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Record W3094872986 · doi:10.3390/cells9112388

Protein Kinase C Alpha Cellular Distribution, Activity, and Proximity with Lamin A/C in Striated Muscle Laminopathies

2020· article· en· W3094872986 on OpenAlexafffund
Hannah A. Nicolas, A. Bertrand, Sarah Labib, Musfira Mohamed-Uvaize, Pierrette M. Bolongo, Wen Wu, Zofia T. Bilińska, Gisèle Bonne, Marie‐Andrée Akimenko, Frédérique Tesson

Bibliographic record

VenueCells · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsUniversity of Ottawa
FundersHeart and Stroke Foundation of CanadaOttawa Hospital Research InstituteCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsLaminCell biologyAlpha (finance)ChemistryBiologyNucleusMedicine

Abstract

fetched live from OpenAlex

Striated muscle laminopathies are cardiac and skeletal muscle conditions caused by mutations in the lamin A/C gene (LMNA). LMNA codes for the A-type lamins, which are nuclear intermediate filaments that maintain the nuclear structure and nuclear processes such as gene expression. Protein kinase C alpha (PKC-α) interacts with lamin A/C and with several lamin A/C partners involved in striated muscle laminopathies. To determine PKC-α’s involvement in muscular laminopathies, PKC-α’s localization, activation, and interactions with the A-type lamins were examined in various cell types expressing pathogenic lamin A/C mutations. The results showed aberrant nuclear PKC-α cellular distribution in mutant cells compared to WT. PKC-α activation (phos-PKC-α) was decreased or unchanged in the studied cells expressing LMNA mutations, and the activation of its downstream targets, ERK 1/2, paralleled PKC-α activation alteration. Furthermore, the phos-PKC-α-lamin A/C proximity was altered. Overall, the data showed that PKC-α localization, activation, and proximity with lamin A/C were affected by certain pathogenic LMNA mutations, suggesting PKC-α involvement in striated muscle 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 score0.024
Threshold uncertainty score0.388

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 head0.181
Teacher spread0.175 · 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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