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13,837 results on '"Gao, C."'

1. 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

2. 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 locations 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

3. Potential Chromospheric Evaporation in A M-dwarf's Flare Triggered by Einstein Probe Mission

Author: Wang, J., Mao, X., Gao, C., Liu, H. Y., Li, H. L., Pan, H. W., Wu, C., Liu, Y., Li, G. W., Xin, L. P., Jin, S., Xu, D. W., Liang, E. W., Yuan, W. M., and Wei, J. Y.
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: Although flares from late-type main-sequence stars have been frequently detected in multi-wavelength, the associated dynamical process has been rarely reported so far. Here, we report follow-up observations of an X-ray transient triggered by WXT onboard the Einstein Probe at UT08:45:08 in 2024, May 7. The photometry in multi-bands and time-resolved spectroscopy started at 3 and 7.5 hours after the trigger, respectively, which enables us to identify the transient as a flare of the M-dwarf 2MASS J12184187-0609123. The bolometric energy released in the flare is estimated to be $\sim10^{36}\ \mathrm{erg}$ from its X-ray light curve. The H$\alpha$ emission-line profile obtained at about 7 hours after the trigger shows an evident blue asymmetry with a maximum velocity of $200-250\ \mathrm{km\ s^{-1}}$. The blue wing can be likely explained by the chromospheric temperature (cool) upflow associated with chromospheric evaporation, in which the mass of the evaporating plasma is estimated to be $1.2\times10^{18}$g. In addition, a prominence eruption with an estimated mass of $7\times10^{15}\mathrm{g}
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. Development of 500kV Modular Cascaded Hybrid HVdC Breaker for dC grid Applications

Author: Tang, G., Zhou, W., HE, Z., Wei, X., and Gao, C.
Published: 2022

6. Age of massive galaxies at redshift 8

Author: Lopez-Corredoira, M., Melia, F., Wei, J. -J., and Gao, C. -Y.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Recent James Webb Space Telescope (JWST) data analyses have shown that massive red galaxies existed at redshifts $z>6$, a discovery that is difficult to understand in the context of standard cosmology ($\Lambda $CDM). Here we analyze these observations more deeply by fitting a stellar population model to the optical and near-infrared photometric data. These fits include a main stellar population in addition to a residual younger population and with the same extinction for both (a lower extinction for the younger population is unphysical). Extra stellar populations or the inclusion of an AGN component do not significantly improve the fits. These galaxies are being viewed at very high redshifts, with an average $\langle z\rangle \approx 8.2$, when the $\Lambda$CDM Universe was only $\approx 600$ Myr old. This result conflicts with the inferred ages of these galaxies, however, which were on average between 0.9 and 2.4 Gyr old within 95% CL. Given the sequence of star formation and galaxy assembly in the standard model, these galaxies should instead be even younger than 290 Myr on average, for which our analysis assigns a probability of only $<3\times 10^{-4}$ ($\gtrsim 3.6\sigma $ tension). This outcome may indicate the need to consider non-standard cosmologies. Nevertheless, our conclusions result from several approximations in stellar astrophysics and extinction, so they should be taken with a grain of salt. Further research is necessary to corroborate the possible existence of galaxies older than the $\Lambda $CDM universe at their observed redshifts., Comment: 16 pages, 8 figures, accepted to be published in ApJ
Published: 2024

7. 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

8. Instability of Circumnuclear Gas Supply as An Origin of 'Changing-look' Phenomenon of Supermassive Blackholes

Author: Wang, J., Xu, D. W., Cao, Xinwu, Gao, C., Xie, C. H., and Wei, J. Y.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The origin of the "Changing-look" (CL) phenomenon in supermassive black holes (SMBHs) remains an open issue. This study aims to shed light on this phenomenon by focusing on a sample that encompasses all known repeating CL active galactic nuclei (AGNs). Through the identification of a characteristic time scale for the CL phenomenon, it was observed that larger SMBHs possess shorter characteristic timescales, while smaller SMBHs exhibit longer timescales. These findings reveal a significant contrast to the traditional AGN variability that has been adequately explained by the AGN's disk instability model. This stark discrepancy highlights a distinct origin of the CL phenomenon, distinguishing it from traditional AGN variability. By properly predicting the characteristic time scale and its dependence on SMBH mass, we propose that the CL phenomenon is likely a result of a variation in accretion rate caused by a sudden change in the supply of circumnuclear gas during the transition between active and passive SMBH fueling stages., Comment: 14 pages, 4 figures and 2 tables, accepted by ApJ
Published: 2024

9. 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

10. 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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11. 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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12. Vulnerable to heat stress: gaps in international standard metric thresholds

Author: Brimicombe, C., Gao, C., and Otto, I. M.
Published: 2024
Full Text: View/download PDF

13. 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

14. 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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15. Association of Stress Hyperglycemia Ratio and in-Hospital Mortality in Patients with Sepsis: A Two Center Retrospective Cohort Study

Author: Ma C, Jiang W, Li J, Sun W, Zhang J, Xu P, Guo Y, Ning N, Zhao B, Mao E, and Gao C
Subjects: sepsis, stress hyperglycemia ratio, mortality, hyperglycemia, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Chaoping Ma,1,&ast; Weisong Jiang,2,&ast; Juan Li,1,&ast; Wenwu Sun,2,&ast; Jiyuan Zhang,1 Peixian Xu,1 Yiran Guo,1 Ning Ning,2 Jiaoyan Li,2 Bing Zhao,2 Enqiang Mao,2 Chengjin Gao1 1Departments of Emergency, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, People’s Republic of China; 2Departments of Emergency, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Chengjin Gao; Enqiang Mao, Email gaochengjin@xinhuamed.com.cn; maoeq@yeah.netIntroduction: In critically ill patients, the stress hyperglycemia ratio (SHR) was significantly associated with mortality. However, the relationship between SHR and mortality in septic patients is still unclear.In this study, patients with sepsis from two Chinese academic centers were identified and divided into quartiles based on SHR levels.Methods: Multivariable regression analysis will be used to determine associations between SHR and clinical outcomes in sepsis patients.The Kaplan-Meier curve was used to predict mortality in various groups of septic patients.Results: A total of 1835 septic patients were included in the study.The in-hospital, 30-day, and 60-day mortality rates for all septic patients were 22.8%, 18.7%, and 21.7%, respectively. Increased SHR was significantly associated with hospital mortality in multivariate regression analysis.These results were further confirmed in the adjusted analysis, where the hospital mortality and the 60-day mortality of the highest SHR quartile were significantly increased compared to the lowest SHR quartile. However, the highest SHR quartile was not associated with 30-day mortality.In addition, the risk of in-hospital mortality, 30-day mortality and 60-day mortality showed a consistent upward trend with increasing SHR quartile. The survival curve showed that the worst prognosis was in the fourth SHR quartile.Discussion: In conclusion, SHR was significantly associated with hospital mortality in patients with sepsis. This finding indicates that the SHR may be useful in identifying septic patients at higher risk of hospital mortality.Keywords: sepsis, stress hyperglycemia ratio, mortality, Hyperglycemia
Published: 2024

16. Bio-Inspired Nanodelivery Platform: Platelet Membrane-Cloaked Genistein Nanosystem for Targeted Lung Cancer Therapy

Author: Gao R, Lin P, Yang W, Fang Z, Gao C, Cheng B, Fang J, and Yu W
Subjects: bionic technology, platelet membrane, genistein, liposomes, lung cancer, targeted therapy, Medicine (General), R5-920
Abstract: Rui Gao,1,&ast; Peihong Lin,1,&ast; Wenjing Yang,1,&ast; Zhengyu Fang,1 Chunxiao Gao,1 Bin Cheng,2 Jie Fang,3 Wenying Yu1 1School of Pharmacy, Hangzhou Medical College, Hangzhou, 310013, People’s Republic of China; 2Department of Traditional Chinese Medicine, Zhejiang Pharmaceutical University, Ningbo, 315500, People’s Republic of China; 3Zhejiang Provincial Laboratory of Experimental Animal’s & Nonclinical Laboratory Studies, Hangzhou Medical College, Hangzhou, 310013, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Bin Cheng; Wenying Yu, Email 44418972@qq.com; zjyuwenying@163.comBackground: Genistein (Gen), a natural polyphenolic compound, has emerged as a promising candidate for lung cancer treatment. However, the potential clinical application of Gen is limited due to its poor solubility, low bioavailability, and toxic side effects. To address these challenges, a biomimetic delivery platform with cell membranes derived from natural cells as carrier material was constructed. This innovative approach aims to facilitate targeted drug delivery and solve the problem of biocompatibility of synthetic materials.Methods: First, the liposomes (LPs) loaded with Gen (LPs@Gen) was prepared using the ethanol injection method. Subsequently, PLTM-LPs@Gen was obtained through co-extrusion after mixing platelet membrane (PLTM) and LPs@Gen. Additionally, the biological and physicochemical properties of PLTM-LPs@Gen were investigated. Finally, the targeting ability, therapeutic efficacy, and safety of PLTM-LPs@Gen for lung cancer were evaluated using both a cell model and a tumor-bearing nude mouse model.Results: The optimal preparation ratio for LPs@Gen was Gen: soybean lecithin: cholesterol: DSPE-PEG2000 (3:30:5:10, mass ratio), while the ideal fusion ratio of LPs@Gen and PLTM was 1:1. The particle size of PLTM-LPs@Gen was 108.33 ± 1.06 nm, and the encapsulation efficiency and drug loading were 94.29% and 3.09% respectively. Gen was released continuously and slowly from PLTM-LPs@Gen. Moreover, PLTM-LPs@Gen exhibited good stability within one week. The results of in vitro cellular uptake and in vivo distribution experiments indicated that the carrier material, PLTM-LPs, has the immune escape ability and tumor targeting ability. Consequently, it showed better therapeutic effects than free drugs and traditional LPs in vitro and in vivo tumor models. In addition, safety experiments demonstrated that PLTM-LPs@Gen possesses good biocompatibility.Conclusion: Biomimetic nanomedicine provides a new strategy for the precision treatment of lung cancer in clinical practice.Keywords: bionic technology, platelet membrane, genistein, liposomes, lung cancer, targeted therapy
Published: 2024

17. Are 'Changing-Look' Active Galactic Nuclei Special in the Coevolution of Supermassive Black Holes and their Hosts? I

Author: Wang, J., Zheng, W. K., Brink, T. G., Xu, D. W., Filippenko, A. V., Gao, C., Xie, C. H., and Wei, J. Y.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The nature of the so-called ``changing-look'' (CL) active galactic nucleus (AGN), which is characterized by spectral-type transitions within $\sim10$~yr, remains an open question. As the first in our series of studies, we here attempt to understand the CL phenomenon from a view of the coevolution of AGNs and their host galaxies (i.e., if CL-AGNs are at a specific evolutionary stage) by focusing on the SDSS local ``partially obscured'' AGNs in which the stellar population of the host galaxy can be easily measured in the integrated spectra. A spectroscopic follow-up program using the Xinglong 2.16~m, Lick/Shane 3~m, and Keck 10~m telescopes enables us to identify in total 9 CL-AGNs from a sample of 59 candidates selected by their mid-infrared variability. Detailed analysis of these spectra shows that the host galaxies of the CL-AGNs are biased against young stellar populations and tend to be dominated by intermediate-age stellar populations. This motivates us to propose that CL-AGNs are probably particular AGNs at a specific evolutionary stage, such as a transition stage from ``feast'' to ``famine'' fueling of the supermassive black hole. In addition, we reinforce the previous claim that CL-AGNs tend to be biased against both a high Eddington ratio and a high bolometric luminosity, suggesting that the disk-wind broad-line-region model is a plausible explanation of the CL phenomenon., Comment: Replaced by updated Acknowledgments. arXiv admin note: substantial text overlap with arXiv:2210.03928
Published: 2023

18. On central focusing for contrast optimization in direct electron ptychography of thick samples

Author: Gao, C., Hofer, C., and Pennycook, T. J.
Subjects: Physics - Applied Physics, Physics - Optics
Abstract: Ptychography provides high dose efficiency images that can reveal light elements next to heavy atoms. However, despite ptychography having an otherwise single signed contrast transfer function, contrast reversals can occur when the projected potential becomes strong for both direct and iterative inversion ptychography methods. It has recently been shown that these reversals can often be counteracted in direct ptychography methods by adapting the focus. Here we provide an explanation of why the best contrast is often found with the probe focused to the middle of the sample. The phase contribution due to defocus at each sample slice above and below the central plane in this configuration effectively cancels out, which can prevent contrast reversals when dynamical scattering effects are not overly strong. In addition we show that the convergence angle can be an important consideration for removal of contrast reversals in relatively thin samples.
Published: 2023

19. 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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20. 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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21. NvDEx-100 Conceptual Design Report

Author: Cao, X., Chang, Y., Chen, K., Ciuffoli, E., Duan, L., Fang, D., Gao, C., Ghorui, S. K., Hu, P., Hu, Q., Huang, S., Huang, Z., Lang, L., Li, Y., Li, Z., Liang, T., Liu, J., Lu, C., Mai, F., Mei, Y., Qiu, H., Sun, X., Tang, X., Wang, H., Wang, Q., Xiao, L., Xiao, M., Xin, J., Xu, N., Yang, P., Yang, Y., Yang, Z., Yu, Z., Zhang, D., Zhang, J., Zhao, C., and Zhu, D.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: Observing nuclear neutrinoless double beta (0vbb) decay would be a revolutionary result in particle physics. Observing such a decay would prove that the neutrinos are their own antiparticles, help to study the absolute mass of neutrinos, explore the origin of their mass, and may explain the matter-antimatter asymmetry in our universe by lepton number violation. We propose developing a time projection chamber (TPC) using high-pressure 82SeF6 gas and top-metal silicon sensors for read-out in the China Jinping Underground Laboratory (CJPL) to search for neutrinoless double beta decay of 82Se, called the NvDEx experiment. Besides being located at CJPL with the world's thickest rock shielding, NvDEx combines the advantages of the high Qbb (2.996 MeV) of 82Se and the TPC's ability to distinguish signal and background events using their different topological characteristics. This makes NvDEx unique, with great potential for low-background and high-sensitivity 0vbb searches. NvDEx-100, a NvDEx experiment phase with 100 kg of SeF6 gas, is being built, with plans to complete installation at CJPL by 2025. This report introduces 0vbb physics, the NvDEx concept and its advantages, and the schematic design of NvDEx-100, its subsystems, and background and sensitivity estimation.
Published: 2023
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22. Sepsis-Induced Coagulopathy Score is Associated with an Increased Risk of New-Onset Atrial Fibrillation in Septic Patients: A Two-Centered Retrospective Study

Author: Li J, Wang S, Ma C, Ning N, Huang Y, Jiao M, Zhang J, Sun W, Zhao B, Mao E, Che Z, and Gao C
Subjects: sepsis, sepsis-induced coagulopathy, new-onset atrial fibrillation, association, mortality, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Juan Li,1,&ast; Shu Wang,2,&ast; Chaoping Ma,1,&ast; Ning Ning,3,&ast; Yingying Huang,1,4,&ast; Min Jiao,1 Jiyuan Zhang,1 Wenwu Sun,3 Jiaoyan Li,3 Bing Zhao,3 Enqiang Mao,3 Zaiqian Che,3 Chengjin Gao1 1Department of Emergency, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China; 2Department of Intensive Care Medicine, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing, 400016, People’s Republic of China; 3Departments of Emergency, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, People’s Republic of China; 4Dementia Research Center, Macquarie University, Sydney, Australia&ast;These authors contributed equally to this workCorrespondence: Chengjin Gao, Department of Emergency, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, People’s Republic of China, Email gaochengjin@xinhuamed.com.cn Zaiqian Che, Departments of Emergency, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China, Email chezaiqian@163.comPurpose: New-onset atrial fibrillation (NOAF) and sepsis-induced coagulopathy (SIC) are severe complications in septic patients. However, the relationship between NOAF and SIC score has not been clearly defined. This study aims to investigate the association between SIC score and NOAF, as well as their effect on mortality in sepsis.Patients and Methods: This study was a two-center retrospective analysis. Medical data were collected from patients diagnosed with sepsis. The patients were divided into NOAF and non-NOAF groups, and the SIC score was calculated for each group. Univariable and multivariable logistic regression analyses were performed to explore the relationship between the SIC score and NOAF, as well as their effects on mortality. The Kaplan-Meier curve was used to assess the survival rate.Results: A total of 2,280 septic patients were included, with 132 (5.7%) suffering from NOAF. Multivariable logistic regression analyses indicated that age, gender, the Acute Physiology and Chronic Health Evaluation II score (APACHE II), heart rate, renal failure, stroke, chronic obstructive pulmonary disease (COPD), and the SIC score were independent risk factors for NOAF in sepsis. Moreover, NOAF was associated with an increased risk of in-hospital mortality, 28-day mortality, and 90-day mortality. These results were consistent across subgroup analyses.Conclusion: The SIC score was an independent risk factor for NOAF in septic patients, and NOAF was an independent risk factor for predicting mortality.Keywords: sepsis, sepsis-induced coagulopathy, new-onset atrial fibrillation, association, mortality
Published: 2024

23. Saikosaponins Targeting Programmed Cell Death as Anticancer Agents: Mechanisms and Future Perspectives

Author: Xiao X and Gao C
Subjects: apoptosis, autophagy, ferroptosis, pyroptosis, Therapeutics. Pharmacology, RM1-950
Abstract: Xiao Xiao, Chunfang Gao Department of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, People’s Republic of ChinaCorrespondence: Chunfang Gao, Department of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, People’s Republic of China, Tel +86-21-65161782-1210, Email gaocf1115@163.com; gaocf1115@shutcm.edu.cnAbstract: Saikosaponins (SS), which are major bioactive compounds in Radix Bupleuri, have long been used clinically for multicomponent, multitarget, and multipathway therapeutic strategies. Programmed cell death (PCD) induction is among the multiple mechanisms of SS and mediates the anticancer efficacy of this drug family. Although SS show promise for anticancer therapy, the available data to explain how SS mediate their key anticancer effects through PCD (apoptosis, autophagy, ferroptosis, and pyroptosis) remain limited and piecemeal. This review offers an extensive analysis of the key pathways and mechanisms involved in PCD and explores the importance of SS in cancer. We believe that high-quality clinical trials and a deeper understanding of the pharmacological targets involved in the signalling cascades that govern tumour initiation and progression are needed to facilitate the development of innovative SS-based treatments. Elucidating the specific anticancer pathways activated by SS and further clarifying how comprehensive therapies lead to cross-link among the different types of cell death will inspire the clinical translation of SS as cancer treatments. Keywords: apoptosis, autophagy, ferroptosis, pyroptosis
Published: 2024

24. Low-Carbohydrate Diet is More Helpful for Weight Loss Than Low-Fat Diet in Adolescents with Overweight and Obesity: A Systematic Review and Meta-Analysis

Author: Zhang Y, He T, Hu Y, and Gao C
Subjects: obesity, diet, weight loss, low-carbohydrate, low-fat, Specialties of internal medicine, RC581-951
Abstract: Yu Zhang,1– 4 Tingting He,1– 4 Yu Hu,1– 4 Chenlin Gao2– 5 1Graduate School, Southwest Medical University, Luzhou, Sichuan, People’s Republic of China; 2Cardiovascular and Metabolic Diseases Key Laboratory of Luzhou, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, People’s Republic of China; 3Sichuan Clinical Research Center for Nephropathy, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, People’s Republic of China; 4Metabolic Vascular Disease Key Laboratory of Sichuan Province, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, People’s Republic of China; 5Department of Endocrinology and Metabolism, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, People’s Republic of ChinaCorrespondence: Chenlin Gao, Department of Endocrinology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, People’s Republic of China, Tel +86-830-3165361, Email gaochenlin00@swmu.edu.cnPurpose: This manuscript performed a meta-analysis to compare the effects of a low-fat diet (LFD) and a low-carbohydrate diet (LCD) on body weight and lipid levels in adolescents with overweight and obesity.Patients and Methods: PubMed and other databases were searched for the full-text literature comparing LFD and LCD up to November 2023 using a subject plus free word strategy, with search terms such as “low-fat diet”, “low-carbohydrate diet”, “obesity”, “weight”, “adolescents”, “RCT”, and so on. Two independent reviewers selected promising candidate trials, collected the data, and assessed the quality of the trials. RevMan 5.3 software was utilized to conduct a meta-analysis of the randomized controlled trials (RCTs) that were included.Results: 5 RCTs with 192 participants were included in this meta-analysis. Weight (mean difference − 2.81; 95% CI − 5.38 to − 0.25), Body Mass Index (BMI) (− 1.13; 95% CI − 2.14 to − 0.11) and Triglyceride (TG) (− 0.36; 95% CI − 0.46 to − 0.27) of the LCD were significantly lower than that of the LFD. At the same time, the high-density lipoprotein cholesterol (HDL) levels of the LCD were significantly higher than those of the LFD (0.08; 95% CI 0.04 to 0.12) (P < 0.05). However, there was no significant difference in the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), percent body fat, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL) between the two groups (P> 0.05).Conclusion: According to this study, LCD is more helpful in improving weight loss, HDL and TG. Thus, LCD may serve as an effective intervention for weight management in adolescents with overweight and obesity, although further research is needed to determine its long-term effects.Keywords: obesity, diet, weight loss, low-carbohydrate, low-fat
Published: 2024

25. Adeno-Associated Virus Engineering and Load Strategy for Tropism Modification, Immune Evasion and Enhanced Transgene Expression

Author: Zhou X, Liu J, Xiao S, Liang X, Li Y, Mo F, Xin X, Yang Y, and Gao C
Subjects: aav engineering, capsid modification, surface tethering, virus load, rational design, directed evolution, machine learning, Medicine (General), R5-920
Abstract: Xun Zhou,1,2,&ast; Jingzhou Liu,2,&ast; Shuang Xiao,2,3,&ast; Xiaoqing Liang,1,2 Yi Li,2 Fengzhen Mo,3 Xin Xin,2 Yang Yang,2 Chunsheng Gao1,2 1School of Pharmacy, Henan University, Kaifeng, People’s Republic of China; 2State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing, People’s Republic of China; 3School of Pharmacy, Guangxi Medical University, Nanning, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Fengzhen Mo; Xin Xin, Email mofzhen@163.com; 13511014091@163.comAbstract: Gene therapy aims to add, replace or turn off genes to help treat disease. To date, the US Food and Drug Administration (FDA) has approved 14 gene therapy products. With the increasing interest in gene therapy, feasible gene delivery vectors are necessary for inserting new genes into cells. There are different kinds of gene delivery vectors including viral vectors like lentivirus, adenovirus, retrovirus, adeno-associated virus et al, and non-viral vectors like naked DNA, lipid vectors, polymer nanoparticles, exosomes et al, with viruses being the most commonly used. Among them, the most concerned vector is adeno-associated virus (AAV) because of its safety, natural ability to efficiently deliver gene into cells and sustained transgene expression in multiple tissues. In addition, the AAV genome can be engineered to generate recombinant AAV (rAAV) containing transgene sequences of interest and has been proven to be a safe gene vector. Recently, rAAV vectors have been approved for the treatment of various rare diseases. Despite these approvals, some major limitations of rAAV remain, namely nonspecific tissue targeting and host immune response. Additional problems include neutralizing antibodies that block transgene delivery, a finite transgene packaging capacity, high viral titer used for per dose and high cost. To deal with these challenges, several techniques have been developed. Based on differences in engineering methods, this review proposes three strategies: gene engineering-based capsid modification (capsid modification), capsid surface tethering through chemical conjugation (surface tethering), and other formulations loaded with AAV (virus load). In addition, the major advantages and limitations encountered in rAAV engineering strategies are summarized.Keywords: AAV engineering, capsid modification, surface tethering, virus load, rational design, directed evolution, machine learning
Published: 2024

26. Longitudinal Relationship Between Psychological Capital and Anxiety in College Students: The Mediating Effect of Emotion Reregulation Strategy and Moderating Effect of Parent-Child Relationship

Author: Liu Z, Bao T, Yang Z, Ruan Y, Gao C, and Wu J
Subjects: psychological capital, emotion regulation strategies, anxiety, parent-child relationship, Psychology, BF1-990, Industrial psychology, HF5548.7-5548.85
Abstract: Zijun Liu,1,&ast; Tianhao Bao,2 Zhilan Yang,2,&ast; Ye Ruan,2 Changqing Gao,2 Jie Wu2 1The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, People’s Republic of China; 2Affiliated Mental Health Center of Kunming Medical University, Kunming, Yunnan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jie Wu, Affiliated Mental Health Center of Kunming Medical University, Kunming, Yunnan, 650224, People’s Republic of China, Email wujie@kmmu.edu.cn Tianhao Bao, Affiliated Mental Health Center of Kunming Medical University, Kunming, Yunnan, 650224, People’s Republic of China, Email Doctor@kmmu.edu.cnObjective: Based on Conservation of resources theory, process model of emotion regulation and attachment theory, the present study examined how psychological capital affects anxiety through the mediation of emotion regulation strategies and explored the moderating role of parent-child relationship.Methods: Using a longitudinal study method, 962 college students were surveyed twice at one-year intervals.Results: (1) College students’ emotion regulation strategies (including cognitive reappraisal and expressive suppression) partially mediated psychological capital and anxiety mood; (2) parent-child relationship moderated the pathways of psychological capital and expressive suppression on anxiety, respectively.Conclusion: College students with higher levels of parent-child relationship had stronger predictive effects of psychological capital and weaker predictive effects of expressive suppression on anxiety mood. The research findings clarify the combined effects of emotion regulation and parent-child relationships on anxiety among college students, providing valuable reference for the design and implementation of interventions to promote individual psychological well-being.Keywords: psychological capital, emotion regulation strategies, anxiety, parent-child relationship
Published: 2024

27. Effects of Ultrasound-Guided Thoracic Paravertebral Nerve Block Combined with Perineural or IV Dexmedetomidine on Acute and Chronic Pain After Thoracoscopic Resection of Lung Lesions: A Double-Blind Randomized Trial

Author: Chen Z, Gao C, Zhang Y, Gao Y, Zhang L, Zhao S, Zhang H, Zhao X, and Jin Y
Subjects: dexmedetomidine, thoracic paravertebral nerve block, neuropathic pain, thoracoscopic surgery, Therapeutics. Pharmacology, RM1-950
Abstract: Zheping Chen,1,&ast; Changli Gao,1,2,&ast; Yingchao Zhang,1,3 Yongxu Gao,1,4 Le Zhang,1 Shanshan Zhao,1 He Zhang,1 Xin Zhao,1 Yanwu Jin1 1Department of Anesthesiology, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, People’s Republic of China; 2Department of Anesthesiology, Laoling People Hospital, Laoling, People’s Republic of China; 3Department of Anesthesiology, Shouguang People Hospital, Weifang, People’s Republic of China; 4Department of Anesthesiology, Jinan Third People’s Hospital, Laoling, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yanwu Jin, Department of Anesthesiology, the Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Bei Yuan Street, Jinan, 250033, People’s Republic of China, Tel +86-17660085535, Email jinyanwu_aa@163.comBackground: Thoracic paravertebral block (TPVB) analgesia can be prolonged by local anesthetic adjuvants such as dexmedetomidine. This study aimed to evaluate the two administration routes of dexmedetomidine on acute pain and chronic neuropathic pain (NeuP) prevention compared with no dexmedetomidine.Methods: A total of 216 patients were randomized to receive TPVB using 0.4% ropivacaine alone (R Group), with perineural dexmedetomidine 0.5 μg·kg− 1 (RD0.5 Group) or 1.0 μg·kg− 1 (RD1.0 Group), or intravenous (IV) dexmedetomidine 0.5 μg·kg− 1·h− 1 (RDiv Group). The primary outcome was the incidence of chronic NeuP, defined as a Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) pain score > 12 points at 3-month after surgery.Results: (1) For the primary outcome, RD0.5 Group and RD1.0 Group demonstrated a decreased incidence of chronic NeuP at 3-month after surgery; (2) Compared with R Group, RDiv Group, RD0.5 Group, and RD1.0 Group can reduce VAS scores at rest and movement and Prince-Henry Pain scores at 12 and 24-h after surgery, the consumption of oral morphine equivalent (OME) and improve QOD-15 at POD1; (3) Compared with RDiv Group, RD0.5 Group and RD1.0 Group can reduce VAS scores at rest and movement and Prince-Henry Pain scores at 12 and 24-h after surgery, the consumption of postoperative OME and improve QOD-15 at POD1; (4) Compared with RD0.5 Group, RD1.0 Group effectively reduced VAS scores at rest at 12 and 24-h after surgery, VAS scores in movement and Prince-Henry Pain scores at 12-h after surgery. However, RD1.0 Group showed an increased incidence of drowsiness.Conclusion: Perineural or IV dexmedetomidine are similarly effective in reducing acute pain, but only perineural dexmedetomidine reduced chronic NeuP. Moreover, considering postoperative complications such as drowsiness, perineural dexmedetomidine (0.5 μg·kg− 1) may be a more appropriate choice.Clinical Trial Registration: Chinese Clinical Trial Registry (ChiCTR2200058982).Keywords: dexmedetomidine, thoracic paravertebral nerve block, neuropathic pain, thoracoscopic surgery
Published: 2024

28. Accretion and Host-Galaxy Properties of 14 New 'Changing-Look' Active Galactic Nuclei Identified from the SDSS-V Survey

Author: Wang, J., Xu, D. W., Bai, J. Y., Brink, T. G., Gao, C., Zheng, W. K., and Filippenko, A. V.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The widely accepted active galactic nucleus (AGN) paradigm has been recently challenged by the discovery of the so-called ``changing-look'' (CL) phenomenon characterized by spectral-type transitions. By comparing the SDSS-V and SDSS DR16 spectroscopic datasets, here we report the identification of 14 new CL-AGNs (redshift $z<0.5$) exhibiting spectral-type changes on a timescale of $\sim 10$yr. Follow-up spectroscopy was conducted with the Lick Shane 3m and Keck 10m telescopes for three of the objects. Detailed analysis of these spectra enables us to arrive at the following two main results. (1) By compiling a sample of 65 CL-AGNs with good measurements, we reinforce the previous claim that CL-AGNs tend to be biased against both a high Eddington ratio ($\lesssim 0.1$) and a high bolometric luminosity ($\lesssim 10^{46}\,\mathrm{erg\,s^{-1}}$). This bias suggests that the disk-wind broad-line-region model is a plausible explanation of the CL phenomenon. (2) The host galaxies of CL-AGNs tend to be dominated by intermediate stellar populations, which motivates us to propose that CL-AGNs are probably particular AGNs at a special evolutionary stage, such as a transition stage from ``feast'' to ``famine'' fueling of the supermassive black hole. In addition, with our spectra, we identify SDSS J025951.22+003744.2 as a new repeat CL narrow-line Seyfert 1 galaxy with a rapid ``turn-on'' timescale of $\sim 1$yr., Comment: arXiv admin comment: This version has been removed by arXiv administrators as the submitter did not have the rights to agree to the license at the time of submission
Published: 2022

29. Genome-Wide Identification and Characterization of the Hsp70/110 Genes in Two Polychaetes, Capitella teleta and Owenia fusiformis

Author: Gao, J., Jiang, X., Liu, L., Shi, Y., Sun, C., Gao, C., Sui, F., Wang, W., and Song, X.
Published: 2023
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30. Influence of Sol-gel Derived Al2O3 Film on the Oxidation Behavior of Ni

Author: Zhang, X. J., Li, Q., Zhao, S. Y., Gao, C. X., Wang, S. J., and Sun, L.
Subjects: Technology, Chemical technology, TP1-1185, Chemicals: Manufacture, use, etc., TP200-248
Published: 2007
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31. Association Between Artificial Intelligence Based Chest Computed Tomography and Clinical/Laboratory Characteristics with Severity and Mortality in COVID-19 Hospitalized Patients

Author: Ye J, Huang Y, Chu C, Li J, Liu G, Li W, and Gao C
Subjects: covid-19, chest ct, artificial intelligence, mortality, severity, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Jiawei Ye,1,&ast; Yingying Huang,2,&ast; Caiting Chu,3 Juan Li,1 Guoxiang Liu,1 Wenjie Li,1 Chengjin Gao1 1Department of Emergency Medicine, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People’s Republic of China; 2Dementia Research Centre, Faculty of Medicine, Health and Human Sciences, Macquarie University Sydney, Australia; 3Department of Radiology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Chengjin Gao; Wenjie Li, Email gaochengjin@xinhuamed.com.cn; kingnever@hotmail.comBackground: Some patients with COVID-19 rapidly develop respiratory failure or mortality, underscoring the necessity for early identification of those prone to severe illness. Numerous studies focus on clinical and lab traits, but only few attend to chest computed tomography. The current study seeks to numerically quantify pulmonary lesions using early-phase CT scans calculated through artificial intelligence algorithms in conjunction with clinical and laboratory helps clinicians to early identify the development of severe illness and death in a group of COVID-19 patients.Methods: From December 15, 2022, to January 30, 2023, 191 confirmed COVID-19 patients admitted to Xinhua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine were consecutively enrolled. All patients underwent chest CT scans and serum tests within 48 hours prior to admission. Variables significantly linked to critical illness or mortality in univariate analysis were subjected to multivariate logistic regression models post collinearity assessment. Adjusted odds ratio, 95% confidence intervals, sensitivity, specificity, Youden index, receiver-operator-characteristics (ROC) curves, and area under the curve (AUC) were computed for predicting severity and in-hospital mortality.Results: Multivariate logistic analysis revealed that myoglobin (OR = 1.003, 95% CI 1.001– 1.005), APACHE II score (OR = 1.387, 95% CI 1.216– 1.583), and the infected CT region percentage (OR = 113.897, 95% CI 4.939– 2626.496) independently correlated with in-hospital COVID-19 mortality. Prealbumin stood as an independent safeguarding factor (OR = 0.965, 95% CI 0.947– 0.984). Neutrophil counts (OR = 1.529, 95% CI 1.131– 2.068), urea nitrogen (OR = 1.587, 95% CI 1.222– 2.062), SOFA score(OR = 3.333, 95% CI 1.476– 7.522), qSOFA score(OR = 15.197, 95% CI 3.281– 70.384), PSI score(OR = 1.053, 95% CI 1.018– 1.090), and the infected CT region percentage (OR = 548.221, 95% CI 2.615– 114,953.586) independently linked to COVID-19 patient severity.Keywords: COVID-19, chest CT, artificial intelligence, mortality, severity
Published: 2024

32. SEPT3 as a Potential Molecular Target of Triple-Negative Breast Cancer

Author: Yang LH, Wang GZ, and Gao C
Subjects: triple-negative breast cancer, step3, prognosis, biomarker, Medicine (General), R5-920
Abstract: Li-Hua Yang,1,&ast; Guo-Zhou Wang,1,&ast; Chao Gao2 1Department of Breast Tumor Surgery, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi, Hubei, People’s Republic of China; 2Department of General Practitioner, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi, Hubei, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Chao Gao, Department of General Practitioner, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi, Hubei, 435000, People’s Republic of China, Email gaochaotongxue1987@163.comBackground: The survival rate for triple-negative breast cancer (TNBC) is very low due to its advanced metastatic and aggressive nature, and there is no specific target to improve the survival rate. The expression and clinical signature of neuronal-specific septin-3 (Septin3, SEPT3) in TNBC remain undetermined.Methods: SEPT3 differential expression in TNBC was detected with the use of bioinformatic approaches based on TCGA and GEO database, which was verified with immunohistochemistry in TNBC tissues. Next, the effect of SEPT3 on survival and the association between SEPT3 expression and clinical characteristics were assessed for TNBC patients. We performed Cox analysis to evaluate whether SEPT3 is an independent predictor for TNBC patients.Results: SEPT3 was identified as a key differentially expressed gene. SEPT3 was observed to be elevated in 112 TNBC significantly. Increased expression of SEPT3 contributed to an unfavorable prognosis in patients with TNBC. Additionally, SEPT3 was associated with several factors including TNM stage, lymph node metastasis, Ki67 level and histological grade. SEPT3 was determined to be an independent risk factor for TNBC patients through Cox regression analysis.Conclusion: This study demonstrated that SEPT3 could be a potential disease marker for TNBC patients by bioinformatics analysis and validation in clinical samples.Keywords: triple-negative breast cancer, STEP3, prognosis, biomarker
Published: 2024

33. Development of Biomarkers and Prognosis Model of Mortality Risk in Patients with COVID-19

Author: Zhang Z, Tang L, Guo Y, Guo X, Pan Z, Ji X, and Gao C
Subjects: covid-19, machine learning, prognosis model, st2, il-8, tni, il-6, il-2r, congestive heart failure, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Zhishuo Zhang,1,&ast; Lujia Tang,1,&ast; Yiran Guo,1 Xin Guo,2 Zhiying Pan,2 Xiaojing Ji,1,&ast; Chengjin Gao1,&ast; 1Department of Emergency, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China; 2School of Information Science and Technology, Sanda University, Shanghai, Pudong District, 201209, China&ast;These authors contributed equally to this workCorrespondence: Xiaojing Ji; Chengjin Gao, Email jixiaojing@xinhuamed.com.cn; gaochengjin@xinhuamed.com.cnBackground: As of 30 April 2023, the COVID-19 pandemic has resulted in over 6.9 million deaths worldwide. The virus continues to spread and mutate, leading to continuously evolving pathological and physiological processes. It is imperative to reevaluate predictive factors for identifying the risk of early disease progression.Methods: A retrospective study was conducted on a cohort of 1379 COVID-19 patients who were discharged from Xin Hua Hospital affiliated with Shanghai Jiao Tong University School of Medicine between 15 December 2022 and 15 February 2023. Patient symptoms, comorbidities, demographics, vital signs, and laboratory test results were systematically documented. The dataset was split into testing and training sets, and 15 different machine learning algorithms were employed to construct prediction models. These models were assessed for accuracy and area under the receiver operating characteristic curve (AUROC), and the best-performing model was selected for further analysis.Results: AUROC for models generated by 15 machine learning algorithms all exceeded 90%, and the accuracy of 10 of them also surpassed 90%. Light Gradient Boosting model emerged as the optimal choice, with accuracy of 0.928 ± 0.0006 and an AUROC of 0.976 ± 0.0028. Notably, the factors with the greatest impact on in-hospital mortality were growth stimulation expressed gene 2 (ST2,19.3%), interleukin-8 (IL-8,17.2%), interleukin-6 (IL-6,6.4%), age (6.1%), NT-proBNP (5.1%), interleukin-2 receptor (IL-2R, 5%), troponin I (TNI,4.6%), congestive heart failure (3.3%) in Light Gradient Boosting model.Conclusion: ST-2, IL-8, IL-6, NT-proBNP, IL-2R, TNI, age and congestive heart failure were significant predictors of in-hospital mortality among COVID-19 patients.Keywords: COVID-19, machine learning, prognosis model, ST2, IL-8, TNI, IL-6, IL-2R, congestive heart failure
Published: 2024

34. Piezo1 Knockout Improves Post-Stroke Cognitive Dysfunction by Inhibiting the Interleukin-6 (IL-6)/Glutathione Peroxidase 4 (GPX4) Pathway

Author: Tang L, Xie D, Wang S, Gao C, and Pan S
Subjects: cerebral infarction, neuroinflammation, astrocytes, blood-brain barrier, tight junctions, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Lujia Tang,&ast; Di Xie,&ast; Shangyuan Wang, Chengjin Gao, Shuming Pan Department of Emergency, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Shuming Pan; Chengjin Gao, Email panshuming@xinhuamed.com.cn; gaochengjin@xinhuamed.com.cnBackground: Cerebral infarction often results in post-stroke cognitive impairment, which impairs the quality of life and causes long-term disability. Astrocytes, the most abundant glial cells in the central nervous system, have a crucial role in cerebral ischemia and neuroinflammation. We explored the possible advantages of interleukin-6 (IL-6), a powerful pro-inflammatory cytokine produced by astrocytes, for post-stroke cognitive function.Methods: Mendelian randomization was applied to analyze the GWAS database of stroke patients, obtaining a causal relationship between IL-6 and stroke. Further validation of this relationship and its mechanisms was conducted. Using a mouse model of cerebral infarction, we demonstrated a significant increase in IL-6 expression in astrocytes surrounding the ischemic lesion. This protective effect of Piezo1 knockout was attributed to the downregulation of matrix metalloproteinases and upregulation of tight junction proteins, such as occludin and zonula occludens-1 (ZO-1).Results: Two-step Mendelian randomization revealed that IL-6 exposure is a risk factor for stroke. Moreover, we conducted behavioral assessments and observed that Piezo1 knockout mice that received intranasal administration of astrocyte-derived IL-6 showed notable improvement in cognitive function compared to control mice. This enhancement was associated with reduced neuronal cell death and suppressed astrocyte activation, preserving ZO-1.Conclusion: Our study shows that astrocyte-derived IL-6 causes cognitive decline after stroke by protecting the blood-brain barrier. This suggests that piezo1 knockout may reduce cognitive impairment after brain ischemia. Further research on the mechanisms and IL-6 delivery methods may lead to new therapies for post-stroke cognition.Keywords: cerebral infarction, neuroinflammation, astrocytes, blood-brain barrier, tight junctions
Published: 2024

35. An Analysis of Preoperative Inflammatory Indicators That Influence the Drainage Tube Retention Time in Patients with Breast Cancer Surgery

Author: Li Q, Gao C, Zhao X, Li J, Shen Q, and Chen L
Subjects: breast cancer, inflammatory indicator, drainage tube, operation, nutritional indicator, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Qi Li,1,&ast; Cong Gao,1 Xinrui Zhao,1 Jiahui Li,1 Qinghong Shen,1 Li Chen2,&ast; 1Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People’s Republic of China; 2Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, 430030, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Qi Li, Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People’s Republic of China, Email 1589898345@qq.com Li Chen, Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, 430030, People’s Republic of China, Email cswtth@163.comObjective: The study was aimed to investigate the influence factor between preoperative inflammatory indicators and drainage tube retention time in patients with breast cancer.Methods: This retrospective study enrolled 121 patients with breast cancer who were undergoing surgery between October 2020 and June 2021. The enumeration data were used the Chi-square test, and the measurement data were used the t-test analysis. The univariate and multivariate logistic regression models were performed to access the risk factors for affecting drainage tube retention time in patients with breast cancer. The receiver operating characteristic curve (ROC) was performed to test the prediction effect of the model.Results: Through the median extraction time of postoperative drainage tube retention time, all patients were divided into two groups: drainage tube retention time (DTRT) < 13 (d) and drainage tube retention time (DTRT) ≥ 13 (d). The results showed that type of surgery, total lymph nodes (TLN), pathological T stage, NLR were related to the drainage tube retention time (P< 0.05). Moreover, the univariate and multivariate logistic regression analysis performed that Hb, type of surgery, pathological T stage, chest wall drainage tube, NRI were the independent risk predictors of affecting drainage tube retention time. Furthermore, a significant correlation existed between NRI and drainage tube retention at different times (P < 0.05).Conclusion: NRI is an independent risk factor for postoperative drainage tube extraction time and can effectively predict the probability of drainage tube retention time. Thus, it can also provide personalized nursing intervention for patients with breast cancer after drainage tube retention time and the rehabilitation process.Keywords: breast cancer, inflammatory indicator, drainage tube, operation, nutritional indicator
Published: 2024

36. Abnormal Behavior of Oxidation Kinetics for Ni-10Cr-10Al Alloy at 1273 and 1373 Κ

Author: Zhang, X. J., Gao, C. X., Wang, S. J., Sun, L., and Tian, S.
Subjects: Technology, Chemical technology, TP1-1185, Chemicals: Manufacture, use, etc., TP200-248
Published: 2006
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37. 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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38. Flaring-associated Complex Dynamics in Two M-dwarfs Revealed by Fast, Time-resolved Spectroscopy

Author: Wang, J., Li, H. L., Xin, L. P., Li, G. W., Bai, J. Y., Gao, C., Ren, B., Song, D., Deng, J. S., Han, X. H., Dai, Z. G., Liang, E. W., Wang, X. Y., and Wei, J. Y.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract: Habitability of an exoplanet is believed to be profoundly affected by activities of the host stars, although the related coronal mass ejections (CMEs) are still rarely detected in solar-like and late-type stars. We here report an observational study on flares of two M-dwarfs triggered by the high-cadence survey performed by the Ground Wide-angle Camera system. In both events, the fast, time-resolved spectroscopy enables us to identify symmetric broad H$\alpha$ emission with not only a nearly zero bulk velocity, but also a large projected maximum velocity as high as $\sim700-800\ \mathrm{km\ s^{-1}}$. This broadening could be resulted from either Stark (pressure) effect or a flaring-associated CME at stellar limb. In the context of the CME scenario, the CME mass is estimated to be $\sim4\times10^{18}$ g and $2\times10^{19}$ g. In addition, our spectral analysis reveals a temporal variation of the line center of the narrow H$\alpha$ emission in both events. The variation amplitudes are at tens of $\mathrm{km\ s^{-1}}$, which could be ascribed to the chromospheric evaporation in one event, and to a binary scenario in the other one. With the total flaring energy determined from our photometric monitor, we show a reinforced trend in which larger the flaring energy, higher the CME mass is., Comment: 15 pages, 10 figures and 3 tables. Accepted by ApJ. arXiv admin note: text overlap with arXiv:2106.04774
Published: 2022
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39. Overcoming contrast reversals in focused probe ptychography of thick materials: an optimal pipeline for efficiently determining local atomic structure in materials science

Author: Gao, C., Hofer, C., Jannis, D., Béché, A., Verbeeck, J., and Pennycook, T. J.
Subjects: Physics - Applied Physics
Abstract: Ptychography provides highly efficient imaging in scanning transmission electron microscopy (STEM), but questions have remained over its applicability to strongly scattering samples such as those most commonly seen in materialsscience. Although contrast reversals can appear in ptychographic phase images as the projected potentials of the sample increase, we show here how these can be easily overcome by a small amount of defocus. The amount of defocus is small enough that it can exist naturally when focusing using the annular dark field (ADF) signal, but can also be adjusted post acquisition. The ptychographic images of strongly scattering materials are clearer at finite doses than other STEM techniques, and can better reveal light atomic columns within heavy lattices. In addition data for ptychography can now be collected simultaneously with the fastest of ADF scans. This combination of sensitivity and interpretability presents an ideal workflow for materials science.
Published: 2022
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40. Retraction Note: The molecular mechanism of microRNA-145 to suppress invasion-metastasis cascade in gastric cancer

Author: Gao, P., Xing, A.-Y., Zhou, G.-Y., Zhang, T.-G., Zhang, J.-P., Gao, C., Li, H., and Shi, D.-B.
Published: 2024
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41. Improving the performance of industrial TOPCon solar cells through the insertion of intrinsic a-Si layer

Author: Ma, S., Du, D.X., Ding, D., Gao, C., Li, Z.P., Wu, X.Y., Zou, S., Su, X., Kong, X.Y., Liao, B., and Shen, W.Z.
Published: 2024
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42. Risks and Clinical Predictors of Hepatocellular Carcinoma in Chinese Populations: A Real-World Study of 10,359 Patients in Six Medical Centers

Author: Huang C, Xiao X, Tong L, Gao Z, Ji J, Zhou L, Li Y, Liu L, Feng H, Fang M, and Gao C
Subjects: hepatocellular carcinoma, real-world data, diagnostic, prognosis, algorithm, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Chenjun Huang,1,&ast; Xiao Xiao,1,&ast; Lin Tong,2,&ast; Zhiyuan Gao,1 Jun Ji,2 Lin Zhou,3 Ya Li,4 Lijuan Liu,5 Huijuan Feng,5 Meng Fang,2 Chunfang Gao1,2 1Department of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, People’s Republic of China; 2Department of Laboratory Medicine, Shanghai Eastern Hepatobiliary Surgery Hospital, Shanghai, 200438, People’s Republic of China; 3Department of Laboratory Medicine, Shanghai Changzheng Hospital, Shanghai, 200003, People’s Republic of China; 4Department of Laboratory Medicine, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, People’s Republic of China; 5Department of Laboratory Medicine, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Chunfang Gao, Department of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, People’s Republic of China, Tel +86-21-65161782-1210, Email gaocf1115@163.com; gaocf1115@shutcm.edu.cnPurpose: Early detection of hepatocellular carcinoma (HCC) through surveillance could reduce this cancer-associated mortality. We aimed to develop and validate algorithms using panel serum biomarkers to identify HCC in a real-world multi-center study in China.Patients and Methods: A total of 10,359 eligible subjects, including HCCs and benign liver diseases (BLDs), were recruited from six Chinese medical centers. The three nomograms were built using logistic regression and their sensitivities and specificities were carefully assessed in training and validation cohorts. HCC patients after surgical resection were followed to determine the prognostic values of these algorithms. Prospective surveillance performance was assessed in a cohort of chronic hepatitis B patients during 144 weeks follow-up.Results: Independent risk factors such as alpha-fetoprotein (AFP), lens cuinaris agglutinin-reactive fraction of AFP (AFP-L3), des-gamma-carboxy prothrombin (DCP), albumin (ALB), and total bilirubin (TBIL) obtained from train cohort were used to construct three nomograms (LAD, C-GALAD, and TAGALAD) using logistic regression. In the training and two validation cohorts, their AUCs were all over 0.900, and the higher AUCs appeared in TAGALAD and C-GALAD. Furthermore, the three nomograms could effectively stratify HCC into two groups with different survival and recurrence outcomes in follow-up validation. Notably, TAGALAD could predict HCC up to 48 weeks (AUC: 0.984) and 24 weeks (AUC: 0.900) before clinical diagnosis.Conclusion: The proposed nomograms generated from real-world Chinese populations are effective and easy-to use for HCC surveillance, diagnosis, as well as prognostic evaluation in various clinical scenarios based on data feasibility.Keywords: hepatocellular carcinoma, real-world data, diagnostic, prognosis, algorithm
Published: 2024

43. Association Between Nonthyroidal Illness Syndrome and Disseminated Intravascular Coagulation in Sepsis

Author: Yao Y, Li J, Sun W, Ma C, Ning N, Ni T, Gui M, Chen Y, Zhao B, Zhang J, Zhu J, Gao C, Sheng H, and Mao E
Subjects: sepsis, low t3 syndrome, nonthyroidal illness syndrome, thyroid function, disseminated intravascular coagulation, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract: Yi Yao,1,&ast; Juan Li,2,&ast; Wenwu Sun,1,&ast; Chaoping Ma,2,&ast; Ning Ning,1 Jiaoyan Li,1 Tongtian Ni,1 Menglu Gui,1 Ying Chen,1 Bing Zhao,1 Jiyuan Zhang,2 Jiyue Zhu,3 Chengjin Gao,2 Huiqiu Sheng,1 Enqiang Mao1 1Departments of Emergency, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, People’s Republic of China; 2Department of Emergency, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China; 3Department of General Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Huiqiu Sheng, Departments of Emergency, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, People’s Republic of China, Tel +86-15801971839, Email shenghq803@163.com Chengjin Gao, Department of Emergency, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China, Tel +86-18221088783, Email gaochengjin@xinhuamed.com.cnPurpose: Both nonthyroidal illness syndrome (NTIS) and disseminated intravascular coagulation (DIC) are commonly occurred in sepsis. The objective of this study is to evaluate the association between NTIS and DIC, as well as their impacts on the mortality in adults with sepsis.Patients and methods: A total of 1219 septic patients in two Chinese academic centers from October 2012 and October 2022 were enrolled in analysis. We conduct logistic regression models to analyze the independent risk factors for DIC. Modified Poisson regression models are used to estimate the relative risk (RR) of NTIS on the 28 days mortality in septic patients with DIC. Correlation analysis between thyroid function parameters and coagulation parameters is performed with Pearson coefficient be reported.Results: DIC is diagnosed on 388 (31.8%) of all the 1219 enrolled septic patients within 72 hours after admission. In multivariate logistic regression models, NTIS (OR 3.19; CI 2.31– 4.46; p< 0.001) is a statistically significant independent risk factor for DIC after adjustment for potential confounders. Twenty-eight days mortality is significantly higher in DIC patients complicated with NTIS compared with the other DIC patients (23.2% vs 14.0%, p=0.024). This result is also robust in different modified Poisson regression models (Model 1: RR 1.46; CI 1.25– 1.70; p< 0.001; Model 2: RR 1.35; CI 1.14– 1.60; p< 0.001; Model 3: RR 1.18; CI 1.02– 1.37; p=0.026). Correlation analysis reveals that the thyroid function parameters of FT3, FT4 and TSH only have weak correlations with coagulation parameters of platelet count, fibrinogen, FDP, D-dimers, PT, APTT and INR in sepsis.Conclusion: NTIS is an independent risk factor for DIC in adults with sepsis. DIC patients complicated with NTIS have significantly higher severity and higher rate of mortality.Keywords: sepsis, low T3 syndrome, nonthyroidal illness syndrome, thyroid function, disseminated intravascular coagulation
Published: 2024

44. Clinical Characteristics of Children Infected with SARS-CoV-2 Omicron (B.1.1.529) in China’s Shanghai

Author: Shu J, Jia L, Zhang P, Wang R, Wang M, Sun X, Peng Y, Wang P, Li X, Tang Z, Han T, Ju T, Wei Y, Pang W, Gao C, and Xia Z
Subjects: omicron variant, covid-19, child patients, clinical characteristics, Medicine (General), R5-920
Abstract: Jiaping Shu,1,&ast; Lili Jia,2,&ast; Pei Zhang,2 Ren Wang,2 Meiqiu Wang,2 Xiaoyi Sun,2 Yingchao Peng,2 Peipei Wang,2 Xiaojie Li,2 Zilu Tang,3 Tingting Han,3 Tao Ju,3 Yaqin Wei,4 Wei Pang,5 Chunlin Gao,2 Zhengkun Xia1 1Department of Pediatrics, School of Medicine, Southeast University, Nanjing, Jiangsu, 210009, People’s Republic of China; 2Department of Pediatrics, Jinling Hospital, Nanjing University, Nanjing, Jiangsu, 210093, People’s Republic of China; 3Department of Pediatrics, Jinling Hospital, Nanjing Medical University, Nanjing, Jiangsu, 210093, People’s Republic of China; 4Department of Pediatrics, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, 510000, People’s Republic of China; 5Department of Military Information, Chinese People’s Liberation Army 31102, Nanjing, Jiangsu, 210000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhengkun Xia, Department of Pediatrics, School of Medicine, Southeast University, Nanjing, Jiangsu, 210009, People’s Republic of China, Email njxzk@126.com Chunlin Gao, Department of Pediatrics, Jinling Hospital, Nanjing University, Nanjing, Jiangsu, 210093, People’s Republic of China, Email shuangmu34@163.comIntroduction: The pandemic of SARS-CoV-2 brings great challenge and threats to humans worldwide. Multiple variants of SARS-CoV-2 tend to be epidemic, among which Omicron is highly infectious within China. The aim of this study was to analyze the clinical characteristics of children infected with SARS-CoV-2 variant B.1.1.529 (Omicron) in the Shanghai, China.Methods: We included 9378 pediatric patients diagnosed with Omicron and treated in the Shanghai International Convention and Exhibition Center between April 1, 2022 and May 31, 2022. We recorded and summarized the clinical characteristics, infectious conditions and biological features of the children infected with Omicron.Results: A total of 9355 paediatric patients were treated in isolation since Makeshift became available, including 5564 males (59.48%) and 3791 females (40.52%). More than half (55.56%) of the affected children were identified at premises screening. The number of symptomatic or asymptomatic patients was 4530 (48.42%) and 4825 (51.58%), respectively. Initial signs or symptoms in asymptomatic patients included fatigue (3582, 38.29%), cough (560, 5.99%), fever (242, 2.59%) and other (146, 1.56%). Age and number of vaccinations in paediatric patients were negatively associated with the number of days from positive to negative nucleic acid test results.Conclusion: Age and number of vaccinations were key factors influencing the conversion of nucleic acid test results in paediatric patients. Early childhood vaccination is encouraged to establish a complete immune barrier.Keywords: Omicron variant, COVID-19, child patients, clinical characteristics
Published: 2024

45. Intramuscular Hemangioma of the Triceps Brachii Muscle: A Case Report

Author: Gao C, Wang H, and Liu H
Subjects: intramuscular hemangioma, fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography, magnetic resonance imaging, Medicine (General), R5-920
Abstract: Cailiang Gao,1 Hu Wang,2 Huiting Liu1 1Department of Nuclear Medicine, Three Gorges Hospital, Chongqing University, Chongqing, People’s Republic of China; 2Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USACorrespondence: Huiting Liu, Department of Nuclear Medicine, Three Gorges Hospital, Chongqing University, No. 165, Xincheng Road, Wanzhou, Chongqing, 404000, People’s Republic of China, Email flyover1818@163.com Hu Wang, Department of neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA, Email biomed_wang@yahoo.comIntroduction: Intramuscular hemangioma (IMH) is a rare type of benign tumor that represents less than 1% of all hemangiomas. Chronic pain and a palpable mass are the most common symptoms. Due to the atypical clinical characteristics of the disease, accurate diagnosis is difficult. Misdiagnosis of IMH as malignancy can occur due to similarities in imaging features between IMH and malignancy. To diagnose IMH accurately, multiple imaging modalities, including X-ray, MRI, CT, and 18F-FDG PET/CT, can be used. However, the final diagnosis of IMH is confirmed through histopathological examination.Case: This case reports a 16-year-old girl diagnosed with IMH in the triceps brachii muscle. Seek medical attention due to pain and discomfort in the left shoulder. Initial imaging with contrast-enhanced MRI and CT suggested synovial sarcomata. The moderate uptake of FDG on positron emission tomography/computed tomography (PET/CT) also raised suspicions of malignancy. The pathological findings revealed an intramuscular hemangioma with thrombosis and thrombus organization.Conclusion: The accurate diagnosis of IMH can be challenging due to the absence of distinct clinical symptoms and imaging findings. When evaluating periarticular intramuscular lesions, IMH should be considered if the MRI shows mixed signals with heterogeneous enhancement. Despite the moderate uptake of FDG seen in some IMH cases, it should not automatically rule out the possibility of IMH. Hence, a combination of imaging modalities and histopathological examination is crucial in ensuring a correct diagnosis of IMH.Keywords: intramuscular hemangioma, fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography, magnetic resonance imaging
Published: 2024

46. Pseudooceanicola albus sp. nov., Isolated from Mangrove Sediment within the Beibu Gulf

Author: Li, M., Li, F. T., Gao, C. H., Liu, Y. H., and Yi, X. X.
Published: 2023
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47. Correlates of substance use in a large naturalistic cohort of young people with early and emerging psychosis

Author: El-Hage, D., Gao, C. X., Bedi, G., Guerin, A., Francey, S., Stavely, H., Rickwood, D., Telford, N., McGorry, P., Thompson, A., and Brown, Ellie
Published: 2023
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48. Retrospective Analysis of 397 Dermatoses Inpatients Associated with Blood Eosinophilia

Author: Zhao Y, Tian J, Gao C, Liu L, Pan L, and Song Z
Subjects: eosinophila, diagnosis, eczema, psoriasis, drug eruption, Dermatology, RL1-803
Abstract: Ying Zhao, Jing Tian, Cuie Gao, Lu Liu, Linxin Pan, Zhiqiang Song Department of Dermatology, Southwest Hospital, Army Medical University, Chongqing, People’s Republic of ChinaCorrespondence: Zhiqiang Song, Department of Dermatology, Southwest Hospital, Army Medical University, No. 30, Gaotanyan Street, Shapingba District, Chongqing, 400038, People’s Republic of China, Email drsongzq@hotmail.comBackground: Blood eosinophilia is often associated with various dermatoses, such as atopic eczema, urticaria, drug eruption, bullous pemphigoid, and hypereosinophilic syndrome (HES). Differential diagnosis is very challenging due to the similarities of clinical and pathological characteristics.Purpose: To investigate and analyze the clinical characteristics of dermatoses associated with blood eosinophilia (DABE) to further optimize disease management.Patients and Methods: We conducted a retrospective analysis on 397 DABE patients with blood absolute eosinophil count (AEC) greater than or equal to 0.5× 109/L. Clinical characteristics, laboratory values, treatment course, and associated diagnoses were evaluated. All DABE patients were grouped based on the severity of eosinophilia as mild group (0.5 ≤ AEC× 109/L < 1.5), moderate group (1.5 ≤ AEC× 109/L < 3), and severe group (AEC× 109/L ≥ 3).Results: Our study revealed three distinct patterns: (1) Mild eosinophilia associated with localized skin lesions, atopic history, mildly elevated total serum IgE level, diagnosed with eczema/dermatitis, and frequent antihistamines use. (2) Moderate eosinophilia has the characteristics of both mild group and severe group. (3) The severe eosinophilia group had a high proportion of elderly people without atopic history, but with acute onset, generalized skin lesions, and high level of lactate dehydrogenase, and the majority of them were diagnosed with systemic diseases (HES or tumor).Conclusion: We summarize the clinical rules of dermatoses associated with blood eosinophilia, hoping to facilitate the diagnosis and treatment for patients.Keywords: eosinophilia, diagnosis, eczema, psoriasis, drug eruption
Published: 2023

49. Comprehensive Analysis Reveals the Potential Roles of CDKN3 in Pancancer and Verification in Endometrial Cancer

Author: Gao C, Fan X, Liu Y, Han Y, Liu S, Li H, Zhang Q, Wang Y, and Xue F
Subjects: cdkn3, pancancer analysis, diagnosis, prognosis, therapeutics, immunity, endometrial cancer, Medicine (General), R5-920
Abstract: Chao Gao,1,2,&ast; Xiangqin Fan,1– 3,&ast; Yanyan Liu,1,2,&ast; Yanyan Han,4,5 Shiqi Liu,1,2 Huanrong Li,1,2 Qiaoling Zhang,1,2 Yingmei Wang,1,2 Fengxia Xue1,2 1Department of Gynecology and Obstetrics, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China; 2Tianjin Key Laboratory of Female Reproductive Health and Eugenics, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China; 3Department of Obstetrics and Gynecology, Zaozhuang Municipal Hospital, Shandong, People’s Republic of China; 4Department of Pathology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 5National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Fengxia Xue; Yingmei Wang, Department of Gynecology and Obstetrics, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China, Tel +86-22-60363769, Email xuefengxia@tmu.edu.cn; wangyingmei@tmu.edu.cnBackground: Cyclin-dependent kinase inhibitor 3 (CDKN3) has been studied in many cancers. However, the comprehensive and systematic pancancer analysis of CDKN3 genes is still lacking.Methods: Data were downloaded from online databases. R was used for analysis of the differential expression and gene alteration of CDKN3 and of the associations between CDKN3 expression and survival, signaling pathways, and drug sensitivity. Clinical samples and in vitro experiments were selected for verification.Results: CDKN3 expression was higher in most types of cancers, and this phenotype was significantly correlated with poor survival. CDKN3 showed gene alterations and copy number alterations in many cancers and associated with some immune-related pathways and factors. Drug sensitivity analysis elucidated that CDKN3 could be a useful marker for therapy selection. Clinical samples elucidated CDKN3 expressed high in endometrial cancer tissue. In vitro studies showed that CDKN3 induced pro-tumor effect in immune environment and facilitated endometrial cancer cell proliferation and G1/S phase transition.Conclusion: CDKN3 has been shown to be highly expressed in most types of cancers and promoted cancer cell progression. CDKN3 may serve as a novel marker in clinical diagnosis, treatment, and prognosis prediction in future.Keywords: CDKN3, pancancer analysis, diagnosis, prognosis, therapeutics, immunity, endometrial cancer
Published: 2023

50. General Population’s Psychological Perceptions of COVID-19: A Systematic Review

Author: Gao C
Subjects: covid-19, attitude, perception, mental health, general population, Psychology, BF1-990, Industrial psychology, HF5548.7-5548.85
Abstract: Chong Gao School of Design and Architecture, Zhejiang University of Technology, Hangzhou, Zhejiang Province, People’s Republic of ChinaCorrespondence: Chong Gao, School of Design and Architecture, Zhejiang University of Technology, 86 Liuhe Road, Xihu District, Hangzhou, Zhejiang Province, 310023, People’s Republic of China, Tel +86 13159850367, Email wenguerzhixin12345@163.comAbstract: During the COVID-19 pandemic, general population’s mental health may be influenced by their perceptions of major pandemic issues. Therefore, a systematic search was conducted to screen out those concerns and analyse the impacts. EBSCO, Scopus and Web of Science were searched for publications from inception to 1 February 2023. Nineteen articles were extracted and four issues were screened out as general population’s major concerns, namely “Risk perception”, “Government trust”, “Media coverage and authenticity”, and “Conspiracy theory”. The population’s perceptions of those issues could affect their mental health by arousing emotional reactions, which vary in different countries, social classes and groups, and would change in different stages of virus outbreak. The findings suggest that the general population’s attitudes towards COVID-19-related social issues could affect their psychological health and should receive more concerns. As different issues are related to one another, an integrated solution system is in need, which would be helpful for coping with similar public emergencies in the future.Keywords: COVID-19, attitude, perception, mental health, general population
Published: 2023

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