Rheological Behavior of High Cell Density Pseudomonas putida LS46 Cultures during Production of Medium Chain Length Polyhydroxyalkanoate (PHA) Polymers
Bibliographic record
Abstract
The rheology of high-cell density (HCD) cultures is an important parameter for its impact on mixing and sparging, process scale-up, and downstream unit operations in bioprocess development. In this work, time-dependent rheological properties of HCD Pseudomonas putida LS46 cultures were monitored for microbial polyhydroxyalkanoate (PHA) production. As the cell density of the fed-batch cultivation increased (0 to 25 g·L−1 cell dry mass, CDM), the apparent viscosity increased nearly nine-fold throughout the fed-batch process. The medium behaved as a nearly Newtonian fluid at lower cell densities, and became increasingly shear-thinning as the cell density increased. However, shear-thickening behavior was observed at shearing rates of approximately 75 rad·s−1 or higher, and its onset increased with viscosity of the sample. The supernatant, which contained up to 9 g·L−1 soluble organic material, contributed more to the observed viscosity effect than did the presence of cells. Owing to this behavior, the oxygen transfer performance of the bioreactor, for otherwise constant operating conditions, was reduced by 50% over the cultivation time. This study has shown that the dynamic rheology of HCD cultures is an important engineering parameter that may impact the final outcome in PHA cultivations. Understanding and anticipating this behavior and its biochemical origins could be important for improving overall productivity, yield, process scalability, and the efficacy of downstream processing unit operations.
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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) | 0.000 | 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 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".