1.Identification and Analysis of bHLH Genes Related to Color Formation of Gastrodia elata Stem
Xue JIANG ; Dandan RAN ; Xiuwen WANG ; Xiaobo ZHANG ; Xiaohong OU ; Jie PAN ; Tao ZHOU ; Zhen OUYANG ; Jiao XU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):202-209
ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently, the gene family members were subject to analysis, including gene structure, chromosomal localization, cis-acting elements, gene synteny, and phylogeny. Combined with transcriptome data and quantitative Real-time PCR, the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally, correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca, unevenly distributed across 17 chromosomes and clustered into 16 subfamilies, with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes, 12 bHLH genes (such as bHLH62-3 and bHLH74) were associated with the bright yellow color of G elata f. elata stem, while 9 bHLH genes (such as PIL13, UNE12, and bHLH130) were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca, the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata, and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes, 21 bHLH genes participate in the coloration metabolic pathway regulation of stems, flowers, and fruits. Specifically, bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata, thus relevant to the color formation of stem. Additionally, GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.
2.Identification and Analysis of bHLH Genes Related to Color Formation of Gastrodia elata Stem
Xue JIANG ; Dandan RAN ; Xiuwen WANG ; Xiaobo ZHANG ; Xiaohong OU ; Jie PAN ; Tao ZHOU ; Zhen OUYANG ; Jiao XU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):202-209
ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently, the gene family members were subject to analysis, including gene structure, chromosomal localization, cis-acting elements, gene synteny, and phylogeny. Combined with transcriptome data and quantitative Real-time PCR, the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally, correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca, unevenly distributed across 17 chromosomes and clustered into 16 subfamilies, with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes, 12 bHLH genes (such as bHLH62-3 and bHLH74) were associated with the bright yellow color of G elata f. elata stem, while 9 bHLH genes (such as PIL13, UNE12, and bHLH130) were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca, the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata, and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes, 21 bHLH genes participate in the coloration metabolic pathway regulation of stems, flowers, and fruits. Specifically, bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata, thus relevant to the color formation of stem. Additionally, GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.
3.Promotion of Angiogenesis by Colorectal Cancer Cell LoVo Derived-exosomes Through Transferring pEGFR
Ya-Jie CHENG ; Xue-Tong ZHOU ; Rui WANG ; Jin FANG
Progress in Biochemistry and Biophysics 2025;52(5):1229-1240
ObjectiveThis study sought to investigate the impact of exosomes derived from LoVo cells (LoVo-Exos) in colorectal cancer (CRC) on tumor angiogenesis, as well as to elucidate the potential molecular mechanisms underlying their pro-angiogenic effects. MethodsLoVo-Exos were isolated via ultracentrifugation, and their internalization into recipient human umbilical vein endothelial cells (HUVECs) was visualized using confocal microscopy. The influence of LoVo-Exos on angiogenesis was assessed through an in vitro tube formation assay. Additionally, the pro-angiogenic effects of LoVo-Exos were evaluated in vivo using a matrix gluing assay in mice. To investigate the molecular mechanisms through which LoVo-Exos facilitate angiogenesis, Western blot analysis was employed to examine the transfer of pEGFR by LoVo-Exos into recipient cells. Both Western blot and ELISA were utilized to assess the expression levels of key signaling proteins within the EGFR-ERK pathway, as well as the expression of downstream angiogenic core molecules. Furthermore, the impact of EGFR knockdown and ERK inhibitor treatment on angiogenesis was evaluated, with subsequent analysis of the expression of downstream angiogenic core molecules following these interventions. ResultsConfocal microscopy demonstrated the internalization of LoVo-Exos into HUVECs. In vitro angiogenesis assays further indicated that LoVo-Exos significantly enhanced the formation of tubular structures in HUVECs. Additionally, macroscopic examination of subcutaneous matrix plug formation in mice revealed a substantial increase in vascular-like structures within the matrix plugs following the administration of LoVo-Exos, compared to the PBS control group. Hematoxylin and eosin (HE) staining revealed the presence of erythrocyte-filled microvessels within the matrix plugs combined with LoVo-Exos. Furthermore, immunohistochemical analysis demonstrated the expression of the endothelial cell marker CD31 in these matrix plugs. The presence of CD31-positive cells in the LoVo-Exos-treated matrix plugs was associated with a significant enhancement in the formation of luminal structures. These findings suggest that LoVo-Exos facilitate the in vivo development of vascular-like structures. Subsequent investigations demonstrated that LoVo-Exos facilitated the delivery of pEGFR to HUVEC, thereby enhancing angiogenesis. Conversely, LoVo-Exos with EGFR knockdown exhibited a diminished capacity to promote angiogenesis, an effect that was further attenuated by the ERK phosphorylation inhibitor U0126. Western blot analysis assessing the activation of the EGFR-ERK signaling pathway in HUVEC indicated that LoVo-Exos augmented angiogenesis through the activation of this pathway. Furthermore, analysis of the impact of LoVo-Exos on the expression of downstream angiogenic core molecules revealed an increase in interleukin-8 (IL-8) secretion in HUVEC. The enhancement observed was diminished in LoVo-Exos following EGFR knockdown, and this reduction was counteracted by the ERK phosphorylation inhibitor U0126. ConclusionThe underlying mechanism may involve the delivery of pEGFR in LoVo-Exos to HUVECs, leading to increased IL-8 secretion via the EGFR-ERK signaling pathway, thereby enhancing the angiogenic potential of HUVECs. This finding may offer new insights into the mechanisms underlying cancer metastasis.
4.Bioinformatics analysis of efferocytosis-related genes in diabetic kidney disease and screening of targeted traditional Chinese medicine.
Yi KANG ; Qian JIN ; Xue-Zhe WANG ; Meng-Qi ZHOU ; Hui-Juan ZHENG ; Dan-Wen LI ; Jie LYU ; Yao-Xian WANG
China Journal of Chinese Materia Medica 2025;50(14):4037-4052
This study employed bioinformatics to screen the feature genes related to efferocytosis in diabetic kidney disease(DKD) and explores traditional Chinese medicine(TCM) regulating these feature genes. The GSE96804 and GSE30528 datasets were integrated as the training set, and the intersection of differentially expressed genes and efferocytosis-related genes(ERGs) was identified as DKD-ERGs. Subsequently, correlation analysis, protein-protein interaction(PPI) network construction, enrichment analysis, and immune infiltration analysis were performed. Consensus clustering was conducted on DKD patients based on the expression levels of DKD-ERGs, and the expression levels, immune infiltration characteristics, and gene set variations between different subtypes were explored. Eight machine learning models were constructed and their prediction performance was evaluated. The best-performing model was evaluated by nomograms, calibration curves, and external datasets, followed by the identification of efferocytosis-related feature genes associated with DKD. Finally, potential TCMs that can regulate these feature genes were predicted. The results showed that the training set contained 640 differentially expressed genes, and after intersecting with ERGs, 12 DKD-ERGs were obtained, which demonstrated mutual regulation and immune modulation effects. Consensus clustering divided DKD into two subtypes, C1 and C2. The support vector machine(SVM) model had the best performance, predicting that growth arrest-specific protein 6(GAS6), S100 calcium-binding protein A9(S100A9), C-X3-C motif chemokine ligand 1(CX3CL1), 5'-nucleotidase(NT5E), and interleukin 33(IL33) were the feature genes of DKD. Potential TCMs with therapeutic effects included Astragali Radix, Trionycis Carapax, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma, which mainly function to clear heat, replenish deficiency, activate blood, resolve stasis, and promote urination and drain dampness. Molecular docking revealed that the key components of these TCMs, including β-sitosterol, quercetin, and sitosterol, exhibited good binding activity with the five target genes. These results indicated that efferocytosis played a crucial role in the development and progression of DKD. The feature genes closely related to both DKD and efferocytosis, such as GAS6, S100A9, CX3CL1, NT5E, and IL33, were identified. TCMs such as Astragali Radix, Trionycis Carapa, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma may provide a new therapeutic strategy for DKD by regulating efferocytosis.
Humans
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Computational Biology
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Diabetic Nephropathies/physiopathology*
;
Protein Interaction Maps
;
Medicine, Chinese Traditional
;
Drugs, Chinese Herbal
;
Phagocytosis/genetics*
;
Efferocytosis
5.Beneficial Bacterial Modulation by Gypsum Fibrosum and Terra Flava Usta in Gut Microbiota.
Meng-Jie LI ; Yang-Yang DONG ; Na LI ; Rui ZHANG ; Hong-Lin ZHANG ; Zhi-Mao BAI ; Xue-Jun KANG ; Peng-Feng XIAO ; Dong-Rui ZHOU
Chinese journal of integrative medicine 2025;31(9):812-820
OBJECTIVE:
To investigate the regulatory effects of two traditional mineral medicines (TMMs), Gypsum Fibrosum (Shigao, GF) and Terra Flava Usta (Zaoxintu, TFU), on gut-beneficial bacteria in mice, and preliminarily explore their mechanisms of action.
METHODS:
Mice were randomly divided into 3 groups (n=10 per group): the control group (standard diet), the GF group (diet supplemented with 2% GF), and the TFU group (diet supplemented with 2% TFU). After 4-week intervention, 16S rRNA gene sequencing was used to analyze the changes in the gut microbiota (GM). Scanning electron microscopy, in combination with coumarin A tetramethyl rhodamine conjugate and Hoechst stainings, was used to observe the bacteria and biofilm formation.
RESULTS:
Principal coordinate analysis revealed that GF and TFU significantly altered the GM composition in mice. Further analysis revealed that GF and TFU affected different types of gut bacteria, suggesting that different TMMs may selectively modulate specific bacterial populations. For certain bacteria, such as Faecalibaculum and Ileibacterium, both GF and TFU exhibited growth-promoting effects, implying that they may be sensitive to TMMs and that different TMMs can increase their abundance through their respective mechanisms. Notably, Lactobacillus reuteri, a widely recognized and used probiotic, was significantly enriched in the GF group. Random forest analysis identified Ileibacterium valens as a potential indicator bacterium for TMMs' impact on GM. Further mechanistic studies showed that gut bacteria formed biofilm structures on the TFU surface.
CONCLUSIONS
This study provides new insights into the interaction between TMMs and GM. As safe and effective natural clays, GF and TFU hold promise as potential candidates for prebiotic development.
Animals
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Gastrointestinal Microbiome/drug effects*
;
Bacteria/growth & development*
;
Mice
;
Biofilms/drug effects*
;
Male
;
RNA, Ribosomal, 16S/genetics*
6.Sex Differences in Pain Contagion Determined by the Balance of Oxytocin and Corticosterone in the Anterior Cingulate Cortex in Rodents.
Zhiyuan XIE ; Wenxi YUAN ; Lingbo ZHOU ; Jie XIAO ; Huabao LIAO ; Jiang-Jian HU ; Xue-Jun SONG
Neuroscience Bulletin 2025;41(12):2167-2183
Empathy is crucial for communication and survival for individuals. Whether empathy in pain contagion shows sex differences and its underlying mechanisms remain unclear. Here, we report that pain contagion can occur in stranger female rats, but not in stranger males. Blocking oxytocin receptors in the anterior cingulate cortex (ACC) suppressed pain contagion in female strangers, while oxytocin administration induced pain contagion in male strangers. In vitro, corticosterone reduces neuronal activation by oxytocin. During male stranger interactions, higher corticosterone decreased oxytocin receptor-positive neuronal activity in the ACC, suppressing pain contagion. These findings highlight the role of oxytocin in pain contagion and suggest that sex differences in empathy may be determined by the balance of oxytocin and corticosterone in the ACC. This study suggests an approach for the treatment of certain mental disorders associated with abnormal empathy, such as autism and depression.
Animals
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Oxytocin/pharmacology*
;
Gyrus Cinguli/drug effects*
;
Male
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Female
;
Corticosterone/pharmacology*
;
Empathy/drug effects*
;
Sex Characteristics
;
Receptors, Oxytocin/antagonists & inhibitors*
;
Pain/psychology*
;
Rats
;
Rats, Sprague-Dawley
;
Neurons/metabolism*
7.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.
8.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.
9.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.
10.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.

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