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The Critical Role of Scleraxis in Pressure Overload‐Induced Cardiac Fibrosis

2018· article· en· W3174135158 on OpenAlexafffundabout
Raghu S. Nagalingam, David Yat‐Chung Cheung, Nina Aroutiounova, Davinder S. Jassal, Michael P. Czubryt

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsSt. Boniface HospitalUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsCardiac fibrosisFibrosisPressure overloadMyofibroblastMedicineFibronectinCTGFPathologyCancer researchBiologyCell biologyEndocrinologyInternal medicineGrowth factorMuscle hypertrophyExtracellular matrixReceptor

Abstract

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Cardiac fibrosis is an independent risk factor for patient morbidity and mortality that is caused by other forms of cardiovascular dysfunction, including myocardial infarction, pressure overload and diabetes, yet lacks any current treatment options. A required step in the pathogenesis of fibrosis is the activation of fibroblasts to myofibroblasts, which secrete high levels of matrix proteins including collagen, resulting in elevated myocardial wall stiffness, loss of compliance and arrhythmias. We previously demonstrated that the transcription factor scleraxis is both sufficient and necessary to drive the phenotype conversion of fibroblasts to myofibroblasts via direct transactivation of key pro‐fibrotic proteins such as collagen 1α2, α‐smooth muscle actin and fibronectin. We hypothesized that genetic deletion of scleraxis would be sufficient to prevent cardiac fibrosis. We used a tamoxifen‐inducible fibroblast‐specific Cre recombinase mouse line (Tcf21‐iCre) crossed to a floxed scleraxis line to permit timed deletion in adult animals. Eight week old mice were gavaged with tamoxifen to induce scleraxis gene deletion, followed by pressure overload (thoracic aortic constriction, TAC) or sham surgery; scleraxis‐intact animals received corn oil carrier. Animals were sacrificed at 4 or 8 weeks post‐surgery and analyzed for cardiac fibrosis and function. Deletion of scleraxis significantly attenuated TAC‐induced up‐regulation of major matrix proteins including collagen 1α1, 1α2, 3α1 and ED‐A fibronectin compared to scleraxis‐intact TAC mice. Masson's trichrome staining revealed that scleraxis deletion drastically reduced fibrotic areas within the myocardium compared to scleraxis‐intact TAC mice. Cardiac structural and functional analysis by echocardiography demonstrated a broad improvement in myocardial systolic and diastolic function in TAC‐operated scleraxis conditional null mice compared to scleraxis‐intact TAC animals, despite the persistency of cardiac hypertrophy in null mice. Ejection fraction and fractional shortening were significantly improved by scleraxis deletion, as was left ventricular internal diameter at both systole and diastole, while heart size normalized to body weight or tibia length was unaffected. While E/A ratio – an indicator of diastolic function – was not altered by TAC at the time points employed in this study, both early and late ventricular filling velocities were decreased in scleraxis‐intact TAC mice, and normalized in scleraxis null mice. Our results show that scleraxis is required for the up‐regulation of extracellular matrix proteins and fibrosis following pressure overload. Intriguingly, scleraxis gene deletion improved cardiac structure and function despite a lack of effect on overall hypertrophy, demonstrating that ameliorating fibrosis alone has salutary benefits. Targeting scleraxis should thus be explored as a potential means of treating cardiac fibrosis. Support or Funding Information RSN was the recipient of a PhD Graduate Studentship from Research Manitoba; MPC was supported by an Open Operating Grant from the Canadian Institutes of Health Research (MOP136862). This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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)0.001
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 score0.322
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.281
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 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

Citations0
Published2018
Admission routes3
Has abstractyes

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