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2.
Front Immunol ; 14: 1281051, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37854598

RESUMO

[This corrects the article DOI: 10.3389/fimmu.2023.1164667.].

3.
Front Immunol ; 14: 1164667, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37215133

RESUMO

Introduction: Periodontitis is an inflammatory disease and its molecular mechanisms is not clear. A recently discovered cell death pathway called cuproptosis, may related to the disease. Methods: The datasets GSE10334 of human periodontitis and control were retrieved from the Gene Expression Omnibus database (GEO) for analysis.Following the use of two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature removal (SVM-RFE) were used to find CRG-based signature. Then the Receiver operating characteristic (ROC) curves was used to evaluate the gene signature's discriminatory ability. The CIBERSORT deconvolution algorithm was used to study the link between hub genes and distinct types of immune cells. Next, the association of the CRGs with immune cells in periodontitis and relevant clusters of cuproptosis were found. The link between various clusters was ascertained by the GSVA and CIBERSORT deconvolution algorithm. Finally, An external dataset (GSE16134) was used to confirm the diagnosis capacity of the identified biomarkers. In addition, clinical samples were examined using qRT-PCR and immunohistochemistry to verifiy the expression of genes related to cuprotosis in periodontitis and the signature may better predict the periodontitis. Results: 15 periodontitis-related DE-CRGs were found,then 11-CRG-based signature was found by using of LASSO and SVM-RFE. ROC curves also supported the value of signature. CIBERSORT results of immune cell signature in periodontitis showed that signature genes is a crucial component of the immune response.The relevant clusters of cuproptosis found that the NFE2L2, SLC31A1, FDX1,LIAS, DLD, DLAT, and DBT showed a highest expression levels in Cluster2 ,while the NLRP3, MTF1, and DLST displayed the lowest level in Cluster 2 but the highest level in Cluster1. The GSVA results also showed that the 11 cuproptosis diagnostic gene may regulate the periodontitis by affecting immune cells. The external dataset (GSE16134) confirm the diagnosis capacity of the identified biomarkers, and clinical samples examined by qRT-PCR and immunohistochemistry also verified that these cuprotosis related signiture genes in periodontitis may better predict the periodontitis. Conclusion: These findings have important implications for the cuproptosis and periodontitis, and highlight further research is needed to better understand the mechanisms underlying this relationship between the cuproptosis and periodontitis.


Assuntos
Algoritmos , Apoptose , Periodontite , Humanos , Morte Celular , Bases de Dados Factuais , Aprendizado de Máquina , Periodontite/genética , Cobre
4.
Front Mol Biosci ; 10: 1112653, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37006615

RESUMO

Osteoarthritis (OA) is a chronic joint disease with increasing prevalence. Chondrocytes (CHs) are highly differentiated end-stage cells with a secretory phenotype that keeps the extracellular matrix (ECM) balanced and the cartilage environment stable. Osteoarthritis dedifferentiation causes cartilage matrix breakdown, accounting for one of the key pathogenesis of osteoarthritis. Recently, the activation of transient receptor potential ankyrin 1 (TRPA1) was claimed to be a risk factor in osteoarthritis by causing inflammation and extracellular matrix degradation. However, the underlying mechanism is still unknown. Due to its mechanosensitive property, we speculated that the role of TRPA1 activation during osteoarthritis is matrix stiffness-dependent. In this study, we cultured the chondrocytes from patients with osteoarthritis on stiff vs. soft substrates, treated them with allyl isothiocyanate (AITC), a transient receptor potential ankyrin 1 agonist, and compared the chondrogenic phenotype, containing cell shape, F-actin cytoskeleton, vinculin, synthesized collagen profiles and their transcriptional regulatory factor, and inflammation-related interleukins. The data suggest that allyl isothiocyanate treatment activates transient receptor potential ankyrin 1 and results in both positive and harmful effects on chondrocytes. In addition, a softer matrix could help enhance the positive effects and alleviate the harmful ones. Thus, the effect of allyl isothiocyanate on chondrocytes is conditionally controllable, which could be associated with transient receptor potential ankyrin 1 activation, and is a promising strategy for osteoarthritis treatment.

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