1.The value of coronary CT angiography-based traditional features and radiomics in identification of culprit plaques to cause acute myocardial infarction
Pei NIE ; Shuo ZHANG ; Yan DENG ; Shifeng YANG ; Xinxin YU ; Kaiyue ZHI ; He ZHU ; Peng LI ; Jingjing CUI ; Wenjing CHEN ; Yanmei WANG ; Yuchao XU ; Dapeng HAO ; Ximing WANG
Chinese Journal of Radiology 2025;59(9):1017-1028
Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.
2.Integrating Single-cell RNA Sequencing and Mendelian Randomization Reveals the Pathogenic Mechanism of Eomes in Renal Cell Carcinoma
Xin-cen WANG ; Hai-xia HUANG ; Xin-hao WANG ; Zhi-fei CHE ; Pei-yu LIANG
Progress in Modern Biomedicine 2025;25(15):2421-2430
Objective:This study employs a combination of single-cell sequencing and Mendelian randomization to explore the genetic associations and molecular mechanisms of Eomes in RCC.Methods:In this study,single-cell transcriptomic data from RCC tissues and adjacent normal tissues were extracted from the GEO database.The data were analyzed using R language and various packages such as Seurat,limma,and CellChat for cell cluster annotation,intercellular communication analysis,and differential expression analysis.Additionally,eQTL data related to differentially expressed genes were retrieved from the GWAS database as exposure variables,with RCC used as the outcome variable in Mendelian randomization analysis to identify the role of Eomes in RCC.Finally,GO functional enrichment and KEGG pathway analyses were conducted to explore the potential molecular mechanisms of Eomes.Results:Single-cell RNA sequencing revealed that B cells play a significant role in the heterogeneity of RCC.Mendelian randomization analysis indicated that Eomes is an important risk factor for RCC(P<0.05).Furthermore,seven highly correlated specific SNPs were identified,including rs 17021298,rs2247056,rs2617170,rs3806624,rs55908509,rs6590334,and rs9420589.GO and KEGG enrichment analyses suggest that Eomes may be involved in early cell fate determination in renal cell carcinoma and participate in the regulation of Th1 and Th2 cell differentiation,HPV infection,and the Notch signaling pathway.Conclusions:This study is the first to combine single-cell sequencing and Mendelian randomization analysis in RCC,confirming a strong positive causal relationship between Eomes and RCC(OR>1).Our findings offer new insights into the pathogenesis of RCC,suggesting that Eomes could serve as a novel target for early diagnosis and personalized treatment of RCC.
3.circHERC4_041 Inhibits the Fibrotic Phenotype of Cardiac Fibroblasts by Encoding Protein
Yuan GAO ; Chuan-Meng ZHOU ; Hua-Yan WU ; Ya WANG ; Ru-Shi WU ; Pei-Ying GUAN ; Jun-Tao FANG ; Jin-Dong XU ; Yu-Peng LIU ; Zhi-Qin HU ; Zhi-Xin SHAN
Chinese Journal of Biochemistry and Molecular Biology 2025;41(3):393-403
A mounting body of research suggests that circRNAs significantly contribute to the develop-ment of myocardial fibrosis.The microarray results of human circular RNA expression profile indicated that circHERC4_041 expression increased in the myocardium of patients with heart failure,RT-qPCR a-nalysis confirmed that the myocardial expression level of circHERC4_041 in individuals with heart failure were considerably elevated compared to that in healthy organ donors.Fluorescence in situ hybridization(FISH)confirmed that circHERC4_041 was abundant in the cytoplasm of human cardiomyocyte AC16.Overexpression of circHERC4_041 in mouse myocardial fibroblasts(mCFs)mediated by adenovirus in-hibited the expression of fibrosis-related proteins in mCFs.Experiments involving cell proliferation,wound healing,and Transwell assays demonstrated that overexpression of circHERC4_041 suppressed the growth and mobility of mCFs(P<0.001).Sequence analysis results suggested that circHERC4_041 con-tains potential ribosome entry sequence(IRES)and open reading frame(ORF).Western blot confirmed that circHERC4_041 could translate the 516 amino acid HERC4-516aa protein,which was mainly located in the cytoplasm of the cell.Cell functional experiments confirmed that circHERC4_041 inhibited the fi-brotic phenotype of mCFs by specifically translating HERC4-516aa(P<0.05).The specific interaction between HERC4-516aa and transglutaminase 2(TGM2)was confirmed by IP-MS screening and Co-IP i-dentification.Further results found that the degradation of TGM2 was promoted through proteasome path-way.The overexpression of TGM2 in mCFs facilitated by adenoviral vectors could counteract the suppres-sive effects of HERC4-516aa on the fibrotic phenotype of mCFs.Therefore,this study confirmed that the HERC4-516aa protein translated by circHERC4_041 can specifically bind to TGM2 to inhibit the fibrotic phenotype of myocardial fibroblasts.
4.ALKBH5 mediated m6A modification of NLRP3 promotes cardiomyocytes pyroptosis in mice with myocardial infarction
Miao-miao ZHAI ; Jian-jian YIN ; Zhi-mo WANG ; Yue-jiao ZHOU ; Qing-wen YU ; Pei WANG ; Li-rong ZHANG ; Sheng-na HAN
Chinese Pharmacological Bulletin 2025;41(3):434-444
Aim To investigate the effects of m6A demethylase ALKBH5 on cardiomyocytes pyroptosis in mice with myocardial infarction(MI).Methods The MI model of left anterior descending coronary artery ligation surgery was established by knocking down ALKBH5 using adeno-associated virus,and the hypox-ia model of mouse cardiomyocytes(HL-1)was estab-lished by knocking down small interfering RNA.The effects of ALKBH5 on the pyroptosis of MI mice and hypoxic HL-1 cells were observed.Subsequently,mechanism studies were conducted at the cellular lev-el,and the binding of ALKBH5 and IGF2BP2 to NL-RP3 mRNA was detected through RNA pull down and RNA immunoprecipitation(RIP)experiments.The MeRIP-qPCR method was used to determine the effects of ALKBH5 on the mRNA m6A level of NLRP3.Acti-nomycin D for RNA stability experiments were conduc-ted to detect the effects of ALKBH5 and IGF2BP2 on the stability of NLRP3 mRNA.Results Knocking down ALKBH5 in vivo and in vitro both inhibited NL-RP3 inflammasome activation and alleviated pyroptosis in MI mice and hypoxic HL-1 cells.Mechanistically,the results showed that NLRP3 mRNA could bind to ALKBH5 protein in HL-1 cells;knocking down ALK-BH5 could increase the m6A level of NLRP3 and re-duce the stability of NLRP3 mRNA;subsequently,it was confirmed that NLRP3 mRNA and IGF2BP2 pro-tein bound to each other;knocking down IGF2BP2 in-creased the mRNA stability of NLRP3.The Rescue ex-periment showed that knocking down IGF2BP2 re-versed the decrease in NLRP3 mRNA expression caused by knocking down ALKBH5.Conclusions ALKBH5 mediated m6A modification of NLRP3 pro-motes cardiomyocytes pyroptosis in mice with myocardi-al infarction.
5.Integrating Single-cell RNA Sequencing and Mendelian Randomization Reveals the Pathogenic Mechanism of Eomes in Renal Cell Carcinoma
Xin-cen WANG ; Hai-xia HUANG ; Xin-hao WANG ; Zhi-fei CHE ; Pei-yu LIANG
Progress in Modern Biomedicine 2025;25(15):2421-2430
Objective:This study employs a combination of single-cell sequencing and Mendelian randomization to explore the genetic associations and molecular mechanisms of Eomes in RCC.Methods:In this study,single-cell transcriptomic data from RCC tissues and adjacent normal tissues were extracted from the GEO database.The data were analyzed using R language and various packages such as Seurat,limma,and CellChat for cell cluster annotation,intercellular communication analysis,and differential expression analysis.Additionally,eQTL data related to differentially expressed genes were retrieved from the GWAS database as exposure variables,with RCC used as the outcome variable in Mendelian randomization analysis to identify the role of Eomes in RCC.Finally,GO functional enrichment and KEGG pathway analyses were conducted to explore the potential molecular mechanisms of Eomes.Results:Single-cell RNA sequencing revealed that B cells play a significant role in the heterogeneity of RCC.Mendelian randomization analysis indicated that Eomes is an important risk factor for RCC(P<0.05).Furthermore,seven highly correlated specific SNPs were identified,including rs 17021298,rs2247056,rs2617170,rs3806624,rs55908509,rs6590334,and rs9420589.GO and KEGG enrichment analyses suggest that Eomes may be involved in early cell fate determination in renal cell carcinoma and participate in the regulation of Th1 and Th2 cell differentiation,HPV infection,and the Notch signaling pathway.Conclusions:This study is the first to combine single-cell sequencing and Mendelian randomization analysis in RCC,confirming a strong positive causal relationship between Eomes and RCC(OR>1).Our findings offer new insights into the pathogenesis of RCC,suggesting that Eomes could serve as a novel target for early diagnosis and personalized treatment of RCC.
6.circHERC4_041 Inhibits the Fibrotic Phenotype of Cardiac Fibroblasts by Encoding Protein
Yuan GAO ; Chuan-Meng ZHOU ; Hua-Yan WU ; Ya WANG ; Ru-Shi WU ; Pei-Ying GUAN ; Jun-Tao FANG ; Jin-Dong XU ; Yu-Peng LIU ; Zhi-Qin HU ; Zhi-Xin SHAN
Chinese Journal of Biochemistry and Molecular Biology 2025;41(3):393-403
A mounting body of research suggests that circRNAs significantly contribute to the develop-ment of myocardial fibrosis.The microarray results of human circular RNA expression profile indicated that circHERC4_041 expression increased in the myocardium of patients with heart failure,RT-qPCR a-nalysis confirmed that the myocardial expression level of circHERC4_041 in individuals with heart failure were considerably elevated compared to that in healthy organ donors.Fluorescence in situ hybridization(FISH)confirmed that circHERC4_041 was abundant in the cytoplasm of human cardiomyocyte AC16.Overexpression of circHERC4_041 in mouse myocardial fibroblasts(mCFs)mediated by adenovirus in-hibited the expression of fibrosis-related proteins in mCFs.Experiments involving cell proliferation,wound healing,and Transwell assays demonstrated that overexpression of circHERC4_041 suppressed the growth and mobility of mCFs(P<0.001).Sequence analysis results suggested that circHERC4_041 con-tains potential ribosome entry sequence(IRES)and open reading frame(ORF).Western blot confirmed that circHERC4_041 could translate the 516 amino acid HERC4-516aa protein,which was mainly located in the cytoplasm of the cell.Cell functional experiments confirmed that circHERC4_041 inhibited the fi-brotic phenotype of mCFs by specifically translating HERC4-516aa(P<0.05).The specific interaction between HERC4-516aa and transglutaminase 2(TGM2)was confirmed by IP-MS screening and Co-IP i-dentification.Further results found that the degradation of TGM2 was promoted through proteasome path-way.The overexpression of TGM2 in mCFs facilitated by adenoviral vectors could counteract the suppres-sive effects of HERC4-516aa on the fibrotic phenotype of mCFs.Therefore,this study confirmed that the HERC4-516aa protein translated by circHERC4_041 can specifically bind to TGM2 to inhibit the fibrotic phenotype of myocardial fibroblasts.
7.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.
8.Chemical constituents from Tetrastigma hemsleyanum and their antitumor activity in vitro
Yi LONG ; Li-zhi ZHANG ; Piao-piao JIANG ; Nan KUANG ; Xin-yu ZHANG ; Yu-pei YANG ; Bin LI ; Wei WANG
Chinese Traditional Patent Medicine 2025;47(9):2932-2941
AIM To study the chemical constituents from Tetrastigma hemsleyanum Diels et Gilg and their antitumor activity in vitro.METHODS Silica gel,ODS,Sephadex LH-20 and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activity in vitro was determined by MTT mothod.RESULTS Twenty-eight compounds were isolated and identified as triphyllin A(1),eruberin B(2),(2S,4R)-5,7-dihydroxy-4,4'-dimethyl-6,8-dimethyl-flavan-5-O-β-D-6-acetylglucopyranoside-7-O-β-D-glucopyranoside(3),eruberin A(4),abacopterin Ⅰ(5),matteucinol(6),homoerodictyol(7),(2S)-5,3',4'-trihydroxy-7-methoxy-flavanone(8),(2S)-5,2',5'-trihydroxy-7-methoxyflavanone(9),galinsonside B(10),quercetin-3-O-β-D-glucopyranoside(11),kaempferol 3-O-robinobioside(12),rutin(13),geniposide(14),jasminoside A(15),β-sitostenone(16),sitosterol palmitate(17),β-sitosterol(18),ursolic acid(19),hyptadienic acid(20),3,4-dihydroxybenzoic acid(21),3,4-dimethoxybenzoic acid(22),gallic acid(23),dibutylphthalate(24),bis-(2-ethylhexyl)phthalate(25),9-nonadecenoic acid(26),triacylglycerol(27),crocin Ⅰ(28).The IC50 values of compound 1 for human gastric adenocarcinoma cells BGC-823 and human colon cancer cells HCT-116 were(22.07±0.38),(20.67±0.11)μmol/L,respectively.The IC50 value of compound 9 for BGC-823 cells was(21.58±0.05)μmol/L,and the IC50 value of compound 4 for HCT-116 cells was(16.67±0.36)μmol/L.CONCLUSION Compounds 1-10,14-15 and 28 are first isolated from Tetrastigma genus.Compounds 1,4,9 have weak antitumor activity in vitro.
9.Glutamine signaling specifically activates c-Myc and Mcl-1 to facilitate cancer cell proliferation and survival.
Meng WANG ; Fu-Shen GUO ; Dai-Sen HOU ; Hui-Lu ZHANG ; Xiang-Tian CHEN ; Yan-Xin SHEN ; Zi-Fan GUO ; Zhi-Fang ZHENG ; Yu-Peng HU ; Pei-Zhun DU ; Chen-Ji WANG ; Yan LIN ; Yi-Yuan YUAN ; Shi-Min ZHAO ; Wei XU
Protein & Cell 2025;16(11):968-984
Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism*
;
Myeloid Cell Leukemia Sequence 1 Protein/genetics*
;
Humans
;
Proto-Oncogene Proteins c-myc/genetics*
;
Cell Proliferation
;
Signal Transduction
;
Neoplasms/pathology*
;
F-Box-WD Repeat-Containing Protein 7/genetics*
;
Cell Survival
;
Cell Line, Tumor
;
Apoptosis
10.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

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