Author: "Bi Y." / Publication Year Range: Last 10 years - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Bi Y."' showing total 4,324 results

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4,324 results on '"Bi Y."'

1. Broadband $\gamma$-ray spectrum of supernova remnant Cassiopeia A

Author: Cao, Zhen, Aharonian, F., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Bian, W., Bukevich, A. V., Cai, C. M., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, H. X., Chen, Liang, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, X. B., Chen, X. J., Chen, Y., Cheng, N., Cheng, Y. D., Chu, M. C., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Diao, Y. X., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, J. H., Fang, K., Feng, C. F., Feng, H., Feng, L., Feng, S. H., Feng, X. T., Feng, Y., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Ge, T. T., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, J., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., Hannuksela, O. A., Hasan, M., He, H. H., He, H. N., He, J. Y., He, X. Y., He, Y., Hernández-Cadena, S., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, S. C., Huang, C., Huang, D. H., Huang, J. J., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Y. Y., Ji, X. L., Jia, H. Y., Jia, K., Jiang, H. B., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kaci, S., Kang, M. M., Karpikov, I., Khangulyan, D., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, Jian, Li, Jie, Li, K., Li, L., Li, R. L., Li, S. D., Li, T. Y., 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, D. B., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. R., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, X., Liu, Y., Liu, Y. N., Lou, Y. Q., Luo, Q., Luo, Y., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mou, G. B., Mu, H. J., Nan, Y. C., Neronov, A., Ng, K. C. Y., Ni, M. Y., Nie, L., Ou, L. J., Pattarakijwanich, P., Pei, Z. Y., Qi, J. C., Qi, M. Y., Qin, J. J., Raza, A., Ren, C. Y., Ruffolo, D., Sáiz, A., Saeed, M., Semikoz, D., Shao, L., Shchegolev, O., Shen, Y. Z., Sheng, X. D., Shi, Z. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, D. X., Sun, H., Sun, Q. N., Sun, X. N., Sun, Z. B., Tabasam, N. H., Takata, J., Tam, P. H. T., Tan, H. B., Tang, Q. W., Tang, R., Tang, Z. B., Tian, W. W., Tong, C. N., Wan, L. H., Wang, C., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, Kai, Wang, L. P., Wang, L. Y., Wang, R., Wang, W., Wang, X. G., Wang, X. J., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Z. H., Wang, Z. X., Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Weng, S. S., Wu, C. Y., Wu, H. R., Wu, Q. W., 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, Y. L., Xing, Y., Xiong, D. R., 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, C. Y., Yang, F. F., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, W. X., Yao, Y. H., Yao, Z. G., Ye, X. A., 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, B. T., Zhang, F., Zhang, H., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. R., Zhang, S. S., Zhang, W. Y., Zhang, X., Zhang, X. P., Zhang, Yi, Zhang, Yong, Zhang, Z. P., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zhao, X. H., Zhao, Z. H., Zheng, F., Zhong, W. J., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, B. Y., 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 core-collapse supernova remnant (SNR) Cassiopeia A (Cas A) is one of the brightest galactic radio sources with an angular radius of $\sim$ 2.5 $\arcmin$. Although no extension of this source has been detected in the $\gamma$-ray band, using more than 1000 days of LHAASO data above $\sim 0.8$ TeV, we find that its spectrum is significantly softer than those obtained with Imaging Air Cherenkov Telescopes (IACTs) and its flux near $\sim 1$ TeV is about two times higher. In combination with analyses of more than 16 years of \textit{Fermi}-LAT data covering $0.1 \, \mathrm{GeV} - 1 \, \mathrm{TeV}$, we find that the spectrum above 30 GeV deviates significantly from a single power-law, and is best described by a smoothly broken power-law with a spectral index of $1.90 \pm 0.15_\mathrm{stat}$ ($3.41 \pm 0.19_\mathrm{stat}$) below (above) a break energy of $0.63 \pm 0.21_\mathrm{stat} \, \mathrm{TeV}$. Given differences in the angular resolution of LHAASO-WCDA and IACTs, TeV $\gamma$-ray emission detected with LHAASO may have a significant contribution from regions surrounding the SNR illuminated by particles accelerated earlier, which, however, are treated as background by IACTs. Detailed modelling can be used to constrain acceleration processes of TeV particles in the early stage of SNR evolution.
Published: 2025

2. Detection of two TeV gamma-ray outbursts from NGC 1275 by LHAASO

Author: Cao, Zhen, Aharonian, F., 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: The Water Cherenkov Detector Array (WCDA) is one of the components of Large High Altitude Air Shower Observatory (LHAASO) and can monitor any sources over two-thirds of the sky for up to 7 hours per day with >98\% duty cycle. In this work, we report the detection of two outbursts of the Fanaroff-Riley I radio galaxy NGC 1275 that were detected by LHAASO-WCDA between November 2022 and January 2023 with statistical significance of 5.2~$\sigma$ and 8.3~$\sigma$. The observed spectral energy distribution in the range from 500 GeV to 3 TeV is fitted by a power-law with a best-fit spectral index of $\alpha=-3.37\pm0.52$ and $-3.35\pm0.29$, respectively. The outburst flux above 0.5~TeV was ($4.55\pm 4.21)\times~10^{-11}~\rm cm^{-2}~s^{-1}$ and ($3.45\pm 1.78)\times~10^{-11}~\rm cm^{-2}~s^{-1}$, corresponding to 60\%, 45\% of Crab Nebula flux. Variation analysis reveals the variability time-scale of days at the TeV energy band. A simple test by one-zone synchrotron self-Compton model reproduces the data in the gamma-ray band well., Comment: 11 pages, 8 figures, 3 tables
Published: 2024

3. LHAASO detection of very-high-energy gamma-ray emission surrounding PSR J0248+6021

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: We report the detection of an extended very-high-energy (VHE) gamma-ray source coincident with the location of middle-aged (62.4~\rm kyr) pulsar PSR J0248+6021, by using the LHAASO-WCDA data of live 796 days and LHAASO-KM2A data of live 1216 days. A significant excess of \gray induced showers is observed both by WCDA in energy bands of 1-25~\rm TeV and KM2A in energy bands of $>$ 25~\rm TeV with 7.3 $\sigma$ and 13.5 $\sigma$, respectively. The best-fit position derived through WCDA data is R.A. = 42.06$^\circ \pm$ 0.12$^\circ$ and Dec. = 60.24$^\circ \pm $ 0.13$^\circ$ with an extension of 0.69$^\circ\pm$0.15$^\circ$ and that of the KM2A data is R.A.= 42.29$^\circ \pm $ 0.13$^\circ$ and Dec. = 60.38$^\circ \pm$ 0.07$^\circ$ with an extension of 0.37$^\circ\pm$0.07$^\circ$. No clear extended multiwavelength counterpart of this LHAASO source has been found from the radio band to the GeV band. The most plausible explanation of the VHE \gray emission is the inverse Compton process of highly relativistic electrons and positrons injected by the pulsar. These electrons/positrons are hypothesized to be either confined within the pulsar wind nebula or to have already escaped into the interstellar medium, forming a pulsar halo., Comment: 12 pages, 10 figures, Accepted by Sci. China-Phys. Mech. Astron
Published: 2024

4. 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

5. Data quality control system and long-term performance monitor of the LHAASO-KM2A

Author: Cao, Zhen, Aharonian, F., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Bian, W., Bukevich, A. V., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, H. X., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S., 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, J. H., Fang, K., Feng, C. F., Feng, H., Feng, L., Feng, S. H., Feng, X. T., Feng, Y., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., 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., Hasan, M., He, H. H., He, H. N., He, J. Y., 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., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Karpikov, I., Kuleshov, D., Kurinov, K., Li, B. B., Li, C. M., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, Jian, Li, Jie, Li, K., Li, S. D., 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, D. B., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Luo, Q., Luo, Y., 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, L. J., Pattarakijwanich, P., Pei, Z. Y., Qi, J. C., Qi, M. Y., Qiao, B. Q., Qin, J. J., Raza, A., Ruffolo, D., Sáiz, A., Saeed, M., Semikoz, D., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, D. X., Sun, Q. N., Sun, X. N., Sun, Z. B., Takata, J., Tam, P. H. T., Tang, Q. W., Tang, R., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, Kai, 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, Q. W., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, Y. L., Xing, Y., Xiong, D. R., 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, C. Y., Yang, F., Yang, F. F., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, W. X., Yao, Y. H., Yao, Z. G., 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., Zhang, H. M., Zhang, H. Y., Zhang, J. L., 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., Zhao, X. H., Zheng, F., Zhong, W. J., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, B. Y., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., Zou, Y. C., and Zuo, X.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: The KM2A is the largest sub-array of the Large High Altitude Air Shower Observatory (LHAASO). It consists of 5216 electromagnetic particle detectors (EDs) and 1188 muon detectors (MDs). The data recorded by the EDs and MDs are used to reconstruct primary information of cosmic ray and gamma-ray showers. This information is used for physical analysis in gamma-ray astronomy and cosmic ray physics. To ensure the reliability of the LHAASO-KM2A data, a three-level quality control system has been established. It is used to monitor the status of detector units, stability of reconstructed parameters and the performance of the array based on observations of the Crab Nebula and Moon shadow. This paper will introduce the control system and its application on the LHAASO-KM2A data collected from August 2021 to July 2023. During this period, the pointing and angular resolution of the array were stable. From the observations of the Moon shadow and Crab Nebula, the results achieved using the two methods are consistent with each other. According to the observation of the Crab Nebula at energies from 25 TeV to 100 TeV, the time averaged pointing errors are estimated to be $-0.003^{\circ} \pm 0.005^{\circ}$ and $0.001^{\circ} \pm 0.006^{\circ}$ in the R.A. and Dec directions, respectively., Comment: 15 pages, 9 figures
Published: 2024

6. 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
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7. 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
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8. 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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9. Bidirectional causal associations between frailty measures and sleep disturbances: a two-sample Mendelian randomization study

Author: Che L, Zang H, Bi Y, Wen B, and Xu L
Subjects: frailty, sleep disturbance, mendelian randomization, the elderly, Psychiatry, RC435-571, Neurophysiology and neuropsychology, QP351-495
Abstract: Lu Che,&ast; Han Zang,&ast; Yaodan Bi, Bei Wen, Li Xu Department of Anesthesiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Li Xu, Email pumchxuli@163.comBackground: Observational studies have demonstrated a strong association between sleep disturbances and frailty. However, the causality remains inconclusive. We aimed to investigate the bidirectional causal relationships between frailty measures and sleep disturbances employing a two-sample Mendelian randomization (MR) analysis.Methods: Two-sample MR analyses were performed based on large-scale genome-wide association studies (GWAS) of the European population for frailty index (FI) (N = 175,226), Fried Frailty Score (FFS) (N = 386,565), insomnia (N = 283,595), sleep duration (N = 445,966) and sleep apnea (N = 523,366). We conducted the causal estimates using the inverse variance-weighted method (IVW), with sensitivity analyses using MR-Egger, weighted median, weighted mode, and MR pleiotropy residual sum and outlier (MR-PRESSO) analysis. Cochran’s Q test was performed to assess heterogeneity.Results: We found that genetically predicted FI was associated with shorter sleep duration and sleep apnea. The genetically predicted FFS was associated with insomnia, shorter sleep duration, and sleep apnea. In the reverse direction analysis, genetic liability to insomnia, short sleep duration, and long sleep duration were associated with an increase in FI. Genetic liability to short sleep duration and long sleep duration were associated with an increase in FFS.Conclusion: Our study provided genetic evidence supporting the bidirectional causality between frailty measures and sleep disturbances. The findings contribute to the prevention and management of frailty and sleep disturbances.Keywords: frailty, sleep disturbances, Mendelian randomization, the elderly
Published: 2025

10. 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

11. 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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12. Morphological evidence for nanoflares heating warm loops in the solar corona

Author: Bi, Y., Yang, J. J., Qin, Y., Qiang, Z. P., Hong, J. C., Yang, B., Xu, Z., Liu, H., and Ji, K. F.
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: Nanoflares are impulsive energy releases by magnetic reconnection in the braided coronal magnetic field, which is a potential mechanism for heating the corona. However, there are still sporadic observations of the interchange of braiding structure segments and footpoints inside coronal loops, which is predicted to be the morphological evolution of the reconnecting magnetic bundles in the nanoflare picture. This work aims to detect the evolutions of the pairs of braiding strands within the apparent single coronal loops observed in Atmospheric Imaging Assembly (AIA) images. The loop strands are detected on two kinds of upsampled AIA 193 \AA\ images, which are obtained by upscaling the Point Spread Function matched AIA images via Bicubic interpolation and are generated using a super-resolution convolutional neural network, respectively. The architecture of the network is designed to map the AIA images to unprecedentedly high spatial resolution coronal images taken by High-resolution Coronal Imager (Hi-C) during its brief flight. At times, pairs of separate strands that appear braided together later evolved into pairs of almost parallel strands with completely exchanged parts. These evolutions offer morphological evidence that magnetic reconnections between the braiding strands have taken place, which is further supported by the appearance of transient hot emissions containing significant high-temperature components (T > 5MK) at the footpoints of the braiding structures. The brief appearances of the two rearranging strands support that magnetic reconnections have occurred within what appears to be a single AIA loop., Comment: Accepted for publication in Astronomy & Astrophysics
Published: 2023
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13. Differences in Haematological and Imaging Features of Lumbar Spine Fungal and Brucella Infections

Author: Fu XW, Bi Y, Wei JL, Qi M, Zhu L, Pu Y, Liu JL, Li X, and Cun XH
Subjects: mycosis, brucellosis, imaging, differential diagnosis, Infectious and parasitic diseases, RC109-216
Abstract: Xu-Wen Fu,1,&ast; Yan Bi,2,&ast; Jia-Lu Wei,3 Min Qi,3 Long Zhu,3 Ying Pu,3 Jing-Liang Liu,2 Xiang Li,3 Xin-Hua Cun4 1Department of Pharmacy, Kunming Third People’s Hospital/Yunnan Clinical Medical Center for Infectious Diseases, Kunming, 650041, People’s Republic of China; 2Department of Radiology, The People’s Hospital of Lincang, Lincang, 677000, People’s Republic of China; 3Department of Radiology, Kunming Third People’s Hospital/Yunnan Clinical Medical Center for Infectious Diseases, Kunming, Yunnan, 650200,People’s Republic of China; 4Department of Orthopaedics, Kunming Third People’s Hospital/Yunnan Clinical Medical Center for Infectious Diseases, Kunming, 650041, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xiang Li, Department of Radiology, Kunming Third People’s Hospital/Yunnan Clinical Medical Center for Infectious Diseases, Kunming, Yunnan, 650041, People’s Republic of China, Tel +86 18108857532, Email li_xiang115@126.com Xin-Hua Cun, Department of Orthopaedics, Kunming Third People’s Hospital/Yunnan Clinical Medical Center for Infectious Diseases, Kunming, Yunnan, 650041, People’s Republic of China, Email xinhuacun_cun6@21cn.comObjective: To observe the clinical characteristics of fungal and Brucella infections of the lumbar spine and explore the key points for their differential diagnosis.Methods: The clinical data of 12 patients with fungal infection (the fungal group) and 31 patients with Brucella infection (the Brucella group) of the lumbar spine confirmed by microbiological culture and antigen test were retrospectively analysed. The differences in the clinical characteristics and imaging manifestations were observed between the two groups.Results: The peripheral blood neutrophil ratio, erythrocyte sedimentation rate, serum total protein and serum globulin levels in the fungal group were higher compared with the Brucella group, while the peripheral blood lymphocyte count, lymphocyte ratio and albumin-globulin ratio were lower in the fungal group compared with the Brucella group (P < 0.05). As for imaging examinations, the proportion of bone destruction centred on the intervertebral disc with surrounding osteosclerosis on computed tomography (CT) imaging showed a statistical difference between the Brucella group and the fungal group (P < 0.05). Fungal infection patients showed more osteosclerosis-free areas around the bone destruction on magnetic resonance imaging (MRI) than Brucella infection patients.Conclusion: There are certain similarities in clinical manifestations between fungal and Brucella infections of the lumbar spine, but the haematological indices and image features of CT and MRI can effectively differentiate between them, providing guidance for the clinical differential diagnosis.Keywords: mycosis, brucellosis, imaging, differential diagnosis
Published: 2024

14. Efficacy and Safety of Jiuxin Pill in the Treatment of Patients with Stable Angina Pectoris: A Protocol for a Randomized, Double-Blind, Placebo-Controlled, Multicenter Clinical Trial

Author: Liu T, Zhang J, Zhao Z, Bi Y, Zheng Y, Wang S, Dai X, Li J, Lin Q, Ni D, Wang C, Wu J, Xue Y, Zhu M, Wang X, and Mao J
Subjects: traditional chinese medicine, jiuxin pill, stable angina pectoris, protocol, randomized controlled trial., Medicine (General), R5-920
Abstract: Tongzuo Liu,1,2,&ast; Jingyi Zhang,1,2,&ast; Zhiqiang Zhao,1 Yingfei Bi,1 Ying Zheng,1 Shuai Wang,1 Xiaohua Dai,3 Jun Li,4 Qian Lin,5 Daimei Ni,6 Chenglong Wang,7 Jianguang Wu,8 Yitao Xue,9 Mingjun Zhu,10 Xianliang Wang,1,&ast; Jingyuan Mao1,&ast; 1Cardiovascular Department, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine/National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, People’s Republic of China; 2Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 3Cardiovascular Department, The First Affiliated Hospital of Anhui University of Chinese Medicine, Anhui, People’s Republic of China; 4Cardiovascular Department, Guang’anmen Hospital of China Academy of Chinese Medicine Science, Beijing, People’s Republic of China; 5Cardiovascular Department, Dongzhimen Hospital of Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 6Cardiovascular Department, Taihe Hospital of Traditional Chinese Medicine Affiliated to Anhui University of Chinese Medicine, Anhui, People’s Republic of China; 7Cardiovascular Department, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China; 8Cardiovascular Department, Affiliated Hospital of Jiangxi University of Chinese Medicine, Jiangxi, People’s Republic of China; 9Cardiovascular Department, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Shandong, People’s Republic of China; 10Cardiovascular Department, The First Affiliated Hospital of He’nan University of Traditional Chinese Medicine, Henan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jingyuan Mao; Xianliang Wang, Cardiovascular Department, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine/National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, People’s Republic of China, Tel +86-13820498886 ; +86-13920007825, Email jymao@126.com; xlwang1981@126.comBackground: Stable angina pectoris (SAP), as a common type of coronary heart disease (CHD), is characterized by transient retrosternal squeezing pain or suffocation induced by exercise, mood swings, or other stress. Most patients with stable angina pectoris do not benefit from interventional therapy and medication, so optimizing treatment plans has important clinical significance. Jiuxin pill is a Chinese patent medicine developed by Huatuo Chinese Medicine Co. Ltd. (Bozhou, China) to relieve the symptoms of stable angina pectoris (SAP). However, there is a lack of evidence support from high-quality clinical studies.Methods: In this randomized, double-blind, placebo-controlled, multicenter clinical trial, 170 patients with SAP were recruited from 11 centers in China. The patients were randomized to either the treatment group (Jiuxin pill, 2 pills, bid) or the control group (Jiuxin pill simulant, 2 pills, bid) without changing the original conventional western medicine. The trial was set up with a run-in period of 7 days, a treatment period of 28 ± 2 days, and a follow-up period of 28 ± 2 days. Total exercise time (TED) in the treadmill test and Seattle Angina Questionnaire (SAQ) scores were set as the main efficacy outcomes, and the 1-minute heart rate recovery (HRR1), metabolic equivalents (METs), maximum ST segment depression, Borg perceived exertion after exercise, the average number of angina attacks per week, usage of nitroglycerin, drug withdrawal and reduction rate, information scoring of four diagnostic methods in traditional Chinese medicine and incidence of major adverse cardiovascular events were set as the secondary efficacy outcomes. Adverse events were monitored throughout the trial.Discussion: In China, the use of Chinese patent medicine in the treatment of stable angina pectoris is more common. This trial evaluated the efficacy and safety of the Jiuxin pill in the treatment of patients with SAP, and the trial results provide high-quality research evidence for its clinical application.Trial Registration: This trial has been registered in the China Clinical Trial Registry on 11 June 2022 (Registration No.: ChiCTR2200060780, https://www.chictr.org.cn/showproj.html?proj=172352).Keywords: traditional Chinese medicine, Jiuxin pill, stable angina pectoris, protocol, randomized controlled trial
Published: 2024

15. 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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16. 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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17. Red Blood Cell-Hitchhiking Delivery of Simvastatin to Relieve Acute Respiratory Distress Syndrome

Author: Sun M, Wei J, Su Y, He Y, Ge L, Shen Y, Xu B, Bi Y, and Zheng C
Subjects: acute lung injury, simvastatin, respiratory distress syndrome, ph response, Medicine (General), R5-920
Abstract: Mengjuan Sun,1,&ast; Jun Wei,1,&ast; Yanhui Su,1,&ast; Yangjingwan He,1 Liang Ge,1 Yan Shen,1 Bohui Xu,2 Yanlong Bi,3 Chunli Zheng1 1Department of Pharmaceutics, China Pharmaceutical University, Nanjing, People’s Republic of China; 2School of Pharmacy, Nantong University, Nantong, People’s Republic of China; 3Pediatric Intensive Care Unit, Children’s Hospital of Nanjing Medical University, Nanjing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Chunli Zheng; Yanlong Bi, Email zhengchunli@cpu.edu.cn; pulong123@163.comPurpose: The purpose of this study is to address the high mortality and poor prognosis associated with Acute Respiratory Distress Syndrome (ARDS), conditions characterized by acute and progressive respiratory failure. The primary goal was to prolong drug circulation time, increase drug accumulation in the lungs, and minimize drug-related side effects.Methods: Simvastatin (SIM) was used as the model drug in this study. Employing a red blood cell surface-loaded nanoparticle drug delivery technique, pH-responsive cationic nanoparticles loaded with SIM were non-covalently adsorbed onto the surface of red blood cells (RBC), creating a novel drug delivery system (RBC@SIM-PEI-PPNPs).Results: The RBC@SIM-PEI-PPNPs delivery system effectively extended the drug’s circulation time, providing an extended therapeutic window. Additionally, this method substantially improved the targeted accumulation of SIM in lung tissues, thereby enhancing the drug’s efficacy in treating ARDS and impeding its progression to ARDS. Crucially, the system showed a reduced risk of adverse drug reactions.Conclusion: RBC@SIM-PEI-PPNPs demonstrates promise in ARDS and ARDS treatment. This innovative approach successfully overcomes the limitations associated with SIM’s poor solubility and low bioavailability, resulting in improved therapeutic outcomes and fewer drug-related side effects. This research holds significant clinical implications and highlights its potential for broader application in drug delivery and lung disease treatment.Keywords: acute lung injury, simvastatin, respiratory distress syndrome, pH response
Published: 2024

18. Mesoporous Silicon with Strontium-Powered Poly(Lactic-Co-Glycolic acid)/Gelatin-Based Dressings Facilitate Skin Tissue Repair

Author: Li N, Zhang W, Wu S, Shafiq M, Xie P, Zhang L, Jiang S, and Bi Y
Subjects: electrospinning, nanofiber membrane, wound healing, mesoporous silicon, strontium, Medicine (General), R5-920
Abstract: Naijing Li,1,&ast; Weiying Zhang,2,&ast; Siyuan Wu,3,&ast; Muhammad Shafiq,4 Peihan Xie,3 Lixiang Zhang,5 Shichao Jiang,3 Yue Bi1 1Department of Orthopedic Oncology, Yantai Shan Hospital, Yantai, People’s Republic of China; 2Health Management Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, People’s Republic of China; 3Department of Orthopedics, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, People’s Republic of China; 4Innovation Center of Nanomedicines, Kawasaki Institute of Industrial Promotion, Kawasaki, Japan; 5Department of Health Management, Characteristic Medical Center of Chinese People’s Armed Police Force, Tianjin, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yue Bi; Shichao Jiang, Email dr_yuebi@126.com; mailjsc@163.comPurpose: Functional inorganic nanomaterials (NMs) are widely exploited as bioactive materials and drug depots. The lack of a stable form of application of NMs at the site of skin injury, may impede the removal of the debridement, elevate pH, induce tissue toxicity, and limit their use in skin repair. This necessitates the advent of innovative wound dressings that overcome the above limitations. The overarching objective of this study was to exploit strontium-doped mesoporous silicon particles (PSiSr) to impart multifunctionality to poly(lactic-co-glycolic acid)/gelatin (PG)-based fibrous dressings (PG@PSiSr) for excisional wound management.Methods: Mesoporous silicon particles (PSi) and PSiSr were synthesized using a chemo-synthetic approach. Both PSi and PSiSr were incorporated into PG fibers using electrospinning. A series of structure, morphology, pore size distribution, and cumulative pH studies on the PG@PSi and PG@PSiSr membranes were performed. Cytocompatibility, hemocompatibility, transwell migration, scratch wound healing, and delineated angiogenic properties of these composite dressings were tested in vitro. The biocompatibility of composite dressings in vivo was assessed by a subcutaneous implantation model of rats, while their potential for wound healing was discerned by implantation in a full-thickness excisional defect model of rats.Results: The PG@PSiSr membranes can afford the sustained release of silicon ions (Si4+) and strontium ions (Sr2+) for up to 192 h as well as remarkably promote human umbilical vein endothelial cells (HUVECs) and NIH-3T3 fibroblasts migration. The PG@PSiSr membranes also showed better cytocompatibility, hemocompatibility, and significant formation of tubule-like networks of HUVECs in vitro. Moreover, PG@PSiSr membranes also facilitated the infiltration of host cells and promoted the deposition of collagen while reducing the accumulation of inflammatory cells in a subcutaneous implantation model in rats as assessed for up to day 14. Further evaluation of membranes transplanted in a full-thickness excisional wound model in rats showed rapid wound closure (PG@SiSr vs control, 96.1% vs 71.7%), re-epithelialization, and less inflammatory response alongside skin appendages formation (eg, blood vessels, glands, hair follicles, etc.).Conclusion: To sum up, we successfully fabricated PSiSr particles and prepared PG@PSiSr dressings using electrospinning. The PSiSr-mediated release of therapeutic ions, such as Si4+ and Sr2+, may improve the functionality of PLGA/Gel dressings for an effective wound repair, which may also have implications for the other soft tissue repair disciplines.Keywords: electrospinning, nanofiber membrane, wound healing, mesoporous silicon, strontium
Published: 2024

19. 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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20. Stem Cell-Derived Extracellular Vesicles: Promising Therapeutic Opportunities for Diabetic Wound Healing

Author: Zhang B, Bi Y, Wang K, Guo X, Liu Z, Li J, and Wu M
Subjects: diabetes, wound healing, stem cells, regeneration, evs, ncrnas, Medicine (General), R5-920
Abstract: Boyu Zhang,1,&ast; Yajun Bi,2,&ast; Kang Wang,1,&ast; Xingjun Guo,3 Zeming Liu,1 Jia Li,1 Min Wu1 1Department of Plastic and Cosmetic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 2Department of Pediatrics, Dalian Municipal Women and Children’s Medical Center (Group), Dalian Medical University, Dalian, Liaoning Province, 116011, People’s Republic of China; 3Department of Biliary-Pancreatic Surgery, Affiliated Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jia Li; Min Wu, Department of Plastic and Cosmetic Surgery, Tongji Hospital, Tongji Medical College 1095 Jiefang Avenue, Wuhan, Hubei, People’s Republic of China, Tel +86 18846818658 ; +86 13554254796, Email 4338311@qq.com; wumin@hust.edu.cnAbstract: Wound healing is a sophisticated and orderly process of cellular interactions in which the body restores tissue architecture and functionality following injury. Healing of chronic diabetic wounds is difficult due to impaired blood circulation, a reduced immune response, and disrupted cellular repair mechanisms, which are often associated with diabetes. Stem cell-derived extracellular vesicles (SC-EVs) hold the regenerative potential, encapsulating a diverse cargo of proteins, RNAs, and cytokines, presenting a safe, bioactivity, and less ethical issues than other treatments. SC-EVs orchestrate multiple regenerative processes by modulating cellular communication, increasing angiogenesis, and promoting the recruitment and differentiation of progenitor cells, thereby potentiating the reparative milieu for diabetic wound healing. Therefore, this review investigated the effects and mechanisms of EVs from various stem cells in diabetic wound healing, as well as their limitations and challenges. Continued exploration of SC-EVs has the potential to revolutionize diabetic wound care. Keywords: diabetes, wound healing, stem cells, EVs, ncRNAs, regeneration
Published: 2024

21. Development and Validation of a Risk Score for Mild Cognitive Impairment in Individuals with Type 2 Diabetes in China: A Practical Cognitive Prescreening Tool

Author: Ding Q, Yu C, Xu X, Hou Y, Miao Y, Yang S, Chen S, Ma X, Zhang Z, and Bi Y
Subjects: mild cognitive impairment, type 2 diabetes mellitus, risk score, prescreening tool, Specialties of internal medicine, RC581-951
Abstract: Qun Ding,1– 4,&ast; Congcong Yu,2,3,&ast; Xiang Xu,1,3 Yinjiao Hou,1,3 Yingwen Miao,2,3 Sijue Yang,2,3 Shihua Chen,2,3 Xuelin Ma,2,3 Zhou Zhang,2,3 Yan Bi1– 3 1Department of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, People’s Republic of China; 2Department of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, People’s Republic of China; 3Branch of National Clinical Research Centre for Metabolic Diseases, Nanjing, People’s Republic of China; 4Department of Endocrinology, the Second People’s Hospital of Lianyungang, Lianyungang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhou Zhang, Department of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Branch of National Clinical Research Centre for Metabolic Diseases, No. 321, Zhongshan Road, Nanjing, 210008, People’s Republic of China, Tel + 86 25-83106666, Email zhangzhou@smail.nju.edu.cn Yan Bi, Department of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Branch of National Clinical Research Centre for Metabolic Diseases, No. 321, Zhongshan Road, Nanjing, 210008, People’s Republic of China, Tel + 86 25-83105313, Email biyan@nju.edu.cnAim: Numerous evidence suggests that diabetes increases the risk of cognitive impairment. This study aimed to develop and validate a multivariable risk score model to identify mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM).Methods: This cross-sectional study included 1256 inpatients (age: 57.5 ± 11.2 years) with T2DM in a tertiary care hospital in China. MCI was diagnosed according to the criteria recommended by the National Institute on Aging-Alzheimer’s Association Workgroup, and a MoCA score of 19– 25 indicated MCI. Participants were randomly allocated into the derivation and validation sets at 7:3 ratio. Logistic regression models were used to identify predictors for MCI in the derivation set. A scoring system based on the predictors’ beta coefficient was developed. Predictive ability of the risk score was tested by discrimination and calibration methods.Results: Totally 880 (285 with MCI, 32.4%) and 376 (167 with MCI, 33.8%) patients were allocated in the derivation and validation set, respectively. Age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease were identified as predictors for MCI and constituted the risk score. The AUCs (95% CI) of the risk score were 0.751 (0.717, 0.784) in derivation set and 0.776 (0.727, 0.824) in validation set. The risk score showed good apparent calibration of observed and predicted MCI probabilities and was capable of stratifying individuals into 3 risk categories by two cut-off points (low risk: ≤ 3, medium risk: 4– 13, and high risk ≥ 14).Conclusion: The risk score based on age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease can effectively assess MCI risk in adults with T2DM at different age. It can serve as a practical prescreening tool for early detection of MCI in daily diabetes care.Keywords: mild cognitive impairment, type 2 diabetes mellitus, risk score, prescreening tool
Published: 2024

22. Adsorption–degradation of methylene blue by natural manganese ore: kinetics, characterization, and mechanism

Author: Cai, Y., Qiu, C., Yang, K., Tian, B., and Bi, Y.
Published: 2024
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23. 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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24. Clinical Evidence of the Relationship Between Alanine Aminotransferase and Diabetic Kidney Disease

Author: Bi Y, Yang Y, Yuan X, Wang J, Liu Z, Tian S, and Sun C
Subjects: alanine aminotransferase, diabetic kidney disease, dose-response relationship, nhanes, Specialties of internal medicine, RC581-951
Abstract: Yaru Bi,1,&ast; Yang Yang,2,&ast; Xiaojie Yuan,3 Jiping Wang,3 Zhiyuan Liu,4 Suyan Tian,5 Chenglin Sun1,3 1Department of Endocrinology and Metabolism, First Hospital of Jilin University, Changchun, 130000, People’s Republic of China; 2Department of Health Examination Center, First Hospital of Jilin University, Changchun, 130000, People’s Republic of China; 3Department of Clinical Nutrition, First Hospital of Jilin University, Changchun, 130000, People’s Republic of China; 4Department of Clinical Medicine, Yanbian University, Yanji, 136200, People’s Republic of China; 5Division of Clinical Research, First Hospital of Jilin University, Changchun, 130000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Suyan Tian; Chenglin Sun, Email wmxt@jlu.edu.cn; chenglins@jlu.edu.cnAim: Multiple studies have investigated the association between alanine aminotransferase (ALT) and diabetes mellitus (DM); however, only a few studies have specifically examined the relationship between ALT and diabetic kidney disease (DKD). This study aimed to investigate the relationship between ALT and DKD using clinical data.Methods: A cross-sectional study was conducted on 668 individuals that included non-DM (N=281), DM without DKD (N=160), and DKD (N=227) patients. A generalized additive model (GAM) was used to examine the dose–response relationship between ALT and DKD risk. We also analyzed the data from the US National Health and Nutrition Examination Survey (NHANES) 2015– 2018 using the same statistical methods; 4481, 1110, and 671 individuals were included in the non-DM, DM without DKD, and DKD groups, respectively.Results: The changes in ALT activity among the non-DM, DM without DKD, and DKD groups showed a similar pattern in both our clinical data and the NHANES dataset. ALT activity increases with the onset of DM, whereas ALT activity decreases when DM progresses to DKD. The GAM revealed a nonlinear U-shaped relationship between ALT and DKD risk in the two datasets, and the lowest range of ALT was 40– 50 IU/L. Both lower (< 40 IU/L) and higher (> 50 IU/L) ALT activity were found to be positively associated with DKD risk.Conclusion: A U-shaped nonlinear association between ALT and DKD was found in our clinical data and NHANES data. DKD risk was increased by both lower or higher ALT activity. To confirm the causality of nonlinear relationship, larger prospective studies or Mendelian randomization analysis are required.Keywords: alanine aminotransferase, diabetic kidney disease, dose–response relationship, NHANES
Published: 2024

25. Therapeutic Potential of Downregulated Interleukin-6 Signaling for the Treatment of Chronic Pain: A Mendelian Randomization Study

Author: Bi Y, Zhu Y, and Tang S
Subjects: il-6 signaling, chronic pain, mendelian randomization, Medicine (General), R5-920
Abstract: Yaodan Bi,1,&ast; Yingchao Zhu,2,&ast; Shuai Tang1 1Department of Anesthesiology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 2Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Shuai Tang, Department of anesthesiology, Peking Union Medical College Hospital, Beijing, People’s Republic of China, Email tangshuai@pumch.cnIntroduction: While numerous studies have emphasized the pivotal involvement of the Interleukin 6 (IL-6) pathway in the development of chronic pain, the causal nature of this relationship remains uncertain.Methods: In this study, we opted to include genetic variants situated within the locus of the IL-6 receptor (IL-6R) that exhibited associations with C-reactive protein (CRP) levels. CRP serves as a downstream effector in the IL-6 pathway. Utilizing these variants as genetic proxies, we aimed to modulate IL-6 signaling. Employing a two-sample Mendelian randomization (MR) approach, we investigated the potential link between the genetic proxy and seven distinct subtypes of chronic pain, categorized based on their corresponding body locations. Moreover, we examined the relationship between chronic pain and an alternative instrument of IL-6 signaling that was weighted based on s-IL-6R levels. Furthermore, we conducted exploratory analyses to estimate the plausible causal association between CRP, gp130, and the subtypes of chronic pain.Results: Our analysis showed that genetic proxied downregulation of IL-6 signaling, weighted on CRP levels, was linked to a reduced risk of chronic back and knee pain. The sensitivity analyses across various MR methods confirmed the consistency of the findings and showed no evidence of horizontal pleiotropy or heterogeneity. Moreover, the results remained robust with different sets of instrument variables. A genetically increased level of s-IL-6R was also negatively associated with chronic back and knee pain. However, there was no causal relationship between CRP and gp130 with chronic pain.Conclusion: Based on our findings, there is evidence to suggest a potential causal relationship between IL-6 signaling and chronic back and knee pain. Consequently, the downregulation of IL-6 signaling holds promise as a potential therapeutic target for addressing chronic back and knee pain.Keywords: IL-6 signaling, chronic pain, Mendelian randomization
Published: 2023

26. Galvanic Corrosion Behavior of 7B04 Aluminum/TC16 Titanium Alloy Joints After Anodized Oxidation and Its Effect on Fatigue Life

Author: Zhang, T., Zhang, T., He, Y., Bi, Y., Hou, B., and Li, C. F.
Published: 2023
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27. 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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28. The significant impact of the crystallization of cementite in high carbon steel wire on its torsional performance

Author: Bi, Y., Wang, Q., He, T., Liu, X.P., Liu, Y.D., Wang, Y.D., and Yao, Z.
Published: 2024
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29. The Emerging Roles of Exosomal miRNAs in Breast Cancer Progression and Potential Clinical Applications

Author: Li J, He D, Bi Y, and Liu S
Subjects: breast cancer, tumor microenvironment, exosome, mirnas, detection, therapy, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Jie Li,1,&ast; Dejiao He,2,&ast; Yajun Bi,3,&ast; Shengxuan Liu4 1Department of Thyroid and Breast Surgery, Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, 518067, People’s Republic of China; 2Department of Nephrology, Renmin Hospital of Wuhan University, Wuhan, 430060, People’s Republic of China; 3Department of Pediatrics, Dalian Municipal Women and Children’s Medical Center (Group), Dalian Medical University, Dalian, Liaoning Province, 116011, People’s Republic of China; 4Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430030, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Shengxuan Liu, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430030, People’s Republic of China, Tel +86 133 8756 1016, Email tongjishengxuanl@163.comAbstract: Breast cancer remains the leading malignancy in terms of morbidity and mortality today. The tumor microenvironment of breast cancer includes multiple cell types, secreted proteins, and signaling components such as exosomes. Among these, exosomes have a lipid bilayer structure. Exosomes can reflect the biological traits of the parent cell and carry a variety of biologically active components, including proteins, lipids, small molecules, and non-coding RNAs, which include miRNA, lncRNA, and circRNA. MiRNAs are a group of non-coding RNAs of approximately 20– 23 nucleotides in length encoded by the genome, triggering silencing and functional repression of target genes. MiRNAs have been shown to play a significant role in the development of cancer owing to their role in the prognosis, pathogenesis, diagnosis, and treatment of cancer. MiRNAs in exosomes can serve as effective mediators of information transfer from parental cells to recipient cells and trigger changes in biological traits such as proliferation, invasion, migration, and drug resistance. These changes can profoundly alter the progression of breast cancer. Therefore, here, we systematically summarize the association of exosomal miRNAs on breast cancer progression, diagnosis, and treatment in the hope of providing novel strategies and directions for subsequent breast cancer treatment.Keywords: breast cancer, tumor microenvironment, exosome, miRNAs, detection, therapy
Published: 2023

30. Magnetic Resonance Imaging Manifestations in 13 Cases of Seminal Vesicle Tuberculosis

Author: Gan W, Bi Y, Fu X, Wei J, Qi M, He J, and Li X
Subjects: seminal vesicle tuberculosis, magnetic resonance imaging, genitourinary tuberculosis, Infectious and parasitic diseases, RC109-216
Abstract: Wei Gan,1,&ast; Yan Bi,2,&ast; Xuwen Fu,1 Jialu Wei,1 Min Qi,1 Jintang He,3 Xiang Li1 1Department of Radiology, Kunming Third People’s Hospital/Yunnan Clinical Medical Center for Infectious Diseases, Kunming, 650041, People’s Republic of China; 2Department of Radiology, The People’s Hospital of Lincang, Lincang, Yunnan, 677000, People’s Republic of China; 3Department of Surgery, Kunming Third People’s Hospital/Yunnan Clinical Medical Center for Infectious Diseases, Kunming, 650041, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xiang Li, Department of Radiology, Kunming Third People’s Hospital /Yunnan Clinical Medical Center for Infectious Diseases, No. 319 of Wujing Street, Guandu District, Kunming, 650041, People’s Republic of China, Tel +86 871 6352 3507, Fax +86 871 6351 4717, Email li_xiang115@126.com Jintang He, Department of Surgery, Kunming Third People’s Hospital/Yunnan Clinical Medical Center for Infectious Diseases, No. 319 of Wujing Street, Guandu District, Kunming, 650041, People’s Republic of China, Tel +86 871 6842 3689, Fax +86 871 6351 4717, Email he_jintang06@21cn.comObjective: This study aimed to examine the radiographic manifestations of seminal vesicle tuberculosis (SVT) on magnetic resonance imaging to gain a deeper understanding of this disease.Methods: The clinical symptoms, general conditions, relevant laboratory tests and radiological data of 13 patients diagnosed with SVT were collected through bacteriological examination. A descriptive analysis was used to explore the composition ratio and rate values of the collected data.Results: All 13 cases (100.0%) showed isointense signals on T1WI and hypointense signals on T2WI in the affected seminal vesicles, with the disappearance of the multi-chambered high signal on T2WI in normal seminal vesicles. Eight cases (61.5%) showed diffusion restriction on DWI of the affected seminal vesicle and significant enhancement on the contrast scan, whereas five cases (38.5%) showed unrestricted diffusion and mild enhancement on the contrast scan. Patients with significant enhancements exhibited higher counts and neutrophil percentages than patients with mild enhancements, with statistically significant differences (Z = 2.196, P = 0.030; Z = 2.781, P = 0.003, respectively). The counts and percentage of lymphocytes, CD3+T cells and CD4+T cells were significantly lower in patients with significant enhancements than in those with mild enhancements, with statistically significant differences (Z = − 2.196, P = 0.030; Z = − 2.928, P = 0.002; Z = − 2.928, P = 0.002; Z = − 2.928, P = 0.002, respectively). Patients with significant enhancements were more likely to have active pulmonary tuberculosis than those with mild enhancements, with a statistically significant difference (P = 0.035).Conclusion: Magnetic resonance imaging reveals distinct radiographic features of SVT, and variations in imaging presentations can indicate a patient’s immune status.Keywords: seminal vesicle tuberculosis, magnetic resonance imaging, genitourinary tuberculosis
Published: 2023

31. 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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32. 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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33. Graphene-Quantum Dots Hybrid Photodetectors with Low Dark-Current Readout

Author: De Fazio, D., Uzlu, B., Torre, I., Monasterio, C., Gupta, S., Khodkov, T., Bi, Y., Wang, Z., Otto, M., Lemme, M. C., Goossens, S., Neumaier, D., and Koppens, F. H. L.
Subjects: Physics - Applied Physics, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract: Graphene-based photodetectors have shown responsivities up to 10$^8$A/W and photoconductive gains up to 10$^{8}$ electrons per photon. These photodetectors rely on a highly absorbing layer in close proximity of graphene, which induces a shift of the graphene chemical potential upon absorption, hence modifying its channel resistance. However, due to the semi-metallic nature of graphene, the readout requires dark currents of hundreds of $\mu$A up to mA, leading to high power consumption needed for the device operation. Here we propose a novel approach for highly responsive graphene-based photodetectors with orders of magnitude lower dark current levels. A shift of the graphene chemical potential caused by light absorption in a layer of colloidal quantum dots, induces a variation of the current flowing across a metal-insulator-graphene diode structure. Owing to the low density of states of graphene near the neutrality point, the light-induced shift in chemical potential can be relatively large, dramatically changing the amount of current flowing across the insulating barrier, and giving rise to a novel type of gain mechanism. This readout requires dark currents of hundreds of nA up to few $\mu$A, orders of magnitude lower than other graphene-based photodetectors, while keeping responsivities of $\sim$70A/W in the infrared, almost two orders of magnitude higher compared to established germanium on silicon and indium gallium arsenide infrared photodetectors. This makes the device appealing for applications where high responsivity and low power consumption are required., Comment: 14 pages, 7 figures
Published: 2020
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34. Changing Trends in the Disease Burden of Cataract and Forecasted Trends in China and Globally from 1990 to 2030

Author: Shu Y, Shao Y, Zhou Q, Lu L, Wang Z, Zhang L, and Bi Y
Subjects: china, cataract, disease burden, risk factors, Infectious and parasitic diseases, RC109-216
Abstract: Yiyang Shu,1 Yuting Shao,1 Qi Zhou,2 Lixia Lu,3 Zhiyue Wang,1 Li Zhang,1 Yanlong Bi1,4 1Department of Ophthalmology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, People’s Republic of China; 2Exam Center of Tongji University School of Medicine, Shanghai, People’s Republic of China; 3Department of Biochemistry and Molecular Biology, Tongji Eye Institute, Tongji University School of Medicine, Shanghai, People’s Republic of China; 4Tongji Eye Institute, Tongji University School of Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Yanlong Bi, Email biyanlong@tongji.edu.cnAim: To explore the trends in the prevalence and disease burden of cataract from 1990 to 2019, evaluate attributable risk factors, and predict trends over the next decade in China and globally.Methods: Data was obtained from Global Burden of Disease Study 2019. We calculated the age-standardized prevalence rate (ASR) and annual percentage change (EAPC) to show the trends of cataract in China and different regions. We calculated and reported the proportion of disability adjusted life years (DALYs) attributable to risk factors by sex in China and different regions. Then, the Bayesian age-period-cohort (BAPC) analysis model was also used to predict the prevalence trends from 2020 to 2030 in China and globally.Results: The ASR increased from 867.09 in 1990 to 991.56 in 2019 per 100,000 with an EAPC of 0.88 in China. The age-standardized DALY rate of females was higher than males. DALY rates were correlated to household air pollution from solid fuels, tobacco, high fasting plasma glucose and high body-mass index. The projective model indicates that the ASR for cataracts will rise to 1101.35× 106 for male and 1616.63× 106 for female by 2030.Conclusion: The trends from 1990 to 2030 suggested that the burden of cataract remains high in China. Maintaining good lifestyle habits such as switching to clean energy, reducing cigar intake, controlling blood glucose and weight can reduce the risk of cataracts. As aging increases, China should pay more attention to cataract-induced low vision and blindness and develop public policies to reduce the disease burden.Keywords: China, cataract, disease burden, risk factors
Published: 2023

35. 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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36. Field-Trial of Machine Learning-Assisted Quantum Key Distribution (QKD) Networking with SDN

Author: Ou, Y., Hugues-Salas, E., Ntavou, F., Wang, R., Bi, Y., Yan, SY., Kanellos, G., Nejabati, R., and Simeonidou, D.
Subjects: Electrical Engineering and Systems Science - Signal Processing, Quantum Physics
Abstract: We demonstrated, for the first time, a machine-learning method to assist the coexistence between quantum and classical communication channels. Software-defined networking was used to successfully enable the key generation and transmission over a city and campus network.
Published: 2018

37. CD133, but Not CD44, May Serve as a Novel Biomarker for Differential Diagnosis Between Basal Cell Carcinoma and Trichoblastomas

Author: Bi Y, Shi X, Chen D, and Zhao Y
Subjects: basal cell carcinoma (bcc), trichoblastomas (tb), differential diagnosis, cd133, cd44, immunohistochemistry, receiver operating characteristic (roc), Dermatology, RL1-803
Abstract: Yalan Bi,1 Xiaohua Shi,2 Dian Chen,1 Yi Zhao1 1Department of Dermatology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, People’s Republic of China; 2Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of ChinaCorrespondence: Yi Zhao, Department of Dermatology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, No. 168 Litang Road, Changping District, Beijing, People’s Republic of China, Tel/Fax +86 010 56119127, Email zhaoyimd@tsinghua.edu.cnPurpose: To investigate the clinical value of CD133 and CD44 as putative cancer stem cell markers in distinguishing between basal cell carcinoma (BCC) and trichoblastomas (TB).Patients and Methods: Tumor samples from 24 BCC and 23 TB patients were retrospectively retrieved for immunohistochemical staining of CD133 and CD44. The results were interpreted using a semiquantitative scoring system (H score). A receiver operating characteristic (ROC) curve was developed to identify an optimal cutoff value for differentiating between BCC and TB.Results: Expression of CD133 was significantly higher in BCC patients than in TB patients (median H score: 30 [IQR: 12.5– 56.3] vs 0 [IQR: 0– 2], P < 0.001). However, there was no significant difference in CD44 expression between the two groups (median H score: 105 [IQR: 63.8– 155.0] vs 60 [IQR: 30– 120], P = 0.095). The ROC analysis of CD133 immunostaining yielded an area under the curve (AUC) of 0.881 (95% CI: 0.756– 1.000) for differentiating between BCC and TB by using a H score of 7 as the cut-off value (98.5% sensitivity and 87.0% specificity). By contrast, immunostaining of CD44 showed a lower diagnostic value, with an AUC of 0.642 (95% CI: 0.476– 0.808) at the optimal cut-off value of 85 (62.5% sensitivity and 73.9% specificity). The positive and negative predictive values were 88.5% and 95.2% for CD133 and 71.4% and 65.4% for CD44, respectively. Additionally, CD133 expression was significantly associated with mitotic activity in BCC patients (r = 0.549, P = 0.005).Conclusion: Our study expanded upon previous studies of CD133 and CD44 expressions in skin tumors, suggesting that CD133, but not CD44, may serve as a novel biomarker for differential diagnosis of BCC, although future studies using a larger number of patients are needed to justify it further.Keywords: basal cell carcinoma, BCC, trichoblastomas, TB, differential diagnosis, CD133, CD44, immunohistochemistry, receiver operating characteristic, ROC
Published: 2022

38. Longitudinal investigations of anatomical and morphological development of the gastrointestinal tract in goats from colostrum to postweaning

Author: Abdelsattar, M.M., Zhuang, Y., Cui, K., Bi, Y., Haridy, M., and Zhang, N.
Published: 2022
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39. Tumor microenvironment and its clinicopathological and prognostic associations in surgically resected cutaneous angiosarcoma

Author: Bi, Y., Ge, L., Ren, X., Pang, J., Zhao, Y., and Liang, Z.
Published: 2022
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40. Tau Pathologies Mediate the Associations of Vascular Risk Burden with Cognitive Impairments in Non-demented Elders: The CABLE Study

Author: Yu, G.-X., Ou, Y.-N., Bi, Y.-L., Ma, Y.-H., Hu, H., Wang, Z.-T., Hou, X.-H., Xu, W., Tan, Lan, and Yu, Jin-Tai
Published: 2022
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41. 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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42. 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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43. The CDEX-1 1 kg Point-Contact Germanium Detector for Low Mass Dark Matter Searches

Author: Kang, K-J, Yue, Q, Wu, Y-C, Cheng, J-P, Li, Y-J, Bai, Y, Bi, Y, Chang, J-P, Chen, N, Chen, Q-H, Chen, Y-H, Chuang, Y-C, Dend, Z, Du, Q, Gong, H, Hao, X-Q, He, Q-J, Hu, X-H, Huang, H-X, Huang, T-R, Jiang, H, Li, H-B, Li, J-M, Li, J, Li, X, Li, X-Y, Li, X-Q, Li, Y-L, Liao, H-Y, Lin, F-K, Lin, S-T, Liu, S-K, Lv, L-C, Ma, H, Mao, S-J, Qin, J-Q, Ren, J, Ruan, X-C, Shen, M-B, Singh, L, Singh, MK, Soma, AK, Su, J, Tang, C-J, Tseng, C-H, Wang, J-M, Wang, L, Wang, Q, Wong, T-KH, Wu, S-Y, Wu, W, Xing, H-Y, Xu, Y, Xue, T, Yang, L-T, Yang, S-W, Yi, N, Yu, C-X, Yu, H, Yu, X-Z, Zeng, X-H, Zeng, Z, Zhang, L, Zhang, Y-H, Zhao, M-G, Zhao, W, Zhong, S-N, Zhou, Z-Y, Zhu, J-J, Zhu, W-B, Zhu, X-Z, and Zhu, Z-H
Subjects: physics.ins-det, physics.ins-det, astro-ph.IM, hep-ex
Abstract: The CDEX Collaboration has been established for direct detection of lightdark matter particles, using ultra-low energy threshold p-type point-contactgermanium detectors, in China JinPing underground Laboratory (CJPL). The first1 kg point-contact germanium detector with a sub-keV energy threshold has beentested in a passive shielding system located in CJPL. The outputs from both thepoint-contact p+ electrode and the outside n+ electrode make it possible toscan the lower energy range of less than 1 keV and at the same time to detectthe higher energy range up to 3 MeV. The outputs from both p+ and n+ electrodemay also provide a more powerful method for signal discrimination for darkmatter experiment. Some key parameters, including energy resolution, dead time,decay times of internal X-rays, and system stability, have been tested andmeasured. The results show that the 1 kg point-contact germanium detector,together with its shielding system and electronics, can run smoothly with goodperformances. This detector system will be deployed for dark matter searchexperiments.
Published: 2017

44. On the characterization of primary iron-rich phase in a high-pressure die-cast hypoeutectic Al-Si alloy

Author: Jiao, X.Y., Liu, C.F., Guo, Z.P., Nishat, Harood, Tong, G.D., Ma, S.L., Bi, Y., Zhang, Y.F., Wiesner, Stuart, and Xiong, S.M.
Published: 2021
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45. Gender and age differences in the association between sleep characteristics and fasting glucose levels in Chinese adults

Author: Zheng, R., Niu, J., Wu, S., Wang, T., Wang, S., Xu, M., Chen, Y., Dai, M., Zhang, D., Yu, X., Tang, X., Hu, R., Ye, Z., Shi, L., Su, Q., Yan, L., Qin, G., Wan, Q., Chen, G., Gao, Z., Wang, G., Shen, F., Luo, Z., Qin, Y., Chen, L., Huo, Y., Li, Q., Zhang, Y., Liu, C., Wang, Y., Yang, T., Deng, H., Zhao, J., Mu, Y., Xu, Y., Li, M., Lu, J., Wang, W., Zhao, Z., Bi, Y., and Ning, G.
Published: 2021
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46. Increasing Age Affected Polymorphonuclear Neutrophils in Prognosis of Mycoplasma pneumoniae Pneumonia

Author: Zhao Q, Zhang T, Zhu B, Bi Y, Jiang SW, Zhu Y, Zhao D, and Liu F
Subjects: refractory mycoplasma pneumoniae pneumonia, mycoplasma pneumoniae, polymorphonuclear neutrophils, reactive oxygen species, neutrophil extracellular traps, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Qianye Zhao,1,2,&ast; Teng Zhang,2,&ast; Beibei Zhu,1 Ying Bi,3 Shi-Wen Jiang,4 Yifan Zhu,1 Deyu Zhao,1 Feng Liu1 1Department of Respiratory Medicine, Children’s Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 2Department of Pediatrics, Lianyungang Maternal and Child Health Care Hospital, Lianyungang, Jiangsu, People’s Republic of China; 3Department of Respiratory Medicine, Xuzhou children’s Hospital, Xuzhou, Jiangsu, People’s Republic of China; 4Research Institute for Reproductive Health and Genetic Diseases, Center of Reproductive Medicine, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi, Jiangsu, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Deyu Zhao; Feng LiuDepartment of Respiratory Medicine, Children’s Hospital of Nanjing Medical University, No. 72, Guangzhou Road, Gulou District, Nanjing, Jiangsu, 210008, People’s Republic of ChinaTel +86 189 5176 9559; +86 189 5176 8373Fax +86 025 83117376Email zhaodeyu988@126.com; axsliu@163.comPurpose: It is well known that age is related to the incidence of Mycoplasma pneumoniae pneumonia (MPP), and how age and other factors contribute to MPP remains unclear. In this study, we investigate how age affects the prognosis of MPP.Patients and Methods: A total number of 1875 hospitalized children with pneumonia were enrolled in this study, including 52 children with refractory M. pneumoniae pneumonia (RMPP) and 298 children with non-RMPP. We used multiple logistic regression analysis to further identify the risk factors of RMPP, and found that age and polymorphonuclear neutrophils (PMNs) count were the key independent risk factors for the occurrence of RMPP. In order to improve specificity, 4.5 years old was taken as the cut-off value. Then, according to the cut-off value of age, 76 participants were recruited and divided into four groups: < 4.5y MPP group, ≥ 4.5y MPP group, < 4.5y health control (< 4.5yHC) and ≥ 4.5y HC group. We explored the diverse functions of primary PMNs from children of different ages with MPP at cellular level. Besides, we studied the relationship between lung injury and PMNs in mice model with MPP of different ages.Results: We found that the age and PMNs count of RMPP group were significantly higher than those of the non-RMPP group. Importantly, there is a linear correlation between the age of patients with RMPP and the percentage of PMNs. Further analysis showed that elderly patients infected with M. pneumoniae had more active PMNs function. Meanwhile, proteomics showed that children with M. pneumoniae infection in different age groups have differences in PMNs apoptosis, nicotinamide adenine dinucleotide phosphate, mitochondrial function and oxidative stress. Finally, we found that age is also involved in the pathogenesis of mouse model with MPP.Conclusion: We speculate that age may contribute to the development of RMPP.Keywords: refractory Mycoplasma pneumoniae pneumonia, Mycoplasma pneumoniae, polymorphonuclear neutrophils, reactive oxygen species, neutrophil extracellular traps
Published: 2021

47. Connecting Peripheral to Central Neuropathy: Examination of Nerve Conduction Combined with Olfactory Tests in Patients with Type 2 Diabetes

Author: Ni W, Zhang Z, Zhang B, Zhang W, Cheng H, Miao Y, Chen W, Liu J, Zhu D, and Bi Y
Subjects: type 2 diabetes mellitus, peripheral neuropathy, cognitive dysfunction, olfactory behavior, odor-induced brain activation, Specialties of internal medicine, RC581-951
Abstract: Wenyu Ni,1,&ast; Zhou Zhang,1,&ast; Bing Zhang,2 Wen Zhang,2 Haiyan Cheng,1 Yingwen Miao,1 Wei Chen,1 Jiani Liu,2 Dalong Zhu,1 Yan Bi1 1Department of Endocrinology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China; 2Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yan BiDepartment of Endocrinology, Drum Tower Hospital, Affiliated to Nanjing University Medical School, No. 321, Zhongshan Road, Nanjing, 210008, People’s Republic of ChinaTel +86 25-83304616-61431Fax +86 25-83304616-61431Email biyan@nju.edu.cnAim: Few studies have investigated the associations between diabetic peripheral neuropathy (DPN) and cognitive decline. Olfactory impairment is related to neurodegenerative diseases and type 2 diabetes mellitus (T2DM); however, the cognitive alterations of patients with DPN and the role of olfactory function in DPN are not known. We explored alterations in cognition with DPN and the associations of neuropathy parameters with cognition and olfaction.Methods: Healthy controls (HCs) and patients with T2DM underwent nerve-conduction tests, detailed cognitive assessment, olfactory-behavior tests, and odor-induced functional magnetic resonance imaging (fMRI). T2DM patients were divided into two groups (non-DPN [NDPN] and DPN). Olfactory brain regions showing different activation between the two groups were selected for functional connectivity (FC) analyses. A structural equation model (SEM) was also generated to demonstrate the association among cognition, olfactory, and neuropathy parameters.Results: One hundred individuals (36 HCs, 36 NDPN, and 28 DPN) were matched for age, sex, and educational level. Compared with the NDPN group, the DPN group had significantly lower scores for memory and processing speed, as well as lower olfactory identification and memory scores, decreased activation of the left frontal lobe, and reduced seed-based functional connectivity in the right insula. The nerve conduction velocity in patients with T2DM was associated with cognitive functions. The association between nerve conduction and executive function was mediated by olfactory behavior.Conclusion: Patients with DPN had worse cognition than the NDPN patients in the domains of memory and processing speed. Cognitive dysfunction could be predicted by olfactory-behavior tests and electrophysiological examination.Keywords: type 2 diabetes mellitus, peripheral neuropathy, cognitive dysfunction, olfactory behavior, odor-induced brain activation
Published: 2021

48. 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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49. The characterization of Fe-rich phases in a high-pressure die cast hypoeutectic aluminum-silicon alloy

Author: Jiao, X.Y., Liu, C.F., Guo, Z.P., Tong, G.D., Ma, S.L., Bi, Y., Zhang, Y.F., and Xiong, S.M.
Published: 2020
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50. SDAGS: SMOTE+FOREST DIFFUSION-BASED DATA AUGMENTATION AND GBT-BASED STACKING ENSEMBLE LEARNING FOR HOLISTIC AI-POWERED DIABETES MELLITUS PREDICTION

Author: Nguyen, An K., primary, Gong, Bi Y., additional, Trinh, Binh T., additional, Le Hong, Thu, additional, Nguyen Tue, Minh, additional, and Du Phuong, Hanh, additional
Published: 2024
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