ArticleFrontiers in genetics2020
Detecting the Multiomics Signatures of Factor-Specific Inflammatory Effects on Airway Smooth Muscles.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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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.
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Who cites it
26 citing papers in PubMed, 34 citations in OpenAlex.
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- A potential host and virus targeting tool against COVID-19: Chemical characterization, antiviral, cytoprotective, antioxidant, respiratory smooth muscle relaxant effects of Paulownia tomentosa Steud.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2023Article
- Vascular dysfunction in COVID-19 patients: update on SARS-CoV-2 infection of endothelial cells and the role of long non-coding RNAs.Clinical science (London, England : 1979) · 2022Article
- Article
- Screening gene signatures for clinical response subtypes of lung transplantation.Molecular genetics and genomics : MGG · 2022Article
- Detecting Blood Methylation Signatures in Response to Childhood Cancer Radiotherapy via Machine Learning Methods.Biology · 2022Article
- Predicting Heart Cell Types by Using Transcriptome Profiles and a Machine Learning Method.Life (Basel, Switzerland) · 2022Article
- Prolonged viral shedding prediction on non-hospitalized, uncomplicated SARS-CoV-2 patients using their transcriptome data.Computer methods and programs in biomedicine update · 2022Article
- Recognition of Immune Cell Markers of COVID-19 Severity with Machine Learning Methods.BioMed research international · 2022Article
- Identification of Type 2 Diabetes Biomarkers From Mixed Single-Cell Sequencing Data With Feature Selection Methods.Frontiers in bioengineering and biotechnology · 2022Article
- Identification of cortical interneuron cell markers in mouse embryos based on machine learning analysis of single-cell transcriptomics.Frontiers in neuroscience · 2022Article
- Similarity-Based Method with Multiple-Feature Sampling for Predicting Drug Side Effects.Computational and mathematical methods in medicine · 2022Article
- Predicting RNA 5-Methylcytosine Sites by Using Essential Sequence Features and Distributions.BioMed research international · 2022Article
- Identifying luminal and basal mammary cell specific genes and their expression patterns during pregnancy.PloS one · 2022Article
- Identifying Lung Cancer Cell Markers with Machine Learning Methods and Single-Cell RNA-Seq Data.Life (Basel, Switzerland) · 2021Article
- Predicting gene phenotype by multi-label multi-class model based on essential functional features.Molecular genetics and genomics : MGG · 2021Article
- Analysis of the Sequence Characteristics of Antifreeze Protein.Life (Basel, Switzerland) · 2021Article
- Article
- Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.Frontiers in genetics · 2021Article
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smooth muscles are a specific muscle subtype that is widely identified in the tissues of internal passageways. This muscle subtype has the capacity for controlled or regulated contraction and relaxation. Airway smooth muscles are a unique type of smooth muscles that constitute the effective, adjustable, and reactive wall that covers most areas of the entire airway from the trachea to lung tissues. Infection with SARS-CoV-2, which caused the world-wide COVID-19 pandemic, involves airway smooth muscles and their surrounding inflammatory environment. Therefore, airway smooth muscles and related inflammatory factors may play an irreplaceable role in the initiation and progression of several severe diseases. Many previous studies have attempted to reveal the potential relationships between interleukins and airway smooth muscle cells only on the omics level, and the continued existence of numerous false-positive optimal genes/transcripts cannot reflect the actual effective biological mechanisms underlying interleukin-based activation effects on airway smooth muscles. Here, on the basis of newly presented machine learning-based computational approaches, we identified specific regulatory factors and a series of rules that contribute to the activation and stimulation of airway smooth muscles by IL-13, IL-17, or the combination of both interleukins on the epigenetic and/or transcriptional levels. The detected discriminative factors (genes) and rules can contribute to the identification of potential regulatory mechanisms linking airway smooth muscle tissues and inflammatory factors and help reveal specific pathological factors for diseases associated with airway smooth muscle inflammation on multiomics levels.
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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 Socratic graph.