Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
3.7
Journals
Bioengineering
Editor’s Choice
share announcement

Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Order results
Result details
Results per page
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
19 pages, 1118 KiB  
Review
Long-Acting Extracellular Vesicle-Based Biologics in Osteoarthritis Immunotherapy
by Philip Drohat, Max Baron, Lee D. Kaplan, Thomas M. Best and Dimitrios Kouroupis
Bioengineering 2025, 12(5), 525; https://doi.org/10.3390/bioengineering12050525 - 15 May 2025
Cited by 1 | Viewed by 937
Abstract
Osteoarthritis (OA) is a chronic degenerative joint disease characterized by low-grade inflammation, cartilage breakdown, and persistent pain. Despite its prevalence, current therapeutic strategies primarily focus on symptom management rather than modifying disease progression. Monoclonal antibodies and cytokine inhibitors targeting inflammatory pathways, including TNF-α [...] Read more.
Osteoarthritis (OA) is a chronic degenerative joint disease characterized by low-grade inflammation, cartilage breakdown, and persistent pain. Despite its prevalence, current therapeutic strategies primarily focus on symptom management rather than modifying disease progression. Monoclonal antibodies and cytokine inhibitors targeting inflammatory pathways, including TNF-α and IL-1, have shown promise but remain limited by inconsistent efficacy and safety concerns. Long-acting biologic therapies—ranging from extended-release formulations, such as monoclonal antibodies and cytokine inhibitors, to gene therapy approaches—have emerged as promising strategies to enhance treatment durability and improve patient outcomes. Extracellular vesicles (EVs) have gained particular attention as a novel delivery platform due to their inherent stability, biocompatibility, and ability to transport therapeutic cargo, including biologics and immunomodulatory agents, directly to joint tissues. This review explores the evolving role of EVs in OA treatment, highlighting their ability to extend drug half-life, improve targeting, and modulate inflammatory responses. Additionally, strategies for EV engineering, including endogenous and exogenous cargo loading, genetic modifications, and biomaterial-based delivery systems, are discussed. 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)
►▼ Show Figures

Figure 1

21 pages, 4080 KiB  
Review
Integrating Artificial Intelligence in Orthopedic Care: Advancements in Bone Care and Future Directions
by Rahul Kumar, Kyle Sporn, Joshua Ong, Ethan Waisberg, Phani Paladugu, Swapna Vaja, Tamer Hage, Tejas C. Sekhar, Amar S. Vadhera, Alex Ngo, Nasif Zaman, Alireza Tavakkoli and Mouayad Masalkhi
Bioengineering 2025, 12(5), 513; https://doi.org/10.3390/bioengineering12050513 - 13 May 2025
Cited by 2 | Viewed by 1843
Abstract
Artificial intelligence (AI) is revolutionizing the field of orthopedic bioengineering by increasing diagnostic accuracy and surgical precision and improving patient outcomes. This review highlights using AI for orthopedics in preoperative planning, intraoperative robotics, smart implants, and bone regeneration. AI-powered imaging, automated 3D anatomical [...] Read more.
Artificial intelligence (AI) is revolutionizing the field of orthopedic bioengineering by increasing diagnostic accuracy and surgical precision and improving patient outcomes. This review highlights using AI for orthopedics in preoperative planning, intraoperative robotics, smart implants, and bone regeneration. AI-powered imaging, automated 3D anatomical modeling, and robotic-assisted surgery have dramatically changed orthopedic practices. AI has improved surgical planning by enhancing complex image interpretation and providing augmented reality guidance to create highly accurate surgical strategies. Intraoperatively, robotic-assisted surgeries enhance accuracy and reduce human error while minimizing invasiveness. AI-powered smart implant sensors allow for in vivo monitoring, early complication detection, and individualized rehabilitation. It has also advanced bone regeneration devices and neuroprosthetics, highlighting its innovation capabilities. While AI advancements in orthopedics are exciting, challenges remain, like the need for standardized surgical system validation protocols, assessing ethical consequences of AI-derived decision-making, and using AI with bioprinting for tissue engineering. Future research should focus on proving the reliability and predictability of the performance of AI-pivoted systems and their adoption within clinical practice. This review synthesizes recent developments and highlights the increasing impact of AI in orthopedic bioengineering and its potential future effectiveness in bone care and beyond. Full article
(This article belongs to the Section Biosignal Processing)
►▼ Show Figures

Figure 1

31 pages, 5264 KiB  
Article
StructureNet: Physics-Informed Hybridized Deep Learning Framework for Protein–Ligand Binding Affinity Prediction
by Arjun Kaneriya, Madhav Samudrala, Harrish Ganesh, James Moran, Somanath Dandibhotla and Sivanesan Dakshanamurthy
Bioengineering 2025, 12(5), 505; https://doi.org/10.3390/bioengineering12050505 - 10 May 2025
Viewed by 1558
Abstract
Accurately predicting protein–ligand binding affinity is an important step in the drug discovery process. Deep learning (DL) methods have improved binding affinity prediction by using diverse categories of molecular data. However, many models rely heavily on interaction and sequence data, which impedes proper [...] Read more.
Accurately predicting protein–ligand binding affinity is an important step in the drug discovery process. Deep learning (DL) methods have improved binding affinity prediction by using diverse categories of molecular data. However, many models rely heavily on interaction and sequence data, which impedes proper learning and limits performance in de novo applications. To address these limitations, we developed a novel graph neural network model, called StructureNet (structure-based graph neural network), to predict protein–ligand binding affinity. StructureNet improves existing DL methods by focusing entirely on structural descriptors to mitigate data memorization issues introduced by sequence and interaction data. StructureNet represents the protein and ligand structures as graphs, which are processed using a GNN-based ensemble deep learning model. StructureNet achieved a PCC of 0.68 and an AUC of 0.75 on the PDBBind v.2020 Refined Set, outperforming similar structure-based models. External validation on the DUDE-Z dataset showed that StructureNet can effectively distinguish between active and decoy ligands. Further testing on a small subset of well-known drugs indicates that StructureNet has high potential for rapid virtual screening applications. We also hybridized StructureNet with interaction- and sequence-based models to investigate their impact on testing accuracy and found minimal difference (0.01 PCC) between merged models and StructureNet as a standalone model. An ablation study found that geometric descriptors were the key drivers of model performance, with their removal leading to a PCC decrease of over 15.7%. Lastly, we tested StructureNet on ensembles of binding complex conformers generated using molecular dynamics (MD) simulations and found that incorporating multiple conformations of the same complex often improves model accuracy by capturing binding site flexibility. Overall, the results show that structural data alone are sufficient for binding affinity predictions and can address pattern recognition challenges introduced by sequence and interaction features. Additionally, structural representations of protein–ligand complexes can be considerably improved using geometric and topological descriptors. We made StructureNet GUI interface freely available online. Full article
(This article belongs to the Section Biosignal Processing)
►▼ Show Figures

Figure 1

23 pages, 4534 KiB  
Review
Branding a New Technological Outlook for Future Orthopaedics
by Nicole Tueni and Farid Amirouche
Bioengineering 2025, 12(5), 494; https://doi.org/10.3390/bioengineering12050494 - 7 May 2025
Cited by 1 | Viewed by 1048
Abstract
Orthopedics is undergoing a transformative shift driven by personalized medical technologies that enhance precision, efficiency, and patient outcomes. Virtual surgical planning, robotic assistance, and real-time 3D navigation have revolutionized procedures like total knee arthroplasty and hip replacement, offering unparalleled accuracy and reducing recovery [...] Read more.
Orthopedics is undergoing a transformative shift driven by personalized medical technologies that enhance precision, efficiency, and patient outcomes. Virtual surgical planning, robotic assistance, and real-time 3D navigation have revolutionized procedures like total knee arthroplasty and hip replacement, offering unparalleled accuracy and reducing recovery times. Integrating artificial intelligence, advanced imaging, and 3D-printed patient-specific implants further elevates surgical precision, minimizes intraoperative complications, and supports individualized care. In sports orthopedics, wearable sensors and motion analysis technologies are revolutionizing diagnostics, injury prevention, and rehabilitation, enabling real-time decision-making and improved patient safety. Health-tracking devices are advancing recovery and supporting preventative care, transforming athletic performance management. Concurrently, breakthroughs in biologics, biomaterials, and bioprinting are reshaping treatments for cartilage defects, ligament injuries, osteoporosis, and meniscal damage. These innovations are poised to establish new benchmarks for regenerative medicine in orthopedics. By combining cutting-edge technologies with interdisciplinary collaboration, the field is redefining surgical standards, optimizing patient care, and paving the way for a highly personalized and efficient future. Full article
(This article belongs to the Special Issue Advanced Engineering Technologies in Orthopaedic Research)
►▼ Show Figures

Figure 1

13 pages, 2387 KiB  
Article
WATCH-PR: Comparison of the Pulse Rate of a WATCH-Type Blood Pressure Monitor with the Pulse Rate of a Conventional Ambulatory Blood Pressure Monitor
by Mathini Vaseekaran, Marcus Wiemer, Sven Kaese, Dennis Görlich, Jochen Hinkelbein, Gerrit Jansen and Alexander Samol
Bioengineering 2025, 12(5), 492; https://doi.org/10.3390/bioengineering12050492 - 5 May 2025
Cited by 1 | Viewed by 616
Abstract
Background: Monitoring pulse rate is fundamental to cardiovascular health management and early detection of rhythm disturbances. While oscillometric blood pressure measurement is well established and validated in clinical practice, its use for pulse rate monitoring, particularly via wrist-worn devices, remains largely unexplored. Objective: [...] Read more.
Background: Monitoring pulse rate is fundamental to cardiovascular health management and early detection of rhythm disturbances. While oscillometric blood pressure measurement is well established and validated in clinical practice, its use for pulse rate monitoring, particularly via wrist-worn devices, remains largely unexplored. Objective: This study investigates whether a smartwatch that performs oscillometric blood pressure measurements at the wrist can also deliver reliable pulse rate readings using the same method. Methods: This study compared pulse rates recorded by the Omron HeartGuide smartwatch and conventional ambulatory blood pressure monitors in 50 patients over 24 h. Measurements were taken consecutively, and data were analyzed using intraclass correlation coefficients (ICCs) and Bland–Altman plots. Results: The study showed a high ICC of 0.971, indicating excellent agreement between devices. The average pulse rate difference was 1.5 bpm, with the Omron HeartGuide reporting slightly lower rates, especially in patients with atrial fibrillation. Conclusions: This study demonstrates that oscillometric pulse-rate monitoring at the wrist can achieve a high degree of accuracy, comparable to conventional upper-arm devices. Given that oscillometric smartwatches like the Omron HeartGuide are already used for blood pressure monitoring, the findings suggest that they may also be suitable for pulse rate measurement, potentially enhancing their role in telemetric healthcare, but further research is needed, particularly in patients with arrhythmias. Full article
(This article belongs to the Special Issue Smart Applications and Technology for Cardiovascular Disease Management)
►▼ Show Figures

Figure 1

19 pages, 5913 KiB  
Article
Putative Endoplasmic Reticulum Stress Inducers Enhance Triacylglycerol Accumulation in Chlorella sorokiniana
by Yoomi Roh, Sujeong Je, Naeun Sheen, Chang Hun Shin and Yasuyo Yamaoka
Bioengineering 2025, 12(5), 452; https://doi.org/10.3390/bioengineering12050452 - 25 Apr 2025
Cited by 1 | Viewed by 500
Abstract
Chlorella, recognized for its high lipid and protein content, is increasingly studied for its potential in the food and bio industries. To enhance its production and understand the underlying mechanisms of lipid accumulation, this study investigated the role of endoplasmic reticulum (ER) [...] Read more.
Chlorella, recognized for its high lipid and protein content, is increasingly studied for its potential in the food and bio industries. To enhance its production and understand the underlying mechanisms of lipid accumulation, this study investigated the role of endoplasmic reticulum (ER) stress in modulating lipid metabolism in Chlorella sorokiniana UTEX 2714, using six putative ER stress inducers: 2-deoxy-D-glucose (2-DG), dithiothreitol (DTT), tunicamycin (TM), thapsigargin (TG), brefeldin A (BFA), and monensin (Mon). The results showed that 2-DG, DTT, TM, BFA, and Mon significantly inhibited cell growth in C. sorokiniana. Treatment with 2-DG, DTT, TM, BFA, or Mon resulted in substantial increases in the triacylglycerol (TAG) to total fatty acid (tFA) ratio, with fold changes of 14.8, 7.9, 6.2, 10.1, and 8.9, respectively. Among the tFAs, cells treated with these compounds exhibited higher levels of saturated fatty acids and lower levels of polyunsaturated fatty acids (PUFAs). In contrast, the fatty acid composition of TAGs showed the opposite trend, with relative enrichment in PUFAs. This study enhances our understanding of Chlorella lipid metabolism, providing valuable insights for optimizing lipid production, particularly TAGs enriched with PUFA content, for applications in functional foods, nutraceuticals, and sustainable bioresources. Full article
(This article belongs to the Special Issue Microalgae Biotechnology and Microbiology: Prospects and Applications)
►▼ Show Figures

Graphical abstract

18 pages, 21454 KiB  
Article
Digital Workflow with Open-Source CAD-CAM Software Aimed to Design a Customized 3D Laser-Printed Titanium Mesh for Guided Bone Regeneration
by Claudio Cirrincione, Giulia Guarnieri and Annamaria Morelli
Bioengineering 2025, 12(5), 436; https://doi.org/10.3390/bioengineering12050436 - 22 Apr 2025
Cited by 1 | Viewed by 623
Abstract
Guided bone regeneration (GBR) is a procedure used for the treatment of bone deficiencies. Computer-Aided Designed–Computer-Aided Manufacturing (CAD-CAM) allows us to design a titanium mesh (TM) for GBR directly on a 3D bone defect model (3DBM). The design and printing of TMs are [...] Read more.
Guided bone regeneration (GBR) is a procedure used for the treatment of bone deficiencies. Computer-Aided Designed–Computer-Aided Manufacturing (CAD-CAM) allows us to design a titanium mesh (TM) for GBR directly on a 3D bone defect model (3DBM). The design and printing of TMs are often delegated to specialized 3D printing centers, thus preventing the surgeon from controlling surgical parameters such as the thickness, pore width, texture, and stiffness. Therefore, we have here proposed a personalized digital workflow for designing a TM. The 3DBM was uploaded to an open-source CAD-CAM software. Following a GBR simulation, a TM was designed as a Standard Tesselation Language (STL) file and 3D laser-printed. The TM was applied to a graft of 50/50% autologous/xenogenic bone, fixed with a bone screw, and covered with a dermal membrane. No TM exposure was observed during the healing phase. The regenerated bone volume was 970 cc, and pseudoperiosteum was class 1. At the 6-month reentry, a 4.1 × 10 standard dental implant with a primary stability of 40 N/cm was placed and after 3 months a zirconia crown screw-on implant was placed. This proposed digital workflow enabled us to successfully tackle this clinical case. However, further clinical investigations will be necessary to confirm the long-term benefits of this procedure. Full article
(This article belongs to the Section Regenerative Engineering)
►▼ Show Figures

Figure 1

20 pages, 6681 KiB  
Article
CRISPR-Cas9-Mediated ATF6B Gene Editing Enhances Membrane Protein Production in HEK293T Cells
by Ho Joong Choi, Ba Reum Kim, Ok-Hee Kim and Say-June Kim
Bioengineering 2025, 12(4), 409; https://doi.org/10.3390/bioengineering12040409 - 11 Apr 2025
Viewed by 624
Abstract
This study aims to enhance membrane protein production in HEK293T cells through genetic modification. HEK293T cells are used for recombinant protein and viral vector production due to their human origin and post-translational modification capabilities. This study explores enhancing membrane protein production in these [...] Read more.
This study aims to enhance membrane protein production in HEK293T cells through genetic modification. HEK293T cells are used for recombinant protein and viral vector production due to their human origin and post-translational modification capabilities. This study explores enhancing membrane protein production in these cells by deleting the C-terminal of the ATF6B gene using CRISPR-Cas9 technology. The objective of this research is to investigate the effect of C-terminal deletion of the ATF6B gene on membrane protein production in HEK293T cells using CRISPR-Cas9 technology. To identify effective gene targets, sgRNAs were initially designed against multiple UPR-related genes, including ATF6A, IRE1A, IRE1B, PERK, and ATF6B. Among them, ATF6B was selected as the primary target for further investigation due to its superior editing efficiency. The efficiency of sgRNAs was evaluated using the T7E1 assay, and sequencing was performed to verify gene editing patterns. Membrane proteins were extracted from both ATF6B C-terminally deleted (ATF6B-ΔC) and wild-type (WT) cell lines for comparison. Flow cytometry was employed to assess membrane protein production by analyzing GFP expression in Membrane-GFP-expressing cells. HEK293T cells with C-terminally deleted ATF6B (ATF6B-ΔC) significantly increased membrane protein production by approximately 40 ± 17.6% compared to WT cells (p < 0.05). Sequencing revealed 11, 14, 1, and 10 bp deletions in the ATF6B-ΔC edited cells, which disrupted exon sequences, induced exon skipping, and introduced premature stop codons, suppressing normal protein expression. Flow cytometry confirmed a 23.9 ± 4.2% increase in GFP intensity in ATF6B-ΔC cells, corroborating the enhanced membrane protein production. These findings suggest that CRISPR-Cas9-mediated C-terminal deletion of the ATF6B gene can effectively enhance membrane protein production in HEK293T cells by activating the unfolded protein response pathway and improving the cell’s capacity to manage misfolded proteins. This strategy presents significant potential for the biotechnology and pharmaceutical industries, where efficient membrane protein production is essential for drug development and various applications. Full article
(This article belongs to the Section Cellular and Molecular Bioengineering)
►▼ Show Figures

Figure 1

14 pages, 2718 KiB  
Article
An Explainable Fusion of ECG and SpO2-Based Models for Real-Time Sleep Apnea Detection
by Tanmoy Paul, Omiya Hassan, Christina S. McCrae, Syed Kamrul Islam and Abu Saleh Mohammad Mosa
Bioengineering 2025, 12(4), 382; https://doi.org/10.3390/bioengineering12040382 - 3 Apr 2025
Viewed by 1044
Abstract
Obstructive sleep apnea (OSA) is a common disorder characterized by disrupted breathing during sleep, leading to serious health consequences such as daytime fatigue, hypertension, metabolic issues, and cardiovascular disease. Polysomnography (PSG) is the standard diagnostic method but is costly and uncomfortable for patients, [...] Read more.
Obstructive sleep apnea (OSA) is a common disorder characterized by disrupted breathing during sleep, leading to serious health consequences such as daytime fatigue, hypertension, metabolic issues, and cardiovascular disease. Polysomnography (PSG) is the standard diagnostic method but is costly and uncomfortable for patients, which has led to interest in artificial intelligence (AI) for automated OSA detection. To develop an explainable AI model that utilizes electrocardiogram (ECG) and blood oxygen saturation (SpO2) data for real-time apnea detection, providing visual explanations to enhance interpretability and support clinical decisions. It emphasizes giving visual explanations to show how specific segments of the signal contribute to the AI’s conclusions. Furthermore, it explores the combination of individual models to improve detection accuracy. The fusion of individual models demonstrates an enhanced performance in detection accuracy. Visual explanations for AI decisions highlight the importance of certain signal features, making the model’s operations transparent to healthcare providers. The proposed AI model addresses the crucial need for transparent and interpretable AI in healthcare. By providing real-time, explainable OSA detection, this approach represents a significant advancement in the field, potentially improving patient care and aiding in the early identification and management of OSA. Full article
(This article belongs to the Special Issue Wearable Sensors and Measurement Systems for Human Physiology Monitoring)
►▼ Show Figures

Figure 1

31 pages, 55958 KiB  
Article
Computational Modelling of Protected and Unprotected Head Impacts in Rugby
by Thea Hodges, Adam Jones, Lucía Pérez del Olmo, Ashwin Mishra, Brian Caulfield, Tahar Kechadi, David MacManus and Michael D. Gilchrist
Bioengineering 2025, 12(4), 361; https://doi.org/10.3390/bioengineering12040361 - 31 Mar 2025
Viewed by 692
Abstract
This study involved the simulation of five real-world head impact events in rugby, to assess the level of protection provided by a novel foam headguard, the N-Pro. The University College Dublin Brain Trauma Model (UCDBTM) was used to estimate the peak resultant head [...] Read more.
This study involved the simulation of five real-world head impact events in rugby, to assess the level of protection provided by a novel foam headguard, the N-Pro. The University College Dublin Brain Trauma Model (UCDBTM) was used to estimate the peak resultant head accelerations and brain tissue responses in different head impact scenarios. The input kinematics were obtained from two sources: video analysis of impact events, and real-time data obtained through instrumented mouthguards. The impact events were simulated under both unprotected and protected conditions. All simulations were performed against a rigid, non-compliant surface model. The results obtained in this study demonstrate the significant potential of the N-Pro in reducing peak head accelerations and brain tissue stress/strain responses by up to c. 70% compared to unprotected head impacts. This study highlights the headguard’s promising potential to reduce the severity of impact-related injuries by effectively attenuating stresses and strains, as well as linear and rotational kinematics. Additionally, the study supports the recommendation in the literature that kinematic data collected from wearable sensors should be supplemented by video analysis to improve accident reconstructions. Full article
(This article belongs to the Section Biomechanics and Sports Medicine)
►▼ Show Figures

Figure 1

18 pages, 2351 KiB  
Review
Pulsed Field Ablation: A Review of Preclinical and Clinical Studies
by Andrew P. Sullivan, Martin Aguilar and Zachary Laksman
Bioengineering 2025, 12(4), 329; https://doi.org/10.3390/bioengineering12040329 - 22 Mar 2025
Viewed by 2482
Abstract
Pulsed field ablation (PFA) is an emerging technology that utilizes ultra-short high-voltage electric pulses to create nanopores in cell membranes, leading to cell death through irreversible electroporation (IRE). PFA is touted to be highly tissue-selective, which may mitigate the risk of collateral injury [...] Read more.
Pulsed field ablation (PFA) is an emerging technology that utilizes ultra-short high-voltage electric pulses to create nanopores in cell membranes, leading to cell death through irreversible electroporation (IRE). PFA is touted to be highly tissue-selective, which may mitigate the risk of collateral injury to vital adjacent structures. In the field of cardiac electrophysiology, initial studies have shown promising results for acute pulmonary vein isolation (PVI) and lesion durability, with overall freedom from recurrent atrial arrhythmia comparable to traditional thermal ablation modalities. While further large studies are required for long-term efficacy and safety data, PFA has the potential to become a preferred energy source for cardiac ablation for some indications. This review outlines the basic principles and biophysics of IRE and its application to cardiac electrophysiology through a review of the existing preclinical and clinical data. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
►▼ Show Figures

Figure 1

49 pages, 8327 KiB  
Review
The Transformation Experiment of Frederick Griffith I: Its Narrowing and Potential for the Creation of Novel Microorganisms
by Günter A. Müller
Bioengineering 2025, 12(3), 324; https://doi.org/10.3390/bioengineering12030324 - 20 Mar 2025
Cited by 1 | Viewed by 1746
Abstract
The construction of artificial microorganisms often relies on the transfer of genomes from donor to acceptor cells. This synthetic biology approach has been considerably fostered by the J. Craig Venter Institute but apparently depends on the use of microorganisms, which are very closely [...] Read more.
The construction of artificial microorganisms often relies on the transfer of genomes from donor to acceptor cells. This synthetic biology approach has been considerably fostered by the J. Craig Venter Institute but apparently depends on the use of microorganisms, which are very closely related. One reason for this limitation of the “creative potential” of “classical” transformation is the requirement for adequate “fitting” of newly synthesized polypeptide components, directed by the donor genome, to interacting counterparts encoded by the pre-existing acceptor genome. Transformation was introduced in 1928 by Frederick Griffith in the course of the demonstration of the instability of pneumococci and their conversion from rough, non-pathogenic into smooth, virulent variants. Subsequently, this method turned out to be critical for the identification of DNA as the sole matter of inheritance. Importantly, the initial experimental design (1.0) also considered the inheritance of both structural (e.g., plasma membranes) and cybernetic information (e.g., metabolite fluxes), which, in cooperation, determine topological and cellular heredity, as well as fusion and blending of bacterial cells. In contrast, subsequent experimental designs (1.X) were focused on the use of whole-cell homogenates and, thereafter, of soluble and water-clear fractions deprived of all information and macromolecules other than those directing protein synthesis, including outer-membrane vesicles, bacterial prions, lipopolysaccharides, lipoproteins, cytoskeletal elements, and complexes thereof. Identification of the reasons for this narrowing may be helpful in understanding the potential of transformation for the creation of novel microorganisms. Full article
(This article belongs to the Section Biochemical Engineering)
►▼ Show Figures

Figure 1

4 pages, 395 KiB  
Editorial
Multiscale Modeling in Computational Biomechanics: A New Era with Virtual Human Twins and Contemporary Artificial Intelligence
by Tien-Tuan Dao
Bioengineering 2025, 12(3), 320; https://doi.org/10.3390/bioengineering12030320 - 20 Mar 2025
Viewed by 536
Abstract
Over the last several decades, computational biomechanics has been intensively investigated as part of the study of human body systems (musculoskeletal, cardiovascular, digestive, etc [...] Full article
(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)
►▼ Show Figures

Figure 1

3 pages, 144 KiB  
Editorial
Musculoskeletal Disorders and Diseases: Biomechanical Modeling in Sport, Health, Rehabilitation and Ergonomics
by Philippe Gorce
Bioengineering 2025, 12(3), 300; https://doi.org/10.3390/bioengineering12030300 - 16 Mar 2025
Viewed by 720
Abstract
Protecting people at work and at leisure, and improving their quality of life, is one of the major challenges faced in this century [...] Full article
(This article belongs to the Special Issue Musculoskeletal Disorders and Diseases: Biomechanical Modeling in Sport, Health, Rehabilitation and Ergonomics)
23 pages, 2755 KiB  
Review
A Sensor-Based Classification for Neuromotor Robot-Assisted Rehabilitation
by Calin Vaida, Gabriela Rus and Doina Pisla
Bioengineering 2025, 12(3), 287; https://doi.org/10.3390/bioengineering12030287 - 13 Mar 2025
Viewed by 1278
Abstract
Neurological diseases leading to motor deficits constitute significant challenges to healthcare systems. Despite technological advancements in data acquisition, sensor development, data processing, and virtual reality (VR), a suitable framework for patient-centered neuromotor robot-assisted rehabilitation using collective sensor information does not exist. An extensive [...] Read more.
Neurological diseases leading to motor deficits constitute significant challenges to healthcare systems. Despite technological advancements in data acquisition, sensor development, data processing, and virtual reality (VR), a suitable framework for patient-centered neuromotor robot-assisted rehabilitation using collective sensor information does not exist. An extensive literature review was achieved based on 124 scientific publications regarding different types of sensors and the usage of the bio-signals they measure for neuromotor robot-assisted rehabilitation. A comprehensive classification of sensors was proposed, distinguishing between specific and non-specific parameters. The classification criteria address essential factors such as the type of sensors, the data they measure, their usability, ergonomics, and their overall impact on personalized treatment. In addition, a framework designed to collect and utilize relevant data for the optimal rehabilitation process efficiently is proposed. The proposed classifications aim to identify a set of key variables that can be used as a building block for a dynamic framework tailored for personalized treatments, thereby enhancing the effectiveness of patient-centered procedures in rehabilitation. Full article
(This article belongs to the Special Issue Wearable Sensors and Measurement Systems for Human Physiology Monitoring)
►▼ Show Figures

Figure 1

16 pages, 6744 KiB  
Article
Effect of Decorin and Aligned Collagen Fibril Topography on TGF-β1 Activation of Corneal Keratocytes
by Nathaniel S. Tjahjono, Divya Subramanian, Tarik Z. Shihabeddin, Hudson D. Hicks, Victor D. Varner, W. Matthew Petroll and David W. Schmidtke
Bioengineering 2025, 12(3), 259; https://doi.org/10.3390/bioengineering12030259 - 5 Mar 2025
Viewed by 1038
Abstract
During corneal wound healing, transforming growth factor-beta 1 (TGF-β1) causes differentiation of quiescent keratocytes into myofibroblasts. Decorin has been investigated as a promising anti-fibrotic therapeutic for corneal healing due to its interaction with TGF-β1, collagen, and cell surface receptors. In this study, a [...] Read more.
During corneal wound healing, transforming growth factor-beta 1 (TGF-β1) causes differentiation of quiescent keratocytes into myofibroblasts. Decorin has been investigated as a promising anti-fibrotic therapeutic for corneal healing due to its interaction with TGF-β1, collagen, and cell surface receptors. In this study, a novel microfluidic method for coating aligned collagen fibrils with decorin was developed to mimic the presence of decorin within the corneal stroma. Decorin was found to bind selectively to collagen and remained bound for at least five days. To investigate the effects of decorin coatings on keratocyte activation, primary rabbit keratocytes were cultured in the presence of TGF-β1 for 5 days on substrates with or without decorin and stained for α-smooth muscle actin (α-SMA). The expression of α-SMA was reduced by similar amounts on monomeric collagen (40%), random collagen fibrils (32%), and aligned collagen fibrils (32%) coated with decorin as controls. However, α-SMA expression was differentially expressed between the collagen substrates not coated with decorin, with significantly lower expression on uncoated aligned collagen fibrils compared to uncoated collagen monomers. Addition of decorin directly to culture media, had a limited effect on reducing myofibroblast differentiation. Taken together, these results demonstrate the importance of topography and ECM composition on keratocyte activation. Full article
(This article belongs to the Special Issue Bioengineering and the Eye—2nd Edition)
►▼ Show Figures

Figure 1

19 pages, 1675 KiB  
Article
A Method for Polyp Segmentation Through U-Net Network
by Antonella Santone, Mario Cesarelli and Francesco Mercaldo
Bioengineering 2025, 12(3), 236; https://doi.org/10.3390/bioengineering12030236 - 26 Feb 2025
Viewed by 1365
Abstract
Early detection of colorectal polyps through endoscopic colonoscopy is crucial in reducing colorectal cancer mortality. While automated polyp segmentation has been explored to enhance detection accuracy and efficiency, challenges remain in achieving precise boundary delineation, particularly for small or flat polyps. In this [...] Read more.
Early detection of colorectal polyps through endoscopic colonoscopy is crucial in reducing colorectal cancer mortality. While automated polyp segmentation has been explored to enhance detection accuracy and efficiency, challenges remain in achieving precise boundary delineation, particularly for small or flat polyps. In this work, we propose a novel U-Net-based segmentation framework specifically optimized for real-world endoscopic colonoscopy data. Unlike conventional approaches, our method leverages high-resolution frames with pixel-level ground-truth annotations to achieve superior segmentation performance. The U-Net architecture, with its symmetric encoder-decoder design and skip connections, is further adapted to enhance both high-level contextual understanding and fine-grained detail preservation. Our model has been rigorously evaluated on a real-world dataset, demonstrating state-of-the-art accuracy in polyp boundary segmentation, even in challenging cases. By improving detection consistency and reducing observer variability, our approach provides a robust tool to support gastroenterologists in clinical decision-making. Beyond real-time clinical applications, this work contributes to advancing automated and standardized polyp detection, paving the way for more reliable AI-assisted endoscopic analysis. Full article
(This article belongs to the Special Issue Applications of Computational Modeling in Biomedical Image and Signal Processing—2nd Edition)
►▼ Show Figures

Figure 1

13 pages, 1473 KiB  
Article
Sensitivity of Lumbar Total Joint Replacement Contact Stresses Under Misalignment Conditions—Finite Element Analysis of a Spine Wear Simulator
by Steven M. Kurtz, Steven A. Rundell, Hannah Spece and Ronald V. Yarbrough
Bioengineering 2025, 12(3), 229; https://doi.org/10.3390/bioengineering12030229 - 24 Feb 2025
Cited by 1 | Viewed by 882
Abstract
A novel total joint replacement (TJR) that treats lumbar spine degeneration was previously assessed under Mode I and Mode IV conditions. In this study, we relied on these previous wear tests to establish a relationship between finite element model (FEM)-based bearing stresses and [...] Read more.
A novel total joint replacement (TJR) that treats lumbar spine degeneration was previously assessed under Mode I and Mode IV conditions. In this study, we relied on these previous wear tests to establish a relationship between finite element model (FEM)-based bearing stresses and in vitro wear penetration maps. Our modeling effort addressed the following question of interest: Under reasonably worst-case misaligned conditions, do the lumbar total joint replacement (L-TJR) polyethylene stresses and strains remain below values associated with Mode IV impingement wear tests? The FEM was first formally verified and validated using the risk-informed credibility assessment framework established by ASME V&V 40 and FDA guidance. Then, based on criteria for unreasonable misuse outlined in the surgical technique guide, a parametric analysis of reasonably worst-case misalignment using the validated L-TJR FEM was performed. Reasonable misalignment was created by altering device positioning from the baseline condition in three scenarios: Axial Plane Convergence (20–40°), Axial Plane A-P Offset (0–4 mm), and Coronal Plane Tilt (±20°). We found that, for the scenarios considered, the contact pressures, von Mises stresses, and effective strains of the L-TJR-bearing surfaces remained consistent with Mode I (clean) conditions. Specifically, the mechanical response values fell below those determined under Mode IV (worst-case) boundary conditions, which provided the upper-bound benchmarks for the study (peak contact pressure 83.3 MPa, peak von Mises stress 32.2 MPa, and peak effective strain 42%). The L-TJR was judged to be insensitive to axial and coronal misalignment under the in vitro boundary conditions imposed by the study. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
►▼ Show Figures

Figure 1

2 pages, 143 KiB  
Editorial
Bioengineering of the Motor System
by Carlo Albino Frigo
Bioengineering 2025, 12(2), 199; https://doi.org/10.3390/bioengineering12020199 - 18 Feb 2025
Viewed by 510
Abstract
About fifty years ago, which seems very recent, new technologies for motion analysis were being developed, promising a more detailed and precise study of the human motor system [...] Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
13 pages, 480 KiB  
Review
Applications of Machine Learning-Driven Molecular Models for Advancing Ophthalmic Precision Medicine
by Rahul Kumar, Joshua Ong, Ethan Waisberg, Ryung Lee, Tuan Nguyen, Phani Paladugu, Maria Chiara Rivolta, Chirag Gowda, John Vincent Janin, Jeremy Saintyl, Dylan Amiri, Ansh Gosain and Ram Jagadeesan
Bioengineering 2025, 12(2), 156; https://doi.org/10.3390/bioengineering12020156 - 6 Feb 2025
Viewed by 1466
Abstract
Ophthalmic diseases such as glaucoma, age-related macular degeneration (ARMD), and optic neuritis involve complex molecular and cellular disruptions that challenge current diagnostic and therapeutic approaches. Advanced artificial intelligence (AI) and machine learning (ML) models offer a novel lens to analyze these diseases by [...] Read more.
Ophthalmic diseases such as glaucoma, age-related macular degeneration (ARMD), and optic neuritis involve complex molecular and cellular disruptions that challenge current diagnostic and therapeutic approaches. Advanced artificial intelligence (AI) and machine learning (ML) models offer a novel lens to analyze these diseases by integrating diverse datasets, identifying patterns, and enabling precision medicine strategies. Over the past decade, applications of AI in ophthalmology have expanded from imaging-based diagnostics to molecular-level modeling, bridging critical gaps in understanding disease mechanisms. This paper systematically reviews the application of AI-driven methods, including reinforcement learning (RL), graph neural networks (GNNs), Bayesian inference, and generative adversarial networks (GANs), in the context of these ophthalmic conditions. RL models simulate transcription factor dynamics in hypoxic or inflammatory environments, offering insights into disrupted molecular pathways. GNNs map intricate molecular networks within affected tissues, identifying key inflammatory or degenerative drivers. Bayesian inference provides probabilistic models for predicting disease progression and response to therapies, while GANs generate synthetic datasets to explore therapeutic interventions. By contextualizing these AI tools within the broader framework of ophthalmic disease management, this review highlights their potential to transform diagnostic precision and therapeutic outcomes. Ultimately, this work underscores the need for continued interdisciplinary collaboration to harness AI’s potential in advancing the field of ophthalmology and improving patient care. Full article
(This article belongs to the Special Issue Translational AI and Computational Tools for Ophthalmic Disease)
►▼ Show Figures

Figure 1

3 pages, 130 KiB  
Editorial
Editorial: Biomechanics, Health, Disease and Rehabilitation—2nd Edition
by Redha Taiar
Bioengineering 2025, 12(2), 121; https://doi.org/10.3390/bioengineering12020121 - 28 Jan 2025
Viewed by 786
Abstract
In the original article [...] Full article
(This article belongs to the Special Issue Biomechanics, Health, Disease and Rehabilitation, 2nd Edition)
17 pages, 7767 KiB  
Article
A Novel Mechanics-Based Design for Overcorrection in Clear Aligner Orthodontics via Finite Element Analysis
by Sensen Yang and Yumin Cheng
Bioengineering 2025, 12(2), 110; https://doi.org/10.3390/bioengineering12020110 - 24 Jan 2025
Viewed by 1341
Abstract
A simplified mechanics model of aligner–tooth interaction was developed to establish a precise computational method for overcorrection design in clear aligner orthodontics. Validated through finite element analysis and experiments, the results demonstrated that designing the movement of only the target teeth on the [...] Read more.
A simplified mechanics model of aligner–tooth interaction was developed to establish a precise computational method for overcorrection design in clear aligner orthodontics. Validated through finite element analysis and experiments, the results demonstrated that designing the movement of only the target teeth on the aligner leads to uneven force distribution on adjacent teeth, while an overcorrection design can evenly distribute the reaction force generated by pushing the target teeth to the anchorage teeth, reducing the maximum force on the anchorage teeth, minimizing unplanned tooth movement, and improving the efficacy of the designed tooth movement for all teeth. Full article
(This article belongs to the Special Issue Orthodontic Biomechanics)
►▼ Show Figures

Graphical abstract

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
Cited by 2 | Viewed by 1746
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)
►▼ Show Figures

Graphical abstract

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
Cited by 5 | Viewed by 2037
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)
►▼ Show Figures

Figure 1

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 1073
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)
►▼ Show Figures

Figure 1

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 1492
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)
►▼ Show Figures

Figure 1

19 pages, 5155 KiB  
Article
Ex Vivo Regional Gene Therapy Compared to Recombinant BMP-2 for the Treatment of Critical-Size Bone Defects: An In Vivo Single-Cell RNA-Sequencing Study
by Arijita Sarkar, Matthew C. Gallo, Jennifer A. Bell, Cory K. Mayfield, Jacob R. Ball, Mina Ayad, Elizabeth Lechtholz-Zey, Stephanie W. Chang, Osamu Sugiyama, Denis Evseenko and Jay R. Lieberman
Bioengineering 2025, 12(1), 29; https://doi.org/10.3390/bioengineering12010029 - 1 Jan 2025
Viewed by 1797
Abstract
Ex vivo regional gene therapy is a promising tissue-engineering strategy for bone regeneration: osteogenic mesenchymal stem cells (MSCs) can be genetically modified to express an osteoinductive stimulus (e.g., bone morphogenetic protein-2), seeded onto an osteoconductive scaffold, and then implanted into a bone defect [...] Read more.
Ex vivo regional gene therapy is a promising tissue-engineering strategy for bone regeneration: osteogenic mesenchymal stem cells (MSCs) can be genetically modified to express an osteoinductive stimulus (e.g., bone morphogenetic protein-2), seeded onto an osteoconductive scaffold, and then implanted into a bone defect to exert a therapeutic effect. Compared to recombinant human BMP-2 (rhBMP-2), which is approved for clinical use, regional gene therapy may have unique benefits related to the addition of MSCs and the sustained release of BMP-2. However, the cellular and transcriptional mechanisms regulating the response to these two strategies for BMP-2 mediated bone regeneration are largely unknown. Here, for the first time, we performed single-cell RNA sequencing (10x Genomics) of hematoma tissue in six rats with critical-sized femoral defects that were treated with either regional gene therapy or rhBMP-2. Our unbiased bioinformatic analysis of 2393 filtered cells in each group revealed treatment-specific differences in their cellular composition, transcriptional profiles, and cellular communication patterns. Gene therapy treatment induced a more robust chondrogenic response, as well as a decrease in the proportion of fibroblasts and the expression of profibrotic pathways. Additionally, gene therapy was associated with an anti-inflammatory microenvironment; macrophages expressing canonical anti-inflammatory markers were more common in the gene therapy group. In contrast, pro-inflammatory markers were more highly expressed in the rhBMP-2 group. Collectively, the results of our study may offer insights into the unique pathways through which ex vivo regional gene therapy can augment bone regeneration compared to rhBMP-2. Furthermore, an improved understanding of the cellular pathways involved in segmental bone defect healing may allow for the further optimization of regional gene therapy or other bone repair strategies. Full article
(This article belongs to the Special Issue Advances in Bone Regeneration with Multipotential Stromal Cells and Bioactive Materials)
►▼ Show Figures

Graphical abstract

15 pages, 3329 KiB  
Article
The Effect of Thigh Muscle Forces on Knee Contact Force in Female Patients with Severe Knee Osteoarthritis
by Tingting Liu, Hao Xie, Songhua Yan, Jizhou Zeng and Kuan Zhang
Bioengineering 2024, 11(12), 1299; https://doi.org/10.3390/bioengineering11121299 - 20 Dec 2024
Cited by 2 | Viewed by 1289
Abstract
Thigh muscles greatly influence knee joint loading, and abnormal loading significantly contributes to the progression of knee osteoarthritis (KOA). Muscle weakness in KOA patients is common, but the specific contribution of each thigh muscle to joint loading is unclear. The gait data from [...] Read more.
Thigh muscles greatly influence knee joint loading, and abnormal loading significantly contributes to the progression of knee osteoarthritis (KOA). Muscle weakness in KOA patients is common, but the specific contribution of each thigh muscle to joint loading is unclear. The gait data from 10 severe female KOA patients and 10 controls were collected, and the maximum isometric forces of the biceps femoris long head (BFL), semitendinosus (ST), rectus femoris (RF), vastus lateralis (VL), and vastus medialis (VM) were calibrated via ultrasound. Four musculoskeletal (MSK) models were developed based on EMG-assisted optimization, static optimization, and ultrasound data. The ultrasound-calibrated EMG-assisted MSK model achieved higher accuracy (R2 > 0.97, RMSE < 0.045 Nm/kg). Patients exhibited increased VL and VM forces (p < 0.004) and decreased RF force (p < 0.006), along with elevated medial and total joint contact forces (p < 0.001) and reduced lateral forces (p < 0.001) compared to controls. The affected side relied on VL and BFL the most (p < 0.042), while RF was key for the unaffected side (p < 0.003). Ultrasound calibration and EMG-assisted optimization significantly enhanced MSK model accuracy. Patients exerted greater quadriceps and hamstring forces bilaterally, shifting knee loading medially, and depended more on the lateral thigh muscles on the affected side. Hamstrings contributed more to joint contact forces, while quadriceps’ contributions decreased. Full article
(This article belongs to the Special Issue Joint Biomechanics and Implant Design)
►▼ Show Figures

Figure 1

17 pages, 5821 KiB  
Article
Development of a Microfluidic Viscometer for Non-Newtonian Blood Analog Fluid Analysis
by Yii-Nuoh Chang and Da-Jeng Yao
Bioengineering 2024, 11(12), 1298; https://doi.org/10.3390/bioengineering11121298 - 20 Dec 2024
Cited by 2 | Viewed by 4791
Abstract
The incidence of stroke is on the rise globally. This affects one in every four individuals each year, underscoring the urgent need for early warning and prevention systems. The existing research highlights the significance of monitoring blood viscosity in stroke risk evaluations. However, [...] Read more.
The incidence of stroke is on the rise globally. This affects one in every four individuals each year, underscoring the urgent need for early warning and prevention systems. The existing research highlights the significance of monitoring blood viscosity in stroke risk evaluations. However, the current methods lack the precision to measure viscosity under low shear rate conditions (<100 s⁻¹), which are observed during pulsatility flow. This study addresses this gap by introducing a novel microfluidic platform designed to measure blood viscosity with high precision under pulsatility flow conditions. The systolic blood viscosity (SBV) and diastolic blood viscosity (DBV) can be differentiated and evaluated by using this system. The non-Newtonian behavior of blood is captured across specific shear rate conditions. The platform employs a meticulously designed microarray to simulate the variations in blood viscosity during pulsation within blood vessels.The results demonstrate an impressive accuracy of 95% and excellent reproducibility when compared to traditional viscometers and rheometers and are within the human blood viscosity range of 1–10 cP. This monitoring system holds promise as a valuable addition to stroke risk evaluation methods, with the potential to enhance prediction accuracy. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
►▼ Show Figures

Figure 1

12 pages, 1677 KiB  
Review
Microfluidic Technology for Measuring Mechanical Properties of Single Cells and Its Application
by Yixin Yin and Ziyuan Liu
Bioengineering 2024, 11(12), 1266; https://doi.org/10.3390/bioengineering11121266 - 13 Dec 2024
Cited by 1 | Viewed by 1389
Abstract
Cellular mechanical properties are critical for tissue and organ homeostasis, which are associated with many diseases and are very promising non-labeled biomarkers. Over the past two decades, many research tools based on microfluidic methods have been developed to measure the biophysical properties of [...] Read more.
Cellular mechanical properties are critical for tissue and organ homeostasis, which are associated with many diseases and are very promising non-labeled biomarkers. Over the past two decades, many research tools based on microfluidic methods have been developed to measure the biophysical properties of single cells; however, it has still not been possible to develop a technique that allows for high-throughput, easy-to-operate and precise measurements of single-cell biophysical properties. In this paper, we review the emerging technologies implemented based on microfluidic approaches for characterizing the mechanical properties of single cells and discuss the methodological principles, advantages, limitations, and applications of various technologies. Full article
(This article belongs to the Section Biomechanics and Sports Medicine)
►▼ Show Figures

Figure 1

16 pages, 5144 KiB  
Systematic Review
Progress in 3D Printing Applications for the Management of Orbital Disorders: A Systematic Review
by Luca Michelutti, Alessandro Tel, Massimo Robiony, Salvatore Sembronio, Riccardo Nocini, Edoardo Agosti, Tamara Ius, Caterina Gagliano and Marco Zeppieri
Bioengineering 2024, 11(12), 1238; https://doi.org/10.3390/bioengineering11121238 - 7 Dec 2024
Cited by 2 | Viewed by 1389
Abstract
Introduction: 3D printing technology has gained considerable interest in the domain of orbital illnesses owing to its capacity to transform diagnosis, surgery planning, and treatment. This systematic review seeks to deliver a thorough examination of the contemporary applications of 3D printing in [...] Read more.
Introduction: 3D printing technology has gained considerable interest in the domain of orbital illnesses owing to its capacity to transform diagnosis, surgery planning, and treatment. This systematic review seeks to deliver a thorough examination of the contemporary applications of 3D printing in the treatment of ocular problems, encompassing tumors, injuries, and congenital defects. This systematic review of recent studies has examined the application of patient-specific 3D-printed models for preoperative planning, personalized implants, and prosthetics. Methods: This systematic review was conducted according to the PRISMA guidelines. The PICOS is “What are the current advances and applications of 3D printing for the management of orbital pathology?” The databases analyzed for the research phase are MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov, ScienceDirect, Scopus, CINAHL, and Web of Science. Results: Out of 314 studies found in the literature, only 12 met the inclusion and exclusion criteria. From the included studies, it is evident that 3D printing can be a useful technology for the management of trauma and oncological pathologies of the orbital region. Discussion: 3D printing proves to be very useful mainly for the purpose of improving the preoperative planning of a surgical procedure, allowing for better preparation by the surgical team and a reduction in operative time and complications. Conclusions: 3D printing has proven to be an outstanding tool in the management of orbit pathology. Comparing the advantages and disadvantages of such technology, the former far outweigh the latter. Full article
(This article belongs to the Special Issue New Sights of Biomaterials and Regenerative Medicine)
►▼ Show Figures

Graphical abstract

12 pages, 576 KiB  
Article
The Effect of EEG Biofeedback Training Frequency and Environmental Conditions on Simple and Complex Reaction Times
by Skalski Dariusz, Maciej Kostrzewa, Prończuk Magdalena, Jarosław Markowski, Jan Pilch, Marcin Żak and Adam Maszczyk
Bioengineering 2024, 11(12), 1208; https://doi.org/10.3390/bioengineering11121208 - 29 Nov 2024
Cited by 4 | Viewed by 1235
Abstract
The objective of this study is to evaluate the impact of EEG biofeedback training under normoxic and normobaric hypoxic conditions on both simple and complex reaction times in judo athletes, and to identify the optimal training frequency and environmental conditions that substantially enhance [...] Read more.
The objective of this study is to evaluate the impact of EEG biofeedback training under normoxic and normobaric hypoxic conditions on both simple and complex reaction times in judo athletes, and to identify the optimal training frequency and environmental conditions that substantially enhance reaction times in the examined athlete groups. The study comprised 20 male judo athlete members of the Polish national judo team in the middleweight and heavyweight categories. We randomly assigned participants to an experimental group and a control group. We conducted the research over four cycles, varying the frequency of EEG biofeedback sessions and environmental circumstances for both the experimental and control groups. Every research cycle had 15 training sessions. The results showed that the experimental group, following the theta/beta regimen, got significantly faster at complex reactions after a training cycle that included sessions every other day at normal oxygen levels. Following daily training sessions in normoxic circumstances, we noted enhancements in simple reaction speeds. Under normobaric hypoxia conditions, the judo athletes showed deterioration in both simple and complex reaction times. The control group showed no similar changes. Daily EEG training in normoxic settings markedly improved simple reaction time, but EEG-BF training conducted every other day greatly raised complicated reaction time. In contrast, training under normobaric hypoxia settings did not result in enhancements in basic or complicated reaction times following EEG training. Full article
(This article belongs to the Special Issue New Sights of EEG and Brain Diseases: Updates and Directions)
►▼ Show Figures

Figure 1

3 pages, 153 KiB  
Editorial
Computational Fluid Dynamics in Medicine and Biology
by Amirtahà Taebi
Bioengineering 2024, 11(11), 1168; https://doi.org/10.3390/bioengineering11111168 - 20 Nov 2024
Viewed by 1472
Abstract
This Special Issue of Bioengineering presents cutting-edge research on the applications of computational fluid dynamics (CFD) in medical and biological contexts [...] Full article
(This article belongs to the Special Issue Computational Fluid Dynamics in Medicine and Biology)
30 pages, 8578 KiB  
Article
Around-Body Versus On-Body Motion Sensing: A Comparison of Efficacy Across a Range of Body Movements and Scales
by Katelyn Rohrer, Luis De Anda, Camila Grubb, Zachary Hansen, Jordan Rodriguez, Greyson St Pierre, Sara Sheikhlary, Suleyman Omer, Binh Tran, Mehrail Lawendy, Farah Alqaraghuli, Chris Hedgecoke, Youssif Abdelkeder, Rebecca C. Slepian, Ethan Ross, Ryan Chung and Marvin J. Slepian
Bioengineering 2024, 11(11), 1163; https://doi.org/10.3390/bioengineering11111163 - 19 Nov 2024
Viewed by 1223
Abstract
Motion is vital for life. Currently, the clinical assessment of motion abnormalities is largely qualitative. We previously developed methods to quantitatively assess motion using visual detection systems (around-body) and stretchable electronic sensors (on-body). Here we compare the efficacy of these methods across predefined [...] Read more.
Motion is vital for life. Currently, the clinical assessment of motion abnormalities is largely qualitative. We previously developed methods to quantitatively assess motion using visual detection systems (around-body) and stretchable electronic sensors (on-body). Here we compare the efficacy of these methods across predefined motions, hypothesizing that the around-body system detects motion with similar accuracy as on-body sensors. Six human volunteers performed six defined motions covering three excursion lengths, small, medium, and large, which were analyzed via both around-body visual marker detection (MoCa version 1.0) and on-body stretchable electronic sensors (BioStamp version 1.0). Data from each system was compared as to the extent of trackability and comparative efficacy between systems. Both systems successfully detected motions, allowing quantitative analysis. Angular displacement between systems had the highest agreement efficiency for the bicep curl and body lean motion, with 73.24% and 65.35%, respectively. The finger pinch motion had an agreement efficiency of 36.71% and chest abduction/adduction had 45.55%. Shoulder abduction/adduction and shoulder flexion/extension motions had the lowest agreement efficiencies with 24.49% and 26.28%, respectively. MoCa was comparable to BioStamp in terms of angular displacement, though velocity and linear speed output could benefit from additional processing. Our findings demonstrate comparable efficacy for non-contact motion detection to that of on-body sensor detection, and offers insight as to the best system selection for specific clinical uses based on the use-case of the desired motion being analyzed. Full article
(This article belongs to the Special Issue Biomechanics and Motion Analysis)
►▼ Show Figures

Figure 1

9 pages, 2282 KiB  
Article
Computational Fluid Dynamic Optimization of Micropatterned Surfaces: Towards Biofunctionalization of Artificial Organs
by Wenxuan He, Aminat M. Ibrahim, Abhishek Karmakar, Shivani Tuli, Jonathan T. Butcher and James F. Antaki
Bioengineering 2024, 11(11), 1092; https://doi.org/10.3390/bioengineering11111092 - 30 Oct 2024
Viewed by 1321
Abstract
Modifying surface topography to prevent surface-induced thrombosis in cardiovascular implants allows endothelialization, which is the natural thrombo-resistance of blood-contacting surfaces, and is deemed to be the only long-term solution for hemocompatible materials. We adapted a simulation framework to predict platelet deposition on a [...] Read more.
Modifying surface topography to prevent surface-induced thrombosis in cardiovascular implants allows endothelialization, which is the natural thrombo-resistance of blood-contacting surfaces, and is deemed to be the only long-term solution for hemocompatible materials. We adapted a simulation framework to predict platelet deposition on a modified surface and developed an optimization strategy to promote endothelial retention and limit platelet deposition. Under supraphysiological bulk shear stress, a maximum of 79% linear coverage was achieved. This study concludes that the addition of microtrenches promotes endothelial retention and can be improved through the optimal selection of geometric parameters. Full article
(This article belongs to the Special Issue Engineered Analysis of Tissue Mechanics and Blood Flow for Cardiovascular Host-Device Interaction)
►▼ Show Figures

Figure 1

5 pages, 184 KiB  
Editorial
Interdisciplinary Innovations and Applications of Bionics and Bioengineering in Kinesiology
by Wei-Hsun Tai, Wenjian Wu, Haibin Yu and Rui Zhang
Bioengineering 2024, 11(10), 1042; https://doi.org/10.3390/bioengineering11101042 - 18 Oct 2024
Viewed by 1865
Abstract
Kinesiology, as an interdisciplinary field, emphasizes the study of human physical activity, with a particular focus on biomechanics and sports science [...] Full article
(This article belongs to the Special Issue Biomechanics and Bionics in Sport and Exercise, Volume II)
15 pages, 2088 KiB  
Review
The Psychological Nature of Female Gait Attractiveness
by Hiroko Tanabe and Kota Yamamoto
Bioengineering 2024, 11(10), 1037; https://doi.org/10.3390/bioengineering11101037 - 17 Oct 2024
Cited by 2 | Viewed by 2522
Abstract
Walking, a basic physical movement of the human body, is a resource for observers in forming interpersonal impressions. We have previously investigated the expression and perception of the attractiveness of female gaits. In this paper, drawing on our previous research, additional analysis, and [...] Read more.
Walking, a basic physical movement of the human body, is a resource for observers in forming interpersonal impressions. We have previously investigated the expression and perception of the attractiveness of female gaits. In this paper, drawing on our previous research, additional analysis, and reviewing previous studies, we seek to deepen our understanding of the function of gait attractiveness. First, we review previous research on gait as nonverbal information. Then, we show that fashion models’ gaits reflect sociocultural genderlessness, while nonmodels express reproductive-related biological attractiveness. Next, we discuss the functions of gait attractiveness based on statistical models that link gait parameters and attractiveness scores. Finally, we focus on observers’ perception of attractiveness, constructing a model of the visual information processing with respect to gait attractiveness. Overall, our results suggest that there are not only biological but also sociocultural criteria for gait attractiveness, and men and women place greater importance on the former and latter criteria, respectively, when assessing female gait attractiveness. This paper forms a major step forward in neuroaesthetics to understand the beauty of the human body and the generation of biological motions. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
►▼ Show Figures

Figure 1

22 pages, 2282 KiB  
Article
Emotion Recognition Using EEG Signals and Audiovisual Features with Contrastive Learning
by Ju-Hwan Lee, Jin-Young Kim and Hyoung-Gook Kim
Bioengineering 2024, 11(10), 997; https://doi.org/10.3390/bioengineering11100997 - 3 Oct 2024
Cited by 7 | Viewed by 3419
Abstract
Multimodal emotion recognition has emerged as a promising approach to capture the complex nature of human emotions by integrating information from various sources such as physiological signals, visual behavioral cues, and audio-visual content. However, current methods often struggle with effectively processing redundant or [...] Read more.
Multimodal emotion recognition has emerged as a promising approach to capture the complex nature of human emotions by integrating information from various sources such as physiological signals, visual behavioral cues, and audio-visual content. However, current methods often struggle with effectively processing redundant or conflicting information across modalities and may overlook implicit inter-modal correlations. To address these challenges, this paper presents a novel multimodal emotion recognition framework which integrates audio-visual features with viewers’ EEG data to enhance emotion classification accuracy. The proposed approach employs modality-specific encoders to extract spatiotemporal features, which are then aligned through contrastive learning to capture inter-modal relationships. Additionally, cross-modal attention mechanisms are incorporated for effective feature fusion across modalities. The framework, comprising pre-training, fine-tuning, and testing phases, is evaluated on multiple datasets of emotional responses. The experimental results demonstrate that the proposed multimodal approach, which combines audio-visual features with EEG data, is highly effective in recognizing emotions, highlighting its potential for advancing emotion recognition systems. 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)
►▼ Show Figures

Figure 1

33 pages, 3011 KiB  
Review
Building an Ethical and Trustworthy Biomedical AI Ecosystem for the Translational and Clinical Integration of Foundation Models
by Baradwaj Simha Sankar, Destiny Gilliland, Jack Rincon, Henning Hermjakob, Yu Yan, Irsyad Adam, Gwyneth Lemaster, Dean Wang, Karol Watson, Alex Bui, Wei Wang and Peipei Ping
Bioengineering 2024, 11(10), 984; https://doi.org/10.3390/bioengineering11100984 - 29 Sep 2024
Cited by 5 | Viewed by 4219
Abstract
Foundation Models (FMs) are gaining increasing attention in the biomedical artificial intelligence (AI) ecosystem due to their ability to represent and contextualize multimodal biomedical data. These capabilities make FMs a valuable tool for a variety of tasks, including biomedical reasoning, hypothesis generation, and [...] Read more.
Foundation Models (FMs) are gaining increasing attention in the biomedical artificial intelligence (AI) ecosystem due to their ability to represent and contextualize multimodal biomedical data. These capabilities make FMs a valuable tool for a variety of tasks, including biomedical reasoning, hypothesis generation, and interpreting complex imaging data. In this review paper, we address the unique challenges associated with establishing an ethical and trustworthy biomedical AI ecosystem, with a particular focus on the development of FMs and their downstream applications. We explore strategies that can be implemented throughout the biomedical AI pipeline to effectively tackle these challenges, ensuring that these FMs are translated responsibly into clinical and translational settings. Additionally, we emphasize the importance of key stewardship and co-design principles that not only ensure robust regulation but also guarantee that the interests of all stakeholders—especially those involved in or affected by these clinical and translational applications—are adequately represented. We aim to empower the biomedical AI community to harness these models responsibly and effectively. As we navigate this exciting frontier, our collective commitment to ethical stewardship, co-design, and responsible translation will be instrumental in ensuring that the evolution of FMs truly enhances patient care and medical decision-making, ultimately leading to a more equitable and trustworthy biomedical AI ecosystem. Full article
(This article belongs to the Special Issue Machine Learning Technology in Biomedical Engineering—2nd Edition)
►▼ Show Figures

Figure 1

6 pages, 213 KiB  
Editorial
Microalgae Biotechnology: Methods and Applications
by Xianmin Wang, Songlin Ma and Fantao Kong
Bioengineering 2024, 11(10), 965; https://doi.org/10.3390/bioengineering11100965 - 26 Sep 2024
Cited by 6 | Viewed by 3025
Abstract
Microalgae are regarded as sustainable and promising chassis for biotechnology due to their efficient photosynthesis and ability to convert CO2 into valuable products [...] Full article
(This article belongs to the Section Biochemical Engineering)
15 pages, 1321 KiB  
Commentary
The Use of Mesenchymal Stem/Stromal Cell-Derived Extracellular Vesicles in the Treatment of Osteoarthritis: Insights from Preclinical Studies
by Mitch Jones, Elena Jones and Dimitrios Kouroupis
Bioengineering 2024, 11(10), 961; https://doi.org/10.3390/bioengineering11100961 - 26 Sep 2024
Cited by 4 | Viewed by 1970
Abstract
Osteoarthritis (OA) is a prominent cause of disability, and has severe social and economic ramifications across the globe. The main driver of OA’s pervasiveness is the fact that no current medical interventions exist to reverse or even attenuate the degeneration of cartilage within [...] Read more.
Osteoarthritis (OA) is a prominent cause of disability, and has severe social and economic ramifications across the globe. The main driver of OA’s pervasiveness is the fact that no current medical interventions exist to reverse or even attenuate the degeneration of cartilage within the articular joint. Crucial for cell-to-cell communication, extracellular vesicles (EVs) contribute to OA progression through the delivery of bioactive molecules in the inflammatory microenvironment. By repurposing this acellular means of signal transmission, therapeutic drugs may be administered to degenerated cartilage tissue in the hopes of encouraging regeneration. Positive outcomes are apparent in in vivo studies on this subject; however, for this therapy to prove itself in the clinical world, efforts towards standardizing the characterization, application, biological contents, and dosage are essential. Full article
(This article belongs to the Section Regenerative Engineering)
►▼ Show Figures

Figure 1

23 pages, 6104 KiB  
Article
Mesenchymal Stem Cell-Conditioned Media-Loaded Microparticles Enhance Acute Patency in Silk-Based Vascular Grafts
by Katherine L. Lorentz, Ande X. Marini, Liza A. Bruk, Prerak Gupta, Biman B. Mandal, Morgan V. DiLeo, Justin S. Weinbaum, Steven R. Little and David A. Vorp
Bioengineering 2024, 11(9), 947; https://doi.org/10.3390/bioengineering11090947 - 21 Sep 2024
Cited by 1 | Viewed by 2690
Abstract
Coronary artery disease leads to over 360,000 deaths annually in the United States, and off-the-shelf bypass graft options are currently limited and/or have high failure rates. Tissue-engineered vascular grafts (TEVGs) present an attractive option, though the promising mesenchymal stem cell (MSC)-based implants face [...] Read more.
Coronary artery disease leads to over 360,000 deaths annually in the United States, and off-the-shelf bypass graft options are currently limited and/or have high failure rates. Tissue-engineered vascular grafts (TEVGs) present an attractive option, though the promising mesenchymal stem cell (MSC)-based implants face uncertain regulatory pathways. In this study, “artificial MSCs” (ArtMSCs) were fabricated by encapsulating MSC-conditioned media (CM) in poly(lactic-co-glycolic acid) microparticles. ArtMSCs and control microparticles (Blank-MPs) were incubated over 7 days to assess the release of total protein and the vascular endothelial growth factor (VEGF-A); releasates were also assessed for cytotoxicity and promotion of smooth muscle cell (SMC) proliferation. Each MP type was loaded in previously published “lyogel” silk scaffolds and implanted as interposition grafts in Lewis rats for 1 or 8 weeks. Explanted grafts were assessed for patency and cell content. ArtMSCs had a burst release of protein and VEGF-A. CM increased proliferation in SMCs, but not after encapsulation. TEVG explants after 1 week had significantly higher patency rates with ArtMSCs compared to Blank-MPs, but similar to unseeded lyogel grafts. ArtMSC explants had lower numbers of infiltrating macrophages compared to Blank-MP explants, suggesting a modulation of inflammatory response by the ArtMSCs. TEVG explants after 8 weeks showed no significant difference in patency among the three groups. The ArtMSC explants showed higher numbers of SMCs and endothelial cells within the neotissue layer of the graft compared to Blank-MP explants. In sum, while the ArtMSCs had positive effects acutely, efficacy was lost in the longer term; therefore, further optimization is needed. Full article
(This article belongs to the Section Regenerative Engineering)
►▼ Show Figures

Graphical abstract

15 pages, 1570 KiB  
Article
Machine Learning-Driven Prediction of Brain Age for Alzheimer’s Risk: APOE4 Genotype and Gender Effects
by Carter Woods, Xin Xing, Subash Khanal and Ai-Ling Lin
Bioengineering 2024, 11(9), 943; https://doi.org/10.3390/bioengineering11090943 - 20 Sep 2024
Cited by 1 | Viewed by 2932
Abstract
Background: Alzheimer’s disease (AD) is a leading cause of dementia, and it is significantly influenced by the apolipoprotein E4 (APOE4) gene and gender. This study aimed to use machine learning (ML) algorithms to predict brain age and assess AD risk by considering the [...] Read more.
Background: Alzheimer’s disease (AD) is a leading cause of dementia, and it is significantly influenced by the apolipoprotein E4 (APOE4) gene and gender. This study aimed to use machine learning (ML) algorithms to predict brain age and assess AD risk by considering the effects of the APOE4 genotype and gender. Methods: We collected brain volumetric MRI data and medical records from 1100 cognitively unimpaired individuals and 602 patients with AD. We applied three ML regression models—XGBoost, random forest (RF), and linear regression (LR)—to predict brain age. Additionally, we introduced two novel metrics, brain age difference (BAD) and integrated difference (ID), to evaluate the models’ performances and analyze the influences of the APOE4 genotype and gender on brain aging. Results: Patients with AD displayed significantly older brain ages compared to their chronological ages, with BADs ranging from 6.5 to 10 years. The RF model outperformed both XGBoost and LR in terms of accuracy, delivering higher ID values and more precise predictions. Comparing the APOE4 carriers with noncarriers, the models showed enhanced ID values and consistent brain age predictions, improving the overall performance. Gender-specific analyses indicated slight enhancements, with the models performing equally well for both genders. Conclusions: This study demonstrates that robust ML models for brain age prediction can play a crucial role in the early detection of AD risk through MRI brain structural imaging. The significant impact of the APOE4 genotype on brain aging and AD risk is also emphasized. These findings highlight the potential of ML models in assessing AD risk and suggest that utilizing AI for AD identification could enable earlier preventative interventions. Full article
(This article belongs to the Special Issue Recent Advances in Biomedical Imaging: 2nd Edition)
►▼ Show Figures

Graphical abstract

10 pages, 2484 KiB  
Article
Thermal Evaluation of Bone Drilling: Assessing Drill Bits and Sequential Drilling
by Sihana Rugova and Marcus Abboud
Bioengineering 2024, 11(9), 928; https://doi.org/10.3390/bioengineering11090928 - 16 Sep 2024
Cited by 5 | Viewed by 1637
Abstract
Sequential drilling is a common practice in dental implant surgery aimed at minimizing thermal damage to bone. This study evaluates the thermal effects of sequential drilling and assesses modifications to drilling protocols to manage heat generation. We utilized a custom drill press and [...] Read more.
Sequential drilling is a common practice in dental implant surgery aimed at minimizing thermal damage to bone. This study evaluates the thermal effects of sequential drilling and assesses modifications to drilling protocols to manage heat generation. We utilized a custom drill press and artificial bone models to test five drill bits under various protocols, including sequential drilling with different loads, spindle speeds, and peck drilling. Infrared thermography recorded temperature changes during the drilling process, with temperatures monitored at various depths around the osteotomy. The results reveal sequential drilling does not eliminate the thermal damage zone it creates (well over 70 °C). It creates harmful heat to surrounding bone that can spread up to 10 mm from the osteotomy. The first drill used in sequential drilling produces the highest temperatures (over 100 °C), and subsequent drill bits cannot remove the thermal trauma incurred; rather, they add to it. Modifying drill bit design and employing proper drilling techniques, such as reducing drilling RPM and load, can reduce thermal trauma by reducing friction. Inadequate management of heat can lead to prolonged recovery, increased patient discomfort, and potential long-term complications such as impaired bone-to-implant integration and chronic conditions like peri-implantitis. Ensuring healthy bone conditions is critical for successful implant outcomes. Full article
(This article belongs to the Special Issue Advanced Assessment of Medical Devices)
►▼ Show Figures

Figure 1

5 pages, 154 KiB  
Editorial
Advanced Engineering Technology in Orthopedic Research
by Rongshan Cheng, Huizhi Wang and Cheng-Kung Cheng
Bioengineering 2024, 11(9), 925; https://doi.org/10.3390/bioengineering11090925 - 15 Sep 2024
Cited by 2 | Viewed by 1367
Abstract
Musculoskeletal injuries are increasing in conjunction with the aging of populations and the rising frequency of exercise [...] Full article
(This article belongs to the Special Issue Advanced Engineering Technology in Orthopaedic Research)
18 pages, 1415 KiB  
Article
Optimizing Fall Risk Diagnosis in Older Adults Using a Bayesian Classifier and Simulated Annealing
by Enrique Hernandez-Laredo, Ángel Gabriel Estévez-Pedraza, Laura Mercedes Santiago-Fuentes and Lorena Parra-Rodríguez
Bioengineering 2024, 11(9), 908; https://doi.org/10.3390/bioengineering11090908 - 11 Sep 2024
Cited by 1 | Viewed by 1692
Abstract
The aim of this study was to improve the diagnostic ability of fall risk classifiers using a Bayesian approach and the Simulated Annealing (SA) algorithm. A total of 47 features from 181 records (40 Center of Pressure (CoP) indices and 7 patient descriptive [...] Read more.
The aim of this study was to improve the diagnostic ability of fall risk classifiers using a Bayesian approach and the Simulated Annealing (SA) algorithm. A total of 47 features from 181 records (40 Center of Pressure (CoP) indices and 7 patient descriptive variables) were analyzed. The wrapper method of feature selection using the SA algorithm was applied to optimize the cost function based on the difference of the mean minus the standard deviation of the Area Under the Curve (AUC) of the fall risk classifiers across multiple dimensions. A stratified 60–20–20% hold-out method was used for train, test, and validation sets, respectively. The results showed that although the highest performance was observed with 31 features (0.815 ± 0.110), lower variability and higher explainability were achieved with only 15 features (0.780 ± 0.055). These findings suggest that the SA algorithm is a valuable tool for feature selection for acceptable fall risk diagnosis. This method offers an alternative or complementary resource in situations where clinical tools are difficult to apply. Full article
(This article belongs to the Special Issue Musculoskeletal Disorders and Diseases: Biomechanical Modeling in Sport, Health, Rehabilitation and Ergonomics)
►▼ Show Figures

Figure 1

18 pages, 7246 KiB  
Article
Comparative Study of Alternative Methods for Measuring Leg Length Discrepancy after Robot-Assisted Total Hip Arthroplasty
by Hamad Nazmy, Giovanni Solitro, Benjamin Domb and Farid Amirouche
Bioengineering 2024, 11(8), 853; https://doi.org/10.3390/bioengineering11080853 - 21 Aug 2024
Cited by 3 | Viewed by 2148
Abstract
Background: Our study addresses the lack of consensus on measuring leg length discrepancy (LLD) after total hip arthroplasty (THA). We will assess the inter-observer variability and correlation between the five most commonly used LLD methods and investigate the use of trigonometric principles in [...] Read more.
Background: Our study addresses the lack of consensus on measuring leg length discrepancy (LLD) after total hip arthroplasty (THA). We will assess the inter-observer variability and correlation between the five most commonly used LLD methods and investigate the use of trigonometric principles in overcoming the limitations of current techniques. Methods: LLD was measured on postoperative AP pelvic radiographs using five conventional methods. CT images created a 3D computer model of the pelvis and femur. The resulting models were projected onto a 2D, used to measure LLD by the five methods. The measurements were evaluated via Taguchi analysis, a statistical method identifying the process’s most influential factors. The approach was used to assess the new trigonometric method. Results: Conventional methods demonstrated poor correlation. Methods referenced to the centers of the femoral heads were insensitive to LLD originating outside the acetabular cup. Methods referencing either the inter-ischial line or the inter-obturator foramina to the lesser trochanter were sensitive to acetabular and femoral components. Trigonometry-based measurements showed a higher correlation. Conclusions: Our results underscore clinicians’ need to specify the methods used to assess LLD. Applying trigonometric principles was shown to be accurate and reliable, but it was contingent on proper radiographic alignment. Full article
(This article belongs to the Special Issue Fundamentals of Orthopaedic Biomechanics: Implants, AI, and Innovation in Surgery)
►▼ Show Figures

Figure 1

20 pages, 4364 KiB  
Article
3D Quantitative-Amplified Magnetic Resonance Imaging (3D q-aMRI)
by Itamar Terem, Kyan Younes, Nan Wang, Paul Condron, Javid Abderezaei, Haribalan Kumar, Hillary Vossler, Eryn Kwon, Mehmet Kurt, Elizabeth Mormino, Samantha Holdsworth and Kawin Setsompop
Bioengineering 2024, 11(8), 851; https://doi.org/10.3390/bioengineering11080851 - 20 Aug 2024
Cited by 5 | Viewed by 3399
Abstract
Amplified MRI (aMRI) is a promising new technique that can visualize pulsatile brain tissue motion by amplifying sub-voxel motion in cine MRI data, but it lacks the ability to quantify the sub-voxel motion field in physical units. Here, we introduce a novel post-processing [...] Read more.
Amplified MRI (aMRI) is a promising new technique that can visualize pulsatile brain tissue motion by amplifying sub-voxel motion in cine MRI data, but it lacks the ability to quantify the sub-voxel motion field in physical units. Here, we introduce a novel post-processing algorithm called 3D quantitative amplified MRI (3D q-aMRI). This algorithm enables the visualization and quantification of pulsatile brain motion. 3D q-aMRI was validated and optimized on a 3D digital phantom and was applied in vivo on healthy volunteers for its ability to accurately measure brain parenchyma and CSF voxel displacement. Simulation results show that 3D q-aMRI can accurately quantify sub-voxel motions in the order of 0.01 of a voxel size. The algorithm hyperparameters were optimized and tested on in vivo data. The repeatability and reproducibility of 3D q-aMRI were shown on six healthy volunteers. The voxel displacement field extracted by 3D q-aMRI is highly correlated with the displacement measurements estimated by phase contrast (PC) MRI. In addition, the voxel displacement profile through the cerebral aqueduct resembled the CSF flow profile reported in previous literature. Differences in brain motion was observed in patients with dementia compared with age-matched healthy controls. In summary, 3D q-aMRI is a promising new technique that can both visualize and quantify pulsatile brain motion. Its ability to accurately quantify sub-voxel motion in physical units holds potential for the assessment of pulsatile brain motion as well as the indirect assessment of CSF homeostasis. While further research is warranted, 3D q-aMRI may provide important diagnostic information for neurological disorders such as Alzheimer’s disease. Full article
(This article belongs to the Special Issue Novel MRI Techniques and Biomedical Image Processing)
►▼ Show Figures

Figure 1

14 pages, 3003 KiB  
Article
Stable and Thin-Polymer-Based Modification of Neurovascular Stents with 2-Methacryloyloxyethyl Phosphorylcholine Polymer for Antithrombogenicity
by Naoki Inuzuka, Yasuhiro Shobayashi, Satoshi Tateshima, Yuya Sato, Yoshio Ohba, Kazuhiko Ishihara and Yuji Teramura
Bioengineering 2024, 11(8), 833; https://doi.org/10.3390/bioengineering11080833 - 15 Aug 2024
Cited by 3 | Viewed by 2828
Abstract
The advent of intracranial stents has revolutionized the endovascular treatment of cerebral aneurysms. The utilization of stents has rendered numerous cerebral aneurysm amenable to endovascular treatment, thereby obviating the need for otherwise invasive open surgical options. Stent placement has become a mainstream approach [...] Read more.
The advent of intracranial stents has revolutionized the endovascular treatment of cerebral aneurysms. The utilization of stents has rendered numerous cerebral aneurysm amenable to endovascular treatment, thereby obviating the need for otherwise invasive open surgical options. Stent placement has become a mainstream approach because of its safety and efficacy. However, further improvements are required for clinically approved devices to avoid the frequent occurrence of thrombotic complications. Therefore, controlling the thrombotic complications associated with the use of devices is of significant importance. Our group has developed a unique stent coated with a 2-methacryloyloxyethyl phosphorylcholine (MPC)-based polymer. In this study, the surface characteristics of the polymer coating were verified using X-ray photoelectron spectroscopy and atomic force microscopy. Subsequently, the antithrombotic properties of the coating were evaluated by measuring platelet count and thrombin–antithrombin complex levels of whole human blood after 3 h of incubation in a Chandler loop model. Scanning electron microscopy was utilized to examine thrombus formation on the stent surface. We observed that MPC polymer-coated stents significantly reduced thrombus formation as compared to bare stents and several clinically approved devices. Finally, the coated stents were further analyzed by implanting them in the internal thoracic arteries of pigs. Angiographic imaging and histopathological examinations that were performed one week after implantation revealed that the vascular lumen was well maintained and coated stents were integrated within the vascular endothelium without inducing adverse effects. Thus, we demonstrated the efficacy of MPC polymer coating as a viable strategy for avoiding the thrombotic risks associated with neurovascular stents. Full article
(This article belongs to the Special Issue Advanced Biomaterials, Coatings, and Techniques: Applications in Medicine)
►▼ Show Figures

Figure 1

16 pages, 5882 KiB  
Article
Perlecan: An Islet Basement Membrane Protein with Protective Anti-Inflammatory Characteristics
by Daniel Brandhorst, Heide Brandhorst, Samuel Acreman and Paul R. V. Johnson
Bioengineering 2024, 11(8), 828; https://doi.org/10.3390/bioengineering11080828 - 13 Aug 2024
Cited by 1 | Viewed by 1450
Abstract
Throughout the isolation process, human islets are subjected to destruction of the islet basement membrane (BM) and reduced oxygen supply. Reconstruction of the BM represents an option to improve islet function and survival post-transplant and may particularly be relevant for islet encapsulation devices [...] Read more.
Throughout the isolation process, human islets are subjected to destruction of the islet basement membrane (BM) and reduced oxygen supply. Reconstruction of the BM represents an option to improve islet function and survival post-transplant and may particularly be relevant for islet encapsulation devices and scaffolds. In the present study, we assessed whether Perlecan, used alone or combined with the BM proteins (BMPs) Collagen-IV and Laminin-521, has the ability to protect isolated human islets from hypoxia-induced damage. Islets isolated from the pancreas of seven different organ donors were cultured for 4–5 days at 2% oxygen in plain CMRL (sham-treated controls) or in CMRL supplemented with BMPs used either alone or in combination. Postculture, islets were characterized regarding survival, in vitro function and production of chemokines and reactive oxygen species (ROS). Individually added BMPs significantly doubled islet survival and increased in vitro function. Combining BMPs did not provide a synergistic effect. Among the tested BMPs, Perlecan demonstrated the significantly strongest inhibitory effect on chemokine and ROS production when compared with sham-treatment (p < 0.001). Perlecan may be useful to improve islet survival prior to and after transplantation. Its anti-inflammatory potency should be considered to optimise encapsulation and scaffolds to protect isolated human islets post-transplant. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying article 1-50 on page 1 of 4.
Go to page     1 2 3 4 chevron_right last_page
Back to TopTop