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Myocardial and Skeletal Muscle Microvascular Dysfunction Manifests Prior to Diabetic Cardiomyopathy: Sex-Dependent Differences

2024· article· en· W4398166799 on OpenAlexaffabout
Sadi Loai, Hai‐Ling Margaret Cheng

Bibliographic record

VenuePhysiology · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiabetic cardiomyopathySkeletal muscleCardiomyopathyInternal medicineCardiologyMedicineDiabetes mellitusCardiac muscleEndocrinologyHeart failure

Abstract

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Introduction: Microvascular dysfunction is a recognized sign of disease in heart failure progression. Blood vessels exhibit abnormal vasoreactivity in early stage, subsequently deteriorating to rarefaction and reduced perfusion. In managing heart failure patients, where diagnosis is typically possible only when the hypertrophic heart is irreversibly damaged, earlier diagnosis is key to improving management. In this study, we apply a blood-pool MRI method for assessing vasomodulation to investigate if it can sensitively detect abnormal leg muscle vasoreactivity posited to manifest before myocardial mvD. Methods: Male and female Sprague-Dawley rats were maintained on a high-fat, high-sugar diet or a control diet for 6 months after the induction of diabetes. Beginning at month 1 or 2 post-induction and every 2 months thereafter, rats underwent blood-pool MRI to assess vasoreactivity in the heart or skeletal muscle, respectively. Ablavar, a T1-reducing blood-pool contrast agent, was administered and the T1 relaxation time dynamically measured as animals breathed in mild CO 2 levels to modulate vessels and elicit a vasodilatory response. CO 2 levels were set at 5% for skeletal muscle and 10% for cardiac muscle, and the gas was administered for 10 minutes. At the final timepoint, invasive laser Doppler perfusion measurements in leg muscle were recorded to verify MRI results. Results/Discussion: In this study, we provide the first demonstration that both skeletal muscle and myocardial microvascular vasoreactivity is altered in a non-obese rodent model of type II diabetes, prior to the development of heart failure symptoms. In male rats, the normally unresponsive heart to 10% CO 2 reveals a pro-vasoconstriction response beginning at 5 months post-diabetes. Abnormal leg skeletal muscle vasoreactivity appeared even earlier, at 2 months: the usual vasodilatory response to 5% CO 2 is interrupted with periods of vasoconstriction in diseased rats. In female rats, differences were observed between healthy and diseased animals only within the first two months post-diabetes and not later. In the heart, vasodilation to 10% CO 2 seen in healthy animals was abolished in diabetes. In skeletal muscle, 5% CO 2 was suboptimal in inducing reproducible vasoreactivity, but young diabetic females responded by vasodilation only. Conclusion: Abnormal vasoreactivity presents earlier than overt structural and functional cardiac changes in both sexes in HFpEF and can be detected using blood-pool MRI in leg skeletal muscle before the myocardium. Our non-invasive MRI technology sets the foundation for a paradigm shift in diagnosing mvD during the early stages of HFpEF, opening the door for early intervention. This work was supported by the Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation/Ontario Research Fund, Dean’s Spark Professorship, Medicine by Design Pivotal Experiment Fund [to H.L.M.C.]; Ted Rogers Centre for Heart Research PhD Education Fund, Scintica Instrumentation Inc [to S.L.]. This is the full abstract presented at the American Physiology Summit 2024 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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.233
Teacher spread0.223 · 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 designObservational
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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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