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1. Catalogue of Phonon Instabilities in Symmetry Group 191 Kagome MT$_6$Z$_6$ Materials

Author

Feng, X., Jiang, Y., Hu, H., Călugăru, D., Regnault, N., Vergniory, M. G., Felser, C., Blanco-Canosa, S., and Bernevig, B. Andrei

Subjects
Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract

Kagome materials manifest rich physical properties due to the emergence of abundant electronic phases. Here, we carry out a high-throughput first-principles study of the kagome 1:6:6 family MT$_6$Z$_6$ materials in space group 191, focusing on their phonon instability and electronic flat bands. Different MT$_6$Z$_6$ kagome candidates reveal a remarkable variety of kagome flat bands ranging from unfilled, partially filled, to fully filled. Notably, the Mn/Fe-166 compounds exhibit partially filled flat bands with a pronounced sharp peak in the density of states near the Fermi level, leading to magnetic orders that polarize the bands and stabilize the otherwise unstable phonon. When the flat bands are located away from the Fermi level, we find a large number of phonon instabilities, which can be classified into three types, based on the phonon dispersion and vibrational modes. Type-I instabilities involve the in-plane distortion of kagome nets, while type-II and type-III present out-of-plane distortion of trigonal M and Z atoms. We take MgNi$_6$Ge$_6$ and HfNi$_6$In$_6$ as examples to illustrate the possible CDW structures derived from the emergent type-I and type-II instabilities. The type-I instability in MgNi$_6$Ge$_6$ suggests a nematic phase transition, governed by the local twisting of kagome nets. The type-II instability in HfNi$_6$In$_6$ may result in a hexagonal-to-orthorhombic transition, offering insight into the formation of MT$_6$Z$_6$ in other space groups. Additionally, the predicted ScNb$_6$Sn$_6$ is analyzed as an example of the type-III instability. Our predictions suggest a vast kagome family with rich properties induced by the flat bands, possible CDW transitions, and their interplay with magnetism., Comment: 14 pages, 7 figures, with 1000 pages of additional supplemental materials

Published
2024

2. Upgrading the existing Haloscope-type detector for sensitive axion detection

Author

Gao, L., Zheng, H., Feng, X. N., Zhao, L. B., and Wei, L. F.

Subjects
High Energy Physics - Experiment
Abstract

Haloscope is one of the typical installations to detect the electromagnetic responses (EMRs) of axion field in radio-frequency (rf) band. Given what the detection by the existing Haloscope-type detector (HTD) biased only by a high stationary magnetic field, is just the second axion-photon energy converted effect and thus the detectable signal is still significantly weak, here we propose a feasible approach to upgrade the existing HTD by additionally applying a transverse rf modulated magnetic field for generating the first-order axion-photon energy converted signal. Accordingly, we argue that the detection sensitivity of the upgrading HTD (UHTD) could be enhanced feasibly by a few orders of magnitude, compared with those achieved by the existing HTDs. The feasibility of the proposed UHTD is also discussed., Comment: 22 pages,3 figures

Published
2024

3. Influences of modified Chaplygin dark fluid around a black hole

Author

Zare, S., Nieto, L. M., Hosseinifar, F., Feng, X. -H., and Hassanabadi, H.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract

In this work, we study a static, spherically charged AdS black hole within a modified cosmological Chaplygin gas (MCG), adhering to the calorific equation of state, as a unified dark fluid model of dark energy and dark matter. We explore the influence of model parameters on several characteristics of the MCG-motivated charged AdS black hole (MCG-AdSBH), including the geodesic structure and some astrophysical phenomena such as null trajectories, shadow silhouettes, light deflection angles, and the determination of greybody bounds. We then discuss how the model parameters affect the Hawking temperature, remnant radius, and evaporation process of the MCG-AdSBH. Quasinormal modes are also investigated using the eikonal approximation method. Constraints on the MCG-AdSBH parameters are derived from EHT observations of M87* and Sgr A*, suggesting that MCG-AdSBH could be strong candidates for astrophysical black hole., Comment: 8 pages, 11 figures, 4 tables

Published
2024

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

Author

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

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

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

Published
2024

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

Author

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

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

The KM2A is the largest sub-array of the Large High Altitude Air Shower Observatory (LHAASO). It consists of 5216 electromagnetic particle detectors (EDs) and 1188 muon detectors (MDs). The data recorded by the EDs and MDs are used to reconstruct primary information of cosmic ray and gamma-ray showers. This information is used for physical analysis in gamma-ray astronomy and cosmic ray physics. To ensure the reliability of the LHAASO-KM2A data, a three-level quality control system has been established. It is used to monitor the status of detector units, stability of reconstructed parameters and the performance of the array based on observations of the Crab Nebula and Moon shadow. This paper will introduce the control system and its application on the LHAASO-KM2A data collected from August 2021 to July 2023. During this period, the pointing and angular resolution of the array were stable. From the observations of the Moon shadow and Crab Nebula, the results achieved using the two methods are consistent with each other. According to the observation of the Crab Nebula at energies from 25 TeV to 100 TeV, the time averaged pointing errors are estimated to be $-0.003^{\circ} \pm 0.005^{\circ}$ and $0.001^{\circ} \pm 0.006^{\circ}$ in the R.A. and Dec directions, respectively., Comment: 15 pages, 9 figures

Published
2024

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

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

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

Published
2024

7. LHAASO-KM2A detector simulation using Geant4

Author

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

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

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

Published
2024
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8. Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

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

Published
2024
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9. Does or did the supernova remnant Cassiopeia A operate as a PeVatron?

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

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

Published
2023

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

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

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

Published
2023
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12. Sub-SQL electronic field sensing by simultaneously using quantum entanglements and squeezings

Author

Feng, X. N., Zhang, M., and Wei, L. F.

Subjects
Quantum Physics
Abstract

Quantum entanglement and quantum squeezing are two most typical approaches to beat the standard quantum limit (SQL) of the sensitive phase estimations in quantum metrology. Each of them has already been utilized individually to improve the sensitivity of electric field sensing with the trapped ion platform, but the upper bound of the demonstrated sensitivity gain is very limited, i.e., the experimental 3dB and theoretical 6dB, over the SQL. Here, by simultaneously using the internal (spin)-external (oscillator) state entanglements and the oscillator squeezings to effectively amplify the accumulation phase, we show that these sensitivity gains can be effectively surpassed. Hopefully, the proposal provides a novel approach to the stronger beaten of the SQL for the sensitive sensings of the desired electric field and also the other metrologies.

Published
2023

13. Expansion of a Novel Subset of L-Selectin+ Classical Monocytes in Kawasaki Disease

Author

Jin Y, Geng Z, Lin K, Gu X, Feng X, Fu S, Wang W, Xie C, Wang Y, and Gong F

Subjects
kawasaki disease, monocyte subsets, l-selectin, coronary artery lesions, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract

Yihua Jin,1,* Zhimin Geng,1,2,* Kun Lin,1 Xinyu Gu,1 Xiwei Feng,1 Songling Fu,1 Wei Wang,1 Chunhong Xie,1 Yujia Wang,1 Fangqi Gong1 1Department of Cardiology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, People’s Republic of China; 2Pediatric Cardiovascular Diseases Laboratory, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Fangqi Gong; Yujia Wang, Email gongfangqi@zju.edu.cn; wangyujia@zju.edu.cnPurpose: Kawasaki disease (KD) is an acute systemic vasculitis that is associated with dysregulated immune responses. Monocytes play a central role in innate immunity. Our previous single-cell RNA sequencing of peripheral blood mononuclear cells (PBMC) revealed a new subset of monocytes in children with KD called L-Selectin+ classical monocytes (SELL+ CM). Therefore, we aimed to investigate the correlation between KD and SELL+ CM.Patients and Methods: Peripheral blood samples were collected from 81 KD patients, 18 febrile patients and 36 healthy children before treatment. Among them, ten KD patients were followed up, and samples were obtained before and after intravenous immunoglobulin (IVIG) treatment. Analysis of SELL+ CM was performed using flow cytometry. Additionally, ROC curve analysis was conducted to assess the diagnostic value of SELL+ CM for KD.Results: Classical monocytes (CM) expressed the highest levels of L-selectin in children with KD. The ratio of SELL+ CM in CM was significantly higher in KD patients than in febrile and healthy children. Following IVIG treatment, the ratio of SELL+ CM in CM showed a downward trend. The receiver operating characteristic (ROC) curve analysis (the area under the curve, AUC = 0.71) indicated the potential diagnostic value of SELL+ CM in KD. The correlation analysis suggested that SELL+ CM may serve as a new clinical index for patients with KD.Conclusion: In KD, the ratio of SELL+ CM in CM significantly increases during the acute phase, which may become a potential biomarker and help facilitate KD diagnosis based on clinical features.Keywords: Kawasaki disease, monocyte subsets, L-Selectin, coronary artery lesions

Published
2024

14. Neoadjuvant-Based Triple Therapy for Hepatocellular Carcinoma with Type I/II Portal Vein Tumor Thrombosis

Author

Hou G, Zhang F, Feng X, Chen Y, Zhang J, and Wang H

Subjects
hepatocellular carcinoma, neoadjuvant treatment, portal vein tumor thrombosis, tace, immunotherapy, tkis., Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Guimin Hou,1,* Feng Zhang,1,* Xielin Feng,1 Yan Chen,2 Jinliang Zhang,1 Haiqing Wang1 1Department of Hepatopancreatobiliary Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, People’s Republic of China; 2Department of Pharmacy, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Haiqing Wang, Department of Hepatopancreatobiliary Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, People’s Republic of China, Tel +86-028-85420945, Email wanghaiqing241286@163.comPurpose: Hepatectomy could provide better survival benefit for hepatocellular carcinoma (HCC) with type I/II portal vein tumor thrombosis (PVTT). However, the postoperative recurrence remains high. We discussed whether neoadjuvant therapy could reduce HCC recurrence for these patients.Patients and Methods: One hundred and thirty-eight resectable HCC with type I–II PVTT were retrospectively included. The neoadjuvant therapy regimens included tyrosine kinase inhibitor (TKI), programmed death 1(PD-1) antibodies and transarterial chemoembolization (TACE). Short-term and long-term outcomes were compared. Propensity score matching (PSM) was performed to minimize the influence of potential confounders.Results: Thirty-three patients underwent neoadjuvant therapy and 105 patients underwent surgery alone. In the neoadjuvant group, 7 (21.2%) patients achieved stable disease, 13 (39.4%) achieved partial response and 13 (39.4%) achieved complete response based on the modified Response Evaluation Criteria in Solid Tumors criterion. By PSM, the neoadjuvant therapy resulted in less microvascular invasion (24.1% vs 50.0%, P=0.021), satellite nodule (6.9% vs 24.1%, P=0.036) and less patients with alpha-fetoprotein> 20(ng/mL) (37.9% vs 69.0%, P=0.006). The neoadjuvant therapy reduced tumor recurrence and prolonged survival. Multivariate analysis found that neoadjuvant therapy was an independent protective factor for overall survival and recurrence free survival.Conclusion: Neoadjuvant treatment presents a promising treatment option for HCC patients with type I/II PVTT.Keywords: hepatocellular carcinoma, neoadjuvant treatment, portal vein tumor thrombosis, TACE, immunotherapy, TKIs

Published
2024

15. Gastroesophageal Reflux Disease and Preterm Birth: Univariate and Multivariate Mendelian Randomization

Author

Han X, Wu TQ, Yao R, Liu C, Chen L, and Feng X

Subjects
mendelian randomization, gastroesophageal reflux disease, preterm birth, causality, Gynecology and obstetrics, RG1-991
Abstract

Xinyu Han,1 Tian Qiang Wu,1 Ruiting Yao,1 Chang Liu,1 Lu Chen,2 Xiaoling Feng2 1Department of First Clinical Medical College, Heilongjiang University of Chinese Medicine, Harbin, People’s Republic of China; 2Department of Gynecology, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, People’s Republic of ChinaCorrespondence: Xiaoling Feng, Department of Gynecology, The First Affiliated Hospital of Heilongjiang University, No. 26, Heping Road, Xiang-Fang District, Harbin City, Heilongjiang Province, People’s Republic of China, Email Doctorfxl@163.comBackground: Observational studies have established a connection between Gastroesophageal reflux disease (GERD) and preterm birth (PTB). Nevertheless, these correlations can be affected by residual confounding or reverse causality, resulting in ambiguity regarding the connection. The objective of this study was to assess the relationship between genetically predicted GERD and PTB.Methods: Initially, we performed bidirectional univariate Mendelian randomization (UVMR) analysis utilizing publicly accessible genome-wide association studies (GWAS) data. The primary analytical approach employed to determine the causal impact between GERD and PTB is the inverse variance weighted technique (IVW). Subsequently, we utilized multivariate Mendelian randomization (MVMR) to adjust for potential factors that could influence the results, such as body mass index (BMI), maternal smoking around birth, educational attainment, household income, and Townsend deprivation index (TDI). Furthermore, we performed a sequence of comprehensive sensitivity analyses to assess the reliability of our MR findings.Results: The UVMR analysis results showed a significant correlation between GERD and PTB (odds ratio [OR]: 1.810; 95% confidence interval [CI]: 1.344– 2.439; P=9.60E-05) in the IVW model, and the Weighted median method (OR=1.591, 95% CI=1.094– 2.315, P=0.015) revealed consistent results. The inverse MR findings suggest no causal link between PTB and the incidence of GERD. In addition, the sensitivity analysis did not detect heterogeneity or horizontal pleiotropy, and the “leave-one-out” examination confirmed that the causal estimation is unlikely to be influenced by the single nucleotide polymorphisms (SNPs) effect. The MVMR analysis demonstrated that the causal association between GERD and PTB still existed after considering BMI, maternal smoking around birth, educational attainment, household income, and TDI (OR=1.921, 95% CI=1.401– 2.634, P=5.08E-05).Conclusion: This study presents evidence indicating that genetically predicted GERD can heighten the risk of PTB. Therefore, it is advisable to perform focused screening for pregnant women with GERD in order to find the initial signs of PTB and promptly apply intervention strategies to extend the duration of pregnancy.Keywords: Mendelian randomization, gastroesophageal reflux disease, preterm birth, causality

Published
2024

16. Identification of Immune Gene Signature Associated with T Cells and Natural Killer Cells in Type 1 Diabetes

Author

Wang N, Wang G, Feng X, and Yang T

Subjects
type 1 diabetes, immune cell infiltration, immune gene signature, diagnosis, csf1, Specialties of internal medicine, RC581-951
Abstract

Na Wang,1,2 Guofeng Wang,2 Xiuli Feng,2 Teng Yang2 1Department of Endocrinology, Lianyungang Clinical College of Nanjing Medical University, Lianyungang City, Jiangsu Province, 222000, People’s Republic of China; 2Department of Endocrinology, Jinzhou Medical University(The First People’s Hospital of Lianyungang), Lianyungang City, Jiangsu Province, 222000, People’s Republic of ChinaCorrespondence: Guofeng Wang, Department of Endocrinology, Lianyungang Clinical College of Nanjing Medical University (The First People’s hospital of Lianyungang), No. 6 Zhenhua East Road, Haizhou District, Lianyungang City, Jiangsu Province, 222000, People’s Republic of China, Email wangguofengo@21cn.comPurpose: This study aimed to investigate the abnormal infiltration of immune cells in type 1 diabetes mellitus (T1D) and elucidate their regulatory mechanisms.Methods: Public T1D-related gene expression data were obtained from the Gene Expression Omnibus database.The GSE123658 dataset analyzed whole blood RNA-seq data from type 1 diabetic patients and healthy volunteers. The GSE110914 dataset analyzed neutrophils purified from peripheral blood of patients with symptomatic and pre-symptomatic type 1 diabetes (T1D), at risk of T1D, and healthy controls. Immune cell infiltration analysis was performed to identify abnormally infiltrating immune cells. Differentially expressed immune genes (DEIGs) in T1D samples were identified, followed by the construction of an immune gene signature (IGS) using a protein-protein interaction (PPI) network and Least absolute shrinkage and selection operator Cox regression analyses (LASSO Cox regression analyses). The regulatory mechanisms underlying IGS were explored using gene set enrichment analysis. Furthermore, expression validation, diagnostic efficacy evaluation, and upstream miRNA prediction of hub signature genes were performed. We verified the miRNA expression of the key gene colony stimulating factor 1 (CSF1) and microRNA-326 (miR-326) by reverse transcription-quantitative PCR (RT‒qPCR).Results: The proportion of infiltrating T and natural killer (NK) cells differed between the T1D and control samples, and 207 immune genes (IGs) related to these immune cells were extracted. After differential expression, PPI, and LASSO Cox regression analyses, four signature DEIGs were identified for IGS construction: notch receptor 1 (NOTCH1), Janus kinase 3 (JAK3), tumor necrosis factor receptor superfamily member 4(TNFRSF4), and CSF1. Key pathways such as the Toll-like receptor signaling pathway were significantly activated in the high-risk group. Moreover, the upregulation of CSF1 in T1D samples was confirmed using a validation dataset, and CSF1 showed high diagnostic efficacy for T1D. Furthermore, CSF1 was targeted by miR-326.We used validated key genes in T1D patients, several of which were confirmed by RT‒qPCR.Conclusion: In conclusion, the identified key IGs may play an important role in T1D. CSF1 can be developed as a novel diagnostic biomarker for T1D.Keywords: Type 1 diabetes, immune cell infiltration, immune gene signature, diagnosis, CSF1

Published
2024

17. Factors Influencing the Use and Demand of New Coronavirus Therapy Drugs Among the Adults During COVID-19 in China

Author

Chen C, Zhang H, Feng X, and Wang H

Subjects
covid-19, drug use, drug demand, drug delivery, drug stockpiling, Public aspects of medicine, RA1-1270
Abstract

Cunchuan Chen,1,2,&ast; Huifang Zhang,1,2,&ast; Xia Feng,1,2 Haipeng Wang1,2 1Center for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, People’s Republic of China; 2NHC Key Laboratory of Health Economics and Policy Research, Shandong University, Jinan, 250012, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Haipeng Wang, Email wanghaipeng@sdu.edu.cnBackground: This alteration in the policy of COVID-19 resulted in widespread infections throughout China. Most people only need some antiviral drugs such as lopinavir/ritonavir or Chinese herbal preparations for treatment. In this context, the lack of drug knowledge and inadequate drug availability are evident. This study aims to explore the factors influencing drug use and demand during the COVID-19 epidemic.Methods: This study used quota sampling based on gender, age, and place of residence to perform a cross-sectional survey on a sample of 771 adults. The researchers used chi-square tests to understand differences in drug use and demand across characteristics, and binary logistic regression to analyse the influencing factors.Results: The study revealed that 85.9% of the participants used drugs following the COVID-19 infection. Participants with college and above, (OR=2.49, 95% CI=1.27– 4.88) annual personal income between 30,000 and 80,000CNY (OR=2.19, 95% CI=1.35– 3.55) and over 80,000CNY (OR=1.96, 95% CI=1.05– 3.66) were more knowledgeable about using drugs. Gender, (OR=0.69, 95% CI=0.50– 0.95) age, (OR=2.11, 95% CI=1.15– 3.88) residence, (OR=1.58, 95% CI=1.06– 2.37) chronic disease conditions (OR=0.46, 95% CI=0.27– 0.78) and infection symptoms (OR=0.60, 95% CI=0.38– 0.93) as factors influencing the need for drug delivery services. (P< 0.05).Conclusion: Research has revealed that a significant proportion of infected people in China chose drug treatment during COVID-19. Individuals with severe symptoms use more medication and require more drug delivery and storage. Low-education and low-income populations are lacking in drug knowledge, and older adults with underlying medical conditions are more likely to need drug delivery services. Therefore, governments should prioritize vulnerable groups when formulating drug policies and target drug literacy and guidance. In addition, it is recommended that a drug distribution system be set up within the community so that those in need can have quick and easy access to drugs.Keywords: COVID-19, drug use, drug demand, drug delivery, drug stockpiling

Published
2024

18. Mechanisms of Zhixiao Tang on Anti-Inflammatory Multiple Targets and Multiple Components: Metabonomics Combined with Database Mining Technology

Author

Zhang K, Li C, Wu P, Gao X, Feng X, Shen J, Zhang N, Hu X, Wang S, Zhang H, Lv J, and Sun J

Subjects
zhixiao tang, pneumonia, network pharmacology, integrated metabolomics, 16hbe, zebrafish, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract

Kaiyue Zhang, Chunnan Li, Peitong Wu, Xiaochen Gao, Xueqin Feng, Jiaming Shen, Nanxi Zhang, Xuesheng Hu, Shuo Wang, Hui Zhang, Jingwei Lv, Jiaming Sun Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun, Jilin, People’s Republic of ChinaCorrespondence: Jiaming Sun; Jingwei Lv, Changchun University of Chinese Medicine, No. 1035, Boshuo Road, Nanguan District, Changchun, 130117, People’s Republic of China, Tel +0431-86763809, Fax + 8676 3968, Email Sun_jiaming2000@163.com; jingwei-lv@hotmail.comPurpose: Zhixiao Tang (ZXT), a traditional Chinese compound prescription, has been used clinically to treat pneumonia in China. However, the underlying mechanism of ZXT treatment in pneumonia is still unclear. The present study aimed to reveal the potential mechanism of ZXT in pneumonia using a strategy combining metabolomics and network pharmacology.Methods: Initially, the chemical compositions were identified by UPLC-QE-Orbitrap-MS, while the prediction of potential signal pathways was performed through network pharmacology. To assess the anti-inflammatory properties of ZXT in the context of pneumonia, models of 16HBE cells induced by LPS and zebrafish induced by CuSO4 were established to measure levels of inflammatory markers and apoptosis. Subsequently, the differential changes of endogenous metabolites in cells caused by ZXT were examined using metabolomics technology, and the molecular docking analysis of key targets was carried out using Autodock Vina software. Ultimately, the validation of the primary pathways and targets was conducted through quantitative RT-PCR and Western blot techniques.Results: A total of 75 compounds were identified through UPLC-QE-Orbitrap-MS analyses. Network pharmacological analysis shows that it plays an anti-inflammatory role in C-type lectin receptor signaling pathway. After ZXT intervention, the inflammatory factors and apoptosis in cells were significantly reduced. Metabonomics analysis showed that 18 metabolites changed significantly. Four key genes were identified, which exhibited partial compatibility with the findings of network pharmacology. Molecular docking analysis confirmed the substantial affinity of the primary targets for ZXT. Furthermore, ZXT exerted a suppressive effect on neutrophil migration, down-regulated the expression of pro-inflammatory cytokine genes, and inhibited the up-regulation of the Dectin-1/SYK/NF-κB signaling pathway. In vivo cell experiments also yielded consistent experimental outcomes.Conclusion: This study enhances comprehension of the pharmacological mechanism underlying ZXT’s efficacy in pneumonia treatment, thereby establishing a scholarly basis for future research and clinical utilization of ZXT in pneumonia management. Keywords: Zhixiao Tang, pneumonia, network pharmacology, integrated metabolomics, 16HBE, Zebrafish

Published
2024

19. Characteristics of the edge temperature ring oscillation during stationary improved confnement mode in EAST

Author

Liu, A. D., Zou, X. L., Zhong, X. M., Song, Y. T., Han, M. K., Duan, Y. M., Liu, H. Q., Wang, T. B., Li, E. Z., Zhang, L., Feng, X., Zhuang, G., and group, EAST I-mode working

Subjects
Physics - Plasma Physics
Abstract

I-mode is a natural ELMy-free regime with H-mode like improved energy confnement and L-mode like particle confnement, making it an attractive scenario for future tokamak based fusion reactors. A kind of low frequency oscillation was widely found and appeared to be unique in I-mode, with the frequency between stationary zonal flow and geodesic-acoustic mode (GAM) zonal flow. In EAST, 90 percent I-mode shots have such mode, called edge temperature ring oscillation (ETRO). The mode probably plays an important role during I-mode development and sustainment, while investigations are needed to clarify the differences between ETRO and the similar mode named as low frequency edge oscillation (LFEO) in AUG and C-Mod, especially whether it is still GAM. In the paper, the ETRO characteristics in EAST were investigated in detail and most do not agree with GAM, including that 1) during L-I transition with edge Te and Ti both increasing, ETRO has a smaller frequency than GAM; 2) ETRO has distinct harmonics in various diagnostics; 3) The magnetic component of ETRO is dominated by m = 1 structure; 4) ETRO is accompanied by turbulence transition between electron-scale and ion-scale; 5) As I-mode approaching to H-mode, ETRO frequency would decrease rapidly with Te increasing. These features imply that ETRO is probably caused by the stationary zonal flow with fnite frequency. Moreover, other damping mechanisms need to be involved besides collision in the Imode edge region. It was found that modest fueling could decrease the ETRO intensity with the I-mode confnement sustaining, suggesting that supersonic molecular beam injection (SMBI) could be used as an effective tool to control ETRO., Comment: 23 pages, 16 figures

Published
2023

20. 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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21. 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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22. Softening of a flat phonon mode in the kagome ScV$_6$Sn$_6$

Author

Korshunov, A., Hu, H., Subires, D., Jiang, Y., Călugăru, D., Feng, X., Rajapitamahuni, A., Yi, C., Roychowdhury, S., Vergniory, M. G., Strempfer, J., Shekhar, C., Vescovo, E., Chernyshov, D., Said, A. H., Bosak, A., Felser, C., Bernevig, B. Andrei, and Blanco-Canosa, S.

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract

The long range electronic modulations recently discovered in the geometrically frustrated kagome lattice have opened new avenues to explore the effect of correlations in materials with topological electron flat bands. The observation of the lattice response to the emergent new phases of matter, a soft phonon mode, has remained elusive and the microscopic origin of charge density waves (CDWs) is still unknown. Here, we show, for the first time, a complete melting of the ScV$_ 6$Sn$_ 6$ (166) kagome lattice. The low energy phonon with propagation vector $\frac{1}{3} \frac{1}{3} \frac{1}{2}$ collapses at 98 K, without the emergence of long-range charge order, which sets in with a propagation vector $\frac{1}{3} \frac{1}{3} \frac{1}{3}$. The CDW is driven (but locks at a different vector) by the softening of an overdamped phonon flat plane at k$_z$=$\pi$. We observe broad phonon anomalies in momentum space, pointing to (1) the existence of approximately flat phonon bands which gain some dispersion due to electron renormalization, and (2) the effects of the momentum dependent electron-phonon interaction in the CDW formation. Ab initio and analytical calculations corroborate the experimental findings to indicate that the weak leading order phonon instability is located at the wave vector $\frac{1}{3} \frac{1}{3} \frac{1}{2}$ of a rather flat collapsed mode. We analytically compute the phonon frequency renormalization from high temperatures to the soft mode, and relate it to a peak in the orbital-resolved susceptibility, obtaining an excellent match with both ab initio and experimental results, and explaining the origin of the approximately flat phonon dispersion. Our data report the first example of the collapse of a softening of a flat phonon plane and promote the 166 compounds of the kagome family as primary candidates to explore correlated flat phonon-topological flat electron physics., Comment: 10 pages, 4 figures

Published
2023
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23. Sensitive detection of millimeter wave electric field by driving trapped surface-state electrons

Author

Zhang, Miao, Wang, Y. F., Peng, X. Y., Feng, X. N., He, S. R., Li, Y. F., and Wei, L. F.

Subjects
Quantum Physics
Abstract

Sensitive detection of electromagnetic wave electric field plays an important role for electromagnetic communication and sensing. Here, we propose a quantum sensor to sensitively detect the electric field of the millimeter (mm) wave. The quantum sensor consists of many surface-state electrons trapped individually on liquid helium by a scalable electrode-network at the bottom of the helium film. On such a chip, each of the trapped electrons can be manipulated by the biased dc-current to deliver the strong spin-orbit couplings. The mm wave signal to be detected is applied to non-dispersively drive the orbital states of the trapped electrons, just resulting in the Stark shifts of the dressed spin-orbital states. As a consequence, the electric field of the applied mm wave could be detected sensitively by using the spin-echo interferometry of the long-lived spin states of the electrons trapped on liquid helium. The reasonable accuracy of the detection and also the feasibility of the proposal are discussed., Comment: 8 pages

Published
2023

24. STCF Conceptual Design Report: Volume 1 -- Physics & Detector

Author

Achasov, M., Ai, X. C., Aliberti, R., An, L. P., An, Q., Bai, X. Z., Bai, Y., Bakina, O., Barnyakov, A., Blinov, V., Bobrovnikov, V., Bodrov, D., Bogomyagkov, A., Bondar, A., Boyko, I., Bu, Z. H., Cai, F. M., Cai, H., Cao, J. J., Cao, Q. H., Cao, Z., Chang, Q., Chao, K. T., Chen, D. Y., Chen, H., Chen, H. X., Chen, J. F., Chen, K., Chen, L. L., Chen, P., Chen, S. L., Chen, S. M., Chen, S., Chen, S. P., Chen, W., Chen, X. F., Chen, X., Chen, Y., Chen, Y. Q., Cheng, H. Y., Cheng, J., Cheng, S., Dai, J. P., Dai, L. Y., Dai, X. C., Dedovich, D., Denig, A., Denisenko, I., Ding, D. Z., Dong, L. Y., Dong, W. H., Druzhinin, V., Du, D. S., Du, Y. J., Du, Z. G., Duan, L. M., Epifanov, D., Fan, Y. L., Fang, S. S., Fang, Z. J., Fedotovich, G., Feng, C. Q., Feng, X., Feng, Y. T., Fu, J. L., Gao, J., Ge, P. S., Geng, C. Q., Geng, L. S., Gilman, A., Gong, L., Gong, T., Gradl, W., Gu, J. L., Escalante, A. G., Gui, L. C., Guo, F. K., Guo, J. C., Guo, J., Guo, Y. P., Guo, Z. H., Guskov, A., Han, K. L., Han, L., Han, M., Hao, X. Q., He, J. B., He, S. Q., He, X. G., He, Y. L., He, Z. B., Heng, Z. X., Hou, B. L., Hou, T. J., Hou, Y. R., Hu, C. Y., Hu, H. M., Hu, K., Hu, R. J., Hu, X. H., Hu, Y. C., Hua, J., Huang, G. S., Huang, J. S., Huang, M., Huang, Q. Y., Huang, W. Q., Huang, X. T., Huang, X. J., Huang, Y. B., Huang, Y. S., Hüsken, N., Ivanov, V., Ji, Q. P., Jia, J. J., Jia, S., Jia, Z. K., Jiang, H. B., Jiang, J., Jiang, S. Z., Jiao, J. B., Jiao, Z., Jing, H. J., Kang, X. L., Kang, X. S., Ke, B. C., Kenzie, M., Khoukaz, A., Koop, I., Kravchenko, E., Kuzmin, A., Lei, Y., Levichev, E., Li, C. H., Li, C., Li, D. Y., Li, F., Li, G., Li, H. B., Li, H., Li, H. N., Li, H. J., Li, H. L., Li, J. M., Li, J., Li, L., Li, L. Y., Li, N., Li, P. R., Li, R. H., Li, S., Li, T., Li, W. J., Li, X. H., Li, X. Q., Li, Y., Li, Y. Y., Li, Z. J., Liang, H., Liang, J. H., Liao, G. R., Liao, L. Z., Liao, Y., Lin, C. X., Lin, X. S., Liu, B. J., Liu, C. W., Liu, D., Liu, F., Liu, G. M., Liu, H. B., Liu, J., Liu, J. J., Liu, J. B., Liu, K., Liu, K. Y., Liu, L., Liu, Q., Liu, S. B., Liu, T., Liu, X., Liu, Y. W., Liu, Y., Liu, Y. L., Liu, Z. Q., Liu, Z. Y., Liu, Z. W., Logashenko, I., Long, Y., Lu, C. G., Lu, N., Lü, Q. F., Lu, Y., Lv, Z., Lukin, P., Luo, F. J., Luo, T., Luo, X. F., Lyu, H. J., Lyu, X. R., Ma, J. P., Ma, P., Ma, Y., Maas, F., Malde, S., Matvienko, D., Meng, Z. X., Mitchell, R., Dias, J. M., Nefediev, A., Nefedov, Y., Olsen, S. L., Ouyang, Q., Pakhlov, P., Pakhlova, G., Pan, X., Pan, Y., Passemar, E., Pei, Y. P., Peng, H. P., Peng, L., Peng, X. Y., Peng, X. J., Peters, K., Pivovarov, S., Pyata, E., Qi, B. B., Qi, Y. Q., Qian, W. B., Qian, Y., Qiao, C. F., Qin, J. J., Qin, L. Q., Qin, X. S., Qiu, T. L., Rademacker, J., Redmer, C. F., Sang, H. Y., Saur, M., Shan, W., Shan, X. Y., Shang, L. L., Shao, M., Shekhtman, L., Shen, C. P., Shen, J. M., Shen, Z. T., Shi, H. C., Shi, X. D., Shwartz, B., Sokolov, A., Song, J. J., Song, W. M., Song, Y., Song, Y. X., Sukharev, A., Sun, J. F., Sun, L., Sun, X. M., Sun, Y. J., Sun, Z. P., Tang, J., Tang, S. S., Tang, Z. B., Tian, C. H., Tian, J. S., Tikhonov, Y., Todyshev, K., Uglov, T., Vorobyev, V., Wan, B. D., Wang, B. L., Wang, B., Wang, D. Y., Wang, G. Y., Wang, G. L., Wang, H. L., Wang, J., Wang, J. H., Wang, J. C., Wang, M. L., Wang, R., Wang, S. B., Wang, W., Wang, W. P., Wang, X. C., Wang, X. D., Wang, X. L., Wang, X. P., Wang, X. F., Wang, Y. D., Wang, Y. P., Wang, Y. Q., Wang, Y. L., Wang, Y. G., Wang, Z. Y., Wang, Z. L., Wang, Z. G., Wei, D. H., Wei, X. L., Wei, X. M., Wen, Q. G., Wen, X. J., Wilkinson, G., Wu, B., Wu, J. J., Wu, L., Wu, P. W., Wu, T. W., Wu, Y. S., Xia, L., Xiang, T., Xiao, C. W., Xiao, D., Xiao, M., Xie, Y. H., Xing, Y., Xing, Z. Z., Xiong, X. N., Xu, F. R., Xu, J., Xu, L. L., Xu, Q. N., Xu, X. C., Xu, X. P., Xu, Y. C., Xu, Y. P., Xu, Y., Xu, Z. Z., Xuan, D. W., Xue, F. F., Yan, L., Yan, M. J., Yan, W. B., Yan, W. C., Yan, X. S., Yang, B. F., Yang, C., Yang, H. J., Yang, H. R., Yang, H. T., Yang, J. F., Yang, S. L., Yang, Y. D., Yang, Y. H., Yang, Y. S., Yang, Y. L., Yang, Z. Y., Yao, D. L., Yin, H., Yin, X. H., Yokozaki, N., You, S. Y., You, Z. Y., Yu, C. X., Yu, F. S., Yu, G. L., Yu, H. L., Yu, J. S., Yu, J. Q., Yuan, L., Yuan, X. B., Yue, Y. F., Zeng, M., Zeng, S., Zhang, A. L., Zhang, B. W., Zhang, G. Y., Zhang, G. Q., Zhang, H. J., Zhang, H. B., Zhang, J. Y., Zhang, J. L., Zhang, J., Zhang, L., Zhang, L. M., Zhang, R., Zhang, S. L., Zhang, T., Zhang, X., Zhang, Y., Zhang, Y. X., Zhang, Y. T., Zhang, Y. F., Zhang, Y. C., Zhang, Y. M., Zhang, Y. L., Zhang, Z. H., Zhang, Z. Y., Zhao, H. Y., Zhao, J., Zhao, L., Zhao, M. G., Zhao, Q., Zhao, R. G., Zhao, R. P., Zhao, Z. G., Zhao, Z. X., Zhemchugov, A., Zheng, B., Zheng, L., Zheng, Q. B., Zheng, R., Zheng, Y. H., Zhong, X. H., Zhou, H. J., Zhou, H. Q., Zhou, H., Zhou, S. H., Zhou, X., Zhou, X. K., Zhou, X. R., Zhou, Y. L., Zhou, Y., Zhou, Y. X., Zhou, Z. Y., Zhu, J. Y., Zhu, K., Zhu, R. D., Zhu, R. L., Zhu, S. H., Zhu, Y. C., Zhu, Z. A., Zhukova, V., Zhulanov, V., Zou, B. S., and Zuo, Y. B.

Subjects
High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract

The Super $\tau$-Charm facility (STCF) is an electron-positron collider proposed by the Chinese particle physics community. It is designed to operate in a center-of-mass energy range from 2 to 7 GeV with a peak luminosity of $0.5\times 10^{35}{\rm cm}^{-2}{\rm s}^{-1}$ or higher. The STCF will produce a data sample about a factor of 100 larger than that by the present $\tau$-Charm factory -- the BEPCII, providing a unique platform for exploring the asymmetry of matter-antimatter (charge-parity violation), in-depth studies of the internal structure of hadrons and the nature of non-perturbative strong interactions, as well as searching for exotic hadrons and physics beyond the Standard Model. The STCF project in China is under development with an extensive R\&D program. This document presents the physics opportunities at the STCF, describes conceptual designs of the STCF detector system, and discusses future plans for detector R\&D and physics case studies.

Published
2023
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25. Robust phase metrology with hybrid quantum interferometers against particle losses

Author

Feng, X. N., He, D., and Wei, L. F.

Subjects
Quantum Physics
Abstract

Entanglement is an important quantum resource to achieve high sensitive quantum metrology. However, the rapid decoherence of quantum entangled states, due to the unavoidable environment noise, result in practically the unwanted sharp drop of the measurement sensitivity. To overcome such a difficulty, here we propose a spin-oscillator hybrid quantum interferometer to achieve the desirable precise estimation of the parameter encoded in the vibrations of the oscillator. Differing from the conventional two-mode quantum interferometers input by the two-mode NOON state or entangled coherent states (ECS), whose achievable sensitivities are strongly limited by the decoherence of the entangled vibrational states, we demonstrate that the present interferometer, input by a spin-dependent two-mode entangled state, possesses a manifest advantage, i.e., the measurement sensitivity of the estimated parameter is not influenced by the decoherence from the spin-oscillator entanglement. This is because that, by applying a spin-oscillator disentangled operation, the information of the estimated parameter encoded originally in the vibrational degrees can be effectively transferred into the spin degree and then can be sensitively estimated by the precise spin-state population measurements. As consequence, the proposed hybrid quantum interferometer possesses a manifest robustness against the particle losses of the vibrational modes. Interestingly, the achieved phase measurement sensitivity can still surpass the SQL obviously, even if relatively large number of particle loss occurs in one of the two modes. The potential application of the proposed spin-oscillator hybrid quantum interferometer is also discussed.

Published
2023
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26. Commensurate-to-incommensurate transition of charge-density-wave order and a possible quantum critical point in pressurized kagome metal CsV$_3$Sb$_5$

Author

Feng, X. Y., Zhao, Z., Luo, J., Yang, J., Fang, A. F., Yang, H. T., Gao, H. J., Zhou, R., and Zheng, Guo-qing

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Superconductivity
Abstract

Clarifying the interplay between charge density waves (CDWs) and superconductivity is important in the kagome metal CsV$_3$Sb$_5$, and pressure ($P$) can play a crucial role. Here, we present $^{121/123}$Sb nuclear quadrupole resonance (NQR) measurements under hydrostatic pressures up to 2.43 GPa in CsV$_3$Sb$_5$ single crystals. We demonstrate that the CDW gradually changes from a commensurate modulation with a star-of-David (SoD) pattern to an incommensurate one with a superimposed SoD and Tri-hexagonal (TrH) pattern stacking along the $c$-axis. Moreover, the linewidth $\delta\nu$ of $^{121/123}$Sb-NQR spectra increases with cooling down to $T_{\rm CDW}$, indicating the appearance of a short-range CDW order due to CDW fluctuations pinned by quenched disorders. The $\delta\nu$ shows a Curie-Weiss temperature dependence and tends to diverge at $P_{\rm c} \sim$ 1.9 GPa, suggesting that a CDW quantum critical point (QCP) exists at $P_{\rm c}$ where $T_{\rm c}$ shows the maximum. For $P > P_{\rm c}$, spin fluctuations are enhanced when the CDW is suppressed. Our results suggest that the maximal $T_{\rm c}$ at $P_{\rm c} \sim$ 1.9 GPa is related to the CDW QCP and the presence of spin fluctuations prevent the $T_{\rm c}$ from a rapid decrease otherwise after the CDW is completely suppressed., Comment: 17 pages, 8 figures

Published
2023
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27. The Mechanism of Catalpol to Improve Oxidative Damage of Dermal Fibroblasts Based on Nrf2/HO-1 Signaling Pathway

Author

Lang X, Xu L, Li L, and Feng X

Subjects
catalpol, oxidative damage, nrf2/ho-1, dermal fibroblasts, oxidative stress, Therapeutics. Pharmacology, RM1-950
Abstract

Xiaona Lang,1 Liyan Xu,2 Lu Li,1 Xin Feng1 1Pharmacy Department, Tianjin Hospital, Tianjin, People’s Republic of China; 2Orthopedic Department, Tianjin Hospital, Tianjin, People’s Republic of ChinaCorrespondence: Xin Feng, Pharmacy Department, Tianjin Hospital, Tianjin, People’s Republic of China, Tel +86-13652001152, Email fx_yutong@126.comObjective: Catalpol, as a natural medicine small-molecule drug, has been proven to have anti-inflammatory and antioxidant pharmacological effects.Methods: The effect of catalpol on oxidative damage of mouse epidermal fibroblast L929 model and its mechanism were investigated by using hydrogen peroxide model, CCK8 method, flow cytometry, and Western blot.Results: The effect of catalpol on Nrf2/HO-1 signaling pathway was further studied to improve oxidative stress in cell models. The results showed that catalpol had no cytotoxicity to L929 cells, and inhibited the apoptosis of L929 cells after oxidative damage in a concentration-dependent manner, thus playing a role in cell protection. The oxidative damage of cells was inhibited by up-regulating the expression of the signature protein of Nrf2/HO-1 signaling pathway and inhibiting the interstitial formation of cells.Conclusion: This study is a preliminary study on the protective function of catalpol against oxidation and apoptosis in dermal fibroblasts, which can provide a theoretical basis and drug guidance for promoting skin wound healing in the later stage.Keywords: catalpol, oxidative damage, Nrf2/HO-1, dermal fibroblasts, oxidative stress

Published
2024

28. Strategies and Recent Advances on Improving Efficient Antitumor of Lenvatinib Based on Nanoparticle Delivery System

Author

Wang H, Bo W, Feng X, Zhang J, Li G, and Chen Y

Subjects
lenvatinib, nano-drug delivery system, antitumor, side effects, diagnosis, Medicine (General), R5-920
Abstract

Haiqing Wang,1,&ast; Wentao Bo,1,&ast; Xielin Feng,1 Jinliang Zhang,1 Ge Li,2 Yan Chen3 1Department of Hepatopancreatobiliary Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, People’s Republic of China; 2Department of Emergency, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, People’s Republic of China; 3Department of Pharmacy, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yan Chen; Ge Li, Email cyfy1112@163.com; chenyanyaoxuebu@scszlyy.org.cn; 13982129787@qq.comAbstract: Lenvatinib (LVN) is a potentially effective multiple-targeted receptor tyrosine kinase inhibitor approved for treating hepatocellular carcinoma, metastatic renal cell carcinoma and thyroid cancer. Nonetheless, poor pharmacokinetic properties including poor water solubility and rapid metabolic, complex tumor microenvironment, and drug resistance have impeded its satisfactory therapeutic efficacy. This article comprehensively reviews the uses of nanotechnology in LVN to improve antitumor effects. With the characteristic of high modifiability and loading capacity of the nano-drug delivery system, an active targeting approach, controllable drug release, and biomimetic strategies have been devised to deliver LVN to target tumors in sequence, compensating for the lack of passive targeting. The existing applications and advances of LVN in improving therapeutic efficacy include improving longer-term efficiency, achieving higher efficiency, combination therapy, tracking and diagnosing application and reducing toxicity. Therefore, using multiple strategies combined with photothermal, photodynamic, and immunoregulatory therapies potentially overcomes multi-drug resistance, regulates unfavorable tumor microenvironment, and yields higher synergistic antitumor effects. In brief, the nano-LVN delivery system has brought light to the war against cancer while at the same time improving the antitumor effect. More intelligent and multifunctional nanoparticles should be investigated and further converted into clinical applications in the future. Keywords: lenvatinib, nano-drug delivery system, antitumor, side effects, diagnosis

Published
2024

29. Applications of Graphene Family Nanomaterials in Regenerative Medicine: Recent Advances, Challenges, and Future Perspectives

Author

Chen X, Zou M, Liu S, Cheng W, Guo W, and Feng X

Subjects
graphene, graphene oxide, regenerative medicine, scaffold, anti-inflammatory, bone regeneration, nerve, angiogenesis, dental pulp stem cells, Medicine (General), R5-920
Abstract

Xiuwen Chen,1,&ast; Meiyan Zou,1,&ast; Siquan Liu,1 Weilin Cheng,1 Weihong Guo,2 Xiaoli Feng1 1Stomatology Hospital, School of Stomatology, Southern Medical University, Guangzhou, People’s Republic of China; 2Department of General Surgery, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Weihong Guo; Xiaoli Feng, Email drguowh@163.com; dentistfxl226@163.comAbstract: Graphene family nanomaterials (GFNs) have attracted considerable attention in diverse fields from engineering and electronics to biomedical applications because of their distinctive physicochemical properties such as large specific surface area, high mechanical strength, and favorable hydrophilic nature. Moreover, GFNs have demonstrated the ability to create an anti-inflammatory environment and exhibit antibacterial effects. Consequently, these materials hold immense potential in facilitating cell adhesion, proliferation, and differentiation, further promoting the repair and regeneration of various tissues, including bone, nerve, oral, myocardial, and vascular tissues. Note that challenges still persist in current applications, including concerns regarding biosecurity risks, inadequate adhesion performance, and unsuitable degradability as matrix materials. This review provides a comprehensive overview of current advancements in the utilization of GFNs in regenerative medicine, as well as their molecular mechanism and signaling targets in facilitating tissue repair and regeneration. Future research prospects for GFNs, such as potential in promoting ocular tissue regeneration, are also discussed in details. We hope to offer a valuable reference for the clinical application of GFNs in the treatment of bone defects, nerve damage, periodontitis, and atherosclerosis. Keywords: graphene, graphene oxide, regenerative medicine, scaffold, anti-inflammatory, bone regeneration, nerve, angiogenesis, dental pulp stem cells

Published
2024

30. Ligusticum chuanxiong Hort. Ameliorates Neuropathic Pain by Regulating Microglial M1 Polarization: A Study Based on Network Pharmacology

Author

Cui S, Feng X, and Xia Z

Subjects
neuropathic pain, ligusticum chuanxiong hort., network pharmacology, molecular docking, microglia, inflammation, Medicine (General), R5-920
Abstract

Shanshan Cui,1 Xiaobo Feng,2 Zhongyuan Xia1 1Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, People’s Republic of China; 2Department of Anesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei Province, People’s Republic of ChinaCorrespondence: Zhongyuan Xia, Department of Anesthesiology, Renmin Hospital of Wuhan University, Ziyang Road, Wuchang District, Wuhan, Hubei Province, People’s Republic of China, Email xiazhongyuan2005@aliyun.comBackground: In traditional Chinese medicine, Ligusticum chuanxiong Hort. (LCH) is used to treat neuropathic pain (NP). This study was performed to investigate the underlying pharmacological mechanisms.Methods: The main components of the LCH were obtained from the TCMSP database. The targets of the active components were obtained using the Swiss Target Prediction database and HERB database. The NP-related genes were obtained from the CTD database and GeneCard database. Protein-protein interaction (PPI) network was constructed using the STRING platform and Cytoscape 3.9.0 software. GO and KEGG enrichment analyses were performed using the DAVID database. Interactions between the key components and hub target proteins were verified using molecular docking and molecular dynamics simulation. In addition, microglial cell line HMC3 was induced to polarize to the M1 phenotype using 100 ng/mL lipopolysaccharide (LPS). Quantitative real-time polymerase chain reaction (qRT-PCR), Western blot and enzyme-linked immunosorbent assays were used to detect the expression levels of M1 markers and inflammatory factors, respectively.Results: Seven LCH active components of LCH were identified, corresponding to 387 target genes. 2019 NP-related genes were obtained, and a total of 174 NP-related genes were identified as target genes that could be modulated by LCH. Beta-sitosterol, senkyunone, wallichilide, myricanone, and mandenol were considered as the key components of LCH in the treatment of NP. SRC, BCL2, AKT1, HIF1A and HSP90AA1 were identified as the hub target proteins. GO analysis showed that 328 biological processes, 61 cell components, and 85 molecular functions were likely modulated by the components of LCH, and KEGG enrichment analysis showed that 132 signaling pathways were likely modulated by the components of LCH. Beta-sitosterol, senkyunone, wallichilide, myricanone, and mandenol showed good binding activity with hub target proteins including SRC, BCL2, AKT1, and HSP90AA1. In addition, beta-sitosterol inhibited LPS-induced M1 polarization in HMC3 in vitro.Conclusion: This study provides a theoretical basis for the application of LCH in the treatment of NP through multicomponent, multitarget, and multiple pathways.Keywords: neuropathic pain, Ligusticum chuanxiong Hort., network pharmacology, molecular docking, microglia, inflammation

Published
2024

31. Strong Homology Between Colonizing and Bloodstream Carbapenem-Resistant Acinetobacter Spp.: Implications for Empiric Antibiotic Therapy in Hematological Patients

Author

Li J, Guo W, Wang J, Feng X, Lin Q, Zheng Y, Zhang F, Mi Y, Zhu X, Jiang E, Xiao Z, and Feng S

Subjects
acinetobacter, colonization, bloodstream infections, homology, therapy, carbapenem-resistant, Infectious and parasitic diseases, RC109-216
Abstract

Jia Li,1,2 Wenjing Guo,1,2 Jieru Wang,1,2 Xiaomeng Feng,1,2 Qingsong Lin,1,2,&ast; Yizhou Zheng,1,2 Fengkui Zhang,1,2 Yingchang Mi,1,2 Xiaofan Zhu,1,2 Erlie Jiang,1,2 Zhijian Xiao,1,2 Jianxiang Wang,1,2 Sizhou Feng1,2,&ast; 1State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, People’s Republic of China; 2Tianjin Institutes of Health Science, Tianjin, 301600, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Sizhou Feng, Hematopoietic Stem Cell Transplantation Center, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 288 Nanjing Road, Tianjin, 300020, People’s Republic of China, Tel +86-022-23909162, Fax +022-23909047, Email doctor_szhfeng@163.com; szfeng@ihcams.ac.cnObjective: This study aimed to assess the impact of colonization status on the outcomes of Acinetobacter spp. bloodstream infection (BSI) and investigate the homology and within-host evolution between colonizing and bloodstream carbapenem-resistant Acinetobacter spp. (CRA) to inform antibiotic therapeutic decisions.Methods: We analyzed clinical outcomes of 46 hematological patients with Acinetobacter spp. BSI and performed whole-genome sequencing on the remaining CRA isolates.Results: Among the patients, 39.1% (n=18) had prior Acinetobacter spp. colonization. Colonized patients had higher rates of polymicrobial BSI (50.0% vs 21.4%, P=0.044) and CRA BSI (72.2% vs 17.9%, P< 0.001), resulting in elevated inflammatory markers and increased 30-day mortality. Each of the eight pairs of the remaining respiratory colonizing and bloodstream CRA strains belonged to the same genomospecies. Each pair exhibited definitive agreement in at least 21 of the 22 most representative antibiotic susceptibility tests. The minimum spanning tree based on multilocus sequence typing (MLST) and phylogenetic trees based on MLST and single nucleotide polymorphism (SNP) all indicated that each pair shared the same minimum branch. Very few non-synonymous SNPs in genic regions were identified during the transition from respiratory colonization to bloodstream infection, with minimal changes in virulence genes. Homology analysis suggested that CRA BSI originated from colonizing isolates in the respiratory tract.Conclusion: Strict infection control measures are needed to manage Acinetobacter spp. colonisation in hematological patients. Appropriate empirical therapy can be administered for suspected CRA BSI based on the antimicrobial minimum inhibitory concentration of CRA colonising the respiratory tract.Keywords: Acinetobacter, colonization, bloodstream infections, homology, therapy, carbapenem-resistant

Published
2024

32. Lactic Acid Chemical Peeling in Skin Disorders

Author

Feng X, Shang J, Gu Z, Luo X, Chen Y, and Liu Y

Subjects
lactic acid, physiological activities, clinical applications, chinese skin, Dermatology, RL1-803
Abstract

Xiaoyue Feng,&ast; Jianli Shang,&ast; Zhengping Gu, Xingyi Luo, Yong Chen, Youting Liu Product Research & Development Center, Beijing Underproved Medical Technology Co., LTD, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Youting Liu, Product Research & Development Center, Beijing Underproved Medical Technology Co., LTD, Beijing, 102699, People’s Republic of China, Tel +86 1 851 025 6963, Email YtLiu.adpt@outlook.comAbstract: Lactic acid is the most widely occurring natural organic acid in nature. It not only exhibits mild and safe properties but also possesses multiple physiological activities, such as antibacterial effects, immune regulation, and promotion of wound healing, making it one of the most popular chemical peeling agents. Chemical peels are commonly used in the field of aesthetic dermatology as a non-invasive therapeutic approach. This research aims to provide valuable references for clinical dermatologists by summarizing the characteristics of lactic acid, elucidating its mechanism of action in peeling, and investigating the clinical applications of this compound. Furthermore, it anticipates the potential for lactic acid to be the most suitable chemical peeling agent for Chinese skin.Keywords: lactic acid, physiological activities, clinical applications, Chinese skin

Published
2024

34. Analyses of Flight Time During Solar Proton Events and Solar Flares

Author

Xu, X. H., Wang, Y., Wei, F. S., Feng, X. S., Bo, M. H., Tang, H. W., Wang, D. S., Lei, B., Wang, B. Y., Zuo, P. B., Jiang, C. W., Xu, X. J., Zhou, Z. L., Li, Z., Zou, P., Wang, L. D., Gu, Y. X., Chen, Y. L., Zhang, W. Y., and Sun, P.

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, Physics - Space Physics
Abstract

Analyzing the effects of space weather on aviation is a new and developing topic. It has been commonly accepted that the flight time of the polar flights may increase during solar proton events because the flights have to change their route to avoid the high-energy particles. However, apart from such phenomenon, researches related to the flight time during space weather events is very rare. Based on the analyses of 39 representative international air routes around westerlies, it is found that 97.44% (94.87%) of the commercial airplanes on the westbound (eastbound) air routes reveal shorter (longer) flight time during solar proton events compared to those during quiet periods, and the averaged magnitude of change in flight time is ~10 min or 0.21%-4.17% of the total flight durations. Comparative investigations reassure the certainty of such phenomenon that the directional differences in flight time are still incontrovertible regardless of over-land routes (China-Europe) or over-sea routes (China-Western America). Further analyses suggest that the solar proton events associated atmospheric heating will change the flight durations by weakening certain atmospheric circulations, such as the polar jet stream. While the polar jet stream will not be obviously altered during solar flares so that the directional differences in flight time are not found. Besides the conventional space weather effects already known, this paper is the first report that indicates a distinct new scenario of how the solar proton events affect flight time. These analyses are also important for aviation since our discoveries could help the airways optimize the air routes to save passenger time costs, reduce fuel costs and even contribute to the global warming issues., Comment: submitted to Scientific Reports

Published
2022

35. Characteristics of Flight Delays during Solar Flares

Author

Xu, X. H., Wang, Y., Wei, F. S., Feng, X. S., Bo, M. H., Tang, H. W., Wang, D. S., Bian, L., Wang, B. Y., Zhang, W. Y., Huang, Y. S., Li, Z., Guo, J. P., Zuo, P. B., Jiang, C. W., Xu, X. J., Zhou, Z. L., and Zou, P.

Subjects
Astrophysics - Solar and Stellar Astrophysics, Physics - Space Physics
Abstract

Solar flare is one of the severest solar activities on the sun, and it has many important impacts on the near-earth space. It has been found that flight arrival delays will increase during solar flare. However, the detailed intrinsic mechanism of how solar flares influence the delays is still unknown. Based on 5-years huge amount of flight data, here we comprehensively analyze the flight departure delays during 57 solar flares. It is found that the averaged flight departure delay time during solar flares increased by 20.68% (7.67 min) compared to those during quiet periods. It is also shown that solar flare related flight delays reveal apparent time and latitude dependencies. Flight delays during dayside solar flares are more serious than those during nightside flares, and the longer (shorter) delays tend to occur in the lower (higher) latitude airport. Further analyses suggest that flight delay time and delay rate would be directly modulated by the solar intensity (soft X-ray flux) and the Solar Zenith Angle. For the first time, these results indicate that the communication interferences caused by solar flares will directly affect flight departure delay time and delay rate. This work also expands our conventional understandings to the impacts of solar flares on human society, and it could also provide us with brand new views to help prevent or cope with flight delays., Comment: submitted to APJL

Published
2022

36. The Effects of Space Weather on Flight Delays

Author

Wang, Y., Xu, X. H., Wei, F. S., Feng, X. S., Bo, M. H., Tang, H. W., Wang, D. S., Bian, L., Wang, B. Y., Zhang, W. Y., Huang, Y. S., Li, Z., Guo, J. P., Zuo, P. B., Jiang, C. W., Xu, X. J., Zhou, Z. L., and Zou, P.

Subjects
Astrophysics - Solar and Stellar Astrophysics, Physics - Space Physics
Abstract

Although the sun is really far away from us, some solar activities could still influence the performance and reliability of space-borne and ground-based technological systems on Earth. Those time-varying conditions in space caused by the sun are also called space weather, as the atmospheric conditions that can affect weather on the ground. It is known that aviation activities can be affected during space weather events, but the exact effects of space weather on aviation are still unclear. Especially how the flight delays, the top topic concerned by most people, will be affected by space weather has never been thoroughly researched. By analyzing huge amount of flight data (~5X106 records), for the first time, we demonstrate that space weather events could have systematically modulating effects on flight delays. The average arrival delay time and 30-minute delay rate during space weather events are significantly increased by 81.34% and 21.45% respectively compared to those during quiet periods. The evident negative correlation between the yearly flight regularity rate and the yearly mean total sunspot number during 22 years also confirms such delay effects. Further studies indicate that the interference in communication and navigation caused by geomagnetic field fluctuations and ionospheric disturbances associated with the space weather events will increase the flight delay time and delay rate. These results expand the traditional field of space weather research and could also provide us with brand new views for improving the flight delay predications., Comment: submitted to science advances

Published
2022

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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40. Effect of Diabetes on Wound Healing: A Bibliometrics and Visual Analysis

Author

Lang X, Li L, Li Y, and Feng X

Subjects
diabetes, wound healing, bibliometrics, visualized analysis；citespace, Medicine (General), R5-920
Abstract

Xiaona Lang,1 Lu Li,1 Yuntao Li,2 Xin Feng1 1Pharmacy Department, Tianjin Hospital, Tianjin, People’s Republic of China; 2Integrative Chinese and Western Medicine Department, Tianjin Hospital, Tianjin, People’s Republic of ChinaCorrespondence: Xin Feng, Pharmacy Department, Tianjin Hospital, Tianjin, People’s Republic of China, Tel +86-13652001152, Email fx_yutong@126.comObjective: The quality of life of diabetic patients is seriously affected by wound healing difficulty, which can lead to increased infection, skin deep tissue injury and continuous pain. By analyzing the research trends and hot spots in this field, the visualization analysis map is constructed.Methods: The contents of the selected articles were sorted out and analyzed by bibliometrics. We use CiteSpace, Vosviewer and HistCite to visualize literature information, including national publication statistics, institutions, authors, journal partnerships, and citations of published articles.Results: Among the 2942 articles, the United States and China ranked first in both article circulation and TGCS, and many countries also cooperated. The collaboration between schools and research institutions is a core part of dissertation research institution collaboration, with most authors coming from the same institution. Most of the literature studies on the mechanisms and methods of promoting diabetic wound healing. Improving cell function or making innovative attempts in local treatment are the fruits of researchers’ efforts to promote diabetic wound healing in recent years.Conclusion: Through the metrology method, the time distribution, author institution, cooperation network, research status, research hotspot and development trend of the literature on the influence of diabetes on wound healing were intuitively displayed, which provided a reference for further research and development direction.Keywords: diabetes, wound healing, bibliometrics, visualized analysis, Citespace

Published
2024

41. Risk Factors for Postoperative Cognitive Decline After Orthopedic Surgery in Elderly Chinese Patients: A Retrospective Cohort Study

Author

Li X, Lai H, Wang P, Feng S, Feng X, Kong C, Wu D, Yin C, Shen J, Yan S, Han R, Liu J, Ren X, Li Y, Tang L, Xue D, Zhao Y, Huang H, Zhang Y, Wang X, Wang C, Jin P, Lu S, Wang T, and Zhao G

Subjects
cognitive dysfunction, postoperative cognitive complications, orthopedic surgery, comprehensive geriatric assessment, risk factors, Geriatrics, RC952-954.6
Abstract

Xian Li,1,&ast; Hong Lai,2,&ast; Peng Wang,3 Shuai Feng,4 Xuexin Feng,4 Chao Kong,3 Dewei Wu,5 Chunlin Yin,5 Jianghua Shen,6 Suying Yan,6 Rui Han,7 Jia Liu,7 Xiaoyi Ren,8 Ying Li,8 Lu Tang,9 Dong Xue,9 Ying Zhao,9 Hao Huang,10 Xiaoying Li,10 Yanhong Zhang,10 Xue Wang,11 Chunxiu Wang,12 Ping Jin,13 Shibao Lu,3 Tianlong Wang,4 Guoguang Zhao,14 Chaodong Wang1 On behalf of the APPLE-MDT Research Team, Xuanwu Hospital, Capital Medical University and National Clinical Research Center for Geriatric Diseases1Department of Neurology & Neurobiology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, People’s Republic of China; 2Department of Neurology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, People’s Republic of China; 3Department of Orthopedic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 4Department of Anesthesiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 5Department of Cardiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 6Department of Pharmacy, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 7Department of Gerontology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 8Department of Nutrition, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 9Department of Oral Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 10Department of Medical Administration, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 11Department of Medical Library, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 12Center for Evidence-Based Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 13Center for Medical Information, Xuanwu Hospital, Capital Medical University, Beijing, 100053, People’s Republic of China; 14Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, 100053, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Chaodong Wang, Department of Neurology, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, No. 45 Changchun Street, Beijing, 100053, People’s Republic of China, Tel/Fax +86-10-8319-8677, Email cdongwang@xwhosp.orgPurpose: We aimed to identify the risk factors for postoperative cognitive decline (POCD) by evaluating the outcomes from preoperative comprehensive geriatric assessment (CGA) and intraoperative anesthetic interventions.Patients and Methods: Data used in the study were obtained from the Aged Patient Perioperative Longitudinal Evaluation–Multidisciplinary Trial (APPLE-MDT) cohort recruited from the Department of Orthopedics in Xuanwu Hospital, Capital Medical University between March, 2019 and June, 2022. All patients accepted preoperative CGA by the multidisciplinary team using 13 common scales across 15 domains reflecting the multi-organ functions. The variables included demographic data, scales in CGA, comorbidities, laboratory tests and intraoperative anesthetic data. Cognitive function was assessed by Montreal Cognitive Assessment scale within 48 hours after admission and after surgery. Dropping of ≥ 1 point between the preoperative and postoperative scale was defined as POCD.Results: We enrolled 119 patients. The median age was 80.00 years [IQR, 77.00, 82.00] and 68 patients (57.1%) were female. Forty-two patients (35.3%) developed POCD. Three cognitive domains including calculation (P = 0.046), recall (P = 0.047) and attention (P = 0.007) were significantly worsened after surgery. Univariate analysis showed that disability of instrumental activity of daily living, incidence rate of postoperative respiratory failure (PRF) ≥ 4.2%, STOP-Bang scale score, Caprini risk scale score and Sufentanil for maintenance of anesthesia were different between the POCD and non-POCD patients. In the multivariable logistic regression analysis, PRF ≥ 4.2% (odds ratio [OR] = 2.343; 95% confidence interval [CI]: 1.028– 5.551; P = 0.046) and Sufentanil for maintenance of anesthesia (OR = 0.260; 95% CI: 0.057– 0.859; P = 0.044) was independently associated with POCD as risk and protective factors, respectively.Conclusion: Our study suggests that POCD is frequent among older patients undergoing elective orthopedic surgery, in which decline of calculation, recall and attention was predominant. Preoperative comprehensive geriatric assessments are important to identify the high-risk individuals of POCD.Keywords: cognitive dysfunction, postoperative cognitive complications, orthopedic surgery, comprehensive geriatric assessment, risk factors

Published
2024

42. Predictive Value of MHR and NLR for Ulcerative Colitis Disease Activity

Author

Liu T, Qin Z, Yang Z, and Feng X

Subjects
ulcerative colitis, monocyte/hdl ratio, neutrophil/lymphocyte ratio, disease activity, Medicine (General), R5-920
Abstract

Tian Liu, Zhenkun Qin, Zhiyue Yang, Xiaoling Feng Division of General Practice, The Fifth Affiliated Hospital of Xinjiang Medical University, Urumqi, People’s Republic of ChinaCorrespondence: Xiaoling Feng, Division of General Practice, The Fifth Affiliated Hospital of Xinjiang Medical University, No. 118, Henan West Road, Urumqi, Xinjiang Uygur Autonomous Region, 830011, People’s Republic of China, Email 1874519696@qq.comBackground: Numerous non-invasive serologic tests are available to diagnose and monitor ulcerative colitis (UC), but their accuracy levels are limited. Thus, there is a pressing need for a serologic biomarker with higher precision for clinical practice. This study aims to evaluate the predictive capacity of monocyte/HDL ratio (MHR) and neutrophil/lymphocyte ratio (NLR) for UC disease activity.Patients and Methods: We conducted a retrospective analysis of 81 UC patients and 77 age- and sex-matched healthy controls. UC patients were categorized into active and inactive groups based on the Mayo score. The Mayo endoscopic subscore classified them into mild-to-moderate and severe UC groups.Results: The optimal cut-off values for diagnosing UC were 0.34 for MHR (85.7% sensitivity, 76.0% specificity, 88.9% positive predictive value, 70.4% negative predictive value) and 2.49 for NLR (66.1% sensitivity, 88.0% specificity, 92.5% positive predictive value, 53.7% negative predictive value). The optimal MHR and NLR cut-off values to differentiate between mild-to-moderate UC and severe UC were 0.38 (92.9% sensitivity, 56.6% specificity, 53.1% positive predictive value, 93.7% negative predictive value) and 3.46 (71.4% sensitivity, 88.7% specificity, 76.9% positive predictive value, 85.5% negative predictive value), respectively.Conclusion: NLR and MHR are simple yet effective biological predictors of disease activity in UC patients.Keywords: ulcerative colitis, monocyte/HDL ratio, neutrophil/lymphocyte ratio, disease activity

Published
2024

43. Bioinformatics Analysis and Experimental Validation of Mitochondrial Autophagy Genes in Knee Osteoarthritis

Author

Tang K, Sun L, Chen L, Feng X, Wu J, Guo H, and Zheng Y

Subjects
gene expression omnibus, diagnostic, bioinformatics analysis, immune infiltration, biomarkers, Medicine (General), R5-920
Abstract

Kuihan Tang,1 Li Sun,2 Long Chen,2 Xiaobo Feng,1 Jiarui Wu,2 Hao Guo,2 Yong Zheng1 1Department of Orthopedics, Beijing Jishuitan Hospital Guizhou Hospital, Guiyang, 550014, People’s Republic of China; 2Department of Orthopedics, Guizhou Provincial People’s Hospital, Guiyang, 550000, People’s Republic of ChinaCorrespondence: Yong Zheng, Email 1210244258@qq.comBackground: Mitochondrial autophagy is closely related to the pathogenesis of osteoarthritis, In order to explore the role of mitochondrial autophagy related genes in knee osteoarthritis (KOA) and its molecular mechanism.Methods: KOA-related transcriptome data were extracted from the Gene Expression Omnibus (GEO) database. Differentially expressed mitochondrial autophagy gene (DEMGs) were screened in patients with KOA by differential expression analysis. The STRING website was used to construct a protein-protein interaction (PPI) network among DEMGs. Molecular complex detection (MCODE) method in Cytoscape software was performed to identify hub DEMGs. Support vector machine recursive feature elimination (SVM-RFE) method was used to construct the hub DEMG diagnosis model. Genes with diagnostic value were identified as biomarkers by plotting receiver operating characteristic (ROC) curves and Expression validation. CIBERSORT algorithm was used to calculate the proportion of 22 immune cells in each sample in the GSE114007 dataset. Finally, biomarker expression was verified by qPCR.Results: A total of 15 DEMGs were obtained and enrichment analyses showed that these DEMG strains were mainly enriched in the mitophagy-animal, shigellosis, autophagy-animal and FoxO signal pathways. The PPI network unveiled 13 DEMGs with interactions. In addition, 8 hub DEMGs (ULK1, CALCOCO2, MAP1LC3B, BNIP3L, GABARAPL1, BNIP3, FKBP8 and FOXO3) were obtained for KOA. And 5 model DEMGs (BNIP3L, BNIP3, MAP1LC3B, ULK1 and FOXO3) were screened. The ROC curves revealed that BNIP3 and FOXO3 has strong diagnostic value in these models of DEMG. Immune-infiltration and correlation analysis showed that BNIP3 and FOXO3 were significantly correlated with three different immune cells, including primary B cells, M0 macrophage and M2 macrophage. The cartilage tissue samples qPCR verification results show that FOXO3 and BNIP3 were all down-regulated in KOA (p < 0.01), and the validation results are consistent with the above analysis.Conclusion: BNIP3 and FOXO3 have been identified as biomarkers for the diagnosis of KOA, which might supply a new insight for the pathogenesis and treatment of KOA.Keywords: Gene Expression Omnibus, diagnostic, bioinformatics analysis, immune infiltration, biomarkers

Published
2024

44. Opportunities and Challenges for Inhalable Nanomedicine Formulations in Respiratory Diseases: A Review

Author

Feng X, Shi Y, Zhang Y, Lei F, Ren R, and Tang X

Subjects
nanoparticles, respiratory system, lungs, nanomaterials, nanotechnology, Medicine (General), R5-920
Abstract

Xujun Feng, Yuan Shi, Ye Zhang, Fei Lei, Rong Ren, Xiangdong Tang Department of Respiratory and Critical Care Medicine, Sleep Medicine Center, Mental Health Center, West China Hospital, Sichuan University, Chengdu, People’s Republic of ChinaCorrespondence: Rong Ren; Xiangdong Tang, Department of Respiratory and Critical Care Medicine, Sleep Medicine Center, Mental Health Center, West China Hospital, Sichuan University, Dian Xin Nan Jie 28&num;, Chengdu, 610041, People’s Republic of China, Tel +86-28-85422733, Email 498880651@qq.com; 2372564613@qq.comAbstract: Lungs experience frequent interactions with the external environment and have an abundant supply of blood; therefore, they are susceptible to invasion by pathogenic microorganisms and tumor cells. However, the limited pharmacokinetics of conventional drugs in the lungs poses a clinical challenge. The emergence of different nano-formulations has been facilitated by advancements in nanotechnology. Inhaled nanomedicines exhibit better targeting and prolonged therapeutic effects. Although nano-formulations have great potential, they still present several unknown risks. Herein, we review the (1) physiological anatomy of the lungs and their biological barriers, (2) pharmacokinetics and toxicology of nanomaterial formulations in the lungs; (3) current nanomaterials that can be applied to the respiratory system and related design strategies, and (4) current applications of inhaled nanomaterials in treating respiratory disorders, vaccine design, and imaging detection based on the characteristics of different nanomaterials. Finally, (5) we analyze and summarize the challenges and prospects of nanomaterials for respiratory disease applications. We believe that nanomaterials, particularly inhaled nano-formulations, have excellent prospects for application in respiratory diseases. However, we emphasize that the simultaneous toxic side effects of biological nanomaterials must be considered during the application of these emerging medicines. This study aims to offer comprehensive guidelines and valuable insights for conducting research on nanomaterials in the domain of the respiratory system. Keywords: nanoparticles, respiratory system, lungs, nanomaterials, nanotechnology

Published
2024

45. Clinical Characteristics, Prenatal Diagnosis and Outcomes of Placenta Accreta Spectrum in Different Placental Locations: A Retrospective Cohort Study

Author

Feng X, Mao X, and Zhao J

Subjects
placenta accreta spectrum, placenta location, clinical characteristics, perinatal outcomes, Gynecology and obstetrics, RG1-991
Abstract

Xiaoling Feng,1 Xun Mao,1 Jianlin Zhao2,3 1Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, People’s Republic of China; 2The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China; 3Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, People’s Republic of ChinaCorrespondence: Jianlin Zhao; Xun Mao, Email zjlchongqing@gmail.com; maoxun@hospital.cqmu.edu.cnObjective: To explore the prenatal diagnosis, clinical characteristics, and perinatal outcomes of placenta accreta spectrum in different placental locations.Methods: This was a retrospective cohort study. Pregnant women who delivered at two tertiary referral hospitals from January 2013 to December 2022 and were ultimately pathologically diagnosed with placenta accreta spectrum were included. They were divided into three groups based on different placental locations (anterior, posterior, and lateral wall/fundus). The differences in prenatal diagnosis, clinical characteristics, and perinatal outcomes among the three groups were compared.Results: There were 115,470 deliveries in a ten-year period at the two hospitals, and 118 case patients were confirmed to have a pathologically diagnosed placenta accreta spectrum. The posterior placenta group had a lower rate of placenta previa (76.9% vs 94.9% vs 100%, p< 0.05) and a higher gestational age at delivery (36.4± 2.45 vs 34.91± 1.76 vs 34.31± 3.41, p< 0.05) compared to the other two groups. The anterior placenta group had a significantly higher rate of invasive (increta/percreta) form placenta accreta spectrum (81.4% vs 36.5% vs 28.6%, p< 0.05) and planned cesarean section (96.6% vs 80.8% vs 71.4%, p< 0.05) compared to the other two groups. In terms of prenatal diagnosis, the anterior placenta group had a significantly higher rate of placenta accreta spectrum prenatal suspicion rate compared to the other two groups (86.4% vs 36.5% vs 57.1%, p< 0.05). The posterior placenta group had a lower rate of preoperative abdominal aortic balloon placement compared to the other two groups (5.8% vs 28.8% vs 28.6%, p< 0.05). There were no statistically significant differences among the three groups in primary perinatal outcomes, though the anterior placenta group had a longer postoperative hospital stay.Conclusion: The prenatal diagnosis rate and proportion of invasive form of placenta accreta spectrum occurring in non-anterior placenta are relatively lower than anterior placenta. There were no significant differences in major perinatal outcomes among the three groups.Keywords: placenta accreta spectrum, placenta location, clinical characteristics, perinatal outcomes

Published
2024

46. Postoperative Coagulation State Predicts Deep Vein Thrombosis After Cesarean Section in Elderly Pregnant Women

Author

Feng X, Ding L, Zhang S, and Zhang H

Subjects
deep vein thrombosis, cesarean section, coagulation, postpartum women, Gynecology and obstetrics, RG1-991
Abstract

Xiaojie Feng, Lige Ding, Shangzhu Zhang, Huan Zhang Department of Emergency, Shijiazhuang Obstetrics and Gynecology Hospital, Shijiazhuang, Hebei, People’s Republic of ChinaCorrespondence: Lige Ding, Department of Emergency, Shijiazhuang Obstetrics and Gynecology Hospital, Zhongshan Road, Shijiazhuang, 050000, Hebei, People’s Republic of China, Tel +86-13673113998, Email 13673113998@163.comIntroduction: We aimed to evaluate the risk factors for the development of deep vein thrombosis (DVT) within one month after delivery in pregnant women of advanced maternal age undergoing cesarean section and explore the predictive value of fasting coagulation indicators in relation to the development of DVT.Methods: A total of 176 eligible postpartum women were included in this study. Sixty-seven cases developed DVT within one month after delivery (DVT group), while 109 cases did not experience DVT (NDVT group). Within 24 hours after cesarean section, fasting coagulation indicators are measured. Coagulation system analysis was performed using the STA-R Evolution fully automated coagulation analyzer.Results: The women who developed DVT were found to be older, had a higher proportion of women with previous childbirth experiences, and had a higher proportion of women with comorbidities. Our results revealed significant differences in the levels of activated partial thromboplastin time and prothrombin time between the NDVT group and the DVT group. In contrast, the DVT group displayed significantly higher levels of D-dimer, plasma fibrinogen and platelet count when compared to the NDVT group. The AUC for the combined test model was substantially higher compared to individual parameters.Discussion: Multiple parameters of the postoperative coagulation state in the combined test model provided a more accurate prediction of DVT occurrence in elderly pregnant women after cesarean section.Keywords: deep vein thrombosis, cesarean section, coagulation, postpartum women

Published
2024

47. Expression Profiles of Matrix Metalloproteinases and Their Inhibitors in Nasal Polyps

Author

Duan C, Yu X, Feng X, Shi L, and Wang D

Subjects
remodeling, inflammatory cells, extracellular matrix, matrix metalloproteinases, Pathology, RB1-214, Therapeutics. Pharmacology, RM1-950
Abstract

Chen Duan,1 Xuemin Yu,2 Xin Feng,1 Li Shi,3 Deyun Wang4 1Department of Otorhinolaryngology, Qilu Hospital of Shandong University, National Health Commission (NHC) Key Laboratory of Otorhinolaryngology, Shandong University, Jinan, Shandong, 250000, People’s Republic of China; 2Department of Otorhinolaryngology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, NHC Key Laboratory of Otorhinolaryngology (Shandong University), Qingdao, Shandong, 250000, People’s Republic of China; 3Department of Otolaryngology, The Second Hospital of Shandong University, Jinan, Shandong, 250000, People’s Republic of China; 4Department of Otolaryngology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, SingaporeCorrespondence: Li Shi, Department of Otolaryngology, The Second Hospital of Shandong University, Jinan, Shandong, 250000, People’s Republic of China, Email shili126@sina.com Xin Feng, Department of Otorhinolaryngology, Qilu Hospital of Shandong University, National Health Commission (NHC) Key Laboratory of Otorhinolaryngology, Shandong University, Jinan, Shandong, 250000, People’s Republic of China, Email drfengxin@sdu.edu.cnPurpose: Nasal polyp (NP) is characterized by inflammation of the sinonasal mucosa with predominant inflammatory cell infiltration. Matrix metalloproteinases (MMPs) and tissue inhibitor of metalloproteinases (TIMPs) are recognized to play an important role in leukocyte migration in airway inflammation. Herein, efforts were made to confirm the expression levels of MMPs/TIMPs and study the relationship between the infiltration of inflammatory cells and local expression levels of MMPs/TIMPs in NPs.Patients and Methods: NP tissues were obtained from 42 Chinese patients with bilateral nasal polyps during the endoscopic sinus surgery. Inferior turbinate (IT) tissues from 19 patients with septal deviation were taken during the rhinoplasty surgery as controls. mRNA and protein levels of MMP1, MMP9, MMP10, MMP12, TIMP1 and TIMP3 were assessed by quantitative PCR and immunohistochemistry.Results: Eosinophilia (72%, 23/32 samples), neutrophilia (41%, 13/32 samples), and increase in macrophages (38%, 12/32 samples) were found in NP tissues. mRNA expression of MMP1 (10.9-fold), MMP9 (4.1-fold), MMP10 (6.7-fold) and MMP12 (3.5-fold) were significantly up-regulated, while TIMP1 (1.5-fold) and TIMP3 (6.0-fold) were significantly down-regulated in NPs (n=42) as compared to the controls (n=19). The immunostaining levels of all 4 MMPs and two TIMPs were higher in NPs than those in controls. The co-localization of MMP1/MMP10/MMP12 and macrophages were identified in NPs. MMP9 was mainly expressed in neutrophils, while TIMP1 or TIMP3 were mostly found in eosinophils in NPs.Conclusion: The results of our study indicate that tissue remodeling is significant in NPs, where MMPs/TIMPs play important roles in both tissue remodeling and inflammatory cells infiltration.Keywords: remodeling, inflammatory cells, extracellular matrix, matrix metalloproteinases

Published
2024

48. Understanding Comorbidity Between Non-Suicidal Self-Injury and Depressive Symptoms in a Clinical Sample of Adolescents: A Network Analysis

Author

Niu S, Yin X, Pan B, Chen H, Dai C, Tong C, Chen F, and Feng X

Subjects
non-suicidal self-injury, depression, comorbidity network, bridge symptoms, network analysis, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract

Shan Niu,1,&ast; Xiaoxiao Yin,1,&ast; Bing Pan,2 Haotian Chen,1 Chunxiao Dai,3 Chunnan Tong,4 Fang Chen,2 Xiuqin Feng1 1Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China; 2Department of Psychiatry, Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 3Department of Clinical Psychology, Affiliated Hangzhou First People’s Hospital Zhejiang University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China; 4Department of Psychiatry, The Second Hospital of Jinhua, Jinhua, Zhejiang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xiuqin FengNursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine, No. 88 Jiefang Road, Hangzhou, Zhejiang, People’s Republic of China, Email fengxiuqin@zju.edu.cnBackground: Non-suicidal self-injury (NSSI) and depression often co-occur among adolescents with more severe clinical symptoms. This study examined the network structures of NSSI and depressive symptoms in adolescents.Methods: Participants were recruited in the psychiatric outpatient clinics of three tertiary hospitals between April 10 and July 10, 2023. All participants been already found with self-injury behaviors in outpatient when enrolled. NSSI diagnostic criteria and Patient Health Questionnaire-9 (PHQ-9) were utilized to collect NSSI and depressive symptoms separately. We performed a network analysis to visualize the correlation between each symptom and to identify core and bridging symptoms in comorbidities.Results: A total of 248 patients were enrolled in the study, with a mean age of 15.48 (SD = 1.62). Based on the PHQ-9 scores and grades, our results showed that the incidence of depression in adolescents with non-suicidal self-injury behavior was relatively high (N=235, 94.76%), with the majority having severe depression. The network analysis revealed that nodes D-6 “feeling bad, failing or letting yourself or your family down”, D-1 “little interest or pleasure” and D-4 “feeling tired” were the most vital and most central symptoms. The most crucial bridging symptom is the node NSSI-8 “frequent thinking about self-injury”, which connects the NSSI to the depression comorbid network.Conclusion: This study offers a significant symptom-level conceptualization of the association between NSSI and depressive symptoms in a clinical sample of adolescents, which not only enhances our understanding of the comorbid but also identifies potential treatment targets to prevent and treat comorbidity between adolescent NSSI and depression.Keywords: non-suicidal self-injury, depression, comorbidity network, bridge symptoms, network analysis

Published
2024

49. STCF conceptual design report (Volume 1): Physics & detector

Author

Achasov, M., Ai, X. C., An, L. P., Aliberti, R., An, Q., Bai, X. Z., Bai, Y., Bakina, O., Barnyakov, A., Blinov, V., Bobrovnikov, V., Bodrov, D., Bogomyagkov, A., Bondar, A., Boyko, I., Bu, Z. H., Cai, F. M., Cai, H., Cao, J. J., Cao, Q. H., Cao, X., Cao, Z., Chang, Q., Chao, K. T., Chen, D. Y., Chen, H., Chen, H. X., Chen, J. F., Chen, K., Chen, L. L., Chen, P., Chen, S. L., Chen, S. M., Chen, S., Chen, S. P., Chen, W., Chen, X., Chen, X. F., Chen, X. R., Chen, Y., Chen, Y. Q., Cheng, H. Y., Cheng, J., Cheng, S., Cheng, T. G., Dai, J. P., Dai, L. Y., Dai, X. C., Dedovich, D., Denig, A., Denisenko, I., Dias, J. M., Ding, D. Z., Dong, L. Y., Dong, W. H., Druzhinin, V., Du, D. S., Du, Y. J., Du, Z. G., Duan, L. M., Epifanov, D., Fan, Y. L., Fang, S. S., Fang, Z. J., Fedotovich, G., Feng, C. Q., Feng, X., Feng, Y. T., Fu, J. L., Gao, J., Gao, Y. N., Ge, P. S., Geng, C. Q., Geng, L. S., Gilman, A., Gong, L., Gong, T., Gou, B., Gradl, W., Gu, J. L., Guevara, A., Gui, L. C., Guo, A. Q., Guo, F. K., Guo, J. C., Guo, J., Guo, Y. P., Guo, Z. H., Guskov, A., Han, K. L., Han, L., Han, M., Hao, X. Q., He, J. B., He, S. Q., He, X. G., He, Y. L., He, Z. B., Heng, Z. X., Hou, B. L., Hou, T. J., Hou, Y. R., Hu, C. Y., Hu, H. M., Hu, K., Hu, R. J., Hu, W. H., Hu, X. H., Hu, Y. C., Hua, J., Huang, G. S., Huang, J. S., Huang, M., Huang, Q. Y., Huang, W. Q., Huang, X. T., Huang, X. J., Huang, Y. B., Huang, Y. S., Hüsken, N., Ivanov, V., Ji, Q. P., Jia, J. J., Jia, S., Jia, Z. K., Jiang, H. B., Jiang, J., Jiang, S. Z., Jiao, J. B., Jiao, Z., Jing, H. J., Kang, X. L., Kang, X. S., Ke, B. C., Kenzie, M., Khoukaz, A., Koop, I., Kravchenko, E., Kuzmin, A., Lei, Y., Levichev, E., Li, C. H., Li, C., Li, D. Y., Li, F., Li, G., Li, G., Li, H. B., Li, H., Li, H. N., Li, H. J., Li, H. L., Li, J. M., Li, J., Li, L., Li, L., Li, L. Y., Li, N., Li, P. R., Li, R. H., Li, S., Li, T., Li, W. J., Li, X., Li, X. H., Li, X. Q., Li, X. H., Li, Y., Li, Y. Y., Li, Z. J., Liang, H., Liang, J. H., Liang, Y. T., Liao, G. R., Liao, L. Z., Liao, Y., Lin, C. X., Lin, D. X., Lin, X. S., Liu, B. J., Liu, C. W., Liu, D., Liu, F., Liu, G. M., Liu, H. B., Liu, J., Liu, J. J., Liu, J. B., Liu, K., Liu, K. Y., Liu, K., Liu, L., Liu, Q., Liu, S. B., Liu, T., Liu, X., Liu, Y. W., Liu, Y., Liu, Y. L., Liu, Z. Q., Liu, Z. Y., Liu, Z. W., Logashenko, I., Long, Y., Lu, C. G., Lu, J. X., Lu, N., Lü, Q. F., Lu, Y., Lu, Y., Lu, Z., Lukin, P., Luo, F. J., Luo, T., Luo, X. F., Lyu, H. J., Lyu, X. R., Ma, J. P., Ma, P., Ma, Y., Ma, Y. M., Maas, F., Malde, S., Matvienko, D., Meng, Z. X., Mitchell, R., Nefediev, A., Nefedov, Y., Olsen, S. L., Ouyang, Q., Pakhlov, P., Pakhlova, G., Pan, X., Pan, Y., Passemar, E., Pei, Y. P., Peng, H. P., Peng, L., Peng, X. Y., Peng, X. J., Peters, K., Pivovarov, S., Pyata, E., Qi, B. B., Qi, Y. Q., Qian, W. B., Qian, Y., Qiao, C. F., Qin, J. J., Qin, J. J., Qin, L. Q., Qin, X. S., Qiu, T. L., Rademacker, J., Redmer, C. F., Sang, H. Y., Saur, M., Shan, W., Shan, X. Y., Shang, L. L., Shao, M., Shekhtman, L., Shen, C. P., Shen, J. M., Shen, Z. T., Shi, H. C., Shi, X. D., Shwartz, B., Sokolov, A., Song, J. J., Song, W. M., Song, Y., Song, Y. X., Sukharev, A., Sun, J. F., Sun, L., Sun, X. M., Sun, Y. J., Sun, Z. P., Tang, J., Tang, S. S., Tang, Z. B., Tian, C. H., Tian, J. S., Tian, Y., Tikhonov, Y., Todyshev, K., Uglov, T., Vorobyev, V., Wan, B. D., Wang, B. L., Wang, B., Wang, D. Y., Wang, G. Y., Wang, G. L., Wang, H. L., Wang, J., Wang, J. H., Wang, J. C., Wang, M. L., Wang, R., Wang, R., Wang, S. B., Wang, W., Wang, W. P., Wang, X. C., Wang, X. D., Wang, X. L., Wang, X. L., Wang, X. P., Wang, X. F., Wang, Y. D., Wang, Y. P., Wang, Y. Q., Wang, Y. L., Wang, Y. G., Wang, Z. Y., Wang, Z. Y., Wang, Z. L., Wang, Z. G., Wei, D. H., Wei, X. L., Wei, X. M., Wen, Q. G., Wen, X. J., Wilkinson, G., Wu, B., Wu, J. J., Wu, L., Wu, P., Wu, T. W., Wu, Y. S., Xia, L., Xiang, T., Xiao, C. W., Xiao, D., Xiao, M., Xie, K. P., Xie, Y. H., Xing, Y., Xing, Z. Z., Xiong, X. N., Xu, F. R., Xu, J., Xu, L. L., Xu, Q. N., Xu, X. C., Xu, X. P., Xu, Y. C., Xu, Y. P., Xu, Y., Xu, Z. Z., Xuan, D. W., Xue, F. F., Yan, L., Yan, M. J., Yan, W. B., Yan, W. C., Yan, X. S., Yang, B. F., Yang, C., Yang, H. J., Yang, H. R., Yang, H. T., Yang, J. F., Yang, S. L., Yang, Y. D., Yang, Y. H., Yang, Y. S., Yang, Y. L., Yang, Z. W., Yang, Z. Y., Yao, D. L., Yin, H., Yin, X. H., Yokozaki, N., You, S. Y., You, Z. Y., Yu, C. X., Yu, F. S., Yu, G. L., Yu, H. L., Yu, J. S., Yu, J. Q., Yuan, L., Yuan, X. B., Yuan, Z. Y., Yue, Y. F., Zeng, M., Zeng, S., Zhang, A. L., Zhang, B. W., Zhang, G. Y., Zhang, G. Q., Zhang, H. J., Zhang, H. B., Zhang, J. Y., Zhang, J. L., Zhang, J., Zhang, L., Zhang, L. M., Zhang, Q. A., Zhang, R., Zhang, S. L., Zhang, T., Zhang, X., Zhang, Y., Zhang, Y. J., Zhang, Y. X., Zhang, Y. T., Zhang, Y. F., Zhang, Y. C., Zhang, Y., Zhang, Y., Zhang, Y. M., Zhang, Y. L., Zhang, Z. H., Zhang, Z. Y., Zhang, Z. Y., Zhao, H. Y., Zhao, J., Zhao, L., Zhao, M. G., Zhao, Q., Zhao, R. G., Zhao, R. P., Zhao, Y. X., Zhao, Z. G., Zhao, Z. X., Zhemchugov, A., Zheng, B., Zheng, L., Zheng, Q. B., Zheng, R., Zheng, Y. H., Zhong, X. H., Zhou, H. J., Zhou, H. Q., Zhou, H., Zhou, S. H., Zhou, X., Zhou, X. K., Zhou, X. P., Zhou, X. R., Zhou, Y. L., Zhou, Y., Zhou, Y. X., Zhou, Z. Y., Zhu, J. Y., Zhu, K., Zhu, R. D., Zhu, R. L., Zhu, S. H., Zhu, Y. C., Zhu, Z. A., Zhukova, V., Zhulanov, V., Zou, B. S., and Zuo, Y. B.

Published
2024
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