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Record W4230768631 · doi:10.1210/en.142.2.544

Cardiac Ion Channel Expression and Contractile Function in Mice with Deletion of Thyroid Hormone Receptor   or  

2001· article· en· W4230768631 on OpenAlexfundno aff
B. Gloss

Bibliographic record

VenueEndocrinology · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsnot available
FundersMedical Research CouncilFondation pour la Recherche MédicaleHeart and Stroke Foundation of Canada
KeywordsInternal medicineEndocrinologyMedicineRepolarizationEuthyroidThyroidElectrophysiology

Abstract

fetched live from OpenAlex

Cardiac myocytes express the two thyroid hormone receptors (T3Rs), T3Rα and T3Rβ. However, which isoform contributes to specific, T3-induced alterations of cardiac function remains unclear. Here, we used individual T3R isoform knockout (KO) mice to study the effects of T3Rα and T3Rβ in the heart. Our findings indicate that potassium channel genes that code for K+ channels involved in action potential repolarization, like KV 4.2 and minK, are T3Rα targets. Both are markedly regulated by thyroid status. The recently identified cyclic nucleotide-gated channels, HCN2 and HCN4, are targets of T3Rα and are unchanged in a euthyroid T3Rβ KO. However, these transcripts respond markedly to altered T3 signaling concomitant with bradycardia in T3Rα KO and hypothyroid animals, as well as tachycardia in hyperthyroid T3Rβ KO mice. SERCA2a and myosins are T3 regulated and were also targets of T3Rα, and the papillary muscles of αKO animals showed a slowed rate of force development. Because of the absence of significant cardiac effects in euthyroid T3Rβ KO mice, we determined messenger RNA levels for both T3Rα and T3Rβ in the heart. We found that T3Rβ is present at a 1:3 ratio to T3Rα1. We conclude that the cardiac phenotype regulated by T3 is predominantly mediated by T3Rα and that the lack of T3Rα cannot be compensated by T3Rβ in the heart.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.227
Teacher spread0.217 · 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

Citations49
Published2001
Admission routes1
Has abstractyes

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