1.The construction and its implication of the cancer life-cycle prevention and control system in Japan
Dong-Ni HONG ; Sheng WANG ; Xian-Ji WANG ; Chun-Feng WU ; Chun-Yu RONG ; Ping ZHOU
Chinese Journal of Health Policy 2024;17(2):72-78
As the country with the largest number of new cancer cases and deaths,China faces a serious situation with a large cancer population base,low relative survival rate,and low adherence to cancer screening.Neighboring Japan,which has the longest life expectancy in the world,has a much higher relative survival rate than China,despite having a similarly high cancer rate,due to its well-established system of cancer prevention and control.Being an Asian country,the major prevalent cancers in China and Japan are similar in spectrum and can be referred to more.This article introduces the construction of Japan's cancer life-cycle prevention and control system of"cancer prevention","cancer care",and"coexistence with cancer"starting from the three major goals of Japan's cancer prevention and control program,and focuses on the improvement of cancer screening in Japan and the improvement of cancer survival in China.It also highlights the means and methods used to increase the cancer screening rate in Japan,with a view to providing suggestions for cancer prevention and control in China.
2.Next-Generation Patient-Based Real-Time Quality Control Models
Xincen DUAN ; Minglong ZHANG ; Yan LIU ; Wenbo ZHENG ; Chun Yee LIM ; Sollip KIM ; Tze Ping LOH ; Wei GUO ; Rui ZHOU ; Tony BADRICK ;
Annals of Laboratory Medicine 2024;44(5):385-391
Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.
3.Next-Generation Patient-Based Real-Time Quality Control Models
Xincen DUAN ; Minglong ZHANG ; Yan LIU ; Wenbo ZHENG ; Chun Yee LIM ; Sollip KIM ; Tze Ping LOH ; Wei GUO ; Rui ZHOU ; Tony BADRICK ;
Annals of Laboratory Medicine 2024;44(5):385-391
Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.
4.Next-Generation Patient-Based Real-Time Quality Control Models
Xincen DUAN ; Minglong ZHANG ; Yan LIU ; Wenbo ZHENG ; Chun Yee LIM ; Sollip KIM ; Tze Ping LOH ; Wei GUO ; Rui ZHOU ; Tony BADRICK ;
Annals of Laboratory Medicine 2024;44(5):385-391
Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.
5.Next-Generation Patient-Based Real-Time Quality Control Models
Xincen DUAN ; Minglong ZHANG ; Yan LIU ; Wenbo ZHENG ; Chun Yee LIM ; Sollip KIM ; Tze Ping LOH ; Wei GUO ; Rui ZHOU ; Tony BADRICK ;
Annals of Laboratory Medicine 2024;44(5):385-391
Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.
6.Safety of high-carbohydrate fluid diet 2 h versus overnight fasting before non-emergency endoscopic retrograde cholangiopancreatography: A single-blind, multicenter, randomized controlled trial
Wenbo MENG ; W. Joseph LEUNG ; Zhenyu WANG ; Qiyong LI ; Leida ZHANG ; Kai ZHANG ; Xuefeng WANG ; Meng WANG ; Qi WANG ; Yingmei SHAO ; Jijun ZHANG ; Ping YUE ; Lei ZHANG ; Kexiang ZHU ; Xiaoliang ZHU ; Hui ZHANG ; Senlin HOU ; Kailin CAI ; Hao SUN ; Ping XUE ; Wei LIU ; Haiping WANG ; Li ZHANG ; Songming DING ; Zhiqing YANG ; Ming ZHANG ; Hao WENG ; Qingyuan WU ; Bendong CHEN ; Tiemin JIANG ; Yingkai WANG ; Lichao ZHANG ; Ke WU ; Xue YANG ; Zilong WEN ; Chun LIU ; Long MIAO ; Zhengfeng WANG ; Jiajia LI ; Xiaowen YAN ; Fangzhao WANG ; Lingen ZHANG ; Mingzhen BAI ; Ningning MI ; Xianzhuo ZHANG ; Wence ZHOU ; Jinqiu YUAN ; Azumi SUZUKI ; Kiyohito TANAKA ; Jiankang LIU ; Ula NUR ; Elisabete WEIDERPASS ; Xun LI
Chinese Medical Journal 2024;137(12):1437-1446
Background::Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients’ recovery.Methods::This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group ( n = 665) and fasting group ( n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results::The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P <0.001) and 20 h (2.4 ± 2.1 vs. 3.4 ± 2.4, t= 7.94, P <0.001) in the CFD group, with least-squares mean differences of 0.48 (95% confidence interval [CI]: 0.26–0.71, P <0.001) and 0.76 (95% CI: 0.57–0.95, P <0.001), respectively. The 4-h pain scores (2.1 ± 1.7 vs. 2.2 ± 1.7, t = 2.60, P = 0.009, with a least-squares mean difference of 0.21 [95% CI: 0.05–0.37]) and positive urine ketone levels (7.7% [39/509] vs. 15.4% [82/533], χ2 = 15.13, P <0.001) were lower in the CFD group. The CFD group had significantly less cholangitis (2.1% [13/634] vs. 4.0% [26/658], χ2 = 3.99, P = 0.046) but not pancreatitis (5.5% [35/634] vs. 6.5% [43/658], χ2 = 0.59, P = 0.444). Subgroup analysis revealed that CFD reduced the incidence of complications in patients with native papilla (odds ratio [OR]: 0.61, 95% CI: 0.39–0.95, P = 0.028) in the multivariable models. Conclusion::Ingesting 400 mL of CFD 2 h before ERCP is safe, with a reduction in post-ERCP fatigue, abdominal pain, and cholangitis during recovery.Trail Registration::ClinicalTrials.gov, No. NCT03075280.
7.Effect and mechanism of astaxanthin on improving intestinal injury of sep-tic mice
Chun-Guang ZHAO ; Kasimu·Yusufu ; Xu-Ping NIU ; Li-Ping ZHOU
Chinese Journal of Infection Control 2024;23(5):574-581
Objective To understand the effect of astaxanthin on intestinal injury of septic mice,and explore the mechanism.Methods Septic mice model was constructed by cecum ligation and puncture(CLP).Sixty-two male Balb/c mice were randomly divided into 4 groups by random number method:Sham surgery+solvent control group(Sham+Vehi group,n=11),Sham surgery+astaxanthin group(Sham+Asta group,n=11),sepsis model+sol-vent control group(CLP+Vehi group,n=20),and sepsis model+astaxanthin group(CLP+Asta group,n=20).In astaxanthin-containing groups,astaxanthin was dissolved in edible olive oil(40 mg/mL),and 100 mg/(kg·d)was gavaged for 7 days before surgery.In solvent-containing groups,the solvent was treated with an equal amount of olive oil by gavage(2.5 mL/kg).Five mice from the Sham groups and 12 mice from the CLP groups were ran-domly selected to observe their 7-day survival after surgery.The remaining mice were given fluorescent isothiocya-nate dextran(FD-40)gavage at 18 hours after surgery.Changes in mice intestinal tissue morphology,intestinal functional injury indicators,intestinal tissue oxidative stress indicators,inflammatory factors expression,and ex-pression of key protein of peroxisome proliferator-activated receptor γ(PPARγ)/nuclear factor kappa B(NF-κB)were detected 24 hours after surgery.Results There were no statistical differences in mice survival rate,intestinal injury indicators,intestinal inflammatory factor levels,oxidative stress indicators,and intestinal tissue injury scores between Sham+Vehi and Sham+Asta groups(all P>0.05).Compared with the Sham+Vehi group,the survival rate of mice in the CLP+Vehi group decreased significantly;serum diamine oxidase(DAO)activities,levels of in-testinal fatty acid binding protein(I-FABP),D-lactate,and FD-40 increased significantly;levels of tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β),interleukin-6(IL-6)and malondialdehyde(MDA)in intestinal tissue in-creased significantly;superoxide dismutase(SOD)activity decreased;intestinal morphological injury score was higher;the expression of PPARγ in intestinal tissue increased,and the ratios of both p-IκBα/IκBα and p-p65/p65 in-creased(all P<0.05).Compared with the CLP+Vehi group,the survival rate of mice in the CLP+Asta group im-proved;serum DAO activities,levels of I-FABP,D-lactate and FD-40 all decreased significantly;levels of TNF-α,IL-1β,IL-6 and MDA in intestinal tissue decreased significantly;SOD activity increased;intestinal morphological injury score decreased;PPARγ expression in intestinal tissue increased,and the ratios of both p-IκBα/IκBα and p-p65/p65 decreased(all P<0.05).Conclusion Astaxanthin decreases intestinal injury in CLP-induced septic mice,and its mechanism may be related to the regulation of PPARγ/NF-κB signaling pathway,as well as the inhibi-tion of inflammatory response and oxidative stress.
8.Mechanism of carvacrol on inhibiting biofilm formation of hypervirulent Klebsiella pneumoniae
Chun-Ping WEI ; Tian-Xin XIANG ; Yang LIU ; Na CHENG ; Fei HAN ; Li ZHOU ; Peng LIU ; Dan-Dan WEI
Chinese Journal of Infection Control 2024;23(7):833-839
Objective To explore the potential mechanism of carvacrol on inhibiting the formation of biofilm of hy-pervirulent Klebsiella pneumoniae(hvKP).Methods The possible mechanisms of carvacrol were analyzed based on the detection of its effects on the formation and morphology of biofilms,changes in extracellular polysaccharide and capsule polysaccharide content,as well as changes in the expression levels of biofilm-related genes rmpA2,mag A,mrkA,mrkB,and treC of hvKP.Results The minimum inhibitory concentration of carvacrol on hvKP was 512 μg/mL,with an obvious inhibitory effect on the biofilm formation of hvKP,presenting a concentration-depen-dent effect.Under the scanning electron microscope,it was observed that the biofilm structure was loose and the in-tercellular connections were not dense under the intervention of carvacrol.The Congo Red adsorption test and m-hydroxybiphenyl colorimetric method showed that carvacrol could reduce the content of capsule polysaccharides of hvKP,but didn't affect the total extracellular polysaccharide content.Fluorescence quantitative polymerase chain reaction(PCR)showed that under the effect of carvacrol at sub-inhibitory concentration,the synthesis of capsule polysaccharide,expression levels of sugar transport system and pili adhesion-related genes all decreased by more than 50%.Conclusion Carvacrol has a significant inhibitory effect on the formation of biofilm in hvKP,and its mechanism may be related to the decrease of synthesis of capsule polysaccharide as well as expression of biofilm-re-lated genes,such as sugar transport system and pili adhesion.
9.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.
10.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; Wen'en LIU ; Yanming LI ; 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 WEN ; 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):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.

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