3,927 results on '"Luo, R"'
Search Results
102. Enhanced laser-energy coupling with small-spot distributed phase plates (SG5-650) in OMEGA DT cryogenic target implosions
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Theobald, W., primary, Cao, D., additional, Shah, R. C., additional, Thomas, C. A., additional, Igumenshchev, I. V., additional, Bauer, K. A., additional, Betti, R., additional, Bonino, M. J., additional, Campbell, E. M., additional, Christopherson, A. R., additional, Churnetski, K., additional, Edgell, D. H., additional, Forrest, C. J., additional, Frenje, J. A., additional, Gatu Johnson, M., additional, Glebov, V. Yu., additional, Goncharov, V. N., additional, Gopalaswamy, V., additional, Harding, D. R., additional, Hu, S. X., additional, Ivancic, S. T., additional, Jacobs-Perkins, D. W., additional, Janezic, R. T., additional, Joshi, T., additional, Knauer, J. P., additional, Lees, A., additional, Luo, R. W., additional, Mannion, O. M., additional, Marshall, F. J., additional, Mohamed, Z. L., additional, Morse, S. F. B., additional, Patel, D., additional, Peebles, J. L., additional, Petrasso, R. D., additional, Radha, P. B., additional, Rinderknecht, H. G., additional, Rosenberg, M. J., additional, Sampat, S., additional, Sangster, T. C., additional, Shmayda, W. T., additional, Shuldberg, C. M., additional, Shvydky, A., additional, Sorce, C., additional, Stoeckl, C., additional, Wittman, M. D., additional, and Regan, S. P., additional
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- 2022
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103. Synthesis, X-ray structure analysis, and vibrational spectral studies of 1-(3-((6-bromopyrido[2,3-d]pyrimidin-4-yl)oxy)phenyl)- 3-cyclopentylurea
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Luo, R.-S., primary, Mao, S.-N., additional, Liu, C.-J., additional, Zhou, Z.-X., additional, and Huang, Z.-Y., additional
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- 2022
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104. Idecabtagene vicleucel for relapsed/refractory multiple myeloma: a review of recent advances
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Tu, W., primary, Xiao, Y., additional, Wang, Y., additional, Luo, R., additional, and Chen, Z.-S., additional
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- 2022
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105. Reinvestigation of the behavior of viscoelastic damping
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Luo, R.
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- 2014
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106. Effects of High-Dose Rosuvastatin on Ventricular Remodelling and Cardiac Function in ST-Segment Elevation Myocardial Infarction
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Luo R, Sun X, Shen F, Hong B, and Wang Z
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st elevation myocardial infarction ,lcsh:Therapeutics. Pharmacology ,blood lipids ,lcsh:RM1-950 ,nutritional and metabolic diseases ,myocardial fibrosis ,inflammatory factor ,ventricularremodelling ,rosuvastatin - Abstract
Rong Luo ,* Xiaochen Sun ,* Feiyan Shen, Bin Hong, Zilong Wang Department of Cardiology, Qingpu Medical Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zilong Wang Email wangthinker123@outlook.comObjective: To investigate the effects of high-dose rosuvastatin on ventricular remodelling and cardiac function in ST-segment elevation myocardial infarction (STEMI).Materials and Methods: From January 2017 to March 2019, the clinical data of 93 patients with STEMI were collected and analysed, with 46 cases in the conventional-dose group (rosuvastatin, 10 mg/d) and 47 cases in the high-dose group (rosuvastatin, 20 mg/d). Blood lipid (TC, TG, LDL-C and HDL-C), serum inflammatory markers (hs-CRP, IL-6, TNF-α and ICAM-1), ventricular remodelling markers (NT-pro BNP, MMP-9, TIMP-4 and Gal-3) and indicators of cardiac function (LVESD, LVESD, LVESV, LVEDV, IVST and LVEF) were collected from all patients at the time of admission and 8 weeks after rosuvastatin treatment.Results: After treatment with rosuvastatin for 8 weeks, compared with those in conventional-dose group, the levels of TC, TG, LDL-C, hs-CRP, IL-6, TNF-α, ICAM-1, NT-pro BNP, MMP-9 and Gal-3 in the high-dose group decreased significantly (P< 0.05), while the increase of HDL-C and TIMP-4 levels was more obvious (P< 0.05) than that in the conventional-dose group. Moreover, LVEF was significantly higher (P< 0.05) and LVESD, LVESD, LVESV, LVEDV and IVST were significantly lower (P< 0.05) after treatment than before treatment in both groups. The improvement of cardiac ultrasound results in the high-dose group was more significant than that in the conventional-dose group (P< 0.05).Conclusion: This study suggests that high-dose rosuvastatin was better than conventional-dose rosuvastatin for improving blood lipid metabolism, reducing the inflammatory response, and preventing and treating ventricular remodelling and myocardial fibrosis, indicating that high-dose rosuvastatin had stronger therapeutic effect on STEMI than conventional-dose rosuvastatin.Keywords: rosuvastatin, ST elevation myocardial infarction, blood lipids, inflammatory factor, ventricular remodelling, myocardial fibrosis
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- 2020
107. miR-34c Targets MET to Improve the Anti-Tumor Effect of Cisplatin on Ovarian Cancer
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Yang S, Li Z, and Luo R
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ovarian cancer ,mir-34c ,met ,cisplatin ,bad ,lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,lcsh:RC254-282 - Abstract
Shiying Yang,1 Zhen Li,2 Rui Luo3 1Department of Gynecology and Obstetrics, Rizhao People’s Hospital, Rizhao City 276800, Shandong Province, People’s Republic of China; 2Reproductive Medicine Center, Qingdao Women and Children Hospital, Qingdao City 266011, Shandong Province, People’s Republic of China; 3Department of Gynecology, Linyi People’s Hospital, Linyi City 276000, Shandong Province, People’s Republic of ChinaCorrespondence: Rui Luo Email luorui5823@163.comBackground: Cisplatin is a commonly used drug for the treatment of various types of malignant cancers, including ovarian cancer. However, resistance to cisplatin is still a considerable obstacle to achieve a satisfactory therapeutic effect. The purpose of this study is to develop a strategy to sensitize ovarian cancer cells to cisplatin-induced cytotoxicity.Methods: miR-34c levels in ovarian cancer tissues and cell lines were tested by qRT-PCR analysis. In vitro assays, the effect of miR-34c on cisplatin was evaluated by using MTT. Expression of MET and phosphorylation of PI3K and AKT were tested by Western blot assays. Conjugation with Bad and Bcl-xl was evaluated through immunoprecipitation. Flow cytometry analysis was performed to measure the apoptotic rate of ovarian cancer cells.Results: Downregulation of miR-34c was observed in ovarian cancer tissues and cell lines. However, miR-34c overexpression was found to sensitize ovarian cancer cells to cisplatin treatment in vitro and in vivo. Mechanically, we found that miR-34c targeted the MET gene, thereby inhibiting the phosphorylation of PI3K and AKT to activate Bad. As a result, miR-34c reduced resistance of ovarian cancer cells to cisplatin-induced apoptosis.Conclusion: miR-34c/MET axis promotes cisplatin-induced cytotoxicity against ovarian cancer by targeting the MET/PI3K/AKT/Bad pathway.Keywords: ovarian cancer, miR-34c, cisplatin, MET, Bad
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- 2020
108. The Influence of Check Valve with a Filter on the Performance of Pulse Tube Refrigerators
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Zhou, Y., Ju, Y. L., Wang, C., Luo, R. C., Wang, J. J., and Kittel, Peter, editor
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- 1996
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109. Design Principles for Engineering Conducting Discotic Liquid Crystals
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Boden, N., Bushby, R. J., Clements, J., Luo, R., Donovan, K. J., Becher, Jan, editor, and Schaumburg, Kjeld, editor
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- 1995
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110. Shear Criterion and Experimental Verification for Antivibration Fatigue Design
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Luo, R. K., primary
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- 2021
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111. Comparison of the Potency of Clinically Relevant Platinum Derivatives to Enhance the Abscopal Effect
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Luo, R., primary, Onyshchenko, K., additional, Wang, L., additional, Firat, E., additional, and Niedermann, G., additional
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- 2021
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112. Model Predictive Power Control of Brushless Doubly-Fed Induction Generator Considering Saturation Effect
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Wei, X, Xu, L, Luo, R, Cheng, M, and Zhu, J
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Electrical & Electronic Engineering - Abstract
This paper proposes a model predictive power control strategy based on a dynamic model and analysis of the power distribution, considering the effects of magnetic saturation of the brushless doubly-fed induction generator (BDFIG). This strategy can realize accurate power control, so as to assure the quality of control winding current and reduce the switching frequency by estimating the magnetic inductance based on the saturation effect and correcting the inductance parameters input to the controller each period. Simulation and experiments were conducted on the BDFIG control system to identify the factors influencing the saturation effect, and validate the effectiveness of the proposed control strategy.
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- 2021
113. Finite-time modified projective synchronization between two different chaotic systems with parameter and model uncertainties and external disturbances via sliding control
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Luo, R Z and Wang, Y L
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- 2014
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114. Regulation of MEIS1 by distal enhancer elements in acute leukemia
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Wang, Q-f, Li, Y-j, Dong, J-f, Li, B, Kaberlein, J J, Zhang, L, Arimura, F E, Luo, R T, Ni, J, He, F, Wu, J, Mattison, R, Zhou, J, Wang, C-z, Prabhakar, S, Nobrega, M A, and Thirman, M J
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- 2014
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115. Tumorablative haploidentical hematopoietic cell transplantation for treatment of hematologic malignancy in children
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Luo, R M, Da, W M, Zhang, X M, Du, Z L, Si, Y J, Wang, Y, Yue, Y, Chen, W, Hu, B, Xing, G S, and Feng, Z C
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- 2016
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116. Mechanistic Studies in Organo-Metallic Electrochemistry. The Role of Computer Based Techniques & Simulation
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Taylor, N., Boddington, T., Halford-Maw, P., Luo, R., Mills, D., Pombeiro, A. J. L., editor, and McCleverty, J. A., editor
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- 1993
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117. Molecules with Identical Electroactive Centres as a Probe for Dielectric Properties of Electrolytes
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Taylor, N., Boddington, T., Dobson, I., Gill, B., Luo, R., Shaw, B., Pombeiro, A. J. L., editor, and McCleverty, J. A., editor
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- 1993
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118. List of contributors
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Audo, M., primary, Beiswenger, J., additional, Bhasin, A., additional, Branthaver, J.F., additional, Cebon, D., additional, Chailleux, E., additional, Cheung, C.Y., additional, Cookman, A., additional, Darabi, M.K., additional, Di Benedetto, H., additional, Goyer, S., additional, Hernando, D., additional, Huang, S.-C., additional, James, A., additional, Kringos, N., additional, Little, D.N., additional, Luo, R., additional, Luo, X., additional, Lytton, R.L., additional, Marzouk, O., additional, Mohajeri, M., additional, Molenaar, A.A.A., additional, Olard, F., additional, Pauli, A.T., additional, Pouget, S., additional, Queffelec, C., additional, Roque, R., additional, Sauzeat, C., additional, Southern, M., additional, Takamura, K., additional, Underwood, B.S., additional, Van de Ven, M.F.C., additional, Varveri, A., additional, Grimes, R. Will, additional, Zhang, Y., additional, Zhu, J., additional, and Zou, J., additional
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- 2015
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119. The fatigue cracking of asphalt mixtures in tension and compression
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Lytton, R.L., primary, Zhang, Y., additional, Luo, X., additional, and Luo, R., additional
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- 2015
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120. 1555 Comparison of Face-To-Face Versus Online Delivery of a Preparatory Course for First Year Clinical Students
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Abdulhussein, D, primary, Luo, R, additional, Abou Sherif, S, additional, Aseem, R, additional, and Pawa, N, additional
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- 2021
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121. “WHAT IS OUV” REVISITED: A COMPUTATIONAL INTERPRETATION ON THE STATEMENTS OF OUTSTANDING UNIVERSAL VALUE
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Bai, N., primary, Nourian, P., additional, Luo, R., additional, and Pereira Roders, A., additional
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- 2021
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122. 81 New candidate fast radio bursts in Parkes archive
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Yang, X, primary, Zhang, S-B, additional, Wang, J-S, additional, Hobbs, G, additional, Sun, T-R, additional, Manchester, R N, additional, Geng, J-J, additional, Russell, C J, additional, Luo, R, additional, Tang, Z-F, additional, Wang, C, additional, Wei, J-J, additional, Staveley-Smith, L, additional, Dai, S, additional, Li, Y, additional, Yang, Y-Y, additional, and Wu, X-F, additional
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- 2021
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123. OC-0184 Comparison of the potency of clinically relevant platinum derivatives to enhance the abscopal effect
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Luo, R., primary, Onyshchenko, K., additional, Wang, L., additional, Firat, E., additional, and Niedermann, G., additional
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- 2021
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124. OC-0183 Hypofractionated radiation synergizes with lenalidomide to induce an abscopal immune response
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Onyshchenko, K., primary, Luo, R., additional, and Niedermann, G., additional
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- 2021
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125. On the Evidence for a Common-spectrum Process in the Search for the Nanohertz Gravitational-wave Background with the Parkes Pulsar Timing Array
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Goncharov, Boris, primary, Shannon, R. M., additional, Reardon, D. J., additional, Hobbs, G., additional, Zic, A., additional, Bailes, M., additional, Curyło, M., additional, Dai, S., additional, Kerr, M., additional, Lower, M. E., additional, Manchester, R. N., additional, Mandow, R., additional, Middleton, H., additional, Miles, M. T., additional, Parthasarathy, A., additional, Thrane, E., additional, Thyagarajan, N., additional, Xue, X., additional, Zhu, X.-J., additional, Cameron, A. D., additional, Feng, Y., additional, Luo, R., additional, Russell, C. J., additional, Sarkissian, J., additional, Spiewak, R., additional, Wang, S., additional, Wang, J. B., additional, Zhang, L., additional, and Zhang, S., additional
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- 2021
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126. Thermal decoupling of deuterium and tritium during the inertial confinement fusion shock-convergence phase
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Kabadi, N. V., primary, Simpson, R., additional, Adrian, P. J., additional, Bose, A., additional, Frenje, J. A., additional, Gatu Johnson, M., additional, Lahmann, B., additional, Li, C. K., additional, Parker, C. E., additional, Séguin, F. H., additional, Sutcliffe, G. D., additional, Petrasso, R. D., additional, Atzeni, S., additional, Eriksson, J., additional, Forrest, C., additional, Fess, S., additional, Glebov, V. Yu, additional, Janezic, R., additional, Mannion, O. M., additional, Rinderknecht, H. G., additional, Rosenberg, M. J., additional, Stoeckl, C., additional, Kagan, G., additional, Hoppe, M., additional, Luo, R., additional, Schoff, M., additional, Shuldberg, C., additional, Sio, H. W., additional, Sanchez, J., additional, Hopkins, L. Berzak, additional, Schlossberg, D., additional, Hahn, K., additional, and Yeamans, C., additional
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- 2021
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127. Development of a 19‐plex short tandem repeat typing system for individual identification and parentage testing of horses (Equus caballus)
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Shang, S., primary, Jiang, R., additional, Luo, R., additional, Jia, S., additional, Irwin, D. M., additional, Wang, Z., additional, and Zhang, S., additional
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- 2021
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128. Traditional Chinese patent medicine for prophylactic treatment of migraine: a meta-analysis of randomized, double-blind, placebo-controlled trials
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Xiao, Y., Yuan, L., Liu, Y., Sun, X., Cheng, J., Wang, T., Li, F., Luo, R., and Zhao, X.
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- 2015
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129. Overexpression of p300 correlates with poor prognosis in patients with cutaneous squamous cell carcinoma
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Chen, M.-K., Cai, M.-Y., Luo, R.-Z., Tian, X., Liao, Q.-M., Zhang, X.-Y., and Han, J.-D.
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- 2015
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130. Analysis of stresses in pipes indented by long external indentations and subsequent stress variations due to pressure fluctuations
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Hyde, T.H., Luo, R., and Becker, A.A.
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- 2009
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131. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)
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Klionsky, DJ, Abdel-Aziz, AK, Abdelfatah, S, Abdellatif, M, Abdoli, A, Abel, S, Abeliovich, H, Abildgaard, MH, Abudu, YP, Acevedo-Arozena, A, Adamopoulos, IE, Adeli, K, Adolph, TE, Adornetto, A, Aflaki, E, Agam, G, Agarwal, A, Aggarwal, BB, Agnello, M, Agostinis, P, Agrewala, JN, Agrotis, A, Aguilar, PV, Ahmad, ST, Ahmed, ZM, Ahumada-Castro, U, Aits, S, Aizawa, S, Akkoc, Y, Akoumianaki, T, Akpinar, HA, Al-Abd, AM, Al-Akra, L, Al-Gharaibeh, A, Alaoui-Jamali, MA, Alberti, S, Alcocer-Gómez, E, Alessandri, C, Ali, M, Alim Al-Bari, MA, Aliwaini, S, Alizadeh, J, Almacellas, E, Almasan, A, Alonso, A, Alonso, GD, Altan-Bonnet, N, Altieri, DC, Álvarez, ÉMC, Alves, S, Alves da Costa, C, Alzaharna, MM, Amadio, M, Amantini, C, Amaral, C, Ambrosio, S, Amer, AO, Ammanathan, V, An, Z, Andersen, SU, Andrabi, SA, Andrade-Silva, M, Andres, AM, Angelini, S, Ann, D, Anozie, UC, Ansari, MY, Antas, P, Antebi, A, Antón, Z, Anwar, T, Apetoh, L, Apostolova, N, Araki, T, Araki, Y, Arasaki, K, Araújo, WL, Araya, J, Arden, C, Arévalo, M-A, Arguelles, S, Arias, E, Arikkath, J, Arimoto, H, Ariosa, AR, Armstrong-James, D, Arnauné-Pelloquin, L, Aroca, A, Arroyo, DS, Arsov, I, Artero, R, Asaro, DML, Aschner, M, Ashrafizadeh, M, Ashur-Fabian, O, Atanasov, AG, Au, AK, Auberger, P, Auner, HW, Aurelian, L, Autelli, R, Avagliano, L, Ávalos, Y, Aveic, S, Aveleira, CA, Avin-Wittenberg, T, Aydin, Y, Ayton, S, Ayyadevara, S, Azzopardi, M, Baba, M, Backer, JM, Backues, SK, Bae, D-H, Bae, O-N, Bae, SH, Baehrecke, EH, Baek, A, Baek, S-H, Baek, SH, Bagetta, G, Bagniewska-Zadworna, A, Bai, H, Bai, J, Bai, X, Bai, Y, Bairagi, N, Baksi, S, Balbi, T, Baldari, CT, Balduini, W, Ballabio, A, Ballester, M, Balazadeh, S, Balzan, R, Bandopadhyay, R, Banerjee, S, Bánréti, Á, Bao, Y, Baptista, MS, Baracca, A, Barbati, C, Bargiela, A, Barilà, D, Barlow, PG, Barmada, SJ, Barreiro, E, Barreto, GE, Bartek, J, Bartel, B, Bartolome, A, Barve, GR, Basagoudanavar, SH, Bassham, DC, Bast, RC, Basu, A, Batoko, H, Batten, I, Baulieu, EE, Baumgarner, BL, Bayry, J, Beale, R, Beau, I, Beaumatin, F, Bechara, LRG, Beck, GR, Beers, MF, Begun, J, Behrends, C, Behrens, GMN, Bei, R, Bejarano, E, Bel, S, Behl, C, Belaid, A, Belgareh-Touzé, N, Bellarosa, C, Belleudi, F, Belló Pérez, M, Bello-Morales, R, Beltran, JSDO, Beltran, S, Benbrook, DM, Bendorius, M, Benitez, BA, Benito-Cuesta, I, Bensalem, J, Berchtold, MW, Berezowska, S, Bergamaschi, D, Bergami, M, Bergmann, A, Berliocchi, L, Berlioz-Torrent, C, Bernard, A, Berthoux, L, Besirli, CG, Besteiro, S, Betin, VM, Beyaert, R, Bezbradica, JS, Bhaskar, K, Bhatia-Kissova, I, Bhattacharya, R, Bhattacharya, S, Bhattacharyya, S, Bhuiyan, MS, Bhutia, SK, Bi, L, Bi, X, Biden, TJ, Bijian, K, Billes, VA, Binart, N, Bincoletto, C, Birgisdottir, AB, Bjorkoy, G, Blanco, G, Blas-Garcia, A, Blasiak, J, Blomgran, R, Blomgren, K, Blum, JS, Boada-Romero, E, Boban, M, Boesze-Battaglia, K, Boeuf, P, Boland, B, Bomont, P, Bonaldo, P, Bonam, SR, Bonfili, L, Bonifacino, JS, Boone, BA, Bootman, MD, Bordi, M, Borner, C, Bornhauser, BC, Borthakur, G, Bosch, J, Bose, S, Botana, LM, Botas, J, Boulanger, CM, Boulton, ME, Bourdenx, M, Bourgeois, B, Bourke, NM, Bousquet, G, Boya, P, Bozhkov, PV, Bozi, LHM, Bozkurt, TO, Brackney, DE, Brandts, CH, Braun, RJ, Braus, GH, Bravo-Sagua, R, Bravo-San Pedro, JM, Brest, P, Bringer, M-A, Briones-Herrera, A, Broaddus, VC, Brodersen, P, Brodsky, JL, Brody, SL, Bronson, PG, Bronstein, JM, Brown, CN, Brown, RE, Brum, PC, Brumell, JH, Brunetti-Pierri, N, Bruno, D, Bryson-Richardson, RJ, Bucci, C, Buchrieser, C, Bueno, M, Buitrago-Molina, LE, Buraschi, S, Buch, S, Buchan, JR, Buckingham, EM, Budak, H, Budini, M, Bultynck, G, Burada, F, Burgoyne, JR, Burón, MI, Bustos, V, Büttner, S, Butturini, E, Byrd, A, Cabas, I, Cabrera-Benitez, S, Cadwell, K, Cai, J, Cai, L, Cai, Q, Cairó, M, Calbet, JA, Caldwell, GA, Caldwell, KA, Call, JA, Calvani, R, Calvo, AC, Calvo-Rubio Barrera, M, Camara, NO, Camonis, JH, Camougrand, N, Campanella, M, Campbell, EM, Campbell-Valois, F-X, Campello, S, Campesi, I, Campos, JC, Camuzard, O, Cancino, J, Candido de Almeida, D, Canesi, L, Caniggia, I, Canonico, B, Cantí, C, Cao, B, Caraglia, M, Caramés, B, Carchman, EH, Cardenal-Muñoz, E, Cardenas, C, Cardenas, L, Cardoso, SM, Carew, JS, Carle, GF, Carleton, G, Carloni, S, Carmona-Gutierrez, D, Carneiro, LA, Carnevali, O, Carosi, JM, Carra, S, Carrier, A, Carrier, L, Carroll, B, Carter, AB, Carvalho, AN, Casanova, M, Casas, C, Casas, J, Cassioli, C, Castillo, EF, Castillo, K, Castillo-Lluva, S, Castoldi, F, Castori, M, Castro, AF, Castro-Caldas, M, Castro-Hernandez, J, Castro-Obregon, S, Catz, SD, Cavadas, C, Cavaliere, F, Cavallini, G, Cavinato, M, Cayuela, ML, Cebollada Rica, P, Cecarini, V, Cecconi, F, Cechowska-Pasko, M, Cenci, S, Ceperuelo-Mallafré, V, Cerqueira, JJ, Cerutti, JM, Cervia, D, Cetintas, VB, Cetrullo, S, Chae, H-J, Chagin, AS, Chai, C-Y, Chakrabarti, G, Chakrabarti, O, Chakraborty, T, Chami, M, Chamilos, G, Chan, DW, Chan, EYW, Chan, ED, Chan, HYE, Chan, HH, Chan, H, Chan, MTV, Chan, YS, Chandra, PK, Chang, C-P, Chang, C, Chang, H-C, Chang, K, Chao, J, Chapman, T, Charlet-Berguerand, N, Chatterjee, S, Chaube, SK, Chaudhary, A, Chauhan, S, Chaum, E, Checler, F, Cheetham, ME, Chen, C-S, Chen, G-C, Chen, J-F, Chen, LL, Chen, L, Chen, M, Chen, M-K, Chen, N, Chen, Q, Chen, R-H, Chen, S, Chen, W, Chen, X-M, Chen, X-W, Chen, X, Chen, Y, Chen, Y-G, Chen, Y-J, Chen, Y-Q, Chen, ZS, Chen, Z, Chen, Z-H, Chen, ZJ, Cheng, H, Cheng, J, Cheng, S-Y, Cheng, W, Cheng, X, Cheng, X-T, Cheng, Y, Cheng, Z, Cheong, H, Cheong, JK, Chernyak, BV, Cherry, S, Cheung, CFR, Cheung, CHA, Cheung, K-H, Chevet, E, Chi, RJ, Chiang, AKS, Chiaradonna, F, Chiarelli, R, Chiariello, M, Chica, N, Chiocca, S, Chiong, M, Chiou, S-H, Chiramel, AI, Chiurchiù, V, Cho, D-H, Choe, S-K, Choi, AMK, Choi, ME, Choudhury, KR, Chow, NS, Chu, CT, Chua, JP, Chua, JJE, Chung, H, Chung, KP, Chung, S, Chung, S-H, Chung, Y-L, Cianfanelli, V, Ciechomska, IA, Cifuentes, M, 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Y, Oshima, S, Rong, Y, Sluimer, JC, Stallings, CL, and Tong, C-K
- Abstract
In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
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- 2021
132. Application advances of artificial intelligence algorithms in dynamics simulation of railway vehicle
- Author
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Tang, Z, Dong, SD, Luo, R, Jiang, T, Deng, R, and Zhang, JJ
- Abstract
The application examples and domestic and foreign literatures using artificial intelligence algorithm for railway vehicle system dynamics simulation were reviewed. The machine learning and deep learning algorithms commonly used in railway vehicle dynamics simulation were summarized, and the application classifications of the 2 algorithms in railway vehicle system dynamics modelling and simulation were concluded and interpreted. According to railway vehicle system dynamics modelling, dynamics performance prediction and dynamics performance optimization, the advantages and limitations of applying artificial intelligence algorithms in force-elements modelling and simulation, track irregularity prediction, running stability prediction, noise prediction, crosswind safety prediction, running safety prediction, suspension optimization, wheel-rail matching optimization, structure optimization, and active and semi-active control were discussed in detail. The problems of applications of artificial intelligence algorithms in railway dynamics simulation were lack of training samples, generalization ability and interpretability. The development directions and key research contents of the interdisciplinary research between artificial intelligence and vehicle system dynamics were given. Research result shows that the hybrid modelling theory combining classical mechanics and artificial intelligence algorithms can be as a key research direction in the future. There is great potential to use the artificial intelligence algorithms to solve the random uncertainty in stochastic dynamics and improve the performance of stochastic dynamics. The artificial intelligence algorithms combinated with optimization algorithms can exploit their advantages in the dynamics performance optimization..
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- 2021
133. Video Assisted Thoracoscopic Surgery (VATS) of Lymphangiomyomatosis (LAM) with Multiple Pulmonary Bullae in a Woman: A Case Report and Literature Review
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Wu L, Liu J, Wu D, Luo R, Hou Q, Xu P, and Li X
- Subjects
medicine.medical_specialty ,business.industry ,medicine.medical_treatment ,Video-assisted thoracoscopic surgery ,medicine ,business ,Surgery - Abstract
Background: Pulmonary lymphangiomyomatosis is relatively rare disease and it is a systemic disease with an unknown etiology. The abnormal proliferation of smooth muscle leads to the obstruction of bronchi, lymphatic vessels and small blood vessels. At present, there are not many clinical reports on the treatment of LAM thoracoscopic surgery. So this article reports a case of LAM in a middle-aged woman and reviews of the relevant literature.
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- 2021
134. Thermal decoupling of deuterium and tritium during the ICF shock-convergence phase
- Author
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Kabadi, N. V., Simpson, R., Adrian, P. J., Bose, A., Frenje, J. A., Gatu Johnson, M., Lahmann, B., C. K., Li, Parker, C. E., Seguin, F. H., Sutclife, G. D., Petrasso, R. D., Atzeni, S., Eriksson, J., Forrest, C., Fess, S., Yu Glebov, V., Janezic, R., Mannion, O., Rinderknecht, H. G., Rosenberg, M. J., Stoeckl, C., Kagan, G., Hoppe, M., Luo, R., Scho, M., Shuldberg, C., Sio, H. W., Sanchez, J., Berzak Hopkins, L., Schlossberg, D., Hahn, K., and Yeamans, C.
- Subjects
inertial confinement fusion ,shock-driven implosion ,Plasma physics - Published
- 2021
135. Support vector machine-based nomogram predicts postoperative distant metastasis for patients with oesophageal squamous cell carcinoma
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Yang, H X, Feng, W, Wei, J C, Zeng, T S, Li, Z D, Zhang, L J, Lin, P, Luo, R Z, He, J H, and Fu, J H
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- 2013
- Full Text
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136. TIP30 loss enhances cytoplasmic and nuclear EGFR signaling and promotes lung adenocarcinogenesis in mice
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Li, A, Zhang, C, Gao, S, Chen, F, Yang, C, Luo, R, and Xiao, H
- Published
- 2013
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137. STIM2 protein regulates Orai1-mediated store-operated Ca2+ entry in cardiomyocytes
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Luo, R., primary, Bedouet, K., additional, Gerbaud, P., additional, Benitah, J.P., additional, and Sabourin, J., additional
- Published
- 2021
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138. Free transverse vibration of rotating blades in a bladed disk assembly
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Luo, R.
- Published
- 2012
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139. Risk of metabolic syndrome in adults exposed to the great Chinese famine during the fetal life and early childhood
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Zheng, X, Wang, Y, Ren, W, Luo, R, Zhang, S, Zhang, J H, and Zeng, Q
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- 2012
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140. ssc-micorRNA-132 suppresses the Clostridium perfringens beta2 toxin induced inflammation and apoptosis of IPEC-J2 cells via targeting DACH1
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Wang P, Xie K, Luo R, Gao X, Yang J, Yan Z, Yang Q, Huang X, Junlian Zhang, Shuangbao Gun, and Wang W
- Subjects
integumentary system ,Toxin ,Cell growth ,Chemistry ,Inflammation ,Clostridium perfringens ,medicine.disease_cause ,Molecular biology ,Virulence factor ,chemistry.chemical_compound ,Apoptosis ,Lactate dehydrogenase ,medicine ,Tumor necrosis factor alpha ,medicine.symptom - Abstract
Clostridium perfringens (C. perfringens) beta2 (CPB2) is the main virulence factor secreted from C. perfringens type C, which caused diarrhea characterized by high mortality in pig, especially newborn piglets. Our previous research found that ssc-miR-132 displayed decreased expression in piglets diarrhea after infected with C. perfringens type C compared with normal piglets. We speculated that ssc-miR-132 may play an important role in the diarrhea. However, the function of ssc-miR-132 in the diarrhea is limited. Thus, we overexpressed and knocked down ssc-miR-132 in intestinal porcine epithelial (IPEC-J2) cells, and then treated the cells with recombinant CPB2 (rCPB2) toxin (20 μg/mL). Our results showed that ssc-miR-132 was significantly decreased after treated with rCPB2 toxin. In addition, overexpression of ssc-miR-132 reduced the expression of lactate dehydrogenase (LDH) and tumor necrosis factor (TNF-α), interleukin-6 (IL-6) and interleukin-8 (IL-8) caused by rCPB2 toxin. The CCK8, Edu and TUNEL staining showed that overexpression of ssc-miR-132 weakened the inhibition of rCPB2 toxin on cell proliferation and reduced the promotion of cell apoptosis; while inhibition of ssc-miR-132 had opposite results. The dual luciferase experiment showed that dachshund family transcription factor 1 (DACH1) was the target gene of ssc-miR-132. Silencing DACH1 was consistent with the results of overexpression of ssc-miR-132, and reversed the apoptosis and inflammation caused by rCPB2 toxin. Overexpression of DACH1 weakened the role of ssc-miR-132 in rCPB2 toxin -induced inflammation and apoptosis. In summary, ssc-miR-132 inhibited rCPB2 toxin-induced apoptosis and inflammation in IPEC-J2 cells by targeting DACH1.
- Published
- 2020
141. An overview of male-sterility systems in pigeonpea [Cajanus cajan (L.) Millsp.]
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Dalvi, V. A., Saxena, K. B., Luo, R. H., and Li, Y. R.
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- 2010
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142. Enhanced expression of FHL2 leads to abnormal myelopoiesis in vivo
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Qian, Z, Mao, L, Fernald, A A, Yu, H, Luo, R, Jiang, Y, Anastasi, J, Valk, P J, Delwel, R, and Le Beau, M M
- Published
- 2009
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143. Fast radio burst detection in the presence of coloured noise
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Zhang, C F, primary, Xu, J W, additional, Men, Y P, additional, Deng, X H, additional, Xu, Heng, additional, Jiang, J C, additional, Wang, B J, additional, Lee, K J, additional, Li, J, additional, Yuan, J P, additional, Liu, Z Y, additional, Huang, Y X, additional, Xu, Y H, additional, Li, Z X, additional, Hao, L F, additional, Luo, J T, additional, Dai, S, additional, Luo, R, additional, Zakie, Hassan, additional, and Ma, Z Y, additional
- Published
- 2021
- Full Text
- View/download PDF
144. OPTIMISATION OF GENERATORS RESTARTING SEQUENCE CONSIDERING OPERATION STATE SWITCH OF PHOTOVOLTAIC AND ENERGY STORAGE SYSTEM
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Li, Q., primary, Wang, C., additional, Luo, R., additional, Wang, J., additional, and xie, Y., additional
- Published
- 2021
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145. THE OPTIMAL DISPATCH OF MOBILE ENERGY STORAGE SYSTEM FOR THE BLACK-START OF TRADITIONAL THERMAL GENERATORS
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Hao, Y., primary, Wang, C., additional, Wang, J., additional, Luo, R., additional, and Xie, Y., additional
- Published
- 2021
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146. Semi-Supervised Neural Architecture Search
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Luo, R., Tan, X., Wang, R., Qin, T., Enhong Chen, and Liu, T. -Y
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Statistics - Machine Learning ,Machine Learning (stat.ML) ,Machine Learning (cs.LG) - Abstract
Neural architecture search (NAS) relies on a good controller to generate better architectures or predict the accuracy of given architectures. However, training the controller requires both abundant and high-quality pairs of architectures and their accuracy, while it is costly to evaluate an architecture and obtain its accuracy. In this paper, we propose SemiNAS, a semi-supervised NAS approach that leverages numerous unlabeled architectures (without evaluation and thus nearly no cost). Specifically, SemiNAS 1) trains an initial accuracy predictor with a small set of architecture-accuracy data pairs; 2) uses the trained accuracy predictor to predict the accuracy of large amount of architectures (without evaluation); and 3) adds the generated data pairs to the original data to further improve the predictor. The trained accuracy predictor can be applied to various NAS algorithms by predicting the accuracy of candidate architectures for them. SemiNAS has two advantages: 1) It reduces the computational cost under the same accuracy guarantee. On NASBench-101 benchmark dataset, it achieves comparable accuracy with gradient-based method while using only 1/7 architecture-accuracy pairs. 2) It achieves higher accuracy under the same computational cost. It achieves 94.02% test accuracy on NASBench-101, outperforming all the baselines when using the same number of architectures. On ImageNet, it achieves 23.5% top-1 error rate (under 600M FLOPS constraint) using 4 GPU-days for search. We further apply it to LJSpeech text to speech task and it achieves 97% intelligibility rate in the low-resource setting and 15% test error rate in the robustness setting, with 9%, 7% improvements over the baseline respectively., Comment: NeurIPS 2020
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- 2020
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147. EE305 Cost Burden of Geographic Atrophy and Visual Impairment/Blindness in US Elderly Patients
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Luo, R., Germain, G., Cheng, W.Y., Mahendran, M., Klimek, J., Sarda, S.P., and Duh, M.S.
- Published
- 2023
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148. E2F–HDAC complexes negatively regulate the tumor suppressor gene ARHI in breast cancer
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Lu, Z, Luo, R Z, Peng, H, Huang, M, Nishmoto, A, Hunt, K K, Helin, K, Liao, W S-L, and Yu, Y
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- 2006
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149. Research on stochastic model and stability analysis of soil-rock mixture slope based on sort judgment
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Luo, R, primary, Zeng, Y, additional, Kong, D, additional, Li, Y, additional, and Wang, Y, additional
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- 2013
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150. Force–deflection analysis of offset indentations on pressurised pipes
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Hyde, T.H., Luo, R., and Becker, A.A.
- Published
- 2007
- Full Text
- View/download PDF
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