1.The Role of Golgi Apparatus Homeostasis in Regulating Cell Death and Major Diseases
Xin-Yue CHENG ; Feng-Hua YAO ; Hui ZHANG ; Yong-Ming YAO
Progress in Biochemistry and Biophysics 2025;52(8):2051-2067
The Golgi apparatus (GA) is a key membranous organelle in eukaryotic cells, acting as a central component of the endomembrane system. It plays an irreplaceable role in the processing, sorting, trafficking, and modification of proteins and lipids. Under normal conditions, the GA cooperates with other organelles, including the endoplasmic reticulum (ER), lysosomes, mitochondria, and others, to achieve the precise processing and targeted transport of nearly one-third of intracellular proteins, thereby ensuring normal cellular physiological functions and adaptability to environmental changes. This function relies on Golgi protein quality control (PQC) mechanisms, which recognize and handle misfolded or aberrantly modified proteins by retrograde transport to the ER, proteasomal degradation, or lysosomal clearance, thus preventing the accumulation of toxic proteins. In addition, Golgi-specific autophagy (Golgiphagy), as a selective autophagy mechanism, is also crucial for removing damaged or excess Golgi components and maintaining its structural and functional homeostasis. Under pathological conditions such as oxidative stress and infection, the Golgi apparatus suffers damage and stress, and its homeostatic regulatory network may be disrupted, leading to the accumulation of misfolded proteins, membrane disorganization, and trafficking dysfunction. When the capacity and function of the Golgi fail to meet cellular demands, cells activate a series of adaptive signaling pathways to alleviate Golgi stress and enhance Golgi function. This process reflects the dynamic regulation of Golgi capacity to meet physiological needs. To date, 7 signaling pathways related to the Golgi stress response have been identified in mammalian cells. Although these pathways have different mechanisms, they all help restore Golgi homeostasis and function and are vital for maintaining overall cellular homeostasis. It is noteworthy that the regulation of Golgi homeostasis is closely related to multiple programmed cell death pathways, including apoptosis, ferroptosis, and pyroptosis. Once Golgi function is disrupted, these signaling pathways may induce cell death, ultimately participating in the occurrence and progression of diseases. Studies have shown that Golgi homeostatic imbalance plays an important pathological role in various major diseases. For example, in Alzheimer’s disease (AD) and Parkinson’s disease (PD), Golgi fragmentation and dysfunction aggravate the abnormal processing of amyloid β-protein (Aβ) and Tau protein, promoting neuronal loss and advancing neurodegenerative processes. In cancer, Golgi homeostatic imbalance is closely associated with increased genomic instability, enhanced tumor cell proliferation, migration, invasion, and increased resistance to cell death, which are important factors in tumor initiation and progression. In infectious diseases, pathogens such as viruses and bacteria hijack the Golgi trafficking system to promote their replication while inducing host defensive cell death responses. This process is also a key mechanism in host-pathogen interactions. This review focuses on the role of the Golgi apparatus in cell death and major diseases, systematically summarizing the Golgi stress response, regulatory mechanisms, and the role of Golgi-specific autophagy in maintaining homeostasis. It emphasizes the signaling regulatory role of the Golgi apparatus in apoptosis, ferroptosis, and pyroptosis. By integrating the latest research progress, it further clarifies the pathological significance of Golgi homeostatic disruption in neurodegenerative diseases, cancer, and infectious diseases, and reveals its potential mechanisms in cellular signal regulation.
2.Illness duration-related developmental trajectory of progressive cerebral gray matter changes in schizophrenia.
Xin CHANG ; Zhihuan YANG ; Yingjie TANG ; Xiaoying SUN ; Cheng LUO ; Dezhong YAO
Journal of Biomedical Engineering 2025;42(2):293-299
In different stages of schizophrenia (SZ), alterations in gray matter volume (GMV) of patients are normally regulated by various pathological mechanisms. Instead of analyzing stage-specific changes, this study employed a multivariate structural covariance model and sliding-window approach to investigate the illness duration-related developmental trajectory of GMV in SZ. The trajectory is defined as a sequence of brain regions activated by illness duration, represented as a sparsely directed matrix. By applying this approach to structural magnetic resonance imaging data from 145 patients with SZ, we observed a continuous developmental trajectory of GMV from cortical to subcortical regions, with an average change occurring every 0.208 years, covering a time window of 20.176 years. The starting points were widely distributed across all networks, except for the ventral attention network. These findings provide insights into the neuropathological mechanism of SZ with a neuroprogressive model and facilitate the development of process for aided diagnosis and intervention with the starting points.
Humans
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Schizophrenia/pathology*
;
Gray Matter/pathology*
;
Magnetic Resonance Imaging
;
Disease Progression
;
Male
;
Female
;
Brain/pathology*
;
Cerebral Cortex/pathology*
;
Adult
3.Preliminary application of human-computer interaction CT imaging AI recognition and positioning technology in the treatment of type C1 distal radius fractures.
Yong-Zhong CHENG ; Xiao-Dong YIN ; Fei LIU ; Xin-Heng DENG ; Chao-Lu WANG ; Shu-Ke CUI ; Yong-Yao LI ; Wei YAN
China Journal of Orthopaedics and Traumatology 2025;38(1):31-40
OBJECTIVE:
To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures.
METHODS:
Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details.
RESULTS:
Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters.
CONCLUSION
Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans
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Male
;
Female
;
Radius Fractures/surgery*
;
Middle Aged
;
Adult
;
Aged
;
Aged, 80 and over
;
Tomography, X-Ray Computed/methods*
;
Retrospective Studies
;
Software
;
Wrist Fractures
4.Chemical diversity of azaphilones from the marine-derived fungus Talaromyces sp. HK1-18
Jia-cheng XUE ; Zhong-hui LI ; Bao-cong HAO ; Yao-yao ZHENG ; Xia-hao ZHU ; Zhi-xin CHEN ; Min CHEN
Acta Pharmaceutica Sinica 2024;59(5):1478-1483
GNPS-based mass spectrum-molecular networks is an effective strategy for rapidly identifying known natural products and discovering novel structures. The chemical diversity of azaphilones from the fermentation extracts of
5.Research progress on food literacy assessment tools for children and adolescents
QIAN Jinwei, TONG Yingge, PAN Xiang, YAO Lan, NI Ke, XIN Mengyu, CHENG Wenqian, HU Yuying
Chinese Journal of School Health 2024;45(6):891-894
Abstract
As dietary issues of children and adolescents become increasingly complex, the assessment of food literacy (FL) is increasingly importance. FL involves a comprehensive cognition and practical ability concerning food among children, playing a key role in fostering healthy eating habits and improving health levels. The article explores the definition and connotations of FL, and introduces eight FL assessment tools in terms of theoretical foundations, dimensions, assessment methods, and their reliability and validity. Moreover, it provides a comparative analysis of these tools by examining their dimensional design, evaluation indicators, strengths, and weaknesses, as well as their applicable subjects and scenarios, aiming to offer references for implementing relevant policies and developing more comprehensive and effective FL assessment tools.
6.Effect of preoperative oral ibuprofen on postoperative pain after dental implantation: a randomized controlled trial
Kang GAO ; Xuezhu WEI ; Bin ZHAO ; Zhiguang LIU ; Conglin DU ; Xin WANG ; Yao WANG ; Changying LIU ; Dezheng TANG ; Qi ZHANG ; Ruiqing WU ; Mingming OU ; Wei LI ; Qian CHENG ; Yilin XIE ; Pan MA ; Jun LI ; Hao WANG ; Zuomin WANG ; Su CHEN ; Wei ZHANG ; Jian ZHOU
Chinese Journal of Stomatology 2024;59(8):777-783
Objective:To evaluate the effect of preemptive analgesia with ibuprofen on postoperative pain following single posterior tooth implantation, aiming to provide a clinical reference for its application.Methods:A multicenter, randomized, double-blind, placebo-controlled parallel-group trial was conducted. A total of 82 participants were included in the trial, meeting the eligibility criteria from April 2022 to April 2024 at the Capital Medical University School of Stomatology (40 cases), Beijing TianTan Hospital, Capital Medical University (22 cases), Beijing Chao-Yang Hospital, Capital Medical University (20 cases). Participants were randomly assigned in a 1∶1 ratio to either the ibuprofen group or the control group, with each group comprising 41 individuals. Participants in the ibuprofen group received 300 mg of sustained-release ibuprofen capsules orally 15 min before surgery, while the control group received a placebo. Both groups received the same postoperative analgesic regimen for 3 days. Pain scores were assessed using the numerical rating scale at 30 min, 4 h, 6 h, 8 h, 24 h, 48 h, and 72 h postoperatively, and the additional use of analgesic medication was recorded from days 4 to 6 postoperatively.Results:A total of 82 participants were initially enrolled in the study, with 7 dropouts (4 from the control group and 3 from the ibuprofen group), resulting in 75 participants (37 in the control group and 38 in the ibuprofen group) completing the trial. There were no reports of adverse events such as nausea or vomiting among the participants. The ibuprofen group exhibited significantly lower pain scores at 4 h, 6 h and 8 h [1.0 (0.0, 2.0), 1.0 (0.0, 2.0), 1.5 (0.0, 3.0) ] postoperatively compared to the control group 4 h, 6 h and 8 h [2.0 (1.0, 3.0), 3.0 (1.5, 4.0), 2.0 (1.0, 4.0)] ( Z=-1.99, P=0.047; Z=-3.01, P=0.003; Z=-2.10, P=0.036). The proportions of patients requiring additional analgesic medication between days 4 and 6 post-surgery were 18.4% (7/38) in the ibuprofen group and 27.0% (10/37) in the control group, with no significant difference (χ 2=0.79, P=0.373). The median additional medication usage postoperatively was [0.0 (0.0, 0.0) pills] in the ibuprofen group and [0.0 (0.0, 1.0) pills] in the control group, with no significant difference ( Z=-0.78, P=0.439). Conclusions:Preemptive analgesia with ibuprofen effectively reduces postoperative pain following tooth implantation, representing a safe and effective perioperative pain management strategy.
7.Bioinformatics analysis and validation of the interaction between PML protein and TAB1 protein
Jiacong CHENG ; Zhihui LI ; Yao LIU ; Cheng LI ; Xin HUANG ; Yinxin TIAN ; Fubing SHEN
Journal of Southern Medical University 2024;44(1):179-186
Objective To analyze the interaction between PML protein and TAB1 protein using bioinformatic approaches and experimentally verify the results.Methods Using Rosetta software,a 3D model of TAB1 protein was constructed through a comparative modeling approach;the secondary structure of PML protein was retrieved in the PDB database and its crystal structure and 3D structure were resolved.Zdock 3.0.2 software was used to perform protein-protein docking of PML and TAB1,and the best conformation was extracted for molecular structure analysis of the docking model.The interaction between the two proteins was detected using immunoprecipitation in α-MMC-treated M1 inflammatory macrophages.Results When 6IMQ of PML was used as the docking site,PML protein formed 3 salt bridges,6 hydrogen bonds and 6 hydrophobic interactions with TAB1 proteins;when 5YUF of PML was used as the docking site,PML protein formed 1 hydrogen bond,3 electrostatic interactions and 9 hydrophobic interactions with TAB1 proteins,and both of the docking modes formed good molecular docking and interactions.In the M1 inflammatory macrophages treated with α-MMC for 4 h,positive protein bands of PML and TAB1 were detected in the cell lysates in PML-IP group.Conclusion PML protein can interact strongly with TAB1 protein.
8.Bioinformatics analysis and validation of the interaction between PML protein and TAB1 protein
Jiacong CHENG ; Zhihui LI ; Yao LIU ; Cheng LI ; Xin HUANG ; Yinxin TIAN ; Fubing SHEN
Journal of Southern Medical University 2024;44(1):179-186
Objective To analyze the interaction between PML protein and TAB1 protein using bioinformatic approaches and experimentally verify the results.Methods Using Rosetta software,a 3D model of TAB1 protein was constructed through a comparative modeling approach;the secondary structure of PML protein was retrieved in the PDB database and its crystal structure and 3D structure were resolved.Zdock 3.0.2 software was used to perform protein-protein docking of PML and TAB1,and the best conformation was extracted for molecular structure analysis of the docking model.The interaction between the two proteins was detected using immunoprecipitation in α-MMC-treated M1 inflammatory macrophages.Results When 6IMQ of PML was used as the docking site,PML protein formed 3 salt bridges,6 hydrogen bonds and 6 hydrophobic interactions with TAB1 proteins;when 5YUF of PML was used as the docking site,PML protein formed 1 hydrogen bond,3 electrostatic interactions and 9 hydrophobic interactions with TAB1 proteins,and both of the docking modes formed good molecular docking and interactions.In the M1 inflammatory macrophages treated with α-MMC for 4 h,positive protein bands of PML and TAB1 were detected in the cell lysates in PML-IP group.Conclusion PML protein can interact strongly with TAB1 protein.
9.Study on improving the photostability of nifedipine by crystal engineering
Xin MENG ; Yao ZOU ; Mei-ju LIU ; Cheng XING ; Ning-bo GONG ; Yang LÜ
Acta Pharmaceutica Sinica 2024;59(12):3374-3378
In order to improve the poor photostability of nifedipine, this study designed a cocrystal based on the principles of crystal engineering and prepared nifedipine-imidazole cocrystal by suspension method. The new cocrystal was characterized by powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetric analysis (TG) and infrared spectroscopy (IR) to confirm the formation of the cocrystal. The photostability of nifedipine and its cocrystal was measured by powder X-ray diffraction and high-performance liquid chromatography (HPLC). The results showed that the nifedipine-imidazole cocrystal improved the photostability of nifedipine to a certain extent. This study provides guidance for the development of nifedipine cocrystals and the improvement of its druggability.
10.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.


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