Modeling Process-Induced Cell Damage in the Biodispensing Process
Bibliographic record
Abstract
Emerging biomanufacturing processes involve incorporation of living cells into various processes and systems by employing different cell manipulation techniques. Among them, biodispensing, in which the cell suspension is extruded via a fine needle under pressurized air, is a promising technique because of its high efficiency. Cells in this process are continually subjected to mechanical forces and may be damaged if the force or manipulation time exceeds certain levels. Modeling cell injury incurred in these processes is lacking in the literature. This article presents a method to quantify the force-induced cell damage in the biodispensing process. This method consists of two steps: first is to establish cell damage laws to relate cell damage to hydrostatic pressure/shear stress; and the second is to represent the process-induced forces experienced by cells during the biodispensing process and apply the established cell damage law to represent the percentage of cell damage. Schwann cells and 3T3 fibroblasts were used to validate the model and the comparisons of experimental and simulation results show the effectiveness of the method presented in this article.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".