The creation of new business is naturally formed by the development of information technology, industrial upgrading, the growth of people’s demand, and the replacement of the employment model, and ...with the support of the government, it will be further developed to realize the replacement of the old and the new and lead to a new generation of employment wave. In this paper, we will analyze the conceptual interpretation, development status and achievements of the new industry to help the new industry to further develop and improve.
Abstract
Motivation
The identification of compound–protein interactions (CPIs) is an essential step in the process of drug discovery. The experimental determination of CPIs is known for a large ...amount of funds and time it consumes. Computational model has therefore become a promising and efficient alternative for predicting novel interactions between compounds and proteins on a large scale. Most supervised machine learning prediction models are approached as a binary classification problem, which aim to predict whether there is an interaction between the compound and the protein or not. However, CPI is not a simple binary on–off relationship, but a continuous value reflects how tightly the compound binds to a particular target protein, also called binding affinity.
Results
In this study, we propose an end-to-end neural network model, called BACPI, to predict CPI and binding affinity. We employ graph attention network and convolutional neural network (CNN) to learn the representations of compounds and proteins and develop a bi-directional attention neural network model to integrate the representations. To evaluate the performance of BACPI, we use three CPI datasets and four binding affinity datasets in our experiments. The results show that, when predicting CPIs, BACPI significantly outperforms other available machine learning methods on both balanced and unbalanced datasets. This suggests that the end-to-end neural network model that predicts CPIs directly from low-level representations is more robust than traditional machine learning-based methods. And when predicting binding affinities, BACPI achieves higher performance on large datasets compared to other state-of-the-art deep learning methods. This comparison result suggests that the proposed method with bi-directional attention neural network can capture the important regions of compounds and proteins for binding affinity prediction.
Availability and implementation
Data and source codes are available at https://github.com/CSUBioGroup/BACPI
Abstract
Herein, an intelligent biodegradable hollow manganese dioxide (H-MnO
2
) nano-platform is developed for not only tumor microenvironment (TME)-specific imaging and on-demand drug release, but ...also modulation of hypoxic TME to enhance cancer therapy, resulting in comprehensive effects favoring anti-tumor immune responses. With hollow structures, H-MnO
2
nanoshells post modification with polyethylene glycol (PEG) could be co-loaded with a photodynamic agent chlorine e6 (Ce6), and a chemotherapy drug doxorubicin (DOX). The obtained H-MnO
2
-PEG/C&D would be dissociated under reduced pH within TME to release loaded therapeutic molecules, and in the meantime induce decomposition of tumor endogenous H
2
O
2
to relieve tumor hypoxia. As a result, a remarkable in vivo synergistic therapeutic effect is achieved through the combined chemo-photodynamic therapy, which simultaneously triggers a series of anti-tumor immune responses. Its further combination with checkpoint-blockade therapy would lead to inhibition of tumors at distant sites, promising for tumor metastasis treatment.
Face de-identification has become increasingly important as the image sources are explosively growing and easily accessible. The advance of new face recognition techniques also arises people’s ...concern regarding the privacy leakage. The mainstream pipelines of face de-identification are mostly based on the k-same framework, which bears critiques of low effectiveness and poor visual quality. In this paper, we propose a new framework called Privacy-Protective-GAN (PP-GAN) that adapts GAN (generative adversarial network) with novel verificator and regulator modules specially designed for the face de-identification problem to ensure generating de-identified output with retained structure similarity according to a single input. We evaluate the proposed approach in terms of privacy protection, utility preservation, and structure similarity. Our approach not only outperforms existing face de-identification techniques but also provides a practical framework of adapting GAN with priors of domain knowledge.
Superhydrophilic-underwater superoleophobic (SUS) membranes have been demonstrated to be promising materials for oily wastewater treatment. However, development of facile, low cost and robust SUS ...membrane with high flux and less membrane fouling is still challenging. In this study, we reported a simple electrospinning/in-situ growth strategy to prepare SUS SiO2@PVA nanofibrous membrane for gravity-driven separation of oil/water mixture. In specific, a highly porous PVA nanofibrous membrane was first fabricated by electrospinning technique, followed by an in-situ growth of silica nanoparticles on the pristine PVA nanofibers through a modified Stöber reaction. The abundant hydroxyl groups on PVA nanofibers enabled uniform and stable deposition of silica nanoparticles, thus simultaneously realizing high surface energy surface (hydrophilic nature of PVA and silica) and multi-scale roughness. As expected, the resultant membrane exhibited excellent in-air “water-loving” (instantaneous in-air water wetting) and underwater “oil-hating” properties (underwater oil contact angle of 161.8° and sliding angle of 6.2°). The SUS SiO2@PVA membranes exhibited efficient separation of both free oil/water mixture and a variety of surfactant-stabilized oil-in-water emulsions in a gravity-driven filtration process. In addition, oil density played an important role during the separation process, due to superior separation performance was achieved for lighter-than-water oil when compared to heavier-than-water oils. Moreover, the membrane showed robust reusability that it maintained stable oil rejection and permeate flux in cyclic experiments.
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•In situ silica growth on PVA nanofibers to achieve superwetting property.•Excellent in-air water-loving and under-water oil-hating properties achieved.•The membrane realized efficient oil-in-water emulsion separation under gravity.•Oil density plays an important role in the oil/water separation process.•The membrane maintained stable rejection and flux in cyclic experiments.
Ion transport in crystalline fast ionic conductors is a complex physical phenomenon. Certain ionic species (e.g., Ag+, Cu+, Li+, F–, O2–, H+) in a solid crystalline framework can move as fast as in ...liquids. This property, although only observed in a limited number of materials, is a key enabler for a broad range of technologies, including batteries, fuel cells, and sensors. However, the mechanisms of ion transport in the crystal lattice of fast ionic conductors are still not fully understood despite the substantial progress achieved in the last 40 years, partly because of the wide range of length and time scales involved in the complex migration processes of ions in solids. Without a comprehensive understanding of these ion transport mechanisms, the rational design of new fast ionic conductors is not possible. In this review, we cover classical and emerging characterization techniques (both experimental and computational) that can be used to investigate ion transport processes in bulk crystalline inorganic materials which exhibit predominant ion conduction (i.e., negligible electronic conductivity) with a primary focus on literature published after 2000 and critically assess their strengths and limitations. Together with an overview of recent understanding, we highlight the need for a combined experimental and computational approach to study ion transport in solids of desired time and length scales and for precise measurements of physical parameters related to ion transport.
Vascular grafts often exhibit low patency rates in clinical settings due to the pathological environment within the patients requiring the surgery. Mesenchymal stem cell (MSC)-derived small ...extracellular vesicles (sEVs) have attracted increasing attention. These sEVs contain many potent signaling molecules that play important roles in tissue regeneration, such as microRNA and cytokines. In this study, a sEVs-functionalized vascular graft was developed, and in vivo performance was systematically evaluated in a rat model of hyperlipidemia. Electrospun poly (ε-caprolactone) (PCL) vascular grafts were first modified with heparin, to enhance the anti-thrombogenicity. MSC-derived sEVs were loaded onto the heparinized PCL grafts to obtain functional vascular grafts. As-prepared vascular grafts were implanted to replace a segment of rat abdominal artery (1 cm) for up to 3 months. Results showed that the incorporation of MSC-derived sEVs effectively inhibited thrombosis and calcification, thus enhancing the patency of vascular grafts. Furthermore, regeneration of the endothelium and vascular smooth muscle was markedly enhanced, as attributed to the bioactive molecules within the sEVs, including vascular endothelial growth factor (VEGF), miRNA126, and miRNA145. More importantly, MSC-derived sEVs demonstrated a robust immunomodulatory effect, that is, they induced the transition of macrophages from a pro-inflammatory and atherogenic (M1) phenotype to an anti-inflammatory and anti-osteogenic (M2c) phenotype. This phenotypic switch was confirmed in both in vitro and in vivo analyses. Taken together, these results suggest that fabrication of vascular grafts with immunomodulatory function can provide an effective approach to improve vascular performance and functionality, with translational implication in cardiovascular regenerative medicine.
Emerging technologies, such as smart wearable devices, augmented reality (AR)/virtual reality (VR) displays, and naked-eye 3D projection, have gradually entered our lives, accompanied by an urgent ...market demand for high-end display technologies. Ultra-high-resolution displays, flexible displays, and transparent displays are all important types of future display technology, and traditional display technology cannot meet the relevant requirements. Micro-light-emitting diodes (micro-LEDs), which have the advantages of a high contrast, a short response time, a wide color gamut, low power consumption, and a long life, are expected to replace traditional liquid-crystal displays (LCD) and organic light-emitting diodes (OLED) screens and become the leaders in the next generation of display technology. However, there are two major obstacles to moving micro-LEDs from the laboratory to the commercial market. One is improving the yield rate and reducing the cost of the mass transfer of micro-LEDs, and the other is realizing a full-color display using micro-LED chips. This review will outline the three main methods for applying current micro-LED full-color displays, red, green, and blue (RGB) three-color micro-LED transfer technology, color conversion technology, and single-chip multi-color growth technology, to summarize present-day micro-LED full-color display technologies and help guide the follow-up research.
Urban agglomerations are sophisticated territorial systems at the mature stage of city development that are concentrated areas of production and economic activity. Therefore, the study of ...vulnerability from the perspective of production-living-ecological space is crucial for the sustainable development of the Yellow River Basin and global urban agglomerations. The relationship between productivity, living conditions, and ecological spatial quality is fully considered in this research. By constructing a vulnerability evaluation index system based on the perspectives of production, ecology, and living space, and adopting the entropy value method, comprehensive vulnerability index model, and obstacle factor diagnostic model, the study comprehensively assesses the vulnerability of the urban agglomerations along the Yellow River from 2001 to 2020. The results reveal that the spatial differentiation characteristics of urban agglomeration vulnerability are significant. A clear three-level gradient distribution of high, medium, and low degrees is seen in the overall vulnerability; these correspond to the lower, middle, and upper reaches of the Yellow River Basin, respectively. The percentage of cities with higher and moderate levels of vulnerability did not vary from 2001 to 2020, while the percentage of cities with high levels of vulnerability did. The four dimensions of economic development, leisure and tourism, resource availability, and ecological pressure are the primary determinants of the urban agglomeration's vulnerability along the Yellow River. And the vulnerability factors of various urban agglomerations showed a significant evolutionary trend; the obstacle degree values have declined, and the importance of tourism and leisure functions has gradually increased. Based on the above conclusions, we propose several suggestions to enhance the quality of urban development along the Yellow River urban agglomeration. Including formulating a three-level development strategy, paying attention to ecological and environmental protection, developing domestic and foreign trade, and properly planning and managing the tourism industry.
Allergic diseases, which are closely related to the composition and metabolism of maternal and infant flora, are prevalent in infants worldwide. The mother's breast milk, intestinal, and vaginal ...flora directly or indirectly influence the development of the infant's immune system from pregnancy to lactation, and the compositional and functional alterations of maternal flora are associated with allergic diseases in infants. Meanwhile, the infant's own flora, represented by the intestinal flora, indicates and regulates the occurrence of allergic diseases and is altered with the intervention of allergic diseases. By searching and selecting relevant literature in PubMed from 2010 to 2023, the mechanisms of allergy development in infants and the links between maternal and infant flora and infant allergic diseases are reviewed, including the effects of flora composition and its consequences on infant metabolism. The critical role of maternal and infant flora in allergic diseases has provided a window for probiotics as a microbial therapy. Therefore, the uses and mechanisms by which probiotics, such as lactic acid bacteria, can help to improve the homeostasis of both the mother and the infant, and thereby treat allergies, are also described.
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