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1. CircRNA circ-OGDH (hsa_circ_0003340) Acts as a ceRNA to Regulate Glutamine Metabolism and Esophageal Squamous Cell Carcinoma Progression by the miR-615-5p/PDX1 Axis

Author

Liang Z, Zhao B, Hou J, Zheng J, and Xin G

Subjects
escc, circ-ogdh, mir-615-5p, pdx1, glutamine, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Zongying Liang, Baoshan Zhao, Jishen Hou, Jingxiong Zheng, Guohua Xin Department of Thoracic Surgery, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, People’s Republic of ChinaCorrespondence: Guohua XinDepartment of Thoracic Surgery, The Affiliated Hospital of Chengde Medical University, No. 36, Nanyingzi Street, Shuangqiao District, Chengde, 067000, People’s Republic of ChinaEmail iqbqth@163.comBackground: Circular RNA hsa_circ_0003340 (circ-OGDH) has been uncovered to be involved in esophageal squamous cell carcinoma (ESCC) progression. However, the mechanism by which circ-OGDH regulates ESCC progression is unclear.Methods: Expression levels of circ-OGDH, microRNA (miR)-615-5p, and PDX1 (pancreatic and duodenal homeobox 1) mRNA were evaluated with quantitative real-time polymerase chain reaction (qRT-PCR). The proliferation, apoptosis, migration, invasion, and cell cycle progression of ESCC cells were analyzed by MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide), colony formation, flow cytometry, and transwell assays. Measurement of glutamine consumption, α-KG (α-ketoglutarate) production, and ATP (Adenosine Triphosphate) content using corresponding kits. Protein levels were analyzed by Western blotting. The targeting relationship between circ-OGDH or PDX1 and miR-615-5p was verified by dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. The function of circ-OGDH in ESCC was confirmed by animal experiments.Results: Circ-OGDH was upregulated in ESCC. Circ-OGDH inhibition reduced ESCC growth in vivo and accelerated cell apoptosis, cell cycle arrest, repressed cell proliferation, migration, invasion, and reduced cell glutamine metabolism in ESCC cells in vitro. MiR-615-5p was downregulated in ESCC, while PDX1 had an opposite result. Circ-OGDH sponged miR-615-5p to regulate PDX1 expression. MiR-615-5p inhibitor neutralized the repressive effect of circ-OGDH knockdown on malignancy and glutamine metabolism of ESCC cells. PDX1 overexpression counteracted the inhibitory impact of miR-615-5p mimic on malignancy and glutamine metabolism of ESCC cells.Conclusion: Circ-OGDH sponged miR-615-5p to elevate PDX1 expression, thus elevating glutamine metabolism and promoting tumor growth in ESCC. The study offered evidence to support circ-OGDH as a promising target for ESCC therapy.Keywords: ESCC, circ-OGDH, miR-615-5p, PDX1, glutamine

Published
2021

2. Constraints on Ultra Heavy Dark Matter Properties from Dwarf Spheroidal Galaxies with LHAASO Observations

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract

In this work we try to search for signals generated by ultra-heavy dark matter at the Large High Altitude Air Shower Observatory (LHAASO) data. We look for possible gamma-ray by dark matter annihilation or decay from 16 dwarf spheroidal galaxies in the field of view of LHAASO. Dwarf spheroidal galaxies are among the most promising targets for indirect detection of dark matter which have low fluxes of astrophysical $\gamma$-ray background while large amount of dark matter. By analyzing more than 700 days observational data at LHAASO, no significant dark matter signal from 1 TeV to 1 EeV is detected. Accordingly we derive the most stringent constraints on the ultra-heavy dark matter annihilation cross-section up to EeV. The constraints on the lifetime of dark matter in decay mode are also derived., Comment: 17 pages, 12 figures, accepted by PRL

Published
2024

3. Discovery of Very-high-energy Gamma-ray Emissions from the Low Luminosity AGN NGC 4278 by LHAASO

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The first source catalog of Large High Altitude Air Shower Observatory reported the detection of a very-high-energy gamma ray source, 1LHAASO J1219+2915. In this paper a further detailed study of the spectral and temporal behavior of this point-like source have been carried. The best-fit position of the TeV source ($\rm{RA}=185.05^{\circ}\pm0.04^{\circ}$, $\rm{Dec}=29.25^{\circ}\pm0.03^{\circ}$) is compatible with NGC 4278 within $\sim0.03$ degree. Variation analysis shows an indication of the variability at a few months level in the TeV band, which is consistent with low frequency observations. Based on these observations, we report the detection of TeV $\gamma$-ray emissions from this low-luminosity AGN NGC 4278. The observations by LHAASO-WCDA during active period has a significance level of 8.8\,$\sigma$ with best-fit photon spectral index $\varGamma=2.56\pm0.14$ and a flux $f_{1-10\,\rm{TeV}}=(7.0\pm1.1_{\rm{sta}}\pm0.35_{\rm{syst}})\times10^{-13}\,\rm{photons\,cm^{-2}\,s^{-1}}$, or approximately $5\%$ of the Crab Nebula. The discovery of VHE from NGC 4278 indicates that the compact, weak radio jet can efficiently accelerate particles and emit TeV photons., Comment: 11 pages, 5 figures

Published
2024

4. LHAASO-KM2A detector simulation using Geant4

Author

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

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

KM2A is one of the main sub-arrays of LHAASO, working on gamma ray astronomy and cosmic ray physics at energies above 10 TeV. Detector simulation is the important foundation for estimating detector performance and data analysis. It is a big challenge to simulate the KM2A detector in the framework of Geant4 due to the need to track numerous photons from a large number of detector units (>6000) with large altitude difference (30 m) and huge coverage (1.3 km^2). In this paper, the design of the KM2A simulation code G4KM2A based on Geant4 is introduced. The process of G4KM2A is optimized mainly in memory consumption to avoid memory overffow. Some simpliffcations are used to signiffcantly speed up the execution of G4KM2A. The running time is reduced by at least 30 times compared to full detector simulation. The particle distributions and the core/angle resolution comparison between simulation and experimental data of the full KM2A array are also presented, which show good agreement.

Published
2024
Full Text
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5. A pH-Sensitive Prodrug Nanocarrier Based on Diosgenin for Doxorubicin Delivery to Efficiently Inhibit Tumor Metastasis

Author

Wei Z, Wang H, Xin G, Zeng Z, Li S, Ming Y, Zhang X, Xing Z, Li L, Li Y, Zhang B, Zhang J, Niu H, and Huang W

Subjects
anti-metastasis, antitumor, self-assembly, codelivery, doxorubicin, Medicine (General), R5-920
Abstract

Zeliang Wei,1,2 Haibo Wang,3 Guang Xin,1 Zhi Zeng,1 Shiyi Li,1 Yue Ming,1 Xiaoyu Zhang,1 Zhihua Xing,1 Li Li,2 Youping Li,1 Boli Zhang,1,4 Junhua Zhang,4 Hai Niu,1,5 Wen Huang1 1Laboratory of Ethnopharmacology, West China Medical School, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 2Department of Dermatology, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 3Textile Institute, College of Light Industry, Textile and Food Engineering, Sichuan University, Chengdu, People’s Republic of China; 4Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 5College of Mathematics, Sichuan University, Chengdu, Sichuan, People’s Republic of ChinaCorrespondence: Wen Huang; Hai Niu Email huangwen@scu.edu.cn; niuhai@scu.edu.cnBackground: The metastasis, one of the biggest barriers in cancer therapy, is the leading cause of tumor deterioration and recurrence. The anti.-metastasis has been considered as a feasible strategy for clinical cancer management. It is well known that diosgenin could inhibit tumor metastasis and doxorubicin (DOX) could induce tumor apoptosis. However, their efficient delivery remains challenging.Purpose: To address these issues, a novel pH-sensitive polymer-prodrug based on diosgenin nanoparticles (NPs) platform was developed to enhance the efficiency of DOX delivery (DOX/NPs) for synergistic therapy of cutaneous melanoma, the most lethal form of skin cancer with high malignancy, early metastasis and high mortality.Methods and Results: The inhibitory effect of DOX/NPs on tumor proliferation and migration was superior to that of NPs or free DOX. What is more, DOX/NPs could combine mitochondria-associated metastasis and apoptosis with unique internalization pathway of carrier to fight tumors. In addition, biodistribution experiments proved that DOX/NPs could efficiently accumulate in tumor sites through enhancing permeation and retention (EPR) effect compared with free DOX. Importantly, the data from in vivo experiment revealed that DOX/NPs without heart toxicity significantly inhibited tumor metastasis by exerting synergistic therapeutic effect, and reduced tumor volume and weight by inducing apoptosis.Conclusion: The nanocarrier DOX/NPs with satisfying pharmaceutical characteristics based on the establishment of two different functional agents is a promising strategy for synergistically enhancing effects of cancer therapy.Keywords: anti-metastasis, antitumor, self-assembly, codelivery, doxorubicin

Published
2020

6. Dihydrodiosgenin inhibits endothelial cell-derived factor VIII and platelet-mediated hepatocellular carcinoma metastasis

Author

Zhuang M, Xin G, Wei Z, Li S, Xing Z, Ji C, Du J, Niu H, and Huang W

Subjects
Dihydrodiosgenin, hepatocellular carcinoma, platelet, endothelial cell, tumor microenvironment, FVIII., Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Manjiao Zhuang,1 Guang Xin,1 Zeliang Wei,1 Shiyi Li,1 Zhihua Xing,1 Chengjie Ji,1,2 Junrong Du,1 Hai Niu,1,3 Wen Huang11Laboratory of Ethnopharmacology, West China School of Pharmacy, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 2Department of Laboratory Medicine, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Chengdu, Sichuan, People’s Republic of China; 3College of Mathematics, Sichuan University, Chengdu, Sichuan, People’s Republic of ChinaBackground: Our previous studies have demonstrated that diosgenin and diosgenin derivatives exhibit excellent antithrombotic activity via regulating platelet function and coagulation factor level. Platelets and blood coagulation system are highly associated with tumor hematogenous metastasis. Therefore, the purpose of this study was to evaluate whether dihydrodiosgenin (dydio) mediated-platelet inhibition or coagulation factor level modulation is involved in hepatocellular carcinoma cell (HCC) metastasis.Methods: Cell viability was examined by MTT and colony formation assays. Platelet aggregation text and morphology were used to assess dydio’s role on tumor cell-induced platelet activation (TCIPA). Scratch assay, adhesion assay and Western blot were used to evaluate dydio’s role on platelet-mediated metastasis. Western blot and fluorescence detection were performed to clarify dydio’s role on endothelial cell (EC) function. The mice lung metastasis model was constructed to investigated dydio’s function on coagulation factor and platelet-mediated metastasis.Results: This study found that pretreatment with dydio caused a significant inhibition of TCIPA. Platelets exposed to dydio significantly inhibited their adhesion to tumor cells, meanwhile, releasates of platelets that pretreated with dydio led to diminished cancer cell proliferation and migration along with the increase of epithelial markers E-cadherin and loss of mesenchymal phenotype. Additionally, ECs pretreated with dydio suppressed factor VIII (FVIII) level which in turn restrained the activation of platelets and the adhesion of cancer cells or platelets to ECs. Interestingly, our study demonstrated that FVIII could promote HCC proliferation. In vivo study revealed that mice intragastrical (i.g.) administration with dydio significantly inhibited the lung metastasis of hepal-6 cells which is highly correlated with the altered platelet function and coagulation level.Conclusion: Taken together, these results demonstrated that dydio altered platelet function and coagulation FVIII level, resulting in decreased metastatic potential of HCC. Thus, our study reveals that dydio exerts novel mechanisms of antitumor action beside its direct antitumor activity.Keywords: dihydrodiosgenin, hepatocellular carcinoma, platelet, endothelial cell, tumor microenvironment, FVIII

Published
2019

7. Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at $3.67 \pm 0.05 \pm 0.15$ PeV. Below the knee, the spectral index is found to be -$2.7413 \pm 0.0004 \pm 0.0050$, while above the knee, it is -$3.128 \pm 0.005 \pm 0.027$, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -$0.1200 \pm 0.0003 \pm 0.0341$. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components., Comment: 8 pages, 3 figures

Published
2024
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8. Inhibition of MUC1-C entering nuclear suppresses MYC expression and attenuates malignant growth in esophageal squamous cell carcinoma

Author

Xin Z, Xin G, Shi M, Song L, Wang Q, Jiang B, and Liu X

Subjects
MUC1 C-terminal subunit (MUC1-C), MYC, Esophageal Squamous Cell Carcinoma (ESCC), GO-201, Malignant Growth, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Zhongwei Xin,* Gongsun Xin,* Mo Shi, Liang Song, Qiang Wang, Bin Jiang, Xiangyan Liu Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, People’s Republic of China *These authors contributed equally to this work Background: The mucin 1 (MUC1) heterodimeric protein (N-terminal subunit and C-terminal subunit) is aberrantly overexpressed in esophageal squamous cell carcinoma (ESCC) and has been linked to poor outcomes in this disease. The detailed mechanism(s), however, remains unclear. In this article, we investigate the effects of the MUC1 C-terminal transmembrane subunit (MUC1-C) through the inhibitor GO-201, which inhibits MUC1-C targeting to nuclear. Patients and methods: The expression of MUC1-C and MYC in the ESCC samples and cell lines was detected by immunohistochemistry, immunofluorescence and western blotting. MYC mRNA level was determined by using quantitative real-time polymerase chain reaction. In addition, Cell Counting Kit-8, clonogenic assay, transwell assay and tumor xenograft in nude mice assay were utilized to determine the role of MUC1-C in proliferation, invasion and migration of ESCC cells. Results: The level of MUC1-C in nuclear and MYC in whole cells in the ESCC tissue is significantly higher than that in the noncancerous tissue. Treatment of MUC1-C-overexpressing ESCC cells with GO-201 was associated with downregulation of MYC expression and induction of apoptosis. Besides, in vitro and in vivo assays have both shown that inhibiting MUC1-C targeting to the nucleus by the GO-201 significantly decreased the abilities of proliferation, invasion and migration in ESCC cells. Conclusion: Our findings suggest that MUC1-C targeting to the nucleus plays an important role in suppressing the malignant growth of ESCC and indicate that MUC1-C is a potential target for the treatment of ESCC. Keywords: MUC1 C-terminal subunit (MUC1-C), MYC, esophageal squamous cell carcinoma (ESCC), GO-201, malignant growth

Published
2018

9. Does or did the supernova remnant Cassiopeia A operate as a PeVatron?

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

For decades, supernova remnants (SNRs) have been considered the prime sources of Galactic Cosmic rays (CRs). But whether SNRs can accelerate CR protons to PeV energies and thus dominate CR flux up to the knee is currently under intensive theoretical and phenomenological debate. The direct test of the ability of SNRs to operate as CR PeVatrons can be provided by ultrahigh-energy (UHE; $E_\gamma \geq 100$~TeV) $\gamma$-rays. In this context, the historical SNR Cassiopeia A (Cas A) is considered one of the most promising target for UHE observations. This paper presents the observation of Cas A and its vicinity by the LHAASO KM2A detector. The exceptional sensitivity of LHAASO KM2A in the UHE band, combined with the young age of Cas A, enabled us to derive stringent model-independent limits on the energy budget of UHE protons and nuclei accelerated by Cas A at any epoch after the explosion. The results challenge the prevailing paradigm that Cas A-type SNRs are major suppliers of PeV CRs in the Milky Way., Comment: 11 pages, 3 figures, Accepted by the APJL

Published
2023

10. Very high energy gamma-ray emission beyond 10 TeV from GRB 221009A

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The highest energy gamma-rays from gamma-ray bursts (GRBs) have important implications for their radiation mechanism. Here we report for the first time the detection of gamma-rays up to 13 TeV from the brightest GRB 221009A by the Large High Altitude Air-shower Observatory (LHAASO). The LHAASO-KM2A detector registered more than 140 gamma-rays with energies above 3 TeV during 230$-$900s after the trigger. The intrinsic energy spectrum of gamma-rays can be described by a power-law after correcting for extragalactic background light (EBL) absorption. Such a hard spectrum challenges the synchrotron self-Compton (SSC) scenario of relativistic electrons for the afterglow emission above several TeV. Observations of gamma-rays up to 13 TeV from a source with a measured redshift of z=0.151 hints more transparency in intergalactic space than previously expected. Alternatively, one may invoke new physics such as Lorentz Invariance Violation (LIV) or an axion origin of very high energy (VHE) signals., Comment: 49pages, 11figures

Published
2023
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11. The First LHAASO Catalog of Gamma-Ray Sources

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract

We present the first catalog of very-high energy and ultra-high energy gamma-ray sources detected by the Large High Altitude Air Shower Observatory (LHAASO). The catalog was compiled using 508 days of data collected by the Water Cherenkov Detector Array (WCDA) from March 2021 to September 2022 and 933 days of data recorded by the Kilometer Squared Array (KM2A) from January 2020 to September 2022. This catalog represents the main result from the most sensitive large coverage gamma-ray survey of the sky above 1 TeV, covering declination from $-$20$^{\circ}$ to 80$^{\circ}$. In total, the catalog contains 90 sources with an extended size smaller than $2^\circ$ and a significance of detection at $> 5\sigma$. Based on our source association criteria, 32 new TeV sources are proposed in this study. Among the 90 sources, 43 sources are detected with ultra-high energy ($E > 100$ TeV) emission at $> 4\sigma$ significance level. We provide the position, extension, and spectral characteristics of all the sources in this catalog., Comment: 40 pages, 13 figures, 4 tables

Published
2023
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12. Measurement of ultra-high-energy diffuse gamma-ray emission of the Galactic plane from 10 TeV to 1 PeV with LHAASO-KM2A

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The diffuse Galactic $\gamma$-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this work we report the measurements of diffuse $\gamma$-rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner ($15^{\circ}10$~TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of $-2.99\pm0.04$, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of $\sim3$ than the prediction. A similar spectrum with an index of $-2.99\pm0.07$ is found in the outer Galaxy region, and the absolute flux for $10\lesssim E\lesssim60$ TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations., Comment: 12 pages, 8 figures, 5 tables; accepted for publication in Physical Review Letters; source mask file provided as ancillary file

Published
2023
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13. Two-Color Attosecond Chronoscope

Author

Wu, J. N., Che, J. Y., Zhang, F. B., Chen, C., Li, W. Y., Xin, G. G., and Chen, Y. J.

Subjects
Physics - Atomic Physics
Abstract

We study ionization of atoms in strong orthogonal two-color ($\omega,2\omega$) (OTC) laser fields numerically and analytically. The calculated photoelectron momentum distribution shows two typical structures: a rectangular-like structure and a shoulder-like structure, the positions of which depend on the laser parameters. Using a strong-field model which allows us to quantitatively evaluate the Coulomb effect, we show that these two structures arise from attosecond response of electron inside an atom to light in OTC-induced photoemission. Some simple mappings between the locations of these structures and response time are derived, with which we are able to establish two-color attosecond chronoscope with high resolution for timing electron emission in OTC-based precise manipulation., Comment: 6 pages, 3 figures. arXiv admin note: text overlap with arXiv:2212.09886, arXiv:2301.00619

Published
2023
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14. Response time of electron inside a molecule to light in strong-field ionization

Author

Che, J. Y., Peng, Y. G., Zhang, F. B., Xie, X. J., Xin, G. G., and Chen, Y. J.

Subjects
Physics - Atomic Physics
Abstract

We study ionization of aligned H$_2^+$ in strong elliptically-polarized laser fields numerically and analytically. The calculated offset angle in photoelectron momentum distribution is several degrees larger for the molecule than a model atom with similar ionization potential at diverse laser parameters. Using a strong-field model that considers the properties of multi-center and single-center Coulomb potentials, we are able to quantitatively reproduce this angle difference between the molecule and the atom. Further analyses based on this model show that the response time of electron to light which is encoded in the offset angle and is manifested as the time spent in tunneling ionization, is about 15 attoseconds longer for the molecule than the atom. This time difference is further enlarged when increasing the internuclear distance of the molecule., Comment: 7 pages,4 figures. arXiv admin note: substantial text overlap with arXiv:2212.09886

Published
2023

15. Roles of laser ellipticity in attoclock

Author

Che, J. Y., Huang, J. Y., Zhang, F. B., Chen, C., Xin, G. G., and Chen, Y. J.

Subjects
Physics - Atomic Physics
Abstract

We study ionization of atoms in strong elliptically-polarized laser fields numerically and analytically. We focus on effects of laser ellipticity on the offset angle in photoelectron momentum distribution. This angle is considered to encode time information of tunneling ionization in attoclock experiments. The calculated offset angle increases with the decrease of ellipticity but the momentum along the major axis of laser polarization related to this angle changes slowly, in agreement with experiments. With a Coulomb-included strong-field model, the scaling laws for ellipticity dependence of this angle and relevant momentum components are obtained, and the ellipticity dependence of Coulomb-induced ionization time lag encoded in this angle is also addressed., Comment: 7 pages, 4 figures

Published
2022
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16. Coulomb scattering inducing time lag in strong-field tunneling ionization

Author

Peng, Y. G., Che, J. Y., Chen, C., Xin, G. G., and Chen, Y. J.

Subjects
Physics - Atomic Physics
Abstract

We study ionization of atoms in strong elliptically-polarized laser fields. We focus on the physical origin of the offset angle in the photoelectron momentum distribution and its possible relation to a specific time. By developing a model which is based on strong-field approximation and considers the classical Coulomb scattering, we are able to quantitatively explain recent attoclock experiments in a wide region of laser and atomic parameters. The offset angle can be understood as arising from the scattering of the electron by the ionic potential when the electron exits the laser-Coulomb-formed barrier through tunneling. The scattering time is manifested as the Coulomb-induced ionization time lag and is encoded in the offset angle., Comment: 5 pages, 4 figures

Published
2022

17. Single-shot Foothold Selection and Constraint Evaluation for Quadruped Locomotion

Author

Belter, D., Bednarek, J., Lin, H. -C., Xin, G., and Mistry, M.

Subjects
Computer Science - Robotics
Abstract

In this paper, we propose a method for selecting the optimal footholds for legged systems. The goal of the proposed method is to find the best foothold for the swing leg on a local elevation map. We apply the Convolutional Neural Network to learn the relationship between the local elevation map and the quality of potential footholds. The proposed network evaluates the geometrical characteristics of each cell on the elevation map, checks kinematic constraints and collisions. During execution time, the controller obtains the qualitative measurement of each potential foothold from the neural model. This method allows to evaluate hundreds of potential footholds and check multiple constraints in a single step which takes 10~ms on a standard computer without GPGPU. The experiments were carried out on a quadruped robot walking over rough terrain in both simulation and real robotic platforms.

Published
2022
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18. Flux Variations of Cosmic Ray Air Showers Detected by LHAASO-KM2A During a Thunderstorm on 10 June 2021

Author

LHAASO Collaboration, Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Zhe, Cao, Zhen, Chang, J., Chang, J. F., Chen, E. S., Chen, Liang, Chen, Long, Chen, M. J., Chen, M. L., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, X. J., Chen, Y., Cheng, H. L., 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., 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, X. T., Feng, Y. L., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Gu, F. L., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, W. H., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Li, B. B., Li, Cheng, Li, Cong, Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, 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., Long, W. J., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Min, Z., Mitthumsiri, W., Nan, Y. C., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Shao, C. Y., 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., Wang, R. N., Wang, W., Wang, X. G., 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, X. F., W, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yan, J. Z., Yang, C. W., Yang, F. F., Yang, H. W., 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., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, Lu, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Y. L., Zhang, Yi, Zhang, Yong, 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.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Experiment
Abstract

The Large High Altitude Air Shower Observatory (LHAASO) has three sub-arrays, KM2A, WCDA and WFCTA. The flux variations of cosmic ray air showers were studied by analyzing the KM2A data during the thunderstorm on 10 June 2021. The number of shower events that meet the trigger conditions increases significantly in atmospheric electric fields, with maximum fractional increase of 20%. The variations of trigger rates (increases or decreases) are found to be strongly dependent on the primary zenith angle. The flux of secondary particles increases significantly, following a similar trend with that of the shower events. To better understand the observed behavior, Monte Carlo simulations are performed with CORSIKA and G4KM2A (a code based on GEANT4). We find that the experimental data (in saturated negative fields) are in good agreement with simulations, assuming the presence of a uniform upward electric field of 700 V/cm with a thickness of 1500 m in the atmosphere above the observation level. Due to the acceleration/deceleration and deflection by the atmospheric electric field, the number of secondary particles with energy above the detector threshold is modified, resulting in the changes in shower detection rate., Comment: 18 pages, 11 figures

Published
2022
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19. Response time of photoemission at quantum-classic boundary

Author

Chen, C., Che, J. Y., Li, W. Y., Wang, S., Xie, X. J., Huang, J. Y., Peng, Y. G., Xin, G. G., and Chen, Y. J.

Subjects
Physics - Atomic Physics
Abstract

The response time of the electron to light in photoemission is difficult to define and measure. Tunneling ionization of atoms, a strong-laser-induced photoemission process, provides a semiclassical case for visiting the problem. Here, we show that the response time can be determined at the boundary between quantum and classic. Specifically, tunneling is instantaneous but a finite response time (about 100 attoseconds) is needed for the state of the tunneling electron to evolve into the ionized state around tunnel exit. This time can be well described with a compact expression related to some basic laser and atomic parameters. Moreover, it can be directly mapped to and easily decoded from photoelectron momentum with a simple mapping, allowing an unambiguous measurement. These results shed light on definition and measurement of the response time of photoemission., Comment: 11 pages, 8 figures. We have changed the title, reorganized this article, and replaced or deleted some of the data plots, but the main conclusions remain unchanged

Published
2021

20. Peta-electron volt gamma-ray emission from the Crab Nebula

Author

The LHAASO Collaboration, Cao, Zhen, 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, 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., Piazzoli, B. D'Ettorre, Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., 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., 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., 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, 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, Cheng, Li, Cong, Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, Jie, Li, Jian, Li, K., Li, W. L., Li, X. R., Li, Xin, 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, Wei, 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, L. X., Zhang, Li, Zhang, Lu, 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, Yi, Zhang, Yong, 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.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Crab pulsar and the surrounding nebula powered by the pulsar's rotational energy through the formation and termination of a relativistic electron-positron wind is a bright source of gamma-rays carrying crucial information about this complex conglomerate. We report the detection of $\gamma$-rays with a spectrum showing gradual steepening over three energy decades, from $5\times 10^{-4}$ to $1.1$ petaelectronvolt (PeV). The ultra-high-energy photons exhibit the presence of a PeV electron accelerator (a pevatron) with an acceleration rate exceeding 15% of the absolute theoretical limit. Assuming that unpulsed $\gamma$-rays are produced at the termination of the pulsar's wind, we constrain the pevatron's size, between $0.025$ and $0.1$ pc, and the magnetic field $\approx 110 \mu$G. The production rate of PeV electrons, $2.5 \times 10^{36}$ erg $\rm s^{-1}$, constitutes 0.5% of the pulsar's spin-down luminosity, although we do not exclude a non-negligible contribution of PeV protons to the production of the highest energy $\gamma$-rays., Comment: 43 pages, 13 figures, 2 tables; Published in Science

Published
2021
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21. Calibration of the Air Shower Energy Scale of the Water and Air Cherenkov Techniques in the LHAASO experiment

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. 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. DEttorre, 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., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, F., 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., Saiz, 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, 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., 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.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Wide Field-of-View Cherenkov Telescope Array (WFCTA) and the Water Cherenkov Detector Arrays (WCDA) of LHAASO are designed to work in combination for measuring the energy spectra of various cosmic ray species over a very wide energy range from a few TeV to 10 PeV. The energy calibration of WCDA can be achieved with a proven technique of measuring the westward shift of the Moon shadow of galactic cosmic rays due to the geomagnetic field. This deflection angle $\Delta$ is inversely proportional to the energy of the cosmic rays. The precise measurements of the shifts by WCDA allows us to calibrate its energy scale for energies as high as 35 TeV. The energy scale measured by WCDA can be used to cross calibrate the energy reconstructed by WFCTA, which spans the whole energy range up to 10 PeV. In this work, we will demonstrate the feasibility of the method using the data collected from April 2019 to January 2020 by the WFCTA array and WCDA-1 detector, the first of the three water Cherenkov ponds, already commissioned at LHAASO site.

Published
2021
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22. Measuring Coulomb-Induced Ionization Time Lag with a Calibrated Attoclock

Author

Che, J. Y., Chen, C., Wang, S., Xin, G. G., and Chen, Y. J.

Subjects
Physics - Atomic Physics, Physics - Optics
Abstract

Electrons in atoms and molecules can not react immediately to the action of intense laser field. A time lag (about 100 attoseconds) between instants of the field maximum and the ionization-rate maximum emerges. This lag characterizes the response time of the electronic wave function to the strong-field ionization event and has important effects on subsequent ultrafast dynamics of the ionized electron. The absolute time lag is not accessible in experiments. Here, a calibrated attoclock procedure, which is related to a simple Coulomb-induced temporal correction to electron trajectories, is proposed to measure the relative lag of two different ionization events. Using this procedure,the difference (i.e., the relative lag) between the ionization time lags of polar molecules in two consecutive half laser cycles can be probed with a high accuracy., Comment: 5 pages, 4 figures

Published
2021

23. Construction and On-site Performance of the LHAASO WFCTA Camera

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., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, F., 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., 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.

Subjects
Physics - Instrumentation and Detectors, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract

The focal plane camera is the core component of the Wide Field-of-view Cherenkov/fluorescence Telescope Array (WFCTA) of the Large High-Altitude Air Shower Observatory (LHAASO). Because of the capability of working under moonlight without aging, silicon photomultipliers (SiPM) have been proven to be not only an alternative but also an improvement to conventional photomultiplier tubes (PMT) in this application. Eighteen SiPM-based cameras with square light funnels have been built for WFCTA. The telescopes have collected more than 100 million cosmic ray events and preliminary results indicate that these cameras are capable of working under moonlight. The characteristics of the light funnels and SiPMs pose challenges (e.g. dynamic range, dark count rate, assembly techniques). In this paper, we present the design features, manufacturing techniques and performances of these cameras. Finally, the test facilities, the test methods and results of SiPMs in the cameras are reported here., Comment: 45 pages, 21 figures, article

Published
2020
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24. The observation of the Crab Nebula with LHAASO-KM2A for the performance study

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., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, F., 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., 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.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

As a sub-array of the Large High Altitude Air Shower Observatory (LHAASO), KM2A is mainly designed to cover a large fraction of the northern sky to hunt for gamma-ray sources at energies above 10 TeV. Even though the detector construction is still underway, a half of the KM2A array has been operating stably since the end of 2019. In this paper, we present the pipeline of KM2A data analysis and the first observation on the Crab Nebula, a standard candle in very high energy gamma-ray astronomy. We detect gamma-ray signals from the Crab Nebula in both energy ranges of 10$-$100 TeV and $>$100 TeV with high significance, by analyzing the KM2A data of 136 live days between December 2019 and May 2020. With the observations, we test the detector performance including angular resolution, pointing accuracy and cosmic ray background rejection power. The energy spectrum of the Crab Nebula in the energy range 10-250 TeV fits well with a single power-law function dN/dE =(1.13$\pm$0.05$_{stat}$$\pm$0.08$_{sys}$)$\times$10$^{-14}$$\cdot$(E/20TeV)$^{-3.09\pm0.06_{stat}\pm0.02_{sys}}$ cm$^{-2}$ s$^{-1}$ TeV$^{-1}$. It is consistent with previous measurements by other experiments. This opens a new window of gamma-ray astronomy above 0.1 PeV through which ultrahigh-energy gamma-ray new phenomena, such as cosmic PeVatrons, might be discovered., Comment: 13 pages, 15 figures,submitted to CPC

Published
2020
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25. Strong-field double ionization dynamics of vibrating HeH$^+$ versus HeT$^+$

Author

Wang, S., Xu, R. H., Li, W. Y., Liu, X., Li, W., Xin, G. G., and Chen, Y. J.

Subjects
Physics - Atomic Physics, Physics - Optics
Abstract

We study double ionization (DI) dynamics of vibrating HeH$^+$ versus its isotopic variant HeT$^+$ in strong laser fields numerically. Our simulations show that for both cases, these two electrons in DI prefer to release together along the H(T) side. At the same time, however, the single ionization (SI) is preferred when the first electron escapes along the He side. This potential mechanism is attributed to the interplay of the rescattering of the first electron and the Coulomb induced large ionization time lag. On the other hand, the nuclear motion increases the contributions of these two electrons releasing together along the He side. This effect differentiates DI of HeH$^+$ from HeT$^+$., Comment: 8 pages,8figures

Published
2019
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26. Reconstruction of Cherenkov image by multiple telescopes of LHAASO-WFCTA

Author

Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Zhe, Cao, Zhen, Chang, J., Chang, J. F., Chen, E. S., Chen, Liang, Chen, Liang, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, H. L., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., D’Ettorre Piazzoli, B., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., 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, X. T., Feng, Y. L., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., 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, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, W. H., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Levochkin, K., Li, B. B., Li, Cheng, Li, Cong, Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Xin, 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., Long, W. J., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Min, Z., Mitthumsiri, W., Nan, Y. C., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Shao, C. Y., 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., Wang, R. N., Wang, W., Wang, X. G., 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, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yan, J. Z., Yang, C. W., Yang, F. F., Yang, H. W., 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., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, Lu, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Y. L., Zhang, Yi, Zhang, Yong, 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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27. Tracing origins of asymmetric momentum distribution for polar molecules in strong linearly-polarized laser fields

Author

Wang, S., Che, J. Y., Chen, C., Xin, G. G., and Chen, Y. J.

Subjects
Physics - Atomic Physics
Abstract

We study the ionization dynamics of oriented HeH$^+$ in strong linearly-polarized laser fields by numerically solving the time-dependent Schr\"{o}dinger equation. The calculated photoelectron momentum distributions for parallel orientation show a striking asymmetric structure. With a developed model pertinent to polar molecules, we trace the electron motion in real time. We show that this asymmetric structure arises from the interplay of the Coulomb effect and the permanent dipole in strong laser fields. This structure can be used to probe the degree of orientation which is important in ultrafast experiments for polar molecules. we also check our results for other polar molecules such as CO and BF., Comment: 6 pages, 6figures; typos corrected; revised argument in section II and section V, results unchanged

Published
2019
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28. Coulomb-induced ionization time lag after electrons tunnel out of a barrier

Author

Chen, Y. J., Xie, X. J., Chen, C., Xin, G. G., and Liu, J.

Subjects
Physics - Atomic Physics
Abstract

After electrons tunnel out of a laser-Coulomb-formed barrier, %formed by the strong laser field and the atomic Coulomb potential, the movement of the tunneling electron can be affected by the Coulomb tail. We show that this Coulomb effect induces a large time difference (longer than a hundred attoseconds) between the exiting time at which the electron exits the barrier and the ionization time at which the electron is free. This large time difference has important influences on strong-field processes such as above-threshold ionization and high-harmonic generation, with remarkably changing time-frequency properties of electron trajectories. Some semi-quantitative evaluations on these influences are addressed, which provide new insight into strong-field physics and give important suggestions on attosecond measurements., Comment: 5 pages, 4 figures

Published
2019

29. Line-of-shower trigger method to lower energy threshold for GRB detection using LHAASO-WCDA

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., Cao, Z., Chang, J., Chang, J. F., Chang, X. C., Chen, B. M., Chen, J., Chen, L., Chen, L., 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, Volpe, D. della, 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., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, C., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, K., Li, W. L., Li, X., Li, X., Li, X. R., Li, Y., Li, Y. Z., Li, 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, W., Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z., 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., 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., Zhang, Y. F., Zhang, Y. L., 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
2021
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30. A dynamic range extension system for LHAASO WCDA-1

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., Cao, Z., Chang, J., Chang, J. F., Chang, X. C., Chen, B. M., Chen, J., Chen, L., Chen, L., 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, Volpe, D. della, 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, Y., Huang, Z. C., Ji, F., Ji, X. L., Jia, H. Y., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, C., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, K., Li, W. L., Li, X., Li, X., Li, X. R., Li, Y., Li, Y. Z., Li, 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, W., Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z., 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., 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., Zhang, Y. F., Zhang, Y. L., 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
2021
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31. Ultrahigh-energy photons up to 1.4 petaelectronvolts from 12 γ-ray Galactic sources

Author

Cao, Zhen, Aharonian, F. A., 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, Zhe, Chang, J., Chang, J. F., Chang, X. C., Chen, B. M., Chen, J., Chen, L., 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., D′Ettorre Piazzoli, B., 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., Jiang, K., Jiang, Z. J., Jin, C., 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, X., 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. 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, W., Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Zheng, Wang, Zhen, 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, Li, Zhang, L. X., Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Yong, Zhang, Yi, Zhang, Y. F., Zhang, Y. L., 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
2021
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32. A new Plethystic Symmetric Function Operator and The rational Compositional Shuffle Conjecture at t=1/q

Author

Garsia, A. M., Leven, E., Wallach, N., and Xin, G.

Subjects
Mathematics - Combinatorics
Abstract

Our main result here is that the specialization at $t=1/q$ of the $Q_{km,kn}$ operators studied in [4] may be given a very simple plethystic form. This discovery yields elementary and direct derivations of several identities relating these operators at $t=1/q$ to the Rational Compositional Shuffle conjecture of [3]. In particular we show that if $m,n $ and $k$ are positive integers and $(m,n)$ is a coprime pair then $$ q^{(km-1)(kn-1)+k-1\over 2} Q_{km,kn}(-1)^{kn}\Big|_{t=1/q} \,=\, \textstyle{[k]_q\over [km]_q} e_{km}\big[ X[km]_q\big] $$ where as customarily, for any integer $s \geq 0$ and indeterminate $u$ we set $[s]_u=1+u+\cdots +u^{s-1}$. We also show that the symmetric polynomial on the right hand side is always Schur positive. Moreover, using the Rational Compositional Shuffle conjecture, we derive a precise formula expressing this polynomial in terms of Parking functions in the $km\times kn$ lattice rectangle.

Published
2015

34. Some new applications of the Stanley-Macdonald Pieri Rules

Author

Garsia, A. M., Haglund, J., Xin, G., and Zabrocki, M.

Subjects
Mathematics - Combinatorics, 05E05
Abstract

In a seminal paper Richard Stanley derived Pieri rules for the Jack symmetric function basis. These rules were extended by Macdonald to his now famous symmetric function basis. The original form of these rules had a forbidding complexity that made them difficult to use in explicit calculations. In the early 90's it was discovered that, due to massive cancellations, the dual rule, which expresses skewing by $e_1$ the modified Macdonald polynomial ${\tilde H}_\mu[X;q,t]$, can be given a very simple combinatorial form in terms of corner weights of the Ferrers' diagram of $\mu$. A similar formula was later obtained by the last named author for the multiplication of ${\tilde H}_\mu[X;q,t]$ by $e_1$, but never published. In the years that followed we have seen some truly remarkable uses of these two Pieri rules in establishing highly non trivial combinatorial results in the Theory of Macdonald polynomials. This theory has recently been spectacularly enriched by various Algebraic Geometrical results in the works of Hikita, Schiffmann, Schiffmann-Vasserot, A. Negut and Gorsky-Negut. This development opens up the challenging task of deriving their results by purely Algebraic Combinatorial methods. In this paper we present the progress obtained by means of Pieri rules., Comment: TeX; 25 pages; for Stanley@70. Massachusetts institute of technology, June 23-27, 2014

Published
2014

35. Construction and on-site performance of the LHAASO WFCTA camera

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., Cao, Z., Chang, J., Chang, J. F., Chang, X. C., Chen, B. M., Chen, J., Chen, L., Chen, L., 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, Volpe, D. della, 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., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, C., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, K., Li, W. L., Li, X., Li, X., Li, X. R., Li, Y., Li, Y. Z., Li, 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, W., Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z., 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., 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., Zhang, Y. F., Zhang, Y. L., 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
2021
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37. Epigenetics and immunotherapy in colorectal cancer: progress and promise

Author

Tianjiao Dang, Xin Guan, Luying Cui, Yuli Ruan, Zhuo Chen, Haoyi Zou, Ya Lan, Chao Liu, and Yanqiao Zhang

Subjects
Epigenetic regulation, Colorectal cancer, Biomarkers, Immunotherapy, Medicine, Genetics, QH426-470
Abstract

Abstract Colorectal cancer (CRC) is a common malignant tumor with the third and second highest incidence and mortality rates among various malignant tumors. Despite significant advancements in the present therapy for CRC, the majority of CRC cases feature proficient mismatch repair/microsatellite stability and have no response to immunotherapy. Therefore, the search for new treatment options holds immense importance in the diagnosis and treatment of CRC. In recent years, clinical research on immunotherapy combined with epigenetic therapy has gradually increased, which may bring hope for these patients. This review explores the role of epigenetic regulation in exerting antitumor effects through its action on immune cell function and highlights the potential of certain epigenetic genes that can be used as markers of immunotherapy to predict therapeutic efficacy. We also discuss the application of epigenetic drug sensitization immunotherapy to develop new treatment options combining epigenetic therapy and immunotherapy.

Published
2024
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38. Prediction of axillary lymph node metastasis using a magnetic resonance imaging radiomics model of invasive breast cancer primary tumor

Author

Wei Shi, Yingshi Su, Rui Zhang, Wei Xia, Zhenqiang Lian, Ning Mao, Yanyu Wang, Anqin Zhang, Xin Gao, and Yan Zhang

Subjects
Breast cancer primary tumor, Axillary lymph node metastasis, Radiomics, Medical physics. Medical radiology. Nuclear medicine, R895-920, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background This study investigated the clinical value of breast magnetic resonance imaging (MRI) radiomics for predicting axillary lymph node metastasis (ALNM) and to compare the discriminative abilities of different combinations of MRI sequences. Methods This study included 141 patients diagnosed with invasive breast cancer from two centers (center 1: n = 101, center 2: n = 40). Patients from center 1 were randomly divided into training set and test set 1. Patients from center 2 were assigned to the test set 2. All participants underwent preoperative MRI, and four distinct MRI sequences were obtained. The volume of interest (VOI) of the breast tumor was delineated on the dynamic contrast-enhanced (DCE) postcontrast phase 2 sequence, and the VOIs of other sequences were adjusted when required. Subsequently, radiomics features were extracted from the VOIs using an open-source package. Both single- and multisequence radiomics models were constructed using the logistic regression method in the training set. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision of the radiomics model for the test set 1 and test set 2 were calculated. Finally, the diagnostic performance of each model was compared with the diagnostic level of junior and senior radiologists. Results The single-sequence ALNM classifier derived from DCE postcontrast phase 1 had the best performance for both test set 1 (AUC = 0.891) and test set 2 (AUC = 0.619). The best-performing multisequence ALNM classifiers for both test set 1 (AUC = 0.910) and test set 2 (AUC = 0.717) were generated from DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging single-sequence ALNM classifiers. Both had a higher diagnostic level than the junior and senior radiologists. Conclusions The combination of DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging radiomics features had the best performance in predicting ALNM from breast cancer. Our study presents a well-performing and noninvasive tool for ALNM prediction in patients with breast cancer.

Published
2024
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39. Neuroimaging markers of aberrant brain activity and treatment response in schizophrenia patients based on brain complexity

Author

Liju Liu, Zezhi Li, Di Kong, Yanqing Huang, Diwei Wu, Huachang Zhao, Xin Gao, Xiangyang Zhang, and Mi Yang

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract The complexity of brain activity reflects its ability to process information, adapt to environmental changes, and transition between states. However, it remains unclear how schizophrenia (SZ) affects brain activity complexity, particularly its dynamic changes. This study aimed to investigate the abnormal patterns of brain activity complexity in SZ, their relationship with cognitive deficits, and the impact of antipsychotic medication. Forty-four drug-naive first-episode (DNFE) SZ patients and thirty demographically matched healthy controls (HC) were included. Functional MRI-based sliding window analysis was utilized for the first time to calculate weighted permutation entropy to characterize complex patterns of brain activity in SZ patients before and after 12 weeks of risperidone treatment. Results revealed reduced complexity in the caudate, putamen, and pallidum at baseline in SZ patients compared to HC, with reduced complexity in the left caudate positively correlated with Continuous Performance Test (CPT) and Category Fluency Test scores. After treatment, the complexity of the left caudate increased. Regions with abnormal complexity showed decreased functional connectivity, with complexity positively correlated with connectivity strength. We observed that the dynamic complexity of the brain exhibited the characteristic of spontaneous, recurring “complexity drop”, potentially reflecting transient state transitions in the resting brain. Compared to HC, patients exhibited reduced scope, intensity, and duration of complexity drop, all of which improved after treatment. Reduced duration was negatively correlated with CPT scores and positively with clinical symptoms. The results suggest that abnormalities in brain activity complexity and its dynamic changes may underlie cognitive deficits and clinical symptoms in SZ patients. Antipsychotic treatment partially restores these abnormalities, highlighting their potential as indicators of treatment efficacy and biomarkers for personalized therapy.

Published
2024
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40. DMSS: An Attention-Based Deep Learning Model for High-Quality Mass Spectrometry Prediction

Author

Yihui Ren, Yu Wang, Wenkai Han, Yikang Huang, Xiaoyang Hou, Chunming Zhang, Dongbo Bu, Xin Gao, and Shiwei Sun

Subjects
mass spectrometry, proteomics, machine learning, deep learning, Electronic computers. Computer science, QA75.5-76.95
Abstract

Accurate prediction of peptide spectra is crucial for improving the efficiency and reliability of proteomic analysis, as well as for gaining insight into various biological processes. In this study, we introduce Deep MS Simulator (DMSS), a novel attention-based model tailored for forecasting theoretical spectra in mass spectrometry. DMSS has undergone rigorous validation through a series of experiments, consistently demonstrating superior performance compared to current methods in forecasting theoretical spectra. The superior ability of DMSS to distinguish extremely similar peptides highlights the potential application of incorporating our predicted intensity information into mass spectrometry search engines to enhance the accuracy of protein identification. These findings contribute to the advancement of proteomics analysis and highlight the potential of the DMSS as a valuable tool in the field.

Published
2024
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41. Repair of annulus fibrosus defects using decellularized annulus fibrosus matrix/chitosan hybrid hydrogels

Author

Chen Liu, Xin Ge, and Yifeng Li

Subjects
Decellularized annulus fibrosus matrix, Chitosan, Annulus fibrosus defect, Orthopedic surgery, RD701-811, Diseases of the musculoskeletal system, RC925-935
Abstract

Abstract Degenerative disc disease is the leading cause of lower back and leg pain, considerably impacting daily life and incurring substantial medical expenses for those affected. The development of annulus fibrosus tissue engineering offers hope for treating this condition. However, the current annulus fibrosus tissue engineering scaffolds fail to accurately mimic the natural biological environment of the annulus fibrosus, resulting in limited secretion of extracellular matrix produced by the seeded cells and poor biomechanical properties of the constructed biomimetic annulus fibrosus tissue. This inability to match the biomechanical performance of the natural annulus fibrosus hinders the successful treatment of annulus fibrosus defects. In this study, we fabricated decellularized annulus fibrosus matrix (DAFM)/chitosan hydrogel-1 (DAFM: Chitosan 6:2) and DAFM/chitosan hydrogel-2 (DAFM: Chitosan 4:4) by varying the ratio of DAFM to chitosan. Rat annulus fibrosus (AF)-derived stem cells were cultured on these hydrogel scaffolds, and the cell morphology, AF-related gene expression, and Interleukin-6 (IL-6) levels were investigated. Additionally, magnetic resonance imaging, Hematoxylin and eosin staining, and Safranine and Fast Green staining were performed to evaluate the repair effect of the DAFM/chitosan hydrogels in vivo. The gene expression results showed that the expression of Collagen type I (Col-I), Collagen type I (Col-II), and aggrecan by annulus fibrosus stem cells (AFSCs) cultured on the DAFM/chitosan-1 hydrogel was higher compared with the DAFM/chitosan-2 hydrogel. Conversely, the expression of metalloproteinase-9 (MMP-9) and IL-6 was lower on the DAFM/chitosan-1 hydrogel compared with the DAFM/chitosan-2 hydrogel. In vivo, both the DAFM/chitosan-1 and DAFM/chitosan-2 hydrogels could partially repair large defects of the annulus fibrosus in rat tail vertebrae. In conclusion, the DAFM/chitosan-1 hydrogel could be regarded as a candidate scaffold material for the repair of annulus fibrosus defects, offering the potential for improved treatment outcomes.

Published
2024
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42. A gap-free genome assembly of Fusarium oxysporum f. sp. conglutinans, a vascular wilt pathogen

Author

Huan Wang, Gang Yao, Weikai Chen, Dilay Hazal Ayhan, Xiangfeng Wang, Jie Sun, Shu Yi, Tan Meng, Shaoying Chen, Xin Geng, Dian Meng, Lili Zhang, and Li Guo

Subjects
Science
Abstract

Abstract Fusarium oxysporum is an asexual filamentous fungus that causes vascular wilt in hundreds of crop plants and poses a threat to public health through Fusariosis. F. oxysporum f. sp. conglutinans strain Fo5176, originally isolated from Brassica oleracea, is pathogenic to Arabidopsis, making it a model pathosystem for dissecting the molecular mechanisms underlying host-pathogen interactions. Assembling the F. oxysporum genome is notoriously challenging due to the presence of repeat-rich accessory chromosomes. Here, we report a gap-free genome assembly of Fo5176 using PacBio HiFi and Hi-C data. The 69.56 Mb assembly contained 18 complete chromosomes, including all centromeres and most telomeres (20/36), representing the first gap-free genome sequence of a pathogenic F. oxysporum strain. In total, 21,460 protein-coding genes were annotated, a 26.3% increase compared to the most recent assembly. This high-quality reference genome for F. oxysporum f. sp. conglutinans Fo5176 provides a valuable resource for further research into fungal pathobiology and evolution.

Published
2024
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43. Unveiling the enigmatic role of MYH9 in tumor biology: a comprehensive review

Author

Yunkuo Li, Yujie Pan, Xiangzhe Yang, Yuxiong Wang, Bin Liu, Yanghe Zhang, Xin Gao, Yishu Wang, Honglan Zhou, and Faping Li

Subjects
MYH9, Cancer, Signaling pathway, Anticancer therapy, Medicine, Cytology, QH573-671
Abstract

Abstract Non-muscle myosin heavy chain IIA (MYH9), a member of the non-muscle myosin II (NM II) family, is widely expressed in cells. The interaction of MYH9 with actin in the cytoplasm can hydrolyze ATP, completing the conversion of chemical energy to mechanical motion. MYH9 participates in various cellular processes, such as cell adhesion, migration, movement, and even signal transduction. Mutations in MYH9 are often associated with autosomal dominant platelet disorders and kidney diseases. Over the past decade, tumor-related research has gradually revealed a close relationship between MYH9 and the occurrence and development of tumors. This article provides a review of the research progress on the role of MYH9 in cancer regulation. We also discussed the anti-cancer effects of MYH9 under special circumstances, as well as its regulation of T cell function. In addition, given the importance of MYH9 as a key hub in oncogenic signal transduction, we summarize the current therapeutic strategies targeting MYH9 as well as the ongoing challenges.

Published
2024
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44. Multiomics and machine learning-based analysis of pancancer pseudouridine modifications

Author

Jiheng Zhang, Lei Xu, Xiuwei Yan, Jiahe Hu, Xin Gao, Hongtao Zhao, Mo Geng, Nan Wang, and Shaoshan Hu

Subjects
Pseudouridine modification, Pancancer, Tumor microenvironment, Machine learning, Antitumor therapy, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Pseudouridine widely affects the stability and function of RNA. However, our knowledge of pseudouridine properties in tumors is incomplete. We systematically analyzed pseudouridine synthases (PUSs) expression, genomic aberrations, and prognostic features in 10907 samples from 33 tumors. We found that the pseudouridine-associated pathway was abnormal in tumors and affected patient prognosis. Dysregulation of the PUSs expression pattern may arise from copy number variation (CNV) mutations and aberrant DNA methylation. Functional enrichment analyses determined that the PUSs expression was closely associated with the MYC, E2F, and MTORC1 signaling pathways. In addition, PUSs are involved in the remodeling of the tumor microenvironment (TME) in solid tumors, such as kidney and lung cancers. Particularly in lung cancer, increased expression of PUSs is accompanied by increased immune checkpoint expression and Treg infiltration. The best signature model based on more than 112 machine learning combinations had good prognostic ability in ACC, DLBC, GBM, KICH, MESO, THYM, TGCT, and PRAD tumors, and is expected to guide immunotherapy for 19 tumor types. The model was also effective in identifying patients with tumors amenable to etoposide, camptothecin, cisplatin, or bexarotene treatment. In conclusion, our work highlights the dysregulated features of PUSs and their role in the TME and patient prognosis, providing an initial molecular basis for future exploration of pseudouridine. Studies targeting pseudouridine are expected to lead to the development of potential diagnostic strategies and the evaluation and improvement of antitumor therapies.

Published
2024
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45. Chromosome-scale pearl millet genomes reveal CLAMT1b as key determinant of strigolactone pattern and Striga susceptibility

Author

Hendrik N. J. Kuijer, Jian You Wang, Salim Bougouffa, Michael Abrouk, Muhammad Jamil, Roberto Incitti, Intikhab Alam, Aparna Balakrishna, Derry Alvarez, Cristina Votta, Guan-Ting Erica Chen, Claudio Martínez, Andrea Zuccolo, Lamis Berqdar, Salim Sioud, Valentina Fiorilli, Angel R. de Lera, Luisa Lanfranco, Takashi Gojobori, Rod A. Wing, Simon G. Krattinger, Xin Gao, and Salim Al-Babili

Subjects
Science
Abstract

Abstract The yield of pearl millet, a resilient cereal crop crucial for African food security, is severely impacted by the root parasitic weed Striga hermonthica, which requires host-released hormones, called strigolactones (SLs), for seed germination. Herein, we identify four SLs present in the Striga-susceptible line SOSAT-C88-P10 (P10) but absent in the resistant 29Aw (Aw). We generate chromosome-scale genome assemblies, including four gapless chromosomes for each line. The Striga-resistant Aw lacks a 0.7 Mb genome segment containing two putative CARLACTONOIC ACID METHYLTRANSFERASE1 (CLAMT1) genes, which may contribute to SL biosynthesis. Functional assays show that P10CLAMT1b produces the SL-biosynthesis intermediate methyl carlactonoate (MeCLA) and that MeCLA is the precursor of P10-specific SLs. Screening a diverse pearl millet panel confirms the pivotal role of the CLAMT1 section for SL diversity and Striga susceptibility. Our results reveal a reason for Striga susceptibility in pearl millet and pave the way for generating resistant lines through marker-assisted breeding or direct genetic modification.

Published
2024
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46. Association between fast eating speed and metabolic dysfunction-associated steatotic liver disease: a multicenter cross-sectional study and meta-analysis

Author

Miao Zhang, Xiaoyang Sun, Xiaopeng Zhu, Lili Zheng, Yufang Bi, Qiang Li, Lirong Sun, Fusheng Di, Yushan Xu, Dalong Zhu, Yanyan Gao, Yuqian Bao, Yao Wang, Lanjie He, Chenmin Fan, Xin Gao, Jian Gao, Mingfeng Xia, and Hua Bian

Subjects
Nutritional diseases. Deficiency diseases, RC620-627
Abstract

Abstract Background With the fast pace of modern life, people have less time for meals, but few studies have examined the association between the habit of fast eating and metabolic diseases. Objective Combining the results of the current study and the prior ones, we aimed to investigate the possible relationship between fast eating and the risk of metabolic dysfunction-associated steatotic liver disease (MASLD). Methods This is a sub-analysis of a multicenter cross-sectional study of 1965 participants investigated the association between fast eating and MASLD in Chinese. Fast eating was defined as meal time less than five minutes and participants were divided into three categories based on their self-reported frequency of fast eating: ≤1 time/month, ≤1 time/week and ≥2 times/week. We further conducted a literature search for available studies published before November, 2023 as well as a meta-analysis to investigate the association between fast eating and MASLD. Results The proportion of MASLD was 59.3%, 50.5%, and 46.2% in participants with fast eating ≥2 times/week, ≤1 time/week and ≤1 time/month, respectively (P for trend

Published
2024
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47. The influence factors on pit and fissure sealing behavior of 12-year-old children: a cross-sectional study in Zhejiang, China

Author

Xin Ge, Huan Zhou, Xuejing Li, Lixuen Siow, Yanyi Xie, Yijie Hu, Yao Wan, Danli Fu, and Haihua Zhu

Subjects
Prevention of caries, Pit and fissure sealants, Preventive dentistry, Social determinants, Oral examination, Pediatrics, RJ1-570
Abstract

Abstract Background In the 21st century, dental caries remains a global burden, particularly severely affecting the growth and quality of life of 12-year-old children. Fortunately, pit and fissure sealing (PFS) procedures can effectively prevent molars from caries. Hence, this study focused on the relationship between PFS and oral epidemiological factors in 12-year-old children. Methods A cross-sectional survey was conducted in 12-year-old children from 11 cities in Zhejiang Province. Their dental conditions were collected through questionnaires, as well as basic information such as relevant family information, oral health knowledge and behavior. Then, logistic regression analysis was used to identify the influencing factors associated with PFS. Results A total of 1204 children were included, with 252 in the PFS group and 952 in the non-PFS group. There were significant differences between the two groups in terms of decayed, missing and filled teeth (DMFT) score, first permanent molar DMFT score, residential area, educational level of parents, tooth-brushing frequency, use of dental floss, oral examination in a medical institution, having taken courses on oral health care, as well as having knowledge that tooth brushing could effectively prevent gingival inflammation, PFS could protect teeth, and oral disease may affect general health. According to further logistic regression analysis, the independent factors influencing PFS included use of dental floss [odds ratios (OR) = 1.672, 95% confidence intervals (CI) = 1.235–2.263, P = 0.001], having taken courses on oral health care (OR = 0.713, 95% CI = 0.515–0.988, P = 0.042), having knowledge that tooth brushing is effective in preventing gingival inflammation (OR = 0.627, 95% CI = 0.389–0.987, P = 0.044) and having knowledge that PFS can protect teeth (OR = 0.589, 95% CI = 0.438–0.791, P

Published
2024
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48. ALA Promotes Sucrose Accumulation in Early Peach Fruit by Regulating SPS Activity

Author

Zheng Chen, Xin Guo, Jinhua Du, and Mingliang Yu

Subjects
5-aminolevulinic acid, peach, SPS activity, PpSPS2, Biology (General), QH301-705.5
Abstract

5-Aminolevulinic acid (ALA), as a novel plant growth regulator, is a critical precursor for the biosynthesis of porphyrin compounds in all organisms. Many studies have reported that exogenous ALA treatment could improve fruit sweetness. However, the mechanism by which ALA promotes the increase in sugar content in fruit remains unclear. In this study, we found that ALA significantly promoted sucrose accumulation and SPS (sucrose phosphate synthase) activity in peach fruit. At 14, 28, 42, 50 and 60 days after ALA treatment, sucrose content of fruit was increased by 23%, 43%, 37%, 40% and 16%, respectively, compared with control treatment, and SPS enzyme activity was increased by 21%, 28%, 47%, 37% and 29%, respectively. Correlation analysis showed that the sucrose content of peach fruit under ALA treatment was significantly positively correlated with SPS activity. Subsequently, bioinformatics was used to identify SPS gene family members in peach fruit, and it was found that there were four members of the PpSPS gene family, distributed on chromosomes 1, 7 and 8, named PpSPS1, PpSPS2, PpSPS3 and PpSPS4, respectively. The results of qRT-PCR showed that PpSPS2 and PpSPS3 were highly expressed in response to ALA during fruit development, and the expression of PpSPS2 was positively correlated with SPS activity and sucrose accumulation in peach fruit. The results of tobacco subcellular localization showed that PpSPS2 was mainly distributed in the cytoplasm and nucleus, while PpSPS3 was mainly distributed in the nucleus. The results of this study will lay the foundation for further study on the functions of PpSPS and the regulation of sugar metabolism during the development and ripening of peach fruit by ALA.

Published
2024
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50. Multilevel neurium-mimetic individualized graft via additive manufacturing for efficient tissue repair

Author

Lingchi Kong, Xin Gao, Xiangyun Yao, Haijiao Xie, Qinglin Kang, Wei Sun, Zhengwei You, Yun Qian, and Cunyi Fan

Subjects
Science
Abstract

Abstract Complicated peripheral nerve injuries or defects, especially at branching sites, remain a prominent clinical challenge after the application of different treatment strategies. Current nerve grafts fail to match the expected shape and size for delicate and precise branched nerve repair on a case-by-case basis, and there is a lack of geometrical and microscale regenerative navigation. In this study, we develop a sugar painting-inspired individualized multilevel epi-/peri-/endoneurium-mimetic device (SpinMed) to customize natural cues, featuring a selectively protective outer sheath and an instructive core, to support rapid vascular reconstruction and consequent efficient neurite extension along the defect area. The biomimetic perineurium dictates host-guest crosslinking in which new vessels secrete multimerin 1 binding to the fibroin filler surface as an anchor, contributing to the biological endoneurium that promotes Schwann cell homing and remyelination. SpinMed implantation into rat sciatic nerve defects yields a satisfactory outcome in terms of structural reconstruction, with sensory and locomotive function restoration. We further customize SpinMed grafts based on anatomy and digital imaging, achieving rapid repair of the nerve trunk and branches superior to that achieved by autografts and decellularized grafts in a specific beagle nerve defect model, with reliable biosafety. Overall, this intelligent art-inspired biomimetic design offers a facile way to customize sophisticated high-performance nerve grafts and holds great potential for application in translational regenerative medicine.

Published
2024
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