Author Report for: Lei TNo contact information in database for Lei T
Ma LJ, Hou XD, Qin XY, He RJ, Yu HN, Hu Q, Guan XQ, Jia SN, Hou J and Ge GB <1 more author(s)> Ma LJ, Hou XD, Qin XY, He RJ, Yu HN, Hu Q, Guan XQ, Jia SN, Hou J, Lei T, Ge GB (- 1) Ref: J Pharm Anal, 12:683, 2022 : PubMed ESTHER: Ma_2022_J.Pharm.Anal_12_683 PubMedSearch: Ma 2022 J.Pharm.Anal 12 683 PubMedID: 36105167 Inhibitor(s) related to this paper: Pentagalloylglucose Abstract Although herbal medicines (HMs) are widely used in the prevention and treatment of obesity and obesity-associated disorders, the key constituents exhibiting anti-obesity activity and their molecular mechanisms are poorly understood. Recently, we assessed the inhibitory potentials of several HMs against human pancreatic lipase (hPL, a key therapeutic target for human obesity), among which the root-extract of Rhodiola crenulata (ERC) showed the most potent anti-hPL activity. In this study, we adopted an integrated strategy, involving bioactivity-guided fractionation techniques, chemical profiling, and biochemical assays, to identify the key anti-hPL constituents in ERC. Nine ERC fractions (retention time = 12.5-35 min), obtained using reverse-phase liquid chromatography, showed strong anti-hPL activity, while the major constituents in these bioactive fractions were subsequently identified using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS/MS). Among the identified ERC constituents, 1,2,3,4,6-penta-O-galloyl-beta-d-glucopyranose (PGG) and catechin gallate (CG) showed the most potent anti-hPL activity, with pIC(50) values of 7.59 +/- 0.03 and 7.68 +/- 0.23, respectively. Further investigations revealed that PGG and CG potently inhibited hPL in a non-competitive manner, with inhibition constant (K (i)) values of 0.012 and 0.082 microM, respectively. Collectively, our integrative analyses enabled us to efficiently identify and characterize the key anti-obesity constituents in ERC, as well as to elucidate their anti-hPL mechanisms. These findings provide convincing evidence in support of the anti-obesity and lipid-lowering properties of ERC. Title: A BCNO QDs-MnO(2) nanosheets based fluorescence off-on-off and colorimetric sensor with smartphone detector for the detection of organophosphorus pesticides Liu F, Lei T, Zhang Y, Wang Y, He Y Ref: Anal Chim Acta, 1184:339026, 2021 : PubMed ESTHER: Liu_2021_Anal.Chim.Acta_1184_339026 PubMedSearch: Liu 2021 Anal.Chim.Acta 1184 339026 PubMedID: 34625266 Abstract In this work, boron carbon oxynitride quantum dots (BCNO QDs) were prepared by a one-step hydrothermal process of ethanolamine and boric acid. BCNO QDs exhibited blue fluorescence with the optimal excitation/emission fluorescence peak at 335 and 420 nm, respectively. As an efficient fluorescence quencher, manganese dioxide (MnO(2)) nanosheets can effectively quench the fluorescence of BCNO QDs via the inner filter effect (IFE). Acetylcholinesterase (AChE) catalyzes the hydrolysis of acetylcholine (ATCh) to produce thiocholine (TCh). TCh can reductively degrade MnO(2) nanosheets to generate Mn(2+), thereby recovering the fluorescence of BCNO QDs. Organophosphorus pesticides (OPs) can inhibit the activity of AChE enzymes, thereby preventing the production of TCh and the decomposition of MnO(2) nanosheets, resulting in the fluorescence "turn-off". Therefore, the concentration of OPs can be detected by measuring the fluorescence intensity change of AChE-ATCh-MnO(2)-BCNO-QDs system. Under optimal experimental conditions, the dynamic detection range of paraoxon is 0.1-250 ng mL(-1), and the detection limit is 0.03 ng mL(-1). Meanwhile, the reaction system also showed concentration-dependent visual color changes from colorless to brownish. Furthermore, we prepared a portable BCNO QDs test paper. By using a smartphone to identify the RGB values of the reaction solution and the corresponding test paper, we carried out the digital image chromaticity analysis, which can shorten the detection time and reduce the detection cost, and provide an effective solution for the rapid detection of OPs on site. Title: The Genomes of Oryza sativa: a history of duplications Yu J, Wang J, Lin W, Li S, Li H, Zhou J, Ni P, Dong W, Hu S and Yang H <88 more author(s)> Yu J, Wang J, Lin W, Li S, Li H, Zhou J, Ni P, Dong W, Hu S, Zeng C, Zhang J, Zhang Y, Li R, Xu Z, Li X, Zheng H, Cong L, Lin L, Yin J, Geng J, Li G, Shi J, Liu J, Lv H, Li J, Deng Y, Ran L, Shi X, Wang X, Wu Q, Li C, Ren X, Li D, Liu D, Zhang X, Ji Z, Zhao W, Sun Y, Zhang Z, Bao J, Han Y, Dong L, Ji J, Chen P, Wu S, Xiao Y, Bu D, Tan J, Yang L, Ye C, Xu J, Zhou Y, Yu Y, Zhang B, Zhuang S, Wei H, Liu B, Lei M, Yu H, Li Y, Xu H, Wei S, He X, Fang L, Huang X, Su Z, Tong W, Tong Z, Ye J, Wang L, Lei T, Chen C, Chen H, Huang H, Zhang F, Li N, Zhao C, Huang Y, Li L, Xi Y, Qi Q, Li W, Hu W, Tian X, Jiao Y, Liang X, Jin J, Gao L, Zheng W, Hao B, Liu S, Wang W, Yuan L, Cao M, McDermott J, Samudrala R, Wong GK, Yang H (- 88) Ref: PLoS Biol, 3:e38, 2005 : PubMed ESTHER: Yu_2005_PLoS.Biol_3_e38 PubMedSearch: Yu 2005 PLoS.Biol 3 e38 PubMedID: 15685292 Gene_locus related to this paper: orysa-Q7XTC5, orysa-Q852M6, orysa-Q8GSE8, orysa-Q9S7P1, orysa-Q9FYP7, orysa-Q5ZBH3, orysa-Q5ZA26, orysa-Q5JLP6, orysa-Q8H5P9, orysa-Q8H5P5, orysa-Q7F1Y5, orysa-Q949C9, orysa-cbp1, orysa-cbp3, orysa-cbpx, orysa-Q33B71, orysa-Q8GSJ3, orysa-LPL1, orysa-Q6YSZ8, orysa-Q8S5X5, orysa-Q8LIG3, orysa-Q6K7F5, orysa-Q7F1B1, orysa-Q8H4S9, orysa-Q69UB1, orysa-Q9FW17, orysa-Q337C3, orysa-Q7F959, orysa-Q84QZ6, orysa-Q84QY7, orysa-Q851E3, orysa-Q6YTH5, orysa-Q0JK71, orysa-Q8S1D9, orysa-Q5N8V4, orysa-Q0JCY4, orysa-Q8GTK2, orysa-B9EWJ8, orysa-Q8H3K6, orysa-Q6ZDG8, orysa-Q6ZDG6, orysa-Q6ZDG5, orysa-Q6ZDG4, orysa-Q5NAI4, orysa-Q658B2, orysa-Q5JMQ8, orysa-Q5QMD9, orysa-Q5N7L1, orysa-Q8RYV9, orysa-Q8H3R3, orysa-Q5SNH3, orysa-Q8W0F0, orysa-pir7a, orysa-pir7b, orysa-q2qlm4, orysa-q2qm78, orysa-q2qm82, orysa-q2qn31, orysa-q2qnj4, orysa-q2qnt9, orysa-q2qur1, orysa-q2qx94, orysa-q2qyi1, orysa-q2qyj1, orysa-q2r051, orysa-q2r077, orysa-q2ram0, orysa-q2rat1, orysa-q2rbb3, orysa-Q4VWY7, orysa-q5na00, orysa-q5nbu1, orysa-Q5QLC0, orysa-q5smv5, orysa-Q5VP27, orysa-q5vrt2, orysa-q5w6c5, orysa-q5z5a3, orysa-q5z9i2, orysa-q5z417, orysa-q5z901, orysa-Q5ZAM8, orysa-Q5ZBI5, orysa-Q5ZCR3, orysa-q6atz0, orysa-q6ave2, orysa-q6f358, orysa-q6h6s1, orysa-q6h7i6, orysa-q6i5q3, orysa-q6i5u7, orysa-q6j657, orysa-q6k3d9, orysa-q6k4q2, orysa-q6k880, orysa-q6l5b6, orysa-Q6L5F5, orysa-q6l556, orysj-q6yse8, orysa-q6yy42, orysa-q6yzk1, orysa-q6z8b1, orysa-q6z995, orysa-q6zc62, orysa-q6zia4, orysa-q6zjq6, orysa-q7x7y5, orysa-Q7XC50, orysa-q7xej4, orysa-q7xem8, orysa-q7xkj9, orysa-q7xr62, orysa-q7xr63, orysa-q7xr64, orysa-q7xsg1, orysa-q7xsq2, orysa-q7xts6, orysa-q7xv53, orysa-Q7XVB5, orysa-Q8L562, orysa-Q8LQS5, orysa-Q8RZ40, orysa-Q8RZ79, orysa-Q8S0U8, orysa-Q8S0V0, orysa-Q8S125, orysa-Q8SAY7, orysa-Q8SAY9, orysa-Q8W3C6, orysa-Q8W3F2, orysa-Q8W3F4, orysa-Q8W3F6, orysa-Q9LHX5, orysa-q33aq0, orysa-q53lh1, orysa-q53m20, orysa-q53nd8, orysa-q60e79, orysa-q60ew8, orysa-q67iz2, orysa-q67iz3, orysa-q67iz7, orysa-q67iz8, orysa-q67j02, orysa-q67j05, orysa-q67j07, orysa-q67j09, orysa-q67j10, orysa-q67tr6, orysa-q67tv0, orysa-q67uz1, orysa-q67v34, orysa-q67wz5, orysa-q69j38, orysa-q69k08, orysa-q69md7, orysa-q69me0, orysa-q69pf3, orysa-q69ti3, orysa-q69xr2, orysa-q69y12, orysa-q69y21, orysa-q75hy2, orysa-q75i01, orysa-Q94JD7, orysa-Q0J0A4, orysa-q651a8, orysa-q651z3, orysa-q652g4, orysa-q688m0, orysa-q688m8, orysa-q688m9, orysa-Q6H8G1, orysi-a2wn01, orysi-a2xc83, orysi-a2yh83, orysi-a2z179, orysi-a2zef2, orysi-b8a7e6, orysi-b8a7e7, orysi-b8bfe5, orysi-b8bhp9, orysj-a3b9l8, orysj-b9eub8, orysj-b9eya5, orysj-b9fi05, orysj-b9fkb0, orysj-b9fn42, orysj-b9gbb7, orysj-cgep, orysj-PLA7, orysj-q0d4u5, orysj-q0djj0, orysj-q0jaf0, orysj-q5jl22, orysj-q5jlw7, orysj-q5z419, orysj-q6h7q9, orysj-q6yvk6, orysj-q6z6i1, orysj-q7f8x1, orysj-q7xcx3, orysj-q9fwm6, orysj-q10j20, orysj-q10ss2, orysj-q69uw6, orysj-q94d71, orysj-q338c0, orysi-b8bly4, orysj-b9gbs4, orysi-a2zb88, orysj-b9gbs1, orysi-b8b698, orysj-pla4, orysj-pla1 Abstract We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000-40,000. Only 2%-3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family. | |||||||
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