ssc-miR-185 targets cell division cycle 42 and promotes the proliferation of intestinal porcine epithelial cell

Wang, Wei,Wang, Pengfei,Xie, Kaihui,Luo, Ruirui,Gao, Xiaoli,Yan, Zunqiang,Huang, Xiaoyu,Yang, Qiaoli,Gun, Shuangbao Asian Australasian Association of Animal Productio 2021 Animal Bioscience Vol.34 No.5

Objective: microRNAs (miRNAs) can play a role in a variety of physiological and pathological processes, and their role is achieved by regulating the expression of target genes. Our previous high-throughput sequencing found that ssc-miR-185 plays an important regulatory role in piglet diarrhea, but its specific target genes and functions in intestinal porcine epithelial cell (IPEC-J2) are still unclear. We intended to verify the target relationship between porcine miR-185 and cell division cycle 42 (CDC42) gene in IPEC-J2 and to explore the effect of miR-185 on the proliferation of IPEC-J2 cells. Methods: The TargetScan, miRDB, and miRanda software were used to predict the target genes of porcine miR-185, and CDC42 was selected as a candidate target gene. The CDC42-3' UTR-wild type (WT) and CDC42-3'UTR-mutant type (MUT) segments were successfully cloned into pmirGLO luciferase vector, and the luciferase activity was detected after co-transfection with miR-185 mimics and pmirGLO-CDC42-3'UTR. The expression level of CDC42 was analyzed using quantitative polymerase chain reaction and Western blot. The proliferation of IPEC-J2 was detected using cell counting kit-8 (CCK-8), methylthiazolyldiphenyl-tetrazolium bromide (MTT), and 5-ethynyl-2'-deoxyuridine (EdU) assays. Results: Double enzyme digestion and sequencing confirmed that CDC42-3'UTR-WT and CDC42-3'UTR-MUT were successfully cloned into pmirGLO luciferase reporter vector, and the luciferase activity was significantly reduced after co-transfection with miR-185 mimics and CDC42-3'UTR-WT. Further we found that the mRNA and protein expression level of CDC42 were down-regulated after transfection with miR-185 mimics, while the opposite trend was observed after transfection with miR-185 inhibitor (p<0.01). In addition, the CCK-8, MTT, and EdU results demonstrated that miR-185 promotes IPEC-J2 cells proliferation by targeting CDC42. Conclusion: These findings indicate that porcine miR-185 can directly target CDC42 and promote the proliferation of IPEC-J2 cells. However, the detailed regulatory mechanism of miR-185/CDC42 axis in piglets' resistance to diarrhea is yet to be elucidated in further investigation.

A TBM Cutter Life Prediction Method Based on Rock Mass Classification

Ruirui Wang,Yaxu Wang,Jianbin Li,Liujie Jing,Guangzu Zhao,Lichao Nie 대한토목학회 2020 KSCE Journal of Civil Engineering Vol.24 No.9

Cutter life is an important economical index for tunnel boring machines (TBM) excavation, and its prediction is widely concerned. This paper introduces a method for predicting cutter life on the basis of statistics and regression. Traditional researches only evaluate the average mileage or time interval of each cutter change. Differently, the proposed method can accurately predict the mileage position of each cutter relatively, on the premise of knowing the installment radius of each cutter and the rock properties along the tunnel. In this procedure, the influence of the rock classification and rock properties of each cutter passing area on their passing distance is obtained by linear regression. For proposing and verifying the prediction method, totally 1,200 records of cutter changing caused by normal cutter wear are collected from the 4th Section of Water Supply Project from Songhua River. Among them, randomly selected 920 samples are used to determine the regression coefficients involved in the method. The method is verified by the rest 280 samples, and a reliable predicted result is obtained (MAPE = 27%, and R2 = 0.69).

Sequential Prediction of the TBM Tunnelling Attitude Based on Long-Short Term Memory with Mechanical Movement Principle

Ruirui Wang,Yuhang Xiao,Qian Guo,Hai Wang,Lingli Zhang,Yaodong Ni 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.2

TBM tunnelling attitude controlling is a significant issue for guaranteeing the tunnel fitting the expected tunnel axis, with directly influence the tunnel quality. The key to solve the problem is to establish the relationship between the tunnelling attitude and the controlling parameters and to predict the tunnelling attitude accordingly. For this, this paper introduced a TBM tunnelling attitude predicting method. In detail, using Long-Short Term Memory (LSTM), the initial tunnelling attitude and the controlling parameters of each later ring are taken as input, while the tunnelling attitude of each later rings are regarded as the output, and the relationship between the input and output is established. Meanwhile, for avoid the over-fitting and error accumulation risk of LSTM, the theoretical relationship between the input and output is also built based on the TBM mechanical movement principle, and it is also involved into the LSTM-based relationship as constraints. The proposed method is verified by the field data collected from the 6th Section of the Qingdao Metro Project, and the results reveal that the proposed LSTM-based method is accurate and acceptable.

A Rock Mass Strength Prediction Method Integrating Wave Velocity and Operational Parameters based on the Bayesian Optimization Catboost Algorithm

Yaxu Wang,Ruirui Wang,Jiwen Wang,Ningbo Li,Hongyi Cao 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.7

Tunnel Boring Machines (TBMs) have been the main equipment for tunneling and underground construction due to their high safety performance and tunneling efficiency. However, the unknown and changing geological conditions during construction pose a challenge to TBM construction. As one of the essential parameters of rock properties, accurate acquisition of uniaxial compressive strength (UCS) is crucial for TBMs to adapt to changing ground conditionsin a timely manner. Therefore, this study proposes a Catboost intelligent model based on Bayesian Optimization to predict UCS. Rock mass are velocity information and key TBM operational parameters are used as model input variables. The Gaussian data augmentation method is used to compensate for the difficulty of obtaining field data in large quantities. The Zhujiang Delta Water Resources Allocation Engineering field data are used in the model, and the obtained evaluation indicators MAPE, RMSE, VAF and a20-index are obtained as 9.91%, 499.38 MPa, 90.7% and 0.95, respectively. In addition, another project is selected to verify the applicability of the model. The validation results also confirm that the model is valid and reliable when applied to practical engineering.

Biochemical Properties and Physiological Roles of NADP-Dependent Malic Enzyme in Escherichia coli

Baojuan Wang,Peng Wang,Enxia Zheng,Xiangxian Chen,Hanjun Zhao,Ping Song,Ruirui Su,Xiaoning Li,Guoping Zhu 한국미생물학회 2011 The journal of microbiology Vol.49 No.5

Malic enzymes catalyze the reversible oxidative decarboxylation of L-malate using NAD(P)^+ as a cofactor. NADP-dependent malic enzyme (MaeB) from Escherichia coli MG1655 was expressed and purified as a fusion protein. The molecular weight of MaeB was about 83 kDa, as determined by SDS-PAGE. The recombinant MaeB showed a maximum activity at pH 7.8 and 46°C. MaeB activity was dependent on the presence of Mn^(2+) but was strongly inhibited by Zn^(2+). In order to understand the physiological roles, recombinant E. coli strains (icdNADP/ΔmaeB and icdNAD/ΔmaeB) containing NADP-dependent isocitrate dehydrogenase (IDH), or engineered NAD-dependent IDH with the deletion of the maeB gene, were constructed using homologous recombination. During growth on acetate, icd^(NAD)/ΔmaeB grew poorly, having a growth rate only 60% that of the wild-type strain (icd^(NADP)). Furthermore, icd^(NAD)P/ΔmaeB exhibited a 2-fold greater adaptability to acetate than icdNAD/ΔmaeB, which may be explained by more NADPH production for biosynthesis in icd^(NAD)P/ΔmaeB due to its NADP-dependent IDH. These results indicated that MaeB was important for NADPH production for bacterial growth on acetate. We also observed that MaeB activity was significantly enhanced (7.83-fold) in icd^(NAD), which was about 3-fold higher than that in icd^(NADP), when switching from glucose to acetate. The marked increase of MaeB activity was probably induced by the shortage of NADPH in icd^(NAD). Evidently, MaeB contributed to the NADPH generation needed for bacterial growth on two carbon compounds.

Arginine-Rich Manganese Silicate Nanobubbles as a Ferroptosis-Inducing Agent for Tumor-Targeted Theranostics

Wang, Shuaifei,Li, Fangyuan,Qiao, Ruirui,Hu, Xi,Liao, Hongwei,Chen, Lumin,Wu, Jiahe,Wu, Haibin,Zhao, Meng,Liu, Jianan,Chen, Rui,Ma, Xibo,Kim, Dokyoon,Sun, Jihong,Davis, Thomas P.,Chen, Chunying,Tian, American Chemical Society 2018 ACS NANO Vol.12 No.12

<P>Ferroptosis, an iron-based cell-death pathway, has recently attracted great attention owing to its effectiveness in killing cancer cells. Previous investigations focused on the development of iron-based nanomaterials to induce ferroptosis in cancer cells by the up-regulation of reactive oxygen species (ROS) generated by the well-known Fenton reaction. Herein, we report a ferroptosis-inducing agent based on arginine-rich manganese silicate nanobubbles (AMSNs) that possess highly efficient glutathione (GSH) depletion ability and thereby induce ferroptosis by the inactivation of glutathione-dependent peroxidases 4 (GPX4). The AMSNs were synthesized <I>via</I> a one-pot reaction with arginine (Arg) as the surface ligand for tumor homing. Subsequently, a significant tumor suppression effect can be achieved by GSH depletion-induced ferroptosis. Moreover, the degradation of AMSNs during the GSH depletion contributed to <I>T</I><SUB>1</SUB>-weighted magnetic resonance imaging (MRI) enhancement as well as on-demand chemotherapeutic drug release for synergistic cancer therapy. We anticipate that the GSH-depletion-induced ferroptosis strategy by using manganese-based nanomaterials would provide insights in designing nanomedicines for tumor-targeted theranostics.</P> [FIG OMISSION]</BR>

Improved Centripetal Accelerated Particle Swarm Optimization for Relevance Feedback in Medical Image Retrieval

Shengsheng Wang,Bolou Bolou Dickson,Ruyi Dong,Ruirui Wu 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.10

Centripetal Accelerated Particle Swarm Optimization (CAPSO) is a recent and well embraced, interest stimulating topic in swarm intelligence (SI). The original CAPSO method does not have parameters to tune or adjust, so two new parameters are introduced to catapult the efficiency and boost the overall performance. For further enhancement of the algorithm’s efficiency, the principle of quantum-behaved particles is also added. In evaluating the capability of the Improved Centripetal Accelerated Particle Swarm Optimization (ICAPSO) algorithm, we tested it on medical image database, in the aspect of Relevance Feedback of a Content-Based Image Retrieval (CBIR) system, clearly, ICAPSO outperformed others.

Amelioration of colitis progression by ginseng-derived exosome-like nanoparticles through suppression of infl ammatory cytokines

Jisu Kim,Shuya Zhang,Ying Zhu,Ruirui Wang,Jianxin Wang 고려인삼학회 2023 Journal of Ginseng Research Vol.47 No.5

Background: Damage to the healthy intestinal epithelial layer and regulation of the intestinal immunesystem, closely interrelated, are considered pivotal parts of the curative treatment for inflammatorybowel disease (IBD). Plant-based diets and phytochemicals can support the immune microenvironmentin the intestinal epithelial barrier for a balanced immune system by improving the intestinal microecologicalbalance and may have therapeutic potential in colitis. However, there have been only a fewreports on the therapeutic potential of plant-derived exosome-like nanoparticles (PENs) and the underlyingmechanism in colitis. This study aimed to assess the therapeutic effect of PENs from Panaxginseng, ginseng-derived exosome-like nanoparticles (GENs), in a mouse model of IBD, with a focus onthe intestinal immune microenvironment. Method: To evaluate the anti-inflammatory effect of GENs on acute colitis, we treated GENs in Caco2 andlipopolysaccharide (LPS) -induced RAW 264.7 macrophages and analyzed the gene expression of proinflammatorycytokines and anti-inflammatory cytokines such as TNF-a, IL-6, and IL-10 by real-timePCR (RT-PCR). Furthermore, we further examined bacterial DNA from feces and determined the alterationof gut microbiota composition in DSS-induced colitis mice after administration of GENs through16S rRNA gene sequencing analysis. Result: GENs with low toxicity showed a long-lasting intestinal retention effect for 48 h, which couldlead to effective suppression of pro-inflammatory cytokines such as TNF-a and IL-6 production throughinhibition of NF-kB in DSS-induced colitis. As a result, it showed longer colon length and suppressedthickening of the colon wall in the mice treated with GENs. Due to the amelioration of the progression ofDSS-induced colitis with GENs treatment, the prolonged survival rate was observed for 17 days comparedto 9 days in the PBS-treated group. In the gut microbiota analysis, the ratio of Firmicutes/Bacteroidotawas decreased, which means GENs have therapeutic effectiveness against IBD. Ingesting GENs would beexpected to slow colitis progression, strengthen the gut microbiota, and maintain gut homeostasis bypreventing bacterial dysbiosis. Conclusion: GENs have a therapeutic effect on colitis through modulation of the intestinal microbiota andimmune microenvironment. GENs not only ameliorate the inflammation in the damaged intestine bydownregulating pro-inflammatory cytokines but also help balance the microbiota on the intestinalbarrier and thereby improve the digestive system.

The Removal of Benzene and Toluene in Natural Gas with Cryogenic Liquid Propane: Effects and a Cyclic Purification Process

Dong Kai,Rong Qianqian,Xiao Ruirui,Gao Yunfei,Wang Fuchen 한국화학공학회 2024 Korean Journal of Chemical Engineering Vol.41 No.4

Liquefi ed natural gas production plants usually suff er from line blockage, which causes economic, environmental, and safety issues. The blockage, mainly caused by the solidifi cation of heavy hydrocarbons, should be avoided or mitigated by removing the impurities as thoroughly as possible. In this work, we proposed a scheme taking cryogenic liquefi ed propane as absorbent to absorb heavy hydrocarbons in the liquefi ed natural gas production process. This paper fi rst investigated freeze-out profi les of liquefi ed natural gas combined with marginal benzene and toluene by the ThermoFAST simulator, which showed that the precipitated solid tended to form under a low temperature, which posed challenges in purifi cation. Subsequently, the feasibility of using liquefi ed propane as an absorbent to remove benzene and toluene was studied using Aspen Plus. A cryogenic absorption and regeneration process for liquefi ed natural gas purifi cation was proposed, and factors infl uencing the performance were investigated. The results showed that the hydrocarbon impurities are removed more thoroughly at a high fl owrate of the recycled absorbent stream. The absorption process exhibited an apparent cooling eff ect mainly caused by the vaporization of liquefi ed propane to the gas phase, and the higher operation temperature impedes the vaporization process. For a better purifi cation eff ect, the system should be operated under a lower pressure or with a higher recycled absorption solution fl owrate. Based on the design simulation results, utilizing liquefi ed propane as an absorbent to remove heavy hydrocarbons is novel and promising for LNG purifi cation.

Improved SVR Method for Predicting the Cutting Force of a TBM Cutter Using Linear Cutting Machine Test Data

Mengmeng Hu,Biao Li,Bo Zhang,Ruirui Wang,Lei Chen 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.11

This research introduces a support vector regression (SVR) method to predict the cutting forces acting on the constant cross section (CCS) disc cutter, including the normal force (FN) and rolling force (FR), based on linear cutting machine (LCM) test data. To improve the prediction effect, an improved SVR-Outlier Detection (SVR-OD) method and an Additional Input Variable (AIV) method are proposed. After removing the outliers, 148 typical LCM test samples form the training set. Here, 70 samples from the Hangzhou No.2 Water Supply Channel constitute the test set. The prediction results show that the Root-mean-squared Relative Error (RMRE) values of the normal force and rolling force are 19.5% and 24.8%, respectively, and the corresponding determination coefficients are 0.845 and 0.807, respectively. For the prediction of the peak cutting force with an important reference to tunnel boring machine (TBM) design, the proportions of samples with an Absolute Relative Error (ARE) value of less than 20% for FN and FR are 9/10 and 7/7, respectively. The above prediction results are better than those of the common SVR method; thus, the developed method can effectively simulate the cutting force required by a rock mass with good integrity. The cutting force prediction using LCM test data is feasible and practical. In addition, the comparison of the prediction results between the improved SVR and common SVR methods shows that the improved SVR-OD and AIV methods play an active role in improving the prediction accuracy of the SVR method.