Increased t-PA Yields Using Ultrafiltration of an Inhibitory Product from CHO Fed-Batch Culture
Bibliographic record
Abstract
Fed-batch operation for the production of t-PA using Chinese Hamster Ovary (CHO) cells was optimized using serial and parallel experimentation. The feed, an isotonic concentrate, was improved to obtain 2- to 2.5-fold increases in integrated viable cell days versus batch. With a low glucose inoculum train, the viability index was further increased up to 4.5-fold. Hydrolysates were substituted for the amino acid portion of the concentrate with no significant change in fed-batch results. The concentrate addition rate was based on a constant 4 pmol/cell.day glucose uptake rate that maintained a relatively constant glucose concentration (approximately 3 mM). Increased viable cell indices did not lead to concomitant increases in t-PA concentrations compared to batch. The fed-batch concentrate and feeding strategy were shown to be effective in hybridoma culture, where a 4-fold increase in viable cell index yielded a 4-fold increase in antibody concentration. The half-life of t-PA decreased from 43 to 15 days with decreasing cell viability (from 92% to 71%), but this was not sufficient to explain the apparent t-PA threshold. Instead, the CHO results were explained by a reduction in t-PA production at higher extracellular t-PA concentrations that limited the fed-batch maximum at 35 mg/L for the cell line investigated. Analysis of both the total and t-PA mRNA levels revealed no response to increasing extracellular t-PA concentrations upon exogenous additions. Instead, intracellular t-PA levels were increased, revealing a possible secretory pathway limitation. A new reactor configuration was developed using an acoustic filter to retain the cells in the reactor while an ultrafiltration module stripped t-PA from the clarified medium before the permeate was returned to the reactor. By adding this harvesting step, the t-PA fed-batch production was increased over 2-fold, up to a yield of 80 mg/L.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".