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Automatic detection of small bowel lesions with different bleeding risks based on deep learning models

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World Journal of Gastroenterology 2024年第2期30卷 170-183页

作者： Rui-Ya Zhang Peng-Peng Qiang Ling-Jun Cai Tao Li yan qin Yu Zhang Yi-qing Zhao Jun-Ping Wang Department of Gastroenterology The Fifth Clinical Medical College of Shanxi Medical UniversityTaiyuan 030012Shanxi ProvinceChina School of Computer and Information Technology Shanxi UniversityTaiyuan 030006Shanxi ProvinceChina School of Life Sciences and Technology Mudanjiang Normal UniversityMudanjiang 157011Heilongjiang ProvinceChina

BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some unresolved challenges.AIM To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups.METHODS The proposed model represents a two-stage method that combined image classification with object detection.First,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid images.Then,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was marked.We constructed training and testing sets and compared model-assisted reading with physician reading.RESULTS The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single module.The sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’diagnoses.The image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.

关键词： Artificial intelligence Deep learning Capsule endoscopy Image classification Object detection Bleeding risk

Treatment of 198 Cases of Thyroid Nodules with Sanying Capsule Combined with Xiaoying Patch

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Medicinal Plant 2024年第3期15卷 56-59页

作者： Shujing SHI Mingyue yanG Yue HAO Haihui ZHU yan qin Shaanxi University of Chinese Medicine Xianyang 712046China Shaanxi Provincial Hospital of Chinese Medicine Xi an 710003China People s Hospital of Heyang County Heyang 715300China

[Objectives]To observe the clinical efficacy of Sanying capsule combined with Xiaoying Patch in treating thyroid nodule(TN).[Methods]Two groups were treated similarly,with 200 cases in the control group undergoing basic treatment for 12 weeks and 198 cases in the observation group receiving Sanying capsule combined with Xiaoying patches for the same duration.The clinical symptoms,number of nodules,diameter of the largest nodule,and maximum reduction of nodules were observed before and after treatment.A control analysis was performed,and the underlying mechanisms were explored.[Results]The primary symptoms of the observation group exhibited a more favorable improvement than those of the control group.Additionally,the number of nodules decreased,the diameter of the largest nodule decreased,and the maximum reduction of nodules decreased in both groups following treatment.However,the observation group demonstrated a more pronounced improvement than the control group(P<0.05).[Conclusions]The combination of Sanying capsule and Xiaoying patch has been demonstrated to be an effective treatment for TN,with a high degree of reliability in terms of safety.

关键词： Thyroid nodule Sanying Capsule Xiaoying Patch Clinical efficacy

The Multiple Roles of Autophagy in Neural Function and Diseases

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Neuroscience Bulletin 2024年第3期40卷 363-382页

作者： yan-yan Li Zheng-Hong qin Rui Sheng Department of Pharmacology and Laboratory of Aging and Nervous Diseases Jiangsu Key laboratory of Neuropsychiatric DiseasesCollege of Pharmaceutical Sciences of Soochow UniversitySuzhou 215123China

Autophagy involves the sequestration and delivery of cytoplasmic materials to lysosomes,where proteins,lipids,and organelles are degraded and recycled.According to the way the cytoplasmic components are engulfed,autophagy can be divided into macroautophagy,microautophagy,and chaperone-mediated autophagy.Recently,many studies have found that autophagy plays an important role in neurological diseases,including Alzheimer's disease,Parkinson's disease,Huntington's disease,neuronal excitotoxicity,and cerebral ischemia.Autophagy maintains cell homeostasis in the nervous system via degradation of misfolded proteins,elimination of damaged organelles,and regulation of apoptosis and inflammation.AMPK-mTOR,Beclin 1,TP53,endoplasmic reticulum stress,and other signal pathways are involved in the regulation of autophagy and can be used as potential therapeutic targets for neurological diseases.Here,we discuss the role,functions,and signal pathways of autophagy in neurological diseases,which will shed light on the pathogenic mechanisms of neurological diseases and suggest novel targets for therapies.

关键词： Autophagy Neurodegenerative diseases Cerebral ischemia AMPK mTOR Beclin 1 TP53 Endoplasmic reticulum stress

Kinetic model of vibration screening for granular materials based on biological neural network

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Particuology 2024年第5期88卷 98-106页

作者： Zhan Zhao yan Zhang Fang qin Mingzhi Jin School of Agricultural Engineering Jiangsu UniversityZhenjiang212013China Shandong Academy of Agricultural Machinery Sciences Ji'nan250100China

The kinetic model is the theoretical basis for optimizing the structure and operation performance of vibration screening devices.In this paper,a biological neurodynamic equation and neural connections were established according to the motion and interaction properties of the material under vibration excitation.The material feeding to the screen and the material passing through apertures were considered as excitatory and inhibitory inputs,respectively,and the generated stable neural activity landscape was used to describe the material distribution on the 2D screen surface.The dynamic process of material vibration screening was simulated using discrete element method(DEM).By comparing the similarity between the material distribution established using biological neural network(BNN)and that obtained using DEM simulation,the optimum coefficients of BNN model under a certain screening parameter were determined,that is,one relationship between the BNN model coefficients and the screening operation parameters was established.Different screening parameters were randomly selected,and the corresponding relationships were established as a database.Then,with straw/grain ratio,aperture diameter,inclination angle,vibration strength in normal and tangential directions as inputs,five independent adaptive neuro-fuzzy inference systems(ANFIS)were established to predict the optimum BNN model coefficients,respectively.The training results indicated that ANFIS models had good stability and accuracy.The flexibility and adaptability of the proposed BNN method was demonstrated by modeling material distribution under complex feeding conditions such as multiple regions and non-uniform rate.

关键词： Kinetic model Material distribution Vibration screening Biological neural network DEM simulation Adaptive neuro-fuzzy inference systems

Control of chiral-optical activities by magnetic field based on the transformation of achiral binary crystals into chiral ternary crystals

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Science China Chemistry 2024年第7期67卷 2300-2305页

作者： Zhiyan Chen yan Lv Wei qin College of Physics Qingdao UniversityQingdao 266071China School of Physics State Key Laboratory of Crystal MaterialsShandong UniversityJinan 250100China Shandong Linuo Photovoltaic Hi-Tech Co. Ltd.Jinan 250100China

Multicomponent self-assembled chiral systems have attracted great attention due to their promising application in the area of spin-photonics and optoelectronics.In this work,through introducing an achiral third component into an achiral binary crystal,a chiral organic ternary crystal is fabricated,where both pronounced chiral-optical coupling and magnetic field dependence of chiral-optical activities are observed.The transformation of achiral structure into chiral structure generates a significant effect on the polarized state of light and the electron spin resonance signals.Moreover,the coupling between circularly polarized photon and spin is observed in chiral ternary crystal with pronounced chiral orbit,where obvious magnetic field-transmissivity loop is generated.Furthermore,temperature could increase the magnitude of lattice parameters to lead to a larger helix radius to increase the chiral orbit effect.Overall,this work indicates that the further exploration of photon-chiral orbit-spin interactions in organic chiral ternary crystals is promising.

关键词： organic chiral ternary crystals chiral orbit chiral-optical activities magnetic field

Empirical likelihood for spatial cross-sectional data models with matrix exponential spatial specification

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Applied Mathematics(A Journal of Chinese Universities) 2024年第1期39卷 125-139页

作者： LIU yan RONG Jian-rong qin Yong-song Nanning University Nanning 530200China Center for Applied Mathematics of Guangxi and College of Mathematics and Statistics Guangxi Normal UniversityGuilin 541004China

In this paper,we study spatial cross-sectional data models in the form of matrix exponential spatial specification(MESS),where MESS appears in both dependent and error terms.The empirical likelihood(EL)ratio statistics are established for the parameters of the MESS model.It is shown that the limiting distributions of EL ratio statistics follow chi-square distributions,which are used to construct the confidence regions of model parameters.Simulation experiments are conducted to compare the performances of confidence regions based on EL method and normal approximation method.

关键词： MESS empirical likelihood con dence region

Systematic investigation of Radix Salviae for treating diabetic peripheral neuropathy disease based on network Pharmacology

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World Journal of Diabetes 2024年第5期15卷 945-957页

作者： Tao Kang Xiao qin yan Chen Qian yang Department of Neurology Shaanxi Provincial People’s HospitalXi'an 710068Shaanxi ProvinceChina

BACKGROUND Diabetic peripheral neuropathy(DPN)is a debilitating complication of diabetes mellitus with limited available treatment options.Radix Salviae,a traditional Chinese herb,has shown promise in treating DPN,but its therapeutic mech-anisms have not been systematically investigated.AIM Radix Salviae(Danshen in pinin),a traditional Chinese medicine(TCM),is widely used to treat DPN in China.However,the mechanism through which Radix Salviae treats DPN remains unclear.Therefore,we aimed to explore the mechanism of action of Radix Salviae against DPN using network pharmacology.METHODS The active ingredients and target genes of Radix Salviae were screened using the TCM pharmacology database and analysis platform.The genes associated with DPN were obtained from the Gene Cards and OMIM databases,a drug-com-position-target-disease network was constructed,and a protein–protein inter-action network was subsequently constructed to screen the main targets.Gene Ontology(GO)functional annotation and pathway enrichment analysis were performed via the Kyoto Encyclopedia of Genes and Genomes(KEGG)using Bioconductor.RESULTS A total of 56 effective components,108 targets and 4581 DPN-related target genes of Radix Salviae were screened.Intervention with Radix Salviae for DPN mainly involved 81 target genes.The top 30 major targets were selected for enrichment analysis of GO and KEGG pathways.CONCLUSION These results suggested that Radix Salviae could treat DPN by regulating the AGE-RAGE signaling pathway and the PI3K-Akt signaling pathway.Therefore,Danshen may affect DPN by regulating inflammation and apoptosis.

关键词： Diabetic peripheral neuropathy Radix Salviae Network pharmacology Systematic investigation

Who could and should give exercise prescription:Physicians,exercise and health scientists,fitness trainers,or ChatGPT?

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Journal of Sport and Health Science 2024年第3期13卷 368-372页

作者： Weimo Zhu Wenguang Geng Lingling Huang Xiong qin Zezhao Chen Hai yan Yunnan Plateau Thermal Health Industry Innovation Research Institute Tengchong 679100China Department of Kinesiology&Community Health University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Physical Education Nanjing Agricultural UniversityNanjing 210095China School of Sports Engineering Beijing Sport UniversityBeijing 100084China School of Strength and Conditioning Training Beijing Sport UniversityBeijing 100084China

Benefits of exercise for personal health,as well as preventing and treating chronic diseases,have been well documented during the past several decades.1 Exercise prescription is a specialized field that involves assessing an individual’s health status,fitness level,and specific goals to create a tailored exercise program based often on the FITT-VP principle.

关键词： prescription diseases assessing

Dietary fiber intake and its association with diabetic kidney disease in American adults with diabetes:A cross-sectional study

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World Journal of Diabetes 2024年第3期15卷 475-487页

作者： Xin-Hua Jia Sheng-yan Wang Ai-qin Sun Department of Critical Care Medicine Dezhou People’s HospitalDezhou 253000Shandong ProvinceChina Emergency Intensive Care Unit Dezhou People’s HospitalDezhou 253000Shandong ProvinceChina

BACKGROUND Dietary fiber(DF)intake may have a protective effect against type 2 diabetes(T2D);however,its relationship with diabetic kidney disease(DKD)remains unclear.AIM To investigate the potential association between DF intake and the prevalence of DKD in individuals diagnosed with T2D.METHODS This cross-sectional study used data from the National Health and Nutrition Examination Survey collected between 2005 and 2018.DF intake was assessed through 24-h dietary recall interviews,and DKD diagnosis in individuals with T2D was based on predefined criteria,including albuminuria,impaired glomerular filtration rate,or a combination of both.Logistic regression analysis was used to assess the association between DF intake and DKD,and comprehensive subgroup and sensitivity analyses were performed.RESULTS Among the 6032 participants,38.4%had DKD.With lower DF intake-T1(≤6.4 g/1000 kcal/day)-as a reference,the adjusted odds ratio for DF and DKD for levels T2(6.5-10.0 g/1000 kcal/day)and T3(≥10.1 g/1000 kcal/day)were 0.97(95%CI:0.84-1.12,P=0.674)and 0.79(95%CI:0.68-0.92,P=0.002),respectively.The subgroup analysis yielded consistent results across various demographic and health-related subgroups,with no statistically significant interactions(all P>0.05).CONCLUSION In United States adults with T2D,increased DF intake may be related to reduced DKD incidence.Further research is required to confirm these findings.

关键词： Dietary fiber Diabetic kidney disease Type 2 diabetes National Health and Nutrition Examination Survey Crosssectional study