Characterization of a Perfusion Reactor Utilizing Mammalian Cells on Microcarrier Beads
Bibliographic record
Abstract
Our overall objective is to develop a cell culture analogue bioreactor (CCA) that can be used together with a corresponding physiologically based pharmacokinetic model (PBPK) to evaluate molecular mechanisms of toxicity. The PBPK is a mathematical model that divides the body into compartments representing organs, integrating the kinetic, thermodynamic, and anatomical parameters of the animal. The CCA bioreactor is a physical replica of the PBPK; where the PBPK specifies organs, the CCA bioreactor contains compartments with a corresponding cell type that mimics some of the characteristic metabolism of that organ. The device is a continuous, dynamic system composed of multiple cell types that interact through a common circulating cell culture medium. The CCA bioreactor and the model can be coupled to evaluate the plausibility of the molecular mechanism that is input into the model. This paper focuses on the design, development, and characterization of a CCA bioreactor to be used in naphthalene dose response studies. A CCA bioreactor prototype developed previously is improved upon by culturing the cells on microcarrier beads. Microcarrier beads with cells attached can form packed beds with cell culture medium perfusing the beds. In this study, two packed beds of cells, one with L2 cells (rat lung) and one with H4IIE cells (rat hepatoma), are linked in a physiologically relevant arrangement by a common recirculating cell culture medium. Studies of this CCA bioreactor presented here include mixing profiles, effect of reactor environment on cell viability and intracellular glutathione, naphthalene distribution profile, and initial naphthalene dosing studies. Unlike the prototype system there is no detectable response to naphthalene addition; in a companion paper we show that this discrepancy can be explained by differences in liquid residence times in the organ compartments. The perfusion reactor design is shown to have significant operating improvements over prototype designs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".