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Record W4410119291 · doi:10.1016/j.exer.2025.110409

A standardized in vivo protocol for ocular biodistribution of gold nanoparticles

2025· article· en· W4410119291 on OpenAlexafffund
Alexis Loiseau, Christelle Gross, Sylvain L. Guérin, Élodie Boisselier

Bibliographic record

VenueExperimental Eye Research · 2025
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchFondation CHU de QuébecCanada Foundation for Innovation
KeywordsBiodistributionIn vivoNanoparticleColloidal goldProtocol (science)NanotechnologyChemistryMaterials scienceMedicinePathologyBiology

Abstract

fetched live from OpenAlex

Effective drug administration plays a pivotal role in the treatment of eye diseases. Each route of ocular administration has its advantages and limitations, but a common challenge is the low bioavailability of drugs at the target sites. New delivery nanosystems are required to ensure sufficient drug concentration over time at the target in order to improve therapeutic efficacy. Gold nanoparticles represent a promising strategy for improving drug delivery to the eye, but they can be difficult to track in biological systems. To optimize the formulations, it is crucial to understand the biodistribution profiles of nanoparticles in the eye. Designing, interpreting and compiling research on the ocular biodistribution of nanoparticles raise major challenges, particularly considering the various nanoparticle-based ocular delivery systems and the multiple available animal models. The in vivo spatiotemporal distribution of nanoparticles in the eye is generally measured at specific time points after animal euthanasia and eye collection. In this technical article, we propose a detailed standardization of in vivo protocols for ocular biodistribution studies of gold-based delivery systems in rabbits following topical application. The protocol covers all steps, including enucleation, eye dissection of various ocular tissues and their digestion, as well as ex vivo analysis of gold (Au) atom content from gold nanoparticles by inductively coupled plasma-mass spectrometry (ICP-MS) at specific time points.

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 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 score0.029
Threshold uncertainty score0.292

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)0.0000.000

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 head0.065
GPT teacher head0.477
Teacher spread0.413 · 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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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