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10. Identification of key genes with prognostic value in gastric cancer by bioinformatics analysis.

Author

Wang, Rongsheng, Chen, Xiaohong, Huang, Cuilan, Yang, Xiaogang, He, Huiwei, OuYang, Chenghong, Li, Hainan, Guo, Jinghua, Yang, Chunli, and Lin, Zhiying

Subjects
Cytoscape, bioinformatics, gastric cancer, key genes, protein–protein interaction network, Cancer, Biotechnology, Digestive Diseases, Genetic Testing, Rare Diseases, Genetics, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, protein-protein interaction network, Clinical Sciences, Law
Abstract

Background: Gastric cancer (GC) is a digestive system tumor with high morbidity and mortality. It is urgently required to identify genes to elucidate the underlying molecular mechanisms. The aim of this study is to identify the key genes which may affect the prognosis of GC patients and be a therapeutic strategy for GC patients by bioinformatic analysis. Methods: The significant prognostic differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. The protein-protein interaction (PPI) network was established by STRING and screening key genes by MCODE and CytoNCA plug-ins in Cytoscape. Functional enrichment analysis, construction of a prognostic risk model, and nomograms verify key genes as potential therapeutic targets. Results: In total, 997 genes and 805 genes were related to the prognosis of GC in the GSE84437 and TCGA datasets, respectively. We define the 128 genes shared by the two datasets as prognostic DEGs (P-DEGs). Then, the first four genes (MYLK, MYL9, LUM, and CAV1) with great node importance in the PPI network of P-DEGs were identified as key genes. Independent prognostic risk analysis found that patients with high key gene expression had a poor prognosis, excluding their age, gender, and TNM stage. GO and KEGG enrichment analyses showed that key genes may exert influence through the PI3K-Akt pathway, in which extracellular matrix organization and focal adhesion may play important roles in key genes influencing the prognosis of GC patients. Conclusion: We found that MYLK, MYL9, LUM, and CAV1 are potential and reliable prognostic key genes that affect the invasion and migration of gastric cancer.

Published
2022

11. Identification of an Immune-Related Prognostic Risk Model in Glioblastoma.

Author

Lin, Zhiying, Wang, Rongsheng, Huang, Cuilan, He, Huiwei, Ouyang, Chenghong, Li, Hainan, Zhong, Zhiru, Guo, Jinghua, Chen, Xiaohong, Yang, Chunli, and Yang, Xiaogang

Subjects
biomarker, glioblastoma, infiltrated immune cell, prognostic risk model, tumor immune microenvironment, Cancer, Immunization, Brain Cancer, Neurosciences, Brain Disorders, Rare Diseases, Genetics, Good Health and Well Being, Clinical Sciences, Law
Abstract

Background: Glioblastoma (GBM) is the most common and malignant type of brain tumor. A large number of studies have shown that the immunotherapy of tumors is effective, but the immunotherapy effect of GBM is not poor. Thus, further research on the immune-related hub genes of GBM is extremely important. Methods: The GBM highly correlated gene clusters were screened out by differential expression, mutation analysis, and weighted gene co-expression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) and proportional hazards model (COX) regressions were implemented to construct prognostic risk models. Survival, receiver operating characteristic (ROC) curve, and compound difference analyses of tumor mutation burden were used to further verify the prognostic risk model. Then, we predicted GBM patient responses to immunotherapy using the ESTIMATE algorithm, GSEA, and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. Results: A total of 834 immune-related differentially expressed genes (DEGs) were identified. The five hub genes (STAT3, SEMA4F, GREM2, MDK, and SREBF1) were identified as the prognostic risk model (PRM) screened out by WGCNA and LASSO analysis of DEGs. In addition, the PRM has a significant positive correlation with immune cell infiltration of the tumor microenvironment (TME) and expression of critical immune checkpoints, indicating that the poor prognosis of patients is due to TIDE. Conclusion: We constructed the PRM composed of five hub genes, which provided a new strategy for developing tumor immunotherapy.

Published
2022

14. Training Sparse Neural Network by Constraining Synaptic Weight on Unit Lp Sphere

Author

Li, Weipeng, Yang, Xiaogang, Li, Chuanxiang, Lu, Ruitao, and Xie, Xueli

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition
Abstract

Sparse deep neural networks have shown their advantages over dense models with fewer parameters and higher computational efficiency. Here we demonstrate constraining the synaptic weights on unit Lp-sphere enables the flexibly control of the sparsity with p and improves the generalization ability of neural networks. Firstly, to optimize the synaptic weights constrained on unit Lp-sphere, the parameter optimization algorithm, Lp-spherical gradient descent (LpSGD) is derived from the augmented Empirical Risk Minimization condition, which is theoretically proved to be convergent. To understand the mechanism of how p affects Hoyer's sparsity, the expectation of Hoyer's sparsity under the hypothesis of gamma distribution is given and the predictions are verified at various p under different conditions. In addition, the "semi-pruning" and threshold adaptation are designed for topology evolution to effectively screen out important connections and lead the neural networks converge from the initial sparsity to the expected sparsity. Our approach is validated by experiments on benchmark datasets covering a wide range of domains. And the theoretical analysis pave the way to future works on training sparse neural networks with constrained optimization.

Published
2021

17. LUDA: Boost LSM Key Value Store Compactions with GPUs

Author

Xu, Peng, Wan, Jiguang, Huang, Ping, Yang, Xiaogang, Tang, Chenlei, Wu, Fei, and Xie, Changsheng

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Log-Structured-Merge (LSM) tree-based key value stores are facing critical challenges of fully leveraging the dramatic performance improvements of the underlying storage devices, which makes the compaction operations of LSM key value stores become CPU-bound, and slow compactions significantly degrade key value store performance. To address this issue, we propose LUDA, an LSM key value store with CUDA, which uses a GPU to accelerate compaction operations of LSM key value stores. How to efficiently parallelize compaction procedures as well as accommodate the optimal performance contract of the GPU architecture challenge LUDA. Specifically, LUDA overcomes these challenges by exploiting the data independence between compaction procedures and using cooperative sort mechanism and judicious data movements. Running on a commodity GPU under different levels of CPU overhead, evaluation results show that LUDA provides up to 2x higher throughput and 2x data processing speed, and achieves more stable 99th percentile latencies than LevelDB and RocksDB.

Published
2020

18. Adaptive Trajectory Estimation with Power Limited Steering Model under Perturbation Compensation

Author

Li, Weipeng, Yang, Xiaogang, Lu, Ruitao, Fan, Jiwei, Zhang, Tao, and He, Chuan

Subjects
Computer Science - Information Theory, Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control, G.3.13, J.2.7
Abstract

Trajectory estimation of maneuvering objects is applied in numerous tasks like navigation, path planning and visual tracking. Many previous works get impressive results in the strictly controlled condition with accurate prior statistics and dedicated dynamic model for certain object. But in challenging conditions without dedicated dynamic model and precise prior statistics, the performance of these methods significantly declines. To solve the problem, a dynamic model called the power-limited steering model (PLS) is proposed to describe the motion of non-cooperative object. It is a natural combination of instantaneous power and instantaneous angular velocity, which relies on the nonlinearity instead of the state switching probability to achieve switching of states. And the renormalization group is introduced to compensate the nonlinear effect of perturbation in PLS model. For robust and efficient trajectory estimation, an adaptive trajectory estimation (AdaTE) algorithm is proposed. By updating the statistics and truncation time online, it corrects the estimation error caused by biased prior statistics and observation drift, while reducing the computational complexity lower than O(n). The experiment of trajectory estimation demonstrates the convergence of AdaTE, and the better robust to the biased prior statistics and the observation drift compared with EKF, UKF and sparse MAP. Other experiments demonstrate through slight modification, AdaTE can also be applied to local navigation in random obstacle environment, and trajectory optimization in visual tracking., Comment: 19 pages, 7 figures

Published
2019

23. Kaempferol Alleviates Oxidative Stress and Apoptosis Through Mitochondria-dependent Pathway During Lung Ischemia-Reperfusion Injury.

Author

Yang, Chunli, Yang, Wenkai, He, Zhaohui, Guo, Jinghua, Yang, Xiaogang, Wang, Rongsheng, and Li, Hongbo

Subjects
PGC-1α, SIRT1, apoptosis, kaempferol, lung ischemia-reperfusion injury, mitochondria, oxidative stress, Lung, Aetiology, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, 2.1 Biological and endogenous factors, PGC-1&#945, Pharmacology and Pharmaceutical Sciences
Abstract

In previous study, we reported that kaempferol ameliorates significantly lung ischemia-reperfusion injury (LIRI), and may be achieved by targeting the SIRT 1 pathway. This study further explored the anti-LIRI mechanism of kaempferol. In vitro, the rat alveolar epithelial cells L2 was cultured and subjected to anoxia/reoxygenation (A/R) insult. In vivo, SD rats were operated to establish LIRI model. The related indicators of oxidative stress and apoptosis in L2 cells and rats lung tissues were detected. Results showed that kaempferol pre-treatment significantly increased the cell viability, improved mitochondrial membrane potential, inhibited the opening of mitochondrial permeability transition pores, reduced the levels of oxidative stress and apoptosis, increased the expressions of Bcl-2 and mitochondrial cytochrome c, and decreased the expressions of Bax and cytoplasmic cytochrome c in L2 cells after A/R insult. In vivo, kaempferol improved the pathological injury, inhibited the levels of oxidative stress and apoptosis, increased the expressions of Bcl-2 and mitochondrial cytochrome c, and decreased the expressions of Bax and cytoplasmic cytochrome c in rats lung tissues after I/R. However, the aforementioned effects of kaempferol were significantly attenuated by the SIRT 1 inhibitor EX527 or the PGC-1α inhibitor SR-18292. What's more, SR-18292 has not reversed the effect of kaempferol on increasing the protein activity of SIRT 1. Above results suggest that kaempferol ameliorates LIRI by improving mitochondrial function, reducing oxidative stress and inhibiting cell apoptosis. Its molecular mechanism of action includes the SIRT 1/PGC-1α/mitochondria signaling pathway.

Published
2021

24. Comparative study on non-on-line seismic while excavating and borehole-blasting method for advanced fault detection

Author

YANG Yanjun, WANG Ji, LIU Haidong, and YANG Xiaogang

Subjects
underground geophysical exploration, seismic while excavating, borehole-blasting method, fault, advanced detection, Mining engineering. Metallurgy, TN1-997
Abstract

Surface drilling and 3D seismic results show that a boundary fault with a maximum drop of nearly 300 m is developed on the east side of the 103 lower 03 working face of a mine in Shandong Province. YTZ3(B) type self-recording seismometer was used to carry out the comparison test of non-on-line seismic while excavating and borehole-blasting method for advanced fault detection in the transportation roadway of 103 lower 03 working face. The non-on-line seismic interpretation showed that the nearest distance between the fault hanging wall and the designed cutting eye was 110 m, the fault plane was relatively straight and the strike was about 62°. The drilling and blasting method is advanced to explain that the nearest distance between the fault hanging wall and the designed cutting eye is 108 m, the fault plane is relatively straight and the strike is about 61°. The test results show that the fault boundaries of non-on-line seismic while excavating and borehole-blasting method are basically consistent with the comprehensive interpretation of ground drilling and 3D seismic. The three independent detection methods verify each other, which improves the detection accuracy of the fault boundary location, and also shows the effectiveness of non-on-line seismic while excavating to detect the fault in front of the roadway.

Published
2023
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28. Quasi-incompressible Multi-species Ionic Fluid Models

Author

Yang, Xiaogang, Gong, Yuezheng, Li, Jun, Eisenberg, Robert S., and Wang, Qi

Subjects
Physics - Fluid Dynamics
Abstract

In traditional hydrodynamic theories for ionic fluids, conservation of the mass and linear momentum is not properly taken care of. In this paper, we develop hydrodynamic theories for a viscous, ionic fluid of $N$ ionic species enforcing mass and momentum conservation as well as considering the size effect of the ionic particles. The theories developed are quasi-incompressible in that the mass-average velocity is no longer divergence-free whenever there exists variability in densities of the fluid components, and the models are dissipative. We present several ways to derive the transport equations for the ions, which lead to different rates of energy dissipation. The theories can be formulated in either number densities, volume fractions or mass densities of the ionic fluid components. We show that the theory with the Cahn-Hilliard transport equation for ionic species reduces to the classical Poisson-Nernst-Planck (PNP) model with the size effect for ionic fluids when the densities of the fluid components are equal and the entropy of the solvent is neglected. It further reduces to the PNP model when the size effect is neglected. A linear stability analysis of the model together with two of its limits, which is the extended PNP model (EPNP defined in the text) and the classical PNP model (CPNP) with the finite size effect, on a constant state and a comparison among the three models in 1D space are presented to highlight the similarity and the departure of this model from the EPNP and the CPNP model.

Published
2018

46. Construction of a novel heterostructure of Bi2S3/Sb2S3 nanorod with improved sodium storage performances.

Author

Dong, Yangtao, Murugesan, Balaji, Lin, Weidi, Wang, Chao, Dai, Junjie, Li, Wenwen, Ma, Quangui, Yang, Xiaogang, and Cai, Yurong

Abstract

In this study, a rod-like heterogeneous Bi2S3/Sb2S3 was systematically engineered through a simple one-step hydrothermal method and subsequently used as an anode active material for sodium-ion batteries (SIBs). The Bi2S3/Sb2S3 heterostructure electrode exhibits a high initial discharge capacity of 972.2 mAh g−1 and maintains a reversible capacity of 369.4 mAh g−1 after 500 cycles at a current density of 1 A g−1. The outstanding electrochemical performance of the Bi2S3/Sb2S3 electrode can be attributed to the synergistic contributions of the high capacity of Sb2S3 and the excellent stability of Bi2S3. Simultaneously, the abundant heterogeneous phase boundaries formed by Bi2S3 and Sb2S3 provide stable reaction interfaces, better structural integrity, and enhanced Na+ reaction kinetics. This work presents an opportunity to develop heterogeneous Bi2S3/Sb2S3 anode materials with excellent properties, holding promise for potential applications in SIBs. [ABSTRACT FROM AUTHOR]

Published
2024
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