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Record W4401549041 · doi:10.1016/j.cjca.2024.08.266

KCa3.1 Promotes the Migration of Macrophages From Epicardial Adipose Tissue to Induce Vulnerability to Atrial Fibrillation During Rapid Pacing

2024· article· en· W4401549041 on OpenAlexvenueno aff
Yuanjia Ke, Zhen Cao, Xuewen Wang, Dishiwen Liu, Yuntao Fu, Huiyu Chen, Yanni Cheng, Kexin Guo, Yajia Li, X. Y. Long, Mei Yang, Qingyan Zhao

Bibliographic record

VenueCanadian Journal of Cardiology · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsnot available
FundersNational Institutes of HealthWuhan UniversityNational Natural Science Foundation of China
KeywordsMedicineAtrial fibrillationEpicardial adipose tissueAdipose tissueCardiologyInternal medicineVulnerability (computing)Epicardial fatComputer security

Abstract

fetched live from OpenAlex

BACKGROUND: 3.1 in the migration of macrophages from EAT to adjacent atrial tissue during rapid pacing. METHODS: Part 1: Eighteen beagles were randomly divided into the sham group, pacing group, and pacing + clodronate liposome (CL) group. Part 2: Eighteen beagles were randomly divided into the sham group, pacing group, and pacing + TRAM-34 group. HL-1 cells and RAW264.7 cells were co-cultured to explore the specific migratory mechanism of macrophages. RESULTS: 3.1 regulated CCL2 secretion through the p65/STAT3 signalling pathway. CONCLUSIONS: 3.1 regulates CCL2 may be related to the p65/STAT3 signalling pathway.

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)0.001
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 score0.689
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.013
GPT teacher head0.261
Teacher spread0.248 · 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".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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