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"Hu, Fei"
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Evaluation of hemp (Cannabis sativa L.) as an industrial crop: a review
Rising human population has increased the utilization of available resources for food, clothes, medicine, and living space, thus menacing natural environment and mounting the gap between available resources, and the skills to meet human desires is necessary. Humans are satisfying their desires by depleting available natural resources. Therefore, multifunctional plants can contribute towards the livelihoods of people, to execute their life requirements without degrading natural resources. Thus, research on multipurpose industrial crops should be of high interest among scientists. Hemp, or industrial hemp, is gaining research interest because of its fastest growth and utilization in commercial products including textile, paper, medicine, food, animal feed, paint, biofuel, biodegradable plastic, and construction material. High biomass production and ability to grow under versatile conditions make hemp, a good candidate species for remediation of polluted soils also. Present review highlights the morphology, adaptability, nutritional constituents, textile use, and medicinal significance of industrial hemp. Moreover, its usage in environmental conservation, building material, and biofuel production has also been discussed.
Journal Article
Single-cell RNA-seq reveals fibroblast heterogeneity and increased mesenchymal fibroblasts in human fibrotic skin diseases
Fibrotic skin disease represents a major global healthcare burden, characterized by fibroblast hyperproliferation and excessive accumulation of extracellular matrix. Fibroblasts are found to be heterogeneous in multiple fibrotic diseases, but fibroblast heterogeneity in fibrotic skin diseases is not well characterized. In this study, we explore fibroblast heterogeneity in keloid, a paradigm of fibrotic skin diseases, by using single-cell RNA-seq. Our results indicate that keloid fibroblasts can be divided into 4 subpopulations: secretory-papillary, secretory-reticular, mesenchymal and pro-inflammatory. Interestingly, the percentage of mesenchymal fibroblast subpopulation is significantly increased in keloid compared to normal scar. Functional studies indicate that mesenchymal fibroblasts are crucial for collagen overexpression in keloid. Increased mesenchymal fibroblast subpopulation is also found in another fibrotic skin disease, scleroderma, suggesting this is a broad mechanism for skin fibrosis. These findings will help us better understand skin fibrotic pathogenesis, and provide potential targets for fibrotic disease therapies.
Fibroblasts are found to be heterogeneous in multiple fibrotic diseases, but fibroblast heterogeneity in fibrotic skin diseases is not well characterized. Here the authors employ scRNA-seq to explore fibroblast heterogeneity in keloid, a paradigm of fibrotic skin diseases.
Journal Article
Synergistic reduction of graphene oxide using vitamin C and urea: Enhanced efficiency and material properties
Synergistic reduction of graphene oxide (GO) using different reducing agents represents an effective approach for reduced graphene oxide (rGO) synthesis. In this study, the rGO (rGO-Vc+Urea) was prepared by combining vitamin C (Vc) and urea as co-reducing agents with the modified Hummer’s method. Compared to samples reduced solely with Vc or urea, the co-reducing agents significantly reduced the required reaction time (to 2 hours) and temperature (to 120°C), while yielding material with superior electrical resistivity (1.2 Ω·cm). The structure of the samples was characterized using XRD, FT-IR, Raman spectroscopy, BET surface area analysis, and SEM. Results indicate that the sample prepared from co-reducing agents possesses a typical graphene structure and incorporates C-N bonds. Furthermore, rGO-Vc+Urea exhibits a higher degree of structural order, as evidenced by a lower Raman (Iᴅ/I G = 0.75), compared to rGO-Vc (Iᴅ/I G = 0.91) and rGO-Urea (Iᴅ/I G = 1.49), along with a higher specific surface area (88.60 m 2 /g). The reduction mechanism of the co-reducing agents was investigated. It was revealed that the alkaline environment generated by urea enhances Vc’s ability to reduce oxygen-containing functional groups in GO, specifically hydroxyl, epoxy, carbonyl, and carboxyl groups, and promotes the elimination of CO 2 released during the reaction. This strategy of employing synergistic multiple reducing agents offers new perspectives for the preparation of rGO.
Journal Article
AI, machine learning and deep learning : a security perspective
\"Today Artificial Intelligence (AI) and Machine/Deep Learning (ML/DL) have become the hottest areas in the information technology. In our society, there are so many intelligent devices that rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms/tools have used in many Internet applications and electronic devices, they are also vulnerable to various attacks and threats. The AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, and many other attacks/threats. Those attacks make the AI products dangerous to use. While the above discussion focuses on the security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models/algorithms can be used for cyber security (i.e., use AI to achieve security). Since the AI/ML/DL security is a new emergent field, many researchers and industry people cannot obtain detailed, comprehensive understanding of this area. This book aims to provide a complete picture on the challenges and solutions to the security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then many sets of promising solutions are described to achieve AI security and privacy in this book. The features of this book consist of 7 aspects: This is the first book to explain various practical attacks and countermeasures to AI systems; Both quantitative math models and practical security implementations are provided; It covers both \"securing the AI system itself\" and \"use AI to achieve security\"; It covers all the advanced AI attacks and threats with detailed attack models; It provides the multiple solution spaces to the security and privacy issues in AI tools; The differences among ML and DL security/privacy issues are explained. Many practical security applications are covered\"-- Provided by publisher.
Book
Multiscale Object Detection in Remote Sensing Images Combined with Multi-Receptive-Field Features and Relation-Connected Attention
Object detection is an important task of remote sensing applications. In recent years, with the development of deep convolutional neural networks, object detection in remote sensing images has made great improvements. However, the large variation of object scales and complex scenarios will seriously affect the performance of the detectors. To solve these problems, a novel object detection algorithm based on multi-receptive-field features and relation-connected attention is proposed for remote sensing images to achieve more accurate detection results. Specifically, we propose a multi-receptive-field feature extraction module with dilated convolution to aggregate the context information of different receptive fields. This achieves a strong capability of feature representation, which can effectively adapt to the scale changes of objects, either due to various object scales or different resolutions. Then, a relation-connected attention module based on relation modeling is constructed to automatically select and refine the features, which combines global and local attention to make the features more discriminative and can effectively improve the robustness of the detector. We designed these two modules as plug-and-play blocks and integrated them into the framework of Faster R-CNN to verify our method. The experimental results on NWPU VHR-10 and HRSC2016 datasets demonstrate that these two modules can effectively improve the performance of basic deep CNNs, and the proposed method can achieve better results of multiscale object detection in complex backgrounds.
Journal Article
Controllable multiple-step configuration transformations in a thermal/photoinduced reaction
Solid-state photochemical reactions of olefinic compounds have been demonstrated to represent powerful access to organic cyclic molecules with specific configurations. However, the precise control of the stereochemistry in these reactions remains challenging owing to complex and fleeting configuration transformations. Herein, we report a unique approach to control the regiospecific configurations of C = C groups and the intermediates by varying temperatures in multiple-step thermal/photoinduced reactions, thus successfully realizing reversible ring closing/opening changes using a single-crystal coordination polymer platform. All stereochemical transitions are observed by in situ single-crystal X-ray diffraction, powder X-ray diffraction and infrared spectroscopy. Density functional theory calculations allow us to rationalize the mechanism of the synergistic thermal/photoinduced transformations. This approach can be generalized to the analysis of the possible configuration transformations of functional groups and intermediates and unravel the detailed mechanism for any inorganic, organic and macromolecular reactions susceptible to incorporation into single-crystal coordination polymer platforms.
Solid-state photochemical reactions of olefinic compounds provide access to organic cyclic molecules with specific configurations but the precise control of the stereochemistry in these reactions remains challenging. Here, the authors demonstrate control of the regiospecific configurations of C=C groups and the intermediates by varying temperatures in multi-step thermal and photoinduced ring opening and closing reactions using a single-crystal coordination polymer platform.
Journal Article
The role of Ca2+ in acid-sensing ion channel 1a-mediated chondrocyte pyroptosis in rat adjuvant arthritis
Rheumatoid arthritis is an autoimmune disease with a poor prognosis. Pyroptosis is a type of proinflammatory programmed cell death that is characterised by the activation of caspase-1 and secretion of the proinflammatory cytokines interleukin (IL)-1β/18. Previous reports have shown that pyroptosis is closely related to the development of some autoimmune diseases, such as rheumatoid arthritis. The decrease in the pH of joint fluid is a main pathogenic feature of RA and leads to excessive apoptosis in chondrocytes. Acid-sensitive ion channels (ASICs) are extracellular H+-activated cation channels that mainly influence Na+ and Ca2+ permeability. In this study, we investigated the role of Ca2+ in acid-sensing ion channel 1a-mediated chondrocyte pyroptosis in an adjuvant arthritis rat model. The expression of apoptosis-associated speck-like protein, NLRP3, caspase-1, ASIC 1a, IL-1β and IL-18 was upregulated in the joints of rats compared with that in normal rats, but the expression of Col2a in cartilage was decreased. However, these changes were reversed by amiloride, which is an inhibitor of ASIC1a. Extracellular acidosis significantly increased the expression of ASIC1a, IL-1β, IL-18, ASC, NLRP3 and caspase-1 and promoted the release of lactate dehydrogenase. Interestingly, Psalmotoxin-1 (Pctx-1) and BAPTA-AM inhibited these effects. These results indicate that ASIC1a mediates pyroptosis in chondrocytes from AA rats. The underlying mechanism may be associated with the ability of ASIC1a to promote [Ca2+]i and upregulate the expression of the NLRP3 inflammasome.
Journal Article