1.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
2.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
3.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
4.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
5.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
6.Identification and expression analysis of the YABBY gene family in strawberry.
Tingting YU ; Shurong SHEN ; Yiling XU ; Xinyu WANG ; Yao YU ; Bojun MA ; Xifeng CHEN
Chinese Journal of Biotechnology 2024;40(1):104-121
YABBY proteins are important transcription factors that regulate morphogenesis and organ development in plants. In order to study the YABBY of strawberry, bioinformatic technique were used to identify the YABBY gene families in Fragaria vesca (diploid) and Fragaria×ananassa (octoploid), and then analyze the sequence characters, phylogeny and collinearity of the family members. The RNA-seq data and the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) technique were used to assay the expression patterns of the family members. A green fluorescent protein (GFP) was fused with FvYABBYs and transiently expressed in tobacco leaf cells for the subcellular localization. As the results, six FvYABBY genes and 26 FxaYABBY genes were identified from F. vesca and F.×ananassa, respectively. The FvYABBY genes were grouped into five clades, and five family members were orthologous with AtYABBY genes of Arabidopsis. In F. vesca, all of the FvYABBYs were basically not expressed not expressed in root and receptacle, while FvYABBY1, FvYABBY2, FvYABBY5 and FvYABBY6 were highly expressed in leaf, shoot, flower and achene. In F.×ananassa, FxaYABBY1, FxaYABBY2, FxaYABBY5 and FxaYABBY6 were expressed in achene, and all FxaYABBY were poorly or not expressed in receptacle. Additionally, under the abiotic stresses of low temperature, high salt and drought, the expression of FvYABBY1, FvYABBY3, FvYABBY4 and FvYABBY6 were down-regulated, FvYABBY5 was up-regulated, and FvYABBY2 was up-regulated and then down-regulated. In tobacco leaf cells, the subcellular localization of FvYABBY proteins were in the nucleus. These results provides a foundation for the functional researches of YABBY gene in strawberry.
Fragaria/genetics*
;
Arabidopsis
;
Biological Assay
;
Cold Temperature
;
Computational Biology
7.The role of iron-uptake factor PiuB in pathogenicity of soybean pathogen Xanthomonas axonopodis pv. glycines.
Ruyi SU ; Luojia JIN ; Jiangling XU ; Huiya GENG ; Xiao CHEN ; Siyi LIN ; Wei GUO ; Zhiyuan JI
Chinese Journal of Biotechnology 2024;40(1):177-189
Iron is an essential element for living organisms that plays critical roles in the process of bacterial growth and metabolism. However, it remains to be elucidated whether piuB encoding iron-uptake factor is involved in iron uptake and pathogenicity of Xanthomonas axonopodis pv. glycines (Xag). To investigate the function of piuB, we firstly generated a piuB deletion mutant (ΔpiuB) by homologous recombination. Compared with the wild-type, the piuB mutant exhibited significantly reduced growth and virulence in host soybean. The mutant displayed markedly increased siderophore secretory volume, and its sensitivity to Fe3+, Cu2+, Zn2+ and Mn2+ was significantly enhanced. Additionally, the H2O2 resistance, exopolysaccharide yield, biofilm formation, and cell mobility of ΔpiuB were significantly diminished compared to that of the wild-type. The addition of exogenous Fe3+ cannot effectively restore the above characteristics of ΔpiuB. However, expressing piuB in trans rescued the properties lost by ΔpiuB to the levels in the wild-type. Taken together, our results demonstrated that PiuB is a potential factor for Xag to assimilate Fe3+, and is necessary for Xag to be pathogenic in host soybean.
Iron
;
Glycine max
;
Virulence
;
Xanthomonas axonopodis/genetics*
;
Hydrogen Peroxide
8.Correlation between nociceptin/orphanin FQ(N/OFQ)and perioperative myocardial injury in elderly patients with coronary heart disease
Danyan ZHU ; Chang XIONG ; Wenyong PENG ; Duojia XU ; Zhijian LAN
China Modern Doctor 2024;62(11):7-10,14
Objective To evaluate the relationship between perioperative myocardial injury(PMI)and serum N/OFQ levels in elderly patients with coronary heart disease.Methods Totally 120 elderly patients who underwent hip fracture surgery under general anesthesia from January 2022 to May 2023 were included,including 60 patients with coronary heart disease(CHD group)and 60 patients without coronary heart disease(control group).The venous blood of patients was collected 10 minutes before anesthesia induction(T0),12 hours after surgery(T1)and 24 hours after surgery(T2)to detect the content of N/OFQ and high-sensitivity myocardial troponin I(hs-cTnI)in serum.Record perioperative adverse cardiovascular events(PACE)and the use of vasoactive drugs during surgery.Results Compared with the control group,the N/OFQ and hs cTnI levels at T0 and T1 in the CHD group were significantly increased(P<0.05).There was a positive correlation between N/OFQ and hs-cTnI levels at T1 and T2 in CHD and control group(P<0.05).The use of PACE and intraoperative vasoactive drugs in the CHD group was higher than that in the control group(P<0.05).Conclusion There is a correlation between the increased N/OFQ content and PMI in elderly patients with coronary heart disease after surgery,which may become an early predictive indicator of PMI.
9.Isoliensinine affects the proliferation, apoptosis and autophagy of colon cancer SW480 cells through PI3K/Akt/mTOR signaling pathway
WANG Xiangning ; ZHANG Jinhua ; JIANG Na ; LIU Zhiping ; XU Ying
Chinese Journal of Cancer Biotherapy 2024;31(7):694-699
[摘 要] 目的:探讨异莲心碱(Iso)通过PI3K/Akt/mTOR信号通路对结肠癌SW480细胞增殖、凋亡和自噬的影响。方法:用10、20和40 μmol/L的Iso处理结肠癌SW480细胞,CCK-8法、流式细胞术和WB法分别检测Iso对细胞增殖活力、凋亡和自噬相关蛋白LC3Ⅰ、LC3Ⅱ、p62表达的影响。然后,用20 μmol/L的Iso和25 μmol/L的PI3K激活剂740 Y-P分别处理SW480细胞,将细胞分为对照组、740 Y-P组、Iso组和Iso+740 Y-P组,流式细胞术、WB法检测Iso和740 Y-P对各组细胞凋亡及细胞中LC3Ⅰ、LC3Ⅱ、p62、PI3K、p-PI3K、 mTOR和p-mTOR蛋白表达的影响。结果:10、20和40 μmol/L的Iso处理后,SW480细胞增殖活力均显著下降(均P<0.05),细胞凋亡率均显著升高(均P<0.05),LC3Ⅱ/LC3Ⅰ表达均显著上调(均P<0.05),p26蛋白表达显著下调(P<0.05)。Iso和740 Y-P处理后,与对照组相比,740 Y-P组细胞凋亡率、LC3Ⅱ/LC3Ⅰ表达均显著下降(均P<0.05),p26、p-PI3K/PI3K和p-mTOR/mTOR表达均显著升高(均P<0.05);Iso组细胞凋亡率、LC3Ⅱ/LC3Ⅰ表达升高(均P<0.05),p26、p-PI3K/PI3K和p-mTOR/mTOR表达均显著下降(均P<0.05);与740 Y-P组相比,Iso+740 Y-P组细胞凋亡率、LC3Ⅱ/LC3Ⅰ表达升高(P<0.05),p26、p-PI3K/PI3K和p-mTOR/mTOR表达均显著下降(均P<0.05);与Iso组相比,Iso+740 Y-P组细胞凋亡率、LC3Ⅱ/LC3Ⅰ表达下降(均P<0.05),p26、p-PI3K/PI3K和p-mTOR/mTOR表达均显著升高(均P<0.05)。结论:Iso通过抑制PI3K/Akt/mTOR信号通路抑制结肠癌SW480细胞增殖并诱导细胞凋亡和自噬。
10.Expert consensus on clinical application of 177Lu-prostate specific membrane antigen radio-ligand therapy in prostate cancer
Guobing LIU ; Weihai ZHUO ; Yushen GU ; Zhi YANG ; Yue CHEN ; Wei FAN ; Jianming GUO ; Jian TAN ; Xiaohua ZHU ; Li HUO ; Xiaoli LAN ; Biao LI ; Weibing MIAO ; Shaoli SONG ; Hao XU ; Rong TIAN ; Quanyong LUO ; Feng WANG ; Xuemei WANG ; Aimin YANG ; Dong DAI ; Zhiyong DENG ; Jinhua ZHAO ; Xiaoliang CHEN ; Yan FAN ; Zairong GAO ; Xingmin HAN ; Ningyi JIANG ; Anren KUANG ; Yansong LIN ; Fugeng LIU ; Cen LOU ; Xinhui SU ; Lijun TANG ; Hui WANG ; Xinlu WANG ; Fuzhou YANG ; Hui YANG ; Xinming ZHAO ; Bo YANG ; Xiaodong HUANG ; Jiliang CHEN ; Sijin LI ; Jing WANG ; Yaming LI ; Hongcheng SHI
Chinese Journal of Clinical Medicine 2024;31(5):844-850,封3
177Lu-prostate specific membrane antigen(PSMA)radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China.Based on domestic clinical practice and experimental data and referred to international experience and viewpoints,the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

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