Breviscapine Ameliorates Fear Extinction and Anxiety in BALB/cJ Mice

Wei Liang(Wei Liang),Jing Huang(Jing Huang),Shuya Yang(Shuya Yang),Peng Huang(Peng Huang),Jun Chen(Jun Chen),Chen Chen(Chen Chen),Qun Yang(Qun Yang),Fengzhan Li(Fengzhan Li) 대한신경정신의학회 2023 PSYCHIATRY INVESTIGATION Vol.20 No.3

Objective In this research, the influence of breviscapine on anxiety, fear elimination, and aggression and the potential mechanism was investigated. Methods Anxiety and locomotion were analyzed by elevated plus maze and open field test in mice. Bussey-Saksida Mouse Touch Screen Chambers were used to perform fear conditioning. Territorial aggression was assessed by resident intruder test. Protein levels were evaluated by Western blot. Breviscapine improved fear-extinction learning in BALB/cJ mice. Results Breviscapine at 20-100 mg/kg increased center cross number, total distance traveled, and velocity in a dose-dependent manner. On the other hand, breviscapine at 20-100 mg/kg decreased the immobility time in open field test. In addition, breviscapine at 20-100 mg/kg increased the ratio of time on the open arm, time on the distal parts of the open arm, and total distance traveled in elevated plus maze. Breviscapine at 100 mg/kg increased the average attack latency and decreased the number of attacks over the last 3 days of resident intruder test. In hippocampus, protein levels of postsynaptic density protein-95 and synaptophysin were elevated by breviscapine at these three doses. Conclusion The administration of breviscapine alleviates fear extinction, anxiety, and aggression, while increases locomotor in a dose-dependent manner, which might be associated with its influence on synaptic function.

Localized surface plasmon resonance enhanced by the light-scattering property of silver nanoparticles for improved luminescence of polymer light-emitting diodes

Cheng-Liang Huang,Hung Ji Huang,Sy-Hann Chen,Yu-Siang Huang,Po-Ching Kao,Yuan-Fong Chou Chau,Hai-Pang Chiang 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.103 No.-

This study used photochemical reduction to successfully synthesize triangular silver nanoplates (TAgNPs)and silver nanodecahedrons (AgNDs) with higher light-absorption and higher light-scattering properties,respectively, for the same wavelength. To analyze the contribution of light-absorption and lightscatteringof silver nanoparticles to the localized surface plasmon resonance (LSPR) effect, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate was doped with TAgNPs or AgNDs at the same concentration(1.17 lg/cm2) and made into polymer light-emitting diodes (PLEDs). According to the current densityvoltageluminancecharacteristics and electroluminescence (EL) spectra, the enhancement factors for currentefficiency and EL intensity for AgND-containing PLEDs were found to be higher than those for PLEDwith TAgNPs by 24.9% and 138%, respectively. This shows that the metal nanoparticles with higher lightscatteringproperty can induce a relatively strong LSPR effect, which possibly gives a hint to design plasmonicphotovoltaic in future.

Research on Task Scheduling Convergence Non-Dominated Sorting Method in Cloud Computing

Liang. Huang,Jun. Zheng,Guolv.Tan 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.1

Cloud computing task scheduling is a multi-objective decision on how to perform a variety of tasks simultaneously reasonable sort is essential. Therefore, this article constructs a population of convergence non-dominated sorting method. This method is based on non-dominated sorting method; the use of distributed estimation method is improved by four steps to complete the task order scheduling. The experimental results show that this method has good convergence and distribution.

Preliminary study of genome-wide association identified novel susceptibility genes for thyroid-related hormones in Chinese population

Huang Liang,Bai Fenghua,Zhang Yutian,Zhang Shanshan,Jin Tianbo,Wei Xingwei,Zhou Xiaoli,Lin Mei,Xie Yufei,He Chanyi,Lin Qi,Xie Tian,Ding Yipeng 한국유전학회 2022 Genes & Genomics Vol.44 No.8

Background: Thyroid hormones are critical regulators of metabolism, development and growth in mammals. However, the genetic association of thyroid-related hormones in the Chinese Han population is not fully understood. Objective: We aimed to identify the genetic loci associated with circulating thyroid-related hormones concentrations in the healthy Chinese Han population. Methods: Genotyping was performed in 124 individuals using Applied Biosystems™ Axiom™ PMDA, and 796,288 single nucleotide polymorphisms (SNPs) were available for the GWAS analysis. For replication, eleven SNPs were selected as candidate loci for genotyping by Agena MassARRAY platform in additional samples (313 subjects). The values of p < 5 × 10- 6 suggest a suggestively significant genome-wide association with circulating thyroid-related hormones concentrations. Results: We identified that rs11178277 (PTPRB, p = 4.88 × 10- 07) and rs7320337 (LMO7DN-KCTD12, p = 1.22 × 10- 06) were associated with serum FT3 level. Three SNPs (rs4850041 in LOC105373394-LINC01249: p = 3.55 × 10- 06, rs6867291 in LINC02208: p = 2.40 × 10- 06 and rs79508321 in WWOX: p = 3.35 × 10- 06) were related to circulating T3 level. Rs12474167 (LOC105373394-LINC01249, p = 1.65 × 10- 06) and rs1864553 (IWS1, p = 2.00 × 10- 06) were associated with circulating T4 concentration. The association with TGA concentration was for rs17163542 in DISP1 (p = 3.46 × 10- 06) and rs12601151 in NOG-C17orf67 (p = 2.72 × 10- 07). Two genome-level significant SNPs (rs2114707 in LINC01314, p = 1.69 × 10- 06 and rs12601151, p = 1.41 × 10- 07) associated with serum TMA concentration were identified. Moreover, rs6083269 (CST1-CST2, p = 3.36 × 10- 06) was a significant locus for circulating TSH level. In replication, rs12601151 in NOG-C17orf67 was still associated with serum TGA level (p = 0.012). Conclusions: The GWAS reported 11 new suggestively significant loci associated with circulating thyroid-related hormones levels among the Chinese Han population. These findings represented suggestively biological candidates for circulating thyroid-related hormones levels and provided new insights into the mechanisms of regulating serum TGA concentration.

Truncated Kernel Projection Machine for Link Prediction

Liang Huang,Ruixuan Li,Hong Chen 한국정보과학회 2016 Journal of Computing Science and Engineering Vol.10 No.2

With the large amount of complex network data that is increasingly available on the Web, link prediction has become a popular data-mining research field. The focus of this paper is on a link-prediction task that can be formulated as a binary classification problem in complex networks. To solve this link-prediction problem, a sparse-classification algorithm called “Truncated Kernel Projection Machine” that is based on empirical-feature selection is proposed. The proposed algorithm is a novel way to achieve a realization of sparse empirical-feature-based learning that is different from those of the regularized kernel-projection machines. The algorithm is more appealing than those of the previous outstanding learning machines since it can be computed efficiently, and it is also implemented easily and stably during the link-prediction task. The algorithm is applied here for link-prediction tasks in different complex networks, and an investigation of several classification algorithms was performed for comparison. The experimental results show that the proposed algorithm outperformed the compared algorithms in several key indices with a smaller number of test errors and greater stability.

Potential Biomarker of L-type Amino Acid Transporter 1 in Breast Cancer Progression

Liang, Zhongxing,Cho, Heidi T.,Williams, Larry,Zhu, Aizhi,Liang, Ke,Huang, Ke,Wu, Hui,Jiang, Chunsu,Hong, Samuel,Crowe, Ronald,Goodman, Mark M.,Shim, Hyun-Suk The Korea Society of Nuclear Medicine 2011 핵의학 분자영상 Vol.45 No.2

Purpose L-type amino acid transporter 1 (LAT1) is essential for the transport of large neutral amino acids. However, its role in breast cancer growth remains largely unknown. The purpose of the study is to investigate whether LAT1 is a potential biomarker for the diagnosis and treatment of breast cancer. Methods LAT1 mRNA and protein levels in breast cancer cell lines and tissues were analyzed. In addition, the effects of targeting LAT1 for the inhibition of breast cancer cell tumorigenesis were assessed with soft agar assay. The imaging of xenograft with anti-1-amino-3-[$^{18}F$]fluorocyclobutane-1-carboxylic acid (anti-[$^{18}F$]FACBC) PET was assessed for its diagnostic biomarker potential. Results Normal breast tissue or low malignant cell lines expressed low levels of LAT1 mRNA and protein, while highly malignant cancer cell lines and high-grade breast cancer tissue expressed high levels of LAT1. In addition, higher expression levels of LAT1 in breast cancer tissues were consistent with advanced-stage breast cancer. Furthermore, the blockade of LAT1 with its inhibitor, 2-aminobicyclo[ 2.2.1]heptane-2-carboxylic acid (BCH), or the knockdown of LAT1 with siRNA, inhibited proliferation and tumorigenesis of breast cancer cells. A leucine analog, anti-[$^{18}F$]FACBC, has been demonstrated to be an excellent PET tracer for the non-invasive imaging of malignant breast cancer using an orthotopic animal model. Conclusions The overexpression of LAT1 is required for the progression of breast cancer. LAT1 represents a potential biomarker for therapy and diagnosis of breast cancer. Anti-[$^{18}F$]FACBC that correlates with LAT1 function is a potential PET tracer for malignant breast tumor imaging.

Truncated Kernel Projection Machine for Link Prediction

Huang, Liang,Li, Ruixuan,Chen, Hong Korean Institute of Information Scientists and Eng 2016 Journal of Computing Science and Engineering Vol.10 No.2

With the large amount of complex network data that is increasingly available on the Web, link prediction has become a popular data-mining research field. The focus of this paper is on a link-prediction task that can be formulated as a binary classification problem in complex networks. To solve this link-prediction problem, a sparse-classification algorithm called "Truncated Kernel Projection Machine" that is based on empirical-feature selection is proposed. The proposed algorithm is a novel way to achieve a realization of sparse empirical-feature-based learning that is different from those of the regularized kernel-projection machines. The algorithm is more appealing than those of the previous outstanding learning machines since it can be computed efficiently, and it is also implemented easily and stably during the link-prediction task. The algorithm is applied here for link-prediction tasks in different complex networks, and an investigation of several classification algorithms was performed for comparison. The experimental results show that the proposed algorithm outperformed the compared algorithms in several key indices with a smaller number of test errors and greater stability.

Checking Relationship Consistency and Class Redundancy in a Class Diagram under Model-Driven Engineering

Liang Huang,Yucong Duan,Honghao Gao,Hui Li,Caimao Li,Zhiyang Lin 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.10

Model-Driven Engineering (MDE) tries to reduce the effort spent on software development by generating codes from models. People concentrate their minds on the transformation between models and models, or between models and codes. People also concentrate on checking consistency between different models such as consistency between a class diagram and a sequence diagram and consistency between a sequence diagram and a state machine diagram. Checking relationship consistency and class redundancy in a class model is still important but ignored in recent years. This paper concentrates on relationship problems between classes in a class diagram and proposes methods of checking various relationship problems. We address the redundancy of a class’s operations and attributes. We identify a large range of the problems for class diagram. Our research is based on the relationship abstraction rules.

Probing two-dimensional metallic-like and localization effects at low magnetic fields

Huang, T.Y.,Liang, C.T.,Kim, G.H.,Huang, C.F.,Huang, C.P.,Ritchie, D.A. North-Holland 2010 Physica E, Low-dimensional systems & nanostructure Vol.42 No.4

The metallic-like regime characterized by Shubnikov-de Haas (SdH) oscillations is investigated between localization-induced weak insulator and quantum Hall liquid in a gated two-dimensional GaAs electron system containing InAs dots. Multiple SdH crossing points are observed in the longitudinal resistivity before the appearance of the critical point of a plateau transition with increasing perpendicular magnetic field. In conductivities, however, there is no corresponding crossing in the metallic-like regime because of the T-dependent Hall slope under electron-electron interaction, which provides an explicit way to distinguish SdH crossing points from the critical point in our study.

Research on the kinematic calibration of the 3-PTT parallel mechanism

Liang'en Huang,Minfang Chen,Shigao Zheng,Chaoyin He,Enxiao Zhu,Yongxia Zhang 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.8

Most of the kinematic calibration methods of parallel mechanisms only consider the geometric error of the mechanism, and the calibration effect is poor. To improve the calibration effect, this paper takes the 3-PTT (3-prismatic hook hook) parallel mechanism as the research object and proposes a kinematics calibration method based on the normalized representation model of the geometric error and non-geometric error of the mechanism. First, the degree of freedom of the mechanism is analyzed, its kinematics positive and negative solutions are solved, and its singularity is analyzed. Secondly, a normalized characterization method of mechanism geometric errors and non-geometric errors is proposed, and an error model without redundant parameters is constructed. The end motion error of the machine is measured by laser tracker, and the objective function is constructed. The genetic algorithm is designed to solve the minimum value of the objective function, and the normalized error of the mechanism is identified. By comparing with the recent methods, the better identification performance of the algorithm in this paper is verified. Finally, the kinematics model was corrected according to the identification results. After the calibration was completed, the movement errors of the end of the mechanism along each coordinate axis were reduced by more than 99 %. Compared with other calibration methods, the better calibration performance of the method in this paper is verified.