ABC transporter-mediated MXR mechanism in fish embryos and its potential role in the efflux of nanoparticles.

ATP-binding cassette (ABC) transporters are believed to protect aquatic organisms by pumping xenobiotics out, and recent investigation has suggested their involvement in the detoxification and efflux of nanoparticles (NPs), but their roles in fish embryos are poorly understood. In this regard, this paper summarizes the recent advances in research pertaining to the development of ABC transporter-mediated multi-xenobiotic resistance (MXR) mechanism in fish embryos and the potential interaction between ABC transporters and NPs. The paper focuses on: (1) Expression, function, and modulation mechanism of ABC proteins in fish embryos; (2) Potential interaction between ABC transporters and NPs in cell models and fish embryos. ABC transporters could be maternally transferred to fish embryos and thus play an important role in the detoxification of various chemical pollutants and NPs. There is a need to understand the specific mechanism to benefit the protection of aquatic resources.

Design and Optimization of Multi-Stage TMR Sensors for Power Equipment AC/DC Leakage Current Detection.

Tunnel magnetoresistance (TMR) can measure weak magnetic fields and has significant advantages for use in alternating current/direct current (AC/DC) leakage current sensors for power equipment; however, TMR current sensors are easily perturbed by external magnetic fields, and their measurement accuracy and measurement stability are limited in complex engineering application environments. To enhance the TMR sensor measurement performance, this paper proposes a new multi-stage TMR weak AC/DC sensor structure with high measurement sensitivity and anti-magnetic interference capability. The front-end magnetic measurement characteristics and interference immunity of the multi-stage TMR sensor are found to be closely related to the multi-stage ring size design via finite element simulation. The optimal size of the multipole magnetic ring is determined using an improved non-dominated ranking genetic algorithm (ACGWO-BP-NSGA-II) to derive the optimal sensor structure. Experimental results demonstrate that the newly designed multi-stage TMR current sensor has a measurement range of 60 mA, a fitting nonlinearity error of less than 1%, a measurement bandwidth of 0-80 kHz, a minimum AC measurement value of 85 µA and a minimum DC measurement value of 50 µA, as well as a strong external electromagnetic interference. The TMR sensor can effectively enhance measurement precision and stability in the presence of intense external electromagnetic interference.

Amyloid Protein Cross-Seeding Provides a New Perspective on Multiple Diseases In Vivo.

Amyloid protein cross-seeding is a peculiar phenomenon of cross-spreading among different diseases. Unlike traditional infectious ones, diseases caused by amyloid protein cross-seeding are spread by misfolded proteins instead of pathogens. As a consequence of the interactions among misfolded heterologous proteins or polypeptides, amyloid protein cross-seeding is considered to be the crucial cause of overlapping pathological transmission between various protein misfolding disorders (PMDs) in multiple tissues and cells. Here, we briefly review the phenomenon of cross-seeding among amyloid proteins. As an interesting example worth mentioning, the potential links between the novel coronavirus pneumonia (COVID-19) and some neurodegenerative diseases might be related to the amyloid protein cross-seeding, thus may cause an undesirable trend in the incidence of PMDs around the world. We then summarize the theoretical models as well as the experimental techniques for studying amyloid protein cross-seeding. Finally, we conclude with an outlook on the challenges and opportunities for basic research in this field. Cross-seeding of amyloid opens up a new perspective in our understanding of the process of amyloidogenesis, which is crucial for the development of new treatments for diseases. It is therefore valuable but still challenging to explore the cross-seeding system of amyloid protein as well as to reveal the structural basis and the intricate processes.

Co-Polymer Carrier with Dual Advantages of Cartilage-Penetrating and Targeting Improves Delivery and Efficacy of MicroRNA Treatment of Osteoarthritis.

Osteoarthritis (OA) is a debilitating joint disease affecting nearly 400 million people with no efficient etiological therapies. OA is primarily identified by cartilage destruction, and gradual degeneration of the whole joint would happen when the OA progresses. Hence, cartilage has been identified as the primary therapeutic target of OA. Unfortunately, numerous barriers block the delivery of therapeutic agents into cartilage, including avascular traits and high hardness of the extracellular matrix. Herein, a cartilage-targeting peptide (CAP) modified polyvinylamine (PVAm)- poly (lactic-co-glycolic acid) (PLGA) copolymer (CAP-PVAm-PLGA) is designed, which can form spherical nanoparticles with the r-miR-140 (CPP-NPs). CPP-NPs possessed enhanced mechanical properties due to the introduction of PLGA to vehicles. Meanwhile, CAP endowed the cartilage targeting which facilitated CPP-NPs localization in cartilage. With such dual advantages, CPP-NPs exhibited outstanding penetrability and accumulation in cartilage even subchondral bone, and can penetrate to a depth of 1000 µm into human cartilage. The degeneration area of cartilage is reduced by 65% and synovial inflammation score by 80% in OA mice, and the microarchitecture of subchondral bone is also ameliorated. These studies established a promising platform for therapeutic RNA delivery in OA therapy that overcame the cartilage barriers.

Machine learning links different gene patterns of viral infection to immunosuppression and immune-related biomarkers in severe burns.

Introduction: Viral infection, typically disregarded, has a significant role in burns. However, there is still a lack of biomarkers and immunotherapy targets related to viral infections in burns. Methods: Virus-related genes (VRGs) that were extracted from Gene Oncology (GO) database were included as hallmarks. Through unsupervised consensus clustering, we divided patients into two VRGs molecular patterns (VRGMPs). Weighted gene co-expression network analysis (WGCNA) was performed to study the relationship between burns and VRGs. Random forest (RF), least absolute shrinkage and selection operator (LASSO) regression, and logistic regression were used to select key genes, which were utilized to construct prognostic signatures by multivariate logistic regression. The risk score of the nomogram defined high- and low-risk groups. We compared immune cells, immune checkpoint-related genes, and prognosis between the two groups. Finally, we used network analysis and molecular docking to predict drugs targeting CD69 and SATB1. Expression of CD69 and SATB1 was validated by qPCR and microarray with the blood sample from the burn patient. Results: We established two VRGMPs, which differed in monocytes, neutrophils, dendritic cells, and T cells. In WGCNA, genes were divided into 14 modules, and the black module was correlated with VRGMPs. A total of 65 genes were selected by WGCNA, STRING, and differential expression analysis. The results of GO enrichment analysis were enriched in Th1 and Th2 cell differentiation, B cell receptor signaling pathway, alpha-beta T cell activation, and alpha-beta T cell differentiation. Then the 2-gene signature was constructed by RF, LASSO, and LOGISTIC regression. The signature was an independent prognostic factor and performed well in ROC, calibration, and decision curves. Further, the expression of immune cells and checkpoint genes differed between high- and low-risk groups. CD69 and SATB1 were differentially expressed in burns. Discussion: This is the first VRG-based signature (including 2 key genes validated by qPCR) for predicting survival, and it could provide vital guidance to achieve optimized immunotherapy for immunosuppression in burns.

A lipid-polymer hybrid nanoparticle (LPN)-loaded dissolving microneedle patch for promoting hair regrowth by transdermal miR-218 delivery.

Alopecia is the most common multifactorial hair loss disorder, affecting almost 50% of the population and even having a serious psychological impact on the patients. miR-218 has therapeutic potential for alopecia since it can activate the Wnt/ß-catenin channel by down-regulating SFRP2, which is a key channel in hair follicle cycle transformation for hair regrowth. Although miR-218 has the potential to treat this disease, several barrier properties of the skin challenge miRNA's delivery to the target location, such as passing through the corneum and resistant enzymatic degradation. To address these challenges, we evaluated a device that combined the use of hyaluronic acid (HA)-based dissolving microneedle (MN) to enhance corneum permeability with the lipid polymer hybrid nanoparticles (LPNs) as a miRNA delivery carrier to protect miR-218 from degradation. The MN patches could promote LPNs/miR-218 diffusing in the dermis region, and significantly increase the bioavailability of miR-218. Furthermore, in the shaved mouse model, the MN patches showed higher efficacy in promoting hair growth than the topical smear treatment, while avoiding the safety concern. This work established a novel and effective combination device with MN and LPNs that can be used for localized transdermal miRNA delivery to promote hair regrowth.

Tensile Experiments and Numerical Analysis of Textile-Reinforced Lightweight Engineered Cementitious Composites.

Despite many cases of textile-reinforced engineered cementitious composites (TR-ECCs) for repairing and strengthening concrete structures in the literature, research on lightweight engineered cementitious composites (LECC) combined with large rupture strain (LRS) textile and the effect of textile arrangement on tensile properties is still lacking. Therefore, this paper develops textile-reinforced lightweight engineered cementitious composites (TR-LECCs) with high strain characteristics through reinforcement ratio, arrangement form, and textile type. The study revealed that, by combining an LRS polypropylene (PP) textile and LECC, TR-LECCs with an ultimate strain of more than 8.0% (3-4 times that of traditional TR-ECCs) could be developed, and the PP textile's utilization rate seemed insensitive to the enhancement rate. The basalt fiber-reinforced polymer (BFRP) textile without epoxy resin coating had no noticeable reinforcement effect because of bond slip; in contrast, the BFRP grid with epoxy resin coating had an apparent improvement in bond performance with the matrix and a better reinforcement effect. The finite element method (FEM) verified that a concentrated arrangement increased the stress concentration in the TR-LECC, as well as the stress value. In contrast, a multilayer arrangement enabled uniform distribution of the stress value and revealed that the weft yarn could help the warp yarn to bear additional tensile loads.

A Versatile Hydrophilic and Antifouling Coating Based on Dopamine Modified Four-Arm Polyethylene Glycol by One-Step Synthesis Method.

A versatile hydrophilic and antifouling coating was designed and prepared based on catechol-modified four-arm polyethylene glycol. The dopamine (DA) molecules were grafted onto the end of the four-arm polyethylene glycol carboxyl (4A-PEG-COOH) through the amidation reaction, which was proven by 1H NMR and FTIR analysis, assisting the strong adhesion of PEG on the surface of various types of materials, including metallic, inorganic, and polymeric materials. The reduction of the water contact angle and the bacteria-repellent and protein-repellent effects indicated that the coating had good hydrophilicity and antifouling performance. Raman spectroscopy analysis demonstrated the affinity between the polymeric surface and water, which further confirmed the hydrophilicity of the coating. Finally, in vitro cytotoxicity assay demonstrated good biocompatibility of the coating layer.

Polyvinylamine with moderate binding affinity as a highly effective vehicle for RNA delivery.

Polymeric carriers for RNA therapy offer potential advantages in terms of low immunogenicity, promoting modifiability and accelerating intracellular transport. However, balancing high transfection efficacy with low toxicity remains challenging with polymer-based vehicles; indeed, polyethyleneimine (PEI) remains the "gold standard" polymer for this purpose despite its significant toxicity limitations. Herein, we demonstrate the potential of polyvinylamine (PVAm), a commodity high-charge cationic polymer used in the papermaking industry and has similar structure with PEI, as an alternative carrier for RNA delivery. High levels of transfection of normal, tumor, and stem cells with a variety of RNA cargoes including small interfering RNA (siRNA), microRNA (miRNA), and recombinant RNA can be achieved in vitro under the proper complex conditions. While, both the anti-tumor effect achieved in a xenograft osteosarcoma model and lipid-lowering activity observed in a hyperlipidemia mice indicate the potential for highly effective in vivo activity. Of note, both the transfection efficiency and the cytotoxicity of PVAm compare more favorably with those of PEI, with PVAm offering the additional advantages of simpler purification and significantly lower cost. In addition, the mechanism for the difference in transfection efficiency between PVAm and PEI is explored by molecular docking as well as analyzing the process of association and dissociation between polymers (PVAm and PEI) and nucleic acids. Our research provides a novel, non-toxic, and cost-effective carrier candidate for next generation RNA therapy, and elucidates the potential mechanism of PVAm for its efficient delivery of RNA.

Vehicle-Assisted UAV Delivery Scheme Considering Energy Consumption for Instant Delivery.

Unmanned aerial vehicles (UAVs) are increasingly used in instant delivery scenarios. The combined delivery of vehicles and UAVs has many advantages compared to their respective separate delivery, which can greatly improve delivery efficiency. Although a few studies in the literature have explored the issue of vehicle-assisted UAV delivery, we did not find any studies on the scenario of an UAV serving several customers. This study aims to design a new vehicle-assisted UAV delivery solution that allows UAVs to serve multiple customers in a single take-off and takes energy consumption into account. A multi-UAV task allocation model and a vehicle path planning model were established to determine the task allocation of the UAVs as well as the path of UAVs and the vehicle, respectively. The model also considered the impact of changing the payload of the UAV on energy consumption, bringing the results closer to reality. Finally, a hybrid heuristic algorithm based on an improved K-means algorithm and ant colony optimization (ACO) was proposed to solve the problem, and the effectiveness of the scheme was proven by multi-scale experimental instances and comparative experiments.

Formation of ß-Lactoglobulin Self-Assemblies via Liquid-Liquid Phase Separation for Applications beyond the Biological Functions.

Proteins are like miracle machines, playing important roles in living organisms. They perform vital biofunctions by further combining together and/or with other biomacromolecules to form assemblies or condensates such as membraneless organelles. Therefore, studying the self-assembly of biomacromolecules is of fundamental importance. In addition to their biological activities, protein assemblies also exhibit extra properties that enable them to achieve applications beyond their original functions. Herein, this study showed that in the presence of monosaccharides, ethylene glycols, and amino acids, ß-lactoglobulin (ß-LG) can form assemblies with specific structures, which were highly reproducible. The mechanism of the assembly process was studied through multi-scale observations and theoretical analysis, and it was found that the assembling all started from the formation of solute-rich liquid droplets via liquid-liquid phase separation (LLPS). These droplets then combined together to form condensates with elaborate structures, and the condensates finally evolved to form assemblies with various morphologies. Such a mechanism of the assembly is valuable for studying the assembly processes that frequently occur in living organisms. Detailed studies concerning the properties and applications of the obtained ß-LG assemblies showed that the assemblies exhibited significantly better performances than the protein itself in terms of autofluorescence, antioxidant activity, and metal ion absorption, which indicates broad applications of these assemblies in bioimaging, biodetection, biodiagnosis, health maintenance, and pollution treatment. This study revealed that biomacromolecules, especially proteins, can be assembled via LLPS, and some unexpected application potentials could be found beyond their original biological functions.

[Self-assembly in the transparent droplets formed during the screening of protein self-assembly conditions].

Protein self-assemblies at the micro- and nano-scale are of great interest because of their morphological diversity and good biocompatibility. High-throughput screening of protein self-assembly at different scales and morphologies using protein crystallization screening conditions is an emerging method. When using this method to screen protein self-assembly conditions, some apparently transparent droplets are often observed, in which it is not clear whether self-assembly occurs. We explored the interaction between ß-lactoglobulin and the protein crystallization kit Index™ C10 and observed the presence of micro- and nano-scale protein self-assemblies in the transparent droplets. The diverse morphology of the micro- and nano-scale self-assemblies in the transparent droplets formed by mixing different initial concentrations of ß-lactoglobulin and Index™ C10 was further investigated by scanning electron microscope. Self-assembly process of fluorescence-labelled ß-lactoglobulin was monitored continuously by laser confocal microscope, allowing real-time observation of the liquid-liquid phase separation phenomenon and the morphology of the final self-assemblies. The internal structure of the self-assemblies was gradually ordered over time by in-situ X-ray diffraction. This indicates that the self-assembly phenomenon within transparent droplets, observed in protein self-assembly condition screening experiments, is worthy of further in-depth exploration.

Database Study on the Expression and Purification of Membrane Proteins.

Membrane proteins are crucial for biological processes, and many of them are important to drug targets. Understanding the three-dimensional structures of membrane proteins are essential to evaluate their bio-function and drug design. High-purity membrane proteins are important for structural determination. Membrane proteins have low yields and are difficult to purify because they tend to aggregate. We summarized membrane protein expression systems, vectors, tags, and detergents, which have deposited in the Protein Data Bank (PDB) in recent four-and-a-half years. Escherichia coli is the most expression system for membrane proteins, and HEK293 cells are the most commonly cell lines for human membrane protein expression. The most frequently vectors are pFastBac1 for alpha-helical membrane proteins, pET28a for beta-barrel membrane proteins, and pTRC99a for monotopic membrane proteins. The most used tag for membrane proteins is the 6×His-tag. FLAG commonly used for alpha-helical membrane proteins, Strep and GST for beta- barrel and monotopic membrane proteins, respectively. The detergents and their concentrations used for alpha-helical, beta-barrel, and monotopic membrane proteins are different, and DDM is commonly used for membrane protein purification. It can guide the expression and purification of membrane proteins, thus contributing to their structure and bio function studying.

Searching for conditions of protein self-assembly by protein crystallization screening method.

The self-assembly of biomacromolecules is an extremely important process. It is potentially useful in the fields of life science and materials science. To carry out the study on the self-assembly of proteins, it is necessary to find out the suitable self-assembly conditions, which have always been a challenging task in practice. Inspired by the screening technique in the field of protein crystallization, we proposed using the same screening technique for seeking suitable protein self-assembly conditions. Based on this consideration, we selected 5 proteins (ß-lactoglobulin, hemoglobin, pepsin, lysozyme, α-chymotrypsinogen (II) A) together with 5 screening kits (IndexTM, BML, Morpheus, JCSG, PEG/Ion ScreenTM) to investigate the performance of these crystallization screening techniques in order to discover new optimized conditions of protein self-assembly. The screens were all kept at 293 K for certain days, and were analyzed using optical microscope, scanning electron microscope, transmission electron microscope, atomic force microscope, fluorescence microscope, and atomic absorption spectroscope. The results demonstrated that the method of protein crystallization screening can be successfully applied in the screening of self-assembly conditions. This method is fast, high throughput, and easily implemented in an automated system, with a low protein consumption feature. These results suggested that such strategy can be applied to finding new conditions or forms in routine research of protein self-assembly. KEY POINTS: • Protein crystallization screening method is successfully applied in the screening of self-assembly conditions. • This screening method can be applied on various kinds of proteins and possess a feature of low protein consumption. • This screening method is fast, high throughput, and easily implemented in an automated system.

Optimizing multi-supplier multi-item joint replenishment problem for non-instantaneous deteriorating items with quantity discounts.

This paper deals with a new joint replenishment problem, in which a number of non-instantaneous deteriorating items are replenished from several suppliers under different quantity discounts schemes. Involving both joint replenishment decisions and supplier selection decisions makes the problem to be NP-hard. In particular, the consideration of non-instantaneous deterioration makes it more challenging to handle. We first construct a mathematical model integrated with a supplier selection system and a joint replenishment program for non-instantaneous deteriorating items to formulate the problem. Then we develop a novel swarm intelligence optimization algorithm, the Improved Moth-flame Optimization (IMFO) algorithm, to solve the proposed model. The results of several numerical experiments analyses reveal that the IMFO algorithm is an effective algorithm for solving the proposed model in terms of solution quality and searching stableness. Finally, we conduct extensive experiments to further investigate the performance of the proposed model.

A study of degradation behaviour and biocompatibility of Zn-Fe alloy prepared by electrodeposition.

Zinc is a biodegradable metal, which exhibits more moderate biodegradability than magnesium and iron, so that it has great application potential in the field of biomedical materials. Alloying of zinc and iron may lead to producing a new type of implant material Zn-Fe alloy, which might be able to meet the requirements for a moderate degradation rate. However, due to the huge difference in the melting point between zinc and iron, the preparation of Zn-Fe alloy is quite challenging and hence rarely reported. In this study, we show that Zn-Fe alloys can be successfully prepared by electrodeposition technology. The microstructures, composition, degradation properties and biocompatibility of the Zn-Fe alloys were systematically studied. The results showed that the content of iron in the alloys ranged from 0 to 8 wt%, depending on the concentration of Fe ions and the current density. In the alloys, the major's phases were η, δ and Г1, and they were mainly affected by the ion concentration in the electrolyte. In the in vitro immersion tests, the Zn-Fe alloy ZF2-1 showed the highest immersion corrosion rate, while ZF3-1 showed the highest electrochemical corrosion rate. Moreover, we found that the corrosion rates of the alloys were significantly higher than that of the pure Fe. In the in vivo experiments, we confirmed that the Zn-Fe alloy possessed good biocompatibility. These results demonstrate that the electrodeposition technology is a good method to prepare Zn-Fe alloys, and the Zn-Fe alloys prepared by this method are potentially promising materials for biomedical applications.

Burn-Induced Apoptosis of Pulmonary Microvascular Endothelial Cell is NHE1 Dependent and Regulated by PI3K-Akt and p38 MAPK Pathways.

Na/H exchanger 1 (NHE1) is a ubiquitously expressed protein on mammalian plasma membranes and involved in cell apoptosis and tissue injury. Our previous study found that NHE1 inhibition prevents burn-induced acute lung injury (ALI). However, the potential mechanism of NHE1 in burn-induced ALI is still unclear. This study investigated the role of NHE1 in burn-induced apoptosis of human pulmonary microvascular endothelial cells. Based on the western blot analyses, real-time PCR, fluorescence spectroscopy, and apoptosis analysis, we found that burn serum significantly induced NHE1 activation, promoted intracellular Na accumulation, and elevated apoptosis ratio. Inhibition of NHE1 with cariporide reversed burn-induced intracellular Na accumulation and cell apoptosis. Different doses of cariporide also significantly decreased Cai concentrations and calpain activity induced by burn serum. Furthermore, inhibition of PI3K contributed to the increase of NHE1 activation and cell apoptosis, whereas the inhibition of p38 MAPK led to inhibition of NHE1 activation and significant decreases of cell apoptosis. The data demonstrate that NHE1 activation facilitates burn-induced endothelial cell apoptosis, mediated by Ca-dependent pathway. PI3K-Akt and p38 MAPK were found to be upstream regulators of NHE1. This study provides new mechanisms underlying burn-induced ALI.

Digital image technology based on PCA and SVM for detection and recognition of foreign bodies in lyophilized powder.

BACKGROUND: Digital image technology has made great progress in the field of foreign body detection and classification, which is of great help to drug purity extraction and impurity analysis and classification. OBJECTIVE: The detection and classification of foreign bodies in lyophilized powder are important. The method which can obtain a higher accuracy of recognition needs to be proposed. METHODS: We used digital image technology to detect and classify foreign bodies in lyophilized powder, and studied the process of image preprocessing, median filtering, Wiener filtering and average filtering balance to better detect and classify foreign bodies in lyophilized powder. RESULTS: Through industrial small sample data simulation, test results show that in the process of image preprocessing, 3 × 3 median filtering is best. In the aspect of foreign body recognition, the recognition based on principal component analysis (PCA) and support vector machine (SVM) algorithm and the recognition based on PCA and Third-Nearest Neighbor classification algorithm are compared and results show that the PCA+SVM algorithm is better. CONCLUSION: We demonstrated that integrating PCA and SVM to classify foreign bodies in lyophilized powder. Our proposed method is effective for the prediction of essential proteins.

Erratum to "The Possibility of Changing the Wettability of Material Surface by Adjusting Gravity".

[This corrects the article DOI: 10.34133/2020/2640834.].