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Shao S, Liao H, Zhou S, Li Y, Yu H, Dai X, Zhu Q, Hua Y, Wang C, Zhou K. Isolated non-immune mediated second-degree atrioventricular block in fetus: natural history and predictive factors for spontaneous recovery. Ultrasound Obstet Gynecol 2024. [PMID: 38642334 DOI: 10.1002/uog.27662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 03/29/2024] [Accepted: 04/03/2024] [Indexed: 04/22/2024]
Abstract
OBJECTIVES To uncover the clinical course of fetal isolated non-immune mediated second-degree AVB and determine the factors associated with the spontaneous recovery for fetal non-immune second-degree atrioventricular block (AVB). METHODS A total of 20 fetuses with isolated, non-immune mediated second-degree AVB were prospectively recruited between 2014 and 2022. These fetuses were divided into the spontaneous recovery group (n=12) and the non-spontaneous recovery group (n=8). Maternal and fetal basic characteristics, intrauterine and postnatal outcomes were compared between groups. RESULTS Twelve fetuses restored 1:1 atrioventricular conduction in utero and did not recur during the postnatal follow-up period. The residual eight fetuses maintained as second-degree AVB and six of them were aborted due to parental request in utero. Of the two live children with second-degree AVB, one of them progressed to complete AVB at the latest follow up at the age of 34 months, but without any symptoms, heart enlargement or dysfunction. The residual one progressed to complete AVB and was finally diagnosed with type 2 long-QT syndrome. Fetuses in the spontaneous recovery group presented with earlier gestational age at diagnosis (20.0[17.0-26.0] vs. 24.5[18.0-35.0] weeks, p=0.004) and higher atrial rate (147[130-160] vs 138.00[125.00-149.00] bpm, p=0.006) in comparison with the non-spontaneous recovery group. A cut-off value of 22.5 weeks of gestational age and 144 bpm of atrial rate at diagnosis could predict the failure of spontaneous recovery, with sensitivities of 87.5%, 75%, and specificities of 92.0%, 87.5%, respectively. CONCLUSIONS The outcome of fetal non-immune second-degree AVB was favorable. Earlier gestational age at diagnosis and higher atrial rate were related to spontaneous reversion for isolated non-immune-mediated second-degree AVB. However, prenatal gene test should be performed for those with persistent AVB to exclude the heritable disorders including LQTS. These findings may provide important references for clinical management and prenatal counseling. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- S Shao
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - H Liao
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - S Zhou
- Department of Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Li
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - H Yu
- Department of Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - X Dai
- Department of Ultrasound, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Q Zhu
- Department of Ultrasound, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Y Hua
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - C Wang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - K Zhou
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
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Dong J, Zhang H, Ai X, Dong Q, Shi X, Zhao X, Zhong C, Yu H. Improving chilling tolerance of peanut seedlings by enhancing antioxidant-modulated ROS scavenging ability, alleviating photosynthetic inhibition, and mobilizing nutrient absorption. Plant Biol (Stuttg) 2024. [PMID: 38597809 DOI: 10.1111/plb.13643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 02/21/2024] [Indexed: 04/11/2024]
Abstract
Peanut production is threatened by climate change. Damage to seedlings from low temperatures in early spring can limit yield. Plant adaptations to chilling stress remain unclear in peanut seedlings. It is essential to understand how peanut acquires chilling tolerance. We evaluated effects of chilling stress on growth and recovery of peanut seedlings. We compared and analysed biological characteristics, antioxidants, photosynthesis, biochemical and physiological responses, and nutrient absorption at varying levels of chilling. Compared with chilling-sensitive FH18, the reduced impact of chilling stress on chilling-tolerant NH5 was associated with reduced ROS accumulation, higher ascorbate peroxidase activity and soluble sugar content, lower soluble protein content, and smaller reductions in nutrient content during stress. After removal of chilling stress, FH18 had significant accumulation of O2 •- and H2O2, which decreased photosynthesis, nutrient absorption, and transport. ROS-scavenging reduced damage from chilling stress, allowed remobilization of nutrients, improved chilling tolerance, and restored plant functioning after chilling stress removal. These findings provide a reference for targeted research on peanut seedling tolerance to chilling and lay the foundation for bioinformatics-based research on peanut chilling tolerance mechanisms.
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Affiliation(s)
- J Dong
- College of Agronomy, Peanut Research Institute, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - H Zhang
- College of Agronomy, Peanut Research Institute, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - X Ai
- College of Agronomy, Peanut Research Institute, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Q Dong
- College of Agronomy, Peanut Research Institute, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - X Shi
- College of Agronomy, Peanut Research Institute, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - X Zhao
- College of Agronomy, Peanut Research Institute, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - C Zhong
- College of Agronomy, Peanut Research Institute, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - H Yu
- College of Agronomy, Peanut Research Institute, Shenyang Agricultural University, Shenyang, Liaoning Province, China
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Chen K, Yu H, Zhu LM, Liu Q, Wang B. [Spatial-temporal distribution characteristics of etiologically positive pulmonary tuberculosis in Jiangsu Province from 2011 to 2021]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:513-519. [PMID: 38678346 DOI: 10.3760/cma.j.cn112338-20230915-00161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/29/2024]
Abstract
Objective: To analyze the spatial-temporal distribution of etiologically positive pulmonary tuberculosis (PTB) at the county (city, district) unit in Jiangsu Province from 2011 to 2021 to provide evidence for the implementation and adjustment of prevention and control strategies of PTB in Jiangsu Province. Methods: The registration data of etiologically positive PTB patients in Jiangsu Province from 2011 to 2021 were collected from the Tuberculosis Management Information System in the China Information System of Disease Control and Prevention. Data on the permanent population were from the statistical yearbook of each county (city, district) in Jiangsu Province. Geoda 1.18.0 software was used to analyze the global and local spatial autocorrelation and explore the spatial clustering. SaTScan 10.1 software was used to analyze the spatial-temporal clusters, and ArcGIS 10.7 software was used to visualize the spatial-temporal clusters. Results: A total of 128 240 etiological positive PTB cases were registered in Jiangsu Province from 2011 to 2021, with an average annual registration rate of 13.99/100 000. The registration rate showed an overall upward trend (trend χ2=63.49, P<0.001) after 2017, and the etiologically positive rate showed an overall upward trend (trend χ2=3 710.86, P<0.001). The annual Moran's I values ranged from 0.107 to 0.343, which showed a spatial clustering distribution. The results of local spatial autocorrelation analysis showed that there were "high-high" clustering areas in Jiangsu Province each year, showing a dynamic distribution, and most of the areas were distributed in the central and southern regions of Jiangsu Province, with the largest number (7) in 2015 and the smallest number (1) in 2011. A total of 4 spatial-temporal clustering areas were explored by spatial-temporal scanning analysis (all P<0.001), among which the first-level clustering area covered 3 counties (cities, districts), namely Changshu, Taicang, and Xiangcheng District of Suzhou, and the clustering time was from 2011 to 2015. The secondary clustering areas covered 24 counties (cities, districts), mainly covering Jiangsu's central and northern regions, such as Huai'an, Suqian, and Yancheng. The third-level clustering areas covered 26 counties (cities, districts); the fourth-level clustering area was the Gaochun District of Nanjing, with the clustering period from 2017 to 2021. Conclusions: From 2011 to 2021, the etiologically positive PTB registration rate at the county (city, district) level in Jiangsu Province had obvious spatial-temporal clustering characteristics. The clustering areas included the northern areas with relatively backward economies and the southern areas with better economic development. Multiple measures should be taken to prevent and control PTB according to the specific situation in different regions.
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Affiliation(s)
- K Chen
- School of Public Health, Southeast University, Nanjing 210009, China
| | - H Yu
- Institute for Chronic Infectious Disease Prevention and Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - L M Zhu
- Institute for Chronic Infectious Disease Prevention and Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Q Liu
- Institute for Chronic Infectious Disease Prevention and Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - B Wang
- School of Public Health, Southeast University, Nanjing 210009, China
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Wei XL, Du WC, Wang R, Zhou JY, Yu H, Lu Y, Wang LC, Huang CY. [Epidemic characteristics and trend analysis of major injuries deaths among children and adolescents in Jiangsu Province from 2012 to 2021]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:536-541. [PMID: 38678349 DOI: 10.3760/cma.j.cn112338-20230912-00150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/29/2024]
Abstract
Objective: To understand the situation and epidemic characteristics of injury deaths among children aged 5 to 24 years in Jiangsu Province from 2012 to 2021 and the trend of annual changes. Methods: The main injury mortality data of children and adolescents was collected, and the crude and standardized mortality rates of road traffic accidents, drowning, suicide, and accidental falls among children and adolescents over a decade and the annual average percentage of change (AAPC) were calculated. The main injury mortality characteristics and trends of children and adolescents of different age groups and genders were analyzed. Results: The total number of injury deaths among 5 to 24 adolescents in Jiangsu Province was 16 052, with a standardized mortality rate of 9.58/100 000. There was no significant trend in the overall standardized mortality rate of injuries (AAPC=-3.450%, P=0.055). The standardized mortality rate of road traffic injuries among children and adolescents showed a decreasing trend over the past decade, with statistical significance (AAPC=-9.406%, P<0.001). The standardized suicide mortality rate showed an upward trend over the past decade, with statistical significance (AAPC=9.000%, P=0.001). The overall injury mortality rate showed an upward trend with age. Suicide rates in males and females were on the rise and both have statistical significance (AAPC=9.420% and AAPC=9.607%, both P<0.05). The standardized mortality rates of female traffic accidents, drowning, and male traffic accidents showed a decreasing trend and were statistically significant (AAPC for female traffic accidents=-7.364%, AAPC for female drowning=-5.352%, and AAPC for male traffic accidents=-10.242%, all P<0.05). The standardized mortality rate of urban and rural traffic accidents showed a decreasing trend and was statistically significant(AAPC=-7.899% and AAPC=-9.421%, both P<0.001). The standardized suicide mortality rate showed an upward trend and statistical significance (AAPC=11.009% and AAPC=7.528%, both P<0.05). Conclusions: The overall injury situation of children and adolescents in Jiangsu Province improved in the past decade from 2012 to 2021, but the suicide mortality rate was on the rise. It is necessary to focus on the mental health issues of this age group and to strengthen the prevention and control of suicide among children and adolescents, in Jiangsu.
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Affiliation(s)
- X L Wei
- Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - W C Du
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - R Wang
- School of Public Health, Southeast University, Nanjing 210009, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Y Lu
- Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - L C Wang
- Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - C Y Huang
- Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
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Yang S, Liu D, Song Y, Liang Y, Yu H, Zuo Y. Designing a structure-function alphabet of helix based on reduced amino acid clusters. Arch Biochem Biophys 2024; 754:109942. [PMID: 38387828 DOI: 10.1016/j.abb.2024.109942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/16/2024] [Accepted: 02/19/2024] [Indexed: 02/24/2024]
Abstract
Several simple secondary structures could form complex and diverse functional proteins, meaning that secondary structures may contain a lot of hidden information and are arranged according to certain principles, to carry enough information of functional specificity and diversity. However, these inner information and principles have not been understood systematically. In our study, we designed a structure-function alphabet of helix based on reduced amino acid clusters to describe the typical features of helices and delve into the information. Firstly, we selected 480 typical helices from membrane proteins, zymoproteins, transcription factors, and other proteins to define and calculate the interval range, and the helices are classified in terms of hydrophilicity, charge and length: (1) hydrophobic helix (≤43%), amphiphilic helix (43%∼71%), and hydrophilic helix (≥71%). (2) positive helix, negative helix, electrically neutral helix and uncharged helix. (3) short helix (≤8 aa), medium-length helix (9-28 aa), and long helix (≥29 aa). Then, we designed an alphabet containing 36 triplet codes according to the above classification, so that the main features of each helix can be represented by only three letters. This alphabet not only preliminarily defined the helix characteristics, but also greatly reduced the informational dimension of protein structure. Finally, we present an application example to demonstrate the value of the structure-function alphabet in protein functional determination and differentiation.
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Affiliation(s)
- Siqi Yang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, 010021, China
| | - Dongyang Liu
- Key Laboratory of Photobiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China; University of Chinese Academy of Sciences, Beijing, China
| | - Yancheng Song
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, 010021, China
| | - Yuchao Liang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, 010021, China
| | - Haoyu Yu
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, 010021, China
| | - Yongchun Zuo
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, 010021, China.
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Yang MS, Fan XK, Su J, Wan XL, Yu H, Lu Y, Hua YJ, Jin JR, Pei P, Yu CQ, Sun DJY, Lyu J, Tao R, Zhou JY. [A prospective study on association between sleep duration and the risk of chronic obstructive pulmonary disease in adults in Suzhou]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:331-338. [PMID: 38514308 DOI: 10.3760/cma.j.cn112338-20230918-00164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Objective: To investigate the prospective association of sleep duration with the development of chronic obstructive pulmonary disease (COPD) in adults in Suzhou. Methods: The study used the data of 53 269 participants aged 30-79 years recruited in the baseline survey from 2004 to 2008 and the follow-up until December 31, 2017 of China Kadoorie Biobank (CKB) conducted in Wuzhong District, Suzhou. After excluding participants with airflow limitation, self-reported chronic bronchitis/emphysema/coronary heart disease history at the baseline survey and abnormal or incomplete data, a total of 45 336 participants were included in the final analysis. The association between daily sleep duration and the risk for developing COPD was analyzed by using a Cox proportional hazard regression model, and the hazard ratio (HR) values and their 95%CI were calculated. The analysis was stratified by age, gender and lifestyle factors, and cross-analysis was conducted according to smoking status and daily sleep duration. Results: The median follow-up time was 11.12 years, with a total of 515 COPD diagnoses in the follow-up. After adjusting for potential confounders, multifactorial Cox proportional hazard regression analysis showed that daily sleep duration ≥10 hours was associated with higher risk for developing COPD (HR=1.42, 95%CI: 1.03-1.97). The cross analysis showed that excessive daily sleep duration increased the risk for COPD in smokers (HR=2.49, 95%CI: 1.35-4.59, interaction P<0.001). Conclusion: Longer daily sleep duration (≥10 hours) might increase the risk for COPD in adults in Suzhou, especially in smokers.
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Affiliation(s)
- M S Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - X K Fan
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Su
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - X L Wan
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - H Yu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Y Lu
- Suzhou Prefectural Center for Disease Control and Prevention, Suzhou 215003, China
| | - Y J Hua
- Suzhou Prefectural Center for Disease Control and Prevention, Suzhou 215003, China
| | - J R Jin
- Wuzhong District Center for Disease Control and Prevention of Suzhou, Suzhou 215128, China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - C Q Yu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - D J Y Sun
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - J Lyu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - R Tao
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - J Y Zhou
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China School of Public Health, Nanjing Medical University, Nanjing 211166, China
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Zhou C, Hu Y, Arkania E, Kilickap S, Ying K, Xu F, Wu L, Wang X, Viguro M, Makharadze T, Sun H, Luo F, Shi J, Zang A, Pan Y, Chen Z, Jia Z, Kuchava V, Lu P, Zhang L, Cheng Y, Kang W, Wang Q, Yu H, Li J, Zhu J. A global phase 3 study of serplulimab plus chemotherapy as first-line treatment for advanced squamous non-small-cell lung cancer (ASTRUM-004). Cancer Cell 2024; 42:198-208.e3. [PMID: 38181795 DOI: 10.1016/j.ccell.2023.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 10/27/2023] [Accepted: 12/07/2023] [Indexed: 01/07/2024]
Abstract
Combining immunotherapy with chemotherapy can provide improved survival in advanced squamous non-small-cell lung cancer (NSCLC) patients without targetable gene alterations. 537 previously untreated patients with stage IIIB/IIIC or IV squamous NSCLC without targetable gene alterations were enrolled and randomized (2:1) to receive serplulimab 4.5 mg/kg or placebo, both in combination with nab-paclitaxel and carboplatin, intravenously in 3-week cycles. The primary endpoint of progression-free survival (PFS) was met at the first interim analysis. At the second interim analysis, PFS benefit was maintained in serplulimab-chemotherapy group (hazard ratio [HR] 0.53, 95% confidence interval [CI] 0.42-0.67). At the final analysis, serplulimab-chemotherapy significantly improved median OS compared to placebo-chemotherapy (HR 0.73, 95% CI 0.58-0.93; p = 0.010). Grade ≥3 serplulimab or placebo-related adverse events occurred in 126 (35.2%) and 58 (32.4%) patients, respectively. Our results demonstrate that adding serplulimab to chemotherapy significantly improves survival in advanced squamous NSCLC patients, with manageable safety.
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Affiliation(s)
- Caicun Zhou
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Shanghai 200433, China.
| | - Yanping Hu
- Department of Medical Oncology, Hubei Cancer Hospital, Wuhan 430000, China
| | - Ekaterine Arkania
- LTD Israeli-Georgian Medical Research Clinic "Helsicore", Tbilisi 0112, Georgia
| | - Saadettin Kilickap
- Department of Medical Oncology, Hacettepe University Faculty of Medicine, Ankara 06230, Turkey
| | - Kejing Ying
- Department of Pneumology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310016, China
| | - Fei Xu
- Department of Pneumology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Lin Wu
- Department of Thoracic Medical Oncology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410013, China
| | - Xiang Wang
- Department of Medical Oncology, Xuzhou Central Hospital, Xuzhou 221009, China
| | - Maksym Viguro
- Clinical Research Department, Medical Center "Mriya Med-Service", Kryvyi Rih 50000, Ukraine
| | | | - Hongmei Sun
- Department of Medical Oncology, Jiamusi Cancer Hospital, Jiamusi 154007, China
| | - Feng Luo
- Lung Cancer Center, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Jianhua Shi
- Department of Medical Oncology, Linyi Cancer Hospital, Linyi 276000, China
| | - Aimin Zang
- Department of Medical Oncology, Affiliated Hospital of Hebei University, Baoding 071000, China
| | - Yueyin Pan
- Department of Medical Oncology, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China, Hefei 230001, China
| | - Zhendong Chen
- Department of Medical Oncology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Zhongyao Jia
- Department of Oncology, Linyi People's Hospital, Linyi 276002, China
| | | | - Ping Lu
- Department of Oncology, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang 453100, China
| | - Ling Zhang
- Department of Oncology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Ying Cheng
- Department of Oncology, Jilin Cancer Hospital, Changchun 130012, China
| | - Wenying Kang
- Shanghai Henlius Biotech, Inc., Shanghai 200233, China
| | - Qingyu Wang
- Shanghai Henlius Biotech, Inc., Shanghai 200233, China
| | - Haoyu Yu
- Shanghai Henlius Biotech, Inc., Shanghai 200233, China
| | - Jing Li
- Shanghai Henlius Biotech, Inc., Shanghai 200233, China
| | - Jun Zhu
- Shanghai Henlius Biotech, Inc., Shanghai 200233, China
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Hu M, Shen Y, Yu H, Song Y, Zheng T, Hong D, Gong L. Prognostic value of cardiac magnetic resonance imaging feature tracking technology in patients with light chain amyloidosis. Clin Radiol 2024; 79:e239-e246. [PMID: 37953095 DOI: 10.1016/j.crad.2023.10.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 06/27/2023] [Accepted: 10/12/2023] [Indexed: 11/14/2023]
Abstract
AIM To undertake a meta-analysis of the prognostic value of cardiac magnetic resonance imaging feature tracking (CMR-FT) in patients with light-chain cardiac amyloidosis (LCA). MATERIALS AND METHODS A systematic search was conducted in PubMed, EMBASE, Web of Science, and the Cochrane Library. All analyses were conducted using RevMan 5.3 software. RESULTS Eight studies were included with 663 patients. For the left ventricle, the results showed that CMR-FT was statistically significant in predicting death, with less impaired global circumferential (GCS), radial (GRS) and longitudinal (GLS) strain in survivors of LCA (odds ratio [OR] 1.17, 95% confidence interval [CI] 1.09-1.25; 0.95, 0.93-0.96; 1.12, 1.05-1.20, all p<0.001). For ejection fraction (EF) and mass index, surviving patients had higher EFs and mass index (OR 0.96, 95% CI 0.96-0.97; 1.01, 1.01-1.02). For the right ventricle, the results showed that CMR-FT was statistically significant in predicting death, with less impaired GLS and GRS in survivors of LCA (OR 1.11, 95% CI 1.08-1.15; 0.93, 0.90-0.96, all p<0.001). Surviving patients had higher EFs (OR 0.97, 95% CI 0.96-0.98, p<0.001). Upon removing the studies one by one, there was no significant change in the results of the study. Both analyses showed no apparent publication deviation on funnel plots. CONCLUSION Parameters derived from CMR-FT technology are promising new predictors for LCA, and are easily available and reliable. Patients with poor myocardial deformability are at highest risk of death.
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Affiliation(s)
- M Hu
- Medical Imaging Center, The Second Affiliated Hospital of Nanchang University, No. 1 Min-de Road, Donghu District, Nanchang, 33000, Jiangxi Province, People's Republic of China
| | - Y Shen
- Department of Neurology, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Donghu District, Nanchang 330006, Jiangxi Province, People's Republic of China
| | - H Yu
- Department of Radiology, Jiangxi Province Medical Imaging Research Institute, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Donghu District, Nanchang 330006, Jiangxi Province, People's Republic of China
| | - Y Song
- Medical Imaging Center, The Second Affiliated Hospital of Nanchang University, No. 1 Min-de Road, Donghu District, Nanchang, 33000, Jiangxi Province, People's Republic of China
| | - T Zheng
- Medical Imaging Center, The Second Affiliated Hospital of Nanchang University, No. 1 Min-de Road, Donghu District, Nanchang, 33000, Jiangxi Province, People's Republic of China
| | - D Hong
- Department of Neurology, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Donghu District, Nanchang 330006, Jiangxi Province, People's Republic of China.
| | - L Gong
- Medical Imaging Center, The Second Affiliated Hospital of Nanchang University, No. 1 Min-de Road, Donghu District, Nanchang, 33000, Jiangxi Province, People's Republic of China.
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Yu H, Zhang Q, Farooqi AA, Wang J, Yue Y, Geng L, Wu N. Opportunities and challenges of fucoidan for tumors therapy. Carbohydr Polym 2024; 324:121555. [PMID: 37985117 DOI: 10.1016/j.carbpol.2023.121555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/28/2023] [Accepted: 10/31/2023] [Indexed: 11/22/2023]
Abstract
The large-scale collections, screening and discovery of biologically active and pharmacologically significant marine-derived natural products have garnered tremendous attraction. Edible brown algae are rich in fucoidan. Importantly, fucoidan has been reported to inhibit carcinogenesis and metastasis mainly through the regulation of deregulated cell signaling pathways. This review summarizes the structural features of fucoidan, including monosaccharide type, sulfate content, and main chain structure. We have set spotlight on fucoidan-mediated tumor suppressive effects in cell cultures studies and tumor-bearing rodent models. Fucoidan exerts anti-tumor effects primarily through the inhibition of tumor cell viability, proliferation and metastatic dissemination of cancer cells from primary tumor sites to distant secondary sites. Fucoidan not only promotes immunological responses in tumor microenvironment but also induces apoptotic death in cancer cells. In addition, fucoidan can be used as a dietary supplement for preventive purposes, in combination with other drugs as complementary and alternative medicine or with nanoparticle modifications will be the future of fucoidan use. Cutting-edge research related to fucoidan has catalyzed the transition of fucoidan from preclinical studies to different phases of clinical trials. Rationally designed clinical trials for the critical evaluation of fucoidan against different cancers will be valuable to reap full benefits.
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Affiliation(s)
- Haoyu Yu
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; Department of Drugs and Bioproducts, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Quanbin Zhang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ammad Ahmad Farooqi
- Department of Molecular Oncology, Institute of Biomedical and Genetic Engineering (IBGE), Islamabad 54000, Pakistan
| | - Jing Wang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yang Yue
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Lihua Geng
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Ning Wu
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; Department of Drugs and Bioproducts, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Jia LH, Lin HL, Zheng SW, Lin XJ, Zhang D, Yu H. [Mitigating metal artifacts from cobalt-chromium alloy crowns in cone-beam CT images through deep learning techniques]. Zhonghua Kou Qiang Yi Xue Za Zhi 2024; 59:71-79. [PMID: 38228542 DOI: 10.3760/cma.j.cn112144-20231030-00228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
Objective: To develop and evaluate metal artifact removal systems (MARS) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images. Methods: A full-mouth standard model (60 mm×75 mm×110 mm) was three-dimensional (3D) printed using photosensitive resin. The model included a removable and replaceable target tooth position where cobalt-chromium alloy crowns with varying thicknesses were inserted to generate matched CBCT images. The artifacts resulting from cobalt-chromium alloys with different thicknesses were evaluated using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR). CNN-MARS and U-net-MARS were developed using a convolutional neural network and U-net architecture, respectively. The effectiveness of both MARSs were assessed through visualization and by measuring SSIM and PSNR values. The SSIM and PSNR values were statistically analyzed using one-way analysis of variance (α=0.05). Results: Significant differences were observed in the range of artifacts produced by different thicknesses of cobalt-chromium alloys (all P<0.05), with 1 mm resulting in the least artifacts. The SSIM values for specimens with thicknesses of 1.0, 1.5, and 2.0 mm were 0.916±0.019, 0.873±0.010, and 0.833±0.010, respectively (F=447.89, P<0.001). The corresponding PSNR values were 20.834±1.176, 17.002±0.427, and 14.673±0.429, respectively (F=796.51, P<0.001). After applying CNN-MARS and U-net-MARS to artifact removal, the SSIM and PSNR values significantly increased for images with the same thickness of metal (both P<0.05). When using the CNN-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.938±0.023, 0.930±0.029, and 0.928±0.020 (F=2.22, P=0.112), while the PSNR values were 30.938±1.495, 30.578±2.154 and 30.553±2.355 (F=0.54, P=0.585). When using the U-net-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.930±0.024, 0.932±0.017 and 0.930±0.012 (F=0.24, P=0.788), and the PSNR values were 30.291±0.934, 30.351±1.002 and 30.271±1.143 (F=0.07, P=0.929). No significant differences were found in SSIM and PSNR values after artifact removal using CNN-MARS and U-net-MARS for different thicknesses of cobalt-chromium alloys (all P>0.05). Visualization demonstrated a high degree of similarity between the images before and after artifact removal using both MARS. However, CNN-MARS displayed clearer metal edges and preserved more tissue details when compared with U-net-MARS. Conclusions: Both the CNN-MARS and U-net-MARS models developed in this study effectively remove the metal artifacts and enhance the image quality. CNN-MARS exhibited an advantage in restoring tissue structure information around the artifacts compared to U-net-MARS.
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Affiliation(s)
- L H Jia
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University & Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University & Institute of Stomatology, Fujian Medical University & Research Center of Dental Esthetics and Biomechanics, Fujian Medical University, Fuzhou 350002, China
| | - H L Lin
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University & Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University & Institute of Stomatology, Fujian Medical University & Research Center of Dental Esthetics and Biomechanics, Fujian Medical University, Fuzhou 350002, China
| | - S W Zheng
- College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
| | - X J Lin
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University & Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University & Institute of Stomatology, Fujian Medical University & Research Center of Dental Esthetics and Biomechanics, Fujian Medical University, Fuzhou 350002, China
| | - D Zhang
- College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
| | - H Yu
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University & Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University & Institute of Stomatology, Fujian Medical University & Research Center of Dental Esthetics and Biomechanics, Fujian Medical University, Fuzhou 350002, China
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Zheng C, Zeng R, Wu G, Hu Y, Yu H. Beyond Vision: A View from Eye to Alzheimer's Disease and Dementia. J Prev Alzheimers Dis 2024; 11:469-483. [PMID: 38374754 DOI: 10.14283/jpad.2023.118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
With the aging of the global population, the health care burden of Alzheimer's disease (AD) and dementia is considered to increase dramatically in the coming decades. Given the insufficiency of effective interventions for AD and dementia, clinical research on identifying potentially modifiable risk factors and early diagnostic biomarkers becomes a public health priority. Currently, extracerebral manifestations with a large proportion of ocular involvement are usually recognized to precede the symptoms of AD and dementia. Growing epidemiologic evidence also suggests that eye disorders, such as cataracts, age-related macular degeneration, glaucoma, diabetic retinopathy, and so on, are closely associated with and even have a higher incidence of AD and dementia. The eye, as an extension of the central nervous system, therefore has the potential to provide a feasible approach to detecting structural and functional abnormalities of the brain. Numerous new imaging modalities are developed and give novel insights into the detection of several neurodegenerative, vascular, neuropathological, and other ocular abnormalities of AD and dementia in scientific research and clinical application. This review provides an overview of the epidemiologic associations between eye disorders and AD or dementia and summarizes the recent advances in ocular examinations and techniques employed for the detection of AD and dementia. With more brain-and-eye interconnections being identified, the eye is becoming a noninvasive and easily accessible window for the early diagnosis and prevention of AD and dementia.
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Affiliation(s)
- C Zheng
- Prof. Honghua Yu, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China. Tel: 86-186-8888-8422.Fax: 86-8382-7812, E-mail: ; Prof. Yijun Hu, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China. Tel: 86-137-1052-6990. Fax: 86-8382-7812; E-mail:
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Staplin N, Haynes R, Judge PK, Wanner C, Green JB, Emberson J, Preiss D, Mayne KJ, Ng SYA, Sammons E, Zhu D, Hill M, Stevens W, Wallendszus K, Brenner S, Cheung AK, Liu ZH, Li J, Hooi LS, Liu WJ, Kadowaki T, Nangaku M, Levin A, Cherney D, Maggioni AP, Pontremoli R, Deo R, Goto S, Rossello X, Tuttle KR, Steubl D, Petrini M, Seidi S, Landray MJ, Baigent C, Herrington WG, Abat S, Abd Rahman R, Abdul Cader R, Abdul Hafidz MI, Abdul Wahab MZ, Abdullah NK, Abdul-Samad T, Abe M, Abraham N, Acheampong S, Achiri P, Acosta JA, Adeleke A, Adell V, Adewuyi-Dalton R, Adnan N, Africano A, Agharazii M, Aguilar F, Aguilera A, Ahmad M, Ahmad MK, Ahmad NA, Ahmad NH, Ahmad NI, Ahmad Miswan N, Ahmad Rosdi H, Ahmed I, Ahmed S, Ahmed S, Aiello J, Aitken A, AitSadi R, Aker S, Akimoto S, Akinfolarin A, Akram S, Alberici F, Albert C, Aldrich L, Alegata M, Alexander L, Alfaress S, Alhadj Ali M, Ali A, Ali A, Alicic R, Aliu A, Almaraz R, Almasarwah R, Almeida J, Aloisi A, Al-Rabadi L, Alscher D, Alvarez P, Al-Zeer B, Amat M, Ambrose C, Ammar H, An Y, Andriaccio L, Ansu K, Apostolidi A, Arai N, Araki H, Araki S, Arbi A, Arechiga O, Armstrong S, Arnold T, Aronoff S, Arriaga W, Arroyo J, Arteaga D, Asahara S, Asai A, Asai N, Asano S, Asawa M, Asmee MF, Aucella F, Augustin M, Avery A, Awad A, Awang IY, Awazawa M, Axler A, Ayub W, Azhari Z, Baccaro R, Badin C, Bagwell B, Bahlmann-Kroll E, Bahtar AZ, Baigent C, Bains D, Bajaj H, Baker R, Baldini E, Banas B, Banerjee D, Banno S, Bansal S, Barberi S, Barnes S, Barnini C, Barot C, Barrett K, Barrios R, Bartolomei Mecatti B, Barton I, Barton J, Basily W, Bavanandan S, Baxter A, Becker L, Beddhu S, Beige J, Beigh S, Bell S, Benck U, Beneat A, Bennett A, Bennett D, Benyon S, Berdeprado J, Bergler T, Bergner A, Berry M, Bevilacqua M, Bhairoo J, Bhandari S, Bhandary N, Bhatt A, Bhattarai M, Bhavsar M, Bian W, Bianchini F, Bianco S, Bilous R, Bilton J, Bilucaglia D, Bird C, Birudaraju D, Biscoveanu M, Blake C, Bleakley N, Bocchicchia K, Bodine S, Bodington R, Boedecker S, Bolduc M, Bolton S, Bond C, Boreky F, Boren K, Bouchi R, Bough L, Bovan D, Bowler C, Bowman L, Brar N, Braun C, Breach A, Breitenfeldt M, Brenner S, Brettschneider B, Brewer A, Brewer G, Brindle V, Brioni E, Brown C, Brown H, Brown L, Brown R, Brown S, Browne D, Bruce K, Brueckmann M, Brunskill N, Bryant M, Brzoska M, Bu Y, Buckman C, Budoff M, Bullen M, Burke A, Burnette S, Burston C, Busch M, Bushnell J, Butler S, Büttner C, Byrne C, Caamano A, Cadorna J, Cafiero C, Cagle M, Cai J, Calabrese K, Calvi C, Camilleri B, Camp S, Campbell D, Campbell R, Cao H, Capelli I, Caple M, Caplin B, Cardone A, Carle J, Carnall V, Caroppo M, Carr S, Carraro G, Carson M, Casares P, Castillo C, Castro C, Caudill B, Cejka V, Ceseri M, Cham L, Chamberlain A, Chambers J, Chan CBT, Chan JYM, Chan YC, Chang E, Chang E, Chant T, Chavagnon T, Chellamuthu P, Chen F, Chen J, Chen P, Chen TM, Chen Y, Chen Y, Cheng C, Cheng H, Cheng MC, Cherney D, Cheung AK, Ching CH, Chitalia N, Choksi R, Chukwu C, Chung K, Cianciolo G, Cipressa L, Clark S, Clarke H, Clarke R, Clarke S, Cleveland B, Cole E, Coles H, Condurache L, Connor A, Convery K, Cooper A, Cooper N, Cooper Z, Cooperman L, Cosgrove L, Coutts P, Cowley A, Craik R, Cui G, Cummins T, Dahl N, Dai H, Dajani L, D'Amelio A, Damian E, Damianik K, Danel L, Daniels C, Daniels T, Darbeau S, Darius H, Dasgupta T, Davies J, Davies L, Davis A, Davis J, Davis L, Dayanandan R, Dayi S, Dayrell R, De Nicola L, Debnath S, Deeb W, Degenhardt S, DeGoursey K, Delaney M, Deo R, DeRaad R, Derebail V, Dev D, Devaux M, Dhall P, Dhillon G, Dienes J, Dobre M, Doctolero E, Dodds V, Domingo D, Donaldson D, Donaldson P, Donhauser C, Donley V, Dorestin S, Dorey S, Doulton T, Draganova D, Draxlbauer K, Driver F, Du H, Dube F, Duck T, Dugal T, Dugas J, Dukka H, Dumann H, Durham W, Dursch M, Dykas R, Easow R, Eckrich E, Eden G, Edmerson E, Edwards H, Ee LW, Eguchi J, Ehrl Y, Eichstadt K, Eid W, Eilerman B, Ejima Y, Eldon H, Ellam T, Elliott L, Ellison R, Emberson J, Epp R, Er A, Espino-Obrero M, Estcourt S, Estienne L, Evans G, Evans J, Evans S, Fabbri G, Fajardo-Moser M, Falcone C, Fani F, Faria-Shayler P, Farnia F, Farrugia D, Fechter M, Fellowes D, Feng F, Fernandez J, Ferraro P, Field A, Fikry S, Finch J, Finn H, Fioretto P, Fish R, Fleischer A, Fleming-Brown D, Fletcher L, Flora R, Foellinger C, Foligno N, Forest S, Forghani Z, Forsyth K, Fottrell-Gould D, Fox P, Frankel A, Fraser D, Frazier R, Frederick K, Freking N, French H, Froment A, Fuchs B, Fuessl L, Fujii H, Fujimoto A, Fujita A, Fujita K, Fujita Y, Fukagawa M, Fukao Y, Fukasawa A, Fuller T, Funayama T, Fung E, Furukawa M, Furukawa Y, Furusho M, Gabel S, Gaidu J, Gaiser S, Gallo K, Galloway C, Gambaro G, Gan CC, Gangemi C, Gao M, Garcia K, Garcia M, Garofalo C, Garrity M, Garza A, Gasko S, Gavrila M, Gebeyehu B, Geddes A, Gentile G, George A, George J, Gesualdo L, Ghalli F, Ghanem A, Ghate T, Ghavampour S, Ghazi A, Gherman A, Giebeln-Hudnell U, Gill B, Gillham S, Girakossyan I, Girndt M, Giuffrida A, Glenwright M, Glider T, Gloria R, Glowski D, Goh BL, Goh CB, Gohda T, Goldenberg R, Goldfaden R, Goldsmith C, Golson B, Gonce V, Gong Q, Goodenough B, Goodwin N, Goonasekera M, Gordon A, Gordon J, Gore A, Goto H, Goto S, Goto S, Gowen D, Grace A, Graham J, Grandaliano G, Gray M, Green JB, Greene T, Greenwood G, Grewal B, Grifa R, Griffin D, Griffin S, Grimmer P, Grobovaite E, Grotjahn S, Guerini A, Guest C, Gunda S, Guo B, Guo Q, Haack S, Haase M, Haaser K, Habuki K, Hadley A, Hagan S, Hagge S, Haller H, Ham S, Hamal S, Hamamoto Y, Hamano N, Hamm M, Hanburry A, Haneda M, Hanf C, Hanif W, Hansen J, Hanson L, Hantel S, Haraguchi T, Harding E, Harding T, Hardy C, Hartner C, Harun Z, Harvill L, Hasan A, Hase H, Hasegawa F, Hasegawa T, Hashimoto A, Hashimoto C, Hashimoto M, Hashimoto S, Haskett S, Hauske SJ, Hawfield A, Hayami T, Hayashi M, Hayashi S, Haynes R, Hazara A, Healy C, Hecktman J, Heine G, Henderson H, Henschel R, Hepditch A, Herfurth K, Hernandez G, Hernandez Pena A, Hernandez-Cassis C, Herrington WG, Herzog C, Hewins S, Hewitt D, Hichkad L, Higashi S, Higuchi C, Hill C, Hill L, Hill M, Himeno T, Hing A, Hirakawa Y, Hirata K, Hirota Y, Hisatake T, Hitchcock S, Hodakowski A, Hodge W, Hogan R, Hohenstatt U, Hohenstein B, Hooi L, Hope S, Hopley M, Horikawa S, Hosein D, Hosooka T, Hou L, Hou W, Howie L, Howson A, Hozak M, Htet Z, Hu X, Hu Y, Huang J, Huda N, Hudig L, Hudson A, Hugo C, Hull R, Hume L, Hundei W, Hunt N, Hunter A, Hurley S, Hurst A, Hutchinson C, Hyo T, Ibrahim FH, Ibrahim S, Ihana N, Ikeda T, Imai A, Imamine R, Inamori A, Inazawa H, Ingell J, Inomata K, Inukai Y, Ioka M, Irtiza-Ali A, Isakova T, Isari W, Iselt M, Ishiguro A, Ishihara K, Ishikawa T, Ishimoto T, Ishizuka K, Ismail R, Itano S, Ito H, Ito K, Ito M, Ito Y, Iwagaitsu S, Iwaita Y, Iwakura T, Iwamoto M, Iwasa M, Iwasaki H, Iwasaki S, Izumi K, Izumi K, Izumi T, Jaafar SM, Jackson C, Jackson Y, Jafari G, Jahangiriesmaili M, Jain N, Jansson K, Jasim H, Jeffers L, Jenkins A, Jesky M, Jesus-Silva J, Jeyarajah D, Jiang Y, Jiao X, Jimenez G, Jin B, Jin Q, Jochims J, Johns B, Johnson C, Johnson T, Jolly S, Jones L, Jones L, Jones S, Jones T, Jones V, Joseph M, Joshi S, Judge P, Junejo N, Junus S, Kachele M, Kadowaki T, Kadoya H, Kaga H, Kai H, Kajio H, Kaluza-Schilling W, Kamaruzaman L, Kamarzarian A, Kamimura Y, Kamiya H, Kamundi C, Kan T, Kanaguchi Y, Kanazawa A, Kanda E, Kanegae S, Kaneko K, Kaneko K, Kang HY, Kano T, Karim M, Karounos D, Karsan W, Kasagi R, Kashihara N, Katagiri H, Katanosaka A, Katayama A, Katayama M, Katiman E, Kato K, Kato M, Kato N, Kato S, Kato T, Kato Y, Katsuda Y, Katsuno T, Kaufeld J, Kavak Y, Kawai I, Kawai M, Kawai M, Kawase A, Kawashima S, Kazory A, Kearney J, Keith B, Kellett J, Kelley S, Kershaw M, Ketteler M, Khai Q, Khairullah Q, Khandwala H, Khoo KKL, Khwaja A, Kidokoro K, Kielstein J, Kihara M, Kimber C, Kimura S, Kinashi H, Kingston H, Kinomura M, Kinsella-Perks E, Kitagawa M, Kitajima M, Kitamura S, Kiyosue A, Kiyota M, Klauser F, Klausmann G, Kmietschak W, Knapp K, Knight C, Knoppe A, Knott C, Kobayashi M, Kobayashi R, Kobayashi T, Koch M, Kodama S, Kodani N, Kogure E, Koizumi M, Kojima H, Kojo T, Kolhe N, Komaba H, Komiya T, Komori H, Kon SP, Kondo M, Kondo M, Kong W, Konishi M, Kono K, Koshino M, Kosugi T, Kothapalli B, Kozlowski T, Kraemer B, Kraemer-Guth A, Krappe J, Kraus D, Kriatselis C, Krieger C, Krish P, Kruger B, Ku Md Razi KR, Kuan Y, Kubota S, Kuhn S, Kumar P, Kume S, Kummer I, Kumuji R, Küpper A, Kuramae T, Kurian L, Kuribayashi C, Kurien R, Kuroda E, Kurose T, Kutschat A, Kuwabara N, Kuwata H, La Manna G, Lacey M, Lafferty K, LaFleur P, Lai V, Laity E, Lambert A, Landray MJ, Langlois M, Latif F, Latore E, Laundy E, Laurienti D, Lawson A, Lay M, Leal I, Leal I, Lee AK, Lee J, Lee KQ, Lee R, Lee SA, Lee YY, Lee-Barkey Y, Leonard N, Leoncini G, Leong CM, Lerario S, Leslie A, Levin A, Lewington A, Li J, Li N, Li X, Li Y, Liberti L, Liberti ME, Liew A, Liew YF, Lilavivat U, Lim SK, Lim YS, Limon E, Lin H, Lioudaki E, Liu H, Liu J, Liu L, Liu Q, Liu WJ, Liu X, Liu Z, Loader D, Lochhead H, Loh CL, Lorimer A, Loudermilk L, Loutan J, Low CK, Low CL, Low YM, Lozon Z, Lu Y, Lucci D, Ludwig U, Luker N, Lund D, Lustig R, Lyle S, Macdonald C, MacDougall I, Machicado R, MacLean D, Macleod P, Madera A, Madore F, Maeda K, Maegawa H, Maeno S, Mafham M, Magee J, Maggioni AP, Mah DY, Mahabadi V, Maiguma M, Makita Y, Makos G, Manco L, Mangiacapra R, Manley J, Mann P, Mano S, Marcotte G, Maris J, Mark P, Markau S, Markovic M, Marshall C, Martin M, Martinez C, Martinez S, Martins G, Maruyama K, Maruyama S, Marx K, Maselli A, Masengu A, Maskill A, Masumoto S, Masutani K, Matsumoto M, Matsunaga T, Matsuoka N, Matsushita M, Matthews M, Matthias S, Matvienko E, Maurer M, Maxwell P, Mayne KJ, Mazlan N, Mazlan SA, Mbuyisa A, McCafferty K, McCarroll F, McCarthy T, McClary-Wright C, McCray K, McDermott P, McDonald C, McDougall R, McHaffie E, McIntosh K, McKinley T, McLaughlin S, McLean N, McNeil L, Measor A, Meek J, Mehta A, Mehta R, Melandri M, Mené P, Meng T, Menne J, Merritt K, Merscher S, Meshykhi C, Messa P, Messinger L, Miftari N, Miller R, Miller Y, Miller-Hodges E, Minatoguchi M, Miners M, Minutolo R, Mita T, Miura Y, Miyaji M, Miyamoto S, Miyatsuka T, Miyazaki M, Miyazawa I, Mizumachi R, Mizuno M, Moffat S, Mohamad Nor FS, Mohamad Zaini SN, Mohamed Affandi FA, Mohandas C, Mohd R, Mohd Fauzi NA, Mohd Sharif NH, Mohd Yusoff Y, Moist L, Moncada A, Montasser M, Moon A, Moran C, Morgan N, Moriarty J, Morig G, Morinaga H, Morino K, Morisaki T, Morishita Y, Morlok S, Morris A, Morris F, Mostafa S, Mostefai Y, Motegi M, Motherwell N, Motta D, Mottl A, Moys R, Mozaffari S, Muir J, Mulhern J, Mulligan S, Munakata Y, Murakami C, Murakoshi M, Murawska A, Murphy K, Murphy L, Murray S, Murtagh H, Musa MA, Mushahar L, Mustafa R, Mustafar R, Muto M, Nadar E, Nagano R, Nagasawa T, Nagashima E, Nagasu H, Nagelberg S, Nair H, Nakagawa Y, Nakahara M, Nakamura J, Nakamura R, Nakamura T, Nakaoka M, Nakashima E, Nakata J, Nakata M, Nakatani S, Nakatsuka A, Nakayama Y, Nakhoul G, Nangaku M, Naverrete G, Navivala A, Nazeer I, Negrea L, Nethaji C, Newman E, Ng SYA, Ng TJ, Ngu LLS, Nimbkar T, Nishi H, Nishi M, Nishi S, Nishida Y, Nishiyama A, Niu J, Niu P, Nobili G, Nohara N, Nojima I, Nolan J, Nosseir H, Nozawa M, Nunn M, Nunokawa S, Oda M, Oe M, Oe Y, Ogane K, Ogawa W, Ogihara T, Oguchi G, Ohsugi M, Oishi K, Okada Y, Okajyo J, Okamoto S, Okamura K, Olufuwa O, Oluyombo R, Omata A, Omori Y, Ong LM, Ong YC, Onyema J, Oomatia A, Oommen A, Oremus R, Orimo Y, Ortalda V, Osaki Y, Osawa Y, Osmond Foster J, O'Sullivan A, Otani T, Othman N, Otomo S, O'Toole J, Owen L, Ozawa T, Padiyar A, Page N, Pajak S, Paliege A, Pandey A, Pandey R, Pariani H, Park J, Parrigon M, Passauer J, Patecki M, Patel M, Patel R, Patel T, Patel Z, Paul R, Paul R, Paulsen L, Pavone L, Peixoto A, Peji J, Peng BC, Peng K, Pennino L, Pereira E, Perez E, Pergola P, Pesce F, 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Yamagata K, Yamaguchi M, Yamaji Y, Yamamoto A, Yamamoto S, Yamamoto S, Yamamoto T, Yamanaka A, Yamano T, Yamanouchi Y, Yamasaki N, Yamasaki Y, Yamasaki Y, Yamashita C, Yamauchi T, Yan Q, Yanagisawa E, Yang F, Yang L, Yano S, Yao S, Yao Y, Yarlagadda S, Yasuda Y, Yiu V, Yokoyama T, Yoshida S, Yoshidome E, Yoshikawa H, Young A, Young T, Yousif V, Yu H, Yu Y, Yuasa K, Yusof N, Zalunardo N, Zander B, Zani R, Zappulo F, Zayed M, Zemann B, Zettergren P, Zhang H, Zhang L, Zhang L, Zhang N, Zhang X, Zhao J, Zhao L, Zhao S, Zhao Z, Zhong H, Zhou N, Zhou S, Zhu D, Zhu L, Zhu S, Zietz M, Zippo M, Zirino F, Zulkipli FH. Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial. Lancet Diabetes Endocrinol 2024; 12:39-50. [PMID: 38061371 PMCID: PMC7615591 DOI: 10.1016/s2213-8587(23)00321-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial. METHODS EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110. FINDINGS Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001). INTERPRETATION Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor. FUNDING Boehringer Ingelheim and Eli Lilly.
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Yu H, Gao R, Liu Y, Fu L, Zhou J, Li L. Stimulus-Responsive Hydrogels as Drug Delivery Systems for Inflammation Targeted Therapy. Adv Sci (Weinh) 2024; 11:e2306152. [PMID: 37985923 PMCID: PMC10767459 DOI: 10.1002/advs.202306152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/19/2023] [Indexed: 11/22/2023]
Abstract
Deregulated inflammations induced by various factors are one of the most common diseases in people's daily life, while severe inflammation can even lead to death. Thus, the efficient treatment of inflammation has always been the hot topic in the research of medicine. In the past decades, as a potential biomaterial, stimuli-responsive hydrogels have been a focus of attention for the inflammation treatment due to their excellent biocompatibility and design flexibility. Recently, thanks to the rapid development of nanotechnology and material science, more and more efforts have been made to develop safer, more personal and more effective hydrogels for the therapy of some frequent but tough inflammations such as sepsis, rheumatoid arthritis, osteoarthritis, periodontitis, and ulcerative colitis. Herein, from recent studies and articles, the conventional and emerging hydrogels in the delivery of anti-inflammatory drugs and the therapy for various inflammations are summarized. And their prospects of clinical translation and future development are also discussed in further detail.
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Affiliation(s)
- Haoyu Yu
- The Eighth Affiliated HospitalSun Yat‐sen UniversityShenzhenGuangdong518033P. R. China
| | - Rongyao Gao
- Department of ChemistryRenmin University of ChinaBeijing100872P. R. China
| | - Yuxin Liu
- Department of Biomolecular SystemsMax‐Planck Institute of Colloids and Interfaces14476PotsdamGermany
| | - Limin Fu
- Department of ChemistryRenmin University of ChinaBeijing100872P. R. China
| | - Jing Zhou
- Department of ChemistryCapital Normal UniversityBeijing100048P. R. China
| | - Luoyuan Li
- The Eighth Affiliated HospitalSun Yat‐sen UniversityShenzhenGuangdong518033P. R. China
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Herfurth K, Hernandez G, Hernandez Pena A, Hernandez-Cassis C, Herrington WG, Herzog C, Hewins S, Hewitt D, Hichkad L, Higashi S, Higuchi C, Hill C, Hill L, Hill M, Himeno T, Hing A, Hirakawa Y, Hirata K, Hirota Y, Hisatake T, Hitchcock S, Hodakowski A, Hodge W, Hogan R, Hohenstatt U, Hohenstein B, Hooi L, Hope S, Hopley M, Horikawa S, Hosein D, Hosooka T, Hou L, Hou W, Howie L, Howson A, Hozak M, Htet Z, Hu X, Hu Y, Huang J, Huda N, Hudig L, Hudson A, Hugo C, Hull R, Hume L, Hundei W, Hunt N, Hunter A, Hurley S, Hurst A, Hutchinson C, Hyo T, Ibrahim FH, Ibrahim S, Ihana N, Ikeda T, Imai A, Imamine R, Inamori A, Inazawa H, Ingell J, Inomata K, Inukai Y, Ioka M, Irtiza-Ali A, Isakova T, Isari W, Iselt M, Ishiguro A, Ishihara K, Ishikawa T, Ishimoto T, Ishizuka K, Ismail R, Itano S, Ito H, Ito K, Ito M, Ito Y, Iwagaitsu S, Iwaita Y, Iwakura T, Iwamoto M, Iwasa M, Iwasaki H, Iwasaki S, Izumi K, Izumi K, Izumi T, Jaafar SM, Jackson C, Jackson Y, Jafari G, Jahangiriesmaili M, Jain N, Jansson K, Jasim H, Jeffers L, Jenkins A, Jesky M, Jesus-Silva J, Jeyarajah D, Jiang Y, Jiao X, Jimenez G, Jin B, Jin Q, Jochims J, Johns B, Johnson C, Johnson T, Jolly S, Jones L, Jones L, Jones S, Jones T, Jones V, Joseph M, Joshi S, Judge P, Junejo N, Junus S, Kachele M, Kadowaki T, Kadoya H, Kaga H, Kai H, Kajio H, Kaluza-Schilling W, Kamaruzaman L, Kamarzarian A, Kamimura Y, Kamiya H, Kamundi C, Kan T, Kanaguchi Y, Kanazawa A, Kanda E, Kanegae S, Kaneko K, Kaneko K, Kang HY, Kano T, Karim M, Karounos D, Karsan W, Kasagi R, Kashihara N, Katagiri H, Katanosaka A, Katayama A, Katayama M, Katiman E, Kato K, Kato M, Kato N, Kato S, Kato T, Kato Y, Katsuda Y, Katsuno T, Kaufeld J, Kavak Y, Kawai I, Kawai M, Kawai M, Kawase A, Kawashima S, Kazory A, Kearney J, Keith B, Kellett J, Kelley S, Kershaw M, Ketteler M, Khai Q, Khairullah Q, Khandwala H, Khoo KKL, Khwaja A, Kidokoro K, Kielstein J, Kihara M, Kimber C, Kimura S, Kinashi H, Kingston H, Kinomura M, Kinsella-Perks E, Kitagawa M, Kitajima M, Kitamura S, Kiyosue A, Kiyota M, Klauser F, Klausmann G, Kmietschak W, Knapp K, Knight C, Knoppe A, Knott C, Kobayashi M, Kobayashi R, Kobayashi T, Koch M, Kodama S, Kodani N, Kogure E, Koizumi M, Kojima H, Kojo T, Kolhe N, Komaba H, Komiya T, Komori H, Kon SP, Kondo M, Kondo M, Kong W, Konishi M, Kono K, Koshino M, Kosugi T, Kothapalli B, Kozlowski T, Kraemer B, Kraemer-Guth A, Krappe J, Kraus D, Kriatselis C, Krieger C, Krish P, Kruger B, Ku Md Razi KR, Kuan Y, Kubota S, Kuhn S, Kumar P, Kume S, Kummer I, Kumuji R, Küpper A, Kuramae T, Kurian L, Kuribayashi C, Kurien R, Kuroda E, Kurose T, Kutschat A, Kuwabara N, Kuwata H, La Manna G, Lacey M, Lafferty K, LaFleur P, Lai V, Laity E, Lambert A, Landray MJ, Langlois M, Latif F, Latore E, Laundy E, Laurienti D, Lawson A, Lay M, Leal I, Leal I, Lee AK, Lee J, Lee KQ, Lee R, Lee SA, Lee YY, Lee-Barkey Y, Leonard N, Leoncini G, Leong CM, Lerario S, Leslie A, Levin A, Lewington A, Li J, Li N, Li X, Li Y, Liberti L, Liberti ME, Liew A, Liew YF, Lilavivat U, Lim SK, Lim YS, Limon E, Lin H, Lioudaki E, Liu H, Liu J, Liu L, Liu Q, Liu WJ, Liu X, Liu Z, Loader D, Lochhead H, Loh CL, Lorimer A, Loudermilk L, Loutan J, Low CK, Low CL, Low YM, Lozon Z, Lu Y, Lucci D, Ludwig U, Luker N, Lund D, Lustig R, Lyle S, Macdonald C, MacDougall I, Machicado R, MacLean D, Macleod P, Madera A, Madore F, Maeda K, Maegawa H, Maeno S, Mafham M, Magee J, Maggioni AP, Mah DY, Mahabadi V, Maiguma M, Makita Y, Makos G, Manco L, Mangiacapra R, Manley J, Mann P, Mano S, Marcotte G, Maris J, Mark P, Markau S, Markovic M, Marshall C, Martin M, Martinez C, Martinez S, Martins G, Maruyama K, Maruyama S, Marx K, Maselli A, Masengu A, Maskill A, Masumoto S, Masutani K, Matsumoto M, Matsunaga T, Matsuoka N, Matsushita M, Matthews M, Matthias S, Matvienko E, Maurer M, Maxwell P, Mayne KJ, Mazlan N, Mazlan SA, Mbuyisa A, McCafferty K, McCarroll F, McCarthy T, McClary-Wright C, McCray K, McDermott P, McDonald C, McDougall R, McHaffie E, McIntosh K, McKinley T, McLaughlin S, McLean N, McNeil L, Measor A, Meek J, Mehta A, Mehta R, Melandri M, Mené P, Meng T, Menne J, Merritt K, Merscher S, Meshykhi C, Messa P, Messinger L, Miftari N, Miller R, Miller Y, Miller-Hodges E, Minatoguchi M, Miners M, Minutolo R, Mita T, Miura Y, Miyaji M, Miyamoto S, Miyatsuka T, Miyazaki M, Miyazawa I, Mizumachi R, Mizuno M, Moffat S, Mohamad Nor FS, Mohamad Zaini SN, Mohamed Affandi FA, Mohandas C, Mohd R, Mohd Fauzi NA, Mohd Sharif NH, Mohd Yusoff Y, Moist L, Moncada A, Montasser M, Moon A, Moran C, Morgan N, Moriarty J, Morig G, Morinaga H, Morino K, Morisaki T, Morishita Y, Morlok S, Morris A, Morris F, Mostafa S, Mostefai Y, Motegi M, Motherwell N, Motta D, Mottl A, Moys R, Mozaffari S, Muir J, Mulhern J, Mulligan S, Munakata Y, Murakami C, Murakoshi M, Murawska A, Murphy K, Murphy L, Murray S, Murtagh H, Musa MA, Mushahar L, Mustafa R, Mustafar R, Muto M, Nadar E, Nagano R, Nagasawa T, Nagashima E, Nagasu H, Nagelberg S, Nair H, Nakagawa Y, Nakahara M, Nakamura J, Nakamura R, Nakamura T, Nakaoka M, Nakashima E, Nakata J, Nakata M, Nakatani S, Nakatsuka A, Nakayama Y, Nakhoul G, Nangaku M, Naverrete G, Navivala A, Nazeer I, Negrea L, Nethaji C, Newman E, Ng SYA, Ng TJ, Ngu LLS, Nimbkar T, Nishi H, Nishi M, Nishi S, Nishida Y, Nishiyama A, Niu J, Niu P, Nobili G, Nohara N, Nojima I, Nolan J, Nosseir H, Nozawa M, Nunn M, Nunokawa S, Oda M, Oe M, Oe Y, Ogane K, Ogawa W, Ogihara T, Oguchi G, Ohsugi M, Oishi K, Okada Y, Okajyo J, Okamoto S, Okamura K, Olufuwa O, Oluyombo R, Omata A, Omori Y, Ong LM, Ong YC, Onyema J, Oomatia A, Oommen A, Oremus R, Orimo Y, Ortalda V, Osaki Y, Osawa Y, Osmond Foster J, O'Sullivan A, Otani T, Othman N, Otomo S, O'Toole J, Owen L, Ozawa T, Padiyar A, Page N, Pajak S, Paliege A, Pandey A, Pandey R, Pariani H, Park J, Parrigon M, Passauer J, Patecki M, Patel M, Patel R, Patel T, Patel Z, Paul R, Paul R, Paulsen L, Pavone L, Peixoto A, Peji J, Peng BC, Peng K, Pennino L, Pereira E, Perez E, Pergola P, Pesce F, Pessolano G, Petchey W, Petr EJ, Pfab T, Phelan P, Phillips R, Phillips T, Phipps M, Piccinni G, Pickett T, Pickworth S, Piemontese M, Pinto D, Piper J, Plummer-Morgan J, Poehler D, Polese L, Poma V, Pontremoli R, Postal A, Pötz C, Power A, Pradhan N, Pradhan R, Preiss D, Preiss E, Preston K, Prib N, Price L, Provenzano C, Pugay C, Pulido R, Putz F, Qiao Y, Quartagno R, Quashie-Akponeware M, Rabara R, Rabasa-Lhoret R, Radhakrishnan D, Radley M, Raff R, Raguwaran S, Rahbari-Oskoui F, Rahman M, Rahmat K, Ramadoss S, Ramanaidu S, Ramasamy S, Ramli R, Ramli S, Ramsey T, Rankin A, Rashidi A, Raymond L, Razali WAFA, Read K, Reiner H, Reisler A, Reith C, Renner J, Rettenmaier B, Richmond L, Rijos D, Rivera R, Rivers V, Robinson H, Rocco M, Rodriguez-Bachiller I, Rodriquez R, Roesch C, Roesch J, Rogers J, Rohnstock M, Rolfsmeier S, Roman M, Romo A, Rosati A, Rosenberg S, Ross T, Rossello X, Roura M, Roussel M, Rovner S, Roy S, Rucker S, Rump L, Ruocco M, Ruse S, Russo F, Russo M, Ryder M, Sabarai A, Saccà C, Sachson R, Sadler E, Safiee NS, Sahani M, Saillant A, Saini J, Saito C, Saito S, Sakaguchi K, Sakai M, Salim H, Salviani C, Sammons E, Sampson A, Samson F, Sandercock P, Sanguila S, Santorelli G, Santoro D, Sarabu N, Saram T, Sardell R, Sasajima H, Sasaki T, Satko S, Sato A, Sato D, Sato H, Sato H, Sato J, Sato T, Sato Y, Satoh M, Sawada K, Schanz M, Scheidemantel F, Schemmelmann M, Schettler E, Schettler V, Schlieper GR, Schmidt C, Schmidt G, Schmidt U, Schmidt-Gurtler H, Schmude M, Schneider A, Schneider I, Schneider-Danwitz C, Schomig M, Schramm T, Schreiber A, Schricker S, Schroppel B, Schulte-Kemna L, Schulz E, Schumacher B, Schuster A, Schwab A, Scolari F, Scott A, Seeger W, Seeger W, Segal M, Seifert L, Seifert M, Sekiya M, Sellars R, Seman MR, Shah S, Shah S, Shainberg L, Shanmuganathan M, Shao F, Sharma K, Sharpe C, Sheikh-Ali M, Sheldon J, Shenton C, Shepherd A, Shepperd M, Sheridan R, Sheriff Z, Shibata Y, Shigehara T, Shikata K, Shimamura K, Shimano H, Shimizu Y, Shimoda H, Shin K, Shivashankar G, Shojima N, Silva R, Sim CSB, Simmons K, Sinha S, Sitter T, Sivanandam S, Skipper M, Sloan K, Sloan L, Smith R, Smyth J, Sobande T, Sobata M, Somalanka S, Song X, Sonntag F, Sood B, Sor SY, Soufer J, Sparks H, Spatoliatore G, Spinola T, Squyres S, Srivastava A, Stanfield J, Staplin N, Staylor K, Steele A, Steen O, Steffl D, Stegbauer J, Stellbrink C, Stellbrink E, Stevens W, Stevenson A, Stewart-Ray V, Stickley J, Stoffler D, Stratmann B, Streitenberger S, Strutz F, Stubbs J, Stumpf J, Suazo N, Suchinda P, Suckling R, Sudin A, Sugamori K, Sugawara H, Sugawara K, Sugimoto D, Sugiyama H, Sugiyama H, Sugiyama T, Sullivan M, Sumi M, Suresh N, Sutton D, Suzuki H, Suzuki R, Suzuki Y, Suzuki Y, Suzuki Y, Swanson E, Swift P, Syed S, Szerlip H, Taal M, Taddeo M, Tailor C, Tajima K, Takagi M, Takahashi K, Takahashi K, Takahashi M, Takahashi T, Takahira E, Takai T, Takaoka M, Takeoka J, Takesada A, Takezawa M, Talbot M, Taliercio J, Talsania T, Tamori Y, Tamura R, Tamura Y, Tan CHH, Tan EZZ, Tanabe A, Tanabe K, Tanaka A, Tanaka A, Tanaka N, Tang S, Tang Z, Tanigaki K, Tarlac M, Tatsuzawa A, Tay JF, Tay LL, Taylor J, Taylor K, Taylor K, Te A, Tenbusch L, Teng KS, Terakawa A, Terry J, Tham ZD, Tholl S, Thomas G, Thong KM, Tietjen D, Timadjer A, Tindall H, Tipper S, Tobin K, Toda N, Tokuyama A, Tolibas M, Tomita A, Tomita T, Tomlinson J, Tonks L, Topf J, Topping S, Torp A, Torres A, Totaro F, Toth P, Toyonaga Y, Tripodi F, Trivedi K, Tropman E, Tschope D, Tse J, Tsuji K, Tsunekawa S, Tsunoda R, Tucky B, Tufail S, Tuffaha A, Turan E, Turner H, Turner J, Turner M, Tuttle KR, Tye YL, Tyler A, Tyler J, Uchi H, Uchida H, Uchida T, Uchida T, Udagawa T, Ueda S, Ueda Y, Ueki K, Ugni S, Ugwu E, Umeno R, Unekawa C, Uozumi K, Urquia K, Valleteau A, Valletta C, van Erp R, Vanhoy C, Varad V, Varma R, Varughese A, Vasquez P, Vasseur A, Veelken R, Velagapudi C, Verdel K, Vettoretti S, Vezzoli G, Vielhauer V, Viera R, Vilar E, Villaruel S, Vinall L, Vinathan J, Visnjic M, Voigt E, von-Eynatten M, Vourvou M, Wada J, Wada J, Wada T, Wada Y, Wakayama K, Wakita Y, Wallendszus K, Walters T, Wan Mohamad WH, Wang L, Wang W, Wang X, Wang X, Wang Y, Wanner C, Wanninayake S, Watada H, Watanabe K, Watanabe K, Watanabe M, Waterfall H, Watkins D, Watson S, Weaving L, Weber B, Webley Y, Webster A, Webster M, Weetman M, Wei W, Weihprecht H, Weiland L, Weinmann-Menke J, Weinreich T, Wendt R, Weng Y, Whalen M, Whalley G, Wheatley R, Wheeler A, Wheeler J, Whelton P, White K, Whitmore B, Whittaker S, Wiebel J, Wiley J, Wilkinson L, Willett M, Williams A, Williams E, Williams K, Williams T, Wilson A, Wilson P, Wincott L, Wines E, Winkelmann B, Winkler M, Winter-Goodwin B, Witczak J, Wittes J, Wittmann M, Wolf G, Wolf L, Wolfling R, Wong C, Wong E, Wong HS, Wong LW, Wong YH, Wonnacott A, Wood A, Wood L, Woodhouse H, Wooding N, Woodman A, Wren K, Wu J, Wu P, Xia S, Xiao H, Xiao X, Xie Y, Xu C, Xu Y, Xue H, Yahaya H, Yalamanchili H, Yamada A, Yamada N, Yamagata K, Yamaguchi M, Yamaji Y, Yamamoto A, Yamamoto S, Yamamoto S, Yamamoto T, Yamanaka A, Yamano T, Yamanouchi Y, Yamasaki N, Yamasaki Y, Yamasaki Y, Yamashita C, Yamauchi T, Yan Q, Yanagisawa E, Yang F, Yang L, Yano S, Yao S, Yao Y, Yarlagadda S, Yasuda Y, Yiu V, Yokoyama T, Yoshida S, Yoshidome E, Yoshikawa H, Young A, Young T, Yousif V, Yu H, Yu Y, Yuasa K, Yusof N, Zalunardo N, Zander B, Zani R, Zappulo F, Zayed M, Zemann B, Zettergren P, Zhang H, Zhang L, Zhang L, Zhang N, Zhang X, Zhao J, Zhao L, Zhao S, Zhao Z, Zhong H, Zhou N, Zhou S, Zhu D, Zhu L, Zhu S, Zietz M, Zippo M, Zirino F, Zulkipli FH. Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial. Lancet Diabetes Endocrinol 2024; 12:51-60. [PMID: 38061372 DOI: 10.1016/s2213-8587(23)00322-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. METHODS EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. FINDINGS Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). INTERPRETATION In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. FUNDING Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.
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Jia LH, Lin HL, Zheng SW, Lin XJ, Zhang D, Yu H. [Mitigating metal artifacts in cone-beam CT images through deep learning techniques]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 59:71-79. [PMID: 38172064 DOI: 10.3760/cma.j.cn112144-20231030-00233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Objective: To develop and evaluate metal artifact removal systems (MARSs) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images. Methods: A full-mouth standard model (60 mm×75 mm×110 mm) was three-dimensional (3D) printed using photosensitive resin. The model included a removable and replaceable target tooth position where cobalt-chromium alloy crowns with varying thicknesses were inserted to generate matched CBCT images. The artifacts resulting from cobalt-chromium alloys with different thicknesses were evaluated using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR). CNN-MARS and U-net-MARS were developed using a convolutional neural network and U-net architecture, respectively. The effectiveness of both MARSs were assessed through visualization and by measuring SSIM and PSNR values. The SSIM and PSNR values were statistically analyzed using one-way analysis of variance (α=0.05). Results: Significant differences were observed in the range of artifacts produced by different thicknesses of cobalt-chromium alloys (all P<0.05), with 1 mm resulting in the least artifacts. The SSIM values for specimens with thicknesses of 1.0 mm, 1.5 mm, and 2.0 mm were 0.916±0.019, 0.873±0.010, and 0.833±0.010, respectively (F=447.89, P<0.001). The corresponding PSNR values were 20.834±1.176, 17.002±0.427, and 14.673±0.429, respectively (F=796.51, P<0.001). After applying CNN-MARS and U-net-MARS to artifact removal, the SSIM and PSNR values significantly increased for images with the same thickness of metal (both P<0.05). When using the CNN-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.938±0.023, 0.930±0.029, and 0.928±0.020 (F=2.22, P=0.112), while the PSNR values were 30.938±1.495, 30.578±2.154 and 30.553±2.355 (F=0.54, P=0.585). When using the U-net-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.930±0.024, 0.932±0.017 and 0.930±0.012 (F=0.24, P=0.788), and the PSNR values were 30.291±0.934, 30.351±1.002 and 30.271±1.143 (F=0.07, P=0.929). No significant differences were found in SSIM and PSNR values after artifact removal using CNN-MARS and U-net-MARS for different thicknesses of cobalt-chromium alloys (all P>0.05). Visualization demonstrated a high degree of similarity between the images before and after artifact removal using both MARSs. However, CNN-MARS displayed clearer metal edges and preserved more tissue details when compared with U-net-MARS. Conclusions: Both the CNN-MARS and U-net-MARS models developed in this study effectively remove the metal artifacts and enhance the image quality. CNN-MARS exhibited an advantage in restoring tissue structure information around the artifacts compared to U-net-MARS.
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Affiliation(s)
- L H Jia
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University, Fuzhou 350002, China
| | - H L Lin
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University, Fuzhou 350002, China
| | - S W Zheng
- College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
| | - X J Lin
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University, Fuzhou 350002, China
| | - D Zhang
- College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
| | - H Yu
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University, Fuzhou 350002, China
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Su C, Lu ZC, Yu H. [10-Methacryloyloxydecyl dihydrogen phosphate in resin-to-zirconia bonding durability: a systematic review and meta-analysis]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 58:1281-1290. [PMID: 38061871 DOI: 10.3760/cma.j.cn112144-20230915-00158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Objective: To systematically assess the durability of the 10-methacryloyloxydecyl dihydrogen phosphate (10-MDP) pretreated resin-to-zirconia bonding and conducted a meta-analysis to provide clinical guidance on zirconia bonding strategies. Methods: A comprehensive search was conducted on PubMed, Scopus, Web of Science, CNKI, and Wanfang database to identify relevant studies on the resin-to-zirconia bonding after surface pretreatment with 10-MDP. Strict inclusion and exclusion criteria were applied to select appropriate literature and extract essential information and data. The included studies were categorized based on aging methods (water storage, thermocycling, or both), 10-MDP application methods (within primer, adhesive, resin cement, or both), and additional surface treatments (alumina sandblasting, tribochemical silica coating, acid etching, laser etching, and plasma treatment) and were analyzed by Review Manager 5.4. The evaluation indicator was the bonding strength of zirconia after surface pretreatment with 10-MDP. Results: A total of 72 studies were included in the systematic review, with 68 studies eligible for the meta-analysis. The bonding strength of zirconia decreased significantly after aging [P<0.001; mean difference (MD): 5.58; 95%CI: 5.11-6.05]. No significant differences in bonding strength of zirconia were observed after aging when employing various application methods of 10-MDP (all P>0.05). The bonding strength of zirconia was significantly enhanced after aging when 10-MDP was applied in conjunction with additional surface treatments, as compared to the application of 10-MDP alone (P<0.001; MD: 10.17; 95%CI: 8.20-12.14). Conclusions: The bonding strength of zirconia pretreated with 10-MDP exhibited a reduction after undergoing water storage or thermocycling. The application of 10-MDP with additional surface treatments enhanced the bonding strength of zirconia after aging, while the application methods of 10-MDP did not exert an influence.
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Affiliation(s)
- C Su
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University & Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University & Institute of Stomatology, Fujian Medical University & Research Center of Dental Esthetics and Biomechanics, Fujian Medical University, Fuzhou 350002, China
| | - Z C Lu
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University & Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University & Institute of Stomatology, Fujian Medical University & Research Center of Dental Esthetics and Biomechanics, Fujian Medical University, Fuzhou 350002, China
| | - H Yu
- Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University & Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University & Institute of Stomatology, Fujian Medical University & Research Center of Dental Esthetics and Biomechanics, Fujian Medical University, Fuzhou 350002, China
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Huang X, Li L, Chen Z, Yu H, You X, Kong N, Tao W, Zhou X, Huang J. Nanomedicine for the Detection and Treatment of Ocular Bacterial Infections. Adv Mater 2023; 35:e2302431. [PMID: 37231939 DOI: 10.1002/adma.202302431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/15/2023] [Indexed: 05/27/2023]
Abstract
Ocular bacterial infection is a prevalent cause of blindness worldwide, with substantial consequences for normal human life. Traditional treatments for ocular bacterial infections areless effective, necessitating the development of novel techniques to enable accurate diagnosis, precise drug delivery, and effective treatment alternatives. With the rapid advancement of nanoscience and biomedicine, increasing emphasis has been placed on multifunctional nanosystems to overcome the challenges posed by ocular bacterial infections. Given the advantages of nanotechnology in the biomedical industry, it can be utilized to diagnose ocular bacterial infections, administer medications, and treat them. In this review, the recent advancements in nanosystems for the detection and treatment of ocular bacterial infections are discussed; this includes the latest application scenarios of nanomaterials for ocular bacterial infections, in addition to the impact of their essential characteristics on bioavailability, tissue permeability, and inflammatory microenvironment. Through an in-depth investigation into the effect of sophisticated ocular barriers, antibacterial drug formulations, and ocular metabolism on drug delivery systems, this review highlights the challenges faced by ophthalmic medicine and encourages basic research and future clinical transformation based on ophthalmic antibacterial nanomedicine.
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Affiliation(s)
- Xiaomin Huang
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University; Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200030, China
- Shanghai Research Center of Ophthalmology and Optometry, Shanghai, 200030, China
- Wenzhou Medical University, Wenzhou, Zhejiang, 325027, China
| | - Luoyuan Li
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University; Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200030, China
- Shanghai Research Center of Ophthalmology and Optometry, Shanghai, 200030, China
- The Eighth Affiliated Hospital Sun Yat-sen University, Shenzhen, Guangdong, 518033, P. R. China
| | - Zhongxing Chen
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University; Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200030, China
- Shanghai Research Center of Ophthalmology and Optometry, Shanghai, 200030, China
| | - Haoyu Yu
- The Eighth Affiliated Hospital Sun Yat-sen University, Shenzhen, Guangdong, 518033, P. R. China
| | - Xinru You
- Center for Nanomedicine and Department of Anesthesiology Brigham and Women's Hospital Harvard Medical School, Boston, MA, 02115, USA
| | - Na Kong
- Center for Nanomedicine and Department of Anesthesiology Brigham and Women's Hospital Harvard Medical School, Boston, MA, 02115, USA
| | - Wei Tao
- Center for Nanomedicine and Department of Anesthesiology Brigham and Women's Hospital Harvard Medical School, Boston, MA, 02115, USA
| | - Xingtao Zhou
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University; Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200030, China
- Shanghai Research Center of Ophthalmology and Optometry, Shanghai, 200030, China
| | - Jinhai Huang
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University; Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, 200030, China
- Shanghai Research Center of Ophthalmology and Optometry, Shanghai, 200030, China
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Liu K, Chen YJ, Su J, Fan XK, Yu H, Qin Y, Yang J, Zhu Z, Guan HY, Shen C, Pan EC, Lu Y, Zhou JY, Wu M. [Association of category of dietary intake and physical activity with the risk of mortality in patients with type 2 diabetes mellitus: a prospective cohort study]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1591-1598. [PMID: 37875446 DOI: 10.3760/cma.j.cn112338-20230328-00188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objective: To investigate the association between dietary intake and physical activity category and their combined effects on all-cause and cause-specific mortality risk in patients with type 2 diabetes mellitus (T2DM). Methods: Between December 2013 and December 2021, a prospective cohort study was conducted on 19 863 T2DM patients in Changshu City, Qingjiangpu District (formerly Qinghe District), and Huai'an District, included in the national basic health service management. Information on deaths and underlying causes of death was obtained from the Jiangsu Provincial CDC and Prevention Death Surveillance System. Cox proportional hazards models were used to estimate the intensity of associations between dietary intake, physical activity, and their combined effects with all-cause and cause-specific mortality in patients with T2DM. Results: As of December 31, 2021, the research subjects had been followed up for 150 283 person-years, with a median follow-up time of 8.15 years. During the follow-up period, 3 293 people died, including 1 124 deaths from cardiovascular disease (CVD) and 875 deaths from cancer. Cox regression analysis showed that compared with the population of 0-1 recommended food group, those having more than five recommended food groups had a 19% lower risk of all-cause mortality [hazard ratio (HR)=0.81, 95%CI: 0.70-0.94] and a 33% lower risk of all-cause mortality (HR=0.67, 95%CI: 0.52-0.87). Compared with the T2DM population in the physical activity Q1 group, the risk of all-cause mortality, CVD mortality, and cancer mortality among the physical activity Q4 group reduced by 50% (HR=0.50, 95%CI: 0.45-0.56), 50% (HR=0.50, 95%CI: 0.41-0.61), and 27% (HR=0.73, 95%CI: 0.60-0.88), respectively. The combined effect showed that compared with the population in the intake of food categories 0-2 and low physical activity groups, the risk of all-cause, CVD mortality, and cancer mortality in the intake of food categories 4-9 and high physical activity groups reduced by 55% (HR=0.45, 95%CI: 0.38-0.53), 56% (HR=0.44, 95%CI: 0.32-0.59), and 40% (HR=0.60, 95%CI: 0.44-0.82), respectively. Conclusion: Type of dietary intake, physical activity, and their combined effects are associated with a reduced mortality risk in patients with T2DM.
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Affiliation(s)
- K Liu
- School of Public Health, Southeast University, Nanjing 210009, China
| | - Y J Chen
- Department of Non-communicable Chronic Disease Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing 210003, China
| | - J Su
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - X K Fan
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Y Qin
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Yang
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Z Zhu
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Y Guan
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - C Shen
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - E C Pan
- Department of Chronic Disease Prevention and Control, Huai'an City Center for Disease Control and Prevention, Huai'an 223001, China
| | - Y Lu
- Department of Chronic Disease Prevention and Control, Suzhou City Center for Disease Control and Prevention, Suzhou 215004, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - M Wu
- School of Public Health, Southeast University, Nanjing 210009, China Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
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Wang H, Yu H, Zhou YY, Cong WM, Dong H. [Combined hepatocellular-cholangiocarcinoma containing both large and small duct type cholangiocarcinoma: report of a case]. Zhonghua Bing Li Xue Za Zhi 2023; 52:1047-1049. [PMID: 37805401 DOI: 10.3760/cma.j.cn112151-20230110-00020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/09/2023]
Affiliation(s)
- H Wang
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
| | - H Yu
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
| | - Y Y Zhou
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
| | - W M Cong
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
| | - H Dong
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
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Yu J, Jiang L, Zhao L, Wang X, Yang X, Yang D, Zhuo M, Chen H, Zhao YD, Zhou F, Li Q, Zhu Z, Chu L, Ma Z, Wang Q, Qu Y, Huang W, Zhang M, Gu T, Liu S, Yang Y, Yang J, Yu H, Yu R, Zhao J, Shi A. High Dose Hyperfractionated Thoracic Radiotherapy vs. Standard Dose for Limited Stage Small-Cell Lung Cancer: A Multicenter, Open-Label Randomized, Phase 3 Trial. Int J Radiat Oncol Biol Phys 2023; 117:S1. [PMID: 37784261 DOI: 10.1016/j.ijrobp.2023.06.205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Limited stage small-cell lung cancer (LS-SCLC) is associated with poor prognosis. We aimed to assess the efficacy and safety of high-dose, hyperfractionated thoracic radiotherapy of 54 Gy in 30 fractions compared with standard dose (45 Gy in 30 fractions) as a first-line treatment for LS-SCLC. MATERIALS/METHODS The study was an open-label, randomized, phase 3 trial, done at 16 public hospitals in China. Key inclusion criteria were patients aged 18-70 years, with previously histologically or cytologically confirmed LS-SCLC, previously untreated or received 1-2 courses of intravenous cisplatin (75 mg/m²of body-surface area, on day 1 or divided into two days of each cycle) or carboplatin (area under the curve of 5 mg/mL per min, day 1 of each cycle)and intravenous etoposide (100 mg/m²of body-surface area, on days 1-3 of each cycle), and an Eastern Cooperative Oncology Group (ECOG) performance status of 0-1.Eligible patients were randomly assigned (1:1) to receive volumetric-modulated arc radiotherapy (VMAT) of 45 Gy in 30 fractions or the simultaneous integrated boost VMAT (SIB-VMAT) of 54 Gy in 30 fractions to the primary lung tumor and lymph node metastases starting 0-42 days after the first chemotherapy course. Both groups of patients received thoracic radiotherapy twice per day and 10 fractions per week. Prophylactic cranial radiation (PCI, 25 Gy in 10 fractions) was implemented to patients with responsive disease. The primary endpoint was overall survival. Safety was analyzed in the as-treated population. RESULTS Between June 30, 2017, and April 6, 2021, 224 eligible patients were enrolled and randomly assigned to 54 Gy (n = 108) or 45 Gy (n = 116). Median follow-up for the primary analysis was 45 months (IQR 41-48). Median overall survival was significantly improved in the 54 Gy group (62.4 months) compared with the 45 Gy group (43.1 months; p = 0.001). Median progression-free survival was significantly improved in the 54 Gy group (30.5 months) compared with the 45 Gy group (16.7 months; p = 0.044). The most common grade 3-4 adverse events were neutropenia (30 [28%] of 108 patients in the 54 Gy group vs 27 [23%] of 116 patients in the 45 Gy group), neutropenic infections (6 [6%] vs 2 [2%]), thrombocytopenia (13 [12%] vs 12 [10%]), anemia (6 [6%] vs 4 [3%]), and esophagitis (1 [1%] vs 3 [3%]). Treatment-related serious adverse events occurred in 9 [8%] patients in the 54 Gy group and 16 [14%] patients in the 45 Gy group. There were one treatment-related deaths in 54 Gy group (myocardial infarction). CONCLUSION Compared with standard thoracic radiotherapy dose of 45 Gy, the high dose of 54 Gy improved overall survival and progression-free survival without increasing toxicities in patients with LS-SCLC, supporting twice-daily hyperfractionated thoracic radiotherapy of 54 Gy with concurrent chemotherapy is an alternative treatment option for LS-SCLC. This study is complete and registered with ClinicalTrials.gov, NCT03214003.
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Affiliation(s)
- J Yu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - L Jiang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - L Zhao
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University. ty, Xi'an, China
| | - X Wang
- Department of Radiation Oncology, Anyang Cancer Hospital, Anyang, China
| | - X Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Medical Oncology, Peking University Cancer Hospital and Institute, Beijing, China., Beijing, China
| | - D Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - M Zhuo
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Medical Oncology, Peking University Cancer Hospital and Institute, Beijing, China., Beijing, China
| | - H Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Medical Oncology, Peking University Cancer Hospital and Institute, Beijing, China., Beijing, China
| | - Y D Zhao
- Department of Radiation Oncology, Anyang Tumor Hospital, Anyang, China
| | - F Zhou
- Yantai Yuhuangding Hospital, Yantai, China
| | - Q Li
- Ordos School of Clinical Medicine I.M.M.U, Ordos, China
| | - Z Zhu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - L Chu
- Fudan University Shanghai Cancer Center, Shanghai, China
| | - Z Ma
- Chifeng Affiliated Hospital, Chifeng, China
| | - Q Wang
- Department of Radiation Oncology, Sichuan Cancer Hospital and Institution, Chengdu, China
| | - Y Qu
- Liaoning cancer hospital & institute, Shenyang, China
| | - W Huang
- Shandong Cancer Hospital & Institute, Jinan, Shandong, China
| | - M Zhang
- Department of Radiation Oncology, Peking University People's Hospital, Beijing, China; Department of Radiation Oncology, Peking University First Hospital, Peking University, Beijing, China
| | - T Gu
- The First Hospital of Qinhuangdao, Qinhuangdao, China
| | - S Liu
- Jilin Provincial Cancer Hospital, Changchun, China
| | - Y Yang
- Jilin Provincial Cancer Hospital, Changchun, China
| | - J Yang
- Department of Oncology, The first Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - H Yu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - R Yu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - J Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Thoracic Medical Oncology, Peking University Cancer Hospital and Institute, Beijing, China., Beijing, China
| | - A Shi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
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Chen F, Zhou P, Lee KW, Liu Q, Helali AE, Jin JY, Lee AWM, Yu H, Kong FM. Interpretable Deep Learning Identified the Significance of 1 Gy Volume on Lymphopenia after Radiotherapy in Breast Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e168. [PMID: 37784771 DOI: 10.1016/j.ijrobp.2023.06.1006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Lymphopenia is common after radiotherapy (RT) and is known for its significance on poor survival outcomes in patients with breast cancer. Previous work has demonstrated the significance of point dosimetric factors like the volume receiving 5 Gy. Considering the full dosimetric data together, this study aimed to develop and validate predictive models for lymphopenia after RT in breast cancer. MATERIALS/METHODS Patients with breast cancer treated with radiation therapy in adjuvant setting and with complete dosimetric data were eligible. Combining dose-volume histogram (DVH) dosimetric and clinical factors, dense neural network (DNN) models were developed to predict both the reduction in lymphocyte counts and the graded lymphopenia in breast cancer patients after adjuvant RT. A Shapley additive explanation was applied to explain each feature's directional contributions. The generalization of DNN models was validated in both internal and independent external validation cohorts. P<0.05 was considered to be significant. RESULTS A total of 928 consecutive patients with invasive breast cancer were eligible for this study. Treatment volumes of nearly all irradiation dose levels of DVH were significant predictors for lymphopenia after RT, including volumes at very low-dose 1 Gy (V1) of all structures considered including the lung, heart and body. DNN models using full DVH dosimetric and clinical factors were built and a simplified model was further established and validated in both internal and external validation cohorts. This simplified DNN AI model, combining full DVH dosimetric parameters of all OARs and five key clinical factors including baseline lymphocyte counts, tumor stage, RT technique, RT fields and RT fractionation, showed a predictive accuracy of 77% and above. CONCLUSION This study demonstrated and externally validated the significance of an AI model of combining clinical and full dosimetric data, especially the volume of low dose at as low as 1 Gy of all critical structures on lymphopenia after RT in patients with breast cancer. The significance of V1 deserves special attention, as modern arc RT technology often has relatively high value of this parameter. Further study warranted for breast cancer RT plan optimization.
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Affiliation(s)
- F Chen
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, China; The University of Hong Kong, Hong Kong, China
| | - P Zhou
- Department of Radiotherapy, The First Affiliated Hospital of Hainan Medical University, Haikou, China
| | - K W Lee
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - Q Liu
- The University of Hong Kong, Hong Kong, China
| | - A E Helali
- The University of Hong Kong, Hong Kong, China
| | - J Y Jin
- School of biomedical engineering, Capital Medical University, Beijing, China
| | - A W M Lee
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - H Yu
- Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology, Shenzhen, China, Shenzhen, China
| | - F M Kong
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, China; The University of Hong Kong, Hong Kong, China
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Zhou Z, Wang Y, Zhao F, Yao G, Yu H, Yu H, Bu L, Lu Z, Yan S. Radiation Induced Lung Injury in Rats after Pre-Oxygenation Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e279-e280. [PMID: 37785046 DOI: 10.1016/j.ijrobp.2023.06.1260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Deep inspiratory breath holding (DIBH) has been widely used during the radiotherapy of thoracic tumors. The main disadvantage of voluntary DIBH is the short duration of each breath hold. The hypocapnia induced by hyperoxia (oxygen concentration > 50%) pre-oxygenation (PreO2) combined with mechanical hyperventilation has been reported to prolong the duration of single breath hold, but its safety remains controversial, especially the sensitivity of lung tissue to radiation damage under hyperoxia exposure has not been elucidated. In this study, we aim to investigate the changes of radiation induced lung injury in rats after PreO2 radiation. MATERIALS/METHODS We evaluated the lung tissue of rats at different time points (48h, 2w, 4w, 8w, 12w) after thoracic radiation (15Gy single fraction to the right lung), and sequenced the transcriptome of lung tissue at 48 hours after irradiation. Rat cohorts (n = 7/group): 1. Control (Con); 2. Radiation group (RT); 3. Pre-oxygenation (oxygen concentration > 90%) for 8 hours before thoracic radiation (PreO2). RESULTS The inflammatory exudation emerged in the pulmonary interstitium at 48 hours, and reached the most serious alveolitis after four weeks of irradiation (the comparison of alveolitis scores in RT4w vs Con4w and PreO2(4w) vs Con4w, P<0.001) on hematoxylin-eosin staining. While the alveolitis scores in RT group and PreO2 group were not statistically different at each time point. Masson staining showed that the pulmonary fibrosis in the RT group and the PreO2 group reached an obvious pathological change at 12 weeks after irradiation, but the difference between the two groups was not significant. Transcriptome sequencing showed that the number of differential genes in PreO2 vs Con was 559 (302 up-regulated genes and 257 down-regulated genes). The GO enrichment analysis indicated that chromosome segregation was the most significant functional item with P value in the comparative analysis, and the KEGG enrichment analysis suggested that cell division was the most significant enrichment pathway of these differential genes. While there was a small quantity of differential genes in PreO2 vs RT group (3 up-regulated genes and 12 down-regulated genes). Pentose and glucuronate conversions were the most significant enrichment pathway of these differential genes. CONCLUSION This study demonstrated that PreO2 radiotherapy did not increase the severity of radiation induced lung injury in rats compared to conventional radiotherapy. Further study should be conducted to confirm these results and to investigate the regulatory mechanism of pneumonia caused by PreO2 radiotherapy.
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Affiliation(s)
- Z Zhou
- Department of Radiation Oncology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Y Wang
- Department of Radiation Oncology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - F Zhao
- Department of Radiation Oncology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - G Yao
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - H Yu
- The First Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, China
| | - H Yu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - L Bu
- Department of Radiation Oncology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Z Lu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - S Yan
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Zhang Y, Ye X, Ge J, Guo D, Zheng D, Yu H, Chen Y, Yao G, Lu Z, Yuille A, Lu L, Jin D, Yan S. Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma. Int J Radiat Oncol Biol Phys 2023; 117:e498. [PMID: 37785566 DOI: 10.1016/j.ijrobp.2023.06.1739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The delineation of primary gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) is an essential step for radiotherapy planning. In clinical practice, radiation oncologists manually delineate the GTV in planning CT with the help of diagnostic MRI. This is because NPC tumors are closely adjacent to many important anatomic structures, and CT and MRI provide complementary strength to accurately determine the tumor extension boundary. Manual delineation is time-consuming with the potential registration errors between MRI and CT decreasing the delineation accuracy. In this study, we propose a fully automated GTV segmentation method based on CT and MRI by first aligning MRI to CT, and then, segmenting the GTV using a multi-modality deep learning model. MATERIALS/METHODS We collected 104 nasopharyngeal carcinoma patients with both planning CT and diagnostic MRI scans (T1 & T2 phases). An experienced radiation oncologists manually delineated the GTV, which was further examined by another senior radiation oncologist. Then, a coarse to fine cross-modality registration from MRI to CT was conducted as follows: (1) A rigid transformation was performed on MRI to roughly align MRI to CT with similar anatomic position. (2) Then, the region of interest (RoI) on both CT and rigid-transformed MRI were cropped. (3) A leading cross-modality deformable registration algorithm, named DEEDS, was applied on the cropped MRI and CT RoIs to find an accurate local alignment. Next, using CT and registered MRI as the combined input, a multi-modality deep segmentation network based on nnUNet was trained to generate the GTV prediction. 20% patients were randomly selected as the unseen testing set to quantitatively evaluate the performance. RESULTS The quantitative NPC GTV segmentation performance is summarized in Table 1. The deep segmentation model using CT alone achieved reasonable high performance with 76.6% Dice score and 1.34mm average surface distance (ASD). When both CT and registered MRI were used, the segmentation model further improved the performance by 0.9% Dice score increase and 11% relative ASD error reduction, demonstrating the complementary strength of CT and MRI in determining NPC GTV. Notably, the achieved 77.5% Dice score and 1.19mm ASD by the multimodality model is among the top performing results reported in recent automatic NPC GTV segmentation using either CT or MRI modality. CONCLUSION We developed a fully automated multi-modal deep-learning model for NPC GTV segmentation. The developed model can segment the NPC GTV in high accuracy. With further optimization and validation, this automated model has potential to standardize the NPC GTV segmentation and significantly decrease the workload of radiation oncologists in clinical practice.
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Affiliation(s)
- Y Zhang
- Johns Hopkins University, Baltimore, MD
| | - X Ye
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - J Ge
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - D Guo
- Alibaba Group (US) Inc., New York, NY
| | - D Zheng
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - H Yu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Y Chen
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - G Yao
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Z Lu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - A Yuille
- Johns Hopkins University, Baltimore, MD
| | - L Lu
- Alibaba Group (US) Inc., New York, NY
| | - D Jin
- Alibaba Group (US) Inc., New York, NY
| | - S Yan
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Park SH, Jeong S, Yu H, Woo D, Chong GO, Han HS, Kim J. Deep Learning vs. Handcrafted Radiomics to Predict Chemoradiotherapy Response for Locally Advanced Cervical Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e480. [PMID: 37785521 DOI: 10.1016/j.ijrobp.2023.06.1700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To predict CRT response in locally advanced cervical cancer (LACC) with handcrafted radiomics (HCR) and deep learning radiomics (DLR) using pretreatment MRI. Furthermore, we investigate whether the incorporation of clinical factors improves prediction performance. MATERIALS/METHODS Two hundred and fifty-two patients with LACC are enrolled. All patients are treated with external beam radiotherapy, followed by high-dose-rate intracavitary brachytherapy with concurrent cisplatin. The patients are randomly divided into two independent groups for the training (167 patients) and test datasets (85 patients). Contrast-enhanced T1- and T2-weighted MR scans are obtained. Patients in the training and test sets have similar characteristics in terms of age, tumor size, FIGO stage, HPV infection status, or CRT response. For HCR analysis, 1890 imaging features are extracted and a support vector machine classifier with a five-fold cross-validation is trained using training dataset to predict CRT response and validated using test dataset. For DLR analysis, a 3-dimensional convolutional neural network was trained and validated using test dataset. RESULTS A comparison of the DLR and HCR models reveals that the DLR model exhibits better prediction performance than the HCR model for the test dataset (AUC = 0.721 vs. 0.597, p = 0.097). The incorporation of clinical factors could improve performance in both DLR and HCR models. CONCLUSION The DLR models outperform the HCR models in predicting CRT responses in patients with LACC. Combining clinical factors and MRI may improve the prediction performance in both HCR and DLR analyses.
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Affiliation(s)
- S H Park
- Department of Radiation Oncology, School of Medicine, Kyungpook National University, Daegu, Korea, Republic of (South) Korea
| | - S Jeong
- Department of Medical Informatics, School of Medicine, Kyungpook National University, Daegu, Korea, Republic of (South) Korea; Research Center for Artificial Intelligence in Medicine, Kyungpook National University Hospital, Daegu, Korea, Republic of (South) Korea
| | - H Yu
- Research Center for Artificial Intelligence in Medicine, Kyungpook National University Hospital, Daegu, Korea, Republic of (South) Korea
| | - D Woo
- Research Center for Artificial Intelligence in Medicine, Kyungpook National University Hospital, Daegu, Korea, Republic of (South) Korea
| | - G O Chong
- Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Daegu, Korea, Republic of (South) Korea; Clinical Omics Research Center, School of Medicine, Kyungpook National University, Daegu, Korea, Republic of (South) Korea
| | - H S Han
- Clinical Omics Research Center, School of Medicine, Kyungpook National University, Daegu, Korea, Republic of (South) Korea; Department of Physiology, School of Medicine, Kyungpook National University, Daegu, Korea, Republic of (South) Korea
| | - J Kim
- Department of Radiation Oncology, School of Medicine, Kyungpook National University, Daegu, Korea, Republic of (South) Korea
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Danyang Z, Xu Z, Ye B, Zhang Y, Zhao C, Xu W, Liang Z, Yu H, Kong FM. Single-Cell and Spatial Transcriptomics Revealing the Role of IDO1 in HPV+ Cervical Cancer Tumor Immune Microenvironment and Its Implications in Radiotherapy and Immunotherapy. Int J Radiat Oncol Biol Phys 2023; 117:S157-S158. [PMID: 37784395 DOI: 10.1016/j.ijrobp.2023.06.583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Persistent infection of human papillomavirus (HPV) is one major etiology of cervical cancer (CC). By now, anti-PD-1 immunotherapy is approved for advanced CC patients, but the response rate was just about 10-20%, tumor immune microenvironment (TIME) might be one factor that affect the efficacy. The indoleamine 2,3-dioxygenase (IDO), a metabolic immune checkpoint, is recently shown to have a correlation-ship with HPV carcinogenesis in CC, with unknown mechanism. This study, using the single cell transcriptomic single-cell sequencing and spatial transcription sequencing analysis/immunologic technology, aimed to exam the role of IDO1 expression in HPV+ CC TIME and explore the changes after radiotherapy. MATERIALS/METHODS Newly diagnosed advanced HPV- CC and HPV+ CC patients were tested for the tumor and tumor immune microenvironment (TIME) heterogeneity and their changes after fractionated radiation therapy. Tumor tissues were collected, single cell suspension was made for Single-cell RNA sequencing (SCRNAseq) using the 10 × Genomics, while frozen tissue was embedded for spatial transcriptome sequencing (STRNAseq). Seurat 4.0 was used to cluster and annotate cell clusters and map SCRNAseq data to the STRNAseq data. The specific characters of cell clusters were computed by Gene Set Enrichment Analysis (GSEA). SPOTLight and CellChat were used to analyze cell location and interaction respectively. RESULTS A total of 28631 cells were clustered into 31 cell subsets in HPV- CC and HPV+ CC tissues, including baseline (Pre HPV- CC and Pre HPV+ CC) and 3-week after radiotherapy (Post 3w HPV- CC and Post 3w HPV+CC). There were 10431 epithelial cells (Epi) in all these 4 tumor tissues, with heterogenous IDO1 expression, including IDO1-high Epi, IDO1-low Epi, and IDO1-neg Epi. Interestingly, more than 99% of Epi in Pre HPV- CC tissues were IDO1-neg cells, while more than 99% in Pre HPV+ CC tissue were IDO1-high. Furthermore, the proportion of IDO1-high Epi in Pre HPV+ CC patient dropped to 16.7% after radiotherapy, while the proportion of IDO1-low Epi rase to 63.3%. Using GSEA, the characters of IDO1-high Epi group was shown to have positive regulation of leukocyte chemotaxis and negative regulation of cell adhesion and differentiation. IDO1-high Epi cells also had the hallmark of interferon gamma response. These cells could mainly receive regulative information of interferon gamma pathway from exhausted CD8 T cells, which could affect the apoptosis of tumor cells. CONCLUSION This study comprehensively analyzed the immune suppressive role of IDO1-high Epi cells in HPV+ CC TIME at the single-cell transcriptional scale and explored their functional characters in CC radiotherapy. This would be able to provide more evidence to combine with radiotherapy and immunotherapy to improve patients' prognosis.
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Affiliation(s)
- Z Danyang
- the University of Hong Kong, Hong Kong, China; Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Z Xu
- University of Virginia Health System, Charlottesville, VA
| | - B Ye
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Y Zhang
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - C Zhao
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - W Xu
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - Z Liang
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - H Yu
- Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology, Shenzhen, China, Shenzhen, China
| | - F M Kong
- The University of Hong Kong, Hong Kong, China
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Iovoli AJ, Yu H, Advani PG, Malhotra H, Fung-Kee-Fung S, Malik NK, Singh AK, Farrugia MK. Sinoatrial Node Irradiation in Patients Undergoing Definitive Stereotactic Body Radiation Therapy (SBRT) for Central Lung Cancers. Int J Radiat Oncol Biol Phys 2023; 117:e27. [PMID: 37785020 DOI: 10.1016/j.ijrobp.2023.06.707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The clinical consequences of sinoatrial node (SAN) and atrioventricular node (AVN) irradiation in patients undergoing thoracic stereotactic body radiation therapy (SBRT) remains unclear. We examined the relationship between SAN and AVN dose with survival outcomes in patients with central non-small cell lung cancer (NSCLC) tumors. MATERIALS/METHODS A single-institutional retrospective review of patients with primary NSCLC undergoing definitive SBRT for centrally located tumors from February 2007 to December 2021 was performed. Central tumors were defined as within 2 cm of the proximal airway, mediastinum, great vessels, or spinal cord whereas ultracentral tumors were directly abutting any of the above structures. All patients underwent five-fraction SBRT to a total dose of 50 to 60 Gy. The SAN and AVN were contoured in accordance with a published contouring atlas and the maximum dose (Dmax) and mean dose (Dmean) for each structure were calculated. Sequential log rank testing between the 50th and 90th percentiles was used to identify potential cutoff values for the corresponding dosimetric parameters and non-cancer associated survival. RESULTS Among 93 eligible patients, the median age was 72.5 years (Inter-Quartile Range [IQR], 66.6-78.3), median follow up was 32.4 months (IQR, 13.0-49.6), and 48 patients were female (52%). There were 49 ultracentral tumors (53%) and the median planning target volume (PTV) was 31.0 cc (IQR, 18.0-53.3). The median SAN Dmax and Dmean were 95 cGy (IQR, 37-1,072) and 58 cGy (IQR, 26-641), respectively. The median AVN Dmax and Dmean were 45 cGy (IQR, 19-506) and 34 cGy (IQR, 15-160), respectively. Candidate cutoff values for SAN Dmax and Dmean were 1,309 cGy and 814 cGy, respectively. No significant cutoff values were identified for either AVN parameter. Kaplan-Meier analysis for the proposed SAN Dmean constraint was significantly associated with overall (p = 0.016) and non-cancer associated survival (p = 0.028). The SAN Dmax constraint was significantly associated with only overall survival (p = 0.029). In a multivariate model, the SAN Dmean cutoff significantly correlated with both overall (Hazard Ratio [HR] 2.1 [1.13-3.78], p = 0.019) and non-cancer associated survival (HR 2.39 [1.12-5.10], p = 0.025) whereas the SAN Dmax cutoff was only significantly associated with overall survival (HR 1.95 [1.03-3.68], p = 0.041). CONCLUSION SAN Dmax and Dmean were associated with significantly worse overall survival using cut-off values of 1,309 cGy and 814 cGy, respectively. SAN dose should be considered in radiation planning and further study on the consequence of SAN irradiation during SBRT is warranted.
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Affiliation(s)
- A J Iovoli
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
| | - H Yu
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
| | - P G Advani
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
| | - H Malhotra
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
| | | | - N K Malik
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
| | - A K Singh
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
| | - M K Farrugia
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
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Veeraraghavan H, Jiang J, Jee J, Lebow ES, Deasy JO, Rimner A, Shaverdian N, Yu H, Gomez DR. AI Serial Image Prediction of Progression-Free Survival (PFS) for Locally Advanced Non-Small Cell Lung Cancer (LA-NSCLC) Patients Treated with Chemoradiation (CRT) and Durvalumab Consolidation. Int J Radiat Oncol Biol Phys 2023; 117:e68. [PMID: 37786001 DOI: 10.1016/j.ijrobp.2023.06.796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Patient outcomes with definitive CRT for LA-NSCLC remain poor, with no imaging biomarkers to predict benefit. Hence, we developed a serial image AI model using paired planning CT (pCT) and first week cone-beam CT (CBCT) to predict PFS and measured AI model fairness defined as the bias in the classification with respect to gender as a protected attribute. MATERIALS/METHODS Sixty-four consecutive patients with LA-NSCLC treated with concurrent CRT to 60 Gy in 30 fractions and durvalumab consolidation were analyzed. Three prediction models were created. A previously developed AI image foundation model [1] was pre-trained with unlabeled 6,402 3D CT scans sourced from institutional and the Cancer Imaging Archive and modified to predict PFS as a binarized outcome (high PFS > 6 months and low PFS < 6 months) using pCT scans. Serial image AI model was created by adding the first week CBCT scan. The third model measured tumor growth rate (TGR) as relative change in tumor and nodal volume from pCT to CBCT derived using a different published AI model [2]. Association with PFS using univariable and multivariable Cox regression after adjusting for age, gender, planning tumor volume, and smoking status were measured using TGR and the two AI model predictions using a cutoff of > 50% probability for low PFS. AI model fairness metrics area under receiver operating curve (AUROC), precision, sensitivity, and specificity were computed. RESULTS TGR was not associated with PFS on univariate (Hazard ratio [HR] of 1.515, 95% confidence interval [CI] of 0.32 to 7.26, p = 0.60) or multivariate analysis (HR: 1.58, 95% CI: 0.32 to 7.80, p = 0.58) and resulted in a Harrell's C-index of 54.7%. The serial image AI model prediction was associated with PFS in both univariable (HR: 2.12, 95% CI: 1.02 to 4.40, p = 0.045) and multivariable analysis (HR 2.39, 95% CI of 1.09 to 5.25, p = 0.029), and a C-index of 62.5%. The pCT AI model was associated with PFS in univariate (HR 2.06, 95% CI of 1.06 to 4.01, p = 0.034) but not in multivariable analysis (HR 1.89, 95% CI of 0.93 to 3.87, p = 0.08), and a C-index of 59.9%. The serial image AI model reduced the parity in classification compared to pCT AI model indicating higher fairness (Table I). CONCLUSION The multi-image AI model predicted PFS with slightly higher accuracy and resulted in higher fairness than the pCT AI model. These results underscore the potential for incorporating multi-imaging biomarkers to predict treatment response.
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Affiliation(s)
- H Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - J Jiang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - J Jee
- Memorial Sloan Kettering Cancer Center, New York, NY
| | - E S Lebow
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - J O Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - A Rimner
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - N Shaverdian
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - H Yu
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - D R Gomez
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
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Chen X, Yu H. Fast Feature Extraction Method for Brillouin Scattering Spectrum of OPGW Optical Cable Based on BOTDR. Sensors (Basel) 2023; 23:8166. [PMID: 37836997 PMCID: PMC10575460 DOI: 10.3390/s23198166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/23/2023] [Accepted: 09/26/2023] [Indexed: 10/15/2023]
Abstract
Brillouin optical time domain reflectometry (BOTDR) detects fiber temperature and strain data and represents one of the most critical ways of identifying abnormal conditions such as ice coverage and lightning strikes on optical fiber composite overhead ground wire (OPGW) cable. Existing BOTDR extracts brillouin frequency shift (BFS) features with cumulative averaging and curve fitting. BFS feature extraction is slow for long-distance measurements, making realizing real-time measurements on fiber optic cables challenging. We propose a fast feature extraction method for block matching and 3D filtering (BM3D) + Sobel brillouin scattering spectroscopy (BGS). BM3D takes the advantage of non-local means (NLM) and wavelet denoising (WD) and utilizes the spatial-domain non-local principle to enhance the denoising in the transform domain. The global filtering capability of BM3D is utilized to filter out the low cumulative average BGS noise and the BFS feature extraction is completed using Sobel edge detection. Simulation verifies the feasibility of the algorithm, and the proposed method is embedded in BOTDR to measure 30 km of actual OPGW line. The experimental results show that under the same conditions, the processing time of this method is reduced by 37 times compared to that with the 50,000-time cumulative averaging + levenberg marquardt (LM) algorithm without severe distortion of the reference resolution. The method improves the sensor demodulation speed by using image processing technology without changing the existing hardware equipment, which is expected to be widely used in the new generation of BOTDR.
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Affiliation(s)
- Xiaojuan Chen
- School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun 130022, China;
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Yang YX, Zhang DK, Lu HY, Zhao XL, Yu H. [Change trends and related risk factors of disease burden on mesothelioma in Jiangsu Province from 1990 to 2019]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2023; 41:594-600. [PMID: 37667155 DOI: 10.3760/cma.j.cn121094-20220815-00400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
Abstract
Objective: To analyze the change trends and risk factors of mesothelioma disease burden in Jiangsu Province from 1990 to 2019. Methods: In January 2022, using the 2019 Global Burden of Disease Study Data, the Joinpoint regression model was used to analyze the change trends of incidence, mortality, disable-adjusted life years (DALY) and premature mortality of mesothelioma residents in Jiangsu Province from 1990 to 2019, and the attribution level of mesothelioma risk factors was estimated by population attributing fraction. Results: The standardized incidence rates of mesothelioma in Jiangsu Province from 1990 to 2019 ranged from 0.07/10(5) to 0.09/10(5), with an average annual percentage change (AAPC) of -1.1% (t=-13.56, P<0.001). AAPCs in males and females were -0.3% (t=-2.18, P=0.029) and -1.6% (t=-11.39, P<0.001), respectively. The standardized mortality rates of mesothelioma ranged from 0.07/10(5) to 0.09/10(5), the AAPC was -1.1% (t=-12.23, P<0.001), AAPC was -1.6% (t=-14.09, P<0.001) for females, and there was no significant change in males (t=-1.83, P=0.068). The premature mortality was 0.004%-0.006%, the AAPC was -1.0% (t=-4.40, P<0.001), AAPC was -1.7% (t=-13.72, P<0.001) for females, and there was no significant change in males (t=-0.68, P=0.495). The standardized DALY rates ranged from 1.86/10(5) to 2.32/10(5), the AAPC was -0.9% (t=-11.08, P<0.001), AAPC was -1.6% (t=-11.05, P<0.001) for females, and there was no significant change in males (t=-0.95, P=0.343). Both the standardized years of life lost (YLL) rate and the standardized years lived with disability (YLD) rate showed a decreasing trend, and the AAPCs were -0.9% (t=-7.66, P<0.001) and -1.0% (t=-12.88, P<0.001), respectively. The proportion of YLL in DALY was more than 98.5%. Among the risk factors for mesothelioma burden attribution, the AAPC attributed to occupational asbestos exposure of DALY was 1.4% (t=3.43, P=0.001). The AAPC of DALY rate of standardized attribution was -1.7% (t=-12.11, P<0.001) . Conclusion: The overall burden of mesothelioma in Jiangsu Province is decreasing, occupational asbestos exposure is still the main risk factor of mesothelioma in Jiangsu Province, and early diagnosis and treatment should be strengthened.
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Affiliation(s)
- Y X Yang
- Department of Non-communicable Chronic Disease Control and Prevention, Taizhou Center for Disease Control and Prevention, Taizhou 225300, China
| | - D K Zhang
- Department of Non-communicable Chronic Disease Control and Prevention, Taizhou Center for Disease Control and Prevention, Taizhou 225300, China
| | - H Y Lu
- Department of Non-communicable Chronic Disease Control and Prevention, Taizhou Center for Disease Control and Prevention, Taizhou 225300, China
| | - X L Zhao
- Department of Non-communicable Chronic Disease Control and Prevention, Taizhou Center for Disease Control and Prevention, Taizhou 225300, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
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Xu WC, Zhou MM, Ding MK, Yu H, Zhu Z, Xu WG, Zhou JY. [Disease burden and risk factors of chronic respiratory diseases in Jiangsu Province from 1990 to 2019]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1141-1146. [PMID: 37574303 DOI: 10.3760/cma.j.cn112150-20230208-00089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Objective: To analyze the prevalence and the trend of the disease burden of chronic respiratory diseases and relevant risk factors in Jiangsu province from 1990 to 2019 and provide evidence for the prevention and treatment of chronic respiratory diseases. Methods: The data from the 2019 Global Burden of Disease Study (GBD2019) were used to calculate the prevalence rate, mortality rate and disability-adjusted life year (DALY) rate. Software Joinpoint was used to calculate the annual percent change (APC) and average annual percent change (AAPC) of the standardized prevalence rate, standardized mortality rate and standardized DALY rate. The population attributable fractions (PAF) were used to estimate the proportion of chronic respiratory disease caused by different risk factors. Results: In 1990 and 2019, the prevalence rates of chronic respiratory diseases were 4.83% and 5.45%. The mortality rates were 134.91/100 000 and 80.99/100 000 respectively, and the DALY rates were 2 678.52/100 000 and 1 534.31/100 000 respectively. From 1990 to 2019, the age-standardized prevalence rate, mortality rate and DALY rate in Jiangsu showed a significant downward trend (AAPC values were -0.90%, -5.28% and -4.70% respectively, P<0.05). Tobacco use was the leading cause of chronic respiratory diseases, followed by air pollution, occupational exposure, suboptimal temperature and high BMI. Compared with 1990, the proportion of DALYs of chronic respiratory diseases attributable to tobacco use and high BMI increased in 2019. Conclusion: The overall burden of chronic respiratory diseases in Jiangsu shows a downward trend. Prevention and health education should be focused on the population with a smoking history and high BMI. At the same time, environmental management, attention to suboptimal temperature and control of occupational exposure factors should also be adopted as important means to prevent and control chronic respiratory diseases.
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Affiliation(s)
- W C Xu
- Department of Chronic Non-communicable Disease Control and Prevention, Changzhou Cencer for Disease Control and Prevention, Changzhou 213022, China
| | - M M Zhou
- Department of Chronic Non-communicable Disease Control and Prevention, Changzhou Cencer for Disease Control and Prevention, Changzhou 213022, China
| | - M K Ding
- Department of Chronic Non-communicable Disease Control and Prevention, Changzhou Cencer for Disease Control and Prevention, Changzhou 213022, China
| | - H Yu
- Department of Chronic Non-communicable Disease Control and Prevention, Jiangsu Cencer for Disease Control and Prevention, Nanjing 210009, China
| | - Z Zhu
- Department of Chronic Non-communicable Disease Control and Prevention, Jiangsu Cencer for Disease Control and Prevention, Nanjing 210009, China
| | - W G Xu
- Changzhou Cencer for Disease Control and Prevention, Changzhou 213022, China
| | - J Y Zhou
- Department of Chronic Non-communicable Disease Control and Prevention, Jiangsu Cencer for Disease Control and Prevention, Nanjing 210009, China
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Wang CH, Huang ML, Zhuo ZQ, Wang ZX, Chen L, Song YQ, Yu H. [Clinical features and antimicrobial resistance of invasive non-typhoid Salmonella infection in children at Xiamen]. Zhonghua Er Ke Za Zhi 2023; 61:685-689. [PMID: 37528007 DOI: 10.3760/cma.j.cn112140-20230227-00135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
Objective: To investigate the clinical characteristics, serogroups and antimicrobial resistance of invasive non-typhoid Salmonella infection in children at Xiamen. Methods: Retrospective cohort study. The clinical manifestations, treatment, prognosis, serogroups and antimicrobial resistance of 29 hospitalized children with invasive non-typhoid Salmonella infection confirmed by blood, cerebrospinal fluid, bone marrow and other sterile body fluids or deep pus culture at the Department of Infectious Diseases, the Department of Orthopedics and the Department of General Surgery in Xiamen Children's Hospital from January 2016 to December 2021 were analyzed. According to the clinical diagnosis criteria, the patients were divided into sepsis group and non-sepsis group (bacteremia and local suppurative infection). The inflammatory markers, serogroups distribution and drug resistance were compared between the two groups. Comparison between groups using Mann-Whitney U test and χ2 test. Results: Among the 29 cases, there were 17 males and 12 females, with an onset age of 14 (9, 25) months, and 10 cases (34%) of patients were younger than 1 year old, 15 cases (52%) under 1 to 3 years old, and 4 cases (14%) greater than or equal 3 years old. The onset time of 25 cases (86%) was from April to September. The diseases included 19 cases (66%) septicemia (2 of which were combined with suppurative meningitis), 10 cases (34%) non-sepsis group, including 7 cases bacteremia and 3 cases local suppurative infection (2 cases of osteomyelitis, 1 case of appendicitis with peritonitis). The clinical manifestations were fever in 29 cases (100%), diarrhea and abdominal pain in 18 cases (62%), cough and runny nose in 10 cases (34%). Eighteen cases (62%) were cured and 11 cases (38%) were improved by effective antibiotics treatment. C-reactive protein in sepsis group was significantly higher than that in non-sepsis group (25.2 (16.1, 56.4) vs. 3.4 (0.5, 7.5) mg/L, Z=-3.81, P<0.001).The serogroups of C, B and E were the most prevalent among non-typhoid Salmonella isolates, accounting for 10 cases (34%), 9 cases (31%) and 7 cases (24%) respectively. Antibacterial drug sensitivity test showed that the sensitivity rates of imipenem, ertapenem and piperaciratazobactam were all 100% (31/31), those of ceftazidime, ceftriaxone, and cefepime were 94% (29/31), 94% (29/31) and 97% (30/31) respectively. The drug resistance rates of ampicillin, ampicillin-sulbactam and trimethoprim-sulfamethoxazole were 51% (16/31), 48% (15/31) and 48% (15/31) respectively, those of cefazolin, cefotetan, tobramycin, gentamicin and amikacinwere all 100% (31/31). There were no significant differences in the drug resistance rates of ceftazidime, ceftriaxone, aztreonam, ampicillin-sulbactam, ampicillin, trimethoprim-sulfamethoxazole and ciprofloxacin between the sepsis group and the non-sepsis group (χ2=0.31,0.31,0.00,0.02,0.02,0.02,0.26, all P>0.05). Conclusions: Invasive non-typhoid Salmonella infection in children at Xiamen mainly occurred in infants younger than 3 years old.The main clinical manifestations are fever, abdominal pain and diarrhea. C-reactive protein can be served as the laboratory indicators for indicating sepsis. The third generation of cephalosporins is recommended as the first choice for treatment.
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Affiliation(s)
- C H Wang
- Department of Infectious Diseases, Xiamen Hospital (Xiamen Children's Hospital), Children's Hospital of Fudan University, Xiamen 361006, China
| | - M L Huang
- Department of Clinical Medical Labortaory,Xiamen Hospital (Xiamen Children's Hospital), Children's Hospital of Fudan University, Xiamen 361006, China
| | - Z Q Zhuo
- Department of Infectious Diseases, Xiamen Hospital (Xiamen Children's Hospital), Children's Hospital of Fudan University, Xiamen 361006, China
| | - Z X Wang
- Department of Infectious Diseases, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - L Chen
- Department of Clinical Medical Labortaory,Xiamen Hospital (Xiamen Children's Hospital), Children's Hospital of Fudan University, Xiamen 361006, China
| | - Y Q Song
- Department of Infectious Diseases, Xiamen Hospital (Xiamen Children's Hospital), Children's Hospital of Fudan University, Xiamen 361006, China
| | - H Yu
- Department of Infectious Diseases, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
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Pofelski A, Deng S, Yu H, Park TJ, Jia H, Manna S, Chan MKY, Sankaranarayanan SKR, Ramanathan S, Zhu Y. Dopant Mapping of Partially Hydrogenated Vanadium Dioxide using the Energy Loss Near Edge Structure Technique. Microsc Microanal 2023; 29:1667-1668. [PMID: 37613910 DOI: 10.1093/micmic/ozad067.858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- A Pofelski
- Condensed Matter Physics and Materials Science Department, Brookhaven National Laboratory, Upton, NY, USA
| | - S Deng
- School of Materials Engineering, Purdue University, West Lafayette, IN, USA
| | - H Yu
- School of Materials Engineering, Purdue University, West Lafayette, IN, USA
| | - T J Park
- School of Materials Engineering, Purdue University, West Lafayette, IN, USA
| | - H Jia
- Center for Nanoscale Materials, Argonne National Laboratory, Lemont, IL, USA
| | - S Manna
- Center for Nanoscale Materials, Argonne National Laboratory, Lemont, IL, USA
- Department of Mechanical and Industrial Engineering, University of Illinois, Chicago, IL, USA
| | - M K Y Chan
- Center for Nanoscale Materials, Argonne National Laboratory, Lemont, IL, USA
| | - S K Rs Sankaranarayanan
- Center for Nanoscale Materials, Argonne National Laboratory, Lemont, IL, USA
- Department of Mechanical and Industrial Engineering, University of Illinois, Chicago, IL, USA
| | - S Ramanathan
- School of Materials Engineering, Purdue University, West Lafayette, IN, USA
- Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Y Zhu
- Condensed Matter Physics and Materials Science Department, Brookhaven National Laboratory, Upton, NY, USA
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Chen YJ, Qin Y, Yu H, Zhu Z, Shen C, Lu Y, Cheng TT, Zhang N, Gu SJ, Zhou JY, Wu M, Su J. [A prospective cohort study of long-term fasting blood glucose variability and risk of mortality in patients with type 2 diabetes]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1099-1105. [PMID: 37482713 DOI: 10.3760/cma.j.cn112338-20221226-01084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Objective: To investigate the association between long-term fasting blood glucose (FPG) variability and all-cause mortality in patients with type 2 diabetes. Methods: A total of 7 174 type 2 diabetic patients included in National Basic Public Health Service Program in Changshu of Jiangsu Province were recruited as participants. Long-term glucose variability was assessed using standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) across FPG measurements at the more than three visits. Death information were mainly obtained from the death registry system in Jiangsu. Then Cox proportional hazards regression models were used to estimate the associations of four variability indicators and all-cause mortality's hazard ratios (HRs) and their 95%CIs. Results: Among 55 058.50 person-years of the follow-up, the mean follow-up time was 7.67 years, and 898 deaths occurred during the follow-up period. After adjustment, compared with T1 group, the Cox regression model showed that HRs of T3 group in SD, CV, ARV and VIM were 1.24 (95%CI: 1.03-1.49), 1.20 (95%CI: 1.01-1.43), 1.28 (95%CI: 1.07-1.55) and 1.20 (95%CI:1.01-1.41), respectively. HRs of per 1 SD higher SD, CV, ARV and VIM were 1.13 (95%CI: 1.06-1.21), 1.08 (95%CI: 1.01-1.15), 1.05 (95%CI: 1.00-1.12) and 1.09 (95%CI: 1.02-1.16) for all-cause mortality, respectively. In the stratified analysis, age, gender, hypoglycemic agent and insulin uses had no effect on the above associations (all P for interaction >0.05). Conclusion: Long-term FPG glycemic variability was positively associated with the risk of all-cause mortality in type 2 diabetes patients.
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Affiliation(s)
- Y J Chen
- Department of Non-communicable Chronic Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing 210003, China
| | - Y Qin
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Z Zhu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - C Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Y Lu
- Department of Non-communicable Chronic Disease Prevention, Suzhou Prefectural Center for Disease Control and Prevention, Suzhou 215004, China
| | - T T Cheng
- Department of Infectious Disease Control Division, Suzhou National New & Hi-Tech Industrial Development Zone (Huqiu District) Center for Disease Control and Prevention, Suzhou 215163, China
| | - N Zhang
- Changshu County Center for Disease Control and Prevention, Changshu 215500, China
| | - S J Gu
- Department of Non-communicable Chronic Disease Prevention, Changshu County Center for Disease Control and Prevention, Changshu 215500, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - M Wu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Su
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
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Zhou W, Wang M, Yu Y, Wang J, Wu Y, Yang G, Yu H, Li J, Zhou L, Zhang Q. Comparing the pharmacokinetics, safety, and immunogenicity of HLX02 to US- and EU-approved trastuzumab in healthy Chinese male subjects: A Phase I, randomized, double-blind, parallel-group study. Expert Opin Biol Ther 2023; 23:717-725. [PMID: 36843059 DOI: 10.1080/14712598.2023.2183117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 02/17/2023] [Indexed: 02/28/2023]
Abstract
BACKGROUND HLX02, the first China-manufactured trastuzumab biosimilar, is approved in Europe (EU) and China. This study evaluated bioequivalence between HLX02 and US-approved trastuzumab (US-trastuzumab). METHOD In this double-blind, parallel-group, Phase I study, healthy Chinese men were randomized (1:1:1) to receive a single 6 mg/kg dose of HLX02, reference US-trastuzumab, or reference EU-approved trastuzumab (EU-trastuzumab). Equivalence in PK profiles was demonstrated if the 90% confidence intervals (CIs) for the geometric mean ratio (GMR) for the difference between the least square means of the area under the curve (AUC) from time 0 to infinity (AUC∞) were 0.8-1.25. RESULTS Pharmacokinetic profiles of the three trastuzumab products were similar in 111 Chinese men. Equivalence was confirmed between HLX02 and US-trastuzumab (GMR for AUC∞ 1.009, 90% CI 0.950-1.072); HLX02 and EU-trastuzumab (GMR for AUC∞ 1.068, 90% CI 1.005-1.135); and EU- and US-trastuzumab (GMR for AUC∞ 0.945, 90% CI 0.889-1004). Exploratory analysis of all other PK parameters also demonstrated equivalence between any two of the three trastuzumab products. HLX02 had similar safety and immunogenicity profiles to US- and EU-trastuzumab. CONCLUSION HLX02 is bioequivalent to US-trastuzumab and EU-trastuzumab, with similar safety and immunogenicity profiles. US- and EU-trastuzumab were also bioequivalent to each other.
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Affiliation(s)
- Wenjia Zhou
- Phase 1 Clinical Trial Center, the Second Affiliated Hospital of Soochow University, Suzhou, Shanghai, China
| | - Meng Wang
- Phase 1 Clinical Trial Center, the Second Affiliated Hospital of Soochow University, Suzhou, Shanghai, China
| | - Yunli Yu
- Phase 1 Clinical Trial Center, the Second Affiliated Hospital of Soochow University, Suzhou, Shanghai, China
| | - Ji Wang
- Department of Medical Oncology, the Second Affiliated Hospital of Soochow University, Suzhou, Shanghai, China
| | - Yanni Wu
- Department of Cardiology, the Second Affiliated Hospital of Soochow University, Suzhou, Shanghai, China
| | - Guiyu Yang
- Shanghai Henlius Biotech, Inc, Shanghai, Shanghai, China
| | - Haoyu Yu
- Shanghai Henlius Biotech, Inc, Shanghai, Shanghai, China
| | - Jing Li
- Shanghai Henlius Biotech, Inc, Shanghai, Shanghai, China
| | - Liang Zhou
- Shanghai Henlius Biotech, Inc, Shanghai, Shanghai, China
| | - Quanying Zhang
- Phase 1 Clinical Trial Center, the Second Affiliated Hospital of Soochow University, Suzhou, Shanghai, China
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Yu H, Yang RT, Wang SY, Wu JH, Wang MY, Qin XY, Wu T, Chen DF, Wu YQ, Hu YH. [Metformin use and risk of ischemic stroke in patients with type 2 diabetes: A cohort study]. Beijing Da Xue Xue Bao Yi Xue Ban 2023; 55:456-464. [PMID: 37291921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
OBJECTIVE To explore the association between the use of metformin and the risk of ischemic stroke in patients with type 2 diabetes. METHODS A prospective cohort study was designed from the Fangshan family cohort in Beijing. According to metformin use at baseline, 2 625 patients with type 2 diabetes in Fangshan, Beijing were divided into metformin group or non-metformin group and the incidence of ischemic stroke between the different groups during follow-up was estimated and compared by Cox proportional hazard regression model. The participants with metformin were first compared with all the parti-cipants who did not use metformin, and then were further compared with those who did not use hypoglycemic agents and those who used other hypoglycemic agents. RESULTS The patients with type 2 diabetes were with an average age of (59.5±8.7) years, and 41.9% of them were male. The median follow-up time was 4.5 years. A total of 84 patients developed ischemic stroke during follow-up, with a crude incidence of 6.4 (95%CI: 5.0-7.7) per 1 000 person-years. Among all the participants, 1 149 (43.8%) took metformin, 1 476 (56.2%) were metformin non-users, including 593 (22.6%) used other hypoglycemic agents, and 883 (33.6%) did not use any hypoglycemic agents. Compared with metformin non-users, the Hazard ratio (HR) for ischemic stroke in metformin users was 0.58 (95%CI: 0.36-0.93; P = 0.024). Compared with other hypoglycemic agents, HR was 0.48 (95%CI: 0.28-0.84; P < 0.01); Compared with the group without hypoglycemic agents, HR was 0.65 (95%CI: 0.37-1.13; P=0.13). The association between metformin and ischemic stroke was statistically significant in the patients ≥ 60 years old compared with all the metformin non-users and those who used other hypoglycemic agents (HR: 0.48, 95%CI: 0.25-0.92; P < 0.05). Metformin use was associated with a lower incidence of ischemic stroke in the patients with good glycemic control (0.32, 95%CI: 0.13-0.77; P < 0.05). In the patients with poor glycemic control, and the association was not statistically significant (HR: 0.97, 95%CI: 0.53-1.79; P>0.05). There was an interaction between glycemic control and metformin use on incidence of ischemic stroke (Pinteraction < 0.05). The results of the sensitivity analysis were consistent with the results in the main analysis. CONCLUSION Among patients with type 2 diabetic in rural areas of northern China, metformin use was associated with lower incidence of ischemic stroke, especially in patients older than 60 years. There was an interaction between glycemic control and metformin use in the incidence of ischemic stroke.
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Affiliation(s)
- H Yu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - R T Yang
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - S Y Wang
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - J H Wu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - M Y Wang
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - X Y Qin
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - T Wu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - D F Chen
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Y Q Wu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - Y H Hu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
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Yang MS, Fan XK, Su J, Yu H, Lu Y, Hua YJ, Pei P, Lyu J, Tao R, Zhou JY, Wu M. [Incidence of chronic obstructive pulmonary disease and risk factors in the Suzhou cohort]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:868-876. [PMID: 37380406 DOI: 10.3760/cma.j.cn112338-20221202-01033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
Objective: To understand the incidence of chronic obstructive pulmonary disease (COPD) in the Suzhou cohort, and explore the risk factors for the development of COPD in Suzhou, and provide a scientific basis for COPD prevention. Methods: This study was based on the China Kadoorie Biobank project in Wuzhong District, Suzhou. After excluding individuals with airflow obstruction and self-reported chronic bronchitis, emphysema, or pulmonary heart disease at baseline, 45 484 individuals were finally included in the analysis. Cox proportional risk models were used to analyze risk factors of COPD and calculate hazard ratios and 95% confidence interval (CI) in the Suzhou cohort. The effect modifications of smoking on the association between other risk factors and COPD were evaluated. Results: Complete follow-up was available through December 31, 2017. Participants were followed up for a median of 11.12 years, and 524 individuals were diagnosed with COPD during the follow-up period; the incidence was 105.54 per 100 000 person-years. Multivariate Cox proportional risk regression models showed that age (HR=3.78, 95%CI:3.32-4.30), former smoking (HR=2.00, 95%CI:1.24-3.22), current smoking (<10 cigarettes/day, HR=2.14, 95%CI:1.36-3.35;≥10 cigarettes/day, HR=2.69, 95%CI:1.60-4.54), history of respiratory disease (HR=2.08, 95%CI:1.33-3.26), daily sleep duration ≥10 hours (HR=1.41, 95%CI:1.02-1.95) were associated with increased risk of COPD. However, education level of primary school and above (primary or junior high school, HR=0.65, 95%CI:0.52-0.81; high school and above, HR=0.54, 95%CI:0.33-0.87), consuming fresh fruit daily (HR=0.59, 95%CI:0.42-0.83) and consuming spicy food weekly (HR=0.71, 95%CI:0.53-0.94) were associated with reduced risk of COPD. Conclusions: The incidence of COPD is low in Suzhou. Older age, smoking, history of respiratory disease, and long sleep duration were risk factors for the development of COPD in the Suzhou cohort.
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Affiliation(s)
- M S Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China
| | - X K Fan
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Su
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Y Lu
- Department of Non-communicable Chronic Disease Control and Prevention, Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - Y J Hua
- Department of Non-communicable Chronic Disease Control and Prevention, Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - P Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - J Lyu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China
| | - R Tao
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - M Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China Department of Non-communicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
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Abratenko P, Aduszkiewicz A, Akbar F, Pons MA, Asaadi J, Aslin M, Babicz M, Badgett WF, Bagby LF, Baibussinov B, Behera B, Bellini V, Beltramello O, Benocci R, Berger J, Berkman S, Bertolucci S, Bertoni R, Betancourt M, Bettini M, Biagi S, Biery K, Bitter O, Bonesini M, Boone T, Bottino B, Braggiotti A, Brailsford D, Bremer J, Brice SJ, Brio V, Brizzolari C, Brown J, Budd HS, Calaon F, Campani A, Carber D, Carneiro M, Terrazas IC, Carranza H, Casazza D, Castellani L, Castro A, Centro S, Cerati G, Chalifour M, Chambouvet P, Chatterjee A, Cherdack D, Cherubini S, Chithirasreemadam N, Cicerchia M, Cicero V, Coan T, Cocco AG, Convery MR, Copello S, Cristaldo E, Dange AA, de Icaza Astiz I, De Roeck A, Di Domizio S, Di Noto L, Di Stefano C, Di Ferdinando D, Diwan M, Dolan S, Domine L, Donati S, Doubnik R, Drielsma F, Dyer J, Dytman S, Fabre C, Fabris F, Falcone A, Farnese C, Fava A, Ferguson H, Ferrari A, Ferraro F, Gallice N, Garcia FG, Geynisman M, Giarin M, Gibin D, Gigli SG, Gioiosa A, Gu W, Guerzoni M, Guglielmi A, Gurung G, Hahn S, Hardin K, Hausner H, Heggestuen A, Hilgenberg C, Hogan M, Howard B, Howell R, Hrivnak J, Iliescu M, Ingratta G, James C, Jang W, Jung M, Jwa YJ, Kashur L, Ketchum W, Kim JS, Koh DH, Kose U, Larkin J, Laurenti G, Lukhanin G, Marchini S, Marshall CM, Martynenko S, Mauri N, Mazzacane A, McFarland KS, Méndez DP, Menegolli A, Meng G, Miranda OG, Mladenov D, Mogan A, Moggi N, Montagna E, Montanari C, Montanari A, Mooney M, Moreno-Granados G, Mueller J, Naples D, Nebot-Guinot M, Nessi M, Nichols T, Nicoletto M, Norris B, Palestini S, Pallavicini M, Paolone V, Papaleo R, Pasqualini L, Patrizii L, Peghin R, Petrillo G, Petta C, Pia V, Pietropaolo F, Poirot J, Poppi F, Pozzato M, Prata MC, Prosser A, Putnam G, Qian X, Rampazzo G, Rappoldi A, Raselli GL, Rechenmacher R, Resnati F, Ricci AM, Riccobene G, Rice L, Richards E, Rigamonti A, Rosenberg M, Rossella M, Rubbia C, Sala P, Sapienza P, Savage G, Scaramelli A, Scarpelli A, Schmitz D, Schukraft A, Sergiampietri F, Sirri G, Smedley JS, Soha AK, Spanu M, Stanco L, Stewart J, Suarez NB, Sutera C, Tanaka HA, Tenti M, Terao K, Terranova F, Togo V, Torretta D, Torti M, Tortorici F, Tosi N, Tsai YT, Tufanli S, Turcato M, Usher T, Varanini F, Ventura S, Vercellati F, Vicenzi M, Vignoli C, Viren B, Warner D, Williams Z, Wilson RJ, Wilson P, Wolfs J, Wongjirad T, Wood A, Worcester E, Worcester M, Wospakrik M, Yu H, Yu J, Zani A, Zatti PG, Zennamo J, Zettlemoyer JC, Zhang C, Zucchelli S, Zuckerbrot M. ICARUS at the Fermilab Short-Baseline Neutrino program: initial operation. Eur Phys J C Part Fields 2023; 83:467. [PMID: 37303462 PMCID: PMC10239613 DOI: 10.1140/epjc/s10052-023-11610-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/12/2023] [Indexed: 06/13/2023]
Abstract
The ICARUS collaboration employed the 760-ton T600 detector in a successful 3-year physics run at the underground LNGS laboratory, performing a sensitive search for LSND-like anomalous ν e appearance in the CERN Neutrino to Gran Sasso beam, which contributed to the constraints on the allowed neutrino oscillation parameters to a narrow region around 1 eV2 . After a significant overhaul at CERN, the T600 detector has been installed at Fermilab. In 2020 the cryogenic commissioning began with detector cool down, liquid argon filling and recirculation. ICARUS then started its operations collecting the first neutrino events from the booster neutrino beam (BNB) and the Neutrinos at the Main Injector (NuMI) beam off-axis, which were used to test the ICARUS event selection, reconstruction and analysis algorithms. ICARUS successfully completed its commissioning phase in June 2022. The first goal of the ICARUS data taking will be a study to either confirm or refute the claim by Neutrino-4 short-baseline reactor experiment. ICARUS will also perform measurement of neutrino cross sections with the NuMI beam and several Beyond Standard Model searches. After the first year of operations, ICARUS will search for evidence of sterile neutrinos jointly with the Short-Baseline Near Detector, within the Short-Baseline Neutrino program. In this paper, the main activities carried out during the overhauling and installation phases are highlighted. Preliminary technical results from the ICARUS commissioning data with the BNB and NuMI beams are presented both in terms of performance of all ICARUS subsystems and of capability to select and reconstruct neutrino events.
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Affiliation(s)
| | | | - F. Akbar
- University of Rochester, Rochester, NY 14627 USA
| | - M. Artero Pons
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - J. Asaadi
- University of Texas at Arlington, Arlington, TX 76019 USA
| | - M. Aslin
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
- Present Address: University of Wisconsin, Madison, USA
| | - M. Babicz
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
- INP-Polish Acad. Sci, Kraków, Poland
- Present Address: University of Zurich, Zurich, Switzerland
| | - W. F. Badgett
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - L. F. Bagby
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - B. Baibussinov
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - B. Behera
- Colorado State University, Fort Collins, CO 80523 USA
| | - V. Bellini
- INFN Sezione di Catania and University of Catania, Catania, Italy
| | - O. Beltramello
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - R. Benocci
- INFN Sezione di Milano Bicocca and University of Milano Bicocca, Milan, Italy
| | - J. Berger
- Colorado State University, Fort Collins, CO 80523 USA
| | - S. Berkman
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - S. Bertolucci
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - R. Bertoni
- INFN Sezione di Milano Bicocca and University of Milano Bicocca, Milan, Italy
| | - M. Betancourt
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - M. Bettini
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | | | - K. Biery
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - O. Bitter
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
- Present Address: Northwestern University, Evanston, USA
| | - M. Bonesini
- INFN Sezione di Milano Bicocca and University of Milano Bicocca, Milan, Italy
| | - T. Boone
- Colorado State University, Fort Collins, CO 80523 USA
| | - B. Bottino
- INFN Sezione di Genova and University of Genova, Genoa, Italy
| | - A. Braggiotti
- INFN Sezione di Padova and University of Padova, Padua, Italy
- Istituto di Neuroscienze, CNR, Padua, Italy
| | - D. Brailsford
- SBND Collaboration, Lancaster University, Lancaster, UK
| | - J. Bremer
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - S. J. Brice
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - V. Brio
- INFN Sezione di Catania and University of Catania, Catania, Italy
| | - C. Brizzolari
- INFN Sezione di Milano Bicocca and University of Milano Bicocca, Milan, Italy
| | - J. Brown
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - H. S. Budd
- University of Rochester, Rochester, NY 14627 USA
| | - F. Calaon
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - A. Campani
- INFN Sezione di Genova and University of Genova, Genoa, Italy
| | - D. Carber
- Colorado State University, Fort Collins, CO 80523 USA
| | - M. Carneiro
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | | | - H. Carranza
- University of Texas at Arlington, Arlington, TX 76019 USA
| | - D. Casazza
- INFN Sezione di Genova and University of Genova, Genoa, Italy
| | - L. Castellani
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - A. Castro
- Centro de Investigacion y de Estudios Avanzados del IPN (Cinvestav), Mexico City, Mexico
| | - S. Centro
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - G. Cerati
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - M. Chalifour
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - P. Chambouvet
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | | | - D. Cherdack
- University of Houston, Houston, TX 77204 USA
| | | | | | - M. Cicerchia
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - V. Cicero
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - T. Coan
- Southern Methodist University, Dallas, TX 75275 USA
| | | | - M. R. Convery
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - S. Copello
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | - E. Cristaldo
- SBND Collaboration, Universidad Nacional de Asuncion, San Lorenzo, Paraguay
| | - A. A. Dange
- University of Texas at Arlington, Arlington, TX 76019 USA
| | | | - A. De Roeck
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - S. Di Domizio
- INFN Sezione di Genova and University of Genova, Genoa, Italy
| | - L. Di Noto
- INFN Sezione di Genova and University of Genova, Genoa, Italy
| | | | - D. Di Ferdinando
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - M. Diwan
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - S. Dolan
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - L. Domine
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | | | - R. Doubnik
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - F. Drielsma
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - J. Dyer
- Colorado State University, Fort Collins, CO 80523 USA
| | - S. Dytman
- University of Pittsburgh, Pittsburgh, PA 15260 USA
| | - C. Fabre
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - F. Fabris
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - A. Falcone
- INFN Sezione di Milano Bicocca and University of Milano Bicocca, Milan, Italy
| | - C. Farnese
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - A. Fava
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - H. Ferguson
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | | | - F. Ferraro
- INFN Sezione di Genova and University of Genova, Genoa, Italy
| | | | - F. G. Garcia
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - M. Geynisman
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - M. Giarin
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - D. Gibin
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - S. G. Gigli
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | | | - W. Gu
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - M. Guerzoni
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - A. Guglielmi
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - G. Gurung
- University of Texas at Arlington, Arlington, TX 76019 USA
| | - S. Hahn
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - K. Hardin
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - H. Hausner
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - A. Heggestuen
- Colorado State University, Fort Collins, CO 80523 USA
| | - C. Hilgenberg
- Colorado State University, Fort Collins, CO 80523 USA
- Present Address: University of Minnesota, Minneapolis, USA
| | - M. Hogan
- Colorado State University, Fort Collins, CO 80523 USA
| | - B. Howard
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - R. Howell
- University of Rochester, Rochester, NY 14627 USA
| | - J. Hrivnak
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - M. Iliescu
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
- Present Address: INFN-LNF, Frascati, Italy
| | - G. Ingratta
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - C. James
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - W. Jang
- University of Texas at Arlington, Arlington, TX 76019 USA
| | - M. Jung
- University of Chicago, Chicago, IL 60637 USA
- SBND Collaboration, Batavia, USA
| | - Y.-J. Jwa
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - L. Kashur
- Colorado State University, Fort Collins, CO 80523 USA
| | - W. Ketchum
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - J. S. Kim
- University of Rochester, Rochester, NY 14627 USA
| | - D.-H. Koh
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - U. Kose
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
- Present Address: ETH Zurich, Zurich, Switzerland
| | - J. Larkin
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - G. Laurenti
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - G. Lukhanin
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - S. Marchini
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | | | | | - N. Mauri
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - A. Mazzacane
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | | | - D. P. Méndez
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - A. Menegolli
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | - G. Meng
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - O. G. Miranda
- Centro de Investigacion y de Estudios Avanzados del IPN (Cinvestav), Mexico City, Mexico
| | - D. Mladenov
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - A. Mogan
- Colorado State University, Fort Collins, CO 80523 USA
| | - N. Moggi
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - E. Montagna
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - C. Montanari
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
- On leave of absence from INFN Pavia, Pavia, Italy
| | - A. Montanari
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - M. Mooney
- Colorado State University, Fort Collins, CO 80523 USA
| | - G. Moreno-Granados
- Centro de Investigacion y de Estudios Avanzados del IPN (Cinvestav), Mexico City, Mexico
| | - J. Mueller
- Colorado State University, Fort Collins, CO 80523 USA
| | - D. Naples
- University of Pittsburgh, Pittsburgh, PA 15260 USA
| | | | - M. Nessi
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - T. Nichols
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - M. Nicoletto
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - B. Norris
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - S. Palestini
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - M. Pallavicini
- INFN Sezione di Genova and University of Genova, Genoa, Italy
| | - V. Paolone
- University of Pittsburgh, Pittsburgh, PA 15260 USA
| | | | - L. Pasqualini
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - L. Patrizii
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - R. Peghin
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - G. Petrillo
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - C. Petta
- INFN Sezione di Catania and University of Catania, Catania, Italy
| | - V. Pia
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - F. Pietropaolo
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
- On leave of absence from INFN Padova, Padua, Italy
| | - J. Poirot
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - F. Poppi
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - M. Pozzato
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - M. C. Prata
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | - A. Prosser
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - G. Putnam
- University of Chicago, Chicago, IL 60637 USA
| | - X. Qian
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - G. Rampazzo
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - A. Rappoldi
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | - G. L. Raselli
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | - R. Rechenmacher
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - F. Resnati
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | | | | | - L. Rice
- University of Pittsburgh, Pittsburgh, PA 15260 USA
| | - E. Richards
- University of Pittsburgh, Pittsburgh, PA 15260 USA
| | - A. Rigamonti
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | | | - M. Rossella
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | | | - P. Sala
- INFN Sezione di Milano, Milan, Italy
| | | | - G. Savage
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - A. Scaramelli
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | - A. Scarpelli
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - D. Schmitz
- University of Chicago, Chicago, IL 60637 USA
| | - A. Schukraft
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - F. Sergiampietri
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
- Present Address: IPSI-INAF Torino, Turin, Italy
| | - G. Sirri
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | | | - A. K. Soha
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - M. Spanu
- INFN Sezione di Milano Bicocca and University of Milano Bicocca, Milan, Italy
| | - L. Stanco
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - J. Stewart
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - N. B. Suarez
- University of Pittsburgh, Pittsburgh, PA 15260 USA
| | - C. Sutera
- INFN Sezione di Catania and University of Catania, Catania, Italy
| | - H. A. Tanaka
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - M. Tenti
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - K. Terao
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - F. Terranova
- INFN Sezione di Milano Bicocca and University of Milano Bicocca, Milan, Italy
| | - V. Togo
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - D. Torretta
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - M. Torti
- INFN Sezione di Milano Bicocca and University of Milano Bicocca, Milan, Italy
| | - F. Tortorici
- INFN Sezione di Catania and University of Catania, Catania, Italy
| | - N. Tosi
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - Y.-T. Tsai
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - S. Tufanli
- CERN, European Organization for Nuclear Research, 1211 Geneva 23, Switzerland
| | - M. Turcato
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - T. Usher
- SLAC National Acceleratory Laboratory, Menlo Park, CA 94025 USA
| | - F. Varanini
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - S. Ventura
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - F. Vercellati
- INFN Sezione di Pavia and University of Pavia, Pavia, Italy
| | - M. Vicenzi
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | | | - B. Viren
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - D. Warner
- Colorado State University, Fort Collins, CO 80523 USA
| | - Z. Williams
- University of Texas at Arlington, Arlington, TX 76019 USA
| | - R. J. Wilson
- Colorado State University, Fort Collins, CO 80523 USA
| | - P. Wilson
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - J. Wolfs
- University of Rochester, Rochester, NY 14627 USA
| | | | - A. Wood
- University of Houston, Houston, TX 77204 USA
| | - E. Worcester
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - M. Worcester
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - M. Wospakrik
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | - H. Yu
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - J. Yu
- University of Texas at Arlington, Arlington, TX 76019 USA
| | - A. Zani
- INFN Sezione di Milano, Milan, Italy
| | - P. G. Zatti
- INFN Sezione di Padova and University of Padova, Padua, Italy
| | - J. Zennamo
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
| | | | - C. Zhang
- Brookhaven National Laboratory, Upton, NY 11973 USA
| | - S. Zucchelli
- INFN Sezione di Bologna and University of Bologna, Bologna, Italy
| | - M. Zuckerbrot
- Fermi National Accelerator Laboratory, Batavia, IL 60510 USA
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Zhang Y, Wang K, Yu H, Zhao T, Lin L, Qin X, Wu T, Chen D, Hu Y, Wu Y. Incidence and characteristics of aspiration pneumonia in adults in Beijing, China, 2011-2017. Public Health 2023; 220:65-71. [PMID: 37270854 DOI: 10.1016/j.puhe.2023.04.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/21/2023] [Accepted: 04/26/2023] [Indexed: 06/06/2023]
Abstract
OBJECTIVES This study aimed to estimate aspiration pneumonia (AP) incidence and describe comorbid characteristics and mortality in Beijing, China. STUDY DESIGN A historical cohort study was conducted based on medical claim records. METHODS Patients admitted with a primary diagnosis of AP were identified from approximately 12 million adults who enrolled in the Urban Employee Basic Medical Insurance program in Beijing, China, from January 2011 to December 2017. The incidences of AP and pneumonia with risk factors for aspiration (PRFA) were estimated by a Poisson distribution. The estimated annual percentage change was reported to represent the average percentage change in incidence per year. Characteristics and 6-month and 1-year all-cause mortality rates for AP and suspected AP patients were described and compared with community-acquired pneumonia (CAP). RESULTS The incidence rates of hospitalized AP and PRFA were 9.4 (95% confidence interval [CI]: 7.6, 11.3) and 102.9 (95% CI: 95.8, 110.3) per 100,000 person-years, respectively. The incidences increased rapidly with age and were stable across the observed years. Patients with AP and PRFA possessed a greater burden of comorbidities than CAP (mean age-adjusted Charlson comorbidity indices for AP: 7.72, PRFA: 7.83, and CAP: 2.84). The 6-month and 1-year all-cause mortality rates for those with AP and PRFA were higher than those for patients with CAP (6-month mortality, AP: 35.2%, PRFA: 21.8%, CAP: 11.1%; 1-year mortality, AP: 42.7%, PRFA: 26.6%, CAP: 13.2%). CONCLUSIONS The incidence of AP and PRFA in Beijing was reported, presenting a full picture of the disease burden. The results provide baseline information for AP prevention.
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Affiliation(s)
- Y Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China
| | - K Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China
| | - H Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China
| | - T Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China
| | - L Lin
- Geriatric Department, Peking University First Hospital, 100034, China
| | - X Qin
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, 100191, China
| | - T Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, 100191, China
| | - D Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, 100191, China
| | - Y Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, 100191, China.
| | - Y Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Health Science Center, 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, 100191, China.
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Wei S, Geng L, Yu H, Wang J, Yue Y, Zhang Q, Wu N. Isolation, Characterization, and Anti-Idiopathic Pulmonary Fibrosis Activity of a Fucoidan from Costaria costata. Molecules 2023; 28:molecules28114343. [PMID: 37298817 DOI: 10.3390/molecules28114343] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 05/12/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023] Open
Abstract
Pulmonary fibrosis is a chronic, progressive, and fatal disease of the interstitial lung. There is currently a lack of efficient therapy to reverse the prognosis of patients. In this study, a fucoidan from Costaria costata was isolated, and its anti-idiopathic fibrosis activity was investigated both in vitro and in vivo. The chemical composition analysis showed that C. costata polysaccharide (CCP) consists of galactose and fucose as the main monosaccharides with a sulfate group content of 18.54%. Further study found that CCP could resist TGF-β1-induced epithelial-mesenchymal transition (EMT) in A549 cells by inhibiting the TGF-β/Smad and PI3K/AKT/mTOR signaling pathways. Moreover, in vivo study found that CCP treatment alleviated bleomycin (BLM)-stimulated fibrosis and inflammation in mice lung tissue. In conclusion, the present study suggests that CCP could protect the lung from fibrosis by relieving the EMT process and inflammation in lung cells.
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Affiliation(s)
- Sijie Wei
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Lihua Geng
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Haoyu Yu
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Jing Wang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Yang Yue
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | - Quanbin Zhang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Ning Wu
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- Drugs and Bioproducts, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
- Nantong Zhongke Marine Science and Technology Research and Development Center, Nantong 226682, China
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Westberry TK, Behrenfeld MJ, Shi YR, Yu H, Remer LA, Bian H. Atmospheric nourishment of global ocean ecosystems. Science 2023; 380:515-519. [PMID: 37141373 DOI: 10.1126/science.abq5252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Over the vast open ocean, vital nutrients for phytoplankton growth in the sunlit surface layer are largely provided through physical transport from deep waters, but some nutrients are also provided through atmospheric deposition of desert dust. The extent and magnitude of dust-mediated effects on surface ocean ecosystems have been difficult to estimate globally. In this work, we use global satellite ocean color products to demonstrate widespread responses to atmospheric dust deposition across a diverse continuum of phytoplankton nutritional conditions. The observed responses vary regionally, with some areas exhibiting substantial changes in phytoplankton biomass, whereas in other areas, the response reflects a change in physiological status or health. Climate-driven changes in atmospheric aerosols will alter the relative importance of this nutrient source.
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Affiliation(s)
- T K Westberry
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - M J Behrenfeld
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Y R Shi
- Joint Center for Earth Systems Technology, University of Maryland, Baltimore County, Baltimore, MD, USA
- Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - H Yu
- Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - L A Remer
- Joint Center for Earth Systems Technology, University of Maryland, Baltimore County, Baltimore, MD, USA
- Airphoton Inc., Baltimore, MD, USA
| | - H Bian
- Joint Center for Earth Systems Technology, University of Maryland, Baltimore County, Baltimore, MD, USA
- Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
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Zhong BJ, Yang S, Hong DW, Cheng YL, Attin T, Yu H. The Efficacy of At-home, In-office, and Combined Bleaching Regimens: A Randomized Controlled Clinical Trial. Oper Dent 2023:492392. [PMID: 37079917 DOI: 10.2341/22-099-c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/06/2023] [Indexed: 04/22/2023]
Abstract
OBJECTIVE The aim of this study was to compare the clinical efficacy of at-home, in-office, and combined bleaching regimens. METHODS Forty-eight participants were recruited and randomly divided into four groups based on the bleaching regimen (n=12) as follows: 1) at-home bleaching using 10% carbamide peroxide (Opalescence PF 10%, Ultradent) for 14 days (HB); 2) two sessions of in-office bleaching using 40% hydrogen peroxide (Opalescence BOOST PF 40%, Ultradent) with a one-week interval (OB); 3) one session of in-office bleaching followed by at-home bleaching for seven days (OHB); and 4) at-home bleaching for seven days followed by one session of in-office bleaching (HOB). Tooth color was measured using a spectrophotometer (Easyshade, Vita ZahnFabrik) at baseline (T0), day 8 (T1), day 15 (T2), and day 43 (T3, four weeks after the end of the bleaching treatment). The color data were calculated using the CIEDE2000 (ΔE00) and whiteness index for dentistry (WID) formulas. Tooth sensitivity (TS) was recorded using a visual analogue scale (VAS) for 16 days. Data were analyzed by one-way analysis of variance (ANOVA) and the Wilcoxon signed-rank test (α=0.05). RESULTS All bleaching regimens resulted in a significant increase in WID values (all p<0.05), while no significant differences in WID and ΔWID values were found among the different groups at each time point (all p>0.05). Significant differences in ΔE00 values were observed between T1 and T3 for all groups (all p<0.05), while no significant differences in ΔE00 values were found among the different groups at any time point (all p>0.05). Significantly lower TS values were observed in the HB group than in the OB and HOB groups (p=0.006 and p=0.001, respectively). CONCLUSIONS All bleaching regimens resulted in great color improvement, and different regimens led to similar color changes at any of the evaluation time points. The sequence of treatments applying in-office bleaching or at-home bleaching did not affect the bleaching efficacy. The in-office bleaching and combined bleaching regimens yielded a higher intensity of TS than did at-home bleaching.
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Affiliation(s)
- B-J Zhong
- †Bing-jie Zhong, DDS, PhD candidate, Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China
| | - S Yang
- †Song Yang, DDS, MS, PhD candidate, Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China
| | - D-W Hong
- Deng-wei Hong, DDS, MS, dentist, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China
| | - Y-L Cheng
- Yi-ling Cheng, DDS, PhD candidate, Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China
| | - T Attin
- Thomas Attin, Dr Med Dent, professor, Clinic of Conservative and Preventive Dentistry, Center for Dental Medicine, University of Zurich, Switzerland
| | - H Yu
- *Hao Yu, DDS, PhD, Dr Med Dent, associate professor and Associate Dean, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China; adjunct professor, Department of Applied Prosthodontics, Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan
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42
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Liu Q, Dai Y, Yu H, Shen Y, Deng J, Lu W, Jin J. [NKD1 promotes glucose uptake in colon cancer cells by activating YWHAE transcription]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:585-589. [PMID: 37202194 DOI: 10.12122/j.issn.1673-4254.2023.04.11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
OBJECTIVE Bo investigate the regulatory relationship between NKD1 and YWHAE and the mechanism of NKD1 for promoting tumor cell proliferation. METHODS HCT116 cells transfected with pcDNA3.0-NKD1 plasmid, SW620 cells transfected with NKD1 siRNA, HCT116 cells with stable NKD1 overexpression (HCT116-NKD1 cells), SW620 cells with nkd1knockout (SW620-nkd1-/- cells), and SW620-nkd1-/- cells transfected with pcDNA3.0-YWHAE plasmid were examined for changes in mRNA and protein expression levels of YWHAE using qRT-PCR and Western blotting. Chromatin immunoprecipitation (ChIP) assay was used to detect the binding of NKD1 to the promoter region of YWHAE gene. The regulatory effect of NKD1 on YWHAE gene promoter activity was analyzed by dual-luciferase reporter gene assay, and the interaction between NKD1 and YWHAE was analyzed with immunofluorescence assay. The regulatory effect of NKD1 on glucose uptake was examined in the tumor cells. RESULTS In HCT116 cells, overexpression of NKD1 significantly enhanced the expression of YWHAE at both the mRNA and protein levels, while NKD1 knockout decreased its expression in SW620 cells (P < 0.001). ChIP assay showed that NKD1 protein was capable of binding to the YWHAE promoter sequence; dual luciferase reporter gene assay showed that NKD1 overexpression (or knockdown) in the colon cancer cells significantly enhanced (or reduced) the transcriptional activity of YWHAE promoter (P < 0.05). Immunofluorescence assay demonstrated the binding of NKD1 and YWHAE proteins in colon cancer cells. NKD1 knockout significantly reduced glucose uptake in colon cancer cells (P < 0.01), while YWHAE overexpression restored the glucose uptake in NKD1-knockout cells (P < 0.05). CONCLUSION NKD1 protein activates the transcriptional activity of YWHAE gene to promote glucose uptake in colon cancer cells.
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Affiliation(s)
- Q Liu
- Department of Oncology, Wujin Hospital Affiliated to Jiangsu University/Wujin Clinical College, Xuzhou Medical University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine/Wujin Institute of Molecular Diagnostics and Precision Cancer Medicine of Jiangsu University, Changzhou 213017, China
| | - Y Dai
- Department of Oncology, Wujin Hospital Affiliated to Jiangsu University/Wujin Clinical College, Xuzhou Medical University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine/Wujin Institute of Molecular Diagnostics and Precision Cancer Medicine of Jiangsu University, Changzhou 213017, China
| | - H Yu
- Department of Oncology, Wujin Hospital Affiliated to Jiangsu University/Wujin Clinical College, Xuzhou Medical University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine/Wujin Institute of Molecular Diagnostics and Precision Cancer Medicine of Jiangsu University, Changzhou 213017, China
| | - Y Shen
- Department of Oncology, Wujin Hospital Affiliated to Jiangsu University/Wujin Clinical College, Xuzhou Medical University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine/Wujin Institute of Molecular Diagnostics and Precision Cancer Medicine of Jiangsu University, Changzhou 213017, China
| | - J Deng
- Department of Oncology, Wujin Hospital Affiliated to Jiangsu University/Wujin Clinical College, Xuzhou Medical University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine/Wujin Institute of Molecular Diagnostics and Precision Cancer Medicine of Jiangsu University, Changzhou 213017, China
| | - W Lu
- Department of Oncology, Wujin Hospital Affiliated to Jiangsu University/Wujin Clinical College, Xuzhou Medical University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine/Wujin Institute of Molecular Diagnostics and Precision Cancer Medicine of Jiangsu University, Changzhou 213017, China
| | - J Jin
- Department of Oncology, Wujin Hospital Affiliated to Jiangsu University/Wujin Clinical College, Xuzhou Medical University, Changzhou 213017, China
- Changzhou Key Laboratory of Molecular Diagnostics and Precision Cancer Medicine/Wujin Institute of Molecular Diagnostics and Precision Cancer Medicine of Jiangsu University, Changzhou 213017, China
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Zheng ZB, Yu H, Zheng W, Chen Q, Lou XQ, Liu XD, Wang HQ, Pan JC. [Drug resistance and genomic characteristics of Salmonella enterica serovar London from clinical and food sources in Hangzhou City from 2017 to 2021]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:508-515. [PMID: 37032160 DOI: 10.3760/cma.j.cn112150-20220622-00645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/11/2023]
Abstract
Objective: To analyze the drug resistance and genomic characteristics of Salmonella enterica serovar London isolated from clinical and food sources in Hangzhou City from 2017 to 2021. Methods: A total of 91 Salmonella enterica serovar London strains isolated from Hangzhou City from 2017 to 2021 were analyzed for drug susceptibility, pulsed field gel electrophoresis (PFGE) typing and whole genome sequencing. Multilocus sequence typing (MLST), core genome multilocus sequence typing (cgMLST) and detection of drug resistance genes were performed by using the sequencing data. Phylogenetic analysis was conducted to compare the 91 genomes from Hangzhou City with 347 genomes from public databases. Results: No significant difference in the drug resistance rate was observed between clinical strains and food strains to 18 drugs in Hangzhou City(all P>0.05), and the multidrug resistance (MDR) rate was 75.8% (69/91). Most strains were resistant to 7 drug classes simultaneously. One strain was resistant to Polymyxin E as well as positive for mcr-1.1, and 50.5% (46/91) of the strains were resistant to Azithromycin and were positive for mph(A). All 91 Salmonella enterica serovar London strains were ST155, which were subdivided into 44 molecular types by PFGE and 82 types by cgMLST. Phylogenetic analysis showed that most strains from Hangzhou City (83/91) were clustered together, and a small number of human isolates from Europe, North America and pork isolates from Hubei and Shenzhen were mixed in the cluster. Other strains from Hangzhou City (8/91) were closely related to strains from Europe, America and Southeast Asia. Strains isolated from pork were the most closely related to clinical strains. Conclusion: The epidemic of Salmonella enterica serovar London in Hangzhou City is mainly caused by the spread of ST155 strains, which is mainly transmitted locally. At the same time, cross-region transmission to Europe, North America, Southeast Asia, and other provinces and cities in China may also occur. There is no significant difference in the drug resistance rate between clinical strains and food strains, and a high level of MDR is found in the strains. Clinical infection of Salmonella enterica serovar London may be closely related to pork consumption in Hangzhou City.
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Affiliation(s)
- Z B Zheng
- Health Inspection Center, Hangzhou Center for Disease Control and Prevention, Hangzhou 310021, China
| | - H Yu
- Health Inspection Center, Hangzhou Center for Disease Control and Prevention, Hangzhou 310021, China
| | - W Zheng
- Health Inspection Center, Hangzhou Center for Disease Control and Prevention, Hangzhou 310021, China
| | - Q Chen
- Health Inspection Center, Hangzhou Center for Disease Control and Prevention, Hangzhou 310021, China
| | - X Q Lou
- Health Inspection Center, Hangzhou Center for Disease Control and Prevention, Hangzhou 310021, China
| | - X D Liu
- Health Inspection Center, Hangzhou Center for Disease Control and Prevention, Hangzhou 310021, China
| | - H Q Wang
- Health Inspection Center, Hangzhou Center for Disease Control and Prevention, Hangzhou 310021, China
| | - J C Pan
- Health Inspection Center, Hangzhou Center for Disease Control and Prevention, Hangzhou 310021, China
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Zhou N, Li X, Wang J, Yu H, Su C, Zu L, Huang D, Xu S. 224P Genetic landscape, PD-L1 expression, and CD8+ infiltration in Chinese pulmonary carcinoids. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00477-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Chen X, He J, Shen H, Xi Y, Chen B, He X, Gao J, Yu H, Shen W. 97P Aumolertinib as adjuvant therapy in postoperative EGFR-mutated stage I–III non-small cell lung cancer with high-risk pathological factors. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00352-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
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Chen M, Yu H. 61P Early palliative care in patients with non-small cell lung cancer: A 36-weeks randomised controlled trial in China. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00315-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Chen M, Yu H. Gut Microbiota Mediates The Protective Effects Of Resveratrol Against The Intestinal Barrier Dysfunction In Non-Alcoholic Steatohepatitis Induced By High-Fat Diet. Clin Nutr ESPEN 2023. [DOI: 10.1016/j.clnesp.2022.09.298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2023]
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Chen M, Yu H. Early Palliative Care Focus On Nutritional Status In Patients With Non-Small-Cell Lung Cancer: A Randomised Controlled Trial In Southwest China. Clin Nutr ESPEN 2023. [DOI: 10.1016/j.clnesp.2022.09.093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2023]
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Liang Q, Allaire J, Celiberto L, Yu H, Vallance B. A40 GUT MICROBIOTA PROMOTES NUTRIENT AVAILABLITY AND PATHOGENESIS OF AN ATTACHING/ EFFACING BACTERIAL PATHOGEN. J Can Assoc Gastroenterol 2023. [PMCID: PMC9991097 DOI: 10.1093/jcag/gwac036.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
Background Our gut microbiota plays an important role in protecting the gastrointestinal (GI) tract from invading enteric pathogens. Much of this colonization resistance is mediated by limiting nutrient availability, however, enteric pathogens have evolved strategies to subvert this competition, utilizing commensal metabolites to facilitate their infection. Access to nutrients is not only crucial for a pathogen’s metabolic fitness, but can also drive the expression of virulence factors, a process high in energy demands. In addition, enteric pathogens, such as the attaching and effacing (A/E) bacterium Citrobacter rodentium, must cross the colonic mucus layer that normally prevents their direct access to the underlying epithelium. Intestinal mucus is comprised of highly glycosylated mucins, with the sugar sialic acid frequently occupying the terminal position of their O-glycan side chains. We hypothesize that C. rodentium utilizes commensal-liberated mucin sugars, such as sialic acid, as nutrients and signals to promote its virulence. Purpose This study investigates the mechanisms by which A/E pathogens reach the colonic mucosal surface, and the role played by commensal microbes in facilitating the infection. Method Expression of virulence factors secreted by C. rodentium in the presence or absence of sialic acid was analyzed by SDS-PAGE and mass spectrometry. Next, we infected specific-pathogen free (SPF), germfree (GF), and previously GF C57Bl/6 mice mono-colonized with Bacteroides thetaotaomicron, a mucus-degrading commensal, to examine their susceptibility to C. rodentium and to measure the levels of free sialic acid in their feces. Result(s) Sensing of sialic acid by C. rodentium, was found to induce the secretion of several key virulence proteins, enhancing the pathogen’s migration across the colonic mucus layer and adhesion to the underlying epithelium. Access to sialic acid within the gut environment was enhanced in the presence of microbiota, as the levels of free sialic acid were low in GF mice. Interestingly, despite GF mice carrying very high C. rodentium burdens, passage across the mucus layer and infection of their colonic epithelium was impaired as compared to SPF mice. Notably, B. thetaotaomicron was found to degrade whole mucus in vitro, facilitating its consumption by C. rodentium for growth, while B. thetaotaomicron mono-colonized GF mice showed increased susceptibility to colonic infection by C. rodentium. Conclusion(s) We demonstrate that although commensal microbes promote colonization resistance, as an A/E pathogen infection establishes, specific commensal bacteria accelerate infection in the GI tract by releasing an important nutrient, ie. sialic acid, from mucus. Access to sialic acid promotes C. rodentium virulence by inducing the key virulence factors that facilitate its translocation across the mucus layer as well as adhesion to the epithelium, thereby expediting disease progression. Please acknowledge all funding agencies by checking the applicable boxes below CCC, CIHR, Other Please indicate your source of funding; CH.I.L.D. Foundation Disclosure of Interest None Declared
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Affiliation(s)
- Q Liang
- Experimental Medicine, University of British Columbia,Pediatrics, BC Children's Hospital Research Institute, Vancouver, BC
| | - J Allaire
- The Janssen Pharmaceutical Companies of Johnson & Johnson, Montreal, QC, Canada
| | - L Celiberto
- Pediatrics, BC Children's Hospital Research Institute, Vancouver, BC
| | - H Yu
- Pediatrics, BC Children's Hospital Research Institute, Vancouver, BC
| | - B Vallance
- Pediatrics, BC Children's Hospital Research Institute, Vancouver, BC
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Yang H, Han X, Ma C, Yu H, Vallance B. A15 GENETIC OR DIET-ASSOCIATED DEFECTS IN MUCUS FACILITATE ULCERATIVE COLITIS PATHOBIONT-DRIVEN COLITIS. J Can Assoc Gastroenterol 2023. [PMCID: PMC9991288 DOI: 10.1093/jcag/gwac036.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
Background The Inflammatory Bowel Diseases (IBD), Crohn’s Disease (CD) and ulcerative colitis (UC) affect > 270,000 Canadians and are increasing in incidence. Ileal CD has been linked to the overgrowth of mucosal adherent E. coli. Recent studies have also implicated the adherence of Escherichia coli pathobionts to the colonic mucosa of UC patients. Using the representative UC E. coli pathobiont p19A, we recently demonstrated it aggravated chemical-induced colitis in susceptible mice, through the actions of the toxin alpha-hemolysin, and by adhering to the inflamed colonic mucosa via the adhesin FimH. It is less clear what host factors control susceptibility to the UC pathobionts. One of the potential candidates is the glycosylated mucin (Muc2) which forms the mucus layer that covers the colonic epithelium and is often impaired in UC patients. Purpose To define the role of mucus structure and function in determining susceptibility to the p19A pathobiont, and its ability to cause colitis in mice. Method In vitro growth was assessed to test p19A’s ability to utilize mucin-derived sugars as nutrients. Susceptibility to p19A was tested in two mouse models of colonic mucus impairment. The first is a mouse strain deficient in core 1 derived O-glycans in their intestinal epithelial cells (IEC C1galt1-/-), resulting in reduced Muc2 glycosylation, and thus a thin and impaired mucus barrier. The second model involves feeding wildtype (WT) C57BL/6CR mice a fiber-free (FF) diet, resulting in a significantly thinner colonic mucus layer. The mice were subsequently orally gavaged with p19A and their susceptibility determined by p19A burdens, intestinal histopathology, inflammatory cytokine and short chain fatty acid (SCFA) production. Result(s) When tested in vitro, the p19A pathobiont was found to use an array of mucin-derived sugars as sole carbon source to proliferate. Following oral gavage of WT mice fed a normal diet, immunostaining identified p19A within the colonic mucus but it did not reach the colonic mucosa or cause disease. In contrast, p19A was found at the colonic mucosal surface of mucus-defective IEC C1galt1-/- mice (as compared to IEC C1galt1flox/flox mice) and in WT mice fed a fiber-free diet. This mucosal adherence was associated with increased body weight loss during the course of infection, as well as increased p19A burdens, colonic pathology and pro-inflammatory cytokine expression. Especially fiber-free diet-fed mice showed reduced SCFA levels in their feces at baseline. When the mice were given exogenous SCFA (tributyrin) orally, p19A infection was reduced. Conclusion(s) Our results indicate that UC E. coli pathobionts are able to dwell within colonic mucus and utilize mucin sugars as nutrients. Moreover, they can reach the mucosal surface and induce colitis in hosts suffering genetic or diet-based mucus dysfunction. In part, this susceptibility reflects the important role played by mucus in the production of SCFA, suggesting potential therapeutic approaches for patients suffering UC. Please acknowledge all funding agencies by checking the applicable boxes below CCC, CIHR Disclosure of Interest None Declared
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Affiliation(s)
- H Yang
- Pediatrics, BC Children's Hospital, Vancouver, Canada
| | - X Han
- Pediatrics, BC Children's Hospital, Vancouver, Canada
| | - C Ma
- Pediatrics, BC Children's Hospital, Vancouver, Canada
| | - H Yu
- Pediatrics, BC Children's Hospital, Vancouver, Canada
| | - B Vallance
- Pediatrics, BC Children's Hospital, Vancouver, Canada
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