1.Identification of a JAK-STAT-miR155HG positive feedback loop in regulating natural killer (NK) cells proliferation and effector functions.
Songyang LI ; Yongjie LIU ; Xiaofeng YIN ; Yao YANG ; Xinjia LIU ; Jiaxing QIU ; Qinglan YANG ; Yana LI ; Zhiguo TAN ; Hongyan PENG ; Peiwen XIONG ; Shuting WU ; Lanlan HUANG ; Xiangyu WANG ; Sulai LIU ; Yuxing GONG ; Yuan GAO ; Lingling ZHANG ; Junping WANG ; Yafei DENG ; Zhaoyang ZHONG ; Youcai DENG
Acta Pharmaceutica Sinica B 2025;15(4):1922-1937
The Janus kinase/signal transducers and activators of transcription (JAK-STAT) control natural killer (NK) cells development and cytotoxic functions, however, whether long non-coding RNAs (lncRNAs) are involved in this pathway remains unknown. We found that miR155HG was elevated in activated NK cells and promoted their proliferation and effector functions in both NK92 and induced-pluripotent stem cells (iPSCs)-derived NK (iPSC-NK) cells, without reliance on its derived miR-155 and micropeptide P155. Mechanistically, miR155HG bound to miR-6756 and relieved its repression of JAK3 expression, thereby promoting the JAK-STAT pathway and enhancing NK cell proliferation and function. Further investigations disclosed that upon cytokine stimulation, STAT3 directly interacts with miR155HG promoter and induces miR155HG transcription. Collectively, we identify a miR155HG-mediated positive feedback loop of the JAK-STAT signaling. Our study will also provide a power target regarding miR155HG for improving NK cell generation and effector function in the field of NK cell adoptive transfer therapy against cancer, especially iPSC-derived NK cells.
2.Establishment and optimization of a high-performance size-exclusion chromatography method for quantifying the classical swine fever virus E2 protein.
Xiaojuan ZHANG ; Bo YANG ; Gaoyuan XU ; Mingxing REN ; Ji TANG ; Hongshuo LIU ; Zhankui LIU ; Yafei LI ; Xiangru WANG
Chinese Journal of Biotechnology 2025;41(7):2774-2788
This study aims to establish a high-performance size-exclusion chromatography (HPSEC) method for determining the content of the classical swine fever virus (CSFV) E2 protein and screen the optimal stabilizer to enhance the stability of this protein. The optimal detection conditions were determined by optimizing the composition of the mobile phase, and characteristic chromatographic peaks were identified by SDS-PAGE and Western blotting. The specificity, repeatability, precision, linearity, limit of detection (LOD), and limit of quantitation (LOQ) of the method were assessed. The method established was used to determine the content of CSFV E2 protein antigen and vaccine. Differential scanning fluorimetry (DSF) was employed to screen the buffer system, pH, and salt ion concentrations, and sugar, amino acid, and alcohol stabilizers were further screened. The results showed that using a 200 mmol/L phosphate buffer provided the best column efficiency. An antigen-specific chromatographic peak appeared at the retention time of 18 min, which was identified as the CSFV E2 protein by SDS-PAGE and Western blotting. The method exhibited high specificity for detecting the CSFV E2 protein, with no absorbance peak observed in the blank control. The relative standard deviation (RSD) of the peak area for six repeated injections of the CSFV E2 protein was 0.74%, indicating good repeatability of the method. The RSD for repeated detection of two different concentrations of CSFV E2 protein samples by different operators at different time points was less than 2%, suggesting good intermediate precision of the method. The peak area of the CSFV E2 protein was linearly related to its concentration, with the regression equation showing R2 of 1.000. The LOD and LOQ of the method were 14.88 μg/mL and 29.75 μg/mL, respectively. Application of the developed method in the detection of three batches of CSFV E2 protein antigen and three batches of vaccine demonstrated results consistent with those from the bicinchoninic acid (BCA) assay, which meant that the method could accurately determine the content of CSFV E2 protein antigen and vaccine. The DSF method identified 50 mmol/L Tris-HCl at pH 8.0 as the optimal buffer, and the addition of sugar and alcohol stabilizers further improved the stability of the CSFV E2 protein. The HPSEC method established in this study is simple, fast, and exhibits good accuracy and repeatability, enabling precise measurement of the CSFV E2 protein content. It is expected to play a crucial role in the quality control of the CSFV E2 vaccine. Furthermore, the strategy for improving the CSFV E2 protein stability, identified through DSF screening, has significant implications for enhancing the stability of the CSFV E2 vaccine.
Classical Swine Fever Virus/chemistry*
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Chromatography, Gel/methods*
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Animals
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Swine
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Viral Envelope Proteins/immunology*
3.Construction and Testing of Health LifeStyle Evidence (HLSE)
Chen TIAN ; Yong WANG ; Yilong YAN ; Yafei LIU ; Yao LU ; Mingyao SUN ; Jianing LIU ; Yan MA ; Jinling NING ; Ziying YE ; Qianji CHENG ; Ying LI ; Jiajie HUANG ; Shuihua YANG ; Yiyun WANG ; Bo TONG ; Jiale LU ; Long GE
Medical Journal of Peking Union Medical College Hospital 2024;15(6):1413-1421
Healthy lifestyles and good living habits are effective strategies and important approaches to prevent chronic non-communicable diseases. With the development of evidence-based medicine, the evidence translation system has made some achievements in clinical practice. There is, however, no comprehensive, professional and efficient system for translating lifestyle evidence globally. Therefore, the Health Lifestyle Evidence (HLSE) Group of Lanzhou University constructed the HLSE Evidence Translation System (
4.Construction and Testing of Health LifeStyle Evidence (HLSE)
Chen TIAN ; Yong WANG ; Yilong YAN ; Yafei LIU ; Yao LU ; Mingyao SUN ; Jianing LIU ; Yan MA ; Jinling NING ; Ziying YE ; Qianji CHENG ; Ying LI ; Jiajie HUANG ; Shuihua YANG ; Yiyun WANG ; Bo TONG ; Jiale LU ; Long GE
Medical Journal of Peking Union Medical College Hospital 2024;15(6):1413-1421
Healthy lifestyles and good living habits are effective strategies and important approaches to prevent chronic non-communicable diseases. With the development of evidence-based medicine, the evidence translation system has made some achievements in clinical practice. There is, however, no comprehensive, professional and efficient system for translating lifestyle evidence globally. Therefore, the Health Lifestyle Evidence (HLSE) Group of Lanzhou University constructed the HLSE Evidence Translation System (
5.Binding and carrying role of human serum albumin from various sources to sphingosine-1-phosphate
Qing LIU ; Yafei ZHAO ; Jun XU ; Lu CHENG ; Yuwei HUANG ; Xi DU ; Changqing LI ; Zongkui WANG ; Li MA
Chinese Journal of Blood Transfusion 2024;37(5):524-533
Objective To investigate the binding and carrying effects of human serum albumin(HSA)from various sources on sphingosine-1-phosphate(S1P).Methods Utilizing human plasma-derived HSA(pHSA)and recombinant HSA(rHSA)samples as the focal points of our investigation,LC-MS/MS technology was employed to meticulously compare and an-alyze the disparities in S1P content among the aforementioned samples.Subsequently,under physiological concentration condi-tions,S1P was directly introduced to HSA samples for loading processing,facilitating a comprehensive comparison of the bind-ing efficacy of HSA from different sources to S1P.Within a serum-free culture setting,HSA samples from various sources were co-cultured with HUVEC cells.The alterations in S1P content within the cell culture supernatant across different treatment groups were meticulously analyzed,allowing for a nuanced comparison of the S1P carry effects exerted by HSA from different sources on cells.The interaction between HSA and S1P molecules from different sources was analyzed and their affinity was cal-culated using surface plasmon resonance(SPR)technology.Furthermore,leveraging AutoDock Vina software and the Mol-prophet platform,the molecular docking analysis of HSA and S1P was conducted,aiming to predict the key binding pocket do-main of S1P within HSA.Results All pHSA samples exhibited detectable levels of S1P(ranging from 3.31±0.03 to 30.35±0.07 μg/L),with significant variations observed among pHSA samples from different manufacturers(P<0.001).Conversely,S1P was undetectable in all rHSA samples.Upon load treatment,the binding affinity of HSA from diverse sources to S1P dem-onstrated significant discrepancies(P<0.001),with rHSA exhibiting approximately double the average S1P loading compared to pHSA(ΔCrHSA=801.75±142.45 μg/L vs ΔCpHSA=461.94±85.73 μg/L;P<0.001,t=5.006).Co-culture treatment out-comes revealed a significant elevation in S1P concentration within the supernatant after 6 hours of co-culture across all HSA sample processing groups with HUVEC cells,while no changes were observed in the supernatant of the blank control group.Notably,significant differences in supernatant S1P concentration were observed among treatment groups at 6 h,12 h,and 24 h(P<0.001).SPR analysis unveiled a stronger affinity of pHSA for S1P compared to rHSA(KDpHSA-S1P:2.38E-06,KDrHSA-S1P:3.72E-06).Molecular docking analysis and binding pocket prediction suggested that the key binding pocket of HSA and S1P may reside in the IB subdomain of the HSA molecule.Conclusion HSA from various sources exhibits distinct binding and carrying effects on S1P,which appear to be closely associated with the IB subdomain of the HSA molecule.
6.Effect of peri-implant soft-tissue phenotype on peri-implant health
Yanxin SHEN ; Wei LIU ; Yafei WU ; Ping GONG
Chinese Journal of Stomatology 2024;59(8):846-850
Dental implant is a commonly used therapeutic option for reconstruction of edentulous space. Adequate peri-implant soft tissue is crucial for preventing biological and esthetic complications. Peri-implant soft-tissue phenotypes including supracrestal tissue height, mucosa thickness and keratinized mucosa width could reflect the quality and quantity of peri-implant soft tissue. Different soft-tissue phenotypes might impact the stability of implant restoration through altering the tissue remodeling or inflammatory response. This review will discuss the influence of peri-implant soft-tissue phenotypes on tissue remodeling and inflammatory response after implant placement.
7.Designs and appropriate choices for diagnostic test accuracy study
Xiaolong LIU ; Na WU ; Yafei LI
Chinese Journal of Epidemiology 2024;45(12):1705-1714
Diagnostic tests are indispensable tools in clinical practice and are rigorously evaluated through scientifically designed accuracy studies before the clinical practice. The accuracy of these tests directly affects the correctness of the diagnosis and the rationality of treatment decisions. This article introduces the types of designs and their characteristics used in diagnostic test accuracy studies, including single-group studies, diagnostic case-control studies, single-group paired studies, and parallel-group studies. It recommends appropriate design types based on the research question stage, the diagnostic test's role in the clinical diagnostic pathway, and the actual clinical application scenario to provide suggestions for further standardizing the design of current clinical diagnostic test accuracy research. This article may help clinical researchers better understand and choose the appropriate type of diagnostic test accuracy study design to improve diagnostic test accuracy research quality.
8.Validity and reliability of the Chinese version of the Cyberbullying Bystander Scale in college students
Caihong YUAN ; Yafei JIA ; Qiongxiang LIU ; Wenqi ZHOU ; Chunyan ZHOU ; Chenling LIU
Chinese Mental Health Journal 2024;38(11):1003-1008
Objective:To test the validity and reliability of the Chinese version of the Cyberbullying Bystand-er Scale(CBS)in Chinese college students.Methods:Totally 722 college students were randomly divided into sample 1(n=356)and sample 2(n=366).Exploratory factor analysis was performed on sample 1,and confirma-tory factor analysis,criterion validity,and internal consistency reliability were performed on sample 2.The criterion validity was tested with the Short Form of Moral Disengagement Scale(MDS).Thirty-seven students of sample 2 were randomly selected and retested 2 week later.Results:The Chinese version of CBS contained 6 distinct factors(40 items),named passive outsider online,defender of the cybervictim online,reinforcer of the cyberbully online,passive face-to-face outsider,face to face defender of the cybervictim,face-to-face reinforcer of the cyberbully.The results of confirmatory factor analysis confirmed that the fitting index of the six-factor modelis good(x2/df=2.83,CFI=0.90,TLI=0.89,RMSEA=0.07,SRMR=0.06).The scores of passive outsider online,reinforcer of the cyberbully online,passive face-to-face outsider and face-to-face reinforcer of the cyberbully were positively correla-ted with the moral disengagement(ICC=0.11-0.28,Ps<0.05).The internal consistency reliabilities of the scale were from 0.89 to 0.96,the retest reliabilities(ICC)of the scale were between 0.75 to 0.89.Conclusion:The Chinese version of the Cyberbullying Bystander Scale(CBS)shows good validity and reliability in Chinese college students.
9.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
10.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

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