Priming and cryopreservation of microencapsulated marrow stromal cells as a strategy for intervertebral disc regeneration
Bibliographic record
Abstract
A challenge in using stromal cells for intervertebral disc (IVD) regeneration is their limited differentiation capacity in vivo without exogenous growth factor (GF) supplementation. Priming of stromal cells prior to transplantation may offer a feasible strategy to overcome this limitation. Furthermore, the ability to cryopreserve cells could help alleviate logistical issues associated with storage and transport. With these critical translational challenges in mind, we aimed to develop a strategy involving priming and subsequent cryopreservation of microencapsulated bone marrow stromal cells (BMSCs). In phase one, we utilised the electrohydrodynamic atomisation process to fabricate BMSC-encapsulated microcapsules that were primed with TGF-β3 for 14 d after which they were cultured for a further 21 d under basal or GF supplemented media conditions. Results showed that priming induced differentiation of BMSC microcapsules such that they synthesised significant amounts of sGAG (61.9 ± 2.0 μg and 55.3 ± 6.1 μg for low and high cell densities) and collagen (24.4 ± 1.9 μg and 55.3 ± 4.6 μg for low and high cell densities) in continued culture without GF supplementation compared to Unprimed microcapsules. Phase two of this work assessed the extracellular matrix forming capacity of Primed BMSC microcapsules over 21 d after cryopreservation. Notably, primed and cryopreserved BMSCs successfully retained the ability to synthesise both sGAG (24.8 ± 2.7 μg and 75.1 ± 11.6 μg for low and high cell densities) and collagen (26.4 ± 7.8 μg and 93.1 ± 10.2 μg for low and high cell densities) post-cryopreservation. These findings demonstrate the significant potential of priming and cryopreservation approaches for IVD repair and could possibly open new horizons for pre-designed, 'off-the-shelf' injectable therapeutics.
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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".