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Record W4410553615 · doi:10.1172/jci.insight.191059

Transcriptional signatures of endothelial cells shape immune responses in cardiopulmonary health and disease

2025· review· en· W4410553615 on OpenAlexaff
Elisabeth Fließer, Katharina Jandl, Shiau-Haln Chen, Mei-Tzu Wang, Jonas C. Schupp, Wolfgang M. Kuebler, Andrew H. Baker, Grażyna Kwapiszewska

Bibliographic record

VenueJCI Insight · 2025
Typereview
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsImmune systemDiseaseImmunologyMedicineCardiovascular healthCell biologyBiologyCardiologyInternal medicine

Abstract

fetched live from OpenAlex

The cardiopulmonary vasculature and its associated endothelial cells (ECs) play an essential role in sustaining life by ensuring the delivery of oxygen and nutrients. Beyond these foundational functions, ECs serve as key regulators of immune responses. Recent advances in single-cell RNA sequencing have revealed that the cardiopulmonary vasculature is composed of diverse EC subpopulations, some of which exhibit specialized immunomodulatory properties. Evidence for immunomodulation includes distinct expression profiles associated with antigen presentation, cytokine secretion, immune cell recruitment, translocation, and clearance - functions critical for maintaining homeostasis in the heart and lungs. In cardiopulmonary diseases, ECs undergo substantial transcriptional reprogramming, leading to a shift from homeostasis to an activated state marked by heightened immunomodulatory activity. This transformation has highlighted the critical role for ECs in disease pathogenesis and their potential as future therapy targets. This Review emphasizes the diverse functions of ECs in the heart and lungs, particularly adaptive and maladaptive immunoregulatory roles in cardiopulmonary health and disease.

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 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 score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.320
Teacher spread0.287 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

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