Search

The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3′ untranslated region (3′-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3′-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3′-UTR eQTLs in immune-related genes. Our approach identifies numerous 3′-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer. The role of non-coding mutations in cancer progression and immune evasion needs to be further explored. Here, the authors investigate the potential of common somatic and germline 3′ untranslated region variants in predicting response to immunotherapy in gastric patients. [ABSTRACT FROM AUTHOR]

There is an urgent need to address sulfur dioxide (SO2) from the burning of fossil fuels, which poses a serious hazard to the surrounding environment due to its emission. In this work, UiO-66-type metal–organic framework materials (MOFs) were prepared by hydrothermal method and applied to flue gas desulfurization. Through characterization analysis, it was found that UiO-66 sample had high crystallinity and good thermal stability. Besides, UiO-66 sample had a large specific surface area (1423 m2/g) and a large pore volume (0.69 cm3/g). In the desulfurization experiments of SO2/CO2/O2/N2 gas mixture (0.3/10.0/5.5/84.2 vol.%), UiO-66 had a breakthrough time of 137.6 min/g for SO2, the high selectivity of SO2/CO2 (36.0), and strong acid resistance. Besides, the adsorption thermodynamic analysis can confirm that the adsorption process of UiO-66 for SO2 was a combination of physical adsorption and chemical adsorption. At 1.0 bar and 298 K, the adsorption capacity of SO2 on UiO-66 reached 8.12 mmol/g. [ABSTRACT FROM AUTHOR]

As opposed to traditional video, a micro-video is a short video that is spread on social platforms. As user-generated contents, micro-videos have stronger social attributes compared to ordinary videos. Research on micro-video analysis has been conducted in both industry and academia and includes venue classification, tag prediction, popularity prediction, action prediction, click prediction, and recommendation. In this paper, we first review the studies on these tasks in terms of micro-video classification, prediction, and recommendation. Thereafter, we present an overview of the methods, features, datasets, and evaluation metrics relating to these studies. Finally, we analyze the challenges of micro-video analysis. Because of the limited research work on micro-video analysis, we can not summarize some aspects of micro-video analysis, such as micro-video classification.We believe that this survey will aid in enhancing the knowledge of researchers and practitioners who are interested in micro-video analysis. [ABSTRACT FROM AUTHOR]

To address the challenges in the era of artificial intelligence, this paper investigates how computing offloading techniques can be utilized to improve the system performance in cellular connected unmanned aerial vehicle (UAV) networks with limited resources using non-orthogonal multiple access (NOMA) and mobile edge computing techniques. Energy consumed by the UAV in performing tasks and the time required to complete tasks are minimized by joint optimal task offloading decision, sub-channel allocation, and computing resource allocation while satisfying the user's quality of service requirements. We consider this problem as a nonlinear programming problem with integer and non-integer variables and solve it by iteratively updating the resource allocation and offloading decision. Specifically, given a fixed offloading decision, a many-to-one matching model is first applied for sub-channel allocation, then a detailed allocation of computing resource is performed by optimizing the total system overhead, and are solved by utilizing the matching algorithm and the Lagrange dual method, respectively. Then, according to the scenarios we have been given for resource allocation, we design a multi-objective task offloading algorithm to update the offloading decision. Simulation experiments demonstrate the feasibility of the scheme, which shows a significant reduction in both energy consumption and latency compared to the benchmark scheme. [ABSTRACT FROM AUTHOR]

Deep hashing has been widely studied in recent years. However, most existing methods learn hash codes from the whole image ignoring the region details which are important for representing the precise semantic contents. To tackle this issue, we proposed a deep regional detail-aware hashing (DDAH) to fully utilize this detail information. Specifically, to well reflect the influence of details on the hash codes, we handle these details in a "near-Hamming" space instead of directly fusing them in the original image feature space. Furthermore, based on the framework of DDAH, we can capture the details in the network without the need to partition the original image to different regions manually. To be more specific, considering multiple regions as overlapping subimages, we first design a deep network to learn multiple regional details from these subimages, and then fuse them in the near-Hamming space, which is highly related to Hamming space (i.e., hash code space). Finally, these regional details in the near-Hamming space are directly used to generate hash code of the corresponding image. In addition, a self-similarity loss term is proposed to force these regional details together in the near-Hamming space. In brief, compared to existing hashing methods, the proposed DDAH not only utilizes detail information for hash learning, but also incorporates them into the final hash codes. Extensive experiments on three datasets have indicated that DDAH outperforms most existing models, verifying its effectiveness. [ABSTRACT FROM AUTHOR]

Due to the increasingly serious environmental problems caused by the combustion of sulfides in fuel, deep desulfurization of fuel became particularly urgent. Herein, the catalyst (PMA@MOF-808) of the Zr-based metal–organic framework (MOF-808) encapsulating phosphomolybdic acid (PMA) was prepared via a one-pot hydrothermal method. Besides, the formate ions of PMA@MOF-808 were removed by posttreatment with methanol, resulting in formate-free PMA@MOF-808-H catalysts with unsaturated open metal sites. The as-synthesized catalysts were systematically characterized by XRD, FT-IR, SEM, BET, TGA, 1H NMR and XPS. The catalysts were also applied in catalytic oxidation desulfurization of fuel. The results indicated that the introduction of PMA and the removal of formate ions can improve the desulfurization performance of catalysts. Formate-free 0.2-PMA@MOF-808-H catalyst can reach 100% desulfurization rate for DBT. Besides, the kinetic properties were studied, and the apparent activation energy was 29.34 kJ/mol. [ABSTRACT FROM AUTHOR]

Somatic mutations that accumulate in normal tissues are associated with ageing and disease1,2. Here we performed a comprehensive genomic analysis of 1,737 morphologically normal tissue biopsies of 9 organs from 5 donors. We found that somatic mutation accumulations and clonal expansions were widespread, although to variable extents, in morphologically normal human tissues. Somatic copy number alterations were rarely detected, except for in tissues from the oesophagus and cardia. Endogenous mutational processes with the SBS1 and SBS5 mutational signatures are ubiquitous among normal tissues, although they exhibit different relative activities. Exogenous mutational processes operate in multiple tissues from the same donor. We reconstructed the spatial somatic clonal architecture with sub-millimetre resolution. In the oesophagus and cardia, macroscopic somatic clones that expanded to hundreds of micrometres were frequently seen, whereas in tissues such as the colon, rectum and duodenum, somatic clones were microscopic in size and evolved independently, possibly restricted by local tissue microstructures. Our study depicts a body map of somatic mutations and clonal expansions from the same individual.Laser-capture microdissection and mini-bulk exome sequencing are combined to analyse somatic mutations in morphologically normal tissues from nine organs from five donors, revealing variation in mutation burdens, mutational signatures and clonal expansions. [ABSTRACT FROM AUTHOR]

Esophageal squamous cell carcinoma (ESCC) is prevalent in some geographical regions of the world. ESCC development presents a multistep pathogenic process from inflammation to invasive cancer; however, what is critical in these processes and how they evolve is largely unknown, obstructing early diagnosis and effective treatment. Here, we create a mouse model mimicking human ESCC development and construct a single-cell ESCC developmental atlas. We identify a set of key transitional signatures associated with oncogenic evolution of epithelial cells and depict the landmark dynamic tumorigenic trajectories. An early downregulation of CD8+ response against the initial tissue damage accompanied by the transition of immune response from type 1 to type 3 results in accumulation and activation of macrophages and neutrophils, which may create a chronic inflammatory environment that promotes carcinogen-transformed epithelial cell survival and proliferation. These findings shed light on how ESCC is initiated and developed. The multistep processes involved in the evolution of inflammation to invasive esophageal squamous cell carcinoma (ESCC) is unclear. Here, the authors report a mouse model of ESCC and the role of interplay between carcinogen-transformed epithelial cells and their microenvironment in ESCC development. [ABSTRACT FROM AUTHOR]

Purpose: Excessive fertilization has led to a high risk of phosphorus (P) leaching and related problems in the North China Plain, where the most typical cropland soil is fluvo-aquic soil. The main factors controlling environmental P behavior and the acting time sequence of these factors in soil after long-term P fertilizer application have not been well recognized. A clear understanding is essential for effective P management. Materials and methods: Effects of Fe minerals, calcium carbonate, and organic matter (OM) on P immobilization in fluvo-aquic soil were studied systematically through farmland investigation and aging experiments. Results and discussion: Phosphorus associated with Ca was the primary fraction in fluvo-aquic soil. Even though there was no significant correlation between the total contents of P and Ca in soils, formation of P-Ca phases facilitated by Ca2+ in soil solution was a mechanism of P retention when soil received excess P fertilizer. Positive correlations between the contents of P and Fe and total organic carbon (TOC) indicate that Fe minerals and OM have significant effects on P immobilization. Through the aging experiments, P was found to primarily adsorb on goethite and gradually forms Ca-P compounds. Organic fertilizer caused P release and inhibition of P adsorption in the initial stages; however, OM derived from organic fertilizer might facilitate P immobilization in the long term through the formation of a P-Ca-OM complex. Conclusions: Although superfluous application of P fertilizers leads to the gradual formation of Ca-P in fluvo-aquic soils, there is still a risk of P loss because P is not immediately adsorbed by Fe minerals. Moreover, application of organic fertilizers increases the risk of P loss. These results provide an important scientific basis for initiating P management policies for fluvo-aquic soils. [ABSTRACT FROM AUTHOR]

Rapid urbanization has led to an increase in urban land surface temperature (LST). In contrast to individual cities or megacity scale, urban agglomeration can increase LST in a continuous area due to decreasing or disappearing distance between cities. Thus, the impact of ISA on LST needs further understanding in the large scale of urban agglomerations. This study investigated the impacts of impervious surface area (ISA) on LST in urban agglomeration region. The distribution of ISA and LST of the Greater Pearl River Delta in 2015 was extracted using the Landsat 8 OLI and Aqua MODIS images. Next, the standard deviational ellipse methods were used to systematically analyze the spatial correlation of ISA and LST. Subsequently, the influences of ISA density and landscape pattern of ISA on LST were analyzed by various methods. The results showed that when the ISA density increased 10%, the daytime LST increased 0.46 °C at the density level lower than 70% and 0.55 °C at the density level higher than 70%, respectively. Likewise, when the ISA density increased 10%, the nighttime LST increased 0.285 °C at the density level lower than 70% and 0.39 °C at the density level higher than 70%, respectively. In addition, the results of correlation analysis indicated that landscape metrics of ISA and the density of ISA had significant correlation with the LST. However, the correlation was higher at daytime than at nighttime, due to the large terrain, complex environment and diverse surface cover types in the study area. [ABSTRACT FROM AUTHOR]

In higher education, the initial studying period of each course plays a crucial role for students, and seriously influences the subsequent learning activities. However, given the large size of a course’s students at universities, it has become impossible for teachers to keep track of the performance of individual students. In this circumstance, an academic early warning system is desirable, which automatically detects students with difficulties in learning (i.e., at-risk students) prior to a course starting. However, previous studies are not well suited to this purpose for two reasons: 1) they have mainly concentrated on e-learning platforms, e.g., massive open online courses (MOOCs), and relied on the data about students’ online activities, which is hardly accessed in traditional teaching scenarios; and 2) they have only made performance prediction when a course is in progress or even close to the end. In this paper, for traditional classroom-teaching scenarios, we investigate the task of pre-course student performance prediction, which refers to detecting at-risk students for each course before its commencement. To better represent a student sample and utilize the correlations among courses, we cast the problem as a multi-instance multi-label (MIML) problem. Besides, given the problem of data scarcity, we propose a novel multi-task learning method, i.e., MIML-Circle, to predict the performance of students from different specialties in a unified framework. Extensive experiments are conducted on five real-world datasets, and the results demonstrate the superiority of our approach over the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Flavokawain B (FKB) possesses strong anti-neoplastic activity against many cancer cells. Here we assessed its antitumor activity and molecular mechanisms in lung cancer H460 cells in vitro. FKB significantly inhibited cell proliferation and caused arrest of the cell cycle G2-M of H460 cells in a dose-dependent manner. FKB also inducted apoptosis, which was associated with cytochrome c release, caspase-7 and caspase-9 activation and Bcl-xL/Bax dys-regulation. FKB significantly down-regulated survivin and XIAP, and the inhibitory effect induced by FKB was greatly attenuated by through over-expression of survivin or Bax MEFs. Furthermore, FKB activated the mitogen-activated protein kinases and the JNK inhibitor SP600125 significantly decreased the growth-inhibitory and apoptotic effects of FKB. Together, these results suggest the anti-lung cancer potential of flavokawain B for the prevention and treatment of lung cancer. [ABSTRACT FROM AUTHOR]

This paper examines the changing regional distribution of grain production in China. Based on the analysis of data from county statistics for the period 2000–2003, major differences in the main grain-output regions in China can be observed. The main grain-producing areas have shifted from the south to the north of China. New grain production regions have been also added to western China since the late 1990s. The per capita grain consumption in one third of China’s main grain-producing counties has fallen below 400 kg; most of these areas are located in southern China. In the new millennium, Northeast China, the central-south North China, and the arid and semi-arid regions of Northwest China produced three quarters of the surplus grains. Most of these areas are located in regions susceptible to environmental change. The amount of grain production in these regions shows high fluctuations. It is argued here that further studies of recent environmental changes as well as a risk assessment of China’s food security in main grain-output regions are needed. [ABSTRACT FROM AUTHOR]

Adenocarcinoma at the gastroesophageal junction (ACGEJ) has dismal clinical outcomes, and there are currently few specific effective therapies because of limited knowledge on its genomic and transcriptomic alterations. The present study investigates genomic and transcriptomic changes in ACGEJ from Chinese patients and analyzes their drug vulnerabilities and associations with the survival time. Here we show that the major genomic changes of Chinese ACGEJ patients are chromosome instability promoted tumorigenic focal copy-number variations and COSMIC Signature 17-featured single nucleotide variations. We provide a comprehensive profile of genetic changes that are potentially vulnerable to existing therapeutic agents and identify Signature 17-correlated IFN-α response pathway as a prognostic marker that might have practical value for clinical prognosis of ACGEJ. These findings further our understanding on the molecular biology of ACGEJ and may help develop more effective therapeutic strategies. Adenocarcinoma at the gastroesophageal junction has a dismal prognosis and few drug options. Here, the authors present genomic and transcriptomic features and potential therapeutic targets and prognostic biomarkers of Chinese and Caucasian tumours, and reveal the molecular similarities. [ABSTRACT FROM AUTHOR]