Clustering and Differentiation of glr-3 Gene Function and Its Homologous Proteins

In order to adapt to the low temperature environment, organisms transmitexcitement to the central system through the thermal sensing system, whichis a classic reflex reaction. The cold receptor GLR-3 perceives cold and produces cold avoidance behavior through peripheral sensory neurons ASER.In order to further understand the gene encoding of the cold sensing glr-3gene and the evolution of its homologous gene group function and proteinfunction, the nucleotide sequence and amino acid sequence of the glr-3gene and its homologous gene in 24 species were obtained and compared.By clustering with the GRIK2 gene sequence of Rana chensinensis, the bioinformatics method was used to predict and sequence analyze the change ofgene, evolution rate, physical and chemical properties of protein, glycosylation sites, phosphorylation sites, secondary structure and tertiary structureof protein. The analysis results show that the glr-3 gene and its homologousgene have obvious positive selection effect. The protein prediction analysisshowed that the glr-3 gene and its homologous genes encoded proteinsin these 25 species were hydrophilic proteins, and the proportion of sidechains of aliphatic amino acids was high. The transmembrane helix waswidespread and there were more N-glycosylation sites and O-glycosylationsites. The protein phosphorylation sites encoded were serine, threonine andtyrosine phosphorylation sites. Secondary structure prediction showed thatthe secondary structure units of the encoded protein were α-helix, β-turn,random coil and extended chain, and the proportion of α-helix was the largest. This study provides useful information on the evolution and function ofthe cold sensing gene glr-3 and its homologous genes

Optimal Routing for Safe Construction and Demolition Waste Transportation: A CVaR Criterion and Big Data Analytics Approach

Rapid urbanisation worldwide, especially in developing countries and areas, has led to the generation of large amounts of construction and demolition waste (C&DW). The resultant transportation demands pose severe threats to safe transportation and secure city operation. By considering the low-probability–high-consequence nature of C&DW traffic accidents and the effectiveness of route optimisation in transportation risk control, a risk-averse project was implemented. Furthermore, an optimal routing model based on the conditional value at risk (CVaR) criterion is proposed. The model considered various risk-averse attitudes of decision-makers. For practicality and for strongly supporting policy-making, big data technology, including the construction of multistructure databases and in-depth analysis, was applied to achieve the proposed CVaR routing model. Therefore, the present study extended the CVaR method to optimal routing design in the field of safe urban C&DW transportation and integrated the optimal model with big data technology

Study on the mixing performance of static mixers in selective catalytic reduction (SCR) systems

Selective catalytic reduction (SCR) is a promising technique for reducing nitrogen oxide (NOx) emissions from diesel engines. Static mixers are widely used in SCR systems before reactors to promote the mixing of ammonia and exhaust streams. This work aims to investigate the effects of the location of static mixers and the volume ratio of two species on mixing quality using the computational fluid dynamics (CFD) method. The simulation results show that a more homogenous ammonia distribution can be achieved at the exit of the pipe if static mixers are placed close to the ammonia injection point or if more ammonia is injected. Another phenomenon found in the study is that the mixing performance of an identical static mixer may behave discrepantly under different flow conditions if using B and C as the evaluating indexes for mixing homogenization

Effects of density dependence in a temperate forest in northeastern China

CITATION: Yao, J., et al. 2016. Effects of density dependence in a temperate forest in northeastern China. Scientific Reports 6:32844, doi:10.1038/srep32844.The original publication is available at http://www.nature.com/srepENGLISH ABSTRACT: Negative density dependence may cause reduced clustering among individuals of the same species, and evidence is accumulating that conspecific density-dependent self-thinning is an important mechanism regulating the spatial structure of plant populations. This study evaluates that specific density dependence in three very large observational studies representing three successional stages in a temperate forest in northeastern China. The methods include standard spatial point pattern analysis and a heterogeneous Poisson process as the null model to eliminate the effects of habitat heterogeneity. The results show that most of the species exhibit conspecific density-dependent self-thinning. In the early successional stage 11 of the 16 species, in the intermediate successional stage 18 of the 21 species and in the old growth stage all 21 species exhibited density dependence after removing the effects of habitat heterogeneity. The prevalence of density dependence thus varies among the three successional stages and exhibits an increase with increasing successional stage. The proportion of species showing density dependence varied depending on whether habitat heterogeneity was removed or not. Furthermore, the strength of density dependence is closely related with species abundance. Abundant species with high conspecific aggregation tend to exhibit greater density dependence than rare species.https://www.nature.com/articles/srep32844Publisher's versio

Numerical Simulation on the Gas Explosion Propagation Related to Roadway

AbstractBased on the combustion, explosions and air dynamics and related theory etc, this paper describes the mathematical model of gas explosion in detail, combined with the gas explosion transmission mechanism, make a research on two wave-three area structure of gas explosion and the energy change rule of the array face of precursor wave and the array face of flame wave, with the fluid dynamics analysis Fluent software, this paper makes a numerical simulation and analysis on the overpressure transmission rule when gas explosion takes place in different types roadways. The results of the study show that: Fluent software can be used to accurately simulate gas explosion condition, when explosion wave spreads in the roadway turns, the bigger of the overpressure value in corner, the stronger of the destructive power; when tunnel has bifurcation, the overpressure will release in bifurcation, but explosions wave with flame wave will produce more powerful destruction effect. The research results can be used as a certain reference for how to prevent and control the gas explosion, and how to reduce the power of the gas explosion etc

Somatic mutation of the cohesin complex subunit confers therapeutic vulnerabilities in cancer

A synthetic lethality-based strategy has been developed to identify therapeutic targets in cancer harboring tumor-suppressor gene mutations, as exemplified by the effectiveness of poly ADP-ribose polymerase (PARP) inhibitors in BRCA1/2-mutated tumors. However, many synthetic lethal interactors are less reliable due to the fact that such genes usually do not perform fundamental or indispensable functions in the cell. Here, we developed an approach to identifying the "essential lethality" arising from these mutated/deleted essential genes, which are largely tolerated in cancer cells due to genetic redundancy. We uncovered the cohesion subunit SA1 as a putative synthetic-essential target in cancers carrying inactivating mutations of its paralog, SA2. In SA2-deficient Ewing sarcoma and bladder cancer, further depletion of SA1 profoundly and specifically suppressed cancer cell proliferation, survival, and tumorigenic potential. Mechanistically, inhibition of SA1 in the SA2-mutated cells led to premature chromatid separation, dramatic extension of mitotic duration, and consequently, lethal failure of cell division. More importantly, depletion of SA1 rendered those SA2-mutated cells more susceptible to DNA damage, especially double-strand breaks (DSBs), due to reduced functionality of DNA repair. Furthermore, inhibition of SA1 sensitized the SA2-deficient cancer cells to PARP inhibitors in vitro and in vivo, providing a potential therapeutic strategy for patients with SA2-deficient tumors

Long non-coding RNA uc.291 controls epithelial differentiation by interfering with the ACTL6A/BAF complex.

The mechanisms that regulate the switch between epidermal progenitor state and differentiation are not fully understood. Recent findings indicate that the chromatin remodelling BAF complex (Brg1-associated factor complex or SWI/SNF complex) and the transcription factor p63 mutually recruit one another to open chromatin during epidermal differentiation. Here, we identify a long non-coding transcript that includes an ultraconserved element, uc.291, which physically interacts with ACTL6A and modulates chromatin remodelling to allow differentiation. Loss of uc.291 expression, both in primary keratinocytes and in three-dimensional skin equivalents, inhibits differentiation as indicated by epidermal differentiation complex genes down-regulation. ChIP experiments reveal that upon uc.291 depletion, ACTL6A is bound to the differentiation gene promoters and inhibits BAF complex targeting to induce terminal differentiation genes. In the presence of uc.291, the ACTL6A inhibitory effect is released, allowing chromatin changes to promote the expression of differentiation genes. Thus, uc.291 interacts with ACTL6A to modulate chromatin remodelling activity, allowing the transcription of late differentiation genes

ICTD: A semi-supervised cell type identification and deconvolution method for multi-omics data

We developed a novel deconvolution method, namely Inference of Cell Types and Deconvolution (ICTD) that addresses the fundamental issue of identifiability and robustness in current tissue data deconvolution problem. ICTD provides substantially new capabilities for omics data based characterization of a tissue microenvironment, including (1) maximizing the resolution in identifying resident cell and sub types that truly exists in a tissue, (2) identifying the most reliable marker genes for each cell type, which are tissue and data set specific, (3) handling the stability problem with co-linear cell types, (4) co-deconvoluting with available matched multi-omics data, and (5) inferring functional variations specific to one or several cell types. ICTD is empowered by (i) rigorously derived mathematical conditions of identifiable cell type and cell type specific functions in tissue transcriptomics data and (ii) a semi supervised approach to maximize the knowledge transfer of cell type and functional marker genes identified in single cell or bulk cell data in the analysis of tissue data, and (iii) a novel unsupervised approach to minimize the bias brought by training data. Application of ICTD on real and single cell simulated tissue data validated that the method has consistently good performance for tissue data coming from different species, tissue microenvironments, and experimental platforms. Other than the new capabilities, ICTD outperformed other state-of-the-art devolution methods on prediction accuracy, the resolution of identifiable cell, detection of unknown sub cell types, and assessment of cell type specific functions. The premise of ICTD also lies in characterizing cell-cell interactions and discovering cell types and prognostic markers that are predictive of clinical outcomes