A Facile Method for Simultaneous Visualization of Wet Cells and Nanostructured Biomaterials in SEM using Ionic Liquids
Bibliographic record
Abstract
Abstract This work presents a successful methodology to image mammalian cells adhered to nanostructured biomaterials using scanning electron microscopy (SEM) operating in low-vacuum mode following ionic liquid treatment. Human osteoblast-like Saos-2 cells were treated with a room-temperature ionic liquid, 1-Ethyl-3-methylimidazolium tetrafluoroborate, and subsequently imaged on titanium utilizing SEM. Titanium substrates were modified to create laser-induced periodic surface structures (LIPSS) for visualizing at the sub-micron scale. Using a combination of fluorescence-based cell metabolism along with light microscopy and SEM image analysis, the shape and location of irradiated cells were confirmed to be unchanged after multiple irradiation sessions while the viability of minimally irradiated cells was unaltered. The wet imaging conditions combined with a rapid facile protocol using ionic liquid allows this technique to fulfill a niche in examining cellular behavior on biomaterials with sub-micron surface features. The demonstrated method to track observed cell adhesion to sub-micron surface features with SEM has great implications for the understanding of cell migration on nanostructured surfaces as well as on the exploration of simpler SEM preparation methods for cellular imaging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".