Bioengineering

15 pages, 2242 KiB

Open AccessArticle

Global Regulator AdpA_1075 Regulates Morphological Differentiation and Ansamitocin Production in Actinosynnema pretiosum subsp. auranticum

by Siyu Guo, Tingting Leng, Xueyuan Sun, Jiawei Zheng, Ruihua Li, Jun Chen, Fengxian Hu, Feng Liu and Qiang Hua

Bioengineering 2022, 9(11), 719; https://doi.org/10.3390/bioengineering9110719 - 21 Nov 2022

Cited by 3 | Viewed by 2040

Abstract

Actinosynnema pretiosum is a well-known producer of maytansinoid antibiotic ansamitocin P-3 (AP-3). Growth of A. pretiosum in submerged culture was characterized by the formation of complex mycelial particles strongly affecting AP-3 production. However, the genetic determinants involved in mycelial morphology are poorly understood [...] Read more.

Actinosynnema pretiosum is a well-known producer of maytansinoid antibiotic ansamitocin P-3 (AP-3). Growth of A. pretiosum in submerged culture was characterized by the formation of complex mycelial particles strongly affecting AP-3 production. However, the genetic determinants involved in mycelial morphology are poorly understood in this genus. Herein a continuum of morphological types of a morphologically stable variant was observed during submerged cultures. Expression analysis revealed that the ssgA_6663 and ftsZ_5883 genes are involved in mycelial aggregation and entanglement. Combing morphology observation and morphology engineering, ssgA_6663 was identified to be responsible for the mycelial intertwining during liquid culture. However, down-regulation of ssgA_6663 transcription was caused by inactivation of adpA_1075, gene coding for an AdpA-like protein. Additionally, the overexpression of adpA_1075 led to an 85% increase in AP-3 production. Electrophoretic mobility shift assays (EMSA) revealed that AdpA_1075 may bind the promoter regions of asm28 gene in asm gene cluster as well as the promoter regions of ssgA_6663. These results confirm that adpA_1075 plays a positive role in AP-3 biosynthesis and morphological differentiation. Full article

(This article belongs to the Special Issue Bioactive Formulations in Agri-Food-Pharma: Source and Applications, Volume II)

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18 pages, 2537 KiB

Open AccessArticle

Cultivation and Imaging of S. latissima Embryo Monolayered Cell Sheets Inside Microfluidic Devices

by Thomas Clerc, Samuel Boscq, Rafaele Attia, Gabriele S. Kaminski Schierle, Bénédicte Charrier and Nino F. Läubli

Bioengineering 2022, 9(11), 718; https://doi.org/10.3390/bioengineering9110718 - 21 Nov 2022

Cited by 1 | Viewed by 2735

Abstract

The culturing and investigation of individual marine specimens in lab environments is crucial to further our understanding of this highly complex ecosystem. However, the obtained results and their relevance are often limited by a lack of suitable experimental setups enabling controlled specimen growth [...] Read more.

The culturing and investigation of individual marine specimens in lab environments is crucial to further our understanding of this highly complex ecosystem. However, the obtained results and their relevance are often limited by a lack of suitable experimental setups enabling controlled specimen growth in a natural environment while allowing for precise monitoring and in-depth observations. In this work, we explore the viability of a microfluidic device for the investigation of the growth of the alga Saccharina latissima to enable high-resolution imaging by confining the samples, which usually grow in 3D, to a single 2D plane. We evaluate the specimen’s health based on various factors such as its growth rate, cell shape, and major developmental steps with regard to the device’s operating parameters and flow conditions before demonstrating its compatibility with state-of-the-art microscopy imaging technologies such as the skeletonisation of the specimen through calcofluor white-based vital staining of its cell contours as well as the immunolocalisation of the specimen’s cell wall. Furthermore, by making use of the on-chip characterisation capabilities, we investigate the influence of altered environmental illuminations on the embryonic development using blue and red light. Finally, live tracking of fluorescent microspheres deposited on the surface of the embryo permits the quantitative characterisation of growth at various locations of the organism. Full article

(This article belongs to the Special Issue Microfluidics and Miniaturized Systems in Bioengineering)

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18 pages, 1389 KiB

Open AccessReview

Stem Cell- and Cell-Based Therapies for Ischemic Stroke

by Delia Carmen Nistor-Cseppentö, Maria Carolina Jurcău, Anamaria Jurcău, Felicia Liana Andronie-Cioară and Florin Marcu

Bioengineering 2022, 9(11), 717; https://doi.org/10.3390/bioengineering9110717 - 20 Nov 2022

Cited by 10 | Viewed by 3502

Abstract

Stroke is the second cause of disability worldwide as it is expected to increase its incidence and prevalence. Despite efforts to increase the number of patients eligible for recanalization therapies, a significant proportion of stroke survivors remain permanently disabled. This outcome boosted the [...] Read more.

Stroke is the second cause of disability worldwide as it is expected to increase its incidence and prevalence. Despite efforts to increase the number of patients eligible for recanalization therapies, a significant proportion of stroke survivors remain permanently disabled. This outcome boosted the search for efficient neurorestorative methods. Stem cells act through multiple pathways: cell replacement, the secretion of growth factors, promoting endogenous reparative pathways, angiogenesis, and the modulation of neuroinflammation. Although neural stem cells are difficult to obtain, pose a series of ethical issues, and require intracerebral delivery, mesenchymal stem cells are less immunogenic, are easy to obtain, and can be transplanted via intravenous, intra-arterial, or intranasal routes. Extracellular vesicles and exosomes have similar actions and are easier to obtain, also allowing for engineering to deliver specific molecules or RNAs and to promote the desired effects. Appropriate timing, dosing, and delivery protocols must be established, and the possibility of tumorigenesis must be settled. Nonetheless, stem cell- and cell-based therapies for stroke have already entered clinical trials. Although safe, the evidence for efficacy is less impressive so far. Hopefully, the STEP guidelines and the SPAN program will improve the success rate. As such, stem cell- and cell-based therapy for ischemic stroke holds great promise. Full article

(This article belongs to the Special Issue Stem Cell Therapy for Cerebrovascular Disease)

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11 pages, 1147 KiB

Open AccessArticle

Identification of Kinetic Abnormalities in Male Patients after Anterior Cruciate Ligament Deficiency Combined with Meniscal Injury: A Musculoskeletal Model Study of Lower Limbs during Jogging

by Shuang Ren, Xiaode Liu, Haoran Li, Yufei Guo, Yuhan Zhang, Zixuan Liang, Si Zhang, Hongshi Huang, Xuhui Huang, Zhe Ma, Qiguo Rong and Yingfang Ao

Bioengineering 2022, 9(11), 716; https://doi.org/10.3390/bioengineering9110716 - 19 Nov 2022

Cited by 1 | Viewed by 2055

Abstract

There is little known about kinetic changes in anterior cruciate ligament deficiency (ACLD) combined with meniscal tears during jogging. Therefore, 29 male patients with injured ACLs and 15 healthy male volunteers were recruited for this study to investigate kinetic abnormalities in male patients [...] Read more.

There is little known about kinetic changes in anterior cruciate ligament deficiency (ACLD) combined with meniscal tears during jogging. Therefore, 29 male patients with injured ACLs and 15 healthy male volunteers were recruited for this study to investigate kinetic abnormalities in male patients after ACL deficiency combined with a meniscal injury during jogging. Based on experimental data measured by an optical tracking system, a subject-specific musculoskeletal model was employed to estimate the tibiofemoral joint kinetics during jogging. Between-limb and interpatient differences were compared by the analysis of variance. The results showed that decreased knee joint forces and moments of both legs in ACLD patients were detected during the stance phase compared to the control group. Meanwhile, compared with ACLD knees, significantly fewer contact forces and flexion moments in ACLD combined with lateral and medial meniscal injury groups were found at the mid-stance, and ACLD with medial meniscal injury group showed a lower axial moment in the loading response (p < 0.05). In conclusion, ACLD knees exhibit reduced tibiofemoral joint forces and moments during jogging when compared with control knees. A combination of meniscus injuries in the ACLD-affected side exhibited abnormal kinetic alterations at the loading response and mid-stance phase. Full article

(This article belongs to the Special Issue Biomechanics and Bionics in Sport and Exercise)

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13 pages, 2663 KiB

Open AccessArticle

Walking Speed Classification from Marker-Free Video Images in Two-Dimension Using Optimum Data and a Deep Learning Method

by Tasriva Sikandar, Sam Matiur Rahman, Dilshad Islam, Md. Asraf Ali, Md. Abdullah Al Mamun, Mohammad Fazle Rabbi, Kamarul H. Ghazali, Omar Altwijri, Mohammed Almijalli and Nizam U. Ahamed

Bioengineering 2022, 9(11), 715; https://doi.org/10.3390/bioengineering9110715 - 19 Nov 2022

Cited by 4 | Viewed by 2962

Abstract

Walking speed is considered a reliable assessment tool for any movement-related functional activities of an individual (i.e., patients and healthy controls) by caregivers and clinicians. Traditional video surveillance gait monitoring in clinics and aged care homes may employ modern artificial intelligence techniques to [...] Read more.

Walking speed is considered a reliable assessment tool for any movement-related functional activities of an individual (i.e., patients and healthy controls) by caregivers and clinicians. Traditional video surveillance gait monitoring in clinics and aged care homes may employ modern artificial intelligence techniques to utilize walking speed as a screening indicator of various physical outcomes or accidents in individuals. Specifically, ratio-based body measurements of walking individuals are extracted from marker-free and two-dimensional video images to create a walk pattern suitable for walking speed classification using deep learning based artificial intelligence techniques. However, the development of successful and highly predictive deep learning architecture depends on the optimal use of extracted data because redundant data may overburden the deep learning architecture and hinder the classification performance. The aim of this study was to investigate the optimal combination of ratio-based body measurements needed for presenting potential information to define and predict a walk pattern in terms of speed with high classification accuracy using a deep learning-based walking speed classification model. To this end, the performance of different combinations of five ratio-based body measurements was evaluated through a correlation analysis and a deep learning-based walking speed classification test. The results show that a combination of three ratio-based body measurements can potentially define and predict a walk pattern in terms of speed with classification accuracies greater than 92% using a bidirectional long short-term memory deep learning method. Full article

(This article belongs to the Special Issue Biomechanics-Based Motion Analysis)

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17 pages, 830 KiB

Open AccessReview

COVID-19 Vaccines: An Updated Overview of Different Platforms

by Dmitry Kudlay, Andrey Svistunov and Oleg Satyshev

Bioengineering 2022, 9(11), 714; https://doi.org/10.3390/bioengineering9110714 - 19 Nov 2022

Cited by 14 | Viewed by 4995

Abstract

Vaccination has been identified as a critical method of disease control in the context of the current COVID-19 pandemic. The goal of this review is to update information on vaccine development and to identify areas of concern that require further research. We reviewed [...] Read more.

Vaccination has been identified as a critical method of disease control in the context of the current COVID-19 pandemic. The goal of this review is to update information on vaccine development and to identify areas of concern that require further research. We reviewed the literature on the development of COVID-19 vaccines, their efficacy, and use in special populations, as well as current vaccination strategies. To date, 170 vaccines are in clinical development, with 41 being already approved for use in various countries. The majority of vaccines approved for human use are vector-, subunit-, DNA-, or mRNA-based vaccines, or inactivated viruses. Because of the ongoing mutation of the SARS-CoV-2 virus, well-studied vector vaccines are losing relevance due to the ability of new virus strains to bypass neutralizing antibodies. Simultaneously, PS-based vaccines are becoming more popular. There is mounting evidence that the immunogenicity of COVID-19 vaccines is linked to their clinical efficacy. This has resulted in a shift in vaccination strategies, as well as the use of booster doses and revaccination. Furthermore, vaccination restrictions for children, pregnant women, the elderly, and people with chronic immunosuppressive diseases have been lifted, allowing more people to be vaccinated. New data on vaccine safety, including the incidence of serious adverse events, have been collected. Despite significant advances in the development of and research on COVID-19 vaccines, many questions remain that require further investigation. Full article

(This article belongs to the Special Issue COVID-19 Diagnostic Strategies: Lessons for Current and Future Pandemic Threats)

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10 pages, 2557 KiB

Open AccessCommunication

Construction of HER2-Specific HIV-1-Based VLPs

by Sofia A. Martins, Joana Santos, Sandra Cabo Verde, João D. G. Correia and Rita Melo

Bioengineering 2022, 9(11), 713; https://doi.org/10.3390/bioengineering9110713 - 19 Nov 2022

Cited by 2 | Viewed by 2261

Abstract

Virus-like particles (VLPs) are nanoplatforms comprised of one or more viral proteins with the capacity to self-assemble without viral genetic material. VLPs arise as promising nanoparticles (NPs) that can be exploited as vaccines, as drug delivery vehicles or as carriers of imaging agents. [...] Read more.

Virus-like particles (VLPs) are nanoplatforms comprised of one or more viral proteins with the capacity to self-assemble without viral genetic material. VLPs arise as promising nanoparticles (NPs) that can be exploited as vaccines, as drug delivery vehicles or as carriers of imaging agents. Engineered antibody constructs, namely single-chain variable fragments (scFv), have been explored as relevant molecules to direct NPs to their target. A vector containing the scFv of an antibody, aimed at the human epidermal growth factor receptor 2 (HER2) and fused to the human immunodeficiency virus (HIV) protein gp41, was previously constructed. The work herein describes the early results concerning the production and the characterization of HIV-1-based VLPs expressing this protein, which could function as potential non-toxic tools for transporting drugs and/or imaging agents. Full article

(This article belongs to the Special Issue Feature Papers in Nanotechnology Applications in Bioengineering)

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17 pages, 350 KiB

Open AccessReview

Cellular and Molecular Events of Wound Healing and the Potential of Silver Based Nanoformulations as Wound Healing Agents

by Caroline Tyavambiza, Mervin Meyer and Samantha Meyer

Bioengineering 2022, 9(11), 712; https://doi.org/10.3390/bioengineering9110712 - 19 Nov 2022

Cited by 18 | Viewed by 3213

Abstract

Chronic wounds are a silent epidemic threatening the lives of many people worldwide. They are associated with social, health care and economic burdens and can lead to death if left untreated. The treatment of chronic wounds is very challenging as it may not [...] Read more.

Chronic wounds are a silent epidemic threatening the lives of many people worldwide. They are associated with social, health care and economic burdens and can lead to death if left untreated. The treatment of chronic wounds is very challenging as it may not be fully effective and may be associated with various adverse effects. New wound healing agents that are potentially more effective are being discovered continuously to combat these chronic wounds. These agents include silver nanoformulations which can contain nanoparticles or nanocomposites. To be effective, the discovered agents need to have good wound healing properties which will enhance their effectiveness in the different stages of wound healing. This review will focus on the process of wound healing and describe the properties of silver nanoformulations that contribute to wound healing. Full article

(This article belongs to the Special Issue Biomaterials for Chronic Wound Healing)

9 pages, 1082 KiB

Open AccessEditor’s ChoiceArticle

Heart and Breathing Rate Variations as Biomarkers for Anxiety Detection

by Florian Ritsert, Mohamed Elgendi, Valeria Galli and Carlo Menon

Bioengineering 2022, 9(11), 711; https://doi.org/10.3390/bioengineering9110711 - 19 Nov 2022

Cited by 14 | Viewed by 4149

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;

\bar{p}

= 0.04), the standard deviation of the heart rate (SD;

\bar{p}

= 0.01), and the standard deviation of NN intervals (SDNN;

\bar{p}

= 0.03) for ECG signals, and the mean breath rate (MBR;

\bar{p}

= 0.002), the standard deviation of the breath rate (SD;

\bar{p}

< 0.0001), the root mean square of successive differences (RMSSD;

\bar{p}

< 0.0001) and SDNN (

\bar{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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18 pages, 7405 KiB

Open AccessArticle

Empirical Study of Autism Spectrum Disorder Diagnosis Using Facial Images by Improved Transfer Learning Approach

by Md Shafiul Alam, Muhammad Mahbubur Rashid, Rupal Roy, Ahmed Rimaz Faizabadi, Kishor Datta Gupta and Md Manjurul Ahsan

Bioengineering 2022, 9(11), 710; https://doi.org/10.3390/bioengineering9110710 - 18 Nov 2022

Cited by 31 | Viewed by 5857

Abstract

Autism spectrum disorder (ASD) is a neurological illness characterized by deficits in cognition, physical activities, and social skills. There is no specific medication to treat this illness; only early intervention can improve brain functionality. Since there is no medical test to identify ASD, [...] Read more.

Autism spectrum disorder (ASD) is a neurological illness characterized by deficits in cognition, physical activities, and social skills. There is no specific medication to treat this illness; only early intervention can improve brain functionality. Since there is no medical test to identify ASD, a diagnosis might be challenging. In order to determine a diagnosis, doctors consider the child’s behavior and developmental history. The human face can be used as a biomarker as it is one of the potential reflections of the brain and thus can be used as a simple and handy tool for early diagnosis. This study uses several deep convolutional neural network (CNN)-based transfer learning approaches to detect autistic children using the facial image. An empirical study is conducted to select the best optimizer and set of hyperparameters to achieve better prediction accuracy using the CNN model. After training and validating with the optimized setting, the modified Xception model demonstrates the best performance by achieving an accuracy of 95% on the test set, whereas the VGG19, ResNet50V2, MobileNetV2, and EfficientNetB0 achieved 86.5%, 94%, 92%, and 85.8%, accuracy, respectively. Our preliminary computational results demonstrate that our transfer learning approaches outperformed existing methods. Our modified model can be employed to assist doctors and practitioners in validating their initial screening to detect children with ASD disease. Full article

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27 pages, 4366 KiB

Open AccessArticle

Automated Lung-Related Pneumonia and COVID-19 Detection Based on Novel Feature Extraction Framework and Vision Transformer Approaches Using Chest X-ray Images

by Chiagoziem C. Ukwuoma, Zhiguang Qin, Md Belal Bin Heyat, Faijan Akhtar, Abla Smahi, Jehoiada K. Jackson, Syed Furqan Qadri, Abdullah Y. Muaad, Happy N. Monday and Grace U. Nneji

Bioengineering 2022, 9(11), 709; https://doi.org/10.3390/bioengineering9110709 - 18 Nov 2022

Cited by 28 | Viewed by 8902

Abstract

According to research, classifiers and detectors are less accurate when images are blurry, have low contrast, or have other flaws which raise questions about the machine learning model’s ability to recognize items effectively. The chest X-ray image has proven to be the preferred [...] Read more.

According to research, classifiers and detectors are less accurate when images are blurry, have low contrast, or have other flaws which raise questions about the machine learning model’s ability to recognize items effectively. The chest X-ray image has proven to be the preferred image modality for medical imaging as it contains more information about a patient. Its interpretation is quite difficult, nevertheless. The goal of this research is to construct a reliable deep-learning model capable of producing high classification accuracy on chest x-ray images for lung diseases. To enable a thorough study of the chest X-ray image, the suggested framework first derived richer features using an ensemble technique, then a global second-order pooling is applied to further derive higher global features of the images. Furthermore, the images are then separated into patches and position embedding before analyzing the patches individually via a vision transformer approach. The proposed model yielded 96.01% sensitivity, 96.20% precision, and 98.00% accuracy for the COVID-19 Radiography Dataset while achieving 97.84% accuracy, 96.76% sensitivity and 96.80% precision, for the Covid-ChestX-ray-15k dataset. The experimental findings reveal that the presented models outperform traditional deep learning models and other state-of-the-art approaches provided in the literature. Full article

(This article belongs to the Special Issue Machine Learning for Biomedical Applications)

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21 pages, 5396 KiB

Open AccessArticle

Influence of Rigid–Elastic Artery Wall of Carotid and Coronary Stenosis on Hemodynamics

by Muhamed Albadawi, Yasser Abuouf, Samir Elsagheer, Hidetoshi Sekiguchi, Shinichi Ookawara and Mahmoud Ahmed

Bioengineering 2022, 9(11), 708; https://doi.org/10.3390/bioengineering9110708 - 18 Nov 2022

Cited by 9 | Viewed by 3122

Abstract

Cardiovascular system abnormalities can result in serious health complications. By using the fluid–structure interaction (FSI) procedure, a comprehensive realistic approach can be employed to accurately investigate blood flow coupled with arterial wall response. The hemodynamics was investigated in both the coronary and carotid [...] Read more.

Cardiovascular system abnormalities can result in serious health complications. By using the fluid–structure interaction (FSI) procedure, a comprehensive realistic approach can be employed to accurately investigate blood flow coupled with arterial wall response. The hemodynamics was investigated in both the coronary and carotid arteries based on the arterial wall response. The hemodynamics was estimated based on the numerical simulation of a comprehensive three-dimensional non-Newtonian blood flow model in elastic and rigid arteries. For stenotic right coronary artery (RCA), it was found that the maximum value of wall shear stress (WSS) for the FSI case is higher than the rigid wall. On the other hand, for the stenotic carotid artery (CA), it was found that the maximum value of WSS for the FSI case is lower than the rigid wall. Moreover, at the peak systole of the cardiac cycle (0.38 s), the maximum percentage of arterial wall deformation was found to be 1.9%. On the other hand, for the stenotic carotid artery, the maximum percentage of arterial wall deformation was found to be 0.46%. A comparison between FSI results and those obtained by rigid wall arteries is carried out. Findings indicate slight differences in results for large-diameter arteries such as the carotid artery. Accordingly, the rigid wall assumption is plausible in flow modeling for relatively large diameters such as the carotid artery. Additionally, the FSI approach is essential in flow modeling in small diameters. Full article

(This article belongs to the Special Issue Computational Fluid Dynamics in Medicine and Biology)

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19 pages, 1446 KiB

Open AccessReview

The Exploration of Microbial Natural Products and Metabolic Interaction Guided by Mass Spectrometry Imaging

by Hao Li and Zhiyong Li

Bioengineering 2022, 9(11), 707; https://doi.org/10.3390/bioengineering9110707 - 18 Nov 2022

Cited by 4 | Viewed by 2992

Abstract

As an impressive mass spectrometry technology, mass spectrometric imaging (MSI) can provide mass spectra data and spatial distribution of analytes simultaneously. MSI has been widely used in diverse fields such as clinical diagnosis, the pharmaceutical industry and environmental study due to its accuracy, [...] Read more.

As an impressive mass spectrometry technology, mass spectrometric imaging (MSI) can provide mass spectra data and spatial distribution of analytes simultaneously. MSI has been widely used in diverse fields such as clinical diagnosis, the pharmaceutical industry and environmental study due to its accuracy, high resolution and developing reproducibility. Natural products (NPs) have been a critical source of leading drugs; almost half of marketed drugs are derived from NPs or their derivatives. The continuous search for bioactive NPs from microorganisms or microbiomes has always been attractive. MSI allows us to analyze and characterize NPs directly in monocultured microorganisms or a microbial community. In this review, we briefly introduce current mainstream ionization technologies for microbial samples and the key issue of sample preparation, and then summarize some applications of MSI in the exploration of microbial NPs and metabolic interaction, especially NPs from marine microbes. Additionally, remaining challenges and future prospects are discussed. Full article

(This article belongs to the Special Issue Marine Microbial Symbionts: Underexplored Microbiome and Novel Metabolites)

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17 pages, 951 KiB

Open AccessArticle

The Assessment of Medication Effects in Omicron Patients through MADM Approach Based on Distance Measures of Interval-Valued Fuzzy Hypersoft Set

by Muhammad Arshad, Muhammad Saeed, Atiqe Ur Rahman, Dilovan Asaad Zebari, Mazin Abed Mohammed, Alaa S. Al-Waisy, Marwan Albahar and Mohammed Thanoon

Bioengineering 2022, 9(11), 706; https://doi.org/10.3390/bioengineering9110706 - 17 Nov 2022

Cited by 9 | Viewed by 1852

Abstract

Omicron, so-called COVID-2, is an emerging variant of COVID-19 which is proved to be the most fatal amongst the other variants such as alpha, beta and gamma variants (

α

,

β

,

γ

variants) due to its stern and perilous nature. It [...] Read more.

Omicron, so-called COVID-2, is an emerging variant of COVID-19 which is proved to be the most fatal amongst the other variants such as alpha, beta and gamma variants (

α

,

β

,

γ

variants) due to its stern and perilous nature. It has caused hazardous effects globally in a very short span of time. The diagnosis and medication of Omicron patients are both challenging undertakings for researchers (medical experts) due to the involvement of various uncertainties and the vagueness of its altering behavior. In this study, an algebraic approach, interval-valued fuzzy hypersoft set (iv-FHSS), is employed to assess the conditions of patients after the application of suitable medication. Firstly, the distance measures between two iv-FHSSs are formulated with a brief description some of its properties, then a multi-attribute decision-making framework is designed through the proposal of an algorithm. This framework consists of three phases of medication. In the first phase, the Omicron-diagnosed patients are shortlisted and an iv-FHSS is constructed for such patients and then they are medicated. Another iv-FHSS is constructed after their first medication. Similarly, the relevant iv-FHSSs are constructed after second and third medications in other phases. The distance measures of these post-medication-based iv-FHSSs are computed with pre-medication-based iv-FHSS and the monotone pattern of distance measures are analyzed. It is observed that a decreasing pattern of computed distance measures assures that the medication is working well and the patients are recovering. In case of an increasing pattern, the medication is changed and the same procedure is repeated for the assessment of its effects. This approach is reliable due to the consideration of parameters (symptoms) and sub parameters (sub symptoms) jointly as multi-argument approximations. Full article

(This article belongs to the Special Issue Advances of Biomedical Signal Processing)

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15 pages, 4120 KiB

Open AccessArticle

Boron- and Boric Acid-Treated Titanium Implant Surfaces in Sheep Tibia: A Histologic, Histomorphometric and Mechanical Study

by Nazlı Ayşeşek, Volkan Arısan, Nilüfer Bölükbaşı Balcıoğlu, Ayşe Erol, Furkan Kuruoğlu, Merva Soluk Tekkeşin and Selim Ersanlı

Bioengineering 2022, 9(11), 705; https://doi.org/10.3390/bioengineering9110705 - 17 Nov 2022

Cited by 3 | Viewed by 1681

Abstract

The aim of this study was to compare the topographical, chemical and osseointegration characteristics of sandblasting and acid-etching (SLA) surfaces and dental implants treated by boron compounds. Titanium (Ti) disks (n = 20) were modified using boron (B) and boric acid (H₃ [...] Read more.

The aim of this study was to compare the topographical, chemical and osseointegration characteristics of sandblasting and acid-etching (SLA) surfaces and dental implants treated by boron compounds. Titanium (Ti) disks (n = 20) were modified using boron (B) and boric acid (H₃BO₃) and then compared with the conventional SLA surface via surface topographic characterizations. Dental implants (3.5 mm in diameter and 8 mm in length) with the experimental surfaces (n = 96) were inserted into the tibias of six sheep, which were left to heal for 3 and 7 weeks. Histologic, histomorphometric (bone–implant contact (BIC%)) and mechanical tests (removal torque value (RTV)) were performed. The boron-coated surface (BC group) was smoother (Rz: 4.51 μm ± 0.13) than the SLA (5.86 μm ± 0.80) and the SLA-B (5.75 μm ± 0.64) groups (p = 0.033). After 3 weeks, the highest mean RTV was found in the SLA group (37 N/cm ± 2.87), and the difference compared with the BC group (30 N/cm ± 2.60) was statistically significant (p = 0.004). After 7 weeks, the mean RTV was >80 N/cm in all groups; the highest was measured in the H₃BO₃-treated (BS) group (89 N/cm ± 1.53) (p < 0.0001). No statistically significant differences were found in the BIC%s during both healing periods between the groups. H₃BO₃ seems to be a promising medium for dental implant osseointegration. Full article

(This article belongs to the Section Regenerative Engineering)

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18 pages, 851 KiB

Open AccessReview

Intraoperative Creation of Tissue-Engineered Grafts with Minimally Manipulated Cells: New Concept of Bone Tissue Engineering In Situ

by Olga A. Krasilnikova, Denis S. Baranovskii, Anna O. Yakimova, Nadezhda Arguchinskaya, Anastas Kisel, Dmitry Sosin, Yana Sulina, Sergey A. Ivanov, Peter V. Shegay, Andrey D. Kaprin and Ilya D. Klabukov

Bioengineering 2022, 9(11), 704; https://doi.org/10.3390/bioengineering9110704 - 17 Nov 2022

Cited by 19 | Viewed by 2839

Abstract

Transfer of regenerative approaches into clinical practice is limited by strict legal regulation of in vitro expanded cells and risks associated with substantial manipulations. Isolation of cells for the enrichment of bone grafts directly in the Operating Room appears to be a promising [...] Read more.

Transfer of regenerative approaches into clinical practice is limited by strict legal regulation of in vitro expanded cells and risks associated with substantial manipulations. Isolation of cells for the enrichment of bone grafts directly in the Operating Room appears to be a promising solution for the translation of biomedical technologies into clinical practice. These intraoperative approaches could be generally characterized as a joint concept of tissue engineering in situ. Our review covers techniques of intraoperative cell isolation and seeding for the creation of tissue-engineered grafts in situ, that is, directly in the Operating Room. Up-to-date, the clinical use of tissue-engineered grafts created in vitro remains a highly inaccessible option. Fortunately, intraoperative tissue engineering in situ is already available for patients who need advanced treatment modalities. Full article

(This article belongs to the Special Issue Mesenchymal Stem Cells for Tissue Engineering and Modelling)

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11 pages, 3173 KiB

Open AccessArticle

The Effect of Arch Stiffness on the Foot–Ankle Temporal Kinematics during Gait Termination: A Statistical Nonparametric Mapping Study

by Xuanzhen Cen, Peimin Yu, Yang Song, József Sárosi, Zhuqing Mao, István Bíró and Yaodong Gu

Bioengineering 2022, 9(11), 703; https://doi.org/10.3390/bioengineering9110703 - 17 Nov 2022

Cited by 5 | Viewed by 1940

Abstract

This study compares foot–ankle temporal kinematics characteristics during planned and unplanned gait termination (PGT and UGT) in subjects with different arch stiffnesses (ASs) based on the statistical nonparametric mapping (SnPM) method. By measuring three-dimensional arch morphological parameters under different loading conditions, 28 healthy [...] Read more.

This study compares foot–ankle temporal kinematics characteristics during planned and unplanned gait termination (PGT and UGT) in subjects with different arch stiffnesses (ASs) based on the statistical nonparametric mapping (SnPM) method. By measuring three-dimensional arch morphological parameters under different loading conditions, 28 healthy male subjects were classified and participated in gait termination (GT) tests to collect metatarsophalangeal (MTP) and ankle-joint kinematics data. The two-way repeated-measures ANOVA using SnPM was employed to assess the impacts of AS on foot–ankle kinematics during PGT and UGT. Our results show that joint angles (MTP and ankle joints) were altered owing to AS and GT factors. The flexible arches hahadve periods of significantly greater MTP and ankle joint angles than those of stiff arches during the stance phase of GT, whereas subjects exhibited significantly smaller ankle and MTP joint angles during UGT. These results add additional insights into the morphological arch biomechanical function, and the comprehensive compensatory adjustment of lower-limb joints during gait stopping caused by unplanned stimulation. Full article

(This article belongs to the Special Issue Biomedical and Bioengineering Technology: Current Applications in Sports Monitoring and Health Care)

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19 pages, 5402 KiB

Open AccessArticle

Addition of ROCK Inhibitors Alleviates Prostaglandin-Induced Inhibition of Adipogenesis in 3T3L-1 Spheroids

by Yosuke Ida, Tatsuya Sato, Araya Umetsu, Megumi Watanabe, Masato Furuhashi, Fumihito Hikage and Hiroshi Ohguro

Bioengineering 2022, 9(11), 702; https://doi.org/10.3390/bioengineering9110702 - 17 Nov 2022

Cited by 6 | Viewed by 1873

Abstract

To elucidate the additive effects of the ROCK inhibitors (ROCK-i), ripasudil (Rip) and Y27632 on bimatoprost acid (BIM-A), a prostaglandin analog (PG), on adipose tissue, two- and three-dimensional (2D or 3D) cultures of 3T3-L1 cells, the most well characterized cells in the field [...] Read more.

To elucidate the additive effects of the ROCK inhibitors (ROCK-i), ripasudil (Rip) and Y27632 on bimatoprost acid (BIM-A), a prostaglandin analog (PG), on adipose tissue, two- and three-dimensional (2D or 3D) cultures of 3T3-L1 cells, the most well characterized cells in the field of lipid research, were used. The cells were subjected to a variety of analyses including lipid staining, real-time cellular metabolic analysis, the mRNA expressions of genes related to adipogenesis and extracellular matrices (ECMs) as well as the sizes and physical properties of the 3D spheroids by a micro-squeezer. BIM-A induced strong inhibitory effects on most of the adipogenesis-related changes in the 2D and 3D cultured 3T3-L1 cells, including (1) the enlargement and softening of the 3D spheroids, (2) a dramatic enhancement in lipid staining and the expression of adipogenesis-related genes, and (3) a decrease in mitochondrial and glycolytic metabolic function. By adding ROCK-i to the BIM-A, most of these BIM-A-induced effects were cancelled. The collective findings reported herein suggest that ROCK-i eliminated the PG-induced suppression of adipogenesis in the 3T3-L1 cells, accompanied by the formation of enlarged 3D spheroids. Such effects of adding ROCK-i to a PG in preadipocytes on cellular properties appear to be associated with the suppression of PG-induced adverse effects, and provide additional insight into our understanding of lipid-related research. Full article

(This article belongs to the Section Nanobiotechnology and Biofabrication)

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13 pages, 2429 KiB

Open AccessArticle

Toward Evaluating Critical Factors of Extubation Outcome with XCSR-Generated Rules

by Po-Hsun Huang, Lian-Yu Chen, Wei-Chan Chung, Chau-Chyun Sheu, Tzu-Chien Hsiao and Jong-Rung Tsai

Bioengineering 2022, 9(11), 701; https://doi.org/10.3390/bioengineering9110701 - 17 Nov 2022

Cited by 2 | Viewed by 2059

Abstract

Predicting the correct timing for extubation is pivotal for critically ill patients with mechanical ventilation support. Evidence suggests that extubation failure occurs in approximately 15–20% of patients, despite their passing of the extubation evaluation, necessitating reintubation. For critically ill patients, reintubation invariably increases [...] Read more.

Predicting the correct timing for extubation is pivotal for critically ill patients with mechanical ventilation support. Evidence suggests that extubation failure occurs in approximately 15–20% of patients, despite their passing of the extubation evaluation, necessitating reintubation. For critically ill patients, reintubation invariably increases mortality risk and medical costs. The numerous parameters that have been proposed for extubation decision-making, which constitute the key predictors of successful extubation, remains unclear. In this study, an extended classifier system capable of processing real-value inputs was proposed to select features of successful extubation. In total, 40 features linked to clinical information and variables acquired during spontaneous breathing trial (SBT) were used as the environmental inputs. According to the number of “don’t care” rules in a population set, Prob_usage, the probability of the feature not being classified as above rules, can be calculated. A total of 228 subjects’ results showed that Prob_usage was higher than 90% for minute ventilation at the 1st, 30th, 60th, and 90th minutes; respiratory rate at the 90th minute; and body weight, indicating that the variance in respiratory parameters during an SBT are critical predictors of successful extubation. The present XCSR model is useful to evaluate critical factors of extubation outcomes. Additionally, the current findings suggest that SBT duration should exceed 90 min, and that clinicians should consider the variance in respiratory variables during an SBT before making extubation decisions. Full article

(This article belongs to the Special Issue New Scenes of Artificial Intelligence in Medical Research: Latest Information and Future Directions)

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12 pages, 1878 KiB

Open AccessReview

Zr-Based Metal-Organic Frameworks for Green Biodiesel Synthesis: A Minireview

by Qiuyun Zhang, Jialu Wang, Shuya Zhang, Juan Ma, Jingsong Cheng and Yutao Zhang

Bioengineering 2022, 9(11), 700; https://doi.org/10.3390/bioengineering9110700 - 17 Nov 2022

Cited by 12 | Viewed by 2884

Abstract

Metal–organic frameworks (MOFs) have widespread application prospects in the field of catalysis owing to their functionally adjustable metal sites and adjustable structure. In this minireview, we summarize the current advancements in zirconium-based metal–organic framework (Zr-based MOF) catalysts (including single Zr-based MOFs, modified Zr-based [...] Read more.

Metal–organic frameworks (MOFs) have widespread application prospects in the field of catalysis owing to their functionally adjustable metal sites and adjustable structure. In this minireview, we summarize the current advancements in zirconium-based metal–organic framework (Zr-based MOF) catalysts (including single Zr-based MOFs, modified Zr-based MOFs, and Zr-based MOF derivatives) for green biofuel synthesis. Additionally, the yields, conversions, and reusability of Zr-based MOF catalysts for the production of biodiesel are compared. Finally, the challenges and future prospects regarding Zr-based MOFs and their derivatives for catalytic application in the biorefinery field are highlighted. Full article

(This article belongs to the Special Issue Acceleration of Biodiesel Production)

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10 pages, 2397 KiB

Open AccessCase Report

The Allogenic Dental Pulp Transplantation from Son/Daughter to Mother/Father: A Follow-Up of Three Clinical Cases

by Victor Pinheiro Feitosa, Mara Natiere Mota, Roseane Savoldi, Tainah Rifane, Diego de Paula, Livia Borges, Luzia Kelly Solheiro, Manoel Aguiar Neto, Lorena Vieira, Ana Carolina Moreira and Salvatore Sauro

Bioengineering 2022, 9(11), 699; https://doi.org/10.3390/bioengineering9110699 - 17 Nov 2022

Cited by 2 | Viewed by 3091

Abstract

The study investigated allogenic pulp transplantation as an innovative method of regenerative endodontic therapy. Three patients were selected for the endodontic treatment of single-root teeth, who also had a son/daughter with deciduous teeth or third molars scheduled for extraction. Receptor teeth were endodontically [...] Read more.

The study investigated allogenic pulp transplantation as an innovative method of regenerative endodontic therapy. Three patients were selected for the endodontic treatment of single-root teeth, who also had a son/daughter with deciduous teeth or third molars scheduled for extraction. Receptor teeth were endodontically instrumented and irrigated using a tri-antibiotic solution. During the transplant procedures, the teeth from the son/daughter were extracted, sectioned, and the pulp was carefully removed. The harvested pulp from the donor was inserted into the root canal of the host tooth (father/mother), followed by direct pulp capping and resin composite restoration. The teeth were followed-up with for 2 years and were surveyed with computed tomography, the electric pulp vitality test, and Doppler ultrasound examination. At the 6-month follow-up, positive pulp vitality and the formation of periapical lesions were verified in cases 1 and 2. Case 3 showed remarkable periapical radiolucency before transplantation, but after 1 year, such lesions disappeared and there was positive vitality. All teeth were revascularized as determined by Doppler imaging after 2 years with no signs of endodontic/periodontal radiolucency. In conclusion, although this was a case series with only three patients and four teeth treated, it is possible to suppose that this allogenic pulp transplantation protocol could represent a potential strategy for pulp revitalization in specific endodontic cases. Full article

(This article belongs to the Special Issue Recent Advances in Biomaterials and Dental Disease)

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32 pages, 15470 KiB

Open AccessArticle

Diverse COVID-19 CT Image-to-Image Translation with Stacked Residual Dropout

by Kin Wai Lee and Renee Ka Yin Chin

Bioengineering 2022, 9(11), 698; https://doi.org/10.3390/bioengineering9110698 - 16 Nov 2022

Cited by 6 | Viewed by 2785

Abstract

Machine learning models are renowned for their high dependency on a large corpus of data in solving real-world problems, including the recent COVID-19 pandemic. In practice, data acquisition is an onerous process, especially in medical applications, due to lack of data availability for [...] Read more.

Machine learning models are renowned for their high dependency on a large corpus of data in solving real-world problems, including the recent COVID-19 pandemic. In practice, data acquisition is an onerous process, especially in medical applications, due to lack of data availability for newly emerged diseases and privacy concerns. This study introduces a data synthesization framework (sRD-GAN) that generates synthetic COVID-19 CT images using a novel stacked-residual dropout mechanism (sRD). sRD-GAN aims to alleviate the problem of data paucity by generating synthetic lung medical images that contain precise radiographic annotations. The sRD mechanism is designed using a regularization-based strategy to facilitate perceptually significant instance-level diversity without content-style attribute disentanglement. Extensive experiments show that sRD-GAN can generate exceptional perceptual realism on COVID-19 CT images examined by an experiment radiologist, with an outstanding Fréchet Inception Distance (FID) of 58.68 and Learned Perceptual Image Patch Similarity (LPIPS) of 0.1370 on the test set. In a benchmarking experiment, sRD-GAN shows superior performance compared to GAN, CycleGAN, and one-to-one CycleGAN. The encouraging results achieved by sRD-GAN in different clinical cases, such as community-acquired pneumonia CT images and COVID-19 in X-ray images, suggest that the proposed method can be easily extended to other similar image synthetization problems. Full article

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13 pages, 3433 KiB

Open AccessArticle

Effective Capacitance from Equivalent Electrical Circuit as a Tool for Monitoring Non-Adherent Cell Suspensions at Low Frequencies

by Alma De León-Hernández, Luisa Romero-Ornelas, Roberto G. Ramírez-Chavarría, Eva Ramón-Gallegos and Celia Sánchez-Pérez

Bioengineering 2022, 9(11), 697; https://doi.org/10.3390/bioengineering9110697 - 16 Nov 2022

Cited by 1 | Viewed by 2023

Abstract

Analyzing the electrical double layer (EDL) in electrical impedance spectroscopy (EIS) measurement at low frequencies remains a challenging task for sensing purposes. In this work, we propose two approaches to deal with the EDL in measuring impedance for particles and non-adherent cells in [...] Read more.

Analyzing the electrical double layer (EDL) in electrical impedance spectroscopy (EIS) measurement at low frequencies remains a challenging task for sensing purposes. In this work, we propose two approaches to deal with the EDL in measuring impedance for particles and non-adherent cells in an electrolytic suspension. The first approach is a simple procedure to compute a normalized electrical impedance spectrum named dispersed medium index (

{DM}_{i}

). The second is the EIS modeling through an equivalent electric circuit based on the so-called effective capacitance (

C_{ef}

), which unifies the EDL phenomena. Firstly, as an experiment under controlled conditions, we examine polymer particles of 6, 15, and 48 μm in diameter suspended in a 0.9% sodium chloride solution. Subsequently, we used K-562 cells and leukocytes suspended in a culture medium (RPMI-1640 supplemented) for a biological assay. As the main result, the

{DM}_{i}

is a function of the particle concentration. In addition, it shows a tendency with the particle size; regardless, it is limited to a volume fraction of 0.03 × 10⁻⁴ to 58 × 10⁻⁴. The

{DM}_{i}

is not significantly different between K-562 cells and leukocytes for most concentrations. On the other hand, the

C_{ef}

exhibits high applicability to retrieve a function that describes the concentration for each particle size, the K-562 cells, and leukocytes. The

C_{ef}

also shows a tendency with the particle size without limitation within the range tested, and it allows distinction between the K-562 and leukocytes in the 25 cells/µL to 400 cells/µL range. We achieved a simple method for determining an

C_{ef}

by unifying the parameters of an equivalent electrical circuit from data obtained with a conventional potentiostat. This simple approach is affordable for characterizing the population of non-adherent cells suspended in a cell culture medium. Full article

(This article belongs to the Special Issue Women's Special Issue Series: Biosensors)

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14 pages, 1164 KiB

Open AccessReview

Advances in Cardiac Tissue Engineering

by Takahiro Kitsuka, Fuga Takahashi, James Reinhardt, Tatsuya Watanabe, Anudari Ulziibayar, Asigul Yimit, John Kelly and Toshiharu Shinoka

Bioengineering 2022, 9(11), 696; https://doi.org/10.3390/bioengineering9110696 - 16 Nov 2022

Cited by 6 | Viewed by 2623

Abstract

Tissue engineering has paved the way for the development of artificial human cardiac muscle patches (hCMPs) and cardiac tissue analogs, especially for treating Myocardial infarction (MI), often by increasing its regenerative abilities. Low engraftment rates, insufficient clinical application scalability, and the creation of [...] Read more.

Tissue engineering has paved the way for the development of artificial human cardiac muscle patches (hCMPs) and cardiac tissue analogs, especially for treating Myocardial infarction (MI), often by increasing its regenerative abilities. Low engraftment rates, insufficient clinical application scalability, and the creation of a functional vascular system remain obstacles to hCMP implementation in clinical settings. This paper will address some of these challenges, present a broad variety of heart cell types and sources that can be applied to hCMP biomanufacturing, and describe some new innovative methods for engineering such treatments. It is also important to note the injection/transplantation of cells in cardiac tissue engineering. Full article

(This article belongs to the Special Issue Advances in Cardiac Tissue Engineering)

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15 pages, 945 KiB

Open AccessReview

The Existing Recovery Approaches of the Huangjiu Lees and the Future Prospects: A Mini Review

by Rongbin Zhang, Yizhou Liu, Shuangping Liu and Jian Mao

Bioengineering 2022, 9(11), 695; https://doi.org/10.3390/bioengineering9110695 - 16 Nov 2022

Cited by 3 | Viewed by 1780

Abstract

Huangjiu lees (HL) is a byproduct in Chinese Huangjiu production with various nutrient and biological functional components. Without efficient treatment, it could cause environmental issues and bioresource wasting. Existing dominant recovery approaches focus on large-scale disposal, but they ignore the application of high-value [...] Read more.

Huangjiu lees (HL) is a byproduct in Chinese Huangjiu production with various nutrient and biological functional components. Without efficient treatment, it could cause environmental issues and bioresource wasting. Existing dominant recovery approaches focus on large-scale disposal, but they ignore the application of high-value components. This study discusses the advantages and limitations of existing resourcing approaches, such as feed, food and biogas biological production, considering the efficiency and value of HL resourcing. The extraction of functional components as a suggestion for HL cascade utilization is pointed out. This study is expected to promote the application of HL resourcing. Full article

(This article belongs to the Special Issue Advances in Food and By-Products Processing)

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13 pages, 657 KiB

Open AccessArticle

Effects of Oxygen Transference on Protease Production by Rhodotorula mucilaginosa CBMAI 1528 in a Stirred Tank Bioreactor

by Suellen Machado, Valker Feitosa, Omar Pillaca-Pullo, Luciana Lario, Lara Sette, Adalberto Pessoa, Jr. and Harley Alves

Bioengineering 2022, 9(11), 694; https://doi.org/10.3390/bioengineering9110694 - 15 Nov 2022

Cited by 2 | Viewed by 2161

Abstract

Microbial proteases, especially aspartic proteases, are an essential group of enzymes produced from different microorganisms. Microbial proteases have several applications, mainly in the food, beverage, cosmetic, and pharmaceutical industries, due to their efficiency in the processing and in the manufacturing stages. The yeast [...] Read more.

Microbial proteases, especially aspartic proteases, are an essential group of enzymes produced from different microorganisms. Microbial proteases have several applications, mainly in the food, beverage, cosmetic, and pharmaceutical industries, due to their efficiency in the processing and in the manufacturing stages. The yeast Rhodotorula mucilaginosa CBMAI 1528 was isolated from the Antarctic environment and was previously reported to have higher extracellular aspartic protease production. In addition, advances in the operational conditions of bioreactors for enzyme production are important to reduce the gap associated with scaling−up processes. This is the first study that evaluates the influence of oxygen transference (k_La) on the protease production of R. mucilaginosa yeast. To that end, batch cultures were created in a stirred tank bioreactor using Sabouraud dextrose broth at 25 °C for 72 h under k_La values from 18 to 135 h⁻¹. The results show that k_La (121 h⁻¹) obtained at 500 rpm and 1.5 vvm plays an important role in protease production (124.9 U/mL) and productivity (6.784 U/L.h) as well as biomass (10.4 g/L), μ_max (0.14 h⁻¹) and Y_x/s (0.484 g/g). In conclusion, R. mucilaginosa showed high yield production in aerobic culture with the efficiency of protease expression and secretion influenced by k_La. In this sense, our results could be used for further industrial investment. Full article

(This article belongs to the Special Issue Advances in Food and By-Products Processing)

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14 pages, 5830 KiB

Open AccessArticle

Engineering Skeletal Muscle Grafts with PAX7::GFP-Sorted Human Pluripotent Stem Cell-Derived Myogenic Progenitors on Fibrin Microfiber Bundles for Tissue Regeneration

by Sarah M. Somers, Jordana Gilbert-Honick, In Young Choi, Emily K. W. Lo, HoTae Lim, Shaquielle Dias, Kathryn R. Wagner, Hai-Quan Mao, Patrick Cahan, Gabsang Lee and Warren L. Grayson

Bioengineering 2022, 9(11), 693; https://doi.org/10.3390/bioengineering9110693 - 15 Nov 2022

Cited by 5 | Viewed by 2506

Abstract

Tissue engineering strategies that combine human pluripotent stem cell-derived myogenic progenitors (hPDMs) with advanced biomaterials provide promising tools for engineering 3D skeletal muscle grafts to model tissue development in vitro and promote muscle regeneration in vivo. We recently demonstrated (i) the potential for [...] Read more.

Tissue engineering strategies that combine human pluripotent stem cell-derived myogenic progenitors (hPDMs) with advanced biomaterials provide promising tools for engineering 3D skeletal muscle grafts to model tissue development in vitro and promote muscle regeneration in vivo. We recently demonstrated (i) the potential for obtaining large numbers of hPDMs using a combination of two small molecules without the overexpression of transgenes and (ii) the application of electrospun fibrin microfiber bundles for functional skeletal muscle restoration following volumetric muscle loss. In this study, we aimed to demonstrate that the biophysical cues provided by the fibrin microfiber bundles induce hPDMs to form engineered human skeletal muscle grafts containing multinucleated myotubes that express desmin and myosin heavy chains and that these grafts could promote regeneration following skeletal muscle injuries. We tested a genetic PAX7 reporter line (PAX7::GFP) to sort for more homogenous populations of hPDMs. RNA sequencing and gene set enrichment analyses confirmed that PAX7::GFP-sorted hPDMs exhibited high expression of myogenic genes. We tested engineered human skeletal muscle grafts derived from PAX7::GFP-sorted hPDMs within in vivo skeletal muscle defects by assessing myogenesis, engraftment and immunogenicity using immunohistochemical staining. The PAX7::GFP-sorted groups had moderately high vascular infiltration and more implanted cell association with embryonic myosin heavy chain (eMHC) regions, suggesting they induced pro-regenerative microenvironments. These findings demonstrated the promise for the use of PAX7::GFP-sorted hPDMs on fibrin microfiber bundles and provided some insights for improving the cell–biomaterial system to stimulate more robust in vivo skeletal muscle regeneration. Full article

(This article belongs to the Special Issue Multifunctional Scaffolds for Musculoskeletal Regeneration)

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17 pages, 5946 KiB

Open AccessArticle

PPG2ABP: Translating Photoplethysmogram (PPG) Signals to Arterial Blood Pressure (ABP) Waveforms

by Nabil Ibtehaz, Sakib Mahmud, Muhammad E. H. Chowdhury, Amith Khandakar, Muhammad Salman Khan, Mohamed Arselene Ayari, Anas M. Tahir and M. Sohel Rahman

Bioengineering 2022, 9(11), 692; https://doi.org/10.3390/bioengineering9110692 - 15 Nov 2022

Cited by 50 | Viewed by 6392

Abstract

Cardiovascular diseases are one of the most severe causes of mortality, annually taking a heavy toll on lives worldwide. Continuous monitoring of blood pressure seems to be the most viable option, but this demands an invasive process, introducing several layers of complexities and [...] Read more.

Cardiovascular diseases are one of the most severe causes of mortality, annually taking a heavy toll on lives worldwide. Continuous monitoring of blood pressure seems to be the most viable option, but this demands an invasive process, introducing several layers of complexities and reliability concerns due to non-invasive techniques not being accurate. This motivates us to develop a method to estimate the continuous arterial blood pressure (ABP) waveform through a non-invasive approach using Photoplethysmogram (PPG) signals. We explore the advantage of deep learning, as it would free us from sticking to ideally shaped PPG signals only by making handcrafted feature computation irrelevant, which is a shortcoming of the existing approaches. Thus, we present PPG2ABP, a two-stage cascaded deep learning-based method that manages to estimate the continuous ABP waveform from the input PPG signal with a mean absolute error of 4.604 mmHg, preserving the shape, magnitude, and phase in unison. However, the more astounding success of PPG2ABP turns out to be that the computed values of Diastolic Blood Pressure (DBP), Mean Arterial Pressure (MAP), and Systolic Blood Pressure (SBP) from the estimated ABP waveform outperform the existing works under several metrics (mean absolute error of 3.449 ± 6.147 mmHg, 2.310 ± 4.437 mmHg, and 5.727 ± 9.162 mmHg, respectively), despite that PPG2ABP is not explicitly trained to do so. Notably, both for DBP and MAP, we achieve Grade A in the BHS (British Hypertension Society) Standard and satisfy the AAMI (Association for the Advancement of Medical Instrumentation) standard. Full article

(This article belongs to the Special Issue Advances of Biomedical Signal Processing)

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11 pages, 3087 KiB

Open AccessReview

Recent Advances of Calcium Carbonate Nanoparticles for Biomedical Applications

by Pengxuan Zhao, Yu Tian, Jia You, Xin Hu and Yani Liu

Bioengineering 2022, 9(11), 691; https://doi.org/10.3390/bioengineering9110691 - 15 Nov 2022

Cited by 29 | Viewed by 4985

Abstract

Calcium carbonate nanoparticles have been widely used in biomedicine due to their biocompatibility and biodegradability. Recently, calcium carbonate nanoparticles are largely integrated with imaging contrast and therapeutic agents for various imaging and therapeutic approaches. In this review, we first described the advantages and [...] Read more.

Calcium carbonate nanoparticles have been widely used in biomedicine due to their biocompatibility and biodegradability. Recently, calcium carbonate nanoparticles are largely integrated with imaging contrast and therapeutic agents for various imaging and therapeutic approaches. In this review, we first described the advantages and preparation methods of calcium carbonate nanoparticles, then the state-of-the-art progress of calcium carbonate nanoparticles in diagnosis, treatment and theranostics was summarized. Finally, we discussed the challenges and recommendations for future studies of the calcium carbonate nanoparticles. Full article

(This article belongs to the Special Issue Nanoparticles in Drug Delivery: Present and Future Trends)

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21 pages, 4136 KiB

Open AccessArticle

Diagnosis of Epilepsy with Functional Connectivity in EEG after a Suspected First Seizure

by João Matos, Guilherme Peralta, Jolan Heyse, Eric Menetre, Margitta Seeck and Pieter van Mierlo

Bioengineering 2022, 9(11), 690; https://doi.org/10.3390/bioengineering9110690 - 14 Nov 2022

Cited by 5 | Viewed by 2325

Abstract

Epilepsy is regarded as a structural and functional network disorder, affecting around 50 million people worldwide. A correct disease diagnosis can lead to quicker medical action, preventing adverse effects. This paper reports the design of a classifier for epilepsy diagnosis in patients after [...] Read more.

Epilepsy is regarded as a structural and functional network disorder, affecting around 50 million people worldwide. A correct disease diagnosis can lead to quicker medical action, preventing adverse effects. This paper reports the design of a classifier for epilepsy diagnosis in patients after a first ictal episode, using electroencephalogram (EEG) recordings. The dataset consists of resting-state EEG from 629 patients, of which 504 were retained for the study. The patient’s cohort exists out of 291 patients with epilepsy and 213 patients with other pathologies. The data were split into two sets: 80% training set and 20% test set. The extracted features from EEG included functional connectivity measures, graph measures, band powers and brain asymmetry ratios. Feature reduction was performed, and the models were trained using Machine Learning (ML) techniques. The models’ evaluation was performed with the area under the receiver operating characteristic curve (AUC). When focusing specifically on focal lesional epileptic patients, better results were obtained. This classification task was optimized using a 5-fold cross-validation, where SVM using PCA for feature reduction achieved an AUC of 0.730 ± 0.030. In the test set, the same model achieved 0.649 of AUC. The verified decrease is justified by the considerable diversity of pathologies in the cohort. An analysis of the selected features across tested models shows that functional connectivity and its graph measures have the most considerable predictive power, along with full-spectrum frequency-based features. To conclude, the proposed algorithms, with some refinement, can be of added value for doctors diagnosing epilepsy from EEG recordings after a suspected first seizure. Full article

(This article belongs to the Special Issue Recent Advance in Epilepsy and Brain Mapping)

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