A novel alginate hollow fiber bioreactor process for cellular therapy applications
Bibliographic record
Abstract
Gel-matrix culture environments provide tissue engineering scaffolds and cues that guide cell differentiation. For many cellular therapy applications such as for the production of islet-like clusters to treat Type 1 diabetes, the need for large-scale production can be anticipated. The throughput of the commonly used nozzle-based devices for cell encapsulation is limited by the rate of droplet formation to approximately 0.5 L/h. This work describes a novel process for larger-scale batch immobilization of mammalian cells in alginate-filled hollow fiber bioreactors (AHFBRs). A methodology was developed whereby (1) alginate obstruction of the intra-capillary space medium flow was negligible, (2) extra-capillary alginate gelling was complete and (3) 83 +/- 4% of the cells seeded and immobilized were recovered from the bioreactor. Chinese hamster ovary (CHO) cells were used as a model aggregate-forming cell line that grew from mostly single cells to pancreatic islet-sized spheroids in 8 days of AHFBR culture. CHO cell growth and metabolic rates in the AHFBR were comparable to small-scale alginate slab controls. Then, the process was applied successfully to the culture of primary neonatal pancreatic porcine cells, without significant differences in cell viability compared with slab controls. As expected, alginate-immobilized culture in the AHFBR increased the insulin content of these cells compared with suspension culture. The AHFBR process could be refined by adding matrix components or adapted to other reversible gels and cell types, providing a practical means for gel-matrix assisted cultures for cellular therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".