Toll-like Receptor Activation Induces Degeneration of Human Intervertebral Discs
Bibliographic record
Abstract
Toll-like receptors (TLR) are activated by endogenous alarmins such as fragmented extracellular matrix compounds found in the degenerating disc. TLRs regulate cytokine, neurotrophin, and protease expression in human disc cells in vitro, and thus control key factors in disc degeneration. However, whether TLR activation leads to degenerative changes in intact human discs is unclear. Nucleus pulposus (NP) cells isolated from non-degenerating discs increase IL-1β and nerve growth factor gene expression following treatment with Pam2CSK4 (TLR2/6 agonist) but not Pam3CSK4 (TLR1/2 agonist). Challenging NP cells with Pam2CSK4 or 30 kDa fibronectin fragments (FN-f, an endogenous TLR2 and TLR4 alarmin) increased secretion of proinflammatory cytokines. We then investigated the effect of TLR activation in intact, non-degenerate, ex vivo human discs. Discs were injected with PBS, Pam2CSK4 and FN-f, and cultured for 28 days. TLR activation increased proteoglycan and ECM protein release into the culture media and decreased proteoglycan content in the NP. Proteases, including MMP3, 13 and HTRA1, are secreted at higher levels following TLR activation. In addition, proinflammatory cytokine levels, including IL-6, TNFα and IFNγ, increased following TLR activation. These results indicate that TLR activation induces degeneration in human discs. Therefore, TLRs are potential disease-modifying therapeutic targets to slow disc degeneration.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".