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Record W6986993611

Role of the USP19 deubiquitinating enzyme in the activation of the ubiquitin proteasome system in skeletal muscle upon stimulation with dexamethasone

2014· dissertation· en· W6986993611 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2014
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsMcGill University
Fundersnot available
KeywordsDeubiquitinating enzymeUbiquitinMuscle atrophySkeletal muscleProtein degradationProteasomeDexamethasoneMyocyte
DOInot available

Abstract

fetched live from OpenAlex

Loss of skeletal muscle occurs with muscle disuse, aging, and in many diseases such as sepsis, chronic obstructive pulmonary disease, chronic heart failure, AIDS, cancer and diabetes. The muscle loss results from decreased protein synthesis and increased degradation. The increase in protein degradation is dependent on the activation of the ubiquitin proteasome system (UPS), a pathway in which selected proteins are labeled with ubiquitin that targets them for degradation. Understanding the precise molecular pathways behind muscle wasting is critical for the development of new therapies to prevent or treat the loss of muscle mass and function associated with many diseases. Many studies have revealed roles for ubiquitin ligases in muscle wasting but little is known about the roles of deubiquitinating enzymes. Our laboratory has previously shown that the induction of USP19, a deubiquitinating enzyme, occurs under different conditions of muscle atrophy including fasting, glucocorticoid treatment, muscle denervation and cancer bearing animals. To further evaluate the role of USP19, our laboratory tested the effects of inactivating USP19 in mice in dexamethasone-induced atrophy. Under dexamethasone induced muscle atrophy, USP19 KO mice lost 64% less tibialis anterior muscle mass than WT mice. In addition, the induction of atrophy genes, ubiquitin ligases MuRF1 and atrogin-1 seen in muscles in WT mice was significantly attenuated in the KO mice. Since these mice were deficient in USP19 in all tissues, I tested in this thesis whether USP19 could act directly on muscle cells. I first screened multiple muscle cell lines to identify ones in which dexamethasone could induce expression of atrogenes. To explore whether these muscle protective effects are likely due to the direct action of USP19 in muscles, I tested the effect of silencing USP19 in myotubes exposed to dexamethasone. Our results show that silencing USP19 in L6 myotubes attenuated the induction of atrophy genes, MuRF1 and atrogin-1, by dexamethasone. Another approach to loss of function is testing the effect of dexamethasone in USP19 KO primary myotubes. Primary myoblasts were isolated from tibialis anterior muscle of USP19 KO mice, and myoblasts were induced to differentiate. Our results show that the inactivation of USP19 in the primary culture attenuated the expression of MuRF1 in both basal and dexamethasone treated states, but had no effect on expression of atrogin-1. Taken together, these results indicate that USP19 modulates muscle atrophy in part by a direct action in skeletal muscle and suggest that inhibition of USP19 may be useful for the prevention of glucocorticoid-induced muscle atrophy.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.223
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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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