Editor’s Choice Articles

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

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12 pages, 1363 KiB  
Article
Assessing the Genotoxicity of Cellulose Nanomaterials in a Co-Culture of Human Lung Epithelial Cells and Monocyte-Derived Macrophages
Bioengineering 2023, 10(8), 986; https://doi.org/10.3390/bioengineering10080986 - 21 Aug 2023
Cited by 1 | Viewed by 1318
Abstract
Cellulose micro/nanomaterials (CMNMs) are innovative materials with a wide spectrum of industrial and biomedical applications. Although cellulose has been recognized as a safe material, the unique properties of its nanosized forms have raised concerns about their safety for human health. Genotoxicity is an [...] Read more.
Cellulose micro/nanomaterials (CMNMs) are innovative materials with a wide spectrum of industrial and biomedical applications. Although cellulose has been recognized as a safe material, the unique properties of its nanosized forms have raised concerns about their safety for human health. Genotoxicity is an endpoint that must be assessed to ensure that no carcinogenic risks are associated with exposure to nanomaterials. In this study, we evaluated the genotoxicity of two types of cellulose micro/nanofibrils (CMF and CNF) and one sample of cellulose nanocrystals (CNC), obtained from industrial bleached Eucalyptus globulus kraft pulp. For that, we exposed co-cultures of human alveolar epithelial A549 cells and THP-1 monocyte-derived macrophages to a concentration range of each CMNM and used the micronucleus (MN) and comet assays. Our results showed that only the lowest concentrations of the CMF sample were able to induce DNA strand breaks (FPG-comet assay). However, none of the three CMNMs produced significant chromosomal alterations (MN assay). These findings, together with results from previous in vitro studies using monocultures of A549 cells, indicate that the tested CNF and CNC are not genotoxic under the conditions tested, while the CMF display a low genotoxic potential. Full article
(This article belongs to the Special Issue Biopolymers and Nano-Objects Applications in Bioengineering)
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9 pages, 517 KiB  
Communication
Retrospective Analysis of Responders and Impaired Patients with Knee Osteoarthritis Treated with Two Consecutive Injections of Very Pure Platelet-Rich Plasma (PRP)
Bioengineering 2023, 10(8), 922; https://doi.org/10.3390/bioengineering10080922 - 03 Aug 2023
Cited by 1 | Viewed by 1288
Abstract
Objectives: To assess the effectiveness of two consecutive intraarticular injections of PRP to treat knee osteoarthritis (KOA), discriminating between responders and impaired patients. Methods: This retrospective study included 73 consecutive patients who were referred for two intra-articular PRP injections (one week apart) for [...] Read more.
Objectives: To assess the effectiveness of two consecutive intraarticular injections of PRP to treat knee osteoarthritis (KOA), discriminating between responders and impaired patients. Methods: This retrospective study included 73 consecutive patients who were referred for two intra-articular PRP injections (one week apart) for treating symptomatic moderate/severe KOA. Biological characterization of the PRP, including platelets, leukocytes and erythrocytes, was evaluated. Patient’s subjective symptoms were recorded before the treatment and 1 year after the second injection using pain VAS and WOMAC scores. Responders were defined by an improvement of 10 points on WOMAC. Results: At a 1-year follow up, we found 36 (49.3%) patients who fulfilled the criteria of responders, and 21 (28.8%) patients were impaired. A statistically and clinically significant global improvement of −29.2 ± 14.3 (p < 0.001) points in WOMAC score was observed 1 year after treatment in the responder group, with a higher response rate in patients with KL 2 (57.7%) compared to KL IV (28.6%). The percentage of patients with KL IV was higher in the impaired group (48.0%) compared to the responders (16.6%). As expected, the evaluation of the functionality of the knee in the impaired group indicates that it significantly worsened after one year from treatment (p = 0.027). However, the average pain score remained stable with no significant differences after 1 year (p = 0.843). No clinical complications or severe adverse events after the PRP injections were reported. Conclusion: The present study suggests that two intra-articular injections of 10 mL of very pure PRP provide pain and functional improvement in symptomatic KOA. Full article
(This article belongs to the Special Issue Advances in Autologous PRP Therapy)
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17 pages, 3240 KiB  
Article
Ex Vivo Model to Evaluate the Antibacterial and Anti-Inflammatory Effects of Gelatin–Tricalcium Phosphate Composite Incorporated with Emodin and Lumbrokinase for Bone Regeneration
Bioengineering 2023, 10(8), 906; https://doi.org/10.3390/bioengineering10080906 - 31 Jul 2023
Viewed by 1139
Abstract
Tricalcium phosphate (TCP) has gained attention due to its interconnected porous structures which promote fibrovascular invasion and bony replacement. Moreover, when gelatin is added and crosslinked with genipin (GGT), TCP exhibits robust biocompatibility and stability, making it an excellent bone substitute. In this [...] Read more.
Tricalcium phosphate (TCP) has gained attention due to its interconnected porous structures which promote fibrovascular invasion and bony replacement. Moreover, when gelatin is added and crosslinked with genipin (GGT), TCP exhibits robust biocompatibility and stability, making it an excellent bone substitute. In this study, we incorporated emodin and lumbrokinase (LK) into GGT to develop an antibacterial biomaterial. Emodin, derived from various plants, possesses antibacterial and anti-inflammatory properties. LK comprises proteolytic enzymes extracted from the earthworm Lumbricus rubellus and exhibits fibrinolytic activity, enabling it to dissolve biofilms. Additionally, LK stimulates osteoblast activity while inhibiting osteoclast differentiation. GGT was combined with emodin and lumbrokinase to produce the GGTELK composite. The biomedical effects of GGTELK were assessed through in vitro assays and an ex vivo bone defect model. The GGTELK composite demonstrated antibacterial properties, inhibiting the growth of S. aureus and reducing biofilm formation. Moreover, it exhibited anti-inflammatory effects by reducing the secretion of IL-6 in both in vivo cell experiments and the ex vivo model. Therefore, the GGTELK composite, with its stability, efficient degradation, biocompatibility, and anti-inflammatory function, is expected to serve as an ideal bone substitute. Full article
(This article belongs to the Special Issue Biomaterials for Cartilage and Bone Tissue Engineering)
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20 pages, 7670 KiB  
Article
A Novel Non-Contact Detection and Identification Method for the Post-Disaster Compression State of Injured Individuals Using UWB Bio-Radar
Bioengineering 2023, 10(8), 905; https://doi.org/10.3390/bioengineering10080905 - 30 Jul 2023
Viewed by 1063
Abstract
Building collapse leads to mechanical injury, which is the main cause of injury and death, with crush syndrome as its most common complication. During the post-disaster search and rescue phase, if rescue personnel hastily remove heavy objects covering the bodies of injured individuals [...] Read more.
Building collapse leads to mechanical injury, which is the main cause of injury and death, with crush syndrome as its most common complication. During the post-disaster search and rescue phase, if rescue personnel hastily remove heavy objects covering the bodies of injured individuals and fail to provide targeted medical care, ischemia-reperfusion injury may be triggered, leading to rhabdomyolysis. This may result in disseminated intravascular coagulation or acute respiratory distress syndrome, further leading to multiple organ failure, which ultimately leads to shock and death. Using bio-radar to detect vital signs and identify compression states can effectively reduce casualties during the search for missing persons behind obstacles. A time-domain ultra-wideband (UWB) bio-radar was applied for the non-contact detection of human vital sign signals behind obstacles. An echo denoising algorithm based on PSO-VMD and permutation entropy was proposed to suppress environmental noise, along with a wounded compression state recognition network based on radar-life signals. Based on training and testing using over 3000 data sets from 10 subjects in different compression states, the proposed multiscale convolutional network achieved a 92.63% identification accuracy. This outperformed SVM and 1D-CNN models by 5.30% and 6.12%, respectively, improving the casualty rescue success and post-disaster precision. Full article
(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)
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17 pages, 1545 KiB  
Review
Recent Advancements in Deep Learning Using Whole Slide Imaging for Cancer Prognosis
Bioengineering 2023, 10(8), 897; https://doi.org/10.3390/bioengineering10080897 - 28 Jul 2023
Cited by 2 | Viewed by 1343
Abstract
This review furnishes an exhaustive analysis of the latest advancements in deep learning techniques applied to whole slide images (WSIs) in the context of cancer prognosis, focusing specifically on publications from 2019 through 2023. The swiftly maturing field of deep learning, in combination [...] Read more.
This review furnishes an exhaustive analysis of the latest advancements in deep learning techniques applied to whole slide images (WSIs) in the context of cancer prognosis, focusing specifically on publications from 2019 through 2023. The swiftly maturing field of deep learning, in combination with the burgeoning availability of WSIs, manifests significant potential in revolutionizing the predictive modeling of cancer prognosis. In light of the swift evolution and profound complexity of the field, it is essential to systematically review contemporary methodologies and critically appraise their ramifications. This review elucidates the prevailing landscape of this intersection, cataloging major developments, evaluating their strengths and weaknesses, and providing discerning insights into prospective directions. In this paper, a comprehensive overview of the field aims to be presented, which can serve as a critical resource for researchers and clinicians, ultimately enhancing the quality of cancer care outcomes. This review’s findings accentuate the need for ongoing scrutiny of recent studies in this rapidly progressing field to discern patterns, understand breakthroughs, and navigate future research trajectories. Full article
(This article belongs to the Special Issue Machine-Learning-Driven Medical Image Analysis)
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15 pages, 3450 KiB  
Article
In Vivo Assessment of High-Strength and Corrosion-Controlled Magnesium-Based Bone Implants
Bioengineering 2023, 10(7), 877; https://doi.org/10.3390/bioengineering10070877 - 24 Jul 2023
Viewed by 1032
Abstract
The biodegradable nature of magnesium in aqueous mediums makes it an attractive material for various biomedical applications when it is not recommended that the material stay permanently in the body. Some of the main challenges that hinder the use of magnesium for bone [...] Read more.
The biodegradable nature of magnesium in aqueous mediums makes it an attractive material for various biomedical applications when it is not recommended that the material stay permanently in the body. Some of the main challenges that hinder the use of magnesium for bone fracture repair are its limited mechanical strength and fast corrosion rates. To this end, we developed a novel Mg-Zn-Ca-Mn-based alloy and post-fabrication methods that can deliver high-strength and corrosion-controlled implant materials to address these challenges. This study is focused on assessing the in vitro corrosion and in vivo biocompatibility of the developed magnesium-based alloy and post-fabrication processes. The developed heat treatment process resulted in an increase in the microhardness from 71.9 ± 5.4 HV for the as-cast Mg alloy to as high as 98.1 ± 6.5 HV for the heat-treated Mg alloy, and the ceramic coating resulted in a significant reduction in the corrosion rate from 10.37 mm/yr for the uncoated alloy to 0.03 mm/yr after coating. The in vivo assessments showed positive levels of biocompatibility in terms of degradation rates and integration of the implants in a rabbit model. In the rabbit studies, the implants became integrated into the bone defect and showed minimal evidence of an immune response. The results of this study show that it is possible to produce biocompatible Mg-based implants with stronger and more corrosion-controlled properties based on the developed Mg-Zn-Ca-Mn-based alloy and post-fabrication methods. Full article
(This article belongs to the Special Issue Engineering Biodegradable-Implant Materials, Volume II)
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16 pages, 1621 KiB  
Article
Correlations between Ratings and Technical Measurements in Hand-Intensive Work
Bioengineering 2023, 10(7), 867; https://doi.org/10.3390/bioengineering10070867 - 21 Jul 2023
Viewed by 1242
Abstract
An accurate rating of hand activity and force is essential in risk assessment and for the effective prevention of work-related musculoskeletal disorders. However, it is unclear whether the subjective ratings of workers and observers correlate to corresponding objective technical measures of exposure. Fifty-nine [...] Read more.
An accurate rating of hand activity and force is essential in risk assessment and for the effective prevention of work-related musculoskeletal disorders. However, it is unclear whether the subjective ratings of workers and observers correlate to corresponding objective technical measures of exposure. Fifty-nine workers were video recorded while performing a hand-intensive work task at their workplace. Self-ratings of hand activity level (HAL) and force (Borg CR10) using the Hand Activity Threshold Limit Value® were assessed. Four ergonomist observers, in two pairs, also rated the hand activity and force level for each worker from video recordings. Wrist angular velocity was measured using inertial movement units. Muscle activity in the forearm muscles flexor carpi radialis (FCR) and extensor carpi radialis (ECR) was measured with electromyography root mean square values (RMS) and normalized to maximal voluntary electrical activation (MVE). Kendall’s tau-b correlations were statistically significant between self-rated hand activity and wrist angular velocity at the 10th, 50th, and 90th percentiles (0.26, 0.31, and 0.23) and for the ratings of observers (0.32, 0.41, and 0.34). Significant correlations for force measures were found only for observer-ratings in five of eight measures (FCR 50th percentile 0.29, time > 10%MVE 0.43, time > 30%MVE 0.44, time < 5% −0.47) and ECR (time > 30%MVE 0.26). The higher magnitude of correlation for observer-ratings suggests that they may be preferred to the self-ratings of workers. When possible, objective technical measures of wrist angular velocity and muscle activity should be preferred to subjective ratings when assessing risks of work-related musculoskeletal disorders. Full article
(This article belongs to the Special Issue Human Movement and Ergonomics)
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19 pages, 9511 KiB  
Article
Biofunctionalized Decellularized Tissue-Engineered Heart Valve with Mesoporous Silica Nanoparticles for Controlled Release of VEGF and RunX2-siRNA against Calcification
Bioengineering 2023, 10(7), 859; https://doi.org/10.3390/bioengineering10070859 - 20 Jul 2023
Viewed by 1123
Abstract
The goal of tissue-engineered heart valves (TEHV) is to replace normal heart valves and overcome the shortcomings of heart valve replacement commonly used in clinical practice. However, calcification of TEHV is the major bottleneck to break for both clinical workers and researchers. Endothelialization [...] Read more.
The goal of tissue-engineered heart valves (TEHV) is to replace normal heart valves and overcome the shortcomings of heart valve replacement commonly used in clinical practice. However, calcification of TEHV is the major bottleneck to break for both clinical workers and researchers. Endothelialization of TEHV plays a crucial role in delaying valve calcification by reducing platelet adhesion and covering the calcified spots. In the present study, we loaded RunX2-siRNA and VEGF into mesoporous silica nanoparticles and investigated the properties of anti-calcification and endothelialization in vitro. Then, the mesoporous silica nanoparticle was immobilized on the decellularized porcine aortic valve (DPAV) by layer self-assembly and investigated the anti-calcification and endothelialization. Our results demonstrated that the mesoporous silica nanoparticles delivery vehicle demonstrated good biocompatibility, and a stable release of RunX2-siRNA and VEGF. The hybrid decellularized valve exhibited a low hemolysis rate and promoted endothelial cell proliferation and adhesion while silencing RunX2 gene expression in valve interstitial cells, and the hybrid decellularized valve showed good mechanical properties. Finally, the in vivo experiment showed that the mesoporous silica nanoparticles delivery vehicle could enhance the endothelialization of the hybrid valve. In summary, we constructed a delivery system based on mesoporous silica to biofunctionalized TEHV scaffold for endothelialization and anti-calcification. Full article
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19 pages, 6368 KiB  
Article
Hydrogel-Impregnated Self-Oxygenating Electrospun Scaffolds for Bone Tissue Engineering
Bioengineering 2023, 10(7), 854; https://doi.org/10.3390/bioengineering10070854 - 19 Jul 2023
Viewed by 1338
Abstract
Bone defects resulting from trauma, disease, or aging present significant challenges in the clinic. Although biomaterial scaffolds for bone-tissue engineering have shown promising results, challenges remain, including the need for adequate mechanical strength and suitable bioactive agents within scaffolds to promote bone formation. [...] Read more.
Bone defects resulting from trauma, disease, or aging present significant challenges in the clinic. Although biomaterial scaffolds for bone-tissue engineering have shown promising results, challenges remain, including the need for adequate mechanical strength and suitable bioactive agents within scaffolds to promote bone formation. Oxygen is a critical factor for successful bone formation, and low oxygen tension inhibits it. In this study, we developed gelatin methacryloyl (GelMA) hydrogel-impregnated electrospun polycaprolactone (PCL) scaffolds that can release oxygen over 3 weeks. We investigated the potential of composite scaffolds for cell survival in bone-tissue engineering. Our results showed that the addition of an increased amount of CaO2 nanoparticles to the PCL scaffolds significantly increased oxygen generation, which was modulated by GelMA impregnation. Moreover, the resulting scaffolds showed improved cytocompatibility, pre-osteoblast adhesion, and proliferation under hypoxic conditions. This finding is particularly relevant since hypoxia is a prevalent feature in various bone diseases. In addition to providing oxygen, CaO2 nanoparticles also act as reinforcing agents improving the mechanical property of the scaffolds, while the incorporation of GelMA enhances cell adhesion and proliferation properties. Overall, our newly developed self-oxygenating composite biomaterials are promising scaffolds for bone-tissue engineering applications. Full article
(This article belongs to the Section Regenerative Engineering)
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16 pages, 1005 KiB  
Review
Microbial PolyHydroxyAlkanoate (PHA) Biopolymers—Intrinsically Natural
Bioengineering 2023, 10(7), 855; https://doi.org/10.3390/bioengineering10070855 - 19 Jul 2023
Cited by 6 | Viewed by 3147
Abstract
Global pollution from fossil plastics is one of the top environmental threats of our time. At their end-of-life phase, fossil plastics, through recycling, incineration, and disposal result in microplastic formation, elevated atmospheric CO2 levels, and the pollution of terrestrial and aquatic environments. [...] Read more.
Global pollution from fossil plastics is one of the top environmental threats of our time. At their end-of-life phase, fossil plastics, through recycling, incineration, and disposal result in microplastic formation, elevated atmospheric CO2 levels, and the pollution of terrestrial and aquatic environments. Current regional, national, and global regulations are centered around banning plastic production and use and/or increasing recycling while ignoring efforts to rapidly replace fossil plastics through the use of alternatives, including those that occur in nature. In particular, this review demonstrates how microbial polyhydroxyalkanoates (PHAs), a class of intrinsically natural polymers, can successfully remedy the fossil and persistent plastic dilemma. PHAs are bio-based, biosynthesized, biocompatible, and biodegradable, and thus, domestically and industrially compostable. Therefore, they are an ideal replacement for the fossil plastics pollution dilemma, providing us with the benefits of fossil plastics and meeting all the requirements of a truly circular economy. PHA biopolyesters are natural and green materials in all stages of their life cycle. This review elaborates how the production, consumption, and end-of-life profile of PHAs are embedded in the current and topical, 12 Principles of Green Chemistry, which constitute the basis for sustainable product manufacturing. The time is right for a paradigm shift in plastic manufacturing, use, and disposal. Humankind needs alternatives to fossil plastics, which, as recalcitrant xenobiotics, contribute to the increasing deterioration of our planet. Natural PHA biopolyesters represent that paradigm shift. Full article
(This article belongs to the Special Issue Advances in Polyhydroxyalkanoate (PHA) Production, Volume 4)
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26 pages, 8055 KiB  
Article
Muscular and Kinematic Responses to Unexpected Translational Balance Perturbation: A Pilot Study in Healthy Young Adults
Bioengineering 2023, 10(7), 831; https://doi.org/10.3390/bioengineering10070831 - 13 Jul 2023
Cited by 2 | Viewed by 1125
Abstract
Falls and fall-related injuries are significant public health problems in older adults. While balance-controlling strategies have been extensively researched, there is still a lack of understanding regarding how fast the lower-limb muscles contract and coordinate in response to a sudden loss of standing [...] Read more.
Falls and fall-related injuries are significant public health problems in older adults. While balance-controlling strategies have been extensively researched, there is still a lack of understanding regarding how fast the lower-limb muscles contract and coordinate in response to a sudden loss of standing balance. Therefore, this pilot study aims to investigate the speed and timing patterns of multiple joint/muscles’ activities among the different challenges in standing balance. Twelve healthy young subjects were recruited, and they received unexpected translational balance perturbations with randomized intensities and directions. Electromyographical (EMG) and mechanomyographical (MMG) signals of eight dominant-leg’s muscles, dominant-leg’s three-dimensional (3D) hip/knee/ankle joint angles, and 3D postural sways were concurrently collected. Two-way ANOVAs were used to examine the difference in timing and speed of the collected signals among muscles/joint motions and among perturbation intensities. This study has found that (1) agonist muscles resisting the induced postural sway tended to activate more rapidly than the antagonist muscles, and ankle muscles contributed the most with the fastest rate of response; (2) voluntary corrective lower-limb joint motions and postural sways could occur as early as the perturbation-induced passive ones; (3) muscles reacted more rapidly under a larger perturbation intensity, while the joint motions or postural sways did not. These findings expand the current knowledge on standing-balance-controlling mechanisms and may potentially provide more insights for developing future fall-prevention strategies in daily life. Full article
(This article belongs to the Special Issue Biomechanics-Based Motion Analysis, Volume II)
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16 pages, 1974 KiB  
Review
Cancer Drug Delivery Systems Using Bacterial Toxin Translocation Mechanisms
Bioengineering 2023, 10(7), 813; https://doi.org/10.3390/bioengineering10070813 - 07 Jul 2023
Cited by 1 | Viewed by 1384
Abstract
Recent advances in targeted cancer therapy hold great promise for both research and clinical applications and push the boundaries in finding new treatments for various currently incurable cancers. However, these therapies require specific cell-targeting mechanisms for the efficient delivery of drug cargo across [...] Read more.
Recent advances in targeted cancer therapy hold great promise for both research and clinical applications and push the boundaries in finding new treatments for various currently incurable cancers. However, these therapies require specific cell-targeting mechanisms for the efficient delivery of drug cargo across the cell membrane to reach intracellular targets and avoid diffusion to unwanted tissues. Traditional drug delivery systems suffer from a limited ability to travel across the barriers posed by cell membranes and, therefore, there is a need for high doses, which are associated with adverse reactions and safety concerns. Bacterial toxins have evolved naturally to specifically target cell subtypes via their receptor binding module, penetrating the cell membrane efficiently through the membrane translocation process and then successfully delivering the toxic cargo into the host cytosol. They have, thus, been harnessed for the delivery of various drugs. In this review, we focus on bacterial toxin translocation mechanisms and recent progress in the targeted delivery systems of cancer therapy drugs that have been inspired by the receptor binding and membrane translocation processes of the anthrax toxin protective antigen, diphtheria toxin, and Pseudomonas exotoxin A. We also discuss the challenges and limitations of these studies that should be addressed before bacterial toxin-based drug delivery systems can become a viable new generation of drug delivery approaches in clinical translation. Full article
(This article belongs to the Special Issue Advances in Bacterial Toxin-Based Platforms)
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15 pages, 2580 KiB  
Article
Model-Based Characterization of E. coli Strains with Impaired Glucose Uptake
Bioengineering 2023, 10(7), 808; https://doi.org/10.3390/bioengineering10070808 - 05 Jul 2023
Viewed by 1762
Abstract
The bacterium Escherichia coli is a widely used organism in biotechnology. For high space-time yields, glucose-limited fed-batch technology is the industry standard; this is because an overflow metabolism of acetate occurs at high glucose concentrations. As an interesting alternative, various strains with limited [...] Read more.
The bacterium Escherichia coli is a widely used organism in biotechnology. For high space-time yields, glucose-limited fed-batch technology is the industry standard; this is because an overflow metabolism of acetate occurs at high glucose concentrations. As an interesting alternative, various strains with limited glucose uptake have been developed. However, these have not yet been characterized under process conditions. To demonstrate the efficiency of our previously developed high-throughput robotic platform, in the present work, we characterized three different exemplary E. coli knockout (KO) strains with limited glucose uptake capacities at three different scales (microtiter plates, 10 mL bioreactor system and 100 mL bioreactor system) under excess glucose conditions with different initial glucose concentrations. The extensive measurements of growth behavior, substrate consumption, respiration, and overflow metabolism were then used to determine the appropriate growth parameters using a mechanistic mathematical model, which allowed for a comprehensive comparative analysis of the strains. The analysis was performed coherently with these different reactor configurations and the results could be successfully transferred from one platform to another. Single and double KO mutants showed reduced specific rates for substrate uptake qSmax and acetate production qApmax; meanwhile, higher glucose concentrations had adverse effects on the biomass yield coefficient YXSem. Additional parameters compared to previous studies for the oxygen uptake rate and carbon dioxide production rate indicated differences in the specific oxygen uptake rate qOmax. This study is an example of how automated robotic equipment, together with mathematical model-based approaches, can be successfully used to characterize strains and obtain comprehensive information more quickly, with a trade-off between throughput and analytical capacity. Full article
(This article belongs to the Special Issue Design, Optimization and Scale-Up of Industrial Bioprocess)
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15 pages, 6536 KiB  
Article
Co-Electrospun Poly(ε-Caprolactone)/Zein Articular Cartilage Scaffolds
Bioengineering 2023, 10(7), 771; https://doi.org/10.3390/bioengineering10070771 - 27 Jun 2023
Viewed by 1273
Abstract
Osteoarthritis scaffold-based grafts fail because of poor integration with the surrounding soft tissue and inadequate tribological properties. To circumvent this, we propose electrospun poly(ε-caprolactone)/zein-based scaffolds owing to their biomimetic capabilities. The scaffold surfaces were characterized using Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, static [...] Read more.
Osteoarthritis scaffold-based grafts fail because of poor integration with the surrounding soft tissue and inadequate tribological properties. To circumvent this, we propose electrospun poly(ε-caprolactone)/zein-based scaffolds owing to their biomimetic capabilities. The scaffold surfaces were characterized using Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, static water contact angles, and profilometry. Scaffold biocompatibility properties were assessed by measuring protein adsorption (Bicinchoninic Acid Assay), cell spreading (stained F-actin), and metabolic activity (PrestoBlue™ Cell Viability Reagent) of primary bovine chondrocytes. The data show that zein surface segregation in the membranes not only completely changed the hydrophobic behavior of the materials, but also increased the cell yield and metabolic activity on the scaffolds. The surface segregation is verified by the infrared peak at 1658 cm−1, along with the presence and increase in N1 content in the survey XPS. This observation could explain the decrease in the water contact angles from 125° to approximately 60° in zein-comprised materials and the decrease in the protein adsorption of both bovine serum albumin and synovial fluid by half. Surface nano roughness in the PCL/zein samples additionally benefited the radial spreading of bovine chondrocytes. This study showed that co-electrospun PCL/zein scaffolds have promising surface and biocompatibility properties for use in articular-tissue-engineering applications. Full article
(This article belongs to the Special Issue Biopolymers and Nano-Objects Applications in Bioengineering)
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17 pages, 10148 KiB  
Article
Progressive Rehabilitation Based on EMG Gesture Classification and an MPC-Driven Exoskeleton
Bioengineering 2023, 10(7), 770; https://doi.org/10.3390/bioengineering10070770 - 27 Jun 2023
Viewed by 1408
Abstract
Stroke is a leading cause of disability and death worldwide, with a prevalence of 200 millions of cases worldwide. Motor disability is presented in 80% of patients. In this context, physical rehabilitation plays a fundamental role for gradually recovery of mobility. In this [...] Read more.
Stroke is a leading cause of disability and death worldwide, with a prevalence of 200 millions of cases worldwide. Motor disability is presented in 80% of patients. In this context, physical rehabilitation plays a fundamental role for gradually recovery of mobility. In this work, we designed a robotic hand exoskeleton to support rehabilitation of patients after a stroke episode. The system acquires electromyographic (EMG) signals in the forearm, and automatically estimates the movement intention for five gestures. Subsequently, we developed a predictive adaptive control of the exoskeleton to compensate for three different levels of muscle fatigue during the rehabilitation therapy exercises. The proposed system could be used to assist the rehabilitation therapy of the patients by providing a repetitive, intense, and adaptive assistance. Full article
(This article belongs to the Section Biosignal Processing)
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16 pages, 7410 KiB  
Article
The Power of ECG in Semi-Automated Seizure Detection in Addition to Two-Channel behind-the-Ear EEG
Bioengineering 2023, 10(4), 491; https://doi.org/10.3390/bioengineering10040491 - 20 Apr 2023
Cited by 2 | Viewed by 1716
Abstract
Long-term home monitoring of people living with epilepsy cannot be achieved using the standard full-scalp electroencephalography (EEG) coupled with video. Wearable seizure detection devices, such as behind-the-ear EEG (bte-EEG), offer an unobtrusive method for ambulatory follow-up of this population. Combining bte-EEG with electrocardiography [...] Read more.
Long-term home monitoring of people living with epilepsy cannot be achieved using the standard full-scalp electroencephalography (EEG) coupled with video. Wearable seizure detection devices, such as behind-the-ear EEG (bte-EEG), offer an unobtrusive method for ambulatory follow-up of this population. Combining bte-EEG with electrocardiography (ECG) can enhance automated seizure detection performance. However, such frameworks produce high false alarm rates, making visual review necessary. This study aimed to evaluate a semi-automated multimodal wearable seizure detection framework using bte-EEG and ECG. Using the SeizeIT1 dataset of 42 patients with focal epilepsy, an automated multimodal seizure detection algorithm was used to produce seizure alarms. Two reviewers evaluated the algorithm’s detections twice: (1) using only bte-EEG data and (2) using bte-EEG, ECG, and heart rate signals. The readers achieved a mean sensitivity of 59.1% in the bte-EEG visual experiment, with a false detection rate of 6.5 false detections per day. Adding ECG resulted in a higher mean sensitivity (62.2%) and a largely reduced false detection rate (mean of 2.4 false detections per day), as well as an increased inter-rater agreement. The multimodal framework allows for efficient review time, making it beneficial for both clinicians and patients. Full article
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15 pages, 41119 KiB  
Article
Establishment of Surgical Difficulty Grading System and Application of MRI-Based Artificial Intelligence to Stratify Difficulty in Laparoscopic Rectal Surgery
Bioengineering 2023, 10(4), 468; https://doi.org/10.3390/bioengineering10040468 - 12 Apr 2023
Cited by 2 | Viewed by 1456
Abstract
(1) Background: The difficulty of pelvic operation is greatly affected by anatomical constraints. Defining this difficulty and assessing it based on conventional methods has some limitations. Artificial intelligence (AI) has enabled rapid advances in surgery, but its role in assessing the difficulty of [...] Read more.
(1) Background: The difficulty of pelvic operation is greatly affected by anatomical constraints. Defining this difficulty and assessing it based on conventional methods has some limitations. Artificial intelligence (AI) has enabled rapid advances in surgery, but its role in assessing the difficulty of laparoscopic rectal surgery is unclear. This study aimed to establish a difficulty grading system to assess the difficulty of laparoscopic rectal surgery, as well as utilize this system to evaluate the reliability of pelvis-induced difficulties described by MRI-based AI. (2) Methods: Patients who underwent laparoscopic rectal surgery from March 2019 to October 2022 were included, and were divided into a non-difficult group and difficult group. This study was divided into two stages. In the first stage, a difficulty grading system was developed and proposed to assess the surgical difficulty caused by the pelvis. In the second stage, AI was used to build a model, and the ability of the model to stratify the difficulty of surgery was evaluated at this stage, based on the results of the first stage; (3) Results: Among the 108 enrolled patients, 53 patients (49.1%) were in the difficult group. Compared to the non-difficult group, there were longer operation times, more blood loss, higher rates of anastomotic leaks, and poorer specimen quality in the difficult group. In the second stage, after training and testing, the average accuracy of the four-fold cross validation models on the test set was 0.830, and the accuracy of the merged AI model was 0.800, the precision was 0.786, the specificity was 0.750, the recall was 0.846, the F1-score was 0.815, the area under the receiver operating curve was 0.78 and the average precision was 0.69; (4) Conclusions: This study successfully proposed a feasible grading system for surgery difficulty and developed a predictive model with reasonable accuracy using AI, which can assist surgeons in determining surgical difficulty and in choosing the optimal surgical approach for rectal cancer patients with a structurally difficult pelvis. Full article
(This article belongs to the Special Issue Deep Learning and Medical Innovation in Minimally Invasive Surgery)
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19 pages, 2715 KiB  
Review
Electrical Stimulation in Cartilage Tissue Engineering
Bioengineering 2023, 10(4), 454; https://doi.org/10.3390/bioengineering10040454 - 07 Apr 2023
Cited by 3 | Viewed by 1874
Abstract
Electrical stimulation (ES) has been frequently used in different biomedical applications both in vitro and in vivo. Numerous studies have demonstrated positive effects of ES on cellular functions, including metabolism, proliferation, and differentiation. The application of ES to cartilage tissue for increasing extracellular [...] Read more.
Electrical stimulation (ES) has been frequently used in different biomedical applications both in vitro and in vivo. Numerous studies have demonstrated positive effects of ES on cellular functions, including metabolism, proliferation, and differentiation. The application of ES to cartilage tissue for increasing extracellular matrix formation is of interest, as cartilage is not able to restore its lesions owing to its avascular nature and lack of cells. Various ES approaches have been used to stimulate chondrogenic differentiation in chondrocytes and stem cells; however, there is a huge gap in systematizing ES protocols used for chondrogenic differentiation of cells. This review focuses on the application of ES for chondrocyte and mesenchymal stem cell chondrogenesis for cartilage tissue regeneration. The effects of different types of ES on cellular functions and chondrogenic differentiation are reviewed, systematically providing ES protocols and their advantageous effects. Moreover, cartilage 3D modeling using cells in scaffolds/hydrogels under ES are observed, and recommendations on reporting about the use of ES in different studies are provided to ensure adequate consolidation of knowledge in the area of ES. This review brings novel insights into the further application of ES in in vitro studies, which are promising for further cartilage repair techniques. Full article
(This article belongs to the Special Issue Design and Fabrication of Artificial Stem Cell Microenvironments II)
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23 pages, 4305 KiB  
Article
Human-Derived Cortical Neurospheroids Coupled to Passive, High-Density and 3D MEAs: A Valid Platform for Functional Tests
Bioengineering 2023, 10(4), 449; https://doi.org/10.3390/bioengineering10040449 - 06 Apr 2023
Viewed by 2190
Abstract
With the advent of human-induced pluripotent stem cells (hiPSCs) and differentiation protocols, methods to create in-vitro human-derived neuronal networks have been proposed. Although monolayer cultures represent a valid model, adding three-dimensionality (3D) would make them more representative of an in-vivo environment. Thus, human-derived [...] Read more.
With the advent of human-induced pluripotent stem cells (hiPSCs) and differentiation protocols, methods to create in-vitro human-derived neuronal networks have been proposed. Although monolayer cultures represent a valid model, adding three-dimensionality (3D) would make them more representative of an in-vivo environment. Thus, human-derived 3D structures are becoming increasingly used for in-vitro disease modeling. Achieving control over the final cell composition and investigating the exhibited electrophysiological activity is still a challenge. Thence, methodologies to create 3D structures with controlled cellular density and composition and platforms capable of measuring and characterizing the functional aspects of these samples are needed. Here, we propose a method to rapidly generate neurospheroids of human origin with control over cell composition that can be used for functional investigations. We show a characterization of the electrophysiological activity exhibited by the neurospheroids by using micro-electrode arrays (MEAs) with different types (i.e., passive, C-MOS, and 3D) and number of electrodes. Neurospheroids grown in free culture and transferred on MEAs exhibited functional activity that can be chemically and electrically modulated. Our results indicate that this model holds great potential for an in-depth study of signal transmission to drug screening and disease modeling and offers a platform for in-vitro functional testing. Full article
(This article belongs to the Special Issue 3D Cell Culture in Disease Modeling and Tissue Regeneration)
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20 pages, 3466 KiB  
Article
Fabrication of Hydrogel-Based Composite Fibers and Computer Simulation of the Filler Dynamics in the Composite Flow
Bioengineering 2023, 10(4), 448; https://doi.org/10.3390/bioengineering10040448 - 06 Apr 2023
Cited by 2 | Viewed by 1633
Abstract
Fibrous structures with anisotropic fillers as composites have found increasing interest in the field of biofabrication since they can mimic the extracellular matrix of anisotropic tissues such as skeletal muscle or nerve tissue. In the present work, the inclusion of anisotropic fillers in [...] Read more.
Fibrous structures with anisotropic fillers as composites have found increasing interest in the field of biofabrication since they can mimic the extracellular matrix of anisotropic tissues such as skeletal muscle or nerve tissue. In the present work, the inclusion of anisotropic fillers in hydrogel-based filaments with an interpenetrating polymeric network (IPN) was evaluated and the dynamics of such fillers in the composite flow were analyzed using computational simulations. In the experimental part, microfabricated rods (200 and 400 μm length, 50 μm width) were used as anisotropic fillers in extrusion of composite filaments using two techniques of wet spinning and 3D printing. Hydrogels such as oxidized alginate (ADA) and methacrylated gelatin (GelMA) were used as matrices. In the computational simulation, a combination of computational fluid dynamics and coarse-grained molecular dynamics was used to study the dynamics of rod-like fillers in the flow field of a syringe. It showed that, during the extrusion process, microrods are far from being well aligned. Instead, many of them tumble on their way through the needle leading to a random orientation in the fiber which was confirmed experimentally. Full article
(This article belongs to the Special Issue 3D-Bioprinting in Bioengineering)
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20 pages, 1639 KiB  
Systematic Review
Machine Learning for Brain MRI Data Harmonisation: A Systematic Review
Bioengineering 2023, 10(4), 397; https://doi.org/10.3390/bioengineering10040397 - 23 Mar 2023
Cited by 3 | Viewed by 2574
Abstract
Background: Magnetic Resonance Imaging (MRI) data collected from multiple centres can be heterogeneous due to factors such as the scanner used and the site location. To reduce this heterogeneity, the data needs to be harmonised. In recent years, machine learning (ML) has been [...] Read more.
Background: Magnetic Resonance Imaging (MRI) data collected from multiple centres can be heterogeneous due to factors such as the scanner used and the site location. To reduce this heterogeneity, the data needs to be harmonised. In recent years, machine learning (ML) has been used to solve different types of problems related to MRI data, showing great promise. Objective: This study explores how well various ML algorithms perform in harmonising MRI data, both implicitly and explicitly, by summarising the findings in relevant peer-reviewed articles. Furthermore, it provides guidelines for the use of current methods and identifies potential future research directions. Method: This review covers articles published through PubMed, Web of Science, and IEEE databases through June 2022. Data from studies were analysed based on the criteria of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Quality assessment questions were derived to assess the quality of the included publications. Results: a total of 41 articles published between 2015 and 2022 were identified and analysed. In the review, MRI data has been found to be harmonised either in an implicit (n = 21) or an explicit (n = 20) way. Three MRI modalities were identified: structural MRI (n = 28), diffusion MRI (n = 7) and functional MRI (n = 6). Conclusion: Various ML techniques have been employed to harmonise different types of MRI data. There is currently a lack of consistent evaluation methods and metrics used across studies, and it is recommended that the issue be addressed in future studies. Harmonisation of MRI data using ML shows promises in improving performance for ML downstream tasks, while caution should be exercised when using ML-harmonised data for direct interpretation. Full article
(This article belongs to the Special Issue Artificial Intelligence in Biomedical Imaging)
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48 pages, 4845 KiB  
Review
Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends
Bioengineering 2023, 10(3), 372; https://doi.org/10.3390/bioengineering10030372 - 17 Mar 2023
Cited by 15 | Viewed by 5035
Abstract
Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and [...] Read more.
Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural activation and connectivity. In this work, we provide a technical account and a categorization of the most-used data-driven approaches to assess brain-functional connectivity, intended as the study of the statistical dependencies between the recorded EEG signals. Different pairwise and multivariate, as well as directed and non-directed connectivity metrics are discussed with a pros–cons approach, in the time, frequency, and information-theoretic domains. The establishment of conceptual and mathematical relationships between metrics from these three frameworks, and the discussion of novel methodological approaches, will allow the reader to go deep into the problem of inferring functional connectivity in complex networks. Furthermore, emerging trends for the description of extended forms of connectivity (e.g., high-order interactions) are also discussed, along with graph-theory tools exploring the topological properties of the network of connections provided by the proposed metrics. Applications to EEG data are reviewed. In addition, the importance of source localization, and the impacts of signal acquisition and pre-processing techniques (e.g., filtering, source localization, and artifact rejection) on the connectivity estimates are recognized and discussed. By going through this review, the reader could delve deeply into the entire process of EEG pre-processing and analysis for the study of brain functional connectivity and learning, thereby exploiting novel methodologies and approaches to the problem of inferring connectivity within complex networks. Full article
(This article belongs to the Special Issue Featured Papers in Computer Methods in Biomedicine)
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15 pages, 1792 KiB  
Article
Prediction of Cognitive Load from Electroencephalography Signals Using Long Short-Term Memory Network
Bioengineering 2023, 10(3), 361; https://doi.org/10.3390/bioengineering10030361 - 15 Mar 2023
Cited by 6 | Viewed by 2138
Abstract
In recent years, the development of adaptive models to tailor instructional content to learners by measuring their cognitive load has become a topic of active research. Brain fog, also known as confusion, is a common cause of poor performance, and real-time detection of [...] Read more.
In recent years, the development of adaptive models to tailor instructional content to learners by measuring their cognitive load has become a topic of active research. Brain fog, also known as confusion, is a common cause of poor performance, and real-time detection of confusion is a challenging and important task for applications in online education and driver fatigue detection. In this study, we propose a deep learning method for cognitive load recognition based on electroencephalography (EEG) signals using a long short-term memory network (LSTM) with an attention mechanism. We obtained EEG signal data from a database of brainwave information and associated data on mental load. We evaluated the performance of the proposed LSTM technique in comparison with random forest, Adaptive Boosting (AdaBoost), support vector machine, eXtreme Gradient Boosting (XGBoost), and artificial neural network models. The experimental results demonstrated that the proposed approach had the highest accuracy of 87.1% compared to those of other algorithms, including random forest (64%), AdaBoost (64.31%), support vector machine (60.9%), XGBoost (67.3%), and artificial neural network models (71.4%). The results of this study support the development of a personalized adaptive learning system designed to measure and actively respond to learners’ cognitive load in real time using wireless portable EEG systems. Full article
(This article belongs to the Special Issue Biomedical Application of Big Data and Artificial Intelligence)
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14 pages, 1546 KiB  
Article
Visual Blood, Visualisation of Blood Gas Analysis in Virtual Reality, Leads to More Correct Diagnoses: A Computer-Based, Multicentre, Simulation Study
Bioengineering 2023, 10(3), 340; https://doi.org/10.3390/bioengineering10030340 - 08 Mar 2023
Cited by 2 | Viewed by 1631
Abstract
Interpreting blood gas analysis results can be challenging for the clinician, especially in stressful situations under time pressure. To foster fast and correct interpretation of blood gas results, we developed Visual Blood. This computer-based, multicentre, noninferiority study compared Visual Blood and conventional arterial [...] Read more.
Interpreting blood gas analysis results can be challenging for the clinician, especially in stressful situations under time pressure. To foster fast and correct interpretation of blood gas results, we developed Visual Blood. This computer-based, multicentre, noninferiority study compared Visual Blood and conventional arterial blood gas (ABG) printouts. We presented six scenarios to anaesthesiologists, once with Visual Blood and once with the conventional ABG printout. The primary outcome was ABG parameter perception. The secondary outcomes included correct clinical diagnoses, perceived diagnostic confidence, and perceived workload. To analyse the results, we used mixed models and matched odds ratios. Analysing 300 within-subject cases, we showed noninferiority of Visual Blood compared to ABG printouts concerning the rate of correctly perceived ABG parameters (rate ratio, 0.96; 95% CI, 0.92–1.00; p = 0.06). Additionally, the study revealed two times higher odds of making the correct clinical diagnosis using Visual Blood (OR, 2.16; 95% CI, 1.42–3.29; p < 0.001) than using ABG printouts. There was no or, respectively, weak evidence for a difference in diagnostic confidence (OR, 0.84; 95% CI, 0.58–1.21; p = 0.34) and perceived workload (Coefficient, 2.44; 95% CI, −0.09–4.98; p = 0.06). This study showed that participants did not perceive the ABG parameters better, but using Visual Blood resulted in more correct clinical diagnoses than using conventional ABG printouts. This suggests that Visual Blood allows for a higher level of situation awareness beyond individual parameters’ perception. However, the study also highlighted the limitations of today’s virtual reality headsets and Visual Blood. Full article
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18 pages, 3863 KiB  
Article
Exploring the Role of Visual Guidance in Motor Imagery-Based Brain-Computer Interface: An EEG Microstate-Specific Functional Connectivity Study
Bioengineering 2023, 10(3), 281; https://doi.org/10.3390/bioengineering10030281 - 21 Feb 2023
Cited by 2 | Viewed by 1857
Abstract
Motor imagery-based brain–computer interfaces (BCI) have been widely recognized as beneficial tools for rehabilitation applications. Moreover, visually guided motor imagery was introduced to improve the rehabilitation impact. However, the reported results to support these techniques remain unsatisfactory. Electroencephalography (EEG) signals can be represented [...] Read more.
Motor imagery-based brain–computer interfaces (BCI) have been widely recognized as beneficial tools for rehabilitation applications. Moreover, visually guided motor imagery was introduced to improve the rehabilitation impact. However, the reported results to support these techniques remain unsatisfactory. Electroencephalography (EEG) signals can be represented by a sequence of a limited number of topographies (microstates). To explore the dynamic brain activation patterns, we conducted EEG microstate and microstate-specific functional connectivity analyses on EEG data under motor imagery (MI), motor execution (ME), and guided MI (GMI) conditions. By comparing sixteen microstate parameters, the brain activation patterns induced by GMI show more similarities to ME than MI from a microstate perspective. The mean duration and duration of microstate four are proposed as biomarkers to evaluate motor condition. A support vector machine (SVM) classifier trained with microstate parameters achieved average accuracies of 80.27% and 66.30% for ME versus MI and GMI classification, respectively. Further, functional connectivity patterns showed a strong relationship with microstates. Key node analysis shows clear switching of key node distribution between brain areas among different microstates. The neural mechanism of the switching pattern is discussed. While microstate analysis indicates similar brain dynamics between GMI and ME, graph theory-based microstate-specific functional connectivity analysis implies that visual guidance may reduce the functional integration of the brain network during MI. Thus, we proposed that combined MI and GMI for BCI can improve neurorehabilitation effects. The present findings provide insights for understanding the neural mechanism of microstates, the role of visual guidance in MI tasks, and the experimental basis for developing new BCI-aided rehabilitation systems. Full article
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21 pages, 6713 KiB  
Article
Multilayer In Vitro Human Skin Tissue Platforms for Quantitative Burn Injury Investigation
Bioengineering 2023, 10(2), 265; https://doi.org/10.3390/bioengineering10020265 - 17 Feb 2023
Cited by 1 | Viewed by 1719
Abstract
This study presents a multilayer in vitro human skin platform to quantitatively relate predicted spatial time–temperature history with measured tissue injury response. This information is needed to elucidate high-temperature, short-duration burn injury kinetics and enables determination of relevant input parameters for computational models [...] Read more.
This study presents a multilayer in vitro human skin platform to quantitatively relate predicted spatial time–temperature history with measured tissue injury response. This information is needed to elucidate high-temperature, short-duration burn injury kinetics and enables determination of relevant input parameters for computational models to facilitate treatment planning. Multilayer in vitro skin platforms were constructed using human dermal keratinocytes and fibroblasts embedded in collagen I hydrogels. After three seconds of contact with a 50–100 °C burn tip, ablation, cell death, apoptosis, and HSP70 expression were spatially measured using immunofluorescence confocal microscopy. Finite element modeling was performed using the measured thermal characteristics of skin platforms to determine the temperature distribution within platforms over time. The process coefficients for the Arrhenius thermal injury model describing tissue ablation and cell death were determined such that the predictions calculated from the time–temperature histories fit the experimental burn results. The activation energy for thermal collagen ablation and cell death was found to be significantly lower for short-duration, high-temperature burns than those found for long-duration, low-temperature burns. Analysis of results suggests that different injury mechanisms dominate at higher temperatures, necessitating burn research in the temperature ranges of interest and demonstrating the practicality of the proposed skin platform for this purpose. Full article
(This article belongs to the Special Issue Advances in Organs-on-a-Chip Engineering)
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18 pages, 10407 KiB  
Article
Characterization of Perinatal Stem Cell Spheroids for the Development of Cell Therapy Strategy
Bioengineering 2023, 10(2), 189; https://doi.org/10.3390/bioengineering10020189 - 02 Feb 2023
Cited by 4 | Viewed by 2336
Abstract
Type 1 diabetes mellitus (T1DM) is a complex metabolic disease characterized by a massive loss of insulin-producing cells due to an autoimmune reaction. Currently, daily subcutaneous administration of exogenous insulin is the only effective treatment. Therefore, in recent years considerable interest has been [...] Read more.
Type 1 diabetes mellitus (T1DM) is a complex metabolic disease characterized by a massive loss of insulin-producing cells due to an autoimmune reaction. Currently, daily subcutaneous administration of exogenous insulin is the only effective treatment. Therefore, in recent years considerable interest has been given to stem cell therapy and in particular to the use of three-dimensional (3D) cell cultures to better reproduce in vivo conditions. The goal of this study is to provide a reliable cellular model that could be investigated for regenerative medicine applications for the replacement of insulin-producing cells in T1DM. To pursue this aim we create a co-culture spheroid of amniotic epithelial cells (AECs) and Wharton’s jelly mesenchymal stromal cells (WJ-MSCs) in a one-to-one ratio. The resulting co-culture spheroids were analyzed for viability, extracellular matrix production, and hypoxic state in both early- and long-term cultures. Our results suggest that co-culture spheroids are stable in long-term culture and are still viable with a consistent extracellular matrix production evaluated with immunofluorescence staining. These findings suggest that this co-culture may potentially be differentiated into endo-pancreatic cells for regenerative medicine applications in T1DM. Full article
(This article belongs to the Special Issue 3D Cell Culture in Disease Modeling and Tissue Regeneration)
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14 pages, 1580 KiB  
Article
Contactless Camera-Based Sleep Staging: The HealthBed Study
Bioengineering 2023, 10(1), 109; https://doi.org/10.3390/bioengineering10010109 - 12 Jan 2023
Cited by 10 | Viewed by 1882
Abstract
Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances in camera sensor technology and data analysis techniques enable contactless monitoring of heart rate variability (HRV). In turn, this may allow remote assessment of sleep stages, as different [...] Read more.
Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances in camera sensor technology and data analysis techniques enable contactless monitoring of heart rate variability (HRV). In turn, this may allow remote assessment of sleep stages, as different HRV metrics indirectly reflect the expression of sleep stages. We evaluated a camera-based remote photoplethysmography (PPG) setup to perform automated classification of sleep stages in near darkness. Based on the contactless measurement of pulse rate variability, we use a previously developed HRV-based algorithm for 3 and 4-class sleep stage classification. Performance was evaluated on data of 46 healthy participants obtained from simultaneous overnight recording of PSG and camera-based remote PPG. To validate the results and for benchmarking purposes, the same algorithm was used to classify sleep stages based on the corresponding ECG data. Compared to manually scored PSG, the remote PPG-based algorithm achieved moderate agreement on both 3 class (Wake–N1/N2/N3–REM) and 4 class (Wake–N1/N2–N3–REM) classification, with average κ of 0.58 and 0.49 and accuracy of 81% and 68%, respectively. This is in range with other performance metrics reported on sensing technologies for wearable sleep staging, showing the potential of video-based non-contact sleep staging. Full article
(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)
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16 pages, 8893 KiB  
Article
Detection of Bacteria-Induced Early-Stage Dental Caries Using Three-Dimensional Mid-Infrared Thermophotonic Imaging
Bioengineering 2023, 10(1), 112; https://doi.org/10.3390/bioengineering10010112 - 12 Jan 2023
Cited by 1 | Viewed by 1962
Abstract
Tooth decay, or dental caries, is a widespread and costly disease that is reversible when detected early in its formation. Current dental caries diagnostic methods including X-ray imaging and intraoral examination lack the sensitivity and specificity required to routinely detect caries early in [...] Read more.
Tooth decay, or dental caries, is a widespread and costly disease that is reversible when detected early in its formation. Current dental caries diagnostic methods including X-ray imaging and intraoral examination lack the sensitivity and specificity required to routinely detect caries early in its formation. Thermophotonic imaging presents itself as a highly sensitive and non-ionizing solution, making it suitable for the frequent monitoring of caries progression. Here, we utilized a treatment protocol to produce bacteria-induced caries lesions. The lesions were imaged using two related three-dimensional photothermal imaging modalities: truncated correlation photothermal coherence tomography (TC-PCT) and its enhanced modification eTC-PCT. In addition, micro-computed tomography (μ-CT) and visual inspection by a clinical dentist were used to validate and quantify the severities of the lesions. The observational findings demonstrate the high sensitivity and depth profiling capabilities of the thermophotonic modalities, showcasing their potential use as a non-ionizing clinical tool for the early detection of dental caries. Full article
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22 pages, 3184 KiB  
Article
A Two-Compartment Fermentation System to Quantify Strain-Specific Interactions in Microbial Co-Cultures
Bioengineering 2023, 10(1), 103; https://doi.org/10.3390/bioengineering10010103 - 11 Jan 2023
Cited by 1 | Viewed by 1751
Abstract
To fulfil the growing interest in investigating microbial interactions in co-cultures, a novel two-compartment bioreactor system was developed, characterised, and implemented. The system allowed for the exchange of amino acids and peptides via a polyethersulfone membrane that retained biomass. Further system characterisation revealed [...] Read more.
To fulfil the growing interest in investigating microbial interactions in co-cultures, a novel two-compartment bioreactor system was developed, characterised, and implemented. The system allowed for the exchange of amino acids and peptides via a polyethersulfone membrane that retained biomass. Further system characterisation revealed a Bodenstein number of 18, which hints at backmixing. Together with other physical settings, the existence of unwanted inner-compartment substrate gradients could be ruled out. Furthermore, the study of Damkoehler numbers indicated that a proper metabolite supply between compartments was enabled. Implementing the two-compartment system (2cs) for growing Streptococcus thermophilus and Lactobacillus delbrueckii subs. bulgaricus, which are microorganisms commonly used in yogurt starter cultures, revealed only a small variance between the one-compartment and two-compartment approaches. The 2cs enabled the quantification of the strain-specific production and consumption rates of amino acids in an interacting S. thermophilusL. bulgaricus co-culture. Therefore, comparisons between mono- and co-culture performance could be achieved. Both species produce and release amino acids. Only alanine was produced de novo from glucose through potential transaminase activity by L. bulgaricus and consumed by S. thermophilus. Arginine availability in peptides was limited to S. thermophilus’ growth, indicating active biosynthesis and dependency on the proteolytic activity of L. bulgaricus. The application of the 2cs not only opens the door for the quantification of exchange fluxes between microbes but also enables continuous production modes, for example, for targeted evolution studies. Full article
(This article belongs to the Topic Bioreactors: Control, Optimization and Applications)
(This article belongs to the Section Biochemical Engineering)
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13 pages, 5187 KiB  
Article
Portable Iontophoresis Device for Efficient Drug Delivery
Bioengineering 2023, 10(1), 88; https://doi.org/10.3390/bioengineering10010088 - 09 Jan 2023
Viewed by 2463
Abstract
The timely delivery of drugs to specific locations in the body is imperative to ensure the efficacy of treatment. This study introduces a portable facial device that can deliver drugs efficiently using iontophoresis. Two types of power supplies—direct current and pulse ionization supplies—were [...] Read more.
The timely delivery of drugs to specific locations in the body is imperative to ensure the efficacy of treatment. This study introduces a portable facial device that can deliver drugs efficiently using iontophoresis. Two types of power supplies—direct current and pulse ionization supplies—were manufactured by injection molding. Electrical stimulation elements, which contained Ag metal wires, were woven into facial mask packs. The diffusion phenomenon in the skin and iontophoresis were numerically modeled. Injection molding was simulated before the device was manufactured. Analysis using rhodamine B demonstrated a remarkable increase in the moisture content of the skin and effective absorption of the drug under an applied electric field upon the application of iontophoresis. The proposed concept and design constitute a new method of achieving effective drug absorption with wearable devices. Full article
(This article belongs to the Special Issue Drug Delivery Systems, What's New?)
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25 pages, 5943 KiB  
Article
Attenuation of SCI-Induced Hypersensitivity by Intensive Locomotor Training and Recombinant GABAergic Cells
Bioengineering 2023, 10(1), 84; https://doi.org/10.3390/bioengineering10010084 - 09 Jan 2023
Viewed by 1364
Abstract
The underlying mechanisms of spinal cord injury (SCI)-induced chronic pain involve dysfunctional GABAergic signaling and enhanced NMDA signaling. Our previous studies showed that SCI hypersensitivity in rats can be attenuated by recombinant rat GABAergic cells releasing NMDA blocker serine-histogranin (SHG) and by intensive [...] Read more.
The underlying mechanisms of spinal cord injury (SCI)-induced chronic pain involve dysfunctional GABAergic signaling and enhanced NMDA signaling. Our previous studies showed that SCI hypersensitivity in rats can be attenuated by recombinant rat GABAergic cells releasing NMDA blocker serine-histogranin (SHG) and by intensive locomotor training (ILT). The current study combines these approaches and evaluates their analgesic effects on a model of SCI pain in rats. Cells were grafted into the spinal cord at 4 weeks post-SCI to target the chronic pain, and ILT was initiated 5 weeks post-SCI. The hypersensitivity was evaluated weekly, which was followed by histological and biochemical assays. Prolonged effects of the treatment were evaluated in subgroups of animals after we discontinued ILT. The results show attenuation of tactile, heat and cold hypersensitivity in all of the treated animals and reduced levels of proinflammatory cytokines IL1β and TNFα in the spinal tissue and CSF. Animals with recombinant grafts and ILT showed the preservation of analgesic effects even during sedentary periods when the ILT was discontinued. Retraining helped to re-establish the effect of long-term training in all of the groups, with the greatest impact being in animals with recombinant grafts. These findings suggest that intermittent training in combination with cell therapy might be an efficient approach to manage chronic pain in SCI patients. Full article
(This article belongs to the Special Issue Regeneration and Repair in the Central Nervous System)
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17 pages, 2610 KiB  
Article
Unsupervised Learning-Based Non-Invasive Fetal ECG Muti-Level Signal Quality Assessment
Bioengineering 2023, 10(1), 66; https://doi.org/10.3390/bioengineering10010066 - 04 Jan 2023
Cited by 1 | Viewed by 1827
Abstract
Objective: To monitor fetal health and growth, fetal heart rate is a critical indicator. The non-invasive fetal electrocardiogram is a widely employed measurement for fetal heart rate estimation, which is extracted from the electrodes placed on the surface of the maternal abdomen. The [...] Read more.
Objective: To monitor fetal health and growth, fetal heart rate is a critical indicator. The non-invasive fetal electrocardiogram is a widely employed measurement for fetal heart rate estimation, which is extracted from the electrodes placed on the surface of the maternal abdomen. The qualities of the fetal ECG recordings, however, are frequently affected by the noises from various interference sources. In general, the fetal heart rate estimates are unreliable when low-quality fetal ECG signals are used for fetal heart rate estimation, which makes accurate fetal heart rate estimation a challenging task. So, the signal quality assessment for the fetal ECG records is an essential step before fetal heart rate estimation. In other words, some low-quality fetal ECG signal segments are supposed to be detected and removed by utilizing signal quality assessment, so as to improve the accuracy of fetal heart rate estimation. A few supervised learning-based fetal ECG signal quality assessment approaches have been introduced and shown to accurately classify high- and low-quality fetal ECG signal segments, but large fetal ECG datasets with quality annotation are required in these methods. Yet, the labeled fetal ECG datasets are limited. Proposed methods: An unsupervised learning-based multi-level fetal ECG signal quality assessment approach is proposed in this paper for identifying three levels of fetal ECG signal quality. We extracted some features associated with signal quality, including entropy-based features, statistical features, and ECG signal quality indices. Additionally, an autoencoder-based feature is calculated, which is related to the reconstruction error of the spectrograms generated from fetal ECG signal segments. The high-, medium-, and low-quality fetal ECG signal segments are classified by inputting these features into a self-organizing map. Main results: The experimental results showed that our proposal achieved a weighted average F1-score of 90% in three-level fetal ECG signal quality classification. Moreover, with the acceptable removal of detected low-quality signal segments, the errors of fetal heart rate estimation were reduced to a certain extent. Full article
(This article belongs to the Special Issue Monitoring and Analysis of Human Biosignals)
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14 pages, 14852 KiB  
Article
Optimization Design of the Inner Structure for a Bioinspired Heel Pad with Distinct Cushioning Property
Bioengineering 2023, 10(1), 49; https://doi.org/10.3390/bioengineering10010049 - 30 Dec 2022
Cited by 3 | Viewed by 1824
Abstract
In the existing research on prosthetic footplates, rehabilitation insoles, and robot feet, the cushioning parts are basically based on simple mechanisms and elastic pads. Most of them are unable to provide adequate impact resistance especially during contact with the ground. This paper developed [...] Read more.
In the existing research on prosthetic footplates, rehabilitation insoles, and robot feet, the cushioning parts are basically based on simple mechanisms and elastic pads. Most of them are unable to provide adequate impact resistance especially during contact with the ground. This paper developed a bioinspired heel pad by optimizing the inner structures inspired from human heel pad which has great cushioning performance. The distinct structures of the human heel pad were determined through magnetic resonance imaging (MRI) technology and related literatures. Five-layer pads with and without inner structures by using two materials (soft rubber and resin) were obtained, resulting in four bionic heel pads. Three finite element simulations (static, impact, and walking) were conducted to compare the cushioning effects in terms of deformations, ground reactions, and principal stress. The optimal pad with bionic structures and soft rubber material reduced 28.0% peak vertical ground reaction force (GRF) during walking compared with the unstructured resin pad. Human walking tests by a healthy subject wearing the 3D printed bionic pads also showed similar findings, with an almost 20% decrease in peak vertical GRF at normal speed. The soft rubber heel pad with bionic structures has the best cushioning performance, while the unstructured resin pad depicts the poorest. This study proves that with proper design of the inner structures and materials, the bionic pads will demonstrate distinct cushioning properties, which could be applied to the engineering fields, including lower limb prosthesis, robotics, and rehabilitations. Full article
(This article belongs to the Special Issue Biomedical Design and Manufacturing)
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10 pages, 1547 KiB  
Article
Making Visible the Invisible: Automatically Measured Global and Regional Brain Volume Is Associated with Cognitive Impairment and Fatigue in Multiple Sclerosis
Bioengineering 2023, 10(1), 41; https://doi.org/10.3390/bioengineering10010041 - 29 Dec 2022
Cited by 2 | Viewed by 1672
Abstract
In multiple sclerosis (MS), the transition from relapsing-remitting to the secondary-progressive phase is characterized by a progression independent of relapse activity (PIRA), resulting in physical disability accumulation and invisible symptoms, i.e., fatigue and cognitive impairment (CI). These symptoms are related to neurodegenerative processes [...] Read more.
In multiple sclerosis (MS), the transition from relapsing-remitting to the secondary-progressive phase is characterized by a progression independent of relapse activity (PIRA), resulting in physical disability accumulation and invisible symptoms, i.e., fatigue and cognitive impairment (CI). These symptoms are related to neurodegenerative processes and have been correlated with MRI measures of brain atrophy only at a group level; however, the application in clinical practice of atrophy-based measurements for single-patient evaluation is yet to be fully investigated. In the present study, we aimed to evaluate the association between brain atrophy, measured with easy-to-use automatic software, and the “invisible” MS symptoms of cognition and fatigue. A total of 69 MS patients were included in the study; cognitive impairment and fatigue (FSS) (in addition to neurological disability, EDSS) were assessed and correlated with brain volumes calculated using the automated software QyScore® which is validated for single-patient use in the clinical setting. Results showed that the cognitive status was accurately reflected by measures of atrophy, with a sensitivity of up to 90%. CI patients showed a lower volume compared to cognitively normal patients in the whole brain (p = 0.017), gray matter (p = 0.042), insula (p = 0.035), cerebellum (p = 0.008), and limbic lobe (p = 0.049). FSS was associated with temporal lobe (r = −0.37, p = 0.013) and insular (r = −0.36, p = 0.019) volumes. The volumes of the same regions were also associated with EDSS. The global/regional atrophy results, assessed with automatic and easy-to-use software, correlated with cognitive and fatigue symptoms, thus supporting the clinical application in routine patient management. Full article
(This article belongs to the Special Issue Cognitive Impairment in Multiple Sclerosis)
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13 pages, 4266 KiB  
Article
Hand Gesture Signatures Acquisition and Processing by Means of a Novel Ultrasound System
Bioengineering 2023, 10(1), 36; https://doi.org/10.3390/bioengineering10010036 - 28 Dec 2022
Cited by 4 | Viewed by 2174
Abstract
Hand gestures represent a natural way to express concepts and emotions which are peculiar to each culture. Several studies exploit biometric traits, such as fingerprint, iris or face for subject identification purposes. Within this paper, a novel ultrasound system for person identification that [...] Read more.
Hand gestures represent a natural way to express concepts and emotions which are peculiar to each culture. Several studies exploit biometric traits, such as fingerprint, iris or face for subject identification purposes. Within this paper, a novel ultrasound system for person identification that exploits hand gestures is presented. The system works as a sonar, measuring the ultrasonic pressure waves scattered by the subject’s hand, and analysing its Doppler information. Further, several transformations for obtaining time/frequency representations of the acquired signal are computed and a deep learning detector is implemented. The proposed system is cheap, reliable, contactless and can be easily integrated with other personal identification approaches allowing different security levels. The performances are evaluated via experimental tests carried out on a group of 25 volunteers. Results are encouraging, showing the promising potential of the system. Full article
(This article belongs to the Section Biosignal Processing)
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18 pages, 5890 KiB  
Article
The Effect of Tissue Stromal Vascular Fraction as Compared to Cellular Stromal Vascular Fraction to Treat Anal Sphincter Incontinence
Bioengineering 2023, 10(1), 32; https://doi.org/10.3390/bioengineering10010032 - 26 Dec 2022
Viewed by 1551
Abstract
Background: The long-term prognosis of current treatments for anal sphincter incontinence (ASI) is poor. Here, we explored the efficacy of tissue adipose stromal vascular fraction SVF (tSVF) on ASI and compared it to that of cellular SVF (cSVF). We then investigated possible mechanisms. [...] Read more.
Background: The long-term prognosis of current treatments for anal sphincter incontinence (ASI) is poor. Here, we explored the efficacy of tissue adipose stromal vascular fraction SVF (tSVF) on ASI and compared it to that of cellular SVF (cSVF). We then investigated possible mechanisms. Methods: Rat cSVF and tSVF were isolated and labeled with DIL. One day after modeling, three groups received phosphate-buffered saline (PBS), cSVF, tSVF, respectively. The control group received nil modeling nor any treatments. The effect was assessed by function test for anal pressure and electromyography, and staining for fiber content, proliferation and differentiation at day 5 and day 10. Results: cSVF injection resulted in faster healing than tSVF. The cSVF group showed significant improvement on anal pressure on day 10. For the electromyography test, cSVF showed significant improvement for the frequencies on day 10, and for the peak values on both time points, while tSVF showed significant improvement for the peak values on day 10. The two SVF both alleviated fibrosis. Immunofluorescence tracing identified differentiation of some injected cells towards myosatellite cells and smooth muscle cells in both SVF groups. For all the tests, the tSVF group tends to have similar or lower effects than the cSVF group with no significant difference. Conclusion: cSVF and tSVF are both safe and effective in treating ASI, while the effect of cSVF is slighter higher than tSVF. Full article
(This article belongs to the Special Issue Stem Cell-Based Technology for Personalized Medicine Solutions)
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28 pages, 3743 KiB  
Review
Advancement in the Cuffless and Noninvasive Measurement of Blood Pressure: A Review of the Literature and Open Challenges
Bioengineering 2023, 10(1), 27; https://doi.org/10.3390/bioengineering10010027 - 24 Dec 2022
Cited by 9 | Viewed by 3664
Abstract
Hypertension is a chronic condition that is one of the prominent reasons behind cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the deterioration in a health condition could even result in mortality. If it can be detected early, with proper [...] Read more.
Hypertension is a chronic condition that is one of the prominent reasons behind cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the deterioration in a health condition could even result in mortality. If it can be detected early, with proper treatment, undesirable outcomes can be avoided. Until now, the gold standard is the invasive way of measuring blood pressure (BP) using a catheter. Additionally, the cuff-based and noninvasive methods are too cumbersome or inconvenient for frequent measurement of BP. With the advancement of sensor technology, signal processing techniques, and machine learning algorithms, researchers are trying to find the perfect relationships between biomedical signals and changes in BP. This paper is a literature review of the studies conducted on the cuffless noninvasive measurement of BP using biomedical signals. Relevant articles were selected using specific criteria, then traditional techniques for BP measurement were discussed along with a motivation for cuffless measurement use of biomedical signals and machine learning algorithms. The review focused on the progression of different noninvasive cuffless techniques rather than comparing performance among different studies. The literature survey concluded that the use of deep learning proved to be the most accurate among all the cuffless measurement techniques. On the other side, this accuracy has several disadvantages, such as lack of interpretability, computationally extensive, standard validation protocol, and lack of collaboration with health professionals. Additionally, the continuing work by researchers is progressing with a potential solution for these challenges. Finally, future research directions have been provided to encounter the challenges. Full article
(This article belongs to the Special Issue Monitoring and Analysis of Human Biosignals)
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19 pages, 4297 KiB  
Article
Clinical Application of Bioresorbable, Synthetic, Electrospun Matrix in Wound Healing
Bioengineering 2023, 10(1), 9; https://doi.org/10.3390/bioengineering10010009 - 21 Dec 2022
Cited by 7 | Viewed by 1569
Abstract
Electrospun polymeric matrices have long been investigated as constructs for use in regenerative medicine, yet relatively few have been commercialized for human clinical use. In 2017, a novel electrospun matrix, composed of two synthetic biocompatible polymers, polyglactin 910 (PLGA 10:90) and polydioxanone (PDO) [...] Read more.
Electrospun polymeric matrices have long been investigated as constructs for use in regenerative medicine, yet relatively few have been commercialized for human clinical use. In 2017, a novel electrospun matrix, composed of two synthetic biocompatible polymers, polyglactin 910 (PLGA 10:90) and polydioxanone (PDO) of varying pore and fiber sizes (i.e., hybrid-scale) was developed and cleared by the FDA for human clinical use. The present review aims to explain the mechanism of action and review the preclinical and clinical results to summarize the efficacy of the matrix across multiple use cases within the wound care setting, including an assessment of over 150 wounds of varying etiologies treated with the synthetic matrix. Clinical data demonstrated effective use of the synthetic hybrid-scale fiber matrix across a variety of wound etiologies, including diabetic foot and venous leg ulcers, pressure ulcers, burns, and surgical wounds. This review represents a comprehensive clinical demonstration of a synthetic, electrospun, hybrid-scale matrix and illustrates its value and versatility across multiple wound etiologies. Full article
(This article belongs to the Special Issue Feature Papers in Nanotechnology Applications in Bioengineering)
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15 pages, 3661 KiB  
Article
Deep Learning Model for Computer-Aided Diagnosis of Urolithiasis Detection from Kidney–Ureter–Bladder Images
Bioengineering 2022, 9(12), 811; https://doi.org/10.3390/bioengineering9120811 - 16 Dec 2022
Cited by 5 | Viewed by 2981
Abstract
Kidney–ureter–bladder (KUB) imaging is a radiological examination with a low cost, low radiation, and convenience. Although emergency room clinicians can arrange KUB images easily as a first-line examination for patients with suspicious urolithiasis, interpreting the KUB images correctly is difficult for inexperienced clinicians. [...] Read more.
Kidney–ureter–bladder (KUB) imaging is a radiological examination with a low cost, low radiation, and convenience. Although emergency room clinicians can arrange KUB images easily as a first-line examination for patients with suspicious urolithiasis, interpreting the KUB images correctly is difficult for inexperienced clinicians. Obtaining a formal radiology report immediately after a KUB imaging examination can also be challenging. Recently, artificial-intelligence-based computer-aided diagnosis (CAD) systems have been developed to help clinicians who are not experts make correct diagnoses for further treatment more effectively. Therefore, in this study, we proposed a CAD system for KUB imaging based on a deep learning model designed to help first-line emergency room clinicians diagnose urolithiasis accurately. A total of 355 KUB images were retrospectively collected from 104 patients who were diagnosed with urolithiasis at Kaohsiung Chang Gung Memorial Hospital. Then, we trained a deep learning model with a ResNet architecture to classify KUB images in terms of the presence or absence of kidney stones with this dataset of pre-processed images. Finally, we tuned the parameters and tested the model experimentally. The results show that the accuracy, sensitivity, specificity, and F1-measure of the model were 0.977, 0.953, 1, and 0.976 on the validation set and 0.982, 0.964, 1, and 0.982 on the testing set, respectively. Moreover, the results demonstrate that the proposed model performed well compared to the existing CNN-based methods and was able to detect urolithiasis in KUB images successfully. We expect the proposed approach to help emergency room clinicians make accurate diagnoses and reduce unnecessary radiation exposure from computed tomography (CT) scans, along with the associated medical costs. Full article
(This article belongs to the Special Issue Advances of Biomedical Signal Processing)
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23 pages, 7494 KiB  
Article
Hypothermic Preservation of Adipose-Derived Mesenchymal Stromal Cells as a Viable Solution for the Storage and Distribution of Cell Therapy Products
Bioengineering 2022, 9(12), 805; https://doi.org/10.3390/bioengineering9120805 - 14 Dec 2022
Cited by 2 | Viewed by 1989
Abstract
Cell and gene therapies (CGT) have reached new therapeutic targets but have noticeably high prices. Solutions to reduce production costs might be found in CGT storage and transportation since they typically involve cryopreservation, which is a heavily burdened process. Encapsulation at hypothermic temperatures [...] Read more.
Cell and gene therapies (CGT) have reached new therapeutic targets but have noticeably high prices. Solutions to reduce production costs might be found in CGT storage and transportation since they typically involve cryopreservation, which is a heavily burdened process. Encapsulation at hypothermic temperatures (e.g., 2–8 °C) could be a feasible alternative. Adipose tissue-derived mesenchymal stromal cells (MSC(AT)) expanded using fetal bovine serum (FBS)- (MSC-FBS) or human platelet lysate (HPL)-supplemented mediums (MSC-HPL) were encapsulated in alginate beads for 30 min, 5 days, and 12 days. After bead release, cell recovery and viability were determined to assess encapsulation performance. MSC identity was verified by flow cytometry, and a set of assays was performed to evaluate functionality. MSC(AT) were able to survive encapsulated for a standard transportation period of 5 days, with recovery values of 56 ± 5% for MSC-FBS and 77 ± 6% for MSC-HPL (which is a negligible drop compared to earlier timepoints). Importantly, MSC function did not suffer from encapsulation, with recovered cells showing robust differentiation potential, expression of immunomodulatory molecules, and hematopoietic support capacity. MSC(AT) encapsulation was proven possible for a remarkable 12 day period. There is currently no solution to completely replace cryopreservation in CGT logistics and supply chain, although encapsulation has shown potential to act as a serious competitor. Full article
(This article belongs to the Special Issue Mesenchymal Stem Cells in Regenerative Medicine)
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15 pages, 3024 KiB  
Article
Evaluation of AMG510 Therapy on KRAS-Mutant Non–Small Cell Lung Cancer and Colorectal Cancer Cell Using a 3D Invasive Tumor Spheroid System under Normoxia and Hypoxia
Bioengineering 2022, 9(12), 792; https://doi.org/10.3390/bioengineering9120792 - 12 Dec 2022
Cited by 1 | Viewed by 1758
Abstract
A 3D tumor spheroid has been increasingly applied in pharmaceutical development for its simulation of the tumor structure and microenvironment. The embedded-culture of a tumor spheroid within a hydrogel microenvironment could help to improve the mimicking of in vivo cell growth and the [...] Read more.
A 3D tumor spheroid has been increasingly applied in pharmaceutical development for its simulation of the tumor structure and microenvironment. The embedded-culture of a tumor spheroid within a hydrogel microenvironment could help to improve the mimicking of in vivo cell growth and the development of 3D models for tumor invasiveness evaluation, which could enhance its drug efficiency prediction together with cell viability detection. NCI-H23 spheroids and CT-26 spheroids, from a non–small cell lung cancer and colorectal cancer cell line, respectively, together with extracellular matrix were generated for evaluating their sensitivity to AMG510 (a KRASG12C inhibitor) under normoxia and hypoxia conditions, which were created by an on-stage environmental chamber. Results demonstrated that NCI-H23, the KRASG12C moderate expression cell line, only mildly responded to AMG510 treatment in normal 2D and 3D cultures and could be clearly evaluated by our system in hypoxia conditions, while the negative control CT-26 (G12D-mutant) spheroid exhibited no significant response to AMG510 treatment. In summary, our system, together with a controlled microenvironment and imaging methodology, provided an easily assessable and effective methodology for 3D in vitro drug efficiency testing and screenings. Full article
(This article belongs to the Special Issue Advances in Organs-on-a-Chip Engineering)
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20 pages, 4012 KiB  
Article
Automatic Localization of Seizure Onset Zone Based on Multi-Epileptogenic Biomarkers Analysis of Single-Contact from Interictal SEEG
Bioengineering 2022, 9(12), 769; https://doi.org/10.3390/bioengineering9120769 - 05 Dec 2022
Viewed by 2223
Abstract
Successful surgery on drug-resistant epilepsy patients (DRE) needs precise localization of the seizure onset zone (SOZ). Previous studies analyzing this issue still face limitations, such as inadequate analysis of features, low sensitivity and limited generality. Our study proposed an innovative and effective SOZ [...] Read more.
Successful surgery on drug-resistant epilepsy patients (DRE) needs precise localization of the seizure onset zone (SOZ). Previous studies analyzing this issue still face limitations, such as inadequate analysis of features, low sensitivity and limited generality. Our study proposed an innovative and effective SOZ localization method based on multiple epileptogenic biomarkers (spike and HFOs), and analysis of single-contact (MEBM-SC) to address the above problems. We extracted contacts epileptic features from signal distributions and signal energy based on machine learning and end-to-end deep learning. Among them, a normalized pathological ripple rate was designed to reduce the disturbance of physiological ripple and enhance the performance of SOZ localization. Then, a feature selection algorithm based on Shapley value and hypothetical testing (ShapHT+) was used to limit interference from irrelevant features. Moreover, an attention mechanism and a focal loss algorithm were used on the classifier to learn significant features and overcome the unbalance of SOZ/nSOZ contacts. Finally, we provided an SOZ prediction and visualization on magnetic resonance imaging (MRI). Ten patients with DRE were selected to verify our method. The experiment performed cross-validation and revealed that MEBM-SC obtains higher sensitivity. Additionally, the spike has better sensitivity while HFOs have better specificity, and the combination of these biomarkers can achieve the best performance. The study confirmed that MEBM-SC can increase the sensitivity and accuracy of SOZ localization and help clinicians to perform a precise and reliable preoperative evaluation based on interictal SEEG. Full article
(This article belongs to the Special Issue Advances of Biomedical Signal Processing)
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14 pages, 885 KiB  
Review
Bio-Activated PEEK: Promising Platforms for Improving Osteogenesis through Modulating Macrophage Polarization
Bioengineering 2022, 9(12), 747; https://doi.org/10.3390/bioengineering9120747 - 01 Dec 2022
Cited by 1 | Viewed by 1389
Abstract
The attention on orthopedic biomaterials has shifted from their direct osteogenic properties to their osteoimmunomodulation, especially the modulation of macrophage polarization. Presently, advanced technologies endow polyetheretherketone (PEEK) with good osteoimmunomodulation by modifying PEEK surface characteristics or incorporating bioactive substances with regulating macrophage polarization. [...] Read more.
The attention on orthopedic biomaterials has shifted from their direct osteogenic properties to their osteoimmunomodulation, especially the modulation of macrophage polarization. Presently, advanced technologies endow polyetheretherketone (PEEK) with good osteoimmunomodulation by modifying PEEK surface characteristics or incorporating bioactive substances with regulating macrophage polarization. Recent studies have demonstrated that the fabrication of a hydrophilic surface and the incorporation of bioactive substances into PEEK (e.g., zinc, calcium, and phosphate) are good strategies to promote osteogenesis by enhancing the polarization of M2 macrophages. Furthermore, the modification by other osteoimmunomodulatory composites (e.g., lncRNA-MM2P, IL-4, IL-10, and chitosan) and their controlled and desired release may make PEEK an optimal bio-activated implant for regulating and balancing the osteogenic system and immune system. The purpose of this review is to comprehensively evaluate the potential of bio-activated PEEK in polarizing macrophages into M2 phenotype to improve osteogenesis. For this objective, we retrieved and discussed different kinds of bio-activated PEEK regarding improving osteogenesis through modulating macrophage polarization. Meanwhile, the relevant challenges and outlook were presented. We hope that this review can shed light on the development of bio-activated PEEK with more favorable osteoimmunomodulation. Full article
(This article belongs to the Special Issue Current Developments and Applications in Bone Tissue Engineering)
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16 pages, 8183 KiB  
Article
Wave-Encoded Model-Based Deep Learning for Highly Accelerated Imaging with Joint Reconstruction
Bioengineering 2022, 9(12), 736; https://doi.org/10.3390/bioengineering9120736 - 29 Nov 2022
Cited by 7 | Viewed by 1745
Abstract
A recently introduced model-based deep learning (MoDL) technique successfully incorporates convolutional neural network (CNN)-based regularizers into physics-based parallel imaging reconstruction using a small number of network parameters. Wave-controlled aliasing in parallel imaging (CAIPI) is an emerging parallel imaging method that accelerates imaging acquisition [...] Read more.
A recently introduced model-based deep learning (MoDL) technique successfully incorporates convolutional neural network (CNN)-based regularizers into physics-based parallel imaging reconstruction using a small number of network parameters. Wave-controlled aliasing in parallel imaging (CAIPI) is an emerging parallel imaging method that accelerates imaging acquisition by employing sinusoidal gradients in the phase- and slice/partition-encoding directions during the readout to take better advantage of 3D coil sensitivity profiles. We propose wave-encoded MoDL (wave-MoDL) combining the wave-encoding strategy with unrolled network constraints for highly accelerated 3D imaging while enforcing data consistency. We extend wave-MoDL to reconstruct multicontrast data with CAIPI sampling patterns to leverage similarity between multiple images to improve the reconstruction quality. We further exploit this to enable rapid quantitative imaging using an interleaved look-locker acquisition sequence with T2 preparation pulse (3D-QALAS). Wave-MoDL enables a 40 s MPRAGE acquisition at 1 mm resolution at 16-fold acceleration. For quantitative imaging, wave-MoDL permits a 1:50 min acquisition for T1, T2, and proton density mapping at 1 mm resolution at 12-fold acceleration, from which contrast-weighted images can be synthesized as well. In conclusion, wave-MoDL allows rapid MR acquisition and high-fidelity image reconstruction and may facilitate clinical and neuroscientific applications by incorporating unrolled neural networks into wave-CAIPI reconstruction. Full article
(This article belongs to the Special Issue AI in MRI: Frontiers and Applications)
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9 pages, 1082 KiB  
Article
Heart and Breathing Rate Variations as Biomarkers for Anxiety Detection
Bioengineering 2022, 9(11), 711; https://doi.org/10.3390/bioengineering9110711 - 19 Nov 2022
Cited by 8 | Viewed by 2408
Abstract
With advances in portable and wearable devices, it should be possible to analyze and interpret the collected biosignals from those devices to tailor a psychological intervention to help patients. This study focuses on detecting anxiety by using a portable device that collects electrocardiogram [...] Read more.
With advances in portable and wearable devices, it should be possible to analyze and interpret the collected biosignals from those devices to tailor a psychological intervention to help patients. This study focuses on detecting anxiety by using a portable device that collects electrocardiogram (ECG) and respiration (RSP) signals. The feature extraction focused on heart-rate variability (HRV) and breathing-rate variability (BRV). We show that a significant change in these signals occurred between the non-anxiety-induced and anxiety-induced states. The HRV biomarkers were the mean heart rate (MHR; p¯ = 0.04), the standard deviation of the heart rate (SD; p¯ = 0.01), and the standard deviation of NN intervals (SDNN; p¯ = 0.03) for ECG signals, and the mean breath rate (MBR; p¯ = 0.002), the standard deviation of the breath rate (SD; p¯ < 0.0001), the root mean square of successive differences (RMSSD; p¯ < 0.0001) and SDNN (p¯ < 0.0001) for RSP signals. This work extends the existing literature on the relationship between stress and HRV/BRV by being the first to introduce a transitional phase. It contributes to systematically processing mental and emotional impulse data in humans measured via ECG and RSP signals. On the basis of these identified biomarkers, artificial-intelligence or machine-learning algorithms, and rule-based classification, the automated biosignal-based psychological assessment of patients could be within reach. This creates a broad basis for detecting and evaluating psychological abnormalities in individuals upon which future psychological treatment methods could be built using portable and wearable devices. Full article
(This article belongs to the Special Issue Advances of Biomedical Signal Processing)
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16 pages, 9125 KiB  
Article
A Surrogate Model Based on a Finite Element Model of Abdomen for Real-Time Visualisation of Tissue Stress during Physical Examination Training
Bioengineering 2022, 9(11), 687; https://doi.org/10.3390/bioengineering9110687 - 14 Nov 2022
Cited by 2 | Viewed by 3710
Abstract
Robotic patients show great potential for helping to improve medical palpation training, as they can provide feedback that cannot be obtained in a real patient. They provide information about internal organ deformation that can significantly enhance palpation training by giving medical trainees visual [...] Read more.
Robotic patients show great potential for helping to improve medical palpation training, as they can provide feedback that cannot be obtained in a real patient. They provide information about internal organ deformation that can significantly enhance palpation training by giving medical trainees visual insight based on the pressure they apply for palpation. This can be achieved by using computational models of abdomen mechanics. However, such models are computationally expensive, and thus unable to provide real-time predictions. In this work, we proposed an innovative surrogate model of abdomen mechanics by using machine learning (ML) and finite element (FE) modelling to virtually render internal tissue deformation in real time. We first developed a new high-fidelity FE model of the abdomen mechanics from computerized tomography (CT) images. We performed palpation simulations to produce a large database of stress distribution on the liver edge, an area of interest in most examinations. We then used artificial neural networks (ANNs) to develop the surrogate model and demonstrated its application in an experimental palpation platform. Our FE simulations took 1.5 h to predict stress distribution for each palpation while this only took a fraction of a second for the surrogate model. Our results show that our artificial neural network (ANN) surrogate has an accuracy of 92.6%. We also showed that the surrogate model is able to use the experimental input of palpation location and force to provide real-time projections onto the robotics platform. This enhanced robotics platform has the potential to be used as a training simulator for trainees to hone their palpation skills. Full article
(This article belongs to the Special Issue Machine Learning for Biomedical Applications)
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33 pages, 4118 KiB  
Review
3D-Printing for Critical Sized Bone Defects: Current Concepts and Future Directions
Bioengineering 2022, 9(11), 680; https://doi.org/10.3390/bioengineering9110680 - 11 Nov 2022
Cited by 9 | Viewed by 2853
Abstract
The management and definitive treatment of segmental bone defects in the setting of acute trauma, fracture non-union, revision joint arthroplasty, and tumor surgery are challenging clinical problems with no consistently satisfactory solution. Orthopaedic surgeons are developing novel strategies to treat these problems, including [...] Read more.
The management and definitive treatment of segmental bone defects in the setting of acute trauma, fracture non-union, revision joint arthroplasty, and tumor surgery are challenging clinical problems with no consistently satisfactory solution. Orthopaedic surgeons are developing novel strategies to treat these problems, including three-dimensional (3D) printing combined with growth factors and/or cells. This article reviews the current strategies for management of segmental bone loss in orthopaedic surgery, including graft selection, bone graft substitutes, and operative techniques. Furthermore, we highlight 3D printing as a technology that may serve a major role in the management of segmental defects. The optimization of a 3D-printed scaffold design through printing technique, material selection, and scaffold geometry, as well as biologic additives to enhance bone regeneration and incorporation could change the treatment paradigm for these difficult bone repair problems. Full article
(This article belongs to the Special Issue Multifunctional Scaffolds for Musculoskeletal Regeneration)
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18 pages, 3996 KiB  
Review
Noble Metal Nanoparticles for Point-of-Care Testing: Recent Advancements and Social Impacts
Bioengineering 2022, 9(11), 666; https://doi.org/10.3390/bioengineering9110666 - 08 Nov 2022
Cited by 2 | Viewed by 1545
Abstract
Point-of-care (POC) tests for the diagnosis of diseases are critical to the improvement of the standard of living, especially for resource-limited areas or countries. In recent years, nanobiosensors based on noble metal nanoparticles (NM NPs) have emerged as a class of effective and [...] Read more.
Point-of-care (POC) tests for the diagnosis of diseases are critical to the improvement of the standard of living, especially for resource-limited areas or countries. In recent years, nanobiosensors based on noble metal nanoparticles (NM NPs) have emerged as a class of effective and versatile POC testing technology. The unique features of NM NPs ensure great performance of associated POC nanobiosensors. In particular, NM NPs offer various signal transduction principles, such as plasmonics, catalysis, photothermal effect, and so on. Significantly, the detectable signal from NM NPs can be tuned and optimized by controlling the physicochemical parameters (e.g., size, shape, and elemental composition) of NPs. In this article, we introduce the inherent merits of NM NPs that make them attractive for POC testing, discuss recent advancement of NM NPs-based POC tests, highlight their social impacts, and provide perspectives on challenges and opportunities in the field. We hope the review and insights provided in this article can inspire new fundamental and applied research in this emerging field. Full article
(This article belongs to the Special Issue Feature Papers in Nanotechnology Applications in Bioengineering)
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16 pages, 4456 KiB  
Article
Development of Adenovirus Containing Liposomes Produced by Extrusion vs. Homogenization: A Comparison for Scale-Up Purposes
Bioengineering 2022, 9(11), 620; https://doi.org/10.3390/bioengineering9110620 - 27 Oct 2022
Cited by 2 | Viewed by 2032
Abstract
Adenovirus (Ad) is a widely studied viral vector for cancer therapy as it can be engineered to cause selective lysis of cancer cells. However, Ad delivery is limited in treating cancers that do not have coxsackievirus and adenovirus receptors (CAR). To overcome this [...] Read more.
Adenovirus (Ad) is a widely studied viral vector for cancer therapy as it can be engineered to cause selective lysis of cancer cells. However, Ad delivery is limited in treating cancers that do not have coxsackievirus and adenovirus receptors (CAR). To overcome this challenge, Ad-encapsulated liposomes were developed that enhance the delivery of Ads and increase therapeutic efficacy. Cationic empty liposomes were manufactured first, to which an anionic Ad were added, which resulted in encapsulated Ad liposomes through charge interaction. Optimization of the liposome formula was carried out with series of formulation variables experiments using an extrusion process, which is ideal for laboratory-scale small batches. Later, the optimized formulation was manufactured with a homogenization technique—A high shear rotor-stator blending, that is ideal for large-scale manufacturing and is in compliance with Good Manufacturing Practices (GMP). Comparative in vitro transduction, physicochemical characterization, long-term storage stability at different temperature conditions, and in vivo animal studies were performed. Ad encapsulated liposomes transduced CAR deficient cells 100-fold more efficiently than the unencapsulated Ad (p ≤ 0.0001) in vitro, and 4-fold higher in tumors injected in nude mice in vivo. Both extrusion and homogenization performed similarly–with equivalent in vitro and in vivo transduction efficiencies, physicochemical characterization, and long-term storage stability. Thus, two Ad encapsulated liposomes preparation methods used herein, i.e., extrusion vs. homogenization were equivalent in terms of enhanced Ad performance and long-term storage stability; this will, hopefully, facilitate translation to the clinic. Full article
(This article belongs to the Special Issue Targeted Nanodelivery systems for Oncology Applications)
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