ArticleHeliyon2020
Urinary metabolomic signatures in reticular oral lichen planus.
Article in Heliyon, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Metabolomic analysis reveals key changes in amino acid metabolism in colorectal cancer patients.Amino acids · 2025Article
- Epinephrine as a potential driver of oral lichen planus pathogenesis.Animal cells and systems · 2025Article
- Metabolomic Profiling of Oral Potentially Malignant Disorders and Its Clinical Values.Biomedicines · 2024Review
- Microbiome landscape of lesions and adjacent normal mucosal areas in oral lichen planus patient.Frontiers in microbiology · 2022Article
- Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Oral lichen planus (OLP) is a chronic inflammatory disease. Among all the clinical forms in OLP, reticular type has the highest incidence rate. Previous studies have applied metabolomics to investigate the metabolic changes of oral mucosa and blood samples from reticular OLP patients. Urinary metabolomic signatures is also useful in analyzing the pathological changes of the patients, which was a complement to the previous studies. Through these researches, we may have a more comprehensive understanding of the disease. Metabolic profiles of urinary samples from OLP patients and control subjects were analyzed by liquid chromatography (LC)-mass spectrometry (MS) system. Differentially expressed metabolites were identified via OSI/SMMS software for the pathology analysis. Totally, 30 differentially expressed metabolites were identified. Pathological network showed that these metabolites participated in 8 pathological processes, that is, DNA damage and repair disorder, apoptosis process, inflammatory lesion, oxidative stress injury, carbohydrate metabolism disorder, mood dysfunction, abnormal energy expenditure, and other pathological process. These findings demonstrated that the analysis of human urine metabolome might be conducive to the achievement of the objectives of this study.
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Registered trials
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