Polyvinylalcohol three‐dimensional matrices for improved long‐term dynamic culture of hepatocytes
Bibliographic record
Abstract
Rat hepatocytes were seeded on three-dimensional highly porous polyvinylalcohol (PVA) and aminoethyl-modified polyvinylalcohol (AE-PVA) matrices. Hepatocytes were cultured under static and dynamic conditions. The three-dimensional matrices offered an improved extracellular microenvironment for long-term (5 days) maintenance of hepatocytes, compared to reference monolayer cultures on collagen. Cellular adhesion exceeded 80% with a viability superior to 70%. The preservation of albumin secretion after 5 days of culture was two times higher for static cultures on three-dimensional matrices (18% on PVA, 13% on AE-PVA) and three times higher for dynamic three-dimensional cultures (25% PVA and AE-PVA), compared to the static two-dimensional culture on collagen film (8%). The biotransformation of ammonia into urea was also maintained throughout the culture period. The addition of the aminoethyl function demonstrated no toxicity for the hepatocyte cultures. This function could be suitable eventually to further improve the hepatocyte culture system by linking more specific adhesion molecules on the polymer surface. This study demonstrated the efficiency of polyvinylalcohol as a three-dimensional matrix coupled to a perfusion culture system, which improves extracellular conditions for hepatocyte survival and promotes preservation of long-term hepatospecific functions.
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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 | 0.000 |
| 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".