1.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
2.Distinct gut microbiota and metabolic profiles in patients with neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein antibody-associated disease
Xiaowei PANG ; Lian CHEN ; Lan ZHANG ; Shu FAN ; Yuxin LIU ; Wei WANG ; Daishi TIAN ; Chuan QIN
Chinese Journal of Neurology 2025;58(11):1160-1168
Objective:To investigate the gut microbiota and metabolic profiles of patients with neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and to identify potential microbial biomarkers with diagnostic values.Methods:A total of 16 NMOSD patients, 6 MOGAD patients, and 22 age- and sex-matched healthy controls were recruited from Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology since June 2024. Fecal samples were subjected to metagenomic sequencing and untargeted metabolomics. Differential microbes were identified using LEfSe (linear discriminant analysis effect size), and receiver operating characteristic curve analysis was performed to evaluate diagnostic potential. Spearman correlation analysis was used to assess relationships between key microbes, metabolites, and serum antibody titers.Results:Distinct alterations in gut microbiota were observed in both disease groups compared with healthy controls. Ligilactobacillus salivarius was significantly enriched in both NMOSD and MOGAD patients and exhibited robust diagnostic accuracy (area under the curve=0.779 P=0.005). Metabolomics revealed that levels of ethosuximide and lysine-proline were elevated, while free fatty acids (15∶1) and 5, 6-dihydrothymine were reduced in the disease groups. Analysis results indicated that Ligilactobacillus salivarius abundance was positively correlated with aquaporin 4 antibody titers in NMOSD patients ( r=0.522, P=0.046). Conclusions:Patients with NMOSD and MOGAD have characteristic alterations in gut microbial and metabolic profiles.
3.EEG phase prediction method based on long short-term memory network
Zi-yan PANG ; Xin-yu ZHAO ; Wen-shu MAI ; Yue-zhuo ZHAO ; Zhi-peng LIU ; Tao YIN ; Jing-na JIN
Chinese Medical Equipment Journal 2025;46(3):1-8
Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P<0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89%)was higher than that by the traditional AR method(about 10%).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]
4.Updates and amendments of the Chinese Pharmacopoeia 2025 Edition (Volume Ⅰ)
LI Hao ; SHEN Mingrui ; ZHANG Pang ; ZHAI Weimin ; NI Long ; HAO Bo ; ZHAO Yuxin ; HE Yi ; MA Shuangcheng ; SHU Rong
Drug Standards of China 2025;26(1):017-022
The Chinese Pharmacopoeia is the legal technical standard which should be followed during the research, production, use, and administration of drugs. At present, the new edition of the Chinese Pharmacopoeia is planned to be promulgated and implemented. This article summarizes and analyzes the main characteristics and the content of updates and amendments of the Chinese Pharmacopoeia 2025 Edition(Volume Ⅰ), to provide a reference for the correct understanding and accurate implementation the new edition of the pharmacopoeia.
5.Electrical stimulation based on triboelectric nanogenerator promotes osteogenesis of MC3T3-E1 cells on titanium surfaces.
Bo PANG ; Shu YANG ; Hongyang HAN ; Xingwei ZHANG ; Tao SONG
Journal of Biomedical Engineering 2025;42(2):366-373
This paper aims to explore the effect of electrical stimulation of triboelectric nanogenerators (TENGs) on the osteogenic and other biological behaviors of mouse embryonic osteoblast precursor cells (MC3T3-E1 cells) on titanium surfaces. First, an origami-type TENG was fabricated, and its electrical output performance was tested. The optimal current of the generator and the feasibility of the experiment were verified by the CCK-8 assay and scratch assay. At the optimal current, the osteogenic conditions of the cells in each group were determined by quantitative analysis of the total protein content, alkaline phosphatase (ALP) activity, and alizarin red staining (ARS) on the titanium surface. Finally, the adhesion and spreading of cells on the titanium surface after electrical stimulation were observed. The results showed that the TENG had good electrical output performance, with an open-circuit voltage of 65 V and a short-circuit current of 42 μA. Compared with the rest of the current, a current strength of 30 μA significantly improved cell proliferation and migration, osteogenesis, and adhesion and spreading capabilities. The above results confirm the safety and operability of TENG in biomedical applications, laying the foundation for future TENG applications in reducing the time of bone integration around titanium implants after surgery.
Titanium/chemistry*
;
Osteogenesis
;
Animals
;
Mice
;
Osteoblasts/cytology*
;
Electric Stimulation/instrumentation*
;
Cell Adhesion
;
Cell Proliferation
;
Surface Properties
;
Cell Differentiation
;
Nanotechnology
6.Distinct gut microbiota and metabolic profiles in patients with neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein antibody-associated disease
Xiaowei PANG ; Lian CHEN ; Lan ZHANG ; Shu FAN ; Yuxin LIU ; Wei WANG ; Daishi TIAN ; Chuan QIN
Chinese Journal of Neurology 2025;58(11):1160-1168
Objective:To investigate the gut microbiota and metabolic profiles of patients with neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and to identify potential microbial biomarkers with diagnostic values.Methods:A total of 16 NMOSD patients, 6 MOGAD patients, and 22 age- and sex-matched healthy controls were recruited from Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology since June 2024. Fecal samples were subjected to metagenomic sequencing and untargeted metabolomics. Differential microbes were identified using LEfSe (linear discriminant analysis effect size), and receiver operating characteristic curve analysis was performed to evaluate diagnostic potential. Spearman correlation analysis was used to assess relationships between key microbes, metabolites, and serum antibody titers.Results:Distinct alterations in gut microbiota were observed in both disease groups compared with healthy controls. Ligilactobacillus salivarius was significantly enriched in both NMOSD and MOGAD patients and exhibited robust diagnostic accuracy (area under the curve=0.779 P=0.005). Metabolomics revealed that levels of ethosuximide and lysine-proline were elevated, while free fatty acids (15∶1) and 5, 6-dihydrothymine were reduced in the disease groups. Analysis results indicated that Ligilactobacillus salivarius abundance was positively correlated with aquaporin 4 antibody titers in NMOSD patients ( r=0.522, P=0.046). Conclusions:Patients with NMOSD and MOGAD have characteristic alterations in gut microbial and metabolic profiles.
7.EEG phase prediction method based on long short-term memory network
Zi-yan PANG ; Xin-yu ZHAO ; Wen-shu MAI ; Yue-zhuo ZHAO ; Zhi-peng LIU ; Tao YIN ; Jing-na JIN
Chinese Medical Equipment Journal 2025;46(3):1-8
Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P<0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89%)was higher than that by the traditional AR method(about 10%).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]
8.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
9.Changes in the Non-targeted Metabolomic Profile of Three-year-old Toddlers with Elevated Exposure to Polycyclic Aromatic Hydrocarbons
Yang LI ; Dan LIN ; Qin Xiu ZHANG ; Xiu Guang JU ; Ya SU ; Qian ZHANG ; Ping Hai DUAN ; Sen Wei YU ; Ling Bing WANG ; Tao Shu PANG
Biomedical and Environmental Sciences 2024;37(5):479-493
Objective To investigate changes in the urinary metabolite profiles of children exposed to polycyclic aromatic hydrocarbons(PAHs)during critical brain development and explore their potential link with the intestinal microbiota. Methods Liquid chromatography-tandem mass spectrometry was used to determine ten hydroxyl metabolites of PAHs(OH-PAHs)in 36-month-old children.Subsequently,37 children were categorized into low-and high-exposure groups based on the sum of the ten OH-PAHs.Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to identify non-targeted metabolites in the urine samples.Furthermore,fecal flora abundance was assessed by 16S rRNA gene sequencing using Illumina MiSeq. Results The concentrations of 21 metabolites were significantly higher in the high exposure group than in the low exposure group(variable importance for projection>1,P<0.05).Most of these metabolites were positively correlated with the hydroxyl metabolites of naphthalene,fluorine,and phenanthrene(r=0.336-0.531).The identified differential metabolites primarily belonged to pathways associated with inflammation or proinflammatory states,including amino acid,lipid,and nucleotide metabolism.Additionally,these distinct metabolites were significantly associated with specific intestinal flora abundances(r=0.34-0.55),which were mainly involved in neurodevelopment. Conclusion Higher PAH exposure in young children affected metabolic homeostasis,particularly that of certain gut microbiota-derived metabolites.Further investigation is needed to explore the potential influence of PAHs on the gut microbiota and their possible association with neurodevelopmental outcomes.
10.The role of prostatic urethral angle and intravesical prostatic protrusion on surgical capsule calculi formation in the prostate:A retrospective study
Jonathan YJ CHEN ; Han-Yu TSAI ; Chen-Pang HOU ; Shu-Han TSAO ; Yu-Ting CHEN ; Horng-Heng JUANG ; Yu-Hsiang LIN
Investigative and Clinical Urology 2024;65(5):459-465
Purpose:
To investigate the relationship between prostatic urethral angle (PUA) and the development of surgical capsule calculi (SCC) within the prostate, and to examine the presence and impact of intravesical prostatic protrusion (IPP).
Materials and Methods:
A retrospective analysis was conducted on 90 patients who underwent radical prostatectomy, with preoperative assessments using both transrectal ultrasound of the prostate (TRUS) and magnetic resonance imaging. Patients were divided into groups with and without SCC and further categorized into type 1 and type 2 stones based on the location and severity of the calculi. Statistical analysis included chi-square and independent sample t-tests, with p<0.05 considered significant.
Results:
Of the patients, 82.2% were diagnosed with SCC. No significant difference in PUA was found between patients with and without SCC. However, a notable disparity in IPP presence was observed, suggesting an inverse correlation with SCC development.Additionally, no significant differences were identified when comparing the two types of SCC based on PUA and IPP measurements.
Conclusions
The presence of IPP exhibited an inverse relationship with SCC, suggesting diminished urine flow pressure over the prostatic urethra may reduce the likelihood of SCC formation. However, no direct association between PUA and the presence or severity of SCC was identified. These findings highlight the complexity of factors contributing to prostatic calculi development and the potential role of IPP in this context.

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