[Purpose]To analyze the results of breast cancer screening among women aged 45～74 in Chongqing from 2012 to 2022 and compare the risk of breast cancer among women with differ-ent characteristics.[Methods]The Urban Cancer Early Diagnosis and Treatment Program was con-ducted in Chongqing from 2012 to 2022,female residents aged 45～74 years old participated in breast cancer screening.The participants who were assessed as at high risk of breast cancer in the preliminary screening were advised to receive ultrasonography and mammography examination in designated hospitals.The study population was followed up annually to obtain information on their health outcomes.The high risk rate of breast cancer,compliance of further examination,the inci-dence density and breast cancer risk were calculated.[Results]A total of 207 891 women com-pleted the questionnaires survey and risk assessment,and 35 947 were assessed as the individuals with high risk of breast cancer with a high risk rate of 17.29％.Among them 14 713 received the imaging screening with a compliance rate of 40.93％.After a mean follow-up of(5.43±3.01)years,847 cases of breast cancer were diagnosed with a cumulative incidence rate of 407.43/105,an in-cidence density of 75.03/105 person-years(95％CI:70.15/105～80.26/105 person-years).Cox pro-portional hazards regression showed that the risk of breast cancer was higher in obese women than that in normal weight women(HR=1.26,95％CI:1.00～1.59);the risk of breast cancer was signifi-cantly higher in those with family history of breast cancer than that in those without family history(HR=1.69,95％CI:1.36～2.09).Compared with non-high-risk groups of breast cancer,the risk of breast cancer was increased in high-risk individuals who were screened or not screened(HR=1.36,95％CI:1.06～1.73 and HR=1.26,95％CI:1.01～1.56).[Conclusion]The breast cancer screening program combining primary risk assessment with ultrasonography and mammography for the high-risk groups can improve the detection rate,and the compliance rate of imaging screening need to be improved in the future and make accurate screening for people with high risk of breast cancer.

AIM To establish a rapid quantitative analysis model for saponins in Paris polyphylla var.yunnanensis(PPY)by near infrared spectroscopy.METHODS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ and there total content in PPY were determined by HPLC,while spectral data within the range of 10 000 to 4 000 cm-1 were collected.A quantitative analysis model was established by combining these data with partial least squares regression(PLSR).Multivariate scatter correction(MSC)and vector normalization(SNV)were applied prior to further preprocessing the spectra with original,first-order derivative(1stD),or second-order derivative(2ndD)treatments.Lastly,the model was optimized through non-smoothing(NS),Norris Derivative filtering(Nd),and Savitzky-Golay filtering(S-G)method.Model stability was evaluated based on correlation coefficients and variance.The predicted contents of each saponin component in the validation set samples were calculated.RESULTS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ were 0.42-17.98,0.46-10.44,0.23-3.86 mg/g,respectively.The total content ranged from 2.91 to 22.1 mg/g.The optimal parameters of three saponins were achieved when selecting the MSC+2ndD+S-G pretreatment method.The corresponding ratio of line segment length to segment gap was 13∶5,15∶5,11∶5,with correlation coefficients of 0.982,0.930,0.958,respectively.The root mean square errors of calibration(RMSEC)were 0.702,0.797,0.238,and the root mean square errors of prediction(RMSEP)were 1.120,0.835,0.304,respectively.The optimal parameters for the total content were obtained when selecting the MSC+2ndD+NS pretreatment method,with a correlation coefficient of 0.970,a RMSEC of 1.090,and a RMSEP of 1.740.CONCLUSION This accurate and rapid method can be used for detection of saponin contents in P.Polyphylla.

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

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.

Aim To explore the mechanism of Jiawei Shaofu Zhuyu decoction in antagonizing endometriosis fibrosis by regulating mitophagy.Methods After the animal model was constructed,the syndrome was evalu-ated by general condition,organ water content and ther-mal imaging.The curative effect was evaluated by the weight of ectopic focus and the degree of adhesion.The pathological changes were compared using HE stai-ning,transmission electron microscopy,Masson and Sir-ius red staining.The expression of PINK1 and Parkin was detected by immunohistochemistry.The expression of mRNA and protein was determined by qPCR and Western blot,and the level of serum ROS was detected by ELISA.Results The autonomic activity of model mice was weakened,the water content of organs rose,and the temperature of limbs and lower abdomen was reduced by thermal imaging.HE staining showed obvi-ous hyperplasia of ectopic epithelium and glands.Transmission electron microscopy showed mitochondrial and endoplasmic reticulum structure damage,and nor-mal autophagy structure disappeared.Masson and Siri-us red staining showed increased collagen deposition;immunohistochemistry showed decreased expression of PINK1 and Parkin in ectopic foci.qPCR and Western blot showed that the expression of PINK1,Parkin,Bec-lin1,LC3 mRNA and protein in ectopic foci of model mice decreased,the expression of p62 mRNA and pro-tein increased,and serum ROS increased.The syn-drome performance of model mice was improved after the intervention of Jiawei Shaofu Zhuyu decoction;the inflammatory infiltration of ectopic foci was relieved,the morphology of mitochondria and endoplasmic retic-ulum was restored,and normal autophagy structure ap-peared.The degree of collagen deposition and fibrosis was reduced;the mRNA and protein expression of PINK1,Parkin,Beclin1 and LC3 increased.The ex-pression of p62 mRNA and protein decreased,and the level of ROS decreased.Conclusions Jiawei Shaofu Zhuyu decoction can improve the fibrosis of ectopic le-sions in mice with endometriosis of cold-dampness sta-sis syndrome,which may be related to the regulation of mitophagy.

Objective To construct a three-dimensional bionic model of intestinal mucosal structure in vitro.Methods Using fibroin protein with villous-crypt structure as scaffold and Caco-2 and HT29-MTX-E12 as seed cells,the intestinal mucosal epithelial-myofibroblast co-culture model was constructed by three-dimensional co-culture with myofibroblasts in vitro.The growth,activity,histological characteristics and expression of functional genes of model cells were investigated through the detection of cell signature proteins and genes.Results 1.An intestinal mucosal epithelial-myofibroblast co-culture model was successfully constructed with good cell activity.2.Mucous secretion increased and muc2 gene expression was up-regulated in the co-culture model.Conclusion The co-culture of intestinal mucosal epithelial-myofibroblasts with villous-crypt structure can promote the functional differentiation of intestinal epithelial cells and better simulate the structure and function of intestinal mucosa in vivo.

This study investigated the role of the nuclear factor of activated T cells c3 (NFATc3) in vascular smooth muscle cells (VSMCs) during aortic aneurysm and dissection (AAD) progression and the underlying molecular mechanisms. Cytoplasmic and nuclear NFATc3 levels were elevated in human and mouse AAD. VSMC-NFATc3 deletion reduced thoracic AAD (TAAD) and abdominal aortic aneurysm (AAA) progression in mice, contrary to VSMC-NFATc3 overexpression. VSMC-NFATc3 deletion reduced extracellular matrix (ECM) degradation and maintained the VSMC contractile phenotype. Nuclear NFATc3 targeted and transcriptionally upregulated matrix metalloproteinase 9 (MMP9) and MMP2, promoting ECM degradation and AAD development. NFATc3 promoted VSMC phenotypic switching by binding to eukaryotic elongation factor 2 (eEF2) and inhibiting its phosphorylation in the VSMC cytoplasm. Restoring eEF2 reversed the beneficial effects in VSMC-specific NFATc3-knockout mice. Cabamiquine-targets eEF2 and inhibits protein synthesis-inhibited AAD development and progression in VSMC-NFATc3-overexpressing mice. VSMC-NFATc3 promoted VSMC switch and ECM degradation while exacerbating AAD development, making it a novel potential therapeutic target for preventing and treating AAD.

OBJECTIVE: Comorbid pain and depression are common but remain difficult to treat. Electroacupuncture (EA) can effectively improve symptoms of depression and relieve pain, but its neural mechanism remains unclear. Therefore, we used resting-state functional magnetic resonance imaging (rs-fMRI) to detect cerebral changes after initiating a mouse pain model via constriction of the infraorbital nerve (CION) and then treating these animals with EA. METHODS: Forty male C57BL/6J mice were divided into 4 groups: control, CION model, EA, and sham acupuncture (without needle insertion). EA was performed on the acupoints Baihui (GV20) and Zusanli (ST36) for 20 min, once a day for 10 consecutive days. The mechanical withdrawal threshold was tested 3 days after the surgery and every 3 days after the intervention. The depressive behavior was evaluated with the tail suspension test, open-field test, elevated plus maze (EPM), sucrose preference test, and marble burying test. The rs-fMRI was used to detect the cerebral changes of the functional connectivity (FC) in the mice following EA treatment. RESULTS: Compared with the CION group, the mechanical withdrawal threshold increased in the EA group at the end of the intervention (P < 0.05); the immobility time in tail suspension test decreased (P < 0.05); and the times of the open arm entry and the open arm time in the EPM increased (both P < 0.001). There was no difference in the sucrose preference or marble burying tests (both P > 0.05). The fMRI results showed that EA treatment downregulated the amplitude of low-frequency fluctuations and regional homogeneity values, while these indicators were elevated in brain regions including the amygdala, hippocampus and cerebral cortex in the CION model for comorbid pain and depression. Selecting the amygdala as the seed region, we found that the FC was higher in the CION group than in the control group. Meanwhile, EA treatment was able to decrease the FC between the amygdala and other brain regions including the caudate putamen, thalamus, and parts of the cerebral cortex. CONCLUSION EA can downregulate the abnormal activation of neurons in the amygdala and improve its FC with other brain regions, thus exerting analgesic and antidepressant effects. Please cite this article as: Yin X, Zeng XL, Lin JJ, Xu WQ, Cui KY, Guo XT, Li W, Xu SF. Brain functional changes following electroacupuncture in a mouse model of comorbid pain and depression: a resting-state functional magnetic resonance imaging study. J Integr Med. 2025; 23(2): 159-168.
Animals ; Electroacupuncture ; Male ; Magnetic Resonance Imaging ; Depression/diagnostic imaging* ; Mice, Inbred C57BL ; Brain/diagnostic imaging* ; Disease Models, Animal ; Mice ; Pain/diagnostic imaging* ; Acupuncture Points

OBJECTIVE: This study explored the job choice preferences of Center for Disease Prevention and Control (CDC) workers to provide CDC management information and recommendations for optimizing employee retention and motivation policies. METHODS: A discrete choice experiment was conducted in nine provinces across China. Seven key attributes were identified to analyze the job preferences of CDC workers. Mixed logit models, latent class models, and policy simulation tools were used. RESULTS: A valid sample of 5,944 cases was included in the analysis. All seven attributes significantly influenced the job choices of CDC workers. Heterogeneity analyses identified two main groups based on different levels of preference for attribute utility. Income-prioritizers were concerned with income and opportunities for career development, whereas bianzhi-prioritizers were concerned with bianzhi and welfare benefits. The policy simulation analysis revealed that income-prioritizers had a relatively higher sensitivity to multiple job preference incentives. CONCLUSION Income and bianzhi were the two key attributes influencing the job choices and retention preferences of CDC workers. Heterogeneity in job preferences was also identified. Based on the preference characteristics of different subgroups, policy content should be skewed to differentiate the importance of incentives.
China ; Humans ; Male ; Female ; Adult ; Centers for Disease Control and Prevention, U.S. ; Middle Aged ; Choice Behavior ; Career Choice ; Motivation