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The impact of sarcolipin ablation on calcineurin signalling and muscle phenotype with aging

2023· article· en· W4378648939 on OpenAlexaff
Paige J. Chambers, Aditya N. Brahmbhatt, A. Russell Tupling

Bibliographic record

VenuePhysiology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNFATDephosphorylationInternal medicineEndocrinologyCalcineurinPhosphorylationPhospholambanSERCAKnockout mouseDownregulation and upregulationChemistryATPaseBiologyPhosphataseMedicineCell biologyBiochemistryReceptorEnzyme

Abstract

fetched live from OpenAlex

Sarcolipin (SLN), a small protein inhibitor of the sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA), is dynamically upregulated in atrophic unloading and disease states where it promotes muscle health by activating calcineurin (Cn) and the dephosphorylation and subsequent nuclear translocation of nuclear factor of activated T-cells (NFAT). This study sought to examine how the ablation of SLN impacted Cn signalling, fibre type profile and muscle mass in both male and female mice with aging. Male and female, wild type (WT) and SLN knockout (SLNKO) mice were assessed at two age groups (young adult (4-6M) and older adult (18+M)) for muscle mass (soleus:body weight ratio, fibre type specific cross-sectional area), fibre type profile and protein expression (SLN, Cn, and NFAT). SLN content was significantly greater in WT females (p <00.1) and older animals (5<0.05) and absent from SLNKO. As SLN has been linked to Cn signalling previously, we hypothesized that the increased SLN content in female and aged animals may promote Cn signalling. While there was a trend for lower Cn expression with aging (p=0.10), neither sex nor genotype significantly impacted Cn expression. To examine activation of Cn, the ratio of inactive phosphorylated NFAT to total NFAT was assessed via Western Blotting. We found that aging significantly increased the activation of Cn (p<0.01) and there was a trend (p=0.10) towards greater NFATp/NFAT with SLN ablation signifying a reduction in Cn signalling. As Cn is a known regulator of muscle fibre type, we examined fibre type profile using immunofluorescence and found aging increased the percentage of type I fibres (p<0.001), which was witnessed more predominately in female mice regardless of genotype. Furthermore, when examining type II fibres, we found a significant sex by age interaction (p<0.05) in which both WT and SLNKO females displayed reduced type II fibres with aging while males did not display this apparent shift. With respect to muscle mass, aging, regardless of sex or genotype, was shown to significantly reduce relative muscle mass (p<0.001), however no significant reductions were found in total fibre count, or cross-sectional area of Type I or Type II fibres. In summary, this study found that WT female and aged animals display increased SLN content. Aligning with our hypothesis, there was a trend towards lower Cn signalling with SLN ablation, regardless of age or sex. However, this does not seem to be linked to changes in muscle fibre type or muscle mass, as SLNKO animals did not display significant differences from their WT counterparts. Further studies should seek to examine the role of SLN in both sex and aging further, with special focus on metabolic energy expenditure and SERCA protection. NSERC This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.275
Teacher spread0.264 · 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
Published2023
Admission routes1
Has abstractyes

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