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Record W2271680231 · doi:10.1149/ma2014-01/42/1597

Autofluoresence of Intralipid Phantoms at Lipid Concentration for Embedding Gold Nanoparticles

2014· article· en· W2271680231 on OpenAlexaffabout
Vinh Nguyen Du Le

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Interaction Studies and Fluorescence Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFluorescenceMaterials scienceColloidal goldNanoparticleAnalytical Chemistry (journal)ScatteringFluorescence spectroscopyBiomedical engineeringNanotechnologyOpticsChemistryChromatographyMedicinePhysics

Abstract

fetched live from OpenAlex

V. N. Du Le 1* , Zhaojun Nie 2 , Joseph E. Hayward 1 , Thomas J. Farrell 1 and Qiyin Fang 2 1 Medical Physics and Applied Radiation Sciences, McMaster University, Hamilton, Ontario, Canada 2 School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada *ledvn@mcmaster.ca Introduction Intralipid with lipid concentration of 1% to 10% v/v has been widely used to simulate background scattering which enables mapping of gold nanoparticle inclusions in spectroscopy [1], ultrasound imaging [2], and photoacoustic tomography [3]. These studies have shown that gold nanoparticles embedded in Intralipid are potential tools for cancer delineation. While optical properties and fluorescence of gold nanoparticles (GNS) were well established [1,3,4], the fluorescence characteristics of Intralipid at the lipid concentration 1% to 10% v/v has not been a subject of extensive study and remain controversy. In the present study, we construct Intralipid phantoms at concentrations that mimic tissue scattering, and measure their autoflouresence in broadband spectral region 350-650 nm using laser excitation at 355 nm with power of 2.8 µ J. Methods Two Intralipid phantoms with lipid concentrations of 1.5% and 2% v/v were created for fluorescence measurements. These phantoms were prepared by diluting the concentrated Intralipid 20% v/v solution in de-ionized water. The selected lipid concentrations produce best simulations for scattering of stromal layer in mucosal tissue which was reported previously [5]. Fluorescence measurements of Intralipid phantoms were performed using an excitation pulsed laser at 355 nm, a single optical fiber with core diameter of 600 µ m, and a calibrated spectrometer to record fluorescence at a broadband wavelength range 350-650 nm. Results The µ s values of Intralipid 10% v/v was extrapolated from the transmission measurement of low lipid concentration using linear regression method and was compared to previous data. As shown in Fig. 1, an agreement (within 10% error) in µ s values between current extrapolated data and van Staveren et al.’s data was obtained [6]. Therefore, we apply similar anisotropy expression to back-calculate reduced scattering coefficients ( µ s ′) values for Intralipid phantoms. We demonstrated that phantoms with lipid concentration of 1.5% and 2% were best simulations for scattering of stromal layer in the mucosa (Fig. 2). The µ s ′ value of lipid 1.5% and 2% at wavelength 355 nm is approximately 28.4 cm -1 and 37.9 cm -1 , respectively. The fluorescence intensity of two phantoms was shown in Fig. 3. As illustrated, autofluoresence of Intralipid increases gradually from 350 nm to 500 nm (with primary peak at 500 nm and secondary peak at 450 nm), and decreases rapidly from 500 nm to 650 nm. It has been shown that GNS have fluorescence emission at wavelength range 330-440 nm when illuminated with laser at 300 nm [4]. Compounds of GNS also have fluorescence emission in visible wavelengths [4]. Therefore, it is very likely for fluorescence of Intralipid to interfere with fluorescence of GNS. Conclusions It has been shown that Intralipid phantoms have a primary emission peak at 500 nm and a secondary emission peak at 450 nm. These measurements proved that fluorescence of Intralipid with lipid concentration at stromal scattering level is significant and should not be ignored in studies of gold nanoparticles embedded in Intralipid. Acknowledgements This project is supported in part by the Natural Sciences and Engineering Research Council (NSERC) of Canada, Canada Foundation for Innovation (CFI), Ontario Ministry of Research and Innovation (MRI), and Canada Canadian Cancer Society Research Institute (CCSRI). References [1] S. Grabtchak et al. J. Biomed. Opt. 16 (7), 2011. [2] H. Horinaka, Electronics Letter , 43 (23), 2007 [3] Q. Zhang et al., Nanotechnology , 20 , 2009 [4] Z. J. Zhang et al., Chinese J Chem Phys , 20 (6), 2007 [5] S. K. Chang et al. J Biomed Opt 9 (3), 2004. [6] H. J. van Staveren et al., Appl. Opt. 30 (31), 1991.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.278
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2014
Admission routes2
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