The production of 2,5-furandicarboxylic acid (FDCA) through green reaction routes is of crucial scientific value for the production of sustainable polymers. This study explores the active centers in ...cobalt-nitrogen-doped carbon (Co-N/C) for FDCA production. It was established that Co-Nx synergistically along with the nitrogen-doped carbon acted as centers for 5-hydroxymethylfurfural (HMF) oxidation. This study demonstrates a sustainable method for FDCA production from HMF without using precious metals, organic solvents, and harsh basic environments. Co-N/C catalyst displayed a high FDCA yield of ∼90% in an aqueous medium under mildly basic conditions in 34 h with 100% HMF conversion. An innovative strategy of stepwise base addition has been proposed to effectively accelerate the generation reaction of FDCA. The detrimental effects of high heating rate and calcination temperature on the active centers were also thoroughly investigated. Through DFT simulations it was established that Co-Nx aided in the activation of oxygen for HMF oxidation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need ...for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety of tissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.
Graphical Abstract
Graphical Abstract
BackgroundImmunotherapies may prolong the survival of patients with small-cell lung cancer (SCLC) to some extent. The role of forkhead box protein P3 (FOXP3) in tumor microenvironment (TME) remains ...controversial. We aimed to examine FOXP3-related expression characteristics and prognostic values and to develop a clinically relevant predictive system for SCLC.MethodsWe enrolled 102 patients with histologically confirmed SCLC at stages I–III. Through immunohistochemistry, we determined the expression pattern of FOXP3 and its association with other immune biomarkers. By machine learning and statistical analysis, we constructed effective immune risk score models. Furthermore, we examined FOXP3-related enrichment pathways and TME traits in distinct cohorts.ResultsIn SCLC, FOXP3 level was significantly associated with status of programmed death-ligand 1 (PD-L1), programmed cell death protein 1 (PD-1), CD4, CD8, and CD3 (p=0.002, p=0.001, p=0.002, p=0.030, and p<0.001). High FOXP3 expression showed longer relapse-free survival (RFS) than the low-level group (41.200 months, 95% CI 26.937 to 55.463, vs 14.000 months, 95% CI 8.133 to 19.867; p=0.008). For tumor-infiltrating lymphocytes (TILs), subgroup analysis demonstrated FOXP3 and PD-1, PD-L1, lymphocyte activation gene-3, CD3, CD4, or CD8 double positive were significantly correlated with longer RFS. We further performed importance evaluation for immune biomarkers, constructed an immune risk score incorporating the top three important biomarkers, FOXP3, TIL PD-L1, and CD8, and found their independently prognostic role to predict SCLC relapse. Better predictive performance was achieved in this immune risk model compared with single-indicator-based or two-indicator-based prediction systems (area under the curve 0.715 vs 0.312–0.711). Then, relapse prediction system integrating clinical staging and immune risk score was established, which performed well in different cohorts. High FOXP3-related genes were enriched in several immune-related pathways, and the close relationships of interleukin-2, CD28, basic excision repair genes MUTYH, POLD1, POLD2, and oxidative phosphorylation related gene cytochrome c oxidase subunit 8A with FOXP3 expression were revealed. Moreover, we found low-immune risk score group had statistically higher activated CD4+ memory T cells (p=0.014) and plasma cells (p=0.049) than the high-risk group. The heterogeneity of tumor-infiltrating immune cells might represent a promising feature for risk prediction in SCLC.ConclusionFOXP3 interacts closely with immune biomarkers on tumor-infiltrating cells in TME. This study highlighted the crucial prognostic value and promising clinical applications of FOXP3 in SCLC.
We used lectin microarray and mass spectrometric analysis to identify the N-linked glycosylation patterns of hepatitis C virus (HCV) particles. HCV J6/JFH-1 chimeric cell culture (HCVcc) in the ...culture supernatant was concentrated and purified by ultrafiltration and sucrose gradient ultracentrifugation. Twelve fractions were collected from the top and analyzed for viral infectivity and HCV RNA content after sucrose gradient separation. HCV RNA and proteins were separated by ultracentrifugation in a continuous 10% to 60% sucrose gradient to purify viral particles based on their sedimentation velocities. HCVcc particles were found mainly in fractions 6 to 8, as determined by quantitative polymerase chain reaction (qPCR) analysis for HCV RNA and ELISA of the HCV core protein. The N-glycans on HCV proteins were analyzed by lectin microarray and mass spectrometry. We identified that 32 of 37 lectins displayed the positive binding signals and 16 types of N-glycoforms of which the major HCV glycoforms were high mannose-type N-linked oligosaccharides, hybrid N-glycans, and fucosylated N-glycans. Our study provided new detailed information regarding the majority of the glycan-protein profile, complementing to previous findings of glycan-HCV protein interactions.
Deep excavations are prone to result in excessive ground surface settlement displacement of surrounding existing structures, which could cause severe economic damage, even casualties. Hence, the ...optimization of pile parameters and evaluation of the stability of the excavation are of paramount importance. This paper aims to evaluate the security of deep excavation and optimize the parameters of supported piles in granular soils. An excavation case in granular soils is used to evaluate the stability of deep excavation using displacement least squares method. The stability of case history, Changqingqiao subway station, using pile and inner support system is evaluated by using the least square method. Subsequently, the finite element method is used to optimize the critical parameters of the supported piles, and it needs to be emphasized that the correctness and reasonability of the finite element (FE) models are evaluated according to field measurements. The optimum pile diameter and embedment ratio for single- and double-row retaining pile are 1.0 m and 0.4. The maximum vertical displacement of surrounding soil and horizontal displacement of piles can be calculated by the equations obtained in this research which can provide useful guidance for the designing of deep excavation.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Abstract
The nervous system is one of the most complicated and enigmatic systems within the animal kingdom. Recently, the emergence and development of spatial transcriptomics (ST) and single-cell RNA ...sequencing (scRNA-seq) technologies have provided an unprecedented ability to systematically decipher the cellular heterogeneity and spatial locations of the nervous system from multiple unbiased aspects. However, efficiently integrating, presenting and analyzing massive multiomic data remains a huge challenge. Here, we manually collected and comprehensively analyzed high-quality scRNA-seq and ST data from the nervous system, covering 10 679 684 cells. In addition, multi-omic datasets from more than 900 species were included for extensive data mining from an evolutionary perspective. Furthermore, over 100 neurological diseases (e.g. Alzheimer's disease, Parkinson's disease, Down syndrome) were systematically analyzed for high-throughput screening of putative biomarkers. Differential expression patterns across developmental time points, cell types and ST spots were discerned and subsequently subjected to extensive interpretation. To provide researchers with efficient data exploration, we created a new database with interactive interfaces and integrated functions called the Spatiotemporal Cloud Atlas for Neural cells (SCAN), freely accessible at http://47.98.139.124:8799 or http://scanatlas.net. SCAN will benefit the neuroscience research community to better exploit the spatiotemporal atlas of the neural system and promote the development of diagnostic strategies for various neurological disorders.
Graphical Abstract
Graphical Abstract
Krüppel-like factor 17 (KLF17), a member of the KLF transcription factor family, has been shown to inhibit the epithelial-mesenchymal transition (EMT) and tumor growth. However, the expression, the ...cellular function and the mechanism of KLF17 in endometrioid endometrial cancer (EEC; a dominant type of endometrial cancer) remain elusive. Here, we report that among the KLF family members, KLF17 was consistently upregulated in EEC cell lines compared with immortalized endometrial epithelial cells. Overexpression of KLF17 in EEC cell lines induced EMT and promoted cell invasion and drug resistance, resulting in increased expression of TWIST1. In contrast, KLF17 suppression reversed EMT, diminished cell invasion, restored drug sensitivity and suppressed TWIST1 expression. Luciferase assays, site-directed mutagenesis and transcription factor DNA-binding analysis demonstrated that KLF17 transactivates TWIST1 expression by directly binding to the TWIST1 promoter. Knockdown of TWIST1 prevented KLF17-induced EMT. Consistent with these results, both KLF17 and TWIST1 levels were found to be elevated in EECs compared with normal tissues. KLF17 expression positively correlated with tumor grade but inversely correlated with estrogen and progesterone receptor expression. Thus, KLF17 may have an oncogenic role during EEC progression via initiating EMT through the regulation of TWIST1.
It is a challenge to efficiently integrate and present the tremendous amounts of single-cell data generated from multiple tissues of various species. Here, we create a new database named SPEED for ...single-cell pan-species atlas in the light of ecology and evolution for development and diseases (freely accessible at http://8.142.154.29 or http://speedatlas.net). SPEED is an online platform with 4 data modules, 7 function modules and 2 display modules. The 'Pan' module is applied for the interactive analysis of single cell sequencing datasets from 127 species, and the 'Evo', 'Devo', and 'Diz' modules provide comprehensive analysis of single-cell atlases on 18 evolution datasets, 28 development datasets, and 85 disease datasets. The 'C2C', 'G2G' and 'S2S' modules explore intercellular communications, genetic regulatory networks, and cross-species molecular evolution. The 'sSearch', 'sMarker', 'sUp', and 'sDown' modules allow users to retrieve specific data information, obtain common marker genes for cell types, freely upload, and download single-cell datasets, respectively. Two display modules ('HOME' and 'HELP') offer easier access to the SPEED database with informative statistics and detailed guidelines. All in all, SPEED is an integrated platform for single-cell RNA sequencing (scRNA-seq) and single-cell whole-genome sequencing (scWGS) datasets to assist the deep-mining and understanding of heterogeneity among cells, tissues, and species at multi-levels, angles, and orientations, as well as provide new insights into molecular mechanisms of biological development and pathogenesis.
This paper analyzes the research articles of language testing studies published between 2008 and 2018, using CiteSpace, a visualization tool in scientometrics. Research data were retrieved from 10 ...highly-cited international academic journals via the Web of Science Core Collection. The analysis focused on the most productive countries/regions/authors, high-impact references and highly cited authors, as well as the research fronts and hotspots in language testing studies. The results demonstrate: 1) The most productive regions are English-speaking countries, though recent years witnessed a significant increase in research output in Asian countries; 2) High-impact references and highly cited authors mainly focus on test validation, social dimensions of language testing, language assessment literacy and performance assessment; 3) Validity remains one of the most important research topics; language assessment and learning will be more closely connected; 4) Technology will continue to play a prominent role in langu
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