生物医学工程学杂志最新文献

{"title":"[Research progress on three-dimensional finite element analysis for fixed implant restoration of edentulous jaw].","authors":"Yue Lan, Baohui Su","doi":"10.7507/1001-5515.202504001","DOIUrl":"https://doi.org/10.7507/1001-5515.202504001","url":null,"abstract":"<p><p>With the intensification of population aging, the number of edentulous patients continues rising. Fixed implant prostheses have become the primary treatment for tooth loss due to their superior chewing efficiency and comfort. However, improper implant prosthetic design may lead to various mechanical and biological complications, and even result in implant failure. Therefore, systematically analyzing the mechanical factors that influence the outcomes of implant restoration and optimizing the design hold significant clinical importance. Finite element analysis, as an effective biomechanical research tool, can simulate the stress distribution in dental implants and bone tissues under different loading conditions, thereby providing a theoretical basis for optimizing implant restoration plans. This review focuses on the impact of factors including implant number, size, shape, inclination angle, framework design and different modeling assumptions on the stress distribution in edentulous implant, aiming to provide references for developing clinically rational implant restoration plans.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"434-440"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112213/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Optimized decomposition of dynamic electroencephalography-functional near infrared spectroscopy brain functional networks for the analysis of repetitive transcranial magnetic stimulation combined with motor training].","authors":"Jiewei Lu, Jianeng Lin, Yinuo Liu, Ying Zhang, Chunfang Wang, Jianda Han, Ningbo Yu","doi":"10.7507/1001-5515.202510062","DOIUrl":"https://doi.org/10.7507/1001-5515.202510062","url":null,"abstract":"<p><p>Repetitive transcranial magnetic stimulation combined with motor training effectively promotes motor recovery in stroke patients. However, its underlying neurophysiological mechanisms remain unclear. Existing single-modal neuroimaging techniques are limited by the incapacity to fully characterize the neural mechanisms of combined interventions. To address the above problem, this paper proposed an optimized decomposition method for dynamic brain functional networks based on electroencephalography and functional near-infrared spectroscopy, in order to reveal the potential neural mechanisms underlying the improvement of motor function in stroke patients through combined repetitive transcranial magnetic stimulation and motor training from a multimodal perspective. Twenty-seven stroke patients were recruited to participate in a clinical trial for this study. The results showed that the real stimulation group exhibited significantly increased flexibility in the frontoparietal network after intervention, with the magnitude of change significantly correlated with clinical improvement, whereas no significant changes were observed in the sham stimulation group. In conclusion, this study reveals the brain functional rehabilitation mechanism under combined intervention, contributing to the development of personalized rehabilitation strategies.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"293-301"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Electroencephalogram emotion recognition based on state-space models combined with spatio-temporal feature].","authors":"Chunli Wang, Jiahao Zhang, Jiarong Dou, Chenming Wang, Wenwen Chang","doi":"10.7507/1001-5515.202508024","DOIUrl":"https://doi.org/10.7507/1001-5515.202508024","url":null,"abstract":"<p><p>To address the challenges of spatiotemporal feature heterogeneity, insufficient utilization of frequency band information, and weak cross-subject generalization in electroencephalogram (EEG)-based emotion recognition, this paper proposes a hierarchical spatiotemporal feature learning architecture named spatio-temporal mamba (ST-Mamba) based on state space models. Firstly, the proposed conv-spatio-temporal (CST) dual-branch collaborative module integrates the local feature extraction capability of convolutional neural network (CNN) with the global modeling ability of state space models. Through adaptive weighted fusion, it effectively mitigates the issue of inadequate modeling of inter-channel relationships in EEG signals. Secondly, the designed multi-band spatio-temporal feature pyramid (MBSTP) module adaptively weights features from different frequency bands via a frequency-band attention mechanism, while capturing spatial topological dependencies across brain regions through a hierarchical fusion strategy. Additionally, a data augmentation framework efficiently enhances the model's cross-subject generalization by applying augmentations in the frequency, temporal, and spatial domains. The proposed model achieves average accuracies of 95.56% and 84.47% on the Shanghai Jiao Tong University emotion EEG dataset (SEED), version III (SEED-III) and version IV (SEED-IV), respectively. Experiments demonstrate that the state space model effectively alleviates the over-smoothing issue in deep networks, offering a novel solution to spatiotemporal heterogeneity and cross-subject generalization challenges in EEG-based emotion recognition.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"311-318"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Cluster-guided adaptive Transformer for muscle fatigue prediction].","authors":"Bo Fan, Xueliang Bao, Lei Ding, Jiao Wu","doi":"10.7507/1001-5515.202601012","DOIUrl":"https://doi.org/10.7507/1001-5515.202601012","url":null,"abstract":"<p><p>Due to the significant non-stationarity and feature distribution discrepancies in surface electromyography (sEMG) signals during muscle fatigue monitoring, traditional fixed-parameter Transformer models often struggle to accurately capture the complex evolution of time-frequency characteristics across different fatigue stages. To address this limitation, this paper proposes a K-means clustering-guided neural architecture search method (CG-NAS) to achieve adaptive optimization of Transformer architectures based on data distribution characteristics. The method first classified input EMG features using the K-means clustering algorithm and constructed Gaussian distributions characterized by mean and variance to quantify the complexity of each cluster. These distribution priors then guided the neural architecture search process, enabling dynamic alignment between the architecture search space and data characteristics: for low-complexity data clusters with small mean and variance, lightweight Transformer architectures were selected, whereas for high-complexity clusters, architectures with greater width and depth were allocated. Experimental results demonstrated the superior performance of CG-NAS in muscle fatigue index prediction tasks, achieving a mean absolute error of 0.098 2 and a coefficient of determination of 0.957 3, significantly outperforming multiple benchmark models. The study shows that CG-NAS effectively aligns with the nonlinear evolution of time-frequency features during the fatigue process and provides an efficient and robust solution for fatigue monitoring.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"250-258"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Exogenous nitric oxide suppresses K _ATP channel activity through S-nitrosylation].","authors":"Xuefei Wang, Yuxin Zhang, Weicao Hu, Xuewei Hao","doi":"10.7507/1001-5515.202511038","DOIUrl":"https://doi.org/10.7507/1001-5515.202511038","url":null,"abstract":"<p><p>The inhibitory effect of exogenous nitric oxide (NO) on the open state of ATP-sensitive potassium channels (K _ATP) and its underlying mechanism remain unclear. In this study, patch-clamp and molecular biology techniques are used to investigate this issue. In acutely isolated rat mesenteric artery smooth muscle cells and human embryonic kidney 293 cells (HEK293) expressing inwardly rectifying potassium channel 6.1 subunit/sulfonylurea receptor 2B subunit (Kir6.1/SUR2B), sodium nitroprusside (SNP) was found to significantly inhibit the activity of open K _ATP channels. Detection using biotin-labeled glutathione ethyl ester (BioGEE) combined with Western blotting showed that Kir6.1 subunit glutathionylation level was significantly decreased after SNP treatment. These results indicate that exogenous NO directly inhibits the activity of open K _ATP channels by nitrosylating key cysteine residues of the Kir6.1 subunit and competitively inhibiting glutathionylation at this site. This study provides new experimental evidence for the molecular mechanism of NO in vascular regulation.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"391-397"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Research progress on the acquisition technology of magnetocardiography].","authors":"Bochao Kang, Ming Dong, Yi Chang, Jingyi Wang, Tairan Zhao, Lihong Fan","doi":"10.7507/1001-5515.202504002","DOIUrl":"https://doi.org/10.7507/1001-5515.202504002","url":null,"abstract":"<p><p>For certain cardiovascular diseases such as coronary artery disease and arrhythmia, electrocardiogram as a conventional cardiac function monitoring method has limitations such as insufficient resolution and unreliable accuracy in diagnosis. In contrast, magnetocardiography (MCG) offers several advantages, such as being unaffected by uneven human body conductivity and skin-electrode contact, and providing higher spatial resolution, which make it more effective than electrocardiogram for pathological characterization and lesion localization. The acquisition technology of MCG, which is a vital component of the overall MCG system, has predominantly utilized superconducting quantum interference device. In recent years innovative cases of MCG acquisition using atomic magnetometers and magneto-resistive sensors have also appeared in academia. In this paper, the MCG acquisition technologies based on three distinct magnetic sensors are reviewed. Firstly, the current research progress on each MCG acquisition technology is introduced. After that, the enhancement approaches of various technologies for improving cardiac magnetic signal acquisition and magnetic shielding conditions are discussed. Subsequently, differences between each technology are analyzed and the existing development difficulties and solutions of MCG technology are discussed. Finally, an outlook on the application prospect of MCG in the clinical field is provided, aiming to provide references for the continuous optimization of MCG technology and accelerate its adoption as a reliable diagnostic method for cardiovascular diseases.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"405-413"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Research on weighted hypergraph attention neural network for the diagnosis of psychiatric disorders using brain functional connectivity networks].","authors":"Xiuwei Lin, Zhifeng Wang, Haotao Yan, Siao Zeng, Peizhou Wang, Zetao Wu, Xin Yu, Junxi Han","doi":"10.7507/1001-5515.202510012","DOIUrl":"https://doi.org/10.7507/1001-5515.202510012","url":null,"abstract":"<p><p>The hypergraph neural network (HGNN) has demonstrated efficacy in modeling high-order interactions among brain regions, thus providing a promising framework for analyzing brain functional connectivity networks in the context of psychiatric research. The present study proposes a phase-amplitude coupling-weighted hypergraph attention neural network (PAC-HyperGAT) model for the diagnosis of psychiatric diseases. The proposed methodology first constructs a functional hypergraph using elastic net-based sparse regression and then assigns physiologically meaningful weights to hyperedges by quantifying the phase-amplitude coupling strength among nodes within each hyperedge. In light of these findings, the present study proposes a novel hypergraph attention convolution kernel. The efficacy of this approach is evidenced by its enhancement of the node-level message passing mechanism, a feat that facilitates the integration of hyperedge weight information. This phenomenon, in turn, results in an enhancement of the discriminative ability of brain functional connectivity network representations. The proposed model is systematically evaluated on publicly available electroencephalogram datasets for attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD). The experimental results demonstrate that PAC-HyperGAT attains an accuracy of (72.14 ± 9.19) % in ADHD classification, surpassing the performance of existing brain functional connectivity network methods across a range of evaluation metrics. The model exhibits notable efficacy in MDD classification, signifying substantial cross-disorder generalization capabilities. Furthermore, PAC-HyperGAT has demonstrated efficacy in identifying brain regions associated with these disorders. In summary, the proposed model demonstrates excellent generalizability, robustness, and neurobiological interpretability, providing a reliable analytical framework for objective diagnosis and mechanistic investigation of psychiatric diseases.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"319-327"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Patient-specific electroencephalography epileptic seizure prediction method using global dynamic multi-scale spatio-temporal features].","authors":"Chenchen Cheng, Haichao Wu, Wanjin Song, Bo You, Yan Liu","doi":"10.7507/1001-5515.202506067","DOIUrl":"https://doi.org/10.7507/1001-5515.202506067","url":null,"abstract":"<p><p>Conducting research on patient-specific electroencephalography-based epilepsy seizure prediction methods enables early identification of seizure risk, providing a basis for timely intervention and treatment. However, existing methods fail to simultaneously account for the dynamic temporal feature differences of electroencephalography signals and the spatial correlations between leads when representing spatio-temporal features, limiting the representation of preictal electroencephalography features and consequently affects prediction performance. To address this issue, this paper proposes a patient-specific electroencephalography seizure prediction method based on global dynamic multi-scale spatio-temporal features. By designing a dynamic temporal attention (DTA) branch, it captures instantaneous dynamic features through convolutional extraction of feature differences between adjacent sampling points, and by designing a multi-scale spatial attention (MSSA) branch, it represents multi-scale spatial features among channels using receptive fields of convolution kernels of different sizes. Furthermore, considering the limited local receptive field of convolution operations, attention modules are introduced into the aforementioned branches to represent global information. Finally, a feature fusion (FF) branch is used to represent global dynamic multi-scale spatio-temporal features, aiming to achieve high-precision epilepsy seizure prediction. The accuracy on two public epilepsy electroencephalography datasets reached 95.36% and 72.98%, with sensitivities of 94.08% and 66.40%, and specificities of 96.91% and 79.55%, respectively. Experimental results indicate that the proposed global dynamic multi-scale spatio-temporal features can effectively characterize the dynamic temporal variations and inter-channel spatial correlations of electroencephalography signals, providing strong support for early warning of epileptic seizures.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"302-310"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112227/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Optical coherence tomography angiography image segmentation based on multi-scale dilated convolution and dual attention network].","authors":"Qinghao Zeng, Zhang Xiao, Bin He, Rushu Peng","doi":"10.7507/1001-5515.202505030","DOIUrl":"https://doi.org/10.7507/1001-5515.202505030","url":null,"abstract":"<p><p>Optical coherence tomography angiography (OCTA) is an emerging non-invasive ophthalmic imaging modality. The morphology and contour of the foveal avascular zone (FAZ) are critical biomarkers for the diagnosis of various ophthalmic and systemic diseases; therefore, achieving its accurate segmentation is of substantial clinical significance. To address challenges such as low contrast, indistinct boundaries, and structural confusion with the surrounding retinal vasculature in OCTA images, this paper proposes a multi-scale dilated convolution and dual attention network (MSAD-Net). By integrating a multi-scale dilated convolution module (MSDM) to capture extensive multi-scale contextual information and employing a dual attention module (DAM) to integrate complementary channel and spatial features, thereby synergistically boosting the feature representation of key regions. Experimental results demonstrated that the model achieved superior performance and robust generalization across multiple evaluation metrics, including the Dice similarity coefficient, Jaccard index, precision, and recall-on two public datasets. These findings confirm the robustness of MSAD-Net in the fine segmentation of the FAZ, providing high-precision technical support for the clinical quantitative analysis of ophthalmic diseases.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"373-381"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Mesothelial impairment induced by peritoneal dialysis and its potential protective strategies].","authors":"Yu Ban, Yingying Mei, Botao Chen, Wen Tang, Hongyan Kang","doi":"10.7507/1001-5515.202511048","DOIUrl":"https://doi.org/10.7507/1001-5515.202511048","url":null,"abstract":"<p><p>Peritoneal dialysis serves as a critical treatment modality for end-stage renal disease. Extensive clinical practice has demonstrated that long-term exposure to high-glucose non-physiological peritoneal dialysis solutions can induce peritoneal injury, which is directly associated with a decline in ultrafiltration function and solute clearance capacity. This represents a significant cause of technical failure in dialysis and adverse clinical outcomes, such as peritonitis. Mesothelial cells and the glycocalyx on their surface, acting as the direct barrier between the peritoneum and the dialysis solution, play essential roles in regulating multiple pathophysiological processes, including fibrosis and inflammation, and are crucial for maintaining peritoneal function. This review provides a brief introduction to mesothelial cells and the glycocalyx, with a focus on elucidating the injury to the mesothelium and glycocalyx caused by high-glucose non-physiological peritoneal dialysis solutions, the associated injury mechanisms, and potential protective strategies. The aim is to offer insights for developing novel therapeutic approaches to preserve the structural and functional integrity of the peritoneum and extend the survival of patients undergoing peritoneal dialysis.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"398-404"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112211/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}