Computer Methods in Biomechanics and Biomedical Engineering最新文献

{"title":"Identification of cancer-associated fibroblast characteristics for predicting outcome and response to immunotherapy in renal cell carcinoma.","authors":"Jie-Bo Zhou, Chun-Xiang Li, Lei Qian, Jian-Hua Chu","doi":"10.1080/10255842.2025.2495299","DOIUrl":"10.1080/10255842.2025.2495299","url":null,"abstract":"<p><strong>Objectives: </strong>To elucidate the prognostic effect of cancer-associated fibroblasts (CAFs) on renal cell carcinoma.</p><p><strong>Methods: </strong>CAFs and stromal scores were calculated using various algorithms including Estimating the Proportions of Immune and Cancer cells (EPIC), Microenvironment Cell Populations-counter (MCP counter), Tumor immune dysfunction and exclusion (TIDE) and xCell. Weighted gene co-expression network analysis (WGCNA) was conducted to determine the CAF-associated modules and key genes. The functional pathways of key genes in important CAF modules were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. CAF-associated signatures were established through univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) analyses. Kaplan-Meier and receiver operating characteristic (ROC) analyses were carried out to assess the predictive value of CAF signatures.</p><p><strong>Results: </strong>WGCNA analysis distinguished several CAF-associated modules for renal clear cell carcinoma (KIRC), renal chromophobe cell carcinoma (KICH) and renal papillary cell carcinoma (KIRP) respectively. CAF signatures were established containing two and four genes for KIRC and KIRP, respectively. In KIRC and KIRP, patients with high-risk scores had unfavorable outcome than those with low-risk scores. Additionally, in both KIRC and KIRP, the ratio of patients responding to immunotherapy was obviously higher in low-risk group than in high-risk group. Finally, the mutation frequency of some genes differed significantly between two groups.</p><p><strong>Conclusion: </strong>Our study provided valuable CAF signatures for predicting the outcome of KIRC and KIRP patients. These CAF signatures were also used to predict immunotherapy response, providing strategies for individualized therapy of patients.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2866-2878"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144004163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HybridGWOSPEA2ABC: a novel feature selection algorithm for gene expression data analysis and cancer classification.","authors":"Ashimjyoti Nath, Chandan Jyoti Kumar, Sanjib Kr Kalita, Thipendra Pal Singh, Renu Dhir","doi":"10.1080/10255842.2025.2495248","DOIUrl":"10.1080/10255842.2025.2495248","url":null,"abstract":"<p><strong>Background and objective: </strong>DNA micro-array technology has a remarkable impact on biological research, particularly in categorizing and diagnosing cancer and studying gene features and functions. With the availability of extensive collections of cancer-related data, there has been an increased focus on developing optimized Machine Learning (ML) techniques for cancer classification through gene pattern analysis and the identification of specific genes for cancer type categorization. The relevant gene selection for diagnosing and treating cancer poses a significant challenge, which requires efficient feature selection methods.</p><p><strong>Methods: </strong>This study introduces a novel hybrid algorithm, for gene selection, integrating the Grey Wolf Optimizer (GWO), Strength Pareto Evolutionary Algorithm 2 (SPEA2), and Artificial Bee Colony (ABC). This combination uses intelligence and evolutionary computation to enhance solution diversity, convergence efficiency, and exploration and exploitation capabilities in high-dimensional gene expression data. The algorithm was compared with five bio-inspired algorithms using five different classifiers on various cancer datasets to validate its effectiveness in feature selection.</p><p><strong>Results: </strong>The HybridGWOSPEA2ABC algorithm demonstrated superior performance in identifying relevant cancer biomarkers compared to the conventional bio-inspired algorithms. Comparison with the benchmark algorithms has shown the hybrid approach's enhanced capability in addressing the challenges of high-dimensional data and advancing the gene selection problem for cancer classification.</p><p><strong>Conclusion: </strong>The novel hybridization algorithm enhances performance by maintaining solution diversity, efficiently converging to optimal solutions, and improving the exploration and exploitation of the search space. This study provides a better understanding of relevant genes for cancer classification and promotes effective methodologies for disease detection and classification.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2786-2807"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144057589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-scale computational approach to evaluate the overall anisotropic elastic moduli of natural enamels accounting for the actual nano-HAP crystallite effect.","authors":"Jian-Tao Liu, Yi-Fei Wan, Zhao-Fei Huang, Zhu-Cheng Jin, Guang-Shen Tan, Zhi-Qiang Feng","doi":"10.1080/10255842.2025.2498043","DOIUrl":"10.1080/10255842.2025.2498043","url":null,"abstract":"<p><p>In this study, a multi-scale computational methodology was developed to directly incorporate the HAP orientation and architecture effects into the overall elastic moduli of natural enamels. Precisely, the strong, weak and discretized governing formulations of the enamel representative unit cell were first constructed, and a numerical approach was then presented to compute the relevant moduli. Further, a top-down modeling scheme was proposed to evaluate the stiffness of each element accurately using the meshing scheme established previously. The computational methodology was validated with the predictions in the open literatures, and discussions were made on the HAP organization and material proportion effects.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2909-2924"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144025455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics analysis unveils hub genes in the pathogenesis of sevoflurane anesthesia-induced respiratory depression.","authors":"Qian Wang, Bowen Feng","doi":"10.1080/10255842.2026.2631138","DOIUrl":"10.1080/10255842.2026.2631138","url":null,"abstract":"<p><p>Sevoflurane dose-dependently suppresses respiratory activity, yet its molecular mechanisms remain incompletely understood. In this study, we integrated transcriptomic data from the Gene Expression Omnibus and GeneCards to identify differentially expressed genes associated with sevoflurane anesthesia and respiratory depression. A protein-protein interaction network was constructed, and hub genes were screened using the MCC, Betweenness, Closeness, and MCODE algorithms. Functional associations of these hub genes were further explored using the GeneMANIA platform. Potential therapeutic compounds were predicted through the Connectivity Map (CMap) database. The effects of sevoflurane on ICAM1 expression and the intervention of PD-98059 were experimentally validated in SH-SY5Y cells. Ultimately, nine hub genes were identified, including MMP9, CXCL1, IL1B, NF-κB1, CXCL8, IL6, CCL2, ICAM1, and VCAM1. These genes were mainly enriched in pathways related to inflammatory responses, immune regulation, and chemotaxis. Increased infiltration of dendritic cells, MHC class I molecules, and neutrophils was observed in the sevoflurane-treated group. PD-98059 was predicted as a potential therapeutic candidate and was confirmed to reverse sevoflurane-induced upregulation of ICAM1. Overall, this study identifies key genes and inflammatory pathways associated with sevoflurane-induced respiratory suppression, providing new insights into its molecular mechanisms and potential therapeutic strategies.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2977-2994"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146221909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of dysregulated competitive endogenous RNA network driven by copy number variation in colon adenocarcinoma.","authors":"Qingliang Lin, Haiyu Liu, Qian Xu","doi":"10.1080/10255842.2025.2498718","DOIUrl":"10.1080/10255842.2025.2498718","url":null,"abstract":"<p><p>Competitive endogenous RNA (ceRNA) network modulation plays a crucial role in pathogenesis of colon adenocarcinoma (COAD). This study analyzed The Cancer Genome Atlas(TCGA) data to identify 151 copy number variation (CNV)-driven lncRNAs in COAD, constructing a ceRNA network (6 lncRNAs-14 miRNAs-68 mRNAs). Functional enrichment revealed their roles in muscle system processes , blood vessel development and extracellular matrix organization. Survival analysis linked LINC00941 amplification to poor prognosis. Two CNV-driven lncRNA-targeting drugs were identified, offering insights into COAD mechanisms and potential biomarkers.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2925-2936"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144058952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomechanical effects of upper articular process resection proportion on lumbar after transforaminal endoscopic spine system surgery.","authors":"Hanqiang Liu, Aobo Zhang, Hao Chen, Yang Liu, Bin Sun, Hao Liu, Qing Han, Jincheng Wang, Peng Xia","doi":"10.1080/10255842.2025.2495252","DOIUrl":"10.1080/10255842.2025.2495252","url":null,"abstract":"<p><p>Transforaminal endoscopic spine system resection of upper articular process with different proportions often has different effects on lumbar spine biomechanics. Therefore, finite element method was used to explore this problem in this study. The Finite Element (FE) model constructed and validated in this study was a 3D heterogeneous model of the L1-S1 lumbar spine. Nine groups of models with different resect proportions were constructed and compared in six physiological movements. Following the experiment, we reached the following main results. The peak Von Mises stress of the left upper articular process of L5 increased most significantly when the resection proportion increased from 40% to 50% under flexion-extension and bending conditions, with an increase value of 6.04-11.47 MPa. When the resection proportion increased from 70% to 80% under rotation conditions, the peak Von Mises stress of the left articular process of L5 increased most significantly, with an increase value of 26.89 and 37.43 MPa. When the resection proportion increased from 70% to 80% under rotation conditions, the peak Von Mises stress of L4-L5 disc increased by 0.69 and 1.84 MPa. The stress concentration area was mainly located in the junction area of articular process and articular cartilage. Based on the above results, we draw the following conclusions. The resection of 50% of the upper articular process is the critical value of lumbar spine biomechanical change. Especially when the proportion of upper articular process resection exceeds 80%, lumbar instability and postoperative pain may occur during rotation. The postoperative pain is related to the stress concentration stimulation of the articular process and articular cartilage junction.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2841-2852"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mathematical modeling and dynamical observations of HIV/AIDS transmission under the role of antiretroviral treatment.","authors":"Muhammad Asad Ullah, Nauman Raza, Parvaiz Ahmad Naik, Muhammad Farman, Younes Chahlaoui, Zhengxin Huang","doi":"10.1080/10255842.2025.2497404","DOIUrl":"10.1080/10255842.2025.2497404","url":null,"abstract":"<p><p>The Human Immunodeficiency Virus (HIV) attacks particular immune system cells such as Tcells (primarily CD+4T cells) and triggers lifetime severe sickness with a prolonged incubation period. This study develops and analyzes a novel mathematical model to understand the spread of the virus, using real-world data reported cases in Taiwan from 2000 to 2023. The mathematical properties of the model, such as existence, uniqueness, positivity, and boundedness, are rigorously examined to ensure reliability. Equilibrium points are determined, and their stability is analyzed to understand the long-term behavior of the disease. The fundamental reproduction number is obtained using the next generation approach. Sensitivity analysis is performed using different variables as response functions each time, employing Latin Hypercube Sampling and Partial Rank Correlation Coefficient with 200 iterations. Theoretical results are validated using numerical simulations and graphically display the impacts of different model parameters. Results indicate that reducing contact with infected individuals and accelerating disease management interventions can significantly lower the burden of infection.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2894-2908"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144037344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gait phase recognition method for lower limb exoskeleton robot based on SE channel attention mechanism enhanced TCN-SVM.","authors":"BinHao Huang, Jian Lv, Ligang Qiang","doi":"10.1080/10255842.2025.2495251","DOIUrl":"10.1080/10255842.2025.2495251","url":null,"abstract":"<p><p>This study develops an integrated system for collecting kinematic signals from lower limb exoskeletons, combining thigh muscle pressure with inertial measurements. The system captures muscle pressure, triaxial acceleration, and angle data. A temporal convolutional network model with an SE attention mechanism and SVM classifier is proposed for gait phase recognition. Results show that the FMG-IMU data fusion strategy achieves high accuracy, stability, and low sensitivity to external noise, effectively recognizing gait phases and improving exoskeleton performance.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2821-2840"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144013589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative study of microneedle insertion across different skin models.","authors":"Xuan He, Xue Sui, Yongchao Liu, Rui Zhou, Shouying Du","doi":"10.1080/10255842.2025.2495300","DOIUrl":"10.1080/10255842.2025.2495300","url":null,"abstract":"<p><p>Microneedles (MNs) enhance drug delivery by painlessly penetrating the stratum corneum, with hardness being crucial for safe insertion. While human/animal skins and synthetic materials are used to test MNs, their variability affects results. Finite element methods (FEM) simulate insertion, but skin model complexity and software limitations cause inconsistencies. This study employs FEM to compare MN performance across skun models under uniform conditions. Results reveal small volume change differences during insertion and rank penetration ease for human/animal models, aiding skin model selection and species-specific MN design optimization.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2879-2893"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144057238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epileptic seizure detection in EEG signals using deep learning: LSTM and bidirectional LSTM.","authors":"Ghezala Chekhmane, Radhwane Benali","doi":"10.1080/10255842.2025.2490136","DOIUrl":"10.1080/10255842.2025.2490136","url":null,"abstract":"<p><p>This paper established a new automatic method to detect epileptic seizures in EEG signals based on discret wavelet transform (DWT) and Deep Learning (DL). DWT is used to decompose EEG into different sub-bands. Moreover, the proposed model combines Long Short-Term Memory (LSTM) and bidirectional LSTM (BiLSTM) networks with one layer of each network consecutive. The experimental results yield higher accuracies of 100% which it is demonstrated that the obtained results achieve better performance by using the new hybrid LSTM-BiLSTM network than other works. Finally, this hybrid LSTM-BiLSTM model confirmed their effectiveness for the classification of epileptic EEG signals.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2751-2774"},"PeriodicalIF":1.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144057586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}