54 results on '"Fengyi ZHAO"'
Search Results
2. Polyphenols from Prunus mume: extraction, purification, and anticancer activity
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Fengyi Zhao, Lanlan Du, Jialuan Wang, Hongxia Liu, Huifang Zhao, Lianfei Lyu, Weifan Wang, Wenlong Wu, and Weilin Li
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General Medicine ,Food Science - Abstract
Prunus mume is an ancient medicinal herb and food that are commonly used in Asian countries with high nutritional ingredients and biological activities.
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- 2023
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3. Correction: The effects of a low carbohydrate diet combined with partial meal replacement on obese individuals
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Yulian Zhong, Ximin Chen, Chao Huang, Yuexiao Chen, Fengyi Zhao, Runhua Hao, Niannian Wang, Wang Liao, Hui Xia, Ligang Yang, Shaokang Wang, and Guiju Sun
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Nutrition and Dietetics ,Endocrinology, Diabetes and Metabolism ,Medicine (miscellaneous) - Published
- 2023
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4. Synergizing Electron and Heat Flows in Photocatalyst for Direct Conversion of Captured CO 2
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Chungseok Choi, Fengyi Zhao, James L Hart, Yuanzuo Gao, Fabian Menges, Conor L. Rooney, Nia J. Harmon, Bo Shang, Zihao Xu, Sa Suo, Quynh Sam, Judy J. Cha, Tianquan Lian, and Hailiang Wang
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General Chemistry ,General Medicine ,Catalysis - Published
- 2023
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5. Monolayer Molecular Functionalization Enabled by Acid–Base Interaction for High-Performance Photochemical CO2 Reduction
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Bo Shang, Fengyi Zhao, Chungseok Choi, Xiaofan Jia, Magnus Pauly, Yueshen Wu, Zixu Tao, Yiren Zhong, Nia Harmon, Paul A. Maggard, Tianquan Lian, Nilay Hazari, and Hailiang Wang
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Fuel Technology ,Renewable Energy, Sustainability and the Environment ,Chemistry (miscellaneous) ,Materials Chemistry ,Energy Engineering and Power Technology - Published
- 2022
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6. Homoleptic Al(III) Photosensitizers for Durable CO
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Jia-Wei, Wang, Fan, Ma, Tao, Jin, Piao, He, Zhi-Mei, Luo, Stephan, Kupfer, Michael, Karnahl, Fengyi, Zhao, Zihao, Xu, Tianquan, Lian, Yong-Liang, Huang, Long, Jiang, Li-Zhi, Fu, Gangfeng, Ouyang, and Xiao-Yi, Yi
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Exploiting noble-metal-free systems for high-performance photocatalytic CO
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- 2022
7. Nanoscale TiO2 Protection Layer Enhances the Built-In Field and Charge Separation Performance of GaP Photoelectrodes
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Yawei Liu, Djamaladdin G. Musaev, Stephen B. Cronin, Matthew Mecklenburg, Fengyi Zhao, Zhi Cai, Bingya Hou, Haotian Shi, Craig L. Hill, Tianquan Lian, and Zihao Xu
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Materials science ,business.industry ,Mechanical Engineering ,Oxide ,Bioengineering ,General Chemistry ,Condensed Matter Physics ,Microsecond ,chemistry.chemical_compound ,Semiconductor ,Depletion region ,chemistry ,Electrode ,Optoelectronics ,General Materials Science ,Charge carrier ,business ,Nanoscopic scale ,Layer (electronics) - Abstract
Nanoscale oxide layer protected semiconductor photoelectrodes show enhanced stability and performance for solar fuels generation, although the mechanism for the performance enhancement remains unclear due to a lack of understanding of the microscopic interfacial field and its effects. Here, we directly probe the interfacial fields at p-GaP electrodes protected by n-TiO2 and its effect on charge carriers by transient reflectance spectroscopy. Increasing the TiO2 layer thickness from 0 to 35 nm increases the field in the GaP depletion region, enhancing the rate and efficiency of interfacial electron transfer from the GaP to TiO2 on the ps time scale as well as retarding interfacial recombination on the microsecond time scale. This study demonstrates a general method for providing a microscopic view of the photogenerated charge carrier's pathway and loss mechanisms from the bulk of the electrode to the long-lived separated charge at the interface that ultimately drives the photoelectrochemical reactions.
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- 2021
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8. Discovery of Genetic Biomarkers for Alzheimer’s Disease Using Adaptive Convolutional Neural Networks Ensemble and Genome-Wide Association Studies
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Longfei Jia, Zeng An, Huabin Rong, Yiqun Zhang, Alzheimer’s Disease Neuroimaging Initiative, Shaoliang Peng, Dan Pan, and Fengyi Zhao
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Ensemble forecasting ,business.industry ,Computer science ,Deep learning ,Health Informatics ,Genome-wide association study ,Pattern recognition ,Convolutional neural network ,Ensemble learning ,General Biochemistry, Genetics and Molecular Biology ,Computer Science Applications ,Neuroimaging ,Discriminative model ,Classifier (linguistics) ,Artificial intelligence ,business - Abstract
To identify candidate neuroimaging and genetic biomarkers for Alzheimer’s disease (AD) and other brain disorders, especially for little-investigated brain diseases, we advocate a data-driven approach which incorporates an adaptive classifier ensemble model acquired by integrating Convolutional Neural Network (CNN) and Ensemble Learning (EL) with Genetic Algorithm (GA), i.e., the CNN-EL-GA method, into Genome-Wide Association Studies (GWAS). Above all, a large number of CNN models as base classifiers were trained using coronal, sagittal, or transverse magnetic resonance imaging slices, respectively, and the CNN models with strong discriminability were then selected to build a single classifier ensemble with the GA for classifying AD, with the help of the CNN-EL-GA method. While the acquired classifier ensemble exhibited the highest generalization capability, the points of intersection were determined with the most discriminative coronal, sagittal, and transverse slices. Finally, we conducted GWAS on the genotype data and the phenotypes, i.e., the gray matter volumes of the top ten most discriminative brain regions, which contained the ten most points of intersection. Six genes of PCDH11X/Y, TPTE2, LOC107985902, MUC16 and LINC01621 as well as Single-Nucleotide Polymorphisms, e.g., rs36088804, rs34640393, rs2451078, rs10496214, rs17016520, rs2591597, rs9352767 and rs5941380, were identified. This approach overcomes the limitations associated with the impact of subjective factors and dependence on prior knowledge while adaptively achieving more robust and effective candidate biomarkers in a data-driven way. The approach is promising to facilitate discovering effective candidate genetic biomarkers for brain disorders, as well as to help improve the effectiveness of identified candidate neuroimaging biomarkers for brain diseases.
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- 2021
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9. Automated piglet tracking using a single convolutional neural network
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Mingqiang Ou, Gan Haiming, Yueju Xue, Fengyi Zhao, Shimei Li, Chengguo Xu, and Chen Changxin
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Computer science ,business.industry ,Feature vector ,010401 analytical chemistry ,Soil Science ,Pattern recognition ,04 agricultural and veterinary sciences ,Frame rate ,Tracking (particle physics) ,01 natural sciences ,Convolutional neural network ,0104 chemical sciences ,Control and Systems Engineering ,Hungarian algorithm ,Feature (computer vision) ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,sort ,Artificial intelligence ,State (computer science) ,business ,Agronomy and Crop Science ,Food Science - Abstract
Piglet tracking is critical to automated piglet behaviour and welfare analysis. Following the tracking-by-detection paradigm, we have developed an online piglet tracking network (OPTN) composed of a base network, a detection head and an association head. The unweaned piglets in video images were detected at the region-based detection head, and the piglet central locations were mapped onto the feature maps produced by the base network and extended network to form central feature vectors. Then the exhaustive central feature vector permutations were input to the affinity estimation network to generate an affinity matrix that accounted for the affinity between the video image pair detections. To make full use of the tracking history, we used the Hungarian algorithm to optimise affinity prediction with affinity accumulation and designed a distance-based tracking state adjustment strategy to correct false state prediction and recovered lost IDs. Our method achieved favourable tracking performance with an IDF1 score and MOTA of 96.55% and 97.04%, respectively, and an inference frame rate of 6.89 fps. Our method outperformed popular MOT methods, such as SORT, SST and CenterTrack, in short video clips and a long video episode. OPTN was robust against large illumination variations with a video rate as low as 1 fps. Our computer vision-based piglet tracking method may aid animal tracking-related behaviour analysis as well as piglet surveillance.
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- 2021
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10. Effect of Chromium Supplementation on Blood Glucose and Lipid Levels in Patients with Type 2 Diabetes Mellitus: a Systematic Review and Meta-analysis
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Guiju Sun, Shaokang Wang, Niannian Wang, Hui Xia, Hong Zhang, Da Pan, and Fengyi Zhao
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Blood Glucose ,Chromium ,medicine.medical_specialty ,Endocrinology, Diabetes and Metabolism ,Clinical Biochemistry ,Blood lipids ,Type 2 diabetes ,010501 environmental sciences ,01 natural sciences ,Biochemistry ,Gastroenterology ,law.invention ,Inorganic Chemistry ,03 medical and health sciences ,chemistry.chemical_compound ,Randomized controlled trial ,law ,Internal medicine ,Diabetes mellitus ,Humans ,Medicine ,Randomized Controlled Trials as Topic ,0105 earth and related environmental sciences ,Glycated Hemoglobin ,0303 health sciences ,medicine.diagnostic_test ,Triglyceride ,business.industry ,030302 biochemistry & molecular biology ,Biochemistry (medical) ,Type 2 Diabetes Mellitus ,General Medicine ,medicine.disease ,Lipids ,Diabetes Mellitus, Type 2 ,chemistry ,Dietary Supplements ,Glycated hemoglobin ,business ,Lipid profile - Abstract
In recent years, the prevalence and incidence of diabetes mellitus (DM) have increased sharply worldwide. In order to evaluate the effect of chromium supplementation on patients with type 2 diabetes, a meta-analysis was conducted by searching the relevant literature. Randomized controlled trials on the effects of chromium supplements on glucose metabolism or lipid profile in patients with type 2 diabetes were retrieved from multiple databases. Literature screening, quality evaluation, and data extraction were conducted according to the inclusion and exclusion criteria, and Review Manager 5.4.0 was used for data analysis. A total of 10 randomized controlled trials involving 509 patients were included, including 269 cases in the experimental group and 240 cases in the placebo control group. Statistical analysis was conducted on the glycosylated hemoglobin (HbA1c), fasting plasma glucose (FPG), triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) to evaluate the blood glucose and lipid levels. Meta-analysis results showed that the differences between the experimental group and the control group in only one indicator of HbA1c were statistically significant, while there were no statistically significant differences in other indicators. The use of chromium supplements can reduce the glycosylated hemoglobin of type 2 diabetic patients to a certain extent, but it cannot effectively improve the fasting blood glucose and blood lipid levels of type 2 diabetic patients.
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- 2021
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11. R‐CHOP immunochemotherapy plus surgery is associated with a superior prognosis in Chinese primary intestinal diffuse large B‐cell lymphoma
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Shengyu Zhou, Liqiang Zhou, Jianliang Yang, Haizeng Zhang, Qiaofeng Zhong, Fengyi Zhao, Xiaohui He, Peng Liu, Yuankai Shi, Xin Wang, Shiyu Jiang, Yu Zhou, Lin Gui, and Yan Qin
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Adult ,Male ,China ,medicine.medical_specialty ,Adolescent ,Population ,Young Adult ,03 medical and health sciences ,0302 clinical medicine ,Risk Factors ,Antineoplastic Combined Chemotherapy Protocols ,medicine ,Humans ,030212 general & internal medicine ,Stage (cooking) ,education ,Cyclophosphamide ,Survival analysis ,Aged ,Retrospective Studies ,Aged, 80 and over ,education.field_of_study ,Univariate analysis ,business.industry ,Cancer ,Retrospective cohort study ,General Medicine ,Middle Aged ,Prognosis ,medicine.disease ,Survival Analysis ,Lymphoma ,Surgery ,Oncology ,Doxorubicin ,Vincristine ,030220 oncology & carcinogenesis ,Prednisone ,Female ,Immunotherapy ,Lymphoma, Large B-Cell, Diffuse ,Rituximab ,business ,Diffuse large B-cell lymphoma - Abstract
Aim The aim of the study was to compare the therapeutic strategies and prognostic factors of patients with primary intestinal diffuse large B-cell lymphoma (PI-DLBCL). Methods A total of 50 PI-DLBCL patients who accepted standard first-line treatment at National Cancer Center in China were included in this retrospective study. Survival analysis was performed to evaluate the prognostic risk factors. Results The 3-year overall survival (OS) and 3-year progression-free survival (PFS) for the entire group were 76.0% and 65.9%, respectively. Univariate analysis showed that B symptom, advanced Lugano stage, elevated LDH status, poor ECOG PS and immunochemotherapy alone were significantly correlated with a poor PFS. Elevated LDH status, poor ECOG PS, advanced Lugano stage, high IPI score and immunochemotherapy alone were significantly correlated with a poor OS. Multivariate analysis revealed that ECOG PS (P= 0.035; HR = 0.233; 95% CI, 0.060-0.905), LDH level (P = 0.010; HR = 0.223; 95% CI, 0.072-0.693) and surgery (P = 0.002; HR = 5.584; 95% CI, 1.883-16.563) were independent prognostic factors for OS. LDH level (P = 0.035; HR = 0.210; 95% CI, 0.049-0.894) and surgery (P = 0.003; HR = 6.410; 95% CI, 1.903-21.593) were independent risk factors for PFS in PI-DLBCL. R-CHOP immunochemotherapy combined surgery treatment was also associated with a lower rate of refractory/relapsed (R/R) disease (P = 0.004). Furthermore, stratified analysis revealed that partial resection or radical resection combined with immunochemotherapy had no significantly difference which affect OS (P = 0.338) and PFS (P = 0.207). Conclusion R-CHOP immunochemotherapy plus surgery was associated with a superior prognosis compared with R-CHOP alone in Chinese PI-DLBCL population.
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- 2020
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12. Research on Anthocyanins from Rubus 'Shuofeng' as Potential Antiproliferative and Apoptosis-Inducing Agents
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Fengyi Zhao, Huifang Zhao, Wenlong Wu, Weifan Wang, and Weilin Li
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Health (social science) ,Plant Science ,Health Professions (miscellaneous) ,Microbiology ,blackberry ,anthocyanin ,antiproliferative activity ,apoptosis ,DNA binding ,Food Science - Abstract
Blackberries have high nutritional value and strong biological activities, such as antiproliferative activity. Anthocyanins are important functional components in blackberries. We collected 25 kinds (lines) of blackberries from our nursery to investigate antiproliferative agents in natural foods. Among them, the Shuofeng variety had the highest anthocyanin content, with 2.54 mg/g of fresh fruit, which increased to 357.75 mg/g of dried powder through ultrasound-assisted solvent extraction and macroporous resin adsorption. Additional experiments showed that Shuofeng’s anthocyanin content had high anti-HepG2 activity in vitro and in vivo, as well as activity against Hela (68.62 μg/mL), HepG2 (55.85 μg/mL), MCF-7 (181.21 μg/mL), and A549 cells (82.01 μg/mL), as determined by MTT assay. It also had no apparent toxic effects. The combination of DDP and DOX significantly enhanced the antiproliferative activity of the four cell lines. The IC50 value of Shuofeng’s anthocyanin content combined with DOX in HepG2 cells was the lowest at only 0.08 μg/mL, indicating that the combination of drugs had additive and synergistic effects. Shuofeng’s anthocyanin content might intercalate into DNA and alter or destroy DNA, causing apoptosis and inhibiting cell proliferation. Our results show that blackberry anthocyanins can inhibit the proliferation of cancer cells and their possible mechanisms. However, we must study the deeper mechanism and explore its targeting effects in the future.
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- 2023
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13. Parental, Teacher and Peer Effects on the Social Behaviors of Chinese Adolescents: A Structural Equation Modeling Analysis
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Chao Huang, Cheng Li, Fengyi Zhao, Jing Zhu, Shaokang Wang, Jin Yang, and Guiju Sun
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behavior development ,parent ,adolescent ,General Neuroscience ,teacher ,peer - Abstract
Adolescent behavior is closely related to academic and long-term personal development, and adolescents are vulnerable to the influences from people around them. This study aimed to analyze the factors and mechanisms that influence the behavior of adolescents. It examines the impact of family, teachers, and peers on adolescent prosocial behavior and misconduct. Data were obtained from the China Education Panel Survey (CEPS) follow-up data (2014–2015 school year) and 7835 middle school student participants were used for analysis. Structural equation modeling (SEM) was used to explore the influence and mechanisms of family, teachers, and peers on the development of adolescent social behavior. The findings showed that parental relationships, parental discipline, teacher supervision, and positive peer behavior were positively associated with adolescent prosocial behaviors and reduced the incidence of delinquent behaviors, while frequent home–school contact was associated with misconduct (all p < 0.01). These results remained significant after controlling for gender, residence, only-child status, family financial situation, and paternal education. Significant others in an adolescent’s life play multiple essential roles in forming and developing adolescent behavior and in directly influencing them. To guide the prosocial behaviors of middle school students and reduce delinquent behavior, we should build harmonious parent—child, peer, and teacher–student relationships, teach according to their aptitudes, pay attention to particular groups and strengthen psychological health education to develop their self-esteem and self-confidence.
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- 2023
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14. Surface-State-Controlled Fluence-Dependent Apce Behavior of p-GaAs-TiO2-Pt Water Reduction Photocathode
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Sa Suo, Fengyi Zhao, Zihao Xu, Haotian Shi, Zhi Cai, Bofan Zhao, Craig L Hill, Djamaladdin G Musaev, and Tianquan Lian
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The demand for reform in energy production and reduction in carbon dioxide emission lays emphasis on the development and mechanistic study of photocatalytic water splitting photoelectrodes. Understanding the bottlenecks of the photoelectrochemical (PEC) conversion efficiency in photocatalytic water splitting systems is essential to impart guidance to material selection and photoelectrode design. Absorbed photon-to-current conversion efficiency (APCE), which represents the fraction of absorbed photons converted into electrons in photocurrents, is the key metric in the evaluation of PEC performance. A large portion of studies have reported an illumination fluence-independent APCE under continuous wave (CW) illumination with power densities around 10~100 mW/cm2, whereas few cases have reported the fluence-dependent APCE performance. In the present work, we observe a rarely reported fluence-dependent APCE performance in the p-GaAs/5 nm TiO2/2 nm Pt photocathode under a low-excitation intensity regime. The APCE reaches close to unity at 0.005 mW/cm2 and gradually decreases to 60% at 1 mW/cm2. However, a theoretical explanation for this fluence-dependent APCE reduction is not established. We develop a steady-state kinetic model with the least parameters to decipher such a phenomenon. In this model, the surface electrons in the GaAs/TiO2/Pt photocathode are consumed by three pathways: 1) transferred to redox active species in solution via the conduction band, 2) trapped into surface states that serve as the reaction sites, which competes with the electron-hole recombination at such surface states, and 3) directly recombining with the surface holes. The APCE decrease at higher illumination intensity is attributed to the increasing recombination between the GaAs holes and the TiO2 electrons caused by the saturation of surface sites. A detailed parametric survey shows that the interfacial electron transfer rate, ks, from the trap states to solution redox species is the only parameter that tunes the extent of the APCE reduction. With higher ks, APCE displays a smaller reduction in response to increasing fluences. Thus, the fluence-dependent feature of the APCE is an indicator that the surface reaction is the efficiency-determining step. Through this work, we establish a kinetic model for the semiconductor photoelectrode with catalyst layer and successfully explain the cause to the fluence-dependent APCE performance. These significant findings can be universally applied to address the function of catalytic layer (nanoparticle or molecular) and surface modifier in hybrid photoelectrode systems that exhibit fluence-dependent APCE.
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- 2022
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15. Direct in Situ Observation of Surface Charge Accumulation Under Water Oxidation Conditions By Electric Field Induced Second Harmonic Generation Measurements
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Fengyi Zhao, Tianquan Lian, Zihao Xu, Sa Suo, Craig L Hill, and Djamaladdin G Musaev
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The water oxidation reaction is considered as the bottleneck and rate-determining step in photoelectrochemical water-splitting processes. To achieve efficient water oxidation on the photoanode, sufficient built-in potential on semiconductors under light illumination needs to be maintained. Herein, we introduced the in-situ Electric Field Induced Second Harmonic Generation (EFISH) technique to probe the change of built-in potential under the water oxidation reaction process of a single-crystal rutile TiO2 photoanode. Under the dark condition, parabolic relation between the second harmonic generation signal and applied potential is observed in TiO2 depletion region. Under UV illumination, the EFISH signal decreased compared to dark at the photocurrent saturation potential region. Change in the signal is attributed to the decrease of built-in potential in TiO2. The amount of built-in potential change increased with light illumination and saturated at 520 mV under 15mW/cm2 360 nm UV illumination in an unbuffered solution. This light-induced band edge unpinning effect can be explained by the accumulation of holes at surface states and surface protons at Helmholtz layer that are generated under illumination. Kinetic isotope EFISH experiments suggest that proton-coupled electron transfer (PCET) is the rate-determining step in water oxidation process. Screening of built-in potential under illumination can be mitigated by adding buffer ions, suggesting that the rate-determining step can be altered by changing the solution microenvironment.
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- 2022
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16. Nanoscale TiO
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Zihao, Xu, Bingya, Hou, Fengyi, Zhao, Zhi, Cai, Haotian, Shi, Yawei, Liu, Craig L, Hill, Djamaladdin G, Musaev, Matthew, Mecklenburg, Stephen B, Cronin, and Tianquan, Lian
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Titanium ,Sunlight ,Oxides ,Electrodes - Abstract
Nanoscale oxide layer protected semiconductor photoelectrodes show enhanced stability and performance for solar fuels generation, although the mechanism for the performance enhancement remains unclear due to a lack of understanding of the microscopic interfacial field and its effects. Here, we directly probe the interfacial fields at p-GaP electrodes protected by n-TiO
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- 2021
17. Enhanced mTOR complex 1 signaling attenuates diabetic cardiac injury in OVE26 mice
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Satoru Kobayashi, Fengyi Zhao, Xianmin Xu, Qiangrong Liang, Yuan Huang, Weinian Shou, and Derek Timm
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0301 basic medicine ,Cardiac function curve ,Diabetic Cardiomyopathies ,Mice, Transgenic ,Mechanistic Target of Rapamycin Complex 2 ,mTORC1 ,Mechanistic Target of Rapamycin Complex 1 ,medicine.disease_cause ,Biochemistry ,mTORC2 ,Diabetes Mellitus, Experimental ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Genetics ,Animals ,Medicine ,Molecular Biology ,Mechanistic target of rapamycin ,PI3K/AKT/mTOR pathway ,biology ,business.industry ,Autophagy ,medicine.disease ,Diabetes Mellitus, Type 1 ,030104 developmental biology ,Heart failure ,Cancer research ,biology.protein ,biological phenomena, cell phenomena, and immunity ,business ,030217 neurology & neurosurgery ,Oxidative stress ,Signal Transduction ,Biotechnology - Abstract
The protein kinase mechanistic target of rapamycin (mTOR) performs diverse cellular functions through 2 distinct multiprotein complexes, mTOR complex (mTORC)1 and 2. Numerous studies using rapamycin, an mTORC1 inhibitor, have implicated a role for mTORC1 in several types of heart disease. People with diabetes are more susceptible to heart failure. mTORC1 activity is increased in the diabetic heart, but its functional significance remains controversial. To investigate the role of mTORC1 in the diabetic heart, we crossed OVE26 type 1 diabetic mice with transgenic mice expressing a constitutively active mTOR (mTORca) or kinase-dead mTOR (mTORkd) in the heart. The expression of mTORca or mTORkd affected only mTORC1 but not mTORC2 activities, with corresponding changes in the activities of autophagy, a cellular degradation pathway negatively regulated by mTORC1. Diabetic cardiac damage in OVE26 mice was dramatically reduced by mTORca but exacerbated by mTORkd expression as assessed by changes in cardiac function, oxidative stress, and myocyte apoptosis. These findings demonstrated that the enhanced mTORC1 signaling in the OVE26 diabetic heart was an adaptive response that limited cardiac dysfunction, suggesting that manipulations that enhance mTORC1 activity may reduce diabetic cardiac injury, in sharp contrast to the results previously obtained with rapamycin.-Xu, X., Kobayashi, S., Timm, D., Huang, Y., Zhao, F., Shou, W., Liang, Q. Enhanced mTOR complex 1 signaling attenuates diabetic cardiac injury in OVE26 mice.
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- 2019
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18. Doxorubicin‐induced cardiomyocyte death is mediated by unchecked mitochondrial fission and mitophagy
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Yuan Huang, Hiromi Sesaki, Cairong Li, Fengyi Zhao, Qiangrong Liang, Amanda Kaminaris, Satoru Kobayashi, Michael P. Catanzaro, Tamayo Kobayashi, Fei Cai, and Ashley Weiner
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Dynamins ,Male ,0301 basic medicine ,Programmed cell death ,Ubiquitin-Protein Ligases ,Mitochondrial Degradation ,Mitochondrion ,Mitochondrial Size ,Mitochondrial Dynamics ,Biochemistry ,Parkin ,Cell Line ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Mitophagy ,polycyclic compounds ,Genetics ,Animals ,Humans ,Myocytes, Cardiac ,RNA, Small Interfering ,Molecular Biology ,Mice, Knockout ,Gene knockdown ,Cell Death ,Caspase 3 ,Chemistry ,Research ,Cardiotoxicity ,Mitochondria ,Rats ,Cell biology ,030104 developmental biology ,Doxorubicin ,Female ,Mitochondrial fission ,030217 neurology & neurosurgery ,Biotechnology - Abstract
Doxorubicin (Dox) is a widely used antineoplastic agent that can cause heart failure. Dox cardiotoxicity is closely associated with mitochondrial damage. Mitochondrial fission and mitophagy are quality control mechanisms that normally help maintain a pool of healthy mitochondria. However, unchecked mitochondrial fission and mitophagy may compromise the viability of cardiomyocytes, predisposing them to cell death. Here, we tested this possibility by using Dox-treated H9c2 cardiac myoblast cells expressing either the mitochondria-targeted fluorescent protein MitoDsRed or the novel dual-fluorescent mitophagy reporter mt-Rosella. Dox induced mitochondrial fragmentation as shown by reduced form factor, aspect ratio, and mean mitochondrial size. This effect was abolished by short interference RNA-mediated knockdown of dynamin-related protein 1 (DRP1), a major regulator of fission. Importantly, DRP1 knockdown decreased cell death as indicated by the reduced number of propidium iodide-positive cells and the cleavage of caspase-3 and poly (ADP-ribose) polymerase. Moreover, DRP1-deficient mice were protected from Dox-induced cardiac damage, strongly supporting a role for DRP1-dependent mitochondrial fragmentation in Dox cardiotoxicity. In addition, Dox accelerated mitophagy flux, which was attenuated by DRP1 knockdown, as assessed by the mitophagy reporter mt-Rosella, suggesting the necessity of mitochondrial fragmentation in Dox-induced mitophagy. Knockdown of parkin, a positive regulator of mitophagy, dramatically diminished Dox-induced cell death, whereas overexpression of parkin had the opposite effect. Together, these results suggested that Dox cardiotoxicity was mediated, at least in part, by the increased mitochondrial fragmentation and accelerated mitochondrial degradation by the lysosome. Strategies that limit mitochondrial fission and mitophagy in the physiologic range may help reduce Dox cardiotoxicity.-Catanzaro, M. P., Weiner, A., Kaminaris, A., Li, C., Cai, F., Zhao, F., Kobayashi, S., Kobayashi, T., Huang, Y., Sesaki, H., Liang, Q. Doxorubicin-induced cardiomyocyte death is mediated by unchecked mitochondrial fission and mitophagy.
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- 2019
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19. Dihydrotestosterone regulates oxidative stress and immunosuppressive cytokines in a female BALB/c mouse model of Graves’ disease
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Bingyin Shi, Yue Wang, Fengyi Zhao, Lingyu Bao, Fei Yang, Xiang Jiao, Yushi Sun, Pu Chen, Liping Wu, Qiangrong Liang, and Lianye Liu
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0301 basic medicine ,Thyroid Hormones ,endocrine system ,medicine.medical_specialty ,BALB/c Mouse ,medicine.drug_class ,Graves' disease ,Immunology ,Disease ,urologic and male genital diseases ,medicine.disease_cause ,Severity of Illness Index ,T-Lymphocytes, Regulatory ,Immunomodulation ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Internal medicine ,parasitic diseases ,medicine ,Animals ,Humans ,Immunology and Allergy ,Autoantibodies ,030203 arthritis & rheumatology ,Autoimmune disease ,Mice, Inbred BALB C ,business.industry ,Dihydrotestosterone ,Receptors, Thyrotropin ,Androgen ,medicine.disease ,Graves Disease ,Disease Models, Animal ,Oxidative Stress ,030104 developmental biology ,Endocrinology ,Cytokines ,Th17 Cells ,Female ,Reactive Oxygen Species ,business ,Oxidative stress ,medicine.drug - Abstract
Background: Graves’ disease (GD) is an autoimmune disease that affects more women than men. In our previous study, a potent bioactive androgen, 5α-dihydrotestosterone (DHT) showed a protective effe...
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- 2019
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20. The association between subclinical hypothyroidism and metabolic syndrome: an update meta-analysis of observational studies
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Zhao-Yi Peng, Yue Wang, Cuomu Deji, Fengyi Zhao, Chun-Ying Zhu, Xi Ding, Bingyin Shi, Liping Wu, and Yang Zhao
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Adult ,Male ,medicine.medical_specialty ,Adolescent ,Endocrinology, Diabetes and Metabolism ,Thyrotropin ,030209 endocrinology & metabolism ,Subgroup analysis ,03 medical and health sciences ,0302 clinical medicine ,Endocrinology ,Hypothyroidism ,Risk Factors ,Internal medicine ,Diabetes mellitus ,medicine ,Odds Ratio ,Humans ,Euthyroid ,Obesity ,Subclinical infection ,Hypertriglyceridemia ,Metabolic Syndrome ,business.industry ,Confounding ,medicine.disease ,Observational Studies as Topic ,030220 oncology & carcinogenesis ,Meta-analysis ,Hypertension ,Female ,Metabolic syndrome ,business - Abstract
The association between subclinical hypothyroidism (SCH) and metabolic syndrome (MetS) has been widely discussed. This study aimed to conduct an update and comprehensive meta-analysis to reveal the risk of MetS and its components in SCH. PubMed, Embase and ISI Web of Knowledge were searched to identify relevant studies through February 20th, 2020. Review Manager 5.3 and Stata 14.0 were used to conduct the meta-analysis. Both fixed-effects and random-effects models were used. In total, 18 articles (19 studies) incorporating 79,727 participants were included. The pooled OR for MetS comparing subjects with SCH with euthyroid subjects was 1.28 (95% CI: 1.19 to 1.39, p = 0.04, I2 = 40%). Subgroup analysis results showed significant associations of SCH and MetS in the adult subgroup (OR = 1.28, 95% CI: 1.18-1.40), Asian population subgroup (OR = 1.30, 95% CI: 1.19-1.42) and cross-sectional study design subgroup (OR = 1.31, 95% CI: 1.16-1.47). Significant associations of SCH and MetS also existed in all MetS definition criteria subgroups except the Chinese Diabetes Society (CDS) subgroup. SCH was correlated with MetS and was not affected by the subgroup analysis stratified by the proportion of females in the total population, the TSH cutoff value in SCH diagnostic criteria, or the adjustment for confounding factors. SCH was identified to be associated with an increased risk of obesity, hypertension, high triglyceride (TG) levels and low high-density lipoprotein cholesterol (HDL-C) levels. In conclusion, SCH is significantly associated with an increased risk of MetS and four out of five components of MetS.
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- 2021
21. The Design of a USB Interface Temperature and Humidity Detector
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Renyu He, Fengyi Zhao, and Junmin Hu
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Universal asynchronous receiver/transmitter ,Computer science ,Plug and play ,business.industry ,Firmware ,Interface (computing) ,Detector ,USB ,Complex programmable logic device ,computer.software_genre ,law.invention ,law ,business ,computer ,Computer hardware ,Data transmission - Abstract
This paper introduces the design of a USB interface temperature and humidity detector. System firmware is implemented by RTL logic based on CPLD, such as interface timing, data processing, communication and so on. USB to UART communication interface realizes the data transmission between the detector and the host computer. The detector is powered by USB, supporting plug and play. This new product design can solve the problems such as poor adaptability of traditional temperature and humidity detector and difficulty in feeding power supply, so as to meet the high requirements of reliability and convenience in industrial field. It has certain practical value and is worthy of promotion.
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- 2021
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22. Lower normal free thyroxine is associated with a higher risk of metabolic syndrome: a retrospective cohort on Chinese population
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Yi-Ming Liu, Fengyi Zhao, Meng Zhang, Mingqian He, Shiqian Hu, Yang Zhao, Rui Li, Ziyi Chen, Bingyin Shi, Chun-Ying Zhu, Yue Wang, Liping Wu, and Xi Ding
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Adult ,Male ,Retrospective cohort study ,China ,Thyroid Hormones ,endocrine system ,medicine.medical_specialty ,Lower normal free thyroxine ,Endocrinology, Diabetes and Metabolism ,lcsh:Diseases of the endocrine glands. Clinical endocrinology ,Cohort Studies ,Thyroid-stimulating hormone ,Risk Factors ,Thyroid stimulating hormone ,Internal medicine ,Humans ,Medicine ,Euthyroid ,Risk factor ,Aged ,Retrospective Studies ,lcsh:RC648-665 ,Triiodothyronine ,business.industry ,Hazard ratio ,General Medicine ,Middle Aged ,medicine.disease ,Metabolic syndrome ,Thyroxine ,Population Surveillance ,Cohort ,Female ,business ,hormones, hormone substitutes, and hormone antagonists ,Research Article ,Follow-Up Studies - Abstract
Background Recently, the relationship between thyroid hormones (THs) across the euthyroid ranges and metabolic syndrome (MetS) has been widely discussed. This study aimed to present specific cutoff values of THs to assess the association between THs and MetS in a euthyroid cohort. Methods Data of 2694 subjects, aged 18–80 years, who attended health examination in Xi’an Electric Power Central Hospital from April 2011 to December 2015 were collected and analyzed. The first cohort enrolled 929 participants (followed up by 2221 person-years totally) to assess correlations between serum thyrotropin (TSH), triiodothyronine (T3), thyroxine (T4) levels and MetS. The second cohort included 698 participants (followed up by 1709 person-years totally) to evaluate relationships between serum free triiodothyronine (FT3), free thyroxine (FT4) levels and MetS. MetS was defined according to the criteria of the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) scientific statements of 2009. Euthyroidism was defined as serum TSH, FT3 and FT4 levels within the reference ranges without taking any thyroid medication. Results The cutoff values for TSH, T3, T4, FT3 and FT4 were 2.0mIU/L, 1.9 nmol/L, 117 nmol/L, 4.3 pmol/L and 16 pmol/L, respectively. Participants were categorized into two groups according to cutoff values: the lower-THs group and the higher-THs group. There was no significant difference in the risk of MetS between two groups in TSH, T3, T4 and FT3. The incidence of MetS was significantly higher in lower-FT4 group than higher-FT4 group (1.00 vs 0.622 (0.458, 0.846), P = 0.002). The lower-FT4/higher-TSH group had the highest hazard ratios of MetS. (2.131vs 1.0 (1.380,3.291), P = 0.006). Conclusions Lower normal FT4 (FT4 ≤ 16.0 pmol/L) is an independent risk factor for MetS, and lower normal thyroid function (TSH > 2.0 mIU/L and FT4 ≤ 16.0 pmol/L) is associated with a higher risk of developing MetS.
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- 2021
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23. Calibration strategy of the JUNO experiment
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Andrea Barresi, Muhammad Usman Rajput, Chengzhuo Yuan, Demin Li, Cédric Huss, Jie Zhao, Xianghui Yu, W. H. Huang, Feng Gao, Sen Qian, Patrick Kinz, Miao He, Axel Müller, Davit Mayilyan, Utane Sawangwit, Jacques Wurtz, Wenju Huo, Hang Hu, Guanghua Gong, G. Andronico, Giuseppe Verde, Si Ma, Livia Ludhova, Xiaoyu Yang, Lucia Votano, Waqas Muhammad, Oleg Smirnov, Jie Yang, Zhe Ning, Y. X. Zhang, Zhuang Shao, Jun Wang, Martin Dvorak, Hao Liang, Nikolay Morozov, Ara Ioannisian, Qingmin Zhang, Ezio Previtali, Barbara Ricci, Ints Mednieks, Wuming Luo, Rossella Caruso, Diru Wu, Alexander Studenikin, Sadia Marium, Jingbo Zhang, M. Settimo, A. Popov, Enrico Bernieri, Xiaowei Liu, Yumei Zhang, Anut Sangka, Feipeng Ning, F. Z. Qi, Simon Blyth, Anatael Cabrera, Antonio Insolia, Donglian Xu, Amir N. Khan, Minghao Gu, Daniel Liebau, Shouyang Hu, Thilo Birkenfeld, Mengyun Guan, Gérard Claverie, Xin Mao, Xingtao Huang, Guoqing Zhang, Markus Robens, Jari Joutsenvaara, Zhibing Li, Can Fang, Nuanwan Sanguansak, Andrey Formozov, Ugur Yegin, Yuekun Heng, Xiaohui Qian, Riccardo Bruno, Zafar Yasin, Selma Conforti Di Lorenzo, Weidong Li, Xiaonan Li, Cédric Schwab, Yuguang Xie, Narumon Suwonjandee, Michael Wurm, Teerapat Payupol, Andrea Serafini, Chunhao Huang, Fangliang Wu, Haoqi Lu, Di Jiang, Salvatore Costa, Yue Meng, Y. Sun, S. Dusini, Mathieu Roche, Stefano Maria Mari, S. Parmeggiano, N. Raper, M. A. Szelezniak, W. J. Wu, Jingbin Lu, Heike Enzmann, Nan Li, Zhonghua Qin, Min Liu, Q. J. Li, Tobias Heinz, Frédéric Druillole, Qun Wu, Anbo Yang, Hongjuan Liu, Sukit Limpijumnong, Peihuai Yi, Cecilia Landini, Jonathan Miller, Yu Xu, Agnese Martini, Vito Antonelli, A. Bolshakova, Alexandre Göttel, X. L. Ji, Yuanqing Wang, Haonan Gan, Lei Yang, Sebastiano Aiello, Leonidas Kalousis, Andre Zambanini, R. T. Lei, Stefan van Waasen, Dmitry Selivanov, Khanchai Khosonthongkee, Yanke Cai, F. Yermia, Yuman Wang, Rong Zhao, Jian Wang, E. Meroni, Filippo Marini, Narine Kazarian, Y. F. Wang, Shanfeng Li, Q. An, Alessandra Re, Chung-Hsiang Wang, Agnese Giaz, Tingxuan Zeng, Guihong Huang, Andrej Babic, Fabio Mantovani, Fang Liu, Richard Ford, Zhe Wang, Christian Grewing, Antonio Bergnoli, Warintorn Sreethawong, Georgy Donchenko, S. Krokhaleva, Mengzhao Li, Rupert Leitner, Monica Sisti, Domizia Orestano, Mario Buscemi, Paolo Montini, Marco Grassi, Zeyuan Yu, Tobias Lachenmaier, Jianrun Hu, Victor Lebrin, Angel Abusleme, Boxiang Yu, Tao Li, Maciej Slupecki, Boonrucksar Soonthornthum, Catia Clementi, Marco Giammarchi, Francesco Manzali, B. Z. Hu, Virginia Strati, Alexey Krasnoperov, Zhang Chen, Hua Zheng, P. Saggese, Minshan Zheng, Xiaolu Ji, Gisele Martin-Chassard, Matthias Raphael Stock, Pablo Walker, Jose Busto, Agustin Campeny, Burin Asavapibhop, Yinhong Zhang, S. B. Liu, Vitaly Shutov, Barbara Clerbaux, Peng Zhang, Zhengyun You, Yayun Ding, Shubin Liu, Ayut Limphirat, S. Dmitrievsky, Siyu Jian, S. Sanfilippo, Cristina Tuve, Shoukang Qiu, Shifeng Sun, Jie Ren, Sébastien Leblanc, Po-An Chen, Xubo Ma, Safeer Hussain, Guangpeng An, Nicomede Pelliccia, Yuhang Guo, Shan Zeng, Konstantin A. Kouzakov, Shaojing Hou, Jing Xu, X. H. Guo, Feiyang Zhang, Dongqin Zheng, Ilya Butorov, Maria Gul, Kunyu Wang, Claudio Lombardo, Zhi Deng, Zhiyan Cai, Yu Gu, Yufei Xi, K. Loo, R. Brugnera, Shu Luo, Jiaheng Zou, Ran Han, Giancarlo Troni, M. H. Ye, Xiaoxu Lu, Fengjiao Luo, H. D. Liu, Haitao Li, Fei Li, Julanan Songwadhana, Xiaomei Zhang, Fengpeng An, X. D. Ruan, Chunxu Yu, Vadim Vedin, Mauro Mezzetto, Jiaqi Li, Caren Hagner, Shu Zhang, Wander Baldini, Yangheng Zheng, Antonio Budano, Michele Montuschi, Zheng Wang, Qin Liu, Pierre-Alexandre Petitjean, Xuefeng Ding, H. R. Pan, Lukas Fajt, Jingyan Shi, David Meyhöfer, Fanrong Xu, Marco Bellato, Zhenyu Zhang, S. J. Zhao, Clément Bordereau, Yan Zhang, Bayarto Lubsandorzhiev, Guang Luo, Benda Xu, Xiangyue Wang, Christophe De La Taille, Miao Yu, Christian Roth, Nina Parkalian, Andrea Fabbri, Fausto Ortica, João Pedro Athayde Marcondes de André, Y. Wang, Liangjian Wen, S. X. Du, Jian Tang, Frederic Lefevre, Tao Hu, Vasily Gromov, Guofu Cao, Liang Zhan, E. Doroshkevich, Steven Chan-Fai Wong, Amélie Fournier, Apimook Watcharangkool, Jinchang Liu, Qian Liu, Yongbo Huang, Bayu Dirgantara, Chiara Sirignano, Qiumei Ma, Yi Wang, A. Sadovsky, Xichao Ruan, Caishen Wang, G. Settanta, Flavio Dal Corso, Beatrice Jelmini, Guillaume Vanroyen, Baojun Yan, Ruhui Li, Mikhail Smirnov, Huan Yang, Z. Wu, Xiao Cai, Yun Chang, Meng Wang, Yufeng Li, Tianchi Zhao, K. L. Jen, Li-Cheng Feng, Guey-Lin Lin, Shuxiang Lu, Massimiliano Nastasi, Thomas Adam, Rizwan Ahmed, David Blum, Marco Fargetta, Didier Auguste, Weiguo Li, Jian Fang, Patrick Hellmuth, Muhammad Akram, Hui Liu, Tomas Tmej, G. X. Sun, Fengyi Zhao, Christian Wysotzki, Wladyslaw Henryk Trzaska, Achim Stahl, Sylvie Blin, Yin Xu, Alexander Tietzsch, Fedor Šimkovic, Haiping Peng, Ziping Ye, Baobiao Yue, A. Sotnikov, Aldo Romani, Anna Chuvashova, Noman Zafar, Tatiana Antoshkina, Wanlei Guo, C. Jollet, Christoph Genster, Sultim Lubsandorzhiev, Y. K. Sun, Xiangwei Yin, Xiaoping Jing, H. Steiger, Muhammad Sohaib Hassan, Cristina Martellini, Wei Wang, B. Viaud, Igor Nemchenok, Zhijian Zhang, Fatma Sawy, Xiaofei Gu, Alexander Olshevskiy, Liang Zong, Pavithra Muralidharan, Xiaomei Li, Alexandr Selyunin, Yu Chen, Jochen Steinmann, Qiang Tang, Daojin Hong, Daniele Corti, Yatian Pei, S. Zhang, Denis Korablev, Yi Chen, Dominique Breton, Franco Giuliani, F. Li, Augusto Brigatti, Artem Chukanov, Nikolaos Vassilopoulos, Jiaxuan Ye, Yi-Wen Chen, K. Treskov, Michael Karagounis, Haiqiong Zhang, Jiang Zhu, Nunzio Giudice, Zongyi Wang, H. L. Zhuang, Marco Aurelio Diaz, Nikolay Kutovskiy, Shakeel Ahmad, Narongkiat Rodphai, Yifan Yang, Huihui Jia, Juan Pedro Ochoa-Ricoux, Jin Li, Hongtao Liu, Andrey Sidorenkov, Qichun Feng, Jiawen Zhang, T. Enqvist, Ruyi Jin, J. J. Ling, Arseniy Rybnikov, Lino Miramonti, Yi Li, Luis Felipe Piñeres Rico, Ziyuan Li, Ziyi Yuan, A. Lokhov, Jie Cheng, Rafael Herrera, Jiaqi Hui, Wathan Pratumwan, En Wang, Konstantin Schweizer, A. Kruth, Tobias Sterr, Shengxin Lin, Anna Fatkina, Fabrizio Petrucci, Mathieu Bongrand, Olivia Dalager, Alessandro Paoloni, Philipp Kampmann, Roberto Isocrate, Jianmeng Dong, Weirong Zhong, Yiyu Zhang, Saroj Rujirawat, Giuseppe Salamanna, Maxim Vialkov, Abdel Rebii, Mengjiao Xiao, Jing Zhou, P. Chimenti, Jingjing Liang, Yuanyuan Zhang, Pingping Chen, Igor Tkachev, A. Cammi, Oliver Pilarczyk, Vit Vorobel, Zhimin Wang, Honghao Zhang, Zhenxiong Yuan, Xiang Zhou, Damien Dornic, Jie Zhang, Zhangquan Xie, Yaping Cheng, Ying Yuan, Maxim Gonchar, Wei Wei, Zhuojun Hu, Ivano Lippi, Xilei Sun, Shaomin Chen, Jun Cao, Li Zhou, Ruiguang Wang, Nikolay Anfimov, Andrea Triossi, Runxuan Liu, Xinglong Li, Waseem Khan, Pasi Kuusiniemi, Xi Wang, Salvatore Monforte, Meihang Xu, Eric Baussan, Haifeng Yao, Xuantong Zhang, Yang Han, Pascal Poussot, Dongmei Xia, Jacky Schuler, Hao Qiao, Hu Liu, Henning Rebber, Dmitry V. Naumov, Luca Stanco, Paul Hackspacher, Y. K. Hor, Lei Fan, Ziyan Deng, Lei Huo, Ondrej Sramek, K. J. Li, Jianglai Liu, Lu Wang, Paolo Lombardi, Marcos Dracos, B. Roskovec, Taras Rezinko, Quan Tang, Jiawei Deng, Jason Leung, Xiao Tang, Junji Jia, Huiling Li, Nunzio Guardone, Chuanya Cao, Diana Navas-Nicolas, A. Meregaglia, Zhi-zhong Xing, V. Fekete, Jilei Xu, W. Wang, Siguang Wang, Yupeng Yan, Hao Cai, Christopher Wiebusch, Y. B. Hsiung, Z. V. Krumshteyn, Sirichok Jungthawan, Thiago Sogo-Bezerra, Yury Malyshkin, S. Li, Dmitry Fedoseev, Tao Lin, Chuan Lu, J. F. Chang, Davide Chiesa, Changgen Yang, A. Garfagnini, F. Perrot, Wilfried Depnering, Xiaoyan Ma, Yadong Wei, M. Wang, O. Gorchakov, Yajun Mao, Anguo Peng, C. Cerna, Wei He, Lothar Oberauer, Konstantin Stankevich, Yuri Gornushkin, Donghua Fan, Cong Guo, Dušan Štefánik, Ming Qi, Lianghong Wei, Jihane Maalmi, E. Naumova, Jaruchit Siripak, Tadeas Dohnal, Julia Sawatzki, Hongbang Liu, X. R. Chen, Bjoern Wonsak, Vladimir Lyashuk, Johannes van den Boom, Qinhua Huang, Jingyuan Guo, Yuda Zeng, Shulin Liu, Tao Zhang, Guo-Li Wang, Hui Gong, Michaela Schever, Jun Hu, K. J. Zhu, P. W. Luo, Shun Zhou, Bin Ren, Nan Zhou, Yan Liu, Li Kang, Junguang Lu, Gioacchino Ranucci, Chiye Yu, Cheng Xu, Hongzhao Yu, Hanxiong Huang, Xiongbo Yan, Sai-Juan Chen, C. Volpe, Hiroshi Nunokawa, Yanchu Wang, Vladislav Sharov, Xiaoshan Jiang, Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, An, F, An, G, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Babic, A, Baldini, W, Barresi, A, Baussan, E, Bellato, M, Bergnoli, A, Bernieri, E, Birkenfeld, T, Blin, S, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Buscemi, M, Busto, J, Butorov, I, Cabrera, A, Cai, H, Cai, X, Cai, Y, Cai, Z, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Chang, J, Chang, Y, Chen, P, Chen, S, Chen, X, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chiesa, D, Chimenti, P, Chukanov, A, Chuvashova, A, Claverie, G, Clementi, C, Clerbaux, B, Lorenzo, S, Corti, D, Costa, S, Corso, F, Dalager, O, Taille, C, Deng, J, Deng, Z, Depnering, W, Diaz, M, Ding, X, Ding, Y, Dirgantara, B, Dmitrievsky, S, Dohnal, T, Donchenko, G, Dong, J, Dornic, D, Doroshkevich, E, Dracos, M, Druillole, F, Du, S, Dusini, S, Dvorak, M, Enqvist, T, Enzmann, H, Fabbri, A, Fajt, L, Fan, D, Fan, L, Fang, C, Fang, J, Fargetta, M, Fatkina, A, Fedoseev, D, Fekete, V, Feng, L, Feng, Q, Ford, R, Formozov, A, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gottel, A, Genster, C, Giammarchi, M, Giaz, A, Giudice, N, Giuliani, F, Gonchar, M, Gong, G, Gong, H, Gorchakov, O, Gornushkin, Y, Grassi, M, Grewing, C, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guardone, N, Gul, M, Guo, C, Guo, J, Guo, W, Guo, X, Guo, Y, Hackspacher, P, Hagner, C, Han, R, Han, Y, Hassan, M, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hong, D, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Z, Huang, C, Huang, G, Huang, H, Huang, Q, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Insolia, A, Ioannisian, A, Isocrate, R, Jelmini, B, Jen, K, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, D, Jiang, X, Jin, R, Jing, X, Jollet, C, Joutsenvaara, J, Jungthawan, S, Kalousis, L, Kampmann, P, Kang, L, Karagounis, M, Kazarian, N, Khan, A, Khan, W, Khosonthongkee, K, Kinz, P, Korablev, D, Kouzakov, K, Krasnoperov, A, Krokhaleva, S, Krumshteyn, Z, Kruth, A, Kutovskiy, N, Kuusiniemi, P, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, H, Li, J, Li, K, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liang, J, Liebau, D, Limphirat, A, Limpijumnong, S, Lin, G, Lin, S, Lin, T, Ling, J, Lippi, I, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, S, Lu, X, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Luo, F, Luo, G, Luo, P, Luo, S, Luo, W, Lyashuk, V, Ma, Q, Ma, S, Ma, X, Maalmi, J, Malyshkin, Y, Mantovani, F, Manzali, F, Mao, X, Mao, Y, Mari, S, Marini, F, Marium, S, Martellini, C, Martin-Chassard, G, Martini, A, Mayilyan, D, Muller, A, Mednieks, I, Meng, Y, Meregaglia, A, Meroni, E, Meyhofer, D, Mezzetto, M, Miller, J, Miramonti, L, Monforte, S, Montini, P, Montuschi, M, Morozov, N, Muhammad, W, Muralidharan, P, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Pan, H, Paoloni, A, Parkalian, N, Parmeggiano, S, Payupol, T, Pei, Y, Pelliccia, N, Peng, A, Peng, H, Perrot, F, Petitjean, P, Petrucci, F, Rico, L, Pilarczyk, O, Popov, A, Poussot, P, Pratumwan, W, Previtali, E, Qi, F, Qi, M, Qian, S, Qian, X, Qiao, H, Qin, Z, Qiu, S, Rajput, M, Ranucci, G, Raper, N, Re, A, Rebber, H, Rebii, A, Ren, B, Ren, J, Rezinko, T, Ricci, B, Robens, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Roth, C, Ruan, X, Rujirawat, S, Rybnikov, A, Sadovsky, A, Saggese, P, Salamanna, G, Sanfilippo, S, Sangka, A, Sanguansak, N, Sawangwit, U, Sawatzki, J, Sawy, F, Schever, M, Schuler, J, Schwab, C, Schweizer, K, Selivanov, D, Selyunin, A, Serafini, A, Settanta, G, Settimo, M, Shao, Z, Sharov, V, Shi, J, Shutov, V, Sidorenkov, A, Simkovic, F, Sirignano, C, Siripak, J, Sisti, M, Slupecki, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Stefanik, D, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Sun, G, Sun, S, Sun, X, Sun, Y, Suwonjandee, N, Szelezniak, M, Tang, J, Tang, Q, Tang, X, Tietzsch, A, Tkachev, I, Tmej, T, Treskov, K, Triossi, A, Troni, G, Trzaska, W, Tuve, C, van Waasen, S, van den Boom, J, Vanroyen, G, Vassilopoulos, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Volpe, C, Vorobel, V, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, K, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Wang, Z, Watcharangkool, A, Wei, L, Wei, W, Wei, Y, Wen, L, Wiebusch, C, Wong, S, Wonsak, B, Wu, D, Wu, F, Wu, Q, Wu, W, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, M, Xie, Y, Xie, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, X, Yan, Y, Yang, A, Yang, C, Yang, H, Yang, J, Yang, L, Yang, X, Yang, Y, Yao, H, Yasin, Z, Ye, J, Ye, M, Ye, Z, Yegin, U, Yermia, F, Yi, P, Yin, X, You, Z, Yu, B, Yu, C, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zambanini, A, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, F, Zhang, G, Zhang, H, Zhang, J, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, F, Zhao, J, Zhao, R, Zhao, S, Zhao, T, Zheng, D, Zheng, H, Zheng, M, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, X, Zhu, J, Zhu, K, Zhuang, H, Zong, L, Zou, J, Institut Pluridisciplinaire Hubert Curien (IPHC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire de physique subatomique et des technologies associées (SUBATECH), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Centre d'Etudes Nucléaires de Bordeaux Gradignan (CENBG), Université Sciences et Technologies - Bordeaux 1-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), JUNO, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Abusleme A., Adam T., Ahmad S., Ahmed R., Aiello S., Akram M., An F., An G., An Q., Andronico G., Anfimov N., Antonelli V., Antoshkina T., Asavapibhop B., de Andre J.P.A.M., Auguste D., Babic A., Baldini W., Barresi A., Baussan E., Bellato M., Bergnoli A., Bernieri E., Birkenfeld T., Blin S., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Buscemi M., Busto J., Butorov I., Cabrera A., Cai H., Cai X., Cai Y., Cai Z., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Chang J., Chang Y., Chen P., Chen P.-A., Chen S., Chen X., Chen Y.-W., Chen Y., Chen Z., Cheng J., Cheng Y., Chiesa D., Chimenti P., Chukanov A., Chuvashova A., Claverie G., Clementi C., Clerbaux B., Lorenzo S.C.D., Corti D., Costa S., Corso F.D., Dalager O., Taille C.D.L., Deng J., Deng Z., Depnering W., Diaz M., Ding X., Ding Y., Dirgantara B., Dmitrievsky S., Dohnal T., Donchenko G., Dong J., Dornic D., Doroshkevich E., Dracos M., Druillole F., Du S., Dusini S., Dvorak M., Enqvist T., Enzmann H., Fabbri A., Fajt L., Fan D., Fan L., Fang C., Fang J., Fargetta M., Fatkina A., Fedoseev D., Fekete V., Feng L.-C., Feng Q., Ford R., Formozov A., Fournier A., Gan H., Gao F., Garfagnini A., Gottel A., Genster C., Giammarchi M., Giaz A., Giudice N., Giuliani F., Gonchar M., Gong G., Gong H., Gorchakov O., Gornushkin Y., Grassi M., Grewing C., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guardone N., Gul M., Guo C., Guo J., Guo W., Guo X., Guo Y., Hackspacher P., Hagner C., Han R., Han Y., Hassan M., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hong D., Hor Y., Hou S., Hsiung Y., Hu B.-Z., Hu H., Hu J., Hu S., Hu T., Hu Z., Huang C., Huang G., Huang H., Huang Q., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Insolia A., Ioannisian A., Isocrate R., Jelmini B., Jen K.-L., Ji X., Jia H., Jia J., Jian S., Jiang D., Jiang X., Jin R., Jing X., Jollet C., Joutsenvaara J., Jungthawan S., Kalousis L., Kampmann P., Kang L., Karagounis M., Kazarian N., Khan A., Khan W., Khosonthongkee K., Kinz P., Korablev D., Kouzakov K., Krasnoperov A., Krokhaleva S., Krumshteyn Z., Kruth A., Kutovskiy N., Kuusiniemi P., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li H., Li J., Li K., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liang J., Liebau D., Limphirat A., Limpijumnong S., Lin G.-L., Lin S., Lin T., Ling J., Lippi I., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu S., Lu X., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Luo F., Luo G., Luo P., Luo S., Luo W., Lyashuk V., Ma Q., Ma S., Ma X., Maalmi J., Malyshkin Y., Mantovani F., Manzali F., Mao X., Mao Y., Mari S.M., Marini F., Marium S., Martellini C., Martin-Chassard G., Martini A., Mayilyan D., Muller A., Mednieks I., Meng Y., Meregaglia A., Meroni E., Meyhofer D., Mezzetto M., Miller J., Miramonti L., Monforte S., Montini P., Montuschi M., Morozov N., Muhammad W., Muralidharan P., Nastasi M., Naumov D.V., Naumova E., Navas-Nicolas D., Nemchenok I., Ning F., Ning Z., Nunokawa H., Oberauer L., Ochoa-Ricoux J.P., Olshevskiy A., Orestano D., Ortica F., Pan H.-R., Paoloni A., Parkalian N., Parmeggiano S., Payupol T., Pei Y., Pelliccia N., Peng A., Peng H., Perrot F., Petitjean P.-A., Petrucci F., Rico L.F.P., Pilarczyk O., Popov A., Poussot P., Pratumwan W., Previtali E., Qi F., Qi M., Qian S., Qian X., Qiao H., Qin Z., Qiu S., Rajput M., Ranucci G., Raper N., Re A., Rebber H., Rebii A., Ren B., Ren J., Rezinko T., Ricci B., Robens M., Roche M., Rodphai N., Romani A., Roskovec B., Roth C., Ruan X., Rujirawat S., Rybnikov A., Sadovsky A., Saggese P., Salamanna G., Sanfilippo S., Sangka A., Sanguansak N., Sawangwit U., Sawatzki J., Sawy F., Schever M., Schuler J., Schwab C., Schweizer K., Selivanov D., Selyunin A., Serafini A., Settanta G., Settimo M., Shao Z., Sharov V., Shi J., Shutov V., Sidorenkov A., Simkovic F., Sirignano C., Siripak J., Sisti M., Slupecki M., Smirnov M., Smirnov O., Sogo-Bezerra T., Songwadhana J., Soonthornthum B., Sotnikov A., Sramek O., Sreethawong W., Stahl A., Stanco L., Stankevich K., Stefanik D., Steiger H., Steinmann J., Sterr T., Stock M.R., Strati V., Studenikin A., Sun G., Sun S., Sun X., Sun Y., Suwonjandee N., Szelezniak M., Tang J., Tang Q., Tang X., Tietzsch A., Tkachev I., Tmej T., Treskov K., Triossi A., Troni G., Trzaska W., Tuve C., van Waasen S., van den Boom J., Vanroyen G., Vassilopoulos N., Vedin V., Verde G., Vialkov M., Viaud B., Volpe C., Vorobel V., Votano L., Walker P., Wang C., Wang C.-H., Wang E., Wang G., Wang J., Wang K., Wang L., Wang M., Wang R., Wang S., Wang W., Wang X., Wang Y., Wang Z., Watcharangkool A., Wei L., Wei W., Wei Y., Wen L., Wiebusch C., Wong S.C.-F., Wonsak B., Wu D., Wu F., Wu Q., Wu W., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao M., Xie Y., Xie Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu J., Xu M., Xu Y., Yan B., Yan X., Yan Y., Yang A., Yang C., Yang H., Yang J., Yang L., Yang X., Yang Y., Yao H., Yasin Z., Ye J., Ye M., Ye Z., Yegin U., Yermia F., Yi P., Yin X., You Z., Yu B., Yu C., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zambanini A., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang F., Zhang G., Zhang H., Zhang J., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao F., Zhao J., Zhao R., Zhao S., Zhao T., Zheng D., Zheng H., Zheng M., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou X., Zhu J., Zhu K., Zhuang H., Zong L., Zou J., Abusleme, A., Adam, T., Ahmad, S., Ahmed, R., Aiello, S., Akram, M., An, F., An, G., An, Q., Andronico, G., Anfimov, N., Antonelli, V., Antoshkina, T., Asavapibhop, B., de Andre, J. P. A. M., Auguste, D., Babic, A., Baldini, W., Barresi, A., Baussan, E., Bellato, M., Bergnoli, A., Bernieri, E., Birkenfeld, T., Blin, S., Blum, D., Blyth, S., Bolshakova, A., Bongrand, M., Bordereau, C., Breton, D., Brigatti, A., Brugnera, R., Bruno, R., Budano, A., Buscemi, M., Busto, J., Butorov, I., Cabrera, A., Cai, H., Cai, X., Cai, Y., Cai, Z., Cammi, A., Campeny, A., Cao, C., Cao, G., Cao, J., Caruso, R., Cerna, C., Chang, J., Chang, Y., Chen, P., Chen, P. -A., Chen, S., Chen, X., Chen, Y. -W., Chen, Y., Chen, Z., Cheng, J., Cheng, Y., Chiesa, D., Chimenti, P., Chukanov, A., Chuvashova, A., Claverie, G., Clementi, C., Clerbaux, B., Lorenzo, S. C. D., Corti, D., Costa, S., Corso, F. D., Dalager, O., Taille, C. D. L., Deng, J., Deng, Z., Depnering, W., Diaz, M., Ding, X., Ding, Y., Dirgantara, B., Dmitrievsky, S., Dohnal, T., Donchenko, G., Dong, J., Dornic, D., Doroshkevich, E., Dracos, M., Druillole, F., Du, S., Dusini, S., Dvorak, M., Enqvist, T., Enzmann, H., Fabbri, A., Fajt, L., Fan, D., Fan, L., Fang, C., Fang, J., Fargetta, M., Fatkina, A., Fedoseev, D., Fekete, V., Feng, L. -C., Feng, Q., Ford, R., Formozov, A., Fournier, A., Gan, H., Gao, F., Garfagnini, A., Gottel, A., Genster, C., Giammarchi, M., Giaz, A., Giudice, N., Giuliani, F., Gonchar, M., Gong, G., Gong, H., Gorchakov, O., Gornushkin, Y., Grassi, M., Grewing, C., Gromov, V., Gu, M., Gu, X., Gu, Y., Guan, M., Guardone, N., Gul, M., Guo, C., Guo, J., Guo, W., Guo, X., Guo, Y., Hackspacher, P., Hagner, C., Han, R., Han, Y., Hassan, M., He, M., He, W., Heinz, T., Hellmuth, P., Heng, Y., Herrera, R., Hong, D., Hor, Y., Hou, S., Hsiung, Y., Hu, B. -Z., Hu, H., Hu, J., Hu, S., Hu, T., Hu, Z., Huang, C., Huang, G., Huang, H., Huang, Q., Huang, W., Huang, X., Huang, Y., Hui, J., Huo, L., Huo, W., Huss, C., Hussain, S., Insolia, A., Ioannisian, A., Isocrate, R., Jelmini, B., Jen, K. -L., Ji, X., Jia, H., Jia, J., Jian, S., Jiang, D., Jiang, X., Jin, R., Jing, X., Jollet, C., Joutsenvaara, J., Jungthawan, S., Kalousis, L., Kampmann, P., Kang, L., Karagounis, M., Kazarian, N., Khan, A., Khan, W., Khosonthongkee, K., Kinz, P., Korablev, D., Kouzakov, K., Krasnoperov, A., Krokhaleva, S., Krumshteyn, Z., Kruth, A., Kutovskiy, N., Kuusiniemi, P., Lachenmaier, T., Landini, C., Leblanc, S., Lebrin, V., Lefevre, F., Lei, R., Leitner, R., Leung, J., Li, D., Li, F., Li, H., Li, J., Li, K., Li, M., Li, N., Li, Q., Li, R., Li, S., Li, T., Li, W., Li, X., Li, Y., Li, Z., Liang, H., Liang, J., Liebau, D., Limphirat, A., Limpijumnong, S., Lin, G. -L., Lin, S., Lin, T., Ling, J., Lippi, I., Liu, F., Liu, H., Liu, J., Liu, M., Liu, Q., Liu, R., Liu, S., Liu, X., Liu, Y., Lokhov, A., Lombardi, P., Lombardo, C., Loo, K., Lu, C., Lu, H., Lu, J., Lu, S., Lu, X., Lubsandorzhiev, B., Lubsandorzhiev, S., Ludhova, L., Luo, F., Luo, G., Luo, P., Luo, S., Luo, W., Lyashuk, V., Ma, Q., Ma, S., Ma, X., Maalmi, J., Malyshkin, Y., Mantovani, F., Manzali, F., Mao, X., Mao, Y., Mari, S. M., Marini, F., Marium, S., Martellini, C., Martin-Chassard, G., Martini, A., Mayilyan, D., Muller, A., Mednieks, I., Meng, Y., Meregaglia, A., Meroni, E., Meyhofer, D., Mezzetto, M., Miller, J., Miramonti, L., Monforte, S., Montini, P., Montuschi, M., Morozov, N., Muhammad, W., Muralidharan, P., Nastasi, M., Naumov, D. V., Naumova, E., Navas-Nicolas, D., Nemchenok, I., Ning, F., Ning, Z., Nunokawa, H., Oberauer, L., Ochoa-Ricoux, J. P., Olshevskiy, A., Orestano, D., Ortica, F., Pan, H. -R., Paoloni, A., Parkalian, N., Parmeggiano, S., Payupol, T., Pei, Y., Pelliccia, N., Peng, A., Peng, H., Perrot, F., Petitjean, P. -A., Petrucci, F., Rico, L. F. P., Pilarczyk, O., Popov, A., Poussot, P., Pratumwan, W., Previtali, E., Qi, F., Qi, M., Qian, S., Qian, X., Qiao, H., Qin, Z., Qiu, S., Rajput, M., Ranucci, G., Raper, N., Re, A., Rebber, H., Rebii, A., Ren, B., Ren, J., Rezinko, T., Ricci, B., Robens, M., Roche, M., Rodphai, N., Romani, A., Roskovec, B., Roth, C., Ruan, X., Rujirawat, S., Rybnikov, A., Sadovsky, A., Saggese, P., Salamanna, G., Sanfilippo, S., Sangka, A., Sanguansak, N., Sawangwit, U., Sawatzki, J., Sawy, F., Schever, M., Schuler, J., Schwab, C., Schweizer, K., Selivanov, D., Selyunin, A., Serafini, A., Settanta, G., Settimo, M., Shao, Z., Sharov, V., Shi, J., Shutov, V., Sidorenkov, A., Simkovic, F., Sirignano, C., Siripak, J., Sisti, M., Slupecki, M., Smirnov, M., Smirnov, O., Sogo-Bezerra, T., Songwadhana, J., Soonthornthum, B., Sotnikov, A., Sramek, O., Sreethawong, W., Stahl, A., Stanco, L., Stankevich, K., Stefanik, D., Steiger, H., Steinmann, J., Sterr, T., Stock, M. R., Strati, V., Studenikin, A., Sun, G., Sun, S., Sun, X., Sun, Y., Suwonjandee, N., Szelezniak, M., Tang, J., Tang, Q., Tang, X., Tietzsch, A., Tkachev, I., Tmej, T., Treskov, K., Triossi, A., Troni, G., Trzaska, W., Tuve, C., van Waasen, S., van den Boom, J., Vanroyen, G., Vassilopoulos, N., Vedin, V., Verde, G., Vialkov, M., Viaud, B., Volpe, C., Vorobel, V., Votano, L., Walker, P., Wang, C., Wang, C. -H., Wang, E., Wang, G., Wang, J., Wang, K., Wang, L., Wang, M., Wang, R., Wang, S., Wang, W., Wang, X., Wang, Y., Wang, Z., Watcharangkool, A., Wei, L., Wei, W., Wei, Y., Wen, L., Wiebusch, C., Wong, S. C. -F., Wonsak, B., Wu, D., Wu, F., Wu, Q., Wu, W., Wu, Z., Wurm, M., Wurtz, J., Wysotzki, C., Xi, Y., Xia, D., Xiao, M., Xie, Y., Xie, Z., Xing, Z., Xu, B., Xu, C., Xu, D., Xu, F., Xu, J., Xu, M., Xu, Y., Yan, B., Yan, X., Yan, Y., Yang, A., Yang, C., Yang, H., Yang, J., Yang, L., Yang, X., Yang, Y., Yao, H., Yasin, Z., Ye, J., Ye, M., Ye, Z., Yegin, U., Yermia, F., Yi, P., Yin, X., You, Z., Yu, B., Yu, C., Yu, H., Yu, M., Yu, X., Yu, Z., Yuan, C., Yuan, Y., Yuan, Z., Yue, B., Zafar, N., Zambanini, A., Zeng, S., Zeng, T., Zeng, Y., Zhan, L., Zhang, F., Zhang, G., Zhang, H., Zhang, J., Zhang, P., Zhang, Q., Zhang, S., Zhang, T., Zhang, X., Zhang, Y., Zhang, Z., Zhao, F., Zhao, J., Zhao, R., Zhao, S., Zhao, T., Zheng, D., Zheng, H., Zheng, M., Zheng, Y., Zhong, W., Zhou, J., Zhou, L., Zhou, N., Zhou, S., Zhou, X., Zhu, J., Zhu, K., Zhuang, H., Zong, L., and Zou, J.
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Nuclear and High Energy Physics ,Physics - Instrumentation and Detectors ,Physics::Instrumentation and Detectors ,measurement methods ,scintillation counter: liquid ,energy resolution ,FOS: Physical sciences ,Photodetector ,Scintillator ,01 natural sciences ,NO ,High Energy Physics - Experiment ,High Energy Physics - Experiment (hep-ex) ,hal-03022811 ,PE2_2 ,Optics ,0103 physical sciences ,[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex] ,Calibration ,lcsh:Nuclear and particle physics. Atomic energy. Radioactivity ,ddc:530 ,[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det] ,010306 general physics ,Astrophysique ,Jiangmen Underground Neutrino Observatory ,Physics ,JUNO ,liquid [scintillation counter] ,010308 nuclear & particles physics ,business.industry ,Settore FIS/01 - Fisica Sperimentale ,Detector ,Astrophysics::Instrumentation and Methods for Astrophysics ,Linearity ,Instrumentation and Detectors (physics.ins-det) ,calibration ,Neutrino Detectors and Telescopes (experiments) ,lcsh:QC770-798 ,High Energy Physics::Experiment ,Neutrino ,business ,Energy (signal processing) - Abstract
We present the calibration strategy for the 20 kton liquid scintillator central detector of the Jiangmen Underground Neutrino Observatory (JUNO). By utilizing a comprehensive multiple-source and multiple-positional calibration program, in combination with a novel dual calorimetry technique exploiting two independent photosensors and readout systems, we demonstrate that the JUNO central detector can achieve a better than 1% energy linearity and a 3% effective energy resolution, required by the neutrino mass ordering determination. [Figure not available: see fulltext.], 0, info:eu-repo/semantics/published
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- 2021
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24. Discovery of Genetic Biomarkers for Alzheimer's Disease Using Adaptive Convolutional Neural Networks Ensemble and Genome-Wide Association Studies
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An, Zeng, Huabin, Rong, Dan, Pan, Longfei, Jia, Yiqun, Zhang, Fengyi, Zhao, and Shaoliang, Peng
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Alzheimer Disease ,Humans ,Neuroimaging ,Neural Networks, Computer ,Magnetic Resonance Imaging ,Genome-Wide Association Study - Abstract
To identify candidate neuroimaging and genetic biomarkers for Alzheimer's disease (AD) and other brain disorders, especially for little-investigated brain diseases, we advocate a data-driven approach which incorporates an adaptive classifier ensemble model acquired by integrating Convolutional Neural Network (CNN) and Ensemble Learning (EL) with Genetic Algorithm (GA), i.e., the CNN-EL-GA method, into Genome-Wide Association Studies (GWAS).Above all, a large number of CNN models as base classifiers were trained using coronal, sagittal, or transverse magnetic resonance imaging slices, respectively, and the CNN models with strong discriminability were then selected to build a single classifier ensemble with the GA for classifying AD, with the help of the CNN-EL-GA method. While the acquired classifier ensemble exhibited the highest generalization capability, the points of intersection were determined with the most discriminative coronal, sagittal, and transverse slices. Finally, we conducted GWAS on the genotype data and the phenotypes, i.e., the gray matter volumes of the top ten most discriminative brain regions, which contained the ten most points of intersection.Six genes of PCDH11X/Y, TPTE2, LOC107985902, MUC16 and LINC01621 as well as Single-Nucleotide Polymorphisms, e.g., rs36088804, rs34640393, rs2451078, rs10496214, rs17016520, rs2591597, rs9352767 and rs5941380, were identified.This approach overcomes the limitations associated with the impact of subjective factors and dependence on prior knowledge while adaptively achieving more robust and effective candidate biomarkers in a data-driven way.The approach is promising to facilitate discovering effective candidate genetic biomarkers for brain disorders, as well as to help improve the effectiveness of identified candidate neuroimaging biomarkers for brain diseases.
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- 2021
25. A novel ruthenium polypyridyl complex for the selective imaging and photodynamic targeting of the Golgi apparatus
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Weifan Wang, Fengyi Zhao, and Wenlong Wu
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DNA damage ,Cell Survival ,Pyridines ,Ultraviolet Rays ,medicine.medical_treatment ,chemistry.chemical_element ,Golgi Apparatus ,Photodynamic therapy ,Antineoplastic Agents ,Ruthenium ,Inorganic Chemistry ,HeLa ,symbols.namesake ,chemistry.chemical_compound ,Coordination Complexes ,medicine ,Humans ,Cell Proliferation ,Photosensitizing Agents ,biology ,Singlet oxygen ,Optical Imaging ,Golgi apparatus ,biology.organism_classification ,Fluorescence ,chemistry ,Photochemotherapy ,Cell culture ,symbols ,Biophysics ,Drug Screening Assays, Antitumor ,HeLa Cells - Abstract
A well-designed heteroleptic ruthenium(ii) polypyridyl complex demonstrated stable target-specific in vitro Golgi apparatus imaging abilities in HeLa cell lines. After utilizing photodynamic therapy via UV excitation, the Ru-SL complex could be triggered to generate singlet oxygen (1O2) and red fluorescence signals. 1O2 was highly cytotoxic and could induce DNA damage and the disappearance of the Golgi apparatus. The red fluorescence signals disappeared gradually, suggesting that the live or dead state of the cells can be estimated from the fluorescence signal intensity.
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- 2021
26. Mitochondrial Fission and Mitophagy Coordinately Restrict High Glucose Toxicity in Cardiomyocytes
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Fengyi Zhao, Yuan Huang, Qiangrong Liang, Weihua Wu, Bingyin Shi, Tamayo Kobayashi, Satoru Kobayashi, and Ziying Zhang
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Programmed cell death ,Physiology ,cardiomyocytes ,DRP1 ,Mitochondrial Size ,lcsh:Physiology ,Parkin ,Physiology (medical) ,Lysosome ,Diabetic cardiomyopathy ,Mitophagy ,medicine ,Original Research ,diabetes ,lcsh:QP1-981 ,Chemistry ,mitochondrial fission ,Autophagy ,medicine.disease ,Cell biology ,cell death ,mitophagy ,medicine.anatomical_structure ,Mitochondrial fission ,hyperglycemia - Abstract
Hyperglycemia-induced mitochondrial dysfunction plays a key role in the pathogenesis of diabetic cardiomyopathy. Injured mitochondrial segments are separated by mitochondrial fission and eliminated by autophagic sequestration and subsequent degradation in the lysosome, a process termed mitophagy. However, it remains poorly understood how high glucose affects the activities of, and the relationship between, mitochondrial fission and mitophagy in cardiomyocytes. In this study, we determined the functional roles of mitochondrial fission and mitophagy in hyperglycemia-induced cardiomyocyte injury. High glucose (30 mM, HG) reduced mitochondrial connectivity and particle size and increased mitochondrial number in neonatal rat ventricular cardiomyocytes, suggesting an enhanced mitochondrial fragmentation. SiRNA knockdown of the pro-fission factor dynamin-related protein 1 (DRP1) restored mitochondrial size but did not affect HG toxicity, and Mdivi-1, a DRP1 inhibitor, even increased HG-induced cardiomyocyte injury, as shown by superoxide production, mitochondrial membrane potential and cell death. However, DRP1 overexpression triggered mitochondrial fragmentation and mitigated HG-induced cardiomyocyte injury, suggesting that the increased mitochondrial fission is beneficial, rather than detrimental, to cardiomyocytes cultured under HG conditions. This is in contrast to the prevailing hypothesis that mitochondrial fragmentation mediates or contributes to HG cardiotoxicity. Meanwhile, HG reduced mitophagy flux as determined by the difference in the levels of mitochondria-associated LC3-II or the numbers of mitophagy foci indicated by the novel dual fluorescent reporter mt-Rosella in the absence and presence of the lysosomal inhibitors. The ability of HG to induce mitochondrial fragmentation and inhibit mitophagy was reproduced in adult mouse cardiomyocytes. Overexpression of Parkin, a positive regulator of mitophagy, or treatment with CCCP, a mitochondrial uncoupler, induced mitophagy and attenuated HG-induced cardiomyocyte death, while Parkin knockdown had opposite effects, suggesting an essential role of mitophagy in cardiomyocyte survival under HG conditions. Strikingly, Parkin overexpression increased mitochondrial fragmentation, while DRP1 overexpression accelerated mitophagy flux, demonstrating a reciprocal activation loop that controls mitochondrial fission and mitophagy. Thus, strategies that promote the mutual positive interaction between mitochondrial fission and mitophagy while simultaneously maintain their levels within the physiological range would be expected to improve mitochondrial health, alleviating hyperglycemic cardiotoxicity.
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- 2020
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27. Application of Deep Reinforcement Learning in the Board Game
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Fengyi Zhao, Junmin Hu, Shiyuan Wu, and Jun Meng
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Core (game theory) ,Artificial neural network ,Value network ,Computer science ,business.industry ,Interface (computing) ,Monte Carlo tree search ,Robot ,Reinforcement learning ,Artificial intelligence ,business ,Reinforcement - Abstract
Deep reinforcement learning is one of the core technologies, which leads to artificial intelligence. It has been used widely not only in robot, autonomous driving, power station control and human-computer interaction in mobile e-commerce platforms, but also in gambling games. The game software AlphaGo of artificial intelligence defeated Ke Jie in 2017. Since then, the study of artificial intelligence and deep reinforcement is widely concerned. We build a Neural Network model using TensorFlow and Monte Carlo tree search algorithm, so that agents can reach the level of playing chess with human beings in board games. The gobang interface is realized by Python, and the PhoenixGo recurrence is completed. The computation is reduced and the training effect of the agent is improved by optimizing the establishment of gobang strategic value network. Black hand first can achieve a 73% winning rate, and white hand first is 64%, when playing against human players.
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- 2020
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28. Lower Normal Thyroid Function is Associated With a Higher Risk of Metabolic Syndrome: A Retrospective Cohort on Chinese Population
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Xi Ding, Chunying Zhu, Rui Li, Liping Wu, Yue Wang, Shiqian Hu, Fengyi Zhao, Yang Zhao, Meng Zhang, Mingqian He, Ziyi Chen, and Bingyin Shi
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endocrine system ,hormones, hormone substitutes, and hormone antagonists - Abstract
BackgroundRecently, the relationship between thyroid hormones (THs) across the euthyroid ranges and metabolic syndrome (MetS) has been widely discussed. This study aimed to present specific cutoff values of THs to assess the association between THs and MetS in a euthyroid cohort.MethodsData of 2694 subjects, aged 18-80 years, who attended health examination in Xi’an Electric Power Central Hospital from April 2011 to December 2015 were collected and analyzed. The basic cohort enrolled 929 participants (followed up by 2221 person-years totally) to assess correlations between serum thyrotropin (TSH), triiodothyronine (T3), thyroxine (T4) levels and MetS. The second cohort included 698 participants (followed up by 1709 person-years totally) to evaluate relationships between serum free triiodothyronine (FT3), free thyroxine (FT4) levels and MetS. MetS was defined according to the criteria of the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) scientific statements of 2009. Euthyroidism was defined as serum TSH, FT3 and FT4 levels within the reference ranges without taking any thyroid medication.ResultsThe cutoff values for TSH, T3, T4, FT3 and FT4 were 2.0mIU/L, 1.9nmol/L, 117nmol/L, 4.3pmol/L and 16pmol/L, respectively. Participants were categorized into two groups according to cutoff values: the lower-THs group and the higher-THs group. There was no significant difference in the risk of MetS between two groups in TSH, T3, T4 and FT3. The incidence of MetS was significantly higher in lower-FT4 group than higher-FT4 group (1.00 vs 0.622 (0.458, 0.846), P=0.002). The lower-FT4/higher-TSH group had the highest hazard ratios of MetS. (2.131vs 1.0 (1.380,3.291), P=0.006)ConclusionsLower normal FT4 (FT4≤16.0 pmol/L) is an independent risk factor for MetS, and lower normal thyroid function (TSH>2.0 mIU/L and FT4≤16.0 pmol/L) is associated with a higher risk of developing MetS.
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- 2020
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29. Novel Dual-Fluorescent Mitophagy Reporter Reveals a Reduced Mitophagy Flux in Type 1 Diabetic Mouse Heart
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Fengyi Zhao, Yuan Huang, Qiangrong Liang, Joy Patel, Satoru Kobayashi, and Tamayo Kobayashi
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0301 basic medicine ,Complementary and Manual Therapy ,Cardiac function curve ,Autophagosome ,genetic structures ,Context (language use) ,Mitochondrion ,Diabetes Mellitus, Experimental ,03 medical and health sciences ,Mice ,0302 clinical medicine ,Lysosome ,Diabetic cardiomyopathy ,Mitophagy ,medicine ,Animals ,Humans ,Myocytes, Cardiac ,business.industry ,medicine.disease ,Cell biology ,Mitochondria ,030104 developmental biology ,medicine.anatomical_structure ,Diabetes Mellitus, Type 1 ,Complementary and alternative medicine ,Heart failure ,business ,030217 neurology & neurosurgery - Abstract
Context: Patients with diabetes are susceptible to heart failure. Defective mitochondria can cause cardiac damage. Mitochondrial autophagy or mitophagy is a quality control mechanism that eliminates dysfunctional mitochondria through lysosome degradation. Mitophagy is essential for maintaining a pool of healthy mitochondria for normal cardiac function. However, the effect of diabetes on the functional status of cardiac mitophagy remains unclear. Objective: To determine and compare cardiac mitophagy flux between diabetic and nondiabetic mice. Methods: Using a novel dual fluorescent mitophagy reporter termed mt-Rosella, we labeled and traced mitochondrial fragments that are sequestered by the autophagosome and delivered to and degraded in the lysosome. Results: Mitophagic activity was reduced in high-glucose–treated cardiomyocytes and in the heart tissue of type 1 diabetic mice. Conclusions: Mitophagy was impaired in the heart of diabetic mice, suggesting that restoring or accelerating mitophagy flux may be a useful strategy to reduce cardiac injury caused by diabetes.
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- 2020
30. Autoantibody profiling identifies predictive biomarkers of response to anti-PD1 therapy in cancer patients
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Yutao Liu, Dan Wang, Shiyu Jiang, Yu Zhou, Puyuan Xing, Qiaoyun Tan, Shasha Wang, Jianliang Yang, Fengyi Zhao, Haoyu Wang, Yan Qin, Xiaobo Yu, Sheng Yang, Yanrong Wang, Di Wu, Yang Li, Shengyu Zhou, Te Liang, Qiaofeng Zhong, Hu Duan, Xiaohui He, Xiaohong Han, Zhishang Zhang, Jiarui Yao, Yan Sun, Jiayu Dai, and Yuankai Shi
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Oncology ,medicine.medical_specialty ,Lymphoma ,Programmed Cell Death 1 Receptor ,Protein Array Analysis ,Medicine (miscellaneous) ,Protein microarray ,Enzyme-Linked Immunosorbent Assay ,Serology ,Cohort Studies ,Autoantibody ,Antigen ,Internal medicine ,Carcinoma, Non-Small-Cell Lung ,Neoplasms ,Alveolar soft part sarcoma ,medicine ,Biomarkers, Tumor ,Humans ,Lung cancer ,Pharmacology, Toxicology and Pharmaceutics (miscellaneous) ,Autoantibodies ,Anti-PD1 therapy ,business.industry ,Area under the curve ,Biomarker ,medicine.disease ,Sarcoma, Alveolar Soft Part ,Treatment Outcome ,Biomarker (medicine) ,business ,Research Paper - Abstract
Background: Programmed cell death protein 1 (PD1) inhibitors have revolutionized cancer therapy, yet many patients fail to respond. Thus, the identification of accurate predictive biomarkers of therapy response will improve the clinical benefit of anti-PD1 therapy. Method: We assessed the baseline serological autoantibody (AAb) profile against ~2300 proteins in 10 samples and ~4600 proteins in 35 samples with alveolar soft part sarcoma (ASPS), non-small-cell lung cancer (NSCLC) and lymphoma using Nucleic Acid Programmable Protein Arrays (NAPPA). 23 selected potential AAb biomarkers were verified using simple, affordable and rapid enzyme linked immune sorbent assay (ELISA) technology with baseline plasma samples from 12 ASPS, 16 NSCLC and 46 lymphoma patients. SIX2 and EIF4E2 AAbs were further validated in independent cohorts of 17 NSCLC and 43 lymphoma patients, respectively, using ELISA. The IgG subtypes in response to therapy were also investigated. Results: Distinct AAb profiles between ASPS, NSCLC and lymphoma were observed. In ASPS, the production of P53 and PD1 AAbs were significantly increased in non-responders (p=0.037). In NSCLC, the SIX2 AAb was predictive of response with area under the curve (AUC) of 0.87, 0.85 and 0.90 at 3 months, 4.5 months, 6 months evaluation time points, respectively. In the validation cohort, the SIX2 AAb was consistently up-regulated in non-responders (p=0.024). For lymphoma, the EIF4E2 AAb correlated with a favorable response with AUCs of 0.68, 0.70, and 0.70 at 3 months, 4.5 months, and 6 months, respectively. In the validation cohort, the AUCs were 0.74, 0.75 and 0.66 at 3 months, 4.5 months, and 6 months, respectively. The PD1 and PD-L1 IgG2 AAbs were highly produced in ~20% of lymphoma responders. Furthermore, bioinformatics analysis revealed antigen functions of these AAb biomarkers. Conclusion: This study provides the first evidence that AAb biomarkers selected using high-throughput protein microarrays can predict anti-PD1 therapeutic response and guide anti-PD1 therapy.
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- 2020
31. Correction to Nanoscale TiO2 Protection Layer Enhances the Built-In Field and Charge Separation Performance of GaP Photoelectrodes
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Zihao Xu, Bingya Hou, Fengyi Zhao, Zhi Cai, Yawei Liu, Craig L. Hill, Djamaladdin G Musaev, Matthew Mecklenburg, Stephen B. Cronin, and Tianquan Lian
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Mechanical Engineering ,General Materials Science ,Bioengineering ,General Chemistry ,Condensed Matter Physics - Published
- 2022
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32. Efficacy and Safety of PD-1 Inhibitor Plus Rituximab in Patients with Relapsed or Refractory Diffuse Large B-Cell Lymphoma
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Yan Qin, Xiaohui He, Sheng Yang, Peng Liu, Shengyu Zhou, Jianliang Yang, Lin Gui, Qiaofeng Zhong, Fengyi Zhao, Yuankai Shi, Hongmei Jing, Shiyue Zhang, and Ruihan Guo
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Immunology ,Cell Biology ,Hematology ,Biochemistry - Abstract
Background: Patients with relapsed or refractory diffuse large B-cell lymphoma (r/r DLBCL) who are ineligible for or progressed from autologous stem-cell transplantation have poor outcomes and few treatment options. Programmed cell death-1 (PD-1) inhibitor monotherapy has limited efficacy in pretreated DLBCL. Previous study has demonstrated that pembrolizumab plus R-CHOP was effective and safe as first-line treatment in patients with DLBCL and in vitro data suggests that rituximab acts partly via antibody-dependent cellular cytotoxicity, which may be enhanced by programmed cell death-1 (PD-1) blockade. Here, we report the preliminary results of a real-world, single-arm study investigating efficacy and safety of PD-1 inhibitor plus rituximab for r/r DLBCL. Methods: This is a real-world, single-center, single-arm study enrolling patients who received at least one dose of PD-1 inhibitor combined with rituximab as salvage therapeutic regimen after R-CHOP treatment in Cancer Hospital, Chinese Academy of Medical Science & Peking Union Medical College. Eligible patients received PD-inhibitors in combination with rituximab (375 mg/m2, q3w) for 6 cycles followed by maintenance therapy of PD-1 inhibitors plus rituximab (q8w) for 6 cycles until unacceptable toxicity, disease progression, death, or completion of 2-year treatment. The outcomes included objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS) and safety. Responses were assessed by Lugano 2014 criteria, and PD-L1 staining (22C3) was performed at a validated central laboratory. Genomic analysis was performed including next generation sequencing (NGS) based sequence variant detection, copy number analysis and structural variant detection. Results: Between Oct 16, 2018, and May 10, 2021, 34 patients were enrolled and received at least one dose of both PD-1 inhibitor including toripalimab (n=24), pembrolizumab (n=3), nivolumab (n=3) and sintilimab (n=4), combined with rituximab. Key baseline characteristics included median age 56.5 (range 20-78) years; stage III/IV disease 58.8%; elevated LDH 41.2%; IPI ≥3 47.1%; median number of prior treatment regimen 2 (range 1-4); primary chemotherapy-refractory disease after R-CHOP 73.5%; median interval from last rituximab administration 5 (range 0.7-26) months. Histology included 30 DLBCL NOS (88.2%; 11 GCB, 19 non-GCB by Han's algorithm), 4 primary mediastinal B-cell lymphoma (PMBCL; 11.8%). Patients received a median of four (range 1-24) doses of PD-1 inhibitor and rituximab. Eight patients (6 DLBCL-NOS, 2 PMBCL) remained on treatment at the time of data cutoff on Jul 5, 2021. With a median follow-up of 21.3 months (95% CI: 9.6-24.2), 16 (53.3%; 95% CI: 34.3%-71.7%) of 30 patients with DLBCL-NOS had an objective response, with 2 (6.7%) having a complete response and 14 (46.7%) achieving a partial response. The median DOR was 16.8 (95%CI: 2.8-NR) months. The median PFS was 2.9 (95%CI: 1.5-18.5) months, and median OS was 25.3 (95%CI: 9.9-NR) months. The 1-year PFS and OS rates were 34.1% (95%CI: 17.3%-51.8%) and 73.6% (95%CI: 49.8%-87.4%), respectively. All of 4 PMBCL cases achieved CR, and their PFS were 21.2, 21.6, 22.9 and 29.2 months, respectively. Overall, 19 of 34 patients had available baseline biopsy samples for NGS analysis. Patients with TET2 mutations had higher ORR (100% versus 31.3%, p=0.058) and longer PFS (NR versus 1.6 months, p=0.019) while patients with β2-MG mutations had lower ORR (0% versus 53.3%, p=0.1) and shorter PFS (1.0 versus 2.8 months, p=0.0025). In addition, patients with BCL2 alteration/amplification/rearrangement had inferior OS than those BCL2 wild-type patients (5.0 versus 17.4 months, p=0.024). PD-L1 expression at baseline had no impact on response and survival. Most treatment-related adverse events were grade 1-2 including rash and neutropenia. Treatment was discontinued in 3 patients (2 interstitial pneumonia and 1 hypophysitis). Conclusion: PD-1 inhibitor combined with rituximab was effective and well tolerated in r/r DLBCL, achieving promising ORR and long-term remission. Further investigation is warranted. Disclosures No relevant conflicts of interest to declare.
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- 2021
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33. Direct Observation of Surface Hole Accumulation Under Water Oxidation Conditions By Efish and Impedance Measurements
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Fengyi Zhao, Zihao Xu, and Tianquan Lian
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Surface (mathematics) ,Materials science ,Direct observation ,Analytical chemistry ,Underwater ,Electrical impedance - Published
- 2021
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34. Boron- and nitrogen-doped photoluminescent polymer carbon nanoparticles as nanosensors for imaging detection of Cu2+ and biothiols in living cells
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Huihua Min, Chaobo Huang, Yingchun Miao, Li Xu, Buhong Gao, and Fengyi Zhao
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chemistry.chemical_classification ,Biocompatibility ,General Chemical Engineering ,Inorganic chemistry ,Nanoparticle ,chemistry.chemical_element ,Nanoprobe ,02 engineering and technology ,General Chemistry ,Polymer ,010402 general chemistry ,021001 nanoscience & nanotechnology ,Photochemistry ,01 natural sciences ,Fluorescence ,0104 chemical sciences ,chemistry.chemical_compound ,chemistry ,Chelation ,Phenylboronic acid ,0210 nano-technology ,Boron - Abstract
Boron and nitrogen co-doped polymer carbon nanoparticles (BNPCNPs) were synthesized by a facile hydrothermal treatment using uric acid as a nitrogen source, and phenylboronic acid as a boron source for the first time. The nanoparticles with sizes in the range of 90 to 180 nm show excellent and stable fluorescence properties. Moreover, these BNPCNPs showed highly efficient fluorescence quenching ability in the presence of copper (Cu2+) ions due to the formed nonfluorescent metal complexes via robust Cu2+–O or Cu2+–N interactions with the O and N of fluorescent BNPCNPs, which allowed the analysis of Cu2+ ions in the range of 0.0033 to 80 μM. Besides Cu2+ sensing, when biothiols were added, the quenched BNPCNPs-Cu2+ system could be regained via the effective coordination/chelation interactions between Cu2+ ions and the plentiful mercapto and amino groups of biothiols. In the light of this theory, simple biothiol sensors were fabricated without complicated, costly and time-consuming operations. The linear range and the limit of detection of the BNPCNPs-Cu2+ system were 0.0078–80 μM and 2.1 nM for Lcy, 0.0085–85 μM and 2.7 nM for Hcy, and 0.013–89 μM and 4.2 nM for GSH, respectively. Especially, the nanoprobe exhibits good cell membrane permeability and excellent biocompatibility by HeLa cells assay, which is favorable for bioimaging applications. So this BNPCNPs probe can be further used for imaging of biothiols in living cells.
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- 2017
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35. A g-C3N4/WO3 photoanode with exceptional ability for photoelectrochemical water splitting
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Lei Luo, Yongchao Huang, Fengyi Zhao, Haibo Li, Hongbing Ji, Yexiang Tong, Jincheng Zhang, and Xujing Xiao
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Photocurrent ,Materials science ,business.industry ,Heterojunction ,02 engineering and technology ,010402 general chemistry ,021001 nanoscience & nanotechnology ,01 natural sciences ,0104 chemical sciences ,Materials Chemistry ,Optoelectronics ,Water splitting ,General Materials Science ,0210 nano-technology ,business - Abstract
Herein, we report a photoanode of g-C3N4/WO3 heterojunctions with exceptional ability and stability for photoelectrochemical (PEC) water splitting which achieved a high photocurrent density of 1.92 mA cm−2 at +1.23 V versus (vs.) RHE which is about 2 times higher than that of the pristine WO3 photoanode (0.71 mA cm−2).
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- 2017
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36. The proportion of peripheral blood Tregs among the CD4+ T cells of autoimmune thyroid disease patients: a meta-analysis
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Fengyi Zhao, Bingyin Shi, Meng Zhang, Xi Ding, Ziyi Chen, Yue Wang, Yang Zhao, Mingqian He, Shiqian Hu, Baosong Xie, and Jingya Wang
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CD4-Positive T-Lymphocytes ,Endocrinology, Diabetes and Metabolism ,Graves' disease ,T cell ,Thyroid Gland ,030209 endocrinology & metabolism ,T-Lymphocytes, Regulatory ,Thyroiditis ,Immune tolerance ,03 medical and health sciences ,0302 clinical medicine ,Endocrinology ,Antigen ,medicine ,Humans ,Cluster of differentiation ,business.industry ,Thyroid ,Thyroiditis, Autoimmune ,FOXP3 ,medicine.disease ,Graves Disease ,medicine.anatomical_structure ,030220 oncology & carcinogenesis ,Immunology ,business - Abstract
Autoimmune thyroid disease (AITD) is characterized by a loss of self-tolerance to thyroid antigen. Tregs, whose proportions are controversial among CD4+ T cell from AITD patients (AITDs), are crucial in immune tolerance. Considering that drugs might affect Treg levels, we assumed that the differences originated from different treatment statuses. Thus, we performed a meta-analysis to explore proportions of Tregs in untreated and treated AITDs. PubMed, Embase and ISI Web of Knowledge were searched for relevant studies. Review Manager 5.3 and Stata 14.0 were used to conduct the meta-analysis. Subgroup analysis based on different diseases and cell surface markers was performed. Egger linear regression analysis was used to assess publication bias. Approximately 1,100 AITDs and healthy controls (HCs) from fourteen studies were included. Proportions of Tregs among CD4+ T cells of untreated AITDs were significantly lower than those in HCs (p = 0.002), but were not in treated patients (p = 0.40). Subgroup analysis revealed lower proportions of Tregs in untreated Graves' disease patients (GDs) (p = 0.001) but did not show obvious differences in untreated Hashimoto's thyroiditis patients (HTs) (p = 0.62). Furthermore, proportions of circulating FoxP3+ Tregs were reduced in untreated GDs (p < 0.00001) and HTs (p = 0.04). No publication bias was found. In this first meta-analysis exploring proportions of circulating Tregs among CD4+ T cells of AITDs with different treatment statuses, we found that Tregs potentially contribute to the pathogenesis of AITD but function differently in GD and HT. Remarkably, FoxP3+ Tregs, which were decreased in both diseases, might be promising targets for novel therapies.
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- 2019
37. Hyperglycemia-induced cardiomyocyte death is mediated by lysosomal membrane injury and aberrant expression of cathepsin D
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Yuan Huang, Mariko Hagiwara, Cairong Li, Tamayo Kobayashi, Satoru Kobayashi, Amanda Kaminaris, Qiangrong Liang, Fengyi Zhao, and Fei Cai
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0301 basic medicine ,Programmed cell death ,Biophysics ,Cardiomyopathy ,Cathepsin D ,Biochemistry ,Article ,Rats, Sprague-Dawley ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,Lysosome ,medicine ,Animals ,Humans ,Myocytes, Cardiac ,RNA, Small Interfering ,Molecular Biology ,Cells, Cultured ,chemistry.chemical_classification ,Gene knockdown ,Cell Death ,Cell Biology ,Hydrogen-Ion Concentration ,medicine.disease ,Cell biology ,Rats ,030104 developmental biology ,Lysosomal lumen ,medicine.anatomical_structure ,Enzyme ,chemistry ,Microscopy, Fluorescence ,030220 oncology & carcinogenesis ,Hyperglycemia ,Lysosomes ,Pepstatin - Abstract
Hyperglycemia is an independent risk factor for diabetic heart failure. However, the mechanisms that mediate hyperglycemia-induced cardiac damage remain poorly understood. Previous studies have shown an association between lysosomal dysfunction and diabetic heart injury. The present study examined if mimicking hyperglycemia in cultured cardiomyocytes could induce lysosomal membrane permeabilization (LMP), leading to the release of lysosome enzymes and subsequent cell death. High glucose (HG) reduced the number of lysosomes with acidic pH as shown by a fluorescent pH indicator. Also, HG induced lysosomal membrane injury as shown by an accumulation of Galectin3-RFP puncta, which was accompanied by the leakage of cathepsin D (CTSD), an aspartic protease that normally resides within the lysosomal lumen. Furthermore, CTSD expression was increased in HG-cultured cardiomyocytes and in the hearts of 2 mouse models of type 1 diabetes. Either CTSD knockdown with siRNA or inhibition of CTSD activity by pepstatin A markedly diminished HG-induced cardiomyocyte death, while CTSD overexpression exaggerated HG-induced cell death. Together, these results suggested that HG increased CTSD expression, induced LMP and triggered CTSD release from the lysosomes, which collectively contributed to HG-induced cardiomyocyte injury.
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- 2019
38. Abstract 265: Thyrotoxic Pericarditis in a Mouse Model of Graves' Disease
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Liping Wu, Fengyi Zhao, and Bingyin Shi
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Pathology ,medicine.medical_specialty ,Physiology ,business.industry ,Hyperthyroid heart disease ,Graves' disease ,Disease ,medicine.disease ,Muscle hypertrophy ,Pericarditis ,Fibrosis ,medicine ,Cardiology and Cardiovascular Medicine ,business ,Pathological - Abstract
Objectives: To investigate the cardiac pathological changes of hyperthyroid heart disease in mice. Methods: A transient model for human Graves’ disease was successfully established in mice using three immunizations with recombinant adenovirus expressing the extracellular A subunit of the human thyrotropin receptor (Ad-TSHR). We induced the hyperthyroid heart mouse model by prolonging the regular injections of Graves’ disease mouse model to nine months. Heart tissues were weighed and stained with hematoxylin-eosin (HE) and MASSON Trichrome staining to check and define the pathological changes. Results: We observed that mice in the Graves’ disease hyperthyroid heart group (GH) showed enhanced cardiac hypertrophy and fibrosis. The HW/BW (ratio of heart weight to body weight) of GH group (5.528±0.4014, n=6) was significantly higher than control group (4.343±0.03913, n=6) (P Conclusions: Pericarditis as a complication of thyrotoxicosis has been reported several times in clinical work. This is the first reported case of pericarditis in the mouse model of Graves’ disease, suggesting a possible link between pericarditis and thyrotoxicosis.
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- 2019
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39. A highly sensitive and selective fluorescent sensor for detection of copper ions based on natural Isorhamnetin from Ginkgo leaves
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Cao Fuliang, Xu Yuanyuan, Ying Tang, Shilong Yang, Fengyi Zhao, Haijun Sun, Li Xu, Weina Jiang, Buhong Gao, and Liting Du
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Detection limit ,Quenching (fluorescence) ,Chemistry ,010401 analytical chemistry ,Metals and Alloys ,Analytical chemistry ,chemistry.chemical_element ,02 engineering and technology ,Buffer solution ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,01 natural sciences ,Binding constant ,Copper ,Fluorescence ,0104 chemical sciences ,Surfaces, Coatings and Films ,Electronic, Optical and Magnetic Materials ,chemistry.chemical_compound ,Linear range ,Materials Chemistry ,Electrical and Electronic Engineering ,0210 nano-technology ,Instrumentation ,Isorhamnetin - Abstract
A natural isorhamnetin-based fluorescent sensor for highly sensitive and selective detection of copper ions had been studied. The fluorescent sensor isorhamnetin (Iso) after binding to Cu 2+ ions in pH 7.40 buffer solution generated quenching in fluorescent emission intensity. The binding constant value was obtained 1.79 × 10 6 . The sensor Iso can be applied to the quantification of Cu 2+ ion with a linear range of 1.0 × 10 −8 –1.9 × 10 −6 mol L −1 , the detection limit of 4.0 × 10 −9 mol L −1 , and the reproducibility of the sensor is good. The sensor showed high selectivity toward Cu 2+ . As a result, the isorhamnetin fluorescent sensor was successfully applied for determination of Cu 2+ in rivers, lakes, vegetables and fruits with good recovery.
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- 2016
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40. Defect Engineering of Bismuth Oxyiodide by IO3– Doping for Increasing Charge Transport in Photocatalysis
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Fengyi Zhao, Hongbing Ji, Yongchao Huang, Yexiang Tong, Weitao Qiu, Wenjie Fan, and Haibo Li
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Materials science ,Doping ,Inorganic chemistry ,Defect engineering ,chemistry.chemical_element ,02 engineering and technology ,010402 general chemistry ,021001 nanoscience & nanotechnology ,01 natural sciences ,Oxygen ,0104 chemical sciences ,Bismuth ,chemistry.chemical_compound ,chemistry ,Chemical engineering ,Methyl orange ,Photocatalysis ,Degradation (geology) ,General Materials Science ,Charge carrier ,0210 nano-technology - Abstract
Defect engineering is regarded as one of the most active projects to monitor the chemical and physical properties of materials, which is expected to increase the photocatalytic activities of the materials. Herein, oxygen vacancies and IO3– doping are introduced into BiOI nanosheets via adding NaH2PO2, which can impact the charge carrier dynamics of BiOI photocatalysts, such as its excitation, separation, trap, and transfer. These oxygen-deficient BiOI nanosheets display attractive photocatalytic activities of gaseous formaldehyde degradation and methyl orange under visible light irradiation, which are 5 and 3.5 times higher than the BiOI samples, respectively. Moreover, the comodified BiOI also displayed superior cycling stability and can be used for practical application. This work not only develops an effective strategy for fabricating oxygen vacancies but also offers deep insight into the impact of surface defects in enhancing photocatalysis.
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- 2016
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41. A highly durable catalyst based on Co x Mn3–x O4 nanosheets for low-temperature formaldehyde oxidation
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Fengyi Zhao, Yongchao Huang, Yuanming Zhang, Kaihang Ye, Hongbing Ji, Wenjie Fan, and Haibo Li
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Materials science ,Inorganic chemistry ,Formaldehyde ,chemistry.chemical_element ,02 engineering and technology ,Manganese ,010402 general chemistry ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,01 natural sciences ,Redox ,Atomic and Molecular Physics, and Optics ,0104 chemical sciences ,Catalysis ,chemistry.chemical_compound ,chemistry ,Catalytic oxidation ,General Materials Science ,Electrical and Electronic Engineering ,0210 nano-technology ,Cobalt oxide ,Carbon ,Nanosheet - Abstract
Cost-effective catalysts for the oxidation of volatile organic compounds (VOCs) are critical to energy conversion applications and environmental protection. The main bottleneck of this process is the development of an efficient, stable, and cost-effective catalyst that can oxidize HCHO at low temperature. Here, an advanced material consisting of manganese cobalt oxide nanosheet arrays uniformly covered on a carbon textile is successfully fabricated by a simple anodic electrodeposition method combined with post annealing treatment, and can be directly applied as a high-performance catalytic material for HCHO elimination. Benefiting from the increased surface oxygen species and improved redox properties, the as-prepared manganese cobalt oxide nanosheets showed substantially higher catalytic activity for HCHO oxidation. The catalyst completely converted HCHO to CO2 at temperatures as low as 100 °C, and exhibited excellent catalytic stability. Such impressive results are rarely achieved by non-precious metal-based catalysts at such low temperatures.
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- 2016
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42. Visible light Bi2S3/Bi2O3/Bi2O2CO3 photocatalyst for effective degradation of organic pollutions
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Yongchao Huang, Yexiang Tong, Hongbing Ji, Fengyi Zhao, Bei Long, Zili Liu, Wenjie Fan, and Haibo Li
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Materials science ,Ion exchange ,Process Chemistry and Technology ,Inorganic chemistry ,Formaldehyde ,02 engineering and technology ,010402 general chemistry ,021001 nanoscience & nanotechnology ,Photochemistry ,01 natural sciences ,Catalysis ,0104 chemical sciences ,chemistry.chemical_compound ,chemistry ,Photocatalysis ,Methyl orange ,Degradation (geology) ,Phenol ,0210 nano-technology ,General Environmental Science ,Visible spectrum - Abstract
Bi2S3/Bi2O3/Bi2O2CO3 photocatalyst was successfully synthesized by combining the rational heat-treatment process and ion exchange technique. These composites exhibited superior photocatalytic activities for organic contaminants (formaldehyde gas, methyl orange and phenol) degradation under the visible light irradiation. These catalysts could eliminate more than 99% of formaldehyde gas within 100 min, which is considerably higher than those of pure Bi2O2CO3 (10.9%) and Bi2O3/Bi2O2CO3 (23.6%) samples at the same condition. Furthermore, these as-prepared Bi2S3/Bi2O3/Bi2O2CO3 composites also show excellent photocatalytic performance for methyl orange and phenol removing as well as good stability. The highly improved performance of the composites can be ascribed to the increased light absorption and efficient charge separation. In addition, the photocatalytic process is mainly governed by the superoxide and the holes rather than the hydroxyl radicals. These features suggest the current heterostructured photocatalysts can be applied in environmental remediation and waste water treatment.
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- 2016
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43. Alkali-modified non-precious metal 3D-NiCo2O4 nanosheets for efficient formaldehyde oxidation at low temperature
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Wenjie Fan, Bei Long, Fengyi Zhao, Hongbing Ji, Yexiang Tong, Weitao Qiu, Yongchao Huang, and Haibo Li
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chemistry.chemical_classification ,Materials science ,Renewable Energy, Sustainability and the Environment ,Inorganic chemistry ,Energy conversion efficiency ,Formaldehyde ,02 engineering and technology ,General Chemistry ,010402 general chemistry ,021001 nanoscience & nanotechnology ,Alkali metal ,01 natural sciences ,0104 chemical sciences ,Catalysis ,Metal ,chemistry.chemical_compound ,Adsorption ,chemistry ,visual_art ,visual_art.visual_art_medium ,General Materials Science ,Volatile organic compound ,0210 nano-technology ,Nanosheet - Abstract
Cost-effective catalysts for volatile organic compound (VOC) oxidation are critical to energy conversion and environmental protection. Herein, we developed new, low-cost and high-performance alkali-promoted 3D-NiCo2O4 nanosheet catalysts for HCHO oxidation at room temperature. Benefiting from the large surface area, high adsorption capacity and surface hydroxyls, the alkali-promoted 3D-NiCo2O4 nanosheet catalysts show substantially high catalytic activities for HCHO oxidation. The alkali-promoted 3D-NiCo2O4 nanosheets yield a remarkable HCHO conversion efficiency of 95.3% at room temperature, which is not achieved by any non-precious metal based catalysts at such low temperature. Additionally, the as-prepared alkali-promoted 3D-NiCo2O4 nanosheets retained excellent catalytic performance after 200 h, which can be applied to practical applications. This work provides a feasible approach to improve the efficiency of metal oxides for HCHO oxidation at low temperature.
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- 2016
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44. Role of Selenium Intake for Risk and Development of Hyperthyroidism
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Mingqian He, Yue Wang, Eddy Rijntjes, Jing Sui, Peng Hou, Qian Wu, Pu Chen, Shiqian Hu, Fengyi Zhao, Lutz Schomburg, Yufeng Liu, Meng Zhang, Liping Wu, and Bingyin Shi
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0301 basic medicine ,Male ,medicine.medical_specialty ,China ,Thyroid Hormones ,Endocrinology, Diabetes and Metabolism ,Graves' disease ,Clinical Biochemistry ,Thyroid Gland ,030209 endocrinology & metabolism ,Biochemistry ,Hyperthyroidism ,03 medical and health sciences ,Mice ,Selenium ,0302 clinical medicine ,Endocrinology ,Immune system ,Sex Factors ,Risk Factors ,Internal medicine ,medicine ,Prevalence ,Animals ,Humans ,Risk factor ,Dose-Response Relationship, Drug ,business.industry ,Thyroid disease ,Incidence ,Biochemistry (medical) ,Thyroid ,Autoantibody ,medicine.disease ,Disease Models, Animal ,030104 developmental biology ,medicine.anatomical_structure ,Cross-Sectional Studies ,Dietary Supplements ,Erythropoiesis ,Female ,business ,Hormone - Abstract
Purpose To investigate the importance of dietary selenium (Se) for hyperthyroidism. Methods We performed a more in-depth analysis of a large cross-sectional study of 6152 participants from two counties within the Shaanxi Province, China. These counties are characterized by different habitual Se intake. We investigated the effects of a different dietary Se supply (0.02, 0.18, 0.6, or 2.0 ppm Se) on disease development in a mouse model of Graves disease (GD). Results The cross-sectional study revealed a comparable prevalence of hyperthyroidism, irrespective of Se intake, in both counties. However, an unexpected sex-specific difference was noted, and Se deficiency might constitute a risk factor for hyperthyroidism, especially in males. In a mouse model, pathological thyroid morphology was affected, and greater Se intake exerted some protecting effects on the pathological distortion. Circulating thyroid hormone levels, malondialdehyde concentrations, total antioxidant capacity, and the titer of GD-causing TSH receptor autoantibodies were not affected by Se. Expression analysis of the transcripts in the spleen indicated regulatory effects on genes implicated in the immune response, erythropoiesis, and oxygen status. However, the humoral immune response, including the CD4/CD8 or T-helper 1/T-helper 2 cell ratio and the concentration of regulatory T cells, was similar between the experimental groups, despite the difference in Se intake. Conclusions Our data have highlighted a sexual dimorphism for the interaction of Se and thyroid disease risk in humans, with indications of a local protective effects of Se on thyroid gland integrity, which appears not to be reflected in the circulating biomarkers tested.
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- 2018
45. Metformin Activates AMPK Signaling but Inhibits Mitophagy in the Mouse Heart
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Michael M. Chang, Qiangrong Liang, Satoru Kobayashi, Yawen Zhang, Tamayo Kobayashi, Yuan Huang, Polina R. Pinkhasova, and Fengyi Zhao
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endocrine system diseases ,medicine.diagnostic_test ,Chemistry ,Endocrinology, Diabetes and Metabolism ,Autophagy ,Alpha (ethology) ,AMPK ,Mitochondrion ,Pharmacology ,Metformin ,Western blot ,Mitophagy ,Internal Medicine ,medicine ,Phosphorylation ,medicine.drug - Abstract
Metformin, a commonly prescribed first-line drug for the treatment of type 2 diabetes mellitus, has been shown to reduce cardiac injury under diabetic and other pathological conditions. However, the mechanisms that mediate the cardioprotective effects of metformin remain controversial. One prevailing hypothesis suggests that metformin activates AMPK-autophagy pathway which eliminates protein aggregates and damaged mitochondria, thus protecting the heart from injury. In the present study, we tested this hypothesis using both in vivo and in vitro models. FVB/N mice were administered 200 mg/kg of metformin through gavage once a day for two days. As expected, metformin activated AMPK signaling in the heart as shown by the increased phosphorylation of AMPK alpha at Thr172 and its downstream effecter Acetyl-CoA Carboxylase at Ser79. Autophagy and mitophagy were determined by Western blot analysis of LC3-II, a well-established marker of autophagic vesicles. Surprisingly, however, metformin did not affect LC3-II levels in total tissue lysates and significantly reduced LC3-II in mitochondrial fractions, suggesting that metformin actually inhibited rather stimulated mitophagy, contrary to the current belief. This was confirmed by measuring mitophagy flux using lysosomal inhibitors pepstatin A and E64d. The ability of metformin to inhibit mitophagy was also corroborated by a novel dual fluorescent mitophagy reporter showing reduced degradation rate of mitochondria in the lysosomes. All these results were reproduced in H9c2 rat cardiac myoblast cells. Collectively, our results show that metformin is able to activate AMPK signaling but paradoxically inhibits mitophagy in the heart, suggesting that the cardioprotective benefit of metformin observed in many different models may be mediated through mechanisms other than autophagy and mitophagy. Future studies will explore the mechanisms by which metformin inhibits mitophagy and protects the heart. Disclosure Y. Zhang: None. M.M. Chang: None. P.R. Pinkhasova: None. F. Zhao: None. T. Kobayashi: None. Y. Huang: None. S. Kobayashi: None. Q. Liang: None.
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- 2018
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46. Carbon Dots Sensitized BiOI with Dominant {001} Facets for Superior Photocatalytic Performance
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Fengyi Zhao, Bei Long, Haibo Li, Zili Liu, Yongchao Huang, Yexiang Tong, Zebao Rui, and Hongbing Ji
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Materials science ,business.industry ,General Chemical Engineering ,Visible light irradiation ,chemistry.chemical_element ,General Chemistry ,Photochemistry ,Industrial and Manufacturing Engineering ,chemistry.chemical_compound ,Semiconductor ,chemistry ,Photocatalysis ,Methyl orange ,Degradation (geology) ,business ,Absorption (electromagnetic radiation) ,Photocatalytic degradation ,Carbon - Abstract
Degrading and removing harmful compounds by the use of semiconductor photocatalysts has been testified to be and effective and attractive green technique in wastewater treatment. Herein, carbon dots sensitized BiOI with highly exposed {001} facets has been prepared and used to study the photocatalytic degradation of methyl orange (MO). Due to the improved charge separation, transfer, and optical absorption, the photocatalytic performance for methyl orange degradation of the carbon dots/{001} BiOI nanosheets is 4 times higher than that of the {001} BiOI nanosheets under visible light irradiation. Additionally, the carbon dots/{001} BiOI nanosheets also have superior stability after 5 cyclings.
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- 2015
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47. The Impact of China 's Economic Growth on Carbon Emission Based on Gray Relational Analysis
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Fengyi Zhao and Jianna Zhao
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chemistry ,Economics ,chemistry.chemical_element ,Gray relational analysis ,Economic geography ,China ,Grey relational analysis ,Carbon - Published
- 2017
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48. Characterization of Methylation Patterns in Diffuse Large B Cell Lymphoma By Genome-Wide Methylation Analysis
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Shiyu Jiang, Lei Zhang, Yan Qin, Yuankai Shi, Fengyi Zhao, Xiaohong Han, and Mingzhe Han
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Immunology ,Cell Biology ,Hematology ,Methylation ,Biology ,medicine.disease ,Biochemistry ,Gene expression profiling ,chemistry.chemical_compound ,CpG site ,Cell-free fetal DNA ,chemistry ,DNA methylation ,Cancer research ,medicine ,KEGG ,Diffuse large B-cell lymphoma ,DNA - Abstract
Background: Diffuse large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma worldwide. Although the reference standard for identifying of the cell types is considered of gene expression profiling (GEP). But immunohistochemistry (IHC) is the most common method commercially available. The purpose of this study was to characterize the circulating cell-free DNA (cfDNA) methylation profile in DLBCL and to compare this profile with methylation observed in formalin fixed paraffin-embedded (FFPE) tissues. Additional efforts were made to correlate the observed methylation patterns with prognostic analysis and selected clinical features. Methods: The cfDNA and DNA of FFPE were extracted from 72 patients and 39 patients respectively. We assessed DNA methylation from plasma samples obtained from 29 individuals with GCB DLBCL at the time before treatment along with 43 samples of non-GCB DLBCL as controls. DNA from FFPE tissues were extracted from 11 individuals of GCB DLBCL and 28 individuals with non-GCB DLBCL. DNA methylation was analyzed with the Infinium MethylationEPIC BeadChip that quantitatively measures the methylation levels of more than 850,000 CpG sites across the genome. M values were used for visualization and intuitive interpretation of the results. Moreover, pathway enrichment analysis was performed with the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database. Results: We found a total of 207 significant differentional differentially methylated positions (DMPs) of cfDNA between the GCB and non-GCB groups, identified with a p value of 0.001 (Fig. 1A). Of these, 65 presented at least 10% (|Δbeta| > 0.1) difference in the methylation level between GCB and non-GCB. 29 (44.6%) were found hypermethylated in GCB DLBCL, while 36 (55.4%) appeared hypomethylated (Fig. 1B). The distribution of the DMPs identified according to their location relative to CpG islands (CGI) were represented in Fig. 1C. Unsupervised clustering performed on DNA methylation values for the 207 DMPs identified is presented in Fig. 1D. These results highlight the differences between GCB and non-GCB samples. There are 1549 significant DMPs of DNA from FFPE between the GCB and non-GCB groups, identified with a p value of 0.001 (Fig. 1E). Of these, 1512 presented at least 10% (|Δbeta| > 0.1) difference in the methylation level between GCB and non-GCB . 1370 (90.6%) were found hypermethylated in GCB DLBCL, while 142 (9.4%) appeared hypomethylated (Fig. 1F). The distribution of the DMPs identified according to their location relative to CpG islands (CGI) were represented in Fig. 1G. Unsupervised clustering performed on DNA methylation values for the 1549 DMPs identified is presented in Fig. 1H. These results highlight the differences between GCB and non-GCB in FFPE samples which according with that in serum. The KEGG pathway enrichment analysis of DNA from FFPE tissue methylation revealed that the process "PI3K/Akt, Ras, MAPK signaling pathway" and "Human papillomavirus infection" are likely major contributors to Hans pathological type. In addition, the enrichment analysis of cfDNA methylation revealed that the process "MAPK signaling pathway" is likely the most important factor. Furthermore, we also have analyzed the methylation level between refractory or relapsed (R/R) DLBCL patients and individuals with a good prognosis. The differential methylation patterns were also found both in serums and FFPE tissues. Conclusions: The DNA methylation differs in GCB and non-GCB DLBCL patients. MAPK signaling pathway plays an important role in it. The mechanism needs to be further explored. Figure 1 Disclosures No relevant conflicts of interest to declare.
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- 2019
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49. Charge Separation Enhancement Mechanism By p-n Junction in Water Reduction Electrode
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Zihao Xu, Bingya Hou, Fengyi Zhao, Stephen B. Cronin, and Tianquan Lian
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Solar water splitting overall efficiency largely depends on the photoanode/photocathode charge carrier separation efficiency. Understanding the competition between charge separation and charge recombination is crucial to improve the device efficiency. In this study first we discussed the challenges in studying such process with femtosecond transient spectroscopy. Then we demonstrated a feasible method by combining transient reflectance (TR) spectroscopy and in situ electrochemical measurement to provide critical information on charge carrier separation efficiency and IPCE on a water/CO2 reduction photoanode, p-type gallium phosphate with protective titanium dioxide (TiO2) layer. Enhanced charge separation at the interface of gallium phosphate (GaP, 100) single crystal and TiO2 layer is observed by TR. The separated charge carrier concentration obtained by reflectance change shows strong correlation to the IPCE measured in situ under same condition. Through this correlation we provided direct evidence that the IPCE is heavily determined by the transiently separated charge carriers. This study also provides an applicable and powerful method to study similar HER and OER semiconductor electrode photogenerated charge carrier dynamics at ultrafast time scale.
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- 2019
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50. Defect Engineering of Bismuth Oxyiodide by IO
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Yongchao, Huang, Haibo, Li, Wenjie, Fan, Fengyi, Zhao, Weitao, Qiu, Hongbing, Ji, and Yexiang, Tong
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Defect engineering is regarded as one of the most active projects to monitor the chemical and physical properties of materials, which is expected to increase the photocatalytic activities of the materials. Herein, oxygen vacancies and IO
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- 2016
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