Hyperosmolar expansion medium improves nucleus pulposus cell phenotype
Bibliographic record
Abstract
Background: Repopulating the degenerated intervertebral disc (IVD) with tissue-specific nucleus pulposus cells (NPCs) has already been shown to promote regeneration in various species. Yet the applicability of NPCs as cell-based therapy has been hampered by the low cell numbers that can be extracted from donor IVDs and their potentially limited regenerative capacity due to their degenerated phenotype. To optimize the expansion conditions, we investigated the effects of increasing culture medium osmolarity during expansion on the phenotype of dog NPCs and their ability to produce a healthy extracellular matrix (ECM) in a 3D culture model. Methods: Dog NPCs were expanded in expansion medium with a standard osmolarity of 300 mOsm/L or adjusted to 400 or 500 mOsm/L in both normoxic and hypoxic conditions. Following expansion, NPCs were cultured in a 3D culture model in chondrogenic culture medium with a standard osmolarity. Read-out parameters included cell proliferaton rate, morphology, phenotype and healthy ECM production. Results: ) and protein (ACAN, PAX1, CD24, TEK, CD73) level. The NPCs expanded at 500 mOsm/L were able to retain most of their phenotypic markers and produce healthy ECM during 3D culture independent of the oxygen level used during expansion. Conclusions: Altogether, our findings show that increasing medium osmolarity during expansion results in an NPC population with improved phenotype, which could enhance the potential of cell-based therapies for IVD regeneration.
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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) | 0.001 | 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".