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23 results on '"Zhang, Y.L."'

7. Absolute calibration of LHAASO WFCTA camera based on LED

Author

Aharonian, F., An, Q., Axikegu, Bai, L.X., Bai, Y.X., Bao, Y.W., Bastieri, D., Bi, X.J., Bi, Y.J., Cai, H., Cai, J.T., Cao, Zhen, Cao, Zhe, Chang, J., Chang, J.F., Chen, B.M., Chen, E.S., Chen, J., Chen, Liang, Chen, Long, Chen, M.J., Chen, M.L., Chen, Q.H., Chen, S.H., Chen, S.Z., Chen, T.L., Chen, X.L., Chen, Y., Cheng, N., Cheng, Y.D., Cui, S.W., Cui, X.H., Cui, Y.D., Dai, B.Z., Dai, H.L., Dai, Z.G., Danzengluobu, della Volpe, D., Piazzoli, B. D’Ettorre, Dong, X.J., Duan, K.K., Fan, J.H., Fan, Y.Z., Fan, Z.X., Fang, J., Fang, K., Feng, C.F., Feng, L., Feng, S.H., Feng, Y.L., Fu, Y.T., Gan, H.Y., Gao, B., Gao, C.D., Gao, L.Q., Gao, Q., Gao, W., Ge, M.M., Geng, L.S., Gong, G.H., Gou, Q.B., Gu, M.H., Guo, F.L., Guo, J.G., Guo, X.L., Guo, Y.Q., Guo, Y.Y., Han, Y.A., He, H.H., He, H.N., He, J.C., He, S.L., He, X.B., He, Y., Heller, M., Hor, Y.K., Hou, C., Hu, H.B., Hu, S., Hu, S.C., Hu, X.J., Huang, D.H., Huang, Q.L., Huang, W.H., Huang, X.T., Huang, X.Y., Huang, Z.C., Ji, F., Ji, X.L., Jia, H.Y., Jiang, K., Jiang, Z.J., Jin, C., Ke, T., Kuleshov, D., Levochkin, K., Li, B.B., Li, Cong, Li, Cheng, Li, F., Li, H.B., Li, H.C., Li, H.Y., Li, J., Li, K., Li, W.L., Li, Xin, Li, X.R., Li, Y., Li, Y.Z., Li, Zhe, Li, Zhuo, Liang, E.W., Liang, Y.F., Lin, S.J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H.D., Liu, J., Liu, J.L., Liu, J.S., Liu, J.Y., Liu, M.Y., Liu, R.Y., Liu, S.M., Liu, W., Liu, Y., Liu, Y.N., Liu, Z.X., Long, W.J., Lu, R., Lv, H.K., Ma, B.Q., Ma, L.L., Ma, X.H., Mao, J.R., Masood, A., Min, Z., Mitthumsiri, W., Montaruli, T., Nan, Y.C., Pang, B.Y., Pattarakijwanich, P., Pei, Z.Y., Qi, M.Y., Qi, Y.Q., Qiao, B.Q., Qin, J.J., Ruffolo, D., Rulev, V., Sáiz, A., Shao, L., Shchegolev, O., Sheng, X.D., Shi, J.Y., Song, H.C., Stenkin, Yu.V., Stepanov, V., Su, Y., Sun, Q.N., Sun, X.N., Sun, Z.B., Tam, P.H.T., Tang, Z.B., Tian, W.W., Wang, B.D., Wang, C., Wang, H., Wang, H.G., Wang, J.C., Wang, J.S., Wang, L.P., Wang, L.Y., Wang, R.N., Wang, W., Wang, X.G., Wang, X.J., Wang, X.Y., Wang, Y., Wang, Y.D., Wang, Y.J., Wang, Y.P., Wang, Z.H., Wang, Z.X., Wang, Zhen, Wang, Zheng, Wei, D.M., Wei, J.J., Wei, Y.J., Wen, T., Wu, C.Y., Wu, H.R., Wu, S., Wu, W.X., Wu, X.F., Xi, S.Q., Xia, J., Xia, J.J., Xiang, G.M., Xiao, D.X., Xiao, G., Xiao, H.B., Xin, G.G., Xin, Y.L., Xing, Y., Xu, D.L., Xu, R.X., Xue, L., Yan, D.H., Yan, J.Z., Yang, C.W., Yang, F.F., Yang, J.Y., Yang, L.L., Yang, M.J., Yang, R.Z., Yang, S.B., Yao, Y.H., Yao, Z.G., Ye, Y.M., Yin, L.Q., Yin, N., You, X.H., You, Z.Y., Yu, Y.H., Yuan, Q., Zeng, H.D., Zeng, T.X., Zeng, W., Zeng, Z.K., Zha, M., Zhai, X.X., Zhang, B.B., Zhang, H.M., Zhang, H.Y., Zhang, J.L., Zhang, J.W., Zhang, Lu, Zhang, Li, Zhang, L.X., Zhang, P.F., Zhang, P.P., Zhang, R., Zhang, S.R., Zhang, S.S., Zhang, X., Zhang, X.P., Zhang, Y.F., Zhang, Y.L., Zhang, Yong, Zhang, Yi, Zhao, B., Zhao, J., Zhao, L., Zhao, L.Z., Zhao, S.P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J.N., Zhou, P., Zhou, R., Zhou, X.X., Zhu, C.G., Zhu, F.R., Zhu, H., Zhu, K.J., and Zuo, X.

Published
2022
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15. Flux variations of cosmic ray air showers detected by LHAASO-KM2A during a thunderstorm on June 10, 2021*

Author

Aharonian, F., primary, An, Q., additional, Bai, L.X., additional, Bai, Y.X., additional, Bao, Y.W., additional, Bastieri, D., additional, Bi, X.J., additional, Bi, Y.J., additional, Cai, J.T., additional, Cao, Zhe, additional, Cao, Zhen, additional, Chang, J., additional, Chang, J.F., additional, Chen, E.S., additional, Chen, Liang, additional, Chen, Long, additional, Chen, M.J., additional, Chen, M.L., additional, Chen, S.H., additional, Chen, S.Z., additional, Chen, T.L., additional, Chen, X. J., additional, Chen, Y., additional, Cheng, H.L., additional, Cheng, N., additional, Cheng, Y.D., additional, Cui, S.W., additional, Cui, X.H., additional, Cui, Y.D., additional, Dai, B.Z., additional, Dai, H.L., additional, Dai, Z.G., additional, Volpe, D. della, additional, Duan, K.K., additional, Fan, J.H., additional, Fan, Y.Z., additional, Fan, Z.X., additional, Fang, J., additional, Fang, K., additional, Feng, C.F., additional, Feng, L., additional, Feng, S.H., additional, Feng, X.T., additional, Feng, Y.L., additional, Gao, B., additional, Gao, C.D., additional, Gao, L.Q., additional, Gao, Q., additional, Gao, W., additional, Gao, W.K., additional, Ge, M.M., additional, Geng, L.S., additional, Gong, G.H., additional, Gou, Q.B., additional, Gu, M.H., additional, Guo, F.L., additional, Guo, J.G., additional, Guo, X.L., additional, Guo, Y.Q., additional, Guo, Y.Y., additional, Han, Y.A., additional, He, H.H., additional, He, H.N., additional, He, S.L., additional, He, X.B., additional, He, Y., additional, Heller, M., additional, Hor, Y.K., additional, Hou, C., additional, Hou, X., additional, Hu, H.B., additional, Hu, Q., additional, Hu, S., additional, Hu, S.C., additional, Hu, X.J., additional, Huang, D.H., additional, Huang, W.H., additional, Huang, X.T., additional, Huang, X.Y., additional, Huang, Y., additional, Huang, Z.C., additional, Ji, X.L., additional, Jia, H.Y., additional, Jia, K., additional, Jiang, K., additional, Jiang, Z.J., additional, Jin, M., additional, Kang, M.M., additional, Ke, T., additional, Kuleshov, D., additional, Li, B.B., additional, Li, Cheng, additional, Li, Cong, additional, Li, F., additional, Li, H.B., additional, Li, H.C., additional, Li, H.Y., additional, Li, J., additional, Li, Jian, additional, Li, Jie, additional, Li, K., additional, Li, W.L., additional, Li, X.R., additional, Li, Xin, additional, Li, Y.Z., additional, Li, Zhe, additional, Li, Zhuo, additional, Liang, E.W., additional, Liang, Y.F., additional, Lin, S.J., additional, Liu, B., additional, Liu, C., additional, Liu, D., additional, Liu, H., additional, Liu, H.D., additional, Liu, J., additional, Liu, J.L., additional, Liu, J.S., additional, Liu, J.Y., additional, Liu, M.Y., additional, Liu, R.Y., additional, Liu, S.M., additional, Liu, W., additional, Liu, Y., additional, Liu, Y.N., additional, Long, W.J., additional, Lu, R., additional, Luo, Q., additional, Lv, H.K., additional, Ma, B.Q., additional, Ma, L.L., additional, Ma, X.H., additional, Mao, J.R., additional, Masood, A., additional, Min, Z., additional, Mitthumsiri, W., additional, Nan, Y.C., additional, Ou, Z.W., additional, Pang, B.Y., additional, Pattarakijwanich, P., additional, Pei, Z.Y., additional, Qi, M.Y., additional, Qi, Y.Q., additional, Qiao, B.Q., additional, Qin, J.J., additional, Ruffolo, D., additional, Sáiz, A., additional, Shao, C.Y., additional, Shao, L., additional, Shchegolev, O., additional, Sheng, X.D., additional, Shi, J.Y., additional, Song, H.C., additional, Stenkin, Yu.V., additional, Stepanov, V., additional, Su, Y., additional, Sun, Q.N., additional, Sun, X.N., additional, Sun, Z.B., additional, Tam, P.H.T., additional, Tang, Z.B., additional, Tian, W.W., additional, Wang, B.D., additional, Wang, C., additional, Wang, H., additional, Wang, H.G., additional, Wang, J.C., additional, Wang, J.S., additional, Wang, L.P., additional, Wang, L.Y., additional, Wang, R., additional, Wang, R.N., additional, Wang, W., additional, Wang, X.G., additional, Wang, X.Y., additional, Wang, Y., additional, Wang, Y.D., additional, Wang, Y.J., additional, Wang, Y.P., additional, Wang, Z.H., additional, Wang, Z.X., additional, Wang, Zhen, additional, Wang, Zheng, additional, Wei, D.M., additional, Wei, J.J., additional, Wei, Y.J., additional, Wen, T., additional, Wu, C.Y., additional, Wu, H.R., additional, Wu, S., additional, Wu, X.F., additional, Wu, Y.S., additional, Xi, S.Q., additional, Xia, J., additional, Xia, J.J., additional, Xiang, G.M., additional, Xiao, D.X., additional, Xiao, G., additional, Xin, G.G., additional, Xin, Y.L., additional, Xing, Y., additional, Xiong, Z., additional, Xu, D.L., additional, Xu, R.X., additional, Xue, L., additional, Yan, D.H., additional, Yan, J.Z., additional, Yang, C.W., additional, Yang, F.F., additional, Yang, H.W., additional, Yang, J.Y., additional, Yang, L.L., additional, Yang, M.J., additional, Yang, R.Z., additional, Yang, S.B., additional, Yao, Y.H., additional, Yao, Z.G., additional, Ye, Y.M., additional, Yin, L.Q., additional, Yin, N., additional, You, X.H., additional, You, Z.Y., additional, Yu, Y.H., additional, Yuan, Q., additional, Yue, H., additional, Zeng, H.D., additional, Zeng, T.X., additional, Zeng, W., additional, Zeng, Z.K., additional, Zha, M., additional, Zhai, X.X., additional, Zhang, B.B., additional, Zhang, F., additional, Zhang, H.M., additional, Zhang, H.Y., additional, Zhang, J.L., additional, Zhang, L.X., additional, Zhang, Li, additional, Zhang, Lu, additional, Zhang, P.F., additional, Zhang, P.P., additional, Zhang, R., additional, Zhang, S.B., additional, Zhang, S.R., additional, Zhang, S.S., additional, Zhang, X., additional, Zhang, X.P., additional, Zhang, Y.F., additional, Zhang, Y.L., additional, Zhang, Yi, additional, Zhang, Yong, additional, Zhao, B., additional, Zhao, J., additional, Zhao, L., additional, Zhao, L.Z., additional, Zhao, S.P., additional, Zheng, F., additional, Zheng, Y., additional, Zhou, B., additional, Zhou, H., additional, Zhou, J.N., additional, Zhou, P., additional, Zhou, R., additional, Zhou, X.X., additional, Zhu, C.G., additional, Zhu, F.R., additional, Zhu, H., additional, Zhu, K.J., additional, and Zuo, X., additional

Published
2023
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16. Risk factors for Clostridioides difficile infection in children: a systematic review and meta-analysis

Author

Dong, N., primary, Li, Z.R., additional, Qin, P., additional, Qiang, C.X., additional, Yang, J., additional, Niu, Y.N., additional, Niu, X.R., additional, Liu, X.X., additional, Wang, W.G., additional, Wen, B.J., additional, Ouyang, Z.R., additional, Zhang, Y.L., additional, Zhao, M., additional, Li, J.Y.R., additional, and Zhao, J.H., additional

Published
2022
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18. Corrigendum to “Performance test of the electromagnetic particle detectors for the LHAASO experiment” [Nucl. Instrum. Methods Phys. Res. A 1001 (2021) 165193]

Author

Aharonian, F., An, Q., Axikegu, Bai, L.X., Bai, Y.X., Bao, Y.W., Bastieri, D., Bi, X.J., Bi, Y.J., Cai, H., Cai, J.T., Cao, Z., Chang, J., Chang, J.F., Chang, X.C., Chen, B.M., Chen, J., Chen, L., Chen, M.J., Chen, M.L., Chen, Q.H., Chen, S.H., Chen, S.Z., Chen, T.L., Chen, X.L., Chen, Y., Cheng, N., Cheng, Y.D., Cui, S.W., Cui, X.H., Cui, Y.D., Dai, B.Z., Dai, H.L., Dai, Z.G., Danzengluobu, della Volpe, D., Piazzoli, B. D’Ettorre, Dong, X.J., Fan, J.H., Fan, Y.Z., Fan, Z.X., Fang, J., Fang, K., Feng, C.F., Feng, L., Feng, S.H., Feng, Y.L., Gao, B., Gao, C.D., Gao, Q., Gao, W., Ge, M.M., Geng, L.S., Gong, G.H., Gou, Q.B., Gu, M.H., Guo, J.G., Guo, X.L., Guo, Y.Q., Guo, Y.Y., Han, Y.A., He, H.H., He, H.N., He, J.C., He, S.L., He, X.B., He, Y., Heller, M., Hor, Y.K., Hou, C., Hou, X., Hu, H.B., Hu, S., Hu, S.C., Hu, X.J., Huang, D.H., Huang, Q.L., Huang, W.H., Huang, X.T., Huang, Z.C., Ji, F., Ji, X.L., Jia, H.Y., Jia, K., Jiang, K., Jiang, Z.J., Jin, C., Kuleshov, D., Levochkin, K., Li, B., Li, B.B., Li, C., Li, F., Li, H., Li, H.B., Li, H.C., Li, H.Y., Li, J., Li, K., Li, W.L., Li, X., Li, X.R., Li, Y., Li, Y.Z., Li, Z., Liang, E.W., Liang, Y.F., Lin, S.J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H.D., Liu, J., Liu, J.L., Liu, J.S., Liu, J.Y., Liu, M.Y., Liu, R.Y., Liu, S.M., Liu, W., Liu, Y.N., Liu, Z.X., Long, W.J., Lu, R., Lv, H.K., Ma, B.Q., Ma, L.L., Ma, X.H., Mao, J.R., Masood, A., Mitthumsiri, W., Montaruli, T., Nan, Y.C., Pang, B.Y., Pattarakijwanich, P., Pei, Z.Y., Qi, M.Y., Ruffolo, D., Rulev, V., Sáiz, A., Shao, L., Shchegolev, O., Sheng, X.D., Shi, J.R., Song, H.C., Stenkin, Yu.V., Stepanov, V., Sun, Q.N., Sun, X.N., Sun, Z.B., Tam, P.H. T., Tang, Z.B., Tian, W.W., Wang, B.D., Wang, C., Wang, H., Wang, H.G., Wang, J.C., Wang, J.S., Wang, L.P., Wang, L.Y., Wang, R.N., Wang, W., Wang, X.G., Wang, X.J., Wang, X.Y., Wang, Y.D., Wang, Y.J., Wang, Y.P., Wang, Z., Wang, Z.H., Wang, Z.X., Wei, D.M., Wei, J.J., Wei, Y.J., Wen, T., Wu, C.Y., Wu, H.R., Wu, S., Wu, W.X., Wu, X.F., Xi, S.Q., Xia, J., Xia, J.J., Xiang, G.M., Xiao, G., Xiao, H.B., Xin, G.G., Xin, Y.L., Xing, Y., Xu, D.L., Xu, R.X., Xue, L., Yan, D.H., Yang, C.W., Yang, F.F., Yang, J.Y., Yang, L.L., Yang, M.J., Yang, R.Z., Yang, S.B., Yao, Y.H., Yao, Z.G., Ye, Y.M., Yin, L.Q., Yin, N., You, X.H., You, Z.Y., Yu, Y.H., Yuan, Q., Zeng, H.D., Zeng, T.X., Zeng, W., Zeng, Z.K., Zha, M., Zhai, X.X., Zhang, B.B., Zhang, H.M., Zhang, H.Y., Zhang, J.L., Zhang, J.W., Zhang, L., Zhang, L.X., Zhang, P.F., Zhang, P.P., Zhang, R., Zhang, S.R., Zhang, S.S., Zhang, X., Zhang, X.P., Zhang, Y., Zhang, Y.F., Zhang, Y.L., Zhao, B., Zhao, J., Zhao, L., Zhao, L.Z., Zhao, S.P., Zhao, X., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J.N., Zhou, P., Zhou, R., Zhou, X.X., Zhu, C.G., Zhu, F.R., Zhu, H., Zhu, K.J., and Zuo, X.

Published
2022
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21. Toward Clinically Applicable 3-Dimensional Tooth Segmentation via Deep Learning.

Author

Hao, J., Liao, W., Zhang, Y.L., Peng, J., Zhao, Z., Chen, Z., Zhou, B.W., Feng, Y., Fang, B., Liu, Z.Z., and Zhao, Z.H.

Subjects
DEEP learning, DENTISTRY, MALOCCLUSION, DIGITAL technology, AUTOMATION
Abstract

Digital dentistry plays a pivotal role in dental health care. A critical step in many digital dental systems is to accurately delineate individual teeth and the gingiva in the 3-dimension intraoral scanned mesh data. However, previous state-of-the-art methods are either time-consuming or error prone, hence hindering their clinical applicability. This article presents an accurate, efficient, and fully automated deep learning model trained on a data set of 4,000 intraoral scanned data annotated by experienced human experts. On a holdout data set of 200 scans, our model achieves a per-face accuracy, average-area accuracy, and area under the receiver operating characteristic curve of 96.94%, 98.26%, and 0.9991, respectively, significantly outperforming the state-of-the-art baselines. In addition, our model takes only about 24 s to generate segmentation outputs, as opposed to >5 min by the baseline and 15 min by human experts. A clinical performance test of 500 patients with malocclusion and/or abnormal teeth shows that 96.9% of the segmentations are satisfactory for clinical applications, 2.9% automatically trigger alarms for human improvement, and only 0.2% of them need rework. Our research demonstrates the potential for deep learning to improve the efficacy and efficiency of dental treatment and digital dentistry. [ABSTRACT FROM AUTHOR]

Published
2022
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22. o 8 G Site-Specifically Modified tRF-1-AspGTC: A Novel Therapeutic Target and Biomarker for Pulmonary Hypertension.

Author

Zhang J, Li Y, Chen Y, Zhang J, Jia Z, He M, Liao X, He S, Bian JS, and Nie XW

Subjects
Humans, Animals, Wnt-5a Protein metabolism, Wnt-5a Protein genetics, Guanine analogs & derivatives, Guanine metabolism, Male, Oxidative Stress, Caspase 3 metabolism, Myocytes, Smooth Muscle metabolism, Cell Proliferation, Apoptosis, Cells, Cultured, Vascular Remodeling, Female, Rats, Reactive Oxygen Species metabolism, Muscle, Smooth, Vascular metabolism, Hypertension, Pulmonary metabolism, Hypertension, Pulmonary genetics, Hypertension, Pulmonary etiology, Bone Morphogenetic Protein Receptors, Type II metabolism, Bone Morphogenetic Protein Receptors, Type II genetics, Biomarkers metabolism, Biomarkers blood, Pulmonary Artery metabolism
Abstract

Background: Hypoxia and oxidative stress contribute to the development of pulmonary hypertension (PH). tRNA-derived fragments play important roles in RNA interference and cell proliferation, but their epitranscriptional roles in PH development have not been investigated. We aimed to gain insight into the mechanistic contribution of oxidative stress-induced 8-oxoguanine in pulmonary vascular remodeling., Methods: Through small RNA modification array analysis and quantitative polymerase chain reaction, a significant upregulation of the 8-oxoguanine -modified tRF-1-AspGTC was found in the lung tissues and the serum of patients with PH., Results: This modification occurs at the position 5 of the tRF-1-AspGTC (5o 8 G tRF). Inhibition of the 5o 8 G tRF reversed hypoxia-induced proliferation and apoptosis resistance in pulmonary artery smooth muscle cells. Further investigation unveiled that the 5o 8 G tRF retargeted mRNA of WNT5A (Wingless-type MMTV integration site family, member 5A) and CASP3 (Caspase3) and inhibited their expression. Ultimately, BMPR2 (Bone morphogenetic protein receptor 2) -reactive oxygen species/5o 8 G tRF/WNT5A signaling pathway exacerbated the progression of PH., Conclusions: Our study highlights the role of site-specific 8-oxoguanine-modified tRF in promoting the development of PH. Our findings present a promising therapeutic avenue for managing PH and propose 5o 8 G tRF as a potential innovative marker for diagnosing this disease., Competing Interests: Disclosures None.

Published
2024
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23. Chylomicrons Regulate Lacteal Permeability and Intestinal Lipid Absorption.

Author

Zarkada G, Chen X, Zhou X, Lange M, Zeng L, Lv W, Zhang X, Li Y, Zhou W, Liu K, Chen D, Ricard N, Liao J, Kim YB, Benedito R, Claesson-Welsh L, Alitalo K, Simons M, Ju R, Li X, Eichmann A, and Zhang F

Subjects
Mice, Animals, Vascular Endothelial Growth Factor A metabolism, Endothelial Cells metabolism, Phosphatidylinositol 3-Kinases metabolism, Chylomicrons metabolism, Capillary Permeability, Lymphatic Vessels metabolism, Monomeric GTP-Binding Proteins metabolism
Abstract

Background: Lymphatic vessels are responsible for tissue drainage, and their malfunction is associated with chronic diseases. Lymph uptake occurs via specialized open cell-cell junctions between capillary lymphatic endothelial cells (LECs), whereas closed junctions in collecting LECs prevent lymph leakage. LEC junctions are known to dynamically remodel in development and disease, but how lymphatic permeability is regulated remains poorly understood., Methods: We used various genetically engineered mouse models in combination with cellular, biochemical, and molecular biology approaches to elucidate the signaling pathways regulating junction morphology and function in lymphatic capillaries., Results: By studying the permeability of intestinal lacteal capillaries to lipoprotein particles known as chylomicrons, we show that ROCK (Rho-associated kinase)-dependent cytoskeletal contractility is a fundamental mechanism of LEC permeability regulation. We show that chylomicron-derived lipids trigger neonatal lacteal junction opening via ROCK-dependent contraction of junction-anchored stress fibers. LEC-specific ROCK deletion abolished junction opening and plasma lipid uptake. Chylomicrons additionally inhibited VEGF (vascular endothelial growth factor)-A signaling. We show that VEGF-A antagonizes LEC junction opening via VEGFR (VEGF receptor) 2 and VEGFR3-dependent PI3K (phosphatidylinositol 3-kinase)/AKT (protein kinase B) activation of the small GTPase RAC1 (Rac family small GTPase 1), thereby restricting RhoA (Ras homolog family member A)/ROCK-mediated cytoskeleton contraction., Conclusions: Our results reveal that antagonistic inputs into ROCK-dependent cytoskeleton contractions regulate the interconversion of lymphatic junctions in the intestine and in other tissues, providing a tunable mechanism to control the lymphatic barrier., Competing Interests: Disclosures None.

Published
2023
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