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Record W3087985405 · doi:10.1038/s41598-020-72737-6

Structural polymorphisms in fibrillar aggregates associated with exfoliation syndrome

2020· article· en· W3087985405 on OpenAlexafffund
Mehdi Ghaffari Sharaf, Sara Amidian, Vineet Rathod, Andrew Crichton, Karim F. Damji, Holger Wille, Larry D. Unsworth

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsUniversity of CalgaryUniversity of Alberta
FundersAlberta Innovates
KeywordsFibrilBiophysicsExfoliation jointCollagen fibrilChemistryCrystallographyBiologyMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

Exfoliation syndrome is largely considered an age-related disease that presents with fibrillar aggregates in the front part of the eye. A growing body of literature has investigated structural diversity of amyloids and fibrillar aggregates associated with neurodegenerative disease. However, in case of exfoliation syndrome, there is a dearth of information on the biophysical characteristics of these fibrils and structural polymorphisms. Herein, structural diversity of fibrils isolated from the anterior lens capsule of patients was evaluated using transmission electron microscopy techniques. It was apparent that, despite having a low sample number of different patients, there exists a wide range of fibril morphologies. As it is not precisely understood how these fibrils form, or what they are composed of, it is difficult to postulate a mechanism responsible for these differences in fibril structure. However, it is apparent that there is a wider range of fibril structure than initially appreciated. Moreover, these data may suggest the variance in fibril structure arises from patient-specific fibril composition and/or formation mechanisms.

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)0.001
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 score0.043
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.262
Teacher spread0.245 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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