A Fast and Accessible Methodology for Micro-Patterning Cells on Standard Culture Substrates Using Parafilm™ Inserts
Bibliographic record
Abstract
Micropatterning techniques provide direct control over the spatial organization of cells at the sub-mm scale. Regulation of these spatial parameters is important for controlling cell fate and cell function. While micropatterning has proved a powerful technique for understanding the impact of cell organization on cell behaviour, current methods for micropatterning cells require complex, specialized equipment that is not readily accessible in most biological and bioengineering laboratories. In addition, currently available methods require significant protocol optimization to ensure reliable and reproducible patterning. The inaccessibility of current methods has severely limited the widespread use of micropatterning as a tool in both biology and tissue engineering laboratories. Here we present a simple, cheap, and fast method to micropattern mammalian cells into stripes and circular patterns using Parafilm™, a common material found in most biology and bioengineering laboratories. Our method does not require any specialized equipment and does not require significant method optimization to ensure reproducible patterning. Although our method is limited to simple patterns, these geometries are sufficient for addressing a wide range of biological problems. Specifically, we demonstrate i) that using our Parafilm™ insert method we can pattern and co-pattern ARPE-19 and MDCK epithelial cells into circular and stripe micropatterns in tissue culture polystyrene (TCPS) wells and on glass slides, ii) that we can contain cells in the desired patterns for more than one month and iii) that upon removal of the Parafilm™ insert we can release the cells from the containment pattern and allow cell migration outward from the original pattern. We also demonstrate that we can exploit this confinement release feature to conduct an epithelial cell wound healing assay. This novel micropatterning method provides a reliable and accessible tool with the flexibility to address a wide range of biological and engineering problems that require control over the spatial and temporal organization of cells.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".