ArticleFrontiers in immunology2021
Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits.
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 19 citations in OpenAlex.
- Secondary Immune Surveillance via upregulation of C-type lectin receptors.Npj gut and liver · 2026Article
- Exploring Functionally Enhanced BLP-Trained Macrophage Subpopulations in S. Aureus Infection: Underlying Mechanisms and Therapeutic Significance.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- CCR2Cellular & molecular immunology · 2025Article
- Immune-enhancing neutrophils reprogrammed by subclinical low-dose endotoxin in cancer treatment.EMBO molecular medicine · 2024Article
- Altered DNA methylation underlies monocyte dysregulation and immune exhaustion memory in sepsis.Cell reports · 2024Article
- Single-nucleus transcriptomic analysis reveals the relationship between gene expression in oligodendrocyte lineage and major depressive disorder.Journal of translational medicine · 2024Article
- Immune Homeostasis Maintenance Through Advanced Immune Therapeutics to Target Atherosclerosis.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Effect of stretching on inflammation in a subcutaneous carrageenan mouse model analyzed at single-cell resolution.Journal of cellular physiology · 2023Article
- Comparative analyses of monocyte memory dynamics from mice to humans.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2023Article
- Generation of resolving memory neutrophils through pharmacological training with 4-PBA or genetic deletion of TRAM.Cell death & disease · 2022Article
- Article
- Multi-Omics Integration Reveals Only Minor Long-Term Molecular and Functional Sequelae in Immune Cells of Individuals Recovered From COVID-19.Frontiers in immunology · 2022Article
- Insights Into Long Non-Coding RNA and mRNA Expression in the Jejunum of Lambs Challenged WithFrontiers in veterinary science · 2022Article
- Monocyte programming by cancer therapy.Frontiers in immunology · 2022Review
- Simultaneous C5 and CD14 inhibition limits inflammation and organ dysfunction in pig polytrauma.Frontiers in immunology · 2022Article
- Development of Exhausted Memory Monocytes and Underlying Mechanisms.Frontiers in immunology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compound which can reduce the inflammation caused by SD-LPS. To understand the gene regulatory networks of these processes, we have generated scRNA-seq data from mouse monocytes treated with these compounds and identified 11 novel cell clusters. We have developed a machine learning method to integrate scRNA-seq, ATAC-seq, and binding motifs to characterize gene regulatory networks underlying these cell clusters. Using guided regularized random forest and feature selection, our method achieved high performance and outperformed a traditional enrichment-based method in selecting candidate regulatory genes. Our method is particularly efficient in selecting a few candidate genes to explain observed expression pattern. In particular, among 531 candidate TFs, our method achieves an auROC of 0.961 with only 10 motifs. Finally, we found two novel subpopulations of monocyte cells in response to SD-LPS and we confirmed our analysis using independent flow cytometry experiments. Our results suggest that our new machine learning method can select candidate regulatory genes as potential targets for developing new therapeutics against low grade inflammation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.