1.Practical exploration of empowering Medical Immunology teaching with digital intelligence
Haiying FU ; Dongmei YAN ; Weihua NI ; Yan QI ; Dong LI ; Jinying XU ; Hongyan YUAN ; Wei YANG
Chinese Journal of Immunology 2025;41(6):1286-1289,中插1,1293
With the rapid development of artificial intelligence(AI),how to digitize the teaching of Medical Immunology is a new challenge posed by the times and education.This study is based on the advanced teaching model of Medical Immunology,which includes lectures-PAD class-flipped classrooms-expert lecture.By introducing knowledge mapping and AI teaching assistant into the entire learning process,the students not only deepen their understanding of the knowledge system of Medical Immunology,but also ex-ercise their ability to apply immunological knowledge to solve practical clinical problems,enhance their self-learning ability,expres-sion ability,communication ability,on-site performance ability,and cultivate a spirit of unity,cooperation,and exploration.The practice of empowering Medical Immunology teaching with digital intelligence achieves the integration of theory and application,the linkage between in class and out of class teaching,the connection between commonalities and individualities,and the union of abili-ties and qualities in Medical Immunology teaching.It also provides practical basis for exploring the implementation path of digital intel-ligence empowerment in Medical Immunology teaching.
2.Analysis of Clinical Characteristics and Risk Factors for Bone Lesions in Patients with Multiple Myeloma
Chen-Yang LI ; Qi-Ke ZHANG ; Xiao-Fang WEI ; You-Fan FENG ; Yuan FU ; Qiao-Lin CHEN ; Wen-Jie ZHANG ; Yuan-Yuan ZHANG ; Shao-Hua ZHANG ; Shang-Yi ZHANG ; Jie LIU
Journal of Experimental Hematology 2025;33(6):1635-1639
Objective:To investigate the clinical characteristics of patients with multiple myeloma(MM)complicated by bone lesions and the risk factors associated with bone lesions.Methods:The clinical data of 294 newly diagnosed MM patients in Gansu Provincial Hospital from January 2017 to June 2021 were retrospectively analyzed.The patients were divided into the bone lesion group(154 cases)and the non-bone lesions group(140 cases)based on the presence of absence of bone lesions at diagnosis.The general data and laboratory parameters were compared between the two groups.The risk factors for bone lesions in MM patients were analyzed by logistic regression analysis,and the characteristic(ROC)curves were plotted to assess the predictive value of each risk factor for the occurrence of bone lesions in MM patients.Results:Compared to the non-bone lesion group,the bone lesion group had significantly higher serum calcium levels and significantly greater proportions of patients with Durie-Salmon(DS)stage Ⅲ,and bone pain(all P<0.05).Logistic regression analysis showed that elevated serum calcium(OR=5.135,95%CI:1.931-13.653,P=0.001),DS stage Ⅲ(OR=1.841,95%CI:1.019-3.328,P=0.043),and bone pain(OR=8.208,95%CI:4.761-14.151,P<0.001)were independent risk factors for bone lesions in MM patients.ROC curve analysis showed that serum calcium(AUC=0.619,95%CI:0.555-0.683,P<0.001)and bone pain(AUC=0.743,95%CI:0.692-0.793,P<0.001)had predictive value for bone lesions in MM patients.Conclusion:MM patients have a high incidence of bone lesions,and active monitoring and management of risk factors may improve treatment outcomes and prognosis.
3.Establishment and practice of scientific research project-based experimental system—exploration of"5+3"integration Medical Immunology experimental teaching
Haiying FU ; Yanling WANG ; Hongyan YUAN ; Dongmei YAN ; Weihua NI ; Yan QI ; Dong LI ; Xia CHEN ; Wei YANG
Chinese Journal of Immunology 2025;41(1):195-197,201
Theory and technology of Medical Immunology are widely used in scientific research.Our teaching and research group uses experimental teaching of Medical Immunology as a platform to carry out practice of scientific research project-based experi-mental system among"5+3"integration students.By completing a mini-project research including experimental design-experimental operation-research article writing,students cultivated scientific research thinking and exercised scientific research practice ability,and generally reported that the course is very difficult,but after completing it,it is very rewarding.
4.Study on the distribution of FMR1 CGG repeat numbers among 16 610 women of childbearing age in China
Yahui SHEN ; Wei HOU ; Xiaolin FU ; Manli ZHANG ; Xiaoxiao XIE ; Chunyan ZHANG ; Jiaxin BIAN ; Xiao MAO ; Juan WEN ; Chunyu LUO ; Hua JIN ; Qian ZHU ; Qingwei QI ; Yeqing QIAN ; Jing YUAN ; Yanyan ZHAO ; Ailan YIN ; Shutie LI ; Yulin JIANG ; Rui XIAO ; Yanping LU
Chinese Journal of Reproduction and Contraception 2025;45(4):398-402
Objective:To investigate the distribution of CGG repeat numbers in the FMR1 gene among reproductive-age women in China, providing data reference for carrier screening and genetic counseling of Fragile X syndrome. Methods:This cross-sectional study recruited 16 610 reproductive-age women from 12 medical institutions between July 2022 and October 2023. Peripheral venous blood samples (3 mL) were collected, and genomic DNA was extracted. The number of CGG repeats in the FMR1 gene was determined using the triplet-primed polymerase chain reaction (TP-PCR) combined with capillary electrophoresis technology. Statistical analyses were performed to assess the prevalence and distribution of CGG repeat expansions. Results:Among 16 610 women of childbearing age, 5 684 (34.220%) women had the same number of CGG repeats in the two alleles of FMR1 gene, and 10 926 (65.780%) women had different numbers of repeats in the two alleles. Among the 33 220 FMR1 alleles in 16 610 women of reproductive age, the most common CGG repeat numbers were 29 [48.645% (16 160/33 220)] and 30 [26.276% (8 729/33 220)], while the most frequent CGG genotype was CGG 29/29 [24.726% (4 107/16 610)]. The CGG repeat numbers of FMR1 gene were normal in 16 498 women (99.326%). Among the 112 women (0.674%) with CGG repeat abnormities, 96 (0.578%) women were classified as intermediate carriers, 15 (0.090%) as premutation carriers, and 1 (0.006%) as a full mutation carrier, whose CGG genotype was (36, >200). Conclusion:In the general reproductive-age female population in China, the normal CGG repeat numbers of the FMR1 gene account for 99.326%, while the intermediate carrier rate is 0.578%, and the combined carrier rate of the premutation and full mutation types is 0.096%.
5.Analysis of Clinical Characteristics and Risk Factors for Bone Lesions in Patients with Multiple Myeloma
Chen-Yang LI ; Qi-Ke ZHANG ; Xiao-Fang WEI ; You-Fan FENG ; Yuan FU ; Qiao-Lin CHEN ; Wen-Jie ZHANG ; Yuan-Yuan ZHANG ; Shao-Hua ZHANG ; Shang-Yi ZHANG ; Jie LIU
Journal of Experimental Hematology 2025;33(6):1635-1639
Objective:To investigate the clinical characteristics of patients with multiple myeloma(MM)complicated by bone lesions and the risk factors associated with bone lesions.Methods:The clinical data of 294 newly diagnosed MM patients in Gansu Provincial Hospital from January 2017 to June 2021 were retrospectively analyzed.The patients were divided into the bone lesion group(154 cases)and the non-bone lesions group(140 cases)based on the presence of absence of bone lesions at diagnosis.The general data and laboratory parameters were compared between the two groups.The risk factors for bone lesions in MM patients were analyzed by logistic regression analysis,and the characteristic(ROC)curves were plotted to assess the predictive value of each risk factor for the occurrence of bone lesions in MM patients.Results:Compared to the non-bone lesion group,the bone lesion group had significantly higher serum calcium levels and significantly greater proportions of patients with Durie-Salmon(DS)stage Ⅲ,and bone pain(all P<0.05).Logistic regression analysis showed that elevated serum calcium(OR=5.135,95%CI:1.931-13.653,P=0.001),DS stage Ⅲ(OR=1.841,95%CI:1.019-3.328,P=0.043),and bone pain(OR=8.208,95%CI:4.761-14.151,P<0.001)were independent risk factors for bone lesions in MM patients.ROC curve analysis showed that serum calcium(AUC=0.619,95%CI:0.555-0.683,P<0.001)and bone pain(AUC=0.743,95%CI:0.692-0.793,P<0.001)had predictive value for bone lesions in MM patients.Conclusion:MM patients have a high incidence of bone lesions,and active monitoring and management of risk factors may improve treatment outcomes and prognosis.
6.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.
7.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.
8.Deep learning dose prediction network-assisted radiotherapy plan design for head and neck cancer
Xuena YAN ; Siqi YUAN ; Xuejie XIE ; Qi FU ; Xinyuan CHEN ; Kuo MEN ; Jianrong DAI
Chinese Journal of Radiation Oncology 2025;34(6):569-575
Objective:To construct a general deep learning dose prediction model applicable to radiotherapy for head and neck tumors, establish design methods for artificial intelligence (AI)-assisted radiotherapy plan and evaluate the accuracy of prediction.Methods:Radiotherapy plans of 818 patients who received radiotherapy for head and neck cancers from January 2018 to June 2021 in Cancer Hospital of Chinese Academy of Medical Sciences were enrolled. Patients involved 17 types of common head and neck cancers, and the prescribed dose covered 5 kinds of dose gradients ranging from 54 Gy to 73.92 Gy. And 1-2 cases per each cancer type (31 cases in total) were randomly selected as the validation set, and the remaining 787 cases were used as the training set to build a deep learning head and neck radiotherapy generalized dose prediction model. Then based on the dose prediction results of this model, a program was written to automatically generate inverse optimization condition scripts, which were sent back to the treatment planning system to achieve AI-assisted radiotherapy plan design. Among the patients who received radiotherapy in our hospital from June 2021 to January 2022, 1 patient for each disease type (17 cases in total) was selected to evaluate the AI-assisted plan design program and evaluate its clinical feasibility using paired t-test. Results:Dose prediction model accuracy evaluation revealed that in the 31-case validation set, there was no statistical difference in the evaluation metrics of clinical concern for organs at risks, except for the D 1 cm3 prediction for spinal cord planning risk volume, which was statistically different compared with the clinical reference plan. The AI-assisted plan design program had higher plan quality metric scores (37.88±6.42) than manual plans (35.00±7.63) in 17 test cases ( t=-1.00, P=0.166). The number of manual adjustments to the inverse optimization conditions was reduced from (5.47±2.97) times to (2.76±1.00) times for the AI-assisted plan compared to the manual-only plan ( t=4.12, P<0.001). And the number of outlined dose shaping structures was reduced from 7.35±3.98 to 3.12±1.18 ( t=5.61, P<0.001). Conclusions:The unified universal model of dose prediction established for different head and neck cancers has high accuracy in dose prediction for all types of head and neck tumor plans. The AI-assisted planning method established in this pattern can reduce the clinical workload of physicists and improve the efficiency of their work.
9.Morin inhibits ubiquitination degradation of BCL-2 associated agonist of cell death and synergizes with BCL-2 inhibitor in gastric cancer cells.
Yi WANG ; Xiao-Yu SUN ; Fang-Qi MA ; Ming-Ming REN ; Ruo-Han ZHAO ; Meng-Meng QIN ; Xiao-Hong ZHU ; Yan XU ; Ni-da CAO ; Yuan-Yuan CHEN ; Tian-Geng DONG ; Yong-Fu PAN ; Ai-Guang ZHAO
Journal of Integrative Medicine 2025;23(3):320-332
OBJECTIVE:
Gastric cancer (GC) is one of the most common malignancies seen in clinic and requires novel treatment options. Morin is a natural flavonoid extracted from the flower stalk of a highly valuable medicinal plant Prunella vulgaris L., which exhibits an anti-cancer effect in multiple types of tumors. However, the therapeutic effect and underlying mechanism of morin in treating GC remains elusive. The study aims to explore the therapeutic effect and underlying molecular mechanisms of morin in GC.
METHODS:
For in vitro experiments, the proliferation inhibition of morin was measured by cell counting kit-8 assay and colony formation assay in human GC cell line MKN45, human gastric adenocarcinoma cell line AGS, and human gastric epithelial cell line GES-1; for apoptosis analysis, microscopic photography, Western blotting, ubiquitination analysis, quantitative polymerase chain reaction analysis, flow cytometry, and RNA interference technology were employed. For in vivo studies, immunohistochemistry, biomedical analysis, and Western blotting were used to assess the efficacy and safety of morin in a xenograft mouse model of GC.
RESULTS:
Morin significantly inhibited the proliferation of GC cells MKN45 and AGS in a dose- and time-dependent manner, but did not inhibit human gastric epithelial cells GES-1. Only the caspase inhibitor Z-VAD-FMK was able to significantly reverse the inhibition of proliferation by morin in both GC cells, suggesting that apoptosis was the main type of cell death during the treatment. Morin induced intrinsic apoptosis in a dose-dependent manner in GC cells, which mainly relied on B cell leukemia/lymphoma 2 (BCL-2) associated agonist of cell death (BAD) but not phorbol-12-myristate-13-acetate-induced protein 1. The upregulation of BAD by morin was due to blocking the ubiquitination degradation of BAD, rather than the transcription regulation and the phosphorylation of BAD. Furthermore, the combination of morin and BCL-2 inhibitor navitoclax (also known as ABT-737) produced a synergistic inhibitory effect in GC cells through amplifying apoptotic signals. In addition, morin treatment significantly suppressed the growth of GC in vivo by upregulating BAD and the subsequent activation of its downstream apoptosis pathway.
CONCLUSION
Morin suppressed GC by inducing apoptosis, which was mainly due to blocking the ubiquitination-based degradation of the pro-apoptotic protein BAD. The combination of morin and the BCL-2 inhibitor ABT-737 synergistically amplified apoptotic signals in GC cells, which may overcome the drug resistance of the BCL-2 inhibitor. These findings indicated that morin was a potent and promising agent for GC treatment. Please cite this article as: Wang Y, Sun XY, Ma FQ, Ren MM, Zhao RH, Qin MM, Zhu XH, Xu Y, Cao ND, Chen YY, Dong TG, Pan YF, Zhao AG. Morin inhibits ubiquitination degradation of BCL-2 associated agonist of cell death and synergizes with BCL-2 inhibitor in gastric cancer cells. J Integr Med. 2025; 23(3): 320-332.
Humans
;
Flavonoids/therapeutic use*
;
Stomach Neoplasms/pathology*
;
Animals
;
Proto-Oncogene Proteins c-bcl-2/metabolism*
;
Cell Line, Tumor
;
Apoptosis/drug effects*
;
Cell Proliferation/drug effects*
;
Ubiquitination/drug effects*
;
Mice
;
Drug Synergism
;
Mice, Inbred BALB C
;
Mice, Nude
;
Xenograft Model Antitumor Assays
;
Flavones
10.Disulfiram alleviates cardiac hypertrophic injury by inhibiting TAK1-mediated PANoptosis.
Wei-Dong LI ; Xuan-Yang SHEN ; Xiao-Lu JIANG ; Hong-Fu WEN ; Yuan SHEN ; Mei-Qi ZHANG ; Wen-Tao TAN
Acta Physiologica Sinica 2025;77(2):222-230
The study aims to examine the effects and potential mechanisms of disulfiram (DSF) on cardiac hypertrophic injury, focusing on the role of transforming growth factor-β-activated kinase 1 (TAK1)-mediated pan-apoptosis (PANoptosis). H9C2 cardiomyocytes were treated with angiotensin II (Ang II, 1 µmol/L) to establish an in vitro model of myocardial hypertrophy. DSF (40 µmol/L) was used to treat cardiomyocyte hypertrophic injury models, either along or in combination with the TAK1 inhibitor, 5z-7-oxozeaenol (5z-7, 0.1 µmol/L). We assessed cell damage using propidium iodide (PI) staining, measured cell viability with CCK8 assay, quantified inflammatory factor levels in cell culture media via ELISA, detected TAK1 and RIPK1 binding rates using immunoprecipitation, and analyzed the protein expression levels of key proteins in the TAK1-mediated PANoptosis pathway using Western blot. In addition, the surface area of cardiomyocytes was measured with Phalloidin staining. The results showed that Ang II significantly reduced the cellular viability of H9C2 cardiomyocytes and the binding rate of TAK1 and RIPK1, significantly increased the surface area of H9C2 cardiomyocytes, PI staining positive rate, levels of inflammatory factors [interleukin-1β (IL-1β), IL-18, and tumor necrosis factor α (TNF-α)] in cell culture media and p-TAK1/TAK1 ratio, and significantly up-regulated key proteins in the PANoptosis pathway [pyroptosis-related proteins NLRP3, Caspase-1 (p20), and GSDMD-N (p30), apoptosis-related proteins Caspase-3 (p17), Caspase-7 (p20), and Caspase-8 (p18), as well as necroptosis-related proteins p-MLKL, RIPK1, and RIPK3]. DSF significantly reversed the above changes induced by Ang II. Both 5z-7 and exogenous IL-1β weakened these cardioprotective effects of DSF. These results suggest that DSF may alleviate cardiac hypertrophic injury by inhibiting TAK1-mediated PANoptosis.
Animals
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MAP Kinase Kinase Kinases/physiology*
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Rats
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Myocytes, Cardiac/pathology*
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Disulfiram/pharmacology*
;
Cardiomegaly
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Apoptosis/drug effects*
;
Cell Line
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Angiotensin II
;
Necroptosis/drug effects*
;
Interleukin-1beta/metabolism*
;
Receptor-Interacting Protein Serine-Threonine Kinases/metabolism*
;
Lactones
;
Resorcinols
;
Zearalenone/administration & dosage*

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