Journal Description
Bioengineering
Bioengineering
is an international, scientific, peer-reviewed, open access journal on the science and technology of bioengineering, published monthly online by MDPI. The Society for Regenerative Medicine (Russian Federation) (RPO) is affiliated with Bioengineering and its members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, CAPlus / SciFinder, Inspec, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Biomedical)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.7 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
4.6 (2022)
Latest Articles
Upper Midline Correction Using the Mesial-Distalslider
Bioengineering 2024, 11(5), 450; https://doi.org/10.3390/bioengineering11050450 - 01 May 2024
Abstract
Aim: The purpose of the present study is the three-dimensional (3D) analysis of molar and incisor movements that occur during the correction of the upper midline deviation by using the Mesial-Distalslider appliance. Materials and Methods: A total of 20 consecutive patients (12 women
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Aim: The purpose of the present study is the three-dimensional (3D) analysis of molar and incisor movements that occur during the correction of the upper midline deviation by using the Mesial-Distalslider appliance. Materials and Methods: A total of 20 consecutive patients (12 women and 8 men; mean age 19.6 ± 11.1 years) were selected from the Orthodontic Department of Heinrich-Heine University of Düsseldorf. To correct the upper midline deviation (>2 mm), the patients were treated with asymmetric mechanics (mesialization on one side and distalization on the contralateral side) with the aid of Mesial-Distalslider. Dental casts were taken for each patient before (T0) and after the treatment (T1). The casts were 3D digitized and the models were superimposed on the palatal anterior region. Three-dimensional molar movements and sagittal incisor movements (proclination and retroclination) were assessed for T0 and T1. Results: At the end of the treatment, the total movements of the molars resulted in 4.5 ± 2.2 mm (antero-posterior direction), −0.4 ± 2.4 mm (transverse direction) and 0.3 ± 0.9 mm (vertical direction) on the mesialization side, and −2.4 ± 1.7 mm (antero-posterior direction), −0.5 ± 1.5 mm (transverse direction) and 0.2 ± 1.4 mm (vertical direction) on the distalization side. Incisor displacement was 0.9 mm ± 1.7 (mesialization side) and 0.6 mm ± 0.7 (distalization side). Conclusion: The Mesial-Distalslider appliance could be considered a valuable tool in orthodontic treatment for upper midline correction. Within the limits of a retrospective study, asymmetric molar movements appeared possible without clinically relevant anchorage loss.
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(This article belongs to the Section Biomedical Engineering and Biomaterials)
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OCT Intensity of the Region between Outer Retina Band 2 and Band 3 as a Biomarker for Retinal Degeneration and Therapy
by
Yong Zeng, Shasha Gao, Yichao Li, Dario Marangoni, Tharindu De Silva, Wai T. Wong, Emily Y. Chew, Xun Sun, Tiansen Li, Paul A. Sieving and Haohua Qian
Bioengineering 2024, 11(5), 449; https://doi.org/10.3390/bioengineering11050449 - 01 May 2024
Abstract
Optical coherence tomography (OCT) is widely used to probe retinal structure and function. This study investigated the outer retina band (ORB) pattern and reflective intensity for the region between bands 2 and 3 (Dip) in three mouse models of inherited retinal degeneration (Rs1KO,
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Optical coherence tomography (OCT) is widely used to probe retinal structure and function. This study investigated the outer retina band (ORB) pattern and reflective intensity for the region between bands 2 and 3 (Dip) in three mouse models of inherited retinal degeneration (Rs1KO, TTLL5KO, RPE65KO) and in human AMD patients from the A2A database. OCT images were manually graded, and reflectivity signals were used to calculate the Dip ratio. Qualitative analyses demonstrated the progressive merging band 2 and band 3 in all three mouse models, leading to a reduction in the Dip ratio compared to wildtype (WT) controls. Gene replacement therapy in Rs1KO mice reverted the ORB pattern to one resembling WT and increased the Dip ratio. The degree of anatomical rescue in these mice was highly correlated with level of transgenic RS1 expression and with the restoration of ERG b-wave amplitudes. While the inner retinal cavity was significantly enlarged in dark-adapted Rs1KO mice, the Dip ratio was not altered. A reduction of the Dip ratio was also detected in AMD patients compared with healthy controls and was also positively correlated with AMD severity on the AMD score. We propose that the ORB and Dip ratio can be used as non-invasive early biomarkers for retina health, which can be used to probe therapeutic gene expression and to evaluate the effectiveness of therapy.
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(This article belongs to the Special Issue Biomedical Imaging and Analysis of the Eye: Second Edition)
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Open AccessArticle
Comparison of De-Torque and Failure Load Evaluation of Selective-Laser-Sintered CoCr, CAD-CAM ZrO, and Machined Implant Abutment/Restoration
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Fahim Vohra, Rawan Alsaif, Rawaiz Khan and Ishfaq A. Bukhari
Bioengineering 2024, 11(5), 448; https://doi.org/10.3390/bioengineering11050448 - 30 Apr 2024
Abstract
Aim: This study aimed to compare the torque loss, fracture load, compressive strength, and failure types of selective-laser-sintered cobalt chromium (SLM-Co-Cr), computer-aided design and computer-aided manufacturing zirconium oxide (CAD-CAM-ZrO), and machined titanium (Ti) implant abutments. Methods: Thirty endosseous dental implants were vertically embedded
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Aim: This study aimed to compare the torque loss, fracture load, compressive strength, and failure types of selective-laser-sintered cobalt chromium (SLM-Co-Cr), computer-aided design and computer-aided manufacturing zirconium oxide (CAD-CAM-ZrO), and machined titanium (Ti) implant abutments. Methods: Thirty endosseous dental implants were vertically embedded with machined Ti (control group), CAD-CAM-ZrO, and SLM-Co-Cr abutments. Abutment fabrication involved CAD-CAM milling and SLM technology. The de-torque assessment included preload reverse torque values (RTVs), cyclic loading, and post-RTVs using a customized protocol. Fracture load assessment employed ISO-14801 standards, and statistical analysis was conducted using ANOVA and Tukey Post hoc tests (p < 0.05). Results: In pre-load RTVs, SLM-Co-Cr showed the lowest mean torque loss (24.30 ± 2.13), followed by machined Ti (27.33 ± 2.74) and CAD-CAM-ZrO (22.07 ± 2.20). Post-load RTVs decreased for all groups. Fracture load and compressive strength were highest for SLM-Co-Cr, with significant differences among groups (p < 0.001). Fracture types included abutment failures in SLM-Co-Cr and machined Ti, while CAD-CAM-ZrO exhibited crown separation with deformation. Conclusion: SLM-Co-Cr-fabricated implant abutments exhibited superior stability and resistance to rotational forces, higher fracture loads, and greater compressive strength compared to CAD-CAM-ZrO and machined Ti.
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(This article belongs to the Special Issue Recent Progress in Dental Biomaterials)
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Open AccessArticle
AGSAM: Agent-Guided Segment Anything Model for Automatic Segmentation in Few-Shot Scenarios
by
Hao Zhou, Yao He, Xiaoxiao Cui and Zhi Xie
Bioengineering 2024, 11(5), 447; https://doi.org/10.3390/bioengineering11050447 - 30 Apr 2024
Abstract
Precise medical image segmentation of regions of interest (ROIs) is crucial for accurate disease diagnosis and progression assessment. However, acquiring high-quality annotated data at the pixel level poses a significant challenge due to the resource-intensive nature of this process. This scarcity of high-quality
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Precise medical image segmentation of regions of interest (ROIs) is crucial for accurate disease diagnosis and progression assessment. However, acquiring high-quality annotated data at the pixel level poses a significant challenge due to the resource-intensive nature of this process. This scarcity of high-quality annotated data results in few-shot scenarios, which are highly prevalent in clinical applications. To address this obstacle, this paper introduces Agent-Guided SAM (AGSAM), an innovative approach that transforms the Segment Anything Model (SAM) into a fully automated segmentation method by automating prompt generation. Capitalizing on the pre-trained feature extraction and decoding capabilities of SAM-Med2D, AGSAM circumvents the need for manual prompt engineering, ensuring adaptability across diverse segmentation methods. Furthermore, the proposed feature augmentation convolution module (FACM) enhances model accuracy by promoting stable feature representations. Experimental evaluations demonstrate AGSAM’s consistent superiority over other methods across various metrics. These findings highlight AGSAM’s efficacy in tackling the challenges associated with limited annotated data while achieving high-quality medical image segmentation.
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(This article belongs to the Section Biosignal Processing)
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Open AccessSystematic Review
Wound Modulations in Glaucoma Surgery: A Systematic Review
by
Bhoomi Dave, Monica Patel, Sruthi Suresh, Mahija Ginjupalli, Arvind Surya, Mohannad Albdour and Karanjit S. Kooner
Bioengineering 2024, 11(5), 446; https://doi.org/10.3390/bioengineering11050446 - 30 Apr 2024
Abstract
Excessive fibrosis and resultant poor control of intraocular pressure (IOP) reduce the efficacy of glaucoma surgeries. Historically, corticosteroids and anti-fibrotic agents, such as mitomycin C (MMC) and 5-fluorouracil (5-FU), have been used to mitigate post-surgical fibrosis, but these have unpredictable outcomes. Therefore, there
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Excessive fibrosis and resultant poor control of intraocular pressure (IOP) reduce the efficacy of glaucoma surgeries. Historically, corticosteroids and anti-fibrotic agents, such as mitomycin C (MMC) and 5-fluorouracil (5-FU), have been used to mitigate post-surgical fibrosis, but these have unpredictable outcomes. Therefore, there is a need to develop novel treatments which provide increased effectiveness and specificity. This review aims to provide insight into the pathophysiology behind wound healing in glaucoma surgery, as well as the current and promising future wound healing agents that are less toxic and may provide better IOP control.
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(This article belongs to the Special Issue Meeting Challenges in the Diagnosis and Treatment of Glaucoma)
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An Automated Video Analysis System for Retrospective Assessment and Real-Time Monitoring of Endoscopic Procedures (with Video)
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Yan Zhu, Ling Du, Pei-Yao Fu, Zi-Han Geng, Dan-Feng Zhang, Wei-Feng Chen, Quan-Lin Li and Ping-Hong Zhou
Bioengineering 2024, 11(5), 445; https://doi.org/10.3390/bioengineering11050445 - 30 Apr 2024
Abstract
Background and Aims: Accurate recognition of endoscopic instruments facilitates quantitative evaluation and quality control of endoscopic procedures. However, no relevant research has been reported. In this study, we aimed to develop a computer-assisted system, EndoAdd, for automated endoscopic surgical video analysis based on
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Background and Aims: Accurate recognition of endoscopic instruments facilitates quantitative evaluation and quality control of endoscopic procedures. However, no relevant research has been reported. In this study, we aimed to develop a computer-assisted system, EndoAdd, for automated endoscopic surgical video analysis based on our dataset of endoscopic instrument images. Methods: Large training and validation datasets containing 45,143 images of 10 different endoscopic instruments and a test dataset of 18,375 images collected from several medical centers were used in this research. Annotated image frames were used to train the state-of-the-art object detection model, YOLO-v5, to identify the instruments. Based on the frame-level prediction results, we further developed a hidden Markov model to perform video analysis and generate heatmaps to summarize the videos. Results: EndoAdd achieved high accuracy (>97%) on the test dataset for all 10 endoscopic instrument types. The mean average accuracy, precision, recall, and F1-score were 99.1%, 92.0%, 88.8%, and 89.3%, respectively. The area under the curve values exceeded 0.94 for all instrument types. Heatmaps of endoscopic procedures were generated for both retrospective and real-time analyses. Conclusions: We successfully developed an automated endoscopic video analysis system, EndoAdd, which supports retrospective assessment and real-time monitoring. It can be used for data analysis and quality control of endoscopic procedures in clinical practice.
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(This article belongs to the Special Issue Diagnostic Biomedical Image and Processing with Artificial Intelligence and Deep Learning)
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Open AccessReview
Innovations in Peripheral Nerve Regeneration
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Ting Chak Lam and Yiu Yan Leung
Bioengineering 2024, 11(5), 444; https://doi.org/10.3390/bioengineering11050444 - 30 Apr 2024
Abstract
The field of peripheral nerve regeneration is a dynamic and rapidly evolving area of research that continues to captivate the attention of neuroscientists worldwide. The quest for effective treatments and therapies to enhance the healing of peripheral nerves has gained significant momentum in
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The field of peripheral nerve regeneration is a dynamic and rapidly evolving area of research that continues to captivate the attention of neuroscientists worldwide. The quest for effective treatments and therapies to enhance the healing of peripheral nerves has gained significant momentum in recent years, as evidenced by the substantial increase in publications dedicated to this field. This surge in interest reflects the growing recognition of the importance of peripheral nerve recovery and the urgent need to develop innovative strategies to address nerve injuries. In this context, this article aims to contribute to the existing knowledge by providing a comprehensive review that encompasses both biomaterial and clinical perspectives. By exploring the utilization of nerve guidance conduits and pharmacotherapy, this article seeks to shed light on the remarkable advancements made in the field of peripheral nerve regeneration. Nerve guidance conduits, which act as artificial channels to guide regenerating nerves, have shown promising results in facilitating nerve regrowth and functional recovery. Additionally, pharmacotherapy approaches have emerged as potential avenues for promoting nerve regeneration, with various therapeutic agents being investigated for their neuroprotective and regenerative properties. The pursuit of advancing the field of peripheral nerve regeneration necessitates persistent investment in research and development. Continued exploration of innovative treatments, coupled with a deeper understanding of the intricate processes involved in nerve regeneration, holds the promise of unlocking the complete potential of these groundbreaking interventions. By fostering collaboration among scientists, clinicians, and industry partners, we can accelerate progress in this field, bringing us closer to the realization of transformative therapies that restore function and quality of life for individuals affected by peripheral nerve injuries.
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(This article belongs to the Special Issue Innovations in Nerve Regeneration)
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Open AccessArticle
Deep Learning-Based Detection of Glottis Segmentation Failures
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Armin A. Dadras and Philipp Aichinger
Bioengineering 2024, 11(5), 443; https://doi.org/10.3390/bioengineering11050443 - 30 Apr 2024
Abstract
Medical image segmentation is crucial for clinical applications, but challenges persist due to noise and variability. In particular, accurate glottis segmentation from high-speed videos is vital for voice research and diagnostics. Manual searching for failed segmentations is labor-intensive, prompting interest in automated methods.
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Medical image segmentation is crucial for clinical applications, but challenges persist due to noise and variability. In particular, accurate glottis segmentation from high-speed videos is vital for voice research and diagnostics. Manual searching for failed segmentations is labor-intensive, prompting interest in automated methods. This paper proposes the first deep learning approach for detecting faulty glottis segmentations. For this purpose, faulty segmentations are generated by applying both a poorly performing neural network and perturbation procedures to three public datasets. Heavy data augmentations are added to the input until the neural network’s performance decreases to the desired mean intersection over union (IoU). Likewise, the perturbation procedure involves a series of image transformations to the original ground truth segmentations in a randomized manner. These data are then used to train a ResNet18 neural network with custom loss functions to predict the IoU scores of faulty segmentations. This value is then thresholded with a fixed IoU of 0.6 for classification, thereby achieving 88.27% classification accuracy with 91.54% specificity. Experimental results demonstrate the effectiveness of the presented approach. Contributions include: (i) a knowledge-driven perturbation procedure, (ii) a deep learning framework for scoring and detecting faulty glottis segmentations, and (iii) an evaluation of custom loss functions.
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(This article belongs to the Special Issue Models and Analysis of Vocal Emissions for Biomedical Applications)
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PA12 Surface Treatment and Its Effect on Compatibility with Nutritional Culture Medium to Maintain Cell Vitality and Proliferation
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Norbert Ferencik, Maria Danko, Zuzana Nadova, Petra Kolembusova and William Steingartner
Bioengineering 2024, 11(5), 442; https://doi.org/10.3390/bioengineering11050442 - 30 Apr 2024
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This research investigates the suitability of printed polyamide 12 (PA12) and its dyed version to support cells in bioengineering applications. For this purpose, human gingival fibroblasts (hGF06) were cultured on PA-12 scaffolds that were 3D-printed by Multi Jet Fusion (MJF). The study examined
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This research investigates the suitability of printed polyamide 12 (PA12) and its dyed version to support cells in bioengineering applications. For this purpose, human gingival fibroblasts (hGF06) were cultured on PA-12 scaffolds that were 3D-printed by Multi Jet Fusion (MJF). The study examined the direct cultivation of cells on MJF-printed cell culture scaffolds and the effect of leachate of PA-12 printed by MJF on the cultured cells. The article presents research on the surface treatment of PA12 material used in 3D printing and the effect of automatic staining on cell vitality and proliferation in vitro. The study presents a unique device designed exclusively for staining prints made of the biocompatible material PA12 and demonstrates the compatibility of 3D-printed polyamide 12 parts stained in the novel device with a nutrient culture medium and cells. This novel PA12 surface treatment for biomedical purposes does not affect the compatibility with the culture medium, which is essential for cell viability and proliferation. Fluorescence microscopy revealed that mitochondrial fitness and cell survival were not affected by prolonged incubation with clear or dyed PA12 3D-printed parts.
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Ultra-High Contrast MRI: Using Divided Subtracted Inversion Recovery (dSIR) and Divided Echo Subtraction (dES) Sequences to Study the Brain and Musculoskeletal System
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Daniel Cornfeld, Paul Condron, Gil Newburn, Josh McGeown, Miriam Scadeng, Mark Bydder, Mark Griffin, Geoffrey Handsfield, Meeghage Randika Perera, Tracy Melzer, Samantha Holdsworth, Eryn Kwon and Graeme Bydder
Bioengineering 2024, 11(5), 441; https://doi.org/10.3390/bioengineering11050441 - 29 Apr 2024
Abstract
Divided and subtracted MRI is a novel imaging processing technique, where the difference of two images is divided by their sum. When the sequence parameters are chosen properly, this results in images with a high T1 or T2 weighting over a
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Divided and subtracted MRI is a novel imaging processing technique, where the difference of two images is divided by their sum. When the sequence parameters are chosen properly, this results in images with a high T1 or T2 weighting over a small range of tissues with specific T1 and T2 values. In the T1 domain, we describe the implementation of the divided Subtracted Inversion Recovery Sequence (dSIR), which is used to image very small changes in T1 from normal in white matter. dSIR has shown widespread changes in otherwise normal-appearing white matter in patients suffering from mild traumatic brain injury (mTBI), substance abuse, and ischemic leukoencephalopathy. It can also be targeted to measure small changes in T1 from normal in other tissues. In the T2 domain, we describe the divided echo subtraction (dES) sequence that is used to image musculoskeletal tissues with a very short T2*. These tissues include fascia, tendons, and aponeuroses. In this manuscript, we explain how this contrast is generated, review how these techniques are used in our research, and discuss the current challenges and limitations of this technique.
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(This article belongs to the Special Issue Novel MRI Techniques and Biomedical Image Processing)
Open AccessArticle
Unveiling the Unpredictable in Parkinson’s Disease: Sensor-Based Monitoring of Dyskinesias and Freezing of Gait in Daily Life
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Alessandro Zampogna, Luigi Borzì, Domiziana Rinaldi, Carlo Alberto Artusi, Gabriele Imbalzano, Martina Patera, Leonardo Lopiano, Francesco Pontieri, Gabriella Olmo and Antonio Suppa
Bioengineering 2024, 11(5), 440; https://doi.org/10.3390/bioengineering11050440 - 29 Apr 2024
Abstract
Background: Dyskinesias and freezing of gait are episodic disorders in Parkinson’s disease, characterized by a fluctuating and unpredictable nature. This cross-sectional study aims to objectively monitor Parkinsonian patients experiencing dyskinesias and/or freezing of gait during activities of daily living and assess possible changes
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Background: Dyskinesias and freezing of gait are episodic disorders in Parkinson’s disease, characterized by a fluctuating and unpredictable nature. This cross-sectional study aims to objectively monitor Parkinsonian patients experiencing dyskinesias and/or freezing of gait during activities of daily living and assess possible changes in spatiotemporal gait parameters. Methods: Seventy-one patients with Parkinson’s disease (40 with dyskinesias and 33 with freezing of gait) were continuously monitored at home for a minimum of 5 days using a single wearable sensor. Dedicated machine-learning algorithms were used to categorize patients based on the occurrence of dyskinesias and freezing of gait. Additionally, specific spatiotemporal gait parameters were compared among patients with and without dyskinesias and/or freezing of gait. Results: The wearable sensor algorithms accurately classified patients with and without dyskinesias as well as those with and without freezing of gait based on the recorded dyskinesias and freezing of gait episodes. Standard spatiotemporal gait parameters did not differ significantly between patients with and without dyskinesias or freezing of gait. Both the time spent with dyskinesias and the number of freezing of gait episodes positively correlated with the disease severity and medication dosage. Conclusions: A single inertial wearable sensor shows promise in monitoring complex, episodic movement patterns, such as dyskinesias and freezing of gait, during daily activities. This approach may help implement targeted therapeutic and preventive strategies for Parkinson’s disease.
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(This article belongs to the Special Issue Intelligent Health Management, Nursing and Rehabilitation Technology)
Open AccessArticle
Bioprinting of Perfusable, Biocompatible Vessel-like Channels with dECM-Based Bioinks and Living Cells
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Marta Klak, Michał Rachalewski, Anna Filip, Tomasz Dobrzański, Andrzej Berman and Michał Wszoła
Bioengineering 2024, 11(5), 439; https://doi.org/10.3390/bioengineering11050439 - 29 Apr 2024
Abstract
There is a growing interest in the production of bioinks that on the one hand, are biocompatible and, on the other hand, have mechanical properties that allow for the production of stable constructs that can survive for a long time after transplantation. While
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There is a growing interest in the production of bioinks that on the one hand, are biocompatible and, on the other hand, have mechanical properties that allow for the production of stable constructs that can survive for a long time after transplantation. While the selection of the right material is crucial for bioprinting, there is another equally important issue that is currently being extensively researched—the incorporation of the vascular system into the fabricated scaffolds. Therefore, in the following manuscript, we present the results of research on bioink with unique physico-chemical and biological properties. In this article, two methods of seeding cells were tested using bioink B and seeding after bioprinting the whole model. After 2, 5, 8, or 24 h of incubation, the flow medium was used in the tested systems. At the end of the experimental trial, for each time variant, the canals were stored in formaldehyde, and immunohistochemical staining was performed to examine the presence of cells on the canal walls and roof. Cells adhered to both ways of fiber arrangement; however, a parallel bioprint with the 5 h incubation and the intermediate plating of cells resulted in better adhesion efficiency. For this test variant, the percentage of cells that adhered was at least 20% higher than in the other analyzed variants. In addition, it was for this variant that the lowest percentage of viable cells was found that were washed out of the tested model. Importantly, hematoxylin and eosin staining showed that after 8 days of culture, the cells were evenly distributed throughout the canal roof. Our study clearly shows that neovascularization-promoting cells effectively adhere to ECM-based pancreatic bioink. Summarizing the presented results, it was demonstrated that the proposed bioink compositions can be used for bioprinting bionic organs with a vascular system formed by endothelial cells and fibroblasts.
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(This article belongs to the Special Issue 3D Bioprinting Advanced Vascularized Tissues and Organs)
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Open AccessArticle
Mendelian Randomization Reveals: Triglycerides and Sensorineural Hearing Loss
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Shun Ding, Yixuan Liu, Tingting Duan, Peng Fang, Qiling Tong, Huawei Li and Huiqian Yu
Bioengineering 2024, 11(5), 438; https://doi.org/10.3390/bioengineering11050438 - 29 Apr 2024
Abstract
Background: Sensorineural hearing loss (SNHL) is a multifactorial disorder with potential links to various physiological systems, including the cardiovascular system via blood lipid levels such as triglycerides (TG). This study investigates the causal relationship between TG levels and SNHL using Mendelian randomization (MR),
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Background: Sensorineural hearing loss (SNHL) is a multifactorial disorder with potential links to various physiological systems, including the cardiovascular system via blood lipid levels such as triglycerides (TG). This study investigates the causal relationship between TG levels and SNHL using Mendelian randomization (MR), which offers a method to reduce confounding and reverse causality by using genetic variants as instrumental variables. Methods: Utilizing publicly available genome-wide association study (GWAS) data, we performed a two-sample MR analysis. The initial analysis unveiled a causal relationship between TG (GWAS ID: ebi-a-GCST90018975) and SNHL (GWAS ID: finn b-H8_HL_SEN-NAS). Subsequent analysis validated this through MR with a larger sample size for TG (GWAS ID: ieu-b-111) and SNHL. To conduct the MR analysis, we utilized several methods including inverse-variance weighted (IVW), MR Egger, weighted median, and weighted mode. We also employed Cochrane’s Q test to identify any heterogeneity in the MR results. To detect horizontal pleiotropy, we conducted the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. We performed a leave-one-out analysis to assess the sensitivity of this association. Finally, a meta-analysis of the MR results was undertaken. Results: Our study found a significant positive correlation between TG and SNHL, with OR values of 1.14 (95% CI: 1.07–1.23, p < 0.001) in the IVW analysis and 1.09 (95% CI: 1.03–1.16, p < 0.006) in the replicate analysis. We also found no evidence of horizontal pleiotropy or heterogeneity between the genetic variants (p > 0.05), and a leave-one-out test confirmed the stability and robustness of this association. The meta-analysis combining the initial and replicate analyses showed a significant causal effect with OR values of 1.11 (95% CI: 1.06–1.16, p = 0.01). Conclusion: These findings indicate TG as a risk factor for SNHL, suggesting potential pathways for prevention and intervention in populations at risk. This conclusion underscores the importance of managing TG levels as a strategy to mitigate the risk of developing SNHL.
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(This article belongs to the Section Biomedical Engineering and Biomaterials)
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Open AccessArticle
Repair of Rat Calvarial Critical-Sized Defects Using Heparin-Conjugated Fibrin Hydrogel Containing BMP-2 and Adipose-Derived Pericytes
by
Gulshakhar Kudaibergen, Sholpan Mukhlis, Ainur Mukhambetova, Assel Issabekova, Aliya Sekenova, Madina Sarsenova, Abay Temirzhan, Murat Baidarbekov, Baurzhan Umbayev and Vyacheslav Ogay
Bioengineering 2024, 11(5), 437; https://doi.org/10.3390/bioengineering11050437 - 29 Apr 2024
Abstract
The repair of critical-sized calvarial defects is a challenging problem for orthopedic surgery. One of the promising strategies of bone bioengineering to enhance the efficacy of large bone defect regeneration is the combined delivery of stem cells with osteoinductive factors within polymer carriers.
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The repair of critical-sized calvarial defects is a challenging problem for orthopedic surgery. One of the promising strategies of bone bioengineering to enhance the efficacy of large bone defect regeneration is the combined delivery of stem cells with osteoinductive factors within polymer carriers. The purpose of the research was to study the regenerative effects of heparin-conjugated fibrin (HCF) hydrogel containing bone morphogenetic protein 2 (BMP-2) and adipose-derived pericytes (ADPs) in a rat critical-sized calvarial defect model. In vitro analysis revealed that the HCF hydrogel was able to control the BMP-2 release and induce alkaline phosphatase (ALP) activity in neonatal rat osteoblasts. In addition, it was found that eluted BMP-2 significantly induced the osteogenic differentiation of ADPs. It was characterized by the increased ALP activity, osteocalcin expression and calcium deposits in ADPs. In vivo studies have shown that both HCF hydrogel with BMP-2 and HCF hydrogel with pericytes are able to significantly increase the regeneration of critical-sized calvarial defects in comparison with the control group. Nevertheless, the greatest regenerative effect was found after the co-delivery of ADPs and BMP-2 into a critical-sized calvarial defect. Thus, our findings suggest that the combined delivery of ADPs and BMP-2 in HCF hydrogel holds promise to be applied as an alternative biopolymer for the critical-sized bone defect restoration.
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(This article belongs to the Special Issue Bone Tissue Engineering and Translational Research)
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Open AccessArticle
Hybrid Materials for Vascular Applications: A Preliminary In Vitro Assessment
by
Martina Todesco, Martina Casarin, Deborah Sandrin, Laura Astolfi, Filippo Romanato, Germana Giuggioli, Fabio Conte, Gino Gerosa, Chiara Giulia Fontanella and Andrea Bagno
Bioengineering 2024, 11(5), 436; https://doi.org/10.3390/bioengineering11050436 - 28 Apr 2024
Abstract
The production of biomedical devices able to appropriately interact with the biological environment is still a great challenge. Synthetic materials are often employed, but they fail to replicate the biological and functional properties of native tissues, leading to a variety of adverse effects.
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The production of biomedical devices able to appropriately interact with the biological environment is still a great challenge. Synthetic materials are often employed, but they fail to replicate the biological and functional properties of native tissues, leading to a variety of adverse effects. Several commercial products are based on chemically treated xenogeneic tissues: their principal drawback is due to weak mechanical stability and low durability. Recently, decellularization has been proposed to bypass the drawbacks of both synthetic and biological materials. Acellular materials can integrate with host tissues avoiding/mitigating any foreign body response, but they often lack sufficient patency and impermeability. The present paper investigates an innovative approach to the realization of hybrid materials that combine decellularized bovine pericardium with polycarbonate urethanes. These hybrid materials benefit from the superior biocompatibility of the biological tissue and the mechanical properties of the synthetic polymers. They were assessed from physicochemical, structural, mechanical, and biological points of view; their ability to promote cell growth was also investigated. The decellularized pericardium and the polymer appeared to well adhere to each other, and the two sides were distinguishable. The maximum elongation of hybrid materials was mainly affected by the pericardium, which allows for lower elongation than the polymer; this latter, in turn, influenced the maximum strength achieved. The results confirmed the promising features of hybrid materials for the production of vascular grafts able to be repopulated by circulating cells, thus, improving blood compatibility.
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(This article belongs to the Special Issue Hybrid and Composite Biomaterials for Healthcare: Toward Innovative Approaches)
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Open AccessArticle
Evaluation of Skin Wound Healing with Biosheets Containing Somatic Stem Cells in a Dog Model: A Pilot Study
by
Noritaka Maeta, Ryosuke Iwai, Hiroshi Takemitsu, Natsuki Akashi, Masahiro Miyabe, Marina Funayama-Iwai and Yasuhide Nakayama
Bioengineering 2024, 11(5), 435; https://doi.org/10.3390/bioengineering11050435 - 28 Apr 2024
Abstract
The administration of mesenchymal stem cells (MSCs) has a positive effect on wound healing; however, the lack of adequate MSC engraftment at the wound site is a major limiting factor in current MSC-based therapies. In this study, a biosheet prepared using in-body tissue
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The administration of mesenchymal stem cells (MSCs) has a positive effect on wound healing; however, the lack of adequate MSC engraftment at the wound site is a major limiting factor in current MSC-based therapies. In this study, a biosheet prepared using in-body tissue architecture (iBTA) was used as a material to address these problems. This study aimed to assess and evaluate whether biosheets containing somatic stem cells would affect the wound healing process in dogs. Biosheets were prepared by subcutaneously embedding molds in beagles. These were then evaluated grossly and histologically, and the mRNA expression of inflammatory cytokines, interleukins, and Nanog was examined in some biosheets. Skin defects were created on the skin of the beagles to which the biosheets were applied. The wound healing processes of the biosheet and control (no biosheet application) groups were compared for 8 weeks. Nanog mRNA was expressed in the biosheets, and SSEA4/CD105 positive cells were observed histologically. Although the wound contraction rates differed significantly in the first week, the biosheet group tended to heal faster than the control group. This study revealed that biosheets containing somatic stem cells may have a positive effect on wound healing.
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(This article belongs to the Section Regenerative Engineering)
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Open AccessArticle
Synergizing Deep Learning-Enabled Preprocessing and Human–AI Integration for Efficient Automatic Ground Truth Generation
by
Christopher Collazo, Ian Vargas, Brendon Cara, Carla J. Weinheimer, Ryan P. Grabau, Dmitry Goldgof, Lawrence Hall, Samuel A. Wickline and Hua Pan
Bioengineering 2024, 11(5), 434; https://doi.org/10.3390/bioengineering11050434 - 28 Apr 2024
Abstract
The progress of incorporating deep learning in the field of medical image interpretation has been greatly hindered due to the tremendous cost and time associated with generating ground truth for supervised machine learning, alongside concerns about the inconsistent quality of images acquired. Active
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The progress of incorporating deep learning in the field of medical image interpretation has been greatly hindered due to the tremendous cost and time associated with generating ground truth for supervised machine learning, alongside concerns about the inconsistent quality of images acquired. Active learning offers a potential solution to these problems of expanding dataset ground truth by algorithmically choosing the most informative samples for ground truth labeling. Still, this effort incurs the costs of human labeling, which needs minimization. Furthermore, automatic labeling approaches employing active learning often exhibit overfitting tendencies while selecting samples closely aligned with the training set distribution and excluding out-of-distribution samples, which could potentially improve the model’s effectiveness. We propose that the majority of out-of-distribution instances can be attributed to inconsistent cross images. Since the FDA approved the first whole-slide image system for medical diagnosis in 2017, whole-slide images have provided enriched critical information to advance the field of automated histopathology. Here, we exemplify the benefits of a novel deep learning strategy that utilizes high-resolution whole-slide microscopic images. We quantitatively assess and visually highlight the inconsistencies within the whole-slide image dataset employed in this study. Accordingly, we introduce a deep learning-based preprocessing algorithm designed to normalize unknown samples to the training set distribution, effectively mitigating the overfitting issue. Consequently, our approach significantly increases the amount of automatic region-of-interest ground truth labeling on high-resolution whole-slide images using active deep learning. We accept 92% of the automatic labels generated for our unlabeled data cohort, expanding the labeled dataset by 845%. Additionally, we demonstrate expert time savings of 96% relative to manual expert ground-truth labeling.
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(This article belongs to the Special Issue Machine Learning Technology in Biomedical Engineering—2nd Edition)
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Open AccessArticle
Impact of Polyethylene-Glycol-Induced Water Potential on Methane Yield and Microbial Consortium Dynamics in the Anaerobic Degradation of Glucose
by
Jin Yeo and Yong-Woo Jeon
Bioengineering 2024, 11(5), 433; https://doi.org/10.3390/bioengineering11050433 - 27 Apr 2024
Abstract
This study investigated the relationship between water potential (Ψ) and the cation-induced inhibition of methane production in anaerobic digesters. The Ψ around methanogens was manipulated using polyethylene glycol (PEG) in a batch anaerobic reactor, ranging from −0.92 to −5.10 MPa. The ultimate methane
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This study investigated the relationship between water potential (Ψ) and the cation-induced inhibition of methane production in anaerobic digesters. The Ψ around methanogens was manipulated using polyethylene glycol (PEG) in a batch anaerobic reactor, ranging from −0.92 to −5.10 MPa. The ultimate methane potential (Bu) decreased significantly from 0.293 to 0.002 Nm3 kg−1-VSadded as Ψ decreased. When Ψ lowered from −0.92 MPa to −1.48 MPa, the community distribution of acetoclastic Methanosarcina decreased from 59.62% to 40.44%, while those of hydrogenotrophic Methanoculleus and Methanobacterium increased from 17.70% and 1.30% to 36.30% and 18.07%, respectively. These results mirrored changes observed in methanogenic communities affected by cation inhibition with KCl. Our findings strongly indicate that the inhibitory effect of cations on methane production may stem more from the water stress induced by cations than from their direct toxic effects. This study highlights the importance of considering Ψ dynamics in understanding cation-mediated inhibition in anaerobic digesters, providing insights into optimizing microbial processes for enhanced methane production from organic substrates.
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(This article belongs to the Section Biochemical Engineering)
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Open AccessReview
Recent Advances of MSCs in Renal IRI: From Injury to Renal Fibrosis
by
Xinhao Niu, Xiaoqing Xu, Cuidi Xu, Yin Celeste Cheuk and Ruiming Rong
Bioengineering 2024, 11(5), 432; https://doi.org/10.3390/bioengineering11050432 - 27 Apr 2024
Abstract
Renal fibrosis is a pathological endpoint of maladaptation after ischemia-reperfusion injury (IRI), and despite many attempts, no good treatment has been achieved so far. At the core of renal fibrosis is the differentiation of various types of cells into myofibroblasts. MSCs were once
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Renal fibrosis is a pathological endpoint of maladaptation after ischemia-reperfusion injury (IRI), and despite many attempts, no good treatment has been achieved so far. At the core of renal fibrosis is the differentiation of various types of cells into myofibroblasts. MSCs were once thought to play a protective role after renal IRI. However, growing evidence suggests that MSCs have a two-sided nature. In spite of their protective role, in maladaptive situations, MSCs start to differentiate towards myofibroblasts, increasing the myofibroblast pool and promoting renal fibrosis. Following renal IRI, it has been observed that Bone Marrow-Derived Mesenchymal Stem Cells (BM-MSCs) and Renal Resident Mesenchymal Stem Cells (RR-MSCs) play important roles. This review presents evidence supporting their involvement, discusses their potential mechanisms of action, and suggests several new targets for future research.
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(This article belongs to the Special Issue A Tribute to Professor Alexander Friedenstein and His Outstanding Achievements in the Area of Stromal Stem Cells)
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Artificial Intelligence in Adult and Pediatric Dentistry: A Narrative Review
by
Seyed Mohammadrasoul Naeimi, Shayan Darvish, Bahareh Nazemi Salman and Ionut Luchian
Bioengineering 2024, 11(5), 431; https://doi.org/10.3390/bioengineering11050431 - 27 Apr 2024
Abstract
Artificial intelligence (AI) has been recently introduced into clinical dentistry, and it has assisted professionals in analyzing medical data with unprecedented speed and an accuracy level comparable to humans. With the help of AI, meaningful information can be extracted from dental databases, especially
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Artificial intelligence (AI) has been recently introduced into clinical dentistry, and it has assisted professionals in analyzing medical data with unprecedented speed and an accuracy level comparable to humans. With the help of AI, meaningful information can be extracted from dental databases, especially dental radiographs, to devise machine learning (a subset of AI) models. This study focuses on models that can diagnose and assist with clinical conditions such as oral cancers, early childhood caries, deciduous teeth numbering, periodontal bone loss, cysts, peri-implantitis, osteoporosis, locating minor apical foramen, orthodontic landmark identification, temporomandibular joint disorders, and more. The aim of the authors was to outline by means of a review the state-of-the-art applications of AI technologies in several dental subfields and to discuss the efficacy of machine learning algorithms, especially convolutional neural networks (CNNs), among different types of patients, such as pediatric cases, that were neglected by previous reviews. They performed an electronic search in PubMed, Google Scholar, Scopus, and Medline to locate relevant articles. They concluded that even though clinicians encounter challenges in implementing AI technologies, such as data management, limited processing capabilities, and biased outcomes, they have observed positive results, such as decreased diagnosis costs and time, as well as early cancer detection. Thus, further research and development should be considered to address the existing complications.
Full article
(This article belongs to the Special Issue Artificial Intelligence in Healthcare)
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