1.Identification and infection rate of densovirus in Culex pipiens pallens in Beijing in 2023
Xiu-yan XU ; Ting YAN ; Si-jie ZHU ; Jing LI ; Mei-de LIU ; Hong-jiang ZHANG ; Ting LIU ; Qiu-hong LI ; Xiao-jie ZHOU ; Ying TONG ; Yong ZHANG
Acta Parasitologica et Medica Entomologica Sinica 2026;33(1):25-30
Objective This study conducted molecular biological identification of the viruses carried by Culex pipiens pallens specimens collected in Shunyi District, Beijing in 2023, and observed the changes in the infection rate of the viruses carried by Cx. pipiens pallens at different collection times. Methods Cx. pipiens pallens were collected using carbon dioxide mosquito traps. The mosquito samples were ground in batches and analyzed by molecular biology technologies. The virus infection rate at different collection times was analyzed statistically. Results 17 strains of Culex pipiens pallens densovirus(CppDNV)were identified from Cx. pipiens pallens samples collected in Shunyi District, Beijing, in 2023. The nucleotide sequence analysis of the virus genome coding region showed that CppDNV was a single-stranded DNA virus with a total length of 3 335 nt, encoding 2 non-structural proteins(NS1, NS2)and 1 capsid protein(VP). The nucleotide(amino acid)sequence lengths of the three proteins were 2 376 nt(791 aa),1 092 nt(363 aa)and 1 071 nt(356 aa), respectively. Phylogenetic analysis showed that CppDNV was located in genus Brevihamaparvovirus. Statistical analysis showed no significant difference in infection rates across collection times(χ2=4.429, P=0.194). Conclusions CppDNV was identified in Cx. pipiens pallens in Beijing, and it was stably maintained in this natural population.
2.Comparison of random forest and Cox regression models for predicting long-term survival after radical resection of HBV-associated hepatocellu-lar carcinoma
Guang-zhou LI ; Hong-lei WANG ; Xi-quan CHEN ; Yang HE ; Yan-hao CHEN ; Cui HU ; Miao WANG ; De-xiao ZHANG
Chinese Journal of Current Advances in General Surgery 2025;28(5):355-360
Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.
3.Comparison of random forest and Cox regression models for predicting long-term survival after radical resection of HBV-associated hepatocellu-lar carcinoma
Guang-zhou LI ; Hong-lei WANG ; Xi-quan CHEN ; Yang HE ; Yan-hao CHEN ; Cui HU ; Miao WANG ; De-xiao ZHANG
Chinese Journal of Current Advances in General Surgery 2025;28(5):355-360
Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.
4.Mechanism of Aerobic Exercise in Delaying Brain Aging in Aging Mice by Regulating Tryptophan Metabolism
De-Man ZHANG ; Chang-Ling WEI ; Yuan-Ting ZHANG ; Yu JIN ; Xiao-Han HUANG ; Min-Yan ZHENG ; Xue LI
Progress in Biochemistry and Biophysics 2025;52(6):1362-1372
ObjectiveTo explore the molecular mechanism of aerobic exercise to improve hippocampal neuronal degeneration by regulating tryptophan metabolic pathway. Methods60 SPF-grade C57BL/6J male mice were divided into a young group (2 months old, n=30) and a senile group (12 months old, n=30), and each group was further divided into a control group (C/A group, n=15) and an exercise group (CE/AE group, n=15). An aerobic exercise program was used for 8 weeks. Learning memory ability was assessed by Y-maze, and anxiety-depression-like behavior was detected by absent field experiment. Hippocampal Trp levels were measured by GC-MS. Nissl staining was used to observe the number and morphology of hippocampal neurons, and electron microscopy was used to detect synaptic ultrastructure. ELISA was used to detect the levels of hippocampal Trp,5-HT, Kyn, KATs, KYNA, KMO, and QUIN; Western blot was used to analyze the activities of TPH2, IDO1, and TDO enzymes. ResultsGroup A mice showed significant decrease in learning and memory ability (P<0.05) and increase in anxiety and depressive behaviors (P<0.05); all of AE group showed significant improvement (P<0.05). Hippocampal Trp levels decreased in group A (P<0.05) and increased in AE group (P<0.05). Nidus vesicles were reduced and synaptic structures were degraded in group A (P<0.05), and both were significantly improved in group AE (P<0.05). The levels of Trp, 5-HT, KATs, and KYNA were decreased (P<0.05) and the levels of Kyn, KMO, and QUIN were increased (P<0.05) in group A. The activity of TPH2 was decreased (P<0.05), and the activities of IDO1 and TDO were increased (P<0.05). The AE group showed the opposite trend. ConclusionThe aging process significantly reduces the learning memory ability and increases the anxiety-depression-like behavior of mice, and leads to the reduction of the number of nidus vesicles and degenerative changes of synaptic structure in the hippocampus, whereas aerobic exercise not only effectively enhances the spatial learning memory ability and alleviates the anxiety-depression-like behavior of aging mice, but also improves the morphology and structure of neurons in hippocampal area, which may be achieved by the mechanism of regulating the tryptophan metabolic pathway.
5.Correlation of MET Status with Clinicopathological Features and Prognosis of Advanced Prostatic Acinar Adenocarcinoma
Weiying HE ; Wenjia SUN ; Huiyu LI ; Yanggeling ZHANG ; De WU ; Chunxia AO ; Jincheng WANG ; Yanan YANG ; Xuexue XIAO ; Luyao ZHANG ; Xiyuan WANG ; Junqiu YUE
Cancer Research on Prevention and Treatment 2025;52(8):698-704
Objective To explore the correlation of MET status in patients with advanced prostatic acinar adenocarcinoma with the clinical pathological parameters and prognosis. Methods The specimen from 135 patients with advanced prostatic acinar adenocarcinoma was included. The expression of c-MET protein was detected via immunohistochemistry, and MET gene amplification was assessed by fluorescence in situ hybridization. The relationships of c-MET expression and gene amplification with clinicopathological features and prognosis were analyzed. Results The positive expression rate of c-MET was 52.60% (71/135). Compared with the c-MET expression in adjacent tissues, that in tumor tissues showed lower heterogeneous expression. Among the cases, 1.71% (2/117) exhibited MET gene polyploidy, but no gene amplification was detected. Positive c-MET expression was significantly correlated with high Gleason scores and grade groups (P=
6.Current situation of medicinal animal breeding and research progress in sustainable utilization of resources.
Cheng-Cai ZHANG ; Jia WANG ; Yu-Jie ZHOU ; Xiao-Yu DAI ; Xiu-Fu WAN ; Chuan-Zhi KANG ; De-Hua WU ; Jia-Hui SUN ; Sheng WANG ; Lan-Ping GUO
China Journal of Chinese Materia Medica 2025;50(16):4397-4406
Traditional Chinese medicine(TCM) is the pillar for the development of motherland medicine, and animal medicine has a long history of application in China, characterized by wide resources, strong activity, definite efficacy, and great benefits. It has significant potential and important status in the consumption market of raw materials of TCM. In the context of global climate change, farming system alterations, and low renewability, the depletion of wild medicinal animal resources has accelerated. Accordingly, the conservation and sustainable utilization of wild resources of animal medicinal materials has become a problem that garners increasing attention and urgently needs to be solved. This paper summarizes the current situation of domestic and foreign medicinal animal breeding and research progress in industrial application in recent years and points out the issues related to standardized breeding, germplasm selection and breeding, and quality evaluation standards for medicinal animals. Furthermore, this paper discusses standardized breeding, quality standards, resource protection and utilization, and the search for alternative resources for rare and endangered medicinal animals. It proposes that researchers should systematically carry out in-depth basic research on animal medicine, improve the breeding scale and level of medicinal animals, employ modern technology to enhance the quality standards of medicinal materials, and strengthen the research and development of alternative resources. This approach aims to effectively address the relationship between protection and utilization and make a significant contribution to the sustainable development of medicinal animal resources and the animal-based Chinese medicinal material industry.
Animals
;
Breeding
;
China
;
Medicine, Chinese Traditional
;
Conservation of Natural Resources
7.Research progress on the regulation of Hippo -YAP signaling pathway in osteoarthritis.
Xi-Yao TAI ; De-Cai HOU ; Jiang ZHANG ; Xiao-Lei DENG
China Journal of Orthopaedics and Traumatology 2025;38(7):759-764
Osteoarthritis (OA) is the most common degenerative joint disease. Its pathological process is related to inflammatory response, chondrocyte apoptosis, and cartilage degeneration. Hippo-yes-associate protein(YAP) signaling pathway plays an important role in mediating organ size and tissue homeostasis. In recent years, the key effector protein YAP in the Hippo-YAP pathway has become a research hotspot in osteoarthritis. This article introduces the activation process of Hippo-YAP signaling pathway and the biological role of YAP. It reviews the progress of YAP in regulating osteoarthritis by influencing the proliferation and differentiation of mesenchymal stem cells and the proliferation, differentiation, and apoptosis of articular chondrocytes. It analyzed the problems encountered in YAP research in OA, introduces the research potential of YAP in other orthopedic diseases, and provides new ideas for subsequent research in Osteoarthritis.
Osteoarthritis/metabolism*
;
Humans
;
Signal Transduction
;
Protein Serine-Threonine Kinases/physiology*
;
Hippo Signaling Pathway
;
YAP-Signaling Proteins
;
Adaptor Proteins, Signal Transducing/physiology*
;
Animals
;
Transcription Factors
;
Chondrocytes/cytology*
;
Cell Cycle Proteins
8.Research on prediction of fracture reduction fixator therapy based on multimodal multi-label method.
Hai-Yu LIU ; De-Long WANG ; Xing-Ping ZHANG ; Hong-de LI ; Yan SUN ; Xiao-Ping ZHANG
China Journal of Orthopaedics and Traumatology 2025;38(11):1164-1169
OBJECTIVE:
To construct a prediction model for fracture reduction fixator therapy using the multi-modal multi-label classification (MMC) method.
METHODS:
Medical record data of 818 orthopedic patients from 2019 to 2023 were collected. Medical image features were extracted using the VGG19 network, text features of TCM four diagnostic methods (Inspection, Auscultation & Olfaction, Inquiry, Palpation) were extracted via the MiniLM model, and clinical case features were extracted through a fully connected neural network. After fusing the multi-modal information, multi-label therapy prediction was achieved using a linear layer.
RESULTS:
Experimental results on the clinical multi-modal dataset showed that the MMC method performed excellently in terms of subset accuracy(SA), accuracy(Acc), precision, and F1-score, reaching 0.661, 0.856, 0.897, and 0.899 respectively. When the image modality and text modality were removed, the model performance decreased by an average of 8.1% and 2.4% respectively, while the hamming loss(HL) increased by 21.1% and 5.6% respectively.
CONCLUSION
The fracture reduction fixator therapy prediction model constructed in this study can effectively fuse multi-modal data, accurately predict personalized treatment plans for patients, and significantly improve the accuracy and reliability of treatment decisions. It provides a new solution for the digitalization and intellectualization of Traditional Chinese Medicine(TCM) in fracture treatment and has important clinical application prospects.
Humans
;
Female
;
Male
;
Middle Aged
;
Fracture Fixation/methods*
;
Adult
;
Fractures, Bone/surgery*
;
Neural Networks, Computer
;
Medicine, Chinese Traditional
;
Aged
9.Chronic prostatitis/chronic pelvic pain syndrome induces metabolomic changes in expressed prostatic secretions and plasma.
Fang-Xing ZHANG ; Xi CHEN ; De-Cao NIU ; Lang CHENG ; Cai-Sheng HUANG ; Ming LIAO ; Yu XUE ; Xiao-Lei SHI ; Zeng-Nan MO
Asian Journal of Andrology 2025;27(1):101-112
Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a complex disease that is often accompanied by mental health disorders. However, the potential mechanisms underlying the heterogeneous clinical presentation of CP/CPPS remain uncertain. This study analyzed widely targeted metabolomic data of expressed prostatic secretions (EPS) and plasma to reveal the underlying pathological mechanisms of CP/CPPS. A total of 24 CP/CPPS patients from The Second Nanning People's Hospital (Nanning, China), and 35 asymptomatic control individuals from First Affiliated Hospital of Guangxi Medical University (Nanning, China) were enrolled. The indicators related to CP/CPPS and psychiatric symptoms were recorded. Differential analysis, coexpression network analysis, and correlation analysis were performed to identify metabolites that were specifically altered in patients and associated with various phenotypes of CP/CPPS. The crucial links between EPS and plasma were further investigated. The metabolomic data of EPS from CP/CPPS patients were significantly different from those from control individuals. Pathway analysis revealed dysregulation of amino acid metabolism, lipid metabolism, and the citrate cycle in EPS. The tryptophan metabolic pathway was found to be the most significantly altered pathway associated with distinct CP/CPPS phenotypes. Moreover, the dysregulation of tryptophan and tyrosine metabolism and elevation of oxidative stress-related metabolites in plasma were found to effectively elucidate the development of depression in CP/CPPS. Overall, metabolomic alterations in the EPS and plasma of patients were primarily associated with oxidative damage, energy metabolism abnormalities, neurological impairment, and immune dysregulation. These alterations may be associated with chronic pain, voiding symptoms, reduced fertility, and depression in CP/CPPS. This study provides a local-global perspective for understanding the pathological mechanisms of CP/CPPS and offers potential diagnostic and therapeutic targets.
Humans
;
Male
;
Prostatitis/blood*
;
Adult
;
Pelvic Pain/blood*
;
Metabolomics
;
Prostate/metabolism*
;
Middle Aged
;
Chronic Pain/blood*
;
Metabolome
;
Case-Control Studies
;
Tryptophan/blood*
;
Depression/blood*
;
Oxidative Stress/physiology*
;
Chronic Disease
;
Lipid Metabolism/physiology*
10.Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound.
Jia-Ying HU ; Zhen-Zhe LIN ; Li DING ; Zhi-Xing ZHANG ; Wan-Ling HUANG ; Sha-Sha HUANG ; Bin LI ; Xiao-Yan XIE ; Ming-De LU ; Chun-Hua DENG ; Hao-Tian LIN ; Yong GAO ; Zhu WANG
Asian Journal of Andrology 2025;27(2):254-260
Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans
;
Male
;
Azoospermia/diagnostic imaging*
;
Deep Learning
;
Testis/pathology*
;
Retrospective Studies
;
Adult
;
Ultrasonography/methods*
;
Sperm Retrieval
;
Sertoli Cell-Only Syndrome/diagnostic imaging*


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