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Background: Gastric cancer is a malignant tumor with high morbidity and mortality. Therefore, the accurate recognition of prognostic molecular markers is the key to improving treatment efficacy and prognosis. Methods: In this study, we developed a stable and robust signature through a series of processes using machine-learning approaches. This PRGS was further experimentally validated in clinical samples and a gastric cancer cell line. Results: The PRGS is an independent risk factor for overall survival that performs reliably and has a robust utility. Notably, PRGS proteins promote cancer cell proliferation by regulating the cell cycle. Besides, the high-risk group displayed a lower tumor purity, higher immune cell infiltration, and lower oncogenic mutation than the low-PRGS group. Conclusions: This PRGS could be a powerful and robust tool to improve clinical outcomes for individual gastric cancer patients.

Red mud is a byproduct of the aluminum oxide refining process that is an industrial waste residue. The storage of red mud can seriously contaminate the soil, water system, and atmosphere while also taking up a lot of valuable land resources. However, the use of stabilized/amended red mud technology in road engineering is relatively limited. Consequently, this research investigates how additives (cement, lime, and phosphogypsum) affect the strength of amended red mud as road base material. Additionally, it examines the effects of dry–wet and freeze–thaw cycles on the UCS, pH, dry density, and evolution of micropore structure in amended red mud with different phosphogypsum content. The findings reveal that, after five dry–wet and freeze–thaw cycles, the samples with 2% phosphogypsum content have a strong assurance rate of more than 85%. The percentage of micropores (0.01–0.1 μm) is reduced, although the percentage of small pores (0.1–1 μm) and medium pores (1–10 μm) is increased by dry–wet and freeze–thaw cycles. The cumulative mercury intake rises as the percentage increases, and the dry–wet cycle has a greater impact on the strength of amended red mud than the freeze–thaw cycle.

Clustering cells and depicting the lineage relationship among cell subpopulations are fundamental tasks in single-cell omics studies. However, existing analytical methods face challenges in stratifying cells, tracking cellular trajectories, and identifying critical points of cell transitions. To overcome these, we proposed a novel Markov hierarchical clustering algorithm (MarkovHC), a topological clustering method that leverages the metastability of exponentially perturbed Markov chains for systematically reconstructing the cellular landscape. Briefly, MarkovHC starts with local connectivity and density derived from the input and outputs a hierarchical structure for the data. We firstly benchmarked MarkovHC on five simulated datasets and ten public single-cell datasets with known labels. Then, we used MarkovHC to investigate the multi-level architectures and transition processes during human embryo preimplantation development and gastric cancer procession. MarkovHC found heterogeneous cell states and sub-cell types in lineage-specific progenitor cells and revealed the most possible transition paths and critical points in the cellular processes. These results demonstrated MarkovHC’s effectiveness in facilitating the stratification of cells, identification of cell populations, and characterization of cellular trajectories and critical points.

Spatial metabolomics can reveal intercellular heterogeneity and tissue organization. Here we report on the spatial single nuclear metabolomics (SEAM) method, a flexible platform combining high-spatial-resolution imaging mass spectrometry and a set of computational algorithms that can display multiscale and multicolor tissue tomography together with identification and clustering of single nuclei by their in situ metabolic fingerprints. We first applied SEAM to a range of wild-type mouse tissues, then delineated a consistent pattern of metabolic zonation in mouse liver. We further studied the spatial metabolic profile in the human fibrotic liver. We discovered subpopulations of hepatocytes with special metabolic features associated with their proximity to the fibrotic niche, and validated this finding by spatial transcriptomics with Geo-seq. These demonstrations highlighted SEAM’s ability to explore the spatial metabolic profile and tissue histology at the single-cell level, leading to a deeper understanding of tissue metabolic organization. SEAM is a platform for the analysis of high-resolution secondary ion mass spectrometry imaging that allows spatially resolved nuclear metabolomic profiling at the single-cell level.

Background Liquid-liquid phase separation (LLPS) is an important organizing principle for biomolecular condensation and chromosome compartmentalization. However, while many proteins have been reported to undergo LLPS, quantitative and global analysis of chromatin LLPS property remains absent. Results Here, by combining chromatin-associated protein pull-down, quantitative proteomics and 1,6-hexanediol (1,6-HD) treatment, we develop Hi-MS and define an anti-1,6-HD index of chromatin-associated proteins (AICAP) to quantify 1,6-HD sensitivity of chromatin-associated proteins under physiological conditions. Compared with known physicochemical properties involved in phase separation, we find that proteins with lower AICAP are associated with higher content of disordered regions, higher hydrophobic residue preference, higher mobility and higher predicted LLPS potential. We also construct BL-Hi-C libraries following 1,6-HD treatment to study the sensitivity of chromatin conformation to 1,6-HD treatment. We find that the active chromatin and high-order structures, as well as the proteins enriched in corresponding regions, are more sensitive to 1,6-HD treatment. Conclusions Our work provides a global quantitative measurement of LLPS properties of chromatin-associated proteins and higher-order chromatin structure. Hi-MS and AICAP data provide an experimental tool and quantitative resources valuable for future studies of biomolecular condensates.

Phase separation is an important mechanism that mediates the compartmentalization of proteins in cells. Proteins that can undergo phase separation in cells share certain typical sequence features, like intrinsically disordered regions (IDRs) and multiple modular domains. Sequence-based analysis tools are commonly used in the screening of these proteins. However, current phase separation predictors are mostly designed for IDR-containing proteins, thus inevitably overlook the phase-separating proteins with relatively low IDR content. Features other than amino acid sequence could provide crucial information for identifying possible phase-separating proteins: protein-protein interaction (PPI) networks show multivalent interactions that underlie phase separation process; post-translational modifications (PTMs) are crucial in the regulation of phase separation behavior; spherical structures revealed in immunofluorescence (IF)images indicate condensed droplets formed by phase-separating proteins, distinguishing these proteins from non-phase-separating proteins. Here, we summarize the sequence-based tools for predicting phase-separating proteins and highlight the importance of incorporating PPIs, PTMs, and IF images into phase separation prediction in future studies.

Piles adjacent to a surcharge load commonly support not only active loads from superstructures but also the passive loads caused by soil lateral movement. To investigate the influence of passive load and the response along pile shafts of existing actively loaded piles, a load transfer model for analyzing the soil-pile interaction was developed based on plastic deformation theory and the triparameter soil model. An analytical solution for the deformation and internal force of such piles was proposed using the transfer matrix method, in which the transfer matrix coefficients for piles in free, plastic, and elastic zones were analytically obtained by considering the second-order axial force effect caused by lateral loading and soil yielding based on the triparameter soil model. The proposed methodology was validated by comparing its predictions with field measurements and previously published results. A good match between model predictions, field measurements, and previously published results implies that the proposed method can be used to evaluate the response of passive piles adjacent to a surcharge load. Parametric studies were also carried out to investigate the influence of surcharge pressure, soil resistance, and boundary conditions on the behavior of passively loaded piles adjacent to a surcharge load.

The rapidly developing spatial omics techniques generate datasets with diverse scales and modalities. However, most existing methods focus on modeling dynamics of single cells while ignore microenvironments (MEs) which bridge single cells to tissues. Here we present SOTIP (Spatial Omics mulTIPle-task analysis), a scalable framework incorporating MEs and their interrelationships into a unified graph. Based on this graph, three tasks can be performed, including spatial heterogeneity (SHN) quantification, spatial domain (SDM) identification and differential microenvironment (DME) analysis. We validate SOTIP’s accuracy, robustness, interpretation, and scalability on various datasets by comparing with state-of-art methods. In mammalian cerebral cortex, we reveal a striking gradient SHN pattern with strong correlations with the cortical depth. In human triple-negative breast cancer (TNBC), we identify previously unreported molecular polarizations around SOTIP-detected tumor-immune boundaries. Most importantly, we discover TNBC subtype-specific MEs, which exhibit interesting compositional and spatial properties, and could be powerful clinical indicators. Overall, by modeling biologically explainable microenvironments, SOTIP outperforms state-of-art methods and provides new perspectives for data interpretation, which facilitates further understanding of spatial information on a variety of biological issues.

Recent developments of single cell RNA-sequencing technologies lead to the exponential growth of single cell sequencing datasets across different conditions. Combining these datasets helps to better understand cellular identity and function. However, it is challenging to integrate different datasets from different laboratories or technologies due to batch effect, which are interspersed with biological variances. To overcome this problem, we have proposed Single Cell Integration by Disentangled Representation Learning (SCIDRL), a domain adaption-based method, to learn low-dimensional representations invariant to batch effect. This method can efficiently remove batch effect while retaining cell type purity. We applied it to thirteen diverse simulated and real datasets. Benchmark results show that SCIDRL outperforms other methods in most cases and exhibits excellent performances in two common situations: (i) effective integration of batch-shared rare cell types and preservation of batch-specific rare cell types; (ii) reliable integration of datasets with different cell compositions. This demonstrates SCIDRL will offer a valuable tool for researchers to decode the enigma of cell heterogeneity.

3D genome alternations can dysregulate gene expression by rewiring enhancer-promoter interactions and lead to diseases. We report integrated analyses of 3D genome alterations and differential gene expressions in 18 newly diagnosed T-lineage acute lymphoblastic leukemia (T-ALL) patients and 4 healthy controls. 3D genome organizations at the levels of compartment, topologically associated domains and loop could hierarchically classify different subtypes of T-ALL according to T cell differentiation trajectory, similar to gene expressions-based classification. Thirty-four previously unrecognized translocations and 44 translocation-mediated neo-loops are mapped by Hi-C analysis. We find that neo-loops formed in the non-coding region of the genome could potentially regulate ectopic expressions of TLX3, TAL2 and HOXA transcription factors via enhancer hijacking. Importantly, both translocation-mediated neo-loops and NUP98-related fusions are associated with HOXA13 ectopic expressions. Patients with HOXA11-A13 expressions, but not other genes in the HOXA cluster, have immature immunophenotype and poor outcomes. Here, we highlight the potentially important roles of 3D genome alterations in the etiology and prognosis of T-ALL., The non-coding genome of T-ALL has not been extensively studied. Here, the authors conduct RNA-seq, ATAC-seq and Hi-C seq analyses and find that T-ALL associated neo-loops may regulate key transcription factors including HOXA13; the aberrant expression of which is associated with poor prognosis.

The odd-mode and even-mode spoof surface plasmon polariton (SSPPs) transmission based on a complementary plasmonic structure are studied in this paper. The dispersion properties and electro...

It's widely appreciated that liquid–liquid phase separation (LLPS) underlies the formation of membraneless organelles, which function to concentrate proteins and nucleic acids. In the past few decades, major efforts have been devoted to identify the phase separation associated proteins and elucidate their functions. To better utilize the knowledge dispersed in published literature, we developed PhaSepDB (http://db.phasep.pro/), a manually curated database of phase separation associated proteins. Currently, PhaSepDB includes 2914 non-redundant proteins localized in different organelles curated from published literature and database. PhaSepDB provides protein summary, publication reference and sequence features of phase separation associated proteins. The sequence features which reflect the LLPS behavior are also available for other human protein candidates. The online database provides a convenient interface for the research community to easily browse, search and download phase separation associated proteins. As a centralized resource, we believe PhaSepDB will facilitate the future study of phase separation.

The genome exists as an organized, three-dimensional (3D) dynamic architecture, and each cell type has a unique 3D genome organization that determines its cell identity. An unresolved question is how cell type-specific 3D genome structures are established during development. Here, we analyzed 3D genome structures in muscle cells from mice lacking the muscle lineage transcription factor (TF), MyoD, versus wild-type mice. We show that MyoD functions as a “genome organizer” that specifies 3D genome architecture unique to muscle cell development, and that H3K27ac is insufficient for the establishment of MyoD-induced chromatin loops in muscle cells. Moreover, we present evidence that other cell lineage-specific TFs might also exert functional roles in orchestrating lineage-specific 3D genome organization during development., Pioneer transcription factors (TFs) have been proposed to act as protein anchors to orchestrate cell type-specific 3D genome architecture. MyoD is a pioneer TF for myogenic lineage specification. Here the authors provide further support for the role of MyoD in 3D genome architecture in muscle stem cells by comparing MyoD knockout and wild-type mice.

BackgroundLiquid–liquid phase separation (LLPS) is an important organizing principle for biomolecular condensation and chromosome compartmentalization. However, while many proteins have been reported to undergo LLPS, quantitative and global analysis of chromatin LLPS property remains absent.ResultsHere, by combing chromatin associated protein pull-down, quantitative proteomics and 1,6-hexanediol treatment, we developed Hi-MS and defined anti-1,6-HD index of chromatin-associated proteins (AICAP) to quantitative measurement of LLPS property of chromatin-associated proteins in their endogenous state and physiological abundance. The AICAP values were verified by previously reported experiments and were reproducible across different MS platforms. Moreover, the AICAP values were highly correlate with protein functions. Proteins act in active/regulatory biological process often exhibit low AICAP values, while proteins act in structural and repressed biological process often exhibit high AICAP values. We further revealed that chromatin organization changes more in compartment A than B, and the changes in chromatin organization at various levels, including compartments, TADs and loops are highly correlated to the LLPS properties of their neighbor nuclear condensates.ConclusionsOur work provided the first global quantitative measurement of LLPS properties of chromatin-associated proteins and higher-order chromatin structure, and demonstrate that the active/regulatory chromatin components, both protein (trans) and DNA (cis), exhibit more hydrophobicity-dependent LLPS properties than the repressed/structural chromatin components.

We consider the commutators $[b,T]$ and $[b,I_{\rho}]$ on Orlicz-Morrey spaces, where $T$ is a Calder\'on-Zygmund operator, $I_{\rho}$ is a generalized fractional integral operator and $b$ is a function in generalized Campanato spaces. We give a necessary and sufficient condition for the boundedness of the commutators on Orlicz-Morrey spaces. To do this we prove the boundedness of generalized fractional maximal operators on Orlicz-Morrey spaces. Moreover, we introduce Orlicz-Campanato spaces and establish their relations to Orlicz-Morrey spaces., Comment: 45 pages. arXiv admin note: text overlap with arXiv:1812.09148

Abutment piles in soft ground are always subjected to both active loads from upper structures and passive loads from horizontal soft ground displacements; however, theoretical solutions fo...

The genome is not a linear molecule of DNA randomly folded in the nucleus, but exists as an organized, three-dimensional (3D) dynamic architecture. Intriguingly, it is now clear that each cell type has a unique and characteristic 3D genome organization that functions in determining cell identity during development. A currently challenging basic question is how cell-type specific 3D genome structures are established during development. Herein, we analyzed 3D genome structures in primary myoblasts and myocytes from MyoD knockout (MKO) and wild type (WT) mice and discovered that MyoD, a pioneer transcription factor (TF), can function as a “genome organizer” that specifies the proper 3D genome architecture unique to muscle cell development. Importantly, we genetically demonstrate that H3K27ac is insufficient for establishing MyoD-induced chromatin loops in muscle cells. The establishment of MyoD’s “architectural role” should have profound impacts on advancing understanding of other pioneer transcription factors in orchestrating lineage specific 3D genome organization during development in a potentially very large number of cell types in diverse organisms.

Spatial metabolomics can reveal intercellular heterogeneity and tissue organization. Here we report on the spatial single nuclear metabolomics (SEAM) method, a flexible platform combining high-spatial-resolution imaging mass spectrometry and a set of computational algorithms that can display multiscale and multicolor tissue tomography together with identification and clustering of single nuclei by their in situ metabolic fingerprints. We first applied SEAM to a range of wild-type mouse tissues, then delineated a consistent pattern of metabolic zonation in mouse liver. We further studied the spatial metabolic profile in the human fibrotic liver. We discovered subpopulations of hepatocytes with special metabolic features associated with their proximity to the fibrotic niche, and validated this finding by spatial transcriptomics with Geo-seq. These demonstrations highlighted SEAM's ability to explore the spatial metabolic profile and tissue histology at the single-cell level, leading to a deeper understanding of tissue metabolic organization.

Recent studies have demonstrated that 3D genome alterations play important roles in tumorigenesis1–3, including the development of hematological malignancies4–7. However, how such alterations may provide key insights into T-lineage acute lymphoblastic leukemia (T-ALL) patients is largely unknown. Here, we report integrated analyses of 3D genome alterations and differentially expressed genes (DEGs) in 18 newly diagnosed T-ALL patients and 4 healthy T cell controls. We found that 3D genome organization at the compartment, topologically associated domains (TAD) and loop levels as well as the gene expression profiles could hierarchically classify different subtypes of T-ALL according to the T cell differentiation trajectory. Alterations in the 3D genome were associated with nearly 45% of the upregulated genes in T-ALL. We also identified 34 previously unrecognized translocations in the noncoding regions of the genome and 44 new loops formed between translocated chromosomes, including translocation-mediated enhancer hijacking of the HOXA cluster. Our analysis demonstrated that T-ALLs with HOXA cluster overexpression were heterogeneous clinical entities, and ectopic expressions of the HOXA11-A13 genes, but not other genes in the HOXA cluster, were associated with immature phenotypes and poor outcomes. Our findings highlight the potentially important roles of 3D genome alterations in the etiology and prognosis of T-ALL.

Phase separation is an important mechanism that mediates the spatial distribution of proteins in different cellular compartments. While phase-separated proteins share certain sequence characteristics, including intrinsically disordered regions (IDRs) and prion-like domains, such characteristics are insufficient for making accurate predictions; thus, a proteome-wide understanding of phase separation is currently lacking. Here, we define phase-separated proteomes based on the systematic analysis of immunofluorescence images of 12 073 proteins in the Human Protein Atlas. The analysis of these proteins reveals that phase-separated candidate proteins exhibit higher IDR contents, higher mean net charge and lower hydropathy and prefer to bind to RNA. Kinases and transcription factors are also enriched among these candidate proteins. Strikingly, both phase-separated kinases and phase-separated transcription factors display significantly reduced substrate specificity. Our work provides the first global view of the phase-separated proteome and suggests that the spatial proximity resulting from phase separation reduces the requirement for motif specificity and expands the repertoire of substrates. The source code and data are available at https://github.com/cheneyyu/deepphase.

In the present paper, we will characterize the boundedness of the generalized fractional integral operators I? and the generalized fractional maximal operators M? on Orlicz spaces, respectively. Moreover, we will give a characterization for the Spanne-type boundedness and the Adams-type boundedness of the operators M? and I? on generalized Orlicz–Morrey spaces, respectively. Also we give criteria for the weak versions of the Spanne-type boundedness and the Adams-type boundedness of the operators M? and I? on generalized Orlicz–Morrey spaces. © 2018, Springer Nature Switzerland AG., Ministry of Education and Science of the Russian Federation: 15H03621, 02. FEF.A4.18.019, EIF-BGM-4-RFTF-1/2017-21/01/1 Japan Society for the Promotion of Science: 16K05209, The research of F. Deringoz was partially supported by the Grant of Ahi Evran University Scientific Research Project (FEF.A4.18.019). The research of V. Guliyev was partially supported by the Grant of 1st Azerbaijan–Russia Joint Grant Competition (Agreement Number No. EIF-BGM-4-RFTF-1/2017-21/01/1) and by the Ministry of Education and Science of the Russian Federation (the Agreement No. 02.a03.21.0008). Eiichi Nakai was supported by Grant-in-Aid for Scientific Research (B), No. 15H03621, Japan Society for the Promotion of Science. Yoshihiro Sawano was supported by Grant-in-Aid for Scientific Research (C) (16K05209), the Japan Society for the Promotion of Science and by Peoples Friendship University of Russia. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Interferon-induced transmembrane protein (IFITM) 1, 2 and 3 genes encode a family of interferon (IFN)-induced transmembrane proteins that block entry of a broad spectrum of pathogens. However, the transcriptional regulation of these genes, especially whether there exist any enhancers and their roles during the IFN induction process remain elusive. Here, through public data mining, episomal luciferase reporter assay and in vivo CRISPR-Cas9 genome editing, we identified an IFN-responsive enhancer located 35 kb upstream of IFITM3 gene promoter upregulating the IFN-induced expression of IFITM1, 2 and 3 genes. Chromatin immunoprecipitation (ChIP), electrophoretic mobility shift assay (EMSA) and luciferase reporter assay demonstrated that signal transducers and activators of transcription (STAT) 1 bound to the enhancer with the treatment of IFN and was indispensable for the enhancer activity. Furthermore, using chromosome conformation capture technique, we revealed that the IFITM1, 2 and 3 genes physically clustered together and constitutively looped to the distal enhancer through long-range interactions in both HEK293 and A549 cells, providing structural basis for coordinated regulation of IFITM1, 2 and 3 by the enhancer. Finally, we showed that in vivo truncation of the enhancer impaired IFN-induced resistance to influenza A virus (IAV) infection. These findings expand our understanding of the mechanisms underlying the transcriptional regulation of IFITM1, 2 and 3 expression and its ability to mediate IFN signaling., Highlights • This is the first report of an enhancer coordinately upregulating IFN-induced expression of IFITM genes • The enhancer functions through IFN-induced STAT1 binding and constitutive long-range interactions • The enhancer contributes to the IFN-induced resistance to IAV infection

Intrinsically disordered region (IDR) analysis has been widely used in the screening of phase-separated proteins. However, the precise sequences determining phase separation remain unclear. Furthermore, a large number of phase-separated proteins that exhibit relatively low IDR content remain uncharacterized. Phase-separated proteins appear as spherical droplet structures in immunofluorescence (IF) images, which renders them distinguishable from non-phase-separated proteins. Here, we transformed the problem of phase-separated protein recognition into a binary classification problem of image recognition. In addition, we established a method named IDeepPhase to identify IF images with spherical droplet structures based on convolutional neural networks. Using IDeepPhase on proteome-scale IF images from the Human Protein Atlas database, we generated a comprehensive list of phase-separated candidates which displayed spherical droplet structures in IF images, allowing nomination of proteins, antibodies and cell lines for subsequent phase separation study.

Field investigations and laboratory tests were performed to determine the cause of engineering distress due to the swelling of lime-stabilized and phosphogypsum-stabilized soil and subseque...

Uranium is a trace elemental in coal. The uranium content from coal mines in China and its distribution in coal-fired power plant effluents was studied and reported in this paper. Chinese coal samples from eighteen coal mines were collected and analyzed for uranium. It was found that the uranium content for most of the coals was in the range from 1 to 3 mg/kg. Laboratory experiments with a tubular furnace indicate that the amount of uranium released from heated coal increases with temperature and with the retention time, when it combust. Most of the uranium (about 90%) in the coal can be transferred to the ash. Full-scale field tests were carried out at a coal-fired power plant to investigate the uranium distribution (and mass balance) in the coal, limestone, fly ash, bottom ash, gypsum and the flue gas. Almost all the uranium in the coal concentrated in the fly ash (about 80%) and the bottom ash (about 10%). The uranium content in the flue gas was less than 1/1000 of the total elemental input, between 0.043 and 0.069 μg/m 3 , which is much lower than the typical concentration of mercury or arsenic in flue gas of coal-fired power plant. The uranium content in the desulfurization gypsum product was found to be slightly larger than the uranium content of the limestone.

This paper designed, fabricated and measured a THz fourth-harmonic conversion system based on GaAs Schottky barrier diode. Using the fourth-harmonic mixing method, the LO frequency is a quarter of (RF-IF) frequency and is corresponding to W band. Furthermore, the generators only need to supply LO signal of Ku band and IF signal of C band due to the sextupler in LO chain and quadrupler in IF chain. Based on the measurement results, this conversion system could generate 364–380 GHz signal with a typical conversion loss of 25.5 dB. The presented conversion system extends the existing microwave generators to THz applications and offers a low-cost, simple and alternative solution for those who lacking of lower THz signal source.

Background Entolimod is a Salmonella enterica flagellin derivate. Previous work has demonstrated that entolimod effectively protects mice and non-human primates from ionizing radiation. However, it caused a “flu-like” syndrome after radioprotective and anticancer clinical application, indicating some type of immunogenicity and toxicity. Cyclization is commonly used to improve the in vivo stability and activity of peptides and proteins. Methods We designed and constructed cyclic entolimod using split Nostoc punctiforme DnaE intein with almost 100% cyclization efficiency. We adopted different strategies to purify the linear and circular entolimod due to their different topologies. Both of linear and circular entolimod were first purified by Ni-chelating affinity chromatography, and then the linear and circular entolimod were purified by size-exclusion and ion-exchange chromatography, respectively. Results The circular entolimod showed significantly increased both the in vitro NF-κB signaling and in vivo radioprotective activity in mice. Conclusion Our data indicates that circular entolimod might be a good candidate for further clinical investigation.