1.Circulating immunological transcriptomic profile identifies DDX3Y and USP9Y on the Y chromosome as promising biomarkers for predicting response to programmed death 1/programmed death ligand 1 blockade.
Liting YOU ; Zhaodan XIN ; Feifei NA ; Min CHEN ; Yang WEN ; Jin LI ; Jiajia SONG ; Ling BAI ; Jianzhao ZHAI ; Xiaohan ZHOU ; Binwu YING ; Juan ZHOU
Chinese Medical Journal 2025;138(3):364-366
2.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.
3.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.
4.Expert consensus on ethical requirements for artificial intelligence (AI) processing medical data.
Cong LI ; Xiao-Yan ZHANG ; Yun-Hong WU ; Xiao-Lei YANG ; Hua-Rong YU ; Hong-Bo JIN ; Ying-Bo LI ; Zhao-Hui ZHU ; Rui LIU ; Na LIU ; Yi XIE ; Lin-Li LYU ; Xin-Hong ZHU ; Hong TANG ; Hong-Fang LI ; Hong-Li LI ; Xiang-Jun ZENG ; Zai-Xing CHEN ; Xiao-Fang FAN ; Yan WANG ; Zhi-Juan WU ; Zun-Qiu WU ; Ya-Qun GUAN ; Ming-Ming XUE ; Bin LUO ; Ai-Mei WANG ; Xin-Wang YANG ; Ying YING ; Xiu-Hong YANG ; Xin-Zhong HUANG ; Ming-Fei LANG ; Shi-Min CHEN ; Huan-Huan ZHANG ; Zhong ZHANG ; Wu HUANG ; Guo-Biao XU ; Jia-Qi LIU ; Tao SONG ; Jing XIAO ; Yun-Long XIA ; You-Fei GUAN ; Liang ZHU
Acta Physiologica Sinica 2024;76(6):937-942
As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence*
;
Humans
;
Consensus
;
Computer Security/standards*
;
Confidentiality/ethics*
;
Informed Consent/ethics*
5.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
6.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
7.Analysis of risk factors of mortality in infants and toddlers with moderate to severe pediatric acute respiratory distress syndrome.
Bo Liang FANG ; Feng XU ; Guo Ping LU ; Xiao Xu REN ; Yu Cai ZHANG ; You Peng JIN ; Ying WANG ; Chun Feng LIU ; Yi Bing CHENG ; Qiao Zhi YANG ; Shu Fang XIAO ; Yi Yu YANG ; Xi Min HUO ; Zhi Xian LEI ; Hong Xing DANG ; Shuang LIU ; Zhi Yuan WU ; Ke Chun LI ; Su Yun QIAN ; Jian Sheng ZENG
Chinese Journal of Pediatrics 2023;61(3):216-221
Objective: To identify the risk factors in mortality of pediatric acute respiratory distress syndrome (PARDS) in pediatric intensive care unit (PICU). Methods: Second analysis of the data collected in the "efficacy of pulmonary surfactant (PS) in the treatment of children with moderate to severe PARDS" program. Retrospective case summary of the risk factors of mortality of children with moderate to severe PARDS who admitted in 14 participating tertiary PICU between December 2016 to December 2021. Differences in general condition, underlying diseases, oxygenation index, and mechanical ventilation were compared after the group was divided by survival at PICU discharge. When comparing between groups, the Mann-Whitney U test was used for measurement data, and the chi-square test was used for counting data. Receiver Operating Characteristic (ROC) curves were used to assess the accuracy of oxygen index (OI) in predicting mortality. Multivariate Logistic regression analysis was used to identify the risk factors for mortality. Results: Among 101 children with moderate to severe PARDS, 63 (62.4%) were males, 38 (37.6%) were females, aged (12±8) months. There were 23 cases in the non-survival group and 78 cases in the survival group. The combined rates of underlying diseases (52.2% (12/23) vs. 29.5% (23/78), χ2=4.04, P=0.045) and immune deficiency (30.4% (7/23) vs. 11.5% (9/78), χ2=4.76, P=0.029) in non-survival patients were significantly higher than those in survival patients, while the use of pulmonary surfactant (PS) was significantly lower (8.7% (2/23) vs. 41.0% (32/78), χ2=8.31, P=0.004). No significant differences existed in age, sex, pediatric critical illness score, etiology of PARDS, mechanical ventilation mode and fluid balance within 72 h (all P>0.05). OI on the first day (11.9(8.3, 17.1) vs.15.5(11.7, 23.0)), the second day (10.1(7.6, 16.6) vs.14.8(9.3, 26.2)) and the third day (9.2(6.6, 16.6) vs. 16.7(11.2, 31.4)) after PARDS identified were all higher in non-survival group compared to survival group (Z=-2.70, -2.52, -3.79 respectively, all P<0.05), and the improvement of OI in non-survival group was worse (0.03(-0.32, 0.31) vs. 0.32(-0.02, 0.56), Z=-2.49, P=0.013). ROC curve analysis showed that the OI on the thind day was more appropriate in predicting in-hospital mortality (area under the curve= 0.76, standard error 0.05,95%CI 0.65-0.87,P<0.001). When OI was set at 11.1, the sensitivity was 78.3% (95%CI 58.1%-90.3%), and the specificity was 60.3% (95%CI 49.2%-70.4%). Multivariate Logistic regression analysis showed that after adjusting for age, sex, pediatric critical illness score and fluid load within 72 h, no use of PS (OR=11.26, 95%CI 2.19-57.95, P=0.004), OI value on the third day (OR=7.93, 95%CI 1.51-41.69, P=0.014), and companied with immunodeficiency (OR=4.72, 95%CI 1.17-19.02, P=0.029) were independent risk factors for mortality in children with PARDS. Conclusions: The mortality of patients with moderate to severe PARDS is high, and immunodeficiency, no use of PS and OI on the third day after PARDS identified are the independent risk factors related to mortality. The OI on the third day after PARDS identified could be used to predict mortality.
Female
;
Male
;
Humans
;
Child, Preschool
;
Infant
;
Child
;
Critical Illness
;
Pulmonary Surfactants/therapeutic use*
;
Retrospective Studies
;
Risk Factors
;
Respiratory Distress Syndrome/therapy*
8.Intestinal and pharyngeal microbiota in early neonates: an analysis based on high-throughput sequencing.
Xue-Juan WANG ; Zhi-Ying SHAO ; Min-Rong ZHU ; Ming-Yu YOU ; Yu-Han ZHANG ; Xiao-Qing CHEN
Chinese Journal of Contemporary Pediatrics 2023;25(5):508-515
OBJECTIVES:
To investigate the distribution characteristics and correlation of intestinal and pharyngeal microbiota in early neonates.
METHODS:
Full-term healthy neonates who were born in Shanghai Pudong New Area Maternal and Child Health Hospital from September 2021 to January 2022 and were given mixed feeding were enrolled. The 16S rRNA sequencing technique was used to analyze the stool and pharyngeal swab samples collected on the day of birth and days 5-7 after birth, and the composition and function of intestinal and pharyngeal microbiota were analyzed and compared.
RESULTS:
The diversity analysis showed that the diversity of pharyngeal microbiota was higher than that of intestinal microbiota in early neonates, but the difference was not statistically significant (P>0.05). On the day of birth, the relative abundance of Proteobacteria in the intestine was significantly higher than that in the pharynx (P<0.05). On days 5-7 after birth, the relative abundance of Actinobacteria and Proteobacteria in the intestine was significantly higher than that in the pharynx (P<0.05), and the relative abundance of Firmicutes in the intestine was significantly lower than that in the pharynx (P<0.05). At the genus level, there was no significant difference in the composition of dominant bacteria between the intestine and the pharynx on the day of birth (P>0.05), while on days 5-7 after birth, there were significant differences in the symbiotic bacteria of Streptococcus, Staphylococcus, Rothia, Bifidobacterium, and Escherichia-Shigella between the intestine and the pharynx (P<0.05). The analysis based on the database of Clusters of Orthologous Groups of proteins showed that pharyngeal microbiota was more concentrated on chromatin structure and dynamics and cytoskeleton, while intestinal microbiota was more abundant in RNA processing and modification, energy production and conversion, amino acid transport and metabolism, carbohydrate transport and metabolism, coenzyme transport and metabolism, and others (P<0.05). The Kyoto Encyclopedia of Genes and Genomes analysis showed that compared with pharyngeal microbiota, intestinal microbiota was more predictive of cell motility, cellular processes and signal transduction, endocrine system, excretory system, immune system, metabolic diseases, nervous system, and transcription parameters (P<0.05).
CONCLUSIONS
The composition and diversity of intestinal and pharyngeal microbiota of neonates are not significantly different at birth. The microbiota of these two ecological niches begin to differentiate and gradually exhibit distinct functions over time.
Humans
;
Infant, Newborn
;
Bacteria
;
China
;
High-Throughput Nucleotide Sequencing
;
Intestines
;
Microbiota
;
Pharynx/microbiology*
;
RNA, Ribosomal, 16S/genetics*
9.Diagnostic value of MDM2 RNA in situ hybridization in atypical lipomatous tumor/well-differentiated liposarcoma and dedifferentiated liposarcoma.
Chen CHEN ; Xin HE ; Wen Yi JING ; Yan QIU ; Min CHEN ; Tian You LUO ; Xiao Yu LIU ; Hui Juan CHEN ; Hong Ying ZHANG ; Hong BU
Chinese Journal of Pathology 2022;51(3):190-195
Objective: To investigate the value of MDM2 RNA in situ hybridization (RNA-ISH) in diagnosing atypical lipomatous tumor/well-differentiated liposarcoma (ALT/WDL) and dedifferentiated liposarcoma (DDL). Methods: A total of 26 ALT/WDL/DDLs diagnosed from March 2017 to May 2019 in West China Hospital, Sichuan University, Chengdu, China and 18 control cases were included. MDM2 RNA-ISH was performed on all samples and compared with the fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) regarding their performance in detecting MDM2. Results: All samples were detected successfully using the three methods. Among 26 ALT/WDL/DDLs, all cases showed MDM2 amplification and positivity for MDM2 RNA-ISH (26/26, 100%). Twenty-four (24/26, 92.3%) of the 26 tested cases were positive for MDM2 IHC while two of them were negative. Eighteen control cases were all negative for MDM2 FISH and RNA-ISH, and 15 (15/18) cases were negative for MDM2 IHC. The sensitivity and specificity of RNA-ISH were both 100%, and those of MDM2 IHC were 92.3% and 83.3%, respectively. Diffuse staining was identified in all MDM2 RNA-ISH positive ALT/WDL/DDLs, but identified in only 8/24 (33.3%) of the MDM2 IHC positive cases. Among the 11 ALT/WDL/DDL samples evaluated on tissue microarray, the positive rate of MDM2 RNA-ISH was 100% with diffuse staining in all cases. The positive rate of MDM2 IHC was 9/11 while only 1 of the 9 cases showed diffuse staining. The result of MDM2 RNA-ISH was identical to that of MDM2 FISH and was overall consistent with that of MDM2 IHC (Kappa=0.763, P<0.001). Conclusions: In ALT/WDL/DDLs, results of MDM2 RNA-ISH are highly consistent with those of FISH. MDM2 RNA-ISH is more sensitive and more specific and has more diffuse positive signals than the IHC. The findings indicate that MDM2 RNA-ISH is highly valuable for the diagnosis and differential diagnosis of ALT/WDL/DDLs.
Biomarkers, Tumor/genetics*
;
Gene Amplification
;
Humans
;
In Situ Hybridization, Fluorescence
;
Liposarcoma/genetics*
;
Proto-Oncogene Proteins c-mdm2/genetics*
;
RNA
10.Advances in research of Musashi2 in solid tumors.
Ying Gui YANG ; Min ZHAO ; Teng Teng DING ; Chu Ping NI ; Qing You ZHENG ; Xin LI
Journal of Southern Medical University 2022;42(3):448-456
RNA binding protein (RBP) plays a key role in gene regulation and participate in RNA translation, modification, splicing, transport and other important biological processes. Studies have shown that abnormal expression of RBP is associated with a variety of diseases. The Musashi (Msi) family of mammals is an evolutionarily conserved and powerful RBP, whose members Msi1 and Msi2 play important roles in the regulation of stem cell activity and tumor development. The Msi family members regulate a variety of biological processes by binding and regulating mRNA translation, stability and downstream cell signaling pathways, and among them, Msi2 is closely related to embryonic growth and development, maintenance of tumor stem cells and development of hematological tumors. Accumulating evidence has shown that Msi2 also plays a crucial role in the development of solid tumors, mainly by affecting the proliferation, invasion, metastasis and drug resistance of tumors, involving Wnt/β-catenin, TGF-β/SMAD3, Akt/mTOR, JAK/STAT, Numb and their related signaling pathways (Notch, p53, and Hedgehog pathway). Preclinical studies of Msi2 gene as a therapeutic target for tumor have achieved preliminary results. This review summarizes the molecular structure, physiological function, role of Msi2 in the development and progression of various solid tumors and the signaling pathways involved.
Animals
;
Hedgehog Proteins
;
Mammals/metabolism*
;
Neoplasms/genetics*
;
Neoplastic Stem Cells
;
RNA-Binding Proteins/metabolism*
;
Signal Transduction

Result Analysis
Print
Save
E-mail