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Record W3124959367 · doi:10.1016/j.exer.2021.108461

The mgΔlpn mouse model for Marfan syndrome recapitulates the ocular phenotypes of the disease

2021· article· en· W3124959367 on OpenAlexaff
Rodrigo Barbosa de Souza, Isabela Gerdes Gyuricza, Luara Lucena Cassiano, Luis Ernesto Farinha-Arcieri, Ana Maria Alvim Liberatore, Sheila Schuindt do Carmo, Waldir Caldeira, M.V. Cruz, Alberto F. Ribeiro, Roberto Tedesco, Dieter P. Reinhardt, Ricardo Luiz Smith, Ivan Hong Jun Koh, Lygia V. Pereira

Bibliographic record

VenueExperimental Eye Research · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsMcGill University
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsFibrillinEctopia lentisCiliary bodyMarfan syndromeCorneaMutantPhenotypeCiliumCiliary processesMicrofibrilPathologyLens (geology)BiologyMedicineOphthalmologyCell biologyInternal medicineGeneGenetics

Abstract

fetched live from OpenAlex

PURPOSE: mouse model for MFS. METHODS: and wild-type mice at 3 and 6 months of age were analyzed by histology. The ciliary zonule was analyzed by scanning electron microscopy (SEM) and immunofluorescence. RESULTS: Mutant mice presented a significantly larger distance of the ciliary body to the lens at 3 and 6 months of age when compared to wild-type, and ectopia lentis. Immunofluorescence and SEM corroborated those findings in MFS mice, revealing a disorganized mesh of microfibrils on the floor of the ciliary body. Moreover, mutant mice also had a larger volume of the anterior chamber, possibly due to excess aqueous humor. Finally, losartan treatment had limited efficacy in improving ocular phenotypes. CONCLUSIONS: mice recapitulate the major ocular phenotypes of MFS and can be instrumental in understanding the development of the disease.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.047
GPT teacher head0.391
Teacher spread0.344 · 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 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

Citations7
Published2021
Admission routes1
Has abstractno

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