Graphene biointerfaces for optical stimulation of cells
Bibliographic record
Abstract
Noninvasive stimulation of cells is crucial for the accurate examination and control of their function both at the cellular and the system levels. To address this need, we present a pioneering optical stimulation platform that does not require genetic modification of cells but instead capitalizes on unique optoelectronic properties of graphene, including its ability to efficiently convert light into electricity. We report the first studies of optical stimulation of cardiomyocytes via graphene-based biointerfaces (G-biointerfaces) in substrate-based and dispersible configurations. The efficiency of stimulation via G-biointerfaces is independent of light wavelength but can be tuned by changing the light intensity. We demonstrate that an all-optical evaluation of use-dependent drug effects in vitro can be enabled using substrate-based G-biointerfaces. Furthermore, using dispersible G-biointerfaces in vivo, we perform optical modulation of the heart activity in zebrafish embryos. Our discovery is expected to empower numerous fundamental and translational biomedical studies.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".