Carotenoid based bio-compatible labels for third harmonic generation microscopy
Bibliographic record
Abstract
The use of carotenoids as biologically friendly labels for third harmonic generation (THG) microscopy is demonstrated. Carotenoid containing liposomes are used to label cell structures via liposome cell fusion. The THG microscopy labels, called harmonophores, were characterized by measuring the third-order nonlinear susceptibility (χ((3))) of carotenoids: violaxanthin, neoxanthin, lutein, β-carotene, zeaxanthin, canthaxanthin and astaxanthin. The THG ratio method was used, which is based on measuring the THG intensity from two interfaces using a nonlinear optical microscope. The second hyperpolarizability values of carotenoids were extracted from χ((3)) measurements taking into account the refractive index at fundamental and third harmonic wavelengths. The length dependence of the second hyperpolarizability of conjugated polyenes from 9 to 13 double bonds with varying oxygen functional groups was investigated. It appears that the presence of epoxides can have a higher influence than an additional conjugated double bond. Furthermore, labelling of both Drosophila Schneider 2 cells and Drosophila melanogaster larvae myocytes with β-carotene was achieved. This study demonstrates that THG enhancement by carotenoids can be used for nontoxic in vivo labelling of subcellular structures for third harmonic generation microscopy.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".