Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning

Relational graph neural networks have garnered particular attention to encode graph context in knowledge graphs (KGs). Although they achieved competitive performance on small KGs, how to efficiently and effectively utilize graph context for large KGs remains an open problem. To this end, we propose the Relation-based Embedding Propagation (REP) method. It is a post-processing technique to adapt pre-trained KG embeddings with graph context. As relations in KGs are directional, we model the incoming head context and the outgoing tail context separately. Accordingly, we design relational context functions with no external parameters. Besides, we use averaging to aggregate context information, making REP more computation-efficient. We theoretically prove that such designs can avoid information distortion during propagation. Extensive experiments also demonstrate that REP has significant scalability while improving or maintaining prediction quality. Notably, it averagely brings about 10% relative improvement to triplet-based embedding methods on OGBL-WikiKG2 and takes 5%-83% time to achieve comparable results as the state-of-the-art GC-OTE.Comment: Accepted by IJCAI 202

The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region

Data and code availability The authors declare that the majority of the data supporting the findings of this study are available through the links given in the paper. The unpublished data are available from the corresponding author upon request. The new estimate of Tibetan soil carbon stock and R code are available in a persistent repository (https://figshare.com/s/4374f28d880f366eff6d). Acknowledgements This study was supported by the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA20050101), the National Natural Science Foundation of China (41871104), Key Research and Development Programs for Global Change and Adaptation (2017YFA0603604), International Partnership Program of the Chinese Academy of Sciences (131C11KYSB20160061) and the Thousand Youth Talents Plan project in China. Jinzhi Ding acknowledges the General (2017M620922) and the Special Grade (2018T110144) of the Financial Grant from the China Postdoctoral Science Foundation.Peer reviewedPublisher PD

Ginsenoside Rc: A potential intervention agent for metabolic syndrome

Ginsenoside Rc, a dammarane-type tetracyclic triterpenoid saponin primarily derived from Panax ginseng, has garnered significant attention due to its diverse pharmacological properties. This review outlined the sources, putative biosynthetic pathways, extraction, and quantification techniques, as well as the pharmacokinetic properties of ginsenoside Rc. Furthermore, this study explored the pharmacological effects of ginsenoside Rc against metabolic syndrome (MetS) across various phenotypes including obesity, diabetes, atherosclerosis, non-alcoholic fatty liver disease, and osteoarthritis. It also highlighted the impact of ginsenoside Rc on multiple associated signaling molecules. In conclusion, the anti-MetS effect of ginsenoside Rc is characterized by its influence on multiple organs, multiple targets, and multiple ways. Although clinical investigations regarding the effects of ginsenoside Rc on MetS are limited, its proven safety and tolerability suggest its potential as an effective treatment option

Study on Improvement Characteristics of a Novel Geotextile with Stitched Transverse Ribs

Geotextile is one of the reinforcement materials adopted in many engineering structures. Conventional geotextiles have a limited reinforcement effect due to the insufficient friction strength between geotextiles and soils. This paper proposes a novel type of geotextile with stitched transverse ribs to improve the reinforcement effect. A series of large-scale direct shear tests have been conducted, and the improvement characteristics between conventional geotextiles, geogrids, and the novel geotextiles have been studied. The results show that the novel stitched transverse rib geotextiles can significantly increase the shear strength compared to conventional geotextiles and geogrids. Moreover, due to the restraint and friction effect of ribs on the soils, the reinforcement effect of the novel geotextile is increased with increasing ribs. Insights from this study can provide a new understanding of the novel stitched transverse ribs geotextile’s reinforcement mechanism in engineering

Numerical Investigation of Mechanical Performance and Micro-Structure Failure of Polymer-Fiber Reinforced Sand

Natural sand has a loose and porous structure with low strength, and is prone to many geoengineering problems that cause huge losses. In this study, an organic polymer-polymer-fiber blend was used to improve the strength of sand. Using a series of laboratory and numerical simulation tests, researchers have investigated the microdamage behavior of an organic polymer and fiber-treated sand in various types of mechanical tests and explored the improvement mechanism. The results showed that the polymer- and fiber-treated sand enhanced the integrity and exhibited differential damage responses under different test conditions. The increase in polymer content induced uniform force transfer, leading to a wider range of particle motion and crack initiation, whereas the fibers adhered and confined the surrounding particles, inducing an arching force chain and dispersive/buckling cracking. Polymer- and fiber-treated sands increased their energy-carrying capacity and improved their energy release, which affected the damage characteristics. Organic polymers, fibers, and sand particles were wrapped around each other to form an effective interlocking structure, which enhances the integrity and mechanical properties of sand. This study provides novel ideas and methods in the polymer-fiber composite treatment of sand in the microscopic field

Glutamine deprivation induces ferroptosis in pancreatic cancer cells

Ferroptosis is a type of programmed cell death closely related to amino acid metabolism. Pancreatic cancer cells have a strong dependence on glutamine, which serves as a carbon and nitrogen substrate to sustain rapid growth. Glutamine also aids in self-protection mechanisms. However, the effect of glutamine on ferroptosis in pancreatic cancer remains largely unknown. Here, we aim to explore the association between ferroptosis and glutamine deprivation in pancreatic cancer. The growth of pancreatic cancer cells in culture media with or without glutamine is evaluated using Cell Counting Kit-8. Reactive oxygen species (ROS) are measured by 2′,7′-dichlorodihydrofluorescein diacetate staining. Ferroptosis is assessed by BODIPY-C11 dye using confocal microscopy and flow cytometry. Amino acid concentrations are measured using ultrahigh-performance liquid chromatography-tandem mass spectrometry. Isotope-labelled metabolic flux analysis is performed to track the metabolic flow of glutamine. Additionally, RNA sequencing is performed to analyse the genetic alterations. Glutamine deprivation inhibits pancreatic cancer growth and induces ferroptosis both in vitro and in vivo. Additionally, glutamine decreases ROS formation via glutathione production in pancreatic cancer cells. Interestingly, glutamine inhibitors (diazooxonorleucine and azaserine) promotes ROS formation and ferroptosis in pancreatic cancer cells. Furthermore, ferrostatin, a ferroptosis inhibitor, rescues ferroptosis in pancreatic cancer cells. Glutamine deprivation leads to changes in molecular pathways, including cytokine-cytokine receptor interaction pathways ( CCL5, CCR4, LTA, CXCR4, IL-6R, and IL-7R). Thus, exogenous glutamine is required for the detoxification of ROS in pancreatic cancer cells, thereby preventing ferroptosis

Characterization of Estrogen Receptors in Pancreatic Adenocarcinoma with Tertiary Lymphoid Structures

The role of estrogen signaling in antitumor immunology remains unknown for non-traditional sex-biased cancer types such as pancreatic adenocarcinoma (PAAD). Tertiary lymphoid structures (TLS) are active zones composed of multiple types of immune cells, whose presence indicates anti-tumor immune responses. In this study, we employed a 12-chemokine signature to characterize potential gene categories associated with TLS development and identified seventeen major gene categories including estrogen receptors (ERs). Immunohistochemistry staining revealed the expression patterns of three ERs (ERα, ERβ, and GPER) in 174 PAAD samples, and their correlation with clinicopathological characteristics, immune cell infiltration levels, and intratumoral TLS presence was analyzed. The results indicated that ERα (+) and ERβ (+) were correlated with high tumor grade, and ERβ (+) and GPER (+) were correlated with lower TNM stage, and both ERα (+) and GPER (+) displayed a beneficial effect on prognosis in this cohort. Interestingly, positive staining of all three ERs was significantly correlated with the presence of intratumoral TLSs and infiltration of more active immune cells into the microenvironment. Moreover, the chemotaxis of CD8+T-cells to PAAD cells was significantly increased in vitro with upregulated expression of ERα or ERβ on PAAD cells. To conclude, our study showed a novel correlation between ER expression and TLS development, suggesting that ERs may play a protective role by enhancing anti-tumor immune responses in PAAD

Expression Profiles of Cuproptosis-Related Genes Determine Distinct Subtypes of Pancreatic Ductal Adenocarcinoma

Background: Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent subtype of pancreatic cancer and one of the most malignant tumors worldwide. Due to the heterogeneity of its genomics and proteomics, the prognosis of PDAC remains disappointing despite advances in surgery and medicines. Recently, a novel form of programmed cell death, cuproptosis, was proposed, although its role in PDAC has not been investigated. This study aimed to quantify the expression of cuproptosis-related genes and characterize the novel subtypes of PDAC. Methods: To evaluate the pattern of cuproptosis in PDAC, the gene expression data and clinical information of 372 samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A consensus cluster analysis was performed using the transcriptional levels, genetic alterations, and individual prognostic values of seven pre-selected cuproptosis-related genes (DLAT, LIPT1, FDX1, DLD, PDHB, PDHA1, and LIAS) to identify the novel subtypes associated with cuproptosis in PDAC. A univariate Cox regression analysis was used to determine the significant prognostic indicators and cuproptosis scores among the differentially expressed genes (DEGs) between the dividing subclusters, followed by a principal component analysis. The prognostic values, immune profiles, treatment sensitivities, and cuproptosis scores were evaluated between the different subgroups. Results: Seven cuproptosis-related genes showed aberrant expression levels and genetic alterations in the PDAC tumor microenvironment. Among them, LIPT1, LIAS, DLAT, PDHA1, and DLD were significantly correlated with overall survival. Based on the expression profiles of the seven cuproptosis-related genes, three cuproptosis clusters (Clusters A, B, and C) were identified, which were represented by different clinicopathologic features, gene expression levels, and biological processes. A total of 686 DEGs were identified among the three cuproptosis clusters, of which 35 prognosis-related DEGs were selected to further classify the PDAC samples into two subgroups with different survival rates, clinicopathologic features, immune infiltration levels, and drug sensitivities. Higher cuproptosis scores were associated with a significantly poorer prognosis. Conclusion: The cuproptosis subtypes, scores, and relevant genes represent valuable information for assessing the heterogeneity, treatment, and prognosis of PDAC

Expression Profiles of Cuproptosis-Related Genes Determine Distinct Subtypes of Pancreatic Ductal Adenocarcinoma

Background: Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent subtype of pancreatic cancer and one of the most malignant tumors worldwide. Due to the heterogeneity of its genomics and proteomics, the prognosis of PDAC remains disappointing despite advances in surgery and medicines. Recently, a novel form of programmed cell death, cuproptosis, was proposed, although its role in PDAC has not been investigated. This study aimed to quantify the expression of cuproptosis-related genes and characterize the novel subtypes of PDAC. Methods: To evaluate the pattern of cuproptosis in PDAC, the gene expression data and clinical information of 372 samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A consensus cluster analysis was performed using the transcriptional levels, genetic alterations, and individual prognostic values of seven pre-selected cuproptosis-related genes (DLAT, LIPT1, FDX1, DLD, PDHB, PDHA1, and LIAS) to identify the novel subtypes associated with cuproptosis in PDAC. A univariate Cox regression analysis was used to determine the significant prognostic indicators and cuproptosis scores among the differentially expressed genes (DEGs) between the dividing subclusters, followed by a principal component analysis. The prognostic values, immune profiles, treatment sensitivities, and cuproptosis scores were evaluated between the different subgroups. Results: Seven cuproptosis-related genes showed aberrant expression levels and genetic alterations in the PDAC tumor microenvironment. Among them, LIPT1, LIAS, DLAT, PDHA1, and DLD were significantly correlated with overall survival. Based on the expression profiles of the seven cuproptosis-related genes, three cuproptosis clusters (Clusters A, B, and C) were identified, which were represented by different clinicopathologic features, gene expression levels, and biological processes. A total of 686 DEGs were identified among the three cuproptosis clusters, of which 35 prognosis-related DEGs were selected to further classify the PDAC samples into two subgroups with different survival rates, clinicopathologic features, immune infiltration levels, and drug sensitivities. Higher cuproptosis scores were associated with a significantly poorer prognosis. Conclusion: The cuproptosis subtypes, scores, and relevant genes represent valuable information for assessing the heterogeneity, treatment, and prognosis of PDAC