Estimating cell specific oxygen uptake and carbon dioxide production rates for mammalian cells in perfusion culture
Bibliographic record
Abstract
We present robust methods for online estimation of cell specific oxygen uptake and carbon dioxide production rates (q(O2) and q(CO2), respectively) during perfusion cultivation of mammalian cells. Perfusion system gas and liquid phase mass balance expressions for oxygen and carbon dioxide were used to estimate q(O2), q(CO2) and the respiratory quotient (RQ) for Chinese hamster ovary (CHO) cells in perfusion culture over 12 steady states with varying dissolved oxygen (DO), pH, and temperature set points. Under standard conditions (DO = 50%, pH = 6.8, T = 36.5°C), q(O2) and q(CO2) ranges were 5.14-5.77 and 5.31-6.36 pmol/cell day, respectively, resulting in RQ values of 0.98-1.14. Changes to DO had a slight reducing effect on respiration rates with q(O2) and q(CO2) values of 4.64 and 5.47, respectively, at DO = 20% and 4.57 and 5.12 at DO = 100%. Respiration rates were lower at low pH with q(O2) and q(CO2) values of 4.07 and 4.15 pmol/cell day at pH = 6.6 and 4.98 and 5.36 pmol/cell day at pH = 7. Temperature also impacted respiration rates with respective q(O2) and q(CO2) values of 3.97 and 4.02 pmol/cell day at 30.5°C and 5.53 and 6.25 pmol/cell day at 37.5°C. Despite these changes in q(O2) and q(CO2) values, the RQ values in this study ranged from 0.98 to 1.23 suggesting that RQ was close to unity. Real-time q(O2) and q(CO2) estimates obtained using the approach presented in this study provide additional quantitative information on cell physiology both during bioprocess development and commercial biotherapeutic manufacturing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".