OBJECTIVE:It has been confirmed that neuromodulation technology can improve the clinical symptoms of patients with Parkinson's disease,and there are differences in the efficacy of different neuromodulation stimulation methods.Herein,a network meta-analysis was used to evaluate the efficacy of different neuromodulation stimulation modalities in improving non-motor symptoms such as sleep disorders and depression and anxiety in patients with Parkinson's disease,thereby exploring the optimal neuromodulation stimulation regimen.METHODS:The Chinese Biomedical Literature Database,WanFang Database,VIP Database,CNKI Database,Web of Science,PubMed,The Cochrane Library,and EMbase databases were searched for randomized controlled trials on neuromodulation techniques to improve sleep disorders,depression and anxiety in patients with Parkinson's disease.The control group was treated with conventional treatments(drugs,conventional rehabilitation therapy,etc.)or sham stimulation,and the experimental group was supplemented with neuromodulation technology on the basis of the control group.The quality of the included studies was evaluated using the PEDro scale and the deviation risk assessment tool recommended by the Cochrane Collaboration.RevMan 5.4 and Stata 17.0 were used for network meta-analysis of the four outcomes(sleep disorders,anxiety symptoms,depressive symptoms,and quality of life).RESULTS:(1)Twenty-nine randomized controlled trials involving six neuromodulation stimulation modalities were included.These modalities were transcranial direct current stimulation,high-frequency repetitive transcranial magnetic stimulation,low-frequency repetitive transcranial magnetic stimulation,deep brain stimulation of the subthalamic nucleus,deep brain stimulation of the globus pallidus,multi-target deep brain stimulation.(2)The results of network meta-analysis showed that compared with conventional treatment,transcranial direct current stimulation[standardized mean difference(SMD)=-2.57,95％confidence interval(CI)=-4.52 to-0.63,P＜0.05)had the best effect in improving sleep disorders in patients with Parkinson's disease.In terms of improving depressive symptoms,deep brain stimulation of the globus pallidus(SMD=-1.00,95％CI=-1.87 to-0.14,P＜0.05)had the best effect,followed by low-frequency repetitive transcranial magnetic stimulation(SMD=-0.91,95％CI=-1.60 to-0.23,P＜0.05),deep brain stimulation of the subthalamic nucleus(SMD=-0.82,95％CI=-1.56 to-0.08,P＜0.05),and high-frequency repetitive transcranial magnetic stimulation(SMD=-0.75,95％CI=-0.97 to-0.53,P＜0.05).In terms of improving anxiety symptoms,high-frequency repetitive transcranial magnetic stimulation(SMD=-0.86,95％CI=-1.54 to-0.18,P＜0.05)had the best effect.In terms of improving the quality of life,deep brain stimulation of the globus pallidus(SMD=-0.79,95％CI=-1.55 to-0.04,P＜0.05)had the best efficacy,followed by high-frequency repetitive transcranial magnetic stimulation(SMD=-0.63,95％CI=-0.90 to-0.36,P＜0.05)and transcranial direct current stimulation(SMD=-0.50,95％CI=-0.80 to-0.19,P＜0.05).CONCLUSION:Neuromodulation technology has significant efficacy in improving non-motor symptoms in patients with Parkinson's disease.Transcranial direct current stimulation has the best efficacy in improving sleep disorders,deep electrical stimulation of the medial cerebral part of the globus pallidus has the best efficacy in improving depressive symptoms,high-frequency repetitive transcranial magnetic stimulation has the best efficacy in improving anxiety symptoms,and deep electrical stimulation of the globus pallidus has the best efficacy in improving quality of life.

OBJECTIVE:It has been confirmed that neuromodulation technology can improve the clinical symptoms of patients with Parkinson's disease,and there are differences in the efficacy of different neuromodulation stimulation methods.Herein,a network meta-analysis was used to evaluate the efficacy of different neuromodulation stimulation modalities in improving non-motor symptoms such as sleep disorders and depression and anxiety in patients with Parkinson's disease,thereby exploring the optimal neuromodulation stimulation regimen.METHODS:The Chinese Biomedical Literature Database,WanFang Database,VIP Database,CNKI Database,Web of Science,PubMed,The Cochrane Library,and EMbase databases were searched for randomized controlled trials on neuromodulation techniques to improve sleep disorders,depression and anxiety in patients with Parkinson's disease.The control group was treated with conventional treatments(drugs,conventional rehabilitation therapy,etc.)or sham stimulation,and the experimental group was supplemented with neuromodulation technology on the basis of the control group.The quality of the included studies was evaluated using the PEDro scale and the deviation risk assessment tool recommended by the Cochrane Collaboration.RevMan 5.4 and Stata 17.0 were used for network meta-analysis of the four outcomes(sleep disorders,anxiety symptoms,depressive symptoms,and quality of life).RESULTS:(1)Twenty-nine randomized controlled trials involving six neuromodulation stimulation modalities were included.These modalities were transcranial direct current stimulation,high-frequency repetitive transcranial magnetic stimulation,low-frequency repetitive transcranial magnetic stimulation,deep brain stimulation of the subthalamic nucleus,deep brain stimulation of the globus pallidus,multi-target deep brain stimulation.(2)The results of network meta-analysis showed that compared with conventional treatment,transcranial direct current stimulation[standardized mean difference(SMD)=-2.57,95％confidence interval(CI)=-4.52 to-0.63,P＜0.05)had the best effect in improving sleep disorders in patients with Parkinson's disease.In terms of improving depressive symptoms,deep brain stimulation of the globus pallidus(SMD=-1.00,95％CI=-1.87 to-0.14,P＜0.05)had the best effect,followed by low-frequency repetitive transcranial magnetic stimulation(SMD=-0.91,95％CI=-1.60 to-0.23,P＜0.05),deep brain stimulation of the subthalamic nucleus(SMD=-0.82,95％CI=-1.56 to-0.08,P＜0.05),and high-frequency repetitive transcranial magnetic stimulation(SMD=-0.75,95％CI=-0.97 to-0.53,P＜0.05).In terms of improving anxiety symptoms,high-frequency repetitive transcranial magnetic stimulation(SMD=-0.86,95％CI=-1.54 to-0.18,P＜0.05)had the best effect.In terms of improving the quality of life,deep brain stimulation of the globus pallidus(SMD=-0.79,95％CI=-1.55 to-0.04,P＜0.05)had the best efficacy,followed by high-frequency repetitive transcranial magnetic stimulation(SMD=-0.63,95％CI=-0.90 to-0.36,P＜0.05)and transcranial direct current stimulation(SMD=-0.50,95％CI=-0.80 to-0.19,P＜0.05).CONCLUSION:Neuromodulation technology has significant efficacy in improving non-motor symptoms in patients with Parkinson's disease.Transcranial direct current stimulation has the best efficacy in improving sleep disorders,deep electrical stimulation of the medial cerebral part of the globus pallidus has the best efficacy in improving depressive symptoms,high-frequency repetitive transcranial magnetic stimulation has the best efficacy in improving anxiety symptoms,and deep electrical stimulation of the globus pallidus has the best efficacy in improving quality of life.

Objective:To develop a deep learning-based automated analysis system for precise segmentation of the optic cup and disc in fundus images and automatic measurement of the vertical cup-to-disc ratio (CDR) for early risk assessment and screening of chronic glaucoma.Methods:The proposed automated system comprised three modules: a dual coding-attention U-net (DCoAtUNet) segmentation network for optic cup and disc segmentation, a conditional random field (CRF) post-processing module, and a CDR measurement and glaucoma screening module based on the segmentation results.The system was designed to enhance boundary detection accuracy and measurement stability and its performance was evaluated on the publicly available Drishti-GS dataset.The dataset was divided into a training set and a test set in a 1∶1 ratio.Dice coefficient and intersection over union (IoU) were used to quantify segmentation accuracy and regional consistency, while accaracy, precision, recall, and F1-score were employed to assess glaucoma screening performance.Results:The DCoAtUNet combined with CRF post-processing achieved Dice coefficients of 0.976 0 for the optic disc and 0.908 1 for the optic cup, with corresponding IoU values of 0.953 4 and 0.837 9, demonstrating high segmentation precision and stability in boundary identification and region overlap.In glaucoma screening, the system achieved an accuracy of 0.843 1, precision of 0.840 9, recall of 0.973 7, and F1-score of 0.902 4, indicating good diagnostic sensitivity and accuracy.Conclusions:By integrating high-precision segmentation and automated measurement strategies, the DCoAtUNet+ CRF model significantly improves the accuracy and stability of CDR evaluation.It effectively assists in identifying high-risk individuals during early glaucoma screening and shows strong potential for clinical application in computer-aided diagnosis workflows.

Objective:To investigate the effects of a visual feedback electromyography-driven exoskeleton on patients with hand injuries and to compare its efficacy with conventional rehabilitation treatment.Method:Patients who met the inclusion and exclusion criteria were randomly divided into two groups,with 15 patients in the experimental group and 15 in the control group.The control group underwent a 4-week con-ventional rehabilitation program,which included occupational therapy,muscle strength training,and range of motion exercises.The experimental group received the same conventional rehabilitation alongside training with the visual feedback electro-myography-driven exoskeleton.All participants were evaluated for grip strength,pinch strength,Purdue Pegboard results,and DASH questionnaire scores before and after treatment.Statistical analyses were performed to compare intra-group and inter-group differences.Result:After 4 weeks of rehabilitation,both groups showed significant differences in grip strength,pinch strength,Purdue Pegboard scores,and DASH questionnaire scores compared to baseline(P＜0.05).Between-group comparisons showed no significant difference in the post-treatment grip weight ratio(P＞0.05),while all other indicators demonstrated significant differences(P＜0.05).Conclusion:Following 4 weeks of rehabilitation,both groups showed improvements in muscle strength,hand dex-terity,and activities of daily living in the upper limbs.However,the functional level of patients in the experimen-tal group was superior to that of the control group,indicating that task-oriented rehabilitation using a visual feed-back electromyography-driven exoskeleton significantly promotes functional recovery in patients with hand trauma.

BACKGROUND:Peripheral nerve injuries can cause severe functional disabilities in patients,and long-segment nerve defects often fail to regenerate spontaneously.In recent years,tissue engineering techniques have gradually been applied to the repair of long-segment nerve injuries,yet research hotspots and development trends are unclear.OBJECTIVE:To analyze the research hotspots and trends in the field of peripheral nerve tissue engineering over the past 20 years using bibliometric software.METHODS:CiteSpace 6.2R6 software was employed to conduct highly cited analysis and keyword analysis on peripheral nerve tissue engineering literature published from 2004 to 2024 in the Web of Science and China National Knowledge Infrastructure(CNKI)databases.The keyword analysis encompasses keyword co-occurrence analysis,keyword clustering analysis,keyword timeline analysis,and keyword emergence analysis.RESULTS AND CONCLUSION:A total of 2 961 articles from the Web of Science database and 1171 articles from the CNKI database were included.The number of publications in the Web of Science database showed fluctuations but exhibited an overall increasing trend year by year,while the publication volume in the CNKI database remained relatively stable annually.Most of the top ten most cited articles in the Web of Science database were review articles.The results of the keyword analysis from Web of Science and CNKI databases indicated that the most studied nerve tissue engineering materials over the past 20 years include silk fibroin,collagen,chitosan,polycaprolactone,polylactic acid,and graphene.The biochemical cues investigated in these materials include olfactory ensheathing cells,Schwann cells,stem cells,and nerve growth factors.The most commonly employed external physical factor is electrical stimulation applied to the materials.Among various tissue engineering techniques,electrospinning technology and 3D printing technology have been the most extensively researched.

BACKGROUND:Cervical disc degeneration is a common degenerative disease,and inflammatory proteins play an important role in cervical disc degeneration,but the specific mechanisms involved remain to be thoroughly investigated.OBJECTIVE:Using the Mendelian randomization method to assess the potential causal relationship between 91 inflammatory proteins and cervical disc degeneration.METHODS:Genome-wide association analysis statistics for 91 inflammatory proteins(from GCST90274758 to GCST90274848)were obtained from the Genome-Wide Association Analysis Catalog of publicly available genome-wide association analysis data and genome-wide association analysis data for cervical disc degeneration from the Finngen database(finngen_R10_M13_CERVICDISCV).Inverse variance weighting,MR-Egger regression,weighted median,weighted modeling,and simple modeling were used to investigate the causal relationship between inflammatory proteins and cervical disc degeneration.Sensitivity analyses were performed to test whether the results of the Mendelian randomization analysis were reliable,and then the inverse Mendelian randomization analysis was performed in the same way.RESULTS AND CONCLUSION:The results of the forward analysis showed that a total of six inflammatory proteins were significantly and causally associated with cervical disc degeneration,of which glial cell lineage-derived neurotrophic factor(odds ratio(OR)=1.095,95%confidence interval(CI):1.012-1.184,P=0.023),interleukin 4(OR=1.094,95%CI:1.002-1.194,P=0.045)and monocyte chemotactic protein-1 levels(OR=1.062,95%CI:1.001-1.127,P=0.048)showed a direct positive causal association with the risk of cervical disc degeneration;interleukin 17C(OR=0.906,95%CI:0.839-0.979,P=0.013),interleukin 18(OR=0.924,95%CI:0.866-0.986,P=0.017)and interleukin 2 levels(OR=0.894,95%CI:0.821-0.973,P=0.010)showed a direct negative causal association with the risk of cervical disc degeneration.The results of the inverse analysis showed that when cervical disc degeneration was used as exposure data,there was no significant causal relationship with any of the 91 inflammatory proteins.The results of the sensitivity analysis showed that the Cochran's Q test for the two-way Mendelian randomization,the MR-Egger regression method,and the MR-PRESSO results had P values greater than 0.05,indicating that there was no significant heterogeneity or multiplicity in the analysis of the causal effect between inflammatory proteins and cervical disc degeneration.To conclude,there may be a relatively significant potential causal relationship between glial cell line-derived neurotrophic factor,interleukin 4,monocyte chemotactic protein-1,interleukin 17C levels,interleukin 18,and interleukin 2 levels and cervical disc degeneration,which provides valuable clues for research on the potential mechanisms of cervical disc degeneration as well as early prevention and drug treatment of cervical disc degeneration.

Objective:To develop a deep learning-based automated analysis system for precise segmentation of the optic cup and disc in fundus images and automatic measurement of the vertical cup-to-disc ratio (CDR) for early risk assessment and screening of chronic glaucoma.Methods:The proposed automated system comprised three modules: a dual coding-attention U-net (DCoAtUNet) segmentation network for optic cup and disc segmentation, a conditional random field (CRF) post-processing module, and a CDR measurement and glaucoma screening module based on the segmentation results.The system was designed to enhance boundary detection accuracy and measurement stability and its performance was evaluated on the publicly available Drishti-GS dataset.The dataset was divided into a training set and a test set in a 1∶1 ratio.Dice coefficient and intersection over union (IoU) were used to quantify segmentation accuracy and regional consistency, while accaracy, precision, recall, and F1-score were employed to assess glaucoma screening performance.Results:The DCoAtUNet combined with CRF post-processing achieved Dice coefficients of 0.976 0 for the optic disc and 0.908 1 for the optic cup, with corresponding IoU values of 0.953 4 and 0.837 9, demonstrating high segmentation precision and stability in boundary identification and region overlap.In glaucoma screening, the system achieved an accuracy of 0.843 1, precision of 0.840 9, recall of 0.973 7, and F1-score of 0.902 4, indicating good diagnostic sensitivity and accuracy.Conclusions:By integrating high-precision segmentation and automated measurement strategies, the DCoAtUNet+ CRF model significantly improves the accuracy and stability of CDR evaluation.It effectively assists in identifying high-risk individuals during early glaucoma screening and shows strong potential for clinical application in computer-aided diagnosis workflows.

BACKGROUND:Peripheral nerve injuries can cause severe functional disabilities in patients,and long-segment nerve defects often fail to regenerate spontaneously.In recent years,tissue engineering techniques have gradually been applied to the repair of long-segment nerve injuries,yet research hotspots and development trends are unclear.OBJECTIVE:To analyze the research hotspots and trends in the field of peripheral nerve tissue engineering over the past 20 years using bibliometric software.METHODS:CiteSpace 6.2R6 software was employed to conduct highly cited analysis and keyword analysis on peripheral nerve tissue engineering literature published from 2004 to 2024 in the Web of Science and China National Knowledge Infrastructure(CNKI)databases.The keyword analysis encompasses keyword co-occurrence analysis,keyword clustering analysis,keyword timeline analysis,and keyword emergence analysis.RESULTS AND CONCLUSION:A total of 2 961 articles from the Web of Science database and 1171 articles from the CNKI database were included.The number of publications in the Web of Science database showed fluctuations but exhibited an overall increasing trend year by year,while the publication volume in the CNKI database remained relatively stable annually.Most of the top ten most cited articles in the Web of Science database were review articles.The results of the keyword analysis from Web of Science and CNKI databases indicated that the most studied nerve tissue engineering materials over the past 20 years include silk fibroin,collagen,chitosan,polycaprolactone,polylactic acid,and graphene.The biochemical cues investigated in these materials include olfactory ensheathing cells,Schwann cells,stem cells,and nerve growth factors.The most commonly employed external physical factor is electrical stimulation applied to the materials.Among various tissue engineering techniques,electrospinning technology and 3D printing technology have been the most extensively researched.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.