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| 1 | Coexpression network analysis reveals an MYB transcriptional activator involved in capsaicinoid biosynthesis in hot peppers显示文摘Plant biosynthesis involves numerous specialized metabolites with diverse chemical natures and biological activities.The biosynthesis of metabolites often exclusively occurs in response to tissue-specific combinatorial developmental cues that are controlled at the transcriptional level.Capsaicinoids are a group of specialized metabolites that confer a pungent flavor to pepper fruits.Capsaicinoid biosynthesis occurs in the fruit placenta and combines its developmental cues.Although the capsaicinoid biosynthetic pathway has been largely characterized,the regulatory mechanisms that control capsaicinoid metabolism have not been fully elucidated.In this study,we combined fruit placenta transcriptome data with weighted gene coexpression network analysis(WGCNA)to generate coexpression networks.A capsaicinoid-related gene module was identified in which the MYB transcription factor CaMYB48 plays a critical role in regulating capsaicinoid in pepper.Capsaicinoid biosynthetic gene(CBG)and CaMYB48 expression primarily occurs in the placenta and is consistent with capsaicinoid biosynthesis.CaMYB48 encodes a nucleus-localized protein that primarily functions as a transcriptional activator through its C-terminal activation motif.CaMYB48 regulates capsaicinoid biosynthesis by directly regulating the expression of CBGs,including AT3a and KasIa.Taken together,the results of this study indicate ways to generate robust networks optimized for the mining of CBG-related regulators,establishing a foundation for future research elucidating capsaicinoid regulation. | Binmei Sun Xin Zhou Changming Chen Chengjie Chen Kunhao Chen Muxi Chen Shaoqun Liu Guoju Chen Bihao Cao Fanrong Cao Jianjun Lei Zhangsheng Zhu | 2020 | Horticulture Research2020，7，1： | 5 |
| 2 | The model of tracing drift targets and its application in the South China Sea显示文摘A Leeway-Trace model was established for the traceability analysis of drifting objects at sea.The model was based on the Leeway model which is a Monte Carlo-based ensemble trajectory model,and a method of realistic traceability analysis was proposed in this study by using virtual spatiotemporal drift trajectory prediction.Here,measured data from a drifting buoy observation experiment in the northern South China Sea in April 2019,combined with surface current data obtained from the finite volume community ocean model(FVCOM),were used for the traceability analysis of humanoid buoys.The results were basically consistent with the observations,and the assimilation of measured current data can significantly improve the accuracy of the traceability analysis.Several sensitive experiments were designed to discuss the effects of wind and tide on the traceability analysis,and their results showed that the wind-driven current and the wind-induced leeway drift are both important to the traceability analysis.The effect of tidal currents on traceability could not be ignored even though they were much weaker than the residual currents in the experimental area of the northern South China Sea. | Yang Chen Shouxian Zhu Wenjing Zhang Zirui Zhu Muxi Bao | 2022 | Acta Oceanologica Sinica2022，41，4： | 2 |
| 3 | BUB1B and circBUB1B_544aa aggravate multiple myeloma malignancy through evoking chromosomal instability显示文摘Multiple myeloma(MM)is an incurable plasma cell malignancy in the bone marrow characterized by chromosome instability(CIN),which contributes to the acquisition of heterogeneity,along with MM progression,drug resistance,and relapse.In this study,we elucidated that the expression of BUB1B increased strikingly in MM patients and was closely correlated with poor outcomes.Overexpression of BUB1B facilitated cellular proliferation and induced drug resistance in vitro and in vivo,while genetic targeting BUB1B abrogated this effect.Mechanistic studies unveiled that enforced expression of BUB1B evoked CIN resulting in MM poor outcomes mainly through phosphorylating CEP170.Interestingly,we discovered the existence of circBUB1B_544aa containing the kinase catalytic center of BUB1B,which was translated by a circular RNA of BUB1B.The circBUB1B_544aa elevated in MM peripheral blood samples was closely associated with MM poor outcomes and played a synergistic effect with BUB1B on evoking CIN.In addition,MM cells could secrete circBUB1B_544aa and interfere the MM microenvironmental cells in the same manner as BUB1B full-length protein.Intriguingly,BUB1B siRNA,targeting the kinase catalytic center of both BUB1B and circBUB1B_544aa,significantly inhibited MM malignancy in vitro and in vivo.Collectively,BUB1B and circBUB1B_544aa are promising prognostic and therapeutic targets of MM. | Xiaozhu Tang Mengjie guo Pinggang Ding Zhendong Deng Mengying Ke Yuxia Yuan Yanyan Zhou Zigen Lin Muxi Li Chunyan Gu Xiaosong Gu Ye Yang | 2021 | Signal Transduction and Targeted Therapy2021，6，11： | 2 |
| 4 | Validating analysis on influence of vehicle structure in considering crash compatibility 显示文摘 | Lei Zhengbao He Ru Lei Muxi | 2012 | Applied Mechanics and Materials2012，，209210211： | 1 |
| 5 | Biotechnol显示文摘 | Quevedo M Guynot E Muxi L Denit rifying potentialof methanogenic sludge | | 0，，12： | 1 |
| 6 | Extramedullary acutepromyelocytic leukemia显示文摘 | Wiernik PH De Bellis R Muxi P | 1996 | Cancer1996，78，12： | 1 |
| 7 | Denitrifying Potential of Methanogenic Sludge显示文摘 | Quevedo M Guynot E Muxi L | 1996 | Biotechnology Letters1996，18，12： | 1 |
| 8 | Radioimmunoguided surgery of colorectal carcinoma with an 111 In-labelled anti-TAG 72 monoclonal antibody显示文摘 | Muxi A Pons F Vidal-Sicurt S | 1999 | Nucl Med Commun1999，20，2： | 1 |
| 9 | Post-treatment of a slaughterhouse wastewater:stability of the microbial community of a sequencing batch reactor operated under oxygen limited conditions显示文摘 | Cabezas A Draper P Muxi L | 2006 | Water Science and Technology2006，54，2： | 1 |
| 10 | Post-treatment of a slaughterhouse wastewater: stability of the microbial community of a sequencing batch reactor operated under oxygen limited conditions 显示文摘 | Cabezas A Draper P Muxi L | 2006 | Water Sci Technol2006，54，2： | 1 |
| 11 | Post-treatment of a slaughterhouse wastewater: stability of the microbial community of a sequencing batch reactor operated under oxygen limited conditions 显示文摘 | Cabezas A Draper P Muxi L | 2006 | Water Science and Technology2006，54，2： | 1 |
| 12 | Community analysis of a denitrifying reactor treatinglandfill leachate 显示文摘 | Etchebehere C Errazquin M I Dabert P Muxi L | 2002 | FEMS Microbiology Ecology2002，40，： | 1 |
| 13 | TheeffectofPA-MSHAvaccineonimmunocompetenceofmiceimmunocytes显示文摘 | ZHANGMC MUXY | | Shanghai上海免疫学杂志0，，： | 1 |
| 14 | Radioimmunoguided surgery of colorectal carcinoma with an 111In-labelled anti-TAG72 monoclonal antibody显示文摘 | MUXI A PONS F VIDAL-SICURT S | 1999 | Nucl Med Commun1999，20，2： | 1 |
| 15 | Denitrifying po- tential of methanogenic sludge 显示文摘 | QUEVEDO M GUYNOT E MUXI L | 1996 | Biotechnology Let- ters1996，18，12： | 1 |
| 16 | Post-treatment of a slaughterhouse waste water: stability of the microbial community of a sequencing batch reactor operated under oxygen limited condition显示文摘 | CABEZAS A DRAPER P MUXI L | 2006 | Water Science and Technology2006，54，2： | 1 |
| 17 | Denitrifying potential of methanogenic sludge 显示文摘 | Quevedo M Guynot E Muxi L | 1996 | Biotechnol Lett1996，18，12： | 1 |
| 18 | A Neural Regression Model for Predicting Thermal Conductivity of CNT Nanofluids with Multiple Base Fluids显示文摘High thermal conductivity of carbon nanotube nanofluids(k_(nf))has received great attention.However,the current researches are limited by experimental conditions and lack a comprehensive understanding of k_(nf) variation law.In view of proposition of data-driven methods in recent years,using experimental data to drive prediction is an effective way to obtain k_(nf),which could clarify variation law of k_(nf) and thus greatly save experimental and time costs.This work proposed a neural regression model for predicting k_(nf).It took into account four influencing factors,including carbon nanotube diameter,volume fraction,temperature and base fluid thermal conductivity(k_(f)).Where,four conventional fluids with k_(f),including R113,water,ethylene glycol and ethylene glycol-water mixed liquid were considered as base fluid considers.By training this model,it can predict k_(nf) with different factors.Also,change law of four influencing factors considered on the k_(nf) enhancement has discussed and the correlation between different influencing factors and k_(nf) enhancement is presented.Finally,compared with nine common machine learning methods,the proposed neural regression model shown the highest accuracy among these. | ZOU Hanying CHEN Cheng ZHA Muxi ZHOU Kangneng XIAO Ruoxiu FENG Yanhui QIU Lin ZHANG Xinxin WANG Zhiliang | 2021 | Journal of Thermal Science2021，30，6： | 1 |
| 19 | Radioimmunoguided surgery of colorectal carcinoma with an II1 In-labelled anti- TAG72 monoclonal antibody 显示文摘 | Muxi A Pons F Vidal-Sicart S | 1999 | Nucl Med Commun1999，20，2： | 1 |
| 20 | Coalescence of Al_(0.3)CoCrFeNi polycrystalline high-entropy alloy in hot-pressed sintering: a molecular dynamics and phase- field study显示文摘Existing hot sintering models based on molecular dynamics focus on single-crystal alloys.This work proposes a new multiparticle model based on molecular dynamics to investigate coalescence kinetics during the hot-pressed sintering of a polycrystalline Al_(0.3)CoCrFeNi high-entropy alloy.The accuracy and effectiveness of the multiparticle model are verified by a phase-field model.Using this model,it is found that when the particle contact zones undergo pressure-induced evolution into exponential power creep zones,the occurrences of phenomena,such as necking,pore formation/filling,dislocation accumulation/decomposition,and particle rotation/rearrangement are accelerated.Based on tensile test results,Young’s modulus of the as-sintered Al_(0.3)CoCrFeNi high-entropy alloy is calculated to be 214.11±1.03 GPa,which deviates only 0.82%from the experimental value,thus further validating the feasibility and accuracy of the multiparticle model. | Qingwei Guo Hua Hou Kaile Wang Muxi Li Peter K.Liaw Yuhong Zhao | 2023 | npj Computational Materials2023，，1： | 0 |
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