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Record W2061157967 · doi:10.1111/his.12715

Abnormal expression of <scp>RNA</scp> polymerase <scp>II</scp>‐associated proteins in muscle of patients with myofibrillar myopathies

2015· article· en· W2061157967 on OpenAlexaff
Valeria Guglielmi, Matteo Marini, Émilie Fiola Masson, Manuela Malatesta, Diane Forget, Giuliano Tomelleri, Benoit Coulombe, Gaetano Vattemi

Bibliographic record

VenueHistopathology · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsMontreal Clinical Research Institute
Fundersnot available
KeywordsMyofibrilImmunostainingMyocyteProtein subunitCytoplasmStainingBiologyMolecular biologyDesminCell biologyChemistryImmunohistochemistryPathologyBiochemistryGeneticsMedicineGeneImmunologyVimentin

Abstract

fetched live from OpenAlex

AIMS: Myofibrillar myopathies (MFMs) are a group of inherited or sporadic neuromuscular disorders characterized morphologically by foci of myofibril dissolution, disintegration of the Z-disk and insoluble protein aggregates within the muscle fibres. The sequential events leading to muscle fibre damage remains largely unknown. METHODS AND RESULTS: We investigated the expression and the cellular localization of RNA polymerase II (RNAPII)-associated proteins (RPAPs) in muscle biopsies from patients with genetically proven and sporadic MFMs. Our data demonstrated that RPAP2, and to a lesser extent GPN1/RPAP4, are accumulated focally in the cytoplasm of MFM muscle fibres in which they co-localize with POLR2A/RPB1, the largest subunit of RNAPII, and correspond to αB-cystallin deposits in distribution and staining intensity. No abnormal staining for RPAP2 has been observed in muscle of patients with central cores, minicores and neurogenic target fibres. CONCLUSIONS: Together, these findings could provide new insights into the molecular pathogenesis of MFMs and suggest that RPAP2 immunostaining can be a useful diagnostic tool to depict protein aggregates in MFMs.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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.

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

Citations5
Published2015
Admission routes1
Has abstractyes

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