1.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.
2.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.
3.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.
4.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.
5.Consensus on informed consent for orthodontic treatment
Yang CAO ; Bing FANG ; Zuolin JIN ; Hong HE ; Yuxing BAI ; Lin WANG ; Haiping LU ; Zhihe ZHAO ; Tianmin XU ; Weiran LI ; Min HU ; Jinlin SONG ; Jun WANG ; Fang JIN ; Ding BAI ; Xianglong HAN ; Yuehua LIU ; Bin YAN ; Jie GUO ; Jiejun SHI ; Yongming LI ; Zhihua LI ; Xiuping WU ; Jiangtian HU ; Linyu XU ; Lin LIU ; Yi LIU ; Yanqin LU ; Wensheng MA ; Shuixue MO ; Liling REN ; Shuxia CUI ; Yongjie FAN ; Jianguang XU ; Lulu XU ; Zhijun ZHENG ; Peijun WANG ; Rui ZOU ; Chufeng LIU ; Lunguo XIA ; Li HU ; Weicai WANG ; Liping WU ; Xiaoxing KOU ; Jiali TAN ; Yuanbo LIU ; Bowen MENG ; Yuantao HAO ; Lili CHEN
Chinese Journal of Stomatology 2025;60(12):1327-1336
This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.
6.Research progress on Astragali Radix for promoting healing of chronic refractory wound
Yangyang YU ; Yuan GAO ; Jinling HE ; Hao WU ; Keyu CHEN ; Yuxing ZHAO
China Pharmacy 2025;36(19):2473-2478
Chronic refractory wound (CRW) presents significant clinical treatment challenges due to pathological characteristics such as persistent inflammation, bacterial infection, oxidative stress and inadequate angiogenesis. Astragali Radix, a traditional Chinese medicinal herb, exerts multi-target pharmacological effects on CRW through its active components, including Astragalus polysaccharides, flavonoids, and astragaloside Ⅳ, etc. Fundamental studies indicate that these components promote CRW healing by modulating inflammatory responses, inhibiting pathogen growth, improving antioxidant capacity and stimulating neovascularization. Network pharmacology and bioinformatics studies have revealed that active components of Astragali Radix target and modulate key signaling nodes such as nuclear factor-κB, phosphatidylinositol 3-kinase/Akt, AMP-activated protein kinase, and vascular endothelial growth factor receptor, as well as inflammation-angiogenesis-related pathways, thereby synergistically exerting anti-inflammatory and pro-angiogenic effect. Clinical applications have demonstrated that oral formulations (e.g., Huangqi guizhi decoction, Danggui huangqi decoction, etc.) reduce healing time of CRW and lower inflammatory marker levels, while topical preparations (e.g., Zizhu ointment, Huangqi shengji ointment, electrostatically spun Astragalus polysaccharide composite nanofibre dressings, etc.) significantly improve healing rates of CRW and minimize complications.
7.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.
8.Expert consensus on the prevention and treatment of enamel demineralization in orthodontic treatment.
Lunguo XIA ; Chenchen ZHOU ; Peng MEI ; Zuolin JIN ; Hong HE ; Lin WANG ; Yuxing BAI ; Lili CHEN ; Weiran LI ; Jun WANG ; Min HU ; Jinlin SONG ; Yang CAO ; Yuehua LIU ; Benxiang HOU ; Xi WEI ; Lina NIU ; Haixia LU ; Wensheng MA ; Peijun WANG ; Guirong ZHANG ; Jie GUO ; Zhihua LI ; Haiyan LU ; Liling REN ; Linyu XU ; Xiuping WU ; Yanqin LU ; Jiangtian HU ; Lin YUE ; Xu ZHANG ; Bing FANG
International Journal of Oral Science 2025;17(1):13-13
Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans
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Consensus
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Dental Caries/etiology*
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Dental Enamel/pathology*
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Tooth Demineralization/etiology*
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Tooth Remineralization
9.Expert consensus on early orthodontic treatment of class III malocclusion.
Xin ZHOU ; Si CHEN ; Chenchen ZHOU ; Zuolin JIN ; Hong HE ; Yuxing BAI ; Weiran LI ; Jun WANG ; Min HU ; Yang CAO ; Yuehua LIU ; Bin YAN ; Jiejun SHI ; Jie GUO ; Zhihua LI ; Wensheng MA ; Yi LIU ; Huang LI ; Yanqin LU ; Liling REN ; Rui ZOU ; Linyu XU ; Jiangtian HU ; Xiuping WU ; Shuxia CUI ; Lulu XU ; Xudong WANG ; Songsong ZHU ; Li HU ; Qingming TANG ; Jinlin SONG ; Bing FANG ; Lili CHEN
International Journal of Oral Science 2025;17(1):20-20
The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans
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Malocclusion, Angle Class III/classification*
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Orthodontics, Corrective/methods*
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Consensus
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Child
10.Machine Learning-Assisted Efficacy Evaluation of Resveratrol Therapy in a Mouse Model of Acute Pancreatitis
Ziyu LI ; Yuxing TIAN ; Wenhao CAI ; Yongzi WU ; Shiyu LIU ; Linbo YAO ; Yuying LI ; Xueying WU ; Tingting LIU ; Wei HUANG
Journal of Sichuan University (Medical Sciences) 2025;56(4):1051-1058
Objective To develop a machine learning(ML)-based prediction model for assessing the therapeutic effects of resveratrol(RES)on the pathological damage of acute pancreatitis(AP),and to optimize RES administration strategies for AP through validation using an animal model.Methods AAn ML-based prediction model was constructed using published data.Interpretability analysis was applied to identify high-efficacy zones within the parameter space of administration dose and frequency,which was followed by rigorous screening to select the optimal dosing strategy that balanced therapeutic efficacy and experimental feasibility.A total of 32 C57BL/6 mice were randomly assigned to 4 groups(n=8 per group),including a control group(Ctrl),an AP model group induced by caerulein(CER)and referred to as CER-AP,a treatment group receiving RES via intraperitoneal injection(RES i.p.),and a treatment group receiving RES via intragastric gavage(RES i.g.).The Ctrl group received intraperitoneal injection of normal saline.The CER-AP and the treatment groups were induced with 10 intraperitoneal injections of CER at 50 μg/kg.RES was administered to the RES i.p.and RES i.g.groups according to the optimal dose and timing predicted by the ML model.Blood and tissue samples were collected 12 hours after the experiment started.Results The gradient boosting decision tree model,optimized via Hyperopt,yielded the best performance,predicting that the optimal dose and administration frequency were 19.992 mg/kg and 3.828 times,respectively.Accordingly,a regimen of 20 mg/kg RES,administered four times,was used in the animal experiments.Compared with the Ctrl group,the CER-AP group exhibited higher pancreatic pathology scores and elevated levels of serum amylase,lipase,pancreatic myeloperoxidase,and trypsin,with all differences reaching statistical significance(all P<0.05).The administration of 20 mg/kg RES via both intraperitoneal injection and intragastric gavage mitigated pancreatic inflammatory cell infiltration and necrosis,improved the overall pathology score,and reduced serum amylase,lipase,and pancreatic myeloperoxidase levels to varying degrees(all P<0.05).Conclusion A regimen of 20 mg/kg RES administered four times effectively alleviates the severity of CER-induced AP.The therapeutic benefits appear to arise from a multi-target regulatory network that simultaneously suppresses inflammatory cascades,mitigates oxidative stress,and reduces apoptosis,thereby reducing pancreatic tissue damage and systemic inflammatory responses.

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