Objective:To mine genes highly related to the pathogenesis of ovarian cancer by using multichip integrated bioinformatics methods and verify them in cells,which provided key genes and important theoretical basis for t...Objective:To mine genes highly related to the pathogenesis of ovarian cancer by using multichip integrated bioinformatics methods and verify them in cells,which provided key genes and important theoretical basis for targeted research of ovarian cancer.Methods:Three datasets,GSE38666,GSE40595 and GSE54388,were downloaded from the Gene Expression Integrated Database database for differential gene(DEGs)screening,including 26 normal samples and 65 ovarian cancer samples.Gene ontology functional annotation of selected DEGs was performed through DAVID online database to clarify the biological characteristics of DEGs.The main pathways of DEGs were obtained by enrichment analysis using Kyoto gene and genomic encyclopedia method.Based on the STRING database,the DEGs protein-protein interaction network was constructed by using CytoScape software,and the key genes were screened by GEPIA2 database to verify the expression at the cell level.Results:A total of 238 DEGs were screened from GSE38666,GSE40595 and GSE54388 datasets,of which 168 DEGs were upregulated and 70 DEGs were down-regulated.The co-expressed DEGs were mainly enriched in biological functions such as mitotic nuclear division,spindle,chromosomal region and DNA helicase activity in ovarian cancer.They were mainly involved in biological processes such as cell cycle,DNA replication,oxidative phosphorylation and biosynthesis of amino acids,thereby affecting the occurrence and development of ovarian cancer.Six genes were highly expressed and associated with the development of ovarian cancer,including IFI27,EPCAM,CXCR4,PEA15,CLDN3 and CAPG.Cell verification showed that the mRNA expression of the six genes in ovarian cancer cells was higher than that in normal ovarian cells(P<0.05),which was consistent with the previous screening results.Conclusion:Multi-chip integrated bioinformatics is an effective method to find ovarian cancer target genes.IFI27,EPCAM,CXCR4,PEA15,CLDN3 and CAPG are highly correlated with the occurrence and development of ovarian cancer,which can be used as target genes for ovarian cancer research.展开更多
Residual antimicrobial agents in wastewater and solid waste from antimicrobial manufacturing facilities can potentially contaminate environments.The World Health Organization has established technical guidelines for m...Residual antimicrobial agents in wastewater and solid waste from antimicrobial manufacturing facilities can potentially contaminate environments.The World Health Organization has established technical guidelines for managing antimicrobial resistance(AMR)in pharmaceutical wastewater and solid waste.However,the scarcity of publicly available data on antimicrobial manufacturing processes impedes the development of effective mitigation strategies.To address this knowledge gap,we developed a comprehensive database documenting antibiotics and antibiotic resistance genes(ARGs)in actual wastewater and solid waste samples,primarily fermentation residues.Through systematic review methodology,we compiled data from extensive searches of Englishlanguage article databases,including Web of Science and PubMed.The database contains data from 270 distinct samples collected across 45 fermentation residue treatment systems and 46 wastewater treatment systems,derived from 70 published English-language articles spanning 2008 to 2024.In operational pharmaceutical facilities,antibiotic concentrations ranged from 82 to 1,663 mg/L in raw wastewater and from 1,000 to 10,182 mg/kg dry matter(DM)in antibiotic fermentation residues.Various treatment technologies demonstrated significant reductions in both antibiotic concentrations and ARG levels within wastes.This database provides the first global perspective on antibiotic and ARG contamination from antibiotic production processes,supporting AMR management initiatives.It establishes a dynamic,continuously updated platform accessible to researchers and industry stakeholders via the link:https://dash.drwater.net/antiboard/.展开更多
基金High-level Talents Project of Hainan Natural Science Foundation(No.821RC691)the Key R&D project of Hainan Province(No.ZDYF2022SHFZ071)。
文摘Objective:To mine genes highly related to the pathogenesis of ovarian cancer by using multichip integrated bioinformatics methods and verify them in cells,which provided key genes and important theoretical basis for targeted research of ovarian cancer.Methods:Three datasets,GSE38666,GSE40595 and GSE54388,were downloaded from the Gene Expression Integrated Database database for differential gene(DEGs)screening,including 26 normal samples and 65 ovarian cancer samples.Gene ontology functional annotation of selected DEGs was performed through DAVID online database to clarify the biological characteristics of DEGs.The main pathways of DEGs were obtained by enrichment analysis using Kyoto gene and genomic encyclopedia method.Based on the STRING database,the DEGs protein-protein interaction network was constructed by using CytoScape software,and the key genes were screened by GEPIA2 database to verify the expression at the cell level.Results:A total of 238 DEGs were screened from GSE38666,GSE40595 and GSE54388 datasets,of which 168 DEGs were upregulated and 70 DEGs were down-regulated.The co-expressed DEGs were mainly enriched in biological functions such as mitotic nuclear division,spindle,chromosomal region and DNA helicase activity in ovarian cancer.They were mainly involved in biological processes such as cell cycle,DNA replication,oxidative phosphorylation and biosynthesis of amino acids,thereby affecting the occurrence and development of ovarian cancer.Six genes were highly expressed and associated with the development of ovarian cancer,including IFI27,EPCAM,CXCR4,PEA15,CLDN3 and CAPG.Cell verification showed that the mRNA expression of the six genes in ovarian cancer cells was higher than that in normal ovarian cells(P<0.05),which was consistent with the previous screening results.Conclusion:Multi-chip integrated bioinformatics is an effective method to find ovarian cancer target genes.IFI27,EPCAM,CXCR4,PEA15,CLDN3 and CAPG are highly correlated with the occurrence and development of ovarian cancer,which can be used as target genes for ovarian cancer research.
基金Supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0750400)the Basic Science Center Project of the Natural Science Foundation of China(52388101)the China Postdoctoral Innovation Talents Support Program(BX20230400).
文摘Residual antimicrobial agents in wastewater and solid waste from antimicrobial manufacturing facilities can potentially contaminate environments.The World Health Organization has established technical guidelines for managing antimicrobial resistance(AMR)in pharmaceutical wastewater and solid waste.However,the scarcity of publicly available data on antimicrobial manufacturing processes impedes the development of effective mitigation strategies.To address this knowledge gap,we developed a comprehensive database documenting antibiotics and antibiotic resistance genes(ARGs)in actual wastewater and solid waste samples,primarily fermentation residues.Through systematic review methodology,we compiled data from extensive searches of Englishlanguage article databases,including Web of Science and PubMed.The database contains data from 270 distinct samples collected across 45 fermentation residue treatment systems and 46 wastewater treatment systems,derived from 70 published English-language articles spanning 2008 to 2024.In operational pharmaceutical facilities,antibiotic concentrations ranged from 82 to 1,663 mg/L in raw wastewater and from 1,000 to 10,182 mg/kg dry matter(DM)in antibiotic fermentation residues.Various treatment technologies demonstrated significant reductions in both antibiotic concentrations and ARG levels within wastes.This database provides the first global perspective on antibiotic and ARG contamination from antibiotic production processes,supporting AMR management initiatives.It establishes a dynamic,continuously updated platform accessible to researchers and industry stakeholders via the link:https://dash.drwater.net/antiboard/.
