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Liénard MA, Baez-Nieto D, Tsai CC, Valencia-Montoya WA, Werin B, Johanson U, Lassance JM, Pan JQ, Yu N, Pierce NE. TRPA5 encodes a thermosensitive ankyrin ion channel receptor in a triatomine insect. iScience 2024; 27:109541. [PMID: 38577108 PMCID: PMC10993193 DOI: 10.1016/j.isci.2024.109541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 02/28/2024] [Accepted: 03/18/2024] [Indexed: 04/06/2024] Open
Abstract
As ectotherms, insects need heat-sensitive receptors to monitor environmental temperatures and facilitate thermoregulation. We show that TRPA5, a class of ankyrin transient receptor potential (TRP) channels absent in dipteran genomes, may function as insect heat receptors. In the triatomine bug Rhodnius prolixus (order: Hemiptera), a vector of Chagas disease, the channel RpTRPA5B displays a uniquely high thermosensitivity, with biophysical determinants including a large channel activation enthalpy change (72 kcal/mol), a high temperature coefficient (Q10 = 25), and in vitro temperature-induced currents from 53°C to 68°C (T0.5 = 58.6°C), similar to noxious TRPV receptors in mammals. Monomeric and tetrameric ion channel structure predictions show reliable parallels with fruit fly dTRPA1, with structural uniqueness in ankyrin repeat domains, the channel selectivity filter, and potential TRP functional modulator regions. Overall, the finding of a member of TRPA5 as a temperature-activated receptor illustrates the diversity of insect molecular heat detectors.
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Affiliation(s)
- Marjorie A. Liénard
- Department of Biology, Lund University, 22362 Lund, Sweden
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
- Broad Institute, Cambridge, MA 02142, USA
| | - David Baez-Nieto
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA 02142, USA
| | - Cheng-Chia Tsai
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Wendy A. Valencia-Montoya
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
| | - Balder Werin
- Division of Biochemistry and Structural Biology, Department of Chemistry, Lund University, 22362 Lund, Sweden
| | - Urban Johanson
- Division of Biochemistry and Structural Biology, Department of Chemistry, Lund University, 22362 Lund, Sweden
| | - Jean-Marc Lassance
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
- Laboratory of Evolutionary Neuroethology, GIGA Institute, University of Liège, 4000 Liège, Belgium
| | - Jen Q. Pan
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA 02142, USA
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Naomi E. Pierce
- Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
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Dang S, Han D, Duan H, Jiang Y, Aihemaiti A, Yu N, Yu Y, Duan X. The value of T2-weighted MRI contrast ratio combined with DWI in evaluating the pathological grade of solid lung adenocarcinoma. Clin Radiol 2024; 79:279-286. [PMID: 38216369 DOI: 10.1016/j.crad.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/30/2023] [Accepted: 12/09/2023] [Indexed: 01/14/2024]
Abstract
AIM To assess the predictive value of T2-weighted (T2W) magnetic resonance imaging (MRI) in combination with diffusion-weighted imaging (DWI) for determining the pathological grading of solid lung adenocarcinoma. MATERIALS AND METHODS The clinical and imaging data from 153 cases of solid lung adenocarcinoma (82 men, 71 women, mean age 63.2 years) confirmed at histopathology in The First Affiliated Hospital of Xi'an Jiaotong University from January 2017 to May 2022 were analysed retrospectively. Adenocarcinomas were classified into low-grade (G1 and G2) and high-grade (G3) groups following the 2020 pathological grading system proposed by the International Association for the Study of Lung Cancer. The T2-weighted contrast ratio (T2CR), calculated as the T2 signal intensity of the lung mass/nodule divided by the T2 signal intensity of the right rhomboid muscle was utilised. Two experienced radiologists reviewed the MRI images independently, measured the T2CR, and obtained apparent diffusion coefficient (ADC) values. The Mann-Whitney U-test was used to compare general characteristics (sex, age, maximum diameter), T2CR, and ADC values between the low-grade and high-grade groups. The non-parametric Kruskal-Wallis test determined differences in T2CR and ADC values among the five adenocarcinoma subtypes. Receiver characteristic curve (ROC) analysis, along with area under the curve (AUC) calculation, assessed the effectiveness of each parameter in distinguishing the pathological grade of lung adenocarcinoma. A Z-test was used to compare the AUC values. RESULTS Among the 153 patients with adenocarcinoma, 103 had low-grade adenocarcinoma, and 50 had high-grade adenocarcinoma. The agreement between T2CR and ADC observers was good (0.948 and 0.929, respectively). None of the parameters followed a normal distribution (p<0.05). The ADC value was lower in the high-grade adenocarcinoma group compared to the low-grade adenocarcinoma group (p=0.004), while the T2CR value was higher in the high-grade group (p=0.011). Statistically significant differences were observed in maximum diameter and gender between the two groups (p<0.001 and p=0.005, respectively), while no significant differences were noted in age (p=0.980). Among the five adenocarcinoma subtypes, only the lepidic and micropapillary subtypes displayed statistical differences in ADC values (p=0.047), with the remaining subtypes showing no statistical differences (p>0.05). The AUC values for distinguishing high-grade adenocarcinoma from low-grade adenocarcinoma were 0.645 for ADC and 0.627 for T2CR. Combining T2CR, ADC, sex, and maximum diameter resulted in an AUC of 0.778, sensitivity of 70%, and specificity of 75%. This combination significantly improved diagnostic efficiency compared to T2CR and ADC alone (p=0.008, z = 2.624; p=0.007, z = 2.679). CONCLUSION The MRI quantitative parameters are useful for distinguishing the pathological grades of solid lung adenocarcinoma, offering valuable insights for precise lung cancer treatment.
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Affiliation(s)
- S Dang
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shannxi 710061, China; Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - D Han
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shannxi 710061, China; Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - H Duan
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shannxi 710061, China; Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - Y Jiang
- Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - A Aihemaiti
- Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - N Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China; Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - Y Yu
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shannxi 710061, China; Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China; Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - X Duan
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shannxi 710061, China.
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Carter MJ, Resneck L, Ra'di Y, Yu N. Flat-Knit, Flexible, Textile Metasurfaces. Adv Mater 2024:e2312087. [PMID: 38419481 DOI: 10.1002/adma.202312087] [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: 11/13/2023] [Revised: 02/18/2024] [Indexed: 03/02/2024]
Abstract
Lightweight, low-cost metasurfaces and reflectarrays that are easy to stow and deploy are desirable for many terrestrial and space-based communications and sensing applications. This work demonstrates a lightweight, flexible metasurface platform based on flat-knit textiles operating in the cm-wave spectral range. By using a colorwork knitting approach called float-jacquard knitting to directly integrate an array of resonant metallic antennas into a textile, we realize two textile reflectarray devices, a metasurface lens (metalens) and a vortex-beam generator. Operating as a receiving antenna, the metalens focuses a collimated normal-incidence beam to a diffraction-limited, off-broadside focal spot. Operating as a transmitting antenna, the metalens converts the divergent emission from a horn antenna into a collimated beam with peak measured directivity, gain, and efficiency of 21.30 dB, 15.30 dB, and -6.00 dB (25.12%), respectively. The vortex-beam generating metasurface produces a focused vortex beam with a topological charge of m = 1 over a wide frequency range of 4.1-5.8 GHz. Strong specular reflection is observed for our textile reflectarrays, caused by wavy yarn floats on the backside of the float-jacquard textiles. Our work demonstrates a novel approach for scalable production of flexible metasurfaces by leveraging commercially available yarns and well-established knitting machinery and techniques. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Michael J Carter
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA
- Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson AFB, OH, 45433-7707, USA
| | - Leah Resneck
- Zeis Textiles Extension, Wilson College of Textiles, North Carolina State University, Raleigh, NC, 27606, USA
| | - Younes Ra'di
- Advanced Science Research Center, City University of New York, New York, NY, 10031, USA
- Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, 13244, USA
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA
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Wu YC, Yu N, Rivas C, Mehrnia N, Kantarci A, Van Dyke T. RvE1 Promotes Axin2+ Cell Regeneration and Reduces Bacterial Invasion. J Dent Res 2023; 102:1478-1487. [PMID: 37837227 PMCID: PMC10767698 DOI: 10.1177/00220345231197156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023] Open
Abstract
Vital pulp therapy and root canal therapy (RCT) are the dominant treatment for irreversible pulpitis. While the success rate of these procedures is favorable, they have some limitations. For instance, RCT leads to removing significant dentin in the coronal third of the tooth that increases root-fracture risk, which forces tooth removal. The ideal therapeutic goal is dental pulp regeneration, which is not achievable with RCT. Specialized proresolving mediators (SPMs) are well known for inflammatory resolution. The resolution of inflammation and tissue restoration or regeneration is a dynamic and continuous process. SPMs not only have potent immune-modulating functions but also effectively promote tissue homeostasis and regeneration. Resolvins have been shown to promote dental pulp regeneration. The purpose of this study was to explore further the cellular target of Resolvin E1 (RvE1) therapy in dental pulp regeneration and the impact of RvE1 in infected pulps. We investigated the actions of RvE1 on experimentally exposed pulps with or without microbial infection in an Axin2Cre-Dox;Ai14 genetically defined mouse model. Our results showed RvE1 promoted Axin2-tdTomato+ cell expansion and odontoblastic differentiation after direct pulp capping in the mouse, which we used to mimic reversible pulpitis cases in the clinic. In cultured mouse dental pulp stem cells (mDPSCs), RvE1 facilitated Axin2-tdTomato+ cell proliferation and odontoblastic differentiation and also rescued impaired functions after lipopolysaccharide stimulation. In infected pulps exposed to the oral environment for 24 h, RvE1 suppressed inflammatory infiltration, reduced bacterial invasion in root canals, and prevented the development of apical periodontitis, while its proregenerative impact was limited. Collectively, topical treatment with RvE1 facilitated dental pulp regenerative properties by promoting Axin2-expressing cell proliferation and differentiation. It also modulated the resolution of inflammation, reduced infection severity, and prevented apical periodontitis, presenting RvE1 as a novel therapeutic for treating endodontic diseases.
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Affiliation(s)
- Y-C. Wu
- The Forsyth Institute, Cambridge, MA, USA
- Harvard School of Dental Medicine, Boston, MA, USA
- Department of Operative Dentistry and Endodontics, School of Dentistry, Tri-Service General Hospital and National Defense Medical Center, Taipei
| | - N. Yu
- The Forsyth Institute, Cambridge, MA, USA
- Harvard School of Dental Medicine, Boston, MA, USA
| | - C.A. Rivas
- The Forsyth Institute, Cambridge, MA, USA
- Harvard School of Dental Medicine, Boston, MA, USA
| | - N. Mehrnia
- The Forsyth Institute, Cambridge, MA, USA
| | - A. Kantarci
- The Forsyth Institute, Cambridge, MA, USA
- Harvard School of Dental Medicine, Boston, MA, USA
| | - T.E. Van Dyke
- The Forsyth Institute, Cambridge, MA, USA
- Harvard School of Dental Medicine, Boston, MA, USA
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Chen XM, Yu N, Yang SM, Jiang QQ. [Research progress on lipid droplet and its role in noise-induced hearing loss]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2023; 58:1050-1053. [PMID: 37840175 DOI: 10.3760/cma.j.cn115330-20230316-00118] [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] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Affiliation(s)
- X M Chen
- Senior Department of Otolaryngology-Head & Neck Surgery, Chinese PLA General Hospital; National Clinical Research Center for Otolaryngologic Diseases; National Key Laboratory for Hearing and Balance; Chinese PLA Institute of Otolaryngology; State Key Lab of Hearing Science, Ministry of Education; Beijing Key Lab of Hearing Impairment Prevention and Treatment, Beijing 100853, China Department of Otolaryngology, Navy 971 Hospital of Chinese PLA, Qingdao 266071, China
| | - N Yu
- Senior Department of Otolaryngology-Head & Neck Surgery, Chinese PLA General Hospital; National Clinical Research Center for Otolaryngologic Diseases; National Key Laboratory for Hearing and Balance; Chinese PLA Institute of Otolaryngology; State Key Lab of Hearing Science, Ministry of Education; Beijing Key Lab of Hearing Impairment Prevention and Treatment, Beijing 100853, China
| | - S M Yang
- Senior Department of Otolaryngology-Head & Neck Surgery, Chinese PLA General Hospital; National Clinical Research Center for Otolaryngologic Diseases; National Key Laboratory for Hearing and Balance; Chinese PLA Institute of Otolaryngology; State Key Lab of Hearing Science, Ministry of Education; Beijing Key Lab of Hearing Impairment Prevention and Treatment, Beijing 100853, China
| | - Q Q Jiang
- Senior Department of Otolaryngology-Head & Neck Surgery, Chinese PLA General Hospital; National Clinical Research Center for Otolaryngologic Diseases; National Key Laboratory for Hearing and Balance; Chinese PLA Institute of Otolaryngology; State Key Lab of Hearing Science, Ministry of Education; Beijing Key Lab of Hearing Impairment Prevention and Treatment, Beijing 100853, China
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Yu N, Li J, Chen X, Wang Z, Kang X, Zhang R, Qin J, Zheng Q, Feng G, Deng L, Zhang T, Wang W, Liu W, Wang J, Feng Q, Lv J, Chen D, Zhou Z, Xiao Z, Li Y, Bi N, Li Y, Wang X. Chemoradiotherapy Combined with Nab-Paclitaxel plus Cisplatin in Patients with Locally Advanced Borderline Resectable or Unresectable Esophageal Squamous Cell Carcinoma: A Phase I/II Study. Int J Radiat Oncol Biol Phys 2023; 117:e354. [PMID: 37785224 DOI: 10.1016/j.ijrobp.2023.06.2433] [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 evaluate the efficacy and safety of nanoparticle albumin-bound paclitaxel (nab-PTX) plus cisplatin as the regimen of conversional chemoradiotherapy (cCRT) in locally advanced borderline resectable or unresectable esophageal squamous cell carcinoma (ESCC). MATERIALS/METHODS Patients with locally advanced ESCC (cT3-4, Nany, M0-1, M1 was limited to lymph node metastasis in the supraclavicular area) were enrolled. All the patients received the cCRT of nab-PTX plus cisplatin. After the cCRT, those resectable patients received esophagectomy; those unresectable patients continued to receive the definitive chemoradiotherapy (dCRT). The locoregional control (LRC), overall survival (OS), progression-free survival (PFS), distant metastasis free survival (DMFS), pathological complete response (pCR), R0 resection rate and adverse events (AEs) were calculated. RESULTS A total of 45 patients with ESCC treated from October 2019 to May 2021 were finally included. The median follow-up time was 30.3 months. The LRC, OS, EFS, DMFS at 1and 2 years were 81.5%, 86.6%, 64.3%, 73.2% and 72.4%, 68.8%, 44.8%, 52.7% respectively. 21 patients (46.7%) received conversional chemoradiotherapy plus surgery (cCRT+S). The pCR rate and R0 resection rate were 47.6% and 84.0%. The LRC rate at 1 and 2 years were 95.0%, 87.1% in cCRT+S patients and 69.3%, 58.7% in dCRT patients respectively (HR, 5.14; 95% CI, 1.10-23.94; P = 0.021). The OS rate at 1 and 2 years were 95.2% and 84.2% in resectable patients compared to 78.8% and 54.4% in unresectable patients (HR, 3.41; 95% CI, 1.10-10.61; P = 0.024). The toxicities during chemoradiotherapy were tolerated, the most common grade 3-4 toxicities were radiation esophagitis (15.6%). CONCLUSION Nab-PTX plus cisplatin were effective and safe as the regimen of conversional chemoradiotherapy of ESCC. The patients receiving conversional chemoradiotherapy plus surgery (cCRT+S) were prone to have a better survival.
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Affiliation(s)
- N Yu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X Chen
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Z Wang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X Kang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - R Zhang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Qin
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Q Zheng
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - G Feng
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - L Deng
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - T Zhang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing, China
| | - W Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - W Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing, China
| | - Q Feng
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Lv
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - D Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Z Zhou
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing, China
| | - Z Xiao
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N Bi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Xue TT, Wang LM, Zhao ZP, Zhang X, Li C, Huang ZJ, Gao XX, Liu CY, Yu N, Zhang YS, Deng XQ, Wang L, Zhang M. [Cardiovascular health status of Chinese adults based on "Life's Essential 8" score]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1054-1062. [PMID: 37482706 DOI: 10.3760/cma.j.cn112338-20221020-00894] [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: 07/25/2023]
Abstract
Objective: To assess the cardiovascular health status of adults in China by using the "Life's Essential 8" score, and provide reference for the development and improvement of cardiovascular disease prevention and control policies and measures. Methods: Chronic Disease and Nutrition Surveillance was conducted in 298 counties/districts in 2015 in 31 provinces (autonomous regions, municipalities) across China, multi-stage stratified cluster random sampling was used to select 45 households in each village or neighborhood, and 20 households were further selected to conduct dietary surveys. In this study, a total of 70 093 adults aged ≥20 years who completed the dietary survey and had complete information were included, their cardiovascular health status were assessed by using the "Life's Essential 8" score, a cardiovascular health scoring standard released by the American Heart Association in 2022. All results were adjusted using complex design-based sampling weights to achieve a better estimate of the population. Results: In 2015, the overall cardiovascular health score of Chinese adults aged ≥20 years was 73.3±12.6, the score was significantly higher in women (77.9±11.6) than in men (68.7±11.8), and higher in urban area (74.5±12.8) than in rural area (71.9±12.2), the differences were significant (P<0.001). It was estimated that about 0.25% (95%CI: 0.16%-0.33%) of adults in China had cardiovascular health score of 100, and 33.0% (95%CI: 31.6%-34.3%), 63.2% (95%CI: 62.1%-64.3%), and 3.9% (95%CI: 3.5%-4.2%) of adults had high, moderate and low cardiovascular health scores, respectively. The proportion of those with high cardiovascular health scores was relatively low in men, those with low education level, those with low income, those living in rural areas, and those living in southwest China (P<0.001). Of the eight factors, diet had the lowest mean score (46.0, 95%CI: 44.7-47.3), followed by blood pressure (59.4, 95%CI: 58.2-60.6) and tobacco exposure (61.4, 95%CI: 60.6-62.2). Conclusions: The cardiovascular health status of two-thirds of adult population in China needs to be improved. Diet, tobacco exposure, and blood pressure are the factors affecting the cardiovascular health of Chinese population, to which close attention needs to be paid, and men, rural residents, and those with lower socioeconomic status are key groups in cardiovascular health promotion.
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Affiliation(s)
- T T Xue
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - L M Wang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z P Zhao
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - X Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - C Li
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z J Huang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - X X Gao
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China School of Public Health, Baotou Medical College, Baotou 014040, China
| | - C Y Liu
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China School of Public Health, Baotou Medical College, Baotou 014040, China
| | - N Yu
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Y S Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - X Q Deng
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - L Wang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - M Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
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Abdulhamid MI, Aboona BE, Adam J, Adams JR, Agakishiev G, Aggarwal I, Aggarwal MM, Ahammed Z, Aitbaev A, Alekseev I, Anderson DM, Aparin A, Aslam S, Atchison J, Averichev GS, Bairathi V, Baker W, Ball Cap JG, Barish K, Bhagat P, Bhasin A, Bhatta S, Bordyuzhin IG, Brandenburg JD, Brandin AV, Cai XZ, Caines H, Calderón de la Barca Sánchez M, Cebra D, Ceska J, Chakaberia I, Chan BK, Chang Z, Chatterjee A, Chen D, Chen J, Chen JH, Chen Z, Cheng J, Cheng Y, Choudhury S, Christie W, Chu X, Crawford HJ, Dale-Gau G, Das A, Daugherity M, Dedovich TG, Deppner IM, Derevschikov AA, Dhamija A, Di Carlo L, Didenko L, Dixit P, Dong X, Drachenberg JL, Duckworth E, Dunlop JC, Engelage J, Eppley G, Esumi S, Evdokimov O, Ewigleben A, Eyser O, Fatemi R, Fazio S, Feng CJ, Feng Y, Finch E, Fisyak Y, Flor FA, Fu C, Geurts F, Ghimire N, Gibson A, Gopal K, Gou X, Grosnick D, Gupta A, Hamed A, Han Y, Harasty MD, Harris JW, Harrison-Smith H, He W, He XH, He Y, Hu C, Hu Q, Hu Y, Huang H, Huang HZ, Huang SL, Huang T, Huang X, Huang Y, Huang Y, Humanic TJ, Isenhower D, Isshiki M, Jacobs WW, Jalotra A, Jena C, Ji Y, Jia J, Jin C, Ju X, Judd EG, Kabana S, Kabir ML, Kalinkin D, Kang K, Kapukchyan D, Kauder K, Ke HW, Keane D, Kechechyan A, Kelsey M, Kimelman B, Kiselev A, Knospe AG, Ko HS, Kochenda L, Korobitsin AA, Kravtsov P, Kumar L, Kumar S, Kunnawalkam Elayavalli R, Lacey R, Landgraf JM, Lebedev A, Lednicky R, Lee JH, Leung YH, Lewis N, Li C, Li W, Li X, Li Y, Li Y, Li Z, Liang X, Liang Y, Lin T, Liu C, Liu F, Liu H, Liu H, Liu L, Liu T, Liu X, Liu Y, Liu Z, Ljubicic T, Llope WJ, Lomicky O, Longacre RS, Loyd EM, Lu T, Lukow NS, Luo XF, Luong VB, Ma L, Ma R, Ma YG, Magdy N, Mallick D, Margetis S, Matis HS, Mazer JA, McNamara G, Mi K, Minaev NG, Mohanty B, Mondal MM, Mooney I, Morozov DA, Mudrokh A, Nagy MI, Nain AS, Nam JD, Nasim M, Neff D, Nelson JM, Nemes DB, Nie M, Nigmatkulov G, Niida T, Nishitani R, Nogach LV, Nonaka T, Odyniec G, Ogawa A, Oh S, Okorokov VA, Okubo K, Page BS, Pak R, Pan J, Pandav A, Pandey AK, Panebratsev Y, Pani T, Parfenov P, Paul A, Perkins C, Pokhrel BR, Posik M, Protzman T, Pruthi NK, Putschke J, Qin Z, Qiu H, Quintero A, Racz C, Radhakrishnan SK, Raha N, Ray RL, Ritter HG, Robertson CW, Rogachevsky OV, Rosales Aguilar MA, Roy D, Ruan L, Sahoo AK, Sahoo NR, Sako H, Salur S, Samigullin E, Sato S, Schmidke WB, Schmitz N, Seger J, Seto R, Seyboth P, Shah N, Shahaliev E, Shanmuganathan PV, Shao T, Sharma M, Sharma N, Sharma R, Sharma SR, Sheikh AI, Shen DY, Shen K, Shi SS, Shi Y, Shou QY, Si F, Singh J, Singha S, Sinha P, Skoby MJ, Söhngen Y, Song Y, Srivastava B, Stanislaus TDS, Stewart DJ, Strikhanov M, Stringfellow B, Su Y, Sun C, Sun X, Sun Y, Sun Y, Surrow B, Svirida DN, Sweger ZW, Tamis A, Tang AH, Tang Z, Taranenko A, Tarnowsky T, Thomas JH, Tlusty D, Todoroki T, Tokarev MV, Tomkiel CA, Trentalange S, Tribble RE, Tribedy P, Tsai OD, Tsang CY, Tu Z, Ullrich T, Underwood DG, Upsal I, Van Buren G, Vasiliev AN, Verkest V, Videbæk F, Vokal S, Voloshin SA, Wang F, Wang G, Wang JS, Wang X, Wang Y, Wang Y, Wang Y, Wang Z, Webb JC, Weidenkaff PC, Westfall GD, Wieman H, Wilks G, Wissink SW, Wu J, Wu J, Wu X, Wu Y, Xi B, Xiao ZG, Xie G, Xie W, Xu H, Xu N, Xu QH, Xu Y, Xu Y, Xu Z, Xu Z, Yan G, Yan Z, Yang C, Yang Q, Yang S, Yang Y, Ye Z, Ye Z, Yi L, Yip K, Yu N, Yu Y, Zha W, Zhang C, Zhang D, Zhang J, Zhang S, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang ZJ, Zhang Z, Zhang Z, Zhao F, Zhao J, Zhao M, Zhou C, Zhou J, Zhou S, Zhou Y, Zhu X, Zurek M, Zyzak M. Beam Energy Dependence of Triton Production and Yield Ratio (N_{t}×N_{p}/N_{d}^{2}) in Au+Au Collisions at RHIC. Phys Rev Lett 2023; 130:202301. [PMID: 37267557 DOI: 10.1103/physrevlett.130.202301] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 02/21/2023] [Accepted: 03/30/2023] [Indexed: 06/04/2023]
Abstract
We report the triton (t) production in midrapidity (|y|<0.5) Au+Au collisions at sqrt[s_{NN}]=7.7-200 GeV measured by the STAR experiment from the first phase of the beam energy scan at the Relativistic Heavy Ion Collider. The nuclear compound yield ratio (N_{t}×N_{p}/N_{d}^{2}), which is predicted to be sensitive to the fluctuation of local neutron density, is observed to decrease monotonically with increasing charged-particle multiplicity (dN_{ch}/dη) and follows a scaling behavior. The dN_{ch}/dη dependence of the yield ratio is compared to calculations from coalescence and thermal models. Enhancements in the yield ratios relative to the coalescence baseline are observed in the 0%-10% most central collisions at 19.6 and 27 GeV, with a significance of 2.3σ and 3.4σ, respectively, giving a combined significance of 4.1σ. The enhancements are not observed in peripheral collisions or model calculations without critical fluctuation, and decreases with a smaller p_{T} acceptance. The physics implications of these results on the QCD phase structure and the production mechanism of light nuclei in heavy-ion collisions are discussed.
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Affiliation(s)
- M I Abdulhamid
- American University of Cairo, New Cairo 11835, New Cairo, Egypt
| | - B E Aboona
- Texas A&M University, College Station, Texas 77843
| | - J Adam
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - J R Adams
- The Ohio State University, Columbus, Ohio 43210
| | - G Agakishiev
- Joint Institute for Nuclear Research, Dubna 141 980
| | - I Aggarwal
- Panjab University, Chandigarh 160014, India
| | | | - Z Ahammed
- Variable Energy Cyclotron Centre, Kolkata 700064, India
| | - A Aitbaev
- Joint Institute for Nuclear Research, Dubna 141 980
| | - I Alekseev
- Alikhanov Institute for Theoretical and Experimental Physics NRC "Kurchatov Institute," Moscow 117218
- National Research Nuclear University MEPhI, Moscow 115409
| | - D M Anderson
- Texas A&M University, College Station, Texas 77843
| | - A Aparin
- Joint Institute for Nuclear Research, Dubna 141 980
| | - S Aslam
- Indian Institute Technology, Patna, Bihar 801106, India
| | - J Atchison
- Abilene Christian University, Abilene, Texas 79699
| | | | - V Bairathi
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica 1000000, Chile
| | - W Baker
- University of California, Riverside, California 92521
| | | | - K Barish
- University of California, Riverside, California 92521
| | - P Bhagat
- University of Jammu, Jammu 180001, India
| | - A Bhasin
- University of Jammu, Jammu 180001, India
| | - S Bhatta
- State University of New York, Stony Brook, New York 11794
| | - I G Bordyuzhin
- Alikhanov Institute for Theoretical and Experimental Physics NRC "Kurchatov Institute," Moscow 117218
| | | | - A V Brandin
- National Research Nuclear University MEPhI, Moscow 115409
| | - X Z Cai
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - H Caines
- Yale University, New Haven, Connecticut 06520
| | | | - D Cebra
- University of California, Davis, California 95616
| | - J Ceska
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - I Chakaberia
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - B K Chan
- University of California, Los Angeles, California 90095
| | - Z Chang
- Indiana University, Bloomington, Indiana 47408
| | - A Chatterjee
- National Institute of Technology Durgapur, Durgapur - 713209, India
| | - D Chen
- University of California, Riverside, California 92521
| | - J Chen
- Shandong University, Qingdao, Shandong 266237
| | - J H Chen
- Fudan University, Shanghai, 200433
| | - Z Chen
- Shandong University, Qingdao, Shandong 266237
| | - J Cheng
- Tsinghua University, Beijing 100084
| | - Y Cheng
- University of California, Los Angeles, California 90095
| | | | - W Christie
- Brookhaven National Laboratory, Upton, New York 11973
| | - X Chu
- Brookhaven National Laboratory, Upton, New York 11973
| | - H J Crawford
- University of California, Berkeley, California 94720
| | - G Dale-Gau
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - A Das
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - M Daugherity
- Abilene Christian University, Abilene, Texas 79699
| | - T G Dedovich
- Joint Institute for Nuclear Research, Dubna 141 980
| | - I M Deppner
- University of Heidelberg, Heidelberg 69120, Germany
| | - A A Derevschikov
- NRC "Kurchatov Institute," Institute of High Energy Physics, Protvino 142281
| | - A Dhamija
- Panjab University, Chandigarh 160014, India
| | - L Di Carlo
- Wayne State University, Detroit, Michigan 48201
| | - L Didenko
- Brookhaven National Laboratory, Upton, New York 11973
| | - P Dixit
- Indian Institute of Science Education and Research (IISER), Berhampur 760010, India
| | - X Dong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | | | | | - J C Dunlop
- Brookhaven National Laboratory, Upton, New York 11973
| | - J Engelage
- University of California, Berkeley, California 94720
| | - G Eppley
- Rice University, Houston, Texas 77251
| | - S Esumi
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - O Evdokimov
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - A Ewigleben
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - O Eyser
- Brookhaven National Laboratory, Upton, New York 11973
| | - R Fatemi
- University of Kentucky, Lexington, Kentucky 40506-0055
| | - S Fazio
- University of Calabria & INFN-Cosenza, Rende 87036, Italy
| | - C J Feng
- National Cheng Kung University, Tainan 70101
| | - Y Feng
- Purdue University, West Lafayette, Indiana 47907
| | - E Finch
- Southern Connecticut State University, New Haven, Connecticut 06515
| | - Y Fisyak
- Brookhaven National Laboratory, Upton, New York 11973
| | - F A Flor
- Yale University, New Haven, Connecticut 06520
| | - C Fu
- Central China Normal University, Wuhan, Hubei 430079
| | - F Geurts
- Rice University, Houston, Texas 77251
| | - N Ghimire
- Temple University, Philadelphia, Pennsylvania 19122
| | - A Gibson
- Valparaiso University, Valparaiso, Indiana 46383
| | - K Gopal
- Indian Institute of Science Education and Research (IISER) Tirupati, Tirupati 517507, India
| | - X Gou
- Shandong University, Qingdao, Shandong 266237
| | - D Grosnick
- Valparaiso University, Valparaiso, Indiana 46383
| | - A Gupta
- University of Jammu, Jammu 180001, India
| | - A Hamed
- American University of Cairo, New Cairo 11835, New Cairo, Egypt
| | - Y Han
- Rice University, Houston, Texas 77251
| | - M D Harasty
- University of California, Davis, California 95616
| | - J W Harris
- Yale University, New Haven, Connecticut 06520
| | | | - W He
- Fudan University, Shanghai, 200433
| | - X H He
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - Y He
- Shandong University, Qingdao, Shandong 266237
| | - C Hu
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - Q Hu
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - Y Hu
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - H Huang
- National Cheng Kung University, Tainan 70101
| | - H Z Huang
- University of California, Los Angeles, California 90095
| | - S L Huang
- State University of New York, Stony Brook, New York 11794
| | - T Huang
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - X Huang
- Tsinghua University, Beijing 100084
| | - Y Huang
- Tsinghua University, Beijing 100084
| | - Y Huang
- Central China Normal University, Wuhan, Hubei 430079
| | - T J Humanic
- The Ohio State University, Columbus, Ohio 43210
| | - D Isenhower
- Abilene Christian University, Abilene, Texas 79699
| | - M Isshiki
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - W W Jacobs
- Indiana University, Bloomington, Indiana 47408
| | - A Jalotra
- University of Jammu, Jammu 180001, India
| | - C Jena
- Indian Institute of Science Education and Research (IISER) Tirupati, Tirupati 517507, India
| | - Y Ji
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J Jia
- Brookhaven National Laboratory, Upton, New York 11973
- State University of New York, Stony Brook, New York 11794
| | - C Jin
- Rice University, Houston, Texas 77251
| | - X Ju
- University of Science and Technology of China, Hefei, Anhui 230026
| | - E G Judd
- University of California, Berkeley, California 94720
| | - S Kabana
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica 1000000, Chile
| | - M L Kabir
- University of California, Riverside, California 92521
| | - D Kalinkin
- University of Kentucky, Lexington, Kentucky 40506-0055
| | - K Kang
- Tsinghua University, Beijing 100084
| | - D Kapukchyan
- University of California, Riverside, California 92521
| | - K Kauder
- Brookhaven National Laboratory, Upton, New York 11973
| | - H W Ke
- Brookhaven National Laboratory, Upton, New York 11973
| | - D Keane
- Kent State University, Kent, Ohio 44242
| | - A Kechechyan
- Joint Institute for Nuclear Research, Dubna 141 980
| | - M Kelsey
- Wayne State University, Detroit, Michigan 48201
| | - B Kimelman
- University of California, Davis, California 95616
| | - A Kiselev
- Brookhaven National Laboratory, Upton, New York 11973
| | - A G Knospe
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - H S Ko
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - L Kochenda
- National Research Nuclear University MEPhI, Moscow 115409
| | | | - P Kravtsov
- National Research Nuclear University MEPhI, Moscow 115409
| | - L Kumar
- Panjab University, Chandigarh 160014, India
| | - S Kumar
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | | | - R Lacey
- State University of New York, Stony Brook, New York 11794
| | - J M Landgraf
- Brookhaven National Laboratory, Upton, New York 11973
| | - A Lebedev
- Brookhaven National Laboratory, Upton, New York 11973
| | - R Lednicky
- Joint Institute for Nuclear Research, Dubna 141 980
| | - J H Lee
- Brookhaven National Laboratory, Upton, New York 11973
| | - Y H Leung
- University of Heidelberg, Heidelberg 69120, Germany
| | - N Lewis
- Brookhaven National Laboratory, Upton, New York 11973
| | - C Li
- Shandong University, Qingdao, Shandong 266237
| | - W Li
- Rice University, Houston, Texas 77251
| | - X Li
- University of Science and Technology of China, Hefei, Anhui 230026
| | - Y Li
- University of Science and Technology of China, Hefei, Anhui 230026
| | - Y Li
- Tsinghua University, Beijing 100084
| | - Z Li
- University of Science and Technology of China, Hefei, Anhui 230026
| | - X Liang
- University of California, Riverside, California 92521
| | - Y Liang
- Kent State University, Kent, Ohio 44242
| | - T Lin
- Shandong University, Qingdao, Shandong 266237
| | - C Liu
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - F Liu
- Central China Normal University, Wuhan, Hubei 430079
| | - H Liu
- Indiana University, Bloomington, Indiana 47408
| | - H Liu
- Central China Normal University, Wuhan, Hubei 430079
| | - L Liu
- Central China Normal University, Wuhan, Hubei 430079
| | - T Liu
- Yale University, New Haven, Connecticut 06520
| | - X Liu
- The Ohio State University, Columbus, Ohio 43210
| | - Y Liu
- Texas A&M University, College Station, Texas 77843
| | - Z Liu
- Central China Normal University, Wuhan, Hubei 430079
| | - T Ljubicic
- Brookhaven National Laboratory, Upton, New York 11973
| | - W J Llope
- Wayne State University, Detroit, Michigan 48201
| | - O Lomicky
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - R S Longacre
- Brookhaven National Laboratory, Upton, New York 11973
| | - E M Loyd
- University of California, Riverside, California 92521
| | - T Lu
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - N S Lukow
- Temple University, Philadelphia, Pennsylvania 19122
| | - X F Luo
- Central China Normal University, Wuhan, Hubei 430079
| | - V B Luong
- Joint Institute for Nuclear Research, Dubna 141 980
| | - L Ma
- Fudan University, Shanghai, 200433
| | - R Ma
- Brookhaven National Laboratory, Upton, New York 11973
| | - Y G Ma
- Fudan University, Shanghai, 200433
| | - N Magdy
- State University of New York, Stony Brook, New York 11794
| | - D Mallick
- National Institute of Science Education and Research, HBNI, Jatni 752050, India
| | | | - H S Matis
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J A Mazer
- Rutgers University, Piscataway, New Jersey 08854
| | - G McNamara
- Wayne State University, Detroit, Michigan 48201
| | - K Mi
- Central China Normal University, Wuhan, Hubei 430079
| | - N G Minaev
- NRC "Kurchatov Institute," Institute of High Energy Physics, Protvino 142281
| | - B Mohanty
- National Institute of Science Education and Research, HBNI, Jatni 752050, India
| | - M M Mondal
- National Institute of Science Education and Research, HBNI, Jatni 752050, India
| | - I Mooney
- Yale University, New Haven, Connecticut 06520
| | - D A Morozov
- NRC "Kurchatov Institute," Institute of High Energy Physics, Protvino 142281
| | - A Mudrokh
- Joint Institute for Nuclear Research, Dubna 141 980
| | - M I Nagy
- ELTE Eötvös Loránd University, Budapest, Hungary H-1117
| | - A S Nain
- Panjab University, Chandigarh 160014, India
| | - J D Nam
- Temple University, Philadelphia, Pennsylvania 19122
| | - Md Nasim
- Indian Institute of Science Education and Research (IISER), Berhampur 760010, India
| | - D Neff
- University of California, Los Angeles, California 90095
| | - J M Nelson
- University of California, Berkeley, California 94720
| | - D B Nemes
- Yale University, New Haven, Connecticut 06520
| | - M Nie
- Shandong University, Qingdao, Shandong 266237
| | - G Nigmatkulov
- National Research Nuclear University MEPhI, Moscow 115409
| | - T Niida
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - R Nishitani
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - L V Nogach
- NRC "Kurchatov Institute," Institute of High Energy Physics, Protvino 142281
| | - T Nonaka
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - G Odyniec
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - A Ogawa
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Oh
- Sejong University, Seoul, 05006, South Korea
| | - V A Okorokov
- National Research Nuclear University MEPhI, Moscow 115409
| | - K Okubo
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - B S Page
- Brookhaven National Laboratory, Upton, New York 11973
| | - R Pak
- Brookhaven National Laboratory, Upton, New York 11973
| | - J Pan
- Texas A&M University, College Station, Texas 77843
| | - A Pandav
- National Institute of Science Education and Research, HBNI, Jatni 752050, India
| | - A K Pandey
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | | | - T Pani
- Rutgers University, Piscataway, New Jersey 08854
| | - P Parfenov
- National Research Nuclear University MEPhI, Moscow 115409
| | - A Paul
- University of California, Riverside, California 92521
| | - C Perkins
- University of California, Berkeley, California 94720
| | - B R Pokhrel
- Temple University, Philadelphia, Pennsylvania 19122
| | - M Posik
- Temple University, Philadelphia, Pennsylvania 19122
| | - T Protzman
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - N K Pruthi
- Panjab University, Chandigarh 160014, India
| | - J Putschke
- Wayne State University, Detroit, Michigan 48201
| | - Z Qin
- Tsinghua University, Beijing 100084
| | - H Qiu
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - A Quintero
- Temple University, Philadelphia, Pennsylvania 19122
| | - C Racz
- University of California, Riverside, California 92521
| | | | - N Raha
- Wayne State University, Detroit, Michigan 48201
| | - R L Ray
- University of Texas, Austin, Texas 78712
| | - H G Ritter
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | | | | | | | - D Roy
- Rutgers University, Piscataway, New Jersey 08854
| | - L Ruan
- Brookhaven National Laboratory, Upton, New York 11973
| | - A K Sahoo
- Indian Institute of Science Education and Research (IISER), Berhampur 760010, India
| | - N R Sahoo
- Shandong University, Qingdao, Shandong 266237
| | - H Sako
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - S Salur
- Rutgers University, Piscataway, New Jersey 08854
| | - E Samigullin
- Alikhanov Institute for Theoretical and Experimental Physics NRC "Kurchatov Institute," Moscow 117218
| | - S Sato
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - W B Schmidke
- Brookhaven National Laboratory, Upton, New York 11973
| | - N Schmitz
- Max-Planck-Institut für Physik, Munich 80805, Germany
| | - J Seger
- Creighton University, Omaha, Nebraska 68178
| | - R Seto
- University of California, Riverside, California 92521
| | - P Seyboth
- Max-Planck-Institut für Physik, Munich 80805, Germany
| | - N Shah
- Indian Institute Technology, Patna, Bihar 801106, India
| | - E Shahaliev
- Joint Institute for Nuclear Research, Dubna 141 980
| | | | - T Shao
- Fudan University, Shanghai, 200433
| | - M Sharma
- University of Jammu, Jammu 180001, India
| | - N Sharma
- Indian Institute of Science Education and Research (IISER), Berhampur 760010, India
| | - R Sharma
- Indian Institute of Science Education and Research (IISER) Tirupati, Tirupati 517507, India
| | - S R Sharma
- Indian Institute of Science Education and Research (IISER) Tirupati, Tirupati 517507, India
| | | | - D Y Shen
- Fudan University, Shanghai, 200433
| | - K Shen
- University of Science and Technology of China, Hefei, Anhui 230026
| | - S S Shi
- Central China Normal University, Wuhan, Hubei 430079
| | - Y Shi
- Shandong University, Qingdao, Shandong 266237
| | - Q Y Shou
- Fudan University, Shanghai, 200433
| | - F Si
- University of Science and Technology of China, Hefei, Anhui 230026
| | - J Singh
- Panjab University, Chandigarh 160014, India
| | - S Singha
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - P Sinha
- Indian Institute of Science Education and Research (IISER) Tirupati, Tirupati 517507, India
| | - M J Skoby
- Ball State University, Muncie, Indiana, 47306
- Purdue University, West Lafayette, Indiana 47907
| | - Y Söhngen
- University of Heidelberg, Heidelberg 69120, Germany
| | - Y Song
- Yale University, New Haven, Connecticut 06520
| | - B Srivastava
- Purdue University, West Lafayette, Indiana 47907
| | | | - D J Stewart
- Wayne State University, Detroit, Michigan 48201
| | - M Strikhanov
- National Research Nuclear University MEPhI, Moscow 115409
| | | | - Y Su
- University of Science and Technology of China, Hefei, Anhui 230026
| | - C Sun
- State University of New York, Stony Brook, New York 11794
| | - X Sun
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - Y Sun
- University of Science and Technology of China, Hefei, Anhui 230026
| | - Y Sun
- Huzhou University, Huzhou, Zhejiang 313000
| | - B Surrow
- Temple University, Philadelphia, Pennsylvania 19122
| | - D N Svirida
- Alikhanov Institute for Theoretical and Experimental Physics NRC "Kurchatov Institute," Moscow 117218
| | - Z W Sweger
- University of California, Davis, California 95616
| | - A Tamis
- Yale University, New Haven, Connecticut 06520
| | - A H Tang
- Brookhaven National Laboratory, Upton, New York 11973
| | - Z Tang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - A Taranenko
- National Research Nuclear University MEPhI, Moscow 115409
| | - T Tarnowsky
- Michigan State University, East Lansing, Michigan 48824
| | - J H Thomas
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - D Tlusty
- Creighton University, Omaha, Nebraska 68178
| | - T Todoroki
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - M V Tokarev
- Joint Institute for Nuclear Research, Dubna 141 980
| | - C A Tomkiel
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - S Trentalange
- University of California, Los Angeles, California 90095
| | - R E Tribble
- Texas A&M University, College Station, Texas 77843
| | - P Tribedy
- Brookhaven National Laboratory, Upton, New York 11973
| | - O D Tsai
- Brookhaven National Laboratory, Upton, New York 11973
- University of California, Los Angeles, California 90095
| | - C Y Tsang
- Brookhaven National Laboratory, Upton, New York 11973
- Kent State University, Kent, Ohio 44242
| | - Z Tu
- Brookhaven National Laboratory, Upton, New York 11973
| | - T Ullrich
- Brookhaven National Laboratory, Upton, New York 11973
| | - D G Underwood
- Argonne National Laboratory, Argonne, Illinois 60439
- Valparaiso University, Valparaiso, Indiana 46383
| | - I Upsal
- Rice University, Houston, Texas 77251
| | - G Van Buren
- Brookhaven National Laboratory, Upton, New York 11973
| | - A N Vasiliev
- National Research Nuclear University MEPhI, Moscow 115409
- NRC "Kurchatov Institute," Institute of High Energy Physics, Protvino 142281
| | - V Verkest
- Wayne State University, Detroit, Michigan 48201
| | - F Videbæk
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Vokal
- Joint Institute for Nuclear Research, Dubna 141 980
| | | | - F Wang
- Purdue University, West Lafayette, Indiana 47907
| | - G Wang
- University of California, Los Angeles, California 90095
| | - J S Wang
- Huzhou University, Huzhou, Zhejiang 313000
| | - X Wang
- Shandong University, Qingdao, Shandong 266237
| | - Y Wang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - Y Wang
- Central China Normal University, Wuhan, Hubei 430079
| | - Y Wang
- Tsinghua University, Beijing 100084
| | - Z Wang
- Shandong University, Qingdao, Shandong 266237
| | - J C Webb
- Brookhaven National Laboratory, Upton, New York 11973
| | | | - G D Westfall
- Michigan State University, East Lansing, Michigan 48824
| | - H Wieman
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - G Wilks
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - S W Wissink
- Indiana University, Bloomington, Indiana 47408
| | - J Wu
- Central China Normal University, Wuhan, Hubei 430079
| | - J Wu
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - X Wu
- University of California, Los Angeles, California 90095
| | - Y Wu
- University of California, Riverside, California 92521
| | - B Xi
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - Z G Xiao
- Tsinghua University, Beijing 100084
| | - G Xie
- University of Chinese Academy of Sciences, Beijing, 101408
| | - W Xie
- Purdue University, West Lafayette, Indiana 47907
| | - H Xu
- Huzhou University, Huzhou, Zhejiang 313000
| | - N Xu
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - Q H Xu
- Shandong University, Qingdao, Shandong 266237
| | - Y Xu
- Shandong University, Qingdao, Shandong 266237
| | - Y Xu
- Central China Normal University, Wuhan, Hubei 430079
| | - Z Xu
- Brookhaven National Laboratory, Upton, New York 11973
| | - Z Xu
- University of California, Los Angeles, California 90095
| | - G Yan
- Shandong University, Qingdao, Shandong 266237
| | - Z Yan
- State University of New York, Stony Brook, New York 11794
| | - C Yang
- Shandong University, Qingdao, Shandong 266237
| | - Q Yang
- Shandong University, Qingdao, Shandong 266237
| | - S Yang
- South China Normal University, Guangzhou, Guangdong 510631
| | - Y Yang
- National Cheng Kung University, Tainan 70101
| | - Z Ye
- Rice University, Houston, Texas 77251
| | - Z Ye
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - L Yi
- Shandong University, Qingdao, Shandong 266237
| | - K Yip
- Brookhaven National Laboratory, Upton, New York 11973
| | - N Yu
- Central China Normal University, Wuhan, Hubei 430079
| | - Y Yu
- Shandong University, Qingdao, Shandong 266237
| | - W Zha
- University of Science and Technology of China, Hefei, Anhui 230026
| | - C Zhang
- State University of New York, Stony Brook, New York 11794
| | - D Zhang
- Central China Normal University, Wuhan, Hubei 430079
| | - J Zhang
- Shandong University, Qingdao, Shandong 266237
| | - S Zhang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - X Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - Y Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - Y Zhang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - Y Zhang
- Central China Normal University, Wuhan, Hubei 430079
| | - Z J Zhang
- National Cheng Kung University, Tainan 70101
| | - Z Zhang
- Brookhaven National Laboratory, Upton, New York 11973
| | - Z Zhang
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - F Zhao
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - J Zhao
- Fudan University, Shanghai, 200433
| | - M Zhao
- Brookhaven National Laboratory, Upton, New York 11973
| | - C Zhou
- Fudan University, Shanghai, 200433
| | - J Zhou
- University of Science and Technology of China, Hefei, Anhui 230026
| | - S Zhou
- Central China Normal University, Wuhan, Hubei 430079
| | - Y Zhou
- Central China Normal University, Wuhan, Hubei 430079
| | - X Zhu
- Tsinghua University, Beijing 100084
| | - M Zurek
- Argonne National Laboratory, Argonne, Illinois 60439
- Brookhaven National Laboratory, Upton, New York 11973
| | - M Zyzak
- Frankfurt Institute for Advanced Studies FIAS, Frankfurt 60438, Germany
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9
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Huang H, Overvig AC, Xu Y, Malek SC, Tsai CC, Alù A, Yu N. Leaky-wave metasurfaces for integrated photonics. Nat Nanotechnol 2023:10.1038/s41565-023-01360-z. [PMID: 37157023 DOI: 10.1038/s41565-023-01360-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 02/22/2023] [Indexed: 05/10/2023]
Abstract
Metasurfaces have been rapidly advancing our command over the many degrees of freedom of light; however, so far, they have been mostly limited to manipulating light in free space. Metasurfaces integrated on top of guided-wave photonic systems have been explored to control the scattering of light off-chip with enhanced functionalities-namely, the point-by-point manipulation of amplitude, phase or polarization. However, these efforts have so far been limited to controlling one or two optical degrees of freedom at best, as well as device configurations much more complex compared with conventional grating couplers. Here we introduce leaky-wave metasurfaces, which are based on symmetry-broken photonic crystal slabs that support quasi-bound states in the continuum. This platform has a compact form factor equivalent to the one of grating couplers, but it provides full command over the amplitude, phase and polarization (four optical degrees of freedom) across large apertures. We present devices for phase and amplitude control at a fixed polarization state, and devices controlling all the four optical degrees of freedom for operation at a wavelength of 1.55 μm. Merging the fields of guided and free-space optics through the hybrid nature of quasi-bound states in the continuum, our leaky-wave metasurfaces may find applications in imaging, communications, augmented reality, quantum optics, LIDAR and integrated photonic systems.
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Affiliation(s)
- Heqing Huang
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
| | - Adam C Overvig
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
- Photonics Initiative, Advanced Science Research Center, City University of New York, New York, NY, USA
| | - Yuan Xu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
| | - Stephanie C Malek
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
| | - Cheng-Chia Tsai
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
| | - Andrea Alù
- Photonics Initiative, Advanced Science Research Center, City University of New York, New York, NY, USA.
- Physics Program, Graduate Center of the City University of New York, New York, NY, USA.
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA.
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10
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Childers RAR, Bernard GD, Huang H, Tsai CC, Stoddard MC, Hogan BG, Greenwood JSF, Soucy ER, Cornwall M, Lim MLM, Liénard MA, Yu N, Pierce NE. A hypothesis for robust polarization vision: An example from the Australian Imperial Blue butterfly, Jalmenus evagoras. J Exp Biol 2023; 226:297475. [PMID: 36967715 PMCID: PMC10120070 DOI: 10.1242/jeb.244515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 03/08/2023] [Indexed: 03/29/2023]
Abstract
The Australian lycaenid butterfly, Jalmenus evagoras, has iridescent wings that are sexually dimorphic, spectrally and in their degree of polarization, suggesting that these properties are likely to be important in mate recognition. We first describe the results of a field experiment showing that free-flying individuals of J. evagoras discriminate between visual stimuli that vary in polarization content in blue wavelengths but not in others. We then present detailed reflectance spectrophotometry measurements of the polarization content of male and female wings, showing that female wings exhibit blue-shifted reflectance, with a lower degree of polarization relative to male wings. Finally, we describe a novel method for measuring alignment of ommatidial arrays: By measuring variation of depolarized eyeshine intensity from patches of ommatidia as a function of eye rotation, we show that a) individual rhabdoms contain mutually perpendicular microvilli; b) many rhabdoms in the array have their microvilli misaligned with respect to neighboring rhabdoms by as much as 45°; c) the misaligned ommatidia are useful for robust polarization detection. By mapping the distribution of the ommatidial misalignments in eye patches of J. evagoras, we show that males and females exhibit differences in the extent to which ommatidia are aligned. Both the number of misaligned ommatidia suitable for robust polarization-detection, and the number of aligned ommatidia suitable for edge-detection, vary with respect to both sex and eye-patch elevation. Thus, J. evagoras exhibits finely-tuned ommatidial arrays suitable for perception of polarized signals, likely to match sex-specific life history differences in the utility of polarized signals.
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Affiliation(s)
- Richard A. Rabideau Childers
- Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
- Authors for correspondence (; ; )
| | - Gary D. Bernard
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA 98195, USA
- Authors for correspondence (; ; )
| | - Heqing Huang
- Department of Applied Physics & Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Cheng-Chia Tsai
- Department of Applied Physics & Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Mary Caswell Stoddard
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Benedict G. Hogan
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Joel S. F. Greenwood
- Center for Brain Science, Harvard University, 52 Oxford St - room 331, Cambridge, MA 02138, USA
- Neurotechnology Core, Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Edward R. Soucy
- Center for Brain Science, Harvard University, 52 Oxford St - room 331, Cambridge, MA 02138, USA
| | - Mark Cornwall
- Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
| | - Matthew Lek Min Lim
- Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
- Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, Singapore117558
| | - Marjorie A. Liénard
- Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Biology, Lund University, 22362 Lund, Sweden
| | - Nanfang Yu
- Department of Applied Physics & Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Naomi E. Pierce
- Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
- Authors for correspondence (; ; )
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11
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Zhang J, Sun L, Withanage M, Ganesan S, Williamson M, Marchesan J, Jiao Y, Teles F, Yu N, Liu Y, Wu D, Moss K, Mangalam A, Zeng E, Lei Y, Zhang S. TRAF3IP2-IL-17 Axis Strengthens the Gingival Defense against Pathogens. J Dent Res 2023; 102:103-115. [PMID: 36281065 PMCID: PMC9780753 DOI: 10.1177/00220345221123256] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Recent genome-wide association studies have suggested novel risk loci associated with periodontitis, which is initiated by dysbiosis in subgingival plaque and leads to destruction of teeth-supporting structures. One such genetic locus was the tumor necrosis factor receptor-associated factor 3 interacting protein 2 (TRAF3IP2), a gene encoding the gate-keeping interleukin (IL)-17 receptor adaptor. In this study, we first determined that carriers of the lead exonic variant rs13190932 within the TRAF3IP2 locus combined with a high plaque microbial burden was associated with more severe periodontitis than noncarriers. We then demonstrated that TRAF3IP2 is essential in the IL-17-mediated CCL2 and IL-8 chemokine production in primary gingival epithelial cells. Further analysis suggested that rs13190932 may serve a surrogate variant for a genuine loss-of-function variant rs33980500 within the same gene. Traf3ip2 null mice (Traf3ip2-/-) were more susceptible than wild-type (WT) mice to the Porphyromonas gingivalis-induced periodontal alveolar bone loss. Such bone loss was associated with a delayed P. gingivalis clearance and an attenuated neutrophil recruitment in the gingiva of Traf3ip2-/- mice. Transcriptomic data showed decreased expression of antimicrobial genes, including Lcn2, S100a8, and Defb1, in the Traf3ip2-/- mouse gingiva in comparison to WT mice prior to or upon P. gingivalis oral challenge. Further 16S ribosomal RNA sequencing analysis identified a distinct microbial community in the Traf3ip2-/- mouse oral plaque, which was featured by a reduced microbial diversity and an overabundance of Streptococcus genus bacteria. More P. gingivalis was observed in the Traf3ip2-/- mouse gingiva than WT control animals in a ligature-promoted P. gingivalis invasion model. In agreement, neutrophil depletion resulted in more local gingival tissue invasion by P. gingivalis. Thus, we identified a homeostatic IL-17-TRAF3IP2-neutrophil axis underpinning host defense against a keystone periodontal pathogen.
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Affiliation(s)
- J. Zhang
- Iowa Institute of Oral Health Research, University of Iowa College of Dentistry, Iowa City, IA, USA,Periodontics, University of Iowa College of Dentistry, Iowa City, IA, USA,S. Zhang, Iowa Institute of Oral Health Research, Periodontics Department, University of Iowa College of Dentistry, Room 401 Dental Science Building, 801 Newton Road, Iowa City, IA 52242, USA.
| | - L. Sun
- Department of Microbiology & Immunology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - M.H.H. Withanage
- Division of Biostatistics and Computational Biology, University of Iowa College of Dentistry, Iowa City, IA, USA
| | - S.M. Ganesan
- Iowa Institute of Oral Health Research, University of Iowa College of Dentistry, Iowa City, IA, USA,Periodontics, University of Iowa College of Dentistry, Iowa City, IA, USA
| | - M.A. Williamson
- Iowa Institute of Oral Health Research, University of Iowa College of Dentistry, Iowa City, IA, USA,Periodontics, University of Iowa College of Dentistry, Iowa City, IA, USA
| | - J.T. Marchesan
- Department of Periodontology, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Y. Jiao
- Department of Periodontology, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - F.R. Teles
- Department of Basic & Translational Sciences, University of Pennsylvania School of Dental Medicine, Philadelphia, PA, USA
| | - N. Yu
- The Forsyth Institute, Cambridge, MA, USA
| | - Y. Liu
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - D. Wu
- Department of Periodontology, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - K.L. Moss
- Department of Periodontology, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - A.K. Mangalam
- Department of Pathology, University of Iowa College of Medicine, Iowa City, IA, USA
| | - E. Zeng
- Division of Biostatistics and Computational Biology, University of Iowa College of Dentistry, Iowa City, IA, USA
| | - Y.L. Lei
- Department of Periodontics & Oral Medicine, University of Michigan School of Dentistry, Ann Harbor, MI, USA
| | - S. Zhang
- Iowa Institute of Oral Health Research, University of Iowa College of Dentistry, Iowa City, IA, USA,Periodontics, University of Iowa College of Dentistry, Iowa City, IA, USA
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12
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Chan WP, Rabideau Childers R, Ashe S, Tsai CC, Elson C, Keleher KJ, Sipe RLH, Maier CA, Sourakov A, Gall LF, Bernard GD, Soucy ER, Yu N, Pierce NE. A high-throughput multispectral imaging system for museum specimens. Commun Biol 2022; 5:1318. [PMID: 36456867 PMCID: PMC9715708 DOI: 10.1038/s42003-022-04282-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 11/18/2022] [Indexed: 12/05/2022] Open
Abstract
We present an economical imaging system with integrated hardware and software to capture multispectral images of Lepidoptera with high efficiency. This method facilitates the comparison of colors and shapes among species at fine and broad taxonomic scales and may be adapted for other insect orders with greater three-dimensionality. Our system can image both the dorsal and ventral sides of pinned specimens. Together with our processing pipeline, the descriptive data can be used to systematically investigate multispectral colors and shapes based on full-wing reconstruction and a universally applicable ground plan that objectively quantifies wing patterns for species with different wing shapes (including tails) and venation systems. Basic morphological measurements, such as body length, thorax width, and antenna size are automatically generated. This system can increase exponentially the amount and quality of trait data extracted from museum specimens.
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Affiliation(s)
- Wei-Ping Chan
- grid.38142.3c000000041936754XDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA ,grid.38142.3c000000041936754XMuseum of Comparative Zoology, Harvard University, Cambridge, MA USA
| | - Richard Rabideau Childers
- grid.38142.3c000000041936754XDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA ,grid.38142.3c000000041936754XMuseum of Comparative Zoology, Harvard University, Cambridge, MA USA
| | - Sorcha Ashe
- grid.38142.3c000000041936754XDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA
| | - Cheng-Chia Tsai
- grid.21729.3f0000000419368729Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY USA
| | - Caroline Elson
- grid.38142.3c000000041936754XDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA
| | - Kirsten J. Keleher
- grid.40803.3f0000 0001 2173 6074Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC USA ,grid.5386.8000000041936877XDepartment of Neurobiology and Behavior, Cornell University, Ithaca, NY USA
| | - Rachel L. Hawkins Sipe
- grid.38142.3c000000041936754XMuseum of Comparative Zoology, Harvard University, Cambridge, MA USA
| | - Crystal A. Maier
- grid.38142.3c000000041936754XMuseum of Comparative Zoology, Harvard University, Cambridge, MA USA
| | - Andrei Sourakov
- grid.15276.370000 0004 1936 8091McGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, Gainesville, FL USA
| | - Lawrence F. Gall
- grid.47100.320000000419368710Computer Systems Office & Division of Entomology, Peabody Museum of Natural History, Yale University, New Haven, CT USA
| | - Gary D. Bernard
- grid.34477.330000000122986657Department of Electrical and Computer Engineering, University of Washington, Seattle, WA USA
| | - Edward R. Soucy
- grid.38142.3c000000041936754XCenter for Brain Science, Harvard University, Cambridge, MA USA
| | - Nanfang Yu
- grid.21729.3f0000000419368729Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY USA
| | - Naomi E. Pierce
- grid.38142.3c000000041936754XDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA USA ,grid.38142.3c000000041936754XMuseum of Comparative Zoology, Harvard University, Cambridge, MA USA
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13
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Yu N, Wan Y, Zuo L, Cao Y, Qu D, Liu W, Deng L, Zhang T, Wang W, Wang J, Feng Q, Zhou Z, Xiao Z, BI N, Niu T, Wang X. MRI and CT Radiomics Features to Predict Overall Survival of Locally Advanced Esophageal Cancer after Definite Chemoradiotherapy. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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14
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Deng XQ, Zhang M, Zhang X, Zhao ZP, Li C, Huang ZJ, Song ZW, Jiang B, Guo XH, Yu N, Wang LM. [Blood glucose levels and the relationship of body mass index and circumference with blood glucose in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1178-1188. [PMID: 35981978 DOI: 10.3760/cma.j.cn112338-20211011-00782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To describe and compare blood glucose levels in adults aged 18 years old and above in China and explore the relationship between BMI and waist circumference with blood glucose. Methods: China Chronic Disease and Risk Factor Surveillance were conducted in 298 counties/districts in China in 2018, covering 31 provinces (autonomous regions, municipalities). A multi-stage stratified cluster random sampling method selected permanent residents aged 18 years and above. Information on demographics, behavior-related risk factors, BMI, waist circumference, and blood glucose were collected through a face-to-face questionnaire, physical measurement, and laboratory examination. After complex weighting of data, they described the blood glucose levels of people with different characteristics and explored the relationship of BMI and waist circumference with blood glucose by multiple linear regression model analysis. Results: A total of 177 816 adults were included in the study. The average fasting blood glucose and average glycosylated hemoglobin were (5.73±1.46) mmol/L and (5.37±0.83) %, with people aged 60 years old and above group highest than that of other, with males higher than females (P<0.001); and urban was higher slightly than rural for the average of average glycosylated hemoglobin (P<0.001). The average fasting blood glucose and average glycosylated hemoglobin increased with increased BMI and waist circumference (P<0.001). Results from multiple linear regression model analysis showed that: 1) for each increase in BMI unit and waist circumference, the fasting glucose levels increased by 0.019 mmol/L and 0.008 mmol/L (all P<0.001) in those not diagnosed with diabetes, 2) by 0.021 mmol/L (P=0.163) and 0.014 mmol/L (P=0.004) in those newly detected as diabetes, and 3) by 0.028 mmol/L (P=0.088) and 0.023 mmol/L (P<0.001) in those self-reported as having been diagnosed as diabetes, respectively. However, glycosylated hemoglobin levels increased: 1) by 0.015% and 0.006% in those not diagnosed as diabetes (all P<0.001), 2) by 0.050% and 0.019% in those newly detected as diabetes (all P<0.001), and 3) by 0.033% and 0.019% in those self-reported as having been diagnosed as diabetes (all P<0.001), respectively. These associations with waist circumference were more robust than with BMI. Conclusions: Adults not diagnosed with diabetes with abnormal BMI or waist circumference are the key population for prevention and control. Measures improving the awareness rate of waist circumference should be taken to maintain average blood glucose in various groups.
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Affiliation(s)
- X Q Deng
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - M Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - X Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z P Zhao
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - C Li
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z J Huang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z W Song
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - B Jiang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - X H Guo
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - N Yu
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - L M Wang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
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15
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Yu N, Zhang M, Zhang X, Zhao ZP, Li C, Huang ZJ, Zhang YS, Deng XQ, Song ZW, Wang LM. [Blood glucose measurement in Chinese adults, 2018]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1196-1204. [PMID: 35981980 DOI: 10.3760/cma.j.cn112338-20211015-00798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To analyze the status of measuring the blood glucose among Chinese residents aged 18 years and above and to provide a scientific basis for evaluating the Healthy China Initiative. Methods: China Chronic Disease and Risk Factor Surveillance were conducted in 298 counties/districts in China in 2018, covering 31 provinces (autonomous regions, municipalities). A multi-stage stratified cluster random sampling method selected permanent residents aged 18 years and above. Questionnaires collected demographic characteristics, blood glucose measurements, and significant chronic disease prevalence. Body measurements were conducted to collect body height, weight, and waist circumference; Fasting venous blood was collected from participants to measure FPG before OGTT-2 h was obtained among participants without a self-reported history of diagnosed diabetes. The analysis included 177 904 residents aged 18 and above. After being weighed, the blood glucose measurement rates of adults in different groups were compared. Results: Among adults who had not been diagnosed with diabetes, The blood glucose measurement rates of regular, prediabetes, and newly detected elevated blood glucose within 12 months were 32.0% (95%CI: 30.5%-33.5%), 39.5% (95%CI: 37.4%-41.6%) and 43.8% (95%CI: 41.0%-46.4%), respectively. The measurement rates were higher in females than males; urban was higher than rural. The blood glucose rates increased with age, education, and BMI. These differences were significant (P<0.05). Among the adults with diabetes, the blood glucose measurement rate within six months was 89.6% (95%CI: 88.4%-90.8%); the measurement rate was higher in females than in males and higher in the west than in east and central regions of China, with statistical significance (P<0.05). Among adults in the study who did not have 1 or 2 or ≥3 major chronic diseases, the blood glucose measurement rates within six months were 19.6% (95%CI: 18.4%-20.7%), 41.8% (95%CI: 40.1%-43.5%), 58.9% (95%CI:57.0%-60.7%),71.9% (95%CI: 69.0%-74.9%), respectively. The blood glucose measurement rate was on the rise and increased with the number of comorbidities (P<0.001). The blood glucose measurement rate of adults who did not have 1 or 2 major chronic diseases was higher in urban areas than in rural areas. The blood glucose rates increased with age, education, and BMI and the differences were significant (P<0.05). The blood glucose measurement rate of adults with ≥3 major chronic diseases was higher in females than in males (P<0.001), and there was no difference among other groups (P>0.05). Conclusion: It is necessary to promote blood glucose measurement in residents aged 18 years and above in China. Relevant departments should strengthen the publicity and education to promote regular blood glucose measurement for high-risk populations to improve the efficiency of preventing and treating diabetes and its complications.
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Affiliation(s)
- N Yu
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - M Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - X Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z P Zhao
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - C Li
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z J Huang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Y S Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - X Q Deng
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - Z W Song
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - L M Wang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
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16
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Gao XX, Wang LM, Zhang X, Zhao ZP, Li C, Huang ZJ, Liu CY, Yu N, Zhang YS, Deng XQ, Zhang M. [Awareness and influencing factors on weight and waist circumference among adult Chinese residents in 2018]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1205-1214. [PMID: 35981981 DOI: 10.3760/cma.j.cn112338-20211129-00924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To understand the awareness of weight and waist circumference and their influencing factors among residents aged ≥18 years in China and provide a reference for the development of relevant prevention and treatment policies and evaluation of intervention effects. Methods: We selected 298 counties (districts) from the 31 provinces (autonomous regions and municipalities) which participated in the 2018 China Chronic Disease and Risk Factor Surveillance program and included 194 779 permanent residents aged ≥18 years. To obtain the demographic characteristics of the study population, we used a multi-stage stratified whole-group random sampling method, questionnaires, and physical measurements. In this study, 179 045 people who completed the survey and had complete information on weight and waist circumference awareness were used as the study subjects. The weight awareness rate and waist circumference awareness rate were calculated by gender stratification, age, urban-rural, and education level groups. A multi-factor logistic regression model was used to analyze the influencing factors related to weight and waist circumference awareness of residents aged ≥18 years. Results: The weight awareness rate of adult residents in China in 2018 was 45.4% (95%CI: 41.9%-48.9%), higher among men [46.2% (95%CI: 42.5%-49.8%)] than women [44.6% (95%CI: 41.1%-48.2%)], and in urban areas [54.3% (95%CI: 49.3%-59.3%)]. The highest weight awareness rate appeared in residents with low BMI grouping [49.9% (95%CI: 44.3%-55.6%)], and the weight awareness rate in residents with undiagnosed central obesity, hypertension, and diabetes was higher than that of residents with diagnosed diabetes, with statistically significant differences (P<0.05). The waist circumference awareness rate of adult residents was 11.6% (95%CI: 9.7%-13.4%), higher in women [12.8% (95%CI: 10.8%-14.8%)] than in men [10.3% (95%CI: 8.6%-12.0%)], higher in urban [14.6% (95%CI: 11.7%-17.4%)] than in rural [8.3% (95%CI: 6.5%-10.2%)], and the waist circumference awareness rate was higher among residents with confirmed diabetes than those with undiagnosed diabetes, with statistically significant differences (P=0.020). The difference was statistically significant (P<0.001). The weight and waist circumference awareness rate increased with education level and annual per capita household income. Multi-factor logistic regression analysis suggested that urban, highly educated, high per capita annual household income and health check-up residents may have higher weight and waist circumference awareness rates among adult residents in China. Conclusion: Less than half of the adult residents in China know their weight status, and only about one-tenth know their waist circumference. Rural residents, those with low education levels and low annual per capita household income, and those who are obese need to be given prioritized attention. The relevant government departments should strengthen the popularization of the importance of weight and waist circumference on health and improve the awareness of our residents about their waist circumference and weight.
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Affiliation(s)
- X X Gao
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China School of Public Health, Baotou Medical College, Baotou 014040, China
| | - L M Wang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - X Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z P Zhao
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - C Li
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z J Huang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - C Y Liu
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China School of Public Health, Baotou Medical College, Baotou 014040, China
| | - N Yu
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Y S Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - X Q Deng
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - M Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
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Zhang YS, Zhang M, Huang ZJ, Li C, Zhao ZP, Zhang X, Jiang B, Gao XX, Yu N, Song ZW, Wang LM. [Analysis of blood pressure measurement among Chinese adults in 2018]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1189-1195. [PMID: 35981979 DOI: 10.3760/cma.j.cn112338-20211017-00802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To analyze the blood pressure measurement of Chinese adult residents in 2018 and provide a scientific basis for early detection and intervention of hypertension. Methods: In 2018, China Chronic Disease and Risk Factor Surveillance were conducted in 298 counties (districts) of 31 provinces (autonomous regions, municipalities) across the country, using a multi-stage stratified cluster random sampling method to survey permanent residents aged 18 years and above. We selected 184 509 people and carried out a face-to-face questionnaire survey and body measurement method to collect demographic data, major chronic diseases, and blood pressure measurement information of the survey subjects. Blood glucose and blood lipid-related indicators were obtained by laboratory testing. There were 170 551 adult residents included in the study after excluding abnormal and missing data for key variables. After complex weighting, blood pressure detection rates and detection times in people with different blood pressure levels and other diseases were analyzed. SAS 9.4 software was used to perform the χ2-test and trend test. Results: Among adult residents in China, the proportions of those with normal blood pressure, commonly recognized 'high' blood pressure, and newly detected hypertension who had their blood pressure tested within three months were 44.4%, 50.4%, and 52.6%, respectively. The proportions all appeared higher in women than in men (all P<0.05), in urban than in rural areas (all P<0.05), and showed an increasing trend with age (all P<0.001); The proportion of these three populations who had never had their blood pressure measured was 27.6%, 24.2%, and 23.5% respectively. The proportion of people with diagnosed hypertension who had their blood pressure tested within seven days was 44.0%, 51.4% in urban areas, higher than 37.7% in rural areas (P<0.001), and the proportion of people who had their blood pressure tested increased with education, per capita annual income and BMI (all P<0.001). Conclusions: The behavior of regular self-monitoring of blood pressure among adult residents in China still needs to be improved, especially among men and rural areas. Relevant health promotion and education should be strengthened. More targeted policies and measures should be developed to improve blood pressure measurement behavior in people with normal high blood pressure and other high-risk groups to control elevated blood pressure effectively.
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Affiliation(s)
- Y S Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
| | - M Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z J Huang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - C Li
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z P Zhao
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - X Zhang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - B Jiang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - X X Gao
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China School of Public Health, Baotou Medical College, Baotou 014040, China
| | - N Yu
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z W Song
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - L M Wang
- Division of Chronic Disease and Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China Department of Health Statistics, School of Public Health, China Medical University, Shenyang 110122, China
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18
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Malek SC, Overvig AC, Alù A, Yu N. Multifunctional resonant wavefront-shaping meta-optics based on multilayer and multi-perturbation nonlocal metasurfaces. Light Sci Appl 2022; 11:246. [PMID: 35922413 PMCID: PMC9349264 DOI: 10.1038/s41377-022-00905-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 06/11/2022] [Accepted: 06/20/2022] [Indexed: 05/22/2023]
Abstract
Photonic devices rarely provide both elaborate spatial control and sharp spectral control over an incoming wavefront. In optical metasurfaces, for example, the localized modes of individual meta-units govern the wavefront shape over a broad bandwidth, while nonlocal lattice modes extended over many unit cells support high quality-factor resonances. Here, we experimentally demonstrate nonlocal dielectric metasurfaces in the near-infrared that offer both spatial and spectral control of light, realizing metalenses focusing light exclusively over a narrowband resonance while leaving off-resonant frequencies unaffected. Our devices attain this functionality by supporting a quasi-bound state in the continuum encoded with a spatially varying geometric phase. We leverage this capability to experimentally realize a versatile platform for multispectral wavefront shaping where a stack of metasurfaces, each supporting multiple independently controlled quasi-bound states in the continuum, molds the optical wavefront distinctively at multiple wavelengths and yet stay transparent over the rest of the spectrum. Such a platform is scalable to the visible for applications in augmented reality and transparent displays.
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Affiliation(s)
- Stephanie C Malek
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA
| | - Adam C Overvig
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA
- Photonics Initiative, Advanced Science Research Center, City University of New York, New York, NY, 10031, USA
| | - Andrea Alù
- Photonics Initiative, Advanced Science Research Center, City University of New York, New York, NY, 10031, USA
- Physics Program, Graduate Center, City University of New York, New York, NY, 10016, USA
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA.
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19
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Dang S, Guo Y, Han D, Ma G, Yu N, Yang Q, Duan X, Duan H, Ren J. MRI-based radiomics analysis in differentiating solid non-small-cell from small-cell lung carcinoma: a pilot study. Clin Radiol 2022; 77:e749-e757. [PMID: 35817610 DOI: 10.1016/j.crad.2022.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 04/29/2022] [Accepted: 06/01/2022] [Indexed: 12/24/2022]
Abstract
AIM To investigate the ability of a T2-weighted (W) magnetic resonance imaging (MRI)-based radiomics signature to differentiate solid non-small-cell lung carcinoma (NSCLC) from small-cell lung carcinoma (SCLC). MATERIALS AND METHODS The present retrospective study enrolled 152 eligible patients (NSCLC = 125, SCLC = 27). All patients underwent MRI using a 3 T scanner and radiomics features were extracted from T2W MRI. The least absolute shrinkage and selection operator (LASSO) logistic regression model was used to identify the optimal radiomics features for the construction of a radiomics model to differentiate solid NSCLC from SCLC. Threefold cross validation repeated 10 times was used for model training and evaluation. The conventional MRI morphology features of the lesions were also evaluated. The performance of the conventional MRI morphological features, and the radiomics signature model and nomogram model (combining radiomics signature with conventional MRI morphological features) was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS Five optimal features were chosen to build a radiomics signature. There was no significant difference in age, gender, and the largest diameter. The radiomics signature and conventional MRI morphological features (only pleural indentation and lymph node enlargement) were independent predictive factors for differentiating solid NSCLC from SCLC. The area under the ROC curves (AUCs) for MRI morphological features, and the radiomics model, and nomogram model was 0.69, 0.85, and 0.90 (ROC), respectively. CONCLUSIONS The T2W MRI-based radiomics signature is a potential non-invasive approach for distinguishing solid NSCLC from SCLC.
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Affiliation(s)
- S Dang
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - Y Guo
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - D Han
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - G Ma
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - N Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China; Shaanxi University of Chinese Medicine, Xianyang, China
| | - Q Yang
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - X Duan
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, China
| | - H Duan
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China; Shaanxi University of Chinese Medicine, Xianyang, China.
| | - J Ren
- GE Healthcare China, Daxing District, Beijing, China
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20
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Kolbe S, Garcia L, Yu N, Boonstra F, Clough M, Sinclair B, White O, van der Walt A, Butzkueven H, Fielding J, Law M. Lesion Volume in Relapsing Multiple Sclerosis is Associated with Perivascular Space Enlargement at the Level of the Basal Ganglia. AJNR Am J Neuroradiol 2022; 43:238-244. [PMID: 35121585 PMCID: PMC8985682 DOI: 10.3174/ajnr.a7398] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 10/19/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND PURPOSE Perivascular spaces surround the blood vessels of the brain and are involved in neuroimmune functions and clearance of metabolites via the glymphatic system of the brain. Enlarged perivascular spaces could be a marker of dysfunction in these processes and, therefore, are highly relevant to monitoring disease activity in MS. This study aimed to compare the number of enlarged perivascular spaces in people with relapsing MS with MR imaging markers of inflammation and brain atrophy. MATERIALS AND METHODS Fifty-nine patients (18 with clinically isolated syndrome, 22 with early and 19 with late relapsing-remitting MS) were scanned longitudinally (mean follow-up duration = 19.6 [SD, 0.5] months) using T2-weighted, T1-weighted, and FLAIR MR imaging. Two expert raters identified and counted enlarged perivascular spaces on T2-weighted MR images from 3 ROIs (the centrum semiovale, basal ganglia, and midbrain). Baseline and change with time in the number of enlarged perivascular spaces were correlated with demographics and lesion and brain volumes. RESULTS Late relapsing-remitting MS had a greater average number of enlarged perivascular spaces at baseline at the level of the basal ganglia (72.3) compared with early relapsing-remitting MS (60.5) and clinically isolated syndrome (54.7) (F = 3.4, P = .042), and this finding correlated with lesion volume (R = 0.44, P = .0004) but not brain atrophy (R = -0.16). Enlarged perivascular spaces increased in number with time in all regions, and the rate of increase did not differ among clinical groups. CONCLUSIONS Enlarged perivascular spaces at the level of the basal ganglia are associated with greater neuroinflammatory burden, and the rate of enlargement appears constant in patients with relapsing-remitting disease phenotypes.
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Affiliation(s)
- S.C. Kolbe
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Departments of Radiology (S.C.K., M.L.)
| | - L.M. Garcia
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - N. Yu
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Department of Neurology (N.Y.), The Nanjing Brain Hospital Affiliated with Nanjing Medical University, Nanjing, Jiangsu, China
| | - F.M. Boonstra
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - M. Clough
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - B. Sinclair
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - O. White
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Neurology (O.W., A.v.d.W., H.B.), Alfred Hospital, Melbourne, Victoria, Australia
| | - A. van der Walt
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Neurology (O.W., A.v.d.W., H.B.), Alfred Hospital, Melbourne, Victoria, Australia
| | - H. Butzkueven
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Neurology (O.W., A.v.d.W., H.B.), Alfred Hospital, Melbourne, Victoria, Australia
| | - J. Fielding
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia
| | - M. Law
- From the Department of Neuroscience (S.C.K., L.M.G., N.Y., F.M.B., M.C., B.S., O.W., A.v.d.W., H.B., J.F., M.L.) Monash University, Melbourne, Victoria, Australia,Departments of Radiology (S.C.K., M.L.)
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21
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Zou SH, Fu XM, Yu N, Tan FB, Shu TT, Li Y, Ji P, Zhang FG. [Simultaneous reconstruction of the mandible and restoration of implant supported dentition: a case report of jaw in a day in China]. Zhonghua Kou Qiang Yi Xue Za Zhi 2021; 56:1267-1270. [PMID: 34915663 DOI: 10.3760/cma.j.cn112144-20210617-00296] [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: 06/14/2023]
Affiliation(s)
- S H Zou
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital of Chongqing Medical University, Chongqing 401147, China
| | - X M Fu
- Department of Prosthodontics, Stomatological Hospital of Chongqing Medical University, Chongqing 401147, China
| | - N Yu
- Department of Prosthodontics Technology, Stomatological Hospital of Chongqing Medical University, Chongqing 401147, China
| | - F B Tan
- Department of Prosthodontics Technology, Stomatological Hospital of Chongqing Medical University, Chongqing 401147, China
| | - T T Shu
- Department of Prosthodontics Technology, Stomatological Hospital of Chongqing Medical University, Chongqing 401147, China
| | - Y Li
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital of Chongqing Medical University, Chongqing 401147, China
| | - P Ji
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital of Chongqing Medical University, Chongqing 401147, China
| | - F G Zhang
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital of Chongqing Medical University, Chongqing 401147, China
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Chen XQ, Zheng DY, Xiao YY, Dong BL, Cao CW, Ma L, Tong ZS, Zhu M, Liu ZH, Xi LY, Fu M, Jin Y, Yin B, Li FQ, Li XF, Abliz P, Liu HF, Zhang Y, Yu N, Wu WW, Xiong XC, Zeng JS, Huang HQ, Jiang YP, Chen GZ, Pan WH, Sang H, Wang Y, Guo Y, Shi DM, Yang JX, Chen W, Wan Z, Li RY, Wang AP, Ran YP, Yu J. Aetiology of tinea capitis in China: A multicentre prospective study. Br J Dermatol 2021; 186:705-712. [PMID: 34741300 DOI: 10.1111/bjd.20875] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/30/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Tinea capitis is still common in developing countries, such as China. Its pathogen spectrum varies across regions and changes over time. OBJECTIVES This study aimed to clarify the current epidemiological characteristics and pathogen spectrum of tinea capitis in China. METHODS A multicentre, prospective descriptive study involving 29 tertiary hospitals in China was conducted. From August 2019 to July 2020, 611 patients with tinea capitis were enrolled. Data concerning demography, risk factors and fungal tests were collected. The pathogens were further identified by morphology or molecular sequencing when necessary in the central laboratory. RESULTS Among all enrolled patients, 74.1% of the cases were 2- to 8-year-olds. The children with tinea capitis were mainly boys (56.2%) and more likely to have an animal contact history (57.4% vs. 35.3%, P = 0.012) and zoophilic dermatophyte infection (73.5%). The adults were mainly females (83.3%) and more likely to have anthropophilic agent infection (53.5%). The most common pathogen was zoophilic Microsporum canis (354, 65.2%), followed by anthropophilic Trichophyton violaceum (74, 13.6%). In contrast to the eastern, western and northeastern regions where zoophilic M. canis predominated, anthropophilic T. violaceum predominated in central China (69.2%, P < 0.0001), where the patients had the most tinea at other sites (20.3%) and dermatophytosis contact (25.9%) with the least animal contact (38.8%). Microsporum ferrugineum was the most common anthropophilic agent in the western area, especially in Xinjiang Province. CONCLUSIONS Boys aged approximately 5 years were mainly affected. Dermatologists are advised to pay more attention to the different transmission routes and pathogen spectra in different age groups from different regions.
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Affiliation(s)
- X-Q Chen
- Department of Dermatology and Venereology, Peking University First Hospital, National Clinical Research Centre for Skin and Immune Diseases, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, NMPA Key Laboratory for Quality Control and Evaluation of Cosmetics, Beijing, China
| | - D-Y Zheng
- Department of Dermatology and Venereology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Y-Y Xiao
- Department of Dermatology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - B-L Dong
- Department of Dermatology, Wuhan No.1 Hospital, Wuhan, China
| | - C-W Cao
- Department of Dermatology and Venereology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - L Ma
- Department of Dermatology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Z-S Tong
- Department of Dermatology, Wuhan No.1 Hospital, Wuhan, China
| | - M Zhu
- Department of Dermatology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Z-H Liu
- Department of Dermatology, Hangzhou Third People's Hospital, Affiliated Hangzhou Dermatology Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - L-Y Xi
- Department of Dermatology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - M Fu
- Department of Dermatology, Xijing Hospital, Xi'an, China
| | - Y Jin
- Department of Dermatology, Dermatology Hospital of Jiangxi Province, Nanchang, China
| | - B Yin
- Department of Dermatology, Chengdu Second People's Hospital, Chengdu, China
| | - F-Q Li
- Department of Dermatology, the Second Hospital of Jilin University, Changchun, China
| | - X-F Li
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
| | - P Abliz
- Department of Dermatology, the First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - H-F Liu
- Department of Dermatology, Dermatology Hospital of Southern Medical University, Guangzhou, China
| | - Y Zhang
- Department of Dermatology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin, China
| | - N Yu
- Department of Dermatology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - W-W Wu
- Department of Dermatology, the Fifth People's Hospital of Hainan Province, Haikou, China
| | - X-C Xiong
- Department of Dermatology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - J-S Zeng
- Department of Dermatology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - H-Q Huang
- Department of Dermatology and Venereology, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Y-P Jiang
- Department of Dermatology, the Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - G-Z Chen
- Department of Dermatology, the Affiliated Hospital of Qingdao University, Qingdao, China
| | - W-H Pan
- Department of Dermatology, Shanghai Changzheng Hospital, Naval Military Medical University, Shanghai, China
| | - H Sang
- Department of Dermatology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Y Wang
- Department of Dermatology, Changhai Hospital of Shanghai, Shanghai, China
| | - Y Guo
- Department of Dermatology, the Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - D-M Shi
- Department of Dermatology, Jining No, People's Hospital, Jining, China
| | - J-X Yang
- Department of Dermatology, 2nd Affiliated Hospital of Harbin Medical University, Harbin, China
| | - W Chen
- Department of Dermatology and Venereology, Peking University First Hospital, National Clinical Research Centre for Skin and Immune Diseases, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, NMPA Key Laboratory for Quality Control and Evaluation of Cosmetics, Beijing, China
| | - Z Wan
- Department of Dermatology and Venereology, Peking University First Hospital, National Clinical Research Centre for Skin and Immune Diseases, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, NMPA Key Laboratory for Quality Control and Evaluation of Cosmetics, Beijing, China
| | - R-Y Li
- Department of Dermatology and Venereology, Peking University First Hospital, National Clinical Research Centre for Skin and Immune Diseases, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, NMPA Key Laboratory for Quality Control and Evaluation of Cosmetics, Beijing, China
| | - A-P Wang
- Department of Dermatology and Venereology, Peking University First Hospital, National Clinical Research Centre for Skin and Immune Diseases, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, NMPA Key Laboratory for Quality Control and Evaluation of Cosmetics, Beijing, China
| | - Y-P Ran
- Department of Dermatology, West China Hospital, Sichuan University, Chengdu, China
| | - J Yu
- Department of Dermatology and Venereology, Peking University First Hospital, National Clinical Research Centre for Skin and Immune Diseases, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, NMPA Key Laboratory for Quality Control and Evaluation of Cosmetics, Beijing, China
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23
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Le BQ, Too JH, Tan TC, Smith RA, Nurcombe V, Cool SM, Yu N. Application of a BMP2-binding heparan sulphate to promote periodontal regeneration. Eur Cell Mater 2021; 42:139-153. [PMID: 34464450 DOI: 10.22203/ecm.v042a10] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Periodontitis is the most common inflammatory disease that leads to periodontal defects and tooth loss. Regeneration of alveolar bone and soft tissue in periodontal defects is highly desirable but remains challenging. A heparan sulphate variant (HS3) with enhanced affinity for bone morphogenetic protein-2 (BMP2) that, when combined with collagen or ceramic biomaterials, enhances bone tissue regeneration in the axial and cranial skeleton in several animal models was reported previously. In the current study, establishing the efficacy of a collagen/HS3 device for the regeneration of alveolar bone and the adjacent periodontal apparatus and related structures was sought. Collagen sponges loaded with phosphate-buffered saline, HS3, BMP2, or HS3 + BMP2 were implanted into surgically-created intra-bony periodontal defects in rat maxillae. At the 6 week end- point the maxillae were decalcified, and the extent of tissue regeneration determined by histomorphometrical analysis. The combination of collagen/HS3, collagen/BMP2 or collagen/HS3 + BMP2 resulted in a three to four-fold increase in bone regeneration and up to a 1.5 × improvement in functional ligament restoration compared to collagen alone. Moreover, the combination of collagen/HS3 + BMP2 improved the alveolar bone height and reduced the amount of epithelial growth in the apical direction. The implantation of a collagen/ HS3 combination device enhanced the regeneration of alveolar bone and associated periodontal tissues at amounts comparable to collagen in combination with the osteogenic factor BMP2. This study highlights the efficacy of a collagen/HS3 combination device for periodontal regeneration that warrants further development as a point-of-care treatment for periodontitis-related bone and soft tissue loss.
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Affiliation(s)
| | | | | | | | | | | | - N Yu
- ational Dental Research Institute Singapore, National Dental Centre Singapore, 5 Second Hospital Avenue, Singapore
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24
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Han D, Yu Y, He T, Yu N, Dang S, Wu H, Ren J, Duan X. Effect of radiomics from different virtual monochromatic images in dual-energy spectral CT on the WHO/ISUP classification of clear cell renal cell carcinoma. Clin Radiol 2021; 76:627.e23-627.e29. [PMID: 33985770 DOI: 10.1016/j.crad.2021.02.033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 02/10/2021] [Indexed: 12/24/2022]
Abstract
AIM To investigate the effect of radiomics obtained from different virtual monochromatic images (VMIs) in dual-energy spectral computed tomography (CT) on the World Health Organization/International Association for Urological Pathology (WHO/ISUP) classification of clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS A retrospective study of 99 ccRCC patients who underwent contrast-enhanced dual-energy CT was undertaken. ccRCC was confirmed at surgery or biopsy and graded according to the WHO/ISUP pathological grading criteria as low grade (n=68, grade I and II) or high grade (n=31, grade III and IV). Radiomics risk scores (RRSs) for differentiating high and low grades of ccRCC were constructed from 11 sets of VMI in (40-140 keV, 10 keV interval) the cortical phase. Receiver operating characteristic (ROC) curves were drawn and the area under the curves (AUCs) was calculated to evaluate the discriminatory power of RRS for each VMI. The Hosmer-Lemeshow test was used to evaluate the goodness-of-fit of each model and the decision curve was used to analyse its net benefit to patients. RESULTS The AUC values for distinguishing low-from high-grade ccRCC with RRS of 40-140 keV VMIs were all >0.920. The Hosmer-Lemeshow test showed that the p-values of RRS of VMIs were >0.05, suggesting good fits. In the decision curve analysis, RRS from the 40-140 keV VMIs had similar decision curves and provided better net benefits than considering all patients either as high-grade or low-grade. CONCLUSIONS The RRS obtained from multiple VMIs in dual-energy spectral CT have high diagnostic efficiencies for distinguishing between low- and high-grade ccRCC with no significant differences between different VMIs.
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Affiliation(s)
- D Han
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Y Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - T He
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - N Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - S Dang
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - H Wu
- Pathology Department, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - J Ren
- GE Healthcare China, Beijing, China
| | - X Duan
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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25
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Qin J, Zhang S, Poon L, Pan Z, Luo J, Yu N, Wang L, Wu X, Cheng X, Xie X, Lu Y, LU W. Doppler-based predictive model for methotrexate resistance in low-risk gestational trophoblastic neoplasia with myometrial invasion: prospective study of 147 patients. Ultrasound Obstet Gynecol 2021; 57:829-839. [PMID: 32385928 PMCID: PMC8251727 DOI: 10.1002/uog.22069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 03/30/2020] [Accepted: 04/22/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVES This prospective clinical study aimed to evaluate the vascularization characteristics of low-risk gestational trophoblastic neoplasia (GTN) using Doppler imaging and to develop a predictive model for resistance to methotrexate (MTX). METHODS Patients with low-risk GTN receiving primary MTX treatment were enrolled from the Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China, from September 2012 to August 2018. The primary endpoint was to develop and internally validate a predictive model for resistance to MTX therapy in these patients. In the training set, clinical features and Doppler hemodynamic parameters before MTX therapy were analyzed using logistic regression to identify independent predictors of MTX resistance, which were integrated into the model. The predictive performance of the model was evaluated by leave-one-out cross-validation in the training dataset and internal validation in an independent-sample test dataset. RESULTS The entire imaging protocol was completed by 147 eligible patients, of which 110 comprised the training set and 37 the test set. In the training set, cases with myometrial invasion (81.8%; 90/110) showed vascular-enriched areas in the myometrium and high velocity and low impedance ratios of the uterine artery (UtA) compared to cases without myometrial invasion (18.2%; 20/110). On multivariate logistic regression analysis, time-averaged mean velocity in UtA (UtA-TAmean) and the International Federation of Gynecology and Obstetrics (FIGO) score were identified as independent predictors (P = 0.009 and P = 0.043, respectively) of MTX resistance. The Doppler-based predictive model, developed based on the 90 cases with myometrial invasion, was y = -2.95332 + 0.41696 × FIGO score + 0.03551 × UtA-TAmean. The model showed an area under the curve of 0.757 (95% CI, 0.653-0.862) and the optimal cut-off value was 0.50622, which had 45.2% sensitivity and 96.6% specificity. The model stratified patients with low-risk GTN into low (< 10%), intermediate (10-90%) and high (> 90%) probability of MTX resistance, based on the threshold values of -1.59544 and 0.10046. The model had an accuracy of 74.4% (95% CI, 64.5-82.3%) in the cross-validation and 72.7% (95% CI, 55.8-84.9%) in the internal validation. CONCLUSIONS The Doppler-based predictive model, combining a non-invasive marker of tumor vascularity with the FIGO scoring system, can differentiate cases with low from those with high probability of developing MTX resistance and therefore has the potential to guide treatment options in patients with low-risk GTN and myometrial invasion. © 2020 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- J. Qin
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
- Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang ProvinceHangzhouZhejiangChina
| | - S. Zhang
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
- Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang ProvinceHangzhouZhejiangChina
| | - L. Poon
- Department of Obstetrics and GynaecologyThe Chinese University of Hong KongHong Kong SAR
| | - Z. Pan
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
- Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang ProvinceHangzhouZhejiangChina
| | - J. Luo
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
| | - N. Yu
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
| | - L. Wang
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
| | - X. Wu
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
| | - X. Cheng
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
- Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang ProvinceHangzhouZhejiangChina
| | - X. Xie
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
- Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang ProvinceHangzhouZhejiangChina
| | - Y. Lu
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
- Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang ProvinceHangzhouZhejiangChina
- Institute of Translational MedicineZhejiang University School of MedicineHangzhouChina
| | - W. LU
- Women's Reproductive Health Key Laboratory of Zhejiang Province, Women's HospitalZhejiang University School of MedicineHangzhouZhejiangChina
- Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang ProvinceHangzhouZhejiangChina
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26
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Wang Y, Zeng S, Crunteanu A, Xie Z, Humbert G, Ma L, Wei Y, Brunel A, Bessette B, Orlianges JC, Lalloué F, Schmidt OG, Yu N, Ho HP. Targeted Sub-Attomole Cancer Biomarker Detection Based on Phase Singularity 2D Nanomaterial-Enhanced Plasmonic Biosensor. Nanomicro Lett 2021; 13:96. [PMID: 34138312 PMCID: PMC7985234 DOI: 10.1007/s40820-021-00613-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 01/23/2021] [Indexed: 05/24/2023]
Abstract
A zero-reflection-induced phase singularity is achieved through precisely controlling the resonance characteristics using two-dimensional nanomaterials. An atomically thin nano-layer having a high absorption coefficient is exploited to enhance the zero-reflection dip, which has led to the subsequent phase singularity and thus a giant lateral position shift. We have improved the detection limit of low molecular weight molecules by more than three orders of magnitude compared to current state-of-art nanomaterial-enhanced plasmonic sensors. Detection of small cancer biomarkers with low molecular weight and a low concentration range has always been challenging yet urgent in many clinical applications such as diagnosing early-stage cancer, monitoring treatment and detecting relapse. Here, a highly enhanced plasmonic biosensor that can overcome this challenge is developed using atomically thin two-dimensional phase change nanomaterial. By precisely engineering the configuration with atomically thin materials, the phase singularity has been successfully achieved with a significantly enhanced lateral position shift effect. Based on our knowledge, it is the first experimental demonstration of a lateral position signal change > 340 μm at a sensing interface from all optical techniques. With this enhanced plasmonic effect, the detection limit has been experimentally demonstrated to be 10-15 mol L-1 for TNF-α cancer marker, which has been found in various human diseases including inflammatory diseases and different kinds of cancer. The as-reported novel integration of atomically thin Ge2Sb2Te5 with plasmonic substrate, which results in a phase singularity and thus a giant lateral position shift, enables the detection of cancer markers with low molecular weight at femtomolar level. These results will definitely hold promising potential in biomedical application and clinical diagnostics.
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Affiliation(s)
- Yuye Wang
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, People's Republic of China
- CNRS, XLIM Research Institute, UMR 7252, University of Limoges, 123, Avenue Albert Thomas, Limoges, France
| | - Shuwen Zeng
- CNRS, XLIM Research Institute, UMR 7252, University of Limoges, 123, Avenue Albert Thomas, Limoges, France.
- Department of Applied Physics and Applied Mathematics, Columbia University, New York City, NY, USA.
| | - Aurelian Crunteanu
- CNRS, XLIM Research Institute, UMR 7252, University of Limoges, 123, Avenue Albert Thomas, Limoges, France
| | - Zhenming Xie
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, People's Republic of China
| | - Georges Humbert
- CNRS, XLIM Research Institute, UMR 7252, University of Limoges, 123, Avenue Albert Thomas, Limoges, France
| | - Libo Ma
- Institute for Integrative Nanosciences, IFW Dresden, Helmholtzstr. 20, Dresden, Germany
| | - Yuanyuan Wei
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, People's Republic of China
| | - Aude Brunel
- Faculty of Medicine, University of Limoges, EA3842-CAPTuR, GEIST, 2 rue du Dr Marcland, Limoges, France
| | - Barbara Bessette
- Faculty of Medicine, University of Limoges, EA3842-CAPTuR, GEIST, 2 rue du Dr Marcland, Limoges, France
| | - Jean-Christophe Orlianges
- CNRS, XLIM Research Institute, UMR 7252, University of Limoges, 123, Avenue Albert Thomas, Limoges, France
| | - Fabrice Lalloué
- Faculty of Medicine, University of Limoges, EA3842-CAPTuR, GEIST, 2 rue du Dr Marcland, Limoges, France
| | - Oliver G Schmidt
- Institute for Integrative Nanosciences, IFW Dresden, Helmholtzstr. 20, Dresden, Germany
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York City, NY, USA
| | - Ho-Pui Ho
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, People's Republic of China.
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Abstract
Quasi-bound states in the continuum (QBICs) are Fano resonant states with long optical lifetimes controlled by symmetry-breaking perturbations. While conventional Fano responses are limited to linear polarizations and do not support tailored phase control, here we introduce QBICs born of chiral perturbations that encode arbitrary elliptical polarization states and enable geometric phase engineering. We thereby design metasurfaces with ultrasharp spectral features that shape the impinging wave front with near-unity efficiency. Our findings extend Fano resonances beyond their conventional limits, opening opportunities for nanophotonics, classical and quantum optics, and acoustics.
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Affiliation(s)
- Adam Overvig
- Photonics Initiative, Advanced Science Research Center at the Graduate Center of the City University of New York, New York, New York 10031, USA
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, USA
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, USA
| | - Andrea Alù
- Photonics Initiative, Advanced Science Research Center at the Graduate Center of the City University of New York, New York, New York 10031, USA
- Physics Program, Graduate Center, City University of New York, New York, New York 10016, USA
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28
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Chen M, Pang D, Mandal J, Chen X, Yan H, He Y, Yu N, Yang Y. Designing Mesoporous Photonic Structures for High-Performance Passive Daytime Radiative Cooling. Nano Lett 2021; 21:1412-1418. [PMID: 33524258 DOI: 10.1021/acs.nanolett.0c04241] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Passive daytime radiative cooling (PDRC) has drawn significant attention recently for electricity-free cooling. Porous polymers are attractive for PDRC since they have excellent performance and scalability. A fundamental question remaining is how PDRC performance depends on pore properties (e.g., radius, porosity), which is critical to guiding future structure designs. In this work, optical simulations are carried out to answer this question, and effects of pore size, porosity, and thickness are studied. We find that mixed nanopores (e.g., radii of 100 and 200 nm) have a much higher solar reflectance R̅solar (0.951) than the single-sized pores (0.811) at a thickness of 300 μm. With an Al substrate underneath, R̅solar, thermal emittance ε̅LWIR, and net cooling power Pcool reach 0.980, 0.984, and 72 W/m2, respectively, under a semihumid atmospheric condition. These simulation results provide a guide for designing high-performance porous coating for PDRC applications.
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Affiliation(s)
- Meijie Chen
- School of Energy Science and Engineering, Central South University, Changsha 410083, China
- Program of Materials Science and Engineering, Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, United States
| | - Dan Pang
- School of Energy Science and Engineering, Central South University, Changsha 410083, China
| | - Jyotirmoy Mandal
- Department of Materials Science and Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Xingyu Chen
- School of Energy Science and Engineering, Central South University, Changsha 410083, China
| | - Hongjie Yan
- School of Energy Science and Engineering, Central South University, Changsha 410083, China
| | - Yurong He
- School of Energy Science and Engineering, Harbin Institution of Technology, Harbin 180001, China
| | - Nanfang Yu
- Program of Materials Science and Engineering, Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, United States
| | - Yuan Yang
- Program of Materials Science and Engineering, Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, United States
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29
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Liénard MA, Bernard GD, Allen A, Lassance JM, Song S, Childers RR, Yu N, Ye D, Stephenson A, Valencia-Montoya WA, Salzman S, Whitaker MRL, Calonje M, Zhang F, Pierce NE. The evolution of red color vision is linked to coordinated rhodopsin tuning in lycaenid butterflies. Proc Natl Acad Sci U S A 2021; 118:e2008986118. [PMID: 33547236 PMCID: PMC8017955 DOI: 10.1073/pnas.2008986118] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Color vision has evolved multiple times in both vertebrates and invertebrates and is largely determined by the number and variation in spectral sensitivities of distinct opsin subclasses. However, because of the difficulty of expressing long-wavelength (LW) invertebrate opsins in vitro, our understanding of the molecular basis of functional shifts in opsin spectral sensitivities has been biased toward research primarily in vertebrates. This has restricted our ability to address whether invertebrate Gq protein-coupled opsins function in a novel or convergent way compared to vertebrate Gt opsins. Here we develop a robust heterologous expression system to purify invertebrate rhodopsins, identify specific amino acid changes responsible for adaptive spectral tuning, and pinpoint how molecular variation in invertebrate opsins underlie wavelength sensitivity shifts that enhance visual perception. By combining functional and optophysiological approaches, we disentangle the relative contributions of lateral filtering pigments from red-shifted LW and blue short-wavelength opsins expressed in distinct photoreceptor cells of individual ommatidia. We use in situ hybridization to visualize six ommatidial classes in the compound eye of a lycaenid butterfly with a four-opsin visual system. We show experimentally that certain key tuning residues underlying green spectral shifts in blue opsin paralogs have evolved repeatedly among short-wavelength opsin lineages. Taken together, our results demonstrate the interplay between regulatory and adaptive evolution at multiple Gq opsin loci, as well as how coordinated spectral shifts in LW and blue opsins can act together to enhance insect spectral sensitivity at blue and red wavelengths for visual performance adaptation.
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Affiliation(s)
- Marjorie A Liénard
- Broad Institute of MIT and Harvard University, Cambridge, MA 02142;
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Gary D Bernard
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195
| | - Andrew Allen
- Broad Institute of MIT and Harvard University, Cambridge, MA 02142
| | - Jean-Marc Lassance
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Siliang Song
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Richard Rabideau Childers
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027
| | - Dajia Ye
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Adriana Stephenson
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Wendy A Valencia-Montoya
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Shayla Salzman
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Melissa R L Whitaker
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | | | - Feng Zhang
- Broad Institute of MIT and Harvard University, Cambridge, MA 02142
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
- Howard Hughes Medical Institute, Cambridge, MA 02139
| | - Naomi E Pierce
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138;
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Yang ZM, Yu N, Wang SJ, Korai SK, Liu ZW. Characterization of ecdysteroid biosynthesis in the pond wolf spider, Pardosa pseudoannulata. Insect Mol Biol 2021; 30:71-80. [PMID: 33131130 DOI: 10.1111/imb.12678] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 10/02/2020] [Accepted: 10/28/2020] [Indexed: 06/11/2023]
Abstract
Ecdysteroids, as the key growth hormones, regulate moulting, metamorphosis and reproduction in arthropods. Ecdysteroid biosynthesis is catalysed by a series of cytochrome P450 monooxygenases (CYP450s) encoded by Halloween genes, including spook (spo), phantom (phm), disembodied (dib), shadow (sad) and shade (shd). The ecdysteroid biosynthesis in insects is clear with 20-hydroxyecdysone (20E) as the main ecdysteroid. However, the information on the major ecdysteroids in arachnids is limited. In this study, Halloween genes spo, dib, sad and shd, but not phm, were identified in the pond wolf spider, Pardosa pseudoannulata. Phylogenetic analysis grouped arachnid and insect Halloween gene products into two CYP450 clades, the CYP2 clan (spo and phm) and the mitochondrial clan (dib, sad, and shd). In P. pseudoannulata, the temporal expression profile of the four Halloween genes in concurrence with spiderling moulting with steady increase in the course of the 2nd instar followed by a rapid dropdown once moulting was completed. Spatially, the four Halloween genes were highly expressed in spiderling abdomen and in the ovaries of female adults. In parallel, ponasterone A (PA), but not 20E, was detected by LC-MS/MS analysis in P. pseudoannulata, and it was demonstrated as a functional ecdysteroid in the spider by accelerating of moulting with PA addition. The present study revealed the different ecdysteroid biosynthesis pathways in spiders and insects.
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Affiliation(s)
- Z-M Yang
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), College of Plant Protection, Nanjing Agricultural University, Nanjing, China
| | - N Yu
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), College of Plant Protection, Nanjing Agricultural University, Nanjing, China
| | - S-J Wang
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), College of Plant Protection, Nanjing Agricultural University, Nanjing, China
| | - S K Korai
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), College of Plant Protection, Nanjing Agricultural University, Nanjing, China
| | - Z-W Liu
- Key Laboratory of Integrated Management of Crop Diseases and Pests (Ministry of Education), College of Plant Protection, Nanjing Agricultural University, Nanjing, China
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Yu BT, Yu N, Wang Y, Zhang H, Wan K, Sun X, Zhang CS. Role of miR-133a in regulating TGF-β1 signaling pathway in myocardial fibrosis after acute myocardial infarction in rats. Eur Rev Med Pharmacol Sci 2020; 23:8588-8597. [PMID: 31646592 DOI: 10.26355/eurrev_201910_19175] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The aim of this research was to explore the effect of microRNA-133a (miR-133a) on myocardial fibrosis and cardiac function after myocardial infarction in rats, and to investigate the possible regulatory mechanism. MATERIALS AND METHODS Myocardial infarction model was successfully established in rats by ligation of the left anterior descending coronary artery. After miR-133a overexpression in rats myocardium, cardiac function was examined by echocardiography. Meanwhile, the degree of myocardial fibrosis was detected by Masson staining. In addition, the expression of α-smooth muscle actin (α-SMA) in cardiomyocytes was detected by immunohistochemistry. Quantitative Real-time polymerase chain reaction (qRT-PCR) was performed to analyze the expression level of miR-133a in the junction of myocardial infarction. The mRNA expressions of transforming growth factor-β1 (TGF-β1), connective tissue growth factor (CTGF), collagen type 1 (col 1), collagen type 3 (col 3) and α-SMA were measured by qRT-PCR as well. Furthermore, the protein levels of the above genes were detected by Western blotting. RESULTS MiR-133a expression in the infarct border zone of myocardial tissue was significantly decreased on the 28th day after myocardial infarction surgery (p<0.05). In addition, up-regulation of miRNA-133a in myocardial tissue of rats with myocardial infarction could remarkably improve cardiac function and reduce collagen volume fraction. Furthermore, the mRNA and protein expression levels of TGF-β1, CTGF, col1, col3, α-SMA in myocardial tissue were obviously decreased after miRNA-133a up-regulation (p<0.001). CONCLUSIONS Overexpression of miR-133a down-regulates the mRNA and protein levels of TGF-β1 and CTGF after myocardial infarction. Moreover, this may eventually reduce myocardial collagen deposition, inhibit myocardial fibrosis and improve cardiac function.
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Affiliation(s)
- B-T Yu
- Department of Emergency, The Affiliated Central Hospital of Qingdao University, Qingdao, China.
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Huang T, Zhao X, Zeng S, Crunteanu A, Shum PP, Yu N. Planar nonlinear metasurface optics and their applications. Rep Prog Phys 2020; 83:126101. [PMID: 33290268 DOI: 10.1088/1361-6633/abb56e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Metasurfaces are artificial two-dimensional (2D) planar surfaces that consist of subwavelength 'meta-atoms' (i.e. metallic or dielectric nanostructures). They are known for their capability to achieve better and more efficient light control in comparison to their traditional optical counterparts. Abrupt and sharp changes in the electromagnetic properties can be induced by the metasurfaces rather than the conventional gradual accumulation that requires greater propagation distances. Based on this feature, planar optical components like mirrors, lenses, waveplates, isolators and even holograms with ultrasmall thicknesses have been developed. Most of the current metasurface studies have focused on tailoring the linear optical effects for applications such as cloaking, lens imaging and 3D holography. Recently, the use of metasurfaces to enhance nonlinear optical effects has attracted significant attention from the research community. Benefiting from the resulting efficient nonlinear optical processes, the fabrication of integrated all-optical nano-devices with peculiar functionalities including broadband frequency conversions and ultrafast optical switching will become achievable. Plasmonic excitation is one of the most effective approaches to increase nonlinear optical responses due to its induced strong local electromagnetic field enhancement. For instance, continuous phase control on the effective nonlinear polarizability of plasmonic metasurfaces has been demonstrated through spin-rotation light coupling. The phase of the nonlinear polarization can be continuously tuned by spatially changing the meta-atoms' orientations during second and third harmonic generation processes, while the nonlinear metasurfaces also exhibit homogeneous linear properties. In addition, an ultrahigh second-order nonlinear susceptibility of up to 104 pm V-1 has recently been reported by coupling the plasmonic modes of patterned metallic arrays with intersubband transition of multi-quantum-well layered substrate. In order to develop ultra-planar nonlinear plasmonic metasurfaces, 2D materials such as graphene and transition metal dichalcogenides (TMDCs) have been extensively studied based on their unique nonlinear optical properties. The third-order nonlinear coefficient of graphene is five times that of gold substrate, while TMDC materials also exhibit a strong second-order magnetic susceptibility. In this review, we first focus on the main principles of planar nonlinear plasmonics based on metasurfaces and 2D nonlinear materials. The advantages and challenges of incorporating 2D nonlinear materials into metasurfaces are discussed, followed by their potential applications including orbital angular momentum manipulating and quantum optics.
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Affiliation(s)
- Tianye Huang
- School of Mechanical Engineering & Electronic Information, China University of Geosciences, Wuhan 430074, People's republic of China
- XLIM Research Institute, UMR 7252 CNRS/University of Limoges, France
- Wuhan National Library for Optoelectronics, Wuhan, 430074, People's republic of China
| | - Xiang Zhao
- School of Mechanical Engineering & Electronic Information, China University of Geosciences, Wuhan 430074, People's republic of China
| | - Shuwen Zeng
- XLIM Research Institute, UMR 7252 CNRS/University of Limoges, France
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, United States of America
| | | | - Perry Ping Shum
- School of Mechanical Engineering & Electronic Information, China University of Geosciences, Wuhan 430074, People's republic of China
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, United States of America
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Campbell S, Juloori A, Smile T, LaHurd D, Yu N, Woody N, Stephans K. Impact of Prior Y90 Dosimetry on Toxicity and Outcomes Following SBRT for Hepatocellular Carcinoma. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.1810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Lee J, Kim YC, Lee S, Yoo S, Davis K, Nagar S, Sawyer W, Yu N, Taylor A. 413P South Korean real-world treatment patterns in patients with EGFRm NSCLC. Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.10.407] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Ma G, Han D, Dang S, Yu N, Yang Q, Yang C, Jin C, Dou Y. Replacing true unenhanced imaging in renal carcinoma with virtual unenhanced images in dual-energy spectral CT: a feasibility study. Clin Radiol 2020; 76:81.e21-81.e27. [PMID: 32993881 DOI: 10.1016/j.crad.2020.08.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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: 11/28/2019] [Accepted: 08/21/2020] [Indexed: 11/18/2022]
Abstract
AIM To investigate the clinical value of virtual unenhanced (VNC) spectral computed tomography (CT) images to replace the conventional true unenhanced spectral CT images (TNC) in diagnosing renal carcinoma. MATERIALS AND METHODS Fifty-six cases of renal carcinoma confirmed by histopathology underwent conventional plain CT and contrast-enhanced spectral CT at arterial phase (AP) and venous phase (VP). VNC images were generated on an AW4.6 workstation. The CT attenuation, image noise, contrast-to-noise ratio (CNR), and signal-noise-ratio (SNR) of the renal lesions and normal kidneys, long and short axis diameters of the lesion were measured from the three image sets and analysed using one-way analysis of variance (ANOVA). Two radiologists evaluated image quality subjectively using a five-point score, and lesion signature using a three-point score. Image quality scores were compared statistically and tested for consistency. RESULTS The two reviewers had good agreement for subjective evaluation (Kappa>0.70) and there was no difference in the quality of the scores among the three image groups. The lesion signature scores were all above the acceptable level. The CNR and SNR values in VNC were significantly higher than in TNC (p<0.05). VNC images had lower renal noise than in TNC (p<0.05). There was no difference in the long and short axis diameters of the lesion among the three image groups. VNC had higher CT attenuation values for the lesion and kidney than TNC (p<0.05), but the differences were <5 HU. CONCLUSION VNC images in spectral CT may be used to replace the conventional plain CT to reduce imaging duration and radiation dose in diagnosing renal carcinoma.
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Affiliation(s)
- G Ma
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, 712000, China
| | - D Han
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, 712000, China
| | - S Dang
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, 712000, China
| | - N Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, 712000, China
| | - Q Yang
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, 712000, China
| | - C Yang
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, 712000, China
| | - C Jin
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Yanta Western Road, Xi'an, Shannxi, 710061, China
| | - Y Dou
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, 712000, China.
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Wang H, Chen ZY, Li ZL, Wang M, Cui J, Yu N, Huang XL, Chang GQ, Wang SM. [The value of color doppler ultrasonography in the diagnosis of impending ruptured abdominal aortic aneurysm]. Zhonghua Yi Xue Za Zhi 2020; 100:2507-2510. [PMID: 32829597 DOI: 10.3760/cma.j.cn112137-20191210-02693] [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: 11/05/2022]
Abstract
Objective: To study the value of color doppler ultrasonography (CDU) in diagnosis of impending ruptured abdominal aortic aneurysm (IRAAA). Methods: A total of 35 cases with IRAAA which were identified by CDU in our department from June 2014 to June 2019 were retrospectively analyzed. All the patients were detected by computed tomographic angiography (CTA). The types, length of the neck of aneurysm, largest diameter, thrombosis, involvement of common iliac artery and impending ruptured conditions were compared. The postoperative patients were followed-up by CDU and CTA (mean time was 2.6 months). Results: Among 35 patients, CDU diagnosed that 5 cases were pararenal types and 30 cases were infrarenal types. CTA showed that 4 cases were pararenal types and 31 cases were infrarenal types. The misdiagnosis rate of CDU was 2.9% (1/35). CDU showed that bilateral common iliac arteries were involved in 21 cases, right common iliac arteries were involved in 3 cases, and left common iliac arteries were involved in 2 cases. CTA detected the same results. There was no statistical difference between CDU and CTA for detection of the largest anteroposterior diameter, transverse diameter and the thickness of thrombosis (P values were 0.354, 0.310 and 0.865). There was statistical difference in the detection of the length of the aneurysm's neck (P=0.006). CDU showed 3 cases of focal wall discontinuity, 4 cases of hyperattenuating crescent sign, 3 cases of thrombus fissuration and 2 cases of saclike protuberance, which were consistent with the detection of CTA. CDU showed that locally thin wall of aneurysm was detected in the rest of 23 cases. CTA showed 2 patients were negative. The misdiagnosis rate of CDU was 5.7% (2/35). Three cases did not undergo surgery. Open repairs (OR) were performed in 5 cases. Endovascular aneurysm repairs (EVAR) were performed in 27 cases. The postoperative patients were followed up by CDU and CTA at 1 month, 3 months, 6 months and 12 months. All the artificial blood vessels and stents were patent. Endoleak was observed in 5 cases. Aneurysm sac thrombosis was found in the rest of the cases. Conclusions: CDU plays an important role in the analysis and diagnosis of the size, range, and the impending ruptured symptoms of the aneurysm. It provides a reliable basis for IRAAA screening, diagnosis and postoperative follow-up, and has important clinical value.
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Affiliation(s)
- H Wang
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
| | - Z Y Chen
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
| | - Z L Li
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
| | - M Wang
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
| | - J Cui
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
| | - N Yu
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
| | - X L Huang
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
| | - G Q Chang
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
| | - S M Wang
- Department of Vascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, National-Local Joint Engineering Laboratory of Vascular Disease Treatment, Guangdong Engineering and Technology Center for Diagnosis and Treatment of Vascular Diseases, Guangzhou 510080, China
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Jagannathan S, Ackerman L, Chen W, Yu N, Cavillon M, Tuggle M, Hawkins TW, Ballato J, Dragic PD. Random lasing from optical fibers with phase separated glass cores. Opt Express 2020; 28:22049-22063. [PMID: 32752473 DOI: 10.1364/oe.396109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 06/29/2020] [Indexed: 06/11/2023]
Abstract
A novel random laser, integrating a passive optical fiber with a phase separated aluminosilicate core-silica cladding as the feedback medium, is proposed and presented. The core exhibits greatly enhanced Rayleigh scattering, therefore requiring a significantly reduced length of scattering fiber (4 m) for lasing. With a Yb-doped fiber as the gain medium, the fiber laser operates at 1050 nm with low threshold power and possesses an output that can be amplified through conventional means. Furthermore, the laser was found to have a high degree of spatial coherence, spectral broadening with increasing input power, and temporal spectral variation. The facile setup and results herein pave the way for further study and applications based on low threshold random fiber lasers.
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Sternbach AJ, Latini S, Chae S, Hübener H, De Giovannini U, Shao Y, Xiong L, Sun Z, Shi N, Kissin P, Ni GX, Rhodes D, Kim B, Yu N, Millis AJ, Fogler MM, Schuck PJ, Lipson M, Zhu XY, Hone J, Averitt RD, Rubio A, Basov DN. Femtosecond exciton dynamics in WSe 2 optical waveguides. Nat Commun 2020; 11:3567. [PMID: 32678086 PMCID: PMC7367278 DOI: 10.1038/s41467-020-17335-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 06/17/2020] [Indexed: 11/29/2022] Open
Abstract
Van-der Waals (vdW) atomically layered crystals can act as optical waveguides over a broad range of the electromagnetic spectrum ranging from Terahertz to visible. Unlike common Si-based waveguides, vdW semiconductors host strong excitonic resonances that may be controlled using non-thermal stimuli including electrostatic gating and photoexcitation. Here, we utilize waveguide modes to examine photo-induced changes of excitons in the prototypical vdW semiconductor, WSe2, prompted by femtosecond light pulses. Using time-resolved scanning near-field optical microscopy we visualize the electric field profiles of waveguide modes in real space and time and extract the temporal evolution of the optical constants following femtosecond photoexcitation. By monitoring the phase velocity of the waveguide modes, we detect incoherent A-exciton bleaching along with a coherent optical Stark shift in WSe2. The authors use time-resolved scanning near-field optical microscopy to probe the ultrafast excitonic processes and their impact on waveguide operation in transition metal dichalcogenide crystals. They observe significant modulation of the complex index by monitoring waveguide modes on the fs time scale, and identify both coherent and incoherent manipulations of WSe2 excitonic resonances.
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Affiliation(s)
- Aaron J Sternbach
- Department of Physics, Columbia University, New York, NY, 10027, USA.
| | - Simone Latini
- Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761, Hamburg, Germany
| | - Sanghoon Chae
- Department of Mechanical Engineering, Columbia University, New York, NY, 10027, USA
| | - Hannes Hübener
- Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761, Hamburg, Germany
| | - Umberto De Giovannini
- Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761, Hamburg, Germany
| | - Yinming Shao
- Department of Physics, Columbia University, New York, NY, 10027, USA
| | - Lin Xiong
- Department of Physics, Columbia University, New York, NY, 10027, USA
| | - Zhiyuan Sun
- Department of Physics, Columbia University, New York, NY, 10027, USA
| | - Norman Shi
- Department of Physics, Columbia University, New York, NY, 10027, USA
| | - Peter Kissin
- Department of Physics, University of California, San Diego, La Jolla, 92093, CA, USA
| | - Guang-Xin Ni
- Department of Physics, Columbia University, New York, NY, 10027, USA
| | - Daniel Rhodes
- Department of Mechanical Engineering, Columbia University, New York, NY, 10027, USA
| | - Brian Kim
- Department of Mechanical Engineering, Columbia University, New York, NY, 10027, USA
| | - Nanfang Yu
- Department of Physics, Columbia University, New York, NY, 10027, USA
| | - Andrew J Millis
- Department of Physics, Columbia University, New York, NY, 10027, USA
| | - Michael M Fogler
- Department of Physics, University of California, San Diego, La Jolla, 92093, CA, USA
| | - Peter J Schuck
- Department of Mechanical Engineering, Columbia University, New York, NY, 10027, USA
| | - Michal Lipson
- Department of Electrical Engineering, Columbia University, New York, NY, 10027, USA
| | - X-Y Zhu
- Department of Chemistry, Columbia University, New York, NY, 10027, USA
| | - James Hone
- Department of Mechanical Engineering, Columbia University, New York, NY, 10027, USA
| | - Richard D Averitt
- Department of Physics, University of California, San Diego, La Jolla, 92093, CA, USA
| | - Angel Rubio
- Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761, Hamburg, Germany.,Center for Computational Quantum Physics (CCQ), Flatiron Institute, 162 Fifth Avenue, New York, NY, 10010, USA
| | - D N Basov
- Department of Physics, Columbia University, New York, NY, 10027, USA
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Abstract
Diffractive photonic devices manipulate light via local and nonlocal optical modes. Local devices, such as metasurfaces, can shape a wave front at multiple selected wavelengths, but inevitably modify light across the spectrum; nonlocal devices, such as grating filters, offer great frequency selectivity but limited spatial control. Here, we introduce a rational design paradigm using quasibound states in the continuum to realize multifunctional nonlocal devices: metasurfaces that produce narrow band spatially tailored wave fronts at multiple selected wavelengths and yet are otherwise transparent.
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Affiliation(s)
- Adam C Overvig
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, USA
| | - Stephanie C Malek
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, USA
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, USA
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40
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Yu N. 023 Circulating serum amyloid A levels correlate with the severity of generalized pustular psoriasis. J Invest Dermatol 2020. [DOI: 10.1016/j.jid.2020.03.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Lee S, Yu N, Laughlin B, Haddock M, Ashman J, Merrell K, Rule W, Wittich MN, Mathis K, Merchea A, Hubbard J, Bekaii-Saab T, Ahn D, Jin Z, Mahipal A, Etzioni D, Mishra N, Krishnan S, Hallemeier C, Sio T. P-130 Short course pelvic radiotherapy for localized and oligometastatic rectal adenocarcinoma: The Mayo Clinic experience. Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.04.212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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Chen Y, Mandal J, Li W, Smith-Washington A, Tsai CC, Huang W, Shrestha S, Yu N, Han RPS, Cao A, Yang Y. Colored and paintable bilayer coatings with high solar-infrared reflectance for efficient cooling. Sci Adv 2020; 6:eaaz5413. [PMID: 32426464 PMCID: PMC7182418 DOI: 10.1126/sciadv.aaz5413] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 01/31/2020] [Indexed: 05/20/2023]
Abstract
Solar reflective and thermally emissive surfaces offer a sustainable way to cool objects under sunlight. However, white or silvery reflectance of these surfaces does not satisfy the need for color. Here, we present a paintable bilayer coating that simultaneously achieves color and radiative cooling. The bilayer comprises a thin, visible-absorptive layer atop a nonabsorptive, solar-scattering underlayer. The top layer absorbs appropriate visible wavelengths to show specific colors, while the underlayer maximizes the reflection of near-to-short wavelength infrared (NSWIR) light to reduce solar heating. Consequently, the bilayer attains higher NSWIR reflectance (by 0.1 to 0.51) compared with commercial paint monolayers of the same color and stays cooler by as much as 3.0° to 15.6°C under strong sunlight. High NSWIR reflectance of 0.89 is realized in the blue bilayer. The performances show that the bilayer paint design can achieve both color and efficient radiative cooling in a simple, inexpensive, and scalable manner.
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Affiliation(s)
- Yijun Chen
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
- Department of Materials Science and Engineering, College of Engineering, Peking University, Beijing 100871, China
| | - Jyotirmoy Mandal
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Wenxi Li
- Department of Mechanical Engineering, Columbia University, New York, NY 10027, USA
| | - Ajani Smith-Washington
- Department of Physics and Astronomy, College of Arts and Sciences, Howard University, Washington, DC 20059, USA
| | - Cheng-Chia Tsai
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Wenlong Huang
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Sajan Shrestha
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
- Corresponding author. (Y.Y.); (N.Y.)
| | - Ray P. S. Han
- Department of Materials Science and Engineering, College of Engineering, Peking University, Beijing 100871, China
| | - Anyuan Cao
- Department of Materials Science and Engineering, College of Engineering, Peking University, Beijing 100871, China
| | - Yuan Yang
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA
- Corresponding author. (Y.Y.); (N.Y.)
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Tsai CC, Childers RA, Nan Shi N, Ren C, Pelaez JN, Bernard GD, Pierce NE, Yu N. Physical and behavioral adaptations to prevent overheating of the living wings of butterflies. Nat Commun 2020; 11:551. [PMID: 31992708 PMCID: PMC6987309 DOI: 10.1038/s41467-020-14408-8] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 12/11/2019] [Indexed: 11/08/2022] Open
Abstract
The wings of Lepidoptera contain a matrix of living cells whose function requires appropriate temperatures. However, given their small thermal capacity, wings can overheat rapidly in the sun. Here we analyze butterfly wings across a wide range of simulated environmental conditions, and find that regions containing living cells are maintained at cooler temperatures. Diverse scale nanostructures and non-uniform cuticle thicknesses create a heterogeneous distribution of radiative cooling that selectively reduces the temperature of structures such as wing veins and androconial organs. These tissues are supplied by circulatory, neural and tracheal systems throughout the adult lifetime, indicating that the insect wing is a dynamic, living structure. Behavioral assays show that butterflies use wings to sense visible and infrared radiation, responding with specialized behaviors to prevent overheating of their wings. Our work highlights the physiological importance of wing temperature and how it is exquisitely regulated by structural and behavioral adaptations.
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Affiliation(s)
- Cheng-Chia Tsai
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA
| | - Richard A Childers
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Norman Nan Shi
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA
- Western Digital, San Jose, CA, 95119, USA
| | - Crystal Ren
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA
| | - Julianne N Pelaez
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Gary D Bernard
- Department of Electrical Engineering, University of Washington, Seattle, WA, 98195, USA
| | - Naomi E Pierce
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA.
- Museum of Comparative Zoology, Harvard University, Cambridge, MA, 02138, USA.
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA.
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Zhang Q, Yu N, Yu BT. MicroRNA-298 regulates apoptosis of cardiomyocytes after myocardial infarction. Eur Rev Med Pharmacol Sci 2019; 22:532-539. [PMID: 29424914 DOI: 10.26355/eurrev_201801_14206] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To investigate the role and mechanism of micro ribonucleic acid (miR)-298 in myocardial apoptosis after myocardial infarction. MATERIALS AND METHODS In vivo experiments, the rat model of myocardial infarction was established, and miR-298 was up-regulated via lentivirus with miR-298 overexpression. Cardiac function of rats was detected via echocardiography, Bcl-2 associated X protein (BAX) expressions in infarction border zone were detected via Real-time Quantitative PCR (qT-PCR) and Western blot, and TUNEL assay was used to detect the myocardial apoptosis. In vitro experiments, myocardial cells were isolated and cultured, an oxygen-glucose deprivation (OGD) model was established to mimicking the ischemic condition, the relationship between miR-298 and BAX was verified using luciferase reporter vector, lentivirus and small-interfering RNA (siRNA) in BAX. RESULTS In vivo experiments showed that the miR-298 expression was down-regulated at 2 and 4 weeks after myocardial infarction. The up-regulation of miR-298 significantly improved the cardiac function, decreased the expressions of BAX, reduced the myocardial apoptosis and inhibit the apoptosis proteins expression including cytochrome-c and cleaved caspase-3. In vitro experiments revealed that BAX was a target gene of miR-298 and further proof that miR-298 could inhibit the cytochrome-c and cleaved caspase-3 expression and myocardial apoptosis through BAX. CONCLUSIONS MiR-298 can improve the myocardial apoptosis through the target gene BAX.
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Affiliation(s)
- Q Zhang
- Department of Cardiology, Coal General Hospital, Beijing, China.
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Yu N, Fan L, Wu JL, Chen SH, Li W. Analysis on the correlations of ENOS and ET-2 gene polymorphisms with eclampsia. Eur Rev Med Pharmacol Sci 2019; 23:6800-6805. [PMID: 31486478 DOI: 10.26355/eurrev_201908_18718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To explore the correlations of endothelial nitric oxide synthase (eNOS) G894T and endothelin-2 (ET-2) A985G gene polymorphisms with eclampsia. PATIENTS AND METHODS A total of 110 eclampsia patients in our hospital from July 2014 to August 2017 were enrolled as the observation group and 100 healthy pregnant women in the same period as the control group. The polymorphisms of eNOS G894T and ET-2 A985G genes in the two groups were analyzed via polymerase chain reaction (PCR), and their correlations with eclampsia risk were investigated. RESULTS The distribution frequency of eNOS G894T genotype TT and GT and T allele, as well as the ET-2 A985G genotype GG and AG and G allele, were evidently higher in the observation group than in the control group (p<0.05). ENOS G894T genotype TT and ET-2 A985G genotype GG were significantly associated with the occurrence of eclampsia. CONCLUSIONS The polymorphisms of eNOS G894T and ET-2 A985G genes are correlated with the occurrence of eclampsia.
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Affiliation(s)
- N Yu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Ren ZL, Hu ZJ, Li D, Jia YJ, Yu N, Yu Y, Guo CY, Zhang XR, He TP. [Application of adaptive statistical iterative reconstruction veo and 80 kv in renal computed tomography angiography]. Zhonghua Yi Xue Za Zhi 2019; 99:1953-1958. [PMID: 31269599 DOI: 10.3760/cma.j.issn.0376-2491.2019.25.010] [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] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Objective: To explore the application of adaptive statistical iterative reconstruction Veo (ASIR-V) and 80 kV in renal computed tomography angiography(CTA). Methods: Eighty patients with renal computed tomography angiography were prospectively collected from April 2018 to July 2018 in the Affiliated Hospital of Shaanxi University of Chinese Medicine and randomly divided into group A and group B. The patients in group A adopted tube voltage 120 kV and contrast agent concentration 600 mgI/kg and reconstructed with filtered back projection (FBP), while the patients in group B were scanned with tube voltage 80 kV and contrast agent concentration 350 mgI/kg and reconstructed with FBP and ASIR-V from 10% to 100% with 10% interval. The CT values and standard deviation (SD) of the right renal artery, left renal artery were measured respectively to calculate the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).The image quality of renal CTA was subjectively scored by two experienced radiologists blindly using a 5-point criteria.The contrast agent,CT volume dose index(CTDI(vol)) and dose length product(DLP) in both groups were recorded and the effective radiation dose(ED) was calculated. Results: The ED ((2.11±0.19)mSv) and contrast agent ((21.9±3.0)g) in group B were 65.1% (P<0.05) and 42.2% (P<0.05) lower than those in group A ((6.04±1.89)mSv and (38.0±3.8)g).With the increase of ASIR-V percentage in group B, CT values showed no significant difference, SD values gradually decreased, SNR values and CNR values gradually increased.The CT values with different reconstruction algorithm showed no statistically significant difference (all P>0.05) between group A and group B. The SD values with 40%ASIR-V to 100%ASIR-V reconstruction in group B were significantly lower than those of group A (all P<0.05).The SNR values with 50% ASIR-V to 100% ASIR-V reconstruction and CNR values with 70%ASIR-V to 100%ASIR-V were significantly higher than those of group A(all P<0.5).Two radiologists had excellent consistency in subjective scores of image quality for renal CTA(all kappa>0.75, P<0.05). The subjective scores with 60% ASIR-V to 90% ASIR-V in group B were significantly higher than those in group A (P<0.05), of which 70%ASIR-V reconstruction achieved the highest subjective score for renal CTA. Conclusion: ASIR-V and 80 kV can significantly reduce radiation dose (about 65.1%) and contrast agent (about 42.2%) in renal CTA, ASIR-V reconstruction can significantly improve the image quality of renal CTA, of which 70% ASIR-V reconstruction achieved the best image quality in 80 kV renal CTA.
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Affiliation(s)
- Z L Ren
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - Z J Hu
- Department of Radiology, Chang'an Hospital, Xi'an 710016, China
| | - D Li
- Department of Radiology, Chang'an Hospital, Xi'an 710016, China
| | - Y J Jia
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - N Yu
- Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - Y Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - C Y Guo
- Department of Radiology, the Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - X R Zhang
- Shaanxi University of Chinese Medicine, Xianyang 712000, China
| | - T P He
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China
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Adam J, Adamczyk L, Adams JR, Adkins JK, Agakishiev G, Aggarwal MM, Ahammed Z, Alekseev I, Anderson DM, Aoyama R, Aparin A, Arkhipkin D, Aschenauer EC, Ashraf MU, Atetalla F, Attri A, Averichev GS, Bai X, Bairathi V, Barish K, Bassill AJ, Behera A, Bellwied R, Bhasin A, Bhati AK, Bielcik J, Bielcikova J, Bland LC, Bordyuzhin IG, Brandenburg JD, Brandin AV, Brown D, Bryslawskyj J, Bunzarov I, Butterworth J, Caines H, Calderón de la Barca Sánchez M, Cebra D, Chakaberia I, Chaloupka P, Chan BK, Chang FH, Chang Z, Chankova-Bunzarova N, Chatterjee A, Chattopadhyay S, Chen JH, Chen X, Chen X, Cheng J, Cherney M, Christie W, Contin G, Crawford HJ, Csanad M, Das S, Dedovich TG, Deppner IM, Derevschikov AA, Didenko L, Dilks C, Dong X, Drachenberg JL, Dunlop JC, Efimov LG, Elsey N, Engelage J, Eppley G, Esha R, Esumi S, Evdokimov O, Ewigleben J, Eyser O, Fatemi R, Fazio S, Federic P, Federicova P, Fedorisin J, Filip P, Finch E, Fisyak Y, Flores CE, Fulek L, Gagliardi CA, Galatyuk T, Geurts F, Gibson A, Grosnick D, Gunarathne DS, Guo Y, Gupta A, Guryn W, Hamad AI, Hamed A, Harlenderova A, Harris JW, He L, Heppelmann S, Heppelmann S, Herrmann N, Hirsch A, Holub L, Hong Y, Horvat S, Huang B, Huang HZ, Huang SL, Huang T, Huang X, Humanic TJ, Huo P, Igo G, Jacobs WW, Jentsch A, Jia J, Jiang K, Jowzaee S, Ju X, Judd EG, Kabana S, Kagamaster S, Kalinkin D, Kang K, Kapukchyan D, Kauder K, Ke HW, Keane D, Kechechyan A, Kikoła DP, Kim C, Kinghorn TA, Kisel I, Kisiel A, Kochenda L, Kosarzewski LK, Kraishan AF, Kramarik L, Krauth L, Kravtsov P, Krueger K, Kulathunga N, Kumar L, Kunnawalkam Elayavalli R, Kvapil J, Kwasizur JH, Lacey R, Landgraf JM, Lauret J, Lebedev A, Lednicky R, Lee JH, Li C, Li W, Li X, Li Y, Liang Y, Lidrych J, Lin T, Lipiec A, Lisa MA, Liu F, Liu H, Liu P, Liu P, Liu Y, Liu Z, Ljubicic T, Llope WJ, Lomnitz M, Longacre RS, Luo S, Luo X, Ma GL, Ma L, Ma R, Ma YG, Magdy N, Majka R, Mallick D, Margetis S, Markert C, Matis HS, Matonoha O, Mazer JA, Meehan K, Mei JC, Minaev NG, Mioduszewski S, Mishra D, Mohanty B, Mondal MM, Mooney I, Morozov DA, Nasim M, Negrete JD, Nelson JM, Nemes DB, Nie M, Nigmatkulov G, Niida T, Nogach LV, Nonaka T, Odyniec G, Ogawa A, Oh K, Oh S, Okorokov VA, Olvitt D, Page BS, Pak R, Panebratsev Y, Pawlik B, Pei H, Perkins C, Pinter RL, Pluta J, Porter J, Posik M, Pruthi NK, Przybycien M, Putschke J, Quintero A, Radhakrishnan SK, Ramachandran S, Ray RL, Reed R, Ritter HG, Roberts JB, Rogachevskiy OV, Romero JL, Ruan L, Rusnak J, Rusnakova O, Sahoo NR, Sahu PK, Salur S, Sandweiss J, Schambach J, Schmah AM, Schmidke WB, Schmitz N, Schweid BR, Seck F, Seger J, Sergeeva M, Seto R, Seyboth P, Shah N, Shahaliev E, Shanmuganathan PV, Shao M, Shen F, Shen WQ, Shi SS, Shou QY, Sichtermann EP, Siejka S, Sikora R, Simko M, Singh J, Singha S, Smirnov D, Smirnov N, Solyst W, Sorensen P, Spinka HM, Srivastava B, Stanislaus TDS, Stewart DJ, Strikhanov M, Stringfellow B, Suaide AAP, Sugiura T, Sumbera M, Summa B, Sun XM, Sun X, Sun Y, Surrow B, Svirida DN, Szymanski P, Tang AH, Tang Z, Taranenko A, Tarnowsky T, Thomas JH, Timmins AR, Tlusty D, Todoroki T, Tokarev M, Tomkiel CA, Trentalange S, Tribble RE, Tribedy P, Tripathy SK, Tsai OD, Tu B, Ullrich T, Underwood DG, Upsal I, Van Buren G, Vanek J, Vasiliev AN, Vassiliev I, Videbæk F, Vokal S, Voloshin SA, Vossen A, Wang F, Wang G, Wang P, Wang Y, Wang Y, Webb JC, Wen L, Westfall GD, Wieman H, Wissink SW, Witt R, Wu Y, Xiao ZG, Xie G, Xie W, Xu J, Xu N, Xu QH, Xu YF, Xu Z, Yang C, Yang Q, Yang S, Yang Y, Ye Z, Ye Z, Yi L, Yip K, Yoo IK, Yu N, Zbroszczyk H, Zha W, Zhang J, Zhang J, Zhang L, Zhang S, Zhang S, Zhang XP, Zhang Y, Zhang Z, Zhao J, Zhong C, Zhou C, Zhu X, Zhu Z, Zyzak M. Azimuthal Harmonics in Small and Large Collision Systems at RHIC Top Energies. Phys Rev Lett 2019; 122:172301. [PMID: 31107064 DOI: 10.1103/physrevlett.122.172301] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 03/26/2019] [Indexed: 06/09/2023]
Abstract
The first (v_{1}^{fluc}), second (v_{2}), and third (v_{3}) harmonic coefficients of the azimuthal particle distribution at midrapidity are extracted for charged hadrons and studied as a function of transverse momentum (p_{T}) and mean charged particle multiplicity density ⟨N_{ch}⟩ in U+U (sqrt[s_{NN}]=193 GeV), Au+Au, Cu+Au, Cu+Cu, d+Au, and p+Au collisions at sqrt[s_{NN}]=200 GeV with the STAR detector. For the same ⟨N_{ch}⟩, the v_{1}^{fluc} and v_{3} coefficients are observed to be independent of the collision system, while v_{2} exhibits such a scaling only when normalized by the initial-state eccentricity (ϵ_{2}). The data also show that ln(v_{2}/ϵ_{2}) scales linearly with ⟨N_{ch}⟩^{-1/3}. These measurements provide insight into initial-geometry fluctuations and the role of viscous hydrodynamic attenuation on v_{n} from small to large collision systems.
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Affiliation(s)
- J Adam
- Creighton University, Omaha, Nebraska 68178
| | - L Adamczyk
- AGH University of Science and Technology, FPACS, Cracow 30-059, Poland
| | - J R Adams
- Ohio State University, Columbus, Ohio 43210
| | - J K Adkins
- University of Kentucky, Lexington, Kentucky 40506-0055
| | - G Agakishiev
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | | | - Z Ahammed
- Variable Energy Cyclotron Centre, Kolkata 700064, India
| | - I Alekseev
- Alikhanov Institute for Theoretical and Experimental Physics, Moscow 117218, Russia
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - D M Anderson
- Texas A&M University, College Station, Texas 77843
| | - R Aoyama
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - A Aparin
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - D Arkhipkin
- Brookhaven National Laboratory, Upton, New York 11973
| | | | | | | | - A Attri
- Panjab University, Chandigarh 160014, India
| | - G S Averichev
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - X Bai
- Central China Normal University, Wuhan, Hubei 430079
| | - V Bairathi
- National Institute of Science Education and Research, HBNI, Jatni 752050, India
| | - K Barish
- University of California, Riverside, California 92521
| | - A J Bassill
- University of California, Riverside, California 92521
| | - A Behera
- State University of New York, Stony Brook, New York 11794
| | - R Bellwied
- University of Houston, Houston, Texas 77204
| | - A Bhasin
- University of Jammu, Jammu 180001, India
| | - A K Bhati
- Panjab University, Chandigarh 160014, India
| | - J Bielcik
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - J Bielcikova
- Nuclear Physics Institute AS CR, Prague 250 68, Czech Republic
| | - L C Bland
- Brookhaven National Laboratory, Upton, New York 11973
| | - I G Bordyuzhin
- Alikhanov Institute for Theoretical and Experimental Physics, Moscow 117218, Russia
| | | | - A V Brandin
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - D Brown
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - J Bryslawskyj
- University of California, Riverside, California 92521
| | - I Bunzarov
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | | | - H Caines
- Yale University, New Haven, Connecticut 06520
| | | | - D Cebra
- University of California, Davis, California 95616
| | - I Chakaberia
- Kent State University, Kent, Ohio 44242
- Shandong University, Qingdao, Shandong 266237
| | - P Chaloupka
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - B K Chan
- University of California, Los Angeles, California 90095
| | - F-H Chang
- National Cheng Kung University, Tainan 70101
| | - Z Chang
- Brookhaven National Laboratory, Upton, New York 11973
| | | | - A Chatterjee
- Variable Energy Cyclotron Centre, Kolkata 700064, India
| | | | - J H Chen
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - X Chen
- University of Science and Technology of China, Hefei, Anhui 230026
| | - X Chen
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - J Cheng
- Tsinghua University, Beijing 100084
| | - M Cherney
- Creighton University, Omaha, Nebraska 68178
| | - W Christie
- Brookhaven National Laboratory, Upton, New York 11973
| | - G Contin
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - H J Crawford
- University of California, Berkeley, California 94720
| | - M Csanad
- Eötvös Loránd University, Budapest, Hungary H-1117
| | - S Das
- Central China Normal University, Wuhan, Hubei 430079
| | - T G Dedovich
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - I M Deppner
- University of Heidelberg, Heidelberg 69120, Germany
| | | | - L Didenko
- Brookhaven National Laboratory, Upton, New York 11973
| | - C Dilks
- Pennsylvania State University, University Park, Pennsylvania 16802
| | - X Dong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | | | - J C Dunlop
- Brookhaven National Laboratory, Upton, New York 11973
| | - L G Efimov
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - N Elsey
- Wayne State University, Detroit, Michigan 48201
| | - J Engelage
- University of California, Berkeley, California 94720
| | - G Eppley
- Rice University, Houston, Texas 77251
| | - R Esha
- University of California, Los Angeles, California 90095
| | - S Esumi
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - O Evdokimov
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - J Ewigleben
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - O Eyser
- Brookhaven National Laboratory, Upton, New York 11973
| | - R Fatemi
- University of Kentucky, Lexington, Kentucky 40506-0055
| | - S Fazio
- Brookhaven National Laboratory, Upton, New York 11973
| | - P Federic
- Nuclear Physics Institute AS CR, Prague 250 68, Czech Republic
| | - P Federicova
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - J Fedorisin
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - P Filip
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - E Finch
- Southern Connecticut State University, New Haven, Connecticut 06515
| | - Y Fisyak
- Brookhaven National Laboratory, Upton, New York 11973
| | - C E Flores
- University of California, Davis, California 95616
| | - L Fulek
- AGH University of Science and Technology, FPACS, Cracow 30-059, Poland
| | | | - T Galatyuk
- Technische Universität Darmstadt, Darmstadt 64289, Germany
| | - F Geurts
- Rice University, Houston, Texas 77251
| | - A Gibson
- Valparaiso University, Valparaiso, Indiana 46383
| | - D Grosnick
- Valparaiso University, Valparaiso, Indiana 46383
| | | | - Y Guo
- Kent State University, Kent, Ohio 44242
| | - A Gupta
- University of Jammu, Jammu 180001, India
| | - W Guryn
- Brookhaven National Laboratory, Upton, New York 11973
| | - A I Hamad
- Kent State University, Kent, Ohio 44242
| | - A Hamed
- Texas A&M University, College Station, Texas 77843
| | - A Harlenderova
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - J W Harris
- Yale University, New Haven, Connecticut 06520
| | - L He
- Purdue University, West Lafayette, Indiana 47907
| | - S Heppelmann
- University of California, Davis, California 95616
| | - S Heppelmann
- Pennsylvania State University, University Park, Pennsylvania 16802
| | - N Herrmann
- University of Heidelberg, Heidelberg 69120, Germany
| | - A Hirsch
- Purdue University, West Lafayette, Indiana 47907
| | - L Holub
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - Y Hong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - S Horvat
- Yale University, New Haven, Connecticut 06520
| | - B Huang
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - H Z Huang
- University of California, Los Angeles, California 90095
| | - S L Huang
- State University of New York, Stony Brook, New York 11794
| | - T Huang
- National Cheng Kung University, Tainan 70101
| | - X Huang
- Tsinghua University, Beijing 100084
| | | | - P Huo
- State University of New York, Stony Brook, New York 11794
| | - G Igo
- University of California, Los Angeles, California 90095
| | - W W Jacobs
- Indiana University, Bloomington, Indiana 47408
| | - A Jentsch
- University of Texas, Austin, Texas 78712
| | - J Jia
- Brookhaven National Laboratory, Upton, New York 11973
- State University of New York, Stony Brook, New York 11794
| | - K Jiang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - S Jowzaee
- Wayne State University, Detroit, Michigan 48201
| | - X Ju
- University of Science and Technology of China, Hefei, Anhui 230026
| | - E G Judd
- University of California, Berkeley, California 94720
| | - S Kabana
- Kent State University, Kent, Ohio 44242
| | - S Kagamaster
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - D Kalinkin
- Indiana University, Bloomington, Indiana 47408
| | - K Kang
- Tsinghua University, Beijing 100084
| | - D Kapukchyan
- University of California, Riverside, California 92521
| | - K Kauder
- Brookhaven National Laboratory, Upton, New York 11973
| | - H W Ke
- Brookhaven National Laboratory, Upton, New York 11973
| | - D Keane
- Kent State University, Kent, Ohio 44242
| | - A Kechechyan
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - D P Kikoła
- Warsaw University of Technology, Warsaw 00-661, Poland
| | - C Kim
- University of California, Riverside, California 92521
| | - T A Kinghorn
- University of California, Davis, California 95616
| | - I Kisel
- Frankfurt Institute for Advanced Studies FIAS, Frankfurt 60438, Germany
| | - A Kisiel
- Warsaw University of Technology, Warsaw 00-661, Poland
| | - L Kochenda
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | | | - A F Kraishan
- Temple University, Philadelphia, Pennsylvania 19122
| | - L Kramarik
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - L Krauth
- University of California, Riverside, California 92521
| | - P Kravtsov
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - K Krueger
- Argonne National Laboratory, Argonne, Illinois 60439
| | | | - L Kumar
- Panjab University, Chandigarh 160014, India
| | | | - J Kvapil
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | | | - R Lacey
- State University of New York, Stony Brook, New York 11794
| | - J M Landgraf
- Brookhaven National Laboratory, Upton, New York 11973
| | - J Lauret
- Brookhaven National Laboratory, Upton, New York 11973
| | - A Lebedev
- Brookhaven National Laboratory, Upton, New York 11973
| | - R Lednicky
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - J H Lee
- Brookhaven National Laboratory, Upton, New York 11973
| | - C Li
- University of Science and Technology of China, Hefei, Anhui 230026
| | - W Li
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - X Li
- University of Science and Technology of China, Hefei, Anhui 230026
| | - Y Li
- Tsinghua University, Beijing 100084
| | - Y Liang
- Kent State University, Kent, Ohio 44242
| | - J Lidrych
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - T Lin
- Texas A&M University, College Station, Texas 77843
| | - A Lipiec
- Warsaw University of Technology, Warsaw 00-661, Poland
| | - M A Lisa
- Ohio State University, Columbus, Ohio 43210
| | - F Liu
- Central China Normal University, Wuhan, Hubei 430079
| | - H Liu
- Indiana University, Bloomington, Indiana 47408
| | - P Liu
- State University of New York, Stony Brook, New York 11794
| | - P Liu
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - Y Liu
- Texas A&M University, College Station, Texas 77843
| | - Z Liu
- University of Science and Technology of China, Hefei, Anhui 230026
| | - T Ljubicic
- Brookhaven National Laboratory, Upton, New York 11973
| | - W J Llope
- Wayne State University, Detroit, Michigan 48201
| | - M Lomnitz
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - R S Longacre
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Luo
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - X Luo
- Central China Normal University, Wuhan, Hubei 430079
| | - G L Ma
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - L Ma
- Fudan University, Shanghai 200433
| | - R Ma
- Brookhaven National Laboratory, Upton, New York 11973
| | - Y G Ma
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - N Magdy
- State University of New York, Stony Brook, New York 11794
| | - R Majka
- Yale University, New Haven, Connecticut 06520
| | - D Mallick
- National Institute of Science Education and Research, HBNI, Jatni 752050, India
| | | | - C Markert
- University of Texas, Austin, Texas 78712
| | - H S Matis
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - O Matonoha
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - J A Mazer
- Rutgers University, Piscataway, New Jersey 08854
| | - K Meehan
- University of California, Davis, California 95616
| | - J C Mei
- Shandong University, Qingdao, Shandong 266237
| | - N G Minaev
- Institute of High Energy Physics, Protvino 142281, Russia
| | | | - D Mishra
- National Institute of Science Education and Research, HBNI, Jatni 752050, India
| | - B Mohanty
- National Institute of Science Education and Research, HBNI, Jatni 752050, India
| | - M M Mondal
- Institute of Physics, Bhubaneswar 751005, India
| | - I Mooney
- Wayne State University, Detroit, Michigan 48201
| | - D A Morozov
- Institute of High Energy Physics, Protvino 142281, Russia
| | - Md Nasim
- University of California, Los Angeles, California 90095
| | - J D Negrete
- University of California, Riverside, California 92521
| | - J M Nelson
- University of California, Berkeley, California 94720
| | - D B Nemes
- Yale University, New Haven, Connecticut 06520
| | - M Nie
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - G Nigmatkulov
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - T Niida
- Wayne State University, Detroit, Michigan 48201
| | - L V Nogach
- Institute of High Energy Physics, Protvino 142281, Russia
| | - T Nonaka
- Central China Normal University, Wuhan, Hubei 430079
| | - G Odyniec
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - A Ogawa
- Brookhaven National Laboratory, Upton, New York 11973
| | - K Oh
- Pusan National University, Pusan 46241, Korea
| | - S Oh
- Yale University, New Haven, Connecticut 06520
| | - V A Okorokov
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - D Olvitt
- Temple University, Philadelphia, Pennsylvania 19122
| | - B S Page
- Brookhaven National Laboratory, Upton, New York 11973
| | - R Pak
- Brookhaven National Laboratory, Upton, New York 11973
| | - Y Panebratsev
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - B Pawlik
- Institute of Nuclear Physics PAN, Cracow 31-342, Poland
| | - H Pei
- Central China Normal University, Wuhan, Hubei 430079
| | - C Perkins
- University of California, Berkeley, California 94720
| | - R L Pinter
- Eötvös Loránd University, Budapest, Hungary H-1117
| | - J Pluta
- Warsaw University of Technology, Warsaw 00-661, Poland
| | - J Porter
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - M Posik
- Temple University, Philadelphia, Pennsylvania 19122
| | - N K Pruthi
- Panjab University, Chandigarh 160014, India
| | - M Przybycien
- AGH University of Science and Technology, FPACS, Cracow 30-059, Poland
| | - J Putschke
- Wayne State University, Detroit, Michigan 48201
| | - A Quintero
- Temple University, Philadelphia, Pennsylvania 19122
| | | | | | - R L Ray
- University of Texas, Austin, Texas 78712
| | - R Reed
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - H G Ritter
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | | | | | - J L Romero
- University of California, Davis, California 95616
| | - L Ruan
- Brookhaven National Laboratory, Upton, New York 11973
| | - J Rusnak
- Nuclear Physics Institute AS CR, Prague 250 68, Czech Republic
| | - O Rusnakova
- Czech Technical University in Prague, FNSPE, Prague 115 19, Czech Republic
| | - N R Sahoo
- Texas A&M University, College Station, Texas 77843
| | - P K Sahu
- Institute of Physics, Bhubaneswar 751005, India
| | - S Salur
- Rutgers University, Piscataway, New Jersey 08854
| | - J Sandweiss
- Yale University, New Haven, Connecticut 06520
| | | | - A M Schmah
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - W B Schmidke
- Brookhaven National Laboratory, Upton, New York 11973
| | - N Schmitz
- Max-Planck-Institut für Physik, Munich 80805, Germany
| | - B R Schweid
- State University of New York, Stony Brook, New York 11794
| | - F Seck
- Technische Universität Darmstadt, Darmstadt 64289, Germany
| | - J Seger
- Creighton University, Omaha, Nebraska 68178
| | - M Sergeeva
- University of California, Los Angeles, California 90095
| | - R Seto
- University of California, Riverside, California 92521
| | - P Seyboth
- Max-Planck-Institut für Physik, Munich 80805, Germany
| | - N Shah
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - E Shahaliev
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | | | - M Shao
- University of Science and Technology of China, Hefei, Anhui 230026
| | - F Shen
- Shandong University, Qingdao, Shandong 266237
| | - W Q Shen
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - S S Shi
- Central China Normal University, Wuhan, Hubei 430079
| | - Q Y Shou
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - E P Sichtermann
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - S Siejka
- Warsaw University of Technology, Warsaw 00-661, Poland
| | - R Sikora
- AGH University of Science and Technology, FPACS, Cracow 30-059, Poland
| | - M Simko
- Nuclear Physics Institute AS CR, Prague 250 68, Czech Republic
| | - J Singh
- Panjab University, Chandigarh 160014, India
| | - S Singha
- Kent State University, Kent, Ohio 44242
| | - D Smirnov
- Brookhaven National Laboratory, Upton, New York 11973
| | - N Smirnov
- Yale University, New Haven, Connecticut 06520
| | - W Solyst
- Indiana University, Bloomington, Indiana 47408
| | - P Sorensen
- Brookhaven National Laboratory, Upton, New York 11973
| | - H M Spinka
- Argonne National Laboratory, Argonne, Illinois 60439
| | - B Srivastava
- Purdue University, West Lafayette, Indiana 47907
| | | | - D J Stewart
- Yale University, New Haven, Connecticut 06520
| | - M Strikhanov
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | | | - A A P Suaide
- Universidade de São Paulo, São Paulo, Brazil 05314-970
| | - T Sugiura
- University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan
| | - M Sumbera
- Nuclear Physics Institute AS CR, Prague 250 68, Czech Republic
| | - B Summa
- Pennsylvania State University, University Park, Pennsylvania 16802
| | - X M Sun
- Central China Normal University, Wuhan, Hubei 430079
| | - X Sun
- Central China Normal University, Wuhan, Hubei 430079
| | - Y Sun
- University of Science and Technology of China, Hefei, Anhui 230026
| | - B Surrow
- Temple University, Philadelphia, Pennsylvania 19122
| | - D N Svirida
- Alikhanov Institute for Theoretical and Experimental Physics, Moscow 117218, Russia
| | - P Szymanski
- Warsaw University of Technology, Warsaw 00-661, Poland
| | - A H Tang
- Brookhaven National Laboratory, Upton, New York 11973
| | - Z Tang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - A Taranenko
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - T Tarnowsky
- Michigan State University, East Lansing, Michigan 48824
| | - J H Thomas
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | | | - D Tlusty
- Rice University, Houston, Texas 77251
| | - T Todoroki
- Brookhaven National Laboratory, Upton, New York 11973
| | - M Tokarev
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | - C A Tomkiel
- Lehigh University, Bethlehem, Pennsylvania 18015
| | - S Trentalange
- University of California, Los Angeles, California 90095
| | - R E Tribble
- Texas A&M University, College Station, Texas 77843
| | - P Tribedy
- Brookhaven National Laboratory, Upton, New York 11973
| | | | - O D Tsai
- University of California, Los Angeles, California 90095
| | - B Tu
- Central China Normal University, Wuhan, Hubei 430079
| | - T Ullrich
- Brookhaven National Laboratory, Upton, New York 11973
| | - D G Underwood
- Argonne National Laboratory, Argonne, Illinois 60439
| | - I Upsal
- Brookhaven National Laboratory, Upton, New York 11973
- Shandong University, Qingdao, Shandong 266237
| | - G Van Buren
- Brookhaven National Laboratory, Upton, New York 11973
| | - J Vanek
- Nuclear Physics Institute AS CR, Prague 250 68, Czech Republic
| | - A N Vasiliev
- Institute of High Energy Physics, Protvino 142281, Russia
| | - I Vassiliev
- Frankfurt Institute for Advanced Studies FIAS, Frankfurt 60438, Germany
| | - F Videbæk
- Brookhaven National Laboratory, Upton, New York 11973
| | - S Vokal
- Joint Institute for Nuclear Research, Dubna 141 980, Russia
| | | | - A Vossen
- Indiana University, Bloomington, Indiana 47408
| | - F Wang
- Purdue University, West Lafayette, Indiana 47907
| | - G Wang
- University of California, Los Angeles, California 90095
| | - P Wang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - Y Wang
- Central China Normal University, Wuhan, Hubei 430079
| | - Y Wang
- Tsinghua University, Beijing 100084
| | - J C Webb
- Brookhaven National Laboratory, Upton, New York 11973
| | - L Wen
- University of California, Los Angeles, California 90095
| | - G D Westfall
- Michigan State University, East Lansing, Michigan 48824
| | - H Wieman
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - S W Wissink
- Indiana University, Bloomington, Indiana 47408
| | - R Witt
- United States Naval Academy, Annapolis, Maryland 21402
| | - Y Wu
- Kent State University, Kent, Ohio 44242
| | - Z G Xiao
- Tsinghua University, Beijing 100084
| | - G Xie
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - W Xie
- Purdue University, West Lafayette, Indiana 47907
| | - J Xu
- Central China Normal University, Wuhan, Hubei 430079
| | - N Xu
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - Q H Xu
- Shandong University, Qingdao, Shandong 266237
| | - Y F Xu
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - Z Xu
- Brookhaven National Laboratory, Upton, New York 11973
| | - C Yang
- Shandong University, Qingdao, Shandong 266237
| | - Q Yang
- Shandong University, Qingdao, Shandong 266237
| | - S Yang
- Brookhaven National Laboratory, Upton, New York 11973
| | - Y Yang
- National Cheng Kung University, Tainan 70101
| | - Z Ye
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - Z Ye
- University of Illinois at Chicago, Chicago, Illinois 60607
| | - L Yi
- Shandong University, Qingdao, Shandong 266237
| | - K Yip
- Brookhaven National Laboratory, Upton, New York 11973
| | - I-K Yoo
- Pusan National University, Pusan 46241, Korea
| | - N Yu
- Central China Normal University, Wuhan, Hubei 430079
| | - H Zbroszczyk
- Warsaw University of Technology, Warsaw 00-661, Poland
| | - W Zha
- University of Science and Technology of China, Hefei, Anhui 230026
| | - J Zhang
- Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - J Zhang
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000
| | - L Zhang
- Central China Normal University, Wuhan, Hubei 430079
| | - S Zhang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - S Zhang
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | | | - Y Zhang
- University of Science and Technology of China, Hefei, Anhui 230026
| | - Z Zhang
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - J Zhao
- Purdue University, West Lafayette, Indiana 47907
| | - C Zhong
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - C Zhou
- Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800
| | - X Zhu
- Tsinghua University, Beijing 100084
| | - Z Zhu
- Shandong University, Qingdao, Shandong 266237
| | - M Zyzak
- Frankfurt Institute for Advanced Studies FIAS, Frankfurt 60438, Germany
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48
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Wang Q, Rao HY, Yu N, Gao SQ, Wei L. [Comorbidities and concomitant medication use in adult patients with chronic hepatitis C: a descriptive epidemiological analysis]. Zhonghua Gan Zang Bing Za Zhi 2019; 26:225-232. [PMID: 29804396 DOI: 10.3760/cma.j.issn.1007-3418.2018.03.011] [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: 11/05/2022]
Abstract
Objective: To analyze the comorbidity and concomitant medications use in adult patients with chronic hepatitis C. Methods: A descriptive epidemiological methods was carried out in adult patients with chronic hepatitis C and data from 2013 to 2015 were accessed through the China Medical Insurance database. Results: Among a chronic HCV cohort of 2 958 cases, the top five comorbidities were diabetes, hypertension, ischemic heart disease, gastroduodenitis, and co-infection with HBV and HCV. The three most common concomitant medications prescribed for mentioned comorbidities were acarbose, metformin and repaglinide (Diabetes), nifedipine, amlodipine and metoprolol (Hypertension), aspirin, nifedipine and amlodipine (Ischemic heart disease), omeprazole, pantoprazole and levolfoxacin (Gastroduodenitis), ribavirin, pegylated interferon alpha-2a and alpha-2b ( Co- infected with hepatitis B and C virus). Conclusion: The five most frequent comorbidities in adult patients with chronic hepatitis C are diabetes, hypertension, ischemic heart disease, gastroduodenitis, and co-infection with HBV and HCV. A concomitant medication use in those patients with comorbidities causes potential drug-drug interactions.
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Affiliation(s)
- Q Wang
- Peking University People's Hospital, Peking University Hepatology Institute, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Diseases, Beijing 100044, China
| | - H Y Rao
- Peking University People's Hospital, Peking University Hepatology Institute, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Diseases, Beijing 100044, China
| | - N Yu
- Beijing Brainpower Pharma Consulting, Beijing 100021, China
| | - S Q Gao
- Beijing North Medical & Health Economics Research Center, Beijing 100021, China
| | - L Wei
- Peking University People's Hospital, Peking University Hepatology Institute, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Diseases, Beijing 100044, China
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49
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Overvig AC, Shrestha S, Malek SC, Lu M, Stein A, Zheng C, Yu N. Dielectric metasurfaces for complete and independent control of the optical amplitude and phase. Light Sci Appl 2019; 8:92. [PMID: 31666948 PMCID: PMC6804926 DOI: 10.1038/s41377-019-0201-7] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 09/06/2019] [Accepted: 09/10/2019] [Indexed: 05/03/2023]
Abstract
Metasurfaces are optically thin metamaterials that promise complete control of the wavefront of light but are primarily used to control only the phase of light. Here, we present an approach, simple in concept and in practice, that uses meta-atoms with a varying degree of form birefringence and rotation angles to create high-efficiency dielectric metasurfaces that control both the optical amplitude and phase at one or two frequencies. This opens up applications in computer-generated holography, allowing faithful reproduction of both the phase and amplitude of a target holographic scene without the iterative algorithms required in phase-only holography. We demonstrate all-dielectric metasurface holograms with independent and complete control of the amplitude and phase at up to two optical frequencies simultaneously to generate two- and three-dimensional holographic objects. We show that phase-amplitude metasurfaces enable a few features not attainable in phase-only holography; these include creating artifact-free two-dimensional holographic images, encoding phase and amplitude profiles separately at the object plane, encoding intensity profiles at the metasurface and object planes separately, and controlling the surface textures of three-dimensional holographic objects.
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Affiliation(s)
- Adam C. Overvig
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027 USA
| | - Sajan Shrestha
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027 USA
| | - Stephanie C. Malek
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027 USA
| | - Ming Lu
- Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, NY 11973 USA
| | - Aaron Stein
- Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, NY 11973 USA
| | - Changxi Zheng
- Department of Computer Science, Columbia University, New York, NY 10027 USA
| | - Nanfang Yu
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027 USA
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50
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Adam J, Adamczyk L, Adams J, Adkins J, Agakishiev G, Aggarwal M, Ahammed Z, Alekseev I, Anderson D, Aoyama R, Aparin A, Arkhipkin D, Aschenauer E, Ashraf M, Atetalla F, Attri A, Averichev G, Bai X, Bairathi V, Barish K, Bassill A, Behera A, Bellwied R, Bhasin A, Bhati A, Bielcik J, Bielcikova J, Bland L, Bordyuzhin I, Brandenburg J, Brandin A, Brown D, Bryslawskyj J, Bunzarov I, Butterworth J, Caines H, Calderón de la Barca Sánchez M, Cebra D, Cendejas R, Chakaberia I, Chaloupka P, Chan B, Chang FH, Chang Z, Chankova-Bunzarova N, Chatterjee A, Chattopadhyay S, Chen J, Chen X, Chen X, Cheng J, Cherney M, Christie W, Contin G, Crawford H, Csanad M, Das S, Dedovich T, Deng J, Deppner I, Derevschikov A, Didenko L, Dilks C, Dong X, Drachenberg J, Dunlop J, Efimov L, Elsey N, Engelage J, Eppley G, Esha R, Esumi S, Evdokimov O, Ewigleben J, Eyser O, Fatemi R, Fazio S, Federic P, Federicova P, Fedorisin J, Filip P, Finch E, Fisyak Y, Flores C, Fulek L, Gagliardi C, Galatyuk T, Geurts F, Gibson A, Grosnick D, Gunarathne D, Guo Y, Gupta A, Guryn W, Hamad A, Hamed A, Harlenderova A, Harris J, He L, Heppelmann S, Heppelmann S, Herrmann N, Hirsch A, Holub L, Hong Y, Horvat S, Huang B, Huang H, Huang S, Huang T, Huang X, Humanic T, Huo P, Igo G, Jacobs W, Jentsch A, Jia J, Jiang K, Jowzaee S, Ju X, Judd E, Kabana S, Kagamaster S, Kalinkin D, Kang K, Kapukchyan D, Kauder K, Ke H, Keane D, Kechechyan A, Kikoła D, Kim C, Kinghorn T, Kisel I, Kisiel A, Kochenda L, Kosarzewski L, Kraishan A, Kramarik L, Krauth L, Kravtsov P, Krueger K, Kulathunga N, Kumar L, Kunnawalkam Elayavalli R, Kvapil J, Kwasizur J, Lacey R, Landgraf J, Lauret J, Lebedev A, Lednicky R, Lee J, Li C, Li W, Li X, Li Y, Liang Y, Lidrych J, Lin T, Lipiec A, Lisa M, Liu F, Liu H, Liu P, Liu P, Liu Y, Liu Z, Ljubicic T, Llope W, Lomnitz M, Longacre R, Luo S, Luo X, Ma G, Ma L, Ma R, Ma Y, Magdy N, Majka R, Mallick D, Margetis S, Markert C, Matis H, Matonoha O, Mazer J, Meehan K, Mei J, Minaev N, Mioduszewski S, Mishra D, Mohanty B, Mondal M, Mooney I, Morozov D, Nasim M, Negrete J, Nelson J, Nemes D, Nie M, Nigmatkulov G, Niida T, Nogach L, Nonaka T, Odyniec G, Ogawa A, Oh K, Oh S, Okorokov V, Olvitt D, Page B, Pak R, Panebratsev Y, Pawlik B, Pei H, Perkins C, Pinter R, Pluta J, Porter J, Posik M, Pruthi N, Przybycien M, Putschke J, Quintero A, Radhakrishnan S, Ramachandran S, Ray R, Reed R, Ritter H, Roberts J, Rogachevskiy O, Romero J, Ruan L, Rusnak J, Rusnakova O, Sahoo N, Sahu P, Salur S, Sandweiss J, Schambach J, Schmah A, Schmidke W, Schmitz N, Schweid B, Seck F, Seger J, Sergeeva M, Seto R, Seyboth P, Shah N, Shahaliev E, Shanmuganathan P, Shao M, Shen F, Shen W, Shi S, Shou Q, Sichtermann E, Siejka S, Sikora R, Simko M, Singh J, Singha S, Smirnov D, Smirnov N, Solyst W, Sorensen P, Spinka H, Srivastava B, Stanislaus T, Stewart D, Strikhanov M, Stringfellow B, Suaide A, Sugiura T, Sumbera M, Summa B, Sun X, Sun X, Sun Y, Surrow B, Svirida D, Szymanski P, Tang A, Tang Z, Taranenko A, Tarnowsky T, Thomas J, Timmins A, Tlusty D, Todoroki T, Tokarev M, Tomkiel C, Trentalange S, Tribble R, Tribedy P, Tripathy S, Tsai O, Tu B, Ullrich T, Underwood D, Upsal I, Van Buren G, Vanek J, Vasiliev A, Vassiliev I, Videbæk F, Vokal S, Voloshin S, Vossen A, Wang F, Wang G, Wang P, Wang Y, Wang Y, Webb J, Wen L, Westfall G, Wieman H, Wissink S, Witt R, Wu Y, Xiao Z, Xie G, Xie W, Xu J, Xu N, Xu Q, Xu Y, Xu Z, Yang C, Yang Q, Yang S, Yang Y, Ye Z, Ye Z, Yi L, Yip K, Yoo IK, Yu N, Zbroszczyk H, Zha W, Zhang J, Zhang J, Zhang L, Zhang S, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao J, Zhong C, Zhou C, Zhu X, Zhu Z, Zyzak M. Improved measurement of the longitudinal spin transfer to
Λ
and
Λ¯
hyperons in polarized proton-proton collisions at
s=200 GeV. Int J Clin Exp Med 2018. [DOI: 10.1103/physrevd.98.112009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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