60 research outputs found

    Multi-fractal analysis of weighted networks

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    In many real complex networks, the fractal and self-similarity properties have been found. The fractal dimension is a useful method to describe fractal property of complex networks. Fractal analysis is inadequate if only taking one fractal dimension to study complex networks. In this case, multifractal analysis of complex networks are concerned. However, multifractal dimension of weighted networks are less involved. In this paper, multifractal dimension of weighted networks is proposed based on box-covering algorithm for fractal dimension of weighted networks (BCANw). The proposed method is applied to calculate the fractal dimensions of some real networks. Our numerical results indicate that the proposed method is efficient for analysis fractal property of weighted networks

    XRoute Environment: A Novel Reinforcement Learning Environment for Routing

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    Routing is a crucial and time-consuming stage in modern design automation flow for advanced technology nodes. Great progress in the field of reinforcement learning makes it possible to use those approaches to improve the routing quality and efficiency. However, the scale of the routing problems solved by reinforcement learning-based methods in recent studies is too small for these methods to be used in commercial EDA tools. We introduce the XRoute Environment, a new reinforcement learning environment where agents are trained to select and route nets in an advanced, end-to-end routing framework. Novel algorithms and ideas can be quickly tested in a safe and reproducible manner in it. The resulting environment is challenging, easy to use, customize and add additional scenarios, and it is available under a permissive open-source license. In addition, it provides support for distributed deployment and multi-instance experiments. We propose two tasks for learning and build a full-chip test bed with routing benchmarks of various region sizes. We also pre-define several static routing regions with different pin density and number of nets for easier learning and testing. For net ordering task, we report baseline results for two widely used reinforcement learning algorithms (PPO and DQN) and one searching-based algorithm (TritonRoute). The XRoute Environment will be available at https://github.com/xplanlab/xroute_env.Comment: arXiv admin note: text overlap with arXiv:1907.11180 by other author

    The research on FBW7 gene enhances antitumor effect of paclitaxel on pancreatic cancer through GSDME-mediated pyroptosis

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    Background and purpose: Pancreatic cancer is a highly malignant disease. Most patients are in advanced stage upon diagnosis. Systemic chemotherapy is an important treatment method, but the chemotherapy drug resistance to tumors brings many problems to clinical treatment. As a commonly used chemotherapy drug, paclitaxel can induce apoptosis in tumor cells. The FBW7 gene is a tumor suppressor gene, and the loss of its function can lead to tumor occurrence and progression. Research has shown that it has the effect of promoting tumor cell apoptosis and inhibiting tumor proliferation. In addition, this gene has been proven to promote apoptosis and ferroptosis, which increase the effect of chemotherapy drugs. Pyroptosis is a programmed cell death mode mediated by gasdermin (GSDM) protein, and this cell death is often accompanied by inflammatory reactions. This study aimed to investigate whether FBW7 gene can promote the anti-tumor effect of paclitaxel by increasing pyroptosis. Methods: A PANC-1 cell line overexpressing FBW7 was constructed using lentivirus transfection. The correlation between FBW7 and GSDME gene expressions was detected by immunohistochemistry in clinical samples, and the expression levels of mRNA and protein were detected by real-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR) and Western blot. We observed the morphological changes of cells treated with paclitaxel under light microscopy. Cell counting kit-8 (CCK-8) was used to detect the effect of paclitaxel on cell viability, and flow cytometry and lactate dehydrogenase (LDH) release assay were performed to detect the effect of paclitaxel on cell death. Western blot was used to detect caspase-3 and GSDME activation after paclitaxel treatment. Results: RTFQ-PCR and Western blot experiments showed that overexpression of FBW7 gene increased the expression of GSDME. Immunohistochemical staining of pathological sections of clinical patients also showed that the expressions of FBW7 and GSDME genes was positively correlated in vivo. Flow cytometry and LDH release experiments showed that the level of cell death in pancreatic cancer cell line PANC-1 overexpressing FBW7 was significantly increased compared with its empty vector (EV) cells after being treated with paclitaxel. Under light microscopy, it was observed that the number of cells with pyroptosis was significantly higher in PANC-1 cell lines overexpressing FBW7 than in EV cells. The CCK-8 experiment results showed that the cell viability was significantly lower in FBW7 overexpressed cell lines than in EV cells after paclitaxel treatment. Western blot experiment results showed that after pancreatic cancer cell line PANC-1 was treated with paclitaxel, the protein expressions of active-caspase-3 and GSDME-NT in FBW7 overexpression cell lines increased, which proved that they had more obvious activation, indicating that the FBW7 gene can increase the sensitivity of PANC-1 cells to paclitaxel through caspase-3/GSDME signaling pathway induced cell pyroptosis. Conclusion: FBW7 can increase the sensitivity of pancreatic cancer cells to paclitaxel by increasing the expression of GSDME, which is realized through caspase-3/GSDME pathway

    Genetic relationships within Brassica rapa as inferred from AFLP finterprints

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    Amplified fragment length polymorphism (AFLP) markers were employed to assess the genetic diversity amongst two large collections of Brassica rapa accessions. Collection A consisted of 161 B. rapa accessions representing different morphotypes among the cultivated B. rapa, including traditional and modern cultivars and breeding materials from geographical locations from all over the world and two Brassica napus accessions. Collection B consisted of 96 accessions, representing mainly leafy vegetable types cultivated in China. On the basis of the AFLP data obtained, we constructed phenetic trees using mega 2.1 software. The level of polymorphism was very high, and it was evident that the amount of genetic variation present within the groups was often comparable to the variation between the different cultivar groups. Cluster analysis revealed groups, often with low bootstrap values, which coincided with cultivar groups. The most interesting information revealed by the phenetic trees was that different morphotypes are often more related to other morphotypes from the same region (East Asia vs. Europe) than to similar morphotypes from different regions, suggesting either an independent origin and or a long and separate domestication and breeding history in both region

    A sequence-based genetic linkage map as a reference for Brassica rapa pseudochromosome assembly

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    <p>Abstract</p> <p>Background</p> <p><it>Brassica rapa </it>is an economically important crop and a model plant for studies concerning polyploidization and the evolution of extreme morphology. The multinational <it>B. rapa </it>Genome Sequencing Project (BrGSP) was launched in 2003. In 2008, next generation sequencing technology was used to sequence the <it>B. rapa </it>genome. Several maps concerning <it>B. rapa </it>pseudochromosome assembly have been published but their coverage of the genome is incomplete, anchoring approximately 73.6% of the scaffolds on to chromosomes. Therefore, a new genetic map to aid pseudochromosome assembly is required.</p> <p>Results</p> <p>This study concerns the construction of a reference genetic linkage map for <it>Brassica rapa</it>, forming the backbone for anchoring sequence scaffolds of the <it>B. rapa </it>genome resulting from recent sequencing efforts. One hundred and nineteen doubled haploid (DH) lines derived from microspore cultures of an F1 cross between a Chinese cabbage (<it>B. rapa </it>ssp. <it>pekinensis</it>) DH line (Z16) and a rapid cycling inbred line (L144) were used to construct the linkage map. PCR-based insertion/deletion (InDel) markers were developed by re-sequencing the two parental lines. The map comprises a total of 507 markers including 415 InDels and 92 SSRs. Alignment and orientation using SSR markers in common with existing <it>B. rapa </it>linkage maps allowed ten linkage groups to be identified, designated A01-A10. The total length of the linkage map was 1234.2 cM, with an average distance of 2.43 cM between adjacent marker loci. The lengths of linkage groups ranged from 71.5 cM to 188.5 cM for A08 and A09, respectively. Using the developed linkage map, 152 scaffolds were anchored on to the chromosomes, encompassing more than 82.9% of the <it>B. rapa </it>genome. Taken together with the previously available linkage maps, 183 scaffolds were anchored on to the chromosomes and the total coverage of the genome was 88.9%.</p> <p>Conclusions</p> <p>The development of this linkage map is vital for the integration of genome sequences and genetic information, and provides a useful resource for the international <it>Brassica </it>research community.</p

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study