Artificial Rod and Cone Photoreceptors with Human‐Like Spectral Sensitivities
Bibliographic record
Abstract
Photosensitive materials contain biologically engineered elements and are constructed using delicate techniques, with special attention devoted to efficiency, stability, and biocompatibility. However, to date, no photosensitive material has been developed to replace damaged visual-systems to detect light and transmit the signal to a neuron in the human body. In the current study, artificial nanovesicle-based photosensitive materials are observed to possess the characteristics of photoreceptors similar to the human eye. The materials exhibit considerably effective spectral characteristics according to each pigment. Four photoreceptors originating from the human eye with color-distinguishability are produced in human embryonic kidney (HEK)-293 cells and partially purified in the form of nanovesicles. Under various wavelengths of visible light, electrochemical measurements are performed to analyze the physiological behavior and kinetics of the photoreceptors, with graphene, performing as an electrode, playing an important role in the lipid bilayer deposition and oxygen reduction processes. Four nanovesicles with different photoreceptors, namely, rhodopsin (Rho), short-, medium-, and longwave sensitive opsin 1 (1SW, 1MW, 1LW), show remarkable color-dependent characteristics, consistent with those of natural human retina. With four different light-emitting diodes for functional verification, the photoreceptors embedded in nanovesicles show remarkably specific color sensitivity. This study demonstrates the potential applications of light-activated platforms in biological optoelectronic industries.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".