<i>In situ</i> base release for <scp>pH</scp> maintenance can allow shake flasks to better mimic bioreactor performance for <scp>CHO</scp> cell culture
Bibliographic record
Abstract
Abstract BACKGROUND Shake flasks are widely used for evaluating mammalian cells in suspension. Lack of pH control can contribute to differences in culture performance between them and bioreactors. This study evaluates whether a previously reported in situ base releasing hydrogel (pHmH) to counter pH decrease can enable shake flask cultures to better mimic bioreactor cultures. RESULTS Compared with bioreactor culture, fed‐batch cultures of a recombinant Chinese hamster ovary (CHO) cell‐line in shake flasks without pHmH showed a decrease in pH to 6.6, accompanied by 40, 60 and 22% lower peak cell density, lactate accumulation, and immunoglobulin G (IgG) titer, respectively. Use of pHmH allowed shake flasks to maintain pH above 6.8 and reduced this difference to 20, 30, and 15%, respectively, thus enabling culture performance in shake flasks to better mimic the bioreactor. IgG glycosylation profiles were similar in identically fed cultures across all three platforms. Application of pHmH hydrogel during clone screening was evaluated by comparing correlation between titers for five recombinant CHO clones in bioreactors and shake flasks with and without pHmH; a higher correlation was found in shake flasks with pHmH than without. CONCLUSION In situ base release through hydrogel can allow identically fed fed‐batch cultures in shake flasks to better mimic cell growth, lactate accumulation and IgG titers in bioreactors, without additional infrastructure. © 2018 Society of Chemical Industry
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".