Nondestructive Online <emphasis>In Vitro</emphasis> Monitoring of Pre-Osteoblast Cell Proliferation Within Microporous Polymer Scaffolds
Bibliographic record
Abstract
We present a system for the online, in vitro, nondestructive monitoring of tissue growth within microporous polymer scaffolds. The system is based on measuring the admittance of the sample over a frequency range of 10-200 MHz using an open-ended coaxial probe and impedance analyzer. The sample admittance is related to the sample complex permittivity (CP) by a quasi-static model of the probe's aperture admittance. A modified effective medium approximation is then used to relate the CP to the cell volume fraction. The change of cell volume fraction is used as a measure of tissue growth inside the scaffold. The system detected relative cell concentration differences between microporous polymer scaffolds seeded with 0.4, 0.45, 0.5, and 0.6 x 10(6) pre-osteoblast cells. In addition, the pre-osteoblast proliferation within 56 scaffolds over 14 days was recorded by the system and a concurrent DNA assay. Both techniques produced cell proliferation curves that corresponded to those found in literature. Thus, our data confirmed that the new system can assess relative cell concentration differences in microporous scaffolds enabling online nondestructive tissue growth monitoring.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".