Objective To investigate the potential mechanism of action of polygonatum odoratum in treating Alzheimer's disease through the utilization of network pharmacology and molecular docking techniques.Methods The methods employed include target screening,Gene Ontology(GO)function and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis,and molecular docking simulations to assess the binding interactions between the active compounds in polygonatum odoratum(POD)and the key target proteins associated with Alzheimer's disease.Subsequently,lipopolysaccharide(LPS)was used to induce an inflammatory cell model in BV2 microglial cells.After treating the cell model with POD extract for 24 hours,the cells were collected,and the expression of the target genes were detected by Real-time PCR.Results Eight active ingredients and 172 targets of POD were screened.The biological processes such as protein phosphorylation and signal transduction,protein binding and ATP binding were obtained by GO functional analysis.KEGG enrichment yielded PI3K/Akt,cAMP and other signaling pathways.The molecular docking result showed that the active ingredient of POD had well binding activity with epidermal growth factor receptor(EGFR),proto-oncogene tyrosine-protein kinase Src(SRC),tumor necrosis factor(TNF),STAT3.Through Real-time PCR experiments,the gene expressions of inducible nitric oxide synthase(iNOS),prostaglandin G/H synthase 2(PTGS2),interleukin(IL)-6,and IL-1β in the LPS-induced inflammatory cell model were significantly upregulated.After treating the inflammatory model with POD extract for 24 hours,the expression of TNF-α was significantly reduced,the expression of STAT3 was upregulated,there were no significant changes in the expressions of SRC and EGFR.Conclusion Network pharmacology suggests polygonatum odoratum's potential anti-Alzheimer's effects may be mediated through its interaction with targets such as EGFR,TNF,SRC,and STAT3.The experimental results suggest that polygonatum odoratum exerts an anti-inflammatory effect by acting on TNF-α,which may further alleviate the symptoms of Alzheimer's disease.

Objective:To analyze the association of apolipoprotein E(ApoE),soluble semaphoring 4D(sSema4D),and cyclophilin A(CypA)levels with unfavorable outcome in patients with chronic heart failure(CHF).Methods:We retrospectively enrolled 108 patients with CHF admitted in the Fifth Affiliated Hospital of Zhengzhou Universi-ty between March 2019 and March 2022.According to the outcome during 6-month follow-up,patients were di-vided into favorable outcome group(n=71)and unfavorable outcome group(n=37).ApoE,sSema4D and CypA levels were compared between the two groups,and multivariate Logistic regression was employed to identify the risk factors of unfavorable outcome within 6-month follow-up in CHF patients.Results:Compared to patients in the favorable outcome group,those in the unfavorable outcome group had significant higher proportion of NYHA classⅣ(59.46％vs.25.35％),serum creatinine[(80.74±3.89)μmol/L vs.(71.36±3.63)μmol/L],ApoE[(69.87±4.25)mg/L vs.(47.36±3.17)mg/L],sSema4D[(916.62±7.32)ng/L vs.(426.42±6.25)ng/L]and CypA[(6.74±1.32)ng/L vs.(4.38±0.72)ng/L](P＜0.001 all).Multivariate Logistic regression indicated that NY-HA class Ⅳ(OR=2.782,95％CI 1.166～6.636),serum creatinine(OR=29.893,95％CI 6.782～131.768),ApoE(OR=12.046,95％CI 4.694～30.913),sSema4D(OR=8.390,95％CI 2.260～31.146)and CypA(OR=6.486,95％CI 1.780～23.635)were independent risk factors for unfavorable outcome within 6-month follow-up in CHF patients(P＜0.05 or＜0.01).Conclusion:The levels of ApoE,sSema4D and CypA were closely associated with short-term unfavorable outcome in patients with chronic heart failure.

Objective:To investigate the clinical efficacy of posterior midline incision combined with anteromedial approach in the treatment of complex olecranon fracture-dislocation.Methods:A retrospective analysis was performed on 26 patients (15 males and 11 females) with olecranon fracture-dislocation who were admitted from January 2020 to January 2024, including 5 cases of anterior transolecranon fracture-dislocation (2 cases of upper ulnar-radial joint dislocation), 21 cases of posterior transolecranon fracture-dislocation (5 cases of them were accompanied by upper ulnar-radial joint dislocation). Among them, there were 13 cases of traffic accidents, 7 cases of falling from heights, and 6 cases of walking falls. The average age is 45.1±15.3 years old (21-84 years old).Results:The operation time was 151.2±41.9 minutes, average tourniquet time was 93.7±22.6 minutes, and the intraoperative blood loss was 76.2±20.2 ml. The average follow-up was 16(12, 23) months, and the VAS score decreased significantly and the MEPS score increased significantly over time. At the last follow-up, the VAS score was 2(1, 2), and the MEPS score was 86.5±10.3, with 16 cases excellent, 7 cases good, and 3 cases medium, with an excellent rate of 89%. The range of motion of flexion-extension and pronation-supination were 119.3°±13.5°and 138.6°±15.2° respectively. Complications included 16 cases of ectopic ossification, of which 4 patients with significant effects on elbow function underwent surgical release 3-6 months after surgery. 1 case of ulnar nerve injury symptoms improved after emergency ulnar nerve release, and 1 case of elbow subluxation due to inaccurate coronoid process reduction and fixation. There were no serious complications such as vascular injury, internal fixation failure, fracture nonunion, and incision infection.Conclusion:The posterior midline incision combined with anteromedial approach can effectively treat complex olecranon fracture-dislocation and meet the requirements of early postoperative elbow rehabilitation.

Objective:To develop and validate a deep learning-based multimodal model integrating clinical and radiomic features for predicting acute kidney injury（AKI）risk after partial nephrectomy.Methods:A retrospective analysis was conducted on 416 patients who underwent partial nephrectomy at Zhongshan Hospital，Fudan University from January 2023 to January 2025. The cohort included 100 AKI patients［defined by a ≥ 25% reduction in postoperative evaluated glomerular filtration rate（eGFR）within 48 hours sustained for >24 hours］and 316 non-AKI patients（1∶3 ratio，randomly matched with 16 additional cases for redundancy）. Clinical and radiomic features were extracted from preoperative contrast-enhanced CT scans using PyRadiomics. Demographics included 259 males and 158 females，with a median age of 57（49，65）years，body mass index of（24.1 ± 3.3）kg/m2，preoperative eGFR of（88.5 ± 18.3）ml/（min·1.73 m2），postoperative eGFR（48-hour）of（76.0 ± 21.9）ml/（min·1.73 m2），Zhongshan Score（ZSscore）of 7.34 ± 2.01，and R.E.N.A.L. score of 7.50 ± 1.71. All tumors were T 1a stage. Patients were divided into training（n = 312）and test（n = 104）sets（3∶1 ratio）. A clinical model was constructed via multivariate logistic regression，while radiomic and combined（clinical + radiomic）models utilized an artificial neural network（ANN）with 1 input layer，5 hidden layers，1 output layer，and 10 5 training epochs. Model performance was evaluated by using receiver operating characteristic（ROC）curves and area under the curve（AUC），and was compared to the Martini model. Feature contributions were interpreted via SHapley Additive exPlanations（SHAP）. Results:In the test set，the results of multivariate logistic regression showed that patient’s weight，preoperative eGFR，R.E.N.A.L. score，surgical approach，and operation time were risk factors for AKI（ P < 0.05）. The AUC of the clinical feature prediction model constructed based on the above factors was 0.852（95% CI 0.775?0.929）. In the test set，the AUC of the Martini model was 0.725（95% CI 0.565?0.791）. The radiomic model，trained on 1 315 imaging features，achieved an AUC of 0.898（95% CI 0.804?0.993）with 94.2%（98/104）accuracy. The combined clinical and radiomic model，integrating 1 315 radiomic features and clinical features，demonstrated superior performance with an AUC of 0.946（95% CI 0.887?1.000）and 96.2%（100/104）accuracy，outperforming both the clinical model（ P = 0.03）and the Martini model（ P < 0.01）. SHAP analysis identified the top five predictors in the combined model：ZSscore（SHAP value：0.78），long-run low gray-level emphasis（SHAP value：0.61），run-length non-uniformity（SHAP value：0.58），size-zone non-uniformity（SHAP value：0.46），and gray-level co-occurrence matrix joint energy（SHAP value：0.36）. Conclusions:The deep learning-based multimodal model integrating clinical and radiomic features accurately predicts AKI risk after partial nephrectomy，offering a novel strategy for preoperative risk stratification and personalized intervention.

Objective:To analyze the role of interleukin-33(IL-33)in the occurrence and development of glioma and its related mechanism by bioinformatics technology,and to validate it through histopathological experiments,and to discuss the possibility of IL-33 as an auxiliary marker for the diagnosis and treatment of brain glioma.Methods:The glioblastoma multiforme/lower grade glioma(GBMLGG)case data were downloaded from the UCSC XENA database,including data of 689 glioma samples,5 paracancerous samples,and 1 152 normal brain tissue samples;Mann-Whitney U test was used to analyze the difference in the expression of IL-33 mRNA between the GBMLGG samples and the normal brain tissues;according to the expression level of IL-33 in GBMLGG tissue,the tumor samples were divided into IL-33 low expression group and IL-33 high expression group;the Human Protein Atlas(HPA)was used to validate the difference in the protein expression of IL-33 in the GBMLGG samples;the R language DESeq2(v.1.36.0)package was used to screen the differentially expressed genes(DEGs)in the GBMLGG tumor case samples;Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis were used to perform pathway analysis on the DEGs;Gene Set Enrichment Analysis(GSEA)was used to discuss the pathways significantly enriched by IL-33 in the GBMLGG tissues;GSVA package was used to analyze the immune infiltration in the GBMLGG samples;survival package and survminer package were used to analyze the effect of IL-33 expression level on the survival of the patients in different clinical subgroups of GBMLGG;univariate and multivariate Cox proportional hazards regression models were used to analyze the relationship between IL-33 expression and the clinicopathological characteristics of the GBMLGG patients;the GBMLGG and control tissue samples were collected;immunohistochemical staining was used to detect the expression levels of IL-33 and its receptor suppression of tumorigenicity 2(ST2)in the GBMLGG and normal brain tissue samples.Results:The expression levels of IL-33 mRNA and protein in the GBMLGG tissues were significantly increased compared with those in normal brain tissues;there were 634 DEGs in total between the IL-33 low and high expression groups,including 283 up-regulated DEGs and 351 down-regulated DEGs;the GO functional enrichment analysis and KEGG signaling pathway enrichment analysis results showed that the DEGs were associated with biological behaviors such as activation of the classical pathway of complement,immunoglobulin complex formation,and mediated immunoglobulin receptor binding;in the course of GBMLGG development,high expression of IL-33 could degrade valine,leucine,and isoleucine,induce limonene and pinene degradation,promote propanoate metabolism,and simultaneously activate the Leishmania infection pathway,NOD-like receptor signaling pathway,and allograft rejection pathway;the infiltration levels of dendritic cell(DC)and mast cell in the IL-33 high expression group were higher than those in IL-33 low expression group;the infiltration levels of eosinophil,helper T cell,and central memory T cell(Tcm)were lower than those in IL-33 low expression group;the expression level of IL-33 was positively correlated with the infiltration of γδT cell(Tgd),helperT cell,macrophage,eosinophil,Tcm,and effector memory T cell(Tem)(P＜0.05);it was negatively correlated with the infiltration levels of DC,natural killer cell(NK),CD8+T cell,and CD56bright NK cell(P＜0.05).There were no significant differences in the overall survival(OS),disease-specific survival(DSS),and disease-free interval(DFI)of the GBMLGG patients between IL-33 high expression group and IL-33 low expression group(P＞0.05);the clinical subgroup analysis results showed that the expression level of IL-33 in oligodendrocytoma tissues was lower than those in astrocytoma and oligoastrocytoma tissues,and the expression level of IL-33 in glioblastoma tissues was higher than that in oligodendroglioma tissues.World Health Organization(WHO)stage and age were risk factors affecting the prognosis of the GBMLGG patients,and IDH mutation and primary treatment effect were protective factors affecting the prognosis;The immunohistochemical staining results showed that compared with normal brain tissues,the expression levels of IL-33 and its receptor ST2 proteins in the malignant glioma tissues were significantly increased(P＜0.05),and their expression levels were positively correlated in both normal brain tissues and malignant glioma tissues(P＜0.05).Conclusion:The expression level of IL-33 in the glioma tissue is significantly increased,and high expression of IL-33 may be a potential factor for poor prognosis in the glioma patients.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract, which increases the incidence of colorectal cancer (CRC). In the pathophysiology of IBD, ubiquitination/deubiquitination plays a critical regulatory function. Josephin domain containing 2 (JOSD2), a deubiquitinating enzyme, controls cell proliferation and carcinogenesis. However, its role in IBD remains unknown. Colitis mice model developed by dextran sodium sulfate (DSS) or colon tissues from individuals with ulcerative colitis and Crohn's disease showed a significant upregulation of JOSD2 expression in the macrophages. JOSD2 deficiency exacerbated the phenotypes of DSS-induced colitis by enhancing colon inflammation. DSS-challenged mice with myeloid-specific JOSD2 deletion developed severe colitis after bone marrow transplantation. Mechanistically, JOSD2 binds to the C-terminal of inosine-5'-monophosphate dehydrogenase 2 (IMPDH2) and preferentially cleaves K63-linked polyubiquitin chains at the K134 site, suppressing IMPDH2 activity and preventing activation of nuclear factor kappa B (NF-κB) and inflammation in macrophages. It was also shown that JOSD2 knockout significantly exacerbated increased azoxymethane (AOM)/DSS-induced CRC, and AAV6-mediated JOSD2 overexpression in macrophages prevented the development of colitis in mice. These outcomes reveal a novel role for JOSD2 in colitis through deubiquitinating IMPDH2, suggesting that targeting JOSD2 is a potential strategy for treating IBD.

Alzheimer's disease (AD) is regarded as a neurodegenerative disease, and it has been proposed that AD may be a systemic disease. Studies have reported associations between non-neurological diseases and AD. The correlations between AD pathology and systemic (non-neurological) pathological changes are intricate, and the mechanisms underlying these correlations and their causality are unclear. In this article, we review the association between AD and disorders of other systems. In addition, we summarize the possible mechanisms associated with AD and disorders of other systems, mainly from the perspective of AD pathology. Regarding the relationship between AD and systemic pathological changes, we aim to provide a new outlook on the early warning signs and treatment of AD, such as establishing a diagnostic and screening system based on more accessible peripheral samples.
Alzheimer Disease/therapy* ; Humans ; Brain/pathology*

OBJECTIVE To observe the effect of acupuncture combined with a modified Zhengan Xifeng Decoction on the early clinical symptoms and oxidative stress status of patients with hypertensive intracerebral hemorrhage(HICH)of liver-kidney yin defi-ciency syndrome.METHODS A total of 60 patients with hypertensive intracerebral hemorrhage(liver-kidney yin deficiency syn-drome)who successfully received 24-hour acute-phase treatment at the Department of Neurosurgery,Acupuncture and Rehabilitation Department,and wards of Kunshan Hospital Affiliated to Nanjing University of Chinese Medicine(Kunshan Traditional Chinese Medi-cine Hospital)from July 2021 to January 2023 were recruited.A randomization table generated by SPSS 22.0 software was used to di-vide the patients into a control group and an observation group,with 30 patients in each group.The control group received symptomatic treatment,conventional rehabilitation training,and modified Zhengan Xifeng Decoction,while the observation group received additional acupuncture treatment on the basis of the control group.The treatment course was 1 month for both groups.Clinical effective rate,TCM syndrome scores,motor and neurological function scores[Activity of Daily Living(ADL)scale,National Institutes of Health Stroke Scale(NIHSS),Modified Ashworth Scale(MAS),Simplified Fugl-Meyer Assessment(FMA)scale],improvement in hematoma lesions,Fraction anisotropy(FA)ratio(rFA),and serum levels of antioxidant stress response factors Kelch-like ECH-associated protein 1(Keap1)and nuclear factor-E2-related factor 2(Nrf2)were observed before and after treatment in both groups.RESULTS After treat-ment,the clinical effective rate in the observation group was significantly higher than that in the control group(P<0.05);the TCM syn-drome scores in both groups decreased significantly(P<0.05),with the observation group showing better results than the control group(P<0.05);the ADL and FMA scores in both groups reduced significantly(P<0.05,P<0.01),while the NIHSS and Ashworth Scale scores increased significantly(P<0.05,P<0.01),with the observation group showing better improvement than the control group(P<0.05);serum Keap1 levels decreased significantly in both groups(P<0.01),while Nrf2 levels enhanced significantly(P<0.05,P<0.01),with the observation group showing better improvement than the control group(P<0.05);imaging studies showed that after treat-ment,the residual hematoma volume decreased significantly in both groups(P<0.05,P<0.01),and the rFA value increased signifi-cantly(P<0.05,P<0.01),with the observation group showing better results than the control group(P<0.01).CONCLUSION On the basis of standard treatment for the acute phase,acupuncture combined with Zhengan Xifeng Decoction can significantly improve the early clinical symptoms of HICH patients with liver-kidney yin deficiency,reduce oxidative stress levels,and promote the recovery of nerve and motor functions.

ObjectiveTo analyze the trend of lung cancer incidence in Fenghua District, Ningbo City of Zhejiang Province from 2009 to 2023, and to estimate the age-period- cohort effects of incidence rate, so as to provide scientific basis for the formulation of lung cancer prevention and control measures in Fenghua District. MethodsJoinpoint software was utilized to analyze the trends and calculate the average annual percentage change (AAPC) of lung cancer incidence based on the tumor incidence surveillance data from Fenghua District, 2009‒2023. The age-period-cohort (APC) model for lung cancer incidence was analyzed using STATA 17.0 software, and net drift and local drift of lung cancer incidence rates were analyzed using online analytical tools. ResultsThe incidence of lung cancer in Fenghua District showed an overall upward trend from 2009 to 2023, with the standardized incidence rate increasing from 45.05/100 000 in 2009 to 108.20/100 000 in 2023(AAPC=7.05%, P<0.05). The increase in the standardized incidence rate for females (AAPC=12.72%, P<0.05) was higher than that for males (AAPC=2.97%, P<0.05). The overall net drift in lung cancer incidence for residents of Fenghua District was 11.71%, with the net drift for females (16.54%) being higher than that for males (6.64%). The local drift in lung cancer incidence among different age groups ranged from -3.37% to 35.18%. The results of APC model showed that the risk of lung cancer incidence increased and then decreased with age, with the highest age effect coefficient observed in the 65‒69 years age group at 1.08. The period effect showed a gradually increasing trend in lung cancer incidence risk with the progression of time, and the period effect coefficient in 2019‒2023 (0.46) was higher than that in 2009‒2013 (-0.39), increasing by 217.95%. The cohort effect coefficient showed a trend of first decreasing and then increasing with the expansion of the birth cohort, in which the lowest cohort effect coefficient was -1.07 observed in the birth cohort of 1964‒1968 and the highest cohort effect coefficient was 1.77 in the birth cohort of 1924‒1928. ConclusionThe incidence of lung cancer in Fenghua District shows an upward trend from 2009 to 2023, with a higher increase in incidence rates among females than that in males. The risk of lung cancer incidence exists a trend of increasing and then decreasing with age growth. With the progression of time, the risk of lung cancer incidence shows a gradually increasing trend. However, with the expansion the birth cohort, the risk of lung cancer incidence demonstrates a trend of first decreasing and then increasing.

Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]