With the fast-developing nanotechnology, metal based nanoparticles (NPs) production and application are increased significantly. These metal based NPs can enter agricultural land through both direct ...and indirect pathways. This review presents an overview of the fate and transport of metal based NPs and their interactions with plants in agricultural ecosystem system. The physical chemical properties of both metal based NPs (e.g. size, surface charge, surface coating) and soil matrix (e.g. pH, ionic strength, mineral composition, dissolved organic matter) all play important roles in determining the mobility, transformation and potential risks of metal based NPs in plant and soil system. NPs can be accumulated to plant roots and translocated to other parts of the plants. The properties of both plant and metal based NPs are playing critical roles to this process. Systematic research of metal based NPs in environmentally relevant concentrations and conditions is needed for the future study.
Genome-wide screening using CRISPR coupled with nuclease Cas9 (CRISPR-Cas9) is a powerful technology for the systematic evaluation of gene function. Statistically principled analysis is needed for ...the accurate identification of gene hits and associated pathways. Here, we describe how to perform computational analysis of CRISPR screens using the MAGeCKFlute pipeline. MAGeCKFlute combines the MAGeCK and MAGeCK-VISPR algorithms and incorporates additional downstream analysis functionalities. MAGeCKFlute is distinguished from other currently available tools by its comprehensive pipeline, which contains a series of functions for analyzing CRISPR screen data. This protocol explains how to use MAGeCKFlute to perform quality control (QC), normalization, batch effect removal, copy-number bias correction, gene hit identification and downstream functional enrichment analysis for CRISPR screens. We also describe gene identification and data analysis in CRISPR screens involving drug treatment. Completing the entire MAGeCKFlute pipeline requires ~3 h on a desktop computer running Linux or Mac OS with R support.
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The energy-energy correlator (EEC) in Quantum Chromodynamics (QCD) serves as an important event shape for probing the substructure of jets in high-energy collisions. A significant progress ...has been made in understanding the collinear limit, where the angle between two detectors approaches zero, from the factorization formula in QCD and the light-ray Operator Product Expansion (OPE) in Conformal Field Theory. Building upon prior research on the renormalization of light-ray operators, we take an innovative step to extend the light-ray OPE into non-conformal contexts, with a specific emphasis on perturbative QCD. Our proposed form of the light-ray OPE is constrained by three fundamental properties: Lorentz symmetry, renormalization group invariance, and constraints from physical observables. This extension allows us to derive a factorization formula for the collinear limit of EEC, facilitating the future exploration and understanding on subleading power corrections in collinear limit.
Abstract
The Cistrome Data Browser (DB) is a resource of human and mouse cis-regulatory information derived from ChIP-seq, DNase-seq and ATAC-seq chromatin profiling assays, which map the genome-wide ...locations of transcription factor binding sites, histone post-translational modifications and regions of chromatin accessible to endonuclease activity. Currently, the Cistrome DB contains approximately 47,000 human and mouse samples with about 24,000 newly collected datasets compared to the previous release two years ago. Furthermore, the Cistrome DB has a new Toolkit module with several features that allow users to better utilize the large-scale ChIP-seq, DNase-seq, and ATAC-seq data. First, users can query the factors which are likely to regulate a specific gene of interest. Second, the Cistrome DB Toolkit facilitates searches for factor binding, histone modifications, and chromatin accessibility in any given genomic interval shorter than 2Mb. Third, the Toolkit can determine the most similar ChIP-seq, DNase-seq, and ATAC-seq samples in terms of genomic interval overlaps with user-provided genomic interval sets. The Cistrome DB is a user-friendly, up-to-date, and well maintained resource, and the new tools will greatly benefit the biomedical research community. The database is freely available at http://cistrome.org/db, and the Toolkit is at http://dbtoolkit.cistrome.org.
Liver cancer is the fifth most common cancer and the second leading cause of malignant death in Asia, and Asia reports 72.5% of the world's cases in 2020. As the most common histological type, ...hepatocellular carcinoma (HCC) accounts for the majority of incidence and mortality of liver cancer cases. This review presents the changing epidemiology of HCC in Asian countries in recent years. Globally, aged, male and Asian populations remain the group with the highest risk of HCC. Hepatitis B virus (HBV) and hepatitis C virus (HCV) are still the leading risk factors of HCC with a slight decline in most Asian countries, which is mainly attributed to HBV vaccination of newborns, prevention of HCV horizontal transmission and treatment of chronic hepatitis. However, the prevalence of HCC caused by metabolic factors, including metabolic syndrome, obesity and non‐alcoholic fatty liver diseases, is increasing rapidly in Asian countries, which may eventually become the major cause of HCC. Excessive alcohol consumption continues to be an important risk factor as the average consumption of alcohol is still growing. Hopefully, great effort has been made to better prevention and treatment of HCC in most Asian regions, which significantly prolongs the survival of HCC patients. Asian countries tend to use more aggressive intervention than European and American countries, but it remains unclear whether this preference is related to a better prognosis. In conclusion, HCC remains a major disease burden in Asia, and the management of HCC should be adjusted dynamically based on the changing epidemiology.
Remote sensing image change detection (CD) is done to identify desired significant changes between bitemporal images. Given two co-registered images taken at different times, the illumination ...variations and misregistration errors overwhelm the real object changes. Exploring the relationships among different spatial–temporal pixels may improve the performances of CD methods. In our work, we propose a novel Siamese-based spatial–temporal attention neural network. In contrast to previous methods that separately encode the bitemporal images without referring to any useful spatial–temporal dependency, we design a CD self-attention mechanism to model the spatial–temporal relationships. We integrate a new CD self-attention module in the procedure of feature extraction. Our self-attention module calculates the attention weights between any two pixels at different times and positions and uses them to generate more discriminative features. Considering that the object may have different scales, we partition the image into multi-scale subregions and introduce the self-attention in each subregion. In this way, we could capture spatial–temporal dependencies at various scales, thereby generating better representations to accommodate objects of various sizes. We also introduce a CD dataset LEVIR-CD, which is two orders of magnitude larger than other public datasets of this field. LEVIR-CD consists of a large set of bitemporal Google Earth images, with 637 image pairs (1024 × 1024) and over 31 k independently labeled change instances. Our proposed attention module improves the F1-score of our baseline model from 83.9 to 87.3 with acceptable computational overhead. Experimental results on a public remote sensing image CD dataset show our method outperforms several other state-of-the-art methods.
High-throughput CRISPR screens have shown great promise in functional genomics. We present MAGeCK-VISPR, a comprehensive quality control (QC), analysis, and visualization workflow for CRISPR screens. ...MAGeCK-VISPR defines a set of QC measures to assess the quality of an experiment, and includes a maximum-likelihood algorithm to call essential genes simultaneously under multiple conditions. The algorithm uses a generalized linear model to deconvolute different effects, and employs expectation-maximization to iteratively estimate sgRNA knockout efficiency and gene essentiality. MAGeCK-VISPR also includes VISPR, a framework for the interactive visualization and exploration of QC and analysis results. MAGeCK-VISPR is freely available at http://bitbucket.org/liulab/mageck-vispr .
Previous RGB-D fusion systems based on convolutional neural networks typically employ a two-stream architecture, in which RGB and depth inputs are learned independently. The multi-modal fusion stage ...is typically performed by concatenating the deep features from each stream in the inference process. The traditional two-stream architecture might experience insufficient multi-modal fusion due to two following limitations: (1) the cross-modal complementarity is rarely studied in the bottom-up path, wherein we believe the cross-modal complements can be combined to learn new discriminative features to enlarge the RGB-D representation community and (2) the cross-modal channels are typically combined by undifferentiated concatenation, which appears ambiguous to selecting cross-modal complementary features. In this paper, we address these two limitations by proposing a novel three-stream attention-aware multi-modal fusion network. In the proposed architecture, a cross-modal distillation stream, accompanying the RGB-specific and depth-specific streams, is introduced to extract new RGB-D features in each level in the bottom-up path. Furthermore, the channel-wise attention mechanism is innovatively introduced to the cross-modal cross-level fusion problem to adaptively select complementary feature maps from each modality in each level. Extensive experiments report the effectiveness of the proposed architecture and the significant improvement over the state-of-the-art RGB-D salient object detection methods.
CRISPR-Cas9 screens have been widely adopted to analyze coding-gene functions, but high-throughput screening of non-coding elements using this method is more challenging because indels caused by a ...single cut in non-coding regions are unlikely to produce a functional knockout. A high-throughput method to produce deletions of non-coding DNA is needed. We report a high-throughput genomic deletion strategy to screen for functional long non-coding RNAs (lncRNAs) that is based on a lentiviral paired-guide RNA (pgRNA) library. Applying our screening method, we identified 51 lncRNAs that can positively or negatively regulate human cancer cell growth. We validated 9 of 51 lncRNA hits using CRISPR-Cas9-mediated genomic deletion, functional rescue, CRISPR activation or inhibition and gene-expression profiling. Our high-throughput pgRNA genome deletion method will enable rapid identification of functional mammalian non-coding elements.
The CRISPR/Cas9 system has revolutionized mammalian somatic cell genetics. Genome-wide functional screens using CRISPR/Cas9-mediated knockout or dCas9 fusion-mediated inhibition/activation ...(CRISPRi/a) are powerful techniques for discovering phenotype-associated gene function. We systematically assessed the DNA sequence features that contribute to single guide RNA (sgRNA) efficiency in CRISPR-based screens. Leveraging the information from multiple designs, we derived a new sequence model for predicting sgRNA efficiency in CRISPR/Cas9 knockout experiments. Our model confirmed known features and suggested new features including a preference for cytosine at the cleavage site. The model was experimentally validated for sgRNA-mediated mutation rate and protein knockout efficiency. Tested on independent data sets, the model achieved significant results in both positive and negative selection conditions and outperformed existing models. We also found that the sequence preference for CRISPRi/a is substantially different from that for CRISPR/Cas9 knockout and propose a new model for predicting sgRNA efficiency in CRISPRi/a experiments. These results facilitate the genome-wide design of improved sgRNA for both knockout and CRISPRi/a studies.
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