Interstitial diffuse radiance spectroscopy of gold nanocages and nanorods in bulk muscle tissues
Bibliographic record
Abstract
Serge Grabtchak,1,2 Logan G Montgomery,1 Bo Pang,3,4 Yi Wang,4,5 Chao Zhang,6,7 Zhiyuan Li,6,7 Younan Xia,4,8 William M Whelan1,91Department of Physics, University of Prince Edward Island, Charlottetown, PEI, Canada; 2Departments of Electrical and Computer Engineering, and Physics, Dalhousie University, Halifax, Canada; 3Department of Biomedical Engineering, Peking University, Beijing, People’s Republic of China; 4The Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA; 5Key Laboratory of Green Synthesis and Applications, College of Chemistry, Chongqing Normal University, Chongqing, People’s Republic of China; 6Laboratory of Optical Physics, Institute of Physics, Chinese Academy of Sciences, Beijing, People’s Republic of China; 7College of Physics and Optoelectronics, South China University of Technology, Guangzhou, People’s Republic of China; 8School of Chemistry and Biochemistry, and School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA; 9Atlantic Veterinary College, Charlottetown, PEI, CanadaAbstract: Radiance spectroscopy was applied to the interstitial detection of localized inclusions containing Au nanocages or nanorods with various concentrations embedded in porcine muscle phantoms. The radiance was quantified using a perturbation approach, which enabled the separation of contributions from the porcine phantom and the localized inclusion, with the inclusion serving as a perturbation probe of photon distributions in the turbid medium. Positioning the inclusion at various places in the phantom allowed for tracking of photons that originated from a light source, passed through the inclusion’s location, and reached a detector. The inclusions with high extinction coefficients were able to absorb nearly all photons in the range of 650–900 nm, leading to a spectrally flat radiance signal. This signal could be converted to the relative density of photons incident on the inclusion. Finally, the experimentally measured quantities were expressed via the relative perturbation and arranged into the classical Beer–Lambert law that allowed one to extract the extinction coefficients of various types of Au nanoparticles in both the transmission and back reflection geometries. It was shown that the spatial variation of perturbation could be described as 1/r dependence, where r is the distance between the inclusion and the detector. Due to a larger absorption cross section, Au nanocages produced greater perturbations than Au nanorods of equal particle concentration, indicating a better suitability of Au nanocages as contrast agents for optical measurements in turbid media. Individual measurements from different inclusions were combined into detectability maps.Keywords: gold nanocages, gold nanorods, turbid media, porcine muscles, diffuse radiance spectroscopy, Beer–Lambert law, perturbation
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".