Reversible Bonding of Thermoplastic Elastomers for Cell Patterning Applications
Bibliographic record
Abstract
In this paper, we present a simple, versatile method that creates patterns for cell migration studies using thermoplastic elastomer (TPE). The TPE material used here can be robustly, but reversibly, bonded to a variety of plastic substrates, allowing patterning of cultured cells in a microenvironment. We first examine the bonding strength of TPE to glass and polystyrene substrates and com-pare it to thermoset silicone-based PDMS under various conditions and demonstrate that the TPE can be strongly and reversibly bonded on commercially available polystyrene culture plates. In cell migration studies, cell patterns are templated around TPE features cored from a thin TPE film. We show that the significance of fibroblast cell growth with fetal bovine serum (FBS)-cell culture media compared to the cells cultured without FBS, analyzed over two days of cell culture. This simple approach allows us to generate cell patterns without harsh manipulations like scratch assays and to avoid damaging the cells. We also confirm that the TPE material is non-toxic to cell growth and supports a high viability of fibroblasts and breast cancer cells. We anticipate this TPE-based patterning approach can be further utilized for many other cell patterning applications such as in cell-to-cell communication studies.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".