Plasmonic Copper Sulfide Nanoparticles Enable Dark Contrast in Optical Coherence Tomography
Bibliographic record
Abstract
Optical coherence tomography (OCT) is an imaging technique affording noninvasive optical biopsies. Like for other imaging techniques, the use of dedicated contrast agents helps better discerning biological features of interest during the clinical practice. Although bright OCT contrast agents have been developed, no dark counterpart has been proposed yet. Herein, plasmonic copper sulfide nanoparticles as the first OCT dark contrast agents working in the second optical transparency window are reported. These nanoparticles virtually possess no light scattering capabilities at the OCT working wavelength (≈1300 nm); thus, they exclusively absorb the probing light, which in turn results in dark contrast. The small size of the nanoparticles and the absence of apparent cytotoxicity support the amenability of this system to biomedical applications. Importantly, in the pursuit of systems apt to yield OCT dark contrast, a library of copper sulfide nanoparticles featuring plasmonic resonances spanning the three optical transparency windows is prepared, thus highlighting the versatility and potential of these systems in light-controlled biomedical applications.
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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) | 0.001 | 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".