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Sarcolipin Deletion Exaggerates Muscle Atrophy and Weakness Induced by Phospholamban Overexpression

2016· article· en· W4389027421 on OpenAlexafffundabout
Val A. Fajardo, Daniel Gamu, Andrew Mitchell, Darin Bloemberg, Éric Bombardier, Joe Quadrilatero, A. Russell Tupling

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversity of Waterloo
FundersCanadian Institutes of Health Research
KeywordsPhospholambanSERCAContractilityInternal medicineEndocrinologySoleus muscleMuscle atrophyChemistryAtrophySkeletal muscleEndoplasmic reticulumBiologyMedicineATPaseBiochemistry

Abstract

fetched live from OpenAlex

Sarcolipin (SLN) and phospholamban (PLN) are two small proteins capable of inhibiting the sarco(endo)plasmic reticulum Ca 2+ ‐ATPase (SERCA) pump. Recent work from our laboratory demonstrates that mice overexpressing PLN ( Pln OE / Sln WT ) in their slow‐twitch type I fibers present with severe impairments in SERCA function, soleus muscle atrophy and weakness, and a centronuclear myopathy (CNM)‐like phenotype. Interestingly, SLN protein was also upregulated 9‐fold in the soleus muscles from these mice, which is consistent with other models of muscle disease where SLN is often upregulated. However, to date, the physiological role of upregulated SLN in states of muscle disease remains unknown. Thus, in this study we generated the Pln OE / Sln KO mouse to determine the effects of genetic Sln deletion on SERCA function, muscle structure and contractility. Since, SLN is a potent inhibitor of the SERCA pump, we initially hypothesized that targeting Sln would lead to improvements in SERCA function, muscle contractility, and alleviate the soleus muscle atrophy and CNM‐like phenotype in this model. Surprisingly, we found that rates of Ca 2+ uptake (−18–20%, P ≤ 0.05) and SERCA's apparent affinity for Ca 2+ (Δ K Ca : −0.07 to −0.10 p Ca units, P ≤ 0.05) were similarly reduced in Pln OE / Sln WT and Pln OE / Sln KO mice compared with Pln WT / Sln WT . Consistent with the lack of improvement in SERCA function, the three typical hallmarks of CNM (1. central nuclei, 2. type I fiber predominance and hypotrophy, and 3. central aggregation of oxidative activity) were found in the soleus muscles from both Pln OE / Sln WT and Pln OE / Sln KO mice. Interestingly, Pln OE / Sln KO mice displayed an exaggerated soleus muscle atrophy and weakness indicated through greater reductions in soleus:body weight ratios ( Pln WT / Sln WT , 0.31 ± 0.01, n = 23; Pln OE / Sln WT , 0.25 ± 0.01, n = 22; Pln OE / Sln KO , 0.20 ± 0.01, n =18, P ≤ 0.05, one‐way ANOVA) and a significant reduction in both submaximal and maximal force (50–100 Hz, P ≤ 0.05). Importantly, the greater reductions in muscle size and force production could not be explained by differences in body weight, food intake, or daily activity. Instead, we attributed these effects to the fact that, in the absence of Sln , type II fibers failed to undergo the necessary myofiber hypertrophy and remodeling that compensates for the deleterious effects imposed by PLN overexpression. Furthermore, this failure to promote myofiber hypertrophy and remodeling was associated with a significantly higher level of phophosphorylated nuclear factor of activated T cell ( Pln OE / Sln WT vs. Pln OE / Sln KO −22% phosphorylation, P ≤ 0.05), a well‐known calcineurin substrate. Therefore, these results suggest that SLN counters the muscle atrophy and weakness found in Pln OE mice by stimulating calcinuerin activation. Support or Funding Information This work was supported by the Canadian Institutes of Health Research (CIHR; MOP 86618 and MOP 47296 to A.R.T).

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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
Published2016
Admission routes3
Has abstractyes

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