Shenzhen University

To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, ∼150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively. The human body plays host to an estimated 100 trillion microbial cells, most of them in the gut where they have a profound influence on human physiology and nutrition — and are now regarded as crucial for human life. Gut microbes contribute to the energy harvest from food, and changes of gut microbiome may be associated with bowel diseases or obesity. Now the international MetaHIT (Metagenomics of the Human Intestinal Tract) project has published a gene catalogue of the human gut microbiome derived from 124 healthy, overweight and obese human adults, as well as inflammatory disease patients, from Denmark and Spain. The resulting data provide the first insights into this gene set — which is over 150 times larger than the human gene complement — and show that the genes are largely shared among individuals. Based on the variety of functions encoded by the gene set, it is possible to define both a minimal gut metagenome and a minimal gut bacterial genome. Deep metagenomic sequencing and characterization of the human gut microbiome from healthy and obese individuals, as well as those suffering from inflammatory bowel disease, provide the first insights into this gene set and how much of it is shared among individuals. The minimal gut metagenome as well as the minimal gut bacterial genome is also described.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Uncertainty quantification (UQ) methods play a pivotal role in reducing the impact of uncertainties during both optimization and decision making processes. They have been applied to solve a variety of real-world problems in science and engineering. Bayesian approximation and ensemble learning techniques are two widely-used types of uncertainty quantification (UQ) methods. In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., self-driving cars and object detection), image processing (e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring), bioinformatics, etc. This study reviews recent advances in UQ methods used in deep learning, investigates the application of these methods in reinforcement learning, and highlights fundamental research challenges and directions associated with UQ.

Thirty years ago, Coullet et al. proposed that a special optical field exists in laser cavities bearing some analogy with the superfluid vortex. Since then, optical vortices have been widely studied, inspired by the hydrodynamics sharing similar mathematics. Akin to a fluid vortex with a central flow singularity, an optical vortex beam has a phase singularity with a certain topological charge, giving rise to a hollow intensity distribution. Such a beam with helical phase fronts and orbital angular momentum reveals a subtle connection between macroscopic physical optics and microscopic quantum optics. These amazing properties provide a new understanding of a wide range of optical and physical phenomena, including twisting photons, spin-orbital interactions, Bose-Einstein condensates, etc., while the associated technologies for manipulating optical vortices have become increasingly tunable and flexible. Hitherto, owing to these salient properties and optical manipulation technologies, tunable vortex beams have engendered tremendous advanced applications such as optical tweezers, high-order quantum entanglement, and nonlinear optics. This article reviews the recent progress in tunable vortex technologies along with their advanced applications.

Along with extensive research on the three-dimensional (3D) printing of polymers and metals, 3D printing of ceramics is now the latest trend to come under the spotlight. The ability to fabricate ceramic components of arbitrarily complex shapes has been extremely challenging without 3D printing. This review focuses on the latest advances in the 3D printing of ceramics and presents the historical origins and evolution of each related technique. The main technical aspects, including feedstock properties, process control, post-treatments and energy source–material interactions, are also discussed. The technical challenges and advice about how to address these are presented. Comparisons are made between the techniques to facilitate the selection of the best ones in practical use. In addition, representative applications of the 3D printing of various types of ceramics are surveyed. Future directions are pointed out on the advancement on materials and forming mechanism for the fabrication of high-performance ceramic components.

Macrophages exist in various tissues, several body cavities, and around mucosal surfaces and are a vital part of the innate immune system for host defense against many pathogens and cancers. Macrophages possess binary M1/M2 macrophage polarization settings, which perform a central role in an array of immune tasks via intrinsic signal cascades and, therefore, must be precisely regulated. Many crucial questions about macrophage signaling and immune modulation are yet to be uncovered. In addition, the clinical importance of tumor-associated macrophages is becoming more widely recognized as significant progress has been made in understanding their biology. Moreover, they are an integral part of the tumor microenvironment, playing a part in the regulation of a wide variety of processes including angiogenesis, extracellular matrix transformation, cancer cell proliferation, metastasis, immunosuppression, and resistance to chemotherapeutic and checkpoint blockade immunotherapies. Herein, we discuss immune regulation in macrophage polarization and signaling, mechanical stresses and modulation, metabolic signaling pathways, mitochondrial and transcriptional, and epigenetic regulation. Furthermore, we have broadly extended the understanding of macrophages in extracellular traps and the essential roles of autophagy and aging in regulating macrophage functions. Moreover, we discussed recent advances in macrophages-mediated immune regulation of autoimmune diseases and tumorigenesis. Lastly, we discussed targeted macrophage therapy to portray prospective targets for therapeutic strategies in health and diseases.

The complexity, diversity, and heterogeneity of tumors seriously undermine the therapeutic potential of treatment. Therefore, the current trend in clinical research has gradually shifted from a focus on monotherapy to combination therapy for enhanced treatment efficacy. More importantly, the cooperative enhancement interactions between several types of monotherapy contribute to the naissance of multimodal synergistic therapy, which results in remarkable superadditive (namely "1 + 1 > 2") effects, stronger than any single therapy or their theoretical combination. In this review, state-of-the-art studies concerning recent advances in nanotechnology-mediated multimodal synergistic therapy will be systematically discussed, with an emphasis on the construction of multifunctional nanomaterials for realizing bimodal and trimodal synergistic therapy as well as the intensive exploration of the underlying synergistic mechanisms for explaining the significant improvements in synergistic therapeutic outcome. Furthermore, the featured applications of multimodal synergistic therapy in overcoming tumor multidrug resistance, hypoxia, and metastasis will also be discussed in detail, which may provide new ways for the efficient regression and even elimination of drug resistant, hypoxic solid, or distant metastatic tumors. Finally, some design tips for multifunctional nanomaterials and an outlook on the future development of multimodal synergistic therapy will be provided, highlighting key scientific issues and technical challenges and requiring remediation to accelerate clinical translation.

Residents of the Tibetan Plateau show heritable adaptations to extreme altitude. We sequenced 50 exomes of ethnic Tibetans, encompassing coding sequences of 92% of human genes, with an average coverage of 18x per individual. Genes showing population-specific allele frequency changes, which represent strong candidates for altitude adaptation, were identified. The strongest signal of natural selection came from endothelial Per-Arnt-Sim (PAS) domain protein 1 (EPAS1), a transcription factor involved in response to hypoxia. One single-nucleotide polymorphism (SNP) at EPAS1 shows a 78% frequency difference between Tibetan and Han samples, representing the fastest allele frequency change observed at any human gene to date. This SNP's association with erythrocyte abundance supports the role of EPAS1 in adaptation to hypoxia. Thus, a population genomic survey has revealed a functionally important locus in genetic adaptation to high altitude.

Photodynamic therapy (PDT) has been applied to treat a wide range of medical conditions, including wet age-related macular degeneration psoriasis, atherosclerosis, viral infection and malignant cancers. However, the tissue penetration limitation of excitation light hinders the widespread clinical use of PDT. To overcome this "Achilles' heel", deep PDT, a novel type of phototherapy, has been developed for the efficient treatment of deep-seated diseases. Based on the different excitation sources, including near-infrared (NIR) light, X-ray radiation, and internal self-luminescence, a series of deep PDT techniques have been explored to demonstrate the advantages of deep cancer therapy over conventional PDT excited by ultraviolet-visible (UV-Vis) light. In particular, the featured applications of deep PDT, such as organelle-targeted deep PDT, hypoxic deep PDT and deep PDT-involved multimodal synergistic therapy are discussed. Finally, the future development and potential challenges of deep PDT are also elucidated for clinical translation. It is highly expected that deep PDT will be developed as a versatile, depth/oxygen-independent and minimally invasive strategy for treating a variety of malignant tumours at deep locations.

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.

All forms of energy follow the law of conservation of energy, by which they can be neither created nor destroyed. Light-to-heat conversion as a traditional yet constantly evolving means of converting light into thermal energy has been of enduring appeal to researchers and the public. With the continuous development of advanced nanotechnologies, a variety of photothermal nanomaterials have been endowed with excellent light harvesting and photothermal conversion capabilities for exploring fascinating and prospective applications. Herein we review the latest progresses on photothermal nanomaterials, with a focus on their underlying mechanisms as powerful light-to-heat converters. We present an extensive catalogue of nanostructured photothermal materials, including metallic/semiconductor structures, carbon materials, organic polymers, and two-dimensional materials. The proper material selection and rational structural design for improving the photothermal performance are then discussed. We also provide a representative overview of the latest techniques for probing photothermally generated heat at the nanoscale. We finally review the recent significant developments of photothermal applications and give a brief outlook on the current challenges and future directions of photothermal nanomaterials.

BACKGROUND: Since its discovery in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 2 180 000 people worldwide and has caused more than 150 000 deaths as of April 16, 2020. SARS-CoV-2, which is the virus causing coronavirus disease 2019 (COVID-19), uses the angiotensin-converting enzyme 2 (ACE2) as a cell receptor to invade human cells. Thus, ACE2 is the key to understanding the mechanism of SARS-CoV-2 infection. This study is to investigate the ACE2 expression in various human tissues in order to provide insights into the mechanism of SARS-CoV-2 infection. METHODS: We compared ACE2 expression levels across 31 normal human tissues between males and females and between younger (ages ≤ 49 years) and older (ages > 49 years) persons using two-sided Student's t test. We also investigated the correlations between ACE2 expression and immune signatures in various tissues using Pearson's correlation test. RESULTS: ACE2 expression levels were the highest in the small intestine, testis, kidneys, heart, thyroid, and adipose tissue, and were the lowest in the blood, spleen, bone marrow, brain, blood vessels, and muscle. ACE2 showed medium expression levels in the lungs, colon, liver, bladder, and adrenal gland. ACE2 was not differentially expressed between males and females or between younger and older persons in any tissue. In the skin, digestive system, brain, and blood vessels, ACE2 expression levels were positively associated with immune signatures in both males and females. In the thyroid and lungs, ACE2 expression levels were positively and negatively associated with immune signatures in males and females, respectively, and in the lungs they had a positive and a negative correlation in the older and younger groups, respectively. CONCLUSIONS: Our data indicate that SARS-CoV-2 may infect other tissues aside from the lungs and infect persons with different sexes, ages, and races equally. The different host immune responses to SARS-CoV-2 infection may partially explain why males and females, young and old persons infected with this virus have markedly distinct disease severity. This study provides new insights into the role of ACE2 in the SARS-CoV-2 pandemic.

Bone marrow derived mesenchymal stem cells (BM-MSCs) have been shown to enhance wound healing; however, the mechanisms involved are barely understood. In this study, we examined paracrine factors released by BM-MSCs and their effects on the cells participating in wound healing compared to those released by dermal fibroblasts. Analyses of BM-MSCs with Real-Time PCR and of BM-MSC-conditioned medium by antibody-based protein array and ELISA indicated that BM-MSCs secreted distinctively different cytokines and chemokines, such as greater amounts of VEGF-alpha, IGF-1, EGF, keratinocyte growth factor, angiopoietin-1, stromal derived factor-1, macrophage inflammatory protein-1alpha and beta and erythropoietin, compared to dermal fibroblasts. These molecules are known to be important in normal wound healing. BM-MSC-conditioned medium significantly enhanced migration of macrophages, keratinocytes and endothelial cells and proliferation of keratinocytes and endothelial cells compared to fibroblast-conditioned medium. Moreover, in a mouse model of excisional wound healing, where concentrated BM-MSC-conditioned medium was applied, accelerated wound healing occurred compared to administration of pre-conditioned or fibroblast-conditioned medium. Analysis of cell suspensions derived from the wound by FACS showed that wounds treated with BM-MSC-conditioned medium had increased proportions of CD4/80-positive macrophages and Flk-1-, CD34- or c-kit-positive endothelial (progenitor) cells compared to wounds treated with pre-conditioned medium or fibroblast-conditioned medium. Consistent with the above findings, immunohistochemical analysis of wound sections showed that wounds treated with BM-MSC-conditioned medium had increased abundance of macrophages. Our results suggest that factors released by BM-MSCs recruit macrophages and endothelial lineage cells into the wound thus enhancing wound healing.

Ubiquitous sensors and smart devices from factories and communities are generating massive amounts of data, and ever-increasing computing power is driving the core of computation and services from the cloud to the edge of the network. As an important enabler broadly changing people's lives, from face recognition to ambitious smart factories and cities, developments of artificial intelligence (especially deep learning, DL) based applications and services are thriving. However, due to efficiency and latency issues, the current cloud computing service architecture hinders the vision of “providing artificial intelligence for every person and every organization at everywhere”. Thus, unleashing DL services using resources at the network edge near the data sources has emerged as a desirable solution. Therefore, edge intelligence, aiming to facilitate the deployment of DL services by edge computing, has received significant attention. In addition, DL, as the representative technique of artificial intelligence, can be integrated into edge computing frameworks to build intelligent edge for dynamic, adaptive edge maintenance and management. With regard to mutually beneficial edge intelligence and intelligent edge, this paper introduces and discusses: 1) the application scenarios of both; 2) the practical implementation methods and enabling technologies, namely DL training and inference in the customized edge computing framework; 3) challenges and future trends of more pervasive and fine-grained intelligence. We believe that by consolidating information scattered across the communication, networking, and DL areas, this survey can help readers to understand the connections between enabling technologies while promoting further discussions on the fusion of edge intelligence and intelligent edge, i.e., Edge DL.

Abstract As an emerging concept, green human resource management (green HRM ) has been conceptualized to influence employee workplace green behavior. This research empirically tested this link. We first developed measures for green HRM , and then drew on the behavioral HRM and psychological climate literature along with the supplies‐values fit theory, to test a conceptual model integrating the effects of psychological green climate and individual green values. Results revealed that green HRM both directly and indirectly influenced in‐role green behavior, but only indirectly influenced extra‐role green behavior, through the mediation of psychological green climate. Individual green values moderated the effect of psychological green climate on extra‐role green behavior, but it did not moderate the effect of either green HRM or psychological green climate on in‐role green behavior. These findings indicate that green HRM affects both employee in‐role and extra‐role workplace green behavior; however, this occurs through different social and psychological processes. © 2016 Wiley Periodicals, Inc.

Using next-generation sequencing technology alone, we have successfully generated and assembled a draft sequence of the giant panda genome. The assembled contigs (2.25 gigabases (Gb)) cover approximately 94% of the whole genome, and the remaining gaps (0.05 Gb) seem to contain carnivore-specific repeats and tandem repeats. Comparisons with the dog and human showed that the panda genome has a lower divergence rate. The assessment of panda genes potentially underlying some of its unique traits indicated that its bamboo diet might be more dependent on its gut microbiome than its own genetic composition. We also identified more than 2.7 million heterozygous single nucleotide polymorphisms in the diploid genome. Our data and analyses provide a foundation for promoting mammalian genetic research, and demonstrate the feasibility for using next-generation sequencing technologies for accurate, cost-effective and rapid de novo assembly of large eukaryotic genomes. The genome of the giant panda — specifically of the female Beijing Olympics mascot Jingjing — has been determined using short-read sequencing technology, a first for such a complex genome. It consists of some 2.4 billion DNA base pairs, compared to 3 billion in humans, and contains around 21,000 protein-encoding genes, similar to the human genome. Genomic diversity reflected in the sequence is high, raising hopes that despite a population of only about 2,500, conservation efforts can keep the species from extinction. Intriguingly, the panda appears to have all the genes needed for a carnivorous digestive system but lacks digestive cellulase genes. It may therefore depend on its gut microbiome to handle its famously limited bamboo diet. Taste may be a diet-limiting factor: loss of function of the T1R1 gene means that pandas may not experience the umami taste associated with high-protein foods. Technical aspects of this work pave the way for the use of next-generation sequencing for rapid de novo assembly of large eukaryotic genomes. Here, a draft sequence of the giant panda genome is assembled using next-generation sequencing technology alone. Genome analysis reveals a low divergence rate in comparison with dog and human genomes and insights into panda-specific traits; for example, the giant panda's bamboo diet may be more dependent on its gut microbiome than its own genetic composition.

In recent years, nanocrystals of metal sulfide materials have attracted scientific research interest for renewable energy applications due to the abundant choice of materials with easily tunable electronic, optical, physical and chemical properties. Metal sulfides are semiconducting compounds where sulfur is an anion associated with a metal cation; and the metal ions may be in mono-, bi- or multi-form. The diverse range of available metal sulfide materials offers a unique platform to construct a large number of potential materials that demonstrate exotic chemical, physical and electronic phenomena and novel functional properties and applications. To fully exploit the potential of these fascinating materials, scalable methods for the preparation of low-cost metal sulfides, heterostructures, and hybrids of high quality must be developed. This comprehensive review indicates approaches for the controlled fabrication of metal sulfides and subsequently delivers an overview of recent progress in tuning the chemical, physical, optical and nano- and micro-structural properties of metal sulfide nanocrystals using a range of material fabrication methods. For hydrogen energy production, three major approaches are discussed in detail: electrocatalytic hydrogen generation, powder photocatalytic hydrogen generation and photoelectrochemical water splitting. A variety of strategies such as structural tuning, composition control, doping, hybrid structures, heterostructures, defect control, temperature effects and porosity effects on metal sulfide nanocrystals are discussed and how they are exploited to enhance performance and develop future energy materials. From this literature survey, energy conversion currently relies on a limited range of metal sulfides and their composites, and several metal sulfides are immature in terms of their dissolution, photocorrosion and long-term durability in electrolytes during water splitting. Future research directions for innovative metal sulfides should be closely allied to energy and environmental issues, along with their advanced characterization, and developing new classes of metal sulfide materials with well-defined fabrication methods.

Metasurfaces have enabled a plethora of emerging functions within an ultrathin dimension, paving way towards flat and highly integrated photonic devices. Despite the rapid progress in this area, simultaneous realization of reconfigurability, high efficiency, and full control over the phase and amplitude of scattered light is posing a great challenge. Here, we try to tackle this challenge by introducing the concept of a reprogrammable hologram based on 1-bit coding metasurfaces. The state of each unit cell of the coding metasurface can be switched between '1' and '0' by electrically controlling the loaded diodes. Our proof-of-concept experiments show that multiple desired holographic images can be realized in real time with only a single coding metasurface. The proposed reprogrammable hologram may be a key in enabling future intelligent devices with reconfigurable and programmable functionalities that may lead to advances in a variety of applications such as microscopy, display, security, data storage, and information processing.Realizing metasurfaces with reconfigurability, high efficiency, and control over phase and amplitude is a challenge. Here, Li et al. introduce a reprogrammable hologram based on a 1-bit coding metasurface, where the state of each unit cell of the coding metasurface can be switched electrically.

We solve the problem of salient object detection by investigating how to expand the role of pooling in convolutional neural networks. Based on the U-shape architecture, we first build a global guidance module (GGM) upon the bottom-up pathway, aiming at providing layers at different feature levels the location information of potential salient objects. We further design a feature aggregation module (FAM) to make the coarse-level semantic information well fused with the fine-level features from the top-down path- way. By adding FAMs after the fusion operations in the top-down pathway, coarse-level features from the GGM can be seamlessly merged with features at various scales. These two pooling-based modules allow the high-level semantic features to be progressively refined, yielding detail enriched saliency maps. Experiment results show that our proposed approach can more accurately locate the salient objects with sharpened details and hence substantially improve the performance compared to the previous state-of-the-arts. Our approach is fast as well and can run at a speed of more than 30 FPS when processing a 300×400 image. Code can be found at http://mmcheng.net/poolnet/.

Black phosphorus quantum dots (BPQDs) were synthesized using a liquid exfoliation method that combined probe sonication and bath sonication. With a lateral size of approximately 2.6 nm and a thickness of about 1.5 nm, the ultrasmall BPQDs exhibited an excellent NIR photothermal performance with a large extinction coefficient of 14.8 L g(-1) cm(-1) at 808 nm, a photothermal conversion efficiency of 28.4%, as well as good photostability. After PEG conjugation, the BPQDs showed enhanced stability in physiological medium, and there was no observable toxicity to different types of cells. NIR photoexcitation of the BPQDs in the presence of C6 and MCF7 cancer cells led to significant cell death, suggesting that the nanoparticles have large potential as photothermal agents.