Best Paper NASS 2013: Link-N can stimulate proteoglycan synthesis in the degenerated human intervertebral discs
Bibliographic record
Abstract
Intervertebral disc (IVD) degeneration is the most common cause of back pain. Presently there is no medical treatment, leaving surgery as the only offered option. Here we evaluate the potential of Link-N to promote extracellular matrix regeneration in human IVDs. Human disc cells cultured in alginate and intact human discs were exposed to a combination of Link-N and ³⁵SO₄ in the presence or absence of interleukin (IL)-1, and the effect on proteoglycan synthesis was evaluated. In addition, message levels of aggrecan, matrix metalloproteinase (MMP)-3, MMP-13, a Disintegrin And Metalloproteinase with Thrombospondin Motifs (ADAMTS)-4 and ADAMTS-5 were evaluated in alginate cultures. Human disc cells responded in a dose dependent manner with maximal proteoglycan synthesis at 1 µg/mL Link-N. Link-N treatment also induced proteoglycan synthesis in intact human discs, and a prolonged effect was found up to one week after Link-N treatment. Message levels of proteinases were decreased by Link-N in the presence of IL-1. Thus, Link-N can promote proteoglycan synthesis and deplete proteinase expression in adult human discs. Link-N could therefore be a promising candidate for biologically-induced disc repair, and could provide an alternative to surgical intervention for early stage disc degeneration.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.045 | 0.009 |
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".