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
Diagnosis of Forme Fruste Keratoconus Using Corvis ST Sequences with Digital Image Correlation and Machine Learning
Bioengineering 2024, 11(5), 429; https://doi.org/10.3390/bioengineering11050429 - 26 Apr 2024
Abstract
Purpose: This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish
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Purpose: This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish forme fruste keratoconus (FFKC) from normal corneas. Methods: 100 subjects were categorized into normal (N = 50) and FFKC (N = 50) groups. Image sequences depicting the horizontal cross-section of the human cornea under air puff were captured using the Corvis ST tonometer. The high-speed evolution of full-field corneal displacement, strain, velocity, and strain rate was reconstructed utilizing the incremental DIC approach. Maximum (max-) and average (ave-) values of full-field displacement V, shear strain γxy, velocity VR, and shear strain rate γxyR were determined over time, generating eight evolution curves denoting max-V, max-γxy, max-VR, max-γxyR, ave-V, ave-γxy, ave-VR, and ave-γxyR, respectively. These evolution data were inputted into two machine learning (ML) models, specifically Naïve Bayes (NB) and Random Forest (RF) models, which were subsequently employed to construct a voting classifier. The performance of the models in diagnosing FFKC from normal corneas was compared to existing CVS parameters. Results: The Normal group and the FFKC group each included 50 eyes. The FFKC group did not differ from healthy controls for age (p = 0.26) and gender (p = 0.36) at baseline, but they had significantly lower bIOP (p < 0.001) and thinner central cornea thickness (CCT) (p < 0.001). The results demonstrated that the proposed voting ensemble model yielded the highest performance with an AUC of 1.00, followed by the RF model with an AUC of 0.99. Radius and A2 Time emerged as the best-performing CVS parameters with AUC values of 0.948 and 0.938, respectively. Nonetheless, no existing Corvis ST parameters outperformed the ML models. A progressive enhancement in performance of the ML models was observed with incremental time points during the corneal deformation. Conclusion: This study represents the first instance where displacement and strain data following incremental DIC analysis of Corvis ST images were integrated with machine learning models to effectively differentiate FFKC corneas from normal ones, achieving superior accuracy compared to existing CVS parameters. Considering biomechanical responses of the inner cornea and their temporal pattern changes may significantly improve the early detection of keratoconus.
Full article
(This article belongs to the Special Issue Ophthalmic Engineering 2.0)
Open AccessArticle
Automatic Estimation of the Interference Subspace Dimension Threshold in the Subspace Projection Algorithms of Magnetoencephalography Based on Evoked State Data
by
Ruochen Zhao, Ruonan Wang, Yang Gao and Xiaolin Ning
Bioengineering 2024, 11(5), 428; https://doi.org/10.3390/bioengineering11050428 - 26 Apr 2024
Abstract
A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference (external) subspace matrix of these algorithms is the key to balancing the denoising effect and the degree of signal
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A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference (external) subspace matrix of these algorithms is the key to balancing the denoising effect and the degree of signal distortion. However, most current methods for estimating the dimension threshold rely on experience, such as observing the signal waveforms and spectrum, which may render the results too subjective and lacking in quantitative accuracy. Therefore, this study proposes a method to automatically estimate a suitable threshold. Time–frequency transformations are performed on the evoked state data to obtain the neural signal of interest and the noise signal in a specific time–frequency band, which are then used to construct the objective function describing the degree of noise suppression and signal distortion. The optimal value of the threshold in the selected range is obtained using the weighted-sum method. Our method was tested on two classical subspace projection algorithms using simulation and two sensory stimulation experiments. The thresholds estimated by the proposed method enabled the algorithms to achieve the best waveform recovery and source location error. Therefore, the threshold selected in this method enables subspace projection algorithms to achieve the best balance between noise removal and neural signal preservation in subsequent MEG analyses.
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(This article belongs to the Special Issue 10th Anniversary of Bioengineering: Biosignal Processing)
Open AccessArticle
A Novel Mis-Seg-Focus Loss Function Based on a Two-Stage nnU-Net Framework for Accurate Brain Tissue Segmentation
by
Keyi He, Bo Peng, Weibo Yu, Yan Liu, Surui Liu, Jian Cheng and Yakang Dai
Bioengineering 2024, 11(5), 427; https://doi.org/10.3390/bioengineering11050427 - 26 Apr 2024
Abstract
Brain tissue segmentation plays a critical role in the diagnosis, treatment, and study of brain diseases. Accurately identifying these boundaries is essential for improving segmentation accuracy. However, distinguishing boundaries between different brain tissues can be challenging, as they often overlap. Existing deep learning
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Brain tissue segmentation plays a critical role in the diagnosis, treatment, and study of brain diseases. Accurately identifying these boundaries is essential for improving segmentation accuracy. However, distinguishing boundaries between different brain tissues can be challenging, as they often overlap. Existing deep learning methods primarily calculate the overall segmentation results without adequately addressing local regions, leading to error propagation and mis-segmentation along boundaries. In this study, we propose a novel mis-segmentation-focused loss function based on a two-stage nnU-Net framework. Our approach aims to enhance the model’s ability to handle ambiguous boundaries and overlapping anatomical structures, thereby achieving more accurate brain tissue segmentation results. Specifically, the first stage targets the identification of mis-segmentation regions using a global loss function, while the second stage involves defining a mis-segmentation loss function to adaptively adjust the model, thus improving its capability to handle ambiguous boundaries and overlapping anatomical structures. Experimental evaluations on two datasets demonstrate that our proposed method outperforms existing approaches both quantitatively and qualitatively.
Full article
(This article belongs to the Special Issue Novel MRI Techniques and Biomedical Image Processing)
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Open AccessArticle
A Novel Recombinant Human Filaggrin Segment (rhFLA-10) Alleviated a Skin Lesion of Atopic Dermatitis
by
Jiawen Zhu, Xinhua Zhong, Hui Liao, Jianhang Cong, Qiqi Wu, Shuang Liang and Qi Xiang
Bioengineering 2024, 11(5), 426; https://doi.org/10.3390/bioengineering11050426 - 26 Apr 2024
Abstract
Atopic dermatitis (AD), a prevalent chronic inflammatory skin disorder, is marked by impaired skin barrier function and persistent pruritus. It significantly deteriorates patients’ quality of life, making it one of the most burdensome non-lethal skin disorders. Filaggrin plays a crucial role in the
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Atopic dermatitis (AD), a prevalent chronic inflammatory skin disorder, is marked by impaired skin barrier function and persistent pruritus. It significantly deteriorates patients’ quality of life, making it one of the most burdensome non-lethal skin disorders. Filaggrin plays a crucial role in the pathophysiology of barrier disruption in AD, interacting with inflammatory mediators. It is an integral part of the extracellular matrix architecture, serving to protect the skin barrier and attenuate the inflammatory cascade. In this study, we engineered a novel recombinant human filaggrin (rhFLA-10) expression vector, which was subsequently synthesized and purified. In vitro and ex vivo efficacy experiments were conducted for AD. rhFLA-10, at low concentrations (5 to 20 μg/mL), was non-toxic to HACaT cells, significantly inhibited the degranulation of P815 mast cells, and was readily absorbed by cells, thereby exerting a soothing therapeutic effect. Furthermore, rhFLA-10 demonstrated anti-inflammatory properties (p < 0.05). In vivo, efficacy experiments further substantiated that rhFLA-10 could effectively ameliorate AD in mice and facilitate the repair of damaged skin (p < 0.001). These findings underscore the considerable potential of rhFLA-10 in the treatment of AD.
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(This article belongs to the Section Biochemical Engineering)
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Open AccessReview
Modern In Vitro Techniques for Modeling Hearing Loss
by
Jamie J. Shah, Couger A. Jimenez-Jaramillo, Zane R. Lybrand, Tony T. Yuan and Isaac D. Erbele
Bioengineering 2024, 11(5), 425; https://doi.org/10.3390/bioengineering11050425 - 26 Apr 2024
Abstract
Sensorineural hearing loss (SNHL) is a prevalent and growing global health concern, especially within operational medicine, with limited therapeutic options available. This review article explores the emerging field of in vitro otic organoids as a promising platform for modeling hearing loss and developing
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Sensorineural hearing loss (SNHL) is a prevalent and growing global health concern, especially within operational medicine, with limited therapeutic options available. This review article explores the emerging field of in vitro otic organoids as a promising platform for modeling hearing loss and developing novel therapeutic strategies. SNHL primarily results from the irreversible loss or dysfunction of cochlear mechanosensory hair cells (HCs) and spiral ganglion neurons (SGNs), emphasizing the need for innovative solutions. Current interventions offer symptomatic relief but do not address the root causes. Otic organoids, three-dimensional multicellular constructs that mimic the inner ear’s architecture, have shown immense potential in several critical areas. They enable the testing of gene therapies, drug discovery for sensory cell regeneration, and the study of inner ear development and pathology. Unlike traditional animal models, otic organoids closely replicate human inner ear pathophysiology, making them invaluable for translational research. This review discusses methodological advances in otic organoid generation, emphasizing the use of human pluripotent stem cells (hPSCs) to replicate inner ear development. Cellular and molecular characterization efforts have identified key markers and pathways essential for otic organoid development, shedding light on their potential in modeling inner ear disorders. Technological innovations, such as 3D bioprinting and microfluidics, have further enhanced the fidelity of these models. Despite challenges and limitations, including the need for standardized protocols and ethical considerations, otic organoids offer a transformative approach to understanding and treating auditory dysfunctions. As this field matures, it holds the potential to revolutionize the treatment landscape for hearing and balance disorders, moving us closer to personalized medicine for inner ear conditions.
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(This article belongs to the Special Issue Operational Medicine Applications of Bioengineering)
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Open AccessCorrection
Correction: Reiter, J.; Beier, M. Deammonification Potential of Pig Slurries and Vapor Condensates from Sewage Sludge Drying—Substrate Quality and Inhibition. Bioengineering 2023, 10, 826
by
Johannes Reiter and Maike Beier
Bioengineering 2024, 11(5), 424; https://doi.org/10.3390/bioengineering11050424 - 25 Apr 2024
Abstract
In the original publication [...]
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Open AccessArticle
Glycosaminoglycans Modulate the Angiogenic Ability of Type I Collagen-Based Scaffolds by Acting on Vascular Network Remodeling and Maturation
by
Enrica Raffaella Grazia Salvante, Anca Voichita Popoiu, Amulya K. Saxena, Tudor Alexandru Popoiu, Eugen Sorin Boia, Anca Maria Cimpean, Florina Stefania Rus, Florica Ramona Dorobantu and Monica Chis
Bioengineering 2024, 11(5), 423; https://doi.org/10.3390/bioengineering11050423 - 25 Apr 2024
Abstract
Type I collagen, prevalent in the extracellular matrix, is biocompatible and crucial for tissue engineering and wound healing, including angiogenesis and vascular maturation/stabilization as required processes of newly formed tissue constructs or regeneration. Sometimes, improper vascularization causes unexpected outcomes. Vascularization failure may be
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Type I collagen, prevalent in the extracellular matrix, is biocompatible and crucial for tissue engineering and wound healing, including angiogenesis and vascular maturation/stabilization as required processes of newly formed tissue constructs or regeneration. Sometimes, improper vascularization causes unexpected outcomes. Vascularization failure may be caused by extracellular matrix collagen and non-collagen components heterogeneously. This study compares the angiogenic potential of collagen type I-based scaffolds and collagen type I/glycosaminoglycans scaffolds by using the chick embryo chorioallantoic membrane (CAM) model and IKOSA digital image analysis. Two clinically used biomaterials, Xenoderm (containing type I collagen derived from decellularized porcine extracellular matrix) and a dual-layer collagen sponge (DLC, with a biphasic composition of type I collagen combined with glycosaminoglycans) were tested for their ability to induce new vascular network formation. The AI-based IKOSA app enhanced the research by calculating from stereomicroscopic images angiogenic parameters such as total vascular area, branching sites, vessel length, and vascular thickness. The study confirmed that Xenoderm caused a fast angiogenic response and substantial vascular growth, but was unable to mature the vascular network. DLC scaffold, in turn, produced a slower angiogenic response, but a more steady and organic vascular maturation and stabilization. This research can improve collagen-based knowledge by better assessing angiogenesis processes. DLC may be preferable to Xenoderm or other materials for functional neovascularization, according to the findings.
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(This article belongs to the Special Issue Biomaterials for Angiogenesis)
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Open AccessReview
Decellularized Human Dermis for Orthoplastic Extremity Reconstruction
by
Christopher Bibbo and K. Ümit Yüksel
Bioengineering 2024, 11(5), 422; https://doi.org/10.3390/bioengineering11050422 - 25 Apr 2024
Abstract
The reconstruction of patients who possess multi morbid medical histories remains a challenge. With the ever-increasing number of patients with diabetes, infections, and trauma, there is a consistent need for promotion of soft tissue healing and a reliable substrate to assist with every
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The reconstruction of patients who possess multi morbid medical histories remains a challenge. With the ever-increasing number of patients with diabetes, infections, and trauma, there is a consistent need for promotion of soft tissue healing and a reliable substrate to assist with every aspect of soft tissue reconstruction, as well as the loss of fascial domain. Several proprietary products filled some of these needs but have failed to fulfill the needs of the clinician when faced with reconstructing multiple soft tissue systems, such as the integument and the musculoskeletal system. In this paper we discuss the use of decellularized human dermis (DermaPure®, Tissue Regenix, Universal City, TX, USA) through which a unique human tissue processing technique (dCELL® technology, Tissue Regenix, Universal City, TX, USA) and the creation of multiple product forms have proven to exhibit versatility in a wide range of clinical needs for successful soft tissue reconstruction. The background of human tissue processing, basic science, and early clinical studies are detailed, which has translated to the rationale for the success of this unique soft tissue substrate in orthoplastic reconstruction, which is also provided here in detail.
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(This article belongs to the Special Issue Foot and Ankle Surgery: Current Progresses and Emerging Technologies in Orthoplastic Reconstruction)
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Open AccessArticle
Deep-Learning-Based Automated Anomaly Detection of EEGs in Intensive Care Units
by
Jacky Chung-Hao Wu, Nien-Chen Liao, Ta-Hsin Yang, Chen-Cheng Hsieh, Jin-An Huang, Yen-Wei Pai, Yi-Jhen Huang, Chieh-Liang Wu and Henry Horng-Shing Lu
Bioengineering 2024, 11(5), 421; https://doi.org/10.3390/bioengineering11050421 - 25 Apr 2024
Abstract
An intensive care unit (ICU) is a special ward in the hospital for patients who require intensive care. It is equipped with many instruments monitoring patients’ vital signs and supported by the medical staff. However, continuous monitoring demands a massive workload of medical
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An intensive care unit (ICU) is a special ward in the hospital for patients who require intensive care. It is equipped with many instruments monitoring patients’ vital signs and supported by the medical staff. However, continuous monitoring demands a massive workload of medical care. To ease the burden, we aim to develop an automatic detection model to monitor when brain anomalies occur. In this study, we focus on electroencephalography (EEG), which monitors the brain electroactivity of patients continuously. It is mainly for the diagnosis of brain malfunction. We propose the gated-recurrent-unit-based (GRU-based) model for detecting brain anomalies; it predicts whether the spike or sharp wave happens within a short time window. Based on the banana montage setting, the proposed model exploits characteristics of multiple channels simultaneously to detect anomalies. It is trained, validated, and tested on separated EEG data and achieves more than 90% testing performance on sensitivity, specificity, and balanced accuracy. The proposed anomaly detection model detects the existence of a spike or sharp wave precisely; it will notify the ICU medical staff, who can provide immediate follow-up treatment. Consequently, it can reduce the medical workload in the ICU significantly.
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(This article belongs to the Special Issue Machine Learning and Artificial Intelligence for Biomedical Applications, 2nd Edition)
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Open AccessArticle
Longitudinal Analysis of Corneal Biomechanics of Suspect Keratoconus: A Prospective Case-Control Study
by
Yan Huo, Xuan Chen, Ruisi Xie, Jing Li and Yan Wang
Bioengineering 2024, 11(5), 420; https://doi.org/10.3390/bioengineering11050420 - 25 Apr 2024
Abstract
Background: To evaluate the corneal biomechanics of stable keratoconus suspects (Stable-KCS) at 1-year follow-up and compare them with those of subclinical keratoconus (SKC). Methods: This prospective case-control study included the eyes of 144 patients. Biomechanical and tomographic parameters were recorded (Corvis ST and
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Background: To evaluate the corneal biomechanics of stable keratoconus suspects (Stable-KCS) at 1-year follow-up and compare them with those of subclinical keratoconus (SKC). Methods: This prospective case-control study included the eyes of 144 patients. Biomechanical and tomographic parameters were recorded (Corvis ST and Pentacam). Patients without clinical signs of keratoconus in both eyes but suspicious tomography findings were included in the Stable-KCS group (n = 72). Longitudinal follow-up was used to evaluate Stable-KCS changes. Unilateral keratoconus contralateral eyes with suspicious tomography were included in the SKC group (n = 72). T-tests and non-parametric tests were used for comparison. Multivariate general linear models were used to adjust for confounding factors for further analysis. Receiver operating characteristic (ROC) curves were used to analyze the distinguishability. Results: The biomechanical and tomographic parameters of Stable-KCS showed no progression during the follow-up time (13.19 ± 2.41 months, p > 0.05). Fifteen biomechanical parameters and the Stress–Strain Index (SSI) differed between the two groups (p < 0.016). The A1 dArc length showed the strongest distinguishing ability (area under the ROC = 0.888) between Stable-KCS and SKC, with 90.28% sensitivity and 77.78% specificity at the cut-off value of −0.0175. Conclusions: The A1 dArc length could distinguish between Stable-KCS and SKC, indicating the need to focus on changes in the A1 dArc length for keratoconus suspects during the follow-up period. Although both have abnormalities on tomography, the corneal biomechanics and SSI of Stable-KCS were stronger than those of SKC, which may explain the lack of progression of Stable-KCS.
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(This article belongs to the Special Issue Ophthalmic Engineering 2.0)
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Ultrasound Imaging in Football Players with Previous Multiple Ankle Sprains: Keeping a Close Eye on Superior Ankle Retinaculum
by
Carmelo Pirri, Nina Pirri, Diego Guidolin, Veronica Macchi, Andrea Porzionato, Raffaele De Caro and Carla Stecco
Bioengineering 2024, 11(5), 419; https://doi.org/10.3390/bioengineering11050419 - 25 Apr 2024
Abstract
The superior extensor ankle retinaculum (SEAR), a transversely fascial thickening positioned above the tibia–talar joint, serves as a crucial anatomical structure in ankle stability. The purpose of this study was to measure and compare by ultrasound (US) imaging the bilateral thickness and echogenicity
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The superior extensor ankle retinaculum (SEAR), a transversely fascial thickening positioned above the tibia–talar joint, serves as a crucial anatomical structure in ankle stability. The purpose of this study was to measure and compare by ultrasound (US) imaging the bilateral thickness and echogenicity of SEAR in football players with previous multiple ankle sprains (group 1) and healthy volunteers (group 2). A cross-sectional study was performed using ultrasound imaging to measure longitudinal and transversal axes using a new protocol in a sample of 50 subjects: 25 football players with previous multiple ankle sprains and 25 healthy subjects. The findings for SEAR thickness revealed statistically significant differences for both axes (p = 0.0011 and p = 0.0032) between the healthy side and the previously sprained side, and with the corresponding side of group 2 (p = 0.003 and p = 0.004). Moreover, in group 1, regarding the ROI echogenicity, a statistically significant difference was found between the sides (p = 0.0378). These findings suggest that the football players with previous ankle sprains showed a thicker and inhomogeneous SEAR on the sprain side, unveiling a remodeling of this structure compared to the other side and to the healthy volunteers. In these athletes, during US examination, one needs to keep “a US eye” on side-to-side SEAR comparisons.
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(This article belongs to the Special Issue Physical Examination and Rehabilitation of Fasciae and Muscles in Sports Injuries)
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Open AccessReview
Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review
by
Jae-Hwan Kang, Jang-Han Bae and Young-Ju Jeon
Bioengineering 2024, 11(5), 418; https://doi.org/10.3390/bioengineering11050418 - 24 Apr 2024
Abstract
The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures
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The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures and functions that lead to age-related pathological disorders. Electroencephalographic (EEG) signals recorded during resting-state conditions have been widely used because of the significant advantage of non-invasive signal acquisition with higher temporal resolution. These advantages include the capability of a variety of linear and nonlinear signal analyses and state-of-the-art machine-learning and deep-learning techniques. Advances in artificial intelligence (AI) can not only reveal the neural mechanisms underlying aging but also enable the assessment of brain age reliably by means of the age-related characteristics of EEG signals. This paper reviews the literature on the age-related features, available analytic methods, large-scale resting-state EEG databases, interpretations of the resulting findings, and recent advances in age-related AI models.
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(This article belongs to the Special Issue Body-Worn Sensors for Biomedical Applications)
Open AccessArticle
Design Optimization and Tradeoff Analysis of an Actuated Continuum Probe for Pulmonary Nodule Localization and Resection
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Madison D. McCullough, Marie Muller, Thomas M. Egan and Gregory D. Buckner
Bioengineering 2024, 11(5), 417; https://doi.org/10.3390/bioengineering11050417 - 24 Apr 2024
Abstract
Pulmonary nodules are abnormal tissue masses in the lungs, typically less than 3.0 cm in diameter, commonly detected during imaging of the chest and lungs. While most pulmonary nodules are not cancerous, surgical resection may be required if growth is detected between scans.
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Pulmonary nodules are abnormal tissue masses in the lungs, typically less than 3.0 cm in diameter, commonly detected during imaging of the chest and lungs. While most pulmonary nodules are not cancerous, surgical resection may be required if growth is detected between scans. This resection is typically performed without the benefit of intraoperative imaging, making it difficult for surgeons to confidently provide appropriate margins. To enhance the efficacy of wedge resection, researchers have developed a modified ultrasound imaging approach that utilizes both multiple scattering (MS) and single scattering (SS) to enhance the accuracy of margin delineation. Clinical deployment of this novel ultrasound technology requires a highly maneuverable ultrasound probe, ideally one that could be deployed and actuated with minimal invasiveness. This study details the design optimization and tradeoff analysis of an actuated continuum probe for pulmonary nodule localization and resection. This device, deployed through intercostal ports, would enable the intraoperative imaging and precise mapping of nodules for improved margin delineation and patient outcomes. To achieve this objective, multiple objective genetic algorithms (MOGAs) and a design of experiments (DOE) study are used to explore the design space and quantify key dimensional relationships and their effects on probe actuation.
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(This article belongs to the Special Issue Visual Image Technologies for Respiratory and Circulatory Management)
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Open AccessArticle
Effect of Plate Configuration in the Primary Stability of Osteotomies and Biological Reconstructions of Femoral Defects: Finite-Element Study
by
M. A. Neto, M. F. Paulino and A. M. Amaro
Bioengineering 2024, 11(5), 416; https://doi.org/10.3390/bioengineering11050416 - 24 Apr 2024
Abstract
Background/objective: Osteosynthesis is an alternative treatment for stabilizing femur-bone traumas. The initial stability of the fixation systems is one of the biomechanical parameters affecting implant failure and bone union, especially in surgeries of intercalary reconstructions after the removal of bone tumors. This study
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Background/objective: Osteosynthesis is an alternative treatment for stabilizing femur-bone traumas. The initial stability of the fixation systems is one of the biomechanical parameters affecting implant failure and bone union, especially in surgeries of intercalary reconstructions after the removal of bone tumors. This study aimed to investigate the initial biomechanical effect of using one or two osteosynthesis plate configurations for femoral fixation and the effect of fastening the allograft to the osteosynthesis plate in the case of femoral allograft reconstructions. Methods: Three finite-element models of a femur with three different fixation conditions for a transverse osteotomy in the middle of the diaphysis, i.e., using one and two osteosynthesis plates and an intercalary allograft, were constructed. An eight-hole compression plate and a six-hole second plate were used to simulate osteosynthesis plates. The plate screws were tightened previously to the loading, and the tightening sequences simulate the bolt-tightening procedure in a surgical environment. The models were imported into the ADINA System for nonlinear analysis, using compression loads applied over the femur head. Results: Models with the dual fixation systems had the most outstanding compression stiffness. The femur head movement in the dual plate system was 24.8% smaller than in the single plate system. A statistical analysis of a region of interest (VOI) placed in the femur diaphysis showed that the biomechanical effect of using the dual plate system is smaller in the osteotomy region than at the femur head, e.g., a displacement average decrease of only 5% between the two systems, while the maximum value decreases by 26.8%. The allograft fixation to the second osteosynthesis plate leads to an improvement in the system stability. Conclusions: The results presented in this work show that including the bolt analysis in the femoral diaphysis osteotomy fixation will allow for capturing the nonlinear behavior of the osteotomy region more realistically. The stability of the intercalary reconstruction of the femoral diaphysis was higher when the allograft was fastened to the second osteosynthesis plate.
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(This article belongs to the Special Issue Biomechanics Analysis in Tissue Engineering)
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Investigating the Effect of Processing and Material Parameters of Alginate Dialdehyde-Gelatin (ADA-GEL)-Based Hydrogels on Stiffness by XGB Machine Learning Model
by
Duygu Ege and Aldo R. Boccaccini
Bioengineering 2024, 11(5), 415; https://doi.org/10.3390/bioengineering11050415 - 24 Apr 2024
Abstract
To address the limitations of alginate and gelatin as separate hydrogels, partially oxidized alginate, alginate dialdehyde (ADA), is usually combined with gelatin to prepare ADA-GEL hydrogels. These hydrogels offer tunable properties, controllable degradation, and suitable stiffness for 3D bioprinting and tissue engineering applications.
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To address the limitations of alginate and gelatin as separate hydrogels, partially oxidized alginate, alginate dialdehyde (ADA), is usually combined with gelatin to prepare ADA-GEL hydrogels. These hydrogels offer tunable properties, controllable degradation, and suitable stiffness for 3D bioprinting and tissue engineering applications. Several processing variables affect the final properties of the hydrogel, including degree of oxidation, gelatin content and type of crosslinking agent. In addition, in 3D-printed structures, pore size and the possible addition of a filler to make a hydrogel composite also affect the final physical and biological properties. This study utilized datasets from 13 research papers, encompassing 33 unique combinations of ADA concentration, gelatin concentration, CaCl2 and microbial transglutaminase (mTG) concentrations (as crosslinkers), pore size, bioactive glass (BG) filler content, and one identified target property of the hydrogels, stiffness, utilizing the Extreme Boost (XGB) machine learning algorithm to create a predictive model for understanding the combined influence of these parameters on hydrogel stiffness. The stiffness of ADA-GEL hydrogels is notably affected by the ADA to GEL ratio, and higher gelatin content for different ADA gel concentrations weakens the scaffold, likely due to the presence of unbound gelatin. Pore size and the inclusion of a BG particulate filler also have a significant impact on stiffness; smaller pore sizes and higher BG content lead to increased stiffness. The optimization of ADA-GEL composition and the inclusion of BG fillers are key determinants to tailor the stiffness of these 3D printed hydrogels, as found by the analysis of the available data.
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(This article belongs to the Section Regenerative Engineering)
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Human versus Rat PRF on Collagen Membranes: A Pilot Study of Mineralization in Rat Calvaria Defect Model
by
Karol Ali Apaza Alccayhuaman, Patrick Heimel, Stefan Tangl, Stefan Lettner, Carina Kampleitner, Layla Panahipour, Ulrike Kuchler and Reinhard Gruber
Bioengineering 2024, 11(5), 414; https://doi.org/10.3390/bioengineering11050414 - 23 Apr 2024
Abstract
Platelet-rich fibrin, the coagulated plasma fraction of blood, is commonly used to support natural healing in clinical applications. The rat calvaria defect is a standardized model to study bone regeneration. It remains, however, unclear if the rat calvaria defect is appropriate to investigate
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Platelet-rich fibrin, the coagulated plasma fraction of blood, is commonly used to support natural healing in clinical applications. The rat calvaria defect is a standardized model to study bone regeneration. It remains, however, unclear if the rat calvaria defect is appropriate to investigate the impact of human PRF (Platelet-Rich Fibrin) on bone regeneration. To this end, we soaked Bio-Gide® collagen membranes in human or rat liquid concentrated PRF before placing them onto 5 mm calvarial defects in Sprague Dawley rats. Three weeks later, histology and micro-computed tomography (μCT) were performed. We observed that the collagen membranes soaked with rat PRF show the characteristic features of new bone and areas of mineralized collagen matrix, indicated by a median mineralized volume of 1.5 mm3 (range: 0.9; 5.3 mm3). Histology revealed new bone growing underneath the membrane and hybrid bone where collagen fibers are embedded in the new bone. Moreover, areas of passive mineralization were observed. The collagen membranes soaked with human PRF, however, were devoid of histological features of new bone formation in the center of the defect; only occasionally, new bone formed at the defect margins. Human PRF (h-PRF) caused a median bone volume of 0.9 mm3 (range: 0.3–3.3 mm3), which was significantly lower than what was observed with rat PRF (r-PRF), with a BV median of 1.2 mm3 (range: 0.3–5.9 mm3). Our findings indicate that the rat calvaria defect model is suitable for assessing the effects of rat PRF on bone formation, but caution is warranted when extrapolating conclusions regarding the efficacy of human PRF.
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(This article belongs to the Special Issue Tissue Engineering for Regenerative Dentistry)
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Predictive Refined Computational Modeling of ACL Tear Injury Patterns
by
Mirit Sharabi, Raz Agron, Amir Dolev, Rami Haj-Ali and Mustafa Yassin
Bioengineering 2024, 11(5), 413; https://doi.org/10.3390/bioengineering11050413 - 23 Apr 2024
Abstract
Anterior cruciate ligament (ACL) ruptures are prevalent knee injuries, with approximately 200,000 ruptures annually, and treatment costs exceed USD two billion in the United States alone. Typically, the initial detection of ACL tears and anterior tibial laxity (ATL) involves manual assessments like the
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Anterior cruciate ligament (ACL) ruptures are prevalent knee injuries, with approximately 200,000 ruptures annually, and treatment costs exceed USD two billion in the United States alone. Typically, the initial detection of ACL tears and anterior tibial laxity (ATL) involves manual assessments like the Lachman test, which examines anterior knee laxity. Partial ACL tears can go unnoticed if they minimally affect knee laxity; however, they will progress to a complete ACL tear requiring surgical treatment. In this study, a computational finite element model (FEM) of the knee joint was generated to investigate the effect of partial ACL tears under the Lachman test (GNRB® testing system) boundary conditions. The ACL was modeled as a hyperelastic composite structure with a refined representation of collagen bundles. Five different tear types (I–V), classified by location and size, were modeled to predict the relationship between tear size, location, and anterior tibial translation (ATT). The results demonstrated different levels of ATT that could not be manually detected. Type I tears demonstrated an almost linear increase in ATT, with the growth in tear size ranging from 3.7 mm to 4.2 mm, from 25% to 85%, respectively. Type II partial tears showed a less linear incline in ATT (3.85, 4.1, and 4.75 mm for 25%, 55%, and 85% partial tears, respectively). Types III, IV, and V maintained a nonlinear trend, with ATTs of 3.85 mm, 4.2 mm, and 4.95 mm for Type III, 3.85 mm, 4.25 mm, and 5.1 mm for Type IV, and 3.6 mm, 4.25 mm, and 5.3 mm for Type V, for 25%, 55%, and 85% partial tears, respectively. Therefore, for small tears (25%), knee stability was most affected when the tears were located around the center of the ligament. For moderate tears (55%), the effect on knee stability was the greatest for tears at the proximal half of the ACL. However, severe tears (85%) demonstrated considerable growth in knee instability from the distal to the proximal ends of the tissue, with a substantial increase in knee instability around the insertion sites. The proposed model can enhance the characterization of partial ACL tears, leading to more accurate preliminary diagnoses. It can aid in developing new techniques for repairing partially torn ACLs, potentially preventing more severe injuries.
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(This article belongs to the Special Issue Computational Biomechanics, Volume II)
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A Novel Bio-Purification Process Employing an Engineered E. coli Strain for Downstream Processing of Lactic Acid Solutions from the Fermentation of Agro-Industrial by-Products
by
Alexandra Nastouli, Alexandra Moschona, Panagiotis A. Bizirtsakis, Joseph Sweeney, Irini Angelidaki, Michael Harasek, Anastasios J. Karabelas and Sotiris I. Patsios
Bioengineering 2024, 11(5), 412; https://doi.org/10.3390/bioengineering11050412 - 23 Apr 2024
Abstract
This study aims to integrate a novel bio-purification process employing an engineered E. coli strain in the downstream processing of lactic acid (LA) fermentation broths from low-cost renewable biological feedstocks. Fermentation broth of candy waste and digestate mixture was used as a real
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This study aims to integrate a novel bio-purification process employing an engineered E. coli strain in the downstream processing of lactic acid (LA) fermentation broths from low-cost renewable biological feedstocks. Fermentation broth of candy waste and digestate mixture was used as a real biological feedstock. An engineered E. coli strain that selectively catabolize impurities without catabolizing LA was initially adapted on the biological feedstock, followed by shake flask experiments to prove the bio-purification concept. Scale-up and validation in a bench-scale bioreactor followed, before developing a semi-continuous membrane bioreactor (MBR) bio-purification process. The MBR bio-purification was assessed with biological feedstocks which simulated ultrafiltration or nanofiltration permeates. Incomplete removal of impurities and increased fouling was observed in the case of the ultrafiltration permeate. Contrarily, the nanofiltration permeate was successfully treated with MBR bio-purification, since low membrane fouling, 100% maltose and acetic acid removal, and no LA catabolism was achieved. MBR bio-purification as a post-treatment step in the downstream processing of LA was demonstrated as a promising technology for increasing the purity of LA solutions.
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(This article belongs to the Special Issue Bio-Applications of Engineered Escherichia coli)
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Optic Nerve Head Pulsatile Displacement in Open-Angle Glaucoma after Intraocular Pressure Reduction Measured by Optical Coherence Tomography: A Pilot Study
by
Marissé Masís Solano, Emmanuelle Richer, Santiago Costantino and Mark R. Lesk
Bioengineering 2024, 11(5), 411; https://doi.org/10.3390/bioengineering11050411 - 23 Apr 2024
Abstract
This study investigated the effect of intraocular pressure (IOP) reduction on pulsatile displacement within the optic nerve head (ONH) in primary open-angle glaucoma (POAG) patients with and without axial myopia. Forty-one POAG patients (19 without myopia, 9 with axial myopia and 13 glaucoma
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This study investigated the effect of intraocular pressure (IOP) reduction on pulsatile displacement within the optic nerve head (ONH) in primary open-angle glaucoma (POAG) patients with and without axial myopia. Forty-one POAG patients (19 without myopia, 9 with axial myopia and 13 glaucoma with no intervention) participated. Swept-source optical coherence tomography (OCT) videos of the ONH were obtained before and after IOP-lowering treatment (medical or surgical) achieving a minimum IOP drop of 3 mmHg. A demons registration-based algorithm measured local pulsatile displacement maps within the ONH. Results demonstrated a significant 14% decrease in pulsatile tissue displacement in the non-myopic glaucoma cohort after intervention (p = 0.03). However, glaucoma patients with axial myopia exhibited no statistically significant change. There were no significant changes in the pulsatile ONH deformation in the control group. These findings suggest a potential link between IOP reduction and reduced pulsatile displacement within the ONH in POAG patients without myopia, offering new insights into the disease’s pathophysiology and warranting further investigation into underlying mechanisms and clinical implications.
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(This article belongs to the Special Issue Biomechanics Studies in Ophthalmology)
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Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach
by
Zubair Saeed, Othmane Bouhali, Jim Xiuquan Ji, Rabih Hammoud, Noora Al-Hammadi, Souha Aouadi and Tarraf Torfeh
Bioengineering 2024, 11(5), 410; https://doi.org/10.3390/bioengineering11050410 - 23 Apr 2024
Abstract
Brain cancer is a life-threatening disease requiring close attention. Early and accurate diagnosis using non-invasive medical imaging is critical for successful treatment and patient survival. However, manual diagnosis by radiologist experts is time-consuming and has limitations in processing large datasets efficiently. Therefore, efficient
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Brain cancer is a life-threatening disease requiring close attention. Early and accurate diagnosis using non-invasive medical imaging is critical for successful treatment and patient survival. However, manual diagnosis by radiologist experts is time-consuming and has limitations in processing large datasets efficiently. Therefore, efficient systems capable of analyzing vast amounts of medical data for early tumor detection are urgently needed. Deep learning (DL) with deep convolutional neural networks (DCNNs) emerges as a promising tool for understanding diseases like brain cancer through medical imaging modalities, especially MRI, which provides detailed soft tissue contrast for visualizing tumors and organs. DL techniques have become more and more popular in current research on brain tumor detection. Unlike traditional machine learning methods requiring manual feature extraction, DL models are adept at handling complex data like MRIs and excel in classification tasks, making them well-suited for medical image analysis applications. This study presents a novel Dual DCNN model that can accurately classify cancerous and non-cancerous MRI samples. Our Dual DCNN model uses two well-performed DL models, i.e., inceptionV3 and denseNet121. Features are extracted from these models by appending a global max pooling layer. The extracted features are then utilized to train the model with the addition of five fully connected layers and finally accurately classify MRI samples as cancerous or non-cancerous. The fully connected layers are retrained to learn the extracted features for better accuracy. The technique achieves 99%, 99%, 98%, and 99% of accuracy, precision, recall, and f1-scores, respectively. Furthermore, this study compares the Dual DCNN’s performance against various well-known DL models, including DenseNet121, InceptionV3, ResNet architectures, EfficientNetB2, SqueezeNet, VGG16, AlexNet, and LeNet-5, with different learning rates. This study indicates that our proposed approach outperforms these established models in terms of performance.
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(This article belongs to the Topic Artificial Intelligence in Public Health: Current Trends and Future Possibilities)
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