1.Mechanism of action of Sterculiae Lychnophorae Semen against PM2.5-induced acute lung injury based on network pharmacology,molecular docking and experimental validation
Fan ZHANG ; Yi-fan DU ; Xiao-shu DENG ; Zu-feng ZHANG ; Xian-lei HAN ; Wei TIAN ; Xiu-mei LI ; Mian CHEN ; Fei LIU ; Nan WANG
Chinese Pharmacological Bulletin 2025;41(12):2362-2369
Aim To investigate the anti-acute lung injury(ALI)effect of Sterculiae Lychnophorae Semen(SLS)and its mechanism.Methods The main ac-tive components of SLS and their core targets and path-ways of action against ALI were obtained by network pharmacology methods.Subsequently,molecular doc-king technology and in vitro cellular experiments were applied for validation.Results A total of 19 core tar-gets were obtained,including HSP90AA1,CASP3,TNF,MAPK8 and MAPK14.The mechanisms may in-volve signaling pathways such as cancer,PI3K/Akt and MAPK.Molecular docking confirmed that the key targets of SLS formed a better binding activity with the relevant active ingredients.The in vitro results showed that SLS was able to protect the PM2.5-contaminated BEAS-2B cells,inhibit their NO,IL-1β and TNF-αlevels,and reduce the expression of p-p38 MAPK and p-JNK proteins.Conclusions The study successfully predicts the active ingredients,targets and signaling pathways of SLS against ALI,and in vitro experiments demonstrate that SLS might protect BEAS-2B cells from PM2.5 stimulus-induced inflammation and apoptosis by inhibiting the over-activation of p38 MAPK and JNK signaling pathways.
2.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
3.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; 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 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
4.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; 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 ; 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 WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
5.Chemical constituents from Commelina communis
Hong-ting YI ; Ding-mei LIANG ; Bin LEI ; Hong-ling ZENG ; Zhong-wen CHEN ; Hua LIU ; Feng LIU
Chinese Traditional Patent Medicine 2025;47(3):827-833
AIM To study the chemical constituents from Commelina communis L.METHODS The 95%ethanol extract from C.Communis was isolated and purified by activated charcoal,silica gel,Sephadex LH-20,and HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Seventeen compounds were isolated and identified as p-hydroxyl ethyl cinnamate(1),p-hydroxybenzaldehyde(2),vanillin(3),4-hydroxy-2,3-dimethyl-2-nonen-4-olide(4),hemeratrol A(5),chakyunglupulin B(6),chakyunglupulin A(7),2-(2-hydroxyethyl)-3-methylfumaric acid(8),N-cis-feruloyl tyramine(9),N-trans-coumaroyltyramine(10),5,6,7,3',4',5'-hexamethoxyflavone(11),N-trans-sinapoyltyramine(12),dihydro-feruloyltyramine(13),N-trans-feruloyltyramine(14),2-phenylethanol-β-D-glucoside(15),quercetin-3-O-β-D-glucoside(16),and isorhamnetin-3-O-β-D-glucopyranoside(17).CONCLUSION Compounds 4-8,10 and 11 are isolated from Commelina genus for the first time,and 1,9,12-15 are first isolated from this plant.
6.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
7.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
8.Research on low-dose CT image denoising method based on improved Corediff model
Li-mei SONG ; Hang WU ; Yi-feng HUANG ; Qiang WANG ; Guan-jun LIU ; Feng CHEN ; Ming YU ; Jian-kun SHEN
Chinese Medical Equipment Journal 2025;46(5):9-13
Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]
9.Chemical constituents of butyl-phthalides from Ligusticum sinense.
Hang LIU ; Xue-Ming ZHOU ; Ting ZHENG ; Mei-Zhu WU ; Shuo FENG ; Ye LIN ; Xin-Ming SONG ; Ji-Ling YI
China Journal of Chinese Materia Medica 2025;50(2):439-443
Eight butyl-phthalides, senkyunolide K(1), senkyunolide N(2), butylphthalide(3), senkyunolide I(4), senkyunolide H(5),(Z)-butylidenephthalide(6),(Z)-ligustilide(7), and 3-butylidene-7-hydroxyphthalide(8) were isolated from the aerial part of Ligusticum sinense by column chromatography on silica gel column, ODS, Sephadex LH-20 and semi-preparative HPLC. Their structures were elucidated on the basis of spectroscopic and chemical data, especially NMR and MS. Compound 1 was a new butyl-phthalide and compounds 2-8 were isolated from the aerial part of L. sinense for the first time. Furthermore, the inhibitory activities of compounds 1-8 against the nitric oxide(NO) production induced by lipopolysaccharide(LPS) in mouse RAW264.7 macrophages in vitro were evaluated. The results showed that compounds 1-8 exerted inhibitory activities on NO production with IC_(50) of 19.34-42.16 μmol·L~(-1).
Animals
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Mice
;
Nitric Oxide/biosynthesis*
;
Ligusticum/chemistry*
;
Benzofurans/isolation & purification*
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Drugs, Chinese Herbal/isolation & purification*
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Macrophages/immunology*
;
RAW 264.7 Cells
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Molecular Structure
10.Banxia Xiexin Decoction suppresses malignant phenotypes of colon cancer cells via PARG/PARP1/NF-κB signaling pathway.
Yu-Qing HUANG ; Jia-Mei WANG ; Heng-Zhou LAI ; Chong XIAO ; Feng-Ming YOU ; Qi-Xuan KUANG ; Yi-Fang JIANG
China Journal of Chinese Materia Medica 2025;50(2):496-506
This study aims to delve into the influences and underlying mechanisms of Banxia Xiexin Decoction(BXD) on the proliferation, apoptosis, invasion, and migration of colon cancer cells. Firstly, the components of BXD in blood were identified by UPLC-MS/MS, and subsequently the content of these components were determined by HPLC. Then, different concentrations of BXD were used to treat both the normal intestinal epithelial cells(NCM460) and the colon cancer cells(HT29 and HCT116). The cell viability and apoptosis were examined by the cell counting kit-8(CCK-8) and flow cytometry, respectively. Western blot was employed to determine the expression of the apoptosis regulators B-cell lymphoma-2(Bcl-2) and Bcl-2-associated X(Bax). The cell wound healing assay and Transwell assay were employed to measure the cell migration and invasion, respectively. Additionally, Western blot was employed to determine the expression levels of epithelial-mesenchymal transition(EMT)-associated proteins, including epithelial cadherin(E-cadherin), neural cadherin(N-cadherin), and vimentin. The protein and mRNA levels of the factors in the poly(ADP-ribose) glycohydrolase(PARG)/poly(ADP-ribose) polymerase 1(PARP1)/nuclear factor kappa-B p65(NF-κB p65) signaling pathway were determined by Western blot and RT-qPCR, respectively. The results demonstrated that following BXD intervention, the proliferation of HT29 and HCT116 cells was significantly reduced. Furthermore, BXD promoted the apoptosis, enhanced the expression of Bcl-2, and suppressed the expression of Bax in colon cancer cells. At the same time, BXD suppressed the cell migration and invasion and augmented the expression of E-cadherin while diminishing the expression of N-cadherin and vimentin. In addition, BXD down-regulated the protein and mRNA levels of PARG, PARP1, and NF-κB p65. In conclusion, BXD may inhibit the malignant phenotypes of colon cancer cells by mediating the PARG/PARP1/NF-κB signaling pathway.
Colonic Neoplasms/pathology*
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Drugs, Chinese Herbal/pharmacology*
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Phenotype
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Signal Transduction/drug effects*
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Cell Proliferation/drug effects*
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Apoptosis
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Cell Movement/drug effects*
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Neoplasm Invasiveness
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HCT116 Cells
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Proto-Oncogene Proteins c-bcl-2/biosynthesis*
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Humans
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Poly (ADP-Ribose) Polymerase-1
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Glycoside Hydrolases
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bcl-2-Associated X Protein
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NF-kappa B p50 Subunit

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