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Record W3038503895 · doi:10.1016/j.celrep.2020.107781

The Leucine-Rich Repeat Region of CARMIL1 Regulates IL-1-Mediated ERK Activation, MMP Expression, and Collagen Degradation

2020· article· en· W3038503895 on OpenAlexafffund
Qin Wang, Karambir Notay, Gregory P. Downey, Christopher A. McCulloch

Bibliographic record

VenueCell Reports · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicS100 Proteins and Annexins
Canadian institutionsUniversity of Toronto
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchCanada Research ChairsGovernment of Canada
KeywordsLeucine-rich repeatMAPK/ERK pathwayCell biologyMutantSignal transductionHEK 293 cellsWild typePhosphorylationImmunoprecipitationChemistryMolecular biologyBiologyKinaseReceptorGeneBiochemistry

Abstract

fetched live from OpenAlex

CARMILs are large, multidomain, membrane-associated proteins that regulate actin assembly and Rho-family GTPases, but their role in inflammatory signaling is not defined. Tandem mass tag mass spectrometry indicated that, in fibroblasts, CARMIL1 associates with interleukin (IL)-1 signaling molecules. Immunoprecipitation of cells transfected with CARMIL1 mutants showed that the leucine-rich repeat (LRR) region of CARMIL1 associates with IL-1 receptor type 1 (IL-1R1) and IL-1 receptor-associated kinase (IRAK). Knockout of CARMIL1 by CRISPR-Cas9 reduced IL-1-induced ERK activation by 72% and MMP3 expression by 40%. Compared with CARMIL1 wild-type (WT), cells expressing mutant CARMIL1 lacking its LRR domain exhibited 45% lower ERK activation and 40% lower MMP3 expression. In fibroblasts transduced with a cell-permeable, TAT CARMIL1 peptide that competed with IL-1R1 and IRAK binding to the LRR of CARMIL1, collagen degradation was reduced by 43%. As the LRR of CARMIL1 evidently regulates IL-1 signaling, CARMIL1 could become a target for anti-inflammatory drug development.

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 score0.040
Threshold uncertainty score0.306

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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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

Citations33
Published2020
Admission routes2
Has abstractyes

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