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"Zhang, Si"
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Graph convolutional networks: a comprehensive review
Graphs naturally appear in numerous application domains, ranging from social analysis, bioinformatics to computer vision. The unique capability of graphs enables capturing the structural relations among data, and thus allows to harvest more insights compared to analyzing data in isolation. However, it is often very challenging to solve the learning problems on graphs, because (1) many types of data are not originally structured as graphs, such as images and text data, and (2) for graph-structured data, the underlying connectivity patterns are often complex and diverse. On the other hand, the representation learning has achieved great successes in many areas. Thereby, a potential solution is to learn the representation of graphs in a low-dimensional Euclidean space, such that the graph properties can be preserved. Although tremendous efforts have been made to address the graph representation learning problem, many of them still suffer from their shallow learning mechanisms. Deep learning models on graphs (e.g., graph neural networks) have recently emerged in machine learning and other related areas, and demonstrated the superior performance in various problems. In this survey, despite numerous types of graph neural networks, we conduct a comprehensive review specifically on the emerging field of graph convolutional networks, which is one of the most prominent graph deep learning models. First, we group the existing graph convolutional network models into two categories based on the types of convolutions and highlight some graph convolutional network models in details. Then, we categorize different graph convolutional networks according to the areas of their applications. Finally, we present several open challenges in this area and discuss potential directions for future research.
Journal Article
Redefining closed pores in carbons by solvation structures for enhanced sodium storage
Closed pores are widely accepted as the critical structure for hard carbon negative electrodes in sodium-ion batteries. However, the lack of a clear definition and design principle of closed pores leads to the undesirable electrochemical performance of hard carbon negative electrodes. Herein, we reveal how the evolution of pore mouth sizes determines the solvation structure and thereby redefine the closed pores. The precise and uniform control of the pore mouth sizes is achieved by using carbon molecular sieves as a model material. We show when the pore mouth is inaccessible to N
2
but accessible to CO
2
molecular probes, only a portion of solvent shells is removed before entering the pores and contact ion pairs dominate inside pores. When the pore mouth is inaccessible to CO
2
molecular probes, namely smaller than 0.35 nm, solvent shells are mostly sieved and dominated anion aggregates produce a thin and inorganic NaF-rich solid electrolyte interphase inside pores. Closed pores are accordingly redefined, and initial coulombic efficiency, cycling and low-temperature performance are largely improved. Furthermore, we show that intrinsic defects inside the redefined closed pores are effectively shielded from the interfacial passivation and contribute to the increased low-potential plateau capacity.
Closed pores govern sodium-ion storage performance of hard carbon negative electrodes. Here, authors link pore mouth size evolution of the closed pores to the solvation structure and propose design principles for optimizing both closed pores and intrinsic defects.
Journal Article
X-ray Image Enhancement Based on Nonsubsampled Shearlet Transform and Gradient Domain Guided Filtering
In this paper, we propose an image enhancement algorithm combining non-subsampled shearlet transform and gradient-domain guided filtering to address the problems of low resolution, noise amplification, missing details, and weak edge gradient retention in the X-ray image enhancement process. First, we decompose histogram equalization and nonsubsampled shearlet transform to the original image. We get a low-frequency sub-band and several high-frequency sub-bands. Adaptive gamma correction with weighting distribution is used for the low-frequency sub-band to highlight image contour information and improve the overall contrast of the image. The gradient-domain guided filtering is conducted for the high-frequency sub-bands to suppress image noise and highlight detail and edge information. Finally, we reconstruct all the effectively processed sub-bands by the inverse non-subsampled shearlet transform and obtain the final enhanced image. The experimental results show that the proposed algorithm has good results in X-ray image enhancement, and its objective index also has evident advantages over some classical algorithms.
Journal Article
A Network Pharmacology-Based Strategy For Predicting Active Ingredients And Potential Targets Of LiuWei DiHuang Pill In Treating Type 2 Diabetes Mellitus
Traditional Chinese medicine (TCM) formulations have proven to be advantageous in clinical treatment and prevention of disease. LiuWei DiHuang Pill (LWDH Pill) is a TCM that was employed to treat type 2 diabetes mellitus (T2DM). However, a holistic network pharmacology approach to understanding the active ingredients and the therapeutic mechanisms underlying T2DM has not been pursued.
A network pharmacology approach including drug-likeness evaluation, oral bioavailability prediction, virtual docking, and network analysis has been used to predict the active ingredients and potential targets of LWDH Pill in the treatment of type 2 diabetes.
The comprehensive network pharmacology approach was successfully to identify 45 active ingredients in LWDH Pill. 45 active ingredients hit by 163 potential targets related to T2DM. Ten of the more highly predictive components (such as :quercetin, Kaempferol, Stigmasterol, beta-sitosterol, Kadsurenone, Diosgenin, hancinone C, Hederagenin, Garcinone B, Isofucosterol) are involved in anti-inflammatory, anti-oxidative stress, and the reduction of beta cell damage. LWDH Pill may play a role in the treatment of T2DM and its complications (atherosclerosis and nephropathy) through the AGE-RAGE signaling pathway, TNF signaling pathway, and NF-kappa B signaling pathway.
Based on a systematic network pharmacology approach, our works successfully predict the active ingredients and potential targets of LWDH Pill for application to T2DM and helps to illustrate mechanism of action on a comprehensive level. This study provides identify key genes and pathway associated with the prognosis and pathogenesis of T2DM from new insights, which also demonstrates a feasible method for the research of chemical basis and pharmacology in LWDH Pill.
Journal Article
Harnessing plant–microbe interactions: strategies for enhancing resilience and nutrient acquisition for sustainable agriculture
The rhizosphere, a biologically active zone where plant roots interface with soil, plays a crucial role in enhancing plant health, resilience, and stress tolerance. As a key component in achieving Sustainable Development Goal 2, the rhizosphere is increasingly recognized for its potential to promote sustainable agricultural productivity. Engineering the rhizosphere microbiome is emerging as an innovative strategy to foster plant growth, improve stress adaptation, and restore soil health while mitigating the detrimental effects of conventional farming practices. This review synthesizes recent advancements in omics technologies, sequencing tools, and synthetic microbial communities (SynComs), which have provided insights into the complex interactions between plants and microbes. We examine the role of root exudates, composed of organic acids, amino acids, sugars, and secondary metabolites, as biochemical cues that shape beneficial microbial communities in the rhizosphere. The review further explores how advanced omics techniques like metagenomics and metabolomics are employed to elucidate the mechanisms by which root exudates influence microbial communities and plant health. Tailored SynComs have shown promising potential in enhancing plant resilience against both abiotic stresses (e.g., drought and salinity) and biotic challenges (e.g., pathogens and pests). Integration of these microbiomes with optimized root exudate profiles has been shown to improve nutrient cycling, suppress diseases, and alleviate environmental stresses, thus contributing to more sustainable agricultural practices. By leveraging multi-disciplinary approaches and optimizing root exudate profiles, ecological engineering of plant-microbiome interactions presents a sustainable pathway for boosting crop productivity. This approach also aids in managing soil-borne diseases, reducing chemical input dependency, and aligning with Sustainable Development Goals aimed at global food security and ecological sustainability. The ongoing research into rhizosphere microbiome engineering offers significant promise for ensuring long-term agricultural productivity while preserving soil and plant health for future generations.
Journal Article
Novel Anti-Cancer Products Targeting AMPK: Natural Herbal Medicine against Breast Cancer
Breast cancer is a common cancer in women worldwide. The existing clinical treatment strategies have been able to limit the progression of breast cancer and cancer metastasis, but abnormal metabolism, immunosuppression, and multidrug resistance involving multiple regulators remain the major challenges for the treatment of breast cancer. Adenosine 5′-monophosphate (AMP)-Activated Protein Kinase (AMPK) can regulate metabolic reprogramming and reverse the “Warburg effect” via multiple metabolic signaling pathways in breast cancer. Previous studies suggest that the activation of AMPK suppresses the growth and metastasis of breast cancer cells, as well as stimulating the responses of immune cells. However, some other reports claim that the development and poor prognosis of breast cancer are related to the overexpression and aberrant activation of AMPK. Thus, the role of AMPK in the progression of breast cancer is still controversial. In this review, we summarize the current understanding of AMPK, particularly the comprehensive bidirectional functions of AMPK in cancer progression; discuss the pharmacological activators of AMPK and some specific molecules, including the natural products (including berberine, curcumin, (−)-epigallocatechin-3-gallate, ginsenosides, and paclitaxel) that influence the efficacy of these activators in cancer therapy; and elaborate the role of AMPK as a potential therapeutic target for the treatment of breast cancer.
Journal Article
Organic fertilization co-selects genetically linked antibiotic and metal(loid) resistance genes in global soil microbiome
Antibiotic resistance genes (ARGs) and metal(loid) resistance genes (MRGs) coexist in organic fertilized agroecosystems based on their correlations in abundance, yet evidence for the genetic linkage of ARG-MRGs co-selected by organic fertilization remains elusive. Here, an analysis of 511 global agricultural soil metagenomes reveals that organic fertilization correlates with a threefold increase in the number of diverse types of ARG-MRG-carrying contigs (AMCCs) in the microbiome (63 types) compared to non-organic fertilized soils (22 types). Metatranscriptomic data indicates increased expression of AMCCs under higher arsenic stress, with co-regulation of the ARG-MRG pairs. Organic fertilization heightens the coexistence of ARG-MRG in genomic elements through impacting soil properties and ARG and MRG abundances. Accordingly, a comprehensive global map was constructed to delineate the distribution of coexistent ARG-MRGs with virulence factors and mobile genes in metagenome-assembled genomes from agricultural lands. The map unveils a heightened relative abundance and potential pathogenicity risks (range of 4-6) for the spread of coexistent ARG-MRGs in Central North America, Eastern Europe, Western Asia, and Northeast China compared to other regions, which acquire a risk range of 1-3. Our findings highlight that organic fertilization co-selects genetically linked ARGs and MRGs in the global soil microbiome, and underscore the need to mitigate the spread of these co-resistant genes to safeguard public health.
In this study, the authors analyzed global metagenomic data from agricultural soils and show that organic fertilization co-selects for antibiotic and metal(loid) resistance genes in genomic elements, while metatranscriptomic data additionally provides evidence for co-regulation of these gene sets.
Journal Article
Broadband generation of perfect Poincaré beams via dielectric spin-multiplexed metasurface
The term Poincaré beam, which describes the space-variant polarization of a light beam carrying spin angular momentum (SAM) and orbital angular momentum (OAM), plays an important role in various optical applications. Since the radius of a Poincaré beam conventionally depends on the topological charge number, it is difficult to generate a stable and high-quality Poincaré beam by two optical vortices with different topological charge numbers, as the Poincaré beam formed in this way collapses upon propagation. Here, based on an all-dielectric metasurface platform, we experimentally demonstrate broadband generation of a generalized perfect Poincaré beam (PPB), whose radius is independent of the topological charge number. By utilizing a phase-only modulation approach, a single-layer spin-multiplexed metasurface is shown to achieve all the states of PPBs on the hybrid-order Poincaré Sphere for visible light. Furthermore, as a proof-of-concept demonstration, a metasurface encoding multidimensional SAM and OAM states in the parallel channels of elliptical and circular PPBs is implemented for optical information encryption. We envision that this work will provide a compact and efficient platform for generation of PPBs for visible light, and may promote their applications in optical communications, information encryption, optical data storage and quantum information sciences.
Well-controlled Poincaré beams are potentially useful in optical communications applications. Here, the authors present phase-only metasurfaces that generate broadband, perfect Poincaré beams in the visible, with radius independent of the topological number.
Journal Article
Nasopharyngeal carcinoma incidence and mortality in China, 2013
Background We estimated the incidence and mortality of nasopharyngeal carcinoma (NPC) in China in 2010 according to the data of 145 domestic population‐based cancer registries in 2014, and no such reports since then. Hence, to further and better understand its epidemiology in China and to provide more precise scientific information for its control and prevention in China, we analyzed the NPC incidence and mortality of 255 domestic population‐based cancer registries, and estimated the national rates in 2013 again. Methods NPC incidence and mortality data of 255 domestic cancer registries in 2013, accepted by the 2016 National Cancer Registry Annual Report, were collected and collated, and the indices of NPC such as the numbers of new cases and deaths, crude rates, age‐standardized rates, and truncated rates of incidence and mortality were calculated and analyzed. The incidence and mortality in China and its constituent areas were estimated according to the national population in 2013. Results An estimated 42,100 new cases and 21,320 deaths were attributed to NPC in China in 2013, accounting for 1.14% of all new cancer cases and 0.96% of all cancer‐related deaths that year in China. Crude incidence and mortality of NPC were 3.09/100,000 and 1.57/100,000, respectively. World age‐standardized incidence and mortality were 2.17/100,000 and 1.08/100,000, respectively. The incidence and mortality of males were obviously higher than those of females and slightly higher in urban areas than in rural areas. Among seven Chinese administrative regions, NPC incidence and mortality were obviously higher in South China than in other regions and lowest in North China. Top 3 incidence and mortality provinces and registering areas all located in South China. The age‐specific incidence and mortality rose quickly from age 25–29 and 35 to 39 years, respectively, peaked at different ages and varied by location. Conclusions These results demonstrated that NPC incidence and mortality in China in 2013 were also at high levels worldwide, which suggested that its control and prevention should be enhanced.
Journal Article