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Tang Q, Zhang G, Fan YS, Sheng W, Yang C, Liu L, Liu X, Liu H, Guo Y, Gao Q, Lu F, He Z, Cui Q, Chen H. An investigation into the abnormal dynamic connection mechanism of generalized anxiety disorders based on non-homogeneous Markov models. J Affect Disord 2024; 354:500-508. [PMID: 38484883 DOI: 10.1016/j.jad.2024.03.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 02/25/2024] [Accepted: 03/09/2024] [Indexed: 03/26/2024]
Abstract
BACKGROUND The dynamic and hierarchical nature of the functional brain network. The neural dynamical systems tend to converge to multiple attractors (stable fixed points or dynamical states) in long run. Little is known about how the changes in this brain dynamic "long-term" behavior of the connectivity flow of brain network in generalized anxiety disorder (GAD). METHODS This study recruited 92 patients with GAD and 77 healthy controls (HC). We applied a reachable probability approach combining a Non-homogeneous Markov model with transition probability to quantify all possible connectivity flows and the hierarchical structure of brain functional systems at the dynamic level and the stationary probability vector (10-step transition probabilities) to describe the steady state of the system in the long run. A random forest algorithm was conducted to predict the severity of anxiety. RESULTS The dynamic functional patterns in distributed brain networks had larger possibility to converge in bilateral thalamus, posterior cingulate cortex (PCC), right superior occipital gyrus (SOG) and smaller possibility to converge in bilateral superior temporal gyrus (STG) and right parahippocampal gyrus (PHG) in patients with GAD compared to HC. The abnormal transition probability pattern could predict anxiety severity in patients with GAD. LIMITATIONS Small samples and subjects taking medications may have influenced our results. Future studies are expected to rule out the potential confounding effects. CONCLUSION Our results have revealed abnormal dynamic neural communication and integration in emotion regulation in patients with GAD, which give new insights to understand the dynamics of brain function of patients with GAD.
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Affiliation(s)
- Qin Tang
- Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing 400038, China; The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Gan Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yun-Shuang Fan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chenguang Yang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Liju Liu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xingli Liu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Haoxiang Liu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuanhong Guo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qing Gao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China.
| | - Huafu Chen
- Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing 400038, China; The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.
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Liu C, Gao Q, Dong J, Cai H. Usf2 Deficiency Promotes Autophagy to Alleviate Cerebral Ischemia-Reperfusion Injury Through Suppressing YTHDF1-m6A-Mediated Cdc25A Translation. Mol Neurobiol 2024; 61:2556-2568. [PMID: 37914905 DOI: 10.1007/s12035-023-03735-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 10/20/2023] [Indexed: 11/03/2023]
Abstract
Autophagy has been involved in protection of ischemia/reperfusion (I/R)-induced injury in many tissues including the brain. The upstream stimulatory factor 2 (Usf2) was proposed as a regulator in aging and degenerative brain diseases; however, the its role in autophagy during cerebral I/R injury remains unclear. Here, the middle cerebral artery occlusion (MCAO) operation was applied to establish an I/R mouse model. We showed that Usf2 was significantly upregulated in I/R-injured brain, accompanied by decreased levels of autophagy. Then, oxygen-glucose deprivation/recovery (OGD/R) treatment was used to establish a cellular I/R model in HT22 neurons, and lentiviral interference vector against Usf2 (LV-sh-Usf2) was used to infect the neurons. Our results showed that Usf2 was significantly upregulated in OGD/R-treated HT22 neurons that displayed an increased level in cell apoptosis and decreased levels in cell viability and autophagy, and interference of Usf2 largely rescued the effects of OGD/R on cell viability, apoptosis, and autophagy, suggesting an important role of Usf2 in neuron autophagy. In the mechanism exploration, we found that, as a transcription factor, Usf2 bound to the promoter of YTHDF1, a famous reader of N6-Methyladenosine (m6A), also induced by OGD/R, and promoted its transcription. Overexpression of YTHDF1 was able to reverse the improvement of Usf2 interference on viability and autophagy of HT22 neurons. Moreover, YTHDF1 suppressed autophagy to induce HT22 cell apoptosis through increasing m6A-mediated stability of Cdc25A, a newly identified autophagy inhibitor. Finally, we demonstrated that interference of Usf2 markedly improved autophagy and alleviated I/R-induced injury in MCAO mice.
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Affiliation(s)
- Chao Liu
- Department of Vascular Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, China
| | - Qing Gao
- Department of Anesthesia Operation, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, China
| | - Jian Dong
- Department of Vascular Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, China
| | - Hui Cai
- Department of Vascular Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, China.
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Ding S, Ni J, Lin L, Gao Q, Kong L. The effect of ADOPT nursing model on the Quality of Life and self-care ability of diabetic patients. Panminerva Med 2024:S0031-0808.24.05135-8. [PMID: 38625045 DOI: 10.23736/s0031-0808.24.05135-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Affiliation(s)
- Shanju Ding
- Department of Endocrinology, Yantai Affiliated Hospital of Binzhou Medical College, Yantai, China
| | - Jin Ni
- Department of Endocrinology, Yantai Affiliated Hospital of Binzhou Medical College, Yantai, China
| | - Lijuan Lin
- Department of General Practice, Yantai Affiliated Hospital of Binzhou Medical College, Yantai, China
| | - Qing Gao
- Department of General Practice, Yantai Affiliated Hospital of Binzhou Medical College, Yantai, China
| | - Lili Kong
- Department of Endocrinology, Yantai Affiliated Hospital of Binzhou Medical College, Yantai, China -
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Zheng J, Gao Q, Ogorzalek M, Lu J, Deng Y. A Quantum Spatial Graph Convolutional Neural Network Model on Quantum Circuits. IEEE Trans Neural Netw Learn Syst 2024; PP:1-15. [PMID: 38619956 DOI: 10.1109/tnnls.2024.3382174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
This article proposes a quantum spatial graph convolutional neural network (QSGCN) model that is implementable on quantum circuits, providing a novel avenue to processing non-Euclidean type data based on the state-of-the-art parameterized quantum circuit (PQC) computing platforms. Four basic blocks are constructed to formulate the whole QSGCN model, including the quantum encoding, the quantum graph convolutional layer, the quantum graph pooling layer, and the network optimization. In particular, the trainability of the QSGCN model is analyzed through discussions on the barren plateau phenomenon. Simulation results from various types of graph data are presented to demonstrate the learning, generalization, and robustness capabilities of the proposed quantum neural network (QNN) model.
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Cheng YJ, Wang F, Feng J, Yu B, Wang B, Gao Q, Wang TY, Hu B, Gao X, Chen JF, Chen YJ, Lv SQ, Feng H, Xiao L, Mei F. Prolonged myelin deficits contribute to neuron loss and functional impairments after ischaemic stroke. Brain 2024; 147:1294-1311. [PMID: 38289861 DOI: 10.1093/brain/awae029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Revised: 12/29/2023] [Accepted: 01/13/2024] [Indexed: 02/01/2024] Open
Abstract
Ischaemic stroke causes neuron loss and long-term functional deficits. Unfortunately, effective approaches to preserving neurons and promoting functional recovery remain unavailable. Oligodendrocytes, the myelinating cells in the CNS, are susceptible to oxygen and nutrition deprivation and undergo degeneration after ischaemic stroke. Technically, new oligodendrocytes and myelin can be generated by the differentiation of oligodendrocyte precursor cells (OPCs). However, myelin dynamics and their functional significance after ischaemic stroke remain poorly understood. Here, we report numerous denuded axons accompanied by decreased neuron density in sections from ischaemic stroke lesions in human brain, suggesting that neuron loss correlates with myelin deficits in these lesions. To investigate the longitudinal changes in myelin dynamics after stroke, we labelled and traced pre-existing and newly-formed myelin, respectively, using cell-specific genetic approaches. Our results indicated massive oligodendrocyte death and myelin loss 2 weeks after stroke in the transient middle cerebral artery occlusion (tMCAO) mouse model. In contrast, myelin regeneration remained insufficient 4 and 8 weeks post-stroke. Notably, neuronal loss and functional impairments worsened in aged brains, and new myelin generation was diminished. To analyse the causal relationship between remyelination and neuron survival, we manipulated myelinogenesis by conditional deletion of Olig2 (a positive regulator) or muscarinic receptor 1 (M1R, a negative regulator) in OPCs. Deleting Olig2 inhibited remyelination, reducing neuron survival and functional recovery after tMCAO. Conversely, enhancing remyelination by M1R conditional knockout or treatment with the pro-myelination drug clemastine after tMCAO preserved white matter integrity and neuronal survival, accelerating functional recovery. Together, our findings demonstrate that enhancing myelinogenesis is a promising strategy to preserve neurons and promote functional recovery after ischaemic stroke.
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Affiliation(s)
- Yong-Jie Cheng
- Department of Neurosurgery and Key Laboratory of Neurotrauma, 1st affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Fei Wang
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Jie Feng
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Bin Yu
- Department of Neurosurgery, 2nd affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Bin Wang
- Department of Physiology, Chongqing Key Laboratory of Neurobiology, Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Third Military Medical University, Chongqing 400038, China
| | - Qing Gao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, PR China
| | - Teng-Yue Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, PR China
| | - Bo Hu
- Department of Physiology, Chongqing Key Laboratory of Neurobiology, Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Third Military Medical University, Chongqing 400038, China
| | - Xing Gao
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Jing-Fei Chen
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Yu-Jie Chen
- Department of Neurosurgery and Key Laboratory of Neurotrauma, 1st affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Sheng-Qing Lv
- Department of Neurosurgery, 2nd affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Hua Feng
- Department of Neurosurgery and Key Laboratory of Neurotrauma, 1st affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Lan Xiao
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University (Army Medical University), Chongqing 400038, China
- Department of Neurosurgery, 2nd affiliated Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Feng Mei
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University (Army Medical University), Chongqing 400038, China
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Gao Q, Luo N, Liang M, Zhou W, Li Y, Li R, Hu X, Zou T, Wang X, Yu J, Leng J, Chen H. A Stepwise Multivariate Granger Causality Method for Constructing Hierarchical Directed Brain Functional Network. IEEE Trans Neural Netw Learn Syst 2024; 35:4974-4984. [PMID: 36099216 DOI: 10.1109/tnnls.2022.3202535] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The directed brain functional network construction gives us the new insights into the relationships between brain regions from the causality point of view. The Granger causality analysis is one of the powerful methods to model the directed network. The complex brain network is also hierarchically constructed, which is particularly suited to facilitate segregated functions and the global integration of the segregated functions. Therefore, it is of great interest to explore new approach to model the hierarchical architecture of the directed network. In the present study, we proposed a new approach, namely, stepwise multivariate Granger causality (SMGC), considering both the directed and hierarchical features of brain functional network to explore the stepwise causal relationship in the network. The simulation study demonstrated that the diverse and complex hierarchical organization could be embedded in the apparently simple directed network. The proposed SMGC method could capture the multiple hierarchy of the directed network. When applying to the real functional magnetic resonance imaging (fMRI) datasets, the core triple resting-state networks in human brain showed within-network directed connections in the first-level directed network and rich and diverse between-network pathways in the second-level hierarchical network. The default mode network (DMN) had a prominent role in the resting-state acting as both the causal source and the important relay station. Further exploratory research on the adaption of directed hierarchical network in athletes suggested the enhanced bidirectional communication between the DMN and the central executive network (CEN) and the enhanced directed connections from the salience network (SN) to the CEN in the athlete group. The SMGC approach is capable of capturing the hierarchical architecture of the brain directed functional network, which refreshes the new stepwise causal relationship in the directed network. This might shed light on the potential application for exploring the altered hierarchical organization of brain directed network in neuropsychiatric disorders.
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Liu H, Yang M, Li K, Gao Q, Zheng J, Gong X, Wang H, Sun Y, Chang X. A transcriptomics-based investigation of the mechanism of pulmonary fibrosis induced by nickel oxide nanoparticles. Environ Toxicol 2024; 39:2374-2389. [PMID: 38165020 DOI: 10.1002/tox.24088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 10/15/2023] [Accepted: 12/01/2023] [Indexed: 01/03/2024]
Abstract
Nickel oxide nanoparticles (NiONPs) are an emerging nanomaterial, which poses a huge threat to the health of workplace population. Nanoparticles induce pulmonary fibrosis, and its mechanisms are associated with noncoding RNAs (ncRNAs). However, ncRNAs and competing endogenous RNA (ceRNA) networks which involved in NiONP-induced pulmonary fibrosis are still unclear. This study aimed to identify ncRNA-related ceRNA networks and investigate the role of the Wnt/β-catenin pathway in pulmonary fibrosis. Male Wistar rats were intratracheally instilled with 0.015, 0.06, and 0.24 mg/kg NiONPs twice a week for 9 weeks. First, we found there were 93 circularRNAs (circRNAs), 74 microRNAs (miRNAs), 124 long non-coding RNAs (lncRNAs), and 1675 messenger RNAs (mRNAs) differentially expressed through microarray analysis. Second, we constructed ceRNA networks among lncRNAs/circRNAs, miRNAs and mRNAs and identified two ceRNA networks (lncMelttl16/miR-382-5p/Hsd17b7 and circIqch/miR-181d-5p/Stat1) after real time-quantitative polymerase chain reaction (RT-qPCR) validation. Furthermore, based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, ncRNAs were found to be involved in biological processes and signaling pathways related to pulmonary fibrosis. KEGG analysis showed that NiONPs activated the Wnt/β-catenin pathway in rats. In vitro, HFL1 cells were treated with 0, 50, 100, and 200 μg/mL NiONPs for 24 h. We found that NiONPs induced collagen deposition and Wnt/β-catenin pathway activation. Moreover, a blockade of Wnt/β-catenin pathway alleviated NiONP-induced collagen deposition. In conclusion, these observations suggested that ncRNAs were crucial in pulmonary fibrosis development and that the Wnt/β-catenin pathway mediated the deposition of collagen.
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Affiliation(s)
- Han Liu
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
| | - Mengmeng Yang
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
| | - Kun Li
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
| | - Qing Gao
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
| | - Jinfa Zheng
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
| | - Xuefeng Gong
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
| | - Hui Wang
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
| | - Yingbiao Sun
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
| | - Xuhong Chang
- Department of Toxicology, School of Public Health, Lanzhou University, Lanzhou, China
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Chen Y, Lu M, Lin M, Gao Q. Network pharmacology and molecular docking to elucidate the common mechanism of hydroxychloroquine treatment in lupus nephritis and IgA nephropathy. Lupus 2024; 33:347-356. [PMID: 38285068 DOI: 10.1177/09612033241230377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
OBJECTIVE Hydroxychloroquine (HCQ), characterized by a broad effect on immune regulation, has been widely used in the treatment of autoimmune glomerulonephritis such as lupus nephritis (LN) and immunoglobulin A nephropathy (IgAN). The current research investigates whether HCQ plays a role in the treatment of LN and IgAN through common mechanisms since the pathogenesis of both LN and IgAN is closely related to immune complex deposition, complement activation, and ultimately inflammation. METHODS Seventy-two common targets were obtained related to the common mechanism of HCQ treatment of LN and IgAN. Targets associated with LN and IgAN were collected based on DisGeNET, GeneCards, and OMIM databases. Possible HCQ targets were obtained from the PubChem database and PharmMapper databases. The overlapping targets of HCQ ingredients, IgAN, and LN were discovered via the Venn 2.1.0 online platform. Through the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted. Cytoscape (v3.9.1) was used to build a protein-protein interaction (PPI) network. Molecular docking was performed by using AutoDockTools 1.5.6 software and PyMol software to match the binding activity between HCQ and the 10 core targets. RESULTS The results showed that core targets (including MMP 2, PPARG, IL-2, MAPK14, MMP 9, and SRC), three signaling pathways (including the PI3K-Akt, AGE-RAGE, and MAPK), and cell differentiation (including Th1, Th2, and Th17) might be related to the body's immunity and inflammation. These results suggested that HCQ might act on targets and pathways involved in inflammation and immune regulation to exert a common effect on the treatment of LN and IgAN. CONCLUSIONS The current study provided new evidence for the protective mechanism and clinical utility of HCQ against LN and IgAN.
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Affiliation(s)
- Yixuan Chen
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, China
| | - Meiqi Lu
- Department of Nephrology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Mengshu Lin
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, China
| | - Qing Gao
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, China
- Department of Nephrology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
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Cao Z, Aharonian F, Axikegu, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Bian W, Bukevich AV, Cao Q, Cao WY, Cao Z, Chang J, Chang JF, Chen AM, Chen ES, Chen HX, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen S, Chen SH, Chen SZ, Chen TL, Chen Y, Cheng N, Cheng YD, Cui MY, Cui SW, Cui XH, Cui YD, Dai BZ, Dai HL, Dai ZG, Danzengluobu, Dong XQ, Duan KK, Fan JH, Fan YZ, Fang J, Fang JH, Fang K, Feng CF, Feng H, Feng L, Feng SH, Feng XT, Feng Y, Feng YL, Gabici S, Gao B, Gao CD, Gao Q, Gao W, Gao WK, Ge MM, Geng LS, Giacinti G, Gong GH, Gou QB, Gu MH, Guo FL, Guo XL, Guo YQ, Guo YY, Han YA, Hasan M, He HH, He HN, He JY, He Y, Hor YK, Hou BW, Hou C, Hou X, Hu HB, Hu Q, Hu SC, Huang DH, Huang TQ, Huang WJ, Huang XT, Huang XY, Huang Y, Ji XL, Jia HY, Jia K, Jiang K, Jiang XW, Jiang ZJ, Jin M, Kang MM, Karpikov I, Kuleshov D, Kurinov K, Li BB, Li CM, Li C, Li C, Li D, Li F, Li HB, Li HC, Li J, Li J, Li K, Li SD, Li WL, Li WL, Li XR, Li X, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu DB, Liu H, Liu HD, Liu J, Liu JL, Liu MY, Liu RY, Liu SM, Liu W, Liu Y, Liu YN, Luo Q, Luo Y, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Min Z, Mitthumsiri W, Mu HJ, Nan YC, Neronov A, Ou LJ, Pattarakijwanich P, Pei ZY, Qi JC, Qi MY, Qiao BQ, Qin JJ, Raza A, Ruffolo D, Sáiz A, Saeed M, Semikoz D, Shao L, Shchegolev O, Sheng XD, Shu FW, Song HC, Stenkin YV, Stepanov V, Su Y, Sun DX, Sun QN, Sun XN, Sun ZB, Takata J, Tam PHT, Tang QW, Tang R, Tang ZB, Tian WW, Wang C, Wang CB, Wang GW, Wang HG, Wang HH, Wang JC, Wang K, Wang K, Wang LP, Wang LY, Wang PH, Wang R, Wang W, Wang XG, Wang XY, Wang Y, Wang YD, Wang YJ, Wang ZH, Wang ZX, Wang Z, Wang Z, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu QW, Wu S, Wu XF, Wu YS, Xi SQ, Xia J, Xiang GM, Xiao DX, Xiao G, Xin YL, Xing Y, Xiong DR, Xiong Z, Xu DL, Xu RF, Xu RX, Xu WL, Xue L, Yan DH, Yan JZ, Yan T, Yang CW, Yang CY, Yang F, Yang FF, Yang LL, Yang MJ, Yang RZ, Yang WX, Yao YH, Yao ZG, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Yue H, Zeng HD, Zeng TX, Zeng W, Zha M, Zhang BB, Zhang F, Zhang H, Zhang HM, Zhang HY, Zhang JL, Zhang L, Zhang PF, Zhang PP, Zhang R, Zhang SB, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang YF, Zhang Y, Zhang Y, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zhao XH, Zheng F, Zhong WJ, Zhou B, Zhou H, Zhou JN, Zhou M, Zhou P, Zhou R, Zhou XX, Zhou XX, Zhu BY, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zou YC, Zuo X. Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A. Phys Rev Lett 2024; 132:131002. [PMID: 38613275 DOI: 10.1103/physrevlett.132.131002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/23/2024] [Accepted: 02/12/2024] [Indexed: 04/14/2024]
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±0.05±0.15 PeV. Below the knee, the spectral index is found to be -2.7413±0.0004±0.0050, while above the knee, it is -3.128±0.005±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±0.0003±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.
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Affiliation(s)
- Zhen Cao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F Aharonian
- Dublin Institute for Advanced Studies, 31 Fitzwilliam Place, 2 Dublin, Ireland
- Max-Planck-Institut for Nuclear Physics, P.O. Box 103980, 69029 Heidelberg, Germany
| | - Axikegu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y X Bai
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y W Bao
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - D Bastieri
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - X J Bi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y J Bi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W Bian
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - A V Bukevich
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - Q Cao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - W Y Cao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Zhe Cao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - J Chang
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J F Chang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - A M Chen
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - E S Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H X Chen
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - Liang Chen
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - Lin Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Long Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - M J Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M L Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Q H Chen
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - S Chen
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - S H Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - S Z Chen
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - T L Chen
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - Y Chen
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - N Cheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y D Cheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Cui
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S W Cui
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - X H Cui
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - Y D Cui
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B Z Dai
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - H L Dai
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Z G Dai
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Danzengluobu
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - X Q Dong
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - K K Duan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J H Fan
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y Z Fan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J Fang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - J H Fang
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - K Fang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C F Feng
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - H Feng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
| | - L Feng
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S H Feng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X T Feng
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - Y Feng
- Research Center for Astronomical Computing, Zhejiang Laboratory, 311121 Hangzhou, Zhejiang, China
| | - Y L Feng
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - S Gabici
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - B Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C D Gao
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - Q Gao
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - W Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W K Gao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M M Ge
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - L S Geng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - G Giacinti
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - G H Gong
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Q B Gou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M H Gu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - F L Guo
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - X L Guo
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y Q Guo
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y Y Guo
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y A Han
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - M Hasan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H H He
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H N He
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J Y He
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y He
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y K Hor
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B W Hou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C Hou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X Hou
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - H B Hu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Q Hu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S C Hu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- China Center of Advanced Science and Technology, Beijing 100190, China
| | - D H Huang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - T Q Huang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W J Huang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - X T Huang
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - X Y Huang
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y Huang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X L Ji
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - H Y Jia
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - K Jia
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - K Jiang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - X W Jiang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z J Jiang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - M Jin
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - M M Kang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - I Karpikov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - D Kuleshov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - K Kurinov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - B B Li
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - C M Li
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Cheng Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Cong Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - H B Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H C Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Jian Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Jie Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - K Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - S D Li
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - W L Li
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - W L Li
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - X R Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Xin Li
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Y Z Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Zhe Li
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Zhuo Li
- School of Physics, Peking University, 100871 Beijing, China
| | - E W Liang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - Y F Liang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - S J Lin
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - B Liu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - C Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Liu
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - D B Liu
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H Liu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H D Liu
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - J Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J L Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Liu
- Key Laboratory of Cosmic Rays (Tibet University), Ministry of Education, 850000 Lhasa, Tibet, China
| | - R Y Liu
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - S M Liu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - W Liu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y Liu
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y N Liu
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Q Luo
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - Y Luo
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H K Lv
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Q Ma
- School of Physics, Peking University, 100871 Beijing, China
| | - L L Ma
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X H Ma
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J R Mao
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Z Min
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - W Mitthumsiri
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - H J Mu
- School of Physics and Microelectronics, Zhengzhou University, 450001 Zhengzhou, Henan, China
| | - Y C Nan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - A Neronov
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - L J Ou
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - P Pattarakijwanich
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Z Y Pei
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - J C Qi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - M Y Qi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Q Qiao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J J Qin
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - A Raza
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Ruffolo
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - A Sáiz
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - M Saeed
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D Semikoz
- APC, Université Paris Cité, CNRS/IN2P3, CEA/IRFU, Observatoire de Paris, 119 75205 Paris, France
| | - L Shao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - O Shchegolev
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
- Moscow Institute of Physics and Technology, 141700 Moscow, Russia
| | - X D Sheng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - F W Shu
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - H C Song
- School of Physics, Peking University, 100871 Beijing, China
| | - Yu V Stenkin
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
- Moscow Institute of Physics and Technology, 141700 Moscow, Russia
| | - V Stepanov
- Institute for Nuclear Research of Russian Academy of Sciences, 117312 Moscow, Russia
| | - Y Su
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - D X Sun
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Q N Sun
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - X N Sun
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - Z B Sun
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - J Takata
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - P H T Tam
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - Q W Tang
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - R Tang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Z B Tang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - W W Tian
- University of Chinese Academy of Sciences, 100049 Beijing, China
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - C Wang
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - C B Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - G W Wang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - H G Wang
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - H H Wang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - J C Wang
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Kai Wang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Kai Wang
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - L P Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Y Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - P H Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - R Wang
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - W Wang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - X G Wang
- Guangxi Key Laboratory for Relativistic Astrophysics, School of Physical Science and Technology, Guangxi University, 530004 Nanning, Guangxi, China
| | - X Y Wang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - Y Wang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y D Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y J Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z H Wang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - Z X Wang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - Zhen Wang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Zheng Wang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - D M Wei
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - J J Wei
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y J Wei
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - T Wen
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - C Y Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H R Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Q W Wu
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - S Wu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X F Wu
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Y S Wu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - S Q Xi
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J Xia
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - G M Xiang
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - D X Xiao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - G Xiao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y L Xin
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Y Xing
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - D R Xiong
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - Z Xiong
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - D L Xu
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - R F Xu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - R X Xu
- School of Physics, Peking University, 100871 Beijing, China
| | - W L Xu
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - L Xue
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - D H Yan
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - J Z Yan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - T Yan
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - C W Yang
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - C Y Yang
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - F Yang
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - F F Yang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - L L Yang
- School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai), Sun Yat-sen University, 519000 Zhuhai and 510275 Guangzhou, Guangdong, China
| | - M J Yang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - R Z Yang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - W X Yang
- Center for Astrophysics, Guangzhou University, 510006 Guangzhou, Guangdong, China
| | - Y H Yao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z G Yao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Q Yin
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - N Yin
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - X H You
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Z Y You
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y H Yu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
| | - Q Yuan
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - H Yue
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H D Zeng
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - T X Zeng
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - W Zeng
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - M Zha
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B B Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - F Zhang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H Zhang
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - H M Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - H Y Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - J L Zhang
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - Li Zhang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - P F Zhang
- School of Physics and Astronomy, Yunnan University, 650091 Kunming, Yunnan, China
| | - P P Zhang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - R Zhang
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - S B Zhang
- University of Chinese Academy of Sciences, 100049 Beijing, China
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - S R Zhang
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - S S Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X Zhang
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - X P Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - Y F Zhang
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - Yi Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - Yong Zhang
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - B Zhao
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - J Zhao
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - L Zhao
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - L Z Zhao
- Hebei Normal University, 050024 Shijiazhuang, Hebei, China
| | - S P Zhao
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - X H Zhao
- Yunnan Observatories, Chinese Academy of Sciences, 650216 Kunming, Yunnan, China
| | - F Zheng
- National Space Science Center, Chinese Academy of Sciences, 100190 Beijing, China
| | - W J Zhong
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - B Zhou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - H Zhou
- Tsung-Dao Lee Institute and School of Physics and Astronomy, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - J N Zhou
- Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 200030 Shanghai, China
| | - M Zhou
- Center for Relativistic Astrophysics and High Energy Physics, School of Physics and Materials Science and Institute of Space Science and Technology, Nanchang University, 330031 Nanchang, Jiangxi, China
| | - P Zhou
- School of Astronomy and Space Science, Nanjing University, 210023 Nanjing, Jiangsu, China
| | - R Zhou
- College of Physics, Sichuan University, 610065 Chengdu, Sichuan, China
| | - X X Zhou
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
| | - X X Zhou
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - B Y Zhu
- University of Science and Technology of China, 230026 Hefei, Anhui, China
- Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, 210023 Nanjing, Jiangsu, China
| | - C G Zhu
- Institute of Frontier and Interdisciplinary Science, Shandong University, 266237 Qingdao, Shandong, China
| | - F R Zhu
- School of Physical Science and Technology and School of Information Science and Technology, Southwest Jiaotong University, 610031 Chengdu, Sichuan, China
| | - H Zhu
- National Astronomical Observatories, Chinese Academy of Sciences, 100101 Beijing, China
| | - K J Zhu
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
- State Key Laboratory of Particle Detection and Electronics, China
| | - Y C Zou
- School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - X Zuo
- Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing, China
- Tianfu Cosmic Ray Research Center, 610000 Chengdu, Sichuan, China
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10
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Xie T, Huang C, Wang Y, Zhang H, Guo P, Phann TT, Cheng Y, Lei L, Tao Z, Gao Q, Wei H, Yu CY. An "All-In-One" Immunomodulator-Engineered Clinical Translatable Immunotherapy of Advanced Hepatocellular Carcinoma. Adv Healthc Mater 2024:e2304476. [PMID: 38519415 DOI: 10.1002/adhm.202304476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 03/19/2024] [Indexed: 03/24/2024]
Abstract
Clinical treatment of advanced hepatocellular carcinoma (HCC) remains a significant challenge. Utilizing 1-bromoacetyl-3,3-dinitroazetidine (RRx-001) to downregulate the expression of innate immune checkpoint molecule, cluster of differentiation 47 (CD47), provides a powerful means for treating advanced HCC containing abundant immunosuppressive macrophages. Herein engineering of a previously optimized Doxorubicin (DOX)-delivery nanoplatform based on sodium alginate is reported to further co-deliver RRx-001 (biotinylated aldehyde alginate-doxorubicin micelle prodrug nanoplatform, BEA-D@R) for efficient immunotherapy of advanced HCC. This groundbreaking technique reveals the "all-in-one" immunotherapeutic functionalities of RRx-001. Besides the previously demonstrated functions of downregulating CD47 expression and increasing reactive nitrogen species (RNS) generation, another key function of RRx-001 for downregulating the expression of the adaptive immune checkpoint molecule programmed cell death 1 ligand 1 (PDL1) is first uncovered here. Combined with the reactive oxygen species (ROS) generation and an upregulated "eat me" signal level of DOX, BEA-D@R collectively increases RNS generation, enhances T-cell infiltration, and maximizes macrophage phagocytosis, leading to an average of 40% tumor elimination in a mice model bearing an initial tumor volume of ≈300 mm3 that mimics advanced HCC. Overall, the "all-in-one" immunotherapeutic functionalities of a clinical translatable nanoplatform are uncovered for enhanced immunotherapy of advanced HCC.
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Affiliation(s)
- Ting Xie
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Cong Huang
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Yuqing Wang
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Haitao Zhang
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Pei Guo
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Thuy Thu Phann
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Yao Cheng
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Longtianyang Lei
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Zhenghao Tao
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Qing Gao
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Hua Wei
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
| | - Cui-Yun Yu
- Hunan Province Cooperative Innovation Center for Molecular Target New Drug Study, School of Pharmaceutical Science, Hengyang Medical School, University of South China, Hengyang, 421001, China
- Affiliated Hospital of Hunan Academy of Chinese Medicine, Hunan Academy of Chinese Medicine, Changsha, 410013, China
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11
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Lu M, Gao Q, Jin R, Gu M, Wang Z, Li X, Li W, Wang J, Ma T. The Ribonuclease ZC3H12A is required for self-inflicted DNA breaks after DNA damage in small cell lung cancer cells. Cell Oncol (Dordr) 2024:10.1007/s13402-024-00941-x. [PMID: 38498096 DOI: 10.1007/s13402-024-00941-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/13/2024] [Indexed: 03/20/2024] Open
Abstract
Radiotherapy is the first line treatment for small cell lung cancer (SCLC); However, radio-resistance accompanies with the treatment and hampers the prognosis for SCLC patients. The underlying mechanisms remains elusive. Here we discovered that self-inflicted DNA breaks exist in SCLC cells after radiation. Moreover, using nuclease siRNA screening combined with high-content ArrayScan™ cell analyzer, we identified that Ribonuclease ZC3H12A is required for the self-inflicted DNA breaks after radiation and for SCLC cell survival after DNA damage. ZC3H12A expression was increased in response to DNA damage and when ZC3H12A was knocked down, the DNA repair ability of the cells was impaired, as evidenced by decreased expression of the DNA damage repair protein BRCA1, and increased γH2AX at DNA damage sites. Colony formation assay demonstrates that ZC3H12A knocked down sensitized small cell lung cancer radiotherapy. Therefore, the Ribonuclease ZC3H12A regulates endogenous secondary breaks in small cell lung cancer and affects DNA damage repair. ZC3H12A may act as an important radiotherapy target in small cell lung cancer.
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Affiliation(s)
- Mingjun Lu
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China
| | - Qing Gao
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China
| | - Renjing Jin
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China
| | - Meng Gu
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China
| | - Ziyu Wang
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China
| | - Xiaobo Li
- Department of Radiation Oncology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China
| | - Weiying Li
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China
| | - Jinghui Wang
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China
| | - Teng Ma
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China.
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12
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Gao Q, Zheng J, Van der Meeren P, Zhang B, Fu X, Huang Q. Stabilization and release of thymol in pre-formed V-type starch: A comparative study with traditional method. Carbohydr Polym 2024; 328:121712. [PMID: 38220323 DOI: 10.1016/j.carbpol.2023.121712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 11/29/2023] [Accepted: 12/17/2023] [Indexed: 01/16/2024]
Abstract
Recently, pre-formed V-type starch has become popular as a versatile carrier in encapsulation systems of containing starch-guest inclusion complexes (ICs). However, the differences in stabilizing and dissociating guests between ICs prepared by either the traditional method or the pre-formed "empty" helix method have not yet been elucidated. Here, starch-thymol ICs were prepared using the traditional high temperature-water method and the pre-formed method, covering different complexation temperatures and solvents, to compare the loading capacity, crystalline structure, thermal stability, and release properties. The highest content of thymol in ICs prepared by the pre-formed and the traditional method was 74.2 and 65.3 mg/g, respectively. Different from ICs prepared by the traditional method (V7-type crystal), ICs prepared by the pre-formed method mostly exhibited a V6a structure with larger crystallinities and a better short-range ordered structure. ICs prepared at 90 °C were type II complexes and efficiently protected thymol from rapid heat loss. A slow release was observed in both cases: about 45 % and 75 % of thymol were released from ICs prepared by the pre-formed and traditional methods, respectively, after two weeks of storage at 25 °C.
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Affiliation(s)
- Qing Gao
- SCUT-Zhuhai Institute of Modern Industrial Innovation, School of Food Science and Engineering, South China University of Technology, Guangzhou 510640, China
| | - Jiabao Zheng
- SCUT-Zhuhai Institute of Modern Industrial Innovation, School of Food Science and Engineering, South China University of Technology, Guangzhou 510640, China
| | - Paul Van der Meeren
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Ghent 9000, Belgium
| | - Bin Zhang
- SCUT-Zhuhai Institute of Modern Industrial Innovation, School of Food Science and Engineering, South China University of Technology, Guangzhou 510640, China; Overseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center), Guangzhou 510640, China
| | - Xiong Fu
- SCUT-Zhuhai Institute of Modern Industrial Innovation, School of Food Science and Engineering, South China University of Technology, Guangzhou 510640, China; Overseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center), Guangzhou 510640, China
| | - Qiang Huang
- SCUT-Zhuhai Institute of Modern Industrial Innovation, School of Food Science and Engineering, South China University of Technology, Guangzhou 510640, China; Overseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center), Guangzhou 510640, China.
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Liang R, Liu D, Zhao JG, Gao Q, Zhai ZG. [Advances in the use of neuromuscular electrical stimulation in the prevention of venous thromboembolism]. Zhonghua Jie He He Hu Xi Za Zhi 2024; 47:269-274. [PMID: 38448181 DOI: 10.3760/cma.j.cn112147-20231017-00243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Pharmacologic prophylaxis is the most commonly used prophylaxis for venous thromboembolism (VTE), but the pharmacologic prophylaxis is limited in patients at high risk of bleeding. Mechanical prophylaxis alone or in combination is an important method of VTE prophylaxis in patients at high risk of bleeding, but the current mainstream mechanical prophylaxis, which includes graded compression stockings, intermittent inflatable compression pumps and plantar venous compression pumps, has some limitations, leading to discomfort for patients wearing them due to the large contact area, and even affecting ability to perform daily activities. Many clinical studies have found that NMES combined with pharmacological prophylaxis has better efficacy and safety than pharmacological prophylaxis alone in preventing VTE in medical and surgical patients, and the preventive effect of NMES alone is not inferior to other mechanical prophylaxis. Besides, it also has the advantages of ease of wear and patient compliance. Currently, clinicians have limited experience and knowledge of NMES. We aimed to present the rationale, progress in clinical research and future perspective of NMES in VTE prophylaxis.
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Affiliation(s)
- R Liang
- Beijing University of Chinese Medicine China-Japan Friendship School of Clinical Medicine, Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Center for Respiratory Medicine Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing 100029, China
| | - D Liu
- Peking University China-Japan Friendship School of Clinical Medicine, Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Center for Respiratory Medicine Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing 100029, China
| | - J G Zhao
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Center for Respiratory Medicine Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing 100029, China
| | - Q Gao
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Center for Respiratory Medicine Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing 100029, China
| | - Z G Zhai
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Center for Respiratory Medicine Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing 100029, China
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14
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Zhuang B, Gan L, Liu B, Yuan W, Shi M, Peng A, Wang L, Chen X, Liu T, Zhang S, Wang S, Gao Q, Wang B, Zheng H, Liu C, Luo Y, Ye H, Lin H, Li Y, He Q, Zheng F, Luo P, Long G, Lu W, Li K, Yang J, Liu YC, Zhang Z, Li X, Zhang W, Zuo L. Efficacy, tolerability, and safety of the oral phosphate binder VS-505 (AP301). Nephrol Dial Transplant 2024:gfae053. [PMID: 38453435 DOI: 10.1093/ndt/gfae053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2024] Open
Abstract
BACKGROUND VS-505 (AP301), an acacia and ferric oxyhydroxide polymer, is a novel fiber-iron-based phosphate binder. This two-part phase 2 study evaluated the tolerability, safety, and efficacy of oral VS-505 administered three times daily with meals in treating hyperphosphatemia in chronic kidney disease (CKD) patients receiving maintenance hemodialysis (MHD). METHODS In Part 1, patients received dose-escalated treatment with VS-505 2.25, 4.50, and 9.00 g/day for 2 weeks each, guided by serum phosphorus levels. In Part 2, patients received randomized, open-label, fixed-dosage treatment with VS-505 (1.50, 2.25, 4.50, or 6.75 g/day) or sevelamer carbonate 4.80 g/day for 6 weeks. The primary efficacy endpoint was the change in serum phosphorus. RESULTS The study enrolled 158 patients (Part 1: 25; Part 2: 133), with 130 exposed to VS-505 in total. VS-505 was well tolerated. The most common adverse events were gastrointestinal disorders, mainly feces discolored (56%) and diarrhea (15%; generally during weeks 1‒2 of treatment). Most gastrointestinal disorders resolved without intervention, and none were serious. In Part 1, serum phosphorus significantly improved (mean change -2.0 mg/dL; 95% confidence interval -2.7, -1.4) after VS-505 dose escalation. In Part 2, serum phosphorus significantly and dose-dependently improved in all VS-505 arms, with clinically meaningful reductions with VS-505 4.50 and 6.75 g/day, and sevelamer carbonate 4.80 g/day (mean change -1.6 (-2.2, -1.0), -1.8 (-2.4, -1.2), and -1.4 (-2.2, -0.5) mg/dL, respectively). In both Parts, serum phosphorus reductions occurred within 1 week of VS-505 initiation, returning to baseline within 2 weeks of VS-505 discontinuation. CONCLUSION VS-505, a novel phosphate binder, was well tolerated with a manageable safety profile, and effectively and dose-dependently reduced serum phosphorus in CKD patients with hyperphosphatemia receiving MHD. Clinical Trial registration number: NCT04551300.
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Affiliation(s)
- Bing Zhuang
- Center for Kidney Disease, Second Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - Liangying Gan
- Department of Nephrology, Peking University People's Hospital, Beijing, China
| | - Bin Liu
- Nephrology Department, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
| | - Weijie Yuan
- Nephrology Department, Shanghai General Hospital, Shanghai, China
| | - Ming Shi
- Nephrology Department, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ai Peng
- Nephrology Department, Shanghai Tenth Hospital, Shanghai, China
| | - Lihua Wang
- Nephrology Department, The Second Hospital of Shanxi Medical University, Taiyuan, China
| | - Xiaolan Chen
- Nephrology Department, Affiliated Hospital of Nantong University, Nantong, China
| | - Tongqiang Liu
- Nephrology Department, Changzhou No. 2 People's Hospital, Changzhou, China
| | - Shiying Zhang
- Nephrology Department Jilin Province People's Hospital, Changchun, China
| | - Song Wang
- Nephrology Department, Peking University Third Hospital, Beijing, China
| | - Qing Gao
- Department of Nephrology, Zhongshan Hospital of Xiamen University School of Medicine, Xiamen, China
| | - Baoxing Wang
- Nephrology Department, The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Huixiao Zheng
- Nephrology Department, The Second Affiliated Hospital of Xingtai Medical College, Xingtai, China
| | - Changhua Liu
- Nephrology Department, Northern Jiangsu People's Hospital, Yangzhou, China
| | - Yuan Luo
- Center for Kidney Disease, Second Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - Hong Ye
- Center for Kidney Disease, Second Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - Hongli Lin
- Nephrology Department, The First Hospital of Dalian Medical University, Dalian, China
| | - Yiwen Li
- Department of Nephrology, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Qiang He
- Department of Nephrology, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Feng Zheng
- Nephrology Department, The Second Hospital of Dalian Medical University, Dalian, China
| | - Ping Luo
- Nephrology Department, The Second Hospital of Jilin University, Changchun, China
| | - Gang Long
- Department of Nephrology, Tianjin Union Medical Center, Tianjin, China
| | - Wei Lu
- Department of Nephrology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kanghui Li
- Nephrology Department, The Affiliated Hospital of Guilin Medical University, Guilin, China
| | - Junwei Yang
- Center for Kidney Disease, Second Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | | | - Zhizheng Zhang
- Shanghai Alebund Pharmaceuticals Limited, Shanghai, China
| | - Xiaolin Li
- Shanghai Alebund Pharmaceuticals Limited, Shanghai, China
| | - Weifeng Zhang
- Shanghai Alebund Pharmaceuticals Limited, Shanghai, China
| | - Li Zuo
- Department of Nephrology, Peking University People's Hospital, Beijing, China
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Duan M, Pan R, Gao Q, Wu X, Lin H, Yuan J, Zhang Y, Liu L, Tian Y, Fu T. A rapid multi-parametric quantitative MR imaging method to assess Parkinson's disease: a feasibility study. BMC Med Imaging 2024; 24:58. [PMID: 38443786 PMCID: PMC10916029 DOI: 10.1186/s12880-024-01229-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 02/15/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND MULTIPLEX is a single-scan three-dimensional multi-parametric MRI technique that provides 1 mm isotropic T1-, T2*-, proton density- and susceptibility-weighted images and the corresponding quantitative maps. This study aimed to investigate its feasibility of clinical application in Parkinson's disease (PD). METHODS 27 PD patients and 23 healthy control (HC) were recruited and underwent a MULTIPLEX scanning. All image reconstruction and processing were automatically performed with in-house C + + programs on the Automatic Differentiation using Expression Template platform. According to the HybraPD atlas consisting of 12 human brain subcortical nuclei, the region-of-interest (ROI) based analysis was conducted to extract quantitative parameters, then identify PD-related abnormalities from the T1, T2* and proton density maps and quantitative susceptibility mapping (QSM), by comparing patients and HCs. RESULTS The ROI-based analysis revealed significantly decreased mean T1 values in substantia nigra pars compacta and habenular nuclei, mean T2* value in subthalamic nucleus and increased mean QSM value in subthalamic nucleus in PD patients, compared to HCs (all p values < 0.05 after FDR correction). The receiver operating characteristic analysis showed all these four quantitative parameters significantly contributed to PD diagnosis (all p values < 0.01 after FDR correction). Furthermore, the two quantitative parameters in subthalamic nucleus showed hemicerebral differences in regard to the clinically dominant side among PD patients. CONCLUSIONS MULTIPLEX might be feasible for clinical application to assist in PD diagnosis and provide possible pathological information of PD patients' subcortical nucleus and dopaminergic midbrain regions.
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Affiliation(s)
- Min Duan
- Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Rongrong Pan
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, 210006, Nanjing, Jiangsu Province, China
| | - Qing Gao
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, 210006, Nanjing, Jiangsu Province, China
| | - Xinying Wu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, 210006, Nanjing, Jiangsu Province, China
| | - Hai Lin
- Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Jianmin Yuan
- Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Yamei Zhang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, 210006, Nanjing, Jiangsu Province, China
| | - Lindong Liu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, 210006, Nanjing, Jiangsu Province, China
| | - Youyong Tian
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, 210006, Nanjing, Jiangsu Province, China.
| | - Tong Fu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, 210006, Nanjing, Jiangsu Province, China.
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Bian Z, Wu X, Chen Q, Gao Q, Xue X, Wang Y. Oct4 activates IL-17A to orchestrate M2 macrophage polarization and cervical cancer metastasis. Cancer Immunol Immunother 2024; 73:73. [PMID: 38430256 PMCID: PMC10908604 DOI: 10.1007/s00262-023-03596-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 12/10/2023] [Indexed: 03/03/2024]
Abstract
BACKGROUND Cervical cancer is a common malignant tumor in the female. Interleukin (IL)-17A is a proinflammatory factor and exerts a vital function in inflammatory diseases and cancers. M2 macrophage has been confirmed to promote tumor development. Nevertheless, it is not yet known whether IL-17A facilitates cervical cancer development by inducing M2 macrophage polarization. Therefore, this study was conducted to investigate the regulatory effect of IL-17A on M2 macrophage polarization and the underlying mechanism in cervical cancer development. METHODS RT-qPCR was utilized for testing IL-17A expression in cancer tissues and cells. Flow cytometry was applied to evaluate the M1 or M2 macrophage polarization. Cell proliferative, migratory, and invasive capabilities were measured through colony formation and transwell assays. ChIP and luciferase reporter assays were applied to determine the interaction between IL-17A and octamer-binding transcription factor 4 (OCT4). RESULTS IL-17A expression and concentration were high in metastatic tissues and cells of cervical cancer. IL-17A was found to facilitate M2 macrophage polarization in cervical cancer. Furthermore, IL-17A facilitated the macrophage-mediated promotion of cervical cancer cell proliferative, migratory, and invasive capabilities. Mechanistic assays manifested that Oct4 binds to and transcriptionally activated IL-17A in cervical cancer cells. Furthermore, Oct4 promoted cervical cancer cell malignant phenotype and M2 macrophage polarization by activating the p38 pathway that, in turn, upregulated IL-17A. Additionally, in vivo experiments confirmed that Oct4 knockdown reduced tumor growth and metastasis. CONCLUSION Oct4 triggers IL-17A to facilitate the polarization of M2 macrophages, which promotes cervical cancer cell metastasis.
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Affiliation(s)
- Zhuoqiong Bian
- Department of the Fifth Rheumatology, The Fifth Hospital of Xi'an City, Xi'an, 710000, Shaanxi, China
| | - Xiaoling Wu
- Department of Obstetrics and Gynecology, Second Affiliated Hospital, Xi'an Jiao Tong University, 157 West Fifth Road, Xincheng District, Xi'an, 710000, Shaanxi, China
| | - Qing Chen
- Department of Obstetrics and Gynecology, Second Affiliated Hospital, Xi'an Jiao Tong University, 157 West Fifth Road, Xincheng District, Xi'an, 710000, Shaanxi, China
| | - Qing Gao
- Department of Obstetrics and Gynecology, Second Affiliated Hospital, Xi'an Jiao Tong University, 157 West Fifth Road, Xincheng District, Xi'an, 710000, Shaanxi, China
| | - Xiang Xue
- Department of Obstetrics and Gynecology, Second Affiliated Hospital, Xi'an Jiao Tong University, 157 West Fifth Road, Xincheng District, Xi'an, 710000, Shaanxi, China
| | - Yidong Wang
- Department of Obstetrics and Gynecology, Second Affiliated Hospital, Xi'an Jiao Tong University, 157 West Fifth Road, Xincheng District, Xi'an, 710000, Shaanxi, China.
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Chen B, Zhang X, Gao Q, Yang D, Chen J, Chang X, Zhang C, Bai Y, Cui M, Wang S, Li H, Flavel BS, Chen J. The Development of Carbon/Silicon Heterojunction Solar Cells through Interface Passivation. Adv Sci (Weinh) 2024; 11:e2306993. [PMID: 38233212 DOI: 10.1002/advs.202306993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/30/2023] [Indexed: 01/19/2024]
Abstract
Passivating contactsin heterojunction (HJ) solar cells have shown great potential in reducing recombination losses, and thereby achieving high power conversion efficiencies in photovoltaic devices. In this direction, carbon nanomaterials have emerged as a promising option for carbon/silicon (C/Si) HJsolar cells due to their tunable band structure, wide spectral absorption, high carrier mobility, and properties such as multiple exciton generation. However, the current limitations in efficiency and active area have hindered the industrialization of these devices. In this review, they examine the progress made in overcoming these constraints and discuss the prospect of achieving high power conversion efficiency (PCE) C/Si HJ devices. A C/Si HJ solar cell is also designed by introducing an innovative interface passivation strategy to further boost the PCE and accelerate the large area preparationof C/Si devices. The physical principle, device design scheme, and performanceoptimization approaches of this passivated C/Si HJ cells are discussed. Additionally, they outline potential future pathways and directions for C/Si HJ devices, including a reduction in their cost to manufacture and their incorporation intotandem solar cells. As such, this review aims to facilitate a deeperunderstanding of C/Si HJ solar cells and provide guidance for their further development.
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Affiliation(s)
- Bingbing Chen
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Xuning Zhang
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Qing Gao
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Dehua Yang
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Jingwei Chen
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Xuan Chang
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Cuili Zhang
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Yuhua Bai
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Mengnan Cui
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Shufang Wang
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
| | - Han Li
- Institute of Nanotechnology, Karlsruhe Institute of Technology, Kaiserstrasse 12, 76131, Karlsruhe, Germany
| | - Benjamin S Flavel
- Institute of Nanotechnology, Karlsruhe Institute of Technology, Kaiserstrasse 12, 76131, Karlsruhe, Germany
| | - Jianhui Chen
- Advanced Passivation Technology Lab, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
- Province-Ministry Co-Construction Collaborative Innovation Center of Hebei Photovoltaic Technology, College of Physics Science and Technology, Hebei University, Baoding, 071002, China
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Li J, Xie S, Gao Q, Deng Z. Evaluation of the potential of endophytic Trichoderma sp. isolated from medicinal plant Ampelopsis japonica against MRSA and bioassay-guided separation of the anti-MRSA compound. Braz J Microbiol 2024; 55:543-556. [PMID: 38261262 PMCID: PMC10920522 DOI: 10.1007/s42770-024-01250-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 01/04/2024] [Indexed: 01/24/2024] Open
Abstract
Endophytic fungi have been recognized as a valuable source for the production of biologically active compounds with potential applications in various domains. This study aimed to isolate endophytic fungi from Ampelopsis japonica (Thunb.) Makino and assess their anti-MRSA activity. Meanwhile, chromatographic separation techniques were applied to analyze the constituents of endophytic fungal secondary metabolites. The isolate BLR24, which exhibited strong inhibition activity against MRSA, was identified as Trichoderma virens based on morphological characteristics and ITS sequence analyses. The ethyl acetate extract of BLR24 (EA-BLR24) showed good anti-MRSA activity with the MIC and MBC values of 25 μg/mL and 50 μg/mL, separately. The inhibition of biofilm formation was up to 34.67% under MIC concentration treatment. Meanwhile, EA-BLR24 could significantly reduce the expression of biofilm-related genes (icaA, sarA, and agrA) of MRSA. Based on LC-MS/MS analysis, twenty compounds in EA-BLR24 could be annotated using the GNPS platform, mainly diketopiperazines. The anti-MRSA compound (Fr.1.1) was obtained from EA-BLR24 by bioassay-guided fractionation and determined as gliotoxin. The results indicated that endophytic Trichoderma virens BLR24 isolated from the medical plant A. japonica roots could be a promising source of natural anti-MRSA agents. Endophytic fungal secondary metabolites are abundant in biologically active compounds. Endophytic fungi from medicinal plants could be a source yielding bioactive metabolites of pharmaceutical importance.
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Affiliation(s)
- Jianbin Li
- School of Basic Medical Sciences, Guangdong Provincial Key Laboratory of Pharmaceutical Bioactive Substances, Guangdong Pharmaceutical University, Guangzhou, 510006, People's Republic of China
- School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Zhongshan, 528458, People's Republic of China
| | - Siyun Xie
- School of Basic Medical Sciences, Guangdong Provincial Key Laboratory of Pharmaceutical Bioactive Substances, Guangdong Pharmaceutical University, Guangzhou, 510006, People's Republic of China
- School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Zhongshan, 528458, People's Republic of China
| | - Qing Gao
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou, 510006, People's Republic of China
| | - Zujun Deng
- School of Basic Medical Sciences, Guangdong Provincial Key Laboratory of Pharmaceutical Bioactive Substances, Guangdong Pharmaceutical University, Guangzhou, 510006, People's Republic of China.
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An X, Zhang Y, Sun W, Kang X, Ji H, Sun Y, Jiang L, Zhao X, Gao Q, Lian F, Tong X. Early effective intervention can significantly reduce all-cause mortality in prediabetic patients: a systematic review and meta-analysis based on high-quality clinical studies. Front Endocrinol (Lausanne) 2024; 15:1294819. [PMID: 38495794 PMCID: PMC10941028 DOI: 10.3389/fendo.2024.1294819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 02/19/2024] [Indexed: 03/19/2024] Open
Abstract
Background Reducing the occurrence of diabetes is considered a primary criterion for evaluating the effectiveness of interventions for prediabetes. There is existing evidence that early lifestyle-based interventions can significantly decrease the incidence of diabetes. However, whether effective interventions can reduce long-term outcomes in patients, including all-cause mortality, cardiovascular risks, and the occurrence of microvascular complications, which are the most concerning issues for both patients and clinicians, remains a subject of inconsistent research findings. And there is no direct evidence to answer whether effective intervention has long-term benefits for prediabetic patients. Therefore, we conducted a systematic review and meta-analysis to assess the relationship between early effective intervention and macrovascular and microvascular complications in prediabetic patients. Methods PubMed, Embase, and Cochrane Central Register of Controlled Trials were searched for the randomized controlled trials of lifestyle or/and drugs intervention in prediabetes from inception to 2023.9.15. Two investigators independently reviewed the included studies and extracted relevant data. Random or fixed effects model meta-analysis to derive overall relative risk (RR) with 95% CI for all-cause mortality, cardiovascular events, and microvascular complications. Results As of September 15, 2023, a total of 7 effective intervention studies were included, comprising 26 articles out of 25,671 articles. These studies involved 26,389 patients with a total follow-up duration of 178,038.6 person-years. The results indicate that effective intervention can significantly reduce all-cause mortality in prediabetic patients without a history of cardiovascular disease by 17% (RR 0.83, 95% CI 0.70-0.98). Additionally, effective intervention reduced the incidence of retinopathy by 38% (RR 0.62, 95% CI 0.70-0.98). Furthermore, the study results suggest that women and younger individuals have lower all-cause mortality and cardiovascular mortality. Subsequently, we conducted an in-depth analysis of patients without a history of cardiovascular disease. The results revealed that prediabetic patients with a 10-year cardiovascular risk >10% experienced more significant benefits in terms of all-cause mortality (P=0.01). When comparing the results of all-cause mortality and cardiovascular mortality from the Da Qing Diabetes Prevention Outcome Study longitudinally, it was evident that the duration of follow-up is a key factor influencing long-term benefits. In other words, the beneficial effects become more pronounced as the intervention duration reaches a certain threshold. Conclusion Early effective intervention, which significantly reduces the incidence of diabetes, can effectively lower all-cause mortality in prediabetic patients without a history of cardiovascular disease (especially those with a 10-year cardiovascular risk >10%), with women and younger individuals benefiting more significantly. Additionally, the duration of follow-up is a key factor influencing outcomes. The conclusions of this study can provide evidence-based guidance for the clinical treatment of prediabetic patients to prevent cardiovascular and microvascular complications. Systematic review registration https://www.crd.york.ac.uk/prospero, identifier CRD42020160985.
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Affiliation(s)
- Xuedong An
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yuehong Zhang
- Fangshan Hospital of Beijing University of Chinese Medicine, Beijing, China
| | - Wenjie Sun
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiaomin Kang
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Hangyu Ji
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yuting Sun
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Linlin Jiang
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xuefei Zhao
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Qing Gao
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Fengmei Lian
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiaolin Tong
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
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Gao Q, Zhang Y, Wang X, Wang R, Zhang L. Regulation of nociception threshold by norepinephrine through adrenergic α2 receptor in rat models of Parkinson's disease. CNS Neurosci Ther 2024; 30:e14446. [PMID: 37721421 PMCID: PMC10916421 DOI: 10.1111/cns.14446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/07/2023] [Accepted: 08/21/2023] [Indexed: 09/19/2023] Open
Abstract
BACKGROUND The mechanism of pain symptoms in Parkinson's disease (PD) is unclear. Norepinephrine (NE) regulates neuropathic pain through ascending and descending pathways. However, the loss of NE neurons in the brain of patients with PD is obvious, it is speculated that NE is involved in the occurrence of PD pain symptoms. AIMS To investigate the effect of NE on the activation of brain cells through adrenergic α2 receptor, so as to regulate the nociception threshold in a 6-OHDA-induced animal model of PD. METHODS PD rat model was established by 6-OHDA injection (6-OHDA group). DSP-4 (or anti-DBH-saporin) was used to reduce the NE level of the PD rat brain. The heat sensitivity threshold (HST) and pressure withdrawal threshold (PWT) were measured. Tyrosine hydroxylase and NE in rat brains were detected by Elisa. The percentage of GFAP-positive cells in the prefrontal cortex, cingulate gyrus and striatum of rats was detected by immunohistochemistry and immunofluorescence. GFAP protein was semiquantified by method of western blot. Then yohimbine and guanfacine were used to increase the NE level in PD rats, and the above experimental changes were observed after drug application. RESULTS The contents of NE in the brain of 6-OHDA-induced PD rats were lower than that of control group. After DSP-4 (or anti-DBH-saporin) injection, PD rats showed the lowest NE level (compared with 6-OHDA group, p ≤ 0.05), and after yohimbine and guanfacine were applied to 6-OHDA group, the contents of NE increased in the prefrontal cortex of rats. The HST and PWT of 6-OHDA group were significantly lower than those of control group, and after DSP-4 (or anti-DBH-saporin) injection, the HST and PWT of rats were lower than those of 6-OHDA group, and after the administration of yohimbine and guanfacine, both HST and PWT were significantly increased. GFAP-positive cells increased in prefrontal cortex and anterior cingulate gyrus of 6-OHDA group rats, and more significantly increased after DSP-4 (or anti-DBH-saporin) injection, and significantly reduced after yohimbine and guanfacine were used. CONCLUSIONS The change of norepinephrine content can affect the activation of prefrontal and cingulate gyrus glial cells and participate in the regulation of nociception threshold in PD rats. Adrenergic α2 receptor agonist and central presynaptic membrane α2 receptor blocker both affect cell activation and improve hyperalgesia.
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Affiliation(s)
- Qing Gao
- Department of NeurologyThe Second Affiliated Hospital of Harbin Medical UniversityHarbinChina
| | - Yingying Zhang
- Department of NeurologyThe Second Affiliated Hospital of Harbin Medical UniversityHarbinChina
| | - Xiaoying Wang
- Department of NeurologyThe Second Affiliated Hospital of Harbin Medical UniversityHarbinChina
| | - Rui Wang
- Department of NeurologyThe Second Affiliated Hospital of Harbin Medical UniversityHarbinChina
| | - Limei Zhang
- Department of NeurologyThe Second Affiliated Hospital of Harbin Medical UniversityHarbinChina
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Chen Y, Lu W, Zhou Y, Hu Z, Wu H, Gao Q, Shi J, Wu W, Lv S, Yao K, He Y, Xie Z. A Spatiotemporal Controllable Biomimetic Skin for Accelerating Wound Repair. Small 2024:e2310556. [PMID: 38386291 DOI: 10.1002/smll.202310556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/04/2024] [Indexed: 02/23/2024]
Abstract
Skin injury repair is a dynamic process involving a series of interactions over time and space. Linking human physiological processes with materials' changes poses a significant challenge. To match the wound healing process, a spatiotemporal controllable biomimetic skin is developed, which comprises a three-dimensional (3D) printed membrane as the epidermis, a cell-containing hydrogel as the dermis, and a cytokine-laden hydrogel as the hypodermis. In the initial stage of the biomimetic skin repair wound, the membrane frame aids wound closure through pre-tension, while cells proliferate within the hydrogel. Next, as the frame disintegrates over time, cells released from the hydrogel migrate along the residual membrane. Throughout the process, continuous cytokines release from the hypodermis hydrogel ensures comprehensive nourishment. The findings reveal that in the rat full-thickness skin defect model, the biomimetic skin demonstrated a wound closure rate eight times higher than the blank group, and double the collagen content, particularly in the early repair process. Consequently, it is reasonable to infer that this biomimetic skin holds promising potential to accelerate wound closure and repair. This biomimetic skin with mechanobiological effects and spatiotemporal regulation emerges as a promising option for tissue regeneration engineering.
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Affiliation(s)
- Yuewei Chen
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Weiying Lu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, 310000, China
| | - Yanyan Zhou
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, 310000, China
| | - Zihe Hu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, 310000, China
| | - Haiyan Wu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, 310000, China
| | - Qing Gao
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Jue Shi
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, 310000, China
| | - Wenzhi Wu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, 310000, China
| | - Shang Lv
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Ke Yao
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Yong He
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Zhijian Xie
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, 310000, China
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Liu X, Guo J, Jiang Z, Liu X, Chen H, Zhang Y, Wang J, Liu C, Gao Q, Chen H. Compressed cerebellar functional connectome hierarchy in spinocerebellar ataxia type 3. Hum Brain Mapp 2024; 45:e26624. [PMID: 38376240 PMCID: PMC10878347 DOI: 10.1002/hbm.26624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 01/27/2024] [Accepted: 01/29/2024] [Indexed: 02/21/2024] Open
Abstract
Spinocerebellar ataxia type 3 (SCA3) is an inherited movement disorder characterized by a progressive decline in motor coordination. Despite the extensive functional connectivity (FC) alterations reported in previous SCA3 studies in the cerebellum and cerebellar-cerebral pathways, the influence of these FC disturbances on the hierarchical organization of cerebellar functional regions remains unclear. Here, we compared 35 SCA3 patients with 48 age- and sex-matched healthy controls using a combination of voxel-based morphometry and resting-state functional magnetic resonance imaging to investigate whether cerebellar hierarchical organization is altered in SCA3. Utilizing connectome gradients, we identified the gradient axis of cerebellar hierarchical organization, spanning sensorimotor to transmodal (task-unfocused) regions. Compared to healthy controls, SCA3 patients showed a compressed hierarchical organization in the cerebellum at both voxel-level (p < .05, TFCE corrected) and network-level (p < .05, FDR corrected). This pattern was observed in both intra-cerebellar and cerebellar-cerebral gradients. We observed that decreased intra-cerebellar gradient scores in bilateral Crus I/II both negatively correlated with SARA scores (left/right Crus I/II: r = -.48/-.50, p = .04/.04, FDR corrected), while increased cerebellar-cerebral gradients scores in the vermis showed a positive correlation with disease duration (r = .48, p = .04, FDR corrected). Control analyses of cerebellar gray matter atrophy revealed that gradient alterations were associated with cerebellar volume loss. Further FC analysis showed increased functional connectivity in both unimodal and transmodal areas, potentially supporting the disrupted cerebellar functional hierarchy uncovered by the gradients. Our findings provide novel evidence regarding alterations in the cerebellar functional hierarchy in SCA3.
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Affiliation(s)
- Xinyuan Liu
- Department of Radiology, Southwest HospitalArmy Medical University (Third Military Medical University)ChongqingChina
- School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Jing Guo
- School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's HospitalUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Zhouyu Jiang
- School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Xingli Liu
- School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Hui Chen
- Department of Radiology, Southwest HospitalArmy Medical University (Third Military Medical University)ChongqingChina
| | - Yuhan Zhang
- Department of Radiology, Southwest HospitalArmy Medical University (Third Military Medical University)ChongqingChina
| | - Jian Wang
- Department of Radiology, Southwest HospitalArmy Medical University (Third Military Medical University)ChongqingChina
| | - Chen Liu
- Department of Radiology, Southwest HospitalArmy Medical University (Third Military Medical University)ChongqingChina
| | - Qing Gao
- MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
- School of Mathematical SciencesUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Huafu Chen
- Department of Radiology, Southwest HospitalArmy Medical University (Third Military Medical University)ChongqingChina
- School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's HospitalUniversity of Electronic Science and Technology of ChinaChengduChina
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Tang S, An X, Sun W, Zhang Y, Yang C, Kang X, Sun Y, Jiang L, Zhao X, Gao Q, Ji H, Lian F. Parallelism and non-parallelism in diabetic nephropathy and diabetic retinopathy. Front Endocrinol (Lausanne) 2024; 15:1336123. [PMID: 38419958 PMCID: PMC10899692 DOI: 10.3389/fendo.2024.1336123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
Diabetic nephropathy (DN) and diabetic retinopathy (DR), as microvascular complications of diabetes mellitus, are currently the leading causes of end-stage renal disease (ESRD) and blindness, respectively, in the adult working population, and they are major public health problems with social and economic burdens. The parallelism between the two in the process of occurrence and development manifests in the high overlap of disease-causing risk factors and pathogenesis, high rates of comorbidity, mutually predictive effects, and partial concordance in the clinical use of medications. However, since the two organs, the eye and the kidney, have their unique internal environment and physiological processes, each with specific influencing molecules, and the target organs have non-parallelism due to different pathological changes and responses to various influencing factors, this article provides an overview of the parallelism and non-parallelism between DN and DR to further recognize the commonalities and differences between the two diseases and provide references for early diagnosis, clinical guidance on the use of medication, and the development of new drugs.
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Affiliation(s)
- Shanshan Tang
- College of Traditional Chinese Medicine, Changchun University of Traditional Chinese Medicine, Changchun, China
| | - Xuedong An
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Wenjie Sun
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Yuehong Zhang
- Fangshan Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Cunqing Yang
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiaomin Kang
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Yuting Sun
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Linlin Jiang
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Xuefei Zhao
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Qing Gao
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Hangyu Ji
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
| | - Fengmei Lian
- Guang’an Men Hospital of China Academy of Chinese Medical Sciences, Beijing, China
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Wang Q, Gan Z, Gao Q, Wang M, Zhan B. The associations of risk of cardiovascular disease with development stages of diabetes in Chinese population: findings from a retrospective cohort study in QuZhou city. BMC Endocr Disord 2024; 24:18. [PMID: 38302943 PMCID: PMC10835855 DOI: 10.1186/s12902-024-01544-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 01/19/2024] [Indexed: 02/03/2024] Open
Abstract
BACKGROUND Risk analysis is an important area of research in diabetes and cardiovascular disease (CVD), both of which have significant global health burdens. Although there is evidence that patients with prediabetes and diabetes mellitus may have an increased risk of CVD, few studies have been conducted in mainland China. METHODS This retrospective cohort study utilized data from the Quzhou City Resident Health Information System and the Zhejiang Province Chronic Disease Surveillance System in China. Prediabetes and diabetes mellitus were the exposure interests, and the outcome event was defined as the onset of cardiovascular and cerebrovascular disease (including coronary heart disease and stroke). The start date of the study was January 1, 2015, and the follow-up deadline was December 31, 2020. Multivariate Cox proportional hazard model were used to assess the associations among prediabetes, diabetes, and CVD risk. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. Our study used follow-up time as the time scale, while adjusting for age, sex, physical activity, smoking, alcohol consumption, BMI in the models Sensitivity analyses were conducted to assess the stability of the results, by excluding participants who smoked and drank alcohol, participants who developed CVD in the first year of follow-up. RESULTS In total, 138,970 participants were included in our study, with a mean follow-up of 5.8 years. The mean age of the participants was 58.82 ± 14.44 years, with 42.79% (n = 59,466) males and 57.21% (n = 79,504) females. During the study period 4357 cases of CVD were recorded. Participants with prediabetes (P = 0.003) and diabetes (P < 0.001) had a higher risk of CVD than those who were Normal (HR [95% CI]: 1.14 [1.05-1.24]; 1.68 [1.55-1.81], respectively). Prediabetes and patients living with diabetes had a 14% and 68% increased risk of CVD, respectively. The results of the sensitivity analyses were consistent with those of the main analyses after excluding those who developed CVD within one year of follow-up and those who were concurrent smokers or alcohol drinkers. CONCLUSIONS Our research found that prediabetes is significantly associated with the risk of diabetes and CVD.
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Affiliation(s)
- Qi Wang
- Zhejiang Chinese Medicine University, 548 Binwen Road, Binjiang District, 310053, Hangzhou, Zhejiang Province, China
| | - Zhijuan Gan
- Quzhou Center for Disease Control and Prevention , 154 Xi'an Road, Kecheng District, 324003, Quzhou , Zhejiang Province, China
| | - Qing Gao
- Zhejiang Chinese Medicine University, 548 Binwen Road, Binjiang District, 310053, Hangzhou, Zhejiang Province, China
| | - Meng Wang
- Zhejiang Provincial Center for Disease Control and Prevention, 3399 Binsheng Road, Hangzhou, China.
| | - Bingdong Zhan
- Zhejiang Chinese Medicine University, 548 Binwen Road, Binjiang District, 310053, Hangzhou, Zhejiang Province, China.
- Quzhou Center for Disease Control and Prevention , 154 Xi'an Road, Kecheng District, 324003, Quzhou , Zhejiang Province, China.
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Zhang C, Liu Y, Corner L, Gao Q, Kang YT, Shi H, Li JW, Shen J. Interaction between handgrip strength and vitamin D deficiency on all-cause mortality in community-dwelling older adults: a prospective cohort study. Public Health 2024; 227:1-8. [PMID: 38096620 DOI: 10.1016/j.puhe.2023.11.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 02/18/2024]
Abstract
OBJECTIVE Muscle strength decline and vitamin D deficiency are coexisting conditions associated with multiple adverse health outcomes. This prospective study aimed to investigate the multiplicative and additive interactions between handgrip strength (HS) and serum 25-hydroxyvitamin D [25(OH)D] on all-cause mortality in Chinese community-dwelling older adults. STUDY DESIGN This is a population-based cohort study. METHODS 2635 older adults (85.15 ± 12.01 years) were recruited from the Chinese Longitudinal Healthy Longevity Survey (2012-2018). Low HS was defined according to the Asian Working Group for Sarcopenia 2019 updated consensus (<28 kg for men and <18 kg for women). Serum 25(OH)D < 50 nmol/L were defined as vitamin D deficiency. Cox proportional hazard models were used to examine the association of HS and 25(OH)D with all-cause mortality. Socio-demographics, health status, and clinical characteristics were included as covariates. RESULTS 1715 (65.09 %) and 1885 (71.54 %) participants had low HS and vitamin D deficiency, respectively. During a median follow-up of 3.52 years, 1107 older people died. After multivariable adjustment, both HS and 25(OH)D levels were inversely associated with all-cause mortality risk (Ps < 0.001). The hazard ratios (HRs) of low HS and vitamin D deficiency for all-cause mortality were 1.73 (95 % CI: 1.41-2.13) and 1.61 (95 % CI: 1.32-1.93), respectively. Although significant multiplicative interactions were not found, the association between low HS and all-cause mortality was attenuated in the higher 25(OH)D subgroup than in the lower 25(OH)D subgroup (stratified by 50 nmol/L). The multiple-adjusted HR of mortality for combined low HS and vitamin D deficiency was 2.18 (95 % CI: 1.73-2.56), which was higher than that for these two conditions alone. Significant additive interactions between low HS and vitamin D deficiency on mortality were observed (relative excess risk due to interaction: 0.71, 95 % CI: 0.37-1.05). CONCLUSIONS Low HS and low 25(OH)D levels synergistically increased the risk of all-cause mortality. Our results added new insights to the priority of early detection for older adults with comorbid muscle strength decline and vitamin D deficiency.
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Affiliation(s)
- C Zhang
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital, National Center of Gerontology of National Health Commission, Beijing 100730, China
| | - Y Liu
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital, National Center of Gerontology of National Health Commission, Beijing 100730, China
| | - L Corner
- UK National Innovation Centre for Ageing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Q Gao
- Department of Science Research, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Y T Kang
- Department of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - H Shi
- Department of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J W Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital, National Center of Gerontology of National Health Commission, Beijing 100730, China.
| | - J Shen
- Department of Geriatrics, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China.
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Gao Q, He F, Wang H, Huang W, Dong H. A primary study of ethanol production in postmortem liver and muscle tissue of rats. J Forensic Leg Med 2024; 102:102653. [PMID: 38422828 DOI: 10.1016/j.jflm.2024.102653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 12/15/2023] [Accepted: 01/30/2024] [Indexed: 03/02/2024]
Abstract
OBJECTIVE To study the characteristics of postmortem ethanol production and its relation with alcohol congeners in postmortem rat liver and muscle tissues. METHOD Postmortem liver and muscle tissues in Sprague-Dawley rats, from postmortem time interval (PMI) day 0-20, were analyzed via headspace gas chromatograph flame ionization detection to observe production of postmortem ethanol and 5 selected alcohol congeners. RESULT 1. Putrid ethanol production increased gradually to a peak and then decreased with the prolongation of PMI; 2. Acetaldehyde, 1-propanol, and 3-methyl-butyraldehyde were produced along with postmortem ethanol; 1-butanol was only detected from day 11-20; 3. The concentrations of acetaldehyde, 1-propanol and 3-methyl-butyraldehyde was related with ethanol production. Fifteen mathematical models were constructed for putrid ethanol production based on acetaldehyde, 1-propanol, and 3-methyl-butyraldehyde. CONCLUSION A peak in postmortem ethanol production was identified. The production trends of acetaldehyde, 1-propanol, and 3-methyl-butyraldehyde in the liver, and of 1-propanol in muscle, were consistent with those of ethanol, and could potentially to be used as biomarkers of postmortem ethanol production. Further human samples and data analysis are needed to verify this.
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Affiliation(s)
- Qing Gao
- Department of Forensic Medicine, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, Hubei, 430030, PR China; Taikang Medical School (School of Basic Medical Sciences), Wuhan University, No. 115 Donghu Road, Wuhan, Hubei, 430071, PR China.
| | - Fanggang He
- Taikang Medical School (School of Basic Medical Sciences), Wuhan University, No. 115 Donghu Road, Wuhan, Hubei, 430071, PR China.
| | - Hao Wang
- Taikang Medical School (School of Basic Medical Sciences), Wuhan University, No. 115 Donghu Road, Wuhan, Hubei, 430071, PR China.
| | - Weisheng Huang
- Department of Forensic Medicine, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, Hubei, 430030, PR China.
| | - Hongmei Dong
- Department of Forensic Medicine, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, Hubei, 430030, PR China.
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Song H, Xiong M, Yu C, Ren B, Zhong M, Zhou S, Gao Q, Ou C, Wang X, Lu J, Zeng M, Cai X, Peng Q. Huang-Qi-Jian-Zhong-Tang accelerates healing of indomethacin-induced gastric ulceration in rats via anti-inflammatory and antioxidant mechanisms. J Ethnopharmacol 2024; 319:117264. [PMID: 37783407 DOI: 10.1016/j.jep.2023.117264] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 10/04/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Huang-Qi-Jian-Zhong-Tang (HQJZT) is a canonical traditional Chinese medicine (TCM) formula that has been widely used in both the prevention and treatment of gastrointestinal diseases, including gastric ulcer, duodenal ulcer, and chronic atrophic gastritis, in China. AIM OF THE STUDY In the present study, we investigated the gastroprotective potential of HQJZT in a rat model of indomethacin (IND)-induced gastric ulcer and explained the biochemical, cellular, and molecular mechanisms involved. MATERIALS AND METHODS Observations were conducted at the macroscopic level to ascertain the ulcer index (UI) and the curative index (CI). Histopathological examinations were conducted, and a microscopic score (MS) was computed. The gastric juice volume, total acidity, pH value, and pepsin activity were quantified. Antioxidant and oxidative parameters were assessed, namely GSH, CAT, SOD, and MDA content. The RFLSI Pro instrument was employed to measure the blood flow within the gastric mucosa continuously. The mRNA levels of the inflammatory cytokines were assessed using droplet digital PCR (ddPCR). Molecular docking was employed to examine the interaction between representative active components of HQJZT and the binding sites associated with the NF-κB and STAT signaling pathways. The protein expression and localization of p-JAK, p-STAT, p-IκBβ, and p-NF-κB were evaluated through immunofluorescence analysis. RESULTS The administration of HQJZT treatment demonstrated a significant reduction in gastric lesions induced by IND, leading to a notable decrease in the UI. Additionally, HQJZT treatment significantly decreased gastric juice volume, acidity, and pepsin activity, accompanied by increased pH value. IND-treated stomachs exhibited severe hemorrhagic necrosis, submucosal edema, and epithelial cell destruction. However, the administration of HQJZT effectively counteracted these pathological changes. Furthermore, HQJZT administration significantly increased blood flow to the gastric mucosa. HQJZT enhanced antioxidant defenses and modulated oxidative stress by increasing SOD, CAT, and GSH activities while reducing MDA levels. Moreover, HQJZT reversed IND-induced increases in mRNA expression levels of inflammatory cytokines. Molecular docking analysis revealed that the representative active components of HQJZT could bind to the NF-κB and STAT signaling pathways. In addition, immunofluorescence microscopy revealed that HQJZT markedly attenuated the phosphorylation of IκΒβ, NF-κB, JAK, and STAT. CONCLUSIONS The therapeutic and protective effect of HQJZT on gastric ulcers is attributed to its ability to suppress gastric acid secretion, enhance antioxidative defenses and blood flow, mitigate proinflammatory cytokines, and inhibit the activation of NF-κB and STAT signaling pathways.
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Affiliation(s)
- Houpan Song
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Meng Xiong
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Chang Yu
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Baoping Ren
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Meiqi Zhong
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Shunhua Zhou
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Qing Gao
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Chen Ou
- Hunan Provincial Key Laboratory for Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Xiaojuan Wang
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Jing Lu
- Hunan Provincial Key Laboratory for Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Meiyan Zeng
- School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Xiong Cai
- School of International Education, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
| | - Qinghua Peng
- Hunan Provincial Key Laboratory of Traditional Chinese Medicine Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan Province, China; Hunan Provincial Key Laboratory for Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan Province, China.
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Zhao W, Gao Q, Cao Y, Meng Y, He J. Kinetics of sterilization of atomized slightly acidic electrolyzed water on tableware. Heliyon 2024; 10:e24721. [PMID: 38312634 PMCID: PMC10835237 DOI: 10.1016/j.heliyon.2024.e24721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/05/2023] [Accepted: 01/12/2024] [Indexed: 02/06/2024] Open
Abstract
The aim of this study was to elucidate the kinetics of atomization of slightly acidic electrolyzed water (SAEW) for use in sterilization of secondary contaminated tableware surfaces. The sterilization efficacy of SAEW was assessed on the basis of the change in the total number of colonies with different contamination levels (101 CFU/mL and 102 CFU/mL), atomization time (10, 20, 30, 40, and 50 s), atomizing distance (5, 10, 15, 20, 25, and 30 cm), and available chlorine concentration (ACC; 25.2, 30.2, 34.9, 40.5, 44.8, and 53.3 mg/L) as the main influencing factors. According to the relationship among flux, atomization area, and time, a kinetic model of SAEW atomization for the sterilization of tableware surfaces was established. The results indicated that the sterilization efficacy of SAEW gradually improved with decreased contamination levels (12.69 %-15.74 %), extended atomization time (13.68 %-46.58 %), and increased ACC (36.89 %-95.14 %). Based on the kinetics analysis, the change law of the kinetic model of SAEW atomization and sterilization of tableware surfaces with secondary pollution was found to be consistent with the change law of sterilization (r2 > 0.8). The results of this study provide a theoretical basis for SAEW atomization for sterilization of secondary contaminated tableware surfaces and also contributes to the improvement of technological theory of SAEW sterilization.
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Affiliation(s)
| | | | - Yu Cao
- College of Food Science and Technology, Yunnan Agricultural University, Kunming, 650201, China
| | - Yuanyan Meng
- College of Food Science and Technology, Yunnan Agricultural University, Kunming, 650201, China
| | - Jinsong He
- College of Food Science and Technology, Yunnan Agricultural University, Kunming, 650201, China
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Gao Q, Wang S, Zhang N, Shi F, Qiao S, Hao Q. Key technology of vector removal decoupling in a slope-based figuring model and application in continuous phase plate fabrication. Appl Opt 2024; 63:585-594. [PMID: 38294368 DOI: 10.1364/ao.506128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 12/09/2023] [Indexed: 02/01/2024]
Abstract
For the high-precision fabrication of a continuous phase plate (CPP), a combined decoupling algorithm of single-step decoupling based on the Clairaut-Schwarz theorem and global decoupling by stagewise iteration is proposed. It attempts to address the problem of the low accuracy and limitation of the existing slope-based figuring (SF) model in two-dimensional applications caused by the vector removal coupling between the tool slope influence function and the material removal slope due to the inherent convolution effect in the SF model. The shortcomings of CPP interferometry and the application bottleneck of the Hartmann test in traditional height-based figuring model are studied. The generation mechanism of vector removal coupling is analyzed and compensated. A CPP of 85m m×85m m was successfully machined by the decoupled slope-based figuring model, and the root mean square (RMS) of the surface height error accounted for 6.01% of the RMS of the design value. The research results can effectively improve the convergence and certainty of CPP fabrication using the slope-based figuring model.
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Gao Q, Wang S, Wang Q, Cao G, Fang C, Zhan B. Epidemiological characteristics and prediction model construction of hemorrhagic fever with renal syndrome in Quzhou City, China, 2005-2022. Front Public Health 2024; 11:1333178. [PMID: 38274546 PMCID: PMC10808376 DOI: 10.3389/fpubh.2023.1333178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 12/29/2023] [Indexed: 01/27/2024] Open
Abstract
Background Hemorrhagic fever with renal syndrome (HFRS) is one of the 10 major infectious diseases that jeopardize human health and is distributed in more than 30 countries around the world. China is the country with the highest number of reported HFRS cases worldwide, accounting for 90% of global cases. The incidence level of HFRS in Quzhou is at the forefront of Zhejiang Province, and there is no specific treatment for it yet. Therefore, it is crucial to grasp the epidemiological characteristics of HFRS in Quzhou and establish a prediction model for HFRS to lay the foundation for early warning of HFRS. Methods Descriptive epidemiological methods were used to analyze the epidemic characteristics of HFRS, the incidence map was drawn by ArcGIS software, the Seasonal AutoRegressive Integrated Moving Average (SARIMA) and Prophet model were established by R software. Then, root mean square error (RMSE) and mean absolute error (MAE) were used to evaluate the fitting and prediction performances of the model. Results A total of 843 HFRS cases were reported in Quzhou City from 2005 to 2022, with the highest annual incidence rate in 2007 (3.93/100,000) and the lowest in 2022 (1.05/100,000) (P trend<0.001). The incidence is distributed in a seasonal double-peak distribution, with the first peak from October to January and the second peak from May to July. The incidence rate in males (2.87/100,000) was significantly higher than in females (1.32/100,000). Farmers had the highest number of cases, accounting for 79.95% of the total number of cases. The incidence is high in the northwest of Quzhou City, with cases concentrated on cultivated land and artificial land. The RMSE and MAE values of the Prophet model are smaller than those of the SARIMA (1,0,1) (2,1,0)12 model. Conclusion From 2005 to 2022, the incidence of HFRS in Quzhou City showed an overall downward trend, but the epidemic in high-incidence areas was still serious. In the future, the dynamics of HFRS outbreaks and host animal surveillance should be continuously strengthened in combination with the Prophet model. During the peak season, HFRS vaccination and health education are promoted with farmers as the key groups.
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Affiliation(s)
- Qing Gao
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Shuangqing Wang
- Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China
| | - Qi Wang
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Guoping Cao
- Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China
| | - Chunfu Fang
- Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China
| | - Bingdong Zhan
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Quzhou Center for Disease Control and Prevention, Quzhou, Zhejiang, China
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31
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Wu JE, Dong Y, Liu SY, Peng J, Gao Q, Bian L, Yang Y. [Factors influencing the interpretation of immunohistochemical results in breast cancer with low expression of estrogen receptor]. Zhonghua Bing Li Xue Za Zhi 2024; 53:83-85. [PMID: 38178754 DOI: 10.3760/cma.j.cn112151-20230730-00040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Affiliation(s)
- J E Wu
- Department of Pathology, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - Y Dong
- Department of Breast Surgery, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - S Y Liu
- Department of Pathology, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - J Peng
- Department of Pathology, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - Q Gao
- Department of Radiology, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - L Bian
- Department of Pathology, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - Y Yang
- Department of Pathology, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
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Zhang X, Yang Q, Zhang R, Zhang Y, Zeng W, Yu Q, Zeng M, Gan J, Li H, Yang L, Gao Q, Jiang X. Sodium Danshensu ameliorates cerebral ischemia/reperfusion injury by inhibiting CLIC4/NLRP3 inflammasome-mediated endothelial cell pyroptosis. Biofactors 2024; 50:74-88. [PMID: 37458329 DOI: 10.1002/biof.1991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 07/03/2023] [Indexed: 02/20/2024]
Abstract
Endothelial pyroptosis promotes cerebral ischemia/reperfusion injury (CIRI). Sodium Danshensu (SDSS) has been shown to attenuate CIRI and have anti-inflammatory properties in endothelial cells. However, the mechanism and effect of SDSS on alleviating endothelial pyroptosis after CIRI remains poorly understood. Thus, we aimed to investigate the efficacy and mechanism of SDSS in reducing endothelial pyroptosis. It has been shown that SDSS administration inhibited NLRP3 inflammasome-mediated pyroptosis. As demonstrated by protein microarrays, molecular docking, CETSA and ITDRFCETSA , SDSS bound strongly to CLIC4. Furthermore, SDSS can decrease its expression and inhibit its translocation. Its effectiveness was lowered by CLIC4 overexpression but not by knockdown. Overall The beneficial effect of SDSS against CIRI in this study can be ascribed to blocking endothelial pyroptosis by binding to CLIC4 and then inhibiting chloride efflux-dependent NLRP3 inflammasome activation.
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Affiliation(s)
- Xiaolu Zhang
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Qiuyue Yang
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Ruifeng Zhang
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Yilin Zhang
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Wenyun Zeng
- Oncology Department, Ganzhou People's Hospital, Ganzhou, People's Republic of China
| | - Qun Yu
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Miao Zeng
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Jiali Gan
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Huhu Li
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Lin Yang
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Qing Gao
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
| | - Xijuan Jiang
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China
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Zhang L, Zhang Z, Pei S, Gao Q, Chen W. Quantifying the presymptomatic transmission of COVID-19 in the USA. Math Biosci Eng 2024; 21:861-883. [PMID: 38303446 DOI: 10.3934/mbe.2024036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
The emergence of many presymptomatic hidden transmission events significantly complicated the intervention and control of the spread of COVID-19 in the USA during the year 2020. To analyze the role that presymptomatic infections play in the spread of this disease, we developed a state-level metapopulation model to simulate COVID-19 transmission in the USA in 2020 during which period the number of confirmed cases was more than in any other country. We estimated that the transmission rate (i.e., the number of new infections per unit time generated by an infected individual) of presymptomatic infections was approximately 59.9% the transmission rate of reported infections. We further estimated that {at any point in time the} average proportion of infected individuals in the presymptomatic stage was consistently over 50% of all infected individuals. Presymptomatic transmission was consistently contributing over 52% to daily new infections, as well as consistently contributing over 50% to the effective reproduction number from February to December. Finally, non-pharmaceutical intervention targeting presymptomatic infections was very effective in reducing the number of reported cases. These results reveal the significant contribution that presymptomatic transmission made to COVID-19 transmission in the USA during 2020, as well as pave the way for the design of effective disease control and mitigation strategies.
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Affiliation(s)
- Luyu Zhang
- LMIB and School of Mathematical Sciences, Beihang University, Beijing 100191, China
| | - Zhaohua Zhang
- LMIB and School of Mathematical Sciences, Beihang University, Beijing 100191, China
| | - Sen Pei
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Qing Gao
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
- Zhongguancun Laboratory, Beijing 100194, China
| | - Wei Chen
- Zhongguancun Laboratory, Beijing 100194, China
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China
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Lin T, Ge Y, Gao Q, Zhang D, Chen X, Hu Y, Fan J. Backbone Cyclization of Flavin Mononucleotide-Based Fluorescent Protein Increases Fluorescence and Stability. J Microbiol Biotechnol 2023; 33:1681-1691. [PMID: 37789714 PMCID: PMC10772547 DOI: 10.4014/jmb.2305.05011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/31/2023] [Accepted: 08/17/2023] [Indexed: 10/05/2023]
Abstract
Flavin mononucleotide-binding proteins or domains emit cyan-green fluorescence under aerobic and anaerobic conditions, but relatively low fluorescence and less thermostability limit their application as reporters. In this work, we incorporated the codon-optimized fluorescent protein from Chlamydomonas reinhardtii with two different linkers independently into the redox-responsive split intein construct, overexpressed the precursors in hyperoxic Escherichia coli SHuffle T7 strain, and cyclized the target proteins in vitro in the presence of the reducing agent. Compared with the purified linear protein, the cyclic protein with the short linker displayed enhanced fluorescence. In contrast, cyclized protein with incorporation of the long linker including the myc-tag and human rhinovirus 3C protease cleavable sequence emitted slightly increased fluorescence compared with the protein linearized with the protease cleavage. The cyclic protein with the short linker also exhibited increased thermal stability and exopeptidase resistance. Moreover, induction of the target proteins in an oxygen-deficient culture rendered fluorescent E. coli BL21 (DE3) cells brighter than those overexpressing the linear construct. Thus, the cyclic reporter can hopefully be used in certain thermophilic anaerobes.
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Affiliation(s)
- Tingting Lin
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, P.R. China
| | - Yuanyuan Ge
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, P.R. China
| | - Qing Gao
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, P.R. China
| | - Di Zhang
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, P.R. China
| | - Xiaofeng Chen
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, P.R. China
| | - Yafang Hu
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, P.R. China
| | - Jun Fan
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, P.R. China
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Sun W, Ye B, Chen S, Zeng L, Lu H, Wan Y, Gao Q, Chen K, Qu Y, Wu B, Lv X, Guo X. Neuro-bone tissue engineering: emerging mechanisms, potential strategies, and current challenges. Bone Res 2023; 11:65. [PMID: 38123549 PMCID: PMC10733346 DOI: 10.1038/s41413-023-00302-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 10/08/2023] [Accepted: 10/31/2023] [Indexed: 12/23/2023] Open
Abstract
The skeleton is a highly innervated organ in which nerve fibers interact with various skeletal cells. Peripheral nerve endings release neurogenic factors and sense skeletal signals, which mediate bone metabolism and skeletal pain. In recent years, bone tissue engineering has increasingly focused on the effects of the nervous system on bone regeneration. Simultaneous regeneration of bone and nerves through the use of materials or by the enhancement of endogenous neurogenic repair signals has been proven to promote functional bone regeneration. Additionally, emerging information on the mechanisms of skeletal interoception and the central nervous system regulation of bone homeostasis provide an opportunity for advancing biomaterials. However, comprehensive reviews of this topic are lacking. Therefore, this review provides an overview of the relationship between nerves and bone regeneration, focusing on tissue engineering applications. We discuss novel regulatory mechanisms and explore innovative approaches based on nerve-bone interactions for bone regeneration. Finally, the challenges and future prospects of this field are briefly discussed.
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Affiliation(s)
- Wenzhe Sun
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Bing Ye
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Siyue Chen
- School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Lian Zeng
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Hongwei Lu
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Yizhou Wan
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Qing Gao
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Kaifang Chen
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Yanzhen Qu
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Bin Wu
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Xiao Lv
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
| | - Xiaodong Guo
- Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
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Wu J, Lu Z, Zhao H, Lu M, Gao Q, Che N, Wang J, Ma T. The expanding Pandora's toolbox of CD8 +T cell: from transcriptional control to metabolic firing. J Transl Med 2023; 21:905. [PMID: 38082437 PMCID: PMC10714647 DOI: 10.1186/s12967-023-04775-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/28/2023] [Indexed: 12/18/2023] Open
Abstract
CD8+ T cells are the executor in adaptive immune response, especially in anti-tumor immunity. They are the subset immune cells that are of high plasticity and multifunction. Their development, differentiation, activation and metabolism are delicately regulated by multiple factors. Stimuli from the internal and external environment could remodel CD8+ T cells, and correspondingly they will also make adjustments to the microenvironmental changes. Here we describe the most updated progresses in CD8+ T biology from transcriptional regulation to metabolism mechanisms, and also their interactions with the microenvironment, especially in cancer and immunotherapy. The expanding landscape of CD8+ T cell biology and discovery of potential targets to regulate CD8+ T cells will provide new viewpoints for clinical immunotherapy.
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Affiliation(s)
- Jinghong Wu
- Cancer Research Center, Beijing Chest Hospital, Beijing Tuberculosis and Thoracic Tumor Research Institute, Capital Medical University, Beijing, 101149, China
| | - Zhendong Lu
- Cancer Research Center, Beijing Chest Hospital, Beijing Tuberculosis and Thoracic Tumor Research Institute, Capital Medical University, Beijing, 101149, China
| | - Hong Zhao
- Department of Pathology, Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China
| | - Mingjun Lu
- Cancer Research Center, Beijing Chest Hospital, Beijing Tuberculosis and Thoracic Tumor Research Institute, Capital Medical University, Beijing, 101149, China
| | - Qing Gao
- Cancer Research Center, Beijing Chest Hospital, Beijing Tuberculosis and Thoracic Tumor Research Institute, Capital Medical University, Beijing, 101149, China
| | - Nanying Che
- Department of Pathology, Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China
| | - Jinghui Wang
- Cancer Research Center, Beijing Chest Hospital, Beijing Tuberculosis and Thoracic Tumor Research Institute, Capital Medical University, Beijing, 101149, China.
| | - Teng Ma
- Cancer Research Center, Beijing Chest Hospital, Beijing Tuberculosis and Thoracic Tumor Research Institute, Capital Medical University, Beijing, 101149, China.
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Su Y, Ye B, Zhang Z, Gao Q, Zeng L, Wan Y, Sun W, Chen S, Quan D, Yu J, Guo X. Corrigendum to "Photocatalytic oxygen evolution and antibacterial biomimetic repair membrane for diabetes wound repair via HIF1-α pathway" [Mater. Today Bio 20 (2023) 100616]. Mater Today Bio 2023; 23:100797. [PMID: 37753376 PMCID: PMC10518471 DOI: 10.1016/j.mtbio.2023.100797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/28/2023] Open
Abstract
[This corrects the article DOI: 10.1016/j.mtbio.2023.100616.].
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Affiliation(s)
- Yanlin Su
- Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
| | - Bing Ye
- Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
| | - Ziming Zhang
- Department of Orthopedics, Zaoyang First People's Hospital, Zaoyang, Hubei, 430022, China
| | - Qing Gao
- Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
| | - Lian Zeng
- Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
| | - Yizhou Wan
- Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
| | - Wenzhe Sun
- Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
| | - Siyue Chen
- School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
| | - Daping Quan
- PCFM Lab, School of Chemistry and School of Materials Science and Engineering, Sun Yat-sen University, Guangzhou, Guangdong, 510000, China
| | - Jialin Yu
- The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, 430022, China
| | - Xiaodong Guo
- Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
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Zhang S, Lin T, Zhang D, Chen X, Ge Y, Gao Q, Fan J. Use of the selected metal-dependent enzymes for exploring applicability of human annexin A1 as a purification tag. J Biosci Bioeng 2023; 136:423-429. [PMID: 37805288 DOI: 10.1016/j.jbiosc.2023.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 08/23/2023] [Accepted: 08/29/2023] [Indexed: 10/09/2023]
Abstract
Several fusion tags have been developed for non-chromatographic fusion protein purification. Previously, we identified that human annexin A1 as a novel N-terminal purification tag was used for purifying the fusion proteins produced in Escherichia coli through precipitation in 10 mM Ca2+ buffer, and redissolution of the precipitate in 15 mM EDTA buffer. In this work, we selected four metal-dependent enzymes including E. coli 5-aminolevulinate dehydratase, yeast 3-hydroxyanthranilate 3,4-dioxygenase, maize serine racemase and copper amine oxidase for investigating the annexin A1 tag applicability. Fusion of the His6-tag or the enzyme changed the behavior of precipitation-redissolution. The relatively high recovery yields of three tagged enzymes with the improved purities were obtained through two rounds of purification, whereas low recovery yield of the annexin A1 tagged maize amine oxidase was prepared. The added EDTA displayed different abilities to redissolve the fusion proteins precipitates in two precipitation-redissolution cycles. It inactivated three enzymes and obviously inhibited the activity of the fused maize serine racemase. Based on current findings, we believe that four enzymes could be applied for evaluating applicability of the proteins or peptides as affinity tags for chromatographic purification in a calcium dependent manner.
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Affiliation(s)
- Shuncheng Zhang
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, China.
| | - Tingting Lin
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, China.
| | - Di Zhang
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, China.
| | - Xiaofeng Chen
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, China.
| | - Yuanyuan Ge
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, China.
| | - Qing Gao
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, China.
| | - Jun Fan
- School of Life Science, Anhui Agricultural University, Hefei, Anhui 230036, China.
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Ma C, Gao Q, Zhang L, Li C, Wu G, Yang L. The Effect of PGAM5 on Regulating Mitochondrial Dysfunction in Ischemic Stroke. Discov Med 2023; 35:1123-1133. [PMID: 38058078 DOI: 10.24976/discov.med.202335179.109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
BACKGROUND Ischemic stroke is an acute cerebrovascular disease with high mortality rates and poor prognoses. The influence of ischemic stroke includes a heavy economic burden to patients and society, making the exploration of new therapeutic targets for preventing and treating ischemic stroke urgent. This study aimed to explore the effect of phosphoglycerate mutase family member 5 (PGAM5) on oxidative stress and mitochondrial dysfunction in ischemic stroke. METHODS The model of ischemic neuronal brain injury was established through culturing purchased human neuroblastoma cells (SH-SY5Y) by oxygen-glucose deprivation/reoxygenation (OGD/R). There were six experimental groups, including the OGD/R model group (SH-cells of OGD/R model), OE-NC group (cells of OGD/R model transfected with scramble cDNA), OE-PGAM5 group (cells of OGD/R model transfected with full-length sequence of PGAM5), si-NC group (cells of OGD/R model transfected with negative control small interference (si)RNA), si-PGAM5 group (cells of OGD/R model transfected with siRNA for PGAM5 knockdown), and a control group (cells cultured normally). Cell counting kit-8 (CCK-8) and flow cytometry were used to determine the activity and apoptosis of cells. Subsequently, the effects of PGAM5 expression on oxidative stress and mitochondrial dysfunction were analyzed. Mitochondrial morphology was observed by transmission electron microscopy (TEM), and mitochondrial membrane potential (MMP) was determined by JC-1 fluorescent probe. The levels of reactive oxygen species (ROS) were measured by flow cytometry, and levels of malondialdehyde (MDA) and superoxide dismutase (SOD) were measured by enzyme-linked immunosorbent assay (ELISA) assay. The expression of light chain (LC)3-II/I and autophagy-related gene 5 (ATG5) proteins were measured, and the regulation of PGAM5 expression on PTEN-induced putative protein kinase 1 (PINK1)/Parkin pathway was also explored. RESULTS PGAM5 overexpression in OGD/R cells decreased the cell viability (p < 0.001) while increasing cell apoptosis (p < 0.01) compared to the OGD/R group. Inhibition of PGAM5 expression reversed the decreased cell viability (p < 0.001) and the increased cell apoptosis (p < 0.01). The JC-1 fluorescence showed that OGD/R treatment reduced mitochondrial membrane potential (p < 0.001) and TEM showed an obvious increase in phagosomes. In addition, OGD/R treatment enhanced oxidative stress (increased ROS, p < 0.01; increased MDA, p < 0.001; decreased SOD, p < 0.001), which could be further enhanced by overexpression of PGAM5 (ROS, p < 0.001; MDA, p < 0.001; SOD, p < 0.001) while reversed by the inhibition of PGAM5 (ROS, p < 0.01; MDA, p < 0.001; SOD, p < 0.001). The OGD/R-activated PINK1/Parkin pathway was inhibited by the knockdown of PGAM5 (p < 0.01) but promoted by the overexpression of PGAM5 (p < 0.05). CONCLUSIONS PGAM5 stimulates oxidative stress and impairs mitochondrial function in ischemic stroke, and regulates the PINK1/Parkin signaling pathway. Therefore, PGAM5 is likely to be a target for the therapy of ischemic stroke.
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Affiliation(s)
- Chunli Ma
- Department of Neurology, The Second Affiliated Hospital, Mudanjiang Medical University, 157011 Mudanjiang, Heilongjiang, China
| | - Qing Gao
- Clinical Skills Center, The First Clinical Medical College, Mudanjiang Medical University, 157011 Mudanjiang, Heilongjiang, China
| | - Li Zhang
- Department of Scientific Research, Affiliated Hongqi Hospital, Mudanjiang Medical University, 157011 Mudanjiang, Heilongjiang, China
| | - Chao Li
- Department of Neurology, Affiliated Hongqi Hospital, Mudanjiang Medical University, 157011 Mudanjiang, Heilongjiang, China
| | - Geng Wu
- Clinical Skills Center, The First Clinical Medical College, Mudanjiang Medical University, 157011 Mudanjiang, Heilongjiang, China
| | - Lei Yang
- Clinical Skills Center, The First Clinical Medical College, Mudanjiang Medical University, 157011 Mudanjiang, Heilongjiang, China
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Chen QS, Zhao YH, Chen X, Xu JK, Gao Q, Zhu JY. Setup error of electronic portal image device in IMRT for thoracic tumors and its influence. Eur Rev Med Pharmacol Sci 2023; 27:12012-12020. [PMID: 38164863 DOI: 10.26355/eurrev_202312_34799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
OBJECTIVE The aim of this study was to analyze the setup error of the electronics portal image device (EPID) in intensity-modulated radiation therapy (IMRT) for thoracic tumors and the influence on the outward expansion distance of the target area. PATIENTS AND METHODS A total of 202 patients with chest tumors admitted to our hospital from March 2016 to March 2018 were selected as the observation subjects. All patients were treated with IMRT. The original plan was developed based on the SM90 obtained by the planning target volume (PTV) expansion method, and the new plan was obtained by shifting the isocenter coordinates of the treatment plan according to the positioning error value obtained by EPID. Before the treatment, EPID scans were performed. The electronic radiation field images (ERIs) were registered with the digitally reconstructed radiographic images (DRRs) generated by the treatment planning system using the image registration software, and the setup errors in the X, Y, and Z directions were further measured. The PTV was developed according to ERIs, and the setup error was simulated to obtain the PTV with 95% internal target volume (ITV) reaching the prescribed dose under the condition of a setup error. The outward expansion distance of clinical target volume (CTV) → PTV was calculated. RESULTS In this experiment, the setup errors in X, Y, and Z directions were (-2.00±1.16) mm, (0.16±1.14) mm, and (-0.55±1.16) mm, respectively. The systematic error in the Z direction was -3.00 mm, and the random error in the X direction was 3.30 mm. The CTV → PTV outward expansion distance was set as 7, 8 and 7 mm in the X direction, Y direction and Z direction, respectively. At this time, under the presence of setup error, the PTV D95 and the ITV V100 in the new plan were (62.23±3.85) Gy and (97.51±1.56) %, respectively, effectively ensuring that 95% ITV of 90% patients reached the prescribed dose. In contrast, the ITV D95 and ITV V100 in the presence of setup error were (56.11±5.26) Gy and (90.15±3.12) %, respectively, at a CTV → PTV outward expansion distance of 5 mm, which could not guarantee that 95% ITV of 90% patients reached the prescribed dose. In the presence of a setup error, the double-lung 5 Gy irradiation of the total heart volume (V5), the double-lung 20 Gy irradiation of the total heart volume (V20), mean lung dose (MLD), mean heart dose (MHD), and D1 cm3 of the new plan increased by 0.89%, 0.29%, 0.13%, 0.06%, and 5 Gy, respectively, compared with the original plan. CONCLUSIONS In general, the first treatment of radiotherapy in thoracic tumors mostly has a certain degree of setup error, which is most evident in the X direction. When the CTV → PTV outward expansion distance is set at 7, 8, and 7 mm in the X direction, Y direction, and Z direction, respectively, it can effectively ensure that 95% ITV reach the prescribed dose in 90% of patients in the presence of a setup error. EPID helps to achieve the desired effect of radiotherapy, improves the efficacy of radiotherapy, and reduces the side effects caused by radiotherapy errors.
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Affiliation(s)
- Q-S Chen
- School of Clinical Medicine, Fujian Medical University, Fuzhou, China.
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Lu F, Cui Q, Zou Y, Guo Y, Luo W, Yu Y, Gao J, Cai X, Fu L, Yuan S, Huang J, Zhang Y, Xie J, Sheng W, Tang Q, Gao Q, He Z, Chen H. Effects of rTMS Intervention on Functional Neuroimaging Activities in Adolescents with Major Depressive Disorder Measured Using Resting-State fMRI. Bioengineering (Basel) 2023; 10:1374. [PMID: 38135965 PMCID: PMC10740826 DOI: 10.3390/bioengineering10121374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 11/10/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) is commonly used for the clinical treatment of major depressive disorder (MDD). The neuroimaging biomarkers and mechanisms of rTMS are still not completely understood. This study aimed to explore the functional neuroimaging changes induced by rTMS in adolescents with MDD. A total of ten sessions of rTMS were administrated to the L-DLPFC in thirteen adolescents with MDD once a day for two weeks. All of them were scanned using resting-state functional magnetic resonance imaging at baseline and after rTMS treatment. The regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and the subgenual anterior cingulate cortex (sgACC)-based functional connectivity (FC) were computed as neuroimaging indicators. The correlation between changes in the sgACC-based FC and the improvement in depressive symptoms was also analyzed. After rTMS treatment, ReHo and ALFF were significantly increased in the L-DLPFC, the left medial prefrontal cortex, bilateral medial orbital frontal cortex, and the left ACC. ReHo and ALFF decreased mainly in the left middle occipital gyrus, the right middle cingulate cortex (MCC), bilateral calcarine, the left cuneus, and the left superior occipital gyrus. Furthermore, the FCs between the left sgACC and the L-DLPFC, the right IFGoper, the left MCC, the left precuneus, bilateral post-central gyrus, the left supplementary motor area, and the left superior marginal gyrus were enhanced after rTMS treatment. Moreover, the changes in the left sgACC-left MCC FC were associated with an improvement in depressive symptoms in early improvers. This study showed that rTMS treatment in adolescents with MDD causes changes in brain activities and sgACC-based FC, which may provide basic neural biomarkers for rTMS clinical trials.
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Affiliation(s)
- Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yang Zou
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yuanhong Guo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Wei Luo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yue Yu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Jingjing Gao
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;
| | - Xiao Cai
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Linna Fu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Shuai Yuan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Juan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yajun Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Jing Xie
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qing Gao
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
- MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
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Chen Y, Zhou Y, Hu Z, Lu W, Li Z, Gao N, Liu N, Li Y, He J, Gao Q, Xie Z, Li J, He Y. Gelatin-Based Metamaterial Hydrogel Films with High Conformality for Ultra-Soft Tissue Monitoring. Nanomicro Lett 2023; 16:34. [PMID: 38019305 PMCID: PMC10686972 DOI: 10.1007/s40820-023-01225-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 09/24/2023] [Indexed: 11/30/2023]
Abstract
Implantable hydrogel-based bioelectronics (IHB) can precisely monitor human health and diagnose diseases. However, achieving biodegradability, biocompatibility, and high conformality with soft tissues poses significant challenges for IHB. Gelatin is the most suitable candidate for IHB since it is a collagen hydrolysate and a substantial part of the extracellular matrix found naturally in most tissues. This study used 3D printing ultrafine fiber networks with metamaterial design to embed into ultra-low elastic modulus hydrogel to create a novel gelatin-based conductive film (GCF) with mechanical programmability. The regulation of GCF nearly covers soft tissue mechanics, an elastic modulus from 20 to 420 kPa, and a Poisson's ratio from - 0.25 to 0.52. The negative Poisson's ratio promotes conformality with soft tissues to improve the efficiency of biological interfaces. The GCF can monitor heartbeat signals and respiratory rate by determining cardiac deformation due to its high conformability. Notably, the gelatin characteristics of the biodegradable GCF enable the sensor to monitor and support tissue restoration. The GCF metamaterial design offers a unique idea for bioelectronics to develop implantable sensors that integrate monitoring and tissue repair and a customized method for endowing implanted sensors to be highly conformal with soft tissues.
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Affiliation(s)
- Yuewei Chen
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, People's Republic of China
- School of Mechanical Engineering, Guizhou University, Guiyang, 550025, People's Republic of China
| | - Yanyan Zhou
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, People's Republic of China
| | - Zihe Hu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, People's Republic of China
| | - Weiying Lu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, People's Republic of China
| | - Zhuang Li
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, People's Republic of China
| | - Ning Gao
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, People's Republic of China
| | - Nian Liu
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, People's Republic of China
| | - Yuanrong Li
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, People's Republic of China
| | - Jing He
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, People's Republic of China
| | - Qing Gao
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, People's Republic of China
| | - Zhijian Xie
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, People's Republic of China.
| | - Jiachun Li
- School of Mechanical Engineering, Guizhou University, Guiyang, 550025, People's Republic of China.
| | - Yong He
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, People's Republic of China.
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Sun C, Geng L, Liu X, Gao Q. Design of Closed-Loop Control Schemes Based on the GA-PID and GA-RBF-PID Algorithms for Brain Dynamic Modulation. Entropy (Basel) 2023; 25:1544. [PMID: 37998236 PMCID: PMC10670460 DOI: 10.3390/e25111544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 11/06/2023] [Accepted: 11/11/2023] [Indexed: 11/25/2023]
Abstract
Neurostimulation can be used to modulate brain dynamics of patients with neuropsychiatric disorders to make abnormal neural oscillations restore to normal. The control schemes proposed on the bases of neural computational models can predict the mechanism of neural oscillations induced by neurostimulation, and then make clinical decisions that are suitable for the patient's condition to ensure better treatment outcomes. The present work proposes two closed-loop control schemes based on the improved incremental proportional integral derivative (PID) algorithms to modulate brain dynamics simulated by Wendling-type coupled neural mass models. The introduction of the genetic algorithm (GA) in traditional incremental PID algorithm aims to overcome the disadvantage that the selection of control parameters depends on the designer's experience, so as to ensure control accuracy. The introduction of the radial basis function (RBF) neural network aims to improve the dynamic performance and stability of the control scheme by adaptively adjusting control parameters. The simulation results show the high accuracy of the closed-loop control schemes based on GA-PID and GA-RBF-PID algorithms for modulation of brain dynamics, and also confirm the superiority of the scheme based on the GA-RBF-PID algorithm in terms of the dynamic performance and stability. This research of making hypotheses and predictions according to model data is expected to improve and perfect the equipment of early intervention and rehabilitation treatment for neuropsychiatric disorders in the biomedical engineering field.
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Affiliation(s)
- Chengxia Sun
- Mechanical and Electrical Engineering College, Hebei Normal University of Science and Technology, Qinhuangdao 066004, China; (C.S.); (L.G.)
| | - Lijun Geng
- Mechanical and Electrical Engineering College, Hebei Normal University of Science and Technology, Qinhuangdao 066004, China; (C.S.); (L.G.)
| | - Xian Liu
- State Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;
| | - Qing Gao
- State Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;
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Jiang H, Li H, Huang D, Zhao Y, Liu J, Gao Q, He H, Liu X. Hot Deformation Behavior and Processing Maps of 26CrMo7S Steel Used in Oil Exploration. Materials (Basel) 2023; 16:7056. [PMID: 37959653 PMCID: PMC10650000 DOI: 10.3390/ma16217056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 11/01/2023] [Accepted: 11/01/2023] [Indexed: 11/15/2023]
Abstract
The hot deformation behavior and flow stress characteristics of experimental 26CrMo7S steel were analyzed using a thermal simulator under a range of conditions, including a strain rate range of 0.01~10 s-1, a temperature range of 850~1250 °C, and a maximum deformation amount of 70%. The Arrhenius constitutive model was built for the corresponding conditions, and the model's accuracy was verified through error analysis. Additionally, hot processing maps were constructed to analyze the processing zone of the steel under different hot deformation conditions. Finally, the microstructure of the processing zones was observed and verified using the electron backscattered diffraction (EBSD). The results indicate that the interaction of work hardening and dynamic softening influences the hot deformation behavior of 26CrMo7S steel. The Arrhenius constitutive equation with a value of the correlation coefficient (r = 0.99523) accurately predicts the flow behavior of 26CrMo7S steel under different strains. The optimal processing zone obtained with the hot processing maps is within a deformation range of 1010~1190 °C and a strain rate range of 0.01~10-1.5 s-1, and the obtained microstructure is in good agreement with the analysis results.
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Affiliation(s)
- Hemiao Jiang
- School of Materials Science and Engineering, Central South University, Changsha 410083, China;
| | - Hongying Li
- School of Materials Science and Engineering, Central South University, Changsha 410083, China;
| | - Dianyuan Huang
- Hengyang Valin Steel Pipe Co., Ltd., Hengyang 421001, China; (D.H.); (Y.Z.); (H.H.)
| | - Yinghui Zhao
- Hengyang Valin Steel Pipe Co., Ltd., Hengyang 421001, China; (D.H.); (Y.Z.); (H.H.)
| | - Jiwen Liu
- Xiangtan Iron & Steel Co., Ltd. of Hunan Valin, Xiangtan 411101, China; (J.L.); (Q.G.); (X.L.)
| | - Qing Gao
- Xiangtan Iron & Steel Co., Ltd. of Hunan Valin, Xiangtan 411101, China; (J.L.); (Q.G.); (X.L.)
| | - Hang He
- Hengyang Valin Steel Pipe Co., Ltd., Hengyang 421001, China; (D.H.); (Y.Z.); (H.H.)
| | - Ximao Liu
- Xiangtan Iron & Steel Co., Ltd. of Hunan Valin, Xiangtan 411101, China; (J.L.); (Q.G.); (X.L.)
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Xia M, Wu M, Li Y, Liu Y, Jia G, Lou Y, Ma J, Gao Q, Xie M, Chen Y, He Y, Li H, Li W. Varying mechanical forces drive sensory epithelium formation. Sci Adv 2023; 9:eadf2664. [PMID: 37922362 PMCID: PMC10624343 DOI: 10.1126/sciadv.adf2664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 10/05/2023] [Indexed: 11/05/2023]
Abstract
The mechanical cues of the external microenvironment have been recognized as essential clues driving cell behavior. Although intracellular signals modulating cell fate during sensory epithelium development is well understood, the driving force of sensory epithelium formation remains elusive. Here, we manufactured a hybrid hydrogel with tunable mechanical properties for the cochlear organoids culture and revealed that the extracellular matrix (ECM) drives sensory epithelium formation through shifting stiffness in a stage-dependent pattern. As the driving force, moderate ECM stiffness activated the expansion of cochlear progenitor cell (CPC)-derived epithelial organoids by modulating the integrin α3 (ITGA3)/F-actin cytoskeleton/YAP signaling. Higher stiffness induced the transition of CPCs into sensory hair cells (HCs) through increasing the intracellular Ca2+ signaling mediated by PIEZO2 and then activating KLF2 to accomplish the cell specification . Our results identify the molecular mechanism of sensory epithelium formation guided by ECM mechanical force and contribute to developing therapeutic approaches for HC regeneration.
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Affiliation(s)
- Mingyu Xia
- ENT institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200031, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
- NHC Key Laboratory of Hearing Medicine, Fudan University, Shanghai 200031, China
- The Institutes of Brain Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai 200032, China
| | - Mingxuan Wu
- ENT institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200031, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Yuanrong Li
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Cancer Center, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Yaoqian Liu
- ENT institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200031, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Gaogan Jia
- ENT institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200031, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Yiyun Lou
- ENT institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200031, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Jiaoyao Ma
- ENT institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200031, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Qing Gao
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Mingjun Xie
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Plastic and Reconstructive Surgery Center, Department of Plastic and Reconstructive Surgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang 310014, China
| | - Yuewei Chen
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Yong He
- State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Cancer Center, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Huawei Li
- ENT institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200031, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
- NHC Key Laboratory of Hearing Medicine, Fudan University, Shanghai 200031, China
- The Institutes of Brain Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai 200032, China
- Shanghai Engineering Research Centre of Cochlear Implant, Shanghai 200031, China
| | - Wenyan Li
- ENT institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200031, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
- NHC Key Laboratory of Hearing Medicine, Fudan University, Shanghai 200031, China
- The Institutes of Brain Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai 200032, China
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Zheng Y, Zhang X, Zhang R, Wang Z, Gan J, Gao Q, Yang L, Xu P, Jiang X. Inflammatory signaling pathways in the treatment of Alzheimer's disease with inhibitors, natural products and metabolites (Review). Int J Mol Med 2023; 52:111. [PMID: 37800614 PMCID: PMC10558228 DOI: 10.3892/ijmm.2023.5314] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 09/11/2023] [Indexed: 10/07/2023] Open
Abstract
The intricate nature of Alzheimer's disease (AD) pathogenesis poses a persistent obstacle to drug development. In recent times, neuroinflammation has emerged as a crucial pathogenic mechanism of AD, and the targeting of inflammation has become a viable approach for the prevention and management of AD. The present study conducted a comprehensive review of the literature between October 2012 and October 2022, identifying a total of 96 references, encompassing 91 distinct pharmaceuticals that have been investigated for their potential impact on AD by inhibiting neuroinflammation. Research has shown that pharmaceuticals have the potential to ameliorate AD by reducing neuroinflammation mainly through regulating inflammatory signaling pathways such as NF‑κB, MAPK, NLRP3, PPARs, STAT3, CREB, PI3K/Akt, Nrf2 and their respective signaling pathways. Among them, tanshinone IIA has been extensively studied for its anti‑inflammatory effects, which have shown significant pharmacological properties and can be applied clinically. Thus, it may hold promise as an effective drug for the treatment of AD. The present review elucidated the inflammatory signaling pathways of pharmaceuticals that have been investigated for their therapeutic efficacy in AD and elucidates their underlying mechanisms. This underscores the auspicious potential of pharmaceuticals in ameliorating AD by impeding neuroinflammation.
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Affiliation(s)
| | | | - Ruifeng Zhang
- Tianjin University of Traditional Chinese Medicine, Tianjin 301617, P.R. China
| | - Ziyu Wang
- Tianjin University of Traditional Chinese Medicine, Tianjin 301617, P.R. China
| | - Jiali Gan
- Tianjin University of Traditional Chinese Medicine, Tianjin 301617, P.R. China
| | - Qing Gao
- Tianjin University of Traditional Chinese Medicine, Tianjin 301617, P.R. China
| | - Lin Yang
- Tianjin University of Traditional Chinese Medicine, Tianjin 301617, P.R. China
| | - Pengjuan Xu
- Tianjin University of Traditional Chinese Medicine, Tianjin 301617, P.R. China
| | - Xijuan Jiang
- Tianjin University of Traditional Chinese Medicine, Tianjin 301617, P.R. China
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Zeng Q, Liu J, Mu J, Yang J, Gao Q, Wu F, Zhou H. Optimal biopsy site for the diagnosis of oral pemphigus vulgaris and mucous membrane pemphigoid: a systematic review and meta-analysis. Int J Oral Maxillofac Surg 2023; 52:1162-1172. [PMID: 37268547 DOI: 10.1016/j.ijom.2023.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 05/07/2023] [Accepted: 05/11/2023] [Indexed: 06/04/2023]
Abstract
The aim of this study was to critically evaluate the diagnostic yields of direct immunofluorescence (DIF) analysis on perilesional and normal-appearing mucosa biopsy samples, to determine the optimal biopsy site for patients presenting with oral pemphigus vulgaris (PV) or mucous membrane pemphigoid (MMP). Electronic databases and article bibliographies were searched in December 2022. The primary outcome was the rate of DIF positivity. Of 374 records identified after the elimination of duplicates, 21 studies with 1027 samples were ultimately included. Meta-analysis revealed a pooled DIF positivity rate of 99.6% (95% confidence interval (CI) 97.4-100.0%, I2 = 0%) for PV and 92.6% (95% CI 87.9-96.5%, I2 = 44%) for MMP for biopsies from perilesional sites, and of 95.4% (95% CI 88.6-99.5%, I2 = 0%) for PV and 94.1% (95% CI 86.5-99.2%, I2 = 42%) for MMP for biopsies from normal-appearing sites. For MMP, there was no significant difference in the rate of DIF positivity between the two biopsy sites (odds ratio 1.91, 95% CI 0.91-4.01, I2 = 0%). The results suggest that the perilesional mucosa remains the optimal biopsy site for DIF diagnosis of oral PV, while the normal-appearing mucosa biopsy is optimal for oral MMP.
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Affiliation(s)
- Q Zeng
- State Key Laboratory of Oral Diseases, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Frontier Innovation Center for Dental Medicine Plus, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - J Liu
- State Key Laboratory of Oral Diseases, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Frontier Innovation Center for Dental Medicine Plus, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - J Mu
- State Key Laboratory of Oral Diseases, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Frontier Innovation Center for Dental Medicine Plus, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - J Yang
- State Key Laboratory of Oral Diseases, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Frontier Innovation Center for Dental Medicine Plus, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - Q Gao
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China
| | - F Wu
- State Key Laboratory of Oral Diseases, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Frontier Innovation Center for Dental Medicine Plus, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
| | - H Zhou
- State Key Laboratory of Oral Diseases, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Frontier Innovation Center for Dental Medicine Plus, West China Hospital of Stomatology, Sichuan University, Chengdu, China
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Chen L, Wu M, Gao Q, Zhang S, Zhang K, Li J, Cha C, Li X, Liu L. The combined effect of pit and fissure sealant application and oral health education on oral health status of children aged 6-9 years: a 12-month follow-up study in Northeast China. BMC Oral Health 2023; 23:809. [PMID: 37891599 PMCID: PMC10612266 DOI: 10.1186/s12903-023-03467-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 09/28/2023] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND Children aged 6-9 years are vulnerable to dental caries due to age-related limitations and a lack of adequate knowledge regarding oral health and hygiene practices. This study aimed to establish a cohort of children aged between 6 and 9 years and conducted a 12-month follow-up to examine the combined effect of pit and fissure sealant (PFS) application and oral health education on their oral health status. METHODS A cohort study with 12-month follow-up was conducted in Liaoning province, China. A multi-stage stratified cluster sampling approach was employed in the study. The enrolled 6- to 9-year-old children were all from the selected primary schools, who had resided in the designated area for at least 6 months. Children who were unable to cooperate with the examiner or without informed consent from their guardians were excluded. Experienced dental professionals examined the oral health status of primary school children aged 6-9 years. All children and their guardians were mandated to complete a questionnaire (qualitative data) at the beginning of the study. In the experiment group, children underwent PFS application and chairside oral health education. Clinical examinations and questionnaire surveys were repeated at the 12-month follow-up. The chi-square test and binary logistic regression were conducted to investigate the potential risk factors associated with dental caries prevalence (dependent variable). Independent variables were items from the questionnaire (such as living place, parents' education level and children' birth weight). The significant variables identified in the chi-square tests were subsequently included in the binary logistic regression analysis. RESULTS A total of 4,085 children aged 6-9 years were included in the study, with 1805 participants assigned to the experiment group and 2280 to the control group. At baseline, the caries rates of the experimental and control group were 77.95% and 80.35%, respectively without any statistically significant differences. However, at the 12-month follow-up, the caries rate in the experimental group (83.65%) was significantly lower than that in the control group (86.62%) (P < 0.05). The results from the binary logistic regression analysis indicated that parents with a college degree and children in the experimental group exhibited lower caries rates. Conversely, higher caries rates were associated with the consumption of sweet beverages and foods more than once a day and a lack of knowledge regarding the causes of caries (P < 0.05). CONCLUSIONS In Liaoning, China, children aged 6 to 9 years exhibited a high prevalence of dental caries. Several factors, including the parent's education level, the frequency of consuming sweet beverages and foods, and the children's understanding of the cause of caries, significantly affected the caries prevalence rates. The implementation of PFS application and oral health education effectively reduce the caries rate among the surveyed children.
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Affiliation(s)
- Liwen Chen
- Department of Preventive Dentistry, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110101, China
| | - Ming Wu
- Liaoning Center for Disease Prevention And Control, Shenyang, 110172, China.
| | - Qing Gao
- Liaoning Center for Disease Prevention And Control, Shenyang, 110172, China
| | - Siyu Zhang
- Department of Preventive Dentistry, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110101, China
| | - Kaiqiang Zhang
- Department of Preventive Dentistry, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110101, China
| | - Jian Li
- Department of Preventive Dentistry, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110101, China
| | - Chang Cha
- Department of Preventive Dentistry, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110101, China
| | - Xiaoli Li
- Department of Preventive Dentistry, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110101, China
| | - Lu Liu
- Department of Preventive Dentistry, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110101, China.
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Teng QL, Sui SJ, Zhu Z, Gao Q, Ge H, Wang KQ, Lino-Silva LS, Sigal M, White JR, Peng QH, Wei YZ. A fucoidan plant drink reduces Helicobacter pylori load in the stomach: a real-world study. Transl Gastroenterol Hepatol 2023; 8:34. [PMID: 38021354 PMCID: PMC10643181 DOI: 10.21037/tgh-23-63] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 10/12/2023] [Indexed: 12/01/2023] Open
Abstract
Background Helicobacter pylori (Hp) infection is highly prevalent globally and is predominantly managed by antibiotics. Recently, the anti-adhesive, antioxidant, antitoxin, immunomodulatory, anti-coagulant, and anti-infective activities of fucoidan, a polysaccharide extracted from brown seaweeds, have been widely studied, and the results showed promise. Fucoidan has the potential to be utilized in Hp eradication therapy. Our present clinical study was designed to evaluate the efficiency of Lewuyou®, a fucoidan plant drink (FPD) in eradicating Hp in humans. Methods This multi-center, clinical study was conducted between October 2020 and July 2021. Hp infection was confirmed by urea breath test (UBT). A total of 122 patients with confirmed Hp infection were enrolled; after exclusion of incomplete data, 85 eligible patients (37 males and 48 females aged 20-81 years) were included in the final analysis. FPD (50 mL per vial) was orally administered twice daily for a 4-week cycle, and 41 patients completed an 8-week cycle. Results No adverse event (AE) was reported in all 122 participants who had consumed FPD. The Hp eradication rate and clearance rate were 77.6% (66/85) and 20.0% (17/85), respectively, after 4 weeks of FPD consumption and 80.5% (33/41) and 26.8 (11/41) , respectively, after 8 weeks of consumption. Conclusions The 4- and 8-week protocols of FPD consumption were safe and effective at reducing Hp load on the gastric mucosa, with Hp eradicated in the majority of participants.
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Affiliation(s)
- Qing-Liang Teng
- Department of Hematology, the Affiliated Hospital of Qingdao University Taian City Central Hospital, Taian, China
| | - Shu-Jing Sui
- Department of Gastroenterology, the Affiliated Hospital of Qingdao University Taian City Central Hospital, Taian, China
| | - Zhen Zhu
- Department of Pathology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Qing Gao
- Department of Emergency, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Hui Ge
- Department of Gastroenterology, Shandong Provincial Taishan Hospital, Taian, China
| | | | - Leonardo S. Lino-Silva
- Department of Surgical Pathology, Oncology Center Tula’s General Hospital, Tula de Allende, Hidalgo, Mexico
| | - Michael Sigal
- Department of Hepatology & Gastroenterology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Jonathan R. White
- NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham, UK
| | - Qi-Hui Peng
- Blue Regale Clinical Nutrition Technology Co., Ltd., Kunshan, China
| | - You-Zhen Wei
- Research Center for Translational Medicine, the Affiliated Hospital of Qingdao University Taian City Central Hospital, Taian, China
- Research Center for Translational Medicine, Jinan People’s Hospital, Jinan, China
- Department of Rehabilitation Medicine, Jinan Hospital (Jinan City Rehabilitation Hospital), Jinan, China
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Hu J, Fan C, Zhou L, Gao Q, Liu H, Lam TL. Lifelong-MonoDepth: Lifelong Learning for Multidomain Monocular Metric Depth Estimation. IEEE Trans Neural Netw Learn Syst 2023; PP:1-11. [PMID: 37874732 DOI: 10.1109/tnnls.2023.3323487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
With the rapid advancements in autonomous driving and robot navigation, there is a growing demand for lifelong learning (LL) models capable of estimating metric (absolute) depth. LL approaches potentially offer significant cost savings in terms of model training, data storage, and collection. However, the quality of RGB images and depth maps is sensor-dependent, and depth maps in the real world exhibit domain-specific characteristics, leading to variations in depth ranges. These challenges limit existing methods to LL scenarios with small domain gaps and relative depth map estimation. To facilitate lifelong metric depth learning, we identify three crucial technical challenges that require attention: 1) developing a model capable of addressing the depth scale variation through scale-aware depth learning; 2) devising an effective learning strategy to handle significant domain gaps; and 3) creating an automated solution for domain-aware depth inference in practical applications. Based on the aforementioned considerations, in this article, we present 1) a lightweight multihead framework that effectively tackles the depth scale imbalance; 2) an uncertainty-aware LL solution that adeptly handles significant domain gaps; and 3) an online domain-specific predictor selection method for real-time inference. Through extensive numerical studies, we show that the proposed method can achieve good efficiency, stability, and plasticity, leading the benchmarks by 8%-15%. The code is available at https://github.com/FreeformRobotics/Lifelong-MonoDepth.
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