ArticleToxics2022
Lipidomics Profiles and Lipid Metabolite Biomarkers in Serum of Coal Workers' Pneumoconiosis.
Article in Toxics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Noninvasive early detection and grading of pneumoconiosis via plasma proteomics and machine learning: PRSS3 as a potential biomarker.Clinical proteomics · 2026Article
- Research on the Prediction of Coal Workers' Pneumoconiosis Based on Easily Detectable Clinical Data: Machine Learning Model Development and Validation Study.JMIR medical informatics · 2026Article
- Targeting Lp-PLA2 inhibits profibrotic monocyte-derived macrophages in silicosis through restoring cardiolipin-mediated mitophagy.Cellular & molecular immunology · 2025Article
- An Analysis of Targeted Serum Lipidomics in Patients with Pneumoconiosis - China, 2022.China CDC weekly · 2023Article
- Novel lipidomes profile and clinical phenotype identified in pneumoconiosis patients.Journal of health, population, and nutrition · 2023Article
- Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022.Analytical science advances · 2023Review
- Machine learning prediction of coal workers' pneumoconiosis classification based on few-shot clinical data.Digital healthArticle
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
As a serious occupational pulmonary fibrosis disease, pneumoconiosis still lacks effective biomarkers. Previous studies suggest that pneumoconiosis may affect the body's lipid metabolism. The purpose of this study was to explore lipidomics profiles and lipid metabolite biomarkers in the serum of coal workers' pneumoconiosis (CWP) by a population case-control study. A total of 150 CWP cases and 120 healthy controls from Beijing, China were included. Blood lipids were detected in serum biochemistry. Lipidomics was performed in serum samples for high-throughput detection of lipophilic metabolites. Serum high density lipoprotein cholesterol (HDL-C) decreased significantly in CWP cases. Lipidomics data found 131 differential lipid metabolites between the CWP case and control groups. Further, the top eight most important differential lipid metabolites were screened. They all belonged to differential metabolites of CWP at different stages. However, adjusting for potential confounding factors, only three of them were significantly related to CWP, including acylhexosylceramide (AHEXCER 43:5), diacylglycerol (DG 34:8) and dimethyl-phosphatidylethanolamine (DMPE 36:0|DMPE 18:0_18:0), of which good sensitivity and specificity were proven. The present study demonstrated that lipidomics profiles could change significantly in the serum of CWP patients and that the lipid metabolites represented by AHEXCER, DG and DMPE may be good biomarkers of CWP.
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