KDGene: knowledge graph completion for disease gene prediction using interactional tensor decomposition.

The accurate identification of disease-associated genes is crucial for understanding the molecular mechanisms underlying various diseases. Most current methods focus on constructing biological networks and utilizing machine learning, particularly deep learning, to identify disease genes. However, these methods overlook complex relations among entities in biological knowledge graphs. Such information has been successfully applied in other areas of life science research, demonstrating their effectiveness. Knowledge graph embedding methods can learn the semantic information of different relations within the knowledge graphs. Nonetheless, the performance of existing representation learning techniques, when applied to domain-specific biological data, remains suboptimal. To solve these problems, we construct a biological knowledge graph centered on diseases and genes, and develop an end-to-end knowledge graph completion framework for disease gene prediction using interactional tensor decomposition named KDGene. KDGene incorporates an interaction module that bridges entity and relation embeddings within tensor decomposition, aiming to improve the representation of semantically similar concepts in specific domains and enhance the ability to accurately predict disease genes. Experimental results show that KDGene significantly outperforms state-of-the-art algorithms, whether existing disease gene prediction methods or knowledge graph embedding methods for general domains. Moreover, the comprehensive biological analysis of the predicted results further validates KDGene's capability to accurately identify new candidate genes. This work proposes a scalable knowledge graph completion framework to identify disease candidate genes, from which the results are promising to provide valuable references for further wet experiments. Data and source codes are available at https://github.com/2020MEAI/KDGene.

Pan-Cancer Analysis of the LOX Family Reveals that LOX Affects Tumor Prognosis by Affecting Immune Infiltration.

The lysyl oxidase (LOX) gene family encodes for a group of copper-dependent enzymes that play a crucial role in the cross-linking of collagen and elastin fibers in the extracellular matrix (ECM). Dysregulation of LOX gene expression has been implicated in various pathological conditions, including cancer. Several studies have shown that the LOX gene family is involved in cancer progression and metastasis. The goal of this article is to conduct a comprehensive analysis of the LOX family's role in pan-cancer multiplexes. We utilized pan-cancer multi-omics sequencing data from TCGA to investigate the relationship between LOX family genes and tumors at four different levels: mutation, copy number variation, methylation, and gene expression. In addition, we also examined the relationship between LOX family genes and tumors at the cell line level using tumor cell line sequencing data from CCLE. Taking into account the impact of LOX family genes on lung cancer, we developed a LOX family lung cancer prognostic model to forecast the disease's prognosis. Our findings revealed that LOXL2 had the highest mutation frequency in tumors, while all four LOX family genes experienced some degree of copy number variation in diverse tumors. We observed that LOX, LOXL1 to LOXL3 were predominantly highly expressed in tumors including LUAD. The expression trends of LOX and LOXL1 to LOXL3 were consistent across tumor cell lines, but differed somewhat from LOXL4. Utilizing 25 LOX family-related genes, we constructed a LOX family prognostic model that performed well in predicting the prognosis of lung cancer. Through pan-cancer analysis, we gain further knowledge of the role of LOX family genes in different tumors, offering a novel pathway for future research into the relationship between LOX family genes and tumors.

The role of desmoglein-2 in kidney disease.

Desmosomes are multi-protein cell-cell adhesion structures supporting cell stability and mechanical stress resilience of tissues, best described in skin and heart. The kidney is exposed to various mechanical stimuli and stress, yet little is known about kidney desmosomes. In healthy kidneys, we found desmosomal proteins located at the apical-junctional complex in tubular epithelial cells. In four different animal models and patient biopsies with various kidney diseases, desmosomal components were significantly upregulated and partly miss-localized outside of the apical-junctional complexes along the whole lateral tubular epithelial cell membrane. The most upregulated component was desmoglein-2 (Dsg2). Mice with constitutive tubular epithelial cell-specific deletion of Dsg2 developed normally, and other desmosomal components were not altered in these mice. When challenged with different types of tubular epithelial cell injury (unilateral ureteral obstruction, ischemia-reperfusion, and 2,8-dihydroxyadenine crystal nephropathy), we found increased tubular epithelial cell apoptosis, proliferation, tubular atrophy, and inflammation compared to wild-type mice in all models and time points. In vitro, silencing DSG2 via siRNA weakened cell-cell adhesion in HK-2 cells and increased cell death. Thus, our data show a prominent upregulation of desmosomal components in tubular cells across species and diseases and suggest a protective role of Dsg2 against various injurious stimuli.

Rubisco Accumulation Factor1-like (RAFL) interacts with RAF1 to mediate Rubisco assembly in Arabidopsis.

Rubisco catalysis a rate-limiting step in photosynthesis. It is a complex of eight large (RbcL) and eight small (RbcS) subunits. The biogenesis of Rubisco requires assembly chaperones. One of the key Rubisco assembly chaperones, Rubisco accumulation factor1 (RAF1), assembled as a dimer, acts downstream of chaperonin-assisted RbcL folding by stabilizing RbcL antiparallel dimers for assembly into RbcL8 complexes. In maize, lacking RAF1 causes Rubisco deficient and seedling lethal. A RAF1 homologue, RAF1-like (RAFL), has been detected in Arabidopsis. We found RAFL shares 61.98 % sequence similarity with RAF1. They have similar conserved domains, predicted 3D structures and gene expression pattern. Phylogenetic tree analysis showed that RAFL and RAF1 only present in analyzed dicots, while only one copy of RAF presented in monocots, mosses and green algae. Combined analysis by three different protein-protein interaction methods showed that RAFL interacts with RAF1 both in vivo and in vitro. Taken together, we conclude that RAFL and RAF1 are close paralogous genes, and they can form heterodimer and/or homodimers to mediate Rubisco assembly in Arabidopsis.

Construction of an Ohmic Contact Cathode by Two Metal Sulfides for efficient Capture and Catalysis of Polysulfide.

The slow reaction kinetics and severe shuttle effect of lithium polysulfide make Li-S battery electrochemical performance difficult to meet the demands of large electronic devices such as electric vehicles. Based on this, an electrocatalyst constructed by metal phase material (MoS2) and semiconductor phase material (SnS2) with ohmic contact is designed for inhibiting the dissolution of lithium polysulfide with improving the reaction kinetics. According to the density-functional theory calculations, it is found that the heterostructured samples with ohmic contacts can effectively reduce the reaction-free energy of lithium polysulfide to accelerate the sulfur redox reaction, in addition to the excellent electron conduction to reduce the overall activation energy. The metallic sulfide can add more sulfophilic sites to promote the capture of polysulfide. Thanks to the ohmic contact design, the carbon nanotube-MoS2-SnS2 achieved a specific capacity of 1437.2 mAh g-1 at 0.1 C current density and 805.5 mAh g-1 after 500 cycles at 1 C current density and is also tested as a pouch cell, which proves to be valuable for practical applications. This work provides a new idea for designing an advanced and efficient polysulfide catalyst based on ohmic contact.

Regulate the Solvation Structure and Interface by Nitrate in Phosphate-Based Electrolytes for 4.5 V-Class Ni-Rich Batteries.

Phosphate-based electrolyte propels the advanced battery system with high safety. Unfortunately, restricted by poor electrochemical stability, it is difficult to be compatible with advanced lithium metal anodes and Ni-rich cathodes. To alleviate these issues, the study has developed a phosphate-based localized high-concentration electrolyte with a nitrate-driven solvation structure, and the nitrate-derived N-rich inorganic interface shows excellent performance in stabilizing the LiNi0.8Co0.1Mn0.1O2 (NCM811) cathode interface and modulating the lithium deposition morphology on the anode. The results show that the Li|| NCM811 cell has exceptional long-cycle stability of >80% capacity retention after 800 cycles at 4.3 V, 1 C. A more prominent capacity retention rate of 93.3% after 200 cycles can be reached with the high voltage of 4.5 V. While being compatible with the phosphate-based electrolyte with good flame retardancy and the good electrochemical stability of Ni-rich lithium metal battery (LMBs) systems, the present work expands the construction of anion-rich solvation structures, which is expected to promote the development of the high-performance LMBs with safety.

Localized High-Concentration Sulfone Electrolytes with High-Voltage Stability and Flame Retardancy for Ni-Rich Lithium Metal Batteries.

The localized high-concentration electrolyte (LHCE) propels the advanced high-voltage battery system. Sulfone-based LHCE is a transformative direction compatible with high energy density and high safety. In this work, the application of lithium bis(trifluoromethanesulphonyl)imide and lithium bis(fluorosulfonyl)imide (LiFSI) in the LHCE system constructed from sulfolane and 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (TTE) is investigated. The addition of diluent causes an increase of contact ion pairs and ionic aggregates in the solvation cluster and an acceptable quantity of free solvent molecules. A small amount of LiFSI as an additive can synergistically decompose with TTE on the cathode and participate in the construction of both electrode interfaces. The designed electrolyte helps the Ni-rich system to cycle firmly at a high voltage of 4.5 V. Even with high mass load and lean electrolyte, it can keep a reversible specific capacity of 91.5% after 50 cycles. The constructed sulfone-based electrolyte system exhibits excellent thermal stability far beyond the commercial electrolytes. Further exploration of in-situ gelation has led to a quick conversion of the designed liquid electrolyte to the gel state, accompanied by preserved stability, which provides a direction for the synergistic development of LHCE with gel electrolytes.

Fano resonance in molecular junctions of spin crossover complexes.

In this paper, we introduce a novel molecular switch paradigm that integrates spin crossover complexes with the Fano resonance effect. Specifically, by performing density-functional theory calculations, the feasibility of achieving Fano resonance using spin crossover complexes is demonstrated in our designed molecular junctions using the complex {Fe[H2B(pz)2]2[Bp(bipy)]} [pz = 1-pyrazolyl, Bp(bipy) = bis(phenylethynyl)(2,2'-bipyridine)]. It is further revealed that the Fano resonance, particularly the Fano dip, is most prominent in the junction with cobalt tips among all the schemes, together with the spin-filtering effect. Most importantly, this junction of cobalt tips is able to exhibit three distinct conductance states, which are controlled by the modulation of Fano resonance due to the spin-state transition of the complex and the applied gate voltage. Such a molecular switch paradigm holds potential for applications in logic gates, memory units, sensors, thermoelectrics, and beyond.

The Role of Platelet-Derived Growth Factor in Focal Segmental Glomerulosclerosis.

BACKGROUND: FSGS is the final common pathway to nephron loss in most forms of severe or progressive glomerular injury. Although podocyte injury initiates FSGS, parietal epithelial cells (PECs) are the main effectors. Because PDGF takes part in fibrotic processes, we hypothesized that the ligand PDGF-B and its receptor PDGFR- ß participate in the origin and progression of FSGS. METHODS: We challenged Thy1.1 transgenic mice, which express Thy1.1 in the podocytes, with anti-Thy1.1 antibody to study the progression of FSGS. We investigated the role of PDGF in FSGS using challenged Thy1.1 mice, 5/6 nephrectomized mice, Col4 -/- (Alport) mice, patient kidney biopsies, and primary murine PECs, and challenged Thy1.1 mice treated with neutralizing anti-PDGF-B antibody therapy. RESULTS: The unchallenged Thy1.1 mice developed only mild spontaneous FSGS, whereas challenged mice developed progressive FSGS accompanied by a decline in kidney function. PEC activation, proliferation, and profibrotic phenotypic switch drove the FSGS. During disease, PDGF-B was upregulated in podocytes, whereas PDGFR- ß was upregulated in PECs from both mice and patients with FSGS. Short- and long-term treatment with PDGF-B neutralizing antibody improved kidney function and reduced FSGS, PEC proliferation, and profibrotic activation. In vitro , stimulation of primary murine PECs with PDGF-B recapitulated in vivo findings with PEC activation and proliferation, which was inhibited by PDGF-B antibody or imatinib. CONCLUSION: PDGF-B-PDGFR- ß molecular crosstalk between podocytes and PECs drives glomerulosclerosis and the progression of FSGS. PODCAST: This article contains a podcast at.

Digital identification of Aucklandiae radix, Vladimiriae radix, and Inulae radix based on multivariate algorithms and UHPLC-QTOF-MS analysis.

INTRODUCTION: The identification of Aucklandiae Radix (AR), Vladimiriae Radix (VR), and Inulae Radix (IR) based on traits and microscopic features is susceptible to the state of samples and the subjective awareness of personnel, and the identification based on a few or single chemical compositions is a cumbersome and time-consuming procedure and fails to rationally and effectively utilize the information of unknown components and is not specificity enough. OBJECTIVES: This study aimed to improve the identification efficiency, strengthen supervision, and realize digital identification of three Chinese medicines. Ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) combined with multivariate algorithms was used to explore the digital identification of AR, VR, and IR. MATERIALS AND METHODS: UHPLC-QTOF-MS was used to analyze AR, VR, and IR. The MS data combined with multivariate algorithms such as partial least squares discrimination analysis (PLS-DA) and artificial neural networks (ANNs) was used to filter important variables and data modeling. Finally, the optimal model was selected for the digital identification of three herbs. RESULTS: The results showed that three herbs can be distinguished on the whole level, and through feature screening, 591 characteristic variables combined with multivariate algorithms to construct data models. The ANN model was the best with accuracy = 0.983, precision = 0.984, and external verification showed the reliability and practicability of ANN model. CONCLUSION: ANN model combined with MS data is of great significance for tdigital identification of AR, VR, and IR. It is an important reference for developing the digital identification of traditional Chinese medicines at the individual level based on UHPLC-QTOF-MS and multivariate algorithms.