A high‐rate perfusion bioreactor for plant cells
Bibliographic record
Abstract
A perfusion bioreactor allowing continuous extraction of secondary metabolites was designed and challenged for Eschscholtzia californica plant cell suspensions. Four sedimentation columns mounted inside a 2.5-L bioreactor separated single cells and cell aggregates from the culture medium. Cells were elicited with chitin at day 4 and the liquid medium free of cells and debris was then continuously pumped to the extraction columns containing fluidized XAD-7 resins, and then recirculated back to the cell suspension. A medium upward velocity corresponding to cell sedimentation velocity maintained a stable cell/medium separation front in the columns for sedimented cell volume (SCV) of 90% (70% packed cell volume, PCV). Two perfusion bioreactor cultures of 10 and 14 days were performed. A maximum dilution rate of 20.4/day was reached from day 4 to day 6, and was then reduced to 5/day at day 9 for 55% SCV. Control cultures were performed without and with free extraction resins into the cell suspension. Perfusion cultures showed similar specific growth rates of 0.24 +/- 0.04/day before and after elicitation. However, production level in the perfusion cultures was similar to that from the culture without resins with a maximum of 2.06 micromole/gDW total alkaloids, with 1.54 micromole/gDW in the resins. Cultures with free resins resulted in 30.94 micromole/gDW with 28.4 +/- 8.8 micromole/gDW in the resins. Difference in the cells nutritional state from elicitation was identified as a major cause in the production reduction. However, pathway to chelilutine was favored in the continuous extraction culture.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".