Bioengineering最新文献

Correction: Patsouris et al. Advances in Innovative Surgical Implant Manufacturing for Hernia Repair and Soft Tissue Reconstruction. Bioengineering 2025, 12, 1182. 更正：Patsouris等人。疝修补及软组织重建外科植入物制造的创新进展。生物工程学报，2015,12,1182。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-21 DOI: 10.3390/bioengineering13040481

Stavros Patsouris, Panagiotis Mallis, Efstathios Michalopoulos, Nefeli Papadopoulou, Michalis Katsimpoulas, Nikolaos Nikiteas

引用次数: 0

Toward Personalized Rotator Cuff Physical Therapy Dosage Using a Machine Learning-Based Pilot Study with EMG. 使用基于机器学习的肌电图先导研究进行个体化肩袖物理治疗剂量。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-21 DOI: 10.3390/bioengineering13040483

AmirHossein MajidiRad, Iram Azam, Japp Adhikari, Mehrnoosh Damircheli

{"title":"Toward Personalized Rotator Cuff Physical Therapy Dosage Using a Machine Learning-Based Pilot Study with EMG.","authors":"AmirHossein MajidiRad, Iram Azam, Japp Adhikari, Mehrnoosh Damircheli","doi":"10.3390/bioengineering13040483","DOIUrl":"10.3390/bioengineering13040483","url":null,"abstract":"Rotator cuff injuries are among the most common musculoskeletal conditions that affect shoulder function and can ultimately impact quality of life. While physical therapy is essential in the care of rotator cuff injuries, the ideal dose of therapeutic exercises continues to be a significant clinical dilemma because of the generalized nature of rehabilitation protocols. This pilot study proposes a machine learning approach to personalize rehabilitation using surface electromyography (sEMG) data collected from eight healthy individuals by testing four key shoulder movements: scaption, internal rotation, external rotation, and external rotation at 90° abduction. In this research, the XGBoost algorithm was used to model muscle activation patterns by achieving a high predictive accuracy (R2 = 0.5325; MSE = 0.0084 μV2). Because sEMG reliably measures superficial muscle activity, a linear programming model was used to divide a 60 min therapy session in a way that increases activation of superficial muscles (such as deltoid and trapezius) while reducing strain on deep muscles (such as supraspinatus and infraspinatus). Three optimization scenarios were tested by reflecting a different clinical goal: prioritizing superficial muscles, minimizing deep muscle strain, or balancing both. Optimized time allocations assigned more time to external rotation at 90° abduction and scaption. This research demonstrates the potential for data-driven methods to transform rotator cuff rehabilitation through personalized and evidence-based treatment plans. The results enhance clinical practice by enabling adaptive rehabilitation planning and show that machine learning can support decision-making in complex muscle activation analysis with strong performance and low latency.","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113416/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810609","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}

引用次数: 0

Recent Findings and Developments in Spine Biomechanics. 脊柱生物力学的最新发现和发展。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-21 DOI: 10.3390/bioengineering13040482

Christian Liebsch

引用次数: 0

An Effective Model-Based Voting Classifier for Diabetes Mellitus Classification. 一种有效的基于模型的投票分类器用于糖尿病分类。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-21 DOI: 10.3390/bioengineering13040480

Diyar Qader Zeebaree, Merdin Shamal Salih, Danial William Odeesho, Dilovan Asaad Zebari, Nechirvan Asaad Zebari, Omar I Dallal Bashi, Reving Masoud Abdulhakeem, Yahya Ahmed Yahya

{"title":"An Effective Model-Based Voting Classifier for Diabetes Mellitus Classification.","authors":"Diyar Qader Zeebaree, Merdin Shamal Salih, Danial William Odeesho, Dilovan Asaad Zebari, Nechirvan Asaad Zebari, Omar I Dallal Bashi, Reving Masoud Abdulhakeem, Yahya Ahmed Yahya","doi":"10.3390/bioengineering13040480","DOIUrl":"10.3390/bioengineering13040480","url":null,"abstract":"Diabetes mellitus is a health issue that is rapidly increasing worldwide, and it affects more than 347 million people globally. It is important to note that the disease can be successfully detected in its early stages, enabling physicians to avoid complications and improve patient outcomes. Despite the fact that machine learning (ML) has been extensively used in diabetes classification, the available solutions tend to place little or no emphasis on feature selection and ensembles, which limits prediction accuracy and generalizability. In this study, we introduce a hybrid framework that is based on three feature-selection algorithms, specifically, genetic algorithm (GA), correlation-based feature selection (CFS) and recursive feature elimination (RFE), in single and hybrid forms, and three classifiers, namely, multi-layer perceptron (MLP), support vector machine (SVM) and random forest (RF), to achieve a greater predictive robustness with the aid of soft voting. Experimental findings obtained from a benchmark diabetes dataset indicate that the RFE + CFS + SVM combination achieves the best performance, with an accuracy of 98.0%, sensitivity of 97.43%, specificity of 99.03%, precision of 99.51% and F1-score of 98.72%. These results indicate that the suggested hybrid feature-selection and ensemble learning model can offer a robust and highly effective approach for early-stage diabetes diagnosis, one which clinicians may use to make timely and accurate decisions.","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113906/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810495","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}

引用次数: 0

Nano-Enhanced Optical Delivery of Multi-Characteristic Opsin Gene for Spinal Optogenetic Modulation of Pain. 纳米增强光传递多特征视蛋白基因用于脊柱光遗传调节疼痛。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-20 DOI: 10.3390/bioengineering13040479

Darryl Narcisse, Robert Benkowski, Matthew Dwyer, Samarendra Mohanty

{"title":"Nano-Enhanced Optical Delivery of Multi-Characteristic Opsin Gene for Spinal Optogenetic Modulation of Pain.","authors":"Darryl Narcisse, Robert Benkowski, Matthew Dwyer, Samarendra Mohanty","doi":"10.3390/bioengineering13040479","DOIUrl":"10.3390/bioengineering13040479","url":null,"abstract":"Optogenetic modulation employs light-sensitive proteins known as opsins to regulate cellular activity. A unique therapeutic application of this technique involves modulating pain perception by selectively targeting neural pathways within the spinal cord. Multi-Characteristic Opsin (MCO) represents an innovative optogenetic actuator capable of activation across a broad spectrum of light wavelengths, exhibiting a slow depolarizing phase that resembles natural photoreceptors. This study examines the current advancements in spinal optogenetic modulation utilizing MCO for pain management. Due to its high sensitivity, MCO facilitates minimally invasive, remotely controlled optogenetic modulation of spinal neurons. This approach enables the regulation of extensive spatial regions, provided the MCO channel receives sufficient light intensity to surpass the activation threshold. Nano-enhanced optical delivery (NOD) successfully transfected spinal neurons with the GAD67-MCO2-mCherry construct, as confirmed by membrane-localized mCherry fluorescence with DAPI-labeled nuclei. Using this platform, 5 Hz spinal optogenetic stimulation produced a significant reduction in formalin-evoked pain behaviors, demonstrating frequency-specific modulation of spinal pain circuits. Neither 2 Hz nor 10 Hz stimulation yielded comparable analgesic effects, underscoring the importance of precise stimulation parameters. The therapeutic impact also depended on transfection efficiency: reducing the fGNR-plasmid concentration diminished MCO expression and weakened the analgesic response. Together, these results show that effective spinal optogenetic pain modulation requires both optimal stimulation frequency and robust gene delivery.","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113707/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810351","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}

引用次数: 0

Photoacoustic Imaging for Women's Gynecological Health: Advances and Clinical Prospects. 光声成像用于妇女妇科健康：进展和临床前景。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-18 DOI: 10.3390/bioengineering13040476

Panangattukara Prabhakaran Praveen Kumar, Dong-Kwon Lim, Taeho Kim

{"title":"Photoacoustic Imaging for Women's Gynecological Health: Advances and Clinical Prospects.","authors":"Panangattukara Prabhakaran Praveen Kumar, Dong-Kwon Lim, Taeho Kim","doi":"10.3390/bioengineering13040476","DOIUrl":"10.3390/bioengineering13040476","url":null,"abstract":"Photoacoustic imaging (PAI) is an emerging hybrid biomedical imaging modality that combines the high molecular contrast of optical excitation with the deep tissue penetration of ultrasound detection. This review presents recent advances in PAI-based techniques for the detection and characterization of gynecological diseases in women, with particular focus on endometriosis and uterine-related disorders. We summarize the application of PAI across preclinical and translational studies, highlighting progress in photoacoustic microscopy, spectroscopic photoacoustic imaging, and endoscopic and probe-based implementations for non-invasive, high-resolution tissue evaluation. The role of functional and contrast-enhanced PAI approaches is discussed, emphasizing their ability to enhance diagnostic sensitivity, enable longitudinal monitoring, and provide detailed information on vascular, biochemical, and structural tissue characteristics. Furthermore, the expanding applications of PAI in assessing uterine, cervical, and ovarian pathologies, including tumor detection and tissue remodeling, are reviewed. Finally, current challenges, limitations, and future directions toward clinical translation are addressed. Collectively, this review underscores the potential of photoacoustic imaging as a powerful, non-invasive platform for early diagnosis, disease monitoring, and improved management of women's health conditions.","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113919/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810395","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}

引用次数: 0

Robust Non-Invasive Cardiac Index Prediction via Feature Integration and Data-Augmented Neural Networks. 基于特征集成和数据增强神经网络的稳健无创心脏指数预测。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-18 DOI: 10.3390/bioengineering13040477

Chih-Hao Chang, Mei-Ling Chan, Yu-Hung Fang, Po-Lin Huang, Tsung-Yi Chen, Tsun-Kuang Chi, I Elizabeth Cha, Tzong-Rong Ger, Kuo-Chen Li, Shih-Lun Chen, Liang-Hung Wang, Jia-Ching Wang, Patricia Angela R Abu

{"title":"Robust Non-Invasive Cardiac Index Prediction via Feature Integration and Data-Augmented Neural Networks.","authors":"Chih-Hao Chang, Mei-Ling Chan, Yu-Hung Fang, Po-Lin Huang, Tsung-Yi Chen, Tsun-Kuang Chi, I Elizabeth Cha, Tzong-Rong Ger, Kuo-Chen Li, Shih-Lun Chen, Liang-Hung Wang, Jia-Ching Wang, Patricia Angela R Abu","doi":"10.3390/bioengineering13040477","DOIUrl":"10.3390/bioengineering13040477","url":null,"abstract":"Concurrent with the rising consumption of ultra-processed, high-calorie diets and the decline in physical activity, obesity and related cardiovascular conditions among young adults have continued to increase, becoming an important global public health concern. This study integrates non-invasive Internet of Things (IoT) sensing devices, including the TERUMO ES-P2000 blood pressure monitor (Terumo Corp., Tokyo, Japan) and the PhysioFlow PF07 Enduro cardiac hemodynamic analyzer (Manatec Biomedical, Poissy, France), with an artificial neural network (ANN) for cardiac index (CI) prediction. Through appropriate data preprocessing and model training strategies, the generalization ability and stability of the proposed CI prediction model were significantly enhanced. Experimental results demonstrate that, when using three physiological parameters as input, the ANN achieved a classification accuracy of 97.78%, substantially outperforming traditional approaches. Even under two-parameter input conditions, the model maintained strong predictive performance. These findings confirm the effectiveness and practical potential of the proposed framework for real-time, non-invasive CI assessment. Moreover, this research has received rigorous assessment and approval from the Institutional Review Board (IRB) under application number 202501987B0.","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113177/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810476","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}

引用次数: 0

Bioengineering Pancreatic Organoids and iPSC-Derived β-Cells for Diabetes: Materials, Devices, and Translational Challenges. 生物工程胰腺类器官和ipsc衍生β细胞用于糖尿病：材料，设备和转化挑战。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-18 DOI: 10.3390/bioengineering13040478

Abdullah Jabri, Mohamed Alsharif, Bader Taftafa, Tasnim Abbad, Dania Sibai, Abdulaziz Mhannayeh, Abdulrahman Elsalti, Islam M Saadeldin, Jahan Salma, Tanveer Ahmad Mir, Ahmed Yaqinuddin

{"title":"Bioengineering Pancreatic Organoids and iPSC-Derived β-Cells for Diabetes: Materials, Devices, and Translational Challenges.","authors":"Abdullah Jabri, Mohamed Alsharif, Bader Taftafa, Tasnim Abbad, Dania Sibai, Abdulaziz Mhannayeh, Abdulrahman Elsalti, Islam M Saadeldin, Jahan Salma, Tanveer Ahmad Mir, Ahmed Yaqinuddin","doi":"10.3390/bioengineering13040478","DOIUrl":"10.3390/bioengineering13040478","url":null,"abstract":"Diabetes mellitus is primarily caused by the loss or malfunction of insulin-producing β-cells, and although current therapies improve glycemic control, they do not restore physiologic insulin secretion. Advances in stem cell biology and organoid engineering have led to the development of pancreatic organoids and induced pluripotent stem cell (iPSC)-derived β-cells as promising platforms for disease modeling, drug testing, and regenerative medicine. Pancreatic organoids generated from ductal, acinar, or progenitor populations can recapitulate key anatomical and functional features of native pancreatic tissue, enabling studies of development, injury, and regeneration. In parallel, improvements in iPSC differentiation protocols have produced β-like cells capable of insulin secretion in response to glucose, although achieving full functional maturity remains a challenge. Bioengineering strategies, including biomaterial scaffolds, microfluidic platforms, endothelial co-culture systems, three-dimensional bioprinting, and CRISPR-based genome editing, have enhanced the stability, vascular compatibility, and functional performance of both organoid and iPSC-derived systems. Despite these advances, variability in differentiation efficiency, limited β-cell maturity, and poor long-term survival continue to hinder clinical translation. Together, pancreatic organoids and iPSC-derived β-cells represent complementary platforms that advance fundamental research and support the development of β-cell replacement therapies, with ongoing integration of bioengineering approaches expected to accelerate progress toward reproducible, scalable, and clinically relevant β-cell regeneration.","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13113633/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810617","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}

引用次数: 0

Efficient and Dynamically Consistent Joint Torque Estimation for Wearable Neurotechnology via Knowledge Distillation. 基于知识蒸馏的可穿戴神经技术关节力矩高效动态一致估计。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-17 DOI: 10.3390/bioengineering13040474

Shu Xu, Zheng Chang, Zenghui Ding, Xianjun Yang, Tao Wang, Dezhang Xu

{"title":"Efficient and Dynamically Consistent Joint Torque Estimation for Wearable Neurotechnology via Knowledge Distillation.","authors":"Shu Xu, Zheng Chang, Zenghui Ding, Xianjun Yang, Tao Wang, Dezhang Xu","doi":"10.3390/bioengineering13040474","DOIUrl":"10.3390/bioengineering13040474","url":null,"abstract":"Wearable neurotechnology depends critically on continuous movement monitoring to characterize motor impairment and recovery in real-world settings. While joint torque serves as a clinically essential kinetic marker, estimating it directly on-device from inertial signals remains challenging due to stringent computational, memory, and energy constraints. Lightweight pipelines typically omit computationally expensive time-frequency processing; however, this omission degrades the observability of dynamics encoded in 1D IMU signals and diminishes the effectiveness of standard knowledge distillation strategies. To enable reliable on-device torque inference, we propose a Physically Guided Dual-Consistency Knowledge Distillation (PDC-KD) framework that explicitly integrates biomechanical priors into the learning process through two collaborative pathways: parameter-manifold alignment and physics-guided compensation. The student network receives guidance through Fisher-information-weighted parameter transfer, ensuring robust knowledge distillation despite significant model capacity mismatch. Furthermore, the framework incorporates a physics-guided regularization term that enforces dynamically consistent torque trajectories via a numerically stable Cholesky-parameterized constraint. Experiments demonstrate that the student model preserves teacher-level predictive accuracy while operating within the stringent resource constraints of edge devices (achieving a 98% parameter reduction, ∼2× faster inference, and ∼1 ms latency). Moreover, the proposed method yields torque estimates with enhanced dynamical consistency, providing an efficient biosignal-processing solution for wearable neurotechnology platforms demanding real-time movement analytics.","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/PMC13113233/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810251","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}

引用次数: 0

Insight into Kidney Function and Microstructure Through Renal MRI-Review of the Literature. 通过肾脏mri研究肾脏功能和微观结构。

IF 3.7 3区医学

Bioengineering Pub Date : 2026-04-17 DOI: 10.3390/bioengineering13040470

Marcin Majos, Artur Klepaczko, Ilona Kurnatowska

{"title":"Insight into Kidney Function and Microstructure Through Renal MRI-Review of the Literature.","authors":"Marcin Majos, Artur Klepaczko, Ilona Kurnatowska","doi":"10.3390/bioengineering13040470","DOIUrl":"10.3390/bioengineering13040470","url":null,"abstract":"Chronic kidney disease (CKD) represents a growing medical, diagnostic and social challenge, and it is estimated to effect 8.5-9.8% of the global population and requires expensive modes of treatment, such as hemodialysis or renal transplants. Currently, a diagnosis of CKD is set based on the level of creatinine in the blood, which is the gold standard of renal function diagnostics. Unfortunately, decrease in GFR is secondary to damage of the kidney parenchyma and indicates that the best time to start more aggressive treatment has already passed. Therefore, several non-invasive methods have been proposed for predicting increased risk of CKD progression; however, in most of the cases kidney biopsy is essential. Currently, the greatest hopes for a method that can confirm CKD are associated with the development of MRI, the most tissue-specific imaging method, and it is already proven to be capable to detect inflammatory and edematous changes, fibrosis, as well as perfusion and oxygenation disturbances. Therefore, in our manuscript we decided to present up-to-date knowledge about kidney MRI from a clinical point of view.","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/PMC13113676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810443","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}

引用次数: 0