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.

The fibrillization of α-synuclein(α-syn)is a key pathological hallmark of Parkinson's disease.Although biointerfaces play a crucial role in α-syn aggregation,the chiral regulation mechanisms remain insufficiently explored.In this work,chiral carbon dots(CD)were employed to construct nanoscale chiral interfaces,and surface-enhanced infrared absorption spectroscopy combined with nanoscale infrared spectroscopy was utilized to investigate the conformational transition ofα-syn at chiral interfaces.The results demonstrated that α-syn primarily adsorbed onto the chiral interfaces via electrostatic interactions,while spatial selectivity further modulated its conformational evolution.Notably,the D-CD interface exhibited high affinity,stabilizingα-syn in its helical conformation,whereas the L-CD and DL-CD interfaces,due to their weaker affinity,exposed aggregation-prone regions,thereby promotingβ-sheet formation and leading to the generation of oligomers and fibrils.This work elucidated the regulatory role of chiral interfaces inα-syn aggregation,providing theoretical insights for the design of protein aggregation inhibitors.

OBJECTIVE: The present study evaluated the effects of deep acupuncture at Weizhong acupoint (BL40) on bladder function and brain activity in a rat model of overactive bladder (OAB), and investigated the possible mechanisms around the acupuncture area that initiate the effects of acupuncture. METHODS: Adult female Sprague-Dawley rats were randomly divided into six groups, comprising a control group, model group, group treated with deep acupuncture at BL40, group treated with shallow acupuncture at BL40, group treated with acupuncture at non-acupoint next to BL40, and group treated with acupuncture at Xuanzhong (GB39). Urodynamic evaluation was used to observe the urination, and functional magnetic resonance imaging was used to observe the brain activation. The mechanism of acupuncture at BL40 in regulating bladder function was explored by toluidine blue staining and enzyme-linked immunosorbent assay, and the mechanism was verified by stabilizing mast cells (MCs) or blocking tibial nerve. RESULTS: Deep acupuncture at BL40 significantly increased the intercontraction interval in OAB rats and enhanced the mean amplitude of low frequency fluctuation of primary motor cortex (M1), periaquaductal gray matter (PAG), and pontine micturition center (PMC). It also increased the zero-lag functional connectivity between M1 and PAG and between PAG and PMC. Shallow acupuncture at BL40 and acupuncture at non-acupoint or GB39 had no effect on these indexes. Further studies suggested that deep acupuncture at BL40 increased the number and degranulation rate of MCs as well as the contents of 5-hydroxytryptamine, substance P, and histamine in the tissues around BL40. Blocking the tibial nerve by lidocaine injection or inhibiting MC degranulation by sodium cromoglycate injection obstructed the effects of acupuncture on restoring urinary function and modulating brain activation in OAB rats. CONCLUSION Deep acupuncture at BL40 may be more effective for inhibiting OAB by promoting degranulation of MCs around the acupoint and stimulating tibial nerve, thereby regulating the activation of the brain area that controls the lower urinary tract. Please cite this article as: Liu X, Zhang CY, Du XY, Li SS, Wang YQ, Zheng Y, Deng HZ, Fang XQ, Li JY, Wang ZQ, Xu SF, Mi YQ. Acupuncture at Weizhong (BL40) attenuates acetic acid-induced overactive bladder in rats by regulating brain neural activity through the modulation of mast cells and tibial nerves. J Integr Med. 2025; 23(1): 46-55.
Animals ; Urinary Bladder, Overactive/physiopathology* ; Mast Cells/physiology* ; Rats, Sprague-Dawley ; Female ; Acupuncture Therapy ; Acupuncture Points ; Rats ; Brain/physiopathology* ; Tibial Nerve/physiopathology* ; Acetic Acid ; Urinary Bladder/physiopathology*

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

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.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective To investigate the epidemiological and clinical characteristics of 954 cases of central nervous system(CNS)infections in Chongqing.Methods A retrospective analysis was conducted on 954 patients with CNS infectious disease diagnosed and treated in the Second Affiliated Hospital of Army Medical University from 2008 to 2021.The analysis encompassed pathogens,patient gender,age of onset,time of onset,urban-rural distribution,education level,occupational distribution,and other epidemiological characteristics.The clinical manifestations,the positive rate of metagenomic next-generation sequencing(mNGS),and prognosis were also analyzed.Results Among the 945 cases of CNS infectious diseases,the pathogens were viruses in 393(41.2%),Mycobacterium tuberculosis in 361(37.8%),other bacteria in 108(11.3%),Cryptococcus in 75(7.9%),Treponema pallidum in 16(1.7%)and parasites in 1(0.1%).The number of CNS infection cases from 2015 to 2021 increased by 85.6%compared with that from 2008 to 2014(620 vs.334,P<0.001).There was no significant difference in seasonal distribution of pathogens(P>0.05).CNS infectious diseases were more prevalent in rural areas(58.0%,P<0.001),with a male-to-female ratio of 1.7:1.0,and a higher incidence in individuals aged between 35 and 60 years.The majority of patients were educated at Junior high school level or below(68.7%)and were farmers or workers(68.1%).Clinical symptoms of CNS infectious disease mainly included fever,headache,signs of meningeal irritation,nausea and vomiting,which could be accompanied by consciousness disorder and focal neurological deficits.mNGS significantly improves the accuracy of clinical diagnosis.The rate of good prognosis of CNS infectious diseases was 97.5%,while the mortality rate was 0.3%.Conclusions In Chongqing area,the categories and species of CNS infectious pathogens are diverse,widely prevalent,and the clinical manifestations are complex.Moreover,the number of cases has been increasing in recent years.Understanding the epidemiological and clinical characteristics of CNS infectious diseases can help to recognize the regional differences,promote early accurate diagnosis and treatment,and improve prognosis.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Objective To investigate the protective effect and mechanism of acellular nerve allografts(ANA)combined with electroacupuncture on spinal ganglia in rats with sciatic nerve injury(SNI).Methods Totally 50 male adult SD rats were randomly selected for this experiment.Ten rats were prepared for the ANA.Forty male SD rats were randomly divided into normal group,model group,ANA group and combinational group,with 10 rats in each group.The SNI model was established by cutting off the nerves 10 mm at the 5 mm on the inferior border of piriformis after separating the right sciatic nerves.The rats in the ANA group were bridged with ANA to the two broken ends of injured nerves.The rats in the combinational group were treated with electroacupuncture 2 days after ANA bridging,Huantiao(GB30)and Yanglingquan(GB34)were performed as the acupuncture points,each electroacupuncture lasted 15 minutes and 7 days as a course of treatment,4 courses in all.Sciatic nerve conduction velocity was measured by electrophysiology to evaluate the regeneration of damaged axons.Morphology of spinal ganglia was observed by Nissl staining.The expression of nerve growth factor(NGF)and brain-derived neurotrophic factor(BDNF)were detected by Western blotting and immunofluorescent staining.Results Compared with the normal group,the sciatic nerve conduction velocity in model group decreased significantly(P<0.01),Nissl bodies in neurons of spinal ganglia were swollen and dissolved,with incomplete structure and the number decreased dramatically(P<0.01),while the level of NGF and BDNF also decreased significantly(P<0.01).Compared with the model group,the sciatic nerve conduction velocity in ANA and combinational groups strongly increased(P<0.01),the damage of Nissl bodies in neurons of spinal ganglia reduced and the number obviously increased(P<0.01),the level of NGF and BDNF increased considerably(P<0.01).Compared with the ANA group,the sciatic nerve conduction velocity in combinational group increased significantly(P<0.01),the morphology of Nissl bodies in neurons of spinal ganglia were more regular and the number increased(P<0.01),moreover,the level of NGF also increased significantly(P<0.01).Conclusion ANA combined with electroacupuncture can enhance the sciatic nerve conduction velocity,improve the morphology of neurons in spinal ganglia and play a protective effect on spinal ganglia.The mechanism can be related to the higher expression of NGF and BDNF proteins,especially the expression of NGF protein.

italic>Platycodon grandiflorum (Jacq.) A. DC is one of the most commonly used bulk medicinal herbs. It has important value in the fields of medicine, food and cosmetics, and its market demand is increasing year by year, and it has a good development prospect. In this study, based on 403 distribution records and 8 environmental variables, we used Maxent model to predict the potential distribution of P. grandiflorum under climate change. The results showed that the model simulation effect was the best when the Maxent parameter was FC (feature combination) = LQPH (L: linear features; Q: quadratic features; P: product features; H: hinge features) and RM (regularization multiplier) = 2.1, AUC (area under curve) = 0.901, and the model prediction showed that P. grandiflorum was widely distributed in 28 provinces of China under the current climate conditions, with a suitable area of 2 337 419.98 km². Under the influence of climate change in the future, the area of suitable habitat of P. grandiflorum showed a decreasing trend, and the distribution center as a whole showed a trend of northward and eastward shift. The distribution area of P. grandiflorum in the three main producing areas is affected by climate change, and the overall trend is that the future suitable distribution area of Chifeng in Inner Mongolia increases, while the future suitable distribution area of Zibo in Shandong and Taihe, Bozhou in Anhui decreases or even disappears under the SSP5-8.5 scenario (shared socioeconomic pathways). It is suggested to maintain and protect the ecological environment and germplasm resources of the reserved area suitable for the growth of P. grandiflorum, and increase the cultivation research in the expansion area of P. grandiflorum, so as to lay a foundation for the subsequent expansion of P. grandiflorum planting and to promote the protection and sustainable development of P. grandiflorum resources.