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- 저자 : Hongyou Li (검색결과 2 건)
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Hongyou Li,Kaifeng Huang,Hanmei Du,Hongling Wang,Xin Chen,Shibin Gao,Hailan Liu,Moju Cao,Yanli Lu,Tingzhao Rong,Su-Zhi Zhang 한국식물학회 2016 Journal of Plant Biology Vol.59 No.6
Gro/Tup1 proteins act as negative transcriptional regulators and play crucial roles in many growth and developmental processes in a wide range of organisms. However, our understanding of Gro/Tup1 protein functions in plants is confined to the model plant Arabidopsis. Here, 11 Gro/Tup1 genes, which were characterized by the typical LisH and WD40 repeat domains, were identified in maize through a genome-wide survey. A phylogenetic analysis revealed that maize Gro/Tup1 proteins could be divided into three subfamilies, in which members shared similar protein and gene structures. The predicted maize Gro/Tup1 genes were distributed on seven chromosomes and segmental duplication contributed to their expansion. Many predicted cis-elements associated with hormones, biotic- or abioticstress responses, meristem and seed development, and circadian rhythms, were found in their putative promoter regions. A potential associated protein analysis identified a large number of candidates, including transcription factors, chromatin-modifying enzymes, protein kinases, and ubiquitinconjugating enzymes. An expression profile derived from the RNA-seq data indicated that Gro/Tup1 genes in maize were widely expressed in various organs and tissues. Quantitative real-time PCR revealed that these genes responded to at least one hormone or abiotic stress, either in roots or in shoots. Our study provides useful information on the Gro/Tup1 genes in maize and will facilitate the further functional validation of these genes in growth and development, hormone responses, and biotic- or abiotic-stress resistance.
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Maolin Shi,Hongyou Li,Xiaomei Liu 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.10
This study aims to propose a Multidisciplinary design optimization (MDO) approach for dental implant based on Finite element method (FEM), surrogate model and a new MDO algorithm. FEM is used to calculate the stress at the implant-bone interface first. Two surrogate models, Support vector regression (SVR) and Kriging (KRG) are built to replace FEM in the following MDO of dental implant, and their verifications indicate their accuracies. A new multidisciplinary design optimization algorithm, named as Homogenizationtarget-values MDO algorithm (HTV-MDO), is established and first tested by a numerical example to demonstrate its effectiveness. After that, it is applied to the MDO of dental implant based on the SVM and KRG. The results indicate that the new MDO approach proposed in this study can effectively deal with the MDO of dental implant. The stress is reduced greatly with other characteristics of dental implant (contact area and volume of implant in this study) optimizing or slightly deteriorating. This approach can be expanded to other MDO of different bio-implants.
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