed for cytokine content and applied to rat pheocromocytoma PC12 cells for neuronal differentiation assessment. RESULTS: HMS caused upregulation of TLR2, TLR4, NGF and TNFα gene expression in IVD cells. Medium from HMS cultures contained elevated levels of growth-related oncogene, interleukin 6 (IL-6), IL-8, IL-15, monocyte chemoattractant protein 1 (MCP-1), MCP-3, monokine induced by γ interferon, transforming growth factor β1, TNFα and NGF. Exposure of PC12 cells to HMS-conditioned media resulted in both increased neurite sprouting and cell death. CONCLUSIONS: HMS culture of IVD cells in vitro drives cytokine and inflammatory responses associated with degenerative disc disease and low-back pain. This study provides evidence for a direct link between cellular strain, secretory factors, neoinnervation and potential degeneration and discogenic pain in vivo.
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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) | 0.002 | 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".