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Record W4402622567 · doi:10.1167/tvst.13.9.23

Lamina Cribrosa Microstructure in Nonhuman Primates With Naturally Occurring Peripapillary Retinal Nerve Fiber Layer Thinning

2024· article· en· W4402622567 on OpenAlexafffund
Palaiologos Alexopoulos, Arthur Gustavo Fernandes, Zeinab Ghassabi, Ronald Zambrano, Anse Vellappally, Eitan Shemuelian, TingFang Lee, Jiyuan Hu, Armando Burgos-Rodriguez, Melween I. Martínez, Joel S. Schuman, Amanda Melin, James P. Higham, John Danias, Gadi Wollstein

Bibliographic record

VenueTranslational Vision Science & Technology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsAlberta Children's HospitalAlberta Health ServicesUniversity of Calgary
FundersNational Eye InstituteNational Institutes of HealthMassachusetts Eye and EarMassachusetts Institute of TechnologyNatural Sciences and Engineering Research Council of CanadaBrightFocus FoundationGlaucoma Research Foundation
KeywordsNerve fiber layerLaminaRetinalAnatomyGlaucomaNerve fiberMedicineRetinaOphthalmologyBiologyNeuroscience

Abstract

fetched live from OpenAlex

Purpose: The lamina cribrosa (LC) is hypothesized to be the site of initial axonal damage in glaucoma with the circumpapillary retinal nerve fiber layer thickness (RNFL-T) widely used as a standard metric for quantifying the glaucomatous damage. The purpose of this study was to determine in vivo, 3-dimensional (3D) differences in the microstructure of the LC in eyes of nonhuman primates (NHPs) with naturally occurring glaucoma. Methods: Spectral-domain optical coherence tomography (OCT) scans (Leica, Chicago, IL, USA) of the optic nerve head were acquired from a colony of 50 adult rhesus monkeys suspected of having high prevalence of glaucoma. The RNFL-T was analyzed globally and in quadrants using a semi-automated segmentation software. From a set of 100 eyes, 18 eyes with the thinnest global RNFL-T were selected as the study group and 18 eyes with RNFL-T values around the 50th percentile were used as controls. A previously described automated segmentation algorithm was used for LC microstructure analysis. Parameters included beam thickness, pore diameter and their ratio (beam-to-pore ratio [BPR]), pore area and shape parameters, beam and pore volume, and connective tissue volume fraction (CTVF; beam volume/total volume). The LC microstructure was analyzed globally and in the following volumetric sectors: quadrants, central and peripheral lamina, and three depth slabs (anterior, middle, and posterior). Results: Although no significant difference was detected between groups for age, weight, or disc size, the study group had significantly thinner RNFL than the control group (P < 0.01). The study group had significantly smaller global and sectoral pore diameter and larger BPR compared with the control group. Across eyes, the global RNFL-T was associated positively with pore diameter globally. BPR and CTVF were significantly and negatively associated with the corresponding RNFL-T in the superior quadrant. Conclusions: Global and sectoral microstructural differences were detected when comparing thin and normal RNFL-T eyes. Whether these LC differences are the cause of RNFL damage or the result of remodeling of the LC requires further investigation. Translational Relevance: Our findings indicate structural alterations in the LC of NHP exhibiting natural thinning of the RNFL, a common characteristic of glaucomatous damage.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.302
Teacher spread0.294 · 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 designObservational
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

Citations4
Published2024
Admission routes2
Has abstractyes

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