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Lan QY, Cao ZH, Qi RF, Luo YF, Zhang JY, Ge HH, Dai P, Liu F, Chen LJ, Li GM, Lu G. [A study on longitudinal changes in white matter microstructure of parents who have lost their only child based on diffusion tensor imaging and its relationship with symptoms of posttraumatic stress disorder]. ZHONGHUA YI XUE ZA ZHI 2022; 102:1760-1765. [PMID: 35705480 DOI: 10.3760/cma.j.cn112137-20211213-02778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To investigate the longitudinal changes of white matter microstructural based on diffusion tensor imaging in parents who lost their only child without psychiatric disorders and its relationship with symptoms of posttraumatic stress disorder (PTSD). Methods: Parents who had who lost their only child and without psychiatric disorders in Jiangsu Province, from September 2016 to March 2017, were retrospectively collected (TENP group, 32). MRI scans were performed at baseline and at the end of 5-year follow-up, and the Clinician Administered PTSD Scales (CAPS) were used for assessing the severity of symptoms. Additionally, sex, age and education level matched healthy subjects were recruited as healthy controls (control group, 27) and underwent MRI scanning using the same protocol. The differences of fractional anisotropy (FA) values between TENP group and control group at baseline were analyzed by using Tract-based spatial statistics method, and the brain areas of lateral differences were used as the regions of interest for longitudinal follow-up analysis of TENP group. Partial correlation analysis was used to evaluate the relationship between FA values changes in longitudinal differences in brain regions and CAPS scores. Results: Compared with the control group, FA values of the right cingulate gyrus, Uncinate fasciculus, superior longitudinal fasciculus, corticospinal tract, Inferior fronto-occipital fasciculus, Inferior longitudinal fasciculus and forceps major in TENP group were decreased at baseline ((0.613±0.032) vs (0.631±0.034), (0.539±0.048) vs (0.563±0.045), (0.534±0.033) vs (0.558±0.039), (0.560±0.038) vs (0.580±0.030), (0.519±0.023) vs(0.549±0.024), (0.489±0.038) vs (0.518±0.027), (0.499±0.027) vs (0.533±0.032); all P<0.05). From baseline to follow-up, scores of trauma reexperience symptoms and avoidance/numbness symptoms were decreased ((5.2±2.8) vs (8.1±4.9), (4.0±3.2) vs (6.6±5.4); all P<0.05); FA values of the right corticospinal tract, Inferior fronto-occipital fasciculus, Inferior longitudinal fasciculus and forceps major were decreased ((0.523±0.049) vs (0.537±0.049), (0.568±0.052) vs (0.590±0.050), (0.540±0.063) vs (0.559±0.059), (0.520±0.059) vs (0.547±0.059); all P<0.05); The decrease of FA values of the right Inferior fronto-occipital fasciculus and right Inferior longitudinal fasciculus was negatively correlated with the decrease of avoidance/numbness symptoms scores (r=-0.458, -0.374, respectively, all P<0.05). Conclusions: The trauma of parents who lost their only child can result in impaired microstructural integrity of white matter. As the post-traumatic time goes by, parents who have lost their only child do not develop to PTSD and other psychiatric disorders, and the clinical symptoms are alleviated, the damage of the white matter microstructure continued to progress.
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Lin YJ, Cai LN, Zhao YY, Cheng HY, Storey KB, Yu DN, Zhang JY. Novel Mitochondrial Gene Rearrangement and Intergenic Regions Exist in the Mitochondrial Genomes from Four Newly Established Families of Praying Mantises (Insecta: Mantodea). INSECTS 2022; 13:insects13070564. [PMID: 35886740 PMCID: PMC9320148 DOI: 10.3390/insects13070564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/07/2022] [Accepted: 06/19/2022] [Indexed: 12/04/2022]
Abstract
Simple Summary Mantodea is regarded as an excellent material to study the gene rearrangements and large non-coding regions (LNCRs) in mitochondrial genomes. Meanwhile, as a result of the convergent evolution and parallelism, the gene rearrangements and LNCRs are specific to some taxonomic groups within Mantodea, which play an important role in phylogenetic relationship research. Nine mitochondrial genomes (mitogenomes) from four newly established families of praying mantises are obtained and annotated. Eight types of gene rearrangements, including four novel types of gene rearrangements in Mantodea, are detected, which can be explained by the tandem replication-random loss (TDRL) model. Moreover, one conserved motif between trnI-trnQ is detected in Toxoderidae. This study shed light on the formation mechanisms of these gene rearrangements and LNCRs in four newly established families of praying mantises. Abstract Long non-coding regions (NCRs) and gene rearrangements are commonly seen in mitochondrial genomes of Mantodea and are primarily focused on three regions: CR-I-Q-M-ND2, COX2-K-D-ATP8, and ND3-A-R-N-S-E-F-ND5. In this study, eight complete and one nearly complete mitochondrial genomes of praying mantises were acquired for the purpose of discussing mitochondrial gene rearrangements and phylogenetic relationships within Mantodea, primarily in the newly established families Haaniidae and Gonypetidae. Except for Heterochaeta sp. JZ-2017, novel mitochondrial gene arrangements were detected in Cheddikulama straminea, Sinomiopteryx graham, Pseudovates chlorophaea, Spilomantis occipitalis. Of note is the fact that one type of novel arrangement was detected for the first time in the Cyt b-S2-ND1 region. This could be reliably explained by the tandem replication-random loss (TDRL) model. The long NCR between trnT and trnP was generally found in Iridopteryginae and was similar to the ND4L or ND6 gene. Combined with gene rearrangements and intergenic regions, the monophyly of Haaniidae was supported, whereas the paraphyly of Gonypetidae was recovered. Furthermore, several synapomorphies unique to some clades were detected that conserved block sequences between trnI and trnQ and gaps between trnT and trnP in Toxoderidae and Iridopteryginae, respectively.
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Zhang JY, Sun YM, Chen SY, You H. [Reversal of hepatic fibrosis: more evidence and more challenges]. ZHONGHUA GAN ZANG BING ZA ZHI = ZHONGHUA GANZANGBING ZAZHI = CHINESE JOURNAL OF HEPATOLOGY 2022; 30:569-571. [PMID: 36038315 DOI: 10.3760/cma.j.cn501113-20220510-00255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Hepatic fibrosis is a response to various types of hepatic injury, which can lead to cirrhosis and its complications. In recent years, in patients with viral hepatitis, nonalcoholic steatohepatitis, alcoholic liver disease, autoimmune liver disease and others the fibrosis or even early cirrhosis can be regressed if the etiology are controlled. Liver biopsy is still the gold standard for assessing fibrosis reversal, but non-invasive methods such as transient elastography hold great promise due to the ease to use for dynamic monitoring. Mechanisms of hepatic fibrosis reversal include extracellular matrix degradation, hepatocyte regeneration, and vascular remodeling. Presently, novel agents targeting the steps of fibrosis are urgently need for achieving regression of liver fibrosis.
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Li QQ, Liang JY, Wang JM, Shen P, Sun YX, Chen Q, Wu JG, Lu P, Zhang JY, Lin HB, Tang X, Gao P. [Applications of the NDR and DIAL models for risk prediction on cardiovascular disease in patients with type 2 diabetes in Ningbo]. ZHONGHUA LIU XING BING XUE ZA ZHI = ZHONGHUA LIUXINGBINGXUE ZAZHI 2022; 43:945-952. [PMID: 35725354 DOI: 10.3760/cma.j.cn112338-20211116-00891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To validate the performance of cardiovascular risk prediction models based on the Sweden National Diabetes Register (NDR) and Diabetes Lifetime-perspective prediction (DIAL) model for assessing risks of 5-year and 10-year cardiovascular disease (CVD) among Chinese patients with type 2 diabetes. Methods: Based on the Chinese Electronic Health Records Research in Yinzhou study, 83 503 patients with type 2 diabetes aged 30-75 years without a history of CVD at baseline were included from January 1, 2010 to December 31, 2020. Recalibrated NDR model was used to estimate 5-year risk, while the recalibrated DIAL model was used to predict 5-year and 10-year risks. The competing events adjusted Kaplan-Meier analysis was used to obtain the observed cardiovascular events. Discrimination C statistics evaluated model accuracy, calibration χ2 value, and calibration plots. Results: Through a median follow-up of 7.0 years, 7 326 cardiovascular events, and 2 937 non-vascular deaths were identified among a total of 83 503 subjects. The recalibrated NDR model overestimated 5-year risk by 39.4% in men and 8.6% in women, whereas the overestimation for the recalibrated DIAL model was 14.6% in men and 50.1% in women. The DIAL model had a better discriminative ability (C-statistic=0.681, 95%CI: 0.672-0.690) than NDR model (C-statistic=0.667, 95%CI: 0.657-0.677) in 5-year risk prediction for men, and the models had a similar ability for women (C-statistic=0.699, 95%CI: 0.690-0.708 for NDR and C-statistic=0.698, 95%CI: 0.689-0.706 for DIAL). The prediction accuracy of the DIAL model was improved in the 10-year risk, with the underestimation being 1.6% for men and the overestimation being 12.8% for women. Conclusions: Both recalibrated NDR and DIAL models overestimated 5-year cardiovascular risk in Chinese patients with type 2 diabetes, while the higher overestimation was shown using the DIAL model. However, the improvement was found in predicting 10-year CVD risk using the DIAL model, which suggested the value of lifetime risk prediction and indicated the need for research on the lifetime risk prediction model for cardiovascular risk assessment in Chinese patients with type 2 diabetes.
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Jiang BY, Salitana A, Yusufu M, Zhang JY, Wang JZ, Deng F, Zhang Y, Sun S. [Prokaryotic expression and purification of nucleoprotein of Guertu virus and its establishment of ELISA detection method]. ZHONGHUA YU FANG YI XUE ZA ZHI [CHINESE JOURNAL OF PREVENTIVE MEDICINE] 2022; 56:824-830. [PMID: 35791033 DOI: 10.3760/cma.j.cn112150-20220326-00286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To obtain purified protein antigen of guertu virus (GTV) nucleoprotein (NP) and establish a rapid and accurate enzyme-linked immunosorbent assay (ELISA) method for detection of GTV antibody. Methods: Codon optimized GTV NP encoding genes were synthesized, cloned into the pet32a (+) vector, and recombinant expression plasmids were constructed and transformed into BL21 (DE3). Recombinant protein (rNP) obtained from the optimized expression were purified over a Ni column and identified by SDS-PAGE and Western blot. The purified protein was used as the antigen to optimize the reaction conditions, and an indirect ELISA assay for GTV IgG antibody was developed and optimized, which was evaluated and initially applied. Results: The prokaryotic expression plasmid pet32a-NP was successfully constructed, the recombinant protein was highly expressed in E. coli in the form of inclusion bodies, the size was about 44 kD, and the results of Western blot indicated that the recombinant protein had good antigenicity with GTV positive serum. The optimized ELISA (GTV-rNP-iELISA) established in this study showed strong specificity, high sensitivity, and the coefficient of variation within and between batches is less than 10%, and has good repeatability; the detection results are consistent with the IFA detection results. Using the established ELISA method to detect 162 sheep sera from some regions of Xinjiang in 2017-2019, the total positive rate of antibodies was 39.8%. Conclusions: The GTV NP antibody detection ELISA method has good sensitivity, reproducibility, and specificity and has the potential to be a powerful tool for the diagnosis and serological investigation of GTV infection.
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Lin YJ, Zhao YY, Yang YM, Jin WT, Cai LN, Storey KB, Zhang JY, Yu DN. The complete mitochondrial genome of Leptomantella tonkinae (Hebard, 1920) (Mantodea: Leptomantellidae) and its phylogeny. Mitochondrial DNA B Resour 2022; 7:1011-1014. [PMID: 35756444 PMCID: PMC9225716 DOI: 10.1080/23802359.2022.2080025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
The complete mitochondrial (mt) genome of Leptomantella tonkinae (Hebard, 1920) was 15,527 bp in length and contained 13 protein-coding genes, 22 transfer RNAs, two ribosomal RNAs, and one control region. The gene arrangement of mt genome of L. tonkinae was identical to the primitive mantis. The overall AT content of the mt genome was 74%. In ML and BI phylogenetic analyses, the monophyly of Leptomantellidae was robustly supported and the clade of Leptomantellidae is a sister clade to the group of (Gonypetidae+(Leptomantellidae+(Amorphoscelidae+Nanomantidae))).
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Tong Y, Wu L, Lin YJ, Ayivi SPG, Storey KB, Zhang JY, Yu DN. The first complete mitochondrial genome of Hexagenia rigida Mc Dunnough, 1924 (Ephemeroptera: Ephemeridae) and its phylogeny. Mitochondrial DNA B Resour 2022; 7:1093-1095. [PMID: 35756439 PMCID: PMC9225702 DOI: 10.1080/23802359.2022.2086498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The phylogenetic relationship of Ephemeridae (Insect: Ephemeroptera) remains hotly debated using mitochondrial (mt) genomes. All previously reported mt genomes of Ephemeridae belong to the genus Ephemera. This study provides the first complete mt genome sequence from the genus Hexagenia with an analysis of the mitogenome of Hexagenia rigida Mc Dunnough, 1924 (Ephemeroptera: Ephemeridae) and providing new information to discuss the phylogenetic relationships within Ephemeroptera. The complete mt genome of H. rigida was a circular molecule of 16,159 bp in length, containing 37 genes (2 rRNA genes, 13 protein-coding genes, 22 tRNA genes), which showed the typical mt gene arrangement of insects. The AT content of the whole genome was 70.0% and the length of the control region was 1091 bp. All protein-coding genes used ATN as the start codon, and most PCGs used TAA/TAG as the stop codons excluding COI, COII, ND5 and Cyt b that used T as the stop codon. BI and ML phylogenetic trees constructed from 27 species of 13 families showed that Ephemeridae is a sister clade to the clade Polymitarcyidae.
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Yang W, Liu L, Guo J, Wang SG, Zhang JY, Fan LW, Tian Y, Wang LL, Luan C, Li ZL, He C, Wang X, Gu QS, Liu XY. Enantioselective Hydroxylation of Dihydrosilanes to Si‐Chiral Silanols Catalyzed by In Situ Generated Copper(II) Species. Angew Chem Int Ed Engl 2022. [DOI: 10.1002/ange.202205743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Jin WT, Guan JY, Dai XY, Wu GJ, Zhang LP, Storey KB, Zhang JY, Zheng RQ, Yu DN. Mitochondrial gene expression in different organs of Hoplobatrachus rugulosus from China and Thailand under low-temperature stress. BMC ZOOL 2022; 7:24. [PMID: 37170336 PMCID: PMC10127437 DOI: 10.1186/s40850-022-00128-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 04/29/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Hoplobatrachus rugulosus (Anura: Dicroglossidae) is distributed in China and Thailand and the former can survive substantially lower temperatures than the latter. The mitochondrial genomes of the two subspecies also differ: Chinese tiger frogs (CT frogs) display two identical ND5 genes whereas Thai tiger frogs (TT frogs) have two different ND5 genes. Metabolism of ectotherms is very sensitive to temperature change and different organs have different demands on energy metabolism at low temperatures. Therefore, we conducted studies to understand: (1) the differences in mitochondrial gene expression of tiger frogs from China (CT frogs) versus Thailand (TT frogs); (2) the differences in mitochondrial gene expression of tiger frogs (CT and TT frogs) under short term 24 h hypothermia exposure at 25 °C and 8 °C; (3) the differences in mitochondrial gene expression in three organs (brain, liver and kidney) of CT and TT frogs.
Results
Utilizing RT-qPCR and comparing control groups at 25 °C with low temperature groups at 8 °C, we came to the following results. (1) At the same temperature, mitochondrial gene expression was significantly different in two subspecies. The transcript levels of two identical ND5 of CT frogs were observed to decrease significantly at low temperatures (P < 0.05) whereas the two different copies of ND5 in TT frogs were not. (2) Under low temperature stress, most of the genes in the brain, liver and kidney were down-regulated (except for COI and ATP6 measured in brain and COI measured in liver of CT frogs). (3) For both CT and TT frogs, the changes in overall pattern of mitochondrial gene expression in different organs under low temperature and normal temperature was brain > liver > kidney.
Conclusions
We mainly drew the following conclusions: (1) The differences in the structure and expression of the ND5 gene between CT and TT frogs could result in the different tolerances to low temperature stress. (2) At low temperatures, the transcript levels of most of mitochondrial protein-encoding genes were down-regulated, which could have a significant effect in reducing metabolic rate and supporting long term survival at low temperatures. (3) The expression pattern of mitochondrial genes in different organs was related to mitochondrial activity and mtDNA replication in different organs.
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Tong Y, Wu L, Ayivi SPG, Storey KB, Ma Y, Yu DN, Zhang JY. Cryptic Species Exist in Vietnamella sinensis Hsu, 1936 (Insecta: Ephemeroptera) from Studies of Complete Mitochondrial Genomes. INSECTS 2022; 13:insects13050412. [PMID: 35621748 PMCID: PMC9143467 DOI: 10.3390/insects13050412] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/20/2022] [Accepted: 04/24/2022] [Indexed: 12/14/2022]
Abstract
Ephemeroptera (Insecta: Pterygota) are widely distributed all over the world with more than 3500 species. During the last decade, the phylogenetic relationships within Ephemeroptera have been a hot topic of research, especially regarding the phylogenetic relationships among Vietnamellidae. In this study, three mitochondrial genomes from three populations of Vienamella sinensis collected from Tonglu (V. sinensis TL), Chun’an (V. sinensis CN), and Qingyuan (V. sinensis QY) in Zhejiang Province, China were compared to discuss the potential existence of cryptic species. We also established their phylogenetic relationship by combining the mt genomes of 69 Ephemeroptera downloaded from NCBI. The mt genomes of V. sinensis TL, V. sinensis CN, and V. sinensis QY showed the same gene arrangement with lengths of 15,674 bp, 15,674 bp, and 15,610 bp, respectively. Comprehensive analyses of these three mt genomes revealed significant differences in mt genome organization, genetic distance, and divergence time. Our results showed that the specimens collected from Chun’an and Tonglu in Zhejiang Province, China belonged to V. sinensis, and the specimens collected from Qingyuan, Zhejiang Province, China were a cryptic species of V. sinensis. In maximum likelihood (ML) and Bayesian inference (BI) phylogenetic trees, the monophyly of the family Vietnamellidae was supported and Vietnamellidae has a close relationship with Ephemerellidae.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai JP, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Guan CY, Guo AQ, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Andersson WI, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, 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 CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu T, Liu T, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XX, Ma XY, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Plura S, Pogodin S, Poling R, Prasad V, 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, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen HF, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu CJ, Xu GF, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng X, Zeng Y, Zhang AQ, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Observation of the Singly Cabibbo Suppressed Decay Λ_{c}^{+}→nπ^{+}. PHYSICAL REVIEW LETTERS 2022; 128:142001. [PMID: 35476477 DOI: 10.1103/physrevlett.128.142001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 02/05/2022] [Accepted: 03/01/2022] [Indexed: 06/14/2023]
Abstract
The singly Cabibbo-suppressed decay Λ_{c}^{+}→nπ^{+} is observed for the first time with a statistical significance of 7.3σ by using 3.9 fb^{-1} of e^{+}e^{-} collision data collected at center-of-mass energies between 4.612 and 4.699 GeV with the BESIII detector at BEPCII. The branching fraction of Λ_{c}^{+}→nπ^{+} is measured to be (6.6±1.2_{stat}±0.4_{syst})×10^{-4}. By taking the upper limit of branching fractions of Λ_{c}^{+}→pπ^{0} from the Belle experiment, the ratio of branching fractions between Λ_{c}^{+}→nπ^{+} and Λ_{c}^{+}→pπ^{0} is calculated to be larger than 7.2 at the 90% confidence level, which disagrees with most predictions of the available phenomenological models. In addition, the branching fractions of the Cabibbo-favored decays Λ_{c}^{+}→Λπ^{+} and Λ_{c}^{+}→Σ^{0}π^{+} are measured to be (1.31±0.08_{stat}±0.05_{syst})×10^{-2} and (1.22±0.08_{stat}±0.07_{syst})×10^{-2}, respectively, which are consistent with previous results.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Andersson WI, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Lin CX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu T, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XX, Ma XY, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pogodin S, Poling R, Prasad V, 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, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen HF, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu GF, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng XZ, Zeng Y, Zhang AQ, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, Zhang XD, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Measurement of the Cross Section for e^{+}e^{-}→Hadrons at Energies from 2.2324 to 3.6710 GeV. PHYSICAL REVIEW LETTERS 2022; 128:062004. [PMID: 35213186 DOI: 10.1103/physrevlett.128.062004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 01/21/2022] [Indexed: 06/14/2023]
Abstract
Based on electron-positron collision data collected with the BESIII detector operating at the Beijing Electron-Positron Collider II storage rings, the value of R≡σ(e^{+}e^{-}→hadrons)/σ(e^{+}e^{-}→μ^{+}μ^{-}) is measured at 14 center-of-mass energies from 2.2324 to 3.6710 GeV. The resulting uncertainties are less than 3.0% and are dominated by systematic uncertainties.
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Chen JL, Zhang JY, Chen MM, Wang XZ. [Conservative management of Oehlers type Ⅲ dens invaginatus in maxillary lateral incisors with periapical periodontitis: a report of three cases]. ZHONGHUA KOU QIANG YI XUE ZA ZHI = ZHONGHUA KOUQIANG YIXUE ZAZHI = CHINESE JOURNAL OF STOMATOLOGY 2022; 57:182-185. [PMID: 35152655 DOI: 10.3760/cma.j.cn112144-20210823-00380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
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89
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Zhang QS, Zhang JY, Zheng J, Chen LL. [The application and research progress of organoids in endocrine diseases]. ZHONGHUA NEI KE ZA ZHI 2022; 61:219-223. [PMID: 35090260 DOI: 10.3760/cma.j.cn112138-20210415-00284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
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90
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Zhang YJ, Jiang L, Ahamd S, Chen Y, Zhang JY, Stanley D, Miao H, Ge LQ. The octopamine receptor, OA2B2, modulates stress resistance and reproduction in Nilaparvata lugens Stål (Hemiptera: Delphacidae). INSECT MOLECULAR BIOLOGY 2022; 31:33-48. [PMID: 34480382 DOI: 10.1111/imb.12736] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 08/19/2021] [Accepted: 08/31/2021] [Indexed: 06/13/2023]
Abstract
The brown planthopper (BPH), Nilaparvata lugens (Stål) is a resurgent pest of rice crops throughout Asia. We recently discovered that octopamine (OA) and OA2B2 operate in the BPH mating system, where it mediates a wide range of molecular, physiological and behavioural changes. Here, we report on outcomes of experiments designed to test the hypothesis that OA/OA2B2 signalling mediates responses to three abiotic stressors, starvation, high temperature (37 °C), and induced oxidative stress. We found per os RNAi-mediated OA2B2 silencing led to significantly decreased survival, measured in days, following exposure to each of these stressors. We selected a biologically costly process, reproductive biology, as a biotic stressor. Silencing of OA2B2 led to decreased total protein content in ovaries and fat bodies, downregulated expression of vitellogenin (Vg) and Vg receptor (VgR), inhibited fat body Vg protein synthesis, shortened the oviposition period, prolonged the preoviposition period, reduced the number of laid eggs, body weight and female longevity. In addition, the silencing treatments also led to inhibited ovarian development, and ovarian Vg uptake, reduced numbers of egg masses and offspring and lower hatching rates and population growth index. These data support our hypothesis that OA2B2 acts in mediating BPH resistance to biotic and abiotic stressors.
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91
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Zhang JY, Zhang XY, Peng Y, Yang ZZ. [Current situation and research progress of quality of life evaluation scale in clinical application of lung cancer patients with brain metastasis]. ZHONGHUA NEI KE ZA ZHI 2022; 61:234-238. [PMID: 35090263 DOI: 10.3760/cma.j.cn112138-20210719-00491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
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92
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Wang R, Yang MY, Zhang JY, Su HQ, Duan J, Mi J, Wang ML. [Performance evaluation and validation of automated digital image analysis in peripheral blood cells morphology examination]. ZHONGHUA YI XUE ZA ZHI 2022; 102:261-266. [PMID: 35073674 DOI: 10.3760/cma.j.cn112137-20211007-02213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To verify and evaluate the performance of automated digital image(DIA) for peripheral blood cell morphology examination. Methods: Three hundred and seventy-nine routine peripheral blood smears and 18 plasmodium positive peripheral blood smears were collected. Blood smears were made and stained by Wright -Giemsa method.White blood cell (WBC) differentiation of blood smears were pre-classified by DIA (DIA direct classification), re-classified (manually reviewed after DIA classification), and artificially classified under microscope. the inter-assay and intra-assay coefficients of variation (CV) of DIA were respectively calculated for repeatability verification. Taking the artificial microscopy as the gold standard, the sensitivity、specificity and accuracy of DIA were calculated. The DIA ability of peripheral blood blast cell morphological count, platelet (PLT) morphological count and morphological examination of plasmodium were also verified. Results: Except for eosinophils and basophils, the inter-assay and intra-assay CV of WBC classification by DIA in normal samples were < 10%. The CV of WBC classification in abnormal samples increased with the decrease of cell percentage. The sensitivity, specificity and accuracy of DIA pre-classification were 90.5%, 99.2%, 98.2%. Through pre-classification and re-classification by DIA,the results of the blood smears which triggered blast cell alarm had a good correlation with manual classification(r=0.812, 0.983, both P<0.01). The PLT morphological count by DIA had high correlation with hematology analyzer (r=0.946, P<0.01). The deviation absolute value of two methods of PLT count was < 15%, while in PLT aggregation or giant thrombocytosis samples,the deviation absolute value of PLT count by two methods was > 15%. After image acquisition by DIA, 17 plasmodium trophozoites were detected in 18 plasmodium-positive peripheral blood smears, and the images were clear. Conclusions: The DIA system has good repeatability, high sensitivity, specificity and accuracy in peripheral blood WBC classification. Its pre-classification and re-classification results have high correlation with the manual classification results.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KL, Heinsius FH, Heinz CH, Held T, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Lin CX, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu S, Liu T, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XX, Ma XY, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Mo YJ, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pogodin S, Poling R, Prasad V, Qi H, Qi HR, Qi KH, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan DC, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen HF, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun WY, Sun X, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu GF, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yan X, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Yuncu A, Zafar AA, Zeng Y, Zhang AQ, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, Zhang XD, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. First Measurement of Polarizations in the Decay D^{0}→ωφ. PHYSICAL REVIEW LETTERS 2022; 128:011803. [PMID: 35061485 DOI: 10.1103/physrevlett.128.011803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 12/14/2021] [Indexed: 06/14/2023]
Abstract
Using a data sample corresponding to an integrated luminosity of 2.93 fb^{-1} collected at a center-of-mass energy sqrt[s]=3.773 GeV by the BESIII detector, the decay D^{0}→ωϕ is observed for the first time. The branching fraction is measured to be (6.48±0.96±0.40)×10^{-4} with a significance of 6.3σ, where the first and second uncertainties are statistical and systematic, respectively. An angular analysis reveals that the ϕ and ω mesons from the D^{0}→ωϕ decay are transversely polarized. The 95% confidence level upper limit on longitudinal polarization fraction is set to be less than 0.24, which is inconsistent with current theoretical expectations and challenges our understanding of the underlying dynamics in charm meson decays.
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Li CX, Lin JT, Zhang Q, Wang JR, Gao SN, Li HW, Wan JX, Zhang JY, Zhang MY, Gao X. [Human bone marrow mesenchymal stem cells improve steroid resistance of human airway epithelial BEAS-2B cells in vitro]. ZHONGHUA JIE HE HE HU XI ZA ZHI = ZHONGHUA JIEHE HE HUXI ZAZHI = CHINESE JOURNAL OF TUBERCULOSIS AND RESPIRATORY DISEASES 2021; 44:1097-1102. [PMID: 34915624 DOI: 10.3760/cma.j.cn112147-20210607-00398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To explore the effect of human bone marrow mesenchymal stem cells(MSC) on the steroid resistance of human airway epithelial cells. Methods: Ovalbumin (OVA)/lipopolysaccharide (LPS) were used to construct steroid resistant BEAS-2B cells, which were then co-cultured with MSC. Groups were set as follows: blank group, model group, Glucocorticoid group, MSC group, MSC+Glucocorticoid group (MSC+bud group). The expression of interleukin (IL)-8 in the cell supernatant was detected by enzyme-linked immunosorbent assay (ELISA); the expression of reactive oxygen species (ROS) in the cells was detected by flow cytometry; the expression of glucocorticoid receptor α (GRα) and histone deacetylase 2 (HDAC2) protein in the cell was detected by Western blotting; and the expression of GRα and HDAC2 mRNA was detected by reverse transcription-polymerase chain reaction (RTPCR). Results: The expression level of IL-8 in the MSC group was significantly lower than that in the Glucocorticoid group (31.7±0.7 vs. 49.8±3.6, P<0.01). The expression of ROS in the MSC group was significantly lower than that in the Glucocorticoid group (2754±154 vs.4624±228, P<0.05). The expression level of HDAC2 mRNA in the MSC group was significantly higher than that in the Glucocorticoid group(1.749±0.005 vs. 1.283±0.098, P<0.05). The expression level of GRα mRNA in the MSC group was significantly higher than that in the Glucocorticoid group (1.623±0.079 vs.1.047±0.220, P<0.01). The expression of HDAC2 protein in the MSC group was significantly higher than that in the Glucocorticoid group (1.067±0.100 vs. 0.620±0.083, P<0.01). The expression of GRα protein in the MSC group was significantly higher than that in the Glucocorticoid group (0.834±0.053 vs. 0.579±0.017, P<0.01). ROS was positively correlated with the IL-8 expression (r=0.796, P<0.01) and negatively correlated with the HDAC2 and GRα mRNA expression (r=-0.893 3, P<0.01; r=0.931 4, P<0.01, respectively), as well as the HDAC2 and GRα Protein expression (r=-0.929 5, P<0.01;r=-0.864 3, P<0.01, respectively). Conclusions: Human MSC can improve steroid resistance of airway epithelial cells in an exocrine manner. The mechanism may be related to the down-regulation of ROS and up-regulation of HDAC2, which lead to GRα overexpression. In addition, MSC may improve the steroid resistance by reducing the expression of IL-8.
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Deng T, Zhang JY, Yang XM. [Research and development technology platform and research progress of universal influenza vaccine]. ZHONGHUA YU FANG YI XUE ZA ZHI [CHINESE JOURNAL OF PREVENTIVE MEDICINE] 2021; 55:1500-1506. [PMID: 34963251 DOI: 10.3760/cma.j.cn112150-20210125-00075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Vaccination is the most effective measure to prevent influenza. However, due to the existence of antigen drift and/or antigen shift of influenza virus, the vaccine strains often do not match the epidemic strains, so that the protection provided by influenza vaccine is still limited. With the rapid development of new vaccine technology, a kind of influenza vaccine with extensive protection or universal has attracted great attention. It can effectively induce humoral and cellular immunity against the conserved epitopes of influenza virus, provide good protection against various types/subtypes of influenza virus, and has a rapid production platform, which is the ideal goal for the development of a new generation of universal influenza vaccine. This article reviews the latest research progress of influenza universal vaccine.
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Chen QP, Wu L, Zhang SS, Liu LL, Jin WT, Zhang JY, Zhang YP, Yu DN. The complete mitochondrial genome of Rana johnsi (Smith, 2009) (Anura: Ranidae) and its phylogeny. Mitochondrial DNA B Resour 2021; 6:3493-3495. [PMID: 34869888 PMCID: PMC8635646 DOI: 10.1080/23802359.2021.2002213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Rana johnsi (Smith 2009) firstly considered as the member of genus Pseudorana, has been moved into the genus Rana. In this study, we sequenced the complete mitochondrial (mt) genome of R. johnsi using the Sanger method. The circular mt genome was 17,873 bp in length and contains 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, two ribosome RNA genes, and one control region. The overall nucleotide composition in majority-strand was 28% A, 29% T, 29% C, and 14% G. We discussed the phylogenetic relationship of R. johnsi in genus Rana using ML and BI analyses based on 13 PCGs. Excluding the clade of subgenus Lithobates, Rana draytonii was the basal clade to all other Rana species, which included R. johnsi as the basal clade. The monophyly of genus Rana was supported, whereas Pseudorana was failed to support.
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Zhan N, Liu XH, Tang FY, Zhang JY. [Identification of potential targets and synergistic mechanism of Kushen Decoction for the treatment of cryptosporidiosis]. ZHONGGUO XUE XI CHONG BING FANG ZHI ZA ZHI = CHINESE JOURNAL OF SCHISTOSOMIASIS CONTROL 2021; 33:483-495. [PMID: 34791846 DOI: 10.16250/j.32.1374.2021169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
OBJECTIVE To explore the potential targets and synergistic mechanisms of Kushen Decoction for the treatment of cryptosporidiosis using network pharmacology and molecular docking methods. METHODS The main active ingredients of Kushen Decoction were captured from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TC-MSP) and the Universal Protein Resource (UniProt) database, and the potential targets were predicted. In addition, the active ingredients of Kushen Decoction that were not included in the TCMSP database were retrieved in CNKI, WanFang Data, CBM, PubMed and Web of Science databases, and the target genes of all supplemented active ingredients were predicted using the online TargetNet database. Network construction and analysis were performed using the Cytoscape software, and cryptosporidiosis-related targets were retrieved in the Comparative Toxicogenomics Database and GeneCards database. The protein-protein interaction (PPI) network was created using the STRING database, and the DAVID database was used for GO enrichment and KEGG pathway analyses. The tissue distribution of key targets was investigated using the BioGPS database, and the AutoDockTools software was employed to verify the molecular docking results. RESULTS A total of 38 active ingredients of Kushen Decoction were screened, and the core ingredients included quercetin, (+)-14α-hydroxymatrine and apigenin. A total of 831 targets of Kushen Decoction and 512 cryptosporidiosis-related targets were predicted, and PPI network analysis revealed 69 key targets, including AKT1, TNF and IL-6. There were 303 biological processes, 46 molecular functions and 29 cellular components involved in the treatment of cryptosporidiosis with Kushen Decoction, and 13 KEGG pathways played a therapeutic role in the synergistic mechanisms of multiple targets, such as Toll-like receptor (TLR), nuclear factor kappa B(NF)-κB, nucleotide binding oligomerization domain like receptor (NLR) signal pathways. The core targets were mainly distributed in the hematologic and immune systems. Molecular docking analysis showed that the binding energy between active ingredients and key targets were all less than 0 kJ/mol, indicating the strong binding of ligands to receptors. CONCLUSIONS The active ingredients of Kushen Decoction, such as quercetin, (+)-14α-hydroxymatrine and apigenin, may act on targets like AKT1, TNF, IL-6 to modulate TLR, NLR and NF-κB signaling pathways to play a synergistic role in the treatment of cryptosporidiosis in the hematologic and immune system.
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Li JH, Tang CX, Liu TY, Chen YC, Zhou CS, Lu GM, Zhang JY, Zhang LJ, Yang G. [Association of coronary perivascular fat attenuation index, the parameters of plaque and fractional flow reserve]. ZHONGHUA YI XUE ZA ZHI 2021; 101:3214-3220. [PMID: 34689533 DOI: 10.3760/cma.j.cn112137-20210414-00889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore the association of coronary perivascular fat attenuation index (FAI), the parameters of plaque and fractional flow reserve (FFR). Methods: A total of 113 patients (with 141 plaques) (78 males and 35 females, age from 40 to 83 years) with stable coronary artery disease were retrospectively collected from Jingling Hospital and Shanghai Sixth People's Hospital. All the patients underwent coronary CT angiography and invasive FFR examinations. The quantitative and qualitative parameters of plaque and vessel (such as the length and volume of plaque, the characteristics of plaque and high-risk plaque) and the FAI around the plaque were measured. The patients were divided into positive FAI group (n=46) and negative FAI group (n=66) according to the standard of whether the threshold of FAI≥ -70 HU. The quantitative indexes, including age, the length and volume of plaque, minimal lumen area (MLA) and FAI, as well as the qualitative indexed, including the characteristics of plaque, the number and characteristic of high-risk plaque and the number of patients and plaque with positive FFR were compared between the two groups. Further, logistic regression analysis was performed to analyze the correlation among myocardial ischemia, age, the length of plaque, minimal lumen area (MLA), FAI and so on. ROC curve was used for evaluating the performance of each parameter. Results: Compared to the negative FAI group, positive FAI group had lower MLA (2.00±1.33 mm2 vs 4.13±2.41 mm2, P<0.001). The proportion of patients and vessels with FFR<0.75 in positive FAI group were significantly higher than that in negative FAI group (21.3% vs 4.5%, P=0.006; 23.2% vs 8.2%, P=0.016). The FAI between high-risk plaque and non-high-risk plaque had no significant difference (21.2% vs 16.1%, P=0.451). FAI predicted myocardial ischemia (AUC=0.666, P=0.021) and significantly improved the prediction efficiency of complex model(0.915 vs 0.951,P=0.033). Conclusion: Lower MLA and higher incidence of myocardial ischemia were associated with patients with higher FAI. In addition, FAI has a certain prediction efficiency and can provide incremental value for the determination of myocardial ischemia.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KL, Heinsius FH, Heinz CH, Held T, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Lin CX, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu S, Liu T, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XX, Ma XY, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Mo YJ, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Poling R, Prasad V, Qi H, Qi HR, Qi KH, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan DC, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen HF, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun WY, Sun X, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu GF, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yan X, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Yuncu A, Zafar AA, Zeng Y, Zeng Y, Zhang AQ, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, Zhang XD, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Measurement of the Absolute Branching Fraction of D_{s}^{+}→τ^{+}ν_{τ} via τ^{+}→e^{+}ν_{e}ν[over ¯]_{τ}. PHYSICAL REVIEW LETTERS 2021; 127:171801. [PMID: 34739288 DOI: 10.1103/physrevlett.127.171801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 08/26/2021] [Accepted: 09/21/2021] [Indexed: 06/13/2023]
Abstract
Using a dataset of 6.32 fb^{-1} of e^{+}e^{-} annihilation data collected with the BESIII detector at center-of-mass energies between 4178 and 4226 MeV, we have measured the absolute branching fraction of the leptonic decay D_{s}^{+}→τ^{+}ν_{τ} via τ^{+}→e^{+}ν_{e}ν[over ¯]_{τ}, and find B_{D_{s}^{+}→τ^{+}ν_{τ}}=(5.27±0.10±0.12)×10^{-2}, where the first uncertainty is statistical and the second is systematic. The precision is improved by a factor of 2 compared to the previous best measurement. Combining with f_{D_{s}^{+}} from lattice quantum chromodynamics calculations or the |V_{cs}| from the CKMfitter group, we extract |V_{cs}|=0.978±0.009±0.012 and f_{D_{s}^{+}}=(251.1±2.4±3.0) MeV, respectively. Combining our result with the world averages of B_{D_{s}^{+}→τ^{+}ν_{τ}} and B_{D_{s}^{+}→μ^{+}ν_{μ}}, we obtain the ratio of the branching fractions B_{D_{s}^{+}→τ^{+}ν_{τ}}/B_{D_{s}^{+}→μ^{+}ν_{μ}}=9.72±0.37, which is consistent with the standard model prediction of lepton flavor universality.
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Xu KK, Chen QP, Guan JY, Zhang ZY, Storey KB, Yu DN, Zhang JY. The mitochondrial genome of Eurycantha calcarata Lucas, 1869 (Phasmatodea: Lonchodinae) and its phylogeny. Mitochondrial DNA B Resour 2021; 6:3109-3111. [PMID: 34621991 PMCID: PMC8491702 DOI: 10.1080/23802359.2021.1964403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022] Open
Abstract
The Lonchodinae (Phasmatodea: Phasmatidae) is rich in insect species with more than 330 species of 40 genera. The phylogenetic relationships within Lonchodinae have been under debate. We successfully sequenced the complete mitogenome of Eurycantha calcarata Lucas, 1869 (Phasmatodea: Lonchodinae) with a length of 16,280 bp, which had the same genes and gene arrangements as those of various published papers on stick insects. The whole mitogenome and control region of E. calcarata had a high AT content of 78.2 and 85.9%, respectively. All PCGs used ATN as the start codon, and most PCGs used TAA/TAG as the stop codons excluding COX2 (T), COX3 (TA), and ND5 (TA). To discuss the phylogeny of Lonchodinae, we reconstructed the phylogenetic relationships of 27 species of Phasmatodea including E. calcarata and two species of Embioptera used as outgroups. In BI and ML trees, the monophyly of Lonchodinae and Necrosciinae was well supported, whereas the monophyly of Clitumninae was not recovered. These results indicated that Lonchodinae was a sister clade to Phylliinae and E. calcarata was a sister clade to Phraortes genus.
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