6,350 Works

Additional file 4 of Discovery of an autophagy inducer J3 to lower mutant huntingtin and alleviate Huntington’s disease-related phenotype

Jiahui Long, Xia Luo, Dongmei Fang, Haikun Song, Weibin Fang, Hao Shan, Peiqing Liu, Boxun Lu, Xiao-Ming Yin, Liang Hong & Min Li
Additional file 4: Figure S4. (A-C) CFP-103Q-HeLa cells were treated with 20 μM of J3 for 48 h. 10 μM of CHX was added at the last 6 h. The protein expression of mHTT (anti-GFP, sc-9996) was detected by western blot (A), and the quantification of insoluble mHTT (B) and soluble mHTT (C) was analyzed. (D-F) CFP-103Q-HeLa cells were treated with 20 μM of J3 for 48 h. 40 μM of CQ was added at...

Additional file 4 of Discovery of an autophagy inducer J3 to lower mutant huntingtin and alleviate Huntington’s disease-related phenotype

Jiahui Long, Xia Luo, Dongmei Fang, Haikun Song, Weibin Fang, Hao Shan, Peiqing Liu, Boxun Lu, Xiao-Ming Yin, Liang Hong & Min Li
Additional file 4: Figure S4. (A-C) CFP-103Q-HeLa cells were treated with 20 μM of J3 for 48 h. 10 μM of CHX was added at the last 6 h. The protein expression of mHTT (anti-GFP, sc-9996) was detected by western blot (A), and the quantification of insoluble mHTT (B) and soluble mHTT (C) was analyzed. (D-F) CFP-103Q-HeLa cells were treated with 20 μM of J3 for 48 h. 40 μM of CQ was added at...

Effect of solvent extraction on the composition of coal tar residues and their pyrolysis characteristics

Zhonghua Lu, Shun Guo, Jun Shen, Yugao Wang, Yanxia Niu, Gang Liu & Qingtao Sheng
A large amount of coal tar residues (CTRs) produced in the coal coking or gasification industry has not been effectively utilized in China. In this study, CTRs are extracted by 12 organic solvents. Detailed investigations are carried out via ultimate analysis, Fourier transform infrared spectroscopy (FTIR) and thermogravimetry (TG) analyzer. The pyrolysis process of CTRs and their extraction residues (RCTRs) can be accurately fitted by Coast-Redfern integral model. The results indicate that the reaction order...

Diversification of phenolic glucosides by two UDP-glucosyltransferases featuring complementary regioselectivity

Fei Guo, Xingwang Zhang, Cai You, Chengjie Zhang, Fengwei Li, Nan Li, Yuwei Xia, Mingyu Liu, Zetian Qiu, Xianliang Zheng, Li Ma, Gang Zhang, Lianzhong Luo, Fei Cao, Yingang Feng, Guang-Rong Zhao, Wei Zhang, Shengying Li & Lei Du
Abstract Background Glucoside natural products have been showing great medicinal values and potentials. However, the production of glucosides by plant extraction, chemical synthesis, and traditional biotransformation is insufficient to meet the fast-growing pharmaceutical demands. Microbial synthetic biology offers promising strategies for synthesis and diversification of plant glycosides. Results In this study, the two efficient UDP-glucosyltransferases (UGTs) (UGT85A1 and RrUGT3) of plant origin, that are capable of recognizing phenolic aglycons, are characterized in vitro. The two...

Diversification of phenolic glucosides by two UDP-glucosyltransferases featuring complementary regioselectivity

Fei Guo, Xingwang Zhang, Cai You, Chengjie Zhang, Fengwei Li, Nan Li, Yuwei Xia, Mingyu Liu, Zetian Qiu, Xianliang Zheng, Li Ma, Gang Zhang, Lianzhong Luo, Fei Cao, Yingang Feng, Guang-Rong Zhao, Wei Zhang, Shengying Li & Lei Du
Abstract Background Glucoside natural products have been showing great medicinal values and potentials. However, the production of glucosides by plant extraction, chemical synthesis, and traditional biotransformation is insufficient to meet the fast-growing pharmaceutical demands. Microbial synthetic biology offers promising strategies for synthesis and diversification of plant glycosides. Results In this study, the two efficient UDP-glucosyltransferases (UGTs) (UGT85A1 and RrUGT3) of plant origin, that are capable of recognizing phenolic aglycons, are characterized in vitro. The two...

Additional file 1 of Using a mixed method to identify communication skills training priorities for Chinese general practitioners in diabetes care

Mi Yao, Gang Yuan, Kai Lin, Lijuan Liu, Hao Tang, Jieying Xie, Xinxin Ji, Rongxin Wang, Binkai Li, Jiajia Hao, Huichang Qiu, Dongying Zhang, Hai Li, Shamil Haroon, Dawn Jackson, Wei Chen, Kar Keung Cheng & Richard Lehman
Additional file 1:

Additional file 1 of AGuIX nanoparticles enhance ionizing radiation-induced ferroptosis on tumor cells by targeting the NRF2-GPX4 signaling pathway

Hao Sun, Hui Cai, Chang Xu, Hezheng Zhai, François Lux, Yi Xie, Li Feng, Liqing Du, Yang Liu, Xiaohui Sun, Qin Wang, Huijuan Song, Ningning He, Manman Zhang, Kaihua Ji, Jinhan Wang, Yeqing Gu, Géraldine Leduc, Tristan Doussineau, Yan Wang, Qiang Liu & Olivier Tillement
Additional file 1: Figure S1. (A) Representative images of dissected tumors across the different treatment groups. (B-C) PCNA protein expression levels were selected as indices of tumor tissue proliferation for immunohistochemical detection and analysis. (D-E) TUNEL experiment of tumor tissues in different treatment groups. Figure S2. Hematoxylin and eosin staining tests (Figure S2A) and serum biochemical indices, including albumin, alanine aminotransferase, creatinine, and urea levels,(Figure S2B-E) showed that there was no significant histological evidence of...

Additional file 1 of Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease

Qian Zhu, Min Qin, Zixian Wang, Yonglin Wu, Xiaoping Chen, Chen Liu, Qilin Ma, Yibin Liu, Weihua Lai, Hui Chen, Jingjing Cai, Yemao Liu, Fang Lei, Bin Zhang, Shuyao Zhang, Guodong He, Hanping Li, Mingliang Zhang, Hui Zheng, Jiyan Chen, Min Huang & Shilong Zhong
Additional file 1: Table S1. Baseline characteristics on death and MACE risks. Table S2. Baseline characteristics on LVEF and LVMI. Table S3. Relationship between metabolites and death risk. Table S4. Relationship between metabolites and MACE risk. Table S5. Multivariate Cox proportional hazards model for clinical outcomes. Table S6. Spearman correlation analysis between clinical factors and those metabolites associated with death risk. Table S7. Spearman correlation analysis between clinical factors and those metabolites associated with death...

Additional file 5 of Combining QTL mapping and RNA-Seq Unravels candidate genes for Alfalfa (Medicago sativa L.) leaf development

Xueqian Jiang, Xijiang Yang, Fan Zhang, Tianhui Yang, Changfu Yang, Fei He, Ting Gao, Chuan Wang, Qingchuan Yang, Zhen Wang & Junmei Kang
Additional file 5: Table S3. List of 2,061 up-regulated genes (‘sativa’ Vs ‘falcata’).

Additional file 6 of Combining QTL mapping and RNA-Seq Unravels candidate genes for Alfalfa (Medicago sativa L.) leaf development

Xueqian Jiang, Xijiang Yang, Fan Zhang, Tianhui Yang, Changfu Yang, Fei He, Ting Gao, Chuan Wang, Qingchuan Yang, Zhen Wang & Junmei Kang
Additional file 6: Table S4. List of 1,709 down-regulated genes (‘sativa’ Vs ‘falcata’).

Additional file 6 of Combining QTL mapping and RNA-Seq Unravels candidate genes for Alfalfa (Medicago sativa L.) leaf development

Xueqian Jiang, Xijiang Yang, Fan Zhang, Tianhui Yang, Changfu Yang, Fei He, Ting Gao, Chuan Wang, Qingchuan Yang, Zhen Wang & Junmei Kang
Additional file 6: Table S4. List of 1,709 down-regulated genes (‘sativa’ Vs ‘falcata’).

Additional file 7 of Combining QTL mapping and RNA-Seq Unravels candidate genes for Alfalfa (Medicago sativa L.) leaf development

Xueqian Jiang, Xijiang Yang, Fan Zhang, Tianhui Yang, Changfu Yang, Fei He, Ting Gao, Chuan Wang, Qingchuan Yang, Zhen Wang & Junmei Kang
Additional file 7: Table S5. The information of the seven candidates.

Additional file 1 of Evaluating the effect of an artificial intelligence system on the anesthesia quality control during gastrointestinal endoscopy with sedation: a randomized controlled trial

Cheng Xu, Yijie Zhu, Lianlian Wu, Honggang Yu, Jun Liu, Fang Zhou, Qiutang Xiong, Shanshan Wang, Shanshan Cui, Xu Huang, Anning Yin, Tingting Xu, Shaoqing Lei & Zhongyuan Xia
Additional file 1.

COMSOL modeling.mph

Jiading Tian, Zehui Wang, Qirong Xiao, Dan Li, Ping Yan & Mali Gong
COMSOL model for the initiation of fiber fuse

Additional file 1 of LncRNA SNHG16 promotes development of oesophageal squamous cell carcinoma by interacting with EIF4A3 and modulating RhoU mRNA stability

Lihua Ren, Xin Fang, Sachin Mulmi Shrestha, Qinghua Ji, Hui Ye, Yan Liang, Yang Liu, Yadong Feng, Jingwu Dong & Ruihua Shi
Additional file 1: Figure S1. EIF4A3 was upregulated in ESCC and promoted ESCC cell proliferation and migration. (A) Relative expression of EIF4A3 in human oesophageal cancer tissues (n = 162) compared with noncancerous tissues (n = 11) and a positive correlation with SNHG16 via the GEPIA database. (B) Western blot analysis of EIF4A3 after si-NC or si-EIF4A3 transfection in ESCC cells. Mock was the blank control group. GAPDH was used as an internal control. CCK-8...

Additional file 11 of The global, regional, and national early-onset colorectal cancer burden and trends from 1990 to 2019: results from the Global Burden of Disease Study 2019

Hongfeng Pan, Zeyi Zhao, Yu Deng, Zhifang Zheng, Ying Huang, Shenghui Huang & Pan Chi
Additional file 11: Table S6. Frontier DALYs, and effective difference by country or territory.

Additional file 1 of The global, regional, and national early-onset colorectal cancer burden and trends from 1990 to 2019: results from the Global Burden of Disease Study 2019

Hongfeng Pan, Zeyi Zhao, Yu Deng, Zhifang Zheng, Ying Huang, Shenghui Huang & Pan Chi
Additional file 1: Figure S1. Age-standardized incidence rate at the global, regional, and national level. (A) Age-standardized incidence s rate of early-onset colorectal cancer globally and for 21 GBD regions by SDI, 1990–2019. (B) Age-standardized incidence rates of early-onset colorectal cancer for 204 countries and territories in 2019. The black line represents the expected age-standardized incidence rate of rheumatic heart disease based solely on SDI. GBD: Global Burden of Diseases, Injuries, and Risk Factors Study;...

Additional file 2 of The global, regional, and national early-onset colorectal cancer burden and trends from 1990 to 2019: results from the Global Burden of Disease Study 2019

Hongfeng Pan, Zeyi Zhao, Yu Deng, Zhifang Zheng, Ying Huang, Shenghui Huang & Pan Chi
Additional file 2: Figure S2. Age-standardized prevalence rate at the global, regional, and national level. (A) Age-standardized prevalence rate of early-onset colorectal cancer globally and for 21 GBD regions by SDI, 1990–2019. (B) Age-standardized prevalence rates of early-onset colorectal cancer for 204 countries and territories in 2019. The black line represents the expected age-standardized prevalence rate of rheumatic heart disease based solely on SDI. GBD: Global Burden of Diseases, Injuries, and Risk Factors Study; SDI:...

Additional file 4 of The global, regional, and national early-onset colorectal cancer burden and trends from 1990 to 2019: results from the Global Burden of Disease Study 2019

Hongfeng Pan, Zeyi Zhao, Yu Deng, Zhifang Zheng, Ying Huang, Shenghui Huang & Pan Chi
Additional file 4: Figure S4. Age-standardized DALYs rate at the global, regional, and national level. (A) Age-standardized DALYs rate of early-onset colorectal cancer globally and for 21 GBD regions by SDI, 1990–2019. (B) Age-standardized DALYs rates of early-onset colorectal cancer for 204 countries and territories in 2019. The black line represents the expected age-standardized DALYs rate of rheumatic heart disease based solely on SDI. GBD: Global Burden of Diseases, Injuries, and Risk Factors Study; SDI:...

sj-doc-1-acr-10.1177_02841851211054191 - Supplemental material for Predictors of sentinel lymph node metastasis in Chinese women with clinical T1-T2 N0 breast cancer and a normal axillary ultrasound

Fenfen Fu, Yonghui Zhang, Jie Sun, Chun Zhang, Dongjie Zhang, Lingduo Xie, Futao Chu, Xue Yu & Yuntao Xie
Supplemental material, sj-doc-1-acr-10.1177_02841851211054191 for Predictors of sentinel lymph node metastasis in Chinese women with clinical T1-T2 N0 breast cancer and a normal axillary ultrasound by Fenfen Fu, Yonghui Zhang, Jie Sun, Chun Zhang, Dongjie Zhang, Lingduo Xie, Futao Chu, Xue Yu and Yuntao Xie in Acta Radiologica

Supplementary document for Theoretical analysis of 60-W solar-pumped single crystal fiber laser - 6067286.pdf

Pengfei Xiang, Lanling Lan, Yan Liu, Hongfei Qi, Yulong Tang & xiuhua ma
supplemental document of the manuscript

Additional file 4 of Functional differentiation determines the molecular basis of the symbiotic lifestyle of Ca. Nanohaloarchaeota

Yuan-Guo Xie, Zhen-Hao Luo, Bao-Zhu Fang, Jian-Yu Jiao, Qi-Jun Xie, Xing-Ru Cao, Yan-Ni Qu, Yan-Lin Qi, Yang-Zhi Rao, Yu-Xian Li, Yong-Hong Liu, Andrew Li, Cale Seymour, Marike Palmer, Brian P. Hedlund, Wen-Jun Li & Zheng-Shuang Hua
Additional file 4. All commands, scripts, and R codes are included.

Association between childhood trauma and medication adherence among patients with major depressive disorder: the moderating role of resilience

Hongqiong Wang, Yuhua Liao, Lan Guo, Huimin Zhang, Yingli Zhang, Wenjian Lai, Kayla M. Teopiz, Weidong Song, Dongjian Zhu, Lingjiang Li, Ciyong Lu, Beifang Fan & Roger S. McIntyre
Abstract Background Suboptimal medication adherence is a major reason for failure in the management of major depressive disorder (MDD), childhood trauma might be an essential risk factor of suboptimal medication adherence. This study aimed to comprehensively explore the associations between different types of childhood trauma and medication adherence among patients with MDD, and to test whether resilience has moderating effects on the foregoing associations. Methods Participants were from the Depression Cohort in China (ChiCTR registry...

Additional file 1 of Association between childhood trauma and medication adherence among patients with major depressive disorder: the moderating role of resilience

Hongqiong Wang, Yuhua Liao, Lan Guo, Huimin Zhang, Yingli Zhang, Wenjian Lai, Kayla M. Teopiz, Weidong Song, Dongjian Zhu, Lingjiang Li, Ciyong Lu, Beifang Fan & Roger S. McIntyre
Additional file 1: eTable 1. Baseline sample characteristics between eligible and ineligible participants. eTable 2. Frequencies of responses on the MARS among the suboptimal adherence group (n=234). eFigure 1. The distribution of suboptimal adherence in the low, medium and high resilience group.

Additional file 1 of The bacterial consortia promote plant growth and secondary metabolite accumulation in Astragalus mongholicus under drought stress

Yixian Lin, Hui Zhang, Peirong Li, Juan Jin & Zhefei Li
Supplementary Material 1

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