Altered Expression of Substance P and NK1R in CCR3+ and CD123+HLA-DR− Basophils Under Airway Allergic Conditions

Geng Shiyang,Xie Hua,Chen Liping,Chen Dong,Lu Sijing,Zhao Nan,Yang Ruiming,Wang Zhao,He Shaoheng,Zhang Huiyun 대한천식알레르기학회 2022 Allergy, Asthma & Immunology Research Vol.14 No.6

Purpose: To explore expression of SP and NK1R in basophils of allergic asthma (AA), allergic rhinitis (AR) and AR combined with AA (ARA), and influence of allergens and immunoglobulin E (IgE) mediated mechanisms on SP and NK1R expression. Methods: Expression of SP and NK1R was detected by flow cytometry, NK1R mRNA expression was detected by real time quantitative polymerase chain reaction (qPCR), and mouse AR and AA models were employed for in vivo study. Results: SP+ and NK1R+ cells increased in CCR3+ and CD123+HLA-DR− granulocytes of AA. PPE elevated proportions of SP+ cells in CCR3+ and CD123+HLA-DR− granulocytes, whereas ASWE and HDME augmented SP+ cells in CD123+HLA-DR− granulocytes of AR and ARA patients. ASWE, HDME and PPE increased proportions of NK1R+ cells in CCR3+ PBMC and CD123+HLA-DR− granulocytes of AR patients. OVA, Der p1, IL-33, IL-37, IgE and SP enhanced NK1R expression on KU812 cells. NK1R expressing basophils were increased in blood of OVA sensitized and challenged AR and AA mice. FcεRI-KO AA mice seemed to have less NK1R+ basophils than WT AA mice in their blood. Conclusion: CCR3+ and CD123+HLA-DR− cells are likely involved in AA and AR via SP and NK1R. IgE-related mechanism may participate in upregulation of NK1R expression.

Research on Ant Colony Algorithm Optimization Neural Network Weights Blind Equalization Algorithm

Yanxiang Geng,Liyi Zhang,Yunshan Sun,Yao Zhang,Nan Yang,Jiawei Wu 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.2

The project of ant colony algorithm optimization neural network combining blind equalization algorithm is proposed. The better initial weights of neural networks are provided because of the randomness, ergodicity and positive feedback of the ant colony algorithm. And then, a combination of optimal weights are found through BP algorithm, which is fast local search speed. Thus blind equalization performance is improved. Computer simulation show that, the novel blind equalization algorithm speeds up the convergence rate, reduces the remaining steady-state error and bit error rate, which is compared with the Neural Network Blind Equalization Algorithm(NNBE) and Genetic Algorithm optimization Neural Network Blind Equalization Algorithm(GA-NNBE) .

Characterization of Squamosa Promoter Binding Protein-LIKE genes in wheat

Bingnan Wang,Shuaifeng Geng,Di Wang,Nan Feng,Dongdong Zhang,Liang Wu,Chenyang Hao,Xueyong Zhang,Aili Li,Long Mao 한국식물학회 2015 Journal of Plant Biology Vol.58 No.4

Common wheat (Triticum aestivum) is an allohexaploid (AABBDD), with Triticum urartu (AA) and Aegilops tauschii (DD) as its A and D genome donors. Squamosa Promoter Binding Protein-Like (SPL) genes play important roles in plant development; however, a systematic study of this gene family in wheat is still lacking. Here, we mined the wheat genomes for SPLs and found 19 SPL genes each from the T. urartu and Ae. tauschii genomes. We also identified 58 SPL genes from the hexaploid wheat genome. We then compared the conservation and divergence of SPLs between the two diploid species in gene structures, tissuespecific expression patterns and responses to salt stress, drought and low temperature. For functional studies, two hexaploid wheat SPLs, TaSPL3 (with miR156 site mutated) and TaSPL6, were overexpressed in Arabidopsis and found to be involved in flowering time and biomass accumulation. In addition, a mutant allele (TaSPL6-D R ) with a 47 bp duplication upstream of the SBP domain was found to be associated with maturity date and grain number per spike among landraces from a Chinese wheat mini-core collection. Collectively, our work provides useful knowledge on the sequences and functions of wheat SPL genes that may help future functional studies and molecular breeding.

Improvement of Biomineralization of Sporosarcina pasteurii as Biocementing Material for Concrete Repair by Atmospheric and Room Temperature Plasma Mutagenesis and Response Surface Methodology

( Pei-pei Han ),( Wen-ji Geng ),( Meng-nan Li ),( Shi-ru Jia ),( Ji-long Yin ),( Run-ze Xue ) 한국미생물 · 생명공학회 2021 Journal of microbiology and biotechnology Vol.31 No.9

Microbially induced calcium carbonate precipitation (MICP) has recently become an intelligent and environmentally friendly method for repairing cracks in concrete. To improve on this ability of microbial materials concrete repair, we applied random mutagenesis and optimization of mineralization conditions to improve the quantity and crystal form of microbially precipitated calcium carbonate. Sporosarcina pasteurii ATCC 11859 was used as the starting strain to obtain the mutant with high urease activity by atmospheric and room temperature plasma (ARTP) mutagenesis. Next, we investigated the optimal biomineralization conditions and precipitation crystal form using Plackett-Burman experimental design and response surface methodology (RSM). Biomineralization with 0.73 mol/l calcium chloride, 45 g/l urea, reaction temperature of 45°C, and reaction time of 22 h, significantly increased the amount of precipitated calcium carbonate, which was deposited in the form of calcite crystals. Finally, the repair of concrete using the optimized biomineralization process was evaluated. A comparison of water absorption and adhesion of concrete specimens before and after repairs showed that concrete cracks and surface defects could be efficiently repaired. This study provides a new method to engineer biocementing material for concrete repair.

Recent advances in control technologies for non-point source pollution with nitrogen and phosphorous from agricultural runof: current practices and future prospects

Yinfeng Xia,Ming Zhang,Daniel C. W. Tsang,Nan Geng,Debao Lu,Lifang Zhu,Avanthi Deshani Igalavithana,Pavani Dulanja Dissanayake,Jörg Rinklebe,Xiao Yang,옥용식 한국응용생명화학회 2020 Applied Biological Chemistry (Appl Biol Chem) Vol.63 No.1

Eutrophication of natural water is a universal problem. Nitrogen (N) and phosphorus (P) from agricultural runoff are the main sources of nutrient input, provided that emissions from industrial point sources (IPS) are under control. Therefore, it is of great environmental importance to reduce pollution associated with agricultural runoff as a means of regulating eutrophication levels in natural water. Numerous methods proposed for treating agricultural runoff can be classified into three categories: source control, process control, and end treatment. In this review, major technologies for N and P control from agricultural runoff are summarized along with discussion of newly proposed technologies such as biochar biomimetics and microbial catalyst. Because agricultural runoff (from farmlands to receiving waters) is a complicated pollution process, it is difficult to regulate the nutrients discharged via such process. This review will thus offer a comprehensive understanding on the overall process of agricultural runoff and eutrophication to help establish control strategies against highly complicated agricultural non-point sources.

Phenolic composition and nutritional attributes of diaphragma juglandis fructus and shell of walnut (Juglans regia L.)

Qiang Hu,Jia Liu,Jun Li,Hui Liu,Nan Dong,Yang-yang Geng,Yang Lu,Yan Wang 한국식품과학회 2020 Food Science and Biotechnology Vol.29 No.2

Phenolic composition and nutritional attributes of diaphragma juglandis fructus (Djf) and walnut shells (Ws) were investigated. Phenolic acids, hydroxybenzoic acid, isoflavone, and flavone were identified in the free phenolic fractions (FPFs) of both Djf and Ws. Bound phenolic fractions were less than FPFs both in content and diversity. The soluble dietary fiber contents of Djf and Ws were 25.56 g/100 g and 9.5 g/100 g, respectively. The contents of unsaturated fatty acids (1912.28 mg/kg and 9137.56 mg/kg, respectively) were significantly higher than that of saturated fatty acid both in Djf and Ws. The content of essential amino acids in Djf (9.67 mg/g) was significantly higher than that in Ws. More than eight types of monosaccharides were detected in Djf and Ws. The monosaccharide content of Djf (314.16 mg/g) was significantly higher than that of Ws (60.97 mg/g). Trehalose was the predominant component both in Djf (71.2%) and Ws (78.6%).

Research on the Attenuation of Blast Wave by Groups of Filled Cracks in Surrounding Rock of Cavern

Xin Liu,Hong-fa Xu,Peng-xian Fan,Jian-nan Zhou,Han-sheng Geng,Jia-quan Mo,Tao-lin Zhang 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.7

This study introduces an approach for constructing groups of filled cracks in the surroundingrock to achieve anti-blasting and wave elimination protection for underground caverns. Toverify the attenuation effect of the explosion wave by the filled cracks, two models, a no-crackmodel, and a filled-crack model, were constructed using a certain proportion of analoguematerials based on the similarity theory. With the implementation of small equivalentexplosion conditions, the peak pressure of the surrounding rock of the cavern and thevibration acceleration of the cavern wall under different explosion conditions were measured. To accurately judge the attenuation efficiency of the filled cracks, the peak pressure attenuationpercentages between different measuring points were calculated. Furthermore, thecorresponding numerical simulation analysis process was performed according to the testconditions. The results show that not only the peak pressure attenuation percentages, but alsothe value of vibration acceleration, were significantly reduced due to the existence of filledcracks in the model. This indicates that filled cracks in the surrounding rock of the cavern caneffectively attenuate the peak pressure and vibration acceleration caused by the explosionwave, thereby achieving the protection engineering goal of anti-explosion and wave elimination.

Development and Validation of a Prognostic Nomogram Based on Clinical and CT Features for Adverse Outcome Prediction in Patients with COVID-19

Zheng Yingyan,Xiao Anling,Yu Xiangrong,Zhao Yajing,Lu Yiping,Li Xuanxuan,Mei Nan,She Dejun,Wang Dongdong,Geng Daoying,Yin Bo 대한영상의학회 2020 Korean Journal of Radiology Vol.21 No.8

Objective: The purpose of our study was to investigate the predictive abilities of clinical and computed tomography (CT) features for outcome prediction in patients with coronavirus disease (COVID-19). Materials and Methods: The clinical and CT data of 238 patients with laboratory-confirmed COVID-19 in our two hospitals were retrospectively analyzed. One hundred sixty-six patients (103 males; age 43.8 ± 12.3 years) were allocated in the training cohort and 72 patients (38 males; age 45.1 ± 15.8 years) from another independent hospital were assigned in the validation cohort. The primary composite endpoint was admission to an intensive care unit, use of mechanical ventilation, or death. Univariate and multivariate Cox proportional hazard analyses were performed to identify independent predictors. A nomogram was constructed based on the combination of clinical and CT features, and its prognostic performance was externally tested in the validation group. The predictive value of the combined model was compared with models built on the clinical and radiological attributes alone. Results: Overall, 35 infected patients (21.1%) in the training cohort and 10 patients (13.9%) in the validation cohort experienced adverse outcomes. Underlying comorbidity (hazard ratio [HR], 3.35; 95% confidence interval [CI], 1.67–6.71; p < 0.001), lymphocyte count (HR, 0.12; 95% CI, 0.04–0.38; p < 0.001) and crazy-paving sign (HR, 2.15; 95% CI, 1.03–4.48; p = 0.042) were the independent factors. The nomogram displayed a concordance index (C-index) of 0.82 (95% CI, 0.76–0.88), and its prognostic value was confirmed in the validation cohort with a C-index of 0.89 (95% CI, 0.82–0.96). The combined model provided the best performance over the clinical or radiological model (p < 0.050). Conclusion: Underlying comorbidity, lymphocyte count and crazy-paving sign were independent predictors of adverse outcomes. The prognostic nomogram based on the combination of clinical and CT features could be a useful tool for predicting adverse outcomes of patients with COVID-19.