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Showing papers in "Frontiers in Bioengineering and Biotechnology in 2022"


Journal ArticleDOI
TL;DR:
Abstract: Exosomes, a nano-sized subtype of extracellular vesicles secreted from almost all living cells, are capable of transferring cell-specific constituents of the source cell to the recipient cell. Cumulative evidence has revealed exosomes play an irreplaceable role in prognostic, diagnostic, and even therapeutic aspects. A method that can efficiently provide intact and pure exosomes samples is the first step to both exosome-based liquid biopsies and therapeutics. Unfortunately, common exosomal separation techniques suffer from operation complexity, time consumption, large sample volumes and low purity, posing significant challenges for exosomal downstream analysis. Efficient, simple, and affordable methods to isolate exosomes are crucial to carrying out relevant researches. In the last decade, emerging technologies, especially microfluidic chips, have proposed superior strategies for exosome isolation and exhibited fascinating performances. While many excellent reviews have overviewed various methods, a compressive review including updated/improved methods for exosomal isolation is indispensable. Herein, we first overview exosomal properties, biogenesis, contents, and functions. Then, we briefly outline the conventional technologies and discuss the challenges of clinical applications of these technologies. Finally, we review emerging exosomal isolation strategies and large-scale GMP production of engineered exosomes to open up future perspectives of next-generation Exo-devices for cancer diagnosis and treatment.

108 citations


Journal ArticleDOI
TL;DR: The contribution of this work is the use of genetic algorithms for path planning of robots, which enables trajectory optimization of mobile robots by reducing the error in the movement trajectory of physical robots through the interaction of virtual and real data.
Abstract: Mobile robots have an important role in material handling in manufacturing and can be used for a variety of automated tasks. The accuracy of the robot’s moving trajectory has become a key issue affecting its work efficiency. This paper presents a method for optimizing the trajectory of the mobile robot based on the digital twin of the robot. The digital twin of the mobile robot is created by Unity, and the trajectory of the mobile robot is trained in the virtual environment and applied to the physical space. The simulation training in the virtual environment provides schemes for the actual movement of the robot. Based on the actual movement data returned by the physical robot, the preset trajectory of the virtual robot is dynamically adjusted, which in turn enables the correction of the movement trajectory of the physical robot. The contribution of this work is the use of genetic algorithms for path planning of robots, which enables trajectory optimization of mobile robots by reducing the error in the movement trajectory of physical robots through the interaction of virtual and real data. It provides a method to map learning in the virtual domain to the physical robot.

54 citations


Journal ArticleDOI
TL;DR: A self-tuning particle swarm optimization (PSO) fuzzy PID positioning controller is designed based on fuzzy PID control and the results show that the transient response speed, tracking accuracy, and follower characteristics of the system are significantly improved.
Abstract: With the manipulator performs fixed-point tasks, it becomes adversely affected by external disturbances, parameter variations, and random noise. Therefore, it is essential to improve the robust and accuracy of the controller. In this article, a self-tuning particle swarm optimization (PSO) fuzzy PID positioning controller is designed based on fuzzy PID control. The quantization and scaling factors in the fuzzy PID algorithm are optimized by PSO in order to achieve high robustness and high accuracy of the manipulator. First of all, a mathematical model of the manipulator is developed, and the manipulator positioning controller is designed. A PD control strategy with compensation for gravity is used for the positioning control system. Then, the PID controller parameters dynamically are minute-tuned by the fuzzy controller 1. Through a closed-loop control loop to adjust the magnitude of the quantization factors–proportionality factors online. Correction values are outputted by the modified fuzzy controller 2. A quantization factor–proportion factor online self-tuning strategy is achieved to find the optimal parameters for the controller. Finally, the control performance of the improved controller is verified by the simulation environment. The results show that the transient response speed, tracking accuracy, and follower characteristics of the system are significantly improved.

51 citations


Journal ArticleDOI
TL;DR: The algorithm proposed in this paper improves the light loss problem in the image enhancement process, enhances the image sharpness, highlights the image details, restores the color of the image, and also reduces image noise with good edge preservation which enables a better visual perception of theimage.
Abstract: In order to solve the problems of poor image quality, loss of detail information and excessive brightness enhancement during image enhancement in low light environment, we propose a low-light image enhancement algorithm based on improved multi-scale Retinex and Artificial Bee Colony (ABC) algorithm optimization in this paper. First of all, the algorithm makes two copies of the original image, afterwards, the irradiation component of the original image is obtained by used the structure extraction from texture via relative total variation for the first image, and combines it with the multi-scale Retinex algorithm to obtain the reflection component of the original image, which are simultaneously enhanced using histogram equalization, bilateral gamma function correction and bilateral filtering. In the next part, the second image is enhanced by histogram equalization and edge-preserving with Weighted Guided Image Filtering (WGIF). Finally, the weight-optimized image fusion is performed by ABC algorithm. The mean values of Information Entropy (IE), Average Gradient (AG) and Standard Deviation (SD) of the enhanced images are respectively 7.7878, 7.5560 and 67.0154, and the improvement compared to original image is respectively 2.4916, 5.8599 and 52.7553. The results of experiment show that the algorithm proposed in this paper improves the light loss problem in the image enhancement process, enhances the image sharpness, highlights the image details, restores the color of the image, and also reduces image noise with good edge preservation which enables a better visual perception of the image.

45 citations


Journal ArticleDOI
TL;DR: The DF-ResNeSt50 network model is proposed, which introduces a simple modularized split attention block, which can improve the attention mechanism of cross-feature graph groups and proves that the proposed network model has good performance and application prospects in the intelligent detection of steel defects.
Abstract: The intelligent monitoring and diagnosis of steel defects plays an important role in improving steel quality, production efficiency, and associated smart manufacturing. The application of the bio-inspired algorithms to mechanical engineering problems is of great significance. The split attention network is an improvement of the residual network, and it is an improvement of the visual attention mechanism in the bionic algorithm. In this paper, based on the feature pyramid network and split attention network, the network is improved and optimised in terms of data enhancement, multi-scale feature fusion and network structure optimisation. The DF-ResNeSt50 network model is proposed, which introduces a simple modularized split attention block, which can improve the attention mechanism of cross-feature graph groups. Finally, experimental validation proves that the proposed network model has good performance and application prospects in the intelligent detection of steel defects.

44 citations


Journal ArticleDOI
TL;DR: In this article , the metabolites secreted by brown algae, Cystoseira crinita, were used as biocatalyst for green synthesis of magnesium oxide nanoparticles (MgO-NPs).
Abstract: Herein, the metabolites secreted by brown algae, Cystoseira crinita, were used as biocatalyst for green synthesis of magnesium oxide nanoparticles (MgO-NPs). The fabricated MgO-NPs were characterized using UV-vis spectroscopy, Fourier transforms infrared spectroscopy (FT-IR), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy linked with energy-dispersive X-ray (SEM-EDX), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Data showed successful formation of crystallographic and spherical MgO-NPs with sizes of 3–18 nm at a maximum surface plasmon resonance of 320 nm. Moreover, EDX analysis confirms the presence of Mg and O in the sample with weight percentages of 54.1% and 20.6%, respectively. Phyco-fabricated MgO-NPs showed promising activities against Gram-positive bacteria, Gram-negative bacteria, and Candida albicans with MIC values ranging between 12.5 and 50 μg mL−1. The IC50 value of MgO-NPs against cancer cell lines (Caco-2) was 113.4 μg mL−1, whereas it was 141.2 μg mL−1 for normal cell lines (Vero cell). Interestingly, the green synthesized MgO-NPs exhibited significant larvicidal and pupicidal activity against Musca domestica. At 10 μg mL−1 MgO-NPs, the highest mortality percentages were 99.0%, 95.0%, 92.2%, and 81.0% for I, II, III instars’ larvae, and pupa of M. domestica, respectively, with LC50 values (3.08, 3.49, and 4.46 μg mL−1), and LC90 values (7.46, 8.89, and 10.43 μg mL−1), respectively. Also, MgO-NPs showed repellence activity for adults of M. domestica at 10 μg mL−1 with 63.0%, 77.9%, 84.9%, and 96.8% after 12, 24, 48, and 72 h, respectively.

42 citations


Journal ArticleDOI
TL;DR: A real-time target detection method based on a lightweight convolutional neural network to reduce the number of model parameters and improve the detection speed is proposed and the experimental results verify the effectiveness and superiority of the proposed method.
Abstract: The continuous development of deep learning improves target detection technology day by day. The current research focuses on improving the accuracy of target detection technology, resulting in the target detection model being too large. The number of parameters and detection speed of the target detection model are very important for the practical application of target detection technology in embedded systems. This article proposed a real-time target detection method based on a lightweight convolutional neural network to reduce the number of model parameters and improve the detection speed. In this article, the depthwise separable residual module is constructed by combining depthwise separable convolution and non–bottleneck-free residual module, and the depthwise separable residual module and depthwise separable convolution structure are used to replace the VGG backbone network in the SSD network for feature extraction of the target detection model to reduce parameter quantity and improve detection speed. At the same time, the convolution kernels of 1 × 3 and 3 × 1 are used to replace the standard convolution of 3 × 3 by adding the convolution kernels of 1 × 3 and 3 × 1, respectively, to obtain multiple detection feature graphs corresponding to SSD, and the real-time target detection model based on a lightweight convolutional neural network is established by integrating the information of multiple detection feature graphs. This article used the self-built target detection dataset in complex scenes for comparative experiments; the experimental results verify the effectiveness and superiority of the proposed method. The model is tested on video to verify the real-time performance of the model, and the model is deployed on the Android platform to verify the scalability of the model.

39 citations


Journal ArticleDOI
TL;DR: An improved particle swarm algorithm for robot inverse kinematics solving, which can ensure higher position accuracy and orientation accuracy of the robotic arm end-effector and has shorter operation time compared with the other two algorithms.
Abstract: The analysis of robot inverse kinematic solutions is the basis of robot control and path planning, and is of great importance for research. Due to the limitations of the analytical and geometric methods, intelligent algorithms are more advantageous because they can obtain approximate solutions directly from the robot’s positive kinematic equations, saving a large number of computational steps. Particle Swarm Algorithm (PSO), as one of the intelligent algorithms, is widely used due to its simple principle and excellent performance. In this paper, we propose an improved particle swarm algorithm for robot inverse kinematics solving. Since the setting of weights affects the global and local search ability of the algorithm, this paper proposes an adaptive weight adjustment strategy for improving the search ability. Considering the running time of the algorithm, this paper proposes a condition setting based on the limit joints, and introduces the position coefficient k in the velocity factor. Meanwhile, an exponential product form modeling method (POE) based on spinor theory is chosen. Compared with the traditional DH modeling method, the spinor approach describes the motion of a rigid body as a whole and avoids the singularities that arise when described by a local coordinate system. In order to illustrate the advantages of the algorithm in terms of accuracy, time, convergence and adaptability, three experiments were conducted with a general six-degree-of-freedom industrial robotic arm, a PUMA560 robotic arm and a seven-degree-of-freedom robotic arm as the research objects. In all three experiments, the parameters of the robot arm, the range of joint angles, and the initial attitude and position of the end-effector of the robot arm are given, and the attitude and position of the impact point of the end-effector are set to verify whether the joint angles found by the algorithm can reach the specified positions. In Experiments 2 and 3, the algorithm proposed in this paper is compared with the traditional particle swarm algorithm (PSO) and quantum particle swarm algorithm (QPSO) in terms of position and direction solving accuracy, operation time, and algorithm convergence. The results show that compared with the other two algorithms, the algorithm proposed in this paper can ensure higher position accuracy and orientation accuracy of the robotic arm end-effector. the position error of the algorithm proposed in this paper is 0 and the maximum orientation error is 1.29 × 10–8. while the minimum position error of the other two algorithms is −1.64 × 10–5 and the minimum orientation error is −4.03 × 10–6. In terms of operation time, the proposed algorithm in this paper has shorter operation time compared with the other two algorithms. In the last two experiments, the computing time of the proposed algorithm is 0.31851 and 0.30004s respectively, while the shortest computing time of the other two algorithms is 0.33359 and 0.30521s respectively. In terms of algorithm convergence, the proposed algorithm can achieve faster and more stable convergence than the other two algorithms. After changing the experimental subjects, the proposed algorithm still maintains its advantages in terms of accuracy, time and convergence, which indicates that the proposed algorithm is more applicable and has certain potential in solving the multi-arm inverse kinematics solution. This paper provides a new way of thinking for solving the multi-arm inverse kinematics solution problem.

39 citations


Journal ArticleDOI
TL;DR: In this paper , a review of green methods of synthesizing nanoparticles and their utilization in the scientific world is presented, where the authors discuss some unresolved issues such as particle size and shape consistency, reproducibility of the synthesis process, and understanding of the mechanisms involved in producing metallic nanoparticles via biological entities.
Abstract: Current advancements in nanotechnology and nanoscience have resulted in new nanomaterials, which may pose health and environmental risks. Furthermore, several researchers are working to optimize ecologically friendly procedures for creating metal and metal oxide nanoparticles. The primary goal is to decrease the adverse effects of synthetic processes, their accompanying chemicals, and the resulting complexes. Utilizing various biomaterials for nanoparticle preparation is a beneficial approach in green nanotechnology. Furthermore, using the biological qualities of nature through a variety of activities is an excellent way to achieve this goal. Algae, plants, bacteria, and fungus have been employed to make energy-efficient, low-cost, and nontoxic metallic nanoparticles in the last few decades. Despite the environmental advantages of using green chemistry-based biological synthesis over traditional methods as discussed in this article, there are some unresolved issues such as particle size and shape consistency, reproducibility of the synthesis process, and understanding of the mechanisms involved in producing metallic nanoparticles via biological entities. Consequently, there is a need for further research to analyze and comprehend the real biological synthesis-dependent processes. This is currently an untapped hot research topic that required more investment to properly leverage the green manufacturing of metallic nanoparticles through living entities. The review covers such green methods of synthesizing nanoparticles and their utilization in the scientific world.

37 citations


Journal ArticleDOI
TL;DR: A highly smooth and time-saving approach to trajectory planning is obtained by improving the kinematic and optimization algorithms for the time-optimal trajectory planning problem by partitioning the joint space and obtains an inverse solution calculation based on the partitioning of the Joint space.
Abstract: Complete trajectory planning includes path planning, inverse solution solving and trajectory optimization. In this paper, a highly smooth and time-saving approach to trajectory planning is obtained by improving the kinematic and optimization algorithms for the time-optimal trajectory planning problem. By partitioning the joint space, the paper obtains an inverse solution calculation based on the partitioning of the joint space, saving 40% of the inverse kinematics solution time. This means that a large number of computational resources can be saved in trajectory planning. In addition, an improved sparrow search algorithm (SSA) is proposed to complete the solution of the time-optimal trajectory. A Tent chaotic mapping was used to optimize the way of generating initial populations. The algorithm was further improved by combining it with an adaptive step factor. The experiments demonstrated the performance of the improved SSA. The robot’s trajectory is further optimized in time by an improved sparrow search algorithm. Experimental results show that the method can improve convergence speed and global search capability and ensure smooth trajectories.

33 citations


Journal ArticleDOI
TL;DR: The role of ROS in the bone microenvironment is introduced, the mechanism and development of ROS-responsive biomaterials are summarized, and their completion and potential for future therapy of bone-related diseases are summarized.
Abstract: Reactive oxygen species (ROS) are the key signaling molecules in many physiological signs of progress and are associated with almost all diseases, such as atherosclerosis, aging, and cancer. Bone is a specific connective tissue consisting of cells, fibers, and mineralized extracellular components, and its quality changes with aging and disease. Growing evidence indicated that overproduced ROS accumulation may disrupt cellular homeostasis in the progress of bone modeling and remodeling, leading to bone metabolic disease. Thus, ROS-responsive biomaterials have attracted great interest from many researchers as promising strategies to realize drug release or targeted therapy for bone-related diseases. Herein, we endeavor to introduce the role of ROS in the bone microenvironment, summarize the mechanism and development of ROS-responsive biomaterials, and their completion and potential for future therapy of bone-related diseases.

Journal ArticleDOI
TL;DR: Recent efforts in converting HA to smart formulation, such as multifunctional coatings, targeted nanoparticles, or injectable hydrogels, which are used in advanced biomedical application are highlighted.
Abstract: Hyaluronic acid (HA) is a large non-sulfated glycosaminoglycan that is the main component of the extracellular matrix (ECM). Because of its strong and diversified functions applied in broad fields, HA has been widely studied and reported previously. The molecular properties of HA and its derivatives, including a wide range of molecular weights but distinct effects on cells, moisture retention and anti-aging, and CD44 targeting, promised its role as a popular participant in tissue engineering, wound healing, cancer treatment, ophthalmology, and cosmetics. In recent years, HA and its derivatives have played an increasingly important role in the aforementioned biomedical fields in the formulation of coatings, nanoparticles, and hydrogels. This article highlights recent efforts in converting HA to smart formulation, such as multifunctional coatings, targeted nanoparticles, or injectable hydrogels, which are used in advanced biomedical application.

Journal ArticleDOI
TL;DR: In this article , a decoupling control algorithm is proposed and a single control volume-single attitude angle model is constructed for the problem of severe coupling in the control system of attitude of six degrees of freedom.
Abstract: Autonomous Underwater Vehicle are widely used in industries, such as marine resource exploitation and fish farming, but they are often subject to a large amount of interference which cause poor control stability, while performing their tasks. A decoupling control algorithm is proposed and A single control volume–single attitude angle model is constructed for the problem of severe coupling in the control system of attitude of six degrees of freedom Autonomous Underwater Vehicle. Aiming at the problem of complex Active Disturbance Rejection Control (ADRC) adjustment relying on manual experience, the PSO-ADRC algorithm is proposed to realize the automatic adjustment of its parameters, which improves the anti-interference ability and control accuracy of Autonomous Underwater Vehicle in dynamic environment. The anti-interference ability and control accuracy of the method were verified through experiments.

Journal ArticleDOI
TL;DR: A snapshot of this fast-evolving OoC technology is provided, discusses current applications and highlights advantages and disadvantages for biomedical approaches.
Abstract: Organ-on-a-chip (OoC), also known as micro physiological systems or “tissue chips” have attracted substantial interest in recent years due to their numerous applications, especially in precision medicine, drug development and screening. Organ-on-a-chip devices can replicate key aspects of human physiology, providing insights into the studied organ function and disease pathophysiology. Moreover, these can accurately be used in drug discovery for personalized medicine. These devices present useful substitutes to traditional preclinical cell culture methods and can reduce the use of in vivo animal studies. In the last few years OoC design technology has seen dramatic advances, leading to a wide range of biomedical applications. These advances have also revealed not only new challenges but also new opportunities. There is a need for multidisciplinary knowledge from the biomedical and engineering fields to understand and realize OoCs. The present review provides a snapshot of this fast-evolving technology, discusses current applications and highlights advantages and disadvantages for biomedical approaches.

Journal ArticleDOI
TL;DR: A review of different natural matrixes recently employed for designing novel therapeutic alternatives for treating cutaneous injuries, and overview some future perspectives in this area can be found in this article , where decellularized tissues have been proposed as an alternative for reconstructing cutaneous lesions since they maintain the complex protein conformation, providing the required functional domains for cell differentiation.
Abstract: The absence or damage of a tissue is the main cause of most acute or chronic diseases and are one of the appealing challenges that novel therapeutic alternatives have, in order to recover lost functions through tissue regeneration. Chronic cutaneous lesions are the most frequent cause of wounds, being a massive area of regenerative medicine and tissue engineering to have efforts to develop new bioactive medical products that not only allow an appropriate and rapid healing, but also avoid severe complications such as bacterial infections. In tissue repair and regeneration processes, there are several overlapping stages that involve the synergy of cells, the extracellular matrix (ECM) and biomolecules, which coordinate processes of ECM remodeling as well as cell proliferation and differentiation. Although these three components play a crucial role in the wound healing process, the ECM has the function of acting as a biological platform to permit the correct interaction between them. In particular, ECM is a mixture of crosslinked proteins that contain bioactive domains that cells recognize in order to promote migration, proliferation and differentiation. Currently, tissue engineering has employed several synthetic polymers to design bioactive scaffolds to mimic the native ECM, by combining biopolymers with growth factors including collagen and fibrinogen. Among these, decellularized tissues have been proposed as an alternative for reconstructing cutaneous lesions since they maintain the complex protein conformation, providing the required functional domains for cell differentiation. In this review, we present an in-depth discussion of different natural matrixes recently employed for designing novel therapeutic alternatives for treating cutaneous injuries, and overview some future perspectives in this area.

Journal ArticleDOI
TL;DR:
Abstract: Treating large bone defects, known as critical-sized defects (CSDs), is challenging because they are not spontaneously healed by the patient’s body. Due to the limitations associated with conventional bone grafts, bone tissue engineering (BTE), based on three-dimensional (3D) bioprinted scaffolds, has emerged as a promising approach for bone reconstitution and treatment. Bioprinting technology allows for incorporation of living cells and/or growth factors into scaffolds aiming to mimic the structure and properties of the native bone. To date, a wide range of biomaterials (either natural or synthetic polymers), as well as various cells and growth factors, have been explored for use in scaffold bioprinting. However, a key challenge that remains is the fabrication of scaffolds that meet structure, mechanical, and osteoconductive requirements of native bone and support vascularization. In this review, we briefly present the latest developments and discoveries of CSD treatment by means of bioprinted scaffolds, with a focus on the biomaterials, cells, and growth factors for formulating bioinks and their bioprinting techniques. Promising state-of-the-art pathways or strategies recently developed for bioprinting bone scaffolds are highlighted, including the incorporation of bioactive ceramics to create composite scaffolds, the use of advanced bioprinting technologies (e.g., core/shell bioprinting) to form hybrid scaffolds or systems, as well as the rigorous design of scaffolds by taking into account of the influence of such parameters as scaffold pore geometry and porosity. We also review in-vitro assays and in-vivo models to track bone regeneration, followed by a discussion of current limitations associated with 3D bioprinting technologies for BTE. We conclude this review with emerging approaches in this field, including the development of gradient scaffolds, four-dimensional (4D) printing technology via smart materials, organoids, and cell aggregates/spheroids along with future avenues for related BTE.

Journal ArticleDOI
TL;DR: In this paper , a deep convolutional neural network based on the encoder-decoder structure is proposed, which can accurately decode stress distribution information from complex photoelastic fringe images generated under different experimental configurations.
Abstract: Recent work has shown that deep convolutional neural network is capable of solving inverse problems in computational imaging, and recovering the stress field of the loaded object from the photoelastic fringe pattern can also be regarded as an inverse problem solving process. However, the formation of the fringe pattern is affected by the geometry of the specimen and experimental configuration. When the loaded object produces complex fringe distribution, the traditional stress analysis methods still face difficulty in unwrapping. In this study, a deep convolutional neural network based on the encoder–decoder structure is proposed, which can accurately decode stress distribution information from complex photoelastic fringe images generated under different experimental configurations. The proposed method is validated on a synthetic dataset, and the quality of stress distribution images generated by the network model is evaluated using mean squared error (MSE), structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and other evaluation indexes. The results show that the proposed stress recovery network can achieve an average performance of more than 0.99 on the SSIM.

Journal ArticleDOI
TL;DR: In this article , an aqueous extract obtained from chickpea (Cicer arietinum L.) (CA) leaves was used in order to synthesize silver nanoparticles (AgNPs).
Abstract: Using biological materials to synthesize metallic nanoparticles has become a frequently preferred method by researchers. This synthesis method is both fast and inexpensive. In this study, an aqueous extract obtained from chickpea (Cicer arietinum L.) (CA) leaves was used in order to synthesize silver nanoparticles (AgNPs). For specification of the synthesized AgNPs, UV-vis spectrophotometer, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction analysis (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), electron dispersive X-ray (EDX), and zeta potential (ZP) analyses data were used. Biologically synthesized AgNPs demonstrated a maximum surface plasmon resonance of 417.47 nm after 3 h. With the powder XRD model, the mean crystallite dimension of nanoparticles was determined as 12.17 mm with a cubic structure. According to the TEM results, the dimensions of the obtained silver nanoparticles were found to be 6.11–9.66 nm. The ZP of the electric charge on the surface of AgNPs was measured as −19.6 mV. The inhibition effect of AgNPs on food pathogen strains and yeast was determined with the minimum inhibition concentration (MIC) method. AgNPs demonstrated highly effective inhibition at low concentrations especially against the growth of B. subtilis (0.0625) and S. aureus (0.125) strains. The cytotoxic effects of silver nanoparticles on cancerous cell lines (CaCo-2, U118, Sk-ov-3) and healthy cell lines (HDF) were revealed. Despite the increase of AgNPs used against cancerous and healthy cell lines, no significant decrease in the percentage of viability was detected.

Journal ArticleDOI
TL;DR: In this paper , the authors investigated the changes in CH4 emission reduction and biological characteristics, and BLCS was prepared as control, and showed that rainwater retention time in HLCS was reduced by half.
Abstract: Biochar-amended landfill cover soil (BLCS) can promote CH4 and O2 diffusion, but it increases rainwater entry in the rainy season, which is not conducive to CH4 emission reduction. Hydrophobic biochar–amended landfill cover soil (HLCS) was prepared to investigate the changes in CH4 emission reduction and biological characteristics, and BLCS was prepared as control. Results showed that rainwater retention time in HLCS was reduced by half. HLCS had a higher CH4 reduction potential, achieving 100% CH4 removal at 25% CH4 content of landfill gas, and its main contributors to CH4 reduction were found to be at depths of 10–30 cm (upper layer) and 50–60 cm (lower layer). The relative abundances of methane-oxidizing bacteria (MOB) in the upper and lower layers of HLCS were 55.93% and 46.93%, respectively, higher than those of BLCS (50.80% and 31.40%, respectively). Hydrophobic biochar amended to the landfill cover soil can realize waterproofing, ventilation, MOB growth promotion, and efficient CH4 reduction.

Journal ArticleDOI
TL;DR: In this paper , the potential of the nanoscale structure is utilized by electrospun nanofibers, which are promising materials for wound dressings and different properties including morphology, physicomechanical, interaction with water, antibacterial efficiency, and in vitro studies were investigated.
Abstract: The potential of the nanoscale structure is utilized by electrospun nanofibers, which are promising materials for wound dressings. Here, we prepared wound dressings constituting polycaprolactone (PCL) and chitosan (CS). Curcumin (Cur) and zinc oxide nanoparticles (ZnO) as antibacterial agents were embedded in PCL/CS electrospun nanofibers and different properties including morphology, physicomechanical, interaction with water, antibacterial efficiency, and in vitro studies were investigated. SEM images confirmed the nanofibrous structure of samples with 100 ± 5 to 212 ± 25 nm in average diameter. Elemental analysis of nanofibers showed a good distribution of ZnO along nanofibers which not only caused decreasing in nanofiber diameter but also increased tensile strength of nanofibers up to 2.9 ± 0.5 MPa and with good elongation at break of 39 ± 2.9. ZnO nanoparticles also facilitated the interaction of nanofibers with water, and this led to the highest water vapor transition rate, which was equal to 0.28 ± 0.02 g cm−2 day−1. The sample containing 3 wt% Cur had the highest water uptake value (367 ± 15%) and the lowest water contact angle (78 ± 3.7°), although Cur has a hydrophobic nature. The release profile of Cur showed a two-stage release and the Peppas model predicted a non-fickian diffusion. Simultaneous incorporation of CS, ZnO, and Cur effectively inhibited bacterial growth. In addition, in vitro studies represented that high content of Cur decreases cell viability and cell attachment. The outcomes from the fabricated nanofibrous scaffolds demonstrated appropriate properties for application as a wound dressing.

Journal ArticleDOI
TL;DR: This review focuses on the design of hydrogels with different stiffness and their effects on the behavior of MSCs, and the relationship between the phenotype changes of macrophages on inflammatory response and tissue repair is discussed.
Abstract: Tissue repair after trauma and infection has always been a difficult problem in regenerative medicine. Hydrogels have become one of the most important scaffolds for tissue engineering due to their biocompatibility, biodegradability and water solubility. Especially, the stiffness of hydrogels is a key factor, which influence the morphology of mesenchymal stem cells (MSCs) and their differentiation. The researches on this point are meaningful to the field of tissue engineering. Herein, this review focus on the design of hydrogels with different stiffness and their effects on the behavior of MSCs. In addition, the effect of hydrogel stiffness on the phenotype of macrophages is introduced, and then the relationship between the phenotype changes of macrophages on inflammatory response and tissue repair is discussed. Finally, the future application of hydrogels with a certain stiffness in regenerative medicine and tissue engineering has been prospected.

Journal ArticleDOI
TL;DR: Yeast surface display is presented as a cutting-edge technology for the vectorial expression of proteins and peptides as a promising technology that is not yet optimized for biotechnological applications.
Abstract: Yeast surface display (YSD) is a “whole-cell” platform used for the heterologous expression of proteins immobilized on the yeast’s cell surface. YSD combines the advantages eukaryotic systems offer such as post-translational modifications, correct folding and glycosylation of proteins, with ease of cell culturing and genetic manipulation, and allows of protein immobilization and recovery. Additionally, proteins displayed on the surface of yeast cells may show enhanced stability against changes in temperature, pH, organic solvents, and proteases. This platform has been used to study protein-protein interactions, antibody design and protein engineering. Other applications for YSD include library screening, whole-proteome studies, bioremediation, vaccine and antibiotics development, production of biosensors, ethanol production and biocatalysis. YSD is a promising technology that is not yet optimized for biotechnological applications. This mini review is focused on recent strategies to improve the efficiency and selection of displayed proteins. YSD is presented as a cutting-edge technology for the vectorial expression of proteins and peptides. Finally, recent biotechnological applications are summarized. The different approaches described herein could allow for a better strategy cascade for increasing protein/peptide interaction and production.

Journal ArticleDOI
TL;DR: In this paper , the authors conducted a series of test tube experiments to investigate the effect of calcium source on the lead and copper removals, and numerical simulations were performed using Visual MINTEQ software package considering different degrees of urea hydrolysis derived from the experiments.
Abstract: Heavy metal contamination not only causes threat to human health but also raises sustainable development concerns. The use of traditional methods to remediate heavy metal contamination is however time-consuming, and the remediation efficiency may not meet the requirements as expected. The present study conducted a series of test tube experiments to investigate the effect of calcium source on the lead and copper removals. In addition to the test tube experiments, numerical simulations were performed using Visual MINTEQ software package considering different degrees of urea hydrolysis derived from the experiments. The remediation efficiency degrades when NH4 + and OH− concentrations are not sufficient to precipitate the majority of Pb2+ and Cu2+. It also degrades when CaO turns pH into highly alkaline conditions. The numerical simulations do not take the dissolution of precipitation into account and therefore overestimate the remediation efficiency when subjected to lower Pb(NO3)2 or Cu(NO3)2 concentrations. The findings highlight the potential of applying the enzyme-induced carbonate precipitation to lead and copper remediations.

Journal ArticleDOI
TL;DR: Gallium (III) is a multi-target antibacterial agent that has an excellent antibacterial activity, especially against MDR pathogens; thus, a gallium ( III)-based treatment is expected to become a new antibacterial strategy.
Abstract: With the abuse and misuse of antibiotics, antimicrobial resistance has become a challenging issue in the medical system. Iatrogenic and non-iatrogenic infections caused by multidrug-resistant (MDR) pathogens pose serious threats to global human life and health because the efficacy of traditional antibiotics has been greatly reduced and the resulting socio-economic burden has increased. It is important to find and develop non-antibiotic-dependent antibacterial strategies because the development of new antibiotics can hardly keep pace with the emergence of resistant bacteria. Gallium (III) is a multi-target antibacterial agent that has an excellent antibacterial activity, especially against MDR pathogens; thus, a gallium (III)-based treatment is expected to become a new antibacterial strategy. However, some limitations of gallium ions as antimicrobials still exist, including low bioavailability and explosive release. In recent years, with the development of nanomaterials and clathrates, the progress of manufacturing technology, and the emergence of synergistic antibacterial strategies, the antibacterial activities of gallium have greatly improved, and the scope of application in medical systems has expanded. This review summarizes the advancement of current optimization for these key factors. This review will enrich the knowledge about the efficiency and mechanism of various gallium-based antibacterial agents and provide strategies for the improvement of the antibacterial activity of gallium-based compounds.

Journal ArticleDOI
TL;DR: An overview of the main bioactive components found in agroindustrial by-products and the biological strategies for their extraction is provided and information to enhance the use of these bioactive compounds, especially for the food and pharmaceutical industries is provided.
Abstract: Bioactive compounds can provide health benefits beyond the nutritional value and are originally present or added to food matrices. However, because they are part of the food matrices, most bioactive compounds remain in agroindustrial by-products. Agro-industrial by-products are generated in large quantities throughout the food production chain and can—when not properly treated—affect the environment, the profit, and the proper and nutritional distribution of food to people. Thus, it is important to adopt processes that increase the use of these agroindustrial by-products, including biological approaches, which can enhance the extraction and obtention of bioactive compounds, which enables their application in food and pharmaceutical industries. Biological processes have several advantages compared to nonbiological processes, including the provision of extracts with high quality and bioactivity, as well as extracts that present low toxicity and environmental impact. Among biological approaches, extraction from enzymes and fermentation stand out as tools for obtaining bioactive compounds from various agro-industrial wastes. In this sense, this article provides an overview of the main bioactive components found in agroindustrial by-products and the biological strategies for their extraction. We also provide information to enhance the use of these bioactive compounds, especially for the food and pharmaceutical industries.

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TL;DR: MSCs-derived exosomes have regenerative and tissue repair functions comparable to MSCs and can circumvent the risks of immune rejection and infection associated with MSC transplantation, indicating that they may be a viable alternative to M SCs’ biological functions.
Abstract: Exosomes are tiny vesicles with a double membrane structure that cells produce. They range in diameter from 40 to 150 nm and may contain a variety of biomolecules including proteins and nucleic acids. Exosomes have low toxicity, low immunogenicity, and the ability to encapsulate a wide variety of substances, making them attractive drug delivery vehicles. MSCs secrete large amounts of exosomes and hence serve as an excellent source of exosomes. MSCs-derived exosomes have regenerative and tissue repair functions comparable to MSCs and can circumvent the risks of immune rejection and infection associated with MSC transplantation, indicating that they may be a viable alternative to MSCs’ biological functions. In this review, we summarized the drug delivery methods and advantages of exosomes, as well as the advancement of MSC exosomes as drug carriers. The challenges and prospects of using exosomes as drug delivery vectors are presented.

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TL;DR: It is suggested that HUC-Exos accelerate diabetic cutaneous wound healing, providing a promising therapeutic strategy for chronic diabetic wound repair.
Abstract: Diabetic wounds remain a great challenge for clinicians due to the multiple bacterial infections and oxidative damage. Exosomes, as an appealing nanodrug delivery system, have been widely applied in the treatment of diabetic wounds. Endovascular cells are important component cells of the vascular wall. Herein, we investigated the effects of HUCMSCs and HUC-Exos (exosomes secreted by HUCMSCs) on diabetic wound healing. In this study, HUVECs were coincubated with HUCMSCs, and HUC-Exos were utilized for in vitro and in vivo experiments to verify their roles in the regulation of diabetic wound healing. Our results demonstrated that HUCMSCs have the ability to regulate oxidative stress injuries of endothelial cells through exosomes and accelerate diabetic cutaneous wound healing in vitro. The present study suggests that HUC-Exos accelerate diabetic cutaneous wound healing, providing a promising therapeutic strategy for chronic diabetic wound repair.

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TL;DR: Zhang et al. as mentioned in this paper improved the vertical grid number of the YOLO algorithm by using 20 convolutional layers and five maximum aggregation layers to detect the target in real time on the processed superpixel image array.
Abstract: With the development of bionic computer vision for images processing, researchers have easily obtained high-resolution zoom sensing images. The development of drones equipped with high-definition cameras has greatly increased the sample size and image segmentation and target detection are important links during the process of image information. As biomimetic remote sensing images are usually prone to blur distortion and distortion in the imaging, transmission and processing stages, this paper improves the vertical grid number of the YOLO algorithm. Firstly, the light and shade of a high-resolution zoom sensing image were abstracted, and the grey-level cooccurrence matrix extracted feature parameters to quantitatively describe the texture characteristics of the zoom sensing image. The Simple Linear Iterative Clustering (SLIC) superpixel segmentation method was used to achieve the segmentation of light/dark scenes, and the saliency area was obtained. Secondly, a high-resolution zoom sensing image model for segmenting light and dark scenes was established to made the dataset meet the recognition standard. Due to the refraction of the light passing through the lens and other factors, the difference of the contour boundary light and dark value between the target pixel and the background pixel would make it difficult to detect the target, and the pixels of the main part of the separated image would be sharper for edge detection. Thirdly, a YOLO algorithm with an improved vertical grid number was proposed to detect the target in real time on the processed superpixel image array. The adjusted aspect ratio of the target in the remote sensing image modified the number of vertical grids in the YOLO network structure by using 20 convolutional layers and five maximum aggregation layers, which was more accurately adapted to “short and coarse” of the identified object in the information density. Finally, through comparison with the improved algorithm and other mainstream algorithms in different environments, the test results on the aid dataset showed that in the target detection of high spatial resolution zoom sensing images, the algorithm in this paper showed higher accuracy than the YOLO algorithm and had real-time performance and detection accuracy.

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TL;DR: This review has outlined recent decellularization and sterilization strategies, evaluation tests for efficient deCellularization, materials processing, application, and challenges and future outlooks of de cellularization in regenerative medicine and tissue engineering.
Abstract: Reproduction of different tissues using scaffolds and materials is a major element in regenerative medicine. The regeneration of whole organs with decellularized extracellular matrix (dECM) has remained a goal despite the use of these materials for different purposes. Recently, decellularization techniques have been widely used in producing scaffolds that are appropriate for regenerating damaged organs and may be able to overcome the shortage of donor organs. Decellularized ECM offers several advantages over synthetic compounds, including the preserved natural microenvironment features. Different decellularization methods have been developed, each of which is appropriate for removing cells from specific tissues under certain conditions. A variety of methods have been advanced for evaluating the decellularization process in terms of cell removal efficiency, tissue ultrastructure preservation, toxicity, biocompatibility, biodegradability, and mechanical resistance in order to enhance the efficacy of decellularization methods. Modification techniques improve the characteristics of decellularized scaffolds, making them available for the regeneration of damaged tissues. Moreover, modification of scaffolds makes them appropriate options for drug delivery, disease modeling, and improving stem cells growth and proliferation. However, considering different challenges in the way of decellularization methods and application of decellularized scaffolds, this field is constantly developing and progressively moving forward. This review has outlined recent decellularization and sterilization strategies, evaluation tests for efficient decellularization, materials processing, application, and challenges and future outlooks of decellularization in regenerative medicine and tissue engineering.

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TL;DR: The importance of tailoring the physicochemical performance and biological functions of polysaccharide-based hydrogel wound dressings is highlighted, aiming to provide valuable hints and references for the future development of more intelligent and multifunctional wound Dressings of polySaccharide hydrogels.
Abstract: Wound management remains a worldwide challenge. It is undeniable that patients with problems such as difficulties in wound healing, metabolic disorder of the wound microenvironment and even severely infected wounds etc. always suffer great pain that affected their quality of lives. The selection of appropriate wound dressings is vital for the healing process. With the advances of technology, hydrogels dressings have been showing great potentials for the treatment of both acute wounds (e.g., burn injuries, hemorrhage, rupturing of internal organs/aorta) and chronic wounds such as diabetic foot and pressure ulcer. Particularly, in the past decade, polysaccharide-based hydrogels which are made up with abundant and reproducible natural materials that are biocompatible and biodegradable present unique features and huge flexibilities for modifications as wound dressings and are widely applicable in clinical practices. They share not only common characteristics of hydrogels such as excellent tissue adhesion, swelling, water absorption, etc., but also other properties (e.g., anti-inflammatory, bactericidal and immune regulation), to accelerate wound re-epithelialization, mimic skin structure and induce skin regeneration. Herein, in this review, we highlighted the importance of tailoring the physicochemical performance and biological functions of polysaccharide-based hydrogel wound dressings. We also summarized and discussed their clinical states of, aiming to provide valuable hints and references for the future development of more intelligent and multifunctional wound dressings of polysaccharide hydrogels.