A novel prognostic 7-methylguanosine signature reflects immune microenvironment and alternative splicing in glioma based on multi-omics analysis

Glioma is the most common type of central nervous system tumor with increasing incidence. 7-methylguanosine (m7G) is one of the diverse RNA modifications that is known to regulate RNA metabolism and its dysregulation was associated with various cancers. However, the expression pattern of m7G regulators and their roles in regulating tumor immune microenvironments (TIMEs) as well as alternative splicing events (ASEs) in glioma has not been reported. In this study, we showed that m7G regulators displayed a close correlation with each other and most of them were differentially expressed between normal and glioma tissues. Two m7G signatures were then constructed to predict the overall survival of both GBM and LGG patients with moderate predictive performance. The risk score calculated from the regression coefficient and expression level of signature genes was proved to be an independent prognostic factor for patients with LGG, thus, a nomogram was established on the risk score and other independent clinical parameters to predict the survival probability of LGG patients. We also investigated the correlation of m7G signatures with TIMEs in terms of immune scores, expression levels of HLA and immune checkpoint genes, immune cell composition, and immune-related functions. While exploring the correlation between signature genes and the ASEs in glioma, we found that EIF4E1B was a key regulator and might play dual roles depending on glioma grade. By incorporating spatial transcriptomic data, we found a cluster of cells featured by high expression of PTN exhibited the highest m7G score and may communicate with adjacent cancer cells via SPP1 and PTN signaling pathways. In conclusion, our work brought novel insights into the roles of m7G modification in TIMEs and ASEs in glioma, suggesting that evaluation of m7G in glioma could predict prognosis. Moreover, our data suggested that blocking SPP1 and PTN pathways might be a strategy for combating glioma

Effect of heat input on nanomechanical properties of wire-arc additive manufactured Al 4047 alloys

Heat input is one of the most important process parameters during additive manufacturing (AM). It is of great significance to understand the effect of heat input on the microstructure and nanomechanical properties, as well as the underlying mechanisms. Wire-arc additive manufactured (WAAM-ed) Al 4047 alloys under different heat inputs were produced and studied in this work. The as-manufactured Al alloys showed hypoeutectic microstructure that consisted of primary Al (α-Al) dendrite and ultrafine Al–Si eutectic. The effect of heat input on hardness and strain rate sensitivity (SRS) were investigated through nanoindentation. The nanohardness decreased with the increasing heat input, in accordance with the trend of yield strength and microhardness in the previous studies, in which the mechanism was usually explained by the grain growth model and Hall-Petch relationship. This work suggests a distinct mechanism regarding the effect of heat input on nanohardness, which is the enhanced solid solution strengthening produced by lower heat input. In addition, the heat input had little effect on the SRS and activation volume. It is hoped that this study leads to new insights into the understanding of the relation between heat input and nanomechanical properties, and further benefits to improve the targeted mechanical properties and engineering applications of the AM-ed materials.publishedVersio

Peak Force Visible Microscopy for Determination of Exciton Diffusion Length in Organic Photovoltaic Blends

In this article, we developed a new nano spectroscopic technique, peak force visible (PF-vis) microscopy, which is based on the peak force tapping mode in an atomic force microscope to both visualize nanoscale morphology and estimate exciton diffusion lengths of donor domains in organic photovoltaic blends. Nano phase-separations in P3HT:PCBM and TFB:PCBM blend films were clearly revealed by PF-vis microscopy with a high spatial resolution less than 10 nm. A model that correlates PF-vis signal and the exciton diffusion length was also developed to estimate the diffusion lengths of P3HT and TFB to be 2.9±0.3 and 9.0±1.5 nm, respectively. PF-vis microscopy is expected to assist the evaluation of OPV materials, therefore accelerating the pace of innovation of OPVs

Tissue- and stage-specific expression of a fatty acid binding protein-like gene from amphioxus Branchiostoma belcheri

A cDNA clone encoding an amphioxus fatty acid binding protein-like (AmphiFABPL) protein was isolated from a gut cDNA library of Branchiostoma belcheri. It contained a 423 bp open reading frame corresponding to a deduced protein of 140 amino acids with a predicted molecular mass of approximately 15.9 kDa. Phylogenetic analysis showed that AmphiFABPL fell outside the vertebrate clade of fatty acid binding proteins (FABPs), being positioned at the base of the chordate lineage, and was almost equally homologous to various vertebrate FABPs, suggesting that it may be the archetype of vertebrate FABPs. Both northern blotting and in situ hybridization analyses demonstrated that AmphiFABPL was expressed in the hepatic caecum and hind-gut, and although at a much lower level, it was also present in the endostyle, ovary and testis. In addition, whole-mount in situ hybridization revealed that AmphiFABPL was initially expressed in the posterior two thirds of the primitive gut, including the mid-gut where the hepatic caecum will form later, in 2-day larvae. The expression pattern is closely similar to that of the L-FABP and I-FABP genes in vertebrates, supporting the hypothesis that the hepatic caecum in the amphioxus is homologous to the vertebrate liver

KG2Vec: A node2vec-based vectorization model for knowledge graph.

Since the word2vec model was proposed, many researchers have vectorized the data in the research field based on it. In the field of social network, the Node2Vec model improved on the basis of word2vec can vectorize nodes and edges in social networks, so as to carry out relevant research on social networks, such as link prediction, and community division. However, social network is a network with homogeneous structure. When dealing with heterogeneous networks such as knowledge graph, Node2Vec will lead to inaccurate prediction and unreasonable vector quantization data. Specifically, in the Node2Vec model, the walk strategy for homogeneous networks is not suitable for heterogeneous networks, because the latter has distinguishing features for nodes and edges. In this paper, a Heterogeneous Network vector representation method is proposed based on random walks and Node2Vec, called KG2vec (Heterogeneous Network to Vector) that solves problems related to the inadequate consideration of the full-text semantics and the contextual relations that are encountered by the traditional vector representation of the knowledge graph. First, the knowledge graph is reconstructed and a new random walk strategy is applied. Then, two training models and optimizing strategies are proposed, so that the contextual environment between entities and relations is obtained, semantically providing a full vector representation of the Heterogeneous Network. The experimental results show that the KG2VEC model solves the problem of insufficient context consideration and unsatisfactory results of one-to-many relationship in the vectorization process of the traditional knowledge graph. Our experiments show that KG2vec achieves better performance with higher accuracy than traditional methods

Mutation analysis of 21 autosomal short tandem repeats in Han population from Hunan, China

Background: Short tandem repeats (STRs) are powerful genetic markers widely used in human genetics. Population data and locus-specific mutation rates of STRs are crucial for the evaluation and interpretation of genetic evidence in forensic and population genetics. Aim: To investigate the mutation rates of 21 autosomal STRs in a population from central south China. Subjects and methods: This study analysed 3420 paternity cases with a Combined Paternity Index >10,000 from Han population in Hunan. A total of 68,743 meiotic transfers were analysed and 62 mutations were identified. Results: The overall mutation rate of STR loci was 0.9 × 10−3 (95% CI, 0.0007–0.0011) and the locus-specific mutation rates were estimated ranging from 0.0000–0.0023. Locus D1S1656 exhibited the highest mutation rate of 2.3 × 10−3 (95% CI, 0.0005–0.0006), followed by D12S391 with a mutation rate of 2.0 × 10−3 (95% CI, 0.0007–0.0044). No mutation was observed at TPOX, D2S1338 or Penta D. One-step mutation cases accounted for 96.77% of total mutations and the ratio of paternal vs maternal mutations was ∼4.85:1. Inter-population comparisons of locus-specific mutation rates of several STRs revealed significant differences between Han in Hunan and Han in other regions of China. Conclusion: The data justified the use of geographical data in further genetic applications

Nanomechanical Characteristics of Trapped Oil Droplets with Nanoparticles: A Molecular Dynamics Simulation

Nanoparticles (NPs) possess great potentials in applications to enhanced oil recovery (EOR), the underlying mechanisms of which however remain to be explored. In this study, the motion of NPs and the local pressure distribution in a trapped oil droplet/nanofluid system in confined nanochannels are scrutinized by molecular dynamic simulations. Depending on the particle wettability, three different motion patterns have been observed: hydrophilic NPs are more likely to be adsorbed on the solid surface of the channel and stay close to the three-phase contact areas, hydrophobic NPs tend to move inside the oil droplet as clusters, and NPs with mixed hydrophobicity are prone to be trapped at the oil-water interface. It is shown that the existence of NPs introduces high local pressure in the nanochannels, especially at locations where NPs aggregate. Significantly, in the three-phase contact area for hydrophilic NPs, the local pressure distribution features the postulated structural disjoining pressure reported in the literature. For the first time, our molecular dynamics simulation results elucidate nanoparticle-induced structural disjoining pressure at the atomistic scale. The results thus provide a better understanding on the fundamentals of nanofluids in confined channels and serve as guidelines for the design of NPs for EOR applications

A framework for predicting the local stress-strain behaviors of additively manufactured multiphase alloys in the sequential layers

The additive manufacturing (AM) process often results in non-uniform microstructure and different mechanical properties in sequential layers, impacting the overall performance of the AM-ed component. However, it is extremely challenging to evaluate the local stress-strain behavior of each individual layer, owing to the limited size of the AM-ed layered structure. To this end, a framework for characterizing and predicting the mechanical evolution of AM-ed multiphase alloys by combing nanoindentation and microstructure-based finite element method (FEM) was proposed. The sample used in this study was superduplex stainless steel (SDSS) manufactured by wire arc additive manufacturing (WAAM), and the microstructure varied from layer to layer. Firstly, the mechanical properties of the two constituent phases in each layer, including elastic modulus and hardness, were obtained by nanoindentation, and the indentation size effect (ISE) was also evaluated. The yield strength and hardening exponent of each phase were subsequently estimated by reverse analysis method, and therefore the constitutive behaviors of the individual phase, which served as input parameters for FEM, were acquired. By aid of real microstructure-based FEM under uniaxial tension, the overall stress-strain behaviors of each layer and the distributions of the stress and strain during the deformation process were investigated. This work provides a new avenue for the characterization of the multiphase alloys in AM industry, beneficial to the understanding of the mechanical evolution in AM-ed materials