AimEvidence linking trace minerals and periodontitis is limited. To investigate the relationship between trace minerals (selenium, manganese, lead, cadmium, and mercury) and periodontitis, data from the National Health and Nutrition Examination Survey (NHANES) were analyzed after accounting for potential confounding factors. No known studies have explored the relationship between these five trace minerals and periodontitis.Materials and methodsA total of 4,964 participants who had undergone a full-mouth periodontal examination and laboratory tests for five trace minerals were studied in a cross-sectional study. Clinical attachment loss (CAL) and periodontitis grading were used to measure periodontitis severity. Linear and logistic regression models were used to evaluate the association between trace minerals and periodontitis. Further subgroup analyses were performed.ResultsBlood lead and cadmium levels were positively associated with mean CAL, and blood selenium was negatively associated with mean CAL; however, blood mercury, blood manganese, and mean CAL were not significantly associated. The association between trace minerals and mean CAL was more significant in males, the elderly, and patients with diabetes. There was a threshold effect between blood cadmium levels and mean CAL. Among the Black population, the relationship between blood cadmium levels and mean CAL followed an inverted U-shaped curve. There was a saturation effect in the study of blood lead in people aged 45–59 years old.ConclusionOur study highlighted that blood selenium, lead, and cadmium levels were significantly associated with periodontitis in a nationally representative sample of United States adults.
Background: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has a serious threat to human health. Oral candidiasis (OC) may be one of the causes of morbidity in severe COVID-19 patients. However, there is currently no treatment for oral candidiasis and COVID-19 (OC/COVID-19). The purpose of this study was to use text mining and data analysis to investigate the target genes for treatment and explore potential therapeutic drugs for OC/COVID-19. Methods: We used the text mining tool pubmed2ensembl to detect genes associated with OC, and the dataset GSE164805 was used for the data analysis. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on the two intersection genes using the Database of Annotation, Visualization and Integrated Discovery (DAVID) platform. The protein-protein interaction (PPI) networks were constructed by STRING software, and gene module analysis was performed using Molecular Complex Detection (MCODE), a plug-in in Cytoscape. The most significant genes were selected as hub genes and their functions and pathways were analyzed using Metascape. We revealed the upstream pathway activity of the hub genes. The drug-gene interaction database (DGIdb) and the traditional Chinese medicines integrated database (TCMID) were used to discover potential drugs for the treatment of OC/COVID-19. Results: The analysis indicated that there were 2869 differentially expressed genes (DEGs) in GSE164805. We identified 161 unique genes associated with oral candidiasis through text mining. A total of 20 intersection genes were identified as the therapeutic targets for OC/COVID-19. Based on the bioinformatics analysis, nine genes (TNF, IL1B, IFNG, CSF2, ELANE, CCL2, MMP9, CXCR4, and IL1A) were identified as hub genes that were mainly enriched in the IL-17 signaling pathway, TNF signaling pathway, AGE-RAGE signaling pathway in diabetic complications and NOD-like receptor signaling pathway. We identified four of the nine genes that target five existing drugs, including BKT140, mavorixafor, sivelestat, canakinumab, and rilonacept. Furthermore, twenty herb ingredients were also screened as potential drugs. Conclusion: In this study, TNF, IL1B, IFNG, CSF2, ELANE, CCL2, MMP9, CXCR4, and IL1A were potentially key genes involved in the treatment of OC/COVID-19. Taken together five drugs and twenty herb ingredients were identified as potential therapeutic agents for OC/COVID-19 treatment and management.
Osteoporosis is a systemic skeletal disease that can easily lead to bone fractures. Berberine has been shown to be effective in treating osteoporosis. This study was conducted to identify the potential mechanism of berberine in treating this complaint. We screened potential targets of berberine and identified the osteoporosis-related differentially expressed genes (DEGs) in the microarray dataset GSE56815. Protein–protein interaction (PPI) network construction, hub targets identification, and pathway enrichment were carried out to find the potential targets. Molecular docking and molecular dynamics studies were performed to verify the combination of berberine with its treatment-related central targets. In addition, SwissADME preliminarily evaluated the physicochemical properties of berberine. Through data mining, 23 osteoporosis-related targets of berberine were selected. PPI and module analyses suggested that AKT1, MAPK1, ESR1, AR, TP53, and PTGS2 are the core targets of berberine. Docking and molecular dynamics studies showed that berberine could stably bind to core proteins to form a protein–ligand complex. The enrichment analysis showed that the estrogen signaling pathway and thyroid hormone signaling pathway play important roles in curing osteoporosis. To sum up, berberine primarily acts on AKT1, MAPK1, ESR1, AR, TP53, and PTGS2, mainly regulating the estrogen and thyroid hormone signaling pathways to treat osteoporosis in a multi-target, multi-pathway, and multi-system manner.
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