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Record W4392967976 · doi:10.1016/j.carpath.2024.107635

Cellular and molecular mechanisms driving cardiac tissue fibrosis: On the precipice of personalized and precision medicine

2024· article· en· W4392967976 on OpenAlexafffund
Ali Fatehi Hassanabad, Anna N. Zarzycki, Paul W.M. Fedak

Bibliographic record

VenueCardiovascular Pathology · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
FundersCumming School of Medicine, University of Calgary
KeywordsFibrosisCardiac fibrosisMedicineHeart failurePathogenesisBioinformaticsPathologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Cardiac fibrosis is a significant contributor to heart failure, a condition that continues to affect a growing number of patients worldwide. Various cardiovascular comorbidities can exacerbate cardiac fibrosis. While fibroblasts are believed to be the primary cell type underlying fibrosis, recent and emerging data suggest that other cell types can also potentiate or expedite fibrotic processes. Over the past few decades, clinicians have developed therapeutics that can blunt the development and progression of cardiac fibrosis. While these strategies have yielded positive results, overall clinical outcomes for patients suffering from heart failure continue to be dire. Herein, we overview the molecular and cellular mechanisms underlying cardiac tissue fibrosis. To do so, we establish the known mechanisms that drive fibrosis in the heart, outline the diagnostic tools available, and summarize the treatment options used in contemporary clinical practice. Finally, we underscore the critical role the immune microenvironment plays in the pathogenesis of cardiac fibrosis.

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)0.002
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 score0.247
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.012
GPT teacher head0.248
Teacher spread0.235 · 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

Citations12
Published2024
Admission routes2
Has abstractyes

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