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Zhao X, Zeng W, Geng S, Wang Z. LB979 Mast cell activation via mas-related g protein-coupled receptor X2 is regulated by ryanodine-sensitive calcium stores. J Invest Dermatol 2022. [DOI: 10.1016/j.jid.2022.05.1002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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Li Y, He Z, Ma X, Zeng W, Liu J, Xu W, Xu Z, Wang S, Wen C, Zeng H, Wu J, Chen W, Lu Y. Architectural distortion detection based on superior-inferior directional context and anatomic prior knowledge in digital breast tomosynthesis. Med Phys 2022; 49:3749-3768. [PMID: 35338787 DOI: 10.1002/mp.15631] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 03/12/2022] [Accepted: 03/12/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND In 2020, breast cancer becomes the most leading diagnosed cancer all over the world. The burden is increasing in the prevention and treatment of breast cancer. Accurately detecting breast lesions in screening images is important for early detection of cancer. Architectural distortion (AD) is one of the breast lesions that need to be detected. PURPOSE To develop a deep-learning-based computer-aided detection (CADe) model for AD in digital breast tomosynthesis (DBT). This model uses the superior-inferior directional context of DBT and anatomic prior knowledge to reduce false positive (FP). It can identify some negative samples that cannot be distinguished by deep learning features. METHODS The proposed CADe model consists of three steps. In the first step, a deep learning detection network detects two-dimensional (2D) candidates of ADs in DBT slices with the inputs preprocessed by Gabor filters and convergence measure. In the second step, three-dimensional (3D) candidates are obtained by stacking 2D candidates along superior-inferior direction. In the last step, FP reduction for 3D candidates is implemented based on superior-inferior directional context and anatomic prior knowledge of breast. DBT data from 99 cases with AD were used as the training set to train the CADe model, and data from 208 cases were used as an independent test set (including 108 cases with AD and 100 cases without AD as the control group). The free-response receiver operating characteristic and mean true positive fraction (MTPF) in the range of 0.05-2.0 FPs per volume are used to evaluate the model. RESULTS Compared with the baseline model based on convergence measure, our proposed method demonstrates significant improvement (MTPF: 0.2826 ± 0.0321vs. 0.6640 ± 0.0399). Results of an ablation study show that our proposed context-based and anatomy-based FP reduction methods improve the detection performance. The number of FPs per DBT volume reduces from 2.47 to 1.66 at 80% sensitivity after employing these two schemes. CONCLUSIONS The deep learning model demonstrates practical value for AD detection. The results indicate that introducing superior-inferior directional context and anatomic prior knowledge into model can indeed reduce FPs and improve the performance of CADe model. This article is protected by copyright. All rights reserved.
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Cao Z, Aharonian F, An Q, Bai LX, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Cai H, Cai JT, Cao Z, Chang J, Chang JF, Chen BM, Chen ES, Chen J, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen SH, Chen SZ, Chen TL, Chen XL, Chen Y, Cheng N, Cheng YD, Cui SW, Cui XH, Cui YD, Piazzoli BD, Dai BZ, Dai HL, Dai ZG, Della Volpe D, Dong XJ, Duan KK, Fan JH, Fan YZ, Fan ZX, Fang J, Fang K, Feng CF, Feng L, Feng SH, Feng YL, Gao B, Gao CD, Gao LQ, Gao Q, Gao W, Ge MM, Geng LS, Gong GH, Gou QB, Gu MH, Guo FL, Guo JG, Guo XL, Guo YQ, Guo YY, Han YA, He HH, He HN, He JC, He SL, He XB, He Y, Heller M, Hor YK, Hou C, Hou X, Hu HB, Hu S, Hu SC, Hu XJ, Huang DH, Huang QL, Huang WH, Huang XT, Huang XY, Huang ZC, Ji F, Ji XL, Jia HY, Jiang K, Jiang ZJ, Jin C, Ke T, Kuleshov D, Levochkin K, Li BB, Li C, Li C, Li F, Li HB, Li HC, Li HY, Li J, Li J, Li K, Li WL, Li XR, Li X, Li X, Li Y, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu H, Liu HD, Liu J, Liu JL, Liu JS, Liu JY, Liu MY, Liu RY, Liu SM, Liu W, Liu Y, Liu YN, Liu ZX, Long WJ, Lu R, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Masood A, Min Z, Mitthumsiri W, Montaruli T, Nan YC, Pang BY, Pattarakijwanich P, Pei ZY, Qi MY, Qi YQ, Qiao BQ, Qin JJ, Ruffolo D, Rulev V, Sáiz A, Shao L, Shchegolev O, Sheng XD, Shi JR, Song HC, Stenkin YV, Stepanov V, Su Y, Sun QN, Sun XN, Sun ZB, Tam PHT, Tang ZB, Tian WW, Wang BD, Wang C, Wang H, Wang HG, Wang JC, Wang JS, Wang LP, Wang LY, Wang RN, Wang W, Wang W, Wang XG, Wang XJ, Wang XY, Wang Y, Wang YD, Wang YJ, Wang YP, Wang ZH, Wang ZX, Wang Z, Wang Z, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu S, Wu WX, Wu XF, Xi SQ, Xia J, Xia JJ, Xiang GM, Xiao DX, Xiao G, Xiao HB, Xin GG, Xin YL, Xing Y, Xu DL, Xu RX, Xue L, Yan DH, Yan JZ, Yang CW, Yang FF, Yang JY, Yang LL, Yang MJ, Yang RZ, Yang SB, Yao YH, Yao ZG, Ye YM, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Zeng HD, Zeng TX, Zeng W, Zeng ZK, Zha M, Zhai XX, Zhang BB, Zhang HM, Zhang HY, Zhang JL, Zhang JW, Zhang LX, Zhang L, Zhang L, Zhang PF, Zhang PP, Zhang R, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang YF, Zhang YL, Zhang Y, Zhang Y, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zheng F, Zheng Y, Zhou B, Zhou H, Zhou JN, Zhou P, Zhou R, Zhou XX, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zuo X. Exploring Lorentz Invariance Violation from Ultrahigh-Energy γ Rays Observed by LHAASO. PHYSICAL REVIEW LETTERS 2022; 128:051102. [PMID: 35179919 DOI: 10.1103/physrevlett.128.051102] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 12/06/2021] [Accepted: 12/24/2021] [Indexed: 06/14/2023]
Abstract
Recently, the LHAASO Collaboration published the detection of 12 ultrahigh-energy γ-ray sources above 100 TeV, with the highest energy photon reaching 1.4 PeV. The first detection of PeV γ rays from astrophysical sources may provide a very sensitive probe of the effect of the Lorentz invariance violation (LIV), which results in decay of high-energy γ rays in the superluminal scenario and hence a sharp cutoff of the energy spectrum. Two highest energy sources are studied in this work. No signature of the existence of the LIV is found in their energy spectra, and the lower limits on the LIV energy scale are derived. Our results show that the first-order LIV energy scale should be higher than about 10^{5} times the Planck scale M_{Pl} and that the second-order LIV scale is >10^{-3}M_{Pl}. Both limits improve by at least one order of magnitude the previous results.
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He Z, Li Y, Zeng W, Xu W, Liu J, Ma X, Wei J, Zeng H, Xu Z, Wang S, Wen C, Wu J, Feng C, Ma M, Qin G, Lu Y, Chen W. Can a Computer-Aided Mass Diagnosis Model Based on Perceptive Features Learned From Quantitative Mammography Radiology Reports Improve Junior Radiologists' Diagnosis Performance? An Observer Study. Front Oncol 2021; 11:773389. [PMID: 34976817 PMCID: PMC8719464 DOI: 10.3389/fonc.2021.773389] [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] [Received: 09/09/2021] [Accepted: 11/22/2021] [Indexed: 11/16/2022] Open
Abstract
Radiologists' diagnostic capabilities for breast mass lesions depend on their experience. Junior radiologists may underestimate or overestimate Breast Imaging Reporting and Data System (BI-RADS) categories of mass lesions owing to a lack of diagnostic experience. The computer-aided diagnosis (CAD) method assists in improving diagnostic performance by providing a breast mass classification reference to radiologists. This study aims to evaluate the impact of a CAD method based on perceptive features learned from quantitative BI-RADS descriptions on breast mass diagnosis performance. We conducted a retrospective multi-reader multi-case (MRMC) study to assess the perceptive feature-based CAD method. A total of 416 digital mammograms of patients with breast masses were obtained from 2014 through 2017, including 231 benign and 185 malignant masses, from which we randomly selected 214 cases (109 benign, 105 malignant) to train the CAD model for perceptive feature extraction and classification. The remaining 202 cases were enrolled as the test set for evaluation, of which 51 patients (29 benign and 22 malignant) participated in the MRMC study. In the MRMC study, we categorized six radiologists into three groups: junior, middle-senior, and senior. They diagnosed 51 patients with and without support from the CAD model. The BI-RADS category, benign or malignant diagnosis, malignancy probability, and diagnosis time during the two evaluation sessions were recorded. In the MRMC evaluation, the average area under the curve (AUC) of the six radiologists with CAD support was slightly higher than that without support (0.896 vs. 0.850, p = 0.0209). Both average sensitivity and specificity increased (p = 0.0253). Under CAD assistance, junior and middle-senior radiologists adjusted the assessment categories of more BI-RADS 4 cases. The diagnosis time with and without CAD support was comparable for five radiologists. The CAD model improved the radiologists' diagnostic performance for breast masses without prolonging the diagnosis time and assisted in a better BI-RADS assessment, especially for junior radiologists.
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Zuo Z, Li Y, Peng K, Li X, Tan Q, Mo Y, Lan Y, Zeng W, Qi W. CT texture analysis-based nomogram for the preoperative prediction of visceral pleural invasion in cT1N0M0 lung adenocarcinoma: an external validation cohort study. Clin Radiol 2021; 77:e215-e221. [PMID: 34916048 DOI: 10.1016/j.crad.2021.11.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 11/12/2021] [Indexed: 12/29/2022]
Abstract
AIM To develop a nomogram based on computed tomography (CT) texture analysis for the preoperative prediction of visceral pleural invasion in patients with cT1N0M0 lung adenocarcinoma. MATERIALS AND METHODS A dataset of chest CT containing lung nodules was collected from two institutions, and all surgically resected nodules were classified pathologically based on the presence of visceral pleural invasion. Each nodule on the CT image was segmented automatically by artificial-intelligence software and its CT texture features were extracted. The dataset was divided into training and external validation cohorts according to the institution, and a nomogram for predicting visceral pleural invasion was developed and validated. RESULTS Of a total of 313 patients enrolled from two independent institutions, 63 were diagnosed with visceral pleural invasion. Three-dimensional (3D) CT long diameter, skewness, and sphericity, and chronic obstructive pulmonary disease were identified as independent predictors for visceral pleural invasion by multivariable logistic regression. The nomogram based on multivariable logistic regression showed great discriminative ability, as indicated by a C-index of 0.890 (95% confidence interval [CI]: 0.867-0.914) and 0.864 (95% CI: 0.817-0.911) for the training and external validation cohorts, respectively. Additionally, calibration of the nomogram revealed good predictive ability, as indicated by the Brier score (0.108 and 0.100 for the training and external validation cohorts, respectively). CONCLUSIONS A nomogram was developed that could compute the probability of visceral pleural invasion in patients with cT1N0M0 lung adenocarcinoma with good calibration and discrimination. The nomogram has potential as a reliable tool for clinical evaluation and decision-making.
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Aharonian F, An Q, Axikegu, Bai LX, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Cai H, Cai JT, Cao Z, Cao Z, Chang J, Chang JF, Chang XC, Chen BM, Chen J, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen SH, Chen SZ, Chen TL, Chen XL, Chen Y, Cheng N, Cheng YD, Cui SW, Cui XH, Cui YD, Dai BZ, Dai HL, Dai ZG, Danzengluobu, Volpe DD, Piazzoli BD, Dong XJ, Fan JH, Fan YZ, Fan ZX, Fang J, Fang K, Feng CF, Feng L, Feng SH, Feng YL, Gao B, Gao CD, Gao Q, Gao W, Ge MM, Geng LS, Gong GH, Gou QB, Gu MH, Guo JG, Guo XL, Guo YQ, Guo YY, Han YA, He HH, He HN, He JC, He SL, He XB, He Y, Heller M, Hor YK, Hou C, Hou X, Hu HB, Hu S, Hu SC, Hu XJ, Huang DH, Huang QL, Huang WH, Huang XT, Huang Y, Huang ZC, Ji F, Ji XL, Jia HY, Jiang K, Jiang ZJ, Jin C, Kuleshov D, Levochkin K, Li BB, Li C, Li C, Li F, Li HB, Li HC, Li HY, Li J, Li K, Li WL, Li X, Li X, Li XR, Li Y, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu H, Liu HD, Liu J, Liu JL, Liu JS, Liu JY, Liu MY, Liu RY, Liu SM, Liu W, Liu YN, Liu ZX, Long WJ, Lu R, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Masood A, Mitthumsiri W, Montaruli T, Nan YC, Pang BY, Pattarakijwanich P, Pei ZY, Qi MY, Ruffolo D, Rulev V, Sáiz A, Shao L, Shchegolev O, Sheng XD, Shi JR, Song HC, Stenkin YV, Stepanov V, Sun QN, Sun XN, Sun ZB, Tam PHT, Tang ZB, Tian WW, Wang BD, Wang C, Wang H, Wang HG, Wang JC, Wang JS, Wang LP, Wang LY, Wang RN, Wang W, Wang W, Wang XG, Wang XJ, Wang XY, Wang YD, Wang YJ, Wang YP, Wang Z, Wang Z, Wang ZH, Wang ZX, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu S, Wu WX, Wu XF, Xi SQ, Xia J, Xia JJ, Xiang GM, Xiao G, Xiao HB, Xin GG, Xin YL, Xing Y, Xu DL, Xu RX, Xue L, Yan DH, Yang CW, Yang FF, Yang JY, Yang LL, Yang MJ, Yang RZ, Yang SB, Yao YH, Yao ZG, Ye YM, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Zeng HD, Zeng TX, Zeng W, Zeng ZK, Zha M, Zhai XX, Zhang BB, Zhang HM, Zhang HY, Zhang JL, Zhang JW, Zhang L, Zhang L, Zhang LX, Zhang PF, Zhang PP, Zhang R, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang Y, Zhang Y, Zhang YF, Zhang YL, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zheng F, Zheng Y, Zhou B, Zhou H, Zhou JN, Zhou P, Zhou R, Zhou XX, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zuo X. A dynamic range extension system for LHAASO WCDA-1. RADIATION DETECTION TECHNOLOGY AND METHODS 2021. [DOI: 10.1007/s41605-021-00275-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Liu R, Pan D, Xu Y, Zeng H, He Z, Lin J, Zeng W, Wu Z, Luo Z, Qin G, Chen W. A deep learning-machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors. Eur Radiol 2021; 32:1371-1383. [PMID: 34432121 DOI: 10.1007/s00330-021-08195-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 06/30/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES To build and validate deep learning and machine learning fusion models to classify benign, malignant, and intermediate bone tumors based on patient clinical characteristics and conventional radiographs of the lesion. METHODS In this retrospective study, data were collected with pathologically confirmed diagnoses of bone tumors between 2012 and 2019. Deep learning and machine learning fusion models were built to classify tumors as benign, malignant, or intermediate using conventional radiographs of the lesion and potentially relevant clinical data. Five radiologists compared diagnostic performance with and without the model. Diagnostic performance was evaluated using the area under the curve (AUC). RESULTS A total of 643 patients' (median age, 21 years; interquartile range, 12-38 years; 244 women) 982 radiographs were included. In the test set, the binary category classification task, the radiological model of classification for benign/not benign, malignant/nonmalignant, and intermediate/not intermediate had AUCs of 0.846, 0.827, and 0.820, respectively; the fusion models had an AUC of 0.898, 0.894, and 0.865, respectively. In the three-category classification task, the radiological model achieved a macro average AUC of 0.813, and the fusion model had a macro average AUC of 0.872. In the observation test, the mean macro average AUC of all radiologists was 0.819. With the three-category classification fusion model support, the macro AUC improved by 0.026. CONCLUSION We built, validated, and tested deep learning and machine learning models that classified bone tumors at a level comparable with that of senior radiologists. Model assistance may somewhat help radiologists' differential diagnoses of bone tumors. KEY POINTS • The deep learning model can be used to classify benign, malignant, and intermediate bone tumors. • The machine learning model fusing information from radiographs and clinical characteristics can improve the classification capacity for bone tumors. • The diagnostic performance of the fusion model is comparable with that of senior radiologists and is potentially useful as a complement to radiologists in a bone tumor differential diagnosis.
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Cao Z, Aharonian F, An Q, Bai LX, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Cai H, Cai JT, Cao Z, Chang J, Chang JF, Chen BM, Chen ES, Chen J, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen SH, Chen SZ, Chen TL, Chen XL, Chen Y, Cheng N, Cheng YD, Cui SW, Cui XH, Cui YD, D'Ettorre Piazzoli B, Dai BZ, Dai HL, Dai ZG, Della Volpe D, Dong XJ, Duan KK, Fan JH, Fan YZ, Fan ZX, Fang J, Fang K, Feng CF, Feng L, Feng SH, Feng YL, Gao B, Gao CD, Gao LQ, Gao Q, Gao W, Ge MM, Geng LS, Gong GH, Gou QB, Gu MH, Guo FL, Guo JG, Guo XL, Guo YQ, Guo YY, Han YA, He HH, He HN, He JC, He SL, He XB, He Y, Heller M, Hor YK, Hou C, Hou X, Hu HB, Hu S, Hu SC, Hu XJ, Huang DH, Huang QL, Huang WH, Huang XT, Huang XY, Huang ZC, Ji F, Ji XL, Jia HY, Jiang K, Jiang ZJ, Jin C, Ke T, Kuleshov D, Levochkin K, Li BB, Li C, Li C, Li F, Li HB, Li HC, Li HY, Li J, Li J, Li K, Li WL, Li XR, Li X, Li X, Li Y, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu H, Liu HD, Liu J, Liu JL, Liu JS, Liu JY, Liu MY, Liu RY, Liu SM, Liu W, Liu Y, Liu YN, Liu ZX, Long WJ, Lu R, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Masood A, Min Z, Mitthumsiri W, Montaruli T, Nan YC, Pang BY, Pattarakijwanich P, Pei ZY, Qi MY, Qi YQ, Qiao BQ, Qin JJ, Ruffolo D, Rulev V, Saiz A, Shao L, Shchegolev O, Sheng XD, Shi JY, Song HC, Stenkin YV, Stepanov V, Su Y, Sun QN, Sun XN, Sun ZB, Tam PHT, Tang ZB, Tian WW, Wang BD, Wang C, Wang H, Wang HG, Wang JC, Wang JS, Wang LP, Wang LY, Wang RN, Wang W, Wang W, Wang XG, Wang XJ, Wang XY, Wang Y, Wang YD, Wang YJ, Wang YP, Wang ZH, Wang ZX, Wang Z, Wang Z, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu S, Wu WX, Wu XF, Xi SQ, Xia J, Xia JJ, Xiang GM, Xiao DX, Xiao G, Xiao HB, Xin GG, Xin YL, Xing Y, Xu DL, Xu RX, Xue L, Yan DH, Yan JZ, Yang CW, Yang FF, Yang JY, Yang LL, Yang MJ, Yang RZ, Yang SB, Yao YH, Yao ZG, Ye YM, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Zeng HD, Zeng TX, Zeng W, Zeng ZK, Zha M, Zhai XX, Zhang BB, Zhang HM, Zhang HY, Zhang JL, Zhang JW, Zhang LX, Zhang L, Zhang L, Zhang PF, Zhang PP, Zhang R, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang YF, Zhang YL, Zhang Y, Zhang Y, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zheng F, Zheng Y, Zhou B, Zhou H, Zhou JN, Zhou P, Zhou R, Zhou XX, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zuo X. Peta-electron volt gamma-ray emission from the Crab Nebula. Science 2021; 373:425-430. [PMID: 34261813 DOI: 10.1126/science.abg5137] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 06/23/2021] [Indexed: 11/03/2022]
Abstract
The Crab Nebula is a bright source of gamma rays powered by the Crab Pulsar's rotational energy through the formation and termination of a relativistic electron-positron wind. We report the detection of gamma rays from this source with energies from 5 × 10-4 to 1.1 peta-electron volts with a spectrum showing gradual steepening over three energy decades. The ultrahigh-energy photons imply the presence of a peta-electron volt electron accelerator (a pevatron) in the nebula, with an acceleration rate exceeding 15% of the theoretical limit. We constrain the pevatron's size between 0.025 and 0.1 parsecs and the magnetic field to ≈110 microgauss. The production rate of peta-electron volt electrons, 2.5 × 1036 ergs per second, constitutes 0.5% of the pulsar spin-down luminosity, although we cannot exclude a contribution of peta-electron volt protons to the production of the highest-energy gamma rays.
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Aharonian F, An Q, Bai LX, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Cai H, Cai JT, Cao Z, Cao Z, Chang J, Chang JF, Chang XC, Chen BM, Chen J, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen SH, Chen SZ, Chen TL, Chen XL, Chen Y, Cheng N, Cheng YD, Cui SW, Cui XH, Cui YD, Dai BZ, Dai HL, Dai ZG, Della Volpe D, D'Ettorre Piazzoli B, Dong XJ, Fan JH, Fan YZ, Fan ZX, Fang J, Fang K, Feng CF, Feng L, Feng SH, Feng YL, Gao B, Gao CD, Gao Q, Gao W, Ge MM, Geng LS, Gong GH, Gou QB, Gu MH, Guo JG, Guo XL, Guo YQ, Guo YY, Han YA, He HH, He HN, He JC, He SL, He XB, He Y, Heller M, Hor YK, Hou C, Hou X, Hu HB, Hu S, Hu SC, Hu XJ, Huang DH, Huang QL, Huang WH, Huang XT, Huang ZC, Ji F, Ji XL, Jia HY, Jiang K, Jiang ZJ, Jin C, Kuleshov D, Levochkin K, Li BB, Li C, Li C, Li F, Li HB, Li HC, Li HY, Li J, Li K, Li WL, Li X, Li X, Li XR, Li Y, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu H, Liu HD, Liu J, Liu JL, Liu JS, Liu JY, Liu MY, Liu RY, Liu SM, Liu W, Liu YN, Liu ZX, Long WJ, Lu R, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Masood A, Mitthumsiri W, Montaruli T, Nan YC, Pang BY, Pattarakijwanich P, Pei ZY, Qi MY, Ruffolo D, Rulev V, Sáiz A, Shao L, Shchegolev O, Sheng XD, Shi JR, Song HC, Stenkin YV, Stepanov V, Sun QN, Sun XN, Sun ZB, Tam PHT, Tang ZB, Tian WW, Wang BD, Wang C, Wang H, Wang HG, Wang JC, Wang JS, Wang LP, Wang LY, Wang RN, Wang W, Wang W, Wang XG, Wang XJ, Wang XY, Wang YD, Wang YJ, Wang YP, Wang Z, Wang Z, Wang ZH, Wang ZX, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu S, Wu WX, Wu XF, Xi SQ, Xia J, Xia JJ, Xiang GM, Xiao G, Xiao HB, Xin GG, Xin YL, Xing Y, Xu DL, Xu RX, Xue L, Yan DH, Yang CW, Yang FF, Yang JY, Yang LL, Yang MJ, Yang RZ, Yang SB, Yao YH, Yao ZG, Ye YM, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Zeng HD, Zeng TX, Zeng W, Zeng ZK, Zha M, Zhai XX, Zhang BB, Zhang HM, Zhang HY, Zhang JL, Zhang JW, Zhang L, Zhang L, Zhang LX, Zhang PF, Zhang PP, Zhang R, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang Y, Zhang Y, Zhang YF, Zhang YL, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zheng F, Zheng Y, Zhou B, Zhou H, Zhou JN, Zhou P, Zhou R, Zhou XX, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zuo X, Huang XY. Extended Very-High-Energy Gamma-Ray Emission Surrounding PSR J0622+3749 Observed by LHAASO-KM2A. PHYSICAL REVIEW LETTERS 2021; 126:241103. [PMID: 34213924 DOI: 10.1103/physrevlett.126.241103] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 03/23/2021] [Accepted: 05/10/2021] [Indexed: 06/13/2023]
Abstract
We report the discovery of an extended very-high-energy (VHE) gamma-ray source around the location of the middle-aged (207.8 kyr) pulsar PSR J0622+3749 with the Large High-Altitude Air Shower Observatory (LHAASO). The source is detected with a significance of 8.2σ for E>25 TeV assuming a Gaussian template. The best-fit location is (right ascension, declination) =(95.47°±0.11°,37.92°±0.09°), and the extension is 0.40°±0.07°. The energy spectrum can be described by a power-law spectrum with an index of -2.92±0.17_{stat}±0.02_{sys}. No clear extended multiwavelength counterpart of the LHAASO source has been found from the radio to sub-TeV bands. The LHAASO observations are consistent with the scenario that VHE electrons escaped from the pulsar, diffused in the interstellar medium, and scattered the interstellar radiation field. If interpreted as the pulsar halo scenario, the diffusion coefficient, inferred for electrons with median energies of ∼160 TeV, is consistent with those obtained from the extended halos around Geminga and Monogem and much smaller than that derived from cosmic ray secondaries. The LHAASO discovery of this source thus likely enriches the class of so-called pulsar halos and confirms that high-energy particles generally diffuse very slowly in the disturbed medium around pulsars.
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Cao Z, Aharonian FA, An Q, Axikegu, Bai LX, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Cai H, Cai JT, Cao Z, Chang J, Chang JF, Chang XC, Chen BM, Chen J, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen SH, Chen SZ, Chen TL, Chen XL, Chen Y, Cheng N, Cheng YD, Cui SW, Cui XH, Cui YD, Dai BZ, Dai HL, Dai ZG, Danzengluobu, Della Volpe D, D Ettorre Piazzoli B, Dong XJ, Fan JH, Fan YZ, Fan ZX, Fang J, Fang K, Feng CF, Feng L, Feng SH, Feng YL, Gao B, Gao CD, Gao Q, Gao W, Ge MM, Geng LS, Gong GH, Gou QB, Gu MH, Guo JG, Guo XL, Guo YQ, Guo YY, Han YA, He HH, He HN, He JC, He SL, He XB, He Y, Heller M, Hor YK, Hou C, Hou X, Hu HB, Hu S, Hu SC, Hu XJ, Huang DH, Huang QL, Huang WH, Huang XT, Huang ZC, Ji F, Ji XL, Jia HY, Jiang K, Jiang ZJ, Jin C, Kuleshov D, Levochkin K, Li BB, Li C, Li C, Li F, Li HB, Li HC, Li HY, Li J, Li K, Li WL, Li X, Li X, Li XR, Li Y, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu H, Liu HD, Liu J, Liu JL, Liu JS, Liu JY, Liu MY, Liu RY, Liu SM, Liu W, Liu YN, Liu ZX, Long WJ, Lu R, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Masood A, Mitthumsiri W, Montaruli T, Nan YC, Pang BY, Pattarakijwanich P, Pei ZY, Qi MY, Ruffolo D, Rulev V, Sáiz A, Shao L, Shchegolev O, Sheng XD, Shi JR, Song HC, Stenkin YV, Stepanov V, Sun QN, Sun XN, Sun ZB, Tam PHT, Tang ZB, Tian WW, Wang BD, Wang C, Wang H, Wang HG, Wang JC, Wang JS, Wang LP, Wang LY, Wang RN, Wang W, Wang W, Wang XG, Wang XJ, Wang XY, Wang YD, Wang YJ, Wang YP, Wang Z, Wang Z, Wang ZH, Wang ZX, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu S, Wu WX, Wu XF, Xi SQ, Xia J, Xia JJ, Xiang GM, Xiao G, Xiao HB, Xin GG, Xin YL, Xing Y, Xu DL, Xu RX, Xue L, Yan DH, Yang CW, Yang FF, Yang JY, Yang LL, Yang MJ, Yang RZ, Yang SB, Yao YH, Yao ZG, Ye YM, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Zeng HD, Zeng TX, Zeng W, Zeng ZK, Zha M, Zhai XX, Zhang BB, Zhang HM, Zhang HY, Zhang JL, Zhang JW, Zhang L, Zhang L, Zhang LX, Zhang PF, Zhang PP, Zhang R, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang Y, Zhang Y, Zhang YF, Zhang YL, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zheng F, Zheng Y, Zhou B, Zhou H, Zhou JN, Zhou P, Zhou R, Zhou XX, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zuo X. Ultrahigh-energy photons up to 1.4 petaelectronvolts from 12 γ-ray Galactic sources. Nature 2021; 594:33-36. [PMID: 34002091 DOI: 10.1038/s41586-021-03498-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 03/26/2021] [Indexed: 02/04/2023]
Abstract
The extension of the cosmic-ray spectrum beyond 1 petaelectronvolt (PeV; 1015 electronvolts) indicates the existence of the so-called PeVatrons-cosmic-ray factories that accelerate particles to PeV energies. We need to locate and identify such objects to find the origin of Galactic cosmic rays1. The principal signature of both electron and proton PeVatrons is ultrahigh-energy (exceeding 100 TeV) γ radiation. Evidence of the presence of a proton PeVatron has been found in the Galactic Centre, according to the detection of a hard-spectrum radiation extending to 0.04 PeV (ref. 2). Although γ-rays with energies slightly higher than 0.1 PeV have been reported from a few objects in the Galactic plane3-6, unbiased identification and in-depth exploration of PeVatrons requires detection of γ-rays with energies well above 0.1 PeV. Here we report the detection of more than 530 photons at energies above 100 teraelectronvolts and up to 1.4 PeV from 12 ultrahigh-energy γ-ray sources with a statistical significance greater than seven standard deviations. Despite having several potential counterparts in their proximity, including pulsar wind nebulae, supernova remnants and star-forming regions, the PeVatrons responsible for the ultrahigh-energy γ-rays have not yet been firmly localized and identified (except for the Crab Nebula), leaving open the origin of these extreme accelerators.
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Feng J, Zeng W, Lu H. 530 Analysis of BRAF mutation and expression of NGFR and P16 in nevus and melanoma. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Wang Y, Gu Y, Zeng W, Lan Y, Zhang W, Lu H. 502 Expression, distribution and subcellular location of RGR in human skin. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.527] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Zeng W, Ma Y, Feng J, Zhang W, Wang Y, Lu H. 531 Opsin 3 promotes invasion of melanoma cells in an artificial melanoma model. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Dai Z, Wang E, Lee E, Zeng W, Perez-Lorenzo R, Christiano A. 038 High-throughput single-cell αβ TCR sequencing identifies pathogenic CD8+ T cell clones that are sufficient to induce alopecia areata in a C3H/HeJ retrogenic model. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Zeng W, Bouey J, Uretsky E, Avila C, Li G, Shen J, Fan X. Strengthening public health governance for disease control: experience from China's approach to managing the COVID-19 pandemic. Public Health 2021; 193:124-125. [PMID: 33812080 PMCID: PMC7923847 DOI: 10.1016/j.puhe.2021.02.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 02/07/2021] [Indexed: 11/18/2022]
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Zhang C, Feng W, Hou R, Zeng W, Zhang Q, Yu W, Cai X, Fu X. P17.01 Adaptive Elastic-Net Nomogram Predicting Disease-Free Survival in Resected Stage IIIA (N2) Non–Small Cell Lung Cancer. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.01.554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Cai WL, Zeng W, Zhu BY, Liu HH, Liu JL. MiR-137 affects bone mineral density in osteoporosis rats through regulating RUNX2. EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES 2021; 24:1023-1029. [PMID: 32096181 DOI: 10.26355/eurrev_202002_20152] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To study the influence of micro ribonucleic acid (miR)-137 on osteoporosis rats by regulating runt-related transcription factor 2 (RUNX2). MATERIALS AND METHODS A total of 36 Sprague-Dawley rats were randomly assigned to the normal group (n=12), model group (n=12), and inhibitor group (n=12). No treatment was performed in the normal group. The osteoporosis model in rats was prepared in the model group, and miR-137 inhibitor was administered in osteoporosis rats of inhibitor group. Following 12 weeks of intervention, sampling was conducted. The expression of RUNX2 was detected via immunohistochemistry, and its protein expression level was determined via Western blotting. Quantitative Polymerase Chain Reaction (qPCR) was carried out to detect the mRNA level of miR-137. The contents of serum bone Gla protein (BGP) and total alkaline phosphatase (TALP) were measured using enzyme-linked immunosorbent assay (ELISA). Finally, bone mineral density was determined with a dual-energy X-ray absorptiometry instrument. RESULTS According to the immunohistochemistry detection, the rats in model group and inhibitor group had a notably lower positive expression level of RUNX2 than normal group (p<0.05), and its expression level in the inhibitor group was substantially higher than that in the model group (p<0.05). Western blotting results showed that compared with that in the normal group, the protein expression level of RUNX2 was notably lowered in the model and inhibitor group (p<0.05), which was markedly higher in the inhibitor group than that in the model group (p<0.05). It was found through the qPCR that the expression level of miR-137 was remarkably raised in both model group and inhibitor group compared with that in the normal group, showing statistically significant differences (p<0.05). The rats in the inhibitor group had a remarkably lower expression level of miR-137 than the model group (p<0.05). ELISA results revealed that the model group and inhibitor group had substantially lower contents of serum BGP and TALP than the normal group (p<0.05), and that their contents rose dramatically in the inhibitor group compared with that in the model group (p<0.05). Additionally, based on the measurement of bone mineral density, compared with that in the normal group, bone mineral density declined considerably in the model group and inhibitor group (p<0.05). It was markedly elevated in inhibitor group in comparison with that in the model group (p<0.05). CONCLUSIONS MiR-137 regulates RUNX2 to affect the bone mineral density of osteoporosis model rats.
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Lan Y, Zeng W, Dong X, Lu H. Opsin 5 is a key regulator of ultraviolet radiation-induced melanogenesis in human epidermal melanocytes. Br J Dermatol 2021; 185:391-404. [PMID: 33400324 PMCID: PMC8453816 DOI: 10.1111/bjd.19797] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/03/2021] [Indexed: 12/24/2022]
Abstract
Background Human skin, which is constantly exposed to solar ultraviolet radiation (UVR), has a unique ability to respond by increasing its pigmentation in a protective process driven by melanogenesis in human epidermal melanocytes (HEMs). However, the molecular mechanisms used by HEMs to detect and respond to UVR remain unclear. Objectives To investigate the function and potential mechanism of opsin 5 (OPN5), a photoreceptor responsive to UVR wavelengths, in melanogenesis in HEMs. Methods Melanin content in HEMs was determined using the NaOH method, and activity of tyrosinase (TYR) (a key enzyme in melanin synthesis) was determined by the l‐DOPA method. OPN5 expression in UVR‐treated vs. untreated HEMs and explant tissues was detected by reverse‐transcription quantitative polymerase chain reaction (RT‐qPCR), Western blotting and immunofluorescence. Short interfering RNA‐mediated OPN5 knockdown and a lentivirus OPN5 overexpression model were used to examine their respective effects on TYR, tyrosinase‐related protein 1 (TRP1), TRP2 and microphthalmia‐associated transcription factor (MITF) expression, under UVR. Changes in expression of TYR, TRP1 and TRP2 caused by changes in OPN5 expression level were detected by RT‐qPCR and Western blot. Furthermore, changes in signalling pathway proteins were assayed. Results We found that OPN5 is the key sensor in HEMs responsible for UVR‐induced melanogenesis. OPN5‐induced melanogenesis required Ca2+‐dependent G protein‐coupled receptor‐ and protein kinase C signal transduction, thus contributing to the UVR‐induced MITF response to mediate downstream cellular effects, and providing evidence of OPN5 function in mammalian phototransduction. Remarkably, OPN5 activation was necessary for UVR‐induced increase in cellular melanin and has an inherent function in melanocyte melanogenesis. Conclusions Our results provide insight into the molecular mechanisms of UVR sensing and phototransduction in melanocytes, and may reveal molecular targets for preventing pigmentation or pigment diseases.
What is already known about this topic?
Ultraviolet radiation (UVR) induces a protective response to DNA damage mediated by melanin synthesis in human epidermal melanocytes (HEMs). Tyrosinase (TYR), with tyrosinase‐related proteins (TRP1, TRP2), are the key enzymes for melanin synthesis. Microphthalmia‐associated transcription factor regulates key genes for melanocyte development and differentiation, and can stimulate melanogenesis by activating transcription of TYR and other pigmentation genes, including TRP1. Opsin 5 (OPN5) is known to function as a photoreceptor responsive to wavelengths in the near UV spectrum.
What does this study add?UVR induces melanogenesis in HEMs via OPN5. OPN5 regulates expression of TYR, TRP1 and TRP2 through the calcium‐dependent G protein‐coupled and protein kinase C signalling pathways. OPN5 has an inherent role in HEMs in mediating melanogenesis.
What is the translational message?OPN5 was discovered as a key sensor for UVR‐induced melanogenesis in human skin melanocytes. It could be a target for early treatment of pigmentation or pigment diseases, to provide a more personalized and economically feasible method.
Linked Comment: L.V.M. de Assis and A.M. de Lauro Castrucci. Br J Dermatol 2021; 185:249–250. Plain language summary available online
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Cai WL, Zeng W, Liu HH, Zhu BY, Liu JL, Liu Y. LncRNA LINC00707 promotes osteogenic differentiation of hBMSCs through the Wnt/β-catenin pathway activated by LINC00707/miR-145/LRP5 axis. EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES 2020; 24:18-28. [PMID: 31957814 DOI: 10.26355/eurrev_202001_19891] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Human bone marrow mesenchymal stem cells (hBMSCs) have a strong self-renewal potential and osteogenic differentiation ability, thus providing a new method for bone defect repair research. LncRNA LINC00707 participates in the regulation of osteogenic differentiation of hBMSCs and our aim was to explore the potential regulatory mechanism. MATERIALS AND METHODS Firstly, quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of LINC00707, miR-145, the low-density lipoprotein receptor-related protein 5 (LRP5) and osteogenesis-related genes. Next, alkaline phosphatase (ALP) activity assay was used to measure the relative activity of ALP in hBMSCs. The protein levels of LRP5 and osteogenesis-related genes were detected by Western blot. Finally, the relationship among LINC00707, miR-145 and LRP5 were predicted by online software and verified by Dual-Luciferase reporter assay, RNA pull-down and RNA immunoprecipitation (RIP). RESULTS LINC00707 and osteogenesis-related genes were gradually upregulated during osteogenesis of hBMSCs. Meanwhile, overexpression of LINC00707 promoted osteogenic differentiation of hBMSCs. Interestingly, we found that LINC00707 negatively regulated the miR-145 expression and osteogenic differentiation functions by directly interacting with miR-145, and LINC00707 affected the functions of LRP5 by sponging miR-145 in hBMSCs. Moreover, LINC00707 promoted the Wnt/β-catenin pathway through the LINC00707/miR-145/LRP5 axis. CONCLUSIONS LncRNA LINC00707 promoted osteogenic differentiation of hBMSCs by targeting LRP5 mediated by miR-145 through the activation of the Wnt/β-catenin pathway.
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Zhang C, Feng W, Zhang Q, Hou R, Zeng W, Yu W, Cai X, Fu X. Prognostic Index for Estimating the Effect of Postoperative Radiotherapy in Pathologic Stage IIIA (N2) Non–Small Cell Lung Cancer: A Real-World Validation Study. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.1257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Yang YX, Kang M, An XQ, Zeng W, Yang ZW, Ma HC. Clean and Selective Oxidation of Alcohols with Oxone and
Phase-Transfer Catalysts in Water. RUSSIAN JOURNAL OF ORGANIC CHEMISTRY 2020. [DOI: 10.1134/s1070428020100206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Tao C, Zeng W, Zhang Q, Liu G, Wu F, Shen H, Zhang W, Bo H, Shao H. Effects of the prebiotic inulin-type fructans on post-antibiotic reconstitution of the gut microbiome. J Appl Microbiol 2020; 130:634-649. [PMID: 32813896 DOI: 10.1111/jam.14827] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 08/14/2020] [Accepted: 08/17/2020] [Indexed: 12/20/2022]
Abstract
AIMS Interventions using prebiotic inulin-type fructans (ITFs) are widely prescribed to modulate the gut microbiota composition and activity to promote health. However, the impacts of ITFs on post-antibiotic reconstitution of the gut microbiome remain incompletely understood. The aim of the present study was to investigate the effects of ITFs supplementation on intestinal inflammation, the composition of the intestinal microbiota and the colonic transcriptome after antibiotic treatment. METHODS AND RESULTS Male BALB/c mice were subjected to an antibiotic cocktail (ABx) treatment for 7 days, and their microbiomes were then reconstituted either spontaneously or with ITFs supplementation (5%) for 14 days. Our data showed that ITFs supplementation delayed the recovery of antibiotic-induced colitis compared with the spontaneous recovery. Neither ITFs supplementation nor spontaneous recovery could restore the microbial community composition at the genus level back to its initial composition. ITFs supplementation increased the relative abundance of some beneficial bacteria and butyrate levels, but resulted in selective blooms of some opportunistic pathogens and elevated the pathways associated with diseases linked to gut microbiota function. Both ITFs supplementation and spontaneous recovery could restore the colonic transcriptome nearly to the initial profile to a certain extent; however, ITFs supplementation delayed the restoration of the immunoglobulin genes compared to spontaneous recovery. CONCLUSION These data showed that post-antibiotic ITFs consumption did not always lead to beneficial effects but might lead to potential adverse effects in the context of dysbiosis. SIGNIFICANCE AND IMPACT OF THE STUDY These findings highlighted that caution is required when supplementing ITFs to restore intestinal homeostasis in the context of dysbiosis resulting from broad-spectrum antibiotics.
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Gao X, Wang S, Zeng W, Chen S, Wu J, Lin X, Liu Y, Sun Z, Feng L. Clinical and immunologic features among COVID-19-affected mother-infant pairs: antibodies to SARS-CoV-2 detected in breast milk. New Microbes New Infect 2020; 37:100752. [PMID: 32904990 PMCID: PMC7462625 DOI: 10.1016/j.nmni.2020.100752] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 08/22/2020] [Accepted: 08/26/2020] [Indexed: 01/22/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic remains threatening to women and children, but clinical evidence regarding women during pregnancy, puerperium and lactation is limited. We assessed clinical and immunologic features of and breastfeeding advice provided to mother–infant pairs. This observational analysis was conducted in a tertiary-care centre in Wuhan, China. Pregnant patients with laboratory-confirmed COVID-19 who delivered during hospitalization were enrolled. Clinical characteristics and serial specimens of the mother–infant pairs were examined, supplemented with follow-ups regarding recovery and breastfeeding. Fourteen pregnant patients had live births and recovered well; four patients continued breastfeeding while taking precautions. No neonatal infections were observed. No infants developed COVID-19 during breastfeeding. Common maternal symptoms were fever (11/14, 78.1%) and cough (6/14, 42.9%). A pregnancy-specific symptom was abnormal foetal movement, which was noticed by three patients (21.4%). The mean virus shedding time was 9 days (standard deviation, 6 days; range, 1–22 days). The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome was not detected in breast milk or maternal vaginal secretions. Immunologic assay revealed seroconversion of IgM on day 8 after onset and IgG on day 28. Both IgM and IgG antibodies to SARS-CoV-2 were detected in breast milk, cord blood and neonatal serum. The study results suggest that passive acquisition of antibodies against SARS-CoV-2 is available by ingesting breast milk. Breastfeeding has a low risk of transmitting SARS-CoV-2 or escalating maternal disease, so continuing breastfeeding with prudent precautions is encouraged.
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Huang H, Huang H, Zeng W, Fan F. Third sacral foramen morphometry analysis in Chinese and lead implantation for sacral neuromodulation. EUR UROL SUPPL 2020. [DOI: 10.1016/s2666-1683(20)33571-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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Zhang W, Zeng W, Liu Z, Dong X, Luo H, Zheng Z, He Z, Ye T, Lu H. 395 Burden of malignant skin melanoma in Worldwide, 1990-2017: An analysis of the Global Burden of Disease Study 2017. J Invest Dermatol 2020. [DOI: 10.1016/j.jid.2020.03.403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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