1.Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey.
Binbin LIN ; Yaoda HU ; Huijing HE ; Xingming CHEN ; Qiong OU ; Yawen LIU ; Tan XU ; Ji TU ; Ang LI ; Qihang LIU ; Tianshu XI ; Zhiming LU ; Weihao WANG ; Haibo HUANG ; Da XU ; Zhili CHEN ; Zichao WANG ; Guangliang SHAN
Environmental Health and Preventive Medicine 2025;30():5-5
BACKGROUND:
The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories.
METHODS:
This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex.
RESULTS:
In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight.
CONCLUSIONS
Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult
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Aged
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Female
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Humans
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Male
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Middle Aged
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Young Adult
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Adipose Tissue
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Body Fat Distribution
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Body Mass Index
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China/epidemiology*
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Cross-Sectional Studies
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Health Surveys
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Phenotype
2.Gene Expression Alteration by Non-thermal Plasma-Activated Media Treatment in Radioresistant Head and Neck Squamous Cell Carcinoma
Sicong ZHENG ; Yudan PIAO ; Seung-Nam JUNG ; Chan OH ; Mi Ae LIM ; QuocKhanh NGUYEN ; Shan SHEN ; Se-Hee PARK ; Shengzhe CUI ; Shuyu PIAO ; Young Il KIM ; Ji Won KIM ; Ho-Ryun WON ; Jae Won CHANG ; Yujuan SHAN ; Lihua LIU ; Bon Seok KOO
Clinical and Experimental Otorhinolaryngology 2025;18(1):73-87
Objectives:
. Head and neck squamous cell carcinoma (HNSCC) exhibits high recurrence rates, particularly in cases of radioresistant HNSCC (RR-HNSCC). Non-thermal plasma (NTP) therapy effectively suppresses the progression of HNSCC. However, the therapeutic mechanisms of NTP therapy in treating RR-HNSCC are not well understood. In this study, we explored the regulatory role of NTP in the RR-HNSCC signaling pathway and identified its signature genes.
Methods:
. After constructing two RR-HNSCC cell lines, we prepared cell lysates from cells treated or not treated with NTP-activated media (NTPAM) and performed RNA sequencing to determine their mRNA expression profiles. Based on the RNA sequencing results, we identified differentially expressed genes (DEGs), followed by a bioinformatics analysis to identify candidate molecules potentially associated with NTPAM therapy for RR-HNSCC.
Results:
. NTPAM reduced RR-HNSCC cell viability in vitro. RNA sequencing results indicated that NTPAM treatment activated the reactive oxygen species (ROS) pathway and induced ferroptosis in RR-HNSCC cell lines. Among the 1,924 genes correlated with radiation treatment, eight showed statistical significance in both the cell lines and The Cancer Genome Atlas (TCGA) cohort. Only five genes—ABCC3, DUSP16, PDGFB, RAF1, and THBS1—showed consistent results between the NTPAM data sequencing and TCGA data. LASSO regression analysis revealed that five genes were associated with cancer prognosis, with a hazard ratio of 2.26. In RR-HNSCC cells, NTPAM affected DUSP16, PDGFB, and THBS1 as activated markers within 6 hours, and this effect persisted for 12 hours. Furthermore, enrichment analysis indicated that these three DEGs were associated with the extracellular matrix, transforming growth factor-beta, phosphoinositide 3-kinase/protein kinase B, and mesenchymal-epithelial transition factor pathways.
Conclusion
. NTPAM therapy exerts cytotoxic effects in RR-HNSCC cell lines by inducing specific ROS-mediated ferroptosis. DUSP16, PDGFB, and THBS1 were identified as crucial targets for reversing the radiation resistance induced by NTPAM therapy, providing insights into the mechanisms and clinical applications of NTPAM treatment in RR-HNSCC.
3.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
4.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
5.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; 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 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 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
6.Fufang Changtai Decoction Inhibites Colorectal Cancer Through Ferroptosis:Investigation of the Underlying Mechanism
Jialin GU ; Lingchang LI ; Ming LIU ; Shan DENG ; Jialin YU ; Jiege HUO ; Yi JI
Journal of Sichuan University (Medical Sciences) 2025;56(3):647-655
Objective To investigate the underlying mechanisms of the effect of Fufang Changtai Decoction(FFCT)in inhibiting colorectal cancer(CRC)through the ferroptosis pathway using network pharmacology combined with experimental validation.Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and Swiss Target Prediction databases were employed for the systematic screening of potent active ingredients and therapeutic targets of FFCT.In addition,the identification of CRC-associated genes and ferroptosis-related genes(FRGs)was accomplished using the Gene Cards and FerrDb databases,respectively.Venn diagrams,coupled with Cytoscape software,facilitated the comprehensive analysis of key FRGs involved in FFCT's intervention in CRC by mapping the TCM compound-therapeutic target network.Transmission electron microscopy was used to examine the mitochondrial ultrastructure of SW480 and HCT116,2 Human CRC cell lines,after treatment with FFCT-containing serum.Intracellular reactive oxygen species(ROS)levels were measured using a ROS detection kit.To assess the role of ferroptosis,ferroptosis inhibitor liproxstatin-1(Lip-1)was co-administered with FFCT-containing serum.The effects on cancer cell viability and proliferation were evaluated using CCK-8 and colony formation assays.Key molecular targets involved in the regulatory effects of FFCT on the expression of FRGs were further analyzed using PCR Array and Western blot.The findings were then validated with human CRC tissue microarrays.Results A total of 103 active ingredients of FFCT,739 therapeutic targets,9 101 disease-related genes,and 564 FRGs were identified.Venn diagram analysis identified 81 FRGs associated with FFCT intervention.Network analysis revealed that NQO1,TP53,and PTGS2 served as hub nodes in the regulatory network.Findings from the in vitro experiments showed that FFCT induced ferroptosis changes,including mitochondrial condensation,membrane thickening,and cristae reduction,in SW480 and HCT116 cells.FFCT treatment significantly increased intracellular ROS levels in a dose-dependent manner(P<0.05)and reduced cancer cell viability and proliferative capacity(P<0.01).These inhibitory effects were partially reversed by Lip-1,suggesting that FFCT's antitumor activity was closely associated with the ferroptosis pathway.PCR Array and Western blot analyses further confirmed that FFCT significantly downregulated NQO1 mRNA and protein expression in cancer cells(P<0.001),which was consistent with network pharmacology predictions.Immunofluorescence analysis of clinical CRC tissue microarrays revealed that NQO1 expression was significantly higher in tumor tissues than in adjacent non-tumor tissues(P<0.001).Conclusion FFCT may induce intracellular ferroptosis by downregulating the oncogenic gene NQO1,thereby exerting anti-CRC effects.
7.Gene Expression Alteration by Non-thermal Plasma-Activated Media Treatment in Radioresistant Head and Neck Squamous Cell Carcinoma
Sicong ZHENG ; Yudan PIAO ; Seung-Nam JUNG ; Chan OH ; Mi Ae LIM ; QuocKhanh NGUYEN ; Shan SHEN ; Se-Hee PARK ; Shengzhe CUI ; Shuyu PIAO ; Young Il KIM ; Ji Won KIM ; Ho-Ryun WON ; Jae Won CHANG ; Yujuan SHAN ; Lihua LIU ; Bon Seok KOO
Clinical and Experimental Otorhinolaryngology 2025;18(1):73-87
Objectives:
. Head and neck squamous cell carcinoma (HNSCC) exhibits high recurrence rates, particularly in cases of radioresistant HNSCC (RR-HNSCC). Non-thermal plasma (NTP) therapy effectively suppresses the progression of HNSCC. However, the therapeutic mechanisms of NTP therapy in treating RR-HNSCC are not well understood. In this study, we explored the regulatory role of NTP in the RR-HNSCC signaling pathway and identified its signature genes.
Methods:
. After constructing two RR-HNSCC cell lines, we prepared cell lysates from cells treated or not treated with NTP-activated media (NTPAM) and performed RNA sequencing to determine their mRNA expression profiles. Based on the RNA sequencing results, we identified differentially expressed genes (DEGs), followed by a bioinformatics analysis to identify candidate molecules potentially associated with NTPAM therapy for RR-HNSCC.
Results:
. NTPAM reduced RR-HNSCC cell viability in vitro. RNA sequencing results indicated that NTPAM treatment activated the reactive oxygen species (ROS) pathway and induced ferroptosis in RR-HNSCC cell lines. Among the 1,924 genes correlated with radiation treatment, eight showed statistical significance in both the cell lines and The Cancer Genome Atlas (TCGA) cohort. Only five genes—ABCC3, DUSP16, PDGFB, RAF1, and THBS1—showed consistent results between the NTPAM data sequencing and TCGA data. LASSO regression analysis revealed that five genes were associated with cancer prognosis, with a hazard ratio of 2.26. In RR-HNSCC cells, NTPAM affected DUSP16, PDGFB, and THBS1 as activated markers within 6 hours, and this effect persisted for 12 hours. Furthermore, enrichment analysis indicated that these three DEGs were associated with the extracellular matrix, transforming growth factor-beta, phosphoinositide 3-kinase/protein kinase B, and mesenchymal-epithelial transition factor pathways.
Conclusion
. NTPAM therapy exerts cytotoxic effects in RR-HNSCC cell lines by inducing specific ROS-mediated ferroptosis. DUSP16, PDGFB, and THBS1 were identified as crucial targets for reversing the radiation resistance induced by NTPAM therapy, providing insights into the mechanisms and clinical applications of NTPAM treatment in RR-HNSCC.
8.Gene Expression Alteration by Non-thermal Plasma-Activated Media Treatment in Radioresistant Head and Neck Squamous Cell Carcinoma
Sicong ZHENG ; Yudan PIAO ; Seung-Nam JUNG ; Chan OH ; Mi Ae LIM ; QuocKhanh NGUYEN ; Shan SHEN ; Se-Hee PARK ; Shengzhe CUI ; Shuyu PIAO ; Young Il KIM ; Ji Won KIM ; Ho-Ryun WON ; Jae Won CHANG ; Yujuan SHAN ; Lihua LIU ; Bon Seok KOO
Clinical and Experimental Otorhinolaryngology 2025;18(1):73-87
Objectives:
. Head and neck squamous cell carcinoma (HNSCC) exhibits high recurrence rates, particularly in cases of radioresistant HNSCC (RR-HNSCC). Non-thermal plasma (NTP) therapy effectively suppresses the progression of HNSCC. However, the therapeutic mechanisms of NTP therapy in treating RR-HNSCC are not well understood. In this study, we explored the regulatory role of NTP in the RR-HNSCC signaling pathway and identified its signature genes.
Methods:
. After constructing two RR-HNSCC cell lines, we prepared cell lysates from cells treated or not treated with NTP-activated media (NTPAM) and performed RNA sequencing to determine their mRNA expression profiles. Based on the RNA sequencing results, we identified differentially expressed genes (DEGs), followed by a bioinformatics analysis to identify candidate molecules potentially associated with NTPAM therapy for RR-HNSCC.
Results:
. NTPAM reduced RR-HNSCC cell viability in vitro. RNA sequencing results indicated that NTPAM treatment activated the reactive oxygen species (ROS) pathway and induced ferroptosis in RR-HNSCC cell lines. Among the 1,924 genes correlated with radiation treatment, eight showed statistical significance in both the cell lines and The Cancer Genome Atlas (TCGA) cohort. Only five genes—ABCC3, DUSP16, PDGFB, RAF1, and THBS1—showed consistent results between the NTPAM data sequencing and TCGA data. LASSO regression analysis revealed that five genes were associated with cancer prognosis, with a hazard ratio of 2.26. In RR-HNSCC cells, NTPAM affected DUSP16, PDGFB, and THBS1 as activated markers within 6 hours, and this effect persisted for 12 hours. Furthermore, enrichment analysis indicated that these three DEGs were associated with the extracellular matrix, transforming growth factor-beta, phosphoinositide 3-kinase/protein kinase B, and mesenchymal-epithelial transition factor pathways.
Conclusion
. NTPAM therapy exerts cytotoxic effects in RR-HNSCC cell lines by inducing specific ROS-mediated ferroptosis. DUSP16, PDGFB, and THBS1 were identified as crucial targets for reversing the radiation resistance induced by NTPAM therapy, providing insights into the mechanisms and clinical applications of NTPAM treatment in RR-HNSCC.
9.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.
10.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.

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