Snap: an integrated SNP annotation platform

Snap (Single Nucleotide Polymorphism Annotation Platform) is a server designed to comprehensively analyze single genes and relationships between genes basing on SNPs in the human genome. The aim of the platform is to facilitate the study of SNP finding and analysis within the framework of medical research. Using a user-friendly web interface, genes can be searched by name, description, position, SNP ID or clone name. Several public databases are integrated, including gene information from Ensembl, protein features from Uniprot/SWISS-PROT, Pfam and DAS-CBS. Gene relationships are fetched from BIND, MINT, KEGG and are integrated with ortholog data from TreeFam to extend the current interaction networks. Integrated tools for primer-design and mis-splicing analysis have been developed to facilitate experimental analysis of individual genes with focus on their variation. Snap is available at and at

Influence of radiation on Hemarthria compressa's genetic variations

Using the material of Hemarthria compressa (L.F.) R.Br. cv. YA’AN, we carried out this research to study the influence of radiation on the genetic variation of plants. Genetic difference was analyzed with expressed sequence tag-simple sequence repeat (EST-SSR) molecular marker through the comparison of 60Co-γ radiation on H. compressa seed stems and original variety. By using 20 primer pairs, 176 polymerase chain reaction (PCR)-amplifications with clear and consistent bands were obtained. The results showed that 155 of 176 bands were polymorphic, which indicating an 88.07% polymorphism rate, and each pair of primers had 8.8 amplified bands on average; the amplitude of polymorphism information content was 0.4709–0.6952 with an average value 0.6081. The genetic similarity coefficient of H. compressa and its mutants ranged from 0.4318 to 0.8239 with an average of 0.6671. As a consequence, existence of genetic differences between the mutants and the basic material was proved.We gratefully acknowledge financial support from the Modern Agro-industry Technology Research System (CARS-34) and the Sichuan Province Breeding Research grant (2016NZ0098-11).Peer reviewe

The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family

S_I_LSTM: stock price prediction based on multiple data sources and sentiment analysis

Stocks price prediction is a current hot spot with great promise and challenges. Recently, there have been many stock price prediction methods. However, the prediction accuracy of these methods is still far from satisfactory. In this paper, we propose a stock price prediction method that incorporates multiple data sources and the investor sentiment, which can be called S_I_LSTM. Firstly, we crawl multiple data sources on the Internet and preprocess them respectively. These data involve stock historical data, technical indicators, and non-traditional data sources, such as stock posts and financial news. Then, we use the sentiment analysis method based on convolutional neural network for the non-traditional data, which can calculate the investors' sentiment index. Finally, we combine sentiment index, technical indicators and stock historical transaction data as the feature set of stock price prediction and adopt the long short-term memory network for predicting the China Shanghai A-share market. The experiments show that the predicted stock closing price is closer to the true closing price than the single data source, and the mean absolute error can achieve 2.386835, which is better than traditional methods. We verified the effectiveness on the real data sets of five listed companies

Analysing the environmental harms caused by coal mining and its protection measures in permafrost regions of Qinghai–Tibet Plateau

The coal mining has brought a series of ecological problems and environmental problems in permafrost regions. Taking Muli coal-mining area as an example, this article attempts to analyse the environmental harms caused by coal mining and its protection measures in permafrost regions of Qinghai–Tibet Plateau. This article analyses the influence of open mining on the surrounding permafrost around the open pit by using the numerical simulation. The results show that (1) based on the interrelation between coal mining and permafrost environment, these main environmental harm include the permafrost change and the natural environment change in cold regions; (2) once the surface temperature rises due to open mining, the permafrost will disappear with the increase of exploitation life. If considering the solar radiation, the climate conditions and the geological condition around the pit edge, the maximum thaw depth will be more than 2 m; (3) the protection measures are proposed to avoid the disadvantage impact on the permafrost environment caused by coal mining. It will provide a scientific basis for the resource development and environment protection in cold regions

Methods for Solving Finite Element Mesh-Dependency Problems in Geotechnical Engineering—A Review

The instabilities of soil specimens in laboratory or soil made geotechnical structures in field are always numerically simulated by the classical continuum mechanics-based constitutive models with finite element method. However, finite element mesh dependency problems are inevitably encountered when the strain localized failure occurs especially in the post-bifurcation regime. In this paper, an attempt is made to summarize several main numerical regularization techniques used in alleviating the mesh dependency problems, i.e., viscosity theory, nonlocal theory, high-order gradient and micropolar theory. Their fundamentals as well as the advantages and limitations are presented, based on which the combinations of two or more regularization techniques are also suggested. For all the regularization techniques, at least one implicit or explicit parameter with length scale is necessary to preserve the ellipticity of the partial differential governing equations. It is worth noting that, however, the physical meanings and their relations between the length parameters in different regularization techniques are still an open question, and need to be further studied. Therefore, the micropolar theory or its combinations with other numerical methods are promising in the future

The experimental study of mir‐99a‐5p negative regulation of TLR8 receptor mediated‐mediated innate immune response in rabbit knee cartilage injury

Abstract Background Traumatic cartilage injury is an important cause of osteoarthritis (OA) and limb disability, and toll‐like receptors (TLRs) mediated innate immune response has been confirmed to play a crucial role in cartilage injury. In the previous study, we found that the activation of TLR8 molecules in injured articular cartilage was more obvious than other TLRs by establishing an animal model of knee impact injury in rabbits, and the changes of TLR8 molecules could significantly affect the process of articular cartilage injury and repair. Objective To verify how mir‐99a‐5p regulates TLR8 receptor mediated innate immune response to treat traumatic cartilage injury. Methods The impact of a heavy object on the medial condyle of the rabbit's knee joint caused damage to the medial condylar cartilage. Through pathological and imaging analysis, it was demonstrated whether the establishment of an animal model of traumatic cartilage injury was successful. Establishing a cell model by virus transfection of chondrocytes to demonstrate the role of TLR8 in the innate immune response to impact cartilage injury. Through transcriptome sequencing, potential targets of TLR8, mir‐99a‐5p, were predicted, and basic experiments were conducted to demonstrate how they interact with innate immune responses to impact cartilage damage. Results TLR8 is a receptor protein of the immune system, which is widely expressed in immune cells. In our study, we found that TLR8 expression is localized in lysosomes and endosomes. Mir‐99a‐5p can negatively regulate TLR8 to activate PI3K‐AKT molecular pathway and aggravate cartilage damage. Inhibiting TLR8 expression can effectively reduce the incidence of articular cartilage damage. Conclusion Based on the results from this study, mir‐99a‐5p may be an effective molecular marker for predicting traumatic cartilage injury and targeting TLR8 is a novel and promising approach for the prevention or early treatment of cartilage damage

ADSC-Exos enhance functional recovery after spinal cord injury by inhibiting ferroptosis and promoting the survival and function of endothelial cells through the NRF2/SLC7A11/GPX4 pathway

Background: Spinal cord injury (SCI) is a devastating disease that causes major motor, sensory and autonomic dysfunctions. Currently, there is a lack of effective treatment. In this study, we aimed to investigate the potential mechanisms of Exosomes from adipose-derived stem cells (ADSC-Exos) in reducing ferroptosis and promoting angiogenesis after spinal cord injury. Methods: We isolated ADSC-Exos, the characteristics of which were confirmed. In vitro, we tested the potential of ADSC-Exos to promote the survival and function of human brain microvascular endothelial cells (HBMECs) and analyzed the ferroptosis of HBMECs. In vivo, we established rat models of SCI and locally injected ADSC-Exos to verify their efficacy. Results: ADSC-Exos can reduce reactive oxygen species (ROS) accumulation and cell damage induced by an excessive inflammatory response in HBMECs. ADSC-Exos inhibit ferroptosis induced by excessive inflammation and upregulate the expression of glutathione peroxidase 4(GPX4) in HBMECs. It can also effectively promote proliferation, migration, and vessel-like structure formation. In vitro, ADSC-Exos improved behavioral function after SCI and increased the number and density of blood vessels around the damaged spinal cord. Moreover, we found that ADSC-Exos could increase nuclear factor erythroid-2-related factor 2(NRF2) expression and nuclear translocation, thereby affecting the expression of solute carrier family 7 member 11(SLC7A11) and GPX4, and the NRF2 inhibitor ML385 could reverse the above changes. Conclusion: Our results suggest that ADSC-Exos may inhibit ferroptosis and promote the recovery of vascular and neural functions after SCI through the NRF2/SLC7A11/GPX4 pathway. This may be a potential therapeutic mechanism for spinal cord injury