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Record W3203112082 · doi:10.1002/dvdy.427

A <scp>CRISPR</scp>/Cas9 zebrafish lamin A/C mutant model of muscular laminopathy

2021· article· en· W3203112082 on OpenAlexafffund
Hannah A. Nicolas, Khang Hua, Hailey Quigley, Joshua Ivare, Frédérique Tesson, Marie‐Andrée Akimenko

Bibliographic record

VenueDevelopmental Dynamics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsLMNAZebrafishBiologySkeletal muscleMutantLaminCell biologyCRISPRMolecular biologyGeneticsGeneAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND: Lamin A/C gene (LMNA) mutations frequently cause cardiac and/or skeletal muscle diseases called striated muscle laminopathies. We created a zebrafish muscular laminopathy model using CRISPR/Cas9 technology to target the zebrafish lmna gene. RESULTS: Heterozygous and homozygous lmna mutants present skeletal muscle damage at 1 day post-fertilization (dpf), and mobility impairment at 4 to 7 dpf. Cardiac structure and function analyses between 1 and 7 dpf show mild and transient defects in the lmna mutants compared to wild type (WT). Quantitative RT-PCR analysis of genes implicated in striated muscle laminopathies show a decrease in jun and nfκb2 expression in 7 dpf homozygous lmna mutants compared to WT. Homozygous lmna mutants have a 1.26-fold protein increase in activated Erk 1/2, kinases associated with striated muscle laminopathies, compared to WT at 7 dpf. Activated Protein Kinase C alpha (Pkc α), a kinase that interacts with lamin A/C and Erk 1/2, is also upregulated in 7 dpf homozygous lmna mutants compared to WT. CONCLUSIONS: This study presents an animal model of skeletal muscle laminopathy where heterozygous and homozygous lmna mutants exhibit prominent skeletal muscle abnormalities during the first week of development. Furthermore, this is the first animal model that potentially implicates Pkc α in muscular laminopathies.

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)0.000
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 score0.083
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.195
Teacher spread0.189 · 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

Citations13
Published2021
Admission routes2
Has abstractyes

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