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Record W2052896610 · doi:10.1002/adfm.200700439

InGaP@ZnS‐Enriched Chitosan Nanoparticles: A Versatile Fluorescent Probe for Deep‐Tissue Imaging

2007· article· en· W2052896610 on OpenAlexaff
Marinella G. Sandros, Maik Behrendt, Dušica Maysinger, Maryam Tabrizian

Bibliographic record

VenueAdvanced Functional Materials · 2007
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceFluorescenceBiocompatibilityNanoparticleChitosanTransmission electron microscopyNanotechnologyLuminescenceFluorescence microscopeBiomedical engineeringChemical engineeringOptoelectronicsOptics

Abstract

fetched live from OpenAlex

Abstract InGaP QDs overcoated with several monolayers of ZnS are covalently bound to chitosan to address the challenges of developing highly biologically stable and fluorescent nanoparticle probes for deep‐tissue imaging. Transmission electron microscopy images reveal that the average diameter of these luminescent nanoparticles is approximately 29 nm, and they contain multiple InGaP@ZnS QDs that have an average diameter between 4 and 5 nm. These new InGaP@ZnS–chitosan nanoparticles emit near the near IR region at 670 nm and are able to penetrate three times deeper into tissue (e.g., even through a mouse skull) while revealing a higher uptake efficiency into PC12 cells with a robust signal. Additionally, a cell viability assay demonstrates that these new fluorescent nanoparticles have good biocompatibility and stability with PC12 cells and neural cells. As a result, these near‐IR‐emitting nanoparticles can be used for real‐time and deep‐tissue examination of diverse specimens, such as lymphatic organs, kidneys, hearts, and brains, while leaving the tissue intact.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.022
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.016
GPT teacher head0.252
Teacher spread0.235 · 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.

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".

Quick stats

Citations44
Published2007
Admission routes1
Has abstractyes

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