Bioengineering最新文献

{"title":"The Influence of Non-Thermal Plasma Treatment on Osseointegration of Endosteal Implants Presenting Decompressing Vertical Chambers.","authors":"Shray Mehra, Hana Shah, Sara E Munkwitz, Nicholas J Iglesias, Tina Joshua, Kashyap K Tadisina, Natalia Fullerton, Vasudev Vivekanand Nayak, Lukasz Witek, Paulo G Coelho","doi":"10.3390/bioengineering13040472","DOIUrl":"10.3390/bioengineering13040472","url":null,"abstract":"<p><p>Current evidence suggests that achieving the desired level of osseointegration necessitates a hierarchical approach to implant design. This is particularly relevant for osseointegration around implant systems such as those presenting vertical decompression chambers and acid-etched surfaces which could further be augmented by non-thermal plasma (NTP) treatment. Three implant systems were compared in this study: (i) ND (GM Helix Acqua Implant; Neodent^®, Curitiba, PR, Brazil-hybrid, acid-etched thread design treated with isotonic sodium chloride solution), (ii) Sin (Epikut Plus; S.I.N. Implant System, São Paulo, Brazil-V-shaped, acid-etched thread design treated with nano-hydroxyapatite), and (iii) Mp (Maestro; Implacil De Bortoli, São Paulo, Brazil-buttress, acid-etched thread design with decompressing vertical chambers). The ND and Sin implants were used directly as supplied by the manufacturer. For the Mp implants, the manufacturer-supplied surface was subjected to supplemental acid etching with 37% hydrochloric acid followed by Argon-based NTP treatment administered with a pulsed plasma generator prior to implantation into the iliac crest of n = 12 adult female sheep. Histomorphometric analysis was conducted at 3- and 12-week post-implantation (n = 6 sheep per time point) to assess bone-to-implant contact (BIC) and bone area fraction occupancy (BAFO). After 3 weeks in vivo, the healing chambers of all implant groups consisted predominantly of newly forming woven bone. By 12 weeks, bone maturation was observed, with the presence of remodeling sites and some areas of well-organized lamellar structures occupying the healing chambers. At both 3 and 12 weeks, the Mp implants demonstrated significantly higher BAFO values relative to ND (<i>p</i> = 0.015 and <i>p</i> = 0.008, respectively). The combination of vertical healing chambers, acid etching, and NTP treatment promoted early vascular infiltration and sustained bone deposition.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Aortic Quantification Based on Artificial Intelligence: Validation Using Contrast-Enhanced and Non-Contrast CT Scans from the Same Session.","authors":"Jia-Sheng Hong, Yun-Hsuan Tzeng, Kuan-Ting Wu, Shih-Yu Huang, Ting-Wei Wang, Guan-Yu Li, Chun-Yi Lin, Ho-Ren Liu, Hai-Neng Fu, Yung-Tsai Lee, Wei-Hsian Yin, Yu-Te Wu","doi":"10.3390/bioengineering13040471","DOIUrl":"10.3390/bioengineering13040471","url":null,"abstract":"<p><p>Early detection of aortic dilatation is clinically important for preventing progression to serious aortic disease and enabling timely intervention. We aimed to develop an AI method for quantifying the aorta in both contrast-enhanced and non-contrast CT scans, assisting early detection of aortic dilation. A total of 190 patient cases were analyzed, each having paired contrast-enhanced and non-contrast CT scans acquired in the same session, resulting in 380 scans. Our approach, based on open-source tools, demonstrated strong agreement with manual annotations, particularly in the ascending aorta. For contrast-enhanced CT, the AI achieved a correlation coefficient of 0.987 and intraclass correlation coefficient (ICC) of 0.986; for non-contrast CT, both were 0.945. Compared with clinical records, the sensitivity of AI detection was 97% for contrast-enhanced CT and 94% for non-contrast CT. This AI-based workflow enables highly sensitive automated aortic quantification in both contrast-enhanced and non-contrast CT scans, supporting broader clinical applicability across different imaging conditions.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113725/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinically Robust Deep Learning for Contrast-Enhanced Mammography: Multicenter Evaluation Across Convolutional Neural Network Architectures.","authors":"Roberta Fusco, Vincenza Granata, Paolo Vallone, Teresa Petrosino, Maria Daniela Iasevoli, Roberta Galdiero, Mauro Mattace Raso, Davide Pupo, Filippo Tovecci, Annamaria Porto, Gerardo Ferrara, Modesta Longobucco, Giulia Capuano, Roberto Morcavallo, Caterina Todisco, Fabiana Antenucci, Mario Sansone, Mimma Castaldo, Daniele La Forgia, Antonella Petrillo","doi":"10.3390/bioengineering13040475","DOIUrl":"10.3390/bioengineering13040475","url":null,"abstract":"<p><strong>Background: </strong>This study investigates the impact of anatomically constrained preprocessing and deep learning architecture selection on benign versus malignant breast lesion classification in contrast-enhanced mammography (CEM), with the goal of improving robustness and clinical reliability across heterogeneous data sources.</p><p><strong>Methods: </strong>In this retrospective multicenter study, CEM images from 300 patients (314 lesions) were combined with 1003 publicly available CEM images, yielding a total of 1120 breast cases. Automatic breast segmentation was performed using the LIBRA framework to generate breast-mask images. Eleven deep learning models, including classical convolutional neural networks, attention-based networks, hybrid convolutional neural networks (CNNs), Transformer architectures, and mammography-specific models, were trained and evaluated using both original DICOM images and breast-mask inputs. Performance was assessed using accuracy, balanced accuracy, sensitivity, specificity, AUROC, and AUPRC on cross-validation and independent test sets. Hyperparameter optimization was conducted for the best-performing architecture.</p><p><strong>Results: </strong>Models trained on breast-mask images consistently outperformed those trained on original DICOM images across all architectures and metrics, with AUROC improvements ranging from +0.06 to +0.21. Among all models, ResNet50 trained on breast-mask images achieved the best performance (AUROC = 0.931; AUPRC = 0.933; balanced accuracy = 0.834), further improved after optimization (balanced accuracy = 0.886; sensitivity = 0.842; specificity = 0.930). Classical CNN architectures demonstrated performance comparable to or exceeding that of more complex hybrid CNN-Transformer models when anatomically focused preprocessing and rigorous optimization were applied.</p><p><strong>Conclusions: </strong>Anatomically constrained preprocessing through breast-mask segmentation substantially enhances deep learning performance and stability in CEM-based breast lesion classification. These findings indicate that input representation quality and training optimization are critical determinants of clinically relevant performance, often outweighing architectural complexity, and may support more reliable AI-assisted decision support in CEM workflows.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112954/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomechanical Factors and Prevention Strategies for Sports-Related Muscle Injuries: A Narrative Review.","authors":"Catalin Ionite, Lucian Indrei, Andrei Gheorghiță, Bogdan Caba, Marius Turnea, Irina Duduca, Cezar Mucileanu, Iustina Condurache, Mariana Rotariu","doi":"10.3390/bioengineering13040473","DOIUrl":"10.3390/bioengineering13040473","url":null,"abstract":"<p><p>Sports-related muscle injuries represent a major challenge in both recreational and professional sports, accounting for a substantial proportion of time-loss injuries and frequently leading to recurrent episodes. The aim of this narrative review was to analyze the biomechanical and neuromuscular mechanisms involved in the occurrence of muscle injuries and to synthesize evidence-based prevention strategies reported in the scientific literature. The literature search was conducted in the Web of Science database using the keyword \"muscle injury prevention\", focusing on studies published between 2010 and 2025. The analyzed literature indicates that muscle injuries are strongly associated with eccentric contractions at long muscle lengths, neuromuscular fatigue, strength imbalances, impaired lumbopelvic stability, and inadequate load management. Preventive strategies based on biomechanical principles, particularly eccentric strength training, neuromuscular training programs, and core stability exercises, have demonstrated consistent effectiveness in reducing injury incidence and recurrence rates across multiple sports disciplines. In addition, emerging technological approaches, including wearable sensors and machine learning models, show promising potential for injury risk prediction and individualized prevention strategies.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113348/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Large Language Models to Generate Dietary Feedback Similar to Human Experts in Weight Management: Experiments on Real-World Scenario Data.","authors":"Ruixin Dai, Liping Cui, Kun Hu, Jiye An, Ning Deng","doi":"10.3390/bioengineering13040468","DOIUrl":"10.3390/bioengineering13040468","url":null,"abstract":"<p><p>Providing dietary feedback is important for promoting healthy behaviors in weight management, but the rapid development of obesity and the shortage of medical nutrition human resources have limited this health service. The rise of large language models (LLMs) offers the possibility of using artificial intelligence (AI) to simulate the behavior of human dietitians. However, existing studies have only explored LLM performance when generating answers to common nutrition-related questions; the use of LLMs to generate situation-adapted dietary feedback in practical weight management scenarios still needs further research. In this study, we collected dietary records and dietary feedback from primary dietitians through an mHealth weight management application. We conducted topic modeling to generalize how dietitians deliver nutrition guidance in real-world dietary feedback scenarios. Combining the in-context learning capability of LLMs with real-world data, we proposed a synthetic data generation approach (HDI-SDG) and trained an LLM for dietary feedback with the synthetic data (LLMDF-EXP). Experiments on automatic and manual evaluation of LLMDF-EXP and an LLM trained directly with the real-world data as well as generalized LLMs illustrated that LLMDF-EXP performed most similarly to human experts. Notably, there were no significant differences from human experts in terms of professionalism (<i>p</i>-value = 0.510) and usefulness (<i>p</i>-value = 0.498). The study highlights that integrating LLMs with real-world data in health management processes can enhance the situational adaptability of LLMs in practical health management environment applications.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113237/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Flexible Copper Electrode Array for High-Density Surface Electromyography.","authors":"Chaoxin Li, Chenghong Lu, Jiuqiang Li, Kai Guo","doi":"10.3390/bioengineering13040467","DOIUrl":"10.3390/bioengineering13040467","url":null,"abstract":"<p><p>Precise monitoring of forearm muscle groups is crucial for decoding motor intentions in human-machine interfaces (HMIs) and rehabilitation. However, traditional surface electromyography (sEMG) electrodes face significant challenges in densely packed muscle regions with large skin deformations, leading to severe signal crosstalk and unstable contact. Here, we report a flexible, low-cost 16-channel copper electrode array system designed for the high-density monitoring of multiple forearm muscle activities. Through a facile fabrication process, rigid copper is transformed into a conformable sensing interface. The optimized serpentine interconnects endow the array with excellent stretchability and effectively isolate motion-induced stress, ensuring high-quality signal acquisition under complex deformations. The high-density 2 × 8 array enables the spatiotemporal mapping of distributed flexor and extensor muscle groups. Integrated with a customized wireless data acquisition system, the array successfully demonstrates real-time, multi-channel sEMG monitoring of various hand movements (e.g., fist clenching, wrist flexion/extension), clearly revealing specific muscle activation patterns. This low-cost, high-performance flexible sensor array provides a highly promising tool for complex gesture decoding, electromyographic imaging, and next-generation wearable HMIs.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113433/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomineralization of Glucose Oxidase from <i>Aspergillus niger</i> in ZIF-zni for Enhanced Biocatalytic Performance.","authors":"Marija Stanišić, Milica Crnoglavac Popović, Nikola Knežević, Marko Radenković, Branimir Bajac, Olivera Prodanović, Radivoje Prodanović","doi":"10.3390/bioengineering13040465","DOIUrl":"10.3390/bioengineering13040465","url":null,"abstract":"<p><p>Biomineralization has recently emerged as a highly effective strategy for enzyme immobilization. Zeolitic imidazolate frameworks (ZIFs), a subclass of metal-organic frameworks (MOFs), are particularly attractive carriers due to their structural tunability and chemical stability. While ZIF-8 has been extensively studied, its denser and thermodynamically more stable analog ZIF-zni has received far less attention. In this work, we report the biomineralization of glucose oxidase (GOx) from <i>Aspergillus niger</i> within the ZIF-zni framework and systematically investigate the influence of zinc and imidazole (Im) concentration on immobilization performance. The optimized biocomposite, obtained at 10 mM Zn²⁺ and a Zn:Im ratio of 1:10, exhibited a specific activity of 2051 IU g^-1, which is more than twice the activity obtained for GOx@ZIF-8 in our previous study (874 IU g^-1). Furthermore, the GOx@ZIF-zni biocomposite demonstrated remarkable resistance to sodium dodecyl sulfate (SDS) and retained up to 50% of its activity after incubation at 65 °C for one hour. These results demonstrate that ZIF-zni is a highly promising carrier for enzyme immobilization and suggest that framework topology and synthesis conditions play a crucial role in determining the catalytic performance and stability of enzyme@MOF biocomposites.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vision-Language Models in Medical Imaging for Cancer Diagnosis: A Bibliometric Review.","authors":"Musa Adamu Wakili, Aminu Bashir Suleiman, Kaloma Usman Majikumna, Harisu Abdullahi Shehu, Huseyin Kusetogullari, Md Haidar Sharif","doi":"10.3390/bioengineering13040466","DOIUrl":"10.3390/bioengineering13040466","url":null,"abstract":"<p><p>The demand for advanced detection methods and accurate staging remains a global challenge in cancer diagnosis. Even though traditional deep learning models in medical imaging achieve high precision, they suffer from limited explainability and multimodal reasoning due to their black-box nature, thereby limiting their clinical applicability. To address this gap, recent research has increasingly explored multimodal approaches that integrate visual and textual clinical data to enhance diagnostic accuracy and interpretability. This study presents a bibliometric analysis of 408 publications from 2021 to 2025, collected from Web of Science and Scopus, using VOSviewer and R-Bibliometrix to map citation networks, co-authorship, and keyword co-occurrences. The results reveal a rapid growth from 1 publication in 2021 to 269 in 2025, with significant contributions from leading countries and institutions. Thematic analysis indicates a shift from conventional convolutional approaches toward transformer-based and self-supervised methods, alongside increasing attention to multimodal learning in cancer imaging tasks such as breast, lung, and brain cancer analysis. Overall, this study provides a structured overview of the evolving research landscape, highlighting key trends, emerging themes, and research gaps to inform future developments in multimodal artificial intelligence for cancer diagnosis.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113868/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the Effectiveness of a Novel Wireless Energy-Transmitting Implantable Diaphragm Pacemaker in Anesthetized Pigs.","authors":"Xiaoyu Gu, Wei Zhong, Zhihao Mao, Yan Shi, Yixuan Wang","doi":"10.3390/bioengineering13040469","DOIUrl":"10.3390/bioengineering13040469","url":null,"abstract":"<p><p><b>Objectives:</b> This study aimed to demonstrate the feasibility of a novel wireless energy-transmitting implantable diaphragm pacemaker for restoring respiratory ventilation. <b>Methods:</b> The diaphragm pacing (DP) system was designed based on the principle of electromagnetic resonance coupling. The safety of device implantation was analyzed through finite-element simulations of multi-field coupling between electromagnetic heating and biological tissue. In vitro testing with coils embedded in pork demonstrated the system output characteristics. This device was used in miniature Bama pigs that underwent deep anesthesia and respiratory arrest (<i>N</i> = 8). Respiratory airflow, diaphragmatic displacement, and blood gases were used to evaluate the effectiveness of the designed DP system. <b>Results:</b> Thermal effect simulation results show that the temperature rise of the surrounding tissue does not exceed 2 °C during 1 h of transmission power (0.5-1.3 W) operation of the receiver. In vitro tests with two receivers embedded in pork showed that the DP system can effectively output stimulation waveforms over a certain transmission distance (5-35 mm). The stimulation waveform output by the receiver is consistent with the parameters set by the external controller. In phrenic nerve electrical stimulation experiments, the peak respiratory airflow and tidal volume remained stable over 50 consecutive respiratory cycles. The tidal volume (108.63 mL) and diaphragmatic displacement (0.883-2.15 cm) in a pig induced by DP demonstrate the effectiveness of respiratory ventilation. The arterial blood gas analysis results and temperature rise experiment during implantation further confirmed the effectiveness and safety of the ventilation. <b>Conclusions:</b> The implantable diaphragmatic pacemaker developed in this study exhibits good thermal safety, stable output, and effective respiratory ventilation. A control group with commercial diaphragmatic pacemakers and data from chronic implantation experiments are needed to further evaluate its effectiveness.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113557/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Purkinje Fiber Conduction Block on Cardiac Pump Function: Computational Modeling Study.","authors":"Sandra P Hager, Vahid Ziaei-Rad, Jenny S Choy, Mengjun Wang, Ghassan S Kassab, Lik Chuan Lee","doi":"10.3390/bioengineering13040464","DOIUrl":"10.3390/bioengineering13040464","url":null,"abstract":"<p><p>Cardiac and hemodynamic conditions such as myocardial infarct, cardiomyopathy, hypertension, and aortic valve disease can impair conduction within the Purkinje fiber network and compromise left ventricular (LV) pump function. We developed a computational framework that couples electrical propagation in a structurally organized Purkinje fiber network with LV electromechanics to analyze the impact of conduction abnormalities on cardiac performance. A <i>baseline</i> simulation reproduced physiological activation patterns and pump indices consistent with healthy human data. Conduction block was then introduced at different locations within the Purkinje fiber network. LV pump function was strongly dependent on block location: <i>left bundle branch block (LBBB)</i> produced the largest reduction in ejection fraction (EF) (59% to 46%) and peak pressure (119 to 97 mmHg), whereas <i>left anterior fascicle block</i> caused smaller functional changes. Across simulations, myocardial activation delay and systolic dyssynchrony index (SDI) exhibited a nonlinear relationship with EF and myocardial strain. A threshold behavior was identified at a simulated LV activation duration of approximately 240 ms and an SDI of 8.4%, beyond which EF and strain decreased by about 5% relative to baseline. These findings provide a mechanistic framework to investigate how Purkinje fiber network conduction abnormalities influence LV pump dysfunction.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}