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Record W2889268520

Biodistribution of near-infrared emitting CuInS2/ZnS Quantum Dots by mass spectroscopy and fluorescence imaging of sentinel lymph node in mice

2012· preprint· en· W2889268520 on OpenAlexaff
Marion Helle, Thomas Pons, Lina Bezdetnaya, François Guillemin, Benoît Dubertret, Frédéric Marchal

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2012
Typepreprint
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsCentre d'expertise et de recherche en infrastructures urbaines
Fundersnot available
KeywordsQuantum dotBiodistributionSentinel lymph nodeIn vivoLymphPhotobleachingLymph nodeContext (archaeology)Materials scienceFluorescenceQuantum yieldNanomedicineChemistryBiomedical engineeringNanoparticleNanotechnologyPathologyMedicineCancerIn vitroBreast cancerInternal medicineOpticsBiologyBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Background: The biopsy of the sentinel lymph nodes in breast cancer patients is now strongly recommended for the definition of the further therapeutic strategy. Although this approach has strong advantages, it has its own limitations (manipulation of radioactive products and possible anaphylactic reactions to the dye). As recently proposed, these limitations could in principle be by-passed if semiconductor nanoparticles (quantum dots or QDs) were used as fluorescent contrast agents for the in vivo imaging of sentinel lymph nodes [1]. QDs are fluorescent nanoparticles with unique optical properties like strong resistance to photobleaching, size dependent emission wavelength, large molar extinction coefficient and good quantum yield [2]. Most synthesized QDs are composed of toxic heavy metals (Cd, Te, Se,...) and as such could not be used in the clinical context. Recently, we have demonstrated excellent imaging properties of Cd-free QDs for in vivo lymph nodes detection along with the greatly diminished acute inflammation in healthy rodents [3, 4]. Far before the clinical settings could be envisaged, the study on biodistribution of CuInS2/ZnS QDs in pre-clinical models and the possibility of visualization of lymph nodes upon metastatic dissemination is mandatory. Material and Methods: In vitro studies: The toxicity of CuInS2/ZnS core/shell QD on red blood cells has been tested using the haemolysis test. Red blood cells were incubated during 2h with different concentration of QDs and the release of haemoglobin was measured by spectrophotometry. In vivo studies: Healthy or tumor-bearing mice received 20 μL of 1 μM CuInS2/ZnS core/shell QD solution subcutaneously in the right anterior paw. Right axillary lymph nodes (RALN) were visualized using a near-infrared imaging system (Fluobeam™) and healthy animals were sacrificed at different time points after QDs injection. Organs, blood and excretions were collected and their indium content was measured by ICP-MS. The sentinel lymph node of tumor-bearing mice was imaged by fluorescence and the metastatic involvement of lymph nodes was assessed by the measurement of cytokeratin 19 by RT-qPCR or immunohistochemistry. Results and Discussion: In vitro assessed toxicity: No haemolysis of red blood cells was detected in the range of concentrations of CuInS2/ZnS QDs from 25 to 150 nM, while Cd-based QDs induced 50% of hemolysis with already 56.3 nM (data not shown). In vivo studies: CuInS2/ZnS QDs were observed in RALN as soon as 5 min (Fig. 1) and up to 7 days after the subcutaneous injection of QD in the right anterior paw by in vivo NIR fluorescence imaging.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.207
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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
Published2012
Admission routes1
Has abstractyes

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