Impaired Intervertebral Disc Development and Premature Disc Degeneration in Mice With Notochord‐Specific Deletion of CCN2
Bibliographic record
Abstract
OBJECTIVE: Currently, our ability to treat intervertebral disc (IVD) degeneration is hampered by an incomplete understanding of disc development and aging. The specific function of matricellular proteins, including CCN2, during these processes remains an enigma. The aim of this study was to determine the tissue-specific localization of CCN proteins and to characterize their role in IVD tissues during embryonic development and age-related degeneration by using a mouse model of notochord-specific CCN2 deletion. METHODS: Expression of CCN proteins was assessed in IVD tissues from wild-type mice beginning on embryonic day 15.5 to 17 months of age. Given the enrichment of CCN2 in notochord-derived tissues, we generated notochord-specific CCN2-null mice to assess the impact on the IVD structure and extracellular matrix composition. Using a combination of histologic evaluation and magnetic resonance imaging (MRI), IVD health was assessed. RESULTS: Loss of the CCN2 gene in notochord-derived cells disrupted the formation of IVDs in embryonic and newborn mice, resulting in decreased levels of aggrecan and type II collagen and concomitantly increased levels of type I collagen within the nucleus pulposus. CCN2-knockout mice also had altered expression of CCN1 (Cyr61) and CCN3 (Nov). Mirroring its role during early development, notochord-specific CCN2 deletion accelerated age-associated degeneration of IVDs. CONCLUSION: Using a notochord-specific gene targeting strategy, this study demonstrates that CCN2 expression by nucleus pulposus cells is essential to the regulation of IVD development and age-associated tissue maintenance. The ability of CCN2 to regulate the composition of the intervertebral disc suggests that it may represent an intriguing clinical target for the treatment of 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".