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Record W2096162303 · doi:10.1093/cvr/cvn060

Heat shock proteins as molecular targets for intervention in atrial fibrillation

2008· review· en· W2096162303 on OpenAlexaff
B Brundel, Lu Ke, Anne‐Jan Dijkhuis, X. Y. Qi, Akiko Shiroshita-Takeshita, Stanley Nattel, Robert H. Henning, Harm H. Kampinga

Bibliographic record

VenueCardiovascular Research · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsAtrial fibrillationHeat shock proteinCardiologyShock (circulatory)MedicineInternal medicineChemistryBiochemistryGene

Abstract

fetched live from OpenAlex

Atrial fibrillation (AF) is the most common sustained clinical tachyarrhythmia. AF is a progressive condition as demonstrated by the finding that maintenance of normal rhythm and contractile function becomes more difficult the longer AF exists. AF causes cellular stress, which induces atrial remodelling, involving reduction in the expression of L-type Ca(2+) channels and structural changes (myolysis), finally resulting in contractile dysfunction. Heat shock proteins (HSPs) comprise a family of proteins involved in the protection against different forms of cellular stress. Their classical function is the prevention of toxic protein aggregation by binding to (partially) unfolded proteins. Recent investigations reveal that HSPs prevent atrial remodelling and attenuate the promotion of AF in both cellular and animal experimental models. Furthermore, studies in humans suggest a protective role for HSPs against progression from paroxysmal AF to chronic, persistent AF. Therefore, manipulation of the HSP system may offer novel therapeutic approaches for the prevention of atrial remodelling. Such approaches may contribute to the maintenance or restoration of tissue integrity and contractile function. Ultimately, this concept may offer an additional treatment strategy to delay progression towards chronic AF and/or improve the outcome of cardioversion.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.006
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.080
GPT teacher head0.413
Teacher spread0.333 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations62
Published2008
Admission routes1
Has abstractyes

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