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Chen G, Liu T, Luan P, Li N, Sun Y, Tao J, Yan B, Cheng Z. Distribution, migration, and removal of N-containing products during polyurethane pyrolysis: A review. JOURNAL OF HAZARDOUS MATERIALS 2023; 453:131406. [PMID: 37084514 DOI: 10.1016/j.jhazmat.2023.131406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 04/06/2023] [Accepted: 04/11/2023] [Indexed: 05/03/2023]
Abstract
Due to the wide applications of polyurethane (PU), production is constantly increasing, accounting for 8% of produced plastics. PU has been regarded as the 6th most used polymer in the world. Improper disposal of waste PU will result in serious environmental consequences. The pyrolysis of polymers is one of the most commonly used disposal methods, but PU pyrolysis easily produces toxic and harmful nitrogen-containing substances due to its high nitrogen content. This paper reviews the decomposition pathways, kinetic characteristics, and migration of N-element by product distribution during PU pyrolysis. PU ester bonds break to produce isocyanates and alcohols or decarboxylate to produce primary amines, which are then further decomposed to MDI, MAI, and MDA. The nitrogenous products, including NH3, HCN, and benzene derivatives, are released by the breakage of C-C and C-N bonds. The N-element migration mechanism is concluded. Meanwhile, this paper reviews the removal of gaseous pollution from PU pyrolysis and discusses the removal mechanism in depth. Among the catalysts for pollutant removal, CaO has the most superior catalytic performance and can convert fuel-N to N2 by adsorption and dehydrogenation reactions. At the end of the review, new challenges for the utilization and high-quality recycling of PU are presented.
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Chen F, Zhao ZG, Yao YJ, Zhu ZK, Li X, Zheng MX, Zhou X, Peng Y, Wei JF, Wei X, Liang YJ, Chen G, Zhu T, Meng W, Feng Y, Chen M. [Feasibility and safety of transseptal transcatheter mitral valve replacement for severe mitral regurgitation]. ZHONGHUA YI XUE ZA ZHI 2023; 103:1849-1854. [PMID: 37357191 DOI: 10.3760/cma.j.cn112137-20221109-02359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/27/2023]
Abstract
A prospective, single-center, single-arm, and open-design study was performed to evaluate the feasibility and safety of transseptal transcatheter mitral valve replacement in the treatment of severe mitral regurgitation. Patients with symptomatic moderate-severe or severe mitral regurgitation at high-surgical risk and anatomically appropriate for the HighLife transseptal mitral valve replacement (TSMVR) system in West China Hospital, Sichuan University from December 2021 to August 2022 were enrolled. Four patients (1 male and 3 females) with severe mitral regurgitation were included, with a median age of 68.5 (64.0-77.0) years and a median Society of Thoracic Surgeons (STS) score of 8.1% (6.4%-8.9%). Technical success was achieved in all the patients. There was no residual mitral regurgitation, paravalvular leakage, or left ventricular outflow tract obstruction. Three major cardiovascular and cerebrovascular adverse events occurred within 30 days after the procedure, including ventricular tachycardia, iatrogenic atrial septal defect closure, and heart failure readmission. The current study preliminarily demonstrates that transcatheter mitral valve replacement using the HighLife system via the transseptal approach for severe mitral regurgitation is feasible and relatively safe.
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Li N, He X, Ye J, Dai H, Peng W, Cheng Z, Yan B, Chen G, Wang S. H 2O 2 activation and contaminants removal in heterogeneous Fenton-like systems. JOURNAL OF HAZARDOUS MATERIALS 2023; 458:131926. [PMID: 37379591 DOI: 10.1016/j.jhazmat.2023.131926] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/23/2023] [Accepted: 06/22/2023] [Indexed: 06/30/2023]
Abstract
Emerging contaminants can be removed effectively in heterogeneous Fenton-like systems. Currently, catalyst activity and contaminant removal mechanisms have been studied extensively in Fenton-like systems. However, a systematic summary was lacking. This review summarized: 1) The effects of various heterogeneous catalysts on emerging contaminants degradation by activating H2O2; 2) The role of active sites in different catalysts during the activation of H2O2 and their contribution to the generation of active species; 3) The modulation of degradation pathways of emerging contaminants. This paper will help scholars to advance the controlled construction of active sites in heterogeneous Fenton-like systems. Suitable heterogeneous Fenton catalysts can be selected in practical water treatment processes.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner MK, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner UW, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. First Study of Reaction Ξ^{0}n→Ξ^{-}p Using Ξ^{0}-Nucleus Scattering at an Electron-Positron Collider. PHYSICAL REVIEW LETTERS 2023; 130:251902. [PMID: 37418739 DOI: 10.1103/physrevlett.130.251902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/20/2023] [Accepted: 05/25/2023] [Indexed: 07/09/2023]
Abstract
Using (1.0087±0.0044)×10^{10} J/ψ events collected with the BESIII detector at the BEPCII storage ring, the process Ξ^{0}n→Ξ^{-}p is studied, where the Ξ^{0} baryon is produced in the process J/ψ→Ξ^{0}Ξ[over ¯]^{0} and the neutron is a component of the ^{9}Be, ^{12}C, and ^{197}Au nuclei in the beam pipe. A clear signal is observed with a statistical significance of 7.1σ. The cross section of the reaction Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be is determined to be σ(Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be)=(22.1±5.3_{stat}±4.5_{sys}) mb at the Ξ^{0} momentum of 0.818 GeV/c, where the first uncertainty is statistical and the second is systematic. No significant H-dibaryon signal is observed in the Ξ^{-}p final state. This is the first study of hyperon-nucleon interactions in electron-positron collisions and opens up a new direction for such research.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao XL, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Measurements of Normalized Differential Cross Sections of Inclusive π^{0} and K_{S}^{0} Production in e^{+}e^{-} Annihilation at Energies from 2.2324 to 3.6710 GeV. PHYSICAL REVIEW LETTERS 2023; 130:231901. [PMID: 37354421 DOI: 10.1103/physrevlett.130.231901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 03/22/2023] [Accepted: 04/03/2023] [Indexed: 06/26/2023]
Abstract
Based on electron positron collision data collected with the BESIII detector operating at the BEPCII storage rings, the differential cross sections of inclusive π^{0} and K_{S}^{0} production as a function of hadron momentum, normalized by the total cross section of the e^{+}e^{-}→hadrons process, are measured at six center-of-mass energies from 2.2324 to 3.6710 GeV. Our results, which cover a relative hadron energy range from 0.1 to 0.9, significantly deviate from several theoretical calculations based on existing fragmentation functions.
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Wang Y, Li N, Fu Q, Cheng Z, Song Y, Yan B, Chen G, Hou L, Wang S. Conversion and impact of dissolved organic matters in a heterogeneous catalytic peroxymonosulfate system for pollutant degradation. WATER RESEARCH 2023; 241:120166. [PMID: 37290196 DOI: 10.1016/j.watres.2023.120166] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 05/22/2023] [Accepted: 06/01/2023] [Indexed: 06/10/2023]
Abstract
Dissolved organic matters (DOM) are widely present in different water sources, causing significant effects on water treatment processes. Herein, the molecular transformation behavior of DOM during peroxymonosulfate (PMS) activation by biochar for organic degradation in a secondary effluent were comprehensively analyzed. Evolution of DOM was identified and inhibition mechanisms to organic degradation were elucidated. DOM underwent oxidative decarbonization (e.g., -C2H2O, -C2H6, -CH2 and -CO2), dehydrogenation (-2H) and dehydration reactions by ·OH and SO4·-. N and S containing compounds witnessed deheteroatomisation (e.g., -NH, -NO2+H, -SO2, -SO3, -SH2), hydration (+H2O) and N/S oxidation reactions. Among DOM, CHO-, CHON-, CHOS-, CHOP- and CHONP-containing molecules showed moderate inhibition while condensed aromatic compounds and aminosugars exhibited strong and moderate inhibition effects on contaminant degradation. The fundamental information could provide references for the rational regulation of ROS composition and DOM conversion process in a PMS system. This in turn offered theoretical guidance to minimize the interference of DOM conversion intermediates on PMS activation and degradation of target pollutants.
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Chen G, Wang Y, Wang J, Wang J, Yu F, Ma Q, Cheng Z, Yan B, Song Y, Cui X. Production of potassium-enriched biochar from Canna indica: Transformation and release of potassium. WASTE MANAGEMENT (NEW YORK, N.Y.) 2023; 164:119-126. [PMID: 37054537 DOI: 10.1016/j.wasman.2023.03.044] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 03/09/2023] [Accepted: 03/29/2023] [Indexed: 06/19/2023]
Abstract
Potassium (K) is one of the essential macronutrients for plant growth, while most agricultural soils are suffering from K deficiency worldwide. Therefore, it is a promising strategy to prepare K-enriched biochar from biomass waste. In this study, various K-enriched biochars were prepared from Canna indica at 300-700 °C by pyrolysis, co-pyrolysis with bentonite, and pelletizing-co-pyrolysis. The chemical speciation and release behaviors of K were investigated. The derived biochars showed high yields, pH values, and mineral contents, which were affected by the pyrolysis temperatures and techniques. The derived biochars contained a significant amount of K (161.3-235.7 mg/g), which was much higher than the biochars derived from agricultural residues and wood. Water-soluble K was the dominant K species in biochars with a proportion of 92.7-96.0%, and co-pyrolysis and pelletizing promoted the transformation of K to the exchangeable K and K silicates. In comparison with the C. indica derived biochars (83.3-98.0%), the bentonite-modified biochar showed a lower cumulative release proportion of K (72.5% and 72.6%) in a 28-day release test, meeting the Chinese National Standard for slow-release fertilizers. In addition, the pseudo-first order, pseudo-second order, and Elovich models well described the K release data of the powdery biochars, and the pseudo-second order model was the best fit for the biochar pellets. The modeling results indicated that the K release rate decreased after the addition of bentonite and pelletizing. These results indicated that the biochars derived from C. indica could be used as potential slow-release K fertilizers for agricultural application.
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Chen C, Wang Z, Ge Y, Liang R, Hou D, Tao J, Yan B, Zheng W, Velichkova R, Chen G. Characteristics prediction of hydrothermal biochar using data enhanced interpretable machine learning. BIORESOURCE TECHNOLOGY 2023; 377:128893. [PMID: 36931444 DOI: 10.1016/j.biortech.2023.128893] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/04/2023] [Accepted: 03/11/2023] [Indexed: 06/18/2023]
Abstract
Hydrothermal biochar is a promising sustainable soil remediation agent for plant growth. Demands for biochar properties differ due to the diversity of soil environment. In order to achieve accurate biochar properties prediction and overcome the interpretability bottleneck of machine learning models, this study established a series of data-enhanced machine learning models and conducted relevant sensitivity analysis. Compared with traditional support vector machine, artificial neural network, and random forest models, the accuracy after data enhancement increased in average from 5.8% to 15.8%, where the optimal random forest model showed the average of accuracy was 94.89%. According to sensitivity analysis results, the essential factors influencing the predicting results of the models were reaction temperature, reaction pressure, and specific element of biomass feedstock. As a result, data-enhanced interpretable machine learning proved promising for the characteristics prediction of hydrothermal biochar.
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Zhang LZ, Yang JG, Xia HF, Huang J, Liu HM, Wu M, Liu B, Wang WM, Chen G. PD-1 Carried on Small Extracellular Vesicles Leads to OSCC Metastasis. J Dent Res 2023:220345231165209. [PMID: 37246810 DOI: 10.1177/00220345231165209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/30/2023] Open
Abstract
Immune checkpoint molecule PD-1, expressed on the cell surface, impairs antigen-driven activation of T cells and thus plays a critical role in tumorigenesis, progression, and the poor prognosis of oral squamous cell carcinoma (OSCC). In addition, increasing evidence indicates that PD-1 carried on small extracellular vesicles (sEVs) also mediates tumor immunity, although their contributions to OSCC are yet unclear. Here, we investigated the biological functions of sEV PD-1 in patients with OSCC. The cell cycle, proliferation, apoptosis, migration, and invasion of CAL27 cell lines treated with or without sEV PD-1 were examined in vitro. We performed mass spectrometry to investigate the underlying biological process, combined with an immunohistochemical study of SCC7-bearing mice models and OSCC patient samples. In vitro data demonstrated that sEV PD-1 induced senescence and subsequent epithelial-mesenchymal transition (EMT) in CAL27 cells by ligating with tumor cell surface PD-L1 and activating the p38 mitogen-activated protein kinase (MAPK) pathway. Comprehensive immunohistochemical analysis of the xenograft mice models and OSCC patient samples revealed a very close correlation between the level of circulating sEV PD-1 and lymph node metastasis. These results demonstrate that circulating sEV PD-1 triggers senescence-initiated EMT in a PD-L1-p38 MAPK-dependent manner, contributing to tumor metastasis. It also suggests that the inhibition of sEV PD-1 may be a promising therapeutic target for the treatment of OSCC.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu WL, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Precision Measurement of the Decay Σ^{+}→pγ in the Process J/ψ→Σ^{+}Σ[over ¯]^{-}. PHYSICAL REVIEW LETTERS 2023; 130:211901. [PMID: 37295102 DOI: 10.1103/physrevlett.130.211901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/29/2023] [Accepted: 05/08/2023] [Indexed: 06/12/2023]
Abstract
Using (10 087±44)×10^{6} J/ψ events collected with the BESIII detector, the radiative hyperon decay Σ^{+}→pγ is studied at an electron-positron collider experiment for the first time. The absolute branching fraction is measured to be (0.996±0.021_{stat}±0.018_{syst})×10^{-3}, which is lower than its world average value by 4.2 standard deviations. Its decay asymmetry parameter is determined to be -0.652±0.056_{stat}±0.020_{syst}. The branching fraction and decay asymmetry parameter are the most precise to date, and the accuracies are improved by 78% and 34%, respectively.
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Cheng X, Liang L, Ye J, Li N, Yan B, Chen G. Influence and mechanism of water matrices on H 2O 2-based Fenton-like oxidation processes: A review. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 888:164086. [PMID: 37201804 DOI: 10.1016/j.scitotenv.2023.164086] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 04/21/2023] [Accepted: 05/07/2023] [Indexed: 05/20/2023]
Abstract
Water matrices often coexist with the target pollutant during H2O2-based Fenton-like processes, which affects H2O2 activation and pollutant removal. Specifically, water matrices include inorganic anions (such as chloride, sulfate, nitrate, bicarbonate, carbonate and phosphate ions) and natural organic matters (such as humic acid (HA) and fulvic acid (FA)). In this review, the roles and mechanisms of water matrices in various Fenton-like systems were analyzed and summarized comprehensively. Carbonate and phosphate ions usually act as inhibitors. In contrast, the effects of other water matrices are usually controversial. Generally, water matrices can inhibit pollutants degradation through scavenging OH, forming low reactive radicals, adsorbing on catalyst sites, and changing solution pH. However, inorganic anions can exhibit a promotion effect, which is attributed to their complexation with copper ions in mixed contaminants as well as with cobalt and copper ions in catalysts. Furthermore, the photo-reactivity of nitrate and the generation of secondary radicals with long lifetime are conducive to the promotion of inorganic anions. Besides, HA (FA) can be activated by external energy or act as electron shuttle, thus displaying a facilitative effect. This review will provide guidance for the practical applications of the Fenton-like process.
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Li N, Ye J, Dai H, Shao P, Liang L, Kong L, Yan B, Chen G, Duan X. A critical review on correlating active sites, oxidative species and degradation routes with persulfate-based antibiotics oxidation. WATER RESEARCH 2023; 235:119926. [PMID: 37004307 DOI: 10.1016/j.watres.2023.119926] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 03/13/2023] [Accepted: 03/26/2023] [Indexed: 06/19/2023]
Abstract
At present, numerous heterogeneous catalysts have been synthesized to activate persulfate (PS) and produce various reactive species for antibiotic degradation from water. However, the systematic summary of the correlation among catalyst active sites, PS activation pathway and pollutant degradation has not been reported. This review summarized the effect of metal-based, carbon-based and metal-carbon composite catalysts on the degradation of antibiotics by activating PS. Metal and non-metal sites are conducive to inducing different oxidation pathways (SO4•-, •OH radical oxidation and 1O2 oxidation, mediated electron transfer, surface-bound reactive complexes and high-valent metal oxidation). SO4•- and •OH are easy to attack CH, S-N, CN bonds, CC double bonds and amino groups in antibiotics. 1O2 is more selective to the structure of the aniline ring and amino group, and also to attacking CS, CN and CH bonds. Surface-bound active species can cleave CC, SN, CS and CN bonds. Other non-radical pathways may also induce different antibiotic degradation routes due to differences in oxidation potential and electronic properties. This critical review clarified the functions of active sites in producing different reactive species for selective oxidation of antibiotics via featured pathways. The outcomes will provide valuable guidance of oriented-regulation of active sites in heterogeneous catalysts to produce on-demand reactive species toward high-efficiency removing antibiotics from water.
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Liang L, Chen G, Zhao J, Shao P, Li N, He M, Fu Q, Yan B, Hou LA. Overlooked impacts of natural organic matter conversion in a Fe(II)-induced peroxymonosulfate activation system for river water remediation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 872:162217. [PMID: 36791865 DOI: 10.1016/j.scitotenv.2023.162217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 02/03/2023] [Accepted: 02/09/2023] [Indexed: 06/18/2023]
Abstract
The peroxymonosulfate (PMS) process may be hindered severely due to natural organic matter (NOM) conversion in the treatment of emerging pollutants from river water, becoming a critical engineering and technical issue. In this study, a Fe(II)-induced river water (RW)/PMS catalytic system was constructed for investigating molecular transformation of NOM and related influence mechanism to sulfamethoxazole (SMX) degradation. Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analysis indicated that NOM molecules containing no more than one heteroatom in river may be attacked by hydroxyl radicals (OH) and then polymerized, converting into molecules with two or three heteroatoms during PMS oxidation. Based on the correlation analysis, CHONP-NOM, CHOSP-NOM and CHONSP-NOM showed a significant inhibition against SMX degradation, while CHONS-NOM exhibited a moderate inhibitory effect. Besides, more condensed aromatic structures, carbohydrates and tannins were generated via reactive species (OH and sulfate radicals (SO4-)) oxidation, radical addition and polymerization reactions. Notably, condensed aromatic structures, carbohydrates and tannins presented weak, modest and strong inhibition to SMX degradation, respectively. Based on the current results, the inhibition of target pollutants degradation would be mitigated via regulation of NOM molecules in a Fe(II)-induced PMS activation system, providing valuable information to reduce NOM impact. In addition, this study paves the way to achieve efficient removal of emerging pollutants from river water.
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Zhang T, Wu S, Li N, Chen G, Hou L. Applications of vacancy defect engineering in persulfate activation: Performance and internal mechanism. JOURNAL OF HAZARDOUS MATERIALS 2023; 449:130971. [PMID: 36805443 DOI: 10.1016/j.jhazmat.2023.130971] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/20/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
The vacancy defects in heterogeneous catalysts have received extensive attention for persulfate (PS) activation. Vacancy defects can tune the electronic structure of metal oxides and generate unsaturated coordination sites. Meanwhile, the adsorption energy of reactants on catalyst surface is optimized. Thereby, the reaction energy barrier between catalysts and PS decreases, which could promote catalytic activation and accelerate pollutants degradation. Nowadays, oxygen vacancy (OV), nitrogen vacancy (NV), sulfur vacancy (SV), selenium vacancy (SeV) and titanium vacancy (TiV) have been widely studied with great potential for water remediation. So far, no review was reported regarding the vacancy activated persulfate systems. This paper summarized the types, preparation, mechanism and applications of vacancy in PS systems systematically. In addition, we put forward possible development of vacancy engineering in PS activation systems. It is expected that this review will contribute to the controllable synthesis and applications of vacancies in catalysts for PS activation and contaminants removal.
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Mu L, Wang Y, Xu F, Li J, Tao J, Sun Y, Song Y, Duan Z, Li S, Chen G. Emerging Strategies for Enhancing Propionate Conversion in Anaerobic Digestion: A Review. Molecules 2023; 28:3883. [PMID: 37175291 PMCID: PMC10180298 DOI: 10.3390/molecules28093883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 04/18/2023] [Accepted: 04/27/2023] [Indexed: 05/15/2023] Open
Abstract
Anaerobic digestion (AD) is a triple-benefit biotechnology for organic waste treatment, renewable production, and carbon emission reduction. In the process of anaerobic digestion, pH, temperature, organic load, ammonia nitrogen, VFAs, and other factors affect fermentation efficiency and stability. The balance between the generation and consumption of volatile fatty acids (VFAs) in the anaerobic digestion process is the key to stable AD operation. However, the accumulation of VFAs frequently occurs, especially propionate, because its oxidation has the highest Gibbs free energy when compared to other VFAs. In order to solve this problem, some strategies, including buffering addition, suspension of feeding, decreased organic loading rate, and so on, have been proposed. Emerging methods, such as bioaugmentation, supplementary trace elements, the addition of electronic receptors, conductive materials, and the degasification of dissolved hydrogen, have been recently researched, presenting promising results. But the efficacy of these methods still requires further studies and tests regarding full-scale application. The main objective of this paper is to provide a comprehensive review of the mechanisms of propionate generation, the metabolic pathways and the influencing factors during the AD process, and the recent literature regarding the experimental research related to the efficacy of various strategies for enhancing propionate biodegradation. In addition, the issues that must be addressed in the future and the focus of future research are identified, and the potential directions for future development are predicted.
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Li J, Lin F, Yu H, Tong X, Cheng Z, Yan B, Song Y, Chen G, Hou L, Crittenden JC. Biochar-Assisted Catalytic Pyrolysis of Oily Sludge to Attain Harmless Disposal and Residue Utilization for Soil Reclamation. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:7063-7073. [PMID: 37018050 DOI: 10.1021/acs.est.2c09099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Pyrolysis of oily sludge (OS) is a feasible technology to match the principle of reduction and recycling; however, it is difficult to confirm the feasible environmental destination and meet the corresponding requirements. Therefore, an integrated strategy of biochar-assisted catalytic pyrolysis (BCP) of OS and residue utilization for soil reclamation is investigated in this study. During the catalytic pyrolysis process, biochar as a catalyst intensifies the removal of recalcitrant petroleum hydrocarbons at the expense of liquid product yield. Concurrently, biochar as an adsorbent can inhibit the release of micromolecular gaseous pollutants (e.g. HCN, H2S, and HCl) and stabilize heavy metals. Due to the assistance of biochar, pyrolysis reactions of OS are more likely to occur and require a lower temperature to achieve the same situation. During the soil reclamation process, the obtained residue as a soil amendment can not only provide a carbon source and mineral nutrients but can also improve the abundance and diversity of microbial communities. Thus, it facilitates the plant germination and the secondary removal of petroleum hydrocarbons. The integrated strategy of BCP of OS and residue utilization for soil reclamation is a promising management strategy, which is expected to realize the coordinated and benign disposal of more than one waste.
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Chen G, Zhang WL, Zhang SM, Tang KL, Zhang Y. LncRNA FOXD2-AS1 facilitates the progression of hepatocellular carcinoma by regulating TWIST1. EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES 2023; 27:4536-4543. [PMID: 37259735 DOI: 10.26355/eurrev_202305_32460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
OBJECTIVE The study aimed at elucidating the role of FOXD2-AS1 in facilitating the malignant progression of hepatocellular carcinoma (HCC) by regulating TWIST1. PATIENTS AND METHODS Relative levels of FOXD2-AS1 and TWIST1 in HCC tissues classified by tumor size and tumor node metastasis (TNM) staging were detected by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR). The Kaplan-Meier method was applied to assess the prognostic potential of FOXD2-AS1 in HCC patients, followed by survival rate comparison using a log-rank test. After the knockdown of FOXD2-AS1 in HepG2 cells, the viability and migratory abilities were examined by Cell Counting Kit-8 (CCK-8) and transwell assay, respectively. The subcellular distribution of FOXD2-AS1 was detected. Finally, the involvement of TWIST1 in the regulation of HCC cell functions influenced by FOXD2-AS1 was explored. RESULTS FOXD2-AS1 was upregulated in HCC tissues, especially large tumor size or stage III-IV cases. High levels of FOXD2-AS1 predicted poor prognosis in HCC patients. FOXD2-AS1 was mainly distributed in the nucleus, and knockdown of FOXD2-AS1 weakened proliferative and migratory abilities in HepG2 cells. TWIST1 was upregulated in HCC tissues, which was positively correlated to FOXD2-AS1 level. The overexpression of TWIST1 could reverse the inhibited proliferative and migratory abilities in HepG2 cells with FOXD2-AS1 knockdown. CONCLUSIONS FOXD2-AS1 facilitates the progression of HCC by upregulating TWIST1.
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Tao J, Yin X, Yao X, Cheng Z, Yan B, Chen G. Prediction of NH 3 and HCN yield from biomass fast pyrolysis: Machine learning modeling and evaluation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 885:163743. [PMID: 37116814 DOI: 10.1016/j.scitotenv.2023.163743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 04/11/2023] [Accepted: 04/21/2023] [Indexed: 05/12/2023]
Abstract
Rapid pyrolysis is a promising technique to convert biomass into fuel oil, where NOX emission remains a substantial environmental risk. NH3 and HCN are top precursors for NOX emission. In order to clarify their migration path and provide appropriate strategies for their controlling, six up-to-date machine learning (ML) models were established to predict the NH3 and HCN yield during rapid pyrolysis of 26 biomass feedstocks. Cross-validation and grid search methods were used to determine the optimal hyperparameters for these ML models. The support vector regression (SVR) model achieved optimal accuracy among them. The optimal root means square error (%), mean absolute error (%), and R2 of test set for NH3/HCN yield were 1.2901/1.1531, 1.0501/0.84712, and 0.98253/0.96152, respectively. In addition, based on the results of Pearson correlation analysis, the input variables with a weak linear correlation with the target product were eliminated, which was found capable of improving the prediction accuracy of almost all ML models except SVR. While after input variables elimination, the SVR model still showed the optimal NH3 and HCN yield prediction accuracy. It reflects SVR's great significance and potential for predicting the yield of NOX precursors during rapid biomass pyrolysis.
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Xue S, Wang PS, Lu QY, Chen G. [Discussion on how to optimize active surveillance for low-risk papillary thyroid microcarcinoma in China]. ZHONGHUA WAI KE ZA ZHI [CHINESE JOURNAL OF SURGERY] 2023; 61:462-466. [PMID: 37088477 DOI: 10.3760/cma.j.cn112139-20221014-00442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Active surveillance, as a first-line treatment strategy for low-risk papillary thyroid microcarcinoma, has been recommended by guidelines worldwide. However, active surveillance has not been widely accepted by doctors and patients in China. In view of the huge challenges faced by active surveillance, doctors should improve their understanding of the "low risk" of papillary thyroid micropapillary cancer, identify some intermediate or high-risk cases, be familiar with the criteria and methods of diagnosis for disease progression, and timely turn patients with disease progression into more active treatment strategies. By analyzing the long-term cost-effectiveness of active surveillance, it is clear that medical expense is only one cost form of medical activities, and the health cost (thyroid removal and surgical complications) paid by patients due to"over-diagnosis and over-treatment" is the most important. Moreover, the weakening of the patients' social function caused by surgical procedures is a more hidden and far-reaching cost. The formulation of health economic policies (including medical insurance) should promote the adjustment of diagnosis and treatment behavior to the direction which is conducive to the long-term life and treatment of patients, improving the overall health level of society and reducing the overall cost. At the same time, doctors should stimulate the subjective initiative of patients, help them fully understand the impact of various treatment methods on their psychological and physical status, support patients psychologically, and strengthen their confidence in implementing active surveillance. By strengthening multi-disciplinary treatment team and system support, doctors can achieve risk stratification of papillary thyroid microcarcinoma, accurate judgment of disease progress, timely counseling for psychological problems, and long-term adherence to active surveillance. Improving the treatment level of advanced thyroid cancer is the key point of improve the prognosis. It is important to promote the development of active surveillance for low-risk papillary thyroid microcarcinoma. In the future, it is necessary to carry out multi-center prospective research and accumulate research evidence for promoting the standardization process of active surveillance. Standardized active surveillance will certainly benefit specific papillary thyroid microcarcinoma patients.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BX, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu WL, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Measurements of the Electric and Magnetic Form Factors of the Neutron for Timelike Momentum Transfer. PHYSICAL REVIEW LETTERS 2023; 130:151905. [PMID: 37115883 DOI: 10.1103/physrevlett.130.151905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/27/2023] [Accepted: 03/23/2023] [Indexed: 06/19/2023]
Abstract
We present the first measurements of the electric and magnetic form factors of the neutron in the timelike (positive q^{2}) region as function of four-momentum transfer. We explored the differential cross sections of the reaction e^{+}e^{-}→n[over ¯]n with data collected with the BESIII detector at the BEPCII accelerator, corresponding to an integrated luminosity of 354.6 pb^{-1} in total at twelve center-of-mass energies between sqrt[s]=2.0-2.95 GeV. A relative uncertainty of 18% and 12% for the electric and magnetic form factors, respectively, is achieved at sqrt[s]=2.3935 GeV. Our results are comparable in accuracy to those from electron scattering in the comparable spacelike region of four-momentum transfer. The electromagnetic form factor ratio R_{em}≡|G_{E}|/|G_{M}| is within the uncertainties close to unity. We compare our result on |G_{E}| and |G_{M}| to recent model predictions, and the measurements in the spacelike region to test the analyticity of electromagnetic form factors.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of a New X(3872) Production Process e^{+}e^{-}→ωX(3872). PHYSICAL REVIEW LETTERS 2023; 130:151904. [PMID: 37115900 DOI: 10.1103/physrevlett.130.151904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 06/19/2023]
Abstract
Using 4.7 fb^{-1} of e^{+}e^{-} collision data at center-of-mass energies from 4.661 to 4.951 GeV collected by the BESIII detector at the BEPCII collider, we observe the X(3872) production process e^{+}e^{-}→ωX(3872) for the first time. The significance is 7.8σ, including both the statistical and systematic uncertainties. The e^{+}e^{-}→ωX(3872) Born cross section and the corresponding upper limit at 90% confidence level at each energy point are reported. The line shape of the cross section indicates that the ωX(3872) signals may be from the decays of some nontrivial structures.
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Liang R, Chen C, Sun T, Tao J, Hao X, Gu Y, Xu Y, Yan B, Chen G. Interpretable machine learning assisted spectroscopy for fast characterization of biomass and waste. WASTE MANAGEMENT (NEW YORK, N.Y.) 2023; 160:90-100. [PMID: 36801592 DOI: 10.1016/j.wasman.2023.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/03/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
The combination of machine learning and infrared spectroscopy was reported as effective for fast characterization of biomass and waste (BW). However, this characterization process is lack of interpretability towards its chemical insights, leading to less satisfactory recognition for its reliability. Accordingly, this paper aimed to explore the chemical insights of the machine learning models in the fast characterization process. A novel dimensional reduction method with significant physicochemical meanings was thus proposed, where the high loading spectral peaks of BW were selected as input features. Combined with functional groups attribution of these spectral peaks, the machine learning models established based on the dimensionally reduced spectral data could be explained with clear chemical insights. The performance of classification and regression models between the proposed dimensional reduction method and principal component analysis method was compared. The influence mechanism of each functional group on the characterization results were discussed. CH deformation, CC stretch & CO stretch and ketone/aldehyde CO stretch played essential roles in C, H/ LHV and O prediction, respectively. The results of this work demonstrated the theoretical fundamentals of the machine learning and spectroscopy based BW fast characterization method.
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Wu YL, Zhang L, Fan Y, Zhou J, Zhang L, Zhou Q, Li W, Hu C, Chen G, Zhang X, Zhou C, Arenas C, Chen Z, Yu W, Mok T. 42P Pembrolizumab vs chemotherapy in Chinese patients with non-small cell lung cancer (NSCLC) and PD-L1 TPS ≥1%: 5-year update from KEYNOTE-042. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00296-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BX, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of Three Charmoniumlike States with J^{PC}=1^{--} in e^{+}e^{-}→D^{*0}D^{*-}π^{+}. PHYSICAL REVIEW LETTERS 2023; 130:121901. [PMID: 37027853 DOI: 10.1103/physrevlett.130.121901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/16/2023] [Accepted: 02/24/2023] [Indexed: 06/19/2023]
Abstract
The Born cross sections of the process e^{+}e^{-}→D^{*0}D^{*-}π^{+} at center-of-mass energies from 4.189 to 4.951 GeV are measured for the first time. The data samples used correspond to an integrated luminosity of 17.9 fb^{-1} and were collected by the BESIII detector operating at the BEPCII storage ring. Three enhancements around 4.20, 4.47, and 4.67 GeV are visible. The resonances have masses of 4209.6±4.7±5.9 MeV/c^{2}, 4469.1±26.2±3.6 MeV/c^{2}, and 4675.3±29.5±3.5 MeV/c^{2} and widths of 81.6±17.8±9.0 MeV, 246.3±36.7±9.4 MeV, and 218.3±72.9±9.3 MeV, respectively, where the first uncertainties are statistical and the second systematic. The first and third resonances are consistent with the ψ(4230) and ψ(4660) states, respectively, while the second one is compatible with the ψ(4500) observed in the e^{+}e^{-}→K^{+}K^{-}J/ψ process. These three charmoniumlike ψ states are observed in the e^{+}e^{-}→D^{*0}D^{*-}π^{+} process for the first time.
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Wu J, Chen G, Wang L, Wang P, Han Y, Yang L, Ouyang X. Investigation on the feasibility of large-volume autologous red blood cells donation: A pilot trial in a small cohort of Chinese. J Clin Apher 2023. [PMID: 36950971 DOI: 10.1002/jca.22048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 01/19/2023] [Accepted: 02/23/2023] [Indexed: 03/24/2023]
Abstract
BACKGROUND Preoperative autologous blood donation (PAD) is used for elective surgical procedures with a predictable blood loss. But a downward trend in PAD is due to the fact that patients with preoperative whole blood donation or two-unit red cell apheresis cannot avoid receiving allogenic blood during intensive surgery. To improve the clinical application of PAD, this study explores the feasibility of large-volume autologous red blood cells (RBCs) donation by a pilot trial in a small cohort of Chinese. METHODS This was a single-center, prospective study and 16 male volunteers were enrolled from May to October in 2020. Each volunteer donated 627.25 ± 109.74 mL (mean ± SD) RBC with apheresis machine or manually, and received 800 mg of intravenous iron in four divided doses. Blood pressure, oxygen saturation (SpO2 ), respiratory rate and heart rate were monitored throughout the procedure. The RBC count, hemoglobin (Hb) concentration, hematocrit (Hct), reticulocyte count, erythropoietin (Epo), serum iron, total iron binding capacity (TIBC), transferrin saturation, transferrin, and ferritin were dynamically detected and analyzed before and 8 weeks after blood donation. RESULTS There was no differences in SpO2 , systolic and diastolic blood pressure before and after blood collection (P ≥ .05). The heart rate and respiratory rate after donation were slightly lower than those before (P < .05). The level of RBC, Hb concentration and Hct fell to a nadir on Day 3 (pre-donation vs post-donation on Day 3: RBC 4.81 ± 0.36*1012 /L vs 3.65 ± 0.31, P < .05; Hb 148.59 ± 11.92 g/L vs 113.19 ± 10.43 g/L, P < .05; Hct 44.08 ± 3.06% vs 33.38 ± 2.57%, P < .05) and recovered to the pre-donation levels at the eighth week post donation (pre-donation vs post-donation at the eighth week: RBC 4.81 ± 0.36*1012 /L vs 4.84 ± 0.34*1012 /L, P ≥ .05; Hb 148.59 ± 11.92 g/L vs 150.91 ± 11.75 g/L, P ≥ .05; Hct 44.08% ± 3.06% vs 43.86 ± 3.06%, P ≥ .05). Epo and the reticulocyte count reached the peak values on Days 1 and 7, respectively (Epo: D0 15.30 ± 7.47 mlU/ML vs D1 43.26 ± 10.52 mlU/ML, P < .05; reticulocyte count: D0 0.07 ± 0.02*109 /L vs D7 0.17 ± 0.04*109 /L, P < .05). The red cell net profits on Day 7, the second, fourth and eighth week postdonation were 160.39 ± 144.33 mL, 387.59 ± 128.74 mL, 530.95 ± 120.37 mL, and 614.18 ± 120.10 mL, and accounted for 27.47% ± 24.70%, 63.75% ± 24.91%, 86.20% ± 22.99%, and 99.20% ± 19.19% of RBC donation, respectively. The levels of serum iron, serum ferritin, and transferrin saturation increased during the first week because of the supplement of intravenous iron, and then gradually decreased and declined to the baseline at the end of the study period at the eighth week. CONCLUSIONS The large-volume autologous RBCs donation of 600 mL is proved safe in our study. Combination support of normal saline to maintain blood volume and intravenous iron supplementation may ensure the safety and effectiveness of large-volume RBC apheresis.
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