Bioengineering

15 pages, 1792 KiB

Open AccessEditor’s ChoiceArticle

Prediction of Cognitive Load from Electroencephalography Signals Using Long Short-Term Memory Network

by Gilsang Yoo, Hyeoncheol Kim and Sungdae Hong

Bioengineering 2023, 10(3), 361; https://doi.org/10.3390/bioengineering10030361 - 15 Mar 2023

Cited by 11 | Viewed by 3355

In recent years, the development of adaptive models to tailor instructional content to learners by measuring their cognitive load has become a topic of active research. Brain fog, also known as confusion, is a common cause of poor performance, and real-time detection of [...] Read more.

In recent years, the development of adaptive models to tailor instructional content to learners by measuring their cognitive load has become a topic of active research. Brain fog, also known as confusion, is a common cause of poor performance, and real-time detection of confusion is a challenging and important task for applications in online education and driver fatigue detection. In this study, we propose a deep learning method for cognitive load recognition based on electroencephalography (EEG) signals using a long short-term memory network (LSTM) with an attention mechanism. We obtained EEG signal data from a database of brainwave information and associated data on mental load. We evaluated the performance of the proposed LSTM technique in comparison with random forest, Adaptive Boosting (AdaBoost), support vector machine, eXtreme Gradient Boosting (XGBoost), and artificial neural network models. The experimental results demonstrated that the proposed approach had the highest accuracy of 87.1% compared to those of other algorithms, including random forest (64%), AdaBoost (64.31%), support vector machine (60.9%), XGBoost (67.3%), and artificial neural network models (71.4%). The results of this study support the development of a personalized adaptive learning system designed to measure and actively respond to learners’ cognitive load in real time using wireless portable EEG systems. Full article

(This article belongs to the Special Issue Biomedical Application of Big Data and Artificial Intelligence)

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14 pages, 1546 KiB

Open AccessEditor’s ChoiceArticle

Visual Blood, Visualisation of Blood Gas Analysis in Virtual Reality, Leads to More Correct Diagnoses: A Computer-Based, Multicentre, Simulation Study

by Lisa Bergauer, Samira Akbas, Julia Braun, Michael T. Ganter, Patrick Meybohm, Sebastian Hottenrott, Kai Zacharowski, Florian J. Raimann, Eva Rivas, Manuel López-Baamonde, Donat R. Spahn, Christoph B. Noethiger, David W. Tscholl and Tadzio R. Roche

Bioengineering 2023, 10(3), 340; https://doi.org/10.3390/bioengineering10030340 - 8 Mar 2023

Cited by 3 | Viewed by 2304

Abstract

Interpreting blood gas analysis results can be challenging for the clinician, especially in stressful situations under time pressure. To foster fast and correct interpretation of blood gas results, we developed Visual Blood. This computer-based, multicentre, noninferiority study compared Visual Blood and conventional arterial [...] Read more.

Interpreting blood gas analysis results can be challenging for the clinician, especially in stressful situations under time pressure. To foster fast and correct interpretation of blood gas results, we developed Visual Blood. This computer-based, multicentre, noninferiority study compared Visual Blood and conventional arterial blood gas (ABG) printouts. We presented six scenarios to anaesthesiologists, once with Visual Blood and once with the conventional ABG printout. The primary outcome was ABG parameter perception. The secondary outcomes included correct clinical diagnoses, perceived diagnostic confidence, and perceived workload. To analyse the results, we used mixed models and matched odds ratios. Analysing 300 within-subject cases, we showed noninferiority of Visual Blood compared to ABG printouts concerning the rate of correctly perceived ABG parameters (rate ratio, 0.96; 95% CI, 0.92–1.00; p = 0.06). Additionally, the study revealed two times higher odds of making the correct clinical diagnosis using Visual Blood (OR, 2.16; 95% CI, 1.42–3.29; p < 0.001) than using ABG printouts. There was no or, respectively, weak evidence for a difference in diagnostic confidence (OR, 0.84; 95% CI, 0.58–1.21; p = 0.34) and perceived workload (Coefficient, 2.44; 95% CI, −0.09–4.98; p = 0.06). This study showed that participants did not perceive the ABG parameters better, but using Visual Blood resulted in more correct clinical diagnoses than using conventional ABG printouts. This suggests that Visual Blood allows for a higher level of situation awareness beyond individual parameters’ perception. However, the study also highlighted the limitations of today’s virtual reality headsets and Visual Blood. Full article

(This article belongs to the Special Issue Artificial Intelligence and Optimization Methods in Biomedical Engineering)

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18 pages, 3863 KiB

Open AccessEditor’s ChoiceArticle

Exploring the Role of Visual Guidance in Motor Imagery-Based Brain-Computer Interface: An EEG Microstate-Specific Functional Connectivity Study

by Tianjun Wang, Yun-Hsuan Chen and Mohamad Sawan

Bioengineering 2023, 10(3), 281; https://doi.org/10.3390/bioengineering10030281 - 21 Feb 2023

Cited by 4 | Viewed by 2744

Abstract

Motor imagery-based brain–computer interfaces (BCI) have been widely recognized as beneficial tools for rehabilitation applications. Moreover, visually guided motor imagery was introduced to improve the rehabilitation impact. However, the reported results to support these techniques remain unsatisfactory. Electroencephalography (EEG) signals can be represented [...] Read more.

Motor imagery-based brain–computer interfaces (BCI) have been widely recognized as beneficial tools for rehabilitation applications. Moreover, visually guided motor imagery was introduced to improve the rehabilitation impact. However, the reported results to support these techniques remain unsatisfactory. Electroencephalography (EEG) signals can be represented by a sequence of a limited number of topographies (microstates). To explore the dynamic brain activation patterns, we conducted EEG microstate and microstate-specific functional connectivity analyses on EEG data under motor imagery (MI), motor execution (ME), and guided MI (GMI) conditions. By comparing sixteen microstate parameters, the brain activation patterns induced by GMI show more similarities to ME than MI from a microstate perspective. The mean duration and duration of microstate four are proposed as biomarkers to evaluate motor condition. A support vector machine (SVM) classifier trained with microstate parameters achieved average accuracies of 80.27% and 66.30% for ME versus MI and GMI classification, respectively. Further, functional connectivity patterns showed a strong relationship with microstates. Key node analysis shows clear switching of key node distribution between brain areas among different microstates. The neural mechanism of the switching pattern is discussed. While microstate analysis indicates similar brain dynamics between GMI and ME, graph theory-based microstate-specific functional connectivity analysis implies that visual guidance may reduce the functional integration of the brain network during MI. Thus, we proposed that combined MI and GMI for BCI can improve neurorehabilitation effects. The present findings provide insights for understanding the neural mechanism of microstates, the role of visual guidance in MI tasks, and the experimental basis for developing new BCI-aided rehabilitation systems. Full article

(This article belongs to the Special Issue Data Processing and Machine Learning for Assistive and Rehabilitation Technologies)

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21 pages, 6713 KiB

Open AccessEditor’s ChoiceArticle

Multilayer In Vitro Human Skin Tissue Platforms for Quantitative Burn Injury Investigation

by Sean Brocklehurst, Neda Ghousifam, Kameel Zuniga, Danielle Stolley and Marissa Nichole Rylander

Bioengineering 2023, 10(2), 265; https://doi.org/10.3390/bioengineering10020265 - 17 Feb 2023

Cited by 3 | Viewed by 2407

Abstract

This study presents a multilayer in vitro human skin platform to quantitatively relate predicted spatial time–temperature history with measured tissue injury response. This information is needed to elucidate high-temperature, short-duration burn injury kinetics and enables determination of relevant input parameters for computational models [...] Read more.

This study presents a multilayer in vitro human skin platform to quantitatively relate predicted spatial time–temperature history with measured tissue injury response. This information is needed to elucidate high-temperature, short-duration burn injury kinetics and enables determination of relevant input parameters for computational models to facilitate treatment planning. Multilayer in vitro skin platforms were constructed using human dermal keratinocytes and fibroblasts embedded in collagen I hydrogels. After three seconds of contact with a 50–100 °C burn tip, ablation, cell death, apoptosis, and HSP70 expression were spatially measured using immunofluorescence confocal microscopy. Finite element modeling was performed using the measured thermal characteristics of skin platforms to determine the temperature distribution within platforms over time. The process coefficients for the Arrhenius thermal injury model describing tissue ablation and cell death were determined such that the predictions calculated from the time–temperature histories fit the experimental burn results. The activation energy for thermal collagen ablation and cell death was found to be significantly lower for short-duration, high-temperature burns than those found for long-duration, low-temperature burns. Analysis of results suggests that different injury mechanisms dominate at higher temperatures, necessitating burn research in the temperature ranges of interest and demonstrating the practicality of the proposed skin platform for this purpose. Full article

(This article belongs to the Section Nanobiotechnology and Biofabrication)

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18 pages, 10407 KiB

Open AccessEditor’s ChoiceArticle

Characterization of Perinatal Stem Cell Spheroids for the Development of Cell Therapy Strategy

by Francesca Paris, Pasquale Marrazzo, Valeria Pizzuti, Cosetta Marchionni, Maura Rossi, Martina Michelotti, Biljana Petrovic, Elisabetta Ciani, Giuliana Simonazzi, Andrea Pession, Laura Bonsi and Francesco Alviano

Bioengineering 2023, 10(2), 189; https://doi.org/10.3390/bioengineering10020189 - 2 Feb 2023

Cited by 7 | Viewed by 3452

Abstract

Type 1 diabetes mellitus (T1DM) is a complex metabolic disease characterized by a massive loss of insulin-producing cells due to an autoimmune reaction. Currently, daily subcutaneous administration of exogenous insulin is the only effective treatment. Therefore, in recent years considerable interest has been [...] Read more.

Type 1 diabetes mellitus (T1DM) is a complex metabolic disease characterized by a massive loss of insulin-producing cells due to an autoimmune reaction. Currently, daily subcutaneous administration of exogenous insulin is the only effective treatment. Therefore, in recent years considerable interest has been given to stem cell therapy and in particular to the use of three-dimensional (3D) cell cultures to better reproduce in vivo conditions. The goal of this study is to provide a reliable cellular model that could be investigated for regenerative medicine applications for the replacement of insulin-producing cells in T1DM. To pursue this aim we create a co-culture spheroid of amniotic epithelial cells (AECs) and Wharton’s jelly mesenchymal stromal cells (WJ-MSCs) in a one-to-one ratio. The resulting co-culture spheroids were analyzed for viability, extracellular matrix production, and hypoxic state in both early- and long-term cultures. Our results suggest that co-culture spheroids are stable in long-term culture and are still viable with a consistent extracellular matrix production evaluated with immunofluorescence staining. These findings suggest that this co-culture may potentially be differentiated into endo-pancreatic cells for regenerative medicine applications in T1DM. Full article

(This article belongs to the Special Issue 3D Cell Culture in Disease Modeling and Tissue Regeneration)

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14 pages, 1580 KiB

Open AccessEditor’s ChoiceArticle

Contactless Camera-Based Sleep Staging: The HealthBed Study

by Fokke B. van Meulen, Angela Grassi, Leonie van den Heuvel, Sebastiaan Overeem, Merel M. van Gilst, Johannes P. van Dijk, Henning Maass, Mark J. H. van Gastel and Pedro Fonseca

Bioengineering 2023, 10(1), 109; https://doi.org/10.3390/bioengineering10010109 - 12 Jan 2023

Cited by 13 | Viewed by 2907

Abstract

Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances in camera sensor technology and data analysis techniques enable contactless monitoring of heart rate variability (HRV). In turn, this may allow remote assessment of sleep stages, as different [...] Read more.

Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances in camera sensor technology and data analysis techniques enable contactless monitoring of heart rate variability (HRV). In turn, this may allow remote assessment of sleep stages, as different HRV metrics indirectly reflect the expression of sleep stages. We evaluated a camera-based remote photoplethysmography (PPG) setup to perform automated classification of sleep stages in near darkness. Based on the contactless measurement of pulse rate variability, we use a previously developed HRV-based algorithm for 3 and 4-class sleep stage classification. Performance was evaluated on data of 46 healthy participants obtained from simultaneous overnight recording of PSG and camera-based remote PPG. To validate the results and for benchmarking purposes, the same algorithm was used to classify sleep stages based on the corresponding ECG data. Compared to manually scored PSG, the remote PPG-based algorithm achieved moderate agreement on both 3 class (Wake–N1/N2/N3–REM) and 4 class (Wake–N1/N2–N3–REM) classification, with average

κ

of 0.58 and 0.49 and accuracy of 81% and 68%, respectively. This is in range with other performance metrics reported on sensing technologies for wearable sleep staging, showing the potential of video-based non-contact sleep staging. Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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16 pages, 8893 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Detection of Bacteria-Induced Early-Stage Dental Caries Using Three-Dimensional Mid-Infrared Thermophotonic Imaging

by Robert Welch, Koneswaran Sivagurunathan, Pantea Tavakolian, Kimberly Ngai, Bo Huang, Stephen Abrams, Yoav Finer and Andreas Mandelis

Bioengineering 2023, 10(1), 112; https://doi.org/10.3390/bioengineering10010112 - 12 Jan 2023

Cited by 3 | Viewed by 2928

Abstract

Tooth decay, or dental caries, is a widespread and costly disease that is reversible when detected early in its formation. Current dental caries diagnostic methods including X-ray imaging and intraoral examination lack the sensitivity and specificity required to routinely detect caries early in [...] Read more.

Tooth decay, or dental caries, is a widespread and costly disease that is reversible when detected early in its formation. Current dental caries diagnostic methods including X-ray imaging and intraoral examination lack the sensitivity and specificity required to routinely detect caries early in its formation. Thermophotonic imaging presents itself as a highly sensitive and non-ionizing solution, making it suitable for the frequent monitoring of caries progression. Here, we utilized a treatment protocol to produce bacteria-induced caries lesions. The lesions were imaged using two related three-dimensional photothermal imaging modalities: truncated correlation photothermal coherence tomography (TC-PCT) and its enhanced modification eTC-PCT. In addition, micro-computed tomography (μ-CT) and visual inspection by a clinical dentist were used to validate and quantify the severities of the lesions. The observational findings demonstrate the high sensitivity and depth profiling capabilities of the thermophotonic modalities, showcasing their potential use as a non-ionizing clinical tool for the early detection of dental caries. Full article

(This article belongs to the Special Issue Novel Approaches for the Treatment of Maxillofacial Defects: From Bone to Skin Regeneration)

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22 pages, 3184 KiB

Open AccessEditor’s ChoiceArticle

A Two-Compartment Fermentation System to Quantify Strain-Specific Interactions in Microbial Co-Cultures

by Andreas Ulmer, Stefan Veit, Florian Erdemann, Andreas Freund, Maren Loesch, Attila Teleki, Ahmad A. Zeidan and Ralf Takors

Bioengineering 2023, 10(1), 103; https://doi.org/10.3390/bioengineering10010103 - 11 Jan 2023

Cited by 2 | Viewed by 2565

Abstract

To fulfil the growing interest in investigating microbial interactions in co-cultures, a novel two-compartment bioreactor system was developed, characterised, and implemented. The system allowed for the exchange of amino acids and peptides via a polyethersulfone membrane that retained biomass. Further system characterisation revealed [...] Read more.

To fulfil the growing interest in investigating microbial interactions in co-cultures, a novel two-compartment bioreactor system was developed, characterised, and implemented. The system allowed for the exchange of amino acids and peptides via a polyethersulfone membrane that retained biomass. Further system characterisation revealed a Bodenstein number of 18, which hints at backmixing. Together with other physical settings, the existence of unwanted inner-compartment substrate gradients could be ruled out. Furthermore, the study of Damkoehler numbers indicated that a proper metabolite supply between compartments was enabled. Implementing the two-compartment system (2cs) for growing Streptococcus thermophilus and Lactobacillus delbrueckii subs. bulgaricus, which are microorganisms commonly used in yogurt starter cultures, revealed only a small variance between the one-compartment and two-compartment approaches. The 2cs enabled the quantification of the strain-specific production and consumption rates of amino acids in an interacting S. thermophilus–L. bulgaricus co-culture. Therefore, comparisons between mono- and co-culture performance could be achieved. Both species produce and release amino acids. Only alanine was produced de novo from glucose through potential transaminase activity by L. bulgaricus and consumed by S. thermophilus. Arginine availability in peptides was limited to S. thermophilus’ growth, indicating active biosynthesis and dependency on the proteolytic activity of L. bulgaricus. The application of the 2cs not only opens the door for the quantification of exchange fluxes between microbes but also enables continuous production modes, for example, for targeted evolution studies. Full article

(This article belongs to the Topic Bioreactors: Control, Optimization and Applications)
(This article belongs to the Section Biochemical Engineering)

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13 pages, 5187 KiB

Open AccessEditor’s ChoiceArticle

Portable Iontophoresis Device for Efficient Drug Delivery

by Moonjeong Bok, Young Il Kwon, Zheng Min Huang and Eunju Lim

Bioengineering 2023, 10(1), 88; https://doi.org/10.3390/bioengineering10010088 - 9 Jan 2023

Cited by 1 | Viewed by 3612

Abstract

The timely delivery of drugs to specific locations in the body is imperative to ensure the efficacy of treatment. This study introduces a portable facial device that can deliver drugs efficiently using iontophoresis. Two types of power supplies—direct current and pulse ionization supplies—were [...] Read more.

The timely delivery of drugs to specific locations in the body is imperative to ensure the efficacy of treatment. This study introduces a portable facial device that can deliver drugs efficiently using iontophoresis. Two types of power supplies—direct current and pulse ionization supplies—were manufactured by injection molding. Electrical stimulation elements, which contained Ag metal wires, were woven into facial mask packs. The diffusion phenomenon in the skin and iontophoresis were numerically modeled. Injection molding was simulated before the device was manufactured. Analysis using rhodamine B demonstrated a remarkable increase in the moisture content of the skin and effective absorption of the drug under an applied electric field upon the application of iontophoresis. The proposed concept and design constitute a new method of achieving effective drug absorption with wearable devices. Full article

(This article belongs to the Special Issue Drug Delivery Systems, What's New?)

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25 pages, 5943 KiB

Open AccessEditor’s ChoiceArticle

Attenuation of SCI-Induced Hypersensitivity by Intensive Locomotor Training and Recombinant GABAergic Cells

by Stanislava Jergova, Elizabeth A. Dugan and Jacqueline Sagen

Bioengineering 2023, 10(1), 84; https://doi.org/10.3390/bioengineering10010084 - 9 Jan 2023

Viewed by 1860

Abstract

The underlying mechanisms of spinal cord injury (SCI)-induced chronic pain involve dysfunctional GABAergic signaling and enhanced NMDA signaling. Our previous studies showed that SCI hypersensitivity in rats can be attenuated by recombinant rat GABAergic cells releasing NMDA blocker serine-histogranin (SHG) and by intensive [...] Read more.

The underlying mechanisms of spinal cord injury (SCI)-induced chronic pain involve dysfunctional GABAergic signaling and enhanced NMDA signaling. Our previous studies showed that SCI hypersensitivity in rats can be attenuated by recombinant rat GABAergic cells releasing NMDA blocker serine-histogranin (SHG) and by intensive locomotor training (ILT). The current study combines these approaches and evaluates their analgesic effects on a model of SCI pain in rats. Cells were grafted into the spinal cord at 4 weeks post-SCI to target the chronic pain, and ILT was initiated 5 weeks post-SCI. The hypersensitivity was evaluated weekly, which was followed by histological and biochemical assays. Prolonged effects of the treatment were evaluated in subgroups of animals after we discontinued ILT. The results show attenuation of tactile, heat and cold hypersensitivity in all of the treated animals and reduced levels of proinflammatory cytokines IL1β and TNFα in the spinal tissue and CSF. Animals with recombinant grafts and ILT showed the preservation of analgesic effects even during sedentary periods when the ILT was discontinued. Retraining helped to re-establish the effect of long-term training in all of the groups, with the greatest impact being in animals with recombinant grafts. These findings suggest that intermittent training in combination with cell therapy might be an efficient approach to manage chronic pain in SCI patients. Full article

(This article belongs to the Special Issue Regeneration and Repair in the Central Nervous System)

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17 pages, 2610 KiB

Open AccessEditor’s ChoiceArticle

Unsupervised Learning-Based Non-Invasive Fetal ECG Muti-Level Signal Quality Assessment

by Xintong Shi, Kohei Yamamoto, Tomoaki Ohtsuki, Yutaka Matsui and Kazunari Owada

Bioengineering 2023, 10(1), 66; https://doi.org/10.3390/bioengineering10010066 - 4 Jan 2023

Cited by 3 | Viewed by 2651

Abstract

Objective: To monitor fetal health and growth, fetal heart rate is a critical indicator. The non-invasive fetal electrocardiogram is a widely employed measurement for fetal heart rate estimation, which is extracted from the electrodes placed on the surface of the maternal abdomen. The [...] Read more.

Objective: To monitor fetal health and growth, fetal heart rate is a critical indicator. The non-invasive fetal electrocardiogram is a widely employed measurement for fetal heart rate estimation, which is extracted from the electrodes placed on the surface of the maternal abdomen. The qualities of the fetal ECG recordings, however, are frequently affected by the noises from various interference sources. In general, the fetal heart rate estimates are unreliable when low-quality fetal ECG signals are used for fetal heart rate estimation, which makes accurate fetal heart rate estimation a challenging task. So, the signal quality assessment for the fetal ECG records is an essential step before fetal heart rate estimation. In other words, some low-quality fetal ECG signal segments are supposed to be detected and removed by utilizing signal quality assessment, so as to improve the accuracy of fetal heart rate estimation. A few supervised learning-based fetal ECG signal quality assessment approaches have been introduced and shown to accurately classify high- and low-quality fetal ECG signal segments, but large fetal ECG datasets with quality annotation are required in these methods. Yet, the labeled fetal ECG datasets are limited. Proposed methods: An unsupervised learning-based multi-level fetal ECG signal quality assessment approach is proposed in this paper for identifying three levels of fetal ECG signal quality. We extracted some features associated with signal quality, including entropy-based features, statistical features, and ECG signal quality indices. Additionally, an autoencoder-based feature is calculated, which is related to the reconstruction error of the spectrograms generated from fetal ECG signal segments. The high-, medium-, and low-quality fetal ECG signal segments are classified by inputting these features into a self-organizing map. Main results: The experimental results showed that our proposal achieved a weighted average F1-score of 90% in three-level fetal ECG signal quality classification. Moreover, with the acceptable removal of detected low-quality signal segments, the errors of fetal heart rate estimation were reduced to a certain extent. Full article

(This article belongs to the Special Issue Monitoring and Analysis of Human Biosignals)

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14 pages, 14852 KiB

Open AccessEditor’s ChoiceArticle

Optimization Design of the Inner Structure for a Bioinspired Heel Pad with Distinct Cushioning Property

by Jianqiao Jin, Kunyang Wang, Lei Ren, Zhihui Qian, Xuewei Lu, Wei Liang, Xiaohan Xu, Shun Zhao, Di Zhao, Xu Wang and Luquan Ren

Bioengineering 2023, 10(1), 49; https://doi.org/10.3390/bioengineering10010049 - 30 Dec 2022

Cited by 3 | Viewed by 2636

Abstract

In the existing research on prosthetic footplates, rehabilitation insoles, and robot feet, the cushioning parts are basically based on simple mechanisms and elastic pads. Most of them are unable to provide adequate impact resistance especially during contact with the ground. This paper developed [...] Read more.

In the existing research on prosthetic footplates, rehabilitation insoles, and robot feet, the cushioning parts are basically based on simple mechanisms and elastic pads. Most of them are unable to provide adequate impact resistance especially during contact with the ground. This paper developed a bioinspired heel pad by optimizing the inner structures inspired from human heel pad which has great cushioning performance. The distinct structures of the human heel pad were determined through magnetic resonance imaging (MRI) technology and related literatures. Five-layer pads with and without inner structures by using two materials (soft rubber and resin) were obtained, resulting in four bionic heel pads. Three finite element simulations (static, impact, and walking) were conducted to compare the cushioning effects in terms of deformations, ground reactions, and principal stress. The optimal pad with bionic structures and soft rubber material reduced 28.0% peak vertical ground reaction force (GRF) during walking compared with the unstructured resin pad. Human walking tests by a healthy subject wearing the 3D printed bionic pads also showed similar findings, with an almost 20% decrease in peak vertical GRF at normal speed. The soft rubber heel pad with bionic structures has the best cushioning performance, while the unstructured resin pad depicts the poorest. This study proves that with proper design of the inner structures and materials, the bionic pads will demonstrate distinct cushioning properties, which could be applied to the engineering fields, including lower limb prosthesis, robotics, and rehabilitations. Full article

(This article belongs to the Special Issue Biomedical Design and Manufacturing)

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10 pages, 1547 KiB

Open AccessEditor’s ChoiceArticle

Making Visible the Invisible: Automatically Measured Global and Regional Brain Volume Is Associated with Cognitive Impairment and Fatigue in Multiple Sclerosis

by Stefano Ziccardi, Francesca Benedetta Pizzini, Maddalena Guandalini, Agnese Tamanti, Cecilia Cristofori and Massimiliano Calabrese

Bioengineering 2023, 10(1), 41; https://doi.org/10.3390/bioengineering10010041 - 29 Dec 2022

Cited by 6 | Viewed by 2279

Abstract

In multiple sclerosis (MS), the transition from relapsing-remitting to the secondary-progressive phase is characterized by a progression independent of relapse activity (PIRA), resulting in physical disability accumulation and invisible symptoms, i.e., fatigue and cognitive impairment (CI). These symptoms are related to neurodegenerative processes [...] Read more.

In multiple sclerosis (MS), the transition from relapsing-remitting to the secondary-progressive phase is characterized by a progression independent of relapse activity (PIRA), resulting in physical disability accumulation and invisible symptoms, i.e., fatigue and cognitive impairment (CI). These symptoms are related to neurodegenerative processes and have been correlated with MRI measures of brain atrophy only at a group level; however, the application in clinical practice of atrophy-based measurements for single-patient evaluation is yet to be fully investigated. In the present study, we aimed to evaluate the association between brain atrophy, measured with easy-to-use automatic software, and the “invisible” MS symptoms of cognition and fatigue. A total of 69 MS patients were included in the study; cognitive impairment and fatigue (FSS) (in addition to neurological disability, EDSS) were assessed and correlated with brain volumes calculated using the automated software QyScore^® which is validated for single-patient use in the clinical setting. Results showed that the cognitive status was accurately reflected by measures of atrophy, with a sensitivity of up to 90%. CI patients showed a lower volume compared to cognitively normal patients in the whole brain (p = 0.017), gray matter (p = 0.042), insula (p = 0.035), cerebellum (p = 0.008), and limbic lobe (p = 0.049). FSS was associated with temporal lobe (r = −0.37, p = 0.013) and insular (r = −0.36, p = 0.019) volumes. The volumes of the same regions were also associated with EDSS. The global/regional atrophy results, assessed with automatic and easy-to-use software, correlated with cognitive and fatigue symptoms, thus supporting the clinical application in routine patient management. Full article

(This article belongs to the Special Issue Cognitive Impairment in Multiple Sclerosis)

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13 pages, 4266 KiB

Open AccessEditor’s ChoiceArticle

Hand Gesture Signatures Acquisition and Processing by Means of a Novel Ultrasound System

by Stefano Franceschini, Michele Ambrosanio, Vito Pascazio and Fabio Baselice

Bioengineering 2023, 10(1), 36; https://doi.org/10.3390/bioengineering10010036 - 28 Dec 2022

Cited by 11 | Viewed by 2726

Abstract

Hand gestures represent a natural way to express concepts and emotions which are peculiar to each culture. Several studies exploit biometric traits, such as fingerprint, iris or face for subject identification purposes. Within this paper, a novel ultrasound system for person identification that [...] Read more.

Hand gestures represent a natural way to express concepts and emotions which are peculiar to each culture. Several studies exploit biometric traits, such as fingerprint, iris or face for subject identification purposes. Within this paper, a novel ultrasound system for person identification that exploits hand gestures is presented. The system works as a sonar, measuring the ultrasonic pressure waves scattered by the subject’s hand, and analysing its Doppler information. Further, several transformations for obtaining time/frequency representations of the acquired signal are computed and a deep learning detector is implemented. The proposed system is cheap, reliable, contactless and can be easily integrated with other personal identification approaches allowing different security levels. The performances are evaluated via experimental tests carried out on a group of 25 volunteers. Results are encouraging, showing the promising potential of the system. Full article

(This article belongs to the Section Biosignal Processing)

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18 pages, 5890 KiB

Open AccessEditor’s ChoiceArticle

The Effect of Tissue Stromal Vascular Fraction as Compared to Cellular Stromal Vascular Fraction to Treat Anal Sphincter Incontinence

by Wenbin Chen, Zijian He, Shuyu Li, Zixin Wu, Jin Tan, Weifeng Yang, Guanwei Li, Xiaoling Pan, Yuying Liu, Feng-Juan Lyu and Wanglin Li

Bioengineering 2023, 10(1), 32; https://doi.org/10.3390/bioengineering10010032 - 26 Dec 2022

Viewed by 2100

Abstract

Background: The long-term prognosis of current treatments for anal sphincter incontinence (ASI) is poor. Here, we explored the efficacy of tissue adipose stromal vascular fraction SVF (tSVF) on ASI and compared it to that of cellular SVF (cSVF). We then investigated possible mechanisms. [...] Read more.

Background: The long-term prognosis of current treatments for anal sphincter incontinence (ASI) is poor. Here, we explored the efficacy of tissue adipose stromal vascular fraction SVF (tSVF) on ASI and compared it to that of cellular SVF (cSVF). We then investigated possible mechanisms. Methods: Rat cSVF and tSVF were isolated and labeled with DIL. One day after modeling, three groups received phosphate-buffered saline (PBS), cSVF, tSVF, respectively. The control group received nil modeling nor any treatments. The effect was assessed by function test for anal pressure and electromyography, and staining for fiber content, proliferation and differentiation at day 5 and day 10. Results: cSVF injection resulted in faster healing than tSVF. The cSVF group showed significant improvement on anal pressure on day 10. For the electromyography test, cSVF showed significant improvement for the frequencies on day 10, and for the peak values on both time points, while tSVF showed significant improvement for the peak values on day 10. The two SVF both alleviated fibrosis. Immunofluorescence tracing identified differentiation of some injected cells towards myosatellite cells and smooth muscle cells in both SVF groups. For all the tests, the tSVF group tends to have similar or lower effects than the cSVF group with no significant difference. Conclusion: cSVF and tSVF are both safe and effective in treating ASI, while the effect of cSVF is slighter higher than tSVF. Full article

(This article belongs to the Special Issue Stem Cell-Based Technology for Personalized Medicine Solutions)

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28 pages, 3743 KiB

Open AccessEditor’s ChoiceReview

Advancement in the Cuffless and Noninvasive Measurement of Blood Pressure: A Review of the Literature and Open Challenges

by Mohammad Mahbubur Rahman Khan Mamun and Ahmed Sherif

Bioengineering 2023, 10(1), 27; https://doi.org/10.3390/bioengineering10010027 - 24 Dec 2022

Cited by 12 | Viewed by 5117

Abstract

Hypertension is a chronic condition that is one of the prominent reasons behind cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the deterioration in a health condition could even result in mortality. If it can be detected early, with proper [...] Read more.

Hypertension is a chronic condition that is one of the prominent reasons behind cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the deterioration in a health condition could even result in mortality. If it can be detected early, with proper treatment, undesirable outcomes can be avoided. Until now, the gold standard is the invasive way of measuring blood pressure (BP) using a catheter. Additionally, the cuff-based and noninvasive methods are too cumbersome or inconvenient for frequent measurement of BP. With the advancement of sensor technology, signal processing techniques, and machine learning algorithms, researchers are trying to find the perfect relationships between biomedical signals and changes in BP. This paper is a literature review of the studies conducted on the cuffless noninvasive measurement of BP using biomedical signals. Relevant articles were selected using specific criteria, then traditional techniques for BP measurement were discussed along with a motivation for cuffless measurement use of biomedical signals and machine learning algorithms. The review focused on the progression of different noninvasive cuffless techniques rather than comparing performance among different studies. The literature survey concluded that the use of deep learning proved to be the most accurate among all the cuffless measurement techniques. On the other side, this accuracy has several disadvantages, such as lack of interpretability, computationally extensive, standard validation protocol, and lack of collaboration with health professionals. Additionally, the continuing work by researchers is progressing with a potential solution for these challenges. Finally, future research directions have been provided to encounter the challenges. Full article

(This article belongs to the Special Issue Monitoring and Analysis of Human Biosignals)

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19 pages, 4297 KiB

Open AccessEditor’s ChoiceArticle

Clinical Application of Bioresorbable, Synthetic, Electrospun Matrix in Wound Healing

by Matthew MacEwan, Lily Jeng, Tamás Kovács and Emily Sallade

Bioengineering 2023, 10(1), 9; https://doi.org/10.3390/bioengineering10010009 - 21 Dec 2022

Cited by 16 | Viewed by 2484

Abstract

Electrospun polymeric matrices have long been investigated as constructs for use in regenerative medicine, yet relatively few have been commercialized for human clinical use. In 2017, a novel electrospun matrix, composed of two synthetic biocompatible polymers, polyglactin 910 (PLGA 10:90) and polydioxanone (PDO) [...] Read more.

Electrospun polymeric matrices have long been investigated as constructs for use in regenerative medicine, yet relatively few have been commercialized for human clinical use. In 2017, a novel electrospun matrix, composed of two synthetic biocompatible polymers, polyglactin 910 (PLGA 10:90) and polydioxanone (PDO) of varying pore and fiber sizes (i.e., hybrid-scale) was developed and cleared by the FDA for human clinical use. The present review aims to explain the mechanism of action and review the preclinical and clinical results to summarize the efficacy of the matrix across multiple use cases within the wound care setting, including an assessment of over 150 wounds of varying etiologies treated with the synthetic matrix. Clinical data demonstrated effective use of the synthetic hybrid-scale fiber matrix across a variety of wound etiologies, including diabetic foot and venous leg ulcers, pressure ulcers, burns, and surgical wounds. This review represents a comprehensive clinical demonstration of a synthetic, electrospun, hybrid-scale matrix and illustrates its value and versatility across multiple wound etiologies. Full article

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

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15 pages, 3661 KiB

Open AccessEditor’s ChoiceArticle

Deep Learning Model for Computer-Aided Diagnosis of Urolithiasis Detection from Kidney–Ureter–Bladder Images

by Yi-Yang Liu, Zih-Hao Huang and Ko-Wei Huang

Bioengineering 2022, 9(12), 811; https://doi.org/10.3390/bioengineering9120811 - 16 Dec 2022

Cited by 7 | Viewed by 3881

Abstract

Kidney–ureter–bladder (KUB) imaging is a radiological examination with a low cost, low radiation, and convenience. Although emergency room clinicians can arrange KUB images easily as a first-line examination for patients with suspicious urolithiasis, interpreting the KUB images correctly is difficult for inexperienced clinicians. [...] Read more.

Kidney–ureter–bladder (KUB) imaging is a radiological examination with a low cost, low radiation, and convenience. Although emergency room clinicians can arrange KUB images easily as a first-line examination for patients with suspicious urolithiasis, interpreting the KUB images correctly is difficult for inexperienced clinicians. Obtaining a formal radiology report immediately after a KUB imaging examination can also be challenging. Recently, artificial-intelligence-based computer-aided diagnosis (CAD) systems have been developed to help clinicians who are not experts make correct diagnoses for further treatment more effectively. Therefore, in this study, we proposed a CAD system for KUB imaging based on a deep learning model designed to help first-line emergency room clinicians diagnose urolithiasis accurately. A total of 355 KUB images were retrospectively collected from 104 patients who were diagnosed with urolithiasis at Kaohsiung Chang Gung Memorial Hospital. Then, we trained a deep learning model with a ResNet architecture to classify KUB images in terms of the presence or absence of kidney stones with this dataset of pre-processed images. Finally, we tuned the parameters and tested the model experimentally. The results show that the accuracy, sensitivity, specificity, and F1-measure of the model were 0.977, 0.953, 1, and 0.976 on the validation set and 0.982, 0.964, 1, and 0.982 on the testing set, respectively. Moreover, the results demonstrate that the proposed model performed well compared to the existing CNN-based methods and was able to detect urolithiasis in KUB images successfully. We expect the proposed approach to help emergency room clinicians make accurate diagnoses and reduce unnecessary radiation exposure from computed tomography (CT) scans, along with the associated medical costs. Full article

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

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23 pages, 7494 KiB

Open AccessEditor’s ChoiceArticle

Hypothermic Preservation of Adipose-Derived Mesenchymal Stromal Cells as a Viable Solution for the Storage and Distribution of Cell Therapy Products

by André Branco, Ana L. Tiago, Paula Laranjeira, Maria C. Carreira, João C. Milhano, Francisco dos Santos, Joaquim M. S. Cabral, Artur Paiva, Cláudia L. da Silva and Ana Fernandes-Platzgummer

Bioengineering 2022, 9(12), 805; https://doi.org/10.3390/bioengineering9120805 - 14 Dec 2022

Cited by 4 | Viewed by 2795

Abstract

Cell and gene therapies (CGT) have reached new therapeutic targets but have noticeably high prices. Solutions to reduce production costs might be found in CGT storage and transportation since they typically involve cryopreservation, which is a heavily burdened process. Encapsulation at hypothermic temperatures [...] Read more.

Cell and gene therapies (CGT) have reached new therapeutic targets but have noticeably high prices. Solutions to reduce production costs might be found in CGT storage and transportation since they typically involve cryopreservation, which is a heavily burdened process. Encapsulation at hypothermic temperatures (e.g., 2–8 °C) could be a feasible alternative. Adipose tissue-derived mesenchymal stromal cells (MSC(AT)) expanded using fetal bovine serum (FBS)- (MSC-FBS) or human platelet lysate (HPL)-supplemented mediums (MSC-HPL) were encapsulated in alginate beads for 30 min, 5 days, and 12 days. After bead release, cell recovery and viability were determined to assess encapsulation performance. MSC identity was verified by flow cytometry, and a set of assays was performed to evaluate functionality. MSC(AT) were able to survive encapsulated for a standard transportation period of 5 days, with recovery values of 56 ± 5% for MSC-FBS and 77 ± 6% for MSC-HPL (which is a negligible drop compared to earlier timepoints). Importantly, MSC function did not suffer from encapsulation, with recovered cells showing robust differentiation potential, expression of immunomodulatory molecules, and hematopoietic support capacity. MSC(AT) encapsulation was proven possible for a remarkable 12 day period. There is currently no solution to completely replace cryopreservation in CGT logistics and supply chain, although encapsulation has shown potential to act as a serious competitor. Full article

(This article belongs to the Special Issue Mesenchymal Stem Cells in Regenerative Medicine)

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15 pages, 3024 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of AMG510 Therapy on KRAS-Mutant Non–Small Cell Lung Cancer and Colorectal Cancer Cell Using a 3D Invasive Tumor Spheroid System under Normoxia and Hypoxia

by Meng Huang, Wei Hou, Jing Zhang, Menglan Li, Zilin Zhang, Xiaoran Li, Zaozao Chen, Cailian Wang and Lihua Yang

Bioengineering 2022, 9(12), 792; https://doi.org/10.3390/bioengineering9120792 - 12 Dec 2022

Cited by 4 | Viewed by 2553

Abstract

A 3D tumor spheroid has been increasingly applied in pharmaceutical development for its simulation of the tumor structure and microenvironment. The embedded-culture of a tumor spheroid within a hydrogel microenvironment could help to improve the mimicking of in vivo cell growth and the [...] Read more.

A 3D tumor spheroid has been increasingly applied in pharmaceutical development for its simulation of the tumor structure and microenvironment. The embedded-culture of a tumor spheroid within a hydrogel microenvironment could help to improve the mimicking of in vivo cell growth and the development of 3D models for tumor invasiveness evaluation, which could enhance its drug efficiency prediction together with cell viability detection. NCI-H23 spheroids and CT-26 spheroids, from a non–small cell lung cancer and colorectal cancer cell line, respectively, together with extracellular matrix were generated for evaluating their sensitivity to AMG510 (a KRAS^G12C inhibitor) under normoxia and hypoxia conditions, which were created by an on-stage environmental chamber. Results demonstrated that NCI-H23, the KRAS^G12C moderate expression cell line, only mildly responded to AMG510 treatment in normal 2D and 3D cultures and could be clearly evaluated by our system in hypoxia conditions, while the negative control CT-26 (G12D-mutant) spheroid exhibited no significant response to AMG510 treatment. In summary, our system, together with a controlled microenvironment and imaging methodology, provided an easily assessable and effective methodology for 3D in vitro drug efficiency testing and screenings. Full article

(This article belongs to the Section Nanobiotechnology and Biofabrication)

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20 pages, 4012 KiB

Open AccessEditor’s ChoiceArticle

Automatic Localization of Seizure Onset Zone Based on Multi-Epileptogenic Biomarkers Analysis of Single-Contact from Interictal SEEG

by Yiping Wang, Yanfeng Yang, Si Li, Zichen Su, Jinjie Guo, Penghu Wei, Jinguo Huang, Guixia Kang and Guoguang Zhao

Bioengineering 2022, 9(12), 769; https://doi.org/10.3390/bioengineering9120769 - 5 Dec 2022

Cited by 1 | Viewed by 3149

Abstract

Successful surgery on drug-resistant epilepsy patients (DRE) needs precise localization of the seizure onset zone (SOZ). Previous studies analyzing this issue still face limitations, such as inadequate analysis of features, low sensitivity and limited generality. Our study proposed an innovative and effective SOZ [...] Read more.

Successful surgery on drug-resistant epilepsy patients (DRE) needs precise localization of the seizure onset zone (SOZ). Previous studies analyzing this issue still face limitations, such as inadequate analysis of features, low sensitivity and limited generality. Our study proposed an innovative and effective SOZ localization method based on multiple epileptogenic biomarkers (spike and HFOs), and analysis of single-contact (MEBM-SC) to address the above problems. We extracted contacts epileptic features from signal distributions and signal energy based on machine learning and end-to-end deep learning. Among them, a normalized pathological ripple rate was designed to reduce the disturbance of physiological ripple and enhance the performance of SOZ localization. Then, a feature selection algorithm based on Shapley value and hypothetical testing (ShapHT+) was used to limit interference from irrelevant features. Moreover, an attention mechanism and a focal loss algorithm were used on the classifier to learn significant features and overcome the unbalance of SOZ/nSOZ contacts. Finally, we provided an SOZ prediction and visualization on magnetic resonance imaging (MRI). Ten patients with DRE were selected to verify our method. The experiment performed cross-validation and revealed that MEBM-SC obtains higher sensitivity. Additionally, the spike has better sensitivity while HFOs have better specificity, and the combination of these biomarkers can achieve the best performance. The study confirmed that MEBM-SC can increase the sensitivity and accuracy of SOZ localization and help clinicians to perform a precise and reliable preoperative evaluation based on interictal SEEG. Full article

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

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14 pages, 885 KiB

Open AccessEditor’s ChoiceReview

Bio-Activated PEEK: Promising Platforms for Improving Osteogenesis through Modulating Macrophage Polarization

by Haobu Chai, Wenzhi Wang, Xiangwei Yuan and Chen Zhu

Bioengineering 2022, 9(12), 747; https://doi.org/10.3390/bioengineering9120747 - 1 Dec 2022

Cited by 1 | Viewed by 1973

Abstract

The attention on orthopedic biomaterials has shifted from their direct osteogenic properties to their osteoimmunomodulation, especially the modulation of macrophage polarization. Presently, advanced technologies endow polyetheretherketone (PEEK) with good osteoimmunomodulation by modifying PEEK surface characteristics or incorporating bioactive substances with regulating macrophage polarization. [...] Read more.

The attention on orthopedic biomaterials has shifted from their direct osteogenic properties to their osteoimmunomodulation, especially the modulation of macrophage polarization. Presently, advanced technologies endow polyetheretherketone (PEEK) with good osteoimmunomodulation by modifying PEEK surface characteristics or incorporating bioactive substances with regulating macrophage polarization. Recent studies have demonstrated that the fabrication of a hydrophilic surface and the incorporation of bioactive substances into PEEK (e.g., zinc, calcium, and phosphate) are good strategies to promote osteogenesis by enhancing the polarization of M2 macrophages. Furthermore, the modification by other osteoimmunomodulatory composites (e.g., lncRNA-MM2P, IL-4, IL-10, and chitosan) and their controlled and desired release may make PEEK an optimal bio-activated implant for regulating and balancing the osteogenic system and immune system. The purpose of this review is to comprehensively evaluate the potential of bio-activated PEEK in polarizing macrophages into M2 phenotype to improve osteogenesis. For this objective, we retrieved and discussed different kinds of bio-activated PEEK regarding improving osteogenesis through modulating macrophage polarization. Meanwhile, the relevant challenges and outlook were presented. We hope that this review can shed light on the development of bio-activated PEEK with more favorable osteoimmunomodulation. Full article

(This article belongs to the Special Issue Current Developments and Applications in Bone Tissue Engineering)

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16 pages, 8183 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Wave-Encoded Model-Based Deep Learning for Highly Accelerated Imaging with Joint Reconstruction

by Jaejin Cho, Borjan Gagoski, Tae Hyung Kim, Qiyuan Tian, Robert Frost, Itthi Chatnuntawech and Berkin Bilgic

Bioengineering 2022, 9(12), 736; https://doi.org/10.3390/bioengineering9120736 - 29 Nov 2022

Cited by 9 | Viewed by 2317

Abstract

A recently introduced model-based deep learning (MoDL) technique successfully incorporates convolutional neural network (CNN)-based regularizers into physics-based parallel imaging reconstruction using a small number of network parameters. Wave-controlled aliasing in parallel imaging (CAIPI) is an emerging parallel imaging method that accelerates imaging acquisition [...] Read more.

A recently introduced model-based deep learning (MoDL) technique successfully incorporates convolutional neural network (CNN)-based regularizers into physics-based parallel imaging reconstruction using a small number of network parameters. Wave-controlled aliasing in parallel imaging (CAIPI) is an emerging parallel imaging method that accelerates imaging acquisition by employing sinusoidal gradients in the phase- and slice/partition-encoding directions during the readout to take better advantage of 3D coil sensitivity profiles. We propose wave-encoded MoDL (wave-MoDL) combining the wave-encoding strategy with unrolled network constraints for highly accelerated 3D imaging while enforcing data consistency. We extend wave-MoDL to reconstruct multicontrast data with CAIPI sampling patterns to leverage similarity between multiple images to improve the reconstruction quality. We further exploit this to enable rapid quantitative imaging using an interleaved look-locker acquisition sequence with T₂ preparation pulse (3D-QALAS). Wave-MoDL enables a 40 s MPRAGE acquisition at 1 mm resolution at 16-fold acceleration. For quantitative imaging, wave-MoDL permits a 1:50 min acquisition for T₁, T₂, and proton density mapping at 1 mm resolution at 12-fold acceleration, from which contrast-weighted images can be synthesized as well. In conclusion, wave-MoDL allows rapid MR acquisition and high-fidelity image reconstruction and may facilitate clinical and neuroscientific applications by incorporating unrolled neural networks into wave-CAIPI reconstruction. Full article

(This article belongs to the Special Issue AI in MRI: Frontiers and Applications)

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9 pages, 1082 KiB

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 3848

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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16 pages, 9125 KiB

Open AccessEditor’s ChoiceArticle

A Surrogate Model Based on a Finite Element Model of Abdomen for Real-Time Visualisation of Tissue Stress during Physical Examination Training

by Florence Leong, Chow Yin Lai, Siamak Farajzadeh Khosroshahi, Liang He, Simon de Lusignan, Thrishantha Nanayakkara and Mazdak Ghajari

Bioengineering 2022, 9(11), 687; https://doi.org/10.3390/bioengineering9110687 - 14 Nov 2022

Cited by 4 | Viewed by 4396

Abstract

Robotic patients show great potential for helping to improve medical palpation training, as they can provide feedback that cannot be obtained in a real patient. They provide information about internal organ deformation that can significantly enhance palpation training by giving medical trainees visual [...] Read more.

Robotic patients show great potential for helping to improve medical palpation training, as they can provide feedback that cannot be obtained in a real patient. They provide information about internal organ deformation that can significantly enhance palpation training by giving medical trainees visual insight based on the pressure they apply for palpation. This can be achieved by using computational models of abdomen mechanics. However, such models are computationally expensive, and thus unable to provide real-time predictions. In this work, we proposed an innovative surrogate model of abdomen mechanics by using machine learning (ML) and finite element (FE) modelling to virtually render internal tissue deformation in real time. We first developed a new high-fidelity FE model of the abdomen mechanics from computerized tomography (CT) images. We performed palpation simulations to produce a large database of stress distribution on the liver edge, an area of interest in most examinations. We then used artificial neural networks (ANNs) to develop the surrogate model and demonstrated its application in an experimental palpation platform. Our FE simulations took 1.5 h to predict stress distribution for each palpation while this only took a fraction of a second for the surrogate model. Our results show that our artificial neural network (ANN) surrogate has an accuracy of 92.6%. We also showed that the surrogate model is able to use the experimental input of palpation location and force to provide real-time projections onto the robotics platform. This enhanced robotics platform has the potential to be used as a training simulator for trainees to hone their palpation skills. Full article

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

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33 pages, 4118 KiB

Open AccessEditor’s ChoiceReview

3D-Printing for Critical Sized Bone Defects: Current Concepts and Future Directions

by Cory K. Mayfield, Mina Ayad, Elizabeth Lechtholz-Zey, Yong Chen and Jay R. Lieberman

Bioengineering 2022, 9(11), 680; https://doi.org/10.3390/bioengineering9110680 - 11 Nov 2022

Cited by 23 | Viewed by 4410

Abstract

The management and definitive treatment of segmental bone defects in the setting of acute trauma, fracture non-union, revision joint arthroplasty, and tumor surgery are challenging clinical problems with no consistently satisfactory solution. Orthopaedic surgeons are developing novel strategies to treat these problems, including [...] Read more.

The management and definitive treatment of segmental bone defects in the setting of acute trauma, fracture non-union, revision joint arthroplasty, and tumor surgery are challenging clinical problems with no consistently satisfactory solution. Orthopaedic surgeons are developing novel strategies to treat these problems, including three-dimensional (3D) printing combined with growth factors and/or cells. This article reviews the current strategies for management of segmental bone loss in orthopaedic surgery, including graft selection, bone graft substitutes, and operative techniques. Furthermore, we highlight 3D printing as a technology that may serve a major role in the management of segmental defects. The optimization of a 3D-printed scaffold design through printing technique, material selection, and scaffold geometry, as well as biologic additives to enhance bone regeneration and incorporation could change the treatment paradigm for these difficult bone repair problems. Full article

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

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18 pages, 3996 KiB

Open AccessEditor’s ChoiceReview

Noble Metal Nanoparticles for Point-of-Care Testing: Recent Advancements and Social Impacts

by Keven Luciano, Xiaochuan Wang, Yaning Liu, Gabriella Eyler, Zhenpeng Qin and Xiaohu Xia

Bioengineering 2022, 9(11), 666; https://doi.org/10.3390/bioengineering9110666 - 8 Nov 2022

Cited by 5 | Viewed by 2182

Abstract

Point-of-care (POC) tests for the diagnosis of diseases are critical to the improvement of the standard of living, especially for resource-limited areas or countries. In recent years, nanobiosensors based on noble metal nanoparticles (NM NPs) have emerged as a class of effective and [...] Read more.

Point-of-care (POC) tests for the diagnosis of diseases are critical to the improvement of the standard of living, especially for resource-limited areas or countries. In recent years, nanobiosensors based on noble metal nanoparticles (NM NPs) have emerged as a class of effective and versatile POC testing technology. The unique features of NM NPs ensure great performance of associated POC nanobiosensors. In particular, NM NPs offer various signal transduction principles, such as plasmonics, catalysis, photothermal effect, and so on. Significantly, the detectable signal from NM NPs can be tuned and optimized by controlling the physicochemical parameters (e.g., size, shape, and elemental composition) of NPs. In this article, we introduce the inherent merits of NM NPs that make them attractive for POC testing, discuss recent advancement of NM NPs-based POC tests, highlight their social impacts, and provide perspectives on challenges and opportunities in the field. We hope the review and insights provided in this article can inspire new fundamental and applied research in this emerging field. Full article

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

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16 pages, 5830 KiB

Open AccessEditor’s ChoiceArticle

Development of Adenovirus Containing Liposomes Produced by Extrusion vs. Homogenization: A Comparison for Scale-Up Purposes

by Jaimin R. Shah, Tao Dong, Abraham T. Phung, Tony Reid, Christopher Larson, Ana B. Sanchez, Bryan Oronsky, Sarah L. Blair, Omonigho Aisagbonhi, William C. Trogler and Andrew C. Kummel

Bioengineering 2022, 9(11), 620; https://doi.org/10.3390/bioengineering9110620 - 27 Oct 2022

Cited by 3 | Viewed by 2740

Abstract

Adenovirus (Ad) is a widely studied viral vector for cancer therapy as it can be engineered to cause selective lysis of cancer cells. However, Ad delivery is limited in treating cancers that do not have coxsackievirus and adenovirus receptors (CAR). To overcome this [...] Read more.

Adenovirus (Ad) is a widely studied viral vector for cancer therapy as it can be engineered to cause selective lysis of cancer cells. However, Ad delivery is limited in treating cancers that do not have coxsackievirus and adenovirus receptors (CAR). To overcome this challenge, Ad-encapsulated liposomes were developed that enhance the delivery of Ads and increase therapeutic efficacy. Cationic empty liposomes were manufactured first, to which an anionic Ad were added, which resulted in encapsulated Ad liposomes through charge interaction. Optimization of the liposome formula was carried out with series of formulation variables experiments using an extrusion process, which is ideal for laboratory-scale small batches. Later, the optimized formulation was manufactured with a homogenization technique—A high shear rotor-stator blending, that is ideal for large-scale manufacturing and is in compliance with Good Manufacturing Practices (GMP). Comparative in vitro transduction, physicochemical characterization, long-term storage stability at different temperature conditions, and in vivo animal studies were performed. Ad encapsulated liposomes transduced CAR deficient cells 100-fold more efficiently than the unencapsulated Ad (p ≤ 0.0001) in vitro, and 4-fold higher in tumors injected in nude mice in vivo. Both extrusion and homogenization performed similarly–with equivalent in vitro and in vivo transduction efficiencies, physicochemical characterization, and long-term storage stability. Thus, two Ad encapsulated liposomes preparation methods used herein, i.e., extrusion vs. homogenization were equivalent in terms of enhanced Ad performance and long-term storage stability; this will, hopefully, facilitate translation to the clinic. Full article

(This article belongs to the Special Issue Targeted Nanodelivery systems for Oncology Applications)

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20 pages, 3762 KiB

Open AccessEditor’s ChoiceArticle

Cervical Net: A Novel Cervical Cancer Classification Using Feature Fusion

by Hiam Alquran, Mohammed Alsalatie, Wan Azani Mustafa, Rabah Al Abdi and Ahmad Rasdan Ismail

Bioengineering 2022, 9(10), 578; https://doi.org/10.3390/bioengineering9100578 - 19 Oct 2022

Cited by 36 | Viewed by 3942

Abstract

Cervical cancer, a common chronic disease, is one of the most prevalent and curable cancers among women. Pap smear images are a popular technique for screening cervical cancer. This study proposes a computer-aided diagnosis for cervical cancer utilizing the novel Cervical Net deep [...] Read more.

Cervical cancer, a common chronic disease, is one of the most prevalent and curable cancers among women. Pap smear images are a popular technique for screening cervical cancer. This study proposes a computer-aided diagnosis for cervical cancer utilizing the novel Cervical Net deep learning (DL) structures and feature fusion with Shuffle Net structural features. Image acquisition and enhancement, feature extraction and selection, as well as classification are the main steps in our cervical cancer screening system. Automated features are extracted using pre-trained convolutional neural networks (CNN) fused with a novel Cervical Net structure in which 544 resultant features are obtained. To minimize dimensionality and select the most important features, principal component analysis (PCA) is used as well as canonical correlation analysis (CCA) to obtain the best discriminant features for five classes of Pap smear images. Here, five different machine learning (ML) algorithms are fed into these features. The proposed strategy achieved the best accuracy ever obtained using a support vector machine (SVM), in which fused features between Cervical Net and Shuffle Net is 99.1% for all classes. Full article

(This article belongs to the Special Issue Artificial Intelligence in Medical Image Processing and Segmentation)

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12 pages, 725 KiB

Open AccessEditor’s ChoiceReview

A Review on the Technological Advances and Future Perspectives of Axon Guidance and Regeneration in Peripheral Nerve Repair

by Arjun Prasad Tiwari, Taylor Lokai, Bayne Albin and In Hong Yang

Bioengineering 2022, 9(10), 562; https://doi.org/10.3390/bioengineering9100562 - 17 Oct 2022

Cited by 5 | Viewed by 2515

Abstract

Despite a significant advance in the pathophysiological understanding of peripheral nerve damage, the successful treatment of large nerve defects remains an unmet medical need. In this article, axon growth guidance for peripheral nerve regeneration was systematically reviewed and discussed mainly from the engineering [...] Read more.

Despite a significant advance in the pathophysiological understanding of peripheral nerve damage, the successful treatment of large nerve defects remains an unmet medical need. In this article, axon growth guidance for peripheral nerve regeneration was systematically reviewed and discussed mainly from the engineering perspective. In addition, the common approaches to surgery, bioengineering approaches to emerging technologies such as optogenetic stimulation and magnetic stimulation for functional recovery were discussed, along with their pros and cons. Additionally, clear future perspectives of axon guidance and nerve regeneration were addressed. Full article

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21 pages, 2316 KiB

Open AccessEditor’s ChoiceArticle

A Novel System for Precise Grading of Glioma

by Ahmed Alksas, Mohamed Shehata, Hala Atef, Fatma Sherif, Norah Saleh Alghamdi, Mohammed Ghazal, Sherif Abdel Fattah, Lamiaa Galal El-Serougy and Ayman El-Baz

Bioengineering 2022, 9(10), 532; https://doi.org/10.3390/bioengineering9100532 - 7 Oct 2022

Cited by 14 | Viewed by 2315

Abstract

Gliomas are the most common type of primary brain tumors and one of the highest causes of mortality worldwide. Accurate grading of gliomas is of immense importance to administer proper treatment plans. In this paper, we develop a comprehensive non-invasive multimodal magnetic resonance [...] Read more.

Gliomas are the most common type of primary brain tumors and one of the highest causes of mortality worldwide. Accurate grading of gliomas is of immense importance to administer proper treatment plans. In this paper, we develop a comprehensive non-invasive multimodal magnetic resonance (MR)-based computer-aided diagnostic (CAD) system to precisely differentiate between different grades of gliomas (Grades: I, II, III, and IV). A total of 99 patients with gliomas (M = 49, F = 50, age range = 1–79 years) were included after providing their informed consent to participate in this study. The proposed imaging-based glioma grading (GG-CAD) system utilizes three different MR imaging modalities, namely; contrast-enhanced T1-MR, T2-MR known as fluid-attenuated inversion-recovery (FLAIR), and diffusion-weighted (DW-MR) to extract the following imaging features: (i) morphological features based on constructing the histogram of oriented gradients (HOG) and estimating the glioma volume, (ii) first and second orders textural features by constructing histogram, gray-level run length matrix (GLRLM), and gray-level co-occurrence matrix (GLCM), (iii) functional features by estimating voxel-wise apparent diffusion coefficients (ADC) and contrast-enhancement slope. These features are then integrated together and processed using a Gini impurity-based selection approach to find the optimal set of significant features. The reduced significant features are then fed to a multi-layer perceptron artificial neural networks (MLP-ANN) classification model to obtain the final diagnosis of a glioma tumor as Grade I, II, III, or IV. The GG-CAD system was evaluated on the enrolled 99 gliomas (Grade I = 13, Grade II = 22, Grade III = 22, and Grade IV = 42) using a leave-one-subject-out (LOSO) and k-fold stratified (with k = 5 and 10) cross-validation approach. The GG-CAD achieved 0.96 ± 0.02 quadratic-weighted Cohen’s kappa and 95.8% ± 1.9% overall diagnostic accuracy at LOSO and an outstanding diagnostic performance at k = 10 and 5. Alternative classifiers, including RFs and SVM

_{l i n}

produced inferior results compared to the proposed MLP-ANN GG-CAD system. These findings demonstrate the feasibility of the proposed CAD system as a novel tool to objectively characterize gliomas using the comprehensive extracted and selected imaging features. The developed GG-CAD system holds promise to be used as a non-invasive diagnostic tool for Precise Grading of Glioma. Full article

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11 pages, 1642 KiB

Open AccessEditor’s ChoiceArticle

Cone-Beam Computed Tomographic Assessment of the Mandibular Condylar Volume in Different Skeletal Patterns: A Retrospective Study in Adult Patients

by Chiara Ceratti, Cinzia Maspero, Dario Consonni, Alberto Caprioglio, Stephen Thaddeus Connelly, Francesco Inchingolo and Gianluca Martino Tartaglia

Bioengineering 2022, 9(3), 102; https://doi.org/10.3390/bioengineering9030102 - 2 Mar 2022

Cited by 34 | Viewed by 4019

Abstract

The aim of this study was to assess the condylar volume in adult patients with different skeletal classes and vertical patterns using cone-beam computed tomography (CBCT). CBCT scans of 146 condyles from 73 patients (mean age 30 ± 12 years old; 49 female, [...] Read more.

The aim of this study was to assess the condylar volume in adult patients with different skeletal classes and vertical patterns using cone-beam computed tomography (CBCT). CBCT scans of 146 condyles from 73 patients (mean age 30 ± 12 years old; 49 female, 24 male) were selected from the archive of the Department of Dentistry and Maxillofacial Surgery of Fondazione IRCCS Ca’ Granda, Milan, Italy, and retrospectively analyzed. The following inclusion criteria were used: adult patients; CBCT performed with the same protocol (0.4 mm slice thickness, 16 × 22 cm field of view, 20 s scan time); no systemic diseases; and no previous orthodontic treatments. Three-dimensional cephalometric tracings were performed for each patient, the mandibular condyles were segmented and the relevant volumes calculated using Mimics Materialize 20.0^® software (Materialise, Leuven, Belgium). Right and left variables were analyzed together using random-intercept linear regression models. No significant association between condylar volumes and skeletal class was found. On the other hand, in relation to vertical patterns, the mean values of the mandibular condyle volumes in hyperdivergent subjects (688 mm³) with a post-rotation growth pattern (625 mm³) were smaller than in hypodivergent patients (812 mm³) with a horizontal growth pattern (900 mm³). Patients with an increased divergence angle had smaller condylar volumes than subjects with normal or decreased mandibular plane divergence. This relationship may help the clinician when planning orthodontic treatment. Full article

(This article belongs to the Special Issue Recent Advances in Drug Delivery and Oral Health: The Impact of Technology and Digital Advances as a New Frontier)

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18 pages, 1289 KiB

Open AccessEditor’s ChoiceArticle

Machine Learning and Deep Learning Algorithms for Skin Cancer Classification from Dermoscopic Images

by Solene Bechelli and Jerome Delhommelle

Bioengineering 2022, 9(3), 97; https://doi.org/10.3390/bioengineering9030097 - 27 Feb 2022

Cited by 71 | Viewed by 8942

Abstract

We carry out a critical assessment of machine learning and deep learning models for the classification of skin tumors. Machine learning (ML) algorithms tested in this work include logistic regression, linear discriminant analysis, k-nearest neighbors classifier, decision tree classifier and Gaussian naive Bayes, [...] Read more.

We carry out a critical assessment of machine learning and deep learning models for the classification of skin tumors. Machine learning (ML) algorithms tested in this work include logistic regression, linear discriminant analysis, k-nearest neighbors classifier, decision tree classifier and Gaussian naive Bayes, while deep learning (DL) models employed are either based on a custom Convolutional Neural Network model, or leverage transfer learning via the use of pre-trained models (VGG16, Xception and ResNet50). We find that DL models, with accuracies up to 0.88, all outperform ML models. ML models exhibit accuracies below 0.72, which can be increased to up to 0.75 with ensemble learning. To further assess the performance of DL models, we test them on a larger and more imbalanced dataset. Metrics, such as the F-score and accuracy, indicate that, after fine-tuning, pre-trained models perform extremely well for skin tumor classification. This is most notably the case for VGG16, which exhibits an F-score of 0.88 and an accuracy of 0.88 on the smaller database, and metrics of 0.70 and 0.88, respectively, on the larger database. Full article

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16 pages, 1200 KiB

Open AccessEditor’s ChoiceReview

Taking It Personally: 3D Bioprinting a Patient-Specific Cardiac Patch for the Treatment of Heart Failure

by Niina Matthews, Berto Pandolfo, Daniel Moses and Carmine Gentile

Bioengineering 2022, 9(3), 93; https://doi.org/10.3390/bioengineering9030093 - 25 Feb 2022

Cited by 6 | Viewed by 7386

Abstract

Despite a massive global preventative effort, heart failure remains the major cause of death globally. The number of patients requiring a heart transplant, the eventual last treatment option, far outnumbers the available donor hearts, leaving many to deteriorate or die on the transplant [...] Read more.

Despite a massive global preventative effort, heart failure remains the major cause of death globally. The number of patients requiring a heart transplant, the eventual last treatment option, far outnumbers the available donor hearts, leaving many to deteriorate or die on the transplant waiting list. Treating heart failure by transplanting a 3D bioprinted patient-specific cardiac patch to the infarcted region on the myocardium has been investigated as a potential future treatment. To date, several studies have created cardiac patches using 3D bioprinting; however, testing the concept is still at a pre-clinical stage. A handful of clinical studies have been conducted. However, moving from animal studies to human trials will require an increase in research in this area. This review covers key elements to the design of a patient-specific cardiac patch, divided into general areas of biological design and 3D modelling. It will make recommendations on incorporating anatomical considerations and high-definition motion data into the process of 3D-bioprinting a patient-specific cardiac patch. Full article

(This article belongs to the Special Issue 3D Bioprinting Advanced Vascularized Tissues and Organs)

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14 pages, 7587 KiB

Open AccessEditor’s ChoiceCommunication

Cell Culture Process Scale-Up Challenges for Commercial-Scale Manufacturing of Allogeneic Pluripotent Stem Cell Products

by Brian Lee, Sunghoon Jung, Yas Hashimura, Maximilian Lee, Breanna S. Borys, Tiffany Dang, Michael S. Kallos, Carlos A. V. Rodrigues, Teresa P. Silva and Joaquim M. S. Cabral

Bioengineering 2022, 9(3), 92; https://doi.org/10.3390/bioengineering9030092 - 25 Feb 2022

Cited by 17 | Viewed by 5878

Abstract

Allogeneic cell therapy products, such as therapeutic cells derived from pluripotent stem cells (PSCs), have amazing potential to treat a wide variety of diseases and vast numbers of patients globally. However, there are various challenges related to manufacturing PSCs in single-use bioreactors, particularly [...] Read more.

Allogeneic cell therapy products, such as therapeutic cells derived from pluripotent stem cells (PSCs), have amazing potential to treat a wide variety of diseases and vast numbers of patients globally. However, there are various challenges related to manufacturing PSCs in single-use bioreactors, particularly at larger volumetric scales. This manuscript addresses these challenges and presents potential solutions to alleviate the anticipated bottlenecks for commercial-scale manufacturing of high-quality therapeutic cells derived from PSCs. Full article

(This article belongs to the Special Issue Stem Cell Bioprocessing and Manufacturing, Volume 2)

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29 pages, 6363 KiB

Open AccessEditor’s ChoiceReview

A New Wave of Industrialization of PHA Biopolyesters

by Martin Koller and Anindya Mukherjee

Bioengineering 2022, 9(2), 74; https://doi.org/10.3390/bioengineering9020074 - 15 Feb 2022

Cited by 127 | Viewed by 16444

Abstract

The ever-increasing use of plastics, their fossil origin, and especially their persistence in nature have started a wave of new innovations in materials that are renewable, offer the functionalities of plastics, and are biodegradable. One such class of biopolymers, polyhydroxyalkanoates (PHAs), are biosynthesized [...] Read more.

The ever-increasing use of plastics, their fossil origin, and especially their persistence in nature have started a wave of new innovations in materials that are renewable, offer the functionalities of plastics, and are biodegradable. One such class of biopolymers, polyhydroxyalkanoates (PHAs), are biosynthesized by numerous microorganisms through the conversion of carbon-rich renewable resources. PHA homo- and heteropolyesters are intracellular products of secondary microbial metabolism. When isolated from microbial biomass, PHA biopolymers mimic the functionalities of many of the top-selling plastics of petrochemical origin, but biodegrade in soil, freshwater, and marine environments, and are both industrial- and home-compostable. Only a handful of PHA biopolymers have been studied in-depth, and five of these reliably match the desired material properties of established fossil plastics. Realizing the positive attributes of PHA biopolymers, several established chemical companies and numerous start-ups, brand owners, and converters have begun to produce and use PHA in a variety of industrial and consumer applications, in what can be described as the emergence of the “PHA industry”. While this positive industrial and commercial relevance of PHA can hardly be described as the first wave in its commercial development, it is nonetheless a very serious one with over 25 companies and start-ups and 30+ brand owners announcing partnerships in PHA production and use. The combined product portfolio of the producing companies is restricted to five types of PHA, namely poly(3-hydroxybutyrate), poly(4-hydroxybutyrate), poly(3-hydroxybutyrate-co-3-hydroxyvalerate), poly(3-hydroxybutyrate-co-4-hydroxybutyrate), and poly(3-hydroxybutyrate-co-3-hydroxyhexanoate), even though PHAs as a class of polymers offer the potential to generate almost limitless combinations of polymers beneficial to humankind. To date, by varying the co-monomer type and content in these PHA biopolymers, their properties emulate those of the seven top-selling fossil plastics, representing 230 million t of annual plastics production. Capacity expansions of 1.5 million t over the next 5 years have been announced. Policymakers worldwide have taken notice and are encouraging industry to adopt biodegradable and compostable material solutions. This wave of commercialization of PHAs in single-use and in durable applications holds the potential to make the decisive quantum leap in reducing plastic pollution, the depletion of fossil resources, and the emission of greenhouse gases and thus fighting climate change. This review presents setbacks and success stories of the past 40 years and the current commercialization wave of PHA biopolymers, their properties, and their fields of application. Full article

(This article belongs to the Special Issue Advances in Polyhydroxyalkanoate (PHA) Production, Volume 3)

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15 pages, 4310 KiB

Open AccessEditor’s ChoiceArticle

Alginate Core–Shell Capsules for 3D Cultivation of Adipose-Derived Mesenchymal Stem Cells

by Sabrina Nebel, Manuel Lux, Sonja Kuth, Faina Bider, Wolf Dietrich, Dominik Egger, Aldo R. Boccaccini and Cornelia Kasper

Bioengineering 2022, 9(2), 66; https://doi.org/10.3390/bioengineering9020066 - 6 Feb 2022

Cited by 16 | Viewed by 10767

Abstract

Mesenchymal stem cells (MSCs) are primary candidates in tissue engineering and stem cell therapies due to their intriguing regenerative and immunomodulatory potential. Their ability to self-assemble into three-dimensional (3D) aggregates further improves some of their therapeutic properties, e.g., differentiation potential, secretion of cytokines, [...] Read more.

Mesenchymal stem cells (MSCs) are primary candidates in tissue engineering and stem cell therapies due to their intriguing regenerative and immunomodulatory potential. Their ability to self-assemble into three-dimensional (3D) aggregates further improves some of their therapeutic properties, e.g., differentiation potential, secretion of cytokines, and homing capacity after administration. However, high hydrodynamic shear forces and the resulting mechanical stresses within commercially available dynamic cultivation systems can decrease their regenerative properties. Cells embedded within a polymer matrix, however, lack cell-to-cell interactions found in their physiological environment. Here, we present a “semi scaffold-free” approach to protect the cells from high shear forces by a physical barrier, but still allow formation of a 3D structure with in vivo-like cell-to-cell contacts. We highlight a relatively simple method to create core–shell capsules by inverse gelation. The capsules consist of an outer barrier made from sodium alginate, which allows for nutrient and waste diffusion and an inner compartment for direct cell-cell interactions. Next to capsule characterization, a harvesting procedure was established and viability and proliferation of human adipose-derived MSCs were investigated. In the future, this encapsulation and cultivation technique might be used for MSC-expansion in scalable dynamic bioreactor systems, facilitating downstream procedures, such as cell harvest and differentiation into mature tissue grafts. Full article

(This article belongs to the Special Issue Material and Engineering-Based Approaches for Organoids)

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24 pages, 1914 KiB

Open AccessEditor’s ChoiceReview

Role of Implantable Drug Delivery Devices with Dual Platform Capabilities in the Prevention and Treatment of Bacterial Osteomyelitis

by Caroline Billings and David E. Anderson

Bioengineering 2022, 9(2), 65; https://doi.org/10.3390/bioengineering9020065 - 6 Feb 2022

Cited by 6 | Viewed by 7088

Abstract

As medicine advances and physicians are able to provide patients with innovative solutions, including placement of temporary or permanent medical devices that drastically improve quality of life of the patient, there is the persistent, recurring problem of chronic bacterial infection, including osteomyelitis. Osteomyelitis [...] Read more.

As medicine advances and physicians are able to provide patients with innovative solutions, including placement of temporary or permanent medical devices that drastically improve quality of life of the patient, there is the persistent, recurring problem of chronic bacterial infection, including osteomyelitis. Osteomyelitis can manifest as a result of traumatic or contaminated wounds or implant-associated infections. This bacterial infection can persist as a result of inadequate treatment regimens or the presence of biofilm on implanted medical devices. One strategy to mitigate these concerns is the use of implantable medical devices that simultaneously act as local drug delivery devices (DDDs). This classification of device has the potential to prevent or aid in clearing chronic bacterial infection by delivering effective doses of antibiotics to the area of interest and can be engineered to simultaneously aid in tissue regeneration. This review will provide a background on bacterial infection and current therapies as well as current and prospective implantable DDDs, with a particular emphasis on local DDDs to combat bacterial osteomyelitis. Full article

(This article belongs to the Special Issue Bioengineered Systems: Implants and Devices for Orthopaedic Applications)

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20 pages, 1129 KiB

Open AccessEditor’s ChoiceReview

Lumbar Intervertebral Disc Herniation: Annular Closure Devices and Key Design Requirements

by Alexandra Alcántara Guardado, Alexander Baker, Andrew Weightman, Judith A. Hoyland and Glen Cooper

Bioengineering 2022, 9(2), 47; https://doi.org/10.3390/bioengineering9020047 - 19 Jan 2022

Cited by 10 | Viewed by 9089

Abstract

Lumbar disc herniation is one of the most common degenerative spinal conditions resulting in lower back pain and sciatica. Surgical treatment options include microdiscectomy, lumbar fusion, total disc replacement, and other minimally invasive approaches. At present, microdiscectomy procedures are the most used technique; [...] Read more.

Lumbar disc herniation is one of the most common degenerative spinal conditions resulting in lower back pain and sciatica. Surgical treatment options include microdiscectomy, lumbar fusion, total disc replacement, and other minimally invasive approaches. At present, microdiscectomy procedures are the most used technique; however, the annulus fibrosus is left with a defect that without treatment may contribute to high reherniation rates and changes in the biomechanics of the lumbar spine. This paper aims to review current commercially available products that mechanically close the annulus including the AnchorKnot^® suture-passing device and the Barricaid^® annular closure device. Previous studies and reviews have focused mainly on a biomimetic biomaterials approach and have described some mechanical and biological requirements for an active annular repair/regeneration strategy but are still far away from clinical implementation. Therefore, in this paper we aim to create a design specification for a mechanical annular closure strategy by identifying the most important mechanical and biological design parameters, including consideration of material selection, preclinical testing requirements, and requirements for clinical implementation. Full article

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

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24 pages, 2436 KiB

Open AccessEditor’s ChoiceReview

Organ on Chip Technology to Model Cancer Growth and Metastasis

by Giorgia Imparato, Francesco Urciuolo and Paolo Antonio Netti

Bioengineering 2022, 9(1), 28; https://doi.org/10.3390/bioengineering9010028 - 11 Jan 2022

Cited by 39 | Viewed by 6374

Abstract

Organ on chip (OOC) has emerged as a major technological breakthrough and distinct model system revolutionizing biomedical research and drug discovery by recapitulating the crucial structural and functional complexity of human organs in vitro. OOC are rapidly emerging as powerful tools for oncology [...] Read more.

Organ on chip (OOC) has emerged as a major technological breakthrough and distinct model system revolutionizing biomedical research and drug discovery by recapitulating the crucial structural and functional complexity of human organs in vitro. OOC are rapidly emerging as powerful tools for oncology research. Indeed, Cancer on chip (COC) can ideally reproduce certain key aspects of the tumor microenvironment (TME), such as biochemical gradients and niche factors, dynamic cell–cell and cell–matrix interactions, and complex tissue structures composed of tumor and stromal cells. Here, we review the state of the art in COC models with a focus on the microphysiological systems that host multicellular 3D tissue engineering models and can help elucidate the complex biology of TME and cancer growth and progression. Finally, some examples of microengineered tumor models integrated with multi-organ microdevices to study disease progression in different tissues will be presented. Full article

(This article belongs to the Special Issue Biomaterials Approaches for Disease Modeling)

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18 pages, 2118 KiB

Open AccessEditor’s ChoiceReview

An Update on Nickel-Titanium Rotary Instruments in Endodontics: Mechanical Characteristics, Testing and Future Perspective—An Overview

by Alessio Zanza, Maurilio D’Angelo, Rodolfo Reda, Gianluca Gambarini, Luca Testarelli and Dario Di Nardo

Bioengineering 2021, 8(12), 218; https://doi.org/10.3390/bioengineering8120218 - 16 Dec 2021

Cited by 52 | Viewed by 7061

Abstract

Since the introduction of Nickel-Titanium alloy as the material of choice for the manufacturing of endodontic rotary instruments, the success rate of the root canal therapies has been significantly increased. This success mainly arises from the properties of the Nickel-Titanium alloy: the biocompatibility, [...] Read more.

Since the introduction of Nickel-Titanium alloy as the material of choice for the manufacturing of endodontic rotary instruments, the success rate of the root canal therapies has been significantly increased. This success mainly arises from the properties of the Nickel-Titanium alloy: the biocompatibility, the superelasticity and the shape memory effect. Those characteristics have led to a reduction in time of endodontic treatments, a simplification of instrumentation procedures and an increase of predictability and effectiveness of endodontic treatments. Nevertheless, the intracanal separation of Nickel-Titanium rotary instruments is still a major concern of endodontists, with a consequent possible reduction in the outcome rate. As thoroughly demonstrated, the two main causes of intracanal separation of endodontic instruments are the cyclic fatigue and the torsional loads. As results, in order to reduce the percentage of intracanal separation research and manufacturers have been focused on the parameters that directly or indirectly influence mechanical properties of endodontic rotary instruments. This review describes the current state of the art regarding the Nickel-Titanium alloy in endodontics, the mechanical behavior of endodontic rotary instruments and the relative stresses acting on them during intracanal instrumentation, highlighting the limitation of the current literature. Full article

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18 pages, 1677 KiB

Open AccessEditor’s ChoiceArticle

Developing a Novel Integrated Generalised Data Envelopment Analysis (DEA) to Evaluate Hospitals Providing Stroke Care Services

by Mirpouya Mirmozaffari, Elham Shadkam, Seyed Mohammad Khalili and Maziar Yazdani

Bioengineering 2021, 8(12), 207; https://doi.org/10.3390/bioengineering8120207 - 10 Dec 2021

Cited by 37 | Viewed by 3680

Abstract

Stroke is the biggest cause of adult disability and the third biggest cause of death in the US. Stroke is a medical emergency, and the treatment given in the early hours is important in shaping the patient’s long-term recovery and prognosis. Despite the [...] Read more.

Stroke is the biggest cause of adult disability and the third biggest cause of death in the US. Stroke is a medical emergency, and the treatment given in the early hours is important in shaping the patient’s long-term recovery and prognosis. Despite the fact that substantial attention has been dedicated to this complex and difficult issue in healthcare, novel strategies such as operation research-based approaches have hardly been used to deal with the difficult challenges associated with stroke. This study proposes a novel approach with data envelopment analysis (DEA) and multi-objective linear programming (MOLP) in hospitals that provide stroke care services to select the most efficient approach, which will be a new experiment in literature perception. DEA and MOLP are widely used for performance evaluation and efficiency measurement. Despite their similarities and common concepts, the two disciplines have evolved separately. The generalised DEA (GDEA) cannot incorporate the preferences of decision-makers (DMs) preferences and historical efficiency data. In contrast, MOLP can incorporate the DM’s preferences into the decision-making process. We transform the GDEA model into MOLP through the max-ordering approach to (i) solve the problem interactively; (ii) use the step method (STEM) and consider DM’s preferences; (iii) eliminate the need for predetermined preference information; and (iv) apply the most preferred solution (MPS) to identify the most efficient approach. A case study of hospitals that provide stroke care services is taken as an example to illustrate the potential application of the proposed approach method. Full article

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16 pages, 1982 KiB

Open AccessEditor’s ChoiceArticle

Integrated Process Model Applications Linking Bioprocess Development to Quality by Design Milestones

by Christopher Taylor, Lukas Marschall, Marco Kunzelmann, Michael Richter, Frederik Rudolph, Judith Vajda, Beate Presser, Thomas Zahel, Joey Studts and Christoph Herwig

Bioengineering 2021, 8(11), 156; https://doi.org/10.3390/bioengineering8110156 - 24 Oct 2021

Cited by 9 | Viewed by 3992

Abstract

Maximizing the value of each available data point in bioprocess development is essential in order to reduce the time-to-market, lower the number of expensive wet-lab experiments, and maximize process understanding. Advanced in silico methods are increasingly being investigated to accomplish these goals. Within [...] Read more.

Maximizing the value of each available data point in bioprocess development is essential in order to reduce the time-to-market, lower the number of expensive wet-lab experiments, and maximize process understanding. Advanced in silico methods are increasingly being investigated to accomplish these goals. Within this contribution, we propose a novel integrated process model procedure to maximize the use of development data to optimize the Stage 1 process validation work flow. We generate an integrated process model based on available data and apply two innovative Monte Carlo simulation-based parameter sensitivity analysis linearization techniques to automate two quality by design activities: determining risk assessment severity rankings and establishing preliminary control strategies for critical process parameters. These procedures are assessed in a case study for proof of concept on a candidate monoclonal antibody bioprocess after process development, but prior to process characterization. The evaluation was successful in returning results that were used to support Stage I process validation milestones and demonstrated the potential to reduce the investigated parameters by up to 24% in process characterization, while simultaneously setting up a strategy for iterative updates of risk assessments and process controls throughout the process life-cycle to ensure a robust and efficient drug supply. Full article

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23 pages, 5060 KiB

Open AccessEditor’s ChoiceArticle

Two-Stage Polyhydroxyalkanoates (PHA) Production from Cheese Whey Using Acetobacter pasteurianus C1 and Bacillus sp. CYR1

by Young-Cheol Chang, Motakatla Venkateswar Reddy, Kazuma Imura, Rui Onodera, Natsumi Kamada and Yuki Sano

Bioengineering 2021, 8(11), 157; https://doi.org/10.3390/bioengineering8110157 - 24 Oct 2021

Cited by 26 | Viewed by 4974

Abstract

Cheese whey (CW) can be an excellent carbon source for polyhydroxyalkanoates (PHA)-producing bacteria. Most studies have used CW, which contains high amounts of lactose, however, there are no reports using raw CW, which has a relatively low amount of lactose. Therefore, in the [...] Read more.

Cheese whey (CW) can be an excellent carbon source for polyhydroxyalkanoates (PHA)-producing bacteria. Most studies have used CW, which contains high amounts of lactose, however, there are no reports using raw CW, which has a relatively low amount of lactose. Therefore, in the present study, PHA production was evaluated in a two-stage process using the CW that contains low amounts of lactose. In first stage, the carbon source existing in CW was converted into acetic acid using the bacteria, Acetobacter pasteurianus C1, which was isolated from food waste. In the second stage, acetic acid produced in the first stage was converted into PHA using the bacteria, Bacillus sp. CYR-1. Under the condition of without the pretreatment of CW, acetic acid produced from CW was diluted at different folds and used for the production of PHA. Strain CYR-1 incubated with 10-fold diluted CW containing 5.7 g/L of acetic acid showed the higher PHA production (240.6 mg/L), whereas strain CYR-1 incubated with four-fold diluted CW containing 12.3 g/L of acetic acid showed 126 mg/L of PHA. After removing the excess protein present in CW, PHA production was further enhanced by 3.26 times (411 mg/L) at a four-fold dilution containing 11.3 g/L of acetic acid. Based on Fourier transform infrared spectroscopy (FT-IR), and ¹H and ¹³C nuclear magnetic resonance (NMR) analyses, it was confirmed that the PHA produced from the two-stage process is poly-β-hydroxybutyrate (PHB). All bands appearing in the FT-IR spectrum and the chemical shifts of NMR nearly matched with those of standard PHB. Based on these studies, we concluded that a two-stage process using Acetobacter pasteurianus C1 and Bacillus sp. CYR-1 would be applicable for the production of PHB using CW containing a low amount of lactose. Full article

(This article belongs to the Special Issue Advances in Polyhydroxyalkanoate (PHA) Production, Volume 3)

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13 pages, 509 KiB

Open AccessEditor’s ChoiceReview

Skin Manifestations after Ionizing Radiation Exposure: A Systematic Review

by Luigi Bennardo, Maria Passante, Norma Cameli, Antonio Cristaudo, Cataldo Patruno, Steven Paul Nisticò and Martina Silvestri

Bioengineering 2021, 8(11), 153; https://doi.org/10.3390/bioengineering8110153 - 22 Oct 2021

Cited by 24 | Viewed by 4570

Abstract

Morphological and functional skin alterations secondary to the action of ionizing radiation are well documented. In addition to its application in the medical field, ionizing radiation represents a public health problem for diagnostic and therapeutic purposes due to the potential risk of exposure [...] Read more.

Morphological and functional skin alterations secondary to the action of ionizing radiation are well documented. In addition to its application in the medical field, ionizing radiation represents a public health problem for diagnostic and therapeutic purposes due to the potential risk of exposure to unexpected events, such as nuclear accidents or malicious acts. With regard to the use of ionizing radiations in the medical field, today, they constitute a fundamental therapeutic method for various neoplastic pathologies. Therefore, the onset of adverse skin events induced by radiation represents a widespread and not negligible problem, affecting 95% of patients undergoing radiotherapy. A systematic literature search was performed from July 2021 up to August 2021 using PubMed, Embase, and Cochrane databases. Articles were screened by title, abstract and full text as needed. A manual search among the references of the included papers was also performed. This systematic review describes the various skin reactions that can arise following exposure to ionizing radiation and which significantly impact the quality of life, especially in cancer patients. Full article

(This article belongs to the Special Issue Quantification of Biological and Mechanical Changes Due to Radiation Exposure)

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16 pages, 17630 KiB

Open AccessEditor’s ChoiceArticle

In Situ Visualization for 3D Ultrasound-Guided Interventions with Augmented Reality Headset

by Nadia Cattari, Sara Condino, Fabrizio Cutolo, Mauro Ferrari and Vincenzo Ferrari

Bioengineering 2021, 8(10), 131; https://doi.org/10.3390/bioengineering8100131 - 25 Sep 2021

Cited by 14 | Viewed by 4002

Abstract

Augmented Reality (AR) headsets have become the most ergonomic and efficient visualization devices to support complex manual tasks performed under direct vision. Their ability to provide hands-free interaction with the augmented scene makes them perfect for manual procedures such as surgery. This study [...] Read more.

Augmented Reality (AR) headsets have become the most ergonomic and efficient visualization devices to support complex manual tasks performed under direct vision. Their ability to provide hands-free interaction with the augmented scene makes them perfect for manual procedures such as surgery. This study demonstrates the reliability of an AR head-mounted display (HMD), conceived for surgical guidance, in navigating in-depth high-precision manual tasks guided by a 3D ultrasound imaging system. The integration between the AR visualization system and the ultrasound imaging system provides the surgeon with real-time intra-operative information on unexposed soft tissues that are spatially registered with the surrounding anatomic structures. The efficacy of the AR guiding system was quantitatively assessed with an in vitro study simulating a biopsy intervention aimed at determining the level of accuracy achievable. In the experiments, 10 subjects were asked to perform the biopsy on four spherical lesions of decreasing sizes (10, 7, 5, and 3 mm). The experimental results showed that 80% of the subjects were able to successfully perform the biopsy on the 5 mm lesion, with a 2.5 mm system accuracy. The results confirmed that the proposed integrated system can be used for navigation during in-depth high-precision manual tasks. Full article

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15 pages, 4832 KiB

Open AccessEditor’s ChoiceArticle

Amphiphilic and Perfluorinated Poly(3-Hydroxyalkanoate) Nanocapsules for ¹⁹F Magnetic Resonance Imaging

by Marion Le Gal, Estelle Renard, Christelle Simon-Colin, Benoit Larrat and Valérie Langlois

Bioengineering 2021, 8(9), 121; https://doi.org/10.3390/bioengineering8090121 - 9 Sep 2021

Cited by 2 | Viewed by 3254

Abstract

Nanoparticles have recently emerged as valuable tools in biomedical imaging techniques. Here PEGylated and fluorinated nanocapsules based on poly(3-hydroxyalkanoate) containing a liquid core of perfluorooctyl bromide PFOB were formulated by an emulsion-evaporation process as potential ¹⁹F MRI imaging agents. Unsaturated poly(hydroxyalkanoate), PHAU, [...] Read more.

Nanoparticles have recently emerged as valuable tools in biomedical imaging techniques. Here PEGylated and fluorinated nanocapsules based on poly(3-hydroxyalkanoate) containing a liquid core of perfluorooctyl bromide PFOB were formulated by an emulsion-evaporation process as potential ¹⁹F MRI imaging agents. Unsaturated poly(hydroxyalkanoate), PHAU, was produced by marine bacteria using coprah oil and undecenoic acid as substrates. PHA-g-(F; PEG) was prepared by two successive controlled thiol-ene reactions from PHAU with firstly three fluorinated thiols having from 3 up to 17 fluorine atoms and secondly with PEG-SH. The resulting PHA-g-(F; PEG)-based PFOB nanocapsules, with a diameter close to 250–300 nm, are shown to be visible in ¹⁹F MRI with an acquisition time of 15 min. The results showed that PFOB-nanocapsules based on PHA-g-(F; PEG) have the potential to be used as novel contrast agents for ¹⁹F MRI. Full article

(This article belongs to the Special Issue Nano-Based Drug Delivery System: Recent Developments and Future Prospects)

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21 pages, 2821 KiB

Open AccessEditor’s ChoiceReview

Pichia pastoris (Komagataella phaffii) as a Cost-Effective Tool for Vaccine Production for Low- and Middle-Income Countries (LMICs)

by Salomé de Sá Magalhães and Eli Keshavarz-Moore

Bioengineering 2021, 8(9), 119; https://doi.org/10.3390/bioengineering8090119 - 31 Aug 2021

Cited by 27 | Viewed by 7598

Abstract

Vaccination is of paramount importance to global health. With the advent of the more recent pandemics, the urgency to expand the range has become even more evident. However, the potential limited availability and affordability of vaccines to resource low- and middle-income countries has [...] Read more.

Vaccination is of paramount importance to global health. With the advent of the more recent pandemics, the urgency to expand the range has become even more evident. However, the potential limited availability and affordability of vaccines to resource low- and middle-income countries has created a need for solutions that will ensure cost-effective vaccine production methods for these countries. Pichia pastoris (P. pastoris) (also known as Komagataella phaffii) is one of the most promising candidates for expression of heterologous proteins in vaccines development. It combines the speed and ease of highly efficient prokaryotic platforms with some key capabilities of mammalian systems, potentially reducing manufacturing costs. This review will examine the latest developments in P. pastoris from cell engineering and design to industrial production systems with focus on vaccine development and with reference to specific key case studies. Full article

(This article belongs to the Special Issue From Yeast to Biotechnology)

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29 pages, 7773 KiB

Open AccessEditor’s ChoiceReview

Stem Cell Niche Microenvironment: Review

by Mohamed Abdul-Al, George Kumi Kyeremeh, Morvarid Saeinasab, Saeed Heidari Keshel and Farshid Sefat

Bioengineering 2021, 8(8), 108; https://doi.org/10.3390/bioengineering8080108 - 28 Jul 2021

Cited by 19 | Viewed by 4754

Abstract

The cornea comprises a pool of self-regenerating epithelial cells that are crucial to preserving clarity and visibility. Limbal epithelial stem cells (LESCs), which live in a specialized stem cell niche (SCN), are crucial for the survival of the human corneal epithelium. They live [...] Read more.

The cornea comprises a pool of self-regenerating epithelial cells that are crucial to preserving clarity and visibility. Limbal epithelial stem cells (LESCs), which live in a specialized stem cell niche (SCN), are crucial for the survival of the human corneal epithelium. They live at the bottom of the limbal crypts, in a physically enclosed microenvironment with a number of neighboring niche cells. Scientists also simplified features of these diverse microenvironments for more analysis in situ by designing and recreating features of different SCNs. Recent methods for regenerating the corneal epithelium after serious trauma, including burns and allergic assaults, focus mainly on regenerating the LESCs. Mesenchymal stem cells, which can transform into self-renewing and skeletal tissues, hold immense interest for tissue engineering and innovative medicinal exploration. This review summarizes all types of LESCs, identity and location of the human epithelial stem cells (HESCs), reconstruction of LSCN and artificial stem cells for self-renewal. Full article

(This article belongs to the Special Issue Design and Fabrication of Artificial Stem Cell Microenvironments)

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29 pages, 9902 KiB

Open AccessEditor’s ChoiceReview

Bioremediation of Agricultural Soils Polluted with Pesticides: A Review

by Carla Maria Raffa and Fulvia Chiampo

Bioengineering 2021, 8(7), 92; https://doi.org/10.3390/bioengineering8070092 - 2 Jul 2021

Cited by 99 | Viewed by 18740

Abstract

Pesticides are chemical compounds used to eliminate pests; among them, herbicides are compounds particularly toxic to weeds, and this property is exploited to protect the crops from unwanted plants. Pesticides are used to protect and maximize the yield and quality of crops. The [...] Read more.

Pesticides are chemical compounds used to eliminate pests; among them, herbicides are compounds particularly toxic to weeds, and this property is exploited to protect the crops from unwanted plants. Pesticides are used to protect and maximize the yield and quality of crops. The excessive use of these chemicals and their persistence in the environment have generated serious problems, namely pollution of soil, water, and, to a lower extent, air, causing harmful effects to the ecosystem and along the food chain. About soil pollution, the residual concentration of pesticides is often over the limits allowed by the regulations. Where this occurs, the challenge is to reduce the amount of these chemicals and obtain agricultural soils suitable for growing ecofriendly crops. The microbial metabolism of indigenous microorganisms can be exploited for degradation since bioremediation is an ecofriendly, cost-effective, rather efficient method compared to the physical and chemical ones. Several biodegradation techniques are available, based on bacterial, fungal, or enzymatic degradation. The removal efficiencies of these processes depend on the type of pollutant and the chemical and physical conditions of the soil. The regulation on the use of pesticides is strictly connected to their environmental impacts. Nowadays, every country can adopt regulations to restrict the consumption of pesticides, prohibit the most harmful ones, and define the admissible concentrations in the soil. However, this variability implies that each country has a different perception of the toxicology of these compounds, inducing different market values of the grown crops. This review aims to give a picture of the bioremediation of soils polluted with commercial pesticides, considering the features that characterize the main and most used ones, namely their classification and their toxicity, together with some elements of legislation into force around the world. Full article

(This article belongs to the Special Issue Bioengineering in Remediation of Polluted Environments)

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