High yields of monomeric recombinant β‐interferon from macroporous microcarrier cultures under hypothermic conditions
Bibliographic record
Abstract
Macroporous microcarriers such as Cytopore entrap mammalian cells in a mesh network allowing growth to high cell concentrations in a protected environment within a stirred culture. Chinese hamster ovary (CHO) cells producing recombinant human beta-interferon (IFN-beta) and grown in Cytopore microcarriers showed a 2.6- to 2.8-fold increase in the volumetric product titer compared with cells grown in an equivalent suspension culture. In an attempt to maximize production of IFN-beta, microcarrier cultures were subjected to a low temperature regime. Low temperature culture conditions (32 degrees C) have been shown previously to enhance cell specific productivity in suspension cultures although at reduced cell growth rates. These conditions can be optimized by a timely shift from physiological to hypothermic conditions during the culture run to maximize volumetric protein production. In the case of IFN-beta production the lower temperature has the added advantage of stabilizing the product and reducing intramolecular aggregation. Using a biphasic temperature-shift regime from 37 to 32 degrees C the volumetric production of IFN-beta was enhanced to 4.2-fold compared with a single temperature suspension culture in a controlled bench-top bioreactor. Furthermore, the degree of intramolecular aggregation of IFN-beta was reduced significantly (59%) compared with control cultures, largely due to the lower temperature but also partially due to the presence of microcarriers. These results indicate that the hypothermic conditions in a Cytopore culture had a combined and possibly synergistic effect of increasing volumetric production of the recombinant protein.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".