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Bioengineering
Volume 9
Issue 4
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Bioengineering, Volume 9, Issue 4 (April 2022) – 51 articles

Cover Story (view full-size image): Lymphedema results from insufficient interstitial fluid drainage secondary to lymphatic injury. It is characterized by progressive and chronic tissue swelling and inflammation due to and local lymph fluid accumulation. At present, lymphedema is a debilitating condition with limited treatment options. With better understanding of the pathophysiology of lymphedema and lymphangiogenesis and advances in tissue engineering technologies, lymphatic tissue bioengineering has emerged as a potential therapeutic option for postsurgical lymphedema. This review provides an overview of current innovative approaches including stem cells, lymphangiogenic factors, bioengineered matrices, and mechanical stimuli that will allow more precisely controlled regeneration of lymphatic tissue at the site of lymphedema. View this paper.
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29 pages, 5119 KiB  
Communication
PHB Producing Cyanobacteria Found in the Neighborhood—Their Isolation, Purification and Performance Testing
by Katharina Meixner, Christina Daffert, Lisa Bauer, Bernhard Drosg and Ines Fritz
Bioengineering 2022, 9(4), 178; https://doi.org/10.3390/bioengineering9040178 - 18 Apr 2022
Cited by 5 | Viewed by 3204
Abstract
Cyanobacteria are a large group of prokaryotic microalgae that are able to grow photo-autotrophically by utilizing sunlight and by assimilating carbon dioxide to build new biomass. One of the most interesting among many cyanobacteria cell components is the storage biopolymer polyhydroxybutyrate (PHB), a [...] Read more.
Cyanobacteria are a large group of prokaryotic microalgae that are able to grow photo-autotrophically by utilizing sunlight and by assimilating carbon dioxide to build new biomass. One of the most interesting among many cyanobacteria cell components is the storage biopolymer polyhydroxybutyrate (PHB), a member of the group of polyhydroxyalkanoates (PHA). Cyanobacteria occur in almost all habitats, ranging from freshwater to saltwater, freely drifting or adhered to solid surfaces or growing in the porewater of soil, they appear in meltwater of glaciers as well as in hot springs and can handle even high salinities and nutrient imbalances. The broad range of habitat conditions makes them interesting for biotechnological production in facilities located in such climate zones with the expectation of using the best adapted organisms in low-tech bioreactors instead of using “universal” strains, which require high technical effort to adapt the production conditions to the organism‘s need. These were the prerequisites for why and how we searched for locally adapted cyanobacteria in different habitats. Our manuscript provides insight to the sites we sampled, how we isolated and enriched, identified (morphology, 16S rDNA), tested (growth, PHB accumulation) and purified (physical and biochemical purification methods) promising PHB-producing cyanobacteria that can be used as robust production strains. Finally, we provide a guideline about how we managed to find potential production strains and prepared others for basic metabolism studies. Full article
(This article belongs to the Special Issue Advances in Polyhydroxyalkanoate (PHA) Production, Volume 3)
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16 pages, 2559 KiB  
Article
HLA-A2 Promotes the Therapeutic Effect of Umbilical Cord Blood-Derived Mesenchymal Stem Cells in Hyperoxic Lung Injury
by Jihye Kwak, Wankyu Choi, Yunkyung Bae, Miyeon Kim, Soojin Choi, Wonil Oh and Hyejin Jin
Bioengineering 2022, 9(4), 177; https://doi.org/10.3390/bioengineering9040177 - 18 Apr 2022
Viewed by 2314
Abstract
Mesenchymal stem cells (MSCs) are one of the most extensively studied stem cell types owing to their capacity for differentiation into multiple lineages as well as their ability to secrete regenerative factors and modulate immune functions. However, issues remain regarding their further application [...] Read more.
Mesenchymal stem cells (MSCs) are one of the most extensively studied stem cell types owing to their capacity for differentiation into multiple lineages as well as their ability to secrete regenerative factors and modulate immune functions. However, issues remain regarding their further application for cell therapy. Here, to demonstrate the superiority of the improvement of MSCs, we divided umbilical cord blood-derived MSCs (UCB-MSCs) from 15 donors into two groups based on efficacy and revealed donor-dependent variations in the anti-inflammatory effect of MSCs on macrophages as well as their immunoregulatory effect on T cells. Through surface marker analyses (242 antibodies), we found that HLA-A2 was positively related to the anti-inflammatory and immunoregulatory function of MSCs. Additionally, HLA-A2 mRNA silencing in MSCs attenuated their therapeutic effects in vitro; namely, the suppression of LPS-stimulated macrophages and phytohemagglutinin-stimulated T cells. Moreover, HLA-A2 silencing in MSCs significantly decreased their therapeutic effects in a rat model of hyperoxic lung damage. The present study provides novel insights into the quality control of donor-derived MSCs for the treatment of inflammatory conditions and diseases. Full article
(This article belongs to the Special Issue Mesenchymal Stem Cells in Regenerative Medicine)
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18 pages, 724 KiB  
Review
Genome Editing Technology for Genetic Amelioration of Fruits and Vegetables for Alleviating Post-Harvest Loss
by Chanchal Kumari, Megha Sharma, Vinay Kumar, Rajnish Sharma, Vinay Kumar, Parul Sharma, Pankaj Kumar and Mohammad Irfan
Bioengineering 2022, 9(4), 176; https://doi.org/10.3390/bioengineering9040176 - 18 Apr 2022
Cited by 25 | Viewed by 6636
Abstract
Food security and crop production are challenged worldwide due to overpopulation, changing environmental conditions, crop establishment failure, and various kinds of post-harvest losses. The demand for high-quality foods with improved nutritional quality is also growing day by day. Therefore, production of high-quality produce [...] Read more.
Food security and crop production are challenged worldwide due to overpopulation, changing environmental conditions, crop establishment failure, and various kinds of post-harvest losses. The demand for high-quality foods with improved nutritional quality is also growing day by day. Therefore, production of high-quality produce and reducing post-harvest losses of produce, particularly of perishable fruits and vegetables, are vital. For many decades, attempts have been made to improve the post-harvest quality traits of horticultural crops. Recently, modern genetic tools such as genome editing emerged as a new approach to manage and overcome post-harvest effectively and efficiently. The different genome editing tools including ZFNs, TALENs, and CRISPR/Cas9 system effectively introduce mutations (In Dels) in many horticultural crops to address and resolve the issues associated with post-harvest storage quality. Henceforth, we provide a broad review of genome editing applications in horticulture crops to improve post-harvest stability traits such as shelf life, texture, and resistance to pathogens without compromising nutritional value. Moreover, major roadblocks, challenges, and their possible solutions for employing genome editing tools are also discussed. Full article
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10 pages, 829 KiB  
Article
Comparison of Unsupervised Machine Learning Approaches for Cluster Analysis to Define Subgroups of Heart Failure with Preserved Ejection Fraction with Different Outcomes
by Hirmand Nouraei, Hooman Nouraei and Simon W. Rabkin
Bioengineering 2022, 9(4), 175; https://doi.org/10.3390/bioengineering9040175 - 16 Apr 2022
Cited by 15 | Viewed by 2469
Abstract
Heart failure with preserved ejection (HFpEF) is a heterogenous condition affecting nearly half of all patients with heart failure (HF). Artificial intelligence methodologies can be useful to identify patient subclassifications with important clinical implications. We sought a comparison of different machine learning (ML) [...] Read more.
Heart failure with preserved ejection (HFpEF) is a heterogenous condition affecting nearly half of all patients with heart failure (HF). Artificial intelligence methodologies can be useful to identify patient subclassifications with important clinical implications. We sought a comparison of different machine learning (ML) techniques and clustering capabilities in defining meaningful subsets of patients with HFpEF. Three unsupervised clustering strategies, hierarchical clustering, K-prototype, and partitioning around medoids (PAM), were used to identify distinct clusters in patients with HFpEF, based on a wide range of demographic, laboratory, and clinical parameters. The study population had a median age of 77 years, with a female majority, and moderate diastolic dysfunction. Hierarchical clustering produced six groups but two were too small (two and seven cases) to be clinically meaningful. The K-prototype methods produced clusters in which several clinical and biochemical features did not show statistically significant differences and there was significant overlap between the clusters. The PAM methodology provided the best group separations and identified six mutually exclusive groups (HFpEF1-6) with statistically significant differences in patient characteristics and outcomes. Comparison of three different unsupervised ML clustering strategies, hierarchical clustering, K-prototype, and partitioning around medoids (PAM), was performed on a mixed dataset of patients with HFpEF containing clinical and numerical data. The PAM method identified six distinct subsets of patients with HFpEF with different long-term outcomes or mortality. By comparison, the two other clustering algorithms, the hierarchical clustering and K-prototype, were less optimal. Full article
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16 pages, 2983 KiB  
Article
Isolation of NELL 1 Aptamers for Rhabdomyosarcoma Targeting
by Chengchen Duan and Helen Elizabeth Townley
Bioengineering 2022, 9(4), 174; https://doi.org/10.3390/bioengineering9040174 - 15 Apr 2022
Cited by 2 | Viewed by 2179
Abstract
NELL1 (Neural epidermal growth factor-like (EGFL)-like protein) is an important biomarker associated with tissue and bone development and regeneration. NELL1 upregulation has been linked with metastasis and negative prognosis in rhabdomyosarcoma (RMS). Furthermore, multiple recent studies have also shown the importance of NELL1 [...] Read more.
NELL1 (Neural epidermal growth factor-like (EGFL)-like protein) is an important biomarker associated with tissue and bone development and regeneration. NELL1 upregulation has been linked with metastasis and negative prognosis in rhabdomyosarcoma (RMS). Furthermore, multiple recent studies have also shown the importance of NELL1 in inflammatory bowel disease and membranous nephropathy, amongst other diseases. In this study, several anti-NELL1 DNA aptamers were selected from a randomized ssDNA pool using a fluorescence-guided method and evaluated for their binding affinity and selectivity. Several other methods such as a metabolic assay and confocal microscopy were also applied for the evaluation of the selected aptamers. The top three candidates were evaluated further, and AptNCan3 was shown to have a binding affinity up to 959.2 nM. Selectivity was examined in the RH30 RMS cells that overexpressed NELL1. Both AptNCan2 and AptNCan3 could significantly suppress metabolic activity in RMS cells. AptNCan3 was found to locate on the cell membrane and also on intracellular vesicles, which matched the location of NELL1 shown by antibodies in previous research. These results indicate that the selected anti-NELL1 aptamer showed strong and highly specific binding to NELL1 and therefore has potential to be used for in vitro or in vivo studies and treatments. Full article
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16 pages, 3790 KiB  
Article
Improved Titer in Late-Stage Mammalian Cell Culture Manufacturing by Re-Cloning
by Qin He, Matthew S. Rehmann, Jun Tian, Jianlin Xu, Luzmary Sabino, Erik Vandermark, Ziev Basson, Iris Po, Kathleen Bierilo, Gabi Tremml, Giovanni Rizzi, Erik F. Langsdorf, Nan-Xin Qian, Michael C. Borys, Anurag Khetan and Zheng-Jian Li
Bioengineering 2022, 9(4), 173; https://doi.org/10.3390/bioengineering9040173 - 15 Apr 2022
Cited by 3 | Viewed by 3552
Abstract
Improving productivity to reduce the cost of biologics manufacturing and ensure that therapeutics can reach more patients remains a major challenge faced by the biopharmaceutical industry. Chinese hamster ovary (CHO) cell lines are commonly prepared for biomanufacturing by single cell cloning post-transfection and [...] Read more.
Improving productivity to reduce the cost of biologics manufacturing and ensure that therapeutics can reach more patients remains a major challenge faced by the biopharmaceutical industry. Chinese hamster ovary (CHO) cell lines are commonly prepared for biomanufacturing by single cell cloning post-transfection and recovery, followed by lead clone screening, generation of a research cell bank (RCB), cell culture process development, and manufacturing of a master cell bank (MCB) to be used in early phase clinical manufacturing. In this study, it was found that an additional round of cloning and clone selection from an established monoclonal RCB or MCB (i.e., re-cloning) significantly improved titer for multiple late phase monoclonal antibody upstream processes. Quality attributes remained comparable between the processes using the parental clones and the re-clones. For two CHO cells expressing different antibodies, the re-clone performance was successfully scaled up at 500-L or at 2000-L bioreactor scales, demonstrating for the first time that the re-clone is suitable for late phase and commercial manufacturing processes for improvement of titer while maintaining comparable product quality to the early phase process. Full article
(This article belongs to the Topic Bioreactors: Control, Optimization and Applications)
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12 pages, 474 KiB  
Article
Machine Learning and Regression Analysis to Model the Length of Hospital Stay in Patients with Femur Fracture
by Carlo Ricciardi, Alfonso Maria Ponsiglione, Arianna Scala, Anna Borrelli, Mario Misasi, Gaetano Romano, Giuseppe Russo, Maria Triassi and Giovanni Improta
Bioengineering 2022, 9(4), 172; https://doi.org/10.3390/bioengineering9040172 - 14 Apr 2022
Cited by 24 | Viewed by 2926
Abstract
Fractures of the femur are a frequent problem in elderly people, and it has been demonstrated that treating them with a diagnostic–therapeutic–assistance path within 48 h of admission to the hospital reduces complications and shortens the length of the hospital stay (LOS). In [...] Read more.
Fractures of the femur are a frequent problem in elderly people, and it has been demonstrated that treating them with a diagnostic–therapeutic–assistance path within 48 h of admission to the hospital reduces complications and shortens the length of the hospital stay (LOS). In this paper, the preoperative data of 1082 patients were used to further extend the previous research and to generate several models that are capable of predicting the overall LOS: First, the LOS, measured in days, was predicted through a regression analysis; then, it was grouped by weeks and was predicted with a classification analysis. The KNIME analytics platform was applied to divide the dataset for a hold-out cross-validation, perform a multiple linear regression and implement machine learning algorithms. The best coefficient of determination (R2) was achieved by the support vector machine (R2 = 0.617), while the mean absolute error was similar for all the algorithms, ranging between 2.00 and 2.11 days. With regard to the classification analysis, all the algorithms surpassed 80% accuracy, and the most accurate algorithm was the radial basis function network, at 83.5%. The use of these techniques could be a valuable support tool for doctors to better manage orthopaedic departments and all their resources, which would reduce both waste and costs in the context of healthcare. Full article
(This article belongs to the Special Issue Machine Learning for Biomedical Applications)
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16 pages, 1706 KiB  
Review
Novel Techniques and Future Perspective for Investigating Critical-Size Bone Defects
by Elijah Ejun Huang, Ning Zhang, Huaishuang Shen, Xueping Li, Masahiro Maruyama, Takeshi Utsunomiya, Qi Gao, Roberto A. Guzman and Stuart B. Goodman
Bioengineering 2022, 9(4), 171; https://doi.org/10.3390/bioengineering9040171 - 11 Apr 2022
Cited by 12 | Viewed by 3811
Abstract
A critical-size bone defect is a challenging clinical problem in which a gap between bone ends will not heal and will become a nonunion. The current treatment is to harvest and transplant an autologous bone graft to facilitate bone bridging. To develop less [...] Read more.
A critical-size bone defect is a challenging clinical problem in which a gap between bone ends will not heal and will become a nonunion. The current treatment is to harvest and transplant an autologous bone graft to facilitate bone bridging. To develop less invasive but equally effective treatment options, one needs to first have a comprehensive understanding of the bone healing process. Therefore, it is imperative to leverage the most advanced technologies to elucidate the fundamental concepts of the bone healing process and develop innovative therapeutic strategies to bridge the nonunion gap. In this review, we first discuss the current animal models to study critical-size bone defects. Then, we focus on four novel analytic techniques and discuss their strengths and limitations. These four technologies are mass cytometry (CyTOF) for enhanced cellular analysis, imaging mass cytometry (IMC) for enhanced tissue special imaging, single-cell RNA sequencing (scRNA-seq) for detailed transcriptome analysis, and Luminex assays for comprehensive protein secretome analysis. With this new understanding of the healing of critical-size bone defects, novel methods of diagnosis and treatment will emerge. Full article
(This article belongs to the Topic Bioreactors for Advanced Cell Culture, (Nano)toxicity, Regenerative Medicine and Organ Bioengineering)
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11 pages, 4165 KiB  
Article
Rylene Dye-Loaded Polymeric Nanoparticles for Photothermal Eradication of Harmful Dinoflagellates, Akashiwo sanguinea and Alexandrium pacificum
by Naz Fathma Tumpa, Mingyeong Kang, Jiae Yoo, Sunju Kim and Minseok Kwak
Bioengineering 2022, 9(4), 170; https://doi.org/10.3390/bioengineering9040170 - 11 Apr 2022
Viewed by 2556
Abstract
In the era of climate changes, harmful dinoflagellate outbreaks that produce potent algal toxins, odor, and water discoloration in aquatic environments have been increasingly reported. Thus, various treatments have been attempted for the mitigation and management of harmful blooms. Here, we report engineered [...] Read more.
In the era of climate changes, harmful dinoflagellate outbreaks that produce potent algal toxins, odor, and water discoloration in aquatic environments have been increasingly reported. Thus, various treatments have been attempted for the mitigation and management of harmful blooms. Here, we report engineered nanoparticles that consist of two different types of rylene derivatives encapsulated in polymeric micelles. In addition, to avoid dissociation of the aggregate, the core of micelle was stabilized via semi-interpenetrating network (sIPN) formation. On two types of the marine red-tide dinoflagellates, Akashiwo sanguinea and Alexandrium pacificum, the nanoparticle uptake followed by fluorescence labeling and photothermal effect was conducted. Firstly, fluorescence microscopy enabled imaging of the dinoflagellates with the ultraviolet chromophore, Lumogen Violet. Lastly, near-infrared (NIR) laser irradiation was exposed on the Lumogen IR788 nanoparticle-treated Ak. Sanguinea. The irradiation resulted in reduced cell survival due to the photothermal effect in microalgae. The results suggested that the nanoparticle, IR788-sIPN, can be applied for potential red-tide algal elimination. Full article
(This article belongs to the Section Nanotechnology Applications in Bioengineering)
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16 pages, 5812 KiB  
Article
Quantitative Analysis of Core Lipid Production in Methanothermobacter marburgensis at Different Scales
by Lydia M. F. Baumann, Ruth-Sophie Taubner, Kinga Oláh, Ann-Cathrin Rohrweber, Bernhard Schuster, Daniel Birgel and Simon K.-M. R. Rittmann
Bioengineering 2022, 9(4), 169; https://doi.org/10.3390/bioengineering9040169 - 10 Apr 2022
Cited by 3 | Viewed by 2027
Abstract
Archaeal lipids have a high biotechnological potential, caused by their high resistance to oxidative stress, extreme pH values and temperatures, as well as their ability to withstand phospholipases. Further, methanogens, a specific group of archaea, are already well-established in the field of biotechnology [...] Read more.
Archaeal lipids have a high biotechnological potential, caused by their high resistance to oxidative stress, extreme pH values and temperatures, as well as their ability to withstand phospholipases. Further, methanogens, a specific group of archaea, are already well-established in the field of biotechnology because of their ability to use carbon dioxide and molecular hydrogen or organic substrates. In this study, we show the potential of the model organism Methanothermobacter marburgensis to act both as a carbon dioxide based biological methane producer and as a potential supplier of archaeal lipids. Different cultivation settings were tested to gain an insight into the optimal conditions to produce specific core lipids. The study shows that up-scaling at a constant particle number (n/n = const.) seems to be a promising approach. Further optimizations regarding the length and number of the incubation periods and the ratio of the interaction area to the total liquid volume are necessary for scaling these settings for industrial purposes. Full article
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16 pages, 1206 KiB  
Review
Bioengineering Strategies to Create 3D Cardiac Constructs from Human Induced Pluripotent Stem Cells
by Fahimeh Varzideh, Pasquale Mone and Gaetano Santulli
Bioengineering 2022, 9(4), 168; https://doi.org/10.3390/bioengineering9040168 - 10 Apr 2022
Cited by 11 | Viewed by 3905
Abstract
Human induced pluripotent stem cells (hiPSCs) can be used to generate various cell types in the human body. Hence, hiPSC-derived cardiomyocytes (hiPSC-CMs) represent a significant cell source for disease modeling, drug testing, and regenerative medicine. The immaturity of hiPSC-CMs in two-dimensional (2D) culture [...] Read more.
Human induced pluripotent stem cells (hiPSCs) can be used to generate various cell types in the human body. Hence, hiPSC-derived cardiomyocytes (hiPSC-CMs) represent a significant cell source for disease modeling, drug testing, and regenerative medicine. The immaturity of hiPSC-CMs in two-dimensional (2D) culture limit their applications. Cardiac tissue engineering provides a new promise for both basic and clinical research. Advanced bioengineered cardiac in vitro models can create contractile structures that serve as exquisite in vitro heart microtissues for drug testing and disease modeling, thereby promoting the identification of better treatments for cardiovascular disorders. In this review, we will introduce recent advances of bioengineering technologies to produce in vitro cardiac tissues derived from hiPSCs. Full article
(This article belongs to the Special Issue Advances in Cardiac Tissue Engineering)
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12 pages, 2240 KiB  
Article
A Comparison of Heart Pulsations Provided by Forcecardiography and Double Integration of Seismocardiogram
by Emilio Andreozzi, Jessica Centracchio, Daniele Esposito and Paolo Bifulco
Bioengineering 2022, 9(4), 167; https://doi.org/10.3390/bioengineering9040167 - 09 Apr 2022
Cited by 14 | Viewed by 2332
Abstract
Seismocardiography (SCG) is largely regarded as the state-of-the-art technique for continuous, long-term monitoring of cardiac mechanical activity in wearable applications. SCG signals are acquired via small, lightweight accelerometers fixed on the chest. They provide timings of important cardiac events, such as heart valves [...] Read more.
Seismocardiography (SCG) is largely regarded as the state-of-the-art technique for continuous, long-term monitoring of cardiac mechanical activity in wearable applications. SCG signals are acquired via small, lightweight accelerometers fixed on the chest. They provide timings of important cardiac events, such as heart valves openings and closures, thus allowing the estimation of cardiac time intervals of clinical relevance. Forcecardiography (FCG) is a novel technique that records the cardiac-induced vibrations of the chest wall by means of specific force sensors, which proved capable of monitoring respiration, heart sounds and infrasonic cardiac vibrations, simultaneously from a single contact point on the chest. A specific infrasonic component captures the heart walls displacements and looks very similar to the Apexcardiogram. This low-frequency component is not visible in SCG recordings, nor it can be extracted by simple filtering. In this study, a feasible way to extract this information from SCG signals is presented. The proposed approach is based on double integration of SCG. Numerical double integration is usually very prone to large errors, therefore a specific numerical procedure was devised. This procedure yields a new displacement signal (DSCG) that features a low-frequency component (LF-DSCG) very similar to that of the FCG (LF-FCG). Experimental tests were carried out using an FCG sensor and an off-the-shelf accelerometer firmly attached to each other and placed onto the precordial region. Simultaneous recordings were acquired from both sensors, together with an electrocardiogram lead (used as a reference). Quantitative morphological comparison confirmed the high similarity between LF-FCG and LF-DSCG (normalized cross-correlation index >0.9). Statistical analyses suggested that LF-DSCG, although achieving a fair sensitivity in heartbeat detection (about 90%), has not a very high consistency within the cardiac cycle, leading to inaccuracies in inter-beat intervals estimation. Future experiments with high-performance accelerometers and improved processing methods are envisioned to investigate the potential enhancement of the accuracy and reliability of the proposed method. Full article
(This article belongs to the Special Issue The Power of Biosignal and Bioimage Processing in Human Healthcare: Advances in the Analysis and Control of Physiological Systems)
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15 pages, 1299 KiB  
Review
In Vitro Cancer Models: A Closer Look at Limitations on Translation
by Nina Antunes, Banani Kundu, Subhas C. Kundu, Rui L. Reis and Vítor Correlo
Bioengineering 2022, 9(4), 166; https://doi.org/10.3390/bioengineering9040166 - 07 Apr 2022
Cited by 11 | Viewed by 3883
Abstract
In vitro cancer models are envisioned as high-throughput screening platforms for potential new therapeutic discovery and/or validation. They also serve as tools to achieve personalized treatment strategies or real-time monitoring of disease propagation, providing effective treatments to patients. To battle the fatality of [...] Read more.
In vitro cancer models are envisioned as high-throughput screening platforms for potential new therapeutic discovery and/or validation. They also serve as tools to achieve personalized treatment strategies or real-time monitoring of disease propagation, providing effective treatments to patients. To battle the fatality of metastatic cancers, the development and commercialization of predictive and robust preclinical in vitro cancer models are of urgent need. In the past decades, the translation of cancer research from 2D to 3D platforms and the development of diverse in vitro cancer models have been well elaborated in an enormous number of reviews. However, the meagre clinical success rate of cancer therapeutics urges the critical introspection of currently available preclinical platforms, including patents, to hasten the development of precision medicine and commercialization of in vitro cancer models. Hence, the present article critically reflects the difficulty of translating cancer therapeutics from discovery to adoption and commercialization in the light of in vitro cancer models as predictive tools. The state of the art of in vitro cancer models is discussed first, followed by identifying the limitations of bench-to-bedside transition. This review tries to establish compatibility between the current findings and obstacles and indicates future directions to accelerate the market penetration, considering the niche market. Full article
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21 pages, 3695 KiB  
Article
Heart Rate Variability Analysis for Seizure Detection in Neonatal Intensive Care Units
by Benedetta Olmi, Claudia Manfredi, Lorenzo Frassineti, Carlo Dani, Silvia Lori, Giovanna Bertini, Cesarina Cossu, Maria Bastianelli, Simonetta Gabbanini and Antonio Lanatà
Bioengineering 2022, 9(4), 165; https://doi.org/10.3390/bioengineering9040165 - 07 Apr 2022
Cited by 3 | Viewed by 2279
Abstract
In Neonatal Intensive Care Units (NICUs), the early detection of neonatal seizures is of utmost importance for a timely clinical intervention. Over the years, several neonatal seizure detection systems were proposed to detect neonatal seizures automatically and speed up seizure diagnosis, most based [...] Read more.
In Neonatal Intensive Care Units (NICUs), the early detection of neonatal seizures is of utmost importance for a timely clinical intervention. Over the years, several neonatal seizure detection systems were proposed to detect neonatal seizures automatically and speed up seizure diagnosis, most based on the EEG signal analysis. Recently, research has focused on other possible seizure markers, such as electrocardiography (ECG). This work proposes an ECG-based NSD system to investigate the usefulness of heart rate variability (HRV) analysis to detect neonatal seizures in the NICUs. HRV analysis is performed considering time-domain, frequency-domain, entropy and multiscale entropy features. The performance is evaluated on a dataset of ECG signals from 51 full-term babies, 29 seizure-free. The proposed system gives results comparable to those reported in the literature: Area Under the Receiver Operating Characteristic Curve = 62%, Sensitivity = 47%, Specificity = 67%. Moreover, the system’s performance is evaluated in a real clinical environment, inevitably affected by several artefacts. To the best of our knowledge, our study proposes for the first time a multi-feature ECG-based NSD system that also offers a comparative analysis between babies suffering from seizures and seizure-free ones. Full article
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21 pages, 4522 KiB  
Review
Lactide: Production Routes, Properties, and Applications
by Bruna L. C. Cunha, Juliana O. Bahú, Letícia F. Xavier, Sara Crivellin, Samuel D. A. de Souza, Leandro Lodi, André L. Jardini, Rubens Maciel Filho, Maria I. R. B. Schiavon, Viktor O. Cárdenas Concha, Patricia Severino and Eliana B. Souto
Bioengineering 2022, 9(4), 164; https://doi.org/10.3390/bioengineering9040164 - 07 Apr 2022
Cited by 28 | Viewed by 5739
Abstract
Lactide dimer is an important monomer produced from lactic acid dehydration, followed by the prepolymer depolymerization process, and subsequent purification. As lactic acid is a chiral molecule, lactide can exist in three isomeric forms: L-, D-, and meso-lactide. Due to its time-consuming [...] Read more.
Lactide dimer is an important monomer produced from lactic acid dehydration, followed by the prepolymer depolymerization process, and subsequent purification. As lactic acid is a chiral molecule, lactide can exist in three isomeric forms: L-, D-, and meso-lactide. Due to its time-consuming synthesis and the need for strict temperature and pressure control, catalyst use, low selectivity, high energy cost, and racemization, the value of a high purity lactide has a high cost in the market; moreover, little is found in scientific articles about the monomer synthesis. Lactide use is mainly for the synthesis of high molar mass poly(lactic acid) (PLA), applied as bio-based material for medical applications (e.g., prostheses and membranes), drug delivery, and hydrogels, or combined with other polymers for applications in packaging. This review elucidates the configurations and conditions of syntheses mapped for lactide production, the main properties of each of the isomeric forms, its industrial production, as well as the main applications in the market. Full article
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16 pages, 2227 KiB  
Article
Demonstrating the Potential of Using Bio-Based Sustainable Polyester Blends for Bone Tissue Engineering Applications
by David H. Ramos-Rodriguez, Samand Pashneh-Tala, Amanpreet Kaur Bains, Robert D. Moorehead, Nikolaos Kassos, Adrian L. Kelly, Thomas E. Paterson, C. Amnael Orozco-Diaz, Andrew A. Gill and Ilida Ortega Asencio
Bioengineering 2022, 9(4), 163; https://doi.org/10.3390/bioengineering9040163 - 06 Apr 2022
Cited by 5 | Viewed by 3396
Abstract
Healthcare applications are known to have a considerable environmental impact and the use of bio-based polymers has emerged as a powerful approach to reduce the carbon footprint in the sector. This research aims to explore the suitability of using a new sustainable polyester [...] Read more.
Healthcare applications are known to have a considerable environmental impact and the use of bio-based polymers has emerged as a powerful approach to reduce the carbon footprint in the sector. This research aims to explore the suitability of using a new sustainable polyester blend (Floreon™) as a scaffold directed to aid in musculoskeletal applications. Musculoskeletal problems arise from a wide range of diseases and injuries related to bones and joints. Specifically, bone injuries may result from trauma, cancer, or long-term infections and they are currently considered a major global problem in both developed and developing countries. In this work we have manufactured a series of 3D-printed constructs from a novel biopolymer blend using fused deposition modelling (FDM), and we have modified these materials using a bioceramic (wollastonite, 15% w/w). We have evaluated their performance in vitro using human dermal fibroblasts and rat mesenchymal stromal cells. The new sustainable blend is biocompatible, showing no differences in cell metabolic activity when compared to PLA controls for periods 1–18 days. FloreonTM blend has proven to be a promising material to be used in bone tissue regeneration as it shows an impact strength in the same range of that shown by native bone (just under 10 kJ/m2) and supports an improvement in osteogenic activity when modified with wollastonite. Full article
(This article belongs to the Special Issue Current Developments and Applications in Bone Tissue Engineering)
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24 pages, 1103 KiB  
Review
Lymphatic Tissue Bioengineering for the Treatment of Postsurgical Lymphedema
by Cynthia J. Sung, Kshitij Gupta, Jin Wang and Alex K. Wong
Bioengineering 2022, 9(4), 162; https://doi.org/10.3390/bioengineering9040162 - 06 Apr 2022
Cited by 6 | Viewed by 4133
Abstract
Lymphedema is characterized by progressive and chronic tissue swelling and inflammation from local accumulation of interstitial fluid due to lymphatic injury or dysfunction. It is a debilitating condition that significantly impacts a patient’s quality of life, and has limited treatment options. With better [...] Read more.
Lymphedema is characterized by progressive and chronic tissue swelling and inflammation from local accumulation of interstitial fluid due to lymphatic injury or dysfunction. It is a debilitating condition that significantly impacts a patient’s quality of life, and has limited treatment options. With better understanding of the molecular mechanisms and pathophysiology of lymphedema and advances in tissue engineering technologies, lymphatic tissue bioengineering and regeneration have emerged as a potential therapeutic option for postsurgical lymphedema. Various strategies involving stem cells, lymphangiogenic factors, bioengineered matrices and mechanical stimuli allow more precisely controlled regeneration of lymphatic tissue at the site of lymphedema without subjecting patients to complications or iatrogenic injuries associated with surgeries. This review provides an overview of current innovative approaches of lymphatic tissue bioengineering that represent a promising treatment option for postsurgical lymphedema. Full article
(This article belongs to the Special Issue Bioengineered Strategies for Surgical Innovation)
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20 pages, 2210 KiB  
Article
Performance Evaluation of Deep Learning Models on Mammogram Classification Using Small Dataset
by Adeyinka P. Adedigba, Steve A. Adeshina and Abiodun M. Aibinu
Bioengineering 2022, 9(4), 161; https://doi.org/10.3390/bioengineering9040161 - 06 Apr 2022
Cited by 17 | Viewed by 2911
Abstract
Cancer is the second leading cause of death globally, and breast cancer (BC) is the second most reported cancer. Although the incidence rate is reducing in developed countries, the reverse is the case in low- and middle-income countries. Early detection has been found [...] Read more.
Cancer is the second leading cause of death globally, and breast cancer (BC) is the second most reported cancer. Although the incidence rate is reducing in developed countries, the reverse is the case in low- and middle-income countries. Early detection has been found to contain cancer growth, prevent metastasis, ease treatment, and reduce mortality by 25%. The digital mammogram is one of the most common, cheapest, and most effective BC screening techniques capable of early detection of up to 90% BC incidence. However, the mammogram is one of the most difficult medical images to analyze. In this paper, we present a method of training a deep learning model for BC diagnosis. We developed a discriminative fine-tuning method which dynamically assigns different learning rates to each layer of the deep CNN. In addition, the model was trained using mixed-precision training to ease the computational demand of training deep learning models. Lastly, we present data augmentation methods for mammograms. The discriminative fine-tuning algorithm enables rapid convergence of the model loss; hence, the models were trained to attain their best performance within 50 epochs. Comparing the results, DenseNet achieved the highest accuracy of 0.998, while AlexNet obtained 0.988. Full article
(This article belongs to the Special Issue Artificial Intelligence Based Computer-Aided Diagnosis)
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14 pages, 699 KiB  
Article
Nanopower Integrated Gaussian Mixture Model Classifier for Epileptic Seizure Prediction
by Vassilis Alimisis, Georgios Gennis, Konstantinos Touloupas, Christos Dimas, Nikolaos Uzunoglu and Paul P. Sotiriadis
Bioengineering 2022, 9(4), 160; https://doi.org/10.3390/bioengineering9040160 - 05 Apr 2022
Cited by 4 | Viewed by 2322
Abstract
This paper presents a new analog front-end classification system that serves as a wake-up engine for digital back-ends, targeting embedded devices for epileptic seizure prediction. Predicting epileptic seizures is of major importance for the patient’s quality of life as they can lead to [...] Read more.
This paper presents a new analog front-end classification system that serves as a wake-up engine for digital back-ends, targeting embedded devices for epileptic seizure prediction. Predicting epileptic seizures is of major importance for the patient’s quality of life as they can lead to paralyzation or even prove fatal. Existing solutions rely on power hungry embedded digital inference engines that typically consume several µW or even mW. To increase the embedded device’s autonomy, a new approach is presented combining an analog feature extractor with an analog Gaussian mixture model-based binary classifier. The proposed classification system provides an initial, power-efficient prediction with high sensitivity to switch on the digital engine for the accurate evaluation. The classifier’s circuit is chip-area efficient, operating with minimal power consumption (180 nW) at low supply voltage (0.6 V), allowing long-term continuous operation. Based on a real-world dataset, the proposed system achieves 100% sensitivity to guarantee that all seizures are predicted and good specificity (69%), resulting in significant power reduction of the digital engine and therefore the total system. The proposed classifier was designed and simulated in a TSMC 90 nm CMOS process, using the Cadence IC suite. Full article
(This article belongs to the Section Biosignal Processing)
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12 pages, 1525 KiB  
Review
Densification: Hyaluronan Aggregation in Different Human Organs
by Antonio Stecco, Mary Cowman, Nina Pirri, Preeti Raghavan and Carmelo Pirri
Bioengineering 2022, 9(4), 159; https://doi.org/10.3390/bioengineering9040159 - 05 Apr 2022
Cited by 11 | Viewed by 3731
Abstract
Hyaluronan (HA) has complex biological roles that have catalyzed clinical interest in several fields of medicine. In this narrative review, we provide an overview of HA aggregation, also called densification, in human organs. The literature suggests that HA aggregation can occur in the [...] Read more.
Hyaluronan (HA) has complex biological roles that have catalyzed clinical interest in several fields of medicine. In this narrative review, we provide an overview of HA aggregation, also called densification, in human organs. The literature suggests that HA aggregation can occur in the liver, eye, lung, kidney, blood vessel, muscle, fascia, skin, pancreatic cancer and malignant melanoma. In all these organs, aggregation of HA leads to an increase in extracellular matrix viscosity, causing stiffness and organ dysfunction. Fibrosis, in some of these organs, may also occur as a direct consequence of densification in the long term. Specific imaging evaluation, such dynamic ultrasonography, elasto-sonography, elasto-MRI and T1ρ MRI can permit early diagnosis to enable the clinician to organize the treatment plan and avoid further progression of the pathology and dysfunction. Full article
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22 pages, 1929 KiB  
Review
Microemulsions and Nanoemulsions in Skin Drug Delivery
by Eliana B. Souto, Amanda Cano, Carlos Martins-Gomes, Tiago E. Coutinho, Aleksandra Zielińska and Amélia M. Silva
Bioengineering 2022, 9(4), 158; https://doi.org/10.3390/bioengineering9040158 - 05 Apr 2022
Cited by 76 | Viewed by 8823
Abstract
Microemulsions and nanoemulsions are lipid-based pharmaceutical systems with a high potential to increase the permeation of drugs through the skin. Although being isotropic dispersions of two nonmiscible liquids (oil and water), significant differences are encountered between microemulsions and nanoemulsions. Microemulsions are thermodynamically stable [...] Read more.
Microemulsions and nanoemulsions are lipid-based pharmaceutical systems with a high potential to increase the permeation of drugs through the skin. Although being isotropic dispersions of two nonmiscible liquids (oil and water), significant differences are encountered between microemulsions and nanoemulsions. Microemulsions are thermodynamically stable o/w emulsions of mean droplet size approximately 100–400 nm, whereas nanoemulsions are thermodynamically unstable o/w emulsions of mean droplet size approximately 1 to 100 nm. Their inner oil phase allows the solubilization of lipophilic drugs, achieving high encapsulation rates, which are instrumental for drug delivery. In this review, the importance of these systems, the key differences regarding their composition and production processes are discussed. While most of the micro/nanoemulsions on the market are held by the cosmetic industry to enhance the activity of drugs used in skincare products, the development of novel pharmaceutical formulations designed for the topical, dermal and transdermal administration of therapeutic drugs is being considered. The delivery of poorly water-soluble molecules through the skin has shown some advantages over the oral route, since drugs escape from first-pass metabolism; particularly for the treatment of cutaneous diseases, topical delivery should be the preferential route in order to reduce the number of drugs used and potential side-effects, while directing the drugs to the site of action. Thus, nanoemulsions and microemulsions represent versatile options for the delivery of drugs through lipophilic barriers, and many synthetic and natural compounds have been formulated using these delivery systems, aiming to improve stability, delivery and bioactivity. Detailed information is provided concerning the most relevant recent scientific publications reporting the potential of these delivery systems to increase the skin permeability of drugs with anti-inflammatory, sun-protection, anticarcinogenic and/or wound-healing activities. The main marketed skincare products using emulsion-based systems are also presented and discussed. Full article
(This article belongs to the Special Issue Drug Delivery Systems, What's New?)
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10 pages, 881 KiB  
Article
Physiological Effect of Deep Pressure in Reducing Anxiety of Children with ASD during Traveling: A Public Transportation Setting
by Ilham Yustar Afif, Aloysius Raynaldo Manik, Kristian Munthe, Mohamad Izzur Maula, Muhammad Imam Ammarullah, Jamari Jamari and Tri Indah Winarni
Bioengineering 2022, 9(4), 157; https://doi.org/10.3390/bioengineering9040157 - 05 Apr 2022
Cited by 29 | Viewed by 4298
Abstract
Traveling with children with autism can be very challenging for parents due to their reactions to sensory stimuli resulting in behavioral problems, which lead to self-injury and danger for themselves and others. Deep pressure was reported to have a calming effect on people [...] Read more.
Traveling with children with autism can be very challenging for parents due to their reactions to sensory stimuli resulting in behavioral problems, which lead to self-injury and danger for themselves and others. Deep pressure was reported to have a calming effect on people with autism. This study was designed to investigate the physiological effect of deep pressure, which is an autism hug machine portable seat (AHMPS) in children with autism spectrum disorders (ASD) in public transportation settings. The study was conducted with 20 children with ASD (16 boys and 4 girls) at the Semarang Public Special School with an age ranging from 4 to 13 years (mean 10.9 ± 2.26 years), who were randomly assigned into two groups. The experiment consisted of group I who used the AHMPS inflatable wraps model and group II who used the AHMPS manual pull model. Heart rate (HR) and skin conductance (SC) were analyzed to measure the physiological calming effect using pulse oximeter oximetry and a galvanic skin response (GSR) sensor. Heart rate was significantly decreased during the treatment compared to the baseline (pre-test) session in group I (inflating wrap model) with p = 0.019, while no change of heart rate variability (HRV) was found in group II (manual pull model) with p = 0.111. There was no remaining effect of deep pressure using the HRV indicator after the treatment in both groups (group I with p = 0.159 and group II with p = 0.566). GSR captured the significant decrease in skin conductance during the treatment with p < 0.0001 in group I, but no significant decrease was recorded in group II with p = 0.062. A skin conductance indicator captured the remaining effect of deep pressure (after the treatment); it was better in group I (p = 0.003) than in group II (p = 0.773). In conclusion, the deep pressure of the AHMPS inflating wrap decreases physiological arousal in children with ASD during traveling. Full article
(This article belongs to the Special Issue Biosensors in Biomedical Applications)
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12 pages, 3608 KiB  
Article
Spectral Methods for Response Enhancement of Microwave Resonant Sensors in Continuous Non-Invasive Blood Glucose Monitoring
by Giovanni Buonanno, Adriana Brancaccio, Sandra Costanzo and Raffaele Solimene
Bioengineering 2022, 9(4), 156; https://doi.org/10.3390/bioengineering9040156 - 04 Apr 2022
Cited by 9 | Viewed by 2207
Abstract
In this paper, the performance of three recent algorithms for the frequency-response enhancement of microwave resonant sensors are compared. The first one, a single-step algorithm, is based on a couple of direct-inverse Fourier transforms, giving a densely sampled response as a result. The [...] Read more.
In this paper, the performance of three recent algorithms for the frequency-response enhancement of microwave resonant sensors are compared. The first one, a single-step algorithm, is based on a couple of direct-inverse Fourier transforms, giving a densely sampled response as a result. The second algorithm exploits an iterative procedure to progressively restricts the frequency response. The final one is based on the super-resolution MUSIC algorithm. The comparison is carried out through a Monte Carlo analysis. In particular, synthetic signals are firstly exploited to mimic the frequency response of a resonant microwave sensor. Then, experimental data collected from water-glucose solutions are adopted as validation test for potential applications in noninvasive blood-glucose monitoring. Full article
(This article belongs to the Special Issue Women's Special Issue Series: Biosensors)
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16 pages, 660 KiB  
Review
Process- and Product-Related Foulants in Virus Filtration
by Solomon Isu, Xianghong Qian, Andrew L. Zydney and S. Ranil Wickramasinghe
Bioengineering 2022, 9(4), 155; https://doi.org/10.3390/bioengineering9040155 - 04 Apr 2022
Cited by 6 | Viewed by 5023
Abstract
Regulatory authorities place stringent guidelines on the removal of contaminants during the manufacture of biopharmaceutical products. Monoclonal antibodies, Fc-fusion proteins, and other mammalian cell-derived biotherapeutics are heterogeneous molecules that are validated based on the production process and not on molecular homogeneity. Validation of [...] Read more.
Regulatory authorities place stringent guidelines on the removal of contaminants during the manufacture of biopharmaceutical products. Monoclonal antibodies, Fc-fusion proteins, and other mammalian cell-derived biotherapeutics are heterogeneous molecules that are validated based on the production process and not on molecular homogeneity. Validation of clearance of potential contamination by viruses is a major challenge during the downstream purification of these therapeutics. Virus filtration is a single-use, size-based separation process in which the contaminating virus particles are retained while the therapeutic molecules pass through the membrane pores. Virus filtration is routinely used as part of the overall virus clearance strategy. Compromised performance of virus filters due to membrane fouling, low throughput and reduced viral clearance, is of considerable industrial significance and is frequently a major challenge. This review shows how components generated during cell culture, contaminants, and product variants can affect virus filtration of mammalian cell-derived biologics. Cell culture-derived foulants include host cell proteins, proteases, and endotoxins. We also provide mitigation measures for each potential foulant. Full article
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20 pages, 1260 KiB  
Article
Sugar Beet Molasses as a Potential C-Substrate for PHA Production by Cupriavidus necator
by Evgeniy G. Kiselev, Aleksey V. Demidenko, Natalia O. Zhila, Ekaterina I. Shishatskaya and Tatiana G. Volova
Bioengineering 2022, 9(4), 154; https://doi.org/10.3390/bioengineering9040154 - 04 Apr 2022
Cited by 16 | Viewed by 4795
Abstract
To increase the availability and expand the raw material base, the production of polyhydroxyalkanoates (PHA) by the wild strain Cupriavidus necator B-10646 on hydrolysates of sugar beet molasses was studied. The hydrolysis of molasses was carried out using β-fructofuranosidase, which provides a [...] Read more.
To increase the availability and expand the raw material base, the production of polyhydroxyalkanoates (PHA) by the wild strain Cupriavidus necator B-10646 on hydrolysates of sugar beet molasses was studied. The hydrolysis of molasses was carried out using β-fructofuranosidase, which provides a high conversion of sucrose (88.9%) to hexoses. We showed the necessity to adjust the chemical composition of molasses hydrolysate to balance with the physiological needs of C. necator B-10646 and reduce excess sugars and nitrogen and eliminate phosphorus deficiency. The modes of cultivation of bacteria on diluted hydrolyzed molasses with the controlled feeding of phosphorus and glucose were implemented. Depending on the ratio of sugars introduced into the bacterial culture due to the molasses hydrolysate and glucose additions, the bacterial biomass concentration was obtained from 20–25 to 80–85 g/L with a polymer content up to 80%. The hydrolysates of molasses containing trace amounts of propionate and valerate were used to synthesize a P(3HB-co-3HV) copolymer with minor inclusions of 3-hydroxyvlaerate monomers. The introduction of precursors into the medium ensured the synthesis of copolymers with reduced values of the degree of crystallinity, containing, in addition to 3HB, monomers 3HB, 4HB, or 3HHx in an amount of 12–16 mol.%. Full article
(This article belongs to the Special Issue Advances in Polyhydroxyalkanoate (PHA) Production, Volume 3)
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18 pages, 919 KiB  
Review
COVID-19 Diagnosis: A Review of Rapid Antigen, RT-PCR and Artificial Intelligence Methods
by Raphael Taiwo Aruleba, Tayo Alex Adekiya, Nimibofa Ayawei, George Obaido, Kehinde Aruleba, Ibomoiye Domor Mienye, Idowu Aruleba and Blessing Ogbuokiri
Bioengineering 2022, 9(4), 153; https://doi.org/10.3390/bioengineering9040153 - 03 Apr 2022
Cited by 22 | Viewed by 4129
Abstract
As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused 5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to artificial intelligence, have been used for its detection, diagnosis, and surveillance. Meanwhile, fast and efficient point-of-care [...] Read more.
As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused 5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to artificial intelligence, have been used for its detection, diagnosis, and surveillance. Meanwhile, fast and efficient point-of-care (POC) testing and self-testing kits have become necessary in the fight against COVID-19 and to assist healthcare personnel and governments curb the spread of the virus. This paper presents a review of the various types of COVID-19 detection methods, diagnostic technologies, and surveillance approaches that have been used or proposed. The review provided in this article should be beneficial to researchers in this field and health policymakers at large. Full article
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26 pages, 2430 KiB  
Article
A Hybrid Deep Learning Approach for ECG-Based Arrhythmia Classification
by Parul Madan, Vijay Singh, Devesh Pratap Singh, Manoj Diwakar, Bhaskar Pant and Avadh Kishor
Bioengineering 2022, 9(4), 152; https://doi.org/10.3390/bioengineering9040152 - 02 Apr 2022
Cited by 48 | Viewed by 5540
Abstract
Arrhythmias are defined as irregularities in the heartbeat rhythm, which may infrequently occur in a human’s life. These arrhythmias may cause potentially fatal complications, which may lead to an immediate risk of life. Thus, the detection and classification of arrhythmias is a pertinent [...] Read more.
Arrhythmias are defined as irregularities in the heartbeat rhythm, which may infrequently occur in a human’s life. These arrhythmias may cause potentially fatal complications, which may lead to an immediate risk of life. Thus, the detection and classification of arrhythmias is a pertinent issue for cardiac diagnosis. (1) Background: To capture these sporadic events, an electrocardiogram (ECG), a register containing the heart’s electrical function, is considered the gold standard. However, since ECG carries a vast amount of information, it becomes very complex and challenging to extract the relevant information from visual analysis. As a result, designing an efficient (automated) system to analyse the enormous quantity of data possessed by ECG is critical. (2) Method: This paper proposes a hybrid deep learning-based approach to automate the detection and classification process. This paper makes two-fold contributions. First, 1D ECG signals are translated into 2D Scalogram images to automate the noise filtering and feature extraction. Then, based on experimental evidence, by combining two learning models, namely 2D convolutional neural network (CNN) and the Long Short-Term Memory (LSTM) network, a hybrid model called 2D-CNN-LSTM is proposed. (3) Result: To evaluate the efficacy of the proposed 2D-CNN-LSTM approach, we conducted a rigorous experimental study using the widely adopted MIT–BIH arrhythmia database. The obtained results show that the proposed approach provides ≈98.7%, 99%, and 99% accuracy for Cardiac Arrhythmias (ARR), Congestive Heart Failure (CHF), and Normal Sinus Rhythm (NSR), respectively. Moreover, it provides an average sensitivity of the proposed model of 98.33% and a specificity value of 98.35%, for all three arrhythmias. (4) Conclusions: For the classification of arrhythmias, a robust approach has been introduced where 2D scalogram images of ECG signals are trained over the CNN-LSTM model. The results obtained are better as compared to the other existing techniques and will greatly reduce the amount of intervention required by doctors. For future work, the proposed method can be applied over some live ECG signals and Bi-LSTM can be applied instead of LSTM. Full article
(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)
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18 pages, 2902 KiB  
Article
Performance Characteristics of a Novel 3D-Printed Bubble Intermittent Mandatory Ventilator (B-IMV) for Adult Pulmonary Support
by Jonathan A. Poli, Christopher Howard, Alfredo J. Garcia III, Don Remboski, Peter B. Littlewood, John P. Kress, Narayanan Kasthuri, Alia Comai, Kiran Soni, Philip Kennedy, John Ogger and Robert M. DiBlasi
Bioengineering 2022, 9(4), 151; https://doi.org/10.3390/bioengineering9040151 - 02 Apr 2022
Cited by 3 | Viewed by 2985
Abstract
The COVID-19 pandemic has brought attention to the need for developing effective respiratory support that can be rapidly implemented during critical surge capacity scenarios in healthcare settings. Lung support with bubble continuous positive airway pressure (B-CPAP) is a well-established therapeutic approach for supporting [...] Read more.
The COVID-19 pandemic has brought attention to the need for developing effective respiratory support that can be rapidly implemented during critical surge capacity scenarios in healthcare settings. Lung support with bubble continuous positive airway pressure (B-CPAP) is a well-established therapeutic approach for supporting neonatal patients. However, the effectiveness of B-CPAP in larger pediatric and adult patients has not been addressed. Using similar principles of B-CPAP pressure generation, application of intermittent positive pressure inflations above CPAP could support gas exchange and high work of breathing levels in larger patients experiencing more severe forms of respiratory failure. This report describes the design and performance characteristics of the BubbleVent, a novel 3D-printed valve system that combined with commonly found tubes, hoses, and connectors can provide intermittent mandatory ventilation (IMV) suitable for adult mechanical ventilation without direct electrification. Testing of the BubbleVent was performed on a passive adult test lung model and compared with a critical care ventilator commonly used in tertiary care centers. The BubbleVent was shown to deliver stable PIP and PEEP levels, as well as timing control of breath delivery that was comparable with a critical care ventilator. Full article
(This article belongs to the Topic Applied System on Biomedical Engineering, Healthcare and Sustainability)
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21 pages, 1316 KiB  
Review
Application of Micro-Engineered Kidney, Liver, and Respiratory System Models to Accelerate Preclinical Drug Testing and Development
by Hanieh Gholizadeh, Shaokoon Cheng, Agisilaos Kourmatzis, Hanwen Xing, Daniela Traini, Paul M. Young and Hui Xin Ong
Bioengineering 2022, 9(4), 150; https://doi.org/10.3390/bioengineering9040150 - 02 Apr 2022
Cited by 2 | Viewed by 3442
Abstract
Developing novel drug formulations and progressing them to the clinical environment relies on preclinical in vitro studies and animal tests to evaluate efficacy and toxicity. However, these current techniques have failed to accurately predict the clinical success of new therapies with a high [...] Read more.
Developing novel drug formulations and progressing them to the clinical environment relies on preclinical in vitro studies and animal tests to evaluate efficacy and toxicity. However, these current techniques have failed to accurately predict the clinical success of new therapies with a high degree of certainty. The main reason for this failure is that conventional in vitro tissue models lack numerous physiological characteristics of human organs, such as biomechanical forces and biofluid flow. Moreover, animal models often fail to recapitulate the physiology, anatomy, and mechanisms of disease development in human. These shortfalls often lead to failure in drug development, with substantial time and money spent. To tackle this issue, organ-on-chip technology offers realistic in vitro human organ models that mimic the physiology of tissues, including biomechanical forces, stress, strain, cellular heterogeneity, and the interaction between multiple tissues and their simultaneous responses to a therapy. For the latter, complex networks of multiple-organ models are constructed together, known as multiple-organs-on-chip. Numerous studies have demonstrated successful application of organ-on-chips for drug testing, with results comparable to clinical outcomes. This review will summarize and critically evaluate these studies, with a focus on kidney, liver, and respiratory system-on-chip models, and will discuss their progress in their application as a preclinical drug-testing platform to determine in vitro drug toxicology, metabolism, and transport. Further, the advances in the design of these models for improving preclinical drug testing as well as the opportunities for future work will be discussed. Full article
(This article belongs to the Special Issue Convergence of Science and Engineering: A Promising Window toward Improving the Public Health)
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17 pages, 2400 KiB  
Review
Body Acoustics for the Non-Invasive Diagnosis of Medical Conditions
by Jadyn Cook, Muneebah Umar, Fardin Khalili and Amirtahà Taebi
Bioengineering 2022, 9(4), 149; https://doi.org/10.3390/bioengineering9040149 - 01 Apr 2022
Cited by 7 | Viewed by 3623
Abstract
In the past few decades, many non-invasive monitoring methods have been developed based on body acoustics to investigate a wide range of medical conditions, including cardiovascular diseases, respiratory problems, nervous system disorders, and gastrointestinal tract diseases. Recent advances in sensing technologies and computational [...] Read more.
In the past few decades, many non-invasive monitoring methods have been developed based on body acoustics to investigate a wide range of medical conditions, including cardiovascular diseases, respiratory problems, nervous system disorders, and gastrointestinal tract diseases. Recent advances in sensing technologies and computational resources have given a further boost to the interest in the development of acoustic-based diagnostic solutions. In these methods, the acoustic signals are usually recorded by acoustic sensors, such as microphones and accelerometers, and are analyzed using various signal processing, machine learning, and computational methods. This paper reviews the advances in these areas to shed light on the state-of-the-art, evaluate the major challenges, and discuss future directions. This review suggests that rigorous data analysis and physiological understandings can eventually convert these acoustic-based research investigations into novel health monitoring and point-of-care solutions. Full article
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