Glucose‐based optimization of CHO‐cell perfusion cultures
Why this work is in the frame
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Bibliographic record
Abstract
Perfusion cultures of CHO cells producing t-PA were performed using acoustic filter cell retention. A robust off-line glucose analysis and predictive control protocol was developed to maintain the process within approximately 0.5 mM of the glucose set point, without the need for a more fallible on-line sensor. Glucose usage (the difference between the inlet and reactor glucose concentrations) provided an easily measured indicator of overall medium utilization for mapping acceptable ranges of operation, including the edge of failure. Earlier onset of perfusion with a ramping glucose set point (1.5 mM/d) resulted in improved growth and consistency during the perfusion culture start-up. At steady state, the t-PA concentration variability increased gradually with increasing glucose usage up to approximately 22 mM, then up to 24 mM the variability increased threefold. Peak t-PA concentrations of over 90 mg/L were obtained by controlling at a glucose usage of approximately 24 mM, but these t-PA levels were not sustainable for more than 3 days. A consistent t-PA concentration of 40 mg/L was obtained at a glucose usage of 21.5 mM.
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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 | 0.000 |
| 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 | 0.000 |
| 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