Topographically grooved gel inserts for aligning epithelial cells during air–liquid-interface culture
Bibliographic record
Abstract
Epithelial tissues are a critical component of all tubular organs. Engineering artificial epithelium requires an understanding of the polarization of epithelia: both apicobasal and in a planar fashion. Air liquid interface (ALI) culture is typically used to generate apicobasal polarized airway epithelium in vitro; however, this approach does not provide any signalling cues to induce morphological planar polarization of the generated epithelial layer. Here we describe a microgrooved gelatin hydrogel insert that can induce alignment of confluent epithelial cell sheets under ALI conditions to induce both apicobasal and morphologically planar polarized epithelium. Microgrooves are imprinted into the surface of the gelatin insert using elastomeric stamps moulded from a diffraction grating film and gels are stabilized by crosslinking with glutaraldehyde. We show that microgrooved gelatin inserts produce alignment of 3T3 fibroblasts and a number of epithelial cell lines (ARPE-19, BEAS2B and IMCD3 cells). Furthermore, we show that BEAS2B apicobasally polarize and form a similar density of cilia on both gelatin inserts and standard transwell filters used for ALI culture but that as apicobasal polarization progresses cell alignment on the grooves is lost. Our method provides a simple strategy that can easily be adopted by labs without microfabrication expertise for manipulating epithelial organization in transwell culture and studying the interplay of various polarization forces.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".