Cell sources proposed for nucleus pulposus regeneration
Bibliographic record
Abstract
Lower back pain (LBP) occurs in 80% of adults in their lifetime; resulting in LBP being one of the biggest causes of disability worldwide. Chronic LBP has been linked to the degeneration of the intervertebral disc (IVD). The current treatments for chronic back pain only provide alleviation of symptoms through pain relief, tissue removal, or spinal fusion; none of which target regenerating the degenerate IVD. As nucleus pulposus (NP) degeneration is thought to represent a key initiation site of IVD degeneration, cell therapy that specifically targets the restoration of the NP has been reviewed here. A literature search to quantitatively assess all cell types used in NP regeneration was undertaken. With key cell sources: NP cells; annulus fibrosus cells; notochordal cells; chondrocytes; bone marrow mesenchymal stromal cells; adipose-derived stromal cells; and induced pluripotent stem cells extensively analyzed for their regenerative potential of the NP. This review highlights: accessibility; expansion capability in vitro; cell survival in an IVD environment; regenerative potential; and safety for these key potential cell sources. In conclusion, while several potential cell sources have been proposed, iPSC may provide the most promising regenerative potential.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".