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Record W4206831034 · doi:10.1002/alz.054572

Characterization of amyloid angiopathy in the retina

2021· article· en· W4206831034 on OpenAlexaff
Melanie C. W. Campbell, Laura Emptage, Rachel Redekop, Monika Kitor, Peter A.C. Neathway, Yifan Ding, Veronica Hirsch‐Reinshagen, Ging‐Yuek Robin Hsiung, Ian R. Mackenzie

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of British ColumbiaVancouver Coastal Health Research InstituteVancouver General HospitalUniversity of Waterloo
Fundersnot available
KeywordsCerebral amyloid angiopathyPathologyAmyloid (mycology)MedicineAngiopathyLumen (anatomy)AmyloidosisThioflavinRetinalAlzheimer's diseaseDementiaDiseaseOphthalmologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Cerebral amyloid angiopathy (CAA) is a vascular brain disease with risk of severe complications, and high prevalence in those with Alzheimer’s disease (AD). Characteristic amyloid beta deposits in blood vessels in the cerebrum are challenging to diagnose. Amyloid deposits in blood vessels in human retinas have been previously reported. Here, we characterize postmortem, retinal amyloid angiopathy (RAA) in individuals with AD and/or CAA brain pathology. We propose a staging of RAA which could be extended to in vivo imaging, modified from CAA staging in the brain. Method Correlation of severity of brain pathology for AD and CAA was assessed for 52 individuals. Formalin fixed retinas from 6 of these individuals were whole‐mounted and stained with thioflavin S and DAPI, then imaged in polarized light and confocal microscopy with 3 florescence channels. While following blood vessels systematically, images of RAA were collected. Result Brain pathology due to CAA increased in severity with increasing severity of AD pathology as previously reported (Figure 1). RAA was present in all donors with evidence of brain CAA and in two donors with no evidence of brain CAA (Figure 2). Amyloid present in vessels can be imaged dye‐free in polarized light. Our proposed staging of RAA severity is modified from two used in the brain (Figures 3‐6). Stage 1): Amyloid within the vessel and not filling the lumen of the vessel: 1A) Amyloid is not circumferential; 1B) Amyloid is circumferential. Stage 2): Amyloid completely fills the lumen of the vessel. Stage 3): Amyloid both within and touching the outside of the vessel, analogous to dysphoric CAA. Conclusion Amyloid angiopathy in the retina (RAA) may occur concurrently with and potentially prior to brain CAA. Further, severity of RAA could be monitored through the proposed staging which in turn could allow comparison of severities of CAA and RAA. This would elucidate whether RAA severity is a good predictor of CAA severity. Our data confirm the previously reported correlation between brain CAA and AD. Further development of RAA imaging in the living eye may allow earlier and improved diagnosis of brain CAA, facilitating the development and testing of new treatments.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.016
GPT teacher head0.251
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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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