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Bioengineering
Volume 12
Issue 9
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Bioengineering, Volume 12, Issue 9 (September 2025) – 110 articles

Cover Story (view full-size image): Surface engineering and structural design are central to advancing total ankle arthroplasty (TAA). This review highlights biointegration strategies, including porous structures, surface modifications, and smart technologies. Architectures with 300–600 µm pores enable bone ingrowth and osseointegration, while functionally graded designs meet regional biomechanical needs. Surface modifications include bioactive coatings, topographical modifications, antimicrobial methods, and wear-resistant layers. Multifunctional approaches simultaneously target infection prevention, osseointegration, and durability. Emerging innovations, including biodegradable scaffolds, biomimetic nanotechnologies, and sensor-based monitoring systems, remain largely preclinical but show potential to establish TAA as a comprehensive alternative to arthrodesis. View this paper
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22 pages, 3356 KB  
Article
MS-LTCAF: A Multi-Scale Lead-Temporal Co-Attention Framework for ECG Arrhythmia Detection
by Na Feng, Chengwei Chen, Peng Du, Chengrong Gong, Jianming Pei and Dong Huang
Bioengineering 2025, 12(9), 1007; https://doi.org/10.3390/bioengineering12091007 - 22 Sep 2025
Viewed by 547
Abstract
Cardiovascular diseases are the leading cause of death worldwide, with arrhythmia being a prevalent and potentially fatal condition. The multi-lead electrocardiogram (ECG) is the primary tool for detecting arrhythmias. However, existing detection methods have shortcomings: they cannot dynamically integrate inter-lead correlations with multi-scale [...] Read more.
Cardiovascular diseases are the leading cause of death worldwide, with arrhythmia being a prevalent and potentially fatal condition. The multi-lead electrocardiogram (ECG) is the primary tool for detecting arrhythmias. However, existing detection methods have shortcomings: they cannot dynamically integrate inter-lead correlations with multi-scale temporal changes in cardiac electrical activity. They also lack mechanisms to simultaneously focus on key leads and time segments, and thus fail to address multi-lead redundancy or capture comprehensive spatial-temporal relationships. To solve these problems, we propose a Multi-Scale Lead-Temporal Co-Attention Framework (MS-LTCAF). Our framework incorporates two key components: a Lead-Temporal Co-Attention Residual (LTCAR) module that dynamically weights the importance of leads and time segments, and a multi-scale branch structure that integrates features of cardiac electrical activity across different time periods. Together, these components enable the framework to automatically extract and integrate features within a single lead, between different leads, and across multiple time scales from ECG signals. Experimental results demonstrate that MS-LTCAF outperforms existing methods. On the PTB-XL dataset, it achieves an AUC of 0.927, approximately 1% higher than the current optimal baseline model (DNN_zhu’s 0.918). On the LUDB dataset, it ranks first in terms of AUC (0.942), accuracy (0.920), and F1-score (0.745). Furthermore, the framework can focus on key leads and time segments through the co-attention mechanism, while the multi-scale branches help capture both the details of local waveforms (such as QRS complexes) and the overall rhythm patterns (such as RR intervals). Full article
(This article belongs to the Special Issue New Insights into Machine Learning and Biomedicine: Updates and Directions, 2nd Edition)
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31 pages, 920 KB  
Article
Relationship Between RAP and Multi-Modal Cerebral Physiological Dynamics in Moderate/Severe Acute Traumatic Neural Injury: A CAHR-TBI Multivariate Analysis
by Abrar Islam, Kevin Y. Stein, Donald Griesdale, Mypinder Sekhon, Rahul Raj, Francis Bernard, Clare Gallagher, Eric P. Thelin, Francois Mathieu, Andreas Kramer, Marcel Aries, Logan Froese and Frederick A. Zeiler
Bioengineering 2025, 12(9), 1006; https://doi.org/10.3390/bioengineering12091006 - 22 Sep 2025
Viewed by 574
Abstract
Background: The cerebral compliance (or compensatory reserve) index, RAP, is a critical yet underutilized physiological marker in the management of moderate-to-severe traumatic brain injury (TBI). While RAP offers promise as a continuous bedside metric, its broader cerebral physiological context remains partly understood. This [...] Read more.
Background: The cerebral compliance (or compensatory reserve) index, RAP, is a critical yet underutilized physiological marker in the management of moderate-to-severe traumatic brain injury (TBI). While RAP offers promise as a continuous bedside metric, its broader cerebral physiological context remains partly understood. This study aims to characterize the burden of impaired RAP in relation to other key components of cerebral physiology. Methods: Archived data from 379 moderate-to-severe TBI patients were analyzed using descriptive and threshold-based methods across three RAP states (impaired, intact/transitional, and exhausted). Agglomerative hierarchical clustering, principal component analysis, and kernel-based clustering were applied to explore multivariate covariance structures. Then, high-frequency temporal analyses, including vector autoregressive integrated moving average impulse response functions (VARIMA IRF), cross-correlation, and Granger causality, were performed to assess dynamic coupling between RAP and other physiological signals. Results: Impaired and exhausted RAP states were associated with elevated intracranial pressure (p = 0.021). Regarding AMP, impaired RAP was associated with elevated levels, while exhausted RAP was associated with reduced pulse amplitude (p = 3.94 × 10−9). These two RAP states were also associated with compromised autoregulation and diminished perfusion. Clustering analyses consistently grouped RAP with its constituent signals (ICP and AMP), followed by brain oxygenation parameters (brain tissue oxygenation (PbtO2) and regional cerebral oxygen saturation (rSO2)). Cerebral autoregulation (CA) indices clustered more closely with RAP under impaired autoregulatory states. Temporal analyses revealed that RAP exhibited comparatively stronger responses to ICP and arterial blood pressure (ABP) at 1-min resolution. Moreover, when comparing ICP-derived and near-infrared spectroscopy (NIRS)-derived CA indices, they clustered more closely to RAP, and RAP demonstrated greater sensitivity to changes in these ICP-derived CA indices in high-frequency temporal analyses. These trends remained consistent at lower temporal resolutions as well. Conclusion: RAP relationships with other parameters remain consistent and differ meaningfully across compliance states. Integrating RAP into patient trajectory modelling and developing predictive frameworks based on these findings across different RAP states can map the evolution of cerebral physiology over time. This approach may improve prognostication and guide individualized interventions in TBI management. Therefore, these findings support RAP’s potential as a valuable metric for bedside monitoring and its prospective role in guiding patient trajectory modeling and interventional studies in TBI. Full article
(This article belongs to the Special Issue Recent Advances in Machine Learning and Explainable Artificial Intelligence in Biomedical Data Mining, and Disease Diagnosis Frameworks)
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19 pages, 3042 KB  
Article
An Implicit Registration Framework Integrating Kolmogorov–Arnold Networks with Velocity Regularization for Image-Guided Radiation Therapy
by Pulin Sun, Chulong Zhang, Zhenyu Yang, Fang-Fang Yin and Manju Liu
Bioengineering 2025, 12(9), 1005; https://doi.org/10.3390/bioengineering12091005 - 22 Sep 2025
Viewed by 487
Abstract
In image-guided radiation therapy (IGRT), deformable image registration between computed tomography (CT) and cone beam computed tomography (CBCT) images remain challenging due to the computational cost of iterative algorithms and the data dependence of supervised deep learning methods. Implicit neural representation (INR) provides [...] Read more.
In image-guided radiation therapy (IGRT), deformable image registration between computed tomography (CT) and cone beam computed tomography (CBCT) images remain challenging due to the computational cost of iterative algorithms and the data dependence of supervised deep learning methods. Implicit neural representation (INR) provides a promising alternative, but conventional multilayer perceptron (MLP) might struggle to efficiently represent complex, nonlinear deformations. This study introduces a novel INR-based registration framework that models the deformation as a continuous, time-varying velocity field, parameterized by a Kolmogorov–Arnold Network (KAN) constructed using Jacobi polynomials. To our knowledge, this is the first integration of KAN into medical image registration, establishing a new paradigm beyond standard MLP-based INR. For improved efficiency, the KAN estimates low-dimensional principal components of the velocity field, which are reconstructed via inverse principal component analysis and temporally integrated to derive the final deformation. This approach achieves a ~70% improvement in computational efficiency relative to direct velocity field modeling while ensuring smooth and topology-preserving transformations through velocity regularization. Evaluation on a publicly available pelvic CT–CBCT dataset demonstrates up to 6% improvement in registration accuracy over traditional iterative methods and ~3% over MLP-based INR baselines, indicating the potential of the proposed method as an efficient and generalizable alternative for deformable registration. Full article
(This article belongs to the Special Issue Novel Imaging Techniques in Radiotherapy)
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11 pages, 5095 KB  
Article
Evaluation of Operator Variability and Validation of an AI-Assisted α-Angle Measurement System for DDH Using a Phantom Model
by Yusuke Ohashi, Tomohiro Shimizu, Hidenori Koyano, Yumejiro Nakamura, Daisuke Takahashi, Katsuhisa Yamada and Norimasa Iwasaki
Bioengineering 2025, 12(9), 1004; https://doi.org/10.3390/bioengineering12091004 - 22 Sep 2025
Viewed by 398
Abstract
Ultrasound examination using the Graf method is widely applied for early detection of developmental dysplasia of the hip (DDH), but intra- and inter-operator variability remains a limitation. This study aimed to quantify operator variability in hip ultrasound assessments and to validate an AI-assisted [...] Read more.
Ultrasound examination using the Graf method is widely applied for early detection of developmental dysplasia of the hip (DDH), but intra- and inter-operator variability remains a limitation. This study aimed to quantify operator variability in hip ultrasound assessments and to validate an AI-assisted system for automated α-angle measurement to improve reproducibility. Thirty participants of different experience levels, including trained clinicians, residents, and medical students, each performed six ultrasound scans on a standardized infant hip phantom. Examination time, iliac margin inclination, and α-angle measurements were analyzed to assess intra- and inter-operator variability. In parallel, an AI-based system was developed to automatically detect anatomical landmarks and calculate α-angles from static images and dynamic video sequences. Validation was conducted using the phantom model with a known α-angle of 70°. Clinicians achieved shorter examination times and higher reproducibility than residents and students, with manual measurements systematically underestimating the reference α-angle. Static AI produced closer estimates with greater variability, whereas dynamic AI achieved the highest accuracy (mean 69.2°) and consistency with narrower limits of agreement than manual measurements. These findings confirm substantial operator variability and demonstrate that AI-assisted dynamic ultrasound analysis can improve reproducibility and reliability in routine DDH screening. Full article
(This article belongs to the Special Issue Artificial Intelligence and Machine Learning in Spine Research)
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11 pages, 1040 KB  
Article
Purification and Characterization of Polyhydroxyalkanoate Synthase from Extremely Halophilic Archaeon Haloferax mediterranei: Key Enzyme of Biodegradable Plastic Synthesis
by Diya Alsafadi, Yomen Ghalawinji and Fawwaz I. Khalili
Bioengineering 2025, 12(9), 1003; https://doi.org/10.3390/bioengineering12091003 - 22 Sep 2025
Viewed by 1920
Abstract
The biosynthesis of polyhydroxyalkanoate (PHA) biopolymer is highly dependent on the activity of a key enzyme, PHA synthase (PhaC). The halophilic archaeon Haloferax mediterranei can accumulate large amounts of PHAs from different carbon sources under non-sterilized conditions. In this study, a PhaC enzyme [...] Read more.
The biosynthesis of polyhydroxyalkanoate (PHA) biopolymer is highly dependent on the activity of a key enzyme, PHA synthase (PhaC). The halophilic archaeon Haloferax mediterranei can accumulate large amounts of PHAs from different carbon sources under non-sterilized conditions. In this study, a PhaC enzyme from H. mediterranei was produced and subsequently partially purified by ion exchange chromatography. The protein was visualized by SDS-PAGE, with a subunit molecular mass of 56.4 kDa. The purified enzyme converts hydroxybutyryl CoA molecules into PHA, being optimally active at pH 10.0 and pH 8.0. The PhaC was thermoactive in the range of 30 °C to 70 °C, with maximum activity registered at 50 °C. The enzyme was confirmed to be haloalkaliphilic (active at pH > 7.0 and high salt concentration) and exhibit a degree of stability at 25 °C for 24 h. Full article
(This article belongs to the Special Issue Advances in Polyhydroxyalkanoate (PHA) Production, 5th Edition)
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12 pages, 835 KB  
Article
Laser Assisted (Er:YAG and Nd:YAG) Minimally Invasive Peri-Odontal Surgery in the Treatment of Intrabony Defects—A 12-Month Observational Randomized Clinical Trial
by Anna Skurska, Ewa Dolińska, Robert Milewski and Małgorzata Pietruska
Bioengineering 2025, 12(9), 1002; https://doi.org/10.3390/bioengineering12091002 - 22 Sep 2025
Viewed by 602
Abstract
Objectives: The objective of our study was to assess changes in the clinical and radiological parameters after modified minimally invasive surgical technique (M-MIST) in the treatment of intrabony periodontal defects with additional Er:YAG and Nd:YAG laser applications. Methods: Thirty-eight patients, each [...] Read more.
Objectives: The objective of our study was to assess changes in the clinical and radiological parameters after modified minimally invasive surgical technique (M-MIST) in the treatment of intrabony periodontal defects with additional Er:YAG and Nd:YAG laser applications. Methods: Thirty-eight patients, each presenting with a single vertical defect, were randomly assigned to either the test (M-MIST+Er:YAG+Nd:YAG) or the control group (M-MIST). Probing depth (PD) reduction, clinical attachment level (CAL) gain (primary outcomes of the study) were assessed prior to therapy and after 12 months following the surgical procedure. Results: Both methods led to statistically significant improvements in clinical (PD reduction and CAL gain) and radiological parameters. No statistical differences were observed between the groups at any time point assessed. At 12 months postoperatively, radiographic defect depth reduction was very similar in both groups. The radiographic defect width decrease was more pronounced in the control group. Conclusions: Results indicate that use of Er:YAG and Nd:YAG lasers combined with the M-MIST procedure and the conventional M-MIST procedure provides comparable clinical and radiological treatment outcomes. Full article
(This article belongs to the Special Issue Advances and Innovations in Wound Repair and Regeneration)
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20 pages, 3123 KB  
Article
Enhancing Melanoma Diagnosis in Histopathology with Deep Learning and Synthetic Data Augmentation
by Alex Rodriguez Alonso, Ana Sanchez Diez, Goikoane Cancho Galán, Rafael Ibarrola Altuna, Gonzalo Irigoyen Miró, Cristina Penas Lago, Mª Dolores Boyano López and Rosa Izu Belloso
Bioengineering 2025, 12(9), 1001; https://doi.org/10.3390/bioengineering12091001 - 21 Sep 2025
Viewed by 531
Abstract
Accurate diagnosis of melanoma using hematoxylin and eosin (H&E)-stained histological images is often challenged by the scarcity and imbalance of biomedical datasets, limiting the performance of deep learning models. This study investigates the impact of synthetic image generation, via generative adversarial networks (GAN), [...] Read more.
Accurate diagnosis of melanoma using hematoxylin and eosin (H&E)-stained histological images is often challenged by the scarcity and imbalance of biomedical datasets, limiting the performance of deep learning models. This study investigates the impact of synthetic image generation, via generative adversarial networks (GAN), on training automatic classifiers based on the ResNet-18 architecture. Two experimental setups were designed: one using only real images and another combining real images with synthetic ones of the melanocytic nevus class to balance the dataset. Models were trained and evaluated at resolutions up to 1024 × 1024 pixels, employing standard classification metrics and the Fréchet Inception Distance (FID) to assess the quality of the generated images. The results suggest that although mixed models do not consistently outperform those trained exclusively on real data, they achieve competitive performance, particularly in terms of specificity and reduction in false negatives. This study supports the use of synthetic data as a complementary tool in scenarios where the acquisition of new samples is limited and lays the groundwork for future research in conditional generation and synthesis of malignant samples. In our best-performing model (1024 × 1024 px, 50 epochs, mixed dataset), we achieved an accuracy of 96.00%, a specificity of 97.00%, and a reduction in false negatives from 80 to 75 cases compared with real-only training. These results highlight the potential of synthetic augmentation to improve clinically relevant outcomes, particularly in reducing missed melanoma diagnoses. Full article
(This article belongs to the Special Issue Artificial Intelligence for Computer-Aided Detection in Biomedical Applications)
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19 pages, 1719 KB  
Article
Evaluation of Measurement Errors in Rotational Stitching, One-Shot, and Slot-Scanning Full-Length Radiography
by Zhengliang Li, Jie Xia, Cong Wang, Zhemin Zhu, Fan Zhang, Tsung-Yuan Tsai, Zhenhong Zhu and Kai Yang
Bioengineering 2025, 12(9), 999; https://doi.org/10.3390/bioengineering12090999 - 19 Sep 2025
Viewed by 446
Abstract
Full-length radiography is essential for evaluating spinal deformities, limb length discrepancies, and preoperative planning in orthopedics, yet the measurement accuracy of different radiographic methods remains unclear. This phantom study compared the accuracy of rotational stitching, one-shot and slot-scanning full-length radiography across six radiographic [...] Read more.
Full-length radiography is essential for evaluating spinal deformities, limb length discrepancies, and preoperative planning in orthopedics, yet the measurement accuracy of different radiographic methods remains unclear. This phantom study compared the accuracy of rotational stitching, one-shot and slot-scanning full-length radiography across six radiographic systems in quantifying distances between anatomical landmarks. Measurement errors were statistically analyzed using appropriate nonparametric tests. The results demonstrated significant differences in measurement accuracy among the three methods (H (2) = 15.86, p < 0.001). Slot-scanning exhibited the highest accuracy, with a mean error of −1.19 ± 10.13 mm, while both rotational stitching and one-shot imaging showed greater systematic underestimation, with mean errors of −18.95 ± 13.77 mm and −15.32 ± 12.38 mm, respectively. These negative biases (approximately 1.9 cm and 1.5 cm) are clinically meaningful because, if unrecognized, they can alter mechanical axis estimation and alignment planning in procedures such as high tibial osteotomy (HTO). Post hoc analysis confirmed the superior accuracy of slot-scanning compared to the other two methods, while no significant difference was found between rotational stitching and one-shot imaging. These findings indicate that system choice substantially impacts measurement accuracy, supporting preferential use of slot-scanning when precise quantitative assessment is required. Full article
(This article belongs to the Special Issue Advanced Engineering Technologies in Orthopaedic Research)
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26 pages, 5057 KB  
Article
Rapamycin Mitigates Corneal Damage in a Mouse Model of Alkali Burn Injury
by Basanta Bhujel, Woojune Hur, Seorin Lee, Hun Lee, Ho Seok Chung and Jae Yong Kim
Bioengineering 2025, 12(9), 998; https://doi.org/10.3390/bioengineering12090998 - 19 Sep 2025
Viewed by 574
Abstract
Alkali burns to the cornea cause severe damage characterized by an intense inflammatory response driven by inflammatory cytokines, which orchestrate pathological processes, including neovascularization, fibrosis, apoptosis, abnormal cell proliferation, and disorganization of the extracellular matrix (ECM), often resulting in permanent vision impairment or [...] Read more.
Alkali burns to the cornea cause severe damage characterized by an intense inflammatory response driven by inflammatory cytokines, which orchestrate pathological processes, including neovascularization, fibrosis, apoptosis, abnormal cell proliferation, and disorganization of the extracellular matrix (ECM), often resulting in permanent vision impairment or loss. Rapamycin (RAPA), a well-known mTOR inhibitor with potent immunosuppressive activity and pleiotropic therapeutic effects, was investigated as a novel restorative modality for promoting corneal wound healing in a mouse model of alkali burn injury. Topical RAPA treatment significantly reduced clinical signs of inflammation and decreased the infiltration of F4/80+ macrophages and CD45+ leukocytes, along with suppressed expression of pro-inflammatory cytokines (TNF-α, IL-1β, IL-6, and IL-17A). RAPA also markedly downregulated angiogenic mediators, such as VEGF, and endothelial markers, like CD31, resulting in significant inhibition of neovascularization. Furthermore, it prevented fibrotic tissue formation and myofibroblast activation, as evidenced by reduced α-SMA levels, and attenuated pathological matrix remodeling through decreased MMP-9 expression. Notably, RAPA preserved epithelial barrier function by maintaining the tight junction protein ZO-1 and reduced both apoptotic cell death (TUNEL) and dysregulated proliferation (Ki67+), thereby preserving the functional and structural integrity of the cornea. In conclusion, RAPA represents a promising therapeutic candidate for managing severe corneal alkali burn injuries, with the potential to enhance corneal wound healing, minimize long-term complications, and protect visual function. Full article
(This article belongs to the Special Issue Bioengineering Strategies for Ophthalmic Diseases)
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22 pages, 6967 KB  
Article
ErisNet: A Deep Learning Model for Noise Reduction in CT Images
by Fabio Mattiussi, Francesco Magoga, Andrea Cozzi, Salvatore Ferraro, Gabrio Cadei, Chiara Martini, Svenja Leu, Ebticem Ben Khalifa, Alcide Alessandro Azzena, Marco Pileggi, Ermidio Rezzonico and Stefania Rizzo
Bioengineering 2025, 12(9), 997; https://doi.org/10.3390/bioengineering12090997 - 19 Sep 2025
Viewed by 668
Abstract
Background: ErisNet, a novel AI model to reduce noise in Computed Tomography images. Methods: We trained ErisNet on 23 post-mortem whole-body CT scans. We assessed the objective performance with mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) [...] Read more.
Background: ErisNet, a novel AI model to reduce noise in Computed Tomography images. Methods: We trained ErisNet on 23 post-mortem whole-body CT scans. We assessed the objective performance with mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) measure, visual information fidelity (VIF), edge preservation index (EPI) and noise variance (NV). We assessed the qualitative performance by six radiologists. To support the visual assessment, we placed circular regions of interest (ROI) in the vitreous body, brain, liver and spleen parenchyma and paravertebral muscle. Results: ErisNet achieved MSE 64.07 ± 46.81, PSNR 31.32 ± 3.69 dB, SSIM 0.93 ± 0.06, VIF 0.49 ± 0.09, EPI 0.97 ± 0.01 and NV 64.69 ± 46.80. The ROI analysis showed a reduction in noise: the SD of the HU decreased by 8% in the vitreous body (from 17.6 to 16.2 HU), by 18% in the brain parenchyma (from 18.85 to 15.40 HU) and by 15–19% in the liver, spleen and paravertebral muscle. The six radiologists confirmed these results by assigning high scores (scale from one to five): overall quality 4.5 ± 0.6, noise suppression/detail preservation 4.7 ± 0.5 and diagnostic confidence 4.8 ± 0.4 (p < 0.01). Conclusions: ErisNet improves the quality of CT images and shows strong potential for processing low-dose scans. Full article
(This article belongs to the Section Biosignal Processing)
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21 pages, 3884 KB  
Article
DSOF: A Rapid Method to Determine the Abundance of Microalgae and Methanotrophic Bacteria in Coculture Using a Combination of Differential Sedimentation, Optical Density, and Fluorescence
by Carlos Cartin-Caballero, Christophe Collet, Daniel Gapes, Peter A. Gostomski, Matthew B. Stott and Carlo R. Carere
Bioengineering 2025, 12(9), 1000; https://doi.org/10.3390/bioengineering12091000 - 19 Sep 2025
Viewed by 572
Abstract
Cocultivation of microalgae and aerobic methanotrophs represents an emerging biotechnology platform to produce high-protein biomass, yet quantifying individual species in mixed cultures remains challenging. Here, we present a rapid, low-cost method—differential sedimentation, optical density, and fluorescence (DSOF)—to determine the abundance of coculture members. [...] Read more.
Cocultivation of microalgae and aerobic methanotrophs represents an emerging biotechnology platform to produce high-protein biomass, yet quantifying individual species in mixed cultures remains challenging. Here, we present a rapid, low-cost method—differential sedimentation, optical density, and fluorescence (DSOF)—to determine the abundance of coculture members. DSOF exploits differences in cell size and pigment autofluorescence between the thermoacidophilic microalga and methanotrophic species Galdieria sp. RTK37.1 and Methylacidiphilum sp. RTK17.1, respectively, to selectively sediment algal cells and estimate population contributions via OD600 and phycocyanin fluorescence. Evaluation with model suspensions across a wide cell density range (0 ≤ [Galdieria]: ≤ 3.23 A.U., and 0 ≤ [Methylacidiphilum] ≤ 1.54 A.U.) showed strong agreement with known values, with most absolute errors < 0.1 A.U. and relative errors < 10% at moderate biomass levels. Application to live batch cocultures under microalga or methanotroph growth-suppressed conditions, and during simultaneous growth, demonstrated accurate tracking of population dynamics and revealed enhanced methanotroph growth in the presence of oxygenic microalgae. While DSOF accuracy decreases at very concentrated biomass (>2.0 A.U. for Galdieria) or under nitrogen-limiting conditions, the model provides a practical, scalable alternative to more complex, invasive or expensive techniques, enabling near real-time monitoring of microalgae–methanotroph cocultures. Full article
(This article belongs to the Special Issue Engineering Microalgal Systems for a Greener Future)
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21 pages, 8924 KB  
Article
Physicochemical and Mechanical Characterization of Two Self-Curing Composite Resins for Direct Provisional Prostheses
by Oscar Javier Valencia Blanco, Saray Fernández-Hernández, Hector de Llanos-Lanchares, Miquel Punset Fuste, José Angel Delgado García-Menocal, Javier Gil Mur and Aritza Brizuela Velasco
Bioengineering 2025, 12(9), 996; https://doi.org/10.3390/bioengineering12090996 - 18 Sep 2025
Viewed by 420
Abstract
In this experimental in vitro study, both the physicochemical and mechanical properties of two self-curing dental composites were compared: Structur 3 (based on Bis-GMA) and Visco III (based on Bis-EMA), which are used for the direct fabrication of temporary dental prostheses. The properties [...] Read more.
In this experimental in vitro study, both the physicochemical and mechanical properties of two self-curing dental composites were compared: Structur 3 (based on Bis-GMA) and Visco III (based on Bis-EMA), which are used for the direct fabrication of temporary dental prostheses. The properties evaluated included flexural strength, toughness, hydrophilicity (measured using the contact angle), density, microhardness, water absorption, and wear and scratch resistance. In terms of flexural strength, Structur 3 exhibited a higher value (127 ± 16 MPa) than Visco III (103 ± 25 MPa). In addition, the dental composite based on Bis-GMA showed a higher toughness (36.52 ± 9.20 mJ) compared to 16.55 ± 7.55 mJ for the dental composite based on Bis-EMA) and a greater displacement to fracture (2.50 ± 0.38 mm compared to 1.72 ± 0.38 mm). However, Visco III showed a higher microhardness (17.045 ± 0.93 HV0.5) compared to Structur 3 (8.10 ± 0.76 HV0.5) and a lower water absorption (11.2 ± 0.4 µg/mm3 compared to Structur 3). In wear tests, Structur 3 showed greater wear (0.047 ± 0.021 mm2 wear channel area) compared to Visco III (0.031 ± 0.013 mm2). Density analysis showed that Visco III is denser (1.5917 ± 0.006 g/cm3) than Structur 3 (1.324 ± 0.005 g/cm3). Fractography analysis showed that both dental composites exhibited brittle fractures. Contact angle tests revealed a similar hydrophilicity of both dental composites with values below 90°. These differences in properties may be influenced by the filler composition of the two dental composites, as Visco III contains macro-fillers with elements such as aluminum and barium, which increase radiopacity. The conclusion is that Visco III is preferable in terms of durability and resistance, while Structur 3 is more suitable for applications that require flexibility, such as in provisional prostheses with pontics or in situations that require high esthetic quality. Full article
(This article belongs to the Special Issue Applications of Biomaterials in Dental Medicine)
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18 pages, 2121 KB  
Article
Characterization of La2O3 Nanoparticles and Their Effects on Bacteria, Vero and MG63 Cells, and Zebrafish Development
by Jugal Kishore, Tharaka Srinatha Dunuwilla, Venkatagiri Krishnamoorthy Bupesh Raja, Stanley Abraham Louis, Lokesh Kumar Boopathy, Durai Saravanan, Mzia Zhvania and Manoj Gupta
Bioengineering 2025, 12(9), 995; https://doi.org/10.3390/bioengineering12090995 - 18 Sep 2025
Viewed by 484
Abstract
This study reports, for the first time, lanthanum oxide (La2O3) nanoparticles (NPs) that simultaneously suppress osteosarcoma MG63 cell proliferation and promote normal Vero cell viability, a dual effect not previously documented for La2O3 or similar metal [...] Read more.
This study reports, for the first time, lanthanum oxide (La2O3) nanoparticles (NPs) that simultaneously suppress osteosarcoma MG63 cell proliferation and promote normal Vero cell viability, a dual effect not previously documented for La2O3 or similar metal oxide NPs. Physico-chemical characterization revealed a unique needle-like morphology, cubic crystallinity, and dispersion stability in DMSO without acidic dispersants, properties that can influence cellular uptake, ROS modulation, and biocompatibility. Comprehensive characterization (fluorescence spectroscopy, particle size/zeta potential, Raman, XRD, TGA, ATR-FTIR, and TEM) confirmed structural stability and surface chemistry relevant to biological interactions.La2O3 NPs exhibited broad-spectrum antibacterial activity (Gram-positive Streptococcus pyogenes, Bacillus cereus; Gram-negative Escherichia coli, Pseudomonas aeruginosa) and strong enzymatic/non-enzymatic antioxidant capacity, supporting potential use in implant coatings and infection control. MTT assays demonstrated dose-dependent cytotoxicity in MG63 cells, with enhanced proliferation in Vero cells. In zebrafish embryos, developmental toxicity assays yielded an LC50 of 2.6 mg/mL higher (less toxic) than values reported for Ag NPs (~0.3–1 mg/mL) with normal development at lower concentrations and dose-dependent malformations (e.g., impaired somite formation and skeletal deformities) at higher doses. Collectively, these findings position La2O3 NPs as a multifunctional platform for oncology and regenerative medicine, uniquely combining selective anticancer activity, normal cell support, antimicrobial and antioxidant functions, and a defined developmental safety margin. Full article
(This article belongs to the Section Nanobiotechnology and Biofabrication)
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24 pages, 2792 KB  
Case Report
Acute and Subacute Effects of Session with the EXOPULSE Mollii Suit in a Multiple Sclerosis Patient: A Case Report
by Serena Filoni, Francesco Romano, Daniela Cardone, Roberta Palmieri, Alessandro Forte, Angelo Di Iorio, Rocco Salvatore Calabrò, Raffaello Pellegrino, Chiara Palmieri, Emanuele Francesco Russo, David Perpetuini and Arcangelo Merla
Bioengineering 2025, 12(9), 994; https://doi.org/10.3390/bioengineering12090994 - 18 Sep 2025
Viewed by 607
Abstract
Multiple sclerosis (MS) is a chronic neurological disease often resulting in motor and autonomic dysfunction. This case report investigates the acute and subacute effects of the EXOPULSE Mollii Suit (EMS), a wearable device capable of delivering transcutaneous electrical nerve stimulation to multiple anatomical [...] Read more.
Multiple sclerosis (MS) is a chronic neurological disease often resulting in motor and autonomic dysfunction. This case report investigates the acute and subacute effects of the EXOPULSE Mollii Suit (EMS), a wearable device capable of delivering transcutaneous electrical nerve stimulation to multiple anatomical regions, in a 43-year-old woman with MS. The patient underwent a clinical evaluation before the EMS treatment, during which central nervous system (CNS) and autonomic nervous system (ANS) responses were monitored using electroencephalography (EEG), heart rate variability (HRV), and infrared thermography (IRT). Immediately after the first EMS application, the clinical evaluation was repeated. The intervention continued at home for one month, followed by a post-treatment evaluation similar to the pre-intervention assessment. Functional evaluations showed improvements in sit-to-stand performance (from 8 s to 6 s), muscle tone (MAS scale for the right side from 3 to 2 and for the left side from 2 to 1), clonus, and spasticity (from 3 to 2). EEG results revealed decreased θ-band power (on average, from 0.394 to 0.253) and microstates’ reorganization. ANS activity modifications were highlighted by both HRV (e.g., RMSSD from 0.118 to 0.0837) and IRT metrics (e.g., nose tip temperature sample entropy from 0.090 to 0.239). This study provides the first integrated analysis of CNS and ANS responses to EMS in an MS patient, combining functional scales with multimodal instrumental measurements, emphasizing the possible advantages EMS for MS treatment. Although preliminary, these results demonstrated the potentiality of the EMS to deliver effective and personalized rehabilitative interventions for MS patients. Full article
(This article belongs to the Special Issue Current Trends in Robotic Rehabilitation Technology)
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9 pages, 1612 KB  
Article
Association of Spinopelvic Anatomy with the Level of Lumbar Disc Herniation
by Jannis Löchel, Moritz Hanisch, Justus Bürger, Kirsten Labbus and Robert Zahn
Bioengineering 2025, 12(9), 993; https://doi.org/10.3390/bioengineering12090993 - 18 Sep 2025
Viewed by 535
Abstract
Aim: The aim of this study was to investigate the association between the level of lumbar disc herniation (LDH) and individual spinopelvic anatomy. Material and methods: Spinopelvic parameters were retrospectively evaluated in 57 patients with symptomatic LDH at L4/5 and L5/S1 undergoing minimal [...] Read more.
Aim: The aim of this study was to investigate the association between the level of lumbar disc herniation (LDH) and individual spinopelvic anatomy. Material and methods: Spinopelvic parameters were retrospectively evaluated in 57 patients with symptomatic LDH at L4/5 and L5/S1 undergoing minimal invasive sequestrectomy at our institution. LDH was diagnosed in 23 patients at L5/S1 and in 34 patients at L4/5. Patients with further segment degeneration at the index level were excluded from the study. Results: Spinopelvic parameters between the two groups were significantly different. Patients with LDH at L5/S1 had statistically significant lower Pelvic Incidence (PI), Pelvic Tilt (PT), Relative Lumbar Lordosis (RLL) and PI-LL than patients with LDH at L4/5. C7 Sagittal Vertical Axis (C7SVA) was statistically significant lower in patients with LDH at L5/S1. Both groups had no sagittal imbalance. Patients with LDH at L5/S1 were significantly younger than patients with LDH at L4/5. There was a significant positive correlation between age and PT. We observed no significant differences for preoperative values of Lumar Lordosis (LL) and Sacral Slope between the two groups. Conclusions: This is the first study to reveal individual spinopelvic anatomy and, in particular, PI to be associated with the distinct level of LDH. These findings substantiate the biomechanical influence of the sagittal profile on the pathogenesis of LDH. Individual spinopelvic compensatory mechanisms were available independently of the patient’s age. Minimal invasive sequestrectomy is a reliable treatment for symptomatic LDH without further segment degeneration. Full article
(This article belongs to the Special Issue Spine Biomechanics)
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17 pages, 3106 KB  
Article
Weakly Supervised Gland Segmentation Based on Hierarchical Attention Fusion and Pixel Affinity Learning
by Yanli Liu, Mengchen Lin, Xiaoqian Sang, Guidong Bao and Yunfeng Wu
Bioengineering 2025, 12(9), 992; https://doi.org/10.3390/bioengineering12090992 - 18 Sep 2025
Viewed by 466
Abstract
Precise segmentation of glands in histopathological images is essential for the diagnosis of colorectal cancer, as the changes in gland morphology are associated with pathological progression. Conventional computer-assisted methods rely on dense pixel-level annotations, which are costly and labor-intensive to obtain. The present [...] Read more.
Precise segmentation of glands in histopathological images is essential for the diagnosis of colorectal cancer, as the changes in gland morphology are associated with pathological progression. Conventional computer-assisted methods rely on dense pixel-level annotations, which are costly and labor-intensive to obtain. The present study proposes a two-stage weakly supervised segmentation framework named Multi-Level Attention and Affinity (MAA). The MAA framework utilizes the image-level labels and combines the Multi-Level Attention Fusion (MAF) and Affinity Refinement (AR) modules. The MAF module extracts the hierarchical features from multiple transformer layers to grasp global semantic context, and generates more comprehensive initial class activation maps. By modeling inter-pixel semantic consistency, the AR module refines pseudo-labels, which can sharpen the boundary delineation and reduce label noise. The experiments on the GlaS dataset showed that the proposed MAA framework achieves the Intersection over Union (IoU) of 81.99% and Dice coefficient of 90.10%, which outperformed the state-of-the-art Online Easy Example Mining (OEEM) method with an improvement of 4.43% in IoU. Such experimental results demonstrated the effectiveness of integrating hierarchical attention mechanisms with affinity-guided refinement for annotation-efficient and robust gland segmentation. Full article
(This article belongs to the Special Issue Recent Progress in Biomedical Image Processing and Analysis)
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19 pages, 1124 KB  
Article
A Comparative Study on COVID-19 Dynamics: Mathematical Modeling, Predictions, and Resource Allocation Strategies in Romania, Italy, and Switzerland
by Cristina-Maria Stăncioi, Iulia Adina Ștefan, Violeta Briciu, Vlad Mureșan, Iulia Clitan, Mihail Abrudean, Mihaela-Ligia Ungureșan, Radu Miron, Ecaterina Stativă, Roxana Carmen Cordoș, Adriana Topan and Ioana Nanu
Bioengineering 2025, 12(9), 991; https://doi.org/10.3390/bioengineering12090991 - 18 Sep 2025
Viewed by 586
Abstract
This research provides valuable insights into the application of mathematical modeling to real-world scenarios, as exemplified by the COVID-19 pandemic. After data collection, the preparation stage included exploratory analysis, standardization and normalization, computation, and validation. A mathematical model initially developed for COVID-19 dynamics [...] Read more.
This research provides valuable insights into the application of mathematical modeling to real-world scenarios, as exemplified by the COVID-19 pandemic. After data collection, the preparation stage included exploratory analysis, standardization and normalization, computation, and validation. A mathematical model initially developed for COVID-19 dynamics in Romania was subsequently applied to data from Italy and Switzerland during the same time interval. The model is structured as a multiple-input single-output (MISO) system, where the inputs underwent a neural network-based training stage to address inconsistencies in the acquired data. In parallel, an ARMAX model was employed to capture the stochastic nature of the epidemic process. Results demonstrate that the Romanian-based model generalized effectively across the three countries, achieving a strong predictive accuracy (forecast accuracy > 98.59%). Importantly, the model maintained robust performance despite significant cross-country differences in testing strategies, policy measures, timing of initial cases, and imported infections. This work contributes a novel perspective by showing that a unified data-driven modeling framework can be transferable across heterogeneous contexts. More broadly, it underscores the potential of integrating mathematical modeling with predictive analytics to support evidence-based decision-making and strengthen preparedness for future global health crises. Full article
(This article belongs to the Special Issue Data Modeling and Algorithms in Biomedical Applications)
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14 pages, 505 KB  
Article
Experimental Setup for the Validation of Photoplethysmography Devices for the Evaluation of Arteriovenous Fistulas
by Simone Chiorboli, Adriano Brugnoli and Vincenzo Piemonte
Bioengineering 2025, 12(9), 990; https://doi.org/10.3390/bioengineering12090990 - 18 Sep 2025
Viewed by 547
Abstract
This study describes the design and validation of an experimental setup for testing photoplethysmographic (PPG) devices intended for the non-invasive monitoring of vascular accesses in hemodialysis patients. Continuous assessment of arteriovenous fistulas is essential to detect pathological conditions such as stenosis, which can [...] Read more.
This study describes the design and validation of an experimental setup for testing photoplethysmographic (PPG) devices intended for the non-invasive monitoring of vascular accesses in hemodialysis patients. Continuous assessment of arteriovenous fistulas is essential to detect pathological conditions such as stenosis, which can compromise patient safety and dialysis efficacy. While PPG-based sensors are capable of detecting such anomalies, their clinical applicability must be supported by controlled in vitro validation. The developed system replicates the anatomical, mechanical, optical, and hemodynamic features of vascular accesses. A 3D fistula model was designed and fabricated via 3D printing and silicone casting. The hydraulic circuit used red India ink and a PWM-controlled pump to simulate physiological blood flow, including stenotic conditions. Quantitative validation confirmed anatomical accuracy within 0.1 mm tolerance. The phantom exhibited an average Shore A hardness of 20.3 ± 1.1, a Young’s modulus of 10.4 ± 0.9 MPa, and a compression modulus of 105 MPa—values consistent with soft tissue behavior. Burst pressure exceeded 2000 mmHg, meeting ISO 7198:2016 standards. Flow rates (400–700 mL/min) showed <1% error. Compliance was 2.4 ± 0.2, and simulated blood viscosity was 3.9 ± 0.3 mPa·s. Systolic and diastolic pressures fell within physiological ranges. Photoplethysmographic signals acquired using a MAX30102 sensor (Analog devices Inc., Wilmington, MA, USA) reproduced key components of in vivo waveforms, confirming the system’s suitability for device testing. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
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21 pages, 1251 KB  
Review
Haptic Feedback Systems for Lower-Limb Prosthetic Applications: A Review of System Design, User Experience, and Clinical Insights
by Mohammadmahdi Karimi, Nashmin Yeganeh, Ivan Makarov, Atli Örn Sverrisson, Karl Fannar Gunnarsson, Kristín Briem, Sigurður Brynjólfsson, Árni Kristjánsson and Runar Unnthorsson
Bioengineering 2025, 12(9), 989; https://doi.org/10.3390/bioengineering12090989 - 18 Sep 2025
Viewed by 1715
Abstract
Systems presenting haptic information have emerged as an important technological advance in assisting individuals with sensory impairments or amputations, where the aim is to enhance sensory perception or provide sensory substitution through tactile feedback. These systems provide information on limb positioning, environmental interactions, [...] Read more.
Systems presenting haptic information have emerged as an important technological advance in assisting individuals with sensory impairments or amputations, where the aim is to enhance sensory perception or provide sensory substitution through tactile feedback. These systems provide information on limb positioning, environmental interactions, and gait events, significantly improving mobility in amputees and their confidence about using such devices. This review summarizes recent progress in haptic feedback systems by providing a comparative analysis of different feedback approaches, evaluating their clinical effectiveness and usability, tactile feedback system design, and user experience, while identifying key gaps in the literature. These insights can contribute to the advancement of more effective, user-centered haptic feedback systems tailored for lower limb prosthetics. The findings are aimed at guiding future research in designing adaptive, intuitive, and clinically viable feedback mechanisms, fostering the widespread implementation of haptic systems in both assistive and rehabilitative applications. Full article
(This article belongs to the Section Biomechanics and Sports Medicine)
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28 pages, 2185 KB  
Review
Biosensor-Integrated Tibial Components in Total Knee Arthroplasty: A Narrative Review of Innovations, Challenges, and Translational Frontiers
by Ahmed Nadeem-Tariq, Christopher J. Fang, Jeffrey Lucas Hii and Karen Nelson
Bioengineering 2025, 12(9), 988; https://doi.org/10.3390/bioengineering12090988 - 17 Sep 2025
Viewed by 686
Abstract
Background: The incorporation of biosensors into orthopedic implants, particularly tibial components in total knee arthroplasty (TKA), marks a new era in personalized joint replacement. These smart systems aim to provide real-time physiological and mechanical data, enabling dynamic postoperative monitoring and enhanced surgical precision. [...] Read more.
Background: The incorporation of biosensors into orthopedic implants, particularly tibial components in total knee arthroplasty (TKA), marks a new era in personalized joint replacement. These smart systems aim to provide real-time physiological and mechanical data, enabling dynamic postoperative monitoring and enhanced surgical precision. Objective: This narrative review synthesizes the current landscape of electrochemical biosensor-embedded tibial implants in TKA, exploring technical mechanisms, clinical applications, challenges, and future directions for translation into clinical practice. Methods: A comprehensive literature review was conducted across PubMed and Google Scholar. Articles were thematically categorized into technology design, integration strategies, preclinical and clinical evidence, regulatory frameworks, ethical considerations, and strategic recommendations. Findings were synthesized narratively and organized to support forward-looking system design. Results: Smart tibial implants have demonstrated feasibility in both bench and early clinical settings. Key advances include pressure-sensing intraoperative tools, inertial measurement units for remote gait tracking, and chemical biosensors for infection surveillance. However, the field remains limited by biological encapsulation, signal degradation, regulatory uncertainty, and data privacy challenges. Interdisciplinary design, standardized testing, translational funding, and ethical oversight are essential to scaling these innovations. Conclusions: Biosensor-enabled tibial components represent a promising convergence of orthopedics, electronics, and data science. By addressing the technological, biological, regulatory, and ethical gaps outlined herein, this field can transition from prototype to widespread clinical reality—offering new precision in arthroplasty care. Full article
(This article belongs to the Special Issue Total Joint Arthroplasty: Technical Developments and Applications, 2nd Edition)
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22 pages, 3254 KB  
Article
An Innovative Interactive Narrative Persona (INP) Approach for Virtual Reality-Based Dementia Tour Design (VDT) in Rehabilitation Contexts
by Yuk Ming Tang, Suet Yi Tse, Hoi Sze Chan, Ho Tung Yip, Hei Tung Cheung and Mohammed Woyeso Geda
Bioengineering 2025, 12(9), 987; https://doi.org/10.3390/bioengineering12090987 - 17 Sep 2025
Viewed by 710
Abstract
The rising prevalence of dementia has raised significant public concern globally. However, the level of understanding and assistance concerning people with dementia remains limited. This study investigates the impact of virtual reality (VR) on enhancing public awareness and empathy toward dementia. We developed [...] Read more.
The rising prevalence of dementia has raised significant public concern globally. However, the level of understanding and assistance concerning people with dementia remains limited. This study investigates the impact of virtual reality (VR) on enhancing public awareness and empathy toward dementia. We developed a Virtual Dementia Tour (VDT) designed to simulate the cognitive and sensory impairments associated with dementia while incorporating interactive decision-making elements. A total of 80 adults aged 18 years or older, residing in Hong Kong and with no personal or close family history of dementia or caregiving experience, were recruited for the study. Quantitative data were analyzed using paired and independent samples t-tests to assess the changes in the Dementia Attitudes Scale (DAS) scores before and after the intervention. The results indicate that the baseline awareness and understanding of dementia were low in both groups. However, participants who experienced the VDT showed significantly greater improvements in knowledge and empathy compared to the control group. The findings suggest that VR interventions can effectively promote dementia awareness, reduce stigma, and contribute to the development of dementia-friendly societies. This study contributes to the growing body of evidence supporting the use of VR as an innovative tool for advancing social awareness and empathy in public health education. Full article
(This article belongs to the Special Issue Innovative Approaches: Harnessing Virtual Reality for Assessment and Rehabilitation in Stroke and Aging-Related Disorders)
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27 pages, 3905 KB  
Article
Linking a Deep Learning Model for Concussion Classification with Reorganization of Large-Scale Brain Networks in Female Youth
by Julianne McLeod, Karun Thanjavur, Sahar Sattari, Arif Babul, D. T. Hristopulos and Naznin Virji-Babul
Bioengineering 2025, 12(9), 986; https://doi.org/10.3390/bioengineering12090986 - 17 Sep 2025
Viewed by 661
Abstract
Concussion, or mild traumatic brain injury, is a significant public health challenge, with females experiencing high rates and prolonged symptoms. Reliable and objective tools for early diagnosis are critically needed, particularly in pediatric populations, where subjective symptom reporting can be inconsistent and neurodevelopmental [...] Read more.
Concussion, or mild traumatic brain injury, is a significant public health challenge, with females experiencing high rates and prolonged symptoms. Reliable and objective tools for early diagnosis are critically needed, particularly in pediatric populations, where subjective symptom reporting can be inconsistent and neurodevelopmental factors may influence presentation. Five minutes of resting-state (RS) EEG data were collected from non-concussed and concussed females between 15 and 24 years of age. We first applied a deep learning approach to classify concussion directly from raw, RS electroencephalography (EEG) data. A long short-term memory (LSTM) recurrent neural network trained on the raw data achieved 84.2% accuracy and an ensemble median area under the receiver operating characteristic curve (AUC) of 0.904. To complement these results, we examined causal connectivity at the source level using information flow rate to explore potential network-level changes associated with concussion. Effective connectivity in the non-concussed cohort was characterized by a symmetric pattern along the central–parietal midline; in contrast, the concussed group showed a more posterior and left-lateralized pattern. These spatial distribution changes were accompanied by significantly higher connection magnitudes in the concussed group (p < 0.001). While these connectivity changes may not directly drive classification, they provide evidence of large-scale brain reorganization following concussion. Together, our results suggest that deep learning models can detect concussion with high accuracy, while connectivity analyses may offer complementary mechanistic insights. Future work with larger datasets is necessary to refine the model specificity, explore subgroup differences related to hormone cycle changes and symptoms, and incorporate data across different sports. Full article
(This article belongs to the Special Issue Machine Learning and Artificial Intelligence in Pediatric Healthcare)
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10 pages, 671 KB  
Article
A Safety Limit of the Number of Artificial Canals That Can Be Prepared by Two Rotary Endodontic Files Operated at Two Different Speeds: A Novel Approach
by Omar Alzahrani, Khalid Merdad, Tariq Abuhaimed, Zuhair S. Natto, Amna Y. Siddiqui and Osama S. Alothmani
Bioengineering 2025, 12(9), 985; https://doi.org/10.3390/bioengineering12090985 - 17 Sep 2025
Viewed by 450
Abstract
Utilizing a novel approach that concomitantly assessed cyclic fatigue and torsional overloading, we aimed to establish the maximum number of artificial canals that can be prepared by Hyflex EDM and NeoNiTi A1 operated at two different speeds until their separation. Forty-eight files were [...] Read more.
Utilizing a novel approach that concomitantly assessed cyclic fatigue and torsional overloading, we aimed to establish the maximum number of artificial canals that can be prepared by Hyflex EDM and NeoNiTi A1 operated at two different speeds until their separation. Forty-eight files were equally divided into four groups: (A) Hyflex EDM operated at 300 rotations per minute (RPM) and (B) at 500 RPM, and (C) NeoNiTi A1 at 300 RPM and (D) at 500 RPM. Files were used to completely shape 10 sequential artificial canals unless file separation occurred. Maximum number of canals prepared was noted and averaged. Fractography was conducted to determine the mechanism of file separation. Hyflex EDM prepared significantly more canals compared to NeoNiTi A1 (p = 0.008). When operated at 300 RPM, Hyflex EDM prepared significantly more canals compared to NeoNiTi A1 (p = 0.028), whereas no significant difference was observed when they were operated at 500 RPM (p = 0.116). One NeoNiTi file broke due to cyclic fatigue while another one separated due to torsional overloading. Hyflex EDM files showed signs of both mechanisms. Within the limitations of this study, one file safely prepared four to five canals before its fracture. There was a trend towards fewer prepared canals as the RPM increased. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
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12 pages, 5832 KB  
Article
The Influence of Reaming Velocity During Preparation of the Femoral Canal—An In Vitro Analysis of Two Straight Femoral Revision Stems with a Fluted Tapered Design
by Oliver E. Bischel, Jörn B. Seeger, Matthias K. Jung, Stefan Dörfler, Arnold J. Höppchen, Alexander Jahnke and Eike Jakubowitz
Bioengineering 2025, 12(9), 984; https://doi.org/10.3390/bioengineering12090984 - 16 Sep 2025
Viewed by 464
Abstract
Background: The use of tapered fluted revision stems has been shown to be reliable and safe. Primary stability is mandatory for a long-lasting fixation between bone and a prosthesis. Nevertheless, aseptic loosening due to insufficient primary stability occurs and may be related to [...] Read more.
Background: The use of tapered fluted revision stems has been shown to be reliable and safe. Primary stability is mandatory for a long-lasting fixation between bone and a prosthesis. Nevertheless, aseptic loosening due to insufficient primary stability occurs and may be related to technically improper preparation of the femoral canal. Instructions of manufacturers are heterogeneous regarding preparation of implant beds. Questions/Purposes: Does speed or the design of the reamer influence the accuracy of the implant bed and, consecutively, primary stability? Materials and Methods: A test foam with an elastic moduli and pressure resistance similar to that of cancellous bone was used. The medullary canal was prepared with the use of reamers of two different straight and tapered femoral revision devices. Three different rotational speeds were used for preparation. After preparation, primary stability was measured and fixating characteristics were derived. Results: Sufficient primary stability was achievable by all three preparation methods but fixating characteristics were different. Significantly higher micro-motions were detected near the tip of the prosthesis compared to those at all more proximal measuring points. Reaming with high velocity resulted in significantly higher micro-motions compared to that with mid- or low-speed burring. Conclusions: Different preparation methods may be one explanation for the range of reported survivorship data of the two devices with aseptic loosening as the end point. The precision of the implant bed and fixating characteristics were best after reaming with lower velocity. Superior but not significantly better fixation characteristics were achieved with the monobloc stem compared to those with the modular device. Full article
(This article belongs to the Special Issue Joint Biomechanics and Implant Design)
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10 pages, 1588 KB  
Article
Ocular Biometry and Refractive Prediction in Short Eyes: A Comparison of Two Swept-Source Optical Coherence Tomography-Based Biometers
by Jiyun Seong and Sang Beom Han
Bioengineering 2025, 12(9), 983; https://doi.org/10.3390/bioengineering12090983 - 16 Sep 2025
Viewed by 534
Abstract
Purpose: To compare the performance of two swept-source optical coherence tomography-based biometers in the measurement of ocular biometry and the prediction of postoperative refractive errors in eyes with short axial length (AL). Methods: A total of 48 eyes from 29 patients with AL [...] Read more.
Purpose: To compare the performance of two swept-source optical coherence tomography-based biometers in the measurement of ocular biometry and the prediction of postoperative refractive errors in eyes with short axial length (AL). Methods: A total of 48 eyes from 29 patients with AL ≤ 22 mm were included. AL, anterior chamber depth (ACD), keratometry (K), and lens thickness (LT) measured using the IOLMaster® 700 and ARGOS® before cataract surgery were compared. The refractive error prediction accuracy of the two devices was also compared. Results: This study included four men (7 eyes) and 25 women (41 eyes), with an average age of 70.7 ± 8.1 years (mean ± SD; range, 47–82 years). The two devices demonstrated good agreement in measurements of ocular biometry with high intraclass correlation coefficients (AL = 0.975; ACD = 0.957; K = 0.988; LT = 0.994). However, AL and ACD were significantly shorter when measured with the IOLMaster® 700 compared to the ARGOS® (p < 0.001 for both). There was no significant difference in mean absolute prediction errors between the two devices (p = 0.423). The IOLMaster® 700 showed a significantly lower mean prediction error than the ARGOS® (+0.12 ± 0.39 diopters vs. +0.20 ± 0.39 diopters, p = 0.006), although the difference was of limited clinical relevance. There were no significant differences in the percentages of eyes within ± 0.50 D (77.1% vs. 75.0%, p = 0.811) and ± 1.00 D (100% vs. 97.9%, p = 0.315) of the predicted refractive error. Conclusions: Although IOLMaster® 700 and ARGOS® showed good agreements in eyes with short AL, significant differences were observed in the measurements of AL and ACD. Both devices demonstrated good efficacy and comparable performance in predicting postoperative refractive errors. Full article
(This article belongs to the Special Issue Advances and Clinical Applications of Anterior Segment Imaging Techniques—2nd Edition)
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18 pages, 2082 KB  
Article
Anterior Mandibular Displacement in Growing Rats Enhances Growth—A 3D Analysis
by Efstratios Ferdianakis, Ioannis Lyros, Demetrios Halazonetis, Georgios Kanavakis, Paula Perlea, Zafeiroula Yfanti, Konstantina-Eleni Alexiou, Dafni Doukaki and Apostolos I. Tsolakis
Bioengineering 2025, 12(9), 982; https://doi.org/10.3390/bioengineering12090982 - 16 Sep 2025
Viewed by 452
Abstract
One of the most common malocclusions encountered in everyday practice by orthodontists is skeletal Class II malocclusion, namely a protrusion of the maxilla, a retrusion of the mandible or a combination of both. To correct it, many clinicians use functional devices that guide [...] Read more.
One of the most common malocclusions encountered in everyday practice by orthodontists is skeletal Class II malocclusion, namely a protrusion of the maxilla, a retrusion of the mandible or a combination of both. To correct it, many clinicians use functional devices that guide the mandible into a more forward position. This stimulates bone growth, correcting the skeletal discrepancy. Controversy exists as to whether these appliances accelerate the growth rate, helping the mandible reach its final size earlier, or whether the growth of the mandible is observed as a positive response to the stimuli. This study examined whether the protrusion of the mandible in rats accelerates the growth rate or increases the overall growth of the mandible in the long run. Relapse was also assessed by removing the appliance prior to the end of the experiment. Seventy-two four-week-old Wistar rats were used. The treatment group, which consisted of 36 rats, had a device fitted on their upper incisors that led to a protrusion of their mandible. The device, a bite-jumping appliance, consisted of an iron-cast inclined plane and was fitted for 24 h a day, inducing a 3.5 mm anterior protrusion and 3 mm inferior displacement of the mandible. The control group consisted of 36 rats that were fed the same soft diet as the treatment group. Both groups were divided into three subgroups. The first was sacrificed 30 days after the onset of the experiment, the second at 60 days, and the last subgroup had the appliance removed for 30 days and was sacrificed 90 days after the onset of the experiment. At the beginning of the experiment, as well as at each time interval prior to the sacrifice of the animals, the appliances were removed, and cone beam-computed tomography was performed on every animal. Linear measurements were made on each 3D scan, measuring the growth of the mandible. Measurements of mandibular growth were higher compared to the control group. For instance, Gonion-Menton was 1.18 mm higher on month 2 compared to month 1 in the control group, whereas the same measurement marked a 1.82 mm difference in the experimental group. Condylion–Menton on the same intervals marked a 0.84 mm difference in the control, whereas a 1.35 mm difference was noted in the experimental group. Given the results, true mandibular growth is achieved using functional appliances for Class II malocclusion correction in rats. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
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19 pages, 1418 KB  
Article
Development of the Direct Deuteration Method for Amino Acids and Characterization of Deuterated Tryptophan
by Chie Shibazaki, Haruki Sugiyama, Misaki Ueda, Takayuki Oku, Motoyasu Adachi, Zoë Fisher and Kazuhiro Akutsu-Suyama
Bioengineering 2025, 12(9), 981; https://doi.org/10.3390/bioengineering12090981 - 16 Sep 2025
Viewed by 895
Abstract
Proteins and peptides are vital biomolecules, and deuterated amino acids are increasingly applied in areas such as drug discovery, metabolic tracing, and neutron scattering studies. In this study, we performed deuteration on all 20 proteinogenic amino acids, including their side chains, and established [...] Read more.
Proteins and peptides are vital biomolecules, and deuterated amino acids are increasingly applied in areas such as drug discovery, metabolic tracing, and neutron scattering studies. In this study, we performed deuteration on all 20 proteinogenic amino acids, including their side chains, and established efficient methods for 13 amino acids. Using a Pt/C-catalyzed hydrogen–deuterium exchange reaction, the reaction parameters were optimized to achieve the selective and stable incorporation of deuterium. In addition, the resulting deuterated compounds, focusing on tryptophan, were characterized in order to assess their physicochemical properties. Because the deuteration reaction caused significant racemization of amino acids, deuterated D/L-tryptophan was isolated using a chiral separation method. Deuterated tryptophan characterization studies confirmed that the photostability was markedly enhanced by deuteration, whereas the acid stability showed no clear isotopic effect. The X-ray crystal structure analyses revealed minimal changes upon the hydrogen-to-deuterium substitution. These results provide a robust platform for the supply of deuterated amino acids, facilitating their application in drug development, structural analysis, and creation of advanced functional biomaterials. Full article
(This article belongs to the Special Issue Design and Synthesis of Functional Deuterated Biomaterials)
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27 pages, 2089 KB  
Article
Dementia and Heart Failure Classification Using Optimized Weighted Objective Distance and Blood Biomarker-Based Features
by Veerasak Noonpan, Supansa Chaising, Georgi Hristov and Punnarumol Temdee
Bioengineering 2025, 12(9), 980; https://doi.org/10.3390/bioengineering12090980 - 15 Sep 2025
Viewed by 487
Abstract
Dementia and heart failure are growing global health issues, exacerbated by aging populations and disparities in care access. Diagnosing these conditions often requires advanced equipment or tests with limited availability. A reliable tool distinguishing between the two conditions is essential, enabling more accurate [...] Read more.
Dementia and heart failure are growing global health issues, exacerbated by aging populations and disparities in care access. Diagnosing these conditions often requires advanced equipment or tests with limited availability. A reliable tool distinguishing between the two conditions is essential, enabling more accurate diagnoses and reducing misclassifications and inappropriate referrals. This study proposes a novel measurement, the optimized weighted objective distance (OWOD), a modified version of the weighted objective distance, for the classification of dementia and heart failure. The OWOD is designed to enhance model generalization through a data-driven approach. By enhancing objective class generalization, applying multi-feature distance normalization, and identifying the most significant features for classification—together with newly integrated blood biomarker features—the OWOD could strengthen the classification of dementia and heart failure. A combination of risk factors and proposed blood biomarkers (derived from 10,000 electronic health records at Chiang Rai Prachanukroh Hospital, Chiang Rai, Thailand), comprising 20 features, demonstrated the best OWOD classification performance. For model evaluation, the proposed OWOD-based classification method attained an accuracy of 95.45%, a precision of 96.14%, a recall of 94.70%, an F1-score of 95.42%, and an area under the receiver operating characteristic curve of 97.10%, surpassing the results obtained using other machine learning-based classification models (gradient boosting, decision tree, neural network, and support vector machine). Full article
(This article belongs to the Special Issue Application of Advanced Mathematical Techniques to Healthcare and Medicine)
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25 pages, 2304 KB  
Article
From Anatomy to Genomics Using a Multi-Task Deep Learning Approach for Comprehensive Glioma Profiling
by Akmalbek Abdusalomov, Sabina Umirzakova, Obidjon Bekmirzaev, Adilbek Dauletov, Abror Buriboev, Alpamis Kutlimuratov, Akhram Nishanov, Rashid Nasimov and Ryumduck Oh
Bioengineering 2025, 12(9), 979; https://doi.org/10.3390/bioengineering12090979 - 15 Sep 2025
Viewed by 775
Abstract
Background: Gliomas are among the most complex and lethal primary brain tumors, necessitating precise evaluation of both anatomical subregions and molecular alterations for effective clinical management. Methods: To find a solution to the disconnected nature of current bioimage analysis pipelines, where anatomical segmentation [...] Read more.
Background: Gliomas are among the most complex and lethal primary brain tumors, necessitating precise evaluation of both anatomical subregions and molecular alterations for effective clinical management. Methods: To find a solution to the disconnected nature of current bioimage analysis pipelines, where anatomical segmentation based on MRI and molecular biomarker prediction are done as separate tasks, we use here Molecular-Genomic and Multi-Task (MGMT-Net), a one deep learning scheme that carries out the task of the multi-modal MRI data without any conversion. MGMT-Net incorporates a novel Cross-Modality Attention Fusion (CMAF) module that dynamically integrates diverse imaging sequences and pairs them with a hybrid Transformer–Convolutional Neural Network (CNN) encoder to capture both global context and local anatomical detail. This architecture supports dual-task decoders, enabling concurrent voxel-wise tumor delineation and subject-level classification of key genomic markers, including the IDH gene mutation, the 1p/19q co-deletion, and the TERT gene promoter mutation. Results: Extensive validation on the Brain Tumor Segmentation (BraTS 2024) dataset and the combined Cancer Genome Atlas/Erasmus Glioma Database (TCGA/EGD) datasets demonstrated high segmentation accuracy and robust biomarker classification performance, with strong generalizability across external institutional cohorts. Ablation studies further confirmed the importance of each architectural component in achieving overall robustness. Conclusions: MGMT-Net presents a scalable and clinically relevant solution that bridges radiological imaging and genomic insights, potentially reducing diagnostic latency and enhancing precision in neuro-oncology decision-making. By integrating spatial and genetic analysis within a single model, this work represents a significant step toward comprehensive, AI-driven glioma assessment. Full article
(This article belongs to the Special Issue Mathematical Models for Medical Diagnosis and Testing)
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Article
PHSP-Net: Personalized Habitat-Aware Deep Learning for Multi-Center Glioblastoma Survival Prediction Using Multiparametric MRI
by Tianci Liu, Yao Zheng, Chengwei Chen, Jie Wei, Dong Huang, Yuefei Feng and Yang Liu
Bioengineering 2025, 12(9), 978; https://doi.org/10.3390/bioengineering12090978 - 15 Sep 2025
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Abstract
Background: Glioblastoma (GBM) is a highly aggressive and heterogeneous primary malignancy of the central nervous system, with a median overall survival (OS) of approximately 15 months. Achieving accurate and generalizable OS prediction across multi-center settings is essential for clinical application. Methods: We propose [...] Read more.
Background: Glioblastoma (GBM) is a highly aggressive and heterogeneous primary malignancy of the central nervous system, with a median overall survival (OS) of approximately 15 months. Achieving accurate and generalizable OS prediction across multi-center settings is essential for clinical application. Methods: We propose a Personalized Habitat-aware Survival Prediction Network (PHSP-Net) that integrates multiparametric MRI with an adaptive habitat partitioning strategy. The network combines deep convolutional feature extraction and interpretable visualization modules to perform patient-specific subregional segmentation and survival prediction. A total of 1084 patients with histologically confirmed WHO grade IV GBM from four centers (UPENN-GBM, UCSF-PDGM, LUMIERE and TCGA-GBM) were included. PHSP-Net was compared with conventional radiomics, habitat imaging models and ResNet10, with independent validation on two external cohorts. Results: PHSP-Net achieved an AUROC of 0.795 (95% CI: 0.731–0.852) in the internal validation set, and 0.707 and 0.726 in the LUMIERE and TCGA-GBM external test sets, respectively—outperforming both comparison models. Kaplan–Meier analysis revealed significant OS differences between predicted high- and low-risk groups (log-rank p < 0.05). Visualization analysis indicated that necrotic-region habitats were key prognostic indicators. Conclusions: PHSP-Net demonstrates high predictive accuracy, robust cross-center generalization and improved interpretability in multi-center GBM cohorts. By enabling personalized habitat visualization, it offers a promising non-invasive tool for prognostic assessment and individualized clinical decision making in GBM. Full article
(This article belongs to the Special Issue Modern Medical Imaging in Disease Diagnosis Applications)
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