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Quantum dots trace lymphatic drainage from the mouse eye

2011· article· en· W2020617821 on OpenAlexafffund
Alex Tam, Neeru Gupta, Zhexue Zhang, Yeni H. Yücel

Bibliographic record

VenueNanotechnology · 2011
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersGlaucoma Research Society of Canada
KeywordsLymphatic systemQuantum dotGlaucomaLymphatic vesselIn vivoBlindnessHuman eyePathologyMaterials scienceMedicineOphthalmologyBiomedical engineeringBiologyOptometryOpticsPhysicsNanotechnologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Glaucoma is a leading cause of blindness in the world, often associated with elevated eye pressure. Currently, all glaucoma treatments aim to lower eye pressure by improving fluid exit from the eye. We recently reported the presence of lymphatics in the human eye. The lymphatic circulation is known to drain fluid from organ tissues and, as such, lymphatics may also play a role in draining fluid from the eye. We investigated whether lymphatic drainage from the eye is present in mice by visualizing the trajectory of quantum dots once injected into the eye. Whole-body hyperspectral fluorescence imaging was performed in 17 live mice. In vivo imaging was conducted prior to injection, and 5, 20, 40 and 70 min, and 2, 6 and 24 h after injection. A quantum dot signal was observed in the left neck region at 6 h after tracer injection into the eye. Examination of immunofluorescence-labelled sections using confocal microscopy showed the presence of a quantum dot signal in the left submandibular lymph node. This is the first direct evidence of lymphatic drainage from the mouse eye. The use of quantum dots to image this lymphatic pathway in vivo is a novel tool to stimulate new treatments to reduce eye pressure and prevent blindness from glaucoma.

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)0.000
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 score0.177
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.020
GPT teacher head0.244
Teacher spread0.223 · 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

Citations56
Published2011
Admission routes2
Has abstractyes

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