Limitations to the amplification and stability of human tissue-type plasminogen activator expression by Chinese hamster ovary cells
Bibliographic record
Abstract
Chinese hamster ovary cell production of recombinant tissue-type plasminogen activator (t-PA) was increased by amplification of cotransfected dihydrofolate reductase cDNA using stepwise adaptation to increasing methotrexate (MTX) concentrations. The highest producing clones were isolated at 5 microM MTX and yielded 26,000 U/10(6) cells/day t-PA (43 microgram/10(6) cells/day). Above 25 microM MTX, cell specific t-PA production rates became increasingly variable and the cDNA copynumbers decreased. No apparent correlation between the cell specific t-PA production rate and the growth rate was observed upon subcloning of the amplified cells. When MTX selection was removed, the t-PA production rate decreased up to tenfold within 40 days; this was accompanied by an up to 60% drop in cDNA copynumber. Subclones isolated after 108 days of culture in the absence of MTX were, on average, sixfold more stable than their parental cells. In culture without MTX, the maximum stable t-PA production rate obtained (over 250 days) was 7000 +/- 750 U/10(6) cells/day (approximately 12 microgram/10(6) cells/day), approximately threefold lower than the maximum unstable levels of production reached under selective pressure. Taken together, these results define a wide range of the highest t-PA expression rates obtained under MTX selection, for which stable expression without selection has not been reported.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".