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The dynamic response description of materials in high-speed impact fields is of practical significance to structural design and practical engineering application. In this paper, an electromagnetic impact (EI) loading process was proposed to acquire dynamic stress-strain relationships of 2A10 aluminum alloys. A modified Johnson-Cook (J-C) material model was obtained by combining with Quasi-static experiments and verified by numerical simulations. Comparing the J-C model obtained by a Split Hopkinson pressure bar, the simulative results about maximum deformation displacements showed the modified J-C model was more in line with actual experimental results. The accuracy under the discharge energy of 4 and 5 kJ was improved by 50% and 11%, respectively. In addition, electromagnetic impact loading characteristics and microstructure evolution of materials were studied. The discharge current with an attenuated sine wave caused that electromagnetic impact forces demonstrated a bimodal trend. The maximum impact velocities reached up to 4.7 m/s and 6.7 m/s under the discharge energy of 4 and 5 kJ, respectively (the maximum strain rates are 655.0 and 932.3 s−1, respectively). The high-speed impact effect led to the emergence of adiabatic shear bands (ASBs) during deformation microstructure evolution. Due to higher impact speed, the deformation concentration degree was more remarkable under the energy of 5 kJ. [ABSTRACT FROM AUTHOR]

Associations between gut microbiota and colorectal cancer (CRC) have been widely investigated. However, the replicable markers for early-stage adenoma diagnosis across multiple populations remain elusive. Here, we perform an integrated analysis on 1056 public fecal samples, to identify adenoma-associated microbial markers for early detection of CRC. After adjusting for potential confounders, Random Forest classifiers are constructed with 11 markers to discriminate adenoma from control (area under the ROC curve (AUC) = 0.80), and 26 markers to discriminate adenoma from CRC (AUC = 0.89), respectively. Moreover, we validate the classifiers in two independent cohorts achieving AUCs of 0.78 and 0.84, respectively. Functional analysis reveals that the altered microbiome is characterized with increased ADP-l-glycero-beta-d-manno-heptose biosynthesis in adenoma and elevated menaquinone-10 biosynthesis in CRC. These findings are validated in a newly-collected cohort of 43 samples using quantitative real-time PCR. This work proves the validity of adenoma-specific markers across multi-populations, which would contribute to the early diagnosis and treatment of CRC. The gut microbiome plays an important role in colorectal carcinogenesis and predictive microbiome signatures have been proposed for colorectal cancer (CRC) diagnosis. Here the authors perform a meta-analysis of 16S rRNA-based profiles to identify microbial markers able to discriminate patients with adenoma from control and CRC, building a model that can be applied for the early detection of CRC. [ABSTRACT FROM AUTHOR]

The early history of life harbours many unresolved evolutionary questions, none more important than the genomic origin and cellular evolution of eukaryotes. An issue central to eukaryote origin concerns the position of eukaryotes in the tree of life and the relationship of the host lineage that acquired the mitochondrion some two billion years ago to lineages of modern-day archaea. Recent analyses indicate that the host lineage branches within the Archaea, prompting the search for novel archaeal lineages that can improve our understanding of the cellular evolution of eukaryotes. Here we give a brief review of the studies on Archaea, the tree of life and the cellular evolution of eukaryotes, which is followed by an overview of recent progress fueled by new genomic technologies and recent status of archaeal research in China. Future directions for the study of early evolution are considered. [ABSTRACT FROM AUTHOR]

Motivation: Protein-binding sites prediction lays a foundation for functional annotation of protein and structure-based drug design. As the number of available protein structures increases, structural alignment based algorithm becomes the dominant approach for protein-binding sites prediction. However, the present algorithms underutilize the ever increasing numbers of three-dimensional protein-ligand complex structures (bound protein), and it could be improved on the process of alignment, selection of templates and clustering of template. Herein, we built so far the largest database of bound templates with stringent quality control. And on this basis, bSiteFinder as a protein-binding sites prediction server was developed. Results: By introducing Homology Indexing, Chain Length Indexing, Stability of Complex and Optimized Multiple-Templates Clustering into our algorithm, the efficiency of our server has been significantly improved. Further, the accuracy was approximately 2-10 % higher than that of other algorithms for the test with either bound dataset or unbound dataset. For 210 bound dataset, bSiteFinder achieved high accuracies up to 94.8 % (MCC 0.95). For another 48 bound/unbound dataset, bSiteFinder achieved high accuracies up to 93.8 % for bound proteins (MCC 0.95) and 85.4 % for unbound proteins (MCC 0.72). Our bSiteFinder server is freely available at , and the source code is provided at the methods page. Conclusion: An online bSiteFinder server is freely available at . Our work lays a foundation for functional annotation of protein and structure-based drug design. With ever increasing numbers of three-dimensional protein-ligand complex structures, our server should be more accurate and less time-consuming.[Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Recently, the study of microRNA expression profile has shown that miR-224 was implicated in neuron injury, but the mechanism of miR-224 on regulating neuronal apoptosis is completely unclear until now. Therefore, the current study aims to illuminate the miR-224 and its target gene on the modulation of neuronal cell apoptosis induced by ischemic injury. In this study, we used oxygen/glucose deprivation (OGD)-induced human-derived HCN-2 cells to establish the model of cerebral ischemia injury. We found that miR-224 was upregulated in injured cells (human brain cortical neuron). Using bioinformatics analyses, we found that miR-224 targeted the 3′UTR of spastic paraplegia 7 (SPG7) and the miR-224 inhibitor promoted expression of SPG7 and promoter activity of SPG7 3′UTR. In addition, we further found that miR-224 inhibitor enhanced interaction SPG7 with mitochondrial voltage-dependent anion channel (VDAC1) detected by co-immunoprecipitation in injured cells. The knockdown of SPG7 reduced mitochondrial membrane potential and caused higher mitochondrial calcium retention in injured cells. Knockdown of SPG7 inhibits expression of nicotinic acetylcholine receptor. Besides, the miR-224 inhibitor reduced neuronal cell apoptosis was increased by knockdown of either SPG7 or VDAC1. Overall, miR-224 inhibitor may prevent neuronal cell apoptosis by targeting SPG7 3′UTR and promote interaction SPG7 with VDAC1 after cerebral ischemia. Downregulation of SPG7 induces VDAC1 to form mitochondria permeability transition pore probably by inhibiting expression of nicotinic acetylcholine receptor, resulting in mitochondrial membrane depolarization and higher mitochondrial calcium retention. [ABSTRACT FROM AUTHOR]

Nuclear receptors (NR) are a class of proteins that are responsible for sensing steroid and thyroid hormones and certain other molecules. In that case, NR have the ability to regulate the expression of specific genes and associated with various diseases, which make it essential drug targets. Approaches which can predict the inhibition ability of compounds for different NR target should be particularly helpful for drug development. In this study, proteochemometric modelling was introduced to analysis the bioactivity between chemical compounds and NR targets. Results illustrated the ability of our PCM model for high-throughput NR-inhibitor screening after evaluated on both internal (AUC > 0.870) and external (AUC > 0.746) validation set. Moreover, in-silico predicted bioactive compounds were clustered according to structure similarity and a series of representative molecular scaffolds can be derived for five major NR targets. Through scaffolds analysis, those essential bioactive scaffolds of different NR target can be detected and compared. Generally, the methods and molecular scaffolds proposed in this article can not only help the screening of potential therapeutic NR-inhibitors but also able to guide the future NR-related drug discovery. [ABSTRACT FROM AUTHOR]