Control of dissolved oxygen significantly increases the yield of skin‐derived Schwann cells during expansion in stirred suspension bioreactors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Peripheral nerve and spinal cord injuries affect millions of people worldwide often leading to lifelong disability and pain. Cell therapy using autologous Schwann cells are currently being investigated for the treatment of these injuries and are showing great potential. In particular, skin‐derived Schwann cells offer a non‐invasive option for highly therapeutic cells that have been shown to regenerate tissue and restore function. However, it is estimated that for an effective therapy, hundreds of millions of Schwann cells are needed, and current static and spinner flask methods cannot generate these clinical numbers. Therefore, this study utilizes control systems facilitated by stirred suspension bioreactors to monitor and maintain the pH and dissolved oxygen at levels that promote cell proliferation and survival. By adapting the current culture practices to scalable bioreactor platforms, we were able to control the dissolved oxygen creating new expansion protocols that enabled the bioreactor process to grow to clinical scale, producing 667 × 10 6 cells in a single 500 mL bioreactor in 7 days. Since individual injury is different in terms of complexity and severity, and therefore cell needs, by changing the available surface area in the bioreactor, this developed process is highly adjustable to meet the cell quantity needs for each individual treatment. Following the bioprocess, cells that were harvested from the microcarriers continue to express typical Schwann cell markers suggesting that they retain phenotypic stability. By increasing the production potential of skin‐derived Schwann cells, this therapy is one step closer to the clinic with the hope for ultimately restoring function and improving quality of life to patients with neural injuries.
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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 | 0.001 |
| 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 it