Development of a Perfusion Reactor for Intervertebral Disk Regeneration
Bibliographic record
Abstract
A tissue-engineered biological disk replacement has been proposed as a promising approach for the treatment of degenerative disk disease. A perfusion bioreactor would be a logical consideration to facilitate this scale-up as such reactors have been shown to improve nutrient delivery and provide beneficial mechanical forces that support the cultivation of large three-dimensional constructs. It was hypothesized that perfusion culture of tissue-engineered intervertebral disk (IVD) tissues would be capable of generating outer annulus fibrosus (oAF) and nucleus pulposus (NP) tissues comparable with established spinner reactor or static cultures, respectively, without compromising cellular viability, nutrient delivery, and tissue formation. In this study, the perfusion grown oAF and NP tissues did not show a significant difference in extracellular matrix (ECM) quantity or cellular phenotype when compared with their control conditions. In addition, they maintained cellular viability at the center core of the tissues and received enhanced diffusion of medium throughout the tissue when compared with static conditions. This study lays the groundwork for future studies to grow an entire IVD tissue to a physiologically relevant size. Degenerative disk disease is associated with back pain and loss of disk function. Bioengineering a replacement intervertebral disk (IVD) is a promising solution, and a perfusion bioreactor may offer the necessary culture conditions to support formation of such tissues. This study demonstrated that in vitro generated components of the disk, the nucleus fibrosus, and annulus fibrosus, grown in perfusion culture, yielded promising improvements to nutrient delivery and cellular viability. This outcome lays the groundwork for constructing IVD constructs that are closer to physiological size and composition, leading us closer to bioengineering a fully functional disk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".