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Bioengineering
Volume 12
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Bioengineering, Volume 12, Issue 1 (January 2025) – 94 articles

Cover Story (view full-size image): Mechanical forces influence cellular proliferation, differentiation, and tissue morphogenesis within the body. Their quantification is essential to comprehend the impact of these forces on living organisms. This study introduces a novel microdifferential pressure measurement device tailored for cellular-scale pressure assessments. The device comprises a glass substrate and a microchannel constructed of polydimethylsiloxane, polytetrafluoroethylene tubes, a glass capillary, and a microsyringe pump. This device obviates the need for electrical measurements, relying solely on the displacement of ultrapure water within the microchannel to assess the measurement of pressure within microcavities in living tissues and other areas requiring precise and localized pressure evaluations. View this paper
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24 pages, 17252 KiB  
Article
3D-Printing of Artificial Aortic Heart Valve Using UV-Cured Silicone: Design and Performance Analysis
by Atila Ertas, Erik Farley-Talamantes, Olkan Cuvalci and Ozhan Gecgel
Bioengineering 2025, 12(1), 94; https://doi.org/10.3390/bioengineering12010094 - 20 Jan 2025
Viewed by 361
Abstract
The advancement of medical 3D printing technology includes several enhancements, such as decreasing the length of surgical procedures and minimizing anesthesia exposure, improving preoperative planning, creating personalized replicas of tissues and bones specific to individual patients, bioprinting, and providing alternatives to human organ [...] Read more.
The advancement of medical 3D printing technology includes several enhancements, such as decreasing the length of surgical procedures and minimizing anesthesia exposure, improving preoperative planning, creating personalized replicas of tissues and bones specific to individual patients, bioprinting, and providing alternatives to human organ transplants. The range of materials accessible for 3D printing within the healthcare industry is significantly narrower when compared with conventional manufacturing techniques. Liquid silicone rubber (LSR) is characterized by its remarkable stability, outstanding biocompatibility, and significant flexibility, thus presenting substantial opportunities for manufacturers of medical devices who are engaged in 3D printing. The main objective of this study is to develop, refine, and assess a 3D printer that can employ UV-cured silicone for the fabrication of aortic heart valves. Additionally, the research aims to produce a 3D-printed silicone aortic heart valve and evaluate the feasibility of the final product. A two-level ANOVA experimental design was utilized to investigate the impacts of print speed, nozzle temperature, and layer height on the print quality of the aortic heart valve. The findings demonstrated that the 3D-printed heart valve’s UV-cured silicone functioned efficiently, achieving the target flow rates of 5 L/min and 7 L/min. Two distinct leaflet thicknesses (LT) of the heart valve, namely 0.8 mm and 1.6 mm, were also analyzed to simulate calcium deposition on the leaflets. Full article
(This article belongs to the Special Issue Innovations in Implantable Cardiac Devices: Design, Materials, and Performance)
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18 pages, 2253 KiB  
Systematic Review
Systematic Review and Meta-Analysis of Remineralizing Agents: Outcomes on White Spot Lesions
by Ana Josefina Monjarás-Ávila, Louis Hardan, Carlos Enrique Cuevas-Suárez, Norma Verónica Zavala Alonso, Miguel Ángel Fernández-Barrera, Carol Moussa, Jamal Jabr, Rim Bourgi and Youssef Haikel
Bioengineering 2025, 12(1), 93; https://doi.org/10.3390/bioengineering12010093 - 20 Jan 2025
Viewed by 365
Abstract
Dental caries is a widespread issue impacting global oral health. White spot lesions, the earliest stage of caries, compromise enamel’s esthetics and integrity. Remineralization therapies, both fluoride and non-fluoride based, aim to restore enamel, but limited comparative data exist on their effects on [...] Read more.
Dental caries is a widespread issue impacting global oral health. White spot lesions, the earliest stage of caries, compromise enamel’s esthetics and integrity. Remineralization therapies, both fluoride and non-fluoride based, aim to restore enamel, but limited comparative data exist on their effects on lesion depth and microhardness. Thus, the aim of this systematic review was to evaluate the efficacy of remineralizing agents on lesion depth and microhardness of human teeth. The literature search included the following five databases: PubMed, Web of Science, Scielo, SCOPUS, and EMBASE from the period 2012 to October 2022. Studies evaluating lesion depth and microhardness in human teeth after the application of a remineralizing agent were considered for review. The meta-analysis was performed using RevMan 5.4 (The Cochrane Collaboration, Copenhagen, Denmark). A random effect model was used to pool estimate of effect and its 95% confidence intervals (CIs) for surface microhardness and depth lesion. Subgroup analyses were performed considering the presence of fluoride or not in the remineralization agent. Thirty-three studies were included in the qualitative review. Of these, twenty-six studies were included in the meta-analysis. The main risks of bias associated with the studies included a lack of blinding of the test operator and failure to obtain sample size. To conclude, fluorinated agents are more effective in remineralizing artificially induced white spot lesion than non-fluoride remineralizing agents. Full article
(This article belongs to the Special Issue Recent Progress in Dental Biomaterials)
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31 pages, 1806 KiB  
Review
Emerging Strategies for Revascularization: Use of Cell-Derived Extracellular Vesicles and Artificial Nanovesicles in Critical Limb Ischemia
by Vijay Murali Ravi Mythili, Ramya Lakshmi Rajendran, Raksa Arun, Vasanth Kanth Thasma Loganathbabu, Danyal Reyaz, ArulJothi Kandasamy Nagarajan, Byeong-Cheol Ahn and Prakash Gangadaran
Bioengineering 2025, 12(1), 92; https://doi.org/10.3390/bioengineering12010092 - 20 Jan 2025
Viewed by 419
Abstract
Critical limb ischemia (CLI) poses a substantial and intricate challenge in vascular medicine, necessitating the development of innovative therapeutic strategies to address its multifaceted pathophysiology. Conventional revascularization approaches often fail to adequately address the complexity of CLI, necessitating the identification of alternative methodologies. [...] Read more.
Critical limb ischemia (CLI) poses a substantial and intricate challenge in vascular medicine, necessitating the development of innovative therapeutic strategies to address its multifaceted pathophysiology. Conventional revascularization approaches often fail to adequately address the complexity of CLI, necessitating the identification of alternative methodologies. This review explores uncharted territory beyond traditional therapies, focusing on the potential of two distinct yet interrelated entities: cell-derived extracellular vesicles (EVs) and artificial nanovesicles. Cell-derived EVs are small membranous structures naturally released by cells, and artificial nanovesicles are artificially engineered nanosized vesicles. Both these vesicles represent promising avenues for therapeutic intervention. They act as carriers of bioactive cargo, including proteins, nucleic acids, and lipids, that can modulate intricate cellular responses associated with ischemic tissue repair and angiogenesis. This review also assesses the evolving landscape of CLI revascularization through the unique perspective of cell-derived EVs and artificial nanovesicles. The review spans the spectrum from early preclinical investigations to the latest translational advancements, providing a comprehensive overview of the current state of research in this emerging field. These groundbreaking vesicle therapies hold immense potential for revolutionizing CLI treatment paradigms. Full article
(This article belongs to the Special Issue Innovations in Regenerative Therapy: Cell and Cell-Free Approaches)
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9 pages, 1502 KiB  
Article
Experimental Biomechanics of Neonatal Brachial Plexus Avulsion Injuries Using a Piglet Model
by Anita Singh, Kalyani Ghuge, Yashvy Patni and Sriram Balasubramanian
Bioengineering 2025, 12(1), 91; https://doi.org/10.3390/bioengineering12010091 - 20 Jan 2025
Viewed by 313
Abstract
Background: A brachial plexus avulsion occurs when the nerve root separates from the spinal cord during birthing trauma, such as shoulder dystocia or a difficult vaginal delivery. A complete paralysis of the affected levels occurs post-brachial plexus avulsion. Despite being reported in 10–20% [...] Read more.
Background: A brachial plexus avulsion occurs when the nerve root separates from the spinal cord during birthing trauma, such as shoulder dystocia or a difficult vaginal delivery. A complete paralysis of the affected levels occurs post-brachial plexus avulsion. Despite being reported in 10–20% of brachial plexus birthing injuries, it remains poorly diagnosed during the acute stages of injury, leading to poor intervention approaches. The poor diagnosis of brachial plexus avulsion injury can be attributed to the currently unavailable biomechanics of brachial plexus avulsion. While the biomechanical properties of neonatal brachial plexus are available, the forces required to avulse a neonatal brachial plexus remain unknown. Methods: This study aims to provide detailed biomechanics of the required forces and corresponding strains for neonatal brachial plexus avulsion. Biomechanical tensile testing was performed on an isolated, clinically relevant piglet spinal cord and brachial plexus complex, and the required avulsion forces and strains were measured. Results: The reported failure forces and corresponding strains were 3.9 ± 1.6 N at a 27.9 ± 6.5% strain, respectively. Conclusion: The obtained data are required to understand the avulsion injury biomechanics and provide the necessary experimental data for computational model development that serves as an ideal surrogate for understanding complicated birthing injuries in newborns. Full article
(This article belongs to the Special Issue Biomechanics Analysis in Tissue Engineering)
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14 pages, 3635 KiB  
Article
Precision Imaging for Early Detection of Esophageal Cancer
by Po-Chun Yang, Chien-Wei Huang, Riya Karmakar, Arvind Mukundan, Tsung-Hsien Chen, Chu-Kuang Chou, Kai-Yao Yang and Hsiang-Chen Wang
Bioengineering 2025, 12(1), 90; https://doi.org/10.3390/bioengineering12010090 - 20 Jan 2025
Viewed by 489
Abstract
Early detection of early-stage esophageal cancer (ECA) is crucial for timely intervention and improved treatment outcomes. Hyperspectral imaging (HSI) and artificial intelligence (AI) technologies offer promising avenues for enhancing diagnostic accuracy in this context. This study utilized a dataset comprising 3984 white light [...] Read more.
Early detection of early-stage esophageal cancer (ECA) is crucial for timely intervention and improved treatment outcomes. Hyperspectral imaging (HSI) and artificial intelligence (AI) technologies offer promising avenues for enhancing diagnostic accuracy in this context. This study utilized a dataset comprising 3984 white light images (WLIs) and 3666 narrow-band images (NBIs). We employed the Yolov5 model, a state-of-the-art object detection algorithm, to predict early ECA based on the provided images. The dataset was divided into two subsets: RGB-WLIs and NBIs, and four distinct models were trained using these datasets. The experimental results revealed that the prediction performance of the training model was notably enhanced when using HSI compared to general NBI training. The HSI training model demonstrated an 8% improvement in accuracy, along with a 5–8% enhancement in precision and recall measures. Notably, the model trained with WLIs exhibited the most significant improvement. Integration of HSI with AI technologies improves the prediction performance for early ECA detection. This study underscores the potential of deep learning identification models to aid in medical detection research. Integrating these models with endoscopic diagnostic systems in healthcare settings could offer faster and more accurate results, thereby improving overall detection performance. Full article
(This article belongs to the Special Issue Machine Learning and Deep Learning Applications in Healthcare)
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17 pages, 4281 KiB  
Article
Release Profile and Antibacterial Activity of Thymus sibthorpii Essential Oil-Incorporated, Optimally Stabilized Type I Collagen Hydrogels
by Caglar Ersanli, Ioannis Skoufos, Konstantina Fotou, Athina Tzora, Yves Bayon, Despoina Mari, Eleftheria Sarafi, Konstantina Nikolaou and Dimitrios I. Zeugolis
Bioengineering 2025, 12(1), 89; https://doi.org/10.3390/bioengineering12010089 - 19 Jan 2025
Viewed by 349
Abstract
Antimicrobial resistance is one of the drastically increasing major global health threats due to the misuse and overuse of antibiotics as traditional antimicrobial agents, which render urgent the need for alternative and safer antimicrobial agents, such as essential oils (EOs). Although the strong [...] Read more.
Antimicrobial resistance is one of the drastically increasing major global health threats due to the misuse and overuse of antibiotics as traditional antimicrobial agents, which render urgent the need for alternative and safer antimicrobial agents, such as essential oils (EOs). Although the strong antimicrobial activity of various EOs has already been studied and revealed, their characteristic high sensitivity and volatility drives the need towards a more efficient drug administration method via a biomaterial system. Herein, the potential of Thymus sibthorpii EO incorporated in functionalized antibacterial collagen hydrogels was investigated. At first, the optimally stabilized type I collagen hydrogels via six different multi-arm poly (ethylene glycol) succinimidyl glutarate (starPEG) crosslinkers were determined by assessing the free amine content and the resistance to enzymatic degradation. Subsequently, 0.5, 1, and 2% v/v of EO were incorporated into optimized collagen hydrogels, and the release profile, as well as release kinetics, were studied. Finally, biomaterial cytocompatibility tests were performed. Thymus sibthorpii EO was released from the hydrogel matrix via Fickian diffusion and showed sustained release and 0.5% v/v EO-loaded hydrogels showed adequate antibacterial activity against Staphylococcus aureus and did not show any statistically significant difference compared to penicillin (p < 0.05). Moreover, none of the fabricated composite antibacterial scaffolds displayed any cytotoxicity on NIH-3T3 fibroblasts. In conclusion, this work presents an innovative antibacterial biomaterial system for tissue engineering applications, which could serve as a promising alternative to antibiotics, contributing to coping with the issue of antimicrobial resistance. Full article
(This article belongs to the Special Issue Fabrication of Biomaterials to Develop Tissue Engineering Scaffolds and Medical Devices)
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31 pages, 2973 KiB  
Article
Metagenomic Insights into Pollutants in Biorefinery and Dairy Wastewater: rDNA Dominance and Electricity Generation in Double Chamber Microbial Fuel Cells
by Khaya Pearlman Shabangu, Manimagalay Chetty and Babatunde Femi Bakare
Bioengineering 2025, 12(1), 88; https://doi.org/10.3390/bioengineering12010088 - 19 Jan 2025
Viewed by 437
Abstract
This study evaluates the potential of biorefinery and dairy wastewater as substrates for electricity generation in double chamber Microbial Fuel Cells (DCMFC), focusing on their microbial taxonomy and electrochemical viability. Taxonomic analysis using 16S/18S rDNA-targeted DGGE and high-throughput sequencing identified Proteobacteria as dominant [...] Read more.
This study evaluates the potential of biorefinery and dairy wastewater as substrates for electricity generation in double chamber Microbial Fuel Cells (DCMFC), focusing on their microbial taxonomy and electrochemical viability. Taxonomic analysis using 16S/18S rDNA-targeted DGGE and high-throughput sequencing identified Proteobacteria as dominant in biorefinery biomass, followed by Firmicutes and Bacteriodota. In dairy biomass, Lactobacillus (77.36%) and Clostridium (15.70%) were most prevalent. Biorefinery wastewater exhibited the highest bioelectrochemical viability due to its superior electrical conductivity and salinity, achieving a voltage yield of 65 mV, compared to 75.2 mV from mixed substrates and 1.7 mV from dairy wastewater. Elevated phosphate levels in dairy wastewater inhibited bioelectrochemical processes. This study recommends Biorefinery wastewater as the most suitable purely organic substrate for efficient bioelectricity generation and scaling up of MFCs, emphasising the importance of substrate selection for optimal energy output for practical and commercial viability. Full article
(This article belongs to the Special Issue Development of Bioelectrochemical Systems for Environmental Engineering)
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17 pages, 3709 KiB  
Article
Constraint of Different Knee Implant Designs Under Anterior–Posterior Shear Forces and Internal–External Rotation Moments in Human Cadaveric Knees
by Saskia A. Brendle, Sven Krueger, Joachim Grifka, Peter E. Müller, William M. Mihalko, Berna Richter and Thomas M. Grupp
Bioengineering 2025, 12(1), 87; https://doi.org/10.3390/bioengineering12010087 - 19 Jan 2025
Viewed by 261
Abstract
Instability remains one of the most common indications for revision after total knee arthroplasty. To gain a better understanding of how an implant will perform in vivo and support surgeons in selecting the most appropriate implant design for an individual patient, it is [...] Read more.
Instability remains one of the most common indications for revision after total knee arthroplasty. To gain a better understanding of how an implant will perform in vivo and support surgeons in selecting the most appropriate implant design for an individual patient, it is crucial to evaluate the implant constraint within clinically relevant ligament and boundary conditions. Therefore, this study investigated the constraint of three different implant designs (symmetrical implants with and without a post-cam mechanism and an asymmetrical medial-stabilized implant) under anterior–posterior shear forces and internal–external rotation moments at different flexion angles in human cadaveric knees using a six-degrees-of-freedom joint motion simulator. Both symmetrical designs showed no significant differences between the anterior–posterior range of motion of the medial and lateral condyles. In contrast, the medial-stabilized implant exhibited less anterior–posterior translation medially than laterally, without constraining the medial condyle to a fixed position. Furthermore, the post-cam implant design showed a significantly more posterior position of the femoral condyles in flexion compared to the other designs. The results show that despite the differences in ligament situations and individual implant positioning, specific characteristics of each implant design can be identified, reflecting the different geometries of the implant components. Full article
(This article belongs to the Special Issue Joint Biomechanics and Implant Design)
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21 pages, 3106 KiB  
Article
LiveDrive AI: A Pilot Study of a Machine Learning-Powered Diagnostic System for Real-Time, Non-Invasive Detection of Mild Cognitive Impairment
by Firas Al-Hindawi, Peter Serhan, Yonas E. Geda, Francis Tsow, Teresa Wu and Erica Forzani
Bioengineering 2025, 12(1), 86; https://doi.org/10.3390/bioengineering12010086 - 17 Jan 2025
Viewed by 306
Abstract
Alzheimer’s disease (AD) represents a significant global health issue, affecting over 55 million individuals worldwide, with a progressive impact on cognitive and functional abilities. Early detection, particularly of mild cognitive impairment (MCI) as an indicator of potential AD onset, is crucial yet challenging, [...] Read more.
Alzheimer’s disease (AD) represents a significant global health issue, affecting over 55 million individuals worldwide, with a progressive impact on cognitive and functional abilities. Early detection, particularly of mild cognitive impairment (MCI) as an indicator of potential AD onset, is crucial yet challenging, given the limitations of current diagnostic biomarkers and the need for non-invasive, accessible tools. This study aims to address these gaps by exploring driving performance as a novel, non-invasive biomarker for MCI detection. Using the LiveDrive AI system, equipped with multimodal sensing (MMS) technology and a driving performance assessment strategy, the proposed work analyzes the predictive capacity of driving patterns in indicating cognitive decline. Machine learning models, trained on an expert-annotated in-house dataset, were employed to detect MCI status from driving performance. Key findings demonstrate the feasibility of using nuanced driving features, such as velocity and acceleration during turning, as indicators of cognitive decline. This approach holds promise for integration into smartphone or car applications, enabling real-time, continuous cognitive health monitoring. The implications of this work suggest a transformative step towards scalable, real-world solutions for early AD diagnosis, with the potential to improve patient outcomes and disease management. Full article
(This article belongs to the Special Issue Applications of AI in Biomedical Engineering for Healthy Ageing)
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24 pages, 7392 KiB  
Article
Weakly Supervised Nuclei Segmentation with Point-Guided Attention and Self-Supervised Pseudo-Labeling
by Yapeng Mo, Lijiang Chen, Lingfeng Zhang and Qi Zhao
Bioengineering 2025, 12(1), 85; https://doi.org/10.3390/bioengineering12010085 - 17 Jan 2025
Viewed by 372
Abstract
Due to the labor-intensive manual annotations for nuclei segmentation, point-supervised segmentation based on nuclei coordinate supervision has gained recognition in recent years. Despite great progress, two challenges hinder the performance of weakly supervised nuclei segmentation methods: (1) The stable and effective segmentation of [...] Read more.
Due to the labor-intensive manual annotations for nuclei segmentation, point-supervised segmentation based on nuclei coordinate supervision has gained recognition in recent years. Despite great progress, two challenges hinder the performance of weakly supervised nuclei segmentation methods: (1) The stable and effective segmentation of adjacent cell nuclei remains an unresolved challenge. (2) Existing approaches rely solely on initial pseudo-labels generated from point annotations for training, and inaccurate labels may lead the model to assimilate a considerable amount of noise information, thereby diminishing performance. To address these issues, we propose a method based on center-point prediction and pseudo-label updating for precise nuclei segmentation. First, we devise a Gaussian kernel mechanism that employs multi-scale Gaussian masks for multi-branch center-point prediction. The generated center points are utilized by the segmentation module to facilitate the effective separation of adjacent nuclei. Next, we introduce a point-guided attention mechanism that concentrates the segmentation module’s attention around authentic point labels, reducing the noise impact caused by pseudo-labels. Finally, a label updating mechanism based on the exponential moving average (EMA) and k-means clustering is introduced to enhance the quality of pseudo-labels. The experimental results on three public datasets demonstrate that our approach has achieved state-of-the-art performance across multiple metrics. This method can significantly reduce annotation costs and reliance on clinical experts, facilitating large-scale dataset training and promoting the adoption of automated analysis in clinical applications. Full article
(This article belongs to the Section Biosignal Processing)
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33 pages, 10768 KiB  
Article
Analysis of Connectivity in Electromyography Signals to Examine Neural Correlations in the Activation of Lower Leg Muscles for Postural Stability: A Pilot Study
by Gordon Alderink, Diana McCrumb, David Zeitler and Samhita Rhodes
Bioengineering 2025, 12(1), 84; https://doi.org/10.3390/bioengineering12010084 - 17 Jan 2025
Viewed by 420
Abstract
In quiet standing, the central nervous system implements a pre-programmed ankle strategy of postural control to maintain upright balance and stability. This strategy comprises a synchronized common neural drive delivered to synergistically grouped muscles. This study evaluated connectivity between EMG signals of the [...] Read more.
In quiet standing, the central nervous system implements a pre-programmed ankle strategy of postural control to maintain upright balance and stability. This strategy comprises a synchronized common neural drive delivered to synergistically grouped muscles. This study evaluated connectivity between EMG signals of the unilateral and bilateral homologous muscle pairs of the lower legs during various standing balance conditions using magnitude-squared coherence (MSC). The leg muscles examined included the right and left tibialis anterior (TA), medial gastrocnemius (MG), and soleus (S). MSC is a frequency domain measure that quantifies the linear phase relation between two signals and was analyzed in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–100 Hz) neural frequency bands for feet together and feet tandem, with eyes open and eyes closed conditions. Results showed that connectivity in the beta and lower and upper gamma bands (30–100 Hz) was influenced by standing balance conditions and was indicative of a neural drive originating from the motor cortex. Instability was evaluated by comparing less stable standing conditions with a baseline—eyes open feet together stance. Changes in connectivity in the beta and gamma bands were found to be most significant in the muscle pairs of the back leg during a tandem stance regardless of dominant foot placement. MSC identified the MG:S muscle pair as significant for the right and left leg. The results of this study provided insight into the neural mechanism of postural control. Full article
(This article belongs to the Special Issue Engineering Neural Motor Control: From Mechanisms to Neural Interfaces)
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15 pages, 2024 KiB  
Article
Manipulating Intracellular Oxidative Conditions to Enhance Porphyrin Production in Escherichia coli
by Bahareh Arab, Murray Moo-Young, Yilan Liu and C. Perry Chou
Bioengineering 2025, 12(1), 83; https://doi.org/10.3390/bioengineering12010083 - 17 Jan 2025
Viewed by 360
Abstract
Being essential intermediates for the biosynthesis of heme, chlorophyll, and several other biologically critical compounds, porphyrins have wide practical applications. However, up till now, their bio-based production remains challenging. In this study, we identified potential metabolic factors limiting the biosynthesis of type-III stereoisomeric [...] Read more.
Being essential intermediates for the biosynthesis of heme, chlorophyll, and several other biologically critical compounds, porphyrins have wide practical applications. However, up till now, their bio-based production remains challenging. In this study, we identified potential metabolic factors limiting the biosynthesis of type-III stereoisomeric porphyrins in Escherichia coli. To alleviate this limitation, we developed bioprocessing strategies by redirecting more dissimilated carbon flux toward the HemD-enzymatic pathway to enhance the production of type-III uroporphyrin (UP-III), which is a key precursor for heme biosynthesis. Our approaches included the use of antioxidant reagents and strain engineering. Supplementation with ascorbic acid (up to 1 g/L) increased the UP-III/UP-I ratio from 0.62 to 2.57. On the other hand, overexpression of ROS-scavenging genes such as sod- and kat-genes significantly enhanced UP production in E. coli. Notably, overexpression of sodA alone led to a 72.9% increase in total porphyrin production (1.56 g/L) while improving the UP-III/UP-I ratio to 1.94. Our findings highlight the potential of both antioxidant supplementation and strain engineering to mitigate ROS-induced oxidative stress and redirect more dissimilated carbon flux toward the biosynthesis of type-III porphyrins in E. coli. This work offers an effective platform to enhance the bio-based production of porphyrins. Full article
(This article belongs to the Special Issue From Residues to Bio-Based Products through Bioprocess Engineering)
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28 pages, 11306 KiB  
Article
Biomarker Investigation Using Multiple Brain Measures from MRI Through Explainable Artificial Intelligence in Alzheimer’s Disease Classification
by Davide Coluzzi, Valentina Bordin, Massimo W. Rivolta, Igor Fortel, Liang Zhan, Alex Leow and Giuseppe Baselli
Bioengineering 2025, 12(1), 82; https://doi.org/10.3390/bioengineering12010082 - 17 Jan 2025
Viewed by 607
Abstract
As the leading cause of dementia worldwide, Alzheimer’s Disease (AD) has prompted significant interest in developing Deep Learning (DL) approaches for its classification. However, it currently remains unclear whether these models rely on established biological indicators. This work compares a novel DL model [...] Read more.
As the leading cause of dementia worldwide, Alzheimer’s Disease (AD) has prompted significant interest in developing Deep Learning (DL) approaches for its classification. However, it currently remains unclear whether these models rely on established biological indicators. This work compares a novel DL model using structural connectivity (namely, BC-GCN-SE adapted from functional connectivity tasks) with an established model using structural magnetic resonance imaging (MRI) scans (namely, ResNet18). Unlike most studies primarily focusing on performance, our work places explainability at the forefront. Specifically, we define a novel Explainable Artificial Intelligence (XAI) metric, based on gradient-weighted class activation mapping. Its aim is quantitatively measuring how effectively these models fare against established AD biomarkers in their decision-making. The XAI assessment was conducted across 132 brain parcels. Results were compared to AD-relevant regions to measure adherence to domain knowledge. Then, differences in explainability patterns between the two models were assessed to explore the insights offered by each piece of data (i.e., MRI vs. connectivity). Classification performance was satisfactory in terms of both the median true positive (ResNet18: 0.817, BC-GCN-SE: 0.703) and true negative rates (ResNet18: 0.816; BC-GCN-SE: 0.738). Statistical tests (p < 0.05) and ranking of the 15% most relevant parcels revealed the involvement of target areas: the medial temporal lobe for ResNet18 and the default mode network for BC-GCN-SE. Additionally, our findings suggest that different imaging modalities provide complementary information to DL models. This lays the foundation for bioengineering advancements in developing more comprehensive and trustworthy DL models, potentially enhancing their applicability as diagnostic support tools for neurodegenerative diseases. Full article
(This article belongs to the Special Issue Machine-Learning-Driven Medical Image Analysis)
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17 pages, 4735 KiB  
Article
Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI
by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim and Jong Hyo Kim
Bioengineering 2025, 12(1), 81; https://doi.org/10.3390/bioengineering12010081 - 16 Jan 2025
Viewed by 510
Abstract
Recent advancements in deep learning have significantly improved medical image segmentation. However, the generalization performance and potential risks of data-driven models remain insufficiently validated. Specifically, unrealistic segmentation predictions deviating from actual anatomical structures, known as a Seg-Hallucination, often occur in deep learning-based models. [...] Read more.
Recent advancements in deep learning have significantly improved medical image segmentation. However, the generalization performance and potential risks of data-driven models remain insufficiently validated. Specifically, unrealistic segmentation predictions deviating from actual anatomical structures, known as a Seg-Hallucination, often occur in deep learning-based models. The Seg-Hallucinations can result in erroneous quantitative analyses and distort critical imaging biomarker information, yet effective audits or corrections to address these issues are rare. Therefore, we propose an automated Seg-Hallucination surveillance and correction (ASHSC) algorithm utilizing only 3D organ mask information derived from CT images without reliance on the ground truth. Two publicly available datasets were used in developing the ASHSC algorithm: 280 CT scans from the TotalSegmentator dataset for training and 274 CT scans from the Cancer Imaging Archive (TCIA) dataset for performance evaluation. The ASHSC algorithm utilizes a two-stage on-demand strategy with mesh-based convolutional neural networks and generative artificial intelligence. The segmentation quality level (SQ-level)-based surveillance stage was evaluated using the area under the receiver operating curve, sensitivity, specificity, and positive predictive value. The on-demand correction performance of the algorithm was assessed using similarity metrics: volumetric Dice score, volume error percentage, average surface distance, and Hausdorff distance. Average performance of the surveillance stage resulted in an AUROC of 0.94 ± 0.01, sensitivity of 0.82 ± 0.03, specificity of 0.90 ± 0.01, and PPV of 0.92 ± 0.01 for test dataset. After the on-demand refinement of the correction stage, all the four similarity metrics were improved compared to a single use of the AI-segmentation model. This study not only enhances the efficiency and reliability of handling the Seg-Hallucination but also eliminates the reliance on ground truth. The ASHSC algorithm offers intuitive 3D guidance for uncertainty regions, while maintaining manageable computational complexity. The SQ-level-based on-demand correction strategy adaptively minimizes uncertainties inherent in deep-learning-based organ masks and advances automated auditing and correction methodologies. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
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17 pages, 3994 KiB  
Article
Can CT Image Reconstruction Parameters Impact the Predictive Value of Radiomics Features in Grading Pancreatic Neuroendocrine Neoplasms?
by Florent Tixier, Felipe Lopez-Ramirez, Alejandra Blanco, Mohammad Yasrab, Ammar A. Javed, Linda C. Chu, Elliot K. Fishman and Satomi Kawamoto
Bioengineering 2025, 12(1), 80; https://doi.org/10.3390/bioengineering12010080 - 16 Jan 2025
Viewed by 393
Abstract
The WHO grading of pancreatic neuroendocrine neoplasms (PanNENs) is essential in patient management and an independent prognostic factor for patient survival. Radiomics features from CE-CT images hold promise for the outcome and tumor grade prediction. However, variations in reconstruction parameters can impact the [...] Read more.
The WHO grading of pancreatic neuroendocrine neoplasms (PanNENs) is essential in patient management and an independent prognostic factor for patient survival. Radiomics features from CE-CT images hold promise for the outcome and tumor grade prediction. However, variations in reconstruction parameters can impact the predictive value of radiomics. 127 patients with histopathologically confirmed PanNENs underwent CT scans with filtered back projection (B20f) and iterative (I26f) reconstruction kernels. 3190 radiomic features were extracted from tumors and pancreatic volumes. Wilcoxon paired tests assessed the impact of reconstruction kernels and ComBat harmonization efficiency. SVM models were employed to predict tumor grade using the entire set of radiomics features or only those identified as harmonizable. The models’ performance was assessed on an independent dataset of 36 patients. Significant differences, after correction for multiple testing, were observed in 69% of features in the pancreatic volume and 51% in the tumor volume with B20f and I26f kernels. SVM models demonstrated accuracy ranging from 0.67 (95%CI: 0.50–0.81) to 0.83 (95%CI: 0.69–0.94) in distinguishing grade 1 cases from higher grades. Reconstruction kernels alter radiomics features and iterative kernel models trended towards higher performance. ComBat harmonization mitigates kernel impacts but addressing this effect is crucial in studies involving data from different kernels. Full article
(This article belongs to the Special Issue Biomedical Imaging and Data Analytics for Disease Diagnosis and Treatment, 2nd Edition)
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17 pages, 1381 KiB  
Article
Comparison of Mirroring and Overlapping Analysis and Three-Dimensional Soft Tissue Spatial Angle Wireframe Template in Evaluating Facial Asymmetry
by Gengchen Yang, Liang Lyu, Aonan Wen, Yijiao Zhao, Yong Wang, Jing Li, Huichun Yan, Mingjin Zhang, Yi Yu, Tingting Yu and Dawei Liu
Bioengineering 2025, 12(1), 79; https://doi.org/10.3390/bioengineering12010079 - 16 Jan 2025
Viewed by 473
Abstract
Aim: The purpose of this study was to evaluate the accuracy and efficacy of a new wireframe template methodology in analyzing three-dimensional facial soft tissue asymmetry. Materials and methods: Three-dimensional facial soft tissue data were obtained for 24 patients. The wireframe template was [...] Read more.
Aim: The purpose of this study was to evaluate the accuracy and efficacy of a new wireframe template methodology in analyzing three-dimensional facial soft tissue asymmetry. Materials and methods: Three-dimensional facial soft tissue data were obtained for 24 patients. The wireframe template was established by identifying 34 facial landmarks and then forming a template on the face with the MeshLab 2020 software. The angle asymmetry index was automatically scored using the template. The mirroring and overlapping technique is accepted as the golden standard method to diagnose facial asymmetry by acquiring deviation values of one’s face. Consistency rates between the two methodologies were determined through a statistical comparison of the angle asymmetry index and deviation values. Results: Overall consistency rates in the labial, mandibular angle, cheek, chin, and articular regions were 87.5%, 95.8%, 87.5%, 91.7%, and 100%, respectively. Regions with consistency rates in three dimensions of more than 85% are the x-axis and the z-axis of all regions and the y-axis of the mandibular angle, chin, and articular region. Conclusions: Soft tissue facial asymmetry can be diagnosed accurately and effectively by using a three-dimensional soft tissue spatial angle wireframe template. Precise localization of asymmetry can be offered, and indiscernible tiny asymmetry can be identified. Full article
(This article belongs to the Section Biosignal Processing)
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18 pages, 1542 KiB  
Review
Image-Based Monitoring of Thermal Ablation
by Xinyi Wang, Shiqing Zhao and Aili Zhang
Bioengineering 2025, 12(1), 78; https://doi.org/10.3390/bioengineering12010078 - 15 Jan 2025
Viewed by 671
Abstract
Thermal therapy is a commonly used local treatment technique in clinical practice. Monitoring the treatment process is essential for ensuring its success. In this review, we analyze recent image-based methods for thermal therapy monitoring, focusing particularly on their feasibility for synchronous or immediate [...] Read more.
Thermal therapy is a commonly used local treatment technique in clinical practice. Monitoring the treatment process is essential for ensuring its success. In this review, we analyze recent image-based methods for thermal therapy monitoring, focusing particularly on their feasibility for synchronous or immediate postoperative monitoring. This includes thermography and other techniques that track the physical changes in tissue during thermal ablation. Potential directions and challenges for further clinical applications are also summarized. Full article
(This article belongs to the Special Issue Advances in Thermal Therapy)
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30 pages, 1412 KiB  
Review
Targeting Chondrocyte Hypertrophy as Strategies for the Treatment of Osteoarthritis
by Da-Long Dong and Guang-Zhen Jin
Bioengineering 2025, 12(1), 77; https://doi.org/10.3390/bioengineering12010077 - 15 Jan 2025
Viewed by 403
Abstract
Osteoarthritis (OA) is a common joint disease characterized by pain and functional impairment, which severely impacts the quality of life of middle-aged and elderly individuals. During normal bone development, chondrocyte hypertrophy is a natural physiological process. However, in the progression of OA, chondrocyte [...] Read more.
Osteoarthritis (OA) is a common joint disease characterized by pain and functional impairment, which severely impacts the quality of life of middle-aged and elderly individuals. During normal bone development, chondrocyte hypertrophy is a natural physiological process. However, in the progression of OA, chondrocyte hypertrophy becomes one of its key pathological features. Although there is no definitive evidence to date confirming that chondrocyte hypertrophy is the direct cause of OA, substantial experimental data indicate that it plays an important role in the disease’s pathogenesis. In this review, we first explore the mechanisms underlying chondrocyte hypertrophy in OA and offer new insights. We then propose strategies for inhibiting chondrocyte hypertrophy from the perspectives of targeting signaling pathways and tissue engineering, ultimately envisioning the future prospects of OA treatment. Full article
(This article belongs to the Special Issue Integrating Novel Therapeutics and Personalized Medicine into Osteoarthritis Treatment: Advancements in Cartilage Regeneration and Joint Preservation)
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23 pages, 1318 KiB  
Review
Bioprinting and Intellectual Property: Challenges, Opportunities, and the Road Ahead
by Antreas Kantaros, Theodore Ganetsos, Florian Ion Tiberiu Petrescu and Elli Alysandratou
Bioengineering 2025, 12(1), 76; https://doi.org/10.3390/bioengineering12010076 - 15 Jan 2025
Viewed by 627
Abstract
Bioprinting, an innovative combination of biotechnology and additive manufacturing, has emerged as a transformative technology in healthcare, enabling the fabrication of functional tissues, organs, and patient-specific implants. The implementation of the aforementioned, however, introduces unique intellectual property (IP) challenges that extend beyond conventional [...] Read more.
Bioprinting, an innovative combination of biotechnology and additive manufacturing, has emerged as a transformative technology in healthcare, enabling the fabrication of functional tissues, organs, and patient-specific implants. The implementation of the aforementioned, however, introduces unique intellectual property (IP) challenges that extend beyond conventional biotechnology. The study explores three critical areas of concern: IP protection for bioprinting hardware and bioinks, ownership and ethical management of digital files derived from biological data, and the implications of commercializing bioprinted tissues and organs. Employing a multidisciplinary approach, the paper analyzes existing IP frameworks, highlights their limitations when applied to bioprinting, and examines ethical dilemmas, such as ownership of bioprinted human tissues and the commodification of biological innovations. Findings suggest that current IP laws inadequately address the complexities of bioprinting, particularly in managing the intersection of proprietary technologies and ethical considerations. The study underscores the need for adaptive legal and ethical frameworks to balance innovation with equitable access and sustainability. Recommendations include the development of tailored IP policies for bioprinting and enhanced international collaboration to harmonize legal protections across jurisdictions. This work aims to provide a comprehensive foundation for stakeholders to navigate the rapidly evolving landscape of bioprinting IP. Full article
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13 pages, 2212 KiB  
Article
Effect of Adapted Ergometer Setup and Rowing Speed on Lower Extremity Loading in People with and Without Spinal Cord Injury
by Ying Fang and Karen L. Troy
Bioengineering 2025, 12(1), 75; https://doi.org/10.3390/bioengineering12010075 - 15 Jan 2025
Viewed by 379
Abstract
Background: Functional electrical stimulation-assisted rowing (FES rowing) is a rehabilitation exercise used to prevent disuse osteoporosis, which is common in people with spinal cord injury (SCI). However, its effect on bone loss prevention varied in SCI patients, potentially due to inconsistent loading. This [...] Read more.
Background: Functional electrical stimulation-assisted rowing (FES rowing) is a rehabilitation exercise used to prevent disuse osteoporosis, which is common in people with spinal cord injury (SCI). However, its effect on bone loss prevention varied in SCI patients, potentially due to inconsistent loading. This study investigates the effect of ergometer setup and rowing speed on lower extremity loading during rowing. Methods: Twenty able-bodied participants and one participant with SCI rowed on an adapted ergometer with different speeds and setups. We calculated foot reaction force and knee moment for all participants, and tibiofemoral force for the rower with SCI. Results: Able-bodied rowers generated 0.22–0.45 body weight (BW) foot reaction forces, and a higher force was associated with a fast speed, forward seat position, and large knee range of motion (RoM). The rower with SCI had the greatest foot reaction force (0.39 BW) when rowing with a small knee RoM at a rear seat position, and the highest tibiofemoral force (2.23 BW) with a large knee RoM or at a rear seat position. Conclusions: Ergometer setup and speed both affect lower limb loading and should be further studied in more rowers with SCI. This can inform rehabilitation protocols to standardize ergometer configuration to improve bone health. Full article
(This article belongs to the Special Issue Biomechanics of Orthopaedic Rehabilitation)
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11 pages, 1693 KiB  
Article
Anterior Cruciate Ligament Mechanical Response to Load in the Setting of Changes to the Medial Meniscus
by Angela Hussain, Muffaddal Madraswala, Jason Koh and Farid Amirouche
Bioengineering 2025, 12(1), 74; https://doi.org/10.3390/bioengineering12010074 - 15 Jan 2025
Viewed by 483
Abstract
The anterior cruciate ligament (ACL) is a major ligament in the knee joint, and its function is crucial for both the movement and stability of the knee. Our research takes a novel approach by investigating the effect of meniscus tears on the ACL, [...] Read more.
The anterior cruciate ligament (ACL) is a major ligament in the knee joint, and its function is crucial for both the movement and stability of the knee. Our research takes a novel approach by investigating the effect of meniscus tears on the ACL, how such tears will impact the stress on the ACL, and its overall compensation in response to the changes in the meniscus. Hypothesis/Purpose: This study aims to investigate how the ACL compensates for the change in knee joint stability and contact pressures due to partial horizontal cleavage tears (HCTs) in the meniscus, such as partial meniscectomy and partial transplantation on knee joint stability and contact pressures. We hypothesize that HCTs will increase contact pressures and decrease joint stability, thereby inducing compensatory stress on the anterior cruciate ligament (ACL). Method: Seven freshly frozen human cadaveric knees were used in a study to investigate the effects of different meniscal conditions and surgical interventions on the meniscus itself. Four testing scenarios were established: intact knees, knees with partial horizontal cleavage tears (HCTs) of the meniscus, knees with partial meniscectomy, and knees with partial transplantation. Axial loading was applied, and the medial meniscus contact pressures were measured at 0° and 30° of flexion. Additionally, a mathematical 3D finite element model was created to evaluate the behavior of the ACL under different meniscus scenarios, which could not have been measured experimentally. Results: ACL contact pressure and stress analysis across various meniscal conditions demonstrated substantial variability. Horizontal cleavage tears (HCTs) resulted in heightened contact pressures and diminished joint stability, as evidenced by increased ACL stress attributed to compensatory mechanisms in the presence of meniscal tears. Conversely, transplantation procedures exhibited a mitigating effect, maintaining joint mechanics closer to intact conditions and minimizing alterations in ACL forces. These trends persisted at 30 degrees of knee flexion, where significant increases in ACL forces were observed in partial and complete HCT conditions. Conclusions: This study uncovers the biomechanical impacts of meniscal injuries, demonstrating how the ACL compensates for various meniscus conditions. In contrast, transplantation and repair conditions only slightly increase the stress on the ACL, putting much less strain on the ACL and supporting structures of the knee joint than an unrepaired tear. Full article
(This article belongs to the Section Biomechanics and Sports Medicine)
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42 pages, 7150 KiB  
Article
LightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection
by Hari Mohan Rai, Joon Yoo, Saurabh Agarwal and Neha Agarwal
Bioengineering 2025, 12(1), 73; https://doi.org/10.3390/bioengineering12010073 - 15 Jan 2025
Viewed by 598
Abstract
Breast cancer ranks as the second most prevalent cancer globally and is the most frequently diagnosed cancer among women; therefore, early, automated, and precise detection is essential. Most AI-based techniques for breast cancer detection are complex and have high computational costs. Hence, to [...] Read more.
Breast cancer ranks as the second most prevalent cancer globally and is the most frequently diagnosed cancer among women; therefore, early, automated, and precise detection is essential. Most AI-based techniques for breast cancer detection are complex and have high computational costs. Hence, to overcome this challenge, we have presented the innovative LightweightUNet hybrid deep learning (DL) classifier for the accurate classification of breast cancer. The proposed model boasts a low computational cost due to its smaller number of layers in its architecture, and its adaptive nature stems from its use of depth-wise separable convolution. We have employed a multimodal approach to validate the model’s performance, using 13,000 images from two distinct modalities: mammogram imaging (MGI) and ultrasound imaging (USI). We collected the multimodal imaging datasets from seven different sources, including the benchmark datasets DDSM, MIAS, INbreast, BrEaST, BUSI, Thammasat, and HMSS. Since the datasets are from various sources, we have resized them to the uniform size of 256 × 256 pixels and normalized them using the Box-Cox transformation technique. Since the USI dataset is smaller, we have applied the StyleGAN3 model to generate 10,000 synthetic ultrasound images. In this work, we have performed two separate experiments: the first on a real dataset without augmentation and the second on a real + GAN-augmented dataset using our proposed method. During the experiments, we used a 5-fold cross-validation method, and our proposed model obtained good results on the real dataset (87.16% precision, 86.87% recall, 86.84% F1-score, and 86.87% accuracy) without adding any extra data. Similarly, the second experiment provides better performance on the real + GAN-augmented dataset (96.36% precision, 96.35% recall, 96.35% F1-score, and 96.35% accuracy). This multimodal approach, which utilizes LightweightUNet, enhances the performance by 9.20% in precision, 9.48% in recall, 9.51% in F1-score, and a 9.48% increase in accuracy on the combined dataset. The LightweightUNet model we proposed works very well thanks to a creative network design, adding fake images to the data, and a multimodal training method. These results show that the model has a lot of potential for use in clinical settings. Full article
(This article belongs to the Special Issue Application of Deep Learning in Medical Diagnosis)
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13 pages, 2076 KiB  
Article
Use of Multimodal Artificial Intelligence in Surgical Instrument Recognition
by Syed Ali Haider, Olivia A. Ho, Sahar Borna, Cesar A. Gomez-Cabello, Sophia M. Pressman, Dave Cole, Ajai Sehgal, Bradley C. Leibovich and Antonio Jorge Forte
Bioengineering 2025, 12(1), 72; https://doi.org/10.3390/bioengineering12010072 - 15 Jan 2025
Viewed by 449
Abstract
Accurate identification of surgical instruments is crucial for efficient workflows and patient safety within the operating room, particularly in preventing complications such as retained surgical instruments. Artificial Intelligence (AI) models have shown the potential to automate this process. This study evaluates the accuracy [...] Read more.
Accurate identification of surgical instruments is crucial for efficient workflows and patient safety within the operating room, particularly in preventing complications such as retained surgical instruments. Artificial Intelligence (AI) models have shown the potential to automate this process. This study evaluates the accuracy of publicly available Large Language Models (LLMs)—ChatGPT-4, ChatGPT-4o, and Gemini—and a specialized commercial mobile application, Surgical-Instrument Directory (SID 2.0), in identifying surgical instruments from images. The study utilized a dataset of 92 high-resolution images of 25 surgical instruments (retractors, forceps, scissors, and trocars) photographed from multiple angles. Model performance was evaluated using accuracy, weighted precision, recall, and F1 score. ChatGPT-4o exhibited the highest accuracy (89.1%) in categorizing instruments (e.g., scissors, forceps). SID 2.0 (77.2%) and ChatGPT-4 (76.1%) achieved comparable accuracy, while Gemini (44.6%) demonstrated lower accuracy in this task. For precise subtype identification of instrument names (like “Mayo scissors” or “Kelly forceps”), all models had low accuracy, with SID 2.0 having an accuracy of 39.1%, followed by ChatGPT-4o (33.69%). Subgroup analysis revealed ChatGPT-4 and 4o recognized trocars in all instances. Similarly, Gemini identified surgical scissors in all instances. In conclusion, publicly available LLMs can reliably identify surgical instruments at the category level, with ChatGPT-4o demonstrating an overall edge. However, precise subtype identification remains a challenge for all models. These findings highlight the potential of AI-driven solutions to enhance surgical-instrument management and underscore the need for further refinements to improve accuracy and support patient safety. Full article
(This article belongs to the Special Issue Deciphering Medicine: The Role of Explainable Artificial Intelligence in Healthcare Innovations)
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20 pages, 318 KiB  
Review
Narrative Review and Guide: State of the Art and Emerging Opportunities of Bioprinting in Tissue Regeneration and Medical Instrumentation
by Jaroslava Halper
Bioengineering 2025, 12(1), 71; https://doi.org/10.3390/bioengineering12010071 - 15 Jan 2025
Viewed by 482
Abstract
Three-dimensional printing was introduced in the 1980s, though bioprinting started developing a few years later. Today, 3D bioprinting is making inroads in medical fields, including the production of biomedical supplies intended for internal use, such as biodegradable staples. Medical bioprinting enables versatility and [...] Read more.
Three-dimensional printing was introduced in the 1980s, though bioprinting started developing a few years later. Today, 3D bioprinting is making inroads in medical fields, including the production of biomedical supplies intended for internal use, such as biodegradable staples. Medical bioprinting enables versatility and flexibility on demand and is able to modify and individualize production using several established printing methods. A great selection of biomaterials and bioinks is available, including natural, synthetic, and mixed options; they are biocompatible and non-toxic. Many bioinks are biodegradable and they accommodate cells so upon implantation, they integrate within the new environment. Bioprinting is suitable for printing tissues using living or viable components, such as collagen scaffolding, cartilage components, and cells, and also for printing parts of structures, such as teeth, using artificial man-made materials that will become embedded in vivo. Bioprinting is an integral part of tissue engineering and regenerative medicine. The addition of newly developed smart biomaterials capable of incorporating dynamic changes in shape depending on the nature of stimuli led to the addition of the fourth dimension of time in the form of changing shape to the three static dimensions. Four-dimensional bioprinting is already making significant inroads in tissue engineering and regenerative medicine, including new ways to create dynamic tissues. Its future lies in constructing partial or whole organ generation. Full article
(This article belongs to the Special Issue The New Frontiers of Artificial Organs Engineering)
2 pages, 143 KiB  
Editorial
Data Processing and Machine Learning for Assistive and Rehabilitation Technologies
by Andrea Tigrini, Agnese Sbrollini and Alessandro Mengarelli
Bioengineering 2025, 12(1), 70; https://doi.org/10.3390/bioengineering12010070 - 15 Jan 2025
Viewed by 380
Abstract
This Special Issue (SI), “Data Processing and Machine Learning for Assistive and Rehabilitation Technologies”, aimed to collect cutting-edge research papers that frame how data-driven approaches and machine learning techniques are advancing the field of assistive and rehabilitation technologies [...] Full article
(This article belongs to the Special Issue Data Processing and Machine Learning for Assistive and Rehabilitation Technologies)
12 pages, 2498 KiB  
Article
Kinematic Alterations with Changes in Putting Distance and Slope Incline in Recreational Golfers
by Shawn M. Robbins, Philippe Renaud and Ukadike Chris Ugbolue
Bioengineering 2025, 12(1), 69; https://doi.org/10.3390/bioengineering12010069 - 15 Jan 2025
Viewed by 378
Abstract
Golfers must modify their motor patterns when the demands of a putting task change. The objective was to compare joint angles and putter kinematics during putting at two distances and inclines. Recreational golfers (n = 14) completed putts over four conditions: 3-foot [...] Read more.
Golfers must modify their motor patterns when the demands of a putting task change. The objective was to compare joint angles and putter kinematics during putting at two distances and inclines. Recreational golfers (n = 14) completed putts over four conditions: 3-foot putts on flat and incline surfaces, and 7-foot putts on flat and incline surfaces. A Vicon motion capture system measured kinematic data. Joint angles, putter angles, and spatiotemporal variables were calculated. Analysis of variance compared spatiotemporal variables, and statistical parametric mapping compared angles between putts. There were faster putter head and ball velocities during longer and incline putts. The amplitude and time of backswing increased with longer putts. Longer putts resulted in increased trunk axial rotation during backswing, downswing, and follow-through, while incline putts only resulted in greater rotation during follow-through. There were minimal differences in shoulder angle. There was greater head rotation toward the hole during all putting phases for longer putts and during follow-through for incline putts. The trunk is the primary mechanism to increase putter head amplitude, and thereby velocity, when putting from longer distances. A similar strategy could be used when putting uphill. Additional work should confirm these results in highly skilled golfers. Full article
(This article belongs to the Special Issue Dynamic Insights: Unveiling the Biomechanics of Sport through Motion Analysis)
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20 pages, 1270 KiB  
Review
Current Understanding on the Heterogenous Expression of Plastic Depolymerising Enzymes in Pichia pastoris
by Shuyan Wu, David Hooks and Gale Brightwell
Bioengineering 2025, 12(1), 68; https://doi.org/10.3390/bioengineering12010068 - 14 Jan 2025
Viewed by 475
Abstract
Enzymatic depolymerisation is increasingly recognised as a reliable and environmentally friendly method. The development of this technology hinges on the availability of high-quality enzymes and associated bioreaction systems for upscaling biodegradation. Microbial heterologous expression systems have been studied for meeting this demand. Among [...] Read more.
Enzymatic depolymerisation is increasingly recognised as a reliable and environmentally friendly method. The development of this technology hinges on the availability of high-quality enzymes and associated bioreaction systems for upscaling biodegradation. Microbial heterologous expression systems have been studied for meeting this demand. Among these systems, the Pichia pastoris expression system has emerged as a widely used platform for producing secreted heterologous proteins. This article provides an overview of studies involving the recombinant expression of polymer-degrading enzymes using the P. pastoris expression system. Research on P. pastoris expression of interested enzymes with depolymerising ability, including cutinase, lipase, and laccase, are highlighted in the review. The key factors influencing the heterologous expression of polymer-degrading enzymes in P. pastoris are discussed, shedding light on the challenges and opportunities in the development of depolymerising biocatalysts through the P. pastoris expression system. Full article
(This article belongs to the Special Issue Synthetic Biology and Bioprocess Engineering for High-Value Compounds)
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14 pages, 3771 KiB  
Article
Analyzing Gait Dynamics and Recovery Trajectory in Lower Extremity Fractures Using Linear Mixed Models and Gait Analysis Variables
by Mostafa Rezapour, Rachel B. Seymour, Suman Medda, Stephen H. Sims, Madhav A. Karunakar, Nahir Habet and Metin Nafi Gurcan
Bioengineering 2025, 12(1), 67; https://doi.org/10.3390/bioengineering12010067 - 14 Jan 2025
Viewed by 489
Abstract
In a prospective study, we examined the recovery trajectory of patients with lower extremity fractures to better understand the healing process in the absence of complications. Using a chest-mounted inertial measurement unit (IMU) device for gait analysis and collecting patient-reported outcome measures, we [...] Read more.
In a prospective study, we examined the recovery trajectory of patients with lower extremity fractures to better understand the healing process in the absence of complications. Using a chest-mounted inertial measurement unit (IMU) device for gait analysis and collecting patient-reported outcome measures, we focused on 12 key gait variables, including Mean Leg Lift Acceleration, Stance Time, and Body Orientation. We employed a linear mixed model (LMM) to analyze these variables over time, incorporating both fixed and random effects to account for individual differences and the time since injury. This model also adjusted for varying intervals between assessments. Our study provided insights into gait recovery across different fracture types using data from 318 patients who experienced no complications or readmissions during their recovery. Through LMM analysis, we found that Tibia-Distal fractures demonstrated the fastest recovery, particularly in terms of mobility and strength. Tibia-Proximal fractures showed balanced improvements in both mobility and stability, suggesting that rehabilitation should target both strength and balance. Femur fractures exhibited varied recovery, with Diaphyseal fractures showing clear improvements in stability, while Distal fractures reflected gains in limb strength but with some variability in stability. To examine patients with readmissions, we conducted a Chi-squared test of independence to determine whether there was a relationship between fracture type and readmission rates, revealing a significant association (p < 0.001). Pelvis fractures had the highest readmission rates, while Tibia-Diaphyseal and Tibia-Distal fractures were more prone to infections, highlighting the need for enhanced infection control strategies. Femur fractures showed moderate readmission and infection rates, indicating a mixed risk profile. In conclusion, our findings emphasize the importance of fracture-specific rehabilitation strategies, focusing on infection prevention and individualized treatment plans to optimize recovery outcomes. Full article
(This article belongs to the Special Issue Technological Advances for Gait and Balance Assessment)
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25 pages, 5975 KiB  
Article
Older Fallers’ Comprehensive Neuromuscular and Kinematic Alterations in Reactive Balance Control: Indicators of Balance Decline or Compensation? A Pilot Study
by Ringo Tang-Long Zhu, Timmi Tim Mei Hung, Freddy Man Hin Lam, Jun-Zhe Li, Yu-Yan Luo, Jingting Sun, Shujun Wang and Christina Zong-Hao Ma
Bioengineering 2025, 12(1), 66; https://doi.org/10.3390/bioengineering12010066 - 14 Jan 2025
Viewed by 411
Abstract
Background: Falls and fall consequences in older adults are global health issues. Previous studies have compared postural sways or stepping strategies between older adults with and without fall histories to identify factors associated with falls. However, more in-depth neuromuscular/kinematic mechanisms have remained [...] Read more.
Background: Falls and fall consequences in older adults are global health issues. Previous studies have compared postural sways or stepping strategies between older adults with and without fall histories to identify factors associated with falls. However, more in-depth neuromuscular/kinematic mechanisms have remained unclear. This study aimed to comprehensively investigate muscle activities and joint kinematics during reactive balance control in older adults with different fall histories. Methods: This pilot observational study recruited six community-dwelling older fallers (≥1 fall in past one year) and six older non-fallers, who received unpredictable translational balance perturbations in randomized directions and intensities during standing. The whole-body center-of-mass (COM) displacements, eight dominant-leg joint motions and muscle electrical activities were collected, and analyzed using the temporal and amplitude parameters. Results: Compared to non-fallers, fallers had significantly: (a) smaller activation rate of the ankle dorsiflexor, delayed activation of the hip flexor/extensor, larger activation rate of the knee flexor, and smaller agonist-antagonist co-contraction in lower-limb muscles; (b) larger knee/hip flexion angles, longer ankle dorsiflexion duration, and delayed timing of recovery in joint motions; and (c) earlier downward COM displacements and larger anteroposterior overshooting COM displacements following unpredictable perturbations (p < 0.05). Conclusions: Compared to non-fallers, fallers used more suspensory strategies for reactive standing balance, which compensated for inadequate ankle/hip strategies but resulted in prolonged recovery. A further longitudinal study with a larger sample is still needed to examine the diagnostic accuracies and training values of these identified neuromuscular/kinematic factors in differentiating fall risks and preventing future falls of older people, respectively. Full article
(This article belongs to the Special Issue Biomechanics and Motion Analysis)
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24 pages, 726 KiB  
Review
A Survey on Optical Coherence Tomography—Technology and Application
by Ali Mokhtari, Bogdan Mihai Maris and Paolo Fiorini
Bioengineering 2025, 12(1), 65; https://doi.org/10.3390/bioengineering12010065 - 14 Jan 2025
Viewed by 484
Abstract
This paper reviews the main research on Optical Coherence Tomography (OCT), focusing on the progress and advancements made by researchers over the past three decades in its methods and medical imaging applications. By analyzing existing studies and developments, this review aims to provide [...] Read more.
This paper reviews the main research on Optical Coherence Tomography (OCT), focusing on the progress and advancements made by researchers over the past three decades in its methods and medical imaging applications. By analyzing existing studies and developments, this review aims to provide a foundation for future research in the field. Full article
(This article belongs to the Special Issue Biomedical Applications of Optical Coherence Tomography, Second Edition)
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