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Abstract 14950: Single-Cell Transcriptomic Analysis Reveals Emergence of Inflammatory and Activated Arterial Endothelial Cells Promoted by Cross-Talk With Mural Cells During Development of Severe Pulmonary Arterial Hypertension

2022· article· en· W4380997330 on OpenAlexaff
Nicholas D Cober, Emma R. McCourt, Rafael Soares Godoy, Yupu Deng, Ken Schlosser, David P. Cook, Liyuan Wang, Duncan J. Stewart

Bibliographic record

VenueCirculation · 2022
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsOttawa Public Health
Fundersnot available
KeywordsMedicineTranscriptomeProinflammatory cytokinePulmonary hypertensionHypoxia (environmental)Internal medicineGene expressionCardiologyPathologyInflammationGeneBiology

Abstract

fetched live from OpenAlex

Introduction: Pulmonary arterial hypertension (PAH) is a lethal disease characterized by occlusive arterial remodelling thought to be triggered by endothelial cell (EC) injury; however, the pathobiological mechanisms are poorly understood. We employed single cell RNA sequencing (scRNAseq) to define transcriptomic changes in the SU5416/chronic hypoxia (SU/CH) rat model. Methods: Sprague-Dawley rats were injected with 20mg/kg SU subcutaneously and exposed to 3 weeks of CH (10% O 2 ). Right ventricular systolic pressure (RVSP) was measured at baseline, 1, 3, 5, and 8-weeks, then lungs were explanted, digested, and dissociated into single cells which were sequenced using the 10x genomics platform. Results: Elevation of RVSP plateaued at >100 mmHg by 5 weeks. Dimensionality reduction of the scRNAseq data was performed using Uniform Manifold Approximation and Projection (UMAP) analysis resulting in 24 lung clusters. Cell prioritization analysis performed using Augur identified vascular cells as the most affected by SU/CH, including arterial ECs, pericytes, and gCap ECs. After sub-clustering the EC populations, eight distinct clusters were identified representing all expected subtypes (capillary, arterial, venous, and lymphatic). As well, two novel EC clusters were detected. The first showed reduced expression of classical EC genes ( Cdh5 , Cldn5 ) and increased proinflammatory markers ( RT1-Da , Cd74 ), termed ‘inflammatory’ ECs. The second was an arterial cluster that exhibited reduced expression of Dll4 and increased Cxcl12 and Fn1 , termed ‘activated’ arterial ECs. Both populations emerging at 1-week post SU, persisting throughout PAH progression. While many EC populations showed marked differential gene expression (DGE) at 1 week, the activated arterial cluster was the only cluster showing progression of DGE throughout progression of PAH. Receptor-ligand analysis with NicheNet identified activated arterial ECs as a top receiver cell responding to multiple ligands, including Bmp4/5 , Col4a1 , and Vegfa/c, which were largely derived from mural fibroblasts. Conclusion: Emergence of inflammatory and activated arterial ECs likely contribute to vascular remodelling associated with PAH promoted by cross-talk with lung stromal cells.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.017
GPT teacher head0.231
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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