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Record W4390512075 · doi:10.1016/j.apsb.2023.12.018

Cardiac resident macrophages: Spatiotemporal distribution, development, physiological functions, and their translational potential on cardiac diseases

2024· article· en· W4390512075 on OpenAlexaff
Jing Jin, Yurou Wang, Yueqin Liu, Subrata Chakrabarti, Zhaoliang Su

Bibliographic record

VenueActa Pharmaceutica Sinica B · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsWestern University
FundersGovernment of Jiangsu ProvinceSix Talent Peaks Project in Jiangsu ProvinceNational Natural Science Foundation of ChinaJiangsu Commission of Health
KeywordsCardiac cellNeuroscienceRegeneration (biology)PopulationMedicineComputational biologyBioinformaticsBiologyCell biologyInternal medicine

Abstract

fetched live from OpenAlex

Cardiac resident macrophages (CRMs) are the main population of cardiac immune cells. The role of these cells in regeneration, functional remodeling, and repair after cardiac injury is always the focus of research. However, in recent years, their dynamic changes and contributions in physiological states have a significant attention. CRMs have specific phenotypes and functions in different cardiac chambers or locations of the heart and at different stages. They further show specific differentiation and development processes. The present review will summarize the new progress about the spatiotemporal distribution, potential developmental regulation, and their roles in cardiac development and aging as well as the translational potential of CRMs on cardiac diseases. Of course, the research tools for CRMs, their respective advantages and disadvantages, and key issues on CRMs will further be discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.849

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 head0.037
GPT teacher head0.319
Teacher spread0.283 · 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 designNot applicable
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

Citations7
Published2024
Admission routes1
Has abstractyes

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