Gel nail polish as an alternative to traditional coverslip sealants: A quick solution to a sticky situation
Bibliographic record
Abstract
A widespread protocol to seal coverslips on a microscope slide for histological analysis utilizes air-drying nail polish. Nail polish is applied to glue the coverslip in place and prevent the leakage of mounting media. Air drying takes time, typically overnight, and generates an unpleasant smell. Equally familiar is the waiting game, lightly touching the polish to check its dryness, while being careful not to disrupt the coverslip, often leaving sticky spots on one's fingertips. An advantageous solution to these drawbacks is to use gel nail polish, which rapidly hardens and dries by being cured under a LED/UV lamp. We show that UV-cured gel nail polish provides a rapid, stable, scentless, nontoxic, and cost-effective solution for coverslip sealing. Cured in 10 s, with no impact on fluorescent labels, gel polish hardens completely and the slide is ready to be imaged. Furthermore, we show that gel nail polish can be used to generate 3D ridges and structures to support coverslipping thicker samples. Gel nail polish is purposefully unscented, and the brands used in our study employ environmentally conscious, vegan, and cruelty-free ingredients. UV-cured gel nail polish is a cost-effective alternative that presents an easy, accessible, and inexpensive solution to traditional coverslip sealing methods.•Inexpensive method to rapidly seal coverslips onto a microscope slide to immediately image samples for Histological analyses.•Utilizes LED/UV light to cure gel nail polish in 10 s without bleaching fluorophores.•Can be used to generate 3D ridges and structures to support coverslipping thicker samples.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".