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Yue C, Cai-Hong W. Study of the optic nerve in patients with type 2 diabetic retinopathy by shear-wave elastography. Clin Radiol 2024; 79:e574-e581. [PMID: 38278740 DOI: 10.1016/j.crad.2023.12.019] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 11/26/2023] [Accepted: 12/24/2023] [Indexed: 01/28/2024]
Abstract
AIM To investigate the clinical value of two-dimensional shear-wave elastography (2D-SWE) in detecting optic nerve elasticity and in-frame adipose tissue elasticity in patients with type 2 diabetic retinopathy (DR). MATERIALS AND METHODS 2D-SWE was used to detect SWE values of the optic nerve and adipose tissue in adjacent optic nerve frames in 30 healthy participants, 30 patients with diabetic non-retinopathy (NDR), 35 patients with non-proliferative diabetic retinopathy (NPDR), and 30 patients with proliferative diabetic retinopathy (PDR). The correlation between SWE values and blood glucose, blood lipid, age, body mass index (BMI) was analysed. Receiver operating characteristic (ROC) curve analysis was performed for SWE values. RESULTS The SWE values of the optic nerve and in-frame adipose tissue increased with the progression of DR, and analysis of variance was compared with groups: the SWE values of the optic nerve and in-frame adipose tissue in each group were significantly different (all p<0.001). The SWE values of the optic nerve and in-frame adipose tissue correlated positively with BMI, age, triglyceride, and fasting blood glucose, and correlated negatively with high-density lipoprotein. The SWE values of the optic nerve and in-frame adipose tissue had higher diagnostic efficacy. The combination of the two had higher diagnostic accuracy. CONCLUSION The elastic modulus of optic nerve and in-frame adipose tissue can effectively predict and grade of DR, that is, 2D-SWE can be used as a non-invasive imaging diagnostic method for DR. The combined diagnostic efficacy of optic nerve SWE value and in-frame adipose tissue SWE value is significantly better than that of single use. This study found that increased BMI, age, triglyceride, and fasting blood glucose, and decreased high-density lipoprotein are risk factors for DR.
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Affiliation(s)
- C Yue
- Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou City, Inner Mongolia Autonomous Region, 014010, China.
| | - W Cai-Hong
- Department of Ultrasound, The Second Affiliated Hospital of Inner Mongolia University of Science and Technology, Baotou City, Inner Mongolia Autonomous Region, 014031, China
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Zhang X, Miao J, Yang J, Liu C, Huang J, Song J, Xie D, Yue C, Kong W, Hu J, Luo W, Liu S, Li F, Zi W. DWI-Based Radiomics Predicts the Functional Outcome of Endovascular Treatment in Acute Basilar Artery Occlusion. AJNR Am J Neuroradiol 2023; 44:536-542. [PMID: 37080720 PMCID: PMC10171394 DOI: 10.3174/ajnr.a7851] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 03/15/2023] [Indexed: 04/22/2023]
Abstract
BACKGROUND AND PURPOSE Endovascular treatment is a reference treatment for acute basilar artery occlusion (ABAO). However, no established and specific methods are available for the preoperative screening of patients with ABAO suitable for endovascular treatment. This study explores the potential value of DWI-based radiomics in predicting the functional outcomes of endovascular treatment in ABAO. MATERIALS AND METHODS Patients with ABAO treated with endovascular treatment from the BASILAR registry (91 patients in the training cohort) and the hospitals in the Northwest of China (31 patients for the external testing cohort) were included in this study. The Mann-Whitney U test, random forests algorithm, and least absolute shrinkage and selection operator were used to reduce the feature dimension. A machine learning model was developed on the basis of the training cohort to predict the prognosis of endovascular treatment. The performance of the model was evaluated on the independent external testing cohort. RESULTS A subset of radiomics features (n = 6) was used to predict the functional outcomes in patients with ABAO. The areas under the receiver operating characteristic curve of the radiomics model were 0.870 and 0.781 in the training cohort and testing cohort, respectively. The accuracy of the radiomics model was 77.4%, with a sensitivity of 78.9%, specificity of 75%, positive predictive value of 83.3%, and negative predictive value of 69.2% in the testing cohort. CONCLUSIONS DWI-based radiomics can predict the prognosis of endovascular treatment in patients with ABAO, hence allowing a potentially better selection of patients who are most likely to benefit from this treatment.
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Affiliation(s)
- X Zhang
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
- Department of Neurology (X.Z.), The Affiliated Hospital of Northwest University Xi'an No.3 Hospital, Xian, China
| | - J Miao
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
- Department of Neurology (J.M.), Xianyang Hospital of Yan'an University, Xianyang, China
| | - J Yang
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - C Liu
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - J Huang
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - J Song
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - D Xie
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - C Yue
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - W Kong
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - J Hu
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - W Luo
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - S Liu
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - F Li
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - W Zi
- From the Department of Neurology (X.Z., J.M., J.Y., C.L., J.H., J.S., D.X., C.Y., W.K., J.H., W.L., S.L., F.L., W.Z.), Xinqiao Hospital and The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
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Liu ZY, Zong QG, Rankin R, Zhang H, Hao YX, He JS, Fu SY, Wu HH, Yue C, Pollock CJ, Le G. Particle-sounding of the spatial structure of kinetic Alfvén waves. Nat Commun 2023; 14:2088. [PMID: 37045846 PMCID: PMC10097679 DOI: 10.1038/s41467-023-37881-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 03/30/2023] [Indexed: 04/14/2023] Open
Abstract
Kinetic Alfvén waves (KAWs) are ubiquitous throughout the plasma universe. Although they are broadly believed to provide a potential approach for energy exchange between electromagnetic fields and plasma particles, neither the detail nor the efficiency of the interactions has been well-determined yet. The primary difficulty has been the paucity of knowledge of KAWs' spatial structure in observation. Here, we apply a particle-sounding technique to Magnetospheric Multiscale mission data to quantitatively determine the perpendicular wavelength of KAWs from ion gyrophase-distribution observations. Our results show that KAWs' perpendicular wavelength is statistically 2.4[Formula: see text] times proton thermal gyro-radius. This observation yields an upper bound of the energy the majority proton population can reach in coherent interactions with KAWs, that is, roughly 5.76 times proton perpendicular thermal energy. Therefore, the method and results shown here provide a basis for unraveling the effects of KAWs in dissipating energy and accelerating particles in a number of astrophysical systems, e.g., planetary magnetosphere, astrophysical shocks, stellar corona and wind, and the interstellar medium.
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Affiliation(s)
- Z-Y Liu
- Institute of Space Physics and Applied Technology, Peking University, Beijing, China
| | - Q-G Zong
- Institute of Space Physics and Applied Technology, Peking University, Beijing, China.
- Key laboratory of solar activity and space weather, National Space Science Center, Chinese Academy of Sciences, Beijing, China.
- Polar Research Institute of China, Shanghai, China.
| | - R Rankin
- Department of Physics, University of Alberta, Edmonton, AB, Canada
| | - H Zhang
- Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA
| | - Y-X Hao
- Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Potsdam, Germany
| | - J-S He
- Institute of Space Physics and Applied Technology, Peking University, Beijing, China
| | - S-Y Fu
- Institute of Space Physics and Applied Technology, Peking University, Beijing, China
| | - H-H Wu
- School of Electronic Information, Wuhan University, Wuhan, China
| | - C Yue
- Institute of Space Physics and Applied Technology, Peking University, Beijing, China
| | | | - G Le
- NASA Goddard Space Flight Center, Greenbelt, MD, USA
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Luo C, Qin SX, Wang QY, Li YF, Qu XL, Yue C, Hu L, Sheng ZF, Wang XB, Wan XM. Cost-effectiveness analysis of five drugs for treating postmenopausal women in the United States with osteoporosis and a very high fracture risk. J Endocrinol Invest 2023; 46:367-379. [PMID: 36044169 PMCID: PMC9428883 DOI: 10.1007/s40618-022-01910-7] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 08/20/2022] [Indexed: 01/25/2023]
Abstract
PURPOSE Five strategies were recommended by the American Association of Clinical Endocrinologists/American College of Endocrinology (AACE/ACE) guidelines for the treatment of postmenopausal osteoporosis (PMO) patients with a very high fracture risk. We aimed to assess their cost-effectiveness in the United States (US). METHODS A microsimulation Markov model was created to compare the cost-effectiveness of five treatment strategies, including zoledronate, denosumab, abaloparatide, teriparatide, and romosozumab in PMO patients with a recent fracture from the healthcare perspective of the US. The data used in the model were obtained from published studies or online resources. Base-case analysis, one-way deterministic sensitivity analysis (DSA) and probability sensitivity analysis (PSA) were conducted for 65-, 70-, 75-, and 80-year-old patients. RESULTS In base case, at 65 years, zoledronate was the cheapest strategy. The incremental cost-effectiveness ratios (ICER, which represent incremental costs per QALY gained) of denosumab, teriparatide, abaloparatide, and romosozumab against zoledronate were $13,020/QALY (quality-adjusted years), $477,331 /QALY, $176,287/QALY, and $98,953/QALY, respectively. Under a willing-to-pay (WTP, which means the highest price a consumer will pay for one unit of a good of service) threshold of $150,000/QALY, denosumab and romosozumab were cost-effective against zoledronate. The PSA results showed that denosumab was the most cost-effective option with WTP thresholds of $50,000/QALY, $100,000/QALY and $150,000/QALY. The results were similar in other age groups. The DSA results indicated that the most common parameters that have important influence on the outcome were drug persistence, incidence of adverse events, the efficacy of drugs on hip fractures and the cost of the drug. CONCLUSION AND RELEVANCE Among PMO patients with a very high fracture risk in the US, zoledronate is the cheapest strategy and denosumab is the most cost-effective choice among these five strategies.
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Affiliation(s)
- C Luo
- Hunan Provincial Key Laboratory of Metabolic Bone Diseases, Department of Metabolism and Endocrinology, Health Management Center, National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China
| | - S-X Qin
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China
| | - Q-Y Wang
- Hunan Provincial Key Laboratory of Metabolic Bone Diseases, Department of Metabolism and Endocrinology, Health Management Center, National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China
| | - Y-F Li
- Hunan Provincial Key Laboratory of Metabolic Bone Diseases, Department of Metabolism and Endocrinology, Health Management Center, National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China
| | - X-L Qu
- Hunan Provincial Key Laboratory of Metabolic Bone Diseases, Department of Metabolism and Endocrinology, Health Management Center, National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China
| | - C Yue
- Hunan Provincial Key Laboratory of Metabolic Bone Diseases, Department of Metabolism and Endocrinology, Health Management Center, National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China
| | - L Hu
- Hunan Provincial Key Laboratory of Metabolic Bone Diseases, Department of Metabolism and Endocrinology, Health Management Center, National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China
| | - Z-F Sheng
- Hunan Provincial Key Laboratory of Metabolic Bone Diseases, Department of Metabolism and Endocrinology, Health Management Center, National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital of Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China.
| | - X-B Wang
- Divisions of Endocrinology, Metabolism, and Nutrition, Departments of Medicine and Surgery, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA
| | - X-M Wan
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, 139 Renmin Middle Road, Changsha, 410011, Hunan, People's Republic of China.
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Yang QC, Zhou HK, Yue C, Wang WD, Gao RQ, Mo ZC, Ji PP, Wei JP, Yang XS, Yu PF, Li XH, Ji G. [The correlation between No. 6 and No. 14v lymph node metastasis and the value of dissecting these lymph nodes in radical gastrectomy]. Zhonghua Wei Chang Wai Ke Za Zhi 2023; 26:38-43. [PMID: 36649998 DOI: 10.3760/cma.j.cn441530-20221123-00491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Radical gastrectomy with D2 lymphadenectomy has been widely performed as the standard surgery for patients with gastric cancer in major medical centers in China and abroad. However, the exact extent of lymph node dissection is still controversial. In the latest version of the Japanese Gastric Cancer Treatment Guidelines, No. 14v lymph nodes (along the root of the superior mesenteric vein) are again defined as loco-regional lymph nodes, and it is clarified that distal gastric cancer presenting with infra-pyloric regional lymph node (No.6) metastasis is recommended for D2+ superior mesenteric vein (No. 14v) lymph node dissection. To explore the relevance and clinical significance of No.6 and No.14v lymphadenectomy in radical gastric cancer surgery, a review of the national and international literature revealed that No.6 lymph node metastasis was associated with No.14v lymph node metastasis, that No.6 lymph node status was a valid predictor of No.14v lymph node negative status and false negative rate, and that for gastric cancer patients with No. 14v lymph node negative and No.6 lymph node positive, the dissection of No.14v lymph node may also have some significance. The addition of No. 14v lymph node dissection in radical gastrectomy is safe, but it is more important to distinguish the patients who can benefit from it. Professor Liang Han of Tianjin Medical University Cancer Hospital is currently leading a multicenter, large-sample, prospective clinical trial (NCT02272894) in China, which is expected to provide higher level evidence for the clinical significance of lymph node dissection in No.14v.
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Affiliation(s)
- Q C Yang
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - H K Zhou
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - C Yue
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - W D Wang
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - R Q Gao
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - Z C Mo
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - P P Ji
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - J P Wei
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - X S Yang
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - P F Yu
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - X H Li
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
| | - G Ji
- Gastrointestinal Surgery Department, the First Affiliated Hospital of Air Force Military Medical University, Xi'an 710032, China
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Wang Y, Li D, Zhu X, Li J, Yue C, Wu L, Zhuan Q, Dou X, Duan W. The monocyte to high-density lipoprotein cholesterol ratio is a risk factor for frequent premature ventricular complexes: a retrospective cohort study. Lipids Health Dis 2022; 21:129. [PMID: 36463190 PMCID: PMC9719165 DOI: 10.1186/s12944-022-01742-7] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 11/18/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Little is known about the link between the monocyte to high-density lipoprotein cholesterol ratio (MHR) and frequent premature ventricular complexes (PVCs). This investigation aimed to evaluate the link between the MHR and frequent PVCs in patients, as well as their outcomes, using the axis, burden, coupling interval-ventricular tachycardia (ABC-VT) risk score (ARS). METHODS Two hundred patients with frequent PVCs and 70 controls were retrospectively enrolled, and their general data were gathered. The MHR and ARS were calculated. Then, patients developing frequent PVCs were classified into a medium-/high-risk subgroup and a low-risk subgroup according to ARS. The results were evaluated employing comparative statistical analyses, Spearman's correlation, logistic regression analyses, and receiver operating characteristic (ROC) curves. RESULTS The MHR in the controls was obviously lower than that in the frequent PVC group. In addition, the MHR was the lowest in the control group and highest in the medium-/high-risk subgroup, with that of the low-risk subgroup falling in the middle. Spearman's correlation analyses showed that the MHR was positively correlated with the ARS (ρ = 0.307, P < 0.001). Ultimately, the MHR was found to be a risk factor for frequent PVCs in the multivariate analysis. In addition, an MHR cutoff point of 254.6 featured 67.50% sensitivity and 67.14% specificity for predicting frequent PVCs, and the area under the curve (AUC) reached 0.694 (95% confidence interval: 0.623-0.766) (P < 0.001). CONCLUSIONS The MHR is positively and independently correlated with frequent PVCs and can be used as a practical, cost-saving and simple biomarker of inflammation owing to its value in predicting frequent PVCs. In addition, the MHR is crucial to risk stratification and prognosis, which may give it clinical value in the prevention and management of frequent PVCs.
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Affiliation(s)
- Yunfei Wang
- Department of Cardiology, HHCH, Hefei, Anhui China
| | - Deming Li
- Department of Cardiology, HHCH, Hefei, Anhui China
| | - Xuetao Zhu
- Department of Cardiology, FAHAMU, Hefei, Anhui China
| | - Jing Li
- Department of Cardiology, HHCH, Hefei, Anhui China
| | - Cui Yue
- Department of Cardiology, HHCH, Hefei, Anhui China
| | - Ling Wu
- Department of Medical Records, HHCH, Hefei, Anhui China
| | | | - Xiaomeng Dou
- Department of Medical Records, HHCH, Hefei, Anhui China
| | - Wei Duan
- Department of Cardiology, HHCH, Hefei, Anhui China
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Magrey M, Jain M, Ranza R, Stigler J, Mcdearmon-Blondell E, Yue C, Padilla B, Kaufmann C, Mcgonagle D. POS1057 IMPACT OF RISANKIZUMAB ON ENTHESITIS AND ASSOCIATED PAIN: POOLED RESULTS FROM THE PHASE 3, RANDOMIZED, DOUBLE-BLIND KEEPsAKE 1 AND 2 TRIALS. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.3161] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BackgroundControlling or improving musculoskeletal disease activity of psoriatic arthritis (PsA) (eg, enthesitis and associated pain) is a treatment priority for patients, rheumatologists, and dermatologists.1 Enthesitis is the cardinal lesion in PsA and is immunogenetically and experimentally linked to the interleukin-23 (IL-23) pathway.2 Risankizumab (RZB), a humanized immunoglobulin G1 monoclonal antibody that specifically inhibits IL-23 by binding to its p19 subunit, was studied in a phase 3 adult PsA program (KEEPsAKE clinical trials).3,4 Pooled analyses from the program demonstrated the efficacy of RZB to treat enthesitis and pain associated with PsA, and increase the proportion of patients whose enthesitis resolved compared with placebo (PBO) in those patients who had an inadequate response or intolerance to ≥1 conventional synthetic disease-modifying antirheumatic drugs (KEEPsAKE 1 and 2) and/or ≤ 2 biological therapies (KEEPsAKE 2).ObjectivesTo investigate whether patients without enthesitis at baseline (BL) (Leeds Enthesitis Index [LEI] = 0 at BL) remained enthesitis-free through week (W) 52, patients with enthesitis at BL (LEI > 0 at BL) had resolution of enthesitis through W52, and if greater pain relief was achieved with RZB 150 mg in patients with enthesitis at BL vs PBO up to W24.MethodsThe study design and primary results of KEEPsAKE 1 (NCT03675308) and KEEPsAKE 2 (NCT03671148) have been previously reported.3,4 Briefly, patients were randomized to receive RZB 150 mg or PBO subcutaneously at weeks 0, 4, and 16 during a 24-week, double-blind treatment period; at W28 all patients received open label RZB 150 mg. For this post hoc analysis, the RZB 150 mg and PBO groups were pooled across the 2 studies. Pain reductions (as measured by change from BL in visual analogue scale [VAS] scores) were assessed at each time point through W24 among patients with enthesitis at BL (LEI > 0 at BL) using mixed-effect model repeated measurement analysis. Additional enthesitis analyses were calculated on the data as observed.ResultsAcross the pooled population, over 60% of patients in each treatment group had enthesitis at BL (RZB=444/707 [63%]; PBO=448/700 [64%]). Conversely, 37% (263/707) and 36% (252/700) had no enthesitis (LEI=0) at BL among those randomized to RZB and PBO, respectively. Among enthesitis-free patients at BL (LEI=0 at BL), 84.7% on PBO and 90% on RZB remained free of enthesitis through W24; by W52, approximately 93% of patients in both groups (RZB and PBO to RZB) remained enthesitis free. A numerically higher proportion of patients with enthesitis at BL (LEI > 0 at BL) treated with RZB (52.1%) achieved an enthesitis-free state at W24 vs PBO (41.8%); similar proportions achieved an enthesitis-free state at W36 and W52 during open label treatment (Figure 1). Among patients with enthesitis at BL, a significantly greater improvement in VAS pain scores was observed in patients treated with RZB 150 mg vs PBO, as early as W4 (P < .01) and increased through W24 (Figure 1; P < .001).Figure 1.ConclusionLong-term maintenance of an enthesitis-free state (LEI = 0) was similar between the RZB 150 mg and PBO groups, with approximately 93% of patients remaining free of enthesitis at W52. For LEI > 0 patients, the RZB 150-mg group had numerically more patients whose enthesitis resolved at W24, and similar proportions were observed at W52 after the open label switch. Patients with enthesitis at BL treated with RZB 150 mg had statistically greater improvements in pain compared with patients taking PBO starting at W4 through to W24.References[1]Orbai A-M, et al. Ann Rheum Dis. 2017;76:673–680.[2]Stavre Z, et al. Arthritis Res Ther. 2022;24(1):24.[3]Kristensen LE, et al. Ann Rheum Dis. 2021;0:1–7.[4]Östör A, et al. Ann Rheum Dis. 2021;0:1–8.AcknowledgementsAbbVie Inc. participated in the study design; study research; collection, analysis, and interpretation of data; and writing, reviewing, and approving this abstract for submission. All authors had access to the data; participated in the development, review, and approval of the abstract; and agreed to submit this abstract to EULAR 2022 for consideration as a poster or oral presentation. No honoraria or payments were made for authorship. AbbVie and the authors thank all study investigators for their contributions and the patients who participated in this study. AbbVie funded the research for this study and provided writing support for this abstract. Medical writing assistance, funded by AbbVie, was provided by Kersten Reich, MPH, and Nancy Niguidula, DPH, of JB Ashtin.Disclosure of InterestsMarina Magrey Consultant of: MM has received consulting fees from UCB, Novartis, Eli Lilly, Pfizer, and Janssen., Grant/research support from: MM received research grants from Amgen, AbbVie, and UCB Pharma, Manish Jain Consultant of: MJ received consulting fees from Amgen, Abbvie, Eli Lilly, Pfizer, and Novartis., Grant/research support from: MJ received research support from Amgen, Abbvie, Eli Lilly, Pfizer, and Novartis., R Ranza Speakers bureau: RR is a member of speaker bureaus for AbbVie, Janssen, Novartis, and Pfizer, Consultant of: RR is a consultant for AbbVie, Janssen, Novartis, and Pfizer, Jayne Stigler Shareholder of: JS may hold AbbVie stock or stock options., Employee of: JS is a full-time employee of AbbVie., Erin McDearmon-Blondell Shareholder of: EMB may hold AbbVie stock or stock options., Employee of: EMB is a full-time employee of AbbVie., Cuiyong Yue Shareholder of: CY may hold AbbVie stock or stock options., Employee of: CY is a full-time employee of AbbVie., Byron Padilla Shareholder of: BP may hold AbbVie stock or stock options., Employee of: BP is a full-time employee of AbbVie., Christian Kaufmann Shareholder of: CK may hold AbbVie stock or stock options., Employee of: CK is a full-time employee of AbbVie., Dennis McGonagle Speakers bureau: DM is a member of speaker bureaus for AbbVie, Janssen, Novartis, and Pfizer., Grant/research support from: DM received research grants from AbbVie, Janssen, Novartis, and Pfizer, UCB, BMS, Celgene.
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Ogdie A, Coates L, Acayaba DE Toledo R, Biljan A, Jones H, Tacelosky K, Yue C, Padilla B, Bergman M. AB0905 Routine Assessment of Patient Index Data 3 (RAPID3) in Patients With Active Psoriatic Arthritis (PsA) After Inadequate Response or Intolerance to DMARDs: Pooled Results From the Phase 3, Randomized, Double-Blind KEEPsAKE 1 and 2 Trials. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.2913] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BackgroundPsA is a chronic, systemic inflammatory disease with diverse clinical manifestations that can impact a patients’ quality of life. Risankizumab (RZB), a humanized immunoglobulin G1 monoclonal antibody that specifically inhibits interleukin 23 by binding to its p19 subunit, is approved for the treatment of active PsA in adults. In the phase 3 KEEPsAKE 1 and 2 studies, RZB treatment resulted in significantly greater improvements in signs and symptoms of active PsA compared with placebo (PBO).1,2 RAPID3 is frequently used in clinical practice to evaluate PsA disease activity and consists of 3 key patient-reported measures (physical function, pain, and patient’s global assessment of disease activity [PtGA]).3ObjectivesTo evaluate short- (24 week) and long-term (52 week) improvements in RAPID3 scores and achievement of RAPID3 minimal clinically important difference (MCID) across the RZB KEEPsAKE 1 and 2 clinical program.MethodsIn KEEPsAKE 1 (NCT03675308) and KEEPsAKE 2 (NCT03671148), patients with active PsA who experienced inadequate response or intolerance to ≥ 1 csDMARD (KEEPsAKE 1) and/or ≤ 2 biological therapies (KEEPsAKE 2) were randomized to PBO or RZB 150 mg from baseline to week (W) 24; from W28–W52, all patients received open-label RZB 150 mg. At W16, nonresponders could add or modify rescue therapy. This post hoc analysis assessed the mean change from baseline to W24 and W52 in RAPID3 scores and the proportion of patients who achieved a RAPID3 MCID (defined as a decrease of ≥3.8 points4). Modified RAPID3 scores (range: 0–30) were calculated using pain scores, PtGA, and HAQ-DI, each rescaled to 0–10 and summed together.3ResultsA total of 961 and 443 patients were included from KEEPsAKE 1 and 2, respectively. At baseline, mean RAPID3 scores were 15.3 in both treatment arms of KEEPsAKE 1 (PBO n = 479, RZB n = 482) and 15.1 (PBO n = 219) and 14.8 (RZB n = 224) in KEEPsAKE 2. From W4 to W24, RAPID3 scores were significantly reduced with RZB treatment compared with PBO in both KEEPsAKE 1 (mean change from baseline at W24 of −5.3 vs −2.4, respectively, P <.001) and KEEPsAKE 2 (−3.8 vs −1.6, P <.001; Figure 1 A, B), and a significantly greater proportion of patients achieved MCID at W24 with RZB than with PBO in KEEPsAKE 1 (57.0% vs 36.4%, P <.001) and KEEPsAKE 2 (48.8% vs 32.8%, P <.001; Table 1). At W52 among patients who received RZB from W0–W52, mean change from baseline was −7.0 (KEEPsAKE 1) and −5.2 (KEEPsAKE 2; Figure 1 C, D), and MCID was achieved by 67.5% (KEEPsAKE 1) and 56.5% (KEEPsAKE 2) of patients. Patients who switched from PBO to RZB at W24 experienced similar and substantial improvements in RAPID3 scores by W52.Table 1.Proportion of Patients Achieving a Minimal Clinically Important Difference From Baseline in RAPID3 (AO).Patients, % (n/N) [95% CI]KEEPsAKE 1KEEPsAKE 2PBORZB 150 mgPBORZB 150 mgW2436.4 (166/456) [32.0, 40.8]57.0 (262/460) [52.4, 61.5]***32.8 (64/195) [26.2, 39.4]48.8 (104/213) [42.1, 55.5]***PBO to RZB 150 mgaRZB 150 mgPBO to RZB 150 mgaRZB 150 mgW5259.8 (260/435) [55.2, 64.4]67.5 (297/440) [63.1, 71.9]57.4 (105/183) [50.2, 64.5]56.5 (109/193) [49.5, 63.5]aPatients randomized to PBO at W0 switched to open-label RZB 150 mg at W24.***, P < .001 vs PBO.AO, as observed; PBO, placebo; RAPID3, Routine Assessment of Patient Index Data 3; RZB, risankizumab; W, week.Figure 1.Mean Change From Baseline in RAPID3 Scores During KEEPsAKE 1 and 2.**, P < .01; ***, P < .001 vs PBO.AO, as observed; LS, least squares; MMRM, mixed-effect model repeated measurement; PBO, placebo; RAPID3, Routine Assessment of Patient Index Data 3; RZB, risankizumab.ConclusionRZB 150 mg was associated with improvement in RAPID3 total scores over 24–52 weeks of treatment in patients with active PsA in KEEPsAKE 1 and 2.References[1]Kristensen LE, et al. Ann Rheum Dis. 2022;81:225–231.[2]Östör A, et al. Ann Rheum Dis. 2021;annrheumdis-2021-221048.[3]Coates LC, et al. Arthritis Care Res (Hoboken). 2018;70:1198–1205.[4]Ward MM, et al. J Rheumatol. 2019;46:27–30.AcknowledgementsAbbVie Inc. participated in the study design; study research; collection, analysis, and interpretation of data; and writing, reviewing, and approving of this abstract for submission. All authors had access to the data; participated in the development, review, and approval of and in the decision to submit this abstract to EULAR 2022 for consideration as a poster or oral presentation. No honoraria or payments were made for authorship. AbbVie and the authors thank all study investigators for their contributions and the patients who participated in this study. AbbVie funded the research for this study and provided writing support for this abstract.Medical writing assistance, funded by AbbVie, was provided by Callie A. S. Corsa, PhD, of JB Ashtin.Disclosure of InterestsAlexis Ogdie Consultant of: AO has received consulting fees and/or honoraria from AbbVie, Amgen, Bristol Myers Squibb, Celgene, CorEvitas, Gilead, Janssen, Eli Lilly, Novartis, Pfizer, and UCB, Grant/research support from: AO has received grants from AbbVie, Novartis, and Pfizer to the trustees of University of Pennsylvania, and from Amgen to Forward., Laura Coates Speakers bureau: LCC has been paid as a speaker for AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer and UCB., Consultant of: LCC has worked as a paid consultant for AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer and UCB, Grant/research support from: LCC has received grants/research support from AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer and UCB, RICARDO ACAYABA DE TOLEDO Speakers bureau: RAT has received honoraria as a speaker/consultant for Abbvie, Celltrion, Janssen, Novartis, Pfizer, and UCB, Consultant of: RAT has received honoraria as a speaker/consultant for Abbvie, Celltrion, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: RAT has received grants as an investigator from Abbvie, GSK, Novartis, and Pfizer., Ana Biljan Shareholder of: AB may hold AbbVie stock or stock options., Employee of: AB is a full-time employee of AbbVie., Heather Jones Shareholder of: HJ may hold AbbVie stock or stock options., Employee of: HJ is a full-time employee of AbbVie., Kristin Tacelosky Shareholder of: KT may hold AbbVie stock or stock options., Employee of: KT is a full-time employee of AbbVie., Cuiyong Yue Shareholder of: CY may hold AbbVie stock or stock options., Employee of: CY is a full-time employee of AbbVie., Byron Padilla Shareholder of: BP may hold AbbVie stock or stock options., Employee of: BP is a full-time employee of AbbVie., Martin Bergman Shareholder of: MB is a stock holder of Johnson & Johnson and Merck., Speakers bureau: MB has received honoraria as a speaker/consultant for Abbvie, Amgen, GSK, Janssen, Novartis, Pfizer, Sanofi, and Scipher, Consultant of: MB has received honoraria as a speaker/consultant for Abbvie, Amgen, GSK, Janssen, Novartis, Pfizer, Sanofi, and Scipher
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Yue C, Cao J, Wong A, Kim JH, Alam S, Luong G, Talegaonkar S, Schwartz Z, Boyan BD, Giannobile WV, Sahingur SE, Lin Z. Human Bone Marrow Stromal Cell Exosomes Ameliorate Periodontitis. J Dent Res 2022; 101:1110-1118. [PMID: 35356822 PMCID: PMC9305845 DOI: 10.1177/00220345221084975] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [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: 12/13/2022] Open
Abstract
Human bone marrow stromal cell (hBMSC)-derived exosomes are promising therapeutics for inflammatory diseases due to their unique microRNA (miRNA) and protein cargos. Periodontal diseases often present with chronicity and corresponding exuberant inflammation, which leads to loss of tooth support. In this study, we explored whether hBMSC exosomes can affect periodontitis progression. hBMSC exosomes were isolated from cell culture medium through sequential ultracentrifugation. miRNAs and proteins that were enriched in hBMSC exosomes were characterized by RNA sequencing and protein array, respectively. hBMSC exosomes significantly suppressed periodontal keystone pathogen Porphyromonas gingivalis-triggered inflammatory response in macrophages in vitro. Transcriptomic analysis suggested that exosomes exerted their effects through regulating cell metabolism, differentiation, and inflammation resolution. In vivo, weekly exosome injection into the gingival tissues reduced the tissue destruction and immune cell infiltration in rat ligature-induced periodontitis model. Collectively, these findings suggest that hBMSC-derived exosomes can potentially be used as a host modulation agent in the management of periodontitis.
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Affiliation(s)
- C Yue
- Department of Periodontics, School of Dentistry, Virginia Commonwealth University, Richmond, VA, USA
| | - J Cao
- Department of Periodontics, School of Dentistry, Virginia Commonwealth University, Richmond, VA, USA.,Department of Periodontology, Peking University School and Hospital of Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, Beijing, People's Republic of China
| | - A Wong
- Department of Periodontics, School of Dentistry, Virginia Commonwealth University, Richmond, VA, USA
| | - J H Kim
- Department of Periodontics, School of Dentistry, Virginia Commonwealth University, Richmond, VA, USA
| | - S Alam
- Department of Periodontics, School of Dentistry, Virginia Commonwealth University, Richmond, VA, USA
| | - G Luong
- Department of Periodontics, School of Dentistry, Virginia Commonwealth University, Richmond, VA, USA
| | - S Talegaonkar
- Department of Periodontics, School of Dentistry, Virginia Commonwealth University, Richmond, VA, USA
| | - Z Schwartz
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - B D Boyan
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - W V Giannobile
- Department of Oral Medicine, Infection, and Immunity, Harvard School of Dental Medicine, Boston, MA, USA
| | - S E Sahingur
- Department of Periodontics, School of Dental Medicine, University of Pennsylvania, PA, USA
| | - Z Lin
- Department of Periodontics, School of Dentistry, Virginia Commonwealth University, Richmond, VA, USA
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Han L, Zhang Y, Yue C, Huang Y, Wu Y, Chen J. Preliminary Study on Risk Factors for Morbidity of Nonalcoholic Fatty Liver Disease in High-Income Male Population. J Healthc Eng 2022; 2022:9331284. [PMID: 35251583 PMCID: PMC8890829 DOI: 10.1155/2022/9331284] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 11/29/2021] [Accepted: 12/14/2021] [Indexed: 12/15/2022]
Abstract
OBJECTIVES Believed to be a result of metabolic syndrome and unhealthy lifestyle, the incidence of nonalcoholic fatty liver disease (NAFLD) has become a serious public health problem. Among the high-income male population, metabolic syndrome and unhealthy lifestyle are particularly prominent. Therefore, we conducted a survey on 375 high-income male subjects, expecting to understand the risk factors and related factors for morbidity of NAFLD among the high-income male population being physically examined in Shanghai. METHODS A cross-sectional study was applied to 375 high-income male subjects (including 190 patients with NAFLD and 185 non-NAFLD subjects) who were examined in the special needs clinic at Huadong Hospital affiliated to Fudan University. In combination with medical history, physical examination, and laboratory test results and by use of a self-made NAFLD health questionnaire, the basic data of the research objects were collected and the obtained data were subject to a correlation analysis. RESULTS This study investigated 375 high-income males, and the morbidity rate of NAFLD was 50.67%. The NAFLD group was higher than the non-NAFLD group in terms of body weight, BMI, systolic blood pressure, and diastolic blood pressure (P < 0.05). Hypertension (OR = 2.944), diabetes (OR = 7.278), and hyperuricemia (OR = 1.922) are the risk factors for NAFLD; compared with no metabolic diseases, one (OR = 1.848), two (OR = 2.417), and three metabolic diseases (OR = 14.788) are risk factors for the development of NAFLD. Compared with the non-NAFLD group, the NAFLD group had a higher level of WBC, RBC, Hb, PLT, FPG, HbA1c, ALT, AST, GGT, ALP, TP, and UA (P < 0.05). There was a statistically significant difference in the intake of supper and staple foods between the NAFLD group and the non-NAFLD group, and the highly greasy diet was a risk factor for NAFLD (OR = 2.173) as opposed to the nongreasy diet. CONCLUSION High-income male population is a high-risk group of NAFLD. Most of the patients with NAFLD have abnormal biochemical indicators as opposed to the healthy population and are more likely to be complicated with other chronic diseases or abnormal health status. And the occurrence of hypertension, diabetes, and hyperuricemia is the risk factor for the development of NAFLD. At the same time, the number of metabolic diseases complicated is also a risk factor for NAFLD as compared with the absence of complications with such metabolic diseases. Compared with a diet that is not greasy, the fact that high-income male NAFLD patients have a very greasy diet increases the risk of NAFLD.
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Affiliation(s)
- Li Han
- Huadong Hospital Affiliated to Fudan University, Department of Traditional Chinese Medicine, 221 Yan'an West Road,Jing'an District, Shanghai 200040, China
| | - Yuting Zhang
- Huadong Hospital Affiliated to Fudan University, Department of Digestion, 221 Yan'an West Road,Jing'an District, Shanghai 200040, China
| | - Cui Yue
- The Office of Good Clinical Practice, 221 West Yan'an Road, Huadong Hospital, Shanghai 200040, China
| | - Yiqin Huang
- Huadong Hospital Affiliated to Fudan University, Department of Digestion, 221 Yan'an West Road,Jing'an District, Shanghai 200040, China
| | - Yumin Wu
- Huadong Hospital Affiliated to Fudan University, Department of Nephrology, 221 Yan'an West Road,Jing'an District, Shanghai 200040, China
| | - Jie Chen
- Huadong Hospital Affiliated to Fudan University, Department of Geriatrics, 317 Room,168 Yan'an West Road,Jing'an District, Shanghai 200040, China
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Alemanno F, An Q, Azzarello P, Barbato FCT, Bernardini P, Bi XJ, Cai MS, Catanzani E, Chang J, Chen DY, Chen JL, Chen ZF, Cui MY, Cui TS, Cui YX, Dai HT, D'Amone A, De Benedittis A, De Mitri I, de Palma F, Deliyergiyev M, Di Santo M, Dong TK, Dong ZX, Donvito G, Droz D, Duan JL, Duan KK, D'Urso D, Fan RR, Fan YZ, Fang K, Fang F, Feng CQ, Feng L, Fusco P, Gao M, Gargano F, Gong K, Gong YZ, Guo DY, Guo JH, Guo XL, Han SX, Hu YM, Huang GS, Huang XY, Huang YY, Ionica M, Jiang W, Kong J, Kotenko A, Kyratzis D, Lei SJ, Li S, Li WL, Li X, Li XQ, Liang YM, Liu CM, Liu H, Liu J, Liu SB, Liu WQ, Liu Y, Loparco F, Luo CN, Ma M, Ma PX, Ma T, Ma XY, Marsella G, Mazziotta MN, Mo D, Niu XY, Pan X, Parenti A, Peng WX, Peng XY, Perrina C, Qiao R, Rao JN, Ruina A, Salinas MM, Shang GZ, Shen WH, Shen ZQ, Shen ZT, Silveri L, Song JX, Stolpovskiy M, Su H, Su M, Sun ZY, Surdo A, Teng XJ, Tykhonov A, Wang H, Wang JZ, Wang LG, Wang S, Wang XL, Wang Y, Wang YF, Wang YZ, Wang ZM, Wei DM, Wei JJ, Wei YF, Wen SC, Wu D, Wu J, Wu LB, Wu SS, Wu X, Xia ZQ, Xu HT, Xu ZH, Xu ZL, Xu ZZ, Xue GF, Yang HB, Yang P, Yang YQ, Yao HJ, Yu YH, Yuan GW, Yuan Q, Yue C, Zang JJ, Zhang F, Zhang SX, Zhang WZ, Zhang Y, Zhang YJ, Zhang YL, Zhang YP, Zhang YQ, Zhang Z, Zhang ZY, Zhao C, Zhao HY, Zhao XF, Zhou CY, Zhu Y. Measurement of the Cosmic Ray Helium Energy Spectrum from 70 GeV to 80 TeV with the DAMPE Space Mission. Phys Rev Lett 2021; 126:201102. [PMID: 34110215 DOI: 10.1103/physrevlett.126.201102] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 03/25/2021] [Accepted: 04/06/2021] [Indexed: 06/12/2023]
Abstract
The measurement of the energy spectrum of cosmic ray helium nuclei from 70 GeV to 80 TeV using 4.5 years of data recorded by the Dark Matter Particle Explorer (DAMPE) is reported in this work. A hardening of the spectrum is observed at an energy of about 1.3 TeV, similar to previous observations. In addition, a spectral softening at about 34 TeV is revealed for the first time with large statistics and well controlled systematic uncertainties, with an overall significance of 4.3σ. The DAMPE spectral measurements of both cosmic protons and helium nuclei suggest a particle charge dependent softening energy, although with current uncertainties a dependence on the number of nucleons cannot be ruled out.
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Affiliation(s)
- F Alemanno
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L'Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Laboratori Nazionali del Gran Sasso, I-67100 Assergi, L'Aquila, Italy
| | - Q An
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - P Azzarello
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - F C T Barbato
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L'Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Laboratori Nazionali del Gran Sasso, I-67100 Assergi, L'Aquila, Italy
| | - P Bernardini
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Lecce, I-73100 Lecce, Italy
| | - X J Bi
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
| | - M S Cai
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - E Catanzani
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Perugia, I-06123 Perugia, Italy
| | - J Chang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - D Y Chen
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - J L Chen
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Z F Chen
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - M Y Cui
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - T S Cui
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - Y X Cui
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - H T Dai
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - A D'Amone
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Lecce, I-73100 Lecce, Italy
| | - A De Benedittis
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Lecce, I-73100 Lecce, Italy
| | - I De Mitri
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L'Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Laboratori Nazionali del Gran Sasso, I-67100 Assergi, L'Aquila, Italy
| | - F de Palma
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Lecce, I-73100 Lecce, Italy
| | - M Deliyergiyev
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - M Di Santo
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Lecce, I-73100 Lecce, Italy
| | - T K Dong
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - Z X Dong
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - G Donvito
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Bari, I-70125 Bari, Italy
| | - D Droz
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - J L Duan
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - K K Duan
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - D D'Urso
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Perugia, I-06123 Perugia, Italy
| | - R R Fan
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - Y Z Fan
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - K Fang
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - F Fang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - C Q Feng
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - L Feng
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - P Fusco
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Bari, I-70125 Bari, Italy
- Dipartimento di Fisica "M. Merlin" dell'Università e del Politecnico di Bari, I-70126 Bari, Italy
| | - M Gao
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - F Gargano
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Bari, I-70125 Bari, Italy
| | - K Gong
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - Y Z Gong
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - D Y Guo
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J H Guo
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - X L Guo
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - S X Han
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - Y M Hu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - G S Huang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - X Y Huang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - Y Y Huang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - M Ionica
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Perugia, I-06123 Perugia, Italy
| | - W Jiang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - J Kong
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - A Kotenko
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - D Kyratzis
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L'Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Laboratori Nazionali del Gran Sasso, I-67100 Assergi, L'Aquila, Italy
| | - S J Lei
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - S Li
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - W L Li
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - X Li
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - X Q Li
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - Y M Liang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - C M Liu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - H Liu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - J Liu
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - S B Liu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - W Q Liu
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y Liu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - F Loparco
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Bari, I-70125 Bari, Italy
- Dipartimento di Fisica "M. Merlin" dell'Università e del Politecnico di Bari, I-70126 Bari, Italy
| | - C N Luo
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - M Ma
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - P X Ma
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - T Ma
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - X Y Ma
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - G Marsella
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Lecce, I-73100 Lecce, Italy
| | - M N Mazziotta
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Bari, I-70125 Bari, Italy
| | - D Mo
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - X Y Niu
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - X Pan
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - A Parenti
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L'Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Laboratori Nazionali del Gran Sasso, I-67100 Assergi, L'Aquila, Italy
| | - W X Peng
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - X Y Peng
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - C Perrina
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - R Qiao
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J N Rao
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - A Ruina
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - M M Salinas
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - G Z Shang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - W H Shen
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - Z Q Shen
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - Z T Shen
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - L Silveri
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L'Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Laboratori Nazionali del Gran Sasso, I-67100 Assergi, L'Aquila, Italy
| | - J X Song
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - M Stolpovskiy
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - H Su
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - M Su
- Department of Physics and Laboratory for Space Research, the University of Hong Kong, Pok Fu Lam, Hong Kong SAR 999077, China
| | - Z Y Sun
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - A Surdo
- Istituto Nazionale di Fisica Nucleare (INFN)-Sezione di Lecce, I-73100 Lecce, Italy
| | - X J Teng
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - A Tykhonov
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - H Wang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - J Z Wang
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - L G Wang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - S Wang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - X L Wang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - Y Wang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - Y F Wang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - Y Z Wang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - Z M Wang
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L'Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)-Laboratori Nazionali del Gran Sasso, I-67100 Assergi, L'Aquila, Italy
| | - D M Wei
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - J J Wei
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - Y F Wei
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - S C Wen
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - D Wu
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J Wu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - L B Wu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - S S Wu
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - X Wu
- Department of Nuclear and Particle Physics, University of Geneva, CH-1211 Geneva, Switzerland
| | - Z Q Xia
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - H T Xu
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - Z H Xu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - Z L Xu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - Z Z Xu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - G F Xue
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - H B Yang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - P Yang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y Q Yang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - H J Yao
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y H Yu
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - G W Yuan
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - Q Yuan
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - C Yue
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - J J Zang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - F Zhang
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - S X Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - W Z Zhang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - Y Zhang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - Y J Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y L Zhang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - Y P Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y Q Zhang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - Z Zhang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China
| | - Z Y Zhang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - C Zhao
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - H Y Zhao
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - X F Zhao
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - C Y Zhou
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
| | - Y Zhu
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian district, Beijing 100190, China
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Hu B, Yan LF, Yang Y, Yu Y, Sun Q, Zhang J, Nan HY, Han Y, Hu YC, Sun YZ, Xiao G, Tian Q, Yue C, Feng JH, Zhai LH, Zhao D, Cui GB, Lockhart Welch V, Cornett EM, Urits I, Viswanath O, Varrassi G, Kaye AD, Wang W. Classification of Prostate Transitional Zone Cancer and Hyperplasia Using Deep Transfer Learning From Disease-Related Images. Cureus 2021; 13:e14108. [PMID: 33927922 PMCID: PMC8075764 DOI: 10.7759/cureus.14108] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Purpose The diagnosis of prostate transition zone cancer (PTZC) remains a clinical challenge due to their similarity to benign prostatic hyperplasia (BPH) on MRI. The Deep Convolutional Neural Networks (DCNNs) showed high efficacy in diagnosing PTZC on medical imaging but was limited by the small data size. A transfer learning (TL) method was combined with deep learning to overcome this challenge. Materials and methods A retrospective investigation was conducted on 217 patients enrolled from our hospital database (208 patients) and The Cancer Imaging Archive (nine patients). Using T2-weighted images (T2WIs) and apparent diffusion coefficient (ADC) maps, DCNN models were trained and compared between different TL databases (ImageNet vs. disease-related images) and protocols (from scratch, fine-tuning, or transductive transferring). Results PTZC and BPH can be classified through traditional DCNN. The efficacy of TL from natural images was limited but improved by transferring knowledge from the disease-related images. Furthermore, transductive TL from disease-related images had comparable efficacy to the fine-tuning method. Limitations include retrospective design and a relatively small sample size. Conclusion Deep TL from disease-related images is a powerful tool for an automated PTZC diagnostic system. In developing regions where only conventional MR scans are available, the accurate diagnosis of PTZC can be achieved via transductive deep TL from disease-related images.
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Affiliation(s)
- Bo Hu
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Lin-Feng Yan
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Yang Yang
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Ying Yu
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Qian Sun
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Jin Zhang
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Hai-Yan Nan
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Yu Han
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Yu-Chuan Hu
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Ying-Zhi Sun
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Gang Xiao
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Qiang Tian
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Cui Yue
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Jia-Hao Feng
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Liang-Hao Zhai
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Di Zhao
- Department of Computer Network Information, Chinese Academy of Science, Beijing, CHN
| | - Guang-Bin Cui
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
| | - Valerie Lockhart Welch
- Department of Pathology, Louisiana State University (LSU) Health Shreveport, Shreveport, USA
| | - Elyse M Cornett
- Department of Anaesthesiology, Louisiana State University (LSU) Health Shreveport, Shreveport, USA
| | - Ivan Urits
- Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA
| | - Omar Viswanath
- Department of Pain Management, University of Arizona, Phoenix, USA
| | | | - Alan D Kaye
- Department of Anesthesiology, Louisiana State University Health Shreveport, Shreveport, USA
| | - Wen Wang
- Department of Radiology, Fourth Military Medical University, Shaanxi, CHN
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13
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Yue C, Yuxin Z, Nan Z, Dongyou Z, Jiangning Y. An inversion model for estimating the negative air ion concentration using MODIS images of the Daxing'anling region. PLoS One 2020; 15:e0242554. [PMID: 33232344 PMCID: PMC7685430 DOI: 10.1371/journal.pone.0242554] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 11/04/2020] [Indexed: 01/10/2023] Open
Abstract
The negative air ion (NAI) concentration is an essential indicator of air quality and atmospheric pollution. The NAI concentration can be used to monitor air quality on a regional scale and is commonly determined using field measurements. However, obtaining these measurements is time-consuming. In this paper, the relationship between remotely sensed surface parameters (such as land surface temperature, normalized difference vegetation index (NDVI), and leaf area index) obtained from MODIS data products and the measured NAI concentration using a stepwise regression method was analyzed to estimate the spatial distribution of the NAI concentration and verify the precision. The results indicated that the NAI concentration had a negative correlation with temperature, leaf area index (LAI), and gross primary production while it exhibited a positive correlation with the NDVI. The relationship between land surface temperature and the NAI concentration in the Daxing’anling region is expressed by the regression equation of y = -35.51x1 + 11206.813 (R2 = 0.6123). Additionally, the NAI concentration in northwest regions with high forest coverage was higher than that in southeast regions with low forest coverage, suggesting that forests influence the air quality and reduce the impact of environmental pollution. The proposed inversion model is suitable for evaluating the air quality in Daxing’anling and provides a reference for air quality evaluation in other areas. In the future, we will expand the quantity and distribution range of sampling points, conduct continuous observations of NAI concentrations and environmental parameters in the research areas with different land-use types, and further improve the accuracy of inversion results to analyze the spatiotemporal dynamic changes in NAI concentration and explore the possibility of expanding the application areas of NAI monitoring.
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Affiliation(s)
- Cui Yue
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin, China
| | - Zhao Yuxin
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin, China
| | - Zhang Nan
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin, China
| | - Zhang Dongyou
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin, China
- * E-mail:
| | - Yang Jiangning
- Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin, China
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Lu JL, Zhao L, Han SC, Bi JL, Liu HX, Yue C, Lin L. MiR-129 is involved in the occurrence of uterine fibroid through inhibiting TET1. Eur Rev Med Pharmacol Sci 2020; 22:4419-4426. [PMID: 30058675 DOI: 10.26355/eurrev_201807_15492] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To detect the expressions of micro ribonucleic acid (miR)-129 and its target gene in uterine fibroid tissues and to investigate the role of miR-129 in the occurrence of uterine fibroid. PATIENTS AND METHODS The expressions of miR-129 and its target gene ten-eleven translocation 1 (TET1) were detected via quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Dual-luciferase reporter gene and Western blotting were used to verify the regulatory relation between miR-129 and target gene. The effects of miR-129 on the proliferation, apoptosis, cycle and extracellular matrix (ECM) of uterine fibroid cells were investigated via transfection with miR-129 mimics and TET1 small-interfering RNA (siRNA). RESULTS MiR-129 was lowly expressed in uterine fibroid. The expression of miR-129 was regulated by sex hormones. The highly expressed miR-129 promoted apoptosis and inhibited proliferation through reducing the low expression of TET1. At the same time, miR-129 affected the accumulation of ECM. CONCLUSIONS The expression of miR-129 in uterine fibroid is lower, and the proliferation capacity of tumor cells is enhanced, thus promoting the occurrence and development of uterine fibroid.
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Affiliation(s)
- J-L Lu
- Department of Gynecology and Obstetrics, The Second Hospital of Dalian Medical University, Dalian, China.
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Sato H, Schoenfeld A, Siau E, Suzawa K, Yue C, Offin M, Drilon A, Davare M, Riely G, Ladanyi M, Somwar R. P1.14-12 A Novel Activating MAP2K1 In-Frame Deletion Mediates Acquired Resistance to ROS1 TKIs in a Patient with ROS1 Fusion-Positive NSCLC. J Thorac Oncol 2019. [DOI: 10.1016/j.jtho.2019.08.1163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Zhang Y, Shi M, Wei L, He J, Zhu Y, Ma W, Yang Y, Zhao H, Jia X, Sun X, Ran L, Hao G, Ai Y, Wang Y, Wang T, Du L, Tang Q, Si Q, Yue C, Cheng G. Safety and Efficacy of Docetaxel plus Cisplatin Versus Cisplatin Concurrent with Radiation in Local Advanced Cervical Cancer: Midterm Results of A Phase III, Multicenter and Randomized Trial. Int J Radiat Oncol Biol Phys 2019. [DOI: 10.1016/j.ijrobp.2019.06.1761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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An Q, Asfandiyarov R, Azzarello P, Bernardini P, Bi XJ, Cai MS, Chang J, Chen DY, Chen HF, Chen JL, Chen W, Cui MY, Cui TS, Dai HT, D’Amone A, De Benedittis A, De Mitri I, Di Santo M, Ding M, Dong TK, Dong YF, Dong ZX, Donvito G, Droz D, Duan JL, Duan KK, D’Urso D, Fan RR, Fan YZ, Fang F, Feng CQ, Feng L, Fusco P, Gallo V, Gan FJ, Gao M, Gargano F, Gong K, Gong YZ, Guo DY, Guo JH, Guo XL, Han SX, Hu YM, Huang GS, Huang XY, Huang YY, Ionica M, Jiang W, Jin X, Kong J, Lei SJ, Li S, Li WL, Li X, Li XQ, Li Y, Liang YF, Liang YM, Liao NH, Liu CM, Liu H, Liu J, Liu SB, Liu WQ, Liu Y, Loparco F, Luo CN, Ma M, Ma PX, Ma SY, Ma T, Ma XY, Marsella G, Mazziotta MN, Mo D, Niu XY, Pan X, Peng WX, Peng XY, Qiao R, Rao JN, Salinas MM, Shang GZ, Shen WH, Shen ZQ, Shen ZT, Song JX, Su H, Su M, Sun ZY, Surdo A, Teng XJ, Tykhonov A, Vitillo S, Wang C, Wang H, Wang HY, Wang JZ, Wang LG, Wang Q, Wang S, Wang XH, Wang XL, Wang YF, Wang YP, Wang YZ, Wang ZM, Wei DM, Wei JJ, Wei YF, Wen SC, Wu D, Wu J, Wu LB, Wu SS, Wu X, Xi K, Xia ZQ, Xu HT, Xu ZH, Xu ZL, Xu ZZ, Xue GF, Yang HB, Yang P, Yang YQ, Yang ZL, Yao HJ, Yu YH, Yuan Q, Yue C, Zang JJ, Zhang F, Zhang JY, Zhang JZ, Zhang PF, Zhang SX, Zhang WZ, Zhang Y, Zhang YJ, Zhang YL, Zhang YP, Zhang YQ, Zhang Z, Zhang ZY, Zhao H, Zhao HY, Zhao XF, Zhou CY, Zhou Y, Zhu X, Zhu Y, Zimmer S. Measurement of the cosmic ray proton spectrum from 40 GeV to 100 TeV with the DAMPE satellite. Sci Adv 2019; 5:eaax3793. [PMID: 31799401 PMCID: PMC6868675 DOI: 10.1126/sciadv.aax3793] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Accepted: 09/03/2019] [Indexed: 05/23/2023]
Abstract
The precise measurement of the spectrum of protons, the most abundant component of the cosmic radiation, is necessary to understand the source and acceleration of cosmic rays in the Milky Way. This work reports the measurement of the cosmic ray proton fluxes with kinetic energies from 40 GeV to 100 TeV, with 2 1/2 years of data recorded by the DArk Matter Particle Explorer (DAMPE). This is the first time that an experiment directly measures the cosmic ray protons up to ~100 TeV with high statistics. The measured spectrum confirms the spectral hardening at ~300 GeV found by previous experiments and reveals a softening at ~13.6 TeV, with the spectral index changing from ~2.60 to ~2.85. Our result suggests the existence of a new spectral feature of cosmic rays at energies lower than the so-called knee and sheds new light on the origin of Galactic cosmic rays.
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Affiliation(s)
| | - Q. An
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - R. Asfandiyarov
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
| | - P. Azzarello
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
| | - P. Bernardini
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Lecce, I-73100 Lecce, Italy
| | - X. J. Bi
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
| | - M. S. Cai
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - J. Chang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - D. Y. Chen
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - H. F. Chen
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - J. L. Chen
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - W. Chen
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - M. Y. Cui
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - T. S. Cui
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - H. T. Dai
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - A. D’Amone
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Lecce, I-73100 Lecce, Italy
| | - A. De Benedittis
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Lecce, I-73100 Lecce, Italy
| | - I. De Mitri
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L’Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)–Laboratori Nazionali del Gran Sasso, Assergi, I-67100 L’Aquila, Italy
| | - M. Di Santo
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Lecce, I-73100 Lecce, Italy
| | - M. Ding
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - T. K. Dong
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Y. F. Dong
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - Z. X. Dong
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - G. Donvito
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Bari, I-70125, Bari, Italy
| | - D. Droz
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
| | - J. L. Duan
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - K. K. Duan
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - D. D’Urso
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Perugia, I-06123 Perugia, Italy
| | - R. R. Fan
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - Y. Z. Fan
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - F. Fang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - C. Q. Feng
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - L. Feng
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - P. Fusco
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Bari, I-70125, Bari, Italy
- Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy
| | - V. Gallo
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
| | - F. J. Gan
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - M. Gao
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - F. Gargano
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Bari, I-70125, Bari, Italy
| | - K. Gong
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - Y. Z. Gong
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - D. Y. Guo
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J. H. Guo
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - X. L. Guo
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - S. X. Han
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - Y. M. Hu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - G. S. Huang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - X. Y. Huang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Y. Y. Huang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - M. Ionica
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Perugia, I-06123 Perugia, Italy
| | - W. Jiang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - X. Jin
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - J. Kong
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - S. J. Lei
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - S. Li
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - W. L. Li
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - X. Li
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - X. Q. Li
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - Y. Li
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y. F. Liang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Y. M. Liang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - N. H. Liao
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - C. M. Liu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - H. Liu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - J. Liu
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - S. B. Liu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - W. Q. Liu
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y. Liu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - F. Loparco
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Bari, I-70125, Bari, Italy
- Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari, I-70126 Bari, Italy
| | - C. N. Luo
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - M. Ma
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - P. X. Ma
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - S. Y. Ma
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - T. Ma
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - X. Y. Ma
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - G. Marsella
- Dipartimento di Matematica e Fisica E. De Giorgi, Università del Salento, I-73100 Lecce, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Lecce, I-73100 Lecce, Italy
| | - M. N. Mazziotta
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Bari, I-70125, Bari, Italy
| | - D. Mo
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - X. Y. Niu
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - X. Pan
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - W. X. Peng
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - X. Y. Peng
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - R. Qiao
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J. N. Rao
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - M. M. Salinas
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
| | - G. Z. Shang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - W. H. Shen
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - Z. Q. Shen
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Z. T. Shen
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - J. X. Song
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - H. Su
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - M. Su
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- Department of Physics and Laboratory for Space Research, The University of Hong Kong, Pok Fu Lam, Hong Kong, China
| | - Z. Y. Sun
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - A. Surdo
- Istituto Nazionale di Fisica Nucleare (INFN)–Sezione di Lecce, I-73100 Lecce, Italy
| | - X. J. Teng
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - A. Tykhonov
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
| | - S. Vitillo
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
| | - C. Wang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - H. Wang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - H. Y. Wang
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J. Z. Wang
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - L. G. Wang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - Q. Wang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - S. Wang
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - X. H. Wang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - X. L. Wang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - Y. F. Wang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - Y. P. Wang
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Y. Z. Wang
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Z. M. Wang
- Gran Sasso Science Institute (GSSI), Via Iacobucci 2, I-67100 L’Aquila, Italy
- Istituto Nazionale di Fisica Nucleare (INFN)–Laboratori Nazionali del Gran Sasso, Assergi, I-67100 L’Aquila, Italy
| | - D. M. Wei
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - J. J. Wei
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Y. F. Wei
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - S. C. Wen
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - D. Wu
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J. Wu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - L. B. Wu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - S. S. Wu
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - X. Wu
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
| | - K. Xi
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Z. Q. Xia
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - H. T. Xu
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - Z. H. Xu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - Z. L. Xu
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Z. Z. Xu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - G. F. Xue
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - H. B. Yang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - P. Yang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y. Q. Yang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Z. L. Yang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - H. J. Yao
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y. H. Yu
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Q. Yuan
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
- School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
| | - C. Yue
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - J. J. Zang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - F. Zhang
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J. Y. Zhang
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - J. Z. Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - P. F. Zhang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - S. X. Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - W. Z. Zhang
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - Y. Zhang
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Y. J. Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y. L. Zhang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - Y. P. Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - Y. Q. Zhang
- University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, China
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Z. Zhang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033, China
| | - Z. Y. Zhang
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - H. Zhao
- Institute of High Energy Physics, Chinese Academy of Sciences, Yuquan Road 19B, Beijing 100049, China
| | - H. Y. Zhao
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - X. F. Zhao
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - C. Y. Zhou
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - Y. Zhou
- Institute of Modern Physics, Chinese Academy of Sciences, Nanchang Road 509, Lanzhou 730000, China
| | - X. Zhu
- State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026, China
- Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
| | - Y. Zhu
- National Space Science Center, Chinese Academy of Sciences, Nanertiao 1, Zhongguancun, Haidian District, Beijing 100190, China
| | - S. Zimmer
- Department of Nuclear and Particle Physics, University of Geneva, Geneva CH-1211, Switzerland
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Yuan X, Yue C, Yu M, Chen P, Du P, Shao CH, Cheng SC, Bian RJ, Wang SY, Wang W, Cui GB. Fetal brain development at 25-39 weeks gestational age: A preliminary study using intravoxel incoherent motion diffusion-weighted imaging. J Magn Reson Imaging 2019; 50:899-909. [PMID: 30677192 DOI: 10.1002/jmri.26667] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [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: 09/18/2018] [Revised: 01/08/2019] [Accepted: 01/09/2019] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND The fetal brain developmental changes of water diffusivity and perfusion has not been extensively explored. PURPOSE/HYPOTHESIS To evaluate the fetal brain developmental changes of water diffusivity and perfusion using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI). STUDY TYPE Prospective. POPULATION Seventy-nine normal singleton fetuses were scanned without sedation of healthy pregnant women. FIELD STRENGTH/SEQUENCE 5 T MRI/T1 /2 -weighted image and IVIM-DWI. ASSESSMENT Pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) values were calculated in the frontal (FWM), temporal (TWM), parietal (PWM), and occipital white matter (OWM) as well as cerebellar hemisphere (CH), basal ganglia region (BGR), thalamus (TH), and pons using an IVIM model. STATISTICAL TESTS One-way analysis of variable (ANOVA) followed by Bonferroni post-hoc multiple comparison was employed to reveal the difference of IVIM parameters among the investigated brain regions. The linear and the nonlinear polynomial regression analyses were utilized to reveal the correlation between gestational age (GA) and IVIM parameters. RESULTS There were significant differences in both D (F(7,623) = 96.64, P = 0.000) and f values (F(7,623) = 2.361, P = 0.0219), but not D* values among the varied brain regions. D values from TWM (r2 = 0.1402, P = 0.0002), PWM (r2 = 0.2245, P = 0.0002), OWM (r2 = 0.2519, P = 0.0002), CH (r2 = 0.2245, P = 0.0002), BGR (r2 = 0.3393, P = 0.0001), TH (r2 = 0.1259, P = 0.0001), and D* value from pons (r2 = 0.2206, P = 0.0002) were significantly correlated with GA using linear regression analysis. Quadratic regression analysis led to results similar to those using the linear regression model. DATA CONCLUSION IVIM-DWI parameters may indicate fetal brain developmental alterations but the conclusion is far from reached due to the not as high-powered correlation between IVIM parameters and GA. LEVEL OF EVIDENCE 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:899-909.
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Affiliation(s)
- Xiao Yuan
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | - Cui Yue
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | - Mei Yu
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | - Ping Chen
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | - Pang Du
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | - Chang-Hua Shao
- Student Brigade, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | - Si-Chao Cheng
- Student Brigade, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | - Ren-Jie Bian
- Student Brigade, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | | | - Wen Wang
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
| | - Guang-Bin Cui
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), Shaanxi, China
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Andela N, Morton DC, Giglio L, Chen Y, van der Werf GR, Kasibhatla PS, DeFries RS, Collatz GJ, Hantson S, Kloster S, Bachelet D, Forrest M, Lasslop G, Li F, Mangeon S, Melton JR, Yue C, Randerson JT. A human-driven decline in global burned area. Science 2018; 356:1356-1362. [PMID: 28663495 DOI: 10.1126/science.aal4108] [Citation(s) in RCA: 211] [Impact Index Per Article: 35.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Accepted: 06/02/2017] [Indexed: 12/11/2022]
Abstract
Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes.
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Affiliation(s)
- N Andela
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA. .,Department of Earth System Science, University of California, Irvine, CA 92697, USA
| | - D C Morton
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
| | - L Giglio
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Y Chen
- Department of Earth System Science, University of California, Irvine, CA 92697, USA
| | - G R van der Werf
- Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - P S Kasibhatla
- Nicholas School of the Environment, Duke University, Durham, NC 27708, USA
| | - R S DeFries
- Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY 10027, USA
| | - G J Collatz
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
| | - S Hantson
- Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, Germany
| | - S Kloster
- Max Planck Institute for Meteorology, Bundesstraße 53, 20164 Hamburg, Germany
| | - D Bachelet
- Biological and Ecological Engineering, Oregon State University, Corvallis, OR 97331, USA
| | - M Forrest
- Senckenberg Biodiversity and Climate Research Institute (BiK-F), Senckenberganlage 25, 60325 Frankfurt am Main, Germany
| | - G Lasslop
- Max Planck Institute for Meteorology, Bundesstraße 53, 20164 Hamburg, Germany
| | - F Li
- International Center for Climate and Environmental Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - S Mangeon
- Department of Physics, Imperial College London, London, UK
| | - J R Melton
- Climate Research Division, Environment Canada, Victoria, BC V8W 2Y2, Canada
| | - C Yue
- Laboratoire des Sciences du Climat et de l'Environnement-Institute Pierre Simon Laplace, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint Quentin, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
| | - J T Randerson
- Department of Earth System Science, University of California, Irvine, CA 92697, USA
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Zhang J, Feng JY, Ni YL, Wen YJ, Niu Y, Tamba CL, Yue C, Song Q, Zhang YM. pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies. Heredity (Edinb) 2017; 118:517-524. [PMID: 28295030 PMCID: PMC5436030 DOI: 10.1038/hdy.2017.8] [Citation(s) in RCA: 117] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 01/14/2017] [Accepted: 01/20/2017] [Indexed: 02/06/2023] Open
Abstract
Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.
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Affiliation(s)
- J Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - J-Y Feng
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Y-L Ni
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Y-J Wen
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Y Niu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - C L Tamba
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - C Yue
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Q Song
- Soybean Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA
| | - Y-M Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
- Statistical Genomics Lab, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
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Roberts J, John S, Bussell C, Grajzel K, Zhao R, Karas S, Six D, Yue C, Gavett B. C-26Age Group, Not Executive Functioning, Predicts Past Susceptibility to Internet Phishing Scams. Arch Clin Neuropsychol 2015. [DOI: 10.1093/arclin/acv047.228] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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22
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Yue C, Zhao B, Ren Y, Kuijer R, van der Mei HC, Busscher HJ, Rochford ETJ, Rochford ETJ. The implant infection paradox: why do some succeed when others fail? Opinion and discussion paper. Eur Cell Mater 2015; 29:303-10; discussion 310-3. [PMID: 26044130 DOI: 10.22203/ecm.v029a23] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Biomaterial-implants are frequently used to restore function and form of human anatomy. However, the presence of implanted biomaterials dramatically elevates infection risk. Paradoxically, dental-implants placed in a bacteria-laden milieu experience moderate failure-rates, due to infection (0.0-1.1%), similar to the ones of joint-arthroplasties placed in a near-sterile environment (0.1-1.3%). Transcutaneous bone-fixation pins breach the immune-barrier of the epidermis, exposing underlying sterile-tissue to an unsterile external environment. In contrast to dental-implants, also placed in a highly unsterile environment, these pins give rise to relatively high infection-associated failure-rates of up to 23.0%. Herein, we attempt to identify causes as to why dental-implants so often succeed, where others fail. The major part of all implants considered are metal-made, with similar surface-finishes. Material choice was therefore discarded as underlying the paradox. Antimicrobial activity of saliva has also been suggested as a cause for the success of dental-implants, but was discarded because saliva is the implant-site-fluid from which viable bacteria adhere. Crevicular fluid was discarded as it is largely analogous to serum. Instead, we attribute the relative success of dental-implants to (1) ability of oral tissues to heal rapidly in the continuous presence of commensal bacteria and opportunistic pathogens, and (2) tolerance of the oral immune-system. Inability of local tissue to adhere, spread and grow in presence of bacteria and an intolerant immune-system are identified as the likely main causes explaining the susceptibility of other implants to infection-associated failure. In conclusion, it is the authors' belief that new anti-infection strategies for a wide range of biomaterial-implants may be derived from the relative success of dental-implants.
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Affiliation(s)
- C Yue
- University of Groningen, University Medical Center Groningen, Department of Biomedical Engineering, Antonius Deusinglaan 1, 9713 AV Groningen, The
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23
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Evangeliou N, Balkanski Y, Cozic A, Hao WM, Mouillot F, Thonicke K, Paugam R, Zibtsev S, Mousseau TA, Wang R, Poulter B, Petkov A, Yue C, Cadule P, Koffi B, Kaiser JW, Møller AP. Fire evolution in the radioactive forests of Ukraine and Belarus: future risks for the population and the environment. ECOL MONOGR 2015. [DOI: 10.1890/14-1227.1] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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24
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Yue C, Bing L, Yuan Z, Tianzi J. Genetic sculpture of fine-grained human cortical regionalization. Front Neurosci 2015. [DOI: 10.3389/conf.fnins.2015.91.00003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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25
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Fan X, Zhao S, Yue C, Yang Q, Gong W, Chen Y, Wang H, Jia Q, Xu Z, Xu X. 1,8-Diiodooctane as the processing additive to improve the efficiency of P3HT:PC61BM solar cells. J Nanosci Nanotechnol 2014; 14:3592-3596. [PMID: 24734595 DOI: 10.1166/jnn.2014.7957] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Controlling the blend morphology is critical for achieving high power conversion efficiency in polymer/fullerene bulk heterojunction (BHJ) photovoltaic devices. As a simple and effective method to control morphology, adding processing additives has been widely applied in the organic BHJ solar cells. In this paper, we demonstrate that adding 1,8-diiodooctane as a processing additives is an effective method to improve the morphology and the efficiency of bulk heterojunctions (BHJ) solar cells based on the regioregular poly(3-hexylthiophene) (P3HT) and a soluble fullerene derivative ([6,6]-phenyl C61-butyric acid methyl ester, PC61BM). We investigated the unique way in which the 1,8-diiodooctane plays the rule to enhance the performance of solar cells according to different morphology and crystallinity of active layers prepared with and without the additive. The morphology is studied with atomic force microscopy (AFM) and Grazing Incidence X-ray Diffraction (GIXRD). We also find a balance between a large interfacial area for exciton dissociation and continuous pathways for carrier transportation when the additive is used.
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26
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Luo ZR, Zhuang XJ, Zhang RZ, Wang JQ, Yue C, Huang X. Automated 3D segmentation of hippocampus based on active appearance model of brain MR images for the early diagnosis of Alzheimer's disease. Minerva Med 2014; 105:157-165. [PMID: 24727880] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
AIM To investigate the hippocampal regional deformation modes by means of a novel method of automatic segmentation for discriminating between Alzheimer's disease (AD) and normal aging; and to further provide the effective evidence for the early diagnosis of AD. METHODS Twenty AD patients and sixty healthy volunteers were included in this retrospective study. High-resolution structural volumetric images were obtained on a 3.0 T MR imaging system. Data were processed to create three-dimensional (3D) active appearance model (AAM) of hippocampus. Automatic recognition and 3D segmentation were carried out on both sides of the hippocampus in brain MR images of individuals with this model, and the hippocampal statistical shape model was established for AD group and control group. Student's t test was used to identify whether there was difference between AD group and control group in the hippocampal regional deformation detected by automatic segmentation, and to compare whether there was difference between the automated segmentation and the manual tracing for quantifying hippocampal volumes on left/right side of the same sex group of healthy volunteers and if there was genderwise difference. Pearson's Correlation test was employed to determine whether there was a correlation between automated segmentation and manual tracing for quantifying hippocampal volumes. RESULTS No significant difference was detected between automated segmentation and manual tracing for quantifying hippocampal volumes on left/right side of the same sex group of healthy volunteers (P>0.05). Further there was no significant genderwise difference (P>0.05). A very strong positive correlation existed between both methods for quantifying hippocampal volumes (denoted R(2) near 1.0, P<0.001). Noticeable atrophy of bilateral hippocampal head was found among twenty patients with AD through statistical shape model compared with control group (P<0.05), especially on the left where inward-deformation was significantly found. CONCLUSION This novel method of automated segmentation of the hippocampus based on AAM has been found to be reliable and accurate in our study, which may be an alternative to manual segmentation. The featured atrophy of hippocampal head can be regarded as an important biomarker for the early diagnosis of AD.
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Affiliation(s)
- Z R Luo
- Department of Radiology, The First Affiliated Hospital, Xiamen University, Xiamen, China -
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27
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Wang J, Yue C, Zhao G, Gao D. 129 Effect of different nanoparticles on the SF21 cell membrane transport properties to water and glycerol. Cryobiology 2013. [DOI: 10.1016/j.cryobiol.2013.09.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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28
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Chi Q, Liu Z, Li Y, Yang J, Chen Z, Yue C, Luo J, Yin H. Development of a Real-Time PCR Assay for Detection and Quantification ofAnaplasma ovisInfection. Transbound Emerg Dis 2013; 60 Suppl 2:119-24. [DOI: 10.1111/tbed.12139] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2012] [Indexed: 12/01/2022]
Affiliation(s)
- Q. Chi
- State Key Laboratory of Veterinary Etiological Biology; Key Laboratory of Grazing Animal Diseases MOA; Key Laboratory of Veterinary Parasitology of Gansu Province; Lanzhou Veterinary Research Institute; Chinese Academy of Agricultural Sciences; Lanzhou China
- College of Veterinary Medicine; Xinjiang Agricultural University; Urumqi China
| | - Z. Liu
- State Key Laboratory of Veterinary Etiological Biology; Key Laboratory of Grazing Animal Diseases MOA; Key Laboratory of Veterinary Parasitology of Gansu Province; Lanzhou Veterinary Research Institute; Chinese Academy of Agricultural Sciences; Lanzhou China
| | - Y. Li
- State Key Laboratory of Veterinary Etiological Biology; Key Laboratory of Grazing Animal Diseases MOA; Key Laboratory of Veterinary Parasitology of Gansu Province; Lanzhou Veterinary Research Institute; Chinese Academy of Agricultural Sciences; Lanzhou China
| | - J. Yang
- State Key Laboratory of Veterinary Etiological Biology; Key Laboratory of Grazing Animal Diseases MOA; Key Laboratory of Veterinary Parasitology of Gansu Province; Lanzhou Veterinary Research Institute; Chinese Academy of Agricultural Sciences; Lanzhou China
| | - Z. Chen
- State Key Laboratory of Veterinary Etiological Biology; Key Laboratory of Grazing Animal Diseases MOA; Key Laboratory of Veterinary Parasitology of Gansu Province; Lanzhou Veterinary Research Institute; Chinese Academy of Agricultural Sciences; Lanzhou China
| | - C. Yue
- College of Veterinary Medicine; Xinjiang Agricultural University; Urumqi China
| | - J. Luo
- State Key Laboratory of Veterinary Etiological Biology; Key Laboratory of Grazing Animal Diseases MOA; Key Laboratory of Veterinary Parasitology of Gansu Province; Lanzhou Veterinary Research Institute; Chinese Academy of Agricultural Sciences; Lanzhou China
| | - H. Yin
- State Key Laboratory of Veterinary Etiological Biology; Key Laboratory of Grazing Animal Diseases MOA; Key Laboratory of Veterinary Parasitology of Gansu Province; Lanzhou Veterinary Research Institute; Chinese Academy of Agricultural Sciences; Lanzhou China
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Wang J, Zhu K, Zhao G, Ren J, Yue C, Gao D. Dual dependence of cryobiogical properties of Sf21 cell membrane on the temperature and the concentration of the cryoprotectant. PLoS One 2013; 8:e72836. [PMID: 24023781 PMCID: PMC3762842 DOI: 10.1371/journal.pone.0072836] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2013] [Accepted: 07/14/2013] [Indexed: 11/25/2022] Open
Abstract
The Sf21 cell line is extensively used for virus research and producing heterologous recombinant proteins. To develop optimal strategies for minimizing cell injury due to intracellular ice formation and excessive volume shrinkage during cryopreservation, the fundamental transport properties including the osmotic inactive volume (Vb), the hydraulic conductivity (Lp), and the glycerol permeability (Ps) of Sf21 cell membrane at 25, 15, 5 and −2°C were characterized using a micro-perfusion chamber. The effects of temperature on the hydraulic conductivity and the glycerol permeability of Sf21 cell membrane, reflected by the activation energies, were quantitatively investigated. It was found that the hydraulic conductivity decreases along with the increase of the final CPA concentration at a given temperature, and quantitative analysis indicates that the hydraulic conductivity has a significant linear attenuation along with the increase of the concentration of glycerol. Therefore, we incorporate the concentration dependence of the hydraulic conductivity into the classic Arrhenius relationship by replacing the constant reference value of the hydraulic conductivity at the reference temperature with a function that is linearly dependent on the CPA concentration. Consequently, the prediction of the Arrhenius relationship is improved, and the novel Arrhenius relationship could be very important to the development of optimal strategies for cell cryopreservation.
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Affiliation(s)
- Jianye Wang
- Institute of Biomedical Engineering, Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, Anhui, People’s Republic China
| | - Kaixuan Zhu
- Institute of Biomedical Engineering, Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, Anhui, People’s Republic China
| | - Gang Zhao
- Institute of Biomedical Engineering, Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, Anhui, People’s Republic China
- * E-mail:
| | - Jian Ren
- Institute of Biomedical Engineering, Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, Anhui, People’s Republic China
| | - Cui Yue
- Institute of Biomedical Engineering, Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, Anhui, People’s Republic China
| | - Dayong Gao
- Institute of Biomedical Engineering, Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, Anhui, People’s Republic China
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Yue C, Fang C, Gong X, Li L, Li T, Liang X. The impact of overnight culture for pregnancy outcomes in thawed - frozen blastocyst transfer cycles. Fertil Steril 2013. [DOI: 10.1016/j.fertnstert.2013.07.1072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Li T, Wang X, Yue C, Fang C. Comparison of pregnant outcomes of thawing blastocyst one day before transfer or not. Fertil Steril 2013. [DOI: 10.1016/j.fertnstert.2013.07.1071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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32
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Yue C, Li J, Li M, Zhang F, Zhao D, Cui Q. Cardiac mass in Behçet's disease. Clin Exp Rheumatol 2012; 30:S27-S31. [PMID: 22935263] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2011] [Accepted: 02/17/2012] [Indexed: 06/01/2023]
Abstract
Cardiac mass is a rare manifestation of Behçet's disease (BD). Intracardiac thrombosis, endomyocardiofibrosis, endocardial fibroelastosis, inflammatory mass and cystic change have been reported as different entities of cardiac mass in BD. Here we presented 6 cases of this rare manifestation of BD. The clinical and pathological features were reviewed.
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Affiliation(s)
- C Yue
- Department of Rheumatology, Peking Union Medical College Hospital, Beijing, China
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Zhang J, Yue C, Zhang YM. Bias correction for estimated QTL effects using the penalized maximum likelihood method. Heredity (Edinb) 2012; 108:396-402. [PMID: 21934700 PMCID: PMC3313049 DOI: 10.1038/hdy.2011.86] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [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: 02/26/2011] [Revised: 08/05/2011] [Accepted: 08/12/2011] [Indexed: 01/22/2023] Open
Abstract
A penalized maximum likelihood method has been proposed as an important approach to the detection of epistatic quantitative trait loci (QTL). However, this approach is not optimal in two special situations: (1) closely linked QTL with effects in opposite directions and (2) small-effect QTL, because the method produces downwardly biased estimates of QTL effects. The present study aims to correct the bias by using correction coefficients and shifting from the use of a uniform prior on the variance parameter of a QTL effect to that of a scaled inverse chi-square prior. The results of Monte Carlo simulation experiments show that the improved method increases the power from 25 to 88% in the detection of two closely linked QTL of equal size in opposite directions and from 60 to 80% in the identification of QTL with small effects (0.5% of the total phenotypic variance). We used the improved method to detect QTL responsible for the barley kernel weight trait using 145 doubled haploid lines developed in the North American Barley Genome Mapping Project. Application of the proposed method to other shrinkage estimation of QTL effects is discussed.
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Affiliation(s)
- J Zhang
- Section on Statistical Genomics, State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - C Yue
- Section on Statistical Genomics, State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Y-M Zhang
- Section on Statistical Genomics, State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Nanjing, China
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Abstract
We present a novel cellular microarray assay using soluble peptide-loaded HLA A2-Ig dimer complexes that optimizes the avidity of peptide-HLA binding by preserving the molecular flexibility of the dimer complex while attaining much higher concentrations of the complex relative to cognate T-cell receptors. A seminal advance in assay development is made by separating the molecular T-cell receptor recognition event from the binding interactions that lead to antigen-specific cell capture on the microarray. This advance enables the quantitative determination of antigen-specific frequencies in heterogeneous T-cell populations without enumerating the number of cells captured on the microarray. The specificity of cell capture, sensitivity to low antigen-specific frequencies, and quantitation of antigenic T-cell specificities are established using CD8 T-cell populations with prepared antigen-specific CTL frequencies and heterogeneous T cells isolated from peripheral blood. The results demonstrate several advantages for high-throughput broad-based, quantitative assessments of low-frequency antigen specificities. The assay enables the use of cellular microarrays to determine the stability and flux of antigen-specific T-cell responses within and across populations.
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Affiliation(s)
- C Yue
- Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA
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Wong J, Chan C, Yue C. Clinical Outcomes and Angiographic Follow-up after Stenting of Unprotected Left Main Coronary Artery Stenosis in a Regional Hospital without Surgical Backup. Heart Lung Circ 2010. [DOI: 10.1016/j.hlc.2010.06.957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Li Y, Yue C, Hart SN, Klaassen CD. Dynamic patterns of histone methylation are associated with ontogenic expression of the Cyp3a genes during mouse liver maturation. FASEB J 2009. [DOI: 10.1096/fasebj.23.1_supplement.752.5] [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: 11/11/2022]
Affiliation(s)
- Ye Li
- PharmacologyKUMCKansas cityKS
| | - Cui Yue
- PharmacologyKUMCKansas cityKS
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Parr A, Kulbatski I, Zahir T, Wang X, Yue C, Keating A, Tator C. Transplanted adult spinal cord–derived neural stem/progenitor cells promote early functional recovery after rat spinal cord injury. Neuroscience 2008; 155:760-70. [DOI: 10.1016/j.neuroscience.2008.05.042] [Citation(s) in RCA: 134] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2008] [Revised: 05/04/2008] [Accepted: 05/05/2008] [Indexed: 01/21/2023]
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Yue C, Mutsuga N, Sugimura Y, Verbalis J, Gainer H. Differential kinetics of oxytocin and vasopressin heteronuclear RNA expression in the rat supraoptic nucleus in response to chronic salt loading in vivo. J Neuroendocrinol 2008; 20:227-32. [PMID: 18088359 DOI: 10.1111/j.1365-2826.2007.01640.x] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Previous studies have shown that the secretion of oxytocin and vasopressin from the posterior pituitary always accompanies systemic hyperosmotic stimuli in rats, and that oxytocin and vasopressin mRNAs consistently increase in response to prolonged hyperosmotic stimuli. Hence, it has been widely interpreted that oxytocin and vasopressin secretion and gene expression are closely coupled. In the present study, we used both vasopressin and oxytocin intron- specific probes to measure vasopressin and oxytocin heteronuclear RNA (hnRNA) levels, respectively, by in situ hybridisation in the rat supraoptic nucleus (SON) in conjunction with radioimmunoassays of vasopressin and oxytocin peptide levels in plasma and in the posterior pituitary in normally hydrated rats and after 1-5 days of salt loading. Increased oxytocin secretion in response to hyperosmotic stimuli exceeded vasopressin secretion at every time point studied. Vasopressin hnRNA in the SON increased to near maximal levels within minutes after the hyperosmotic stimulus, and was maintained throughout all 5 days of salt loading. By contrast, oxytocin hnRNA did not significantly change from control levels until approximately 2 days after hyperosmotic stimulation, and was not maximal until 3 days. In summary, increases in oxytocin gene transcription in response to osmotic stimuli are dramatically delayed compared to increases in vasopressin gene transcription under the same conditions. These data indicate that oxytocin gene transcription is not as closely correlated with pituitary peptide secretion as is vasopressin gene transcription, and suggests that there is a fundamental difference in excitation-secretion-transcription coupling mechanisms that regulate these two closely related genes in the rat magnocellular neurones in the SON.
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Affiliation(s)
- C Yue
- Laboratory of Neurochemistry, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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Trachtenberg J, Bogaards A, Weersink RA, Haider MA, Evans A, McCluskey SA, Scherz A, Gertner MR, Yue C, Appu S, Aprikian A, Savard J, Wilson BC, Elhilali M. Vascular targeted photodynamic therapy with palladium-bacteriopheophorbide photosensitizer for recurrent prostate cancer following definitive radiation therapy: assessment of safety and treatment response. J Urol 2007; 178:1974-9; discussion 1979. [PMID: 17869307 DOI: 10.1016/j.juro.2007.07.036] [Citation(s) in RCA: 115] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2007] [Indexed: 11/30/2022]
Abstract
PURPOSE Tookad is a novel intravascular photosensitizer. When activated by 763 nm light, it destroys tumors by damaging their blood supply. It then clears rapidly from the circulatory system. To our knowledge we report the first application of Tookad vascular targeted photodynamic therapy in humans. We assessed the safety, pharmacokinetics and preliminary treatment response as a salvage procedure after external beam radiation therapy. MATERIALS AND METHODS Patients received escalating drug doses of 0.1 to 2 mg/kg at a fixed light dose of 100 J/cm or escalated light doses of 230 and 360 J/cm at the 2 mg/kg dose. Four optical fibers were placed transperineally in the prostate, including 2 for light delivery and 2 for light dosimetry. Treatment response was assessed primarily by hypovascular lesion formation on contrast enhanced magnetic resonance imaging and transrectal ultrasound guided biopsies targeting areas of lesion formation and secondarily by serum prostate specific antigen changes. RESULTS Tookad vascular targeted photodynamic therapy was technically feasible. The plasma drug concentration was negligible by 2 hours after infusion. In the drug escalation arm 3 of 6 patients responded, as seen on magnetic resonance imaging, including 1 at 1 mg/kg and 2 at 2 mg/kg. The light dose escalation demonstrated an increasing volume of effect with 2 of 3 patients in the first light escalation cohort responding and all 6 responding at the highest light dose with lesions encompassing up to 70% of the peripheral zone. There were no serious adverse events, and continence and potency were maintained. CONCLUSIONS Tookad vascular targeted photodynamic therapy salvage therapy is safe and well tolerated. Lesion formation is strongly drug and light dose dependent. Early histological and magnetic resonance imaging responses highlight the clinical potential of Tookad vascular targeted photodynamic therapy to manage post-external beam radiation therapy recurrence.
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Affiliation(s)
- J Trachtenberg
- Department of Surgical Oncology, Ontario Cancer Institute/Princess Margaret Hospital/University Health Network, Toronto, Ontario, Canada.
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Kong X, Zhang Y, Zhu X, Guo J, Wang R, Zhang W, Zhang C, Yue C, Jia Z. Effect of dietary NDF levels on nutrient digestion
in hindgut of sheep. J Anim Feed Sci 2007. [DOI: 10.22358/jafs/74477/2007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Beilin J, Harewood L, Frydenberg M, Mameghan H, Martyres RF, Farish SJ, Yue C, Deam DR, Byron KA, Zajac JD. A case-control study of the androgen receptor gene CAG repeat polymorphism in Australian prostate carcinoma subjects. Cancer 2001; 92:941-9. [PMID: 11550169 DOI: 10.1002/1097-0142(20010815)92:4<941::aid-cncr1404>3.0.co;2-p] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND The development of prostate carcinoma is androgen-dependent. The coding sequence of the androgen receptor (AR) gene contains a CAG repeat polymorphism that has been shown to influence AR activity in vitro. Studies of this polymorphism as a prostate carcinoma risk factor have been conflicting. METHODS A matched case-control design was used in a clinic-based multicenter study of Australian prostate carcinoma subjects. Cancer subjects were matched by age and locality with controls, all of whom had a serum prostate specific antigen (PSA) level of less than 4 mg/L. Conditional logistic regression was used to determine the relative risk of prostate carcinoma dependent on AR gene CAG number. The association of disease characteristics at diagnosis with the polymorphism also was assessed. RESULTS Five hundred forty-five cases of prostate carcinoma and 456 matched case-control pairs were recruited. Association studies of disease characteristics at diagnosis showed age at diagnosis to be associated with AR CAG number by univariate (P = 0.004) and multivariate (adjusting for PSA, stage, and grade) linear regression (P = 0.018). No association was observed between the polymorphism and disease stage (TNM-based categories; P = 0.277), histologic grade (P = 0.41), or PSA level at diagnosis (P = 0.48). In the pairwise case-control analysis, the odds ratio of prostate carcinoma for a change of 5 CAG repeats gave an odds ratio of 0.9821 (95% confidence interval, 0.84-1.15). CONCLUSIONS In this Australian study population, the AR CAG repeat polymorphism was not a risk factor for prostate carcinoma, but a shorter repeat sequence was associated with earlier age at diagnosis.
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Affiliation(s)
- J Beilin
- Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, Victoria, Australia.
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42
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Xia C, Bao Z, Yue C, Sanborn BM, Liu M. Phosphorylation and regulation of G-protein-activated phospholipase C-beta 3 by cGMP-dependent protein kinases. J Biol Chem 2001; 276:19770-7. [PMID: 11278298 DOI: 10.1074/jbc.m006266200] [Citation(s) in RCA: 83] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Among the drugs that are known to relax the vascular smooth muscle and regulate other cellular functions, beta-adrenergic agonists and nitric oxide-containing compounds are some of the most effective ones. The mechanisms of these drugs are thought to lower agonist-induced intracellular [Ca(2+)] by increasing intracellular cAMP and cGMP, activating their respective protein kinases. However, the physiological targets of cyclic nucleotide-dependent protein kinases are not clear. The molecular basis for the regulation of intracellular Ca(2+) by signaling pathways coupled to cyclic nucleotides is not well defined. G-protein-activated phospholipase C (PLC-beta) catalyzes the hydrolysis of phosphatidylinositol 4,5-bisphosphates to generate diacylglycerol and inositol 1,4,5-triphosphate, leading to the activation of protein kinase C and the mobilization of intracellular Ca(2+). In this study, we shown that G-protein-activated PLC enzymes are the potential targets of cGMP-dependent protein kinases (PKG). PKG can directly phosphorylate PLC-beta2 and PLC-beta3 in vitro with purified proteins and in vivo with metabolic labeling. Phosphorylation of PLC-beta leads to the inhibition of G-protein-activated PLC-beta3 activity by 50-70% in COS-7 cell transfection assays. By using phosphopeptide mapping and site-directed mutagenesis, we further identified two key phosphorylation sites for the regulation of PLC-beta3 by PKG (Ser(26) and Ser(1105)). Mutation at these two sites (S26A and S1105A) of PLC-beta3 completely blocked the phosphorylation of PLC-beta3 protein catalyzed by PKG. Furthermore, mutation of these serine residues removed the inhibitory effect of PKG on the activation of the mutant PLC-beta3 proteins by G-protein subunits. Our results suggest a molecular mechanism for the regulation of G-protein-mediated intracellular [Ca(2+)] by the NO-cGMP-dependent signaling pathway.
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Affiliation(s)
- C Xia
- Department of Medical Biochemistry and Genetics, Center for Cancer Biology and Nutrition, Institute of Biosciences and Technology, Texas A & M University System Health Science Center, Houston, Texas 77030, USA
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D'Souza CA, Alspaugh JA, Yue C, Harashima T, Cox GM, Perfect JR, Heitman J. Cyclic AMP-dependent protein kinase controls virulence of the fungal pathogen Cryptococcus neoformans. Mol Cell Biol 2001; 21:3179-91. [PMID: 11287622 PMCID: PMC86952 DOI: 10.1128/mcb.21.9.3179-3191.2001] [Citation(s) in RCA: 261] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Cryptococcus neoformans is an opportunistic fungal pathogen that infects the human central nervous system. This pathogen elaborates two specialized virulence factors: the antioxidant melanin and an antiphagocytic immunosuppressive polysaccharide capsule. A signaling cascade controlling mating and virulence was identified. The PKA1 gene encoding the major cyclic AMP (cAMP)-dependent protein kinase catalytic subunit was identified and disrupted. pka1 mutant strains were sterile, failed to produce melanin or capsule, and were avirulent. The PKR1 gene encoding the protein kinase A (PKA) regulatory subunit was also identified and disrupted. pkr1 mutant strains overproduced capsule and were hypervirulent in animal models of cryptococcosis. pkr1 pka1 double mutant strains exhibited phenotypes similar to that of pka1 mutants, providing epistasis evidence that the Pka1 catalytic subunit functions downstream of the Pkr1 regulatory subunit. The PKA pathway was also shown to function downstream of the Galpha protein Gpa1 and to regulate cAMP production by feedback inhibition. These findings define a Galpha protein-cAMP-PKA signaling pathway regulating differentiation and virulence of a human fungal pathogen.
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Affiliation(s)
- C A D'Souza
- Departments of Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA
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Yue C, Sanborn BM. KN-93 inhibition of G protein signaling is independent of the ability of Ca2+/calmodulin-dependent protein kinase II to phosphorylate phospholipase Cbeta3 on 537-Ser. Mol Cell Endocrinol 2001; 175:149-56. [PMID: 11325525 DOI: 10.1016/s0303-7207(01)00383-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Stimulation of the phospholipase Cbeta (PLC) signaling pathway results in intracellular Ca2+ release and subsequent activation of calmodulin (CaM) and CaM kinase II (CaMK II). KN-93, an inhibitor of CaMK II, reduced the stimulation of phosphatidylinositide (PI) turnover by Galphai-coupled (formyl-Met-Leu-Phe, fMLP) or Galphaq-coupled [M1 muscarinic and oxytocin (OT)] receptors. The inhibitory effect of KN-93 was also observed when PLCbeta3 was stimulated directly by Galphaq or Gbetagamma in overexpression assays. CaMK II phosphorylated PLCbeta3 but not PLCbeta1 in vitro. Phosphorylation occurred exclusively on 537Ser in the X-Y linker region of PLCbeta3. 537Ser was also phosphorylated in the basal state in cells and phosphorylation was enhanced by ionomycin treatment. However, mutation of 537Ser to Glu had no effect on inhibition of Galphaq or Gbetagamma-stimulated PLCbeta3 activity by KN-93. KN-93 also inhibited Galphaq -stimulated PLCbeta1 activity, even though this enzyme is not a substrate for CaMK II. These data indicate that phosphorylation of PLCbeta3 by CaMK II is not directly involved in the inhibitory effect of KN-93 on phosphatidylinositide turnover.
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Affiliation(s)
- C Yue
- Department of Biochemistry and Molecular Biology, University of Texas Houston Medical School, PO Box 20708, Houston, TX 77225, USA
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Yue C. [The administration of military households and their disputes over military service in the Jiangxi guards and battalions during the Ming and Qing periods]. Bull Inst Mod Hist Acad Sin 2001; 72:833-887. [PMID: 20043358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
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Abstract
Activation of protein kinase C (PKC) can result from stimulation of the receptor-G protein-phospholipase C (PLCbeta) pathway. In turn, phosphorylation of PLCbeta by PKC may play a role in the regulation of receptor-mediated phosphatidylinositide (PI) turnover and intracellular Ca(2+) release. Activation of endogenous PKC by phorbol 12-myristate 13-acetate inhibited both Galpha(q)-coupled (oxytocin and M1 muscarinic) and Galpha(i)-coupled (formyl-Met-Leu-Phe) receptor-stimulated PI turnover by 50-100% in PHM1, HeLa, COSM6, and RBL-2H3 cells expressing PLCbeta(3). Activation of conventional PKCs with thymeleatoxin similarly inhibited oxytocin or formyl-Met-Leu-Phe receptor-stimulated PI turnover. The PKC inhibitory effect was also observed when PLCbeta(3) was stimulated directly by Galpha(q) or Gbetagamma in overexpression assays. PKC phosphorylated PLCbeta(3) at the same predominant site in vivo and in vitro. Peptide sequencing of in vitro phosphorylated recombinant PLCbeta(3) and site-directed mutagenesis identified Ser(1105) as the predominant phosphorylation site. Ser(1105) is also phosphorylated by protein kinase A (PKA; Yue, C., Dodge, K. L., Weber, G., and Sanborn, B. M. (1998) J. Biol. Chem. 273, 18023-18027). Similar to PKA, the inhibition by PKC of Galpha(q)-stimulated PLCbeta(3) activity was completely abolished by mutation of Ser(1105) to Ala. In contrast, mutation of Ser(1105) or Ser(26), another putative phosphorylation target, to Ala had no effect on inhibition of Gbetagamma-stimulated PLCbeta(3) activity by PKC or PKA. These data indicate that PKC and PKA act similarly in that they inhibit Galpha(q)-stimulated PLCbeta(3) as a result of phosphorylation of Ser(1105). Moreover, PKC and PKA both inhibit Gbetagamma-stimulated activity by mechanisms that do not involve Ser(1105).
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Affiliation(s)
- C Yue
- Department of Biochemistry and Molecular Biology, University of Texas Medical School, Houston, Texas 77225, USA
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Zhang X, Qu F, Yue C, Yang X, Hong S, Xu G. [Expression of multidrug resistance gene and its reversion by cyclosporine in non-small cell lung cancer]. Zhongguo Fei Ai Za Zhi 2000; 3:170-4. [PMID: 20950543 DOI: 10.3779/j.issn.1009-3419.2000.03.03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND To investigate relation between the multidrug resistance gene (MDR1) expression and chemotherapeutic response for non-small cell lung cancer (NSCLC) and to evaluate the effect of cyclosporine (CsA) on reversion of MDR1. METHODS Cancer tissue specimens and peripheral blood samples were collected from 46 patients with NSCLC. MDR1 was amplified in total RNA extracted from cancer cell specimens and peripheral blood lymphocyte (PBL) by RT-PCR assay. According to the result of detection , some MDR1-positive patients were treated with CsA and anticancer drugs (reverse group) , other MDR1-positive patients (positive control group) and MDR1-negative patients (negative control group) were treated with anticancer drugs alone. RESULTS The MDR1 positive rate of cancer cells was 65. 2 %(30/ 46) , and of PBL was 58. 7 %(27/ 46) ; twenty-four cases were MDR1-positive both in cancer cells and PBL. The positive rate of patients with recurrence was 81. 3 %(26/ 32) ; of untreated patients was 28. 6 %(4/ 14) ; of patients with multi-cycle chemotherapy was 85. 7 %(24/ 28) ; of patients with non-chemotherapy was 33. 3 %(6/ 18) . The differences were significant ( P < 0. 01) . The response rate was 46. 7 %(7/ 15) in reverse group and 20 %(3/ 15) in positive control group and 37. 5 %(6/ 16) in negative control group. There were no significant differences in the toxicities and immunity changes except for hematological toxicity and impaired liver function between reverse group and other groups. CONCLUSIONS RT-PCR examination of MDR1 expression is useful for predicting response to chemotherapy and prognosis in NSCLC patients. MDR1-positive is associated with poor prognosis. The reverse effect of CsA for expression of MDR1 requires further clinical study.
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Affiliation(s)
- X Zhang
- Cancer Research And Treatment Center , Shandong Province Hospital , Jinan , Shandong 250021 , P. R. China
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Yue C, Liu Z, Zeng X, Shao Z, Yu Z. [Expression and insecticidal characteristics of cry3A in Lepidoptera-specific Bacillus thuringiensis]. Wei Sheng Wu Xue Bao 2000; 40:139-42. [PMID: 12548935] [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: 02/28/2023]
Abstract
The cry3A gene coding Coleoptera-specific protein was transformed into a wild strain YBT803-1 by electroporation, A transformant BMBY-001 was obtained. SDS-PAGE analysis demonstrated that cry3A could express 64 kD protein in BMBY-001. However, the expression of cry1Ab and cry1Ac were effected. Bioassay showed that BMBY-001 was not only highly toxic to Phyllodecta vulgatissima larva(LC50 0.413 microL/mL) but also toxic to Plutella xylostella(LC50 3.319 microL/mL).
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Affiliation(s)
- C Yue
- Department of Microbial Science and Technology, Huazhong Agricultural University, Wuhan 430070
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Yue C, Cavallo LM, Alspaugh JA, Wang P, Cox GM, Perfect JR, Heitman J. The STE12alpha homolog is required for haploid filamentation but largely dispensable for mating and virulence in Cryptococcus neoformans. Genetics 1999; 153:1601-15. [PMID: 10581270 PMCID: PMC1460866 DOI: 10.1093/genetics/153.4.1601] [Citation(s) in RCA: 115] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Cryptococcus neoformans is a fungal pathogen that causes meningitis in immunocompromised hosts. The organism has a known sexual cycle, and strains of the MATalpha mating type are more virulent than isogenic MATa strains in mice, and they are more common in the environment and infected hosts. A C. neoformans homolog of the STE12 transcription factor that regulates mating, filamentation, and virulence in Saccharomyces cerevisiae and Candida albicans was identified previously, found to be encoded by a novel region of the MATalpha mating type locus, and shown to enhance filamentous growth when overexpressed. We have disrupted the C. neoformans STE12 gene in a pathogenic serotype A isolate. ste12 mutant strains exhibit a severe defect in filamentation and sporulation (haploid fruiting) in response to nitrogen starvation. In contrast, ste12 mutant strains have only modest mating defects and are fully virulent in two animal models compared to the STE12 wild-type strain. In genetic epistasis experiments, STE12 functions in a MAP kinase cascade to regulate fruiting, but not mating. Thus, the C. neoformans STE12alpha transcription factor homolog plays a specialized function in haploid fruiting, but it is dispensable or redundant for mating and virulence. The association of the MATalpha locus with virulence may involve additional genes, and other transcription factors that regulate mating and virulence remain to be identified.
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Affiliation(s)
- C Yue
- Department of Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA
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Dodge KL, Carr DW, Yue C, Sanborn BM. A role for AKAP (A kinase anchoring protein) scaffolding in the loss of a cyclic adenosine 3',5'-monophosphate inhibitory response in late pregnant rat myometrium. Mol Endocrinol 1999; 13:1977-87. [PMID: 10598575 DOI: 10.1210/mend.13.12.0378] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
During pregnancy in the rat, there is a change in the ability of chlorophenylthio (CPT)-cAMP to inhibit myometrial phosphatidylinositide turnover. This is accompanied by a change in the association of proteins with a plasma membrane A kinase anchoring protein (AKAP). Both CPT-cAMP and isoproterenol inhibited oxytocin-stimulated phosphatidylinositide turnover on days 12 through 20 of gestation, whereas neither agent had an effect on day 21. Accompanying this change was a dramatic decrease in the concentration and activity of cAMP-dependent protein kinase [protein kinase A (PKA)] and an increase in the concentration of protein phosphatase 2B (PP2B) in plasma membranes from day 21 compared with day 19 pregnant rats. In contrast, both PKA and PP2B concentrations and activities increased in total myometrial homogenates. Both PKA and PP2B coimmunoprecipitated with an antibody against the 150-kDa AKAP found in rat myometrial plasma membranes. More PKA was associated with AKAP150 on day 19 than on day 21, while the reverse was true for PP2B. Disruption of PKA/AKAP association in day 19 pregnant rat myometrial cells with the specific interaction inhibitor peptide S-Ht31 resulted in the loss of the cAMP-inhibitory effect on phosphatidylinositide turnover. PP2B activity in myometrial homogenates dephosphorylated PLCbeta3, a PKA substrate targeted in the inhibition of Galphaq-stimulated phosphatidylinositide turnover. The dramatic loss of the cAMP-inhibitory effect on day 21 of pregnancy may alter the balance between uterine contraction and relaxation near parturition. The changes in the relative concentrations of PKA and PP2B associated with AKAP150 are consistent with a functional role for AKAP150 scaffolding in the alteration of cellular signaling.
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Affiliation(s)
- K L Dodge
- Department of Biochemistry and Molecular Biology, University of Texas Medical School at Houston, 77030, USA
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