Scaled‐up production of mammalian neural precursor cell aggregates in computer‐controlled suspension bioreactors
Bibliographic record
Abstract
The clinical use of neural precursor cells (NPCs) for the treatment of neurological diseases, such as Parkinson's disease and Huntington's disease, requires overcoming the scarcity of these cells through controlled expansion. The main objective of the present study was to develop a large-scale computer-controlled bioprocess for the expansion of mammalian NPCs in suspension culture by scaling up existing reactor protocols. In order to support the oxygen demands of the maximum cell densities achieved, the volumetric mass transfer coefficient was kept above 1.10/h while scaling-up from small-scale 125 mL vessels to large-scale 500 mL bioreactors. In addition, the maximum shear stress at the impeller tip was maintained between 0.30 and 0.75 Pa to reduce damage to the cells. The resulting large-scale bioprocess achieved maximum viable cell densities of 1.2 x 10(6) cells/mL and a batch multiplication ratio of 9.1. Moreover, the process successfully maintained the NPC characteristics observed in small-scale studies.
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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 | 0.001 |
| 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".