1.Construction and Optimization of Alzheimer's Disease Classification Model Based on Brain Mixed Function Network Topology Parameters and Machine Learning
Xiao-yu HAN ; Xiu-zhu JIA ; Yang LI ; Meng-ying LOU ; Yong-qi NIE ; Xin-ping GUO ; Lu YU ; Zhi-yuan LI ; Lian-zheng SU
Progress in Modern Biomedicine 2025;25(11):1770-1778
Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P<0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7%,and the AUC values were up to 100%,99.5%,99.1%and 99.5%,respectively.The accuracy(98.5%),precision(98.5%),recall(98.5%),and AUC(99.1%)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0%,while Bagging has the lowest AUC value(99.1%)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13%),AUC(99.42%),recall rate(99.46%)and specificity(99.42%)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.
2.PD-L1 inhibits and regulates liver CD8+IFN-γ+ T cells to damage liver function and participate in atherosclerosis
Xiao LIU ; Xin WU ; Zi-yi ZHEN ; Jia-ying ZHANG ; Qi LI ; Chang CHEN
Chinese Pharmacological Bulletin 2025;41(4):638-645
Aim To study the effect of anti-PD-L1 monoclonal antibody on high-fat diet-induced athero-sclerosis in ApoE-/-mice.Methods Twenty-four ApoE-/-mice were randomly divided into the normal group,high-fat group,and high-fat+anti-PD-L1 mAb group.After 70 days,the blood samples were harves-ted.Blood vessels(aortic root to abdominal aorta)and liver from each groups were stained with Oil Red O.Hematoxylin-eosin staining(HE)was employed to vis-ualize structural changes in liver.Enzyme-linked im-munosorbent assay(ELISA)was applied to detect the serum levels of total cholesterol(CHO),triglyceride(TG),high-density lipoprotein(HDL-c),low-density lipoprotein(LDL-c)and inflammatory factors(IFN-γ,TNF-α,IL-1 β).Flow cytometry was used to detect the proportion of lymphocytes(CD4 and CD8).RT-PCR was utilized to assess the expressions of IFN-γ,TNF-α,IL-1 β,CD4 and CD8 in liver.Results Compared with the high-fat group,the treatment with anti-PD-L1 monoclonal antibody promoted vascular wall and liver lipid accumulation,and also up-regulated serum and liver content of cholesterol(CHO),triglyceride(TG)and high-density lipoprotein(HDL-c).Treatment with anti-PD-L1 monoclonal antibody up-regulated the con-tent of alanine aminotransferase(GPT)and aspartate aminotransferase(GOT)in serum and liver,but not al-kaline phosphatase(AKP).ELISA test indicated that treatment with anti-PD-L1 monoclonal antibody stimu-lated the serum level of IFN-γ,TNF-α and IL-1 β.Fur-thermore,the mRNA level of IFN-γ,TNF-α and IL-1 βin liver was also up-regulated after treatment with anti-PD-L1 monoclonal antibody.With flow cytometry,we observed that treatment with anti-PD-L1 monoclonal antibody promoted hepatic CD8+T and CD8+IFN-γ+T cell activation,but had no effect on CD4+IFN-γ+T cell activation under high-fat feeding conditions.Con-clusions Anti-PD-L1 monoclonal antibody adminis-tered under high-fat feeding conditions can damage liv-er function and aggravate atherosclerosis by activating liver CD8+IFN-γ+T cells.
3.Construction and Optimization of Alzheimer's Disease Classification Model Based on Brain Mixed Function Network Topology Parameters and Machine Learning
Xiao-yu HAN ; Xiu-zhu JIA ; Yang LI ; Meng-ying LOU ; Yong-qi NIE ; Xin-ping GUO ; Lu YU ; Zhi-yuan LI ; Lian-zheng SU
Progress in Modern Biomedicine 2025;25(11):1770-1778
Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P<0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7%,and the AUC values were up to 100%,99.5%,99.1%and 99.5%,respectively.The accuracy(98.5%),precision(98.5%),recall(98.5%),and AUC(99.1%)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0%,while Bagging has the lowest AUC value(99.1%)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13%),AUC(99.42%),recall rate(99.46%)and specificity(99.42%)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.
4.Adenoid cystic carcinoma of the cervix:6 cases report and literature review
Ting JIANG ; Ying-xin GONG ; Miao MA ; Yan XU ; Jia-min ZHOU ; Jing-xin DING ; Xiao-xia LIU
Fudan University Journal of Medical Sciences 2025;52(1):139-142
Adenoid cystic carcinoma(ACC)of the cervix is a rare and highly aggressive subtype of cervical cancer,accounting for less than 1%of all cervical cancer cases.ACC predominantly affects postmenopausal women over the age of 60,with postmenopausal vaginal bleeding being the most common symptom.Diagnosis of ACC primarily relies on histopathological examination and immunohistochemical analysis.Although there is currently no standard treatment protocol,surgical resection combined with radiotherapy or concurrent chemoradiotherapy is considered to be an effective approach.However,the effectiveness is limited,particularly in advanced cases,which generally have a poor prognosis.The treatment and prognosis of ACC are closely related to tumor staging,perineural invasion,and margin status.This paper discusses the clinical data and follow-up of six ACC patients treated at our institution,and goes through a literature review,examines its clinical features and treatment outcomes,underscores the critical importance of early diagnosis and individualized treatment.
5.Research progress of exoskeleton robot for lower limb medical rehabilitation
Hua-jun WANG ; Lian-xin HU ; Ze-feng WANG ; PEYRODIE LAURENT ; Ying NIE ; Shi-jia HU ; Xin-xin NI
Chinese Medical Equipment Journal 2025;46(1):88-100
The exoskeleton robot for lower limb medical rehabilitation in foreign countries and China was introduced in terms of the research status,structure and working principle,and analysis was carried out over its key technologies.It's pointed out the exoskeleton robot for lower limb medical rehabilitation would be enhanced in energy endurance,safety and comfort,individualized and intelligent control,modularity and lightweight design.[Chinese Medical Equipment Journal,2025,46(1):88-100]
6.Structural challenges and development pathways of the disease control supervisor system:A SWOT-CLPV integrated analysis
Yan-ling HAN ; Quan WANG ; Si-qi LIU ; Yu-meng LYU ; Yi-xin QIN ; Ying-ming SONG ; Jia-kun WANG ; Li YANG
Chinese Journal of Health Policy 2025;18(6):26-33
Objective:This study applies an integrated SWOT-CLPV framework combined with stakeholder analysis to systematically assess the strengths,weaknesses,opportunities,and threats of China's disease control inspector system,while identifying its control factors,leverage points,key problems,and vulnerabilities.Methods:Drawing on literature review,policy document analysis,and expert interviews with seven public health professionals,we extracted and categorized SWOT elements.A CLPV interaction analysis was conducted alongside stakeholder mapping to evaluate internal dynamics and systemic risks.Results:The inspector system demonstrates strengths in policy innovation and medical-public health integration,with external opportunities stemming from rising public health awareness and digital health advancements.However,the system faces weak endogenous momentum,limited leverage,and prominent control constraints and problem-prone areas,especially among grassroots institutions and inspectors themselves.Cross-sectoral coordination barriers and uneven local implementation contribute to significant institutional vulnerabilities.Conclusion:To enhance implementation and resilience,the system requires capacity building for key actors,improved governance structures,incentive and evaluation reforms,and strengthened coordination mechanisms to support the sustained and adaptive development of public health supervision.
7.Clinical trial of budesonide and formoterol fumarate powder for inhalation in the treatment of elderly patients with cough variant asthma
Ying SUN ; Xin SONG ; Jia WANG ; Yan-fang HOU ; Qun FU ; Qi ZHANG ; Jie LAI ; Tao GENG ; Chang-xin LI ; Jia-hui HUO ; Ying ZHANG ; Yan WENG
The Chinese Journal of Clinical Pharmacology 2025;41(1):1-5
Objective To compare the effects of different doses of budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet in the treatment of cough variant asthma(CVA)and the improvement of airway function and inflammatory factors.Methods Elderly patients with cough variant asthma were randomly divided into group A and group B.Both groups of patients received budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet.Group A was given budesonide and formoterol fumarate powder for inhalation(Ⅱ),2 inhalation per time,twice a day;Group B was given budesonide and formoterol fumarate powder for inhalation,4 inhalation per time,twice a day;budesonide fumatrol inhalation powder mist for continuous treatment for 6 months,and montelukast sodium tablet 10 mg once a day for at least 3 months.The nighttime cough scores of the two groups were compared before treatment and after treatment.The percentage of forced expiratory volume in one second(FEV1)in the predicted value,the maximum mid expiratory flow(MMEF),the fractional exhaled nitric oxide(FeNO),interleukin-5(IL-5)and eosinophils were compared between the two groups.The incidence of adverse drug reactions and the recurrence rate within 1 year were compared between the two groups.Results A total of 45 cases were enrolled in both the group A and the group B.At 9 months after treatment,the nocturnal cough scores of the group A and the group B were(0.93±0.42)and(0.65±0.29)points,respectively;the percentage of FEV1 in the predicted value were(97.75±9.67)%and(100.93±11.06)%,respectively;the MMEF values were(2.81±1.04)and(3.08±1.09)L·s-1,respectively;the FeNO values were(18.94±9.75)and(15.94±7.96)ppb,respectively;the IL-5 levels were(10.88±7.06)and(8.11±5.56)pg·mL-1,respectively.The above indicators in group B showed statistically significant differences compared to group A(all P<0.05).The total incidence of adverse drug reactions in group A and group B were 8.89%(5 cases/45 cases)and 13.33%(6 cases/45 cases),respectively.The recurrence rates was 15.56%(7 cases/45 cases)and 13.33%(6 cases/45 cases),respectively.There was no statistically significant difference in the above indicators between group B and group A(all P>0.05).Conclusion For elderly patients with CVA,higher dose of budesonide and formoterol fumarate powder for inhalation combined with montelukast sodium tablet can better improve cough symptoms,reduce the level of airway hyperresponsiveness and inflammatory factors,reduce the recurrence rate,and the patients are well tolerated.
8.PD-L1 inhibits and regulates liver CD8+IFN-γ+ T cells to damage liver function and participate in atherosclerosis
Xiao LIU ; Xin WU ; Zi-yi ZHEN ; Jia-ying ZHANG ; Qi LI ; Chang CHEN
Chinese Pharmacological Bulletin 2025;41(4):638-645
Aim To study the effect of anti-PD-L1 monoclonal antibody on high-fat diet-induced athero-sclerosis in ApoE-/-mice.Methods Twenty-four ApoE-/-mice were randomly divided into the normal group,high-fat group,and high-fat+anti-PD-L1 mAb group.After 70 days,the blood samples were harves-ted.Blood vessels(aortic root to abdominal aorta)and liver from each groups were stained with Oil Red O.Hematoxylin-eosin staining(HE)was employed to vis-ualize structural changes in liver.Enzyme-linked im-munosorbent assay(ELISA)was applied to detect the serum levels of total cholesterol(CHO),triglyceride(TG),high-density lipoprotein(HDL-c),low-density lipoprotein(LDL-c)and inflammatory factors(IFN-γ,TNF-α,IL-1 β).Flow cytometry was used to detect the proportion of lymphocytes(CD4 and CD8).RT-PCR was utilized to assess the expressions of IFN-γ,TNF-α,IL-1 β,CD4 and CD8 in liver.Results Compared with the high-fat group,the treatment with anti-PD-L1 monoclonal antibody promoted vascular wall and liver lipid accumulation,and also up-regulated serum and liver content of cholesterol(CHO),triglyceride(TG)and high-density lipoprotein(HDL-c).Treatment with anti-PD-L1 monoclonal antibody up-regulated the con-tent of alanine aminotransferase(GPT)and aspartate aminotransferase(GOT)in serum and liver,but not al-kaline phosphatase(AKP).ELISA test indicated that treatment with anti-PD-L1 monoclonal antibody stimu-lated the serum level of IFN-γ,TNF-α and IL-1 β.Fur-thermore,the mRNA level of IFN-γ,TNF-α and IL-1 βin liver was also up-regulated after treatment with anti-PD-L1 monoclonal antibody.With flow cytometry,we observed that treatment with anti-PD-L1 monoclonal antibody promoted hepatic CD8+T and CD8+IFN-γ+T cell activation,but had no effect on CD4+IFN-γ+T cell activation under high-fat feeding conditions.Con-clusions Anti-PD-L1 monoclonal antibody adminis-tered under high-fat feeding conditions can damage liv-er function and aggravate atherosclerosis by activating liver CD8+IFN-γ+T cells.
9.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
10.Analysis of the influencing factors of early enteral nutrition-related diarrhea in severe patients with temporary ileostomy
Jia-Jia HU ; Lu-Lu GU ; Cui-Li WU ; Xiang-Hong YE ; Yan JIANG ; Xin-Ying WANG
Parenteral & Enteral Nutrition 2025;32(1):48-53
Objective:To investigate the influencing factors of diarrhea during early enteral nutrition(EEN)therapy in severe patients with temporary ileostomy.Method:A total of 154 patients with temporary ileostomy who received EEN in the Department of General Surgery,Jinling Hospital from November 2019 to November 2023 were included in this study.All patients were divided into two groups:the diarrhea group(n=43)and the non-diarrhea group(n=111).The clinical data of the patients were retrospectively collected and analyzed,and univariate analysis was performed to compare the differences between groups.The indicators with significant differences were subjected to multivariate logistic regression analysis to determine the influencing factors of diarrhea during EEN therapy in severe patients with temporary ileostomy.Result:Among the 154 patients,43 developed diarrhea during EEN therapy,with an incidence of 27.9%.Multivariate logistic regression analysis showed that enteral nutrition(EN)infusion rate(OR=6.342,P=0.001,95%CI:2.055~19.572),antibiotics type(OR=8.342,P=0.013,95%CI:1.577~44.119),mechanical ventilation(OR=7.011,P=0.001,95%CI:2.272~21.629),EN formulation type(OR=6.497,P=0.001,95%CI:2.177~19.392),and diabetes(OR=3.321,P=0.036,95%CI:1.080~10.215)were closely associated with EN-related diarrhea in severe patients with temporary ileostomy.Conclusion:There was a high incidence of diarrhea in severe patients with temporary ileostomy who received EEN.EN infusion rate,antibiotics use,mechanical ventilation,EN formulation type and diabetes were the influencing factors for presence of EEN-related diarrhea in the patients.Our data could provide a reference for preventing EEN-related diarrhea in severe patients with temporary ileostomy after surgery.

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