Neuron‐like PC12 cell patterning on a photoactive self‐assembled monolayer
Bibliographic record
Abstract
A new approach to pattern cells using photochemistry and self-assembled monolayer (SAM) was described in this study. Photocleavable 4,5-dimethoxy-2-nitrobenzyl chloroformate (NVOC) protected amine on an alkanethiol-gold SAM was developed for cell patterning. The cleavage of NVOC and the deprotection of amines on the SAM were controlled spatially by two sequential UV exposures with a photomask. Biomolecule patterning was achieved by introducing cell nonadhesive poly(ethylene glycol) after the first exposure and subsequently cell adhesive protein laminin after the second exposure to create surface cell adhesiveness differential for cell patterning. UV-Vis spectrophotometry was used to determine the photolysis of caged self-assembled molecules; in addition, water contact angle, atomic force microscopy, cyclic voltammetry, and X-ray photoelectron spectroscopy were used to characterize properties of different surfaces. To test the efficacy of resulting surfaces in patterning cells, a neuron-like cell line, PC12 cell line, was used. The in vitro cell studies showed successful PC12 cell patterns on the photoactive SAM surfaces. This patterning technique is unique in that it does not rely on cell adhesive or nonadhesive properties of the starting base material as both cell adhesive and cell nonadhesive molecules were individually introduced onto the base material surface through photo-uncaging at preselected regions for the ultimate cell patterning.
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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 | 0.000 |
| 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 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".