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Yuan Y, Tan M, Zhou M, Hassan MJ, Lin L, Lin J, Zhang Y, Li Z. Drought priming-induced stress memory improves subsequent drought or heat tolerance via activation of γ-aminobutyric acid-regulated pathways in creeping bentgrass. Plant Biol (Stuttg) 2024. [PMID: 38509772 DOI: 10.1111/plb.13636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 02/14/2024] [Indexed: 03/22/2024]
Abstract
Recurrent drought can induce stress memory in plants to induce tolerance to subsequent stress, such as high temperature or drought. Drought priming (DP) is an effective approach to improve tolerance to various stresses; however, the potential mechanism of DP-induced stress memory has not been fully resoved. We examined DP-regulated subsequent drought tolerance or thermotolerance associated with changes in physiological responses, GABA and NO metabolism, heat shock factor (HSF) and dehydrin (DHN) pathways in perennial creeping bentgrass. Plants can recover after two cycle of DP, and DP-treated plants had significantly higher tolerance to subsequent drought or heat stress, with higher leaf RWC, Chl content, photochemical efficiency, and cell membrane stability. DP significantly alleviated oxidative damage through enhancing total antioxidant capacity in response to subsequent drought or heat stress. Endogenous GABA was significantly increased by DP through activating glutamic acid decarboxylase activity and inhibiting GABA transaminase activity. DP also enhanced accumulation of NO, depending on NOS activity, under subsequent drought or heat stress. Transcript levels of multiple transcription factors, heat shock proteins, and DHNs in the HSF and DHN pathways were up-regulated by DP under drought or heat stress, but there were differences between DP-regulated heat tolerance and drought tolerance in these pathways. The findings indicate that under recurrent moderate drought, DP improves subsequent tolerance to drought or heat stress in relation to GABA-regulated pathways, providing new insight into understanding of the role of stress memory in plant adaptation to complex environmental stresses.
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Affiliation(s)
- Y Yuan
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - M Tan
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - M Zhou
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - M J Hassan
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - L Lin
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - J Lin
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Y Zhang
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Z Li
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China
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2
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de Silva TA, Apte S, Voisey J, Spann K, Tan M, Chambers D, O'Sullivan B. Immunological Landscapes in Lung Transplantation: Insights from T Cell Profiling in BAL and PBMC. Int J Mol Sci 2024; 25:2476. [PMID: 38473722 DOI: 10.3390/ijms25052476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 02/05/2024] [Accepted: 02/15/2024] [Indexed: 03/14/2024] Open
Abstract
Lung transplant recipients frequently encounter immune-related complications, including chronic lung allograft dysfunction (CLAD). Monitoring immune cells within the lung microenvironment is pivotal for optimizing post-transplant outcomes. This study examined the proportion of T cell subsets in paired bronchoalveolar lavage (BAL) and peripheral PBMC comparing healthy (n = 4) and lung transplantation patients (n = 6, no CLAD and n = 14 CLAD) using 14-color flow cytometry. CD4+ T cell proportions were reduced in CD3 cells in both PBMC and BAL, and positive correlations were discerned between T cell populations in peripheral PBMC and BAL, suggesting the prospect of employing less invasive PBMC sampling as a means of monitoring lung T cells. Furthermore, regulatory T cells (Tregs) were enriched in BAL when compared to peripheral PBMC for transplant recipients. A parallel positive correlation emerged between Treg proportions in BAL and peripheral PBMC, underscoring potential avenues for monitoring lung Tregs. Finally, the most promising biomarker was the Teff (CD8+Granzyme B+)-Treg ratio, which was higher in both the PBMC and BAL of transplant recipients compared to healthy individuals, and increased in the patients with CLAD compared to no CLAD and healthy patients. Conclusions: Distinct T cell profiles in BAL and peripheral PBMC underscore the significance of localized immune monitoring in lung transplantation. The Teff (CD8+granzyme B+)-Treg ratio, particularly within the context of CLAD, emerges as a promising blood and BAL biomarker reflective of inflammation and transplant-related complications. These findings emphasize the imperative need for personalized immune monitoring strategies that tailored to address the unique immunological milieu in post-transplant lungs.
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Affiliation(s)
- Tharushi Ayanthika de Silva
- Centre for Genomics and Personalised Health, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Brisbane, QLD 4001, Australia
| | - Simon Apte
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Brisbane, QLD 4001, Australia
- Facility of Clinical Medicine, The University of Queensland, Brisbane, QLD 4001, Australia
| | - Joanne Voisey
- Centre for Genomics and Personalised Health, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia
| | - Kirsten Spann
- Centre for Immunology and Infection Control, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia
| | - Maxine Tan
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Brisbane, QLD 4001, Australia
- Facility of Clinical Medicine, The University of Queensland, Brisbane, QLD 4001, Australia
| | - Daniel Chambers
- Centre for Genomics and Personalised Health, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Brisbane, QLD 4001, Australia
- Facility of Clinical Medicine, The University of Queensland, Brisbane, QLD 4001, Australia
| | - Brendan O'Sullivan
- Centre for Genomics and Personalised Health, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Brisbane, QLD 4001, Australia
- Facility of Clinical Medicine, The University of Queensland, Brisbane, QLD 4001, Australia
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3
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Yu F, Fu J, Tan M, Xu R, Tian Y, Jia L, Zhang D, Wang Q, Gao Z. Norovirus outbreaks in hospitals in China: a systematic review. J Hosp Infect 2023; 142:32-38. [PMID: 37805116 DOI: 10.1016/j.jhin.2023.09.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 10/09/2023]
Abstract
BACKGROUND Norovirus outbreaks in hospitals can potentially impair patient care and result in significant financial expenses. There is currently limited information on hospital norovirus outbreaks in the Chinese mainland. AIM To systematically review the published literature to describe the characteristics of norovirus outbreaks in Chinese mainland hospitals to facilitate prompt identification and control of outbreaks. METHODS A systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis standards. Databases including PubMed, Web of Science, and Chinese Journals Online databases (China National Knowledge Infrastructure (CNKI), Chinese Wan Fang digital database (WANFANG) were searched from inception to July 18th, 2022. FINDINGS A total of 41 norovirus Chinese hospital outbreaks occurring before July 18th, 2022 were reported in 32 articles. Most reported outbreaks were from Shanghai and Beijing, and occurred in December and January. Cases were mainly adults. The male:female ratio was 1.22:1. The majority of cases in norovirus outbreaks were hospitalized patients (56.82%); medical staff were affected in 15 outbreaks. Norovirus outbreaks occurred in both private and public hospitals, and in secondary and tertiary care centres, and occurred mainly in internal medicine and geriatric departments. Person-to-person transmission was the primary transmission mode and GII was more prevalent. CONCLUSION Norovirus outbreaks in hospitals can affect both patients and healthcare workers, sometimes causing serious financial losses. In order to have a more complete understanding of the disease burden caused by norovirus outbreaks, surveillance needs to be established in hospitals.
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Affiliation(s)
- F Yu
- The University of Hong Kong, School of Public Health, Hong Kong, China
| | - J Fu
- China Medical University, School of Public Health, Shenyang, China
| | - M Tan
- China Medical University, School of Public Health, Shenyang, China
| | - R Xu
- China Medical University, School of Public Health, Shenyang, China
| | - Y Tian
- China Medical University, School of Public Health, Shenyang, China
| | - L Jia
- Beijing Center for Disease Prevention and Control, Beijing, China
| | - D Zhang
- Beijing Center for Disease Prevention and Control, Beijing, China
| | - Q Wang
- Beijing Center for Disease Prevention and Control, Beijing, China
| | - Z Gao
- Beijing Center for Disease Prevention and Control, Beijing, China.
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Ye Z, Nguyen TL, Dite GS, MacInnis RJ, Schmidt DF, Makalic E, Al-Qershi OM, Bui M, Esser VFC, Dowty JG, Trinh HN, Evans CF, Tan M, Sung J, Jenkins MA, Giles GG, Southey MC, Hopper JL, Li S. Causal relationships between breast cancer risk factors based on mammographic features. Breast Cancer Res 2023; 25:127. [PMID: 37880807 PMCID: PMC10598934 DOI: 10.1186/s13058-023-01733-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/17/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology. METHODS We used digitised mammograms for 371 monozygotic twin pairs, aged 40-70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method. RESULTS The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22-0.81; all P < 0.005). We estimated that 28-92% of the associations between the risk scores could be attributed to causal relationships between the scores, with the rest attributed to familial confounders shared by the scores. There was consistent evidence for positive causal effects: of Cirrus, light areas, and bright areas on the brightest areas (accounting for 34%, 55%, and 85% of the associations, respectively); and of light areas and bright areas on Cirrus (accounting for 37% and 28%, respectively). CONCLUSIONS In a mammogram, the lighter (less dense) areas have a causal effect on the brightest (highly dense) areas, including through a causal pathway via textural features. These causal relationships help us gain insight into the relative aetiological importance of different mammographic features in breast cancer. For example our findings are consistent with the brightest areas being more aetiologically important than lighter areas for screen-detected breast cancer; conversely, light areas being more aetiologically important for interval breast cancer. Additionally, specific textural features capture aetiologically independent breast cancer risk information from dense areas. These findings highlight the utility of ICE FALCON and family data in decomposing the associations between intercorrelated disease biomarkers into distinct biological pathways.
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Affiliation(s)
- Zhoufeng Ye
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Tuong L Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
- Genetic Technologies Limited, Fitzroy, VIC, 3065, Australia
| | - Robert J MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia
| | - Daniel F Schmidt
- Department of Data Science and AI, Faculty of IT, Monash University, Melbourne, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Osamah M Al-Qershi
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Minh Bui
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Vivienne F C Esser
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - James G Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Ho N Trinh
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Christopher F Evans
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Maxine Tan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, 47500, Sunway City, Malaysia
- School of Electrical and Computer Engineering, The University of Oklahoma, Norman, OK, 73019, USA
| | - Joohon Sung
- Department of Public Health Sciences, Division of Genome and Health Big Data, Graduate School of Public Health, Seoul National University, Seoul, 08826, Korea
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia
| | - Melissa C Southey
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia
- Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia.
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia.
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, CB1 8RN, UK.
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, VIC, 3051, Australia.
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5
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de Silva TA, Apte S, Voisey J, Spann K, Tan M, Divithotawela C, Chambers D, O’Sullivan B. Single-Cell Profiling of Cells in the Lung of a Patient with Chronic Hypersensitivity Pneumonitis Reveals Inflammatory Niche with Abundant CD39+ T Cells with Functional ATPase Phenotype: A Case Study. Int J Mol Sci 2023; 24:14442. [PMID: 37833889 PMCID: PMC10572861 DOI: 10.3390/ijms241914442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/13/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
This study investigated immune cell characteristics in chronic hypersensitivity pneumonitis (HP), focusing on CD39-expressing cells' impact on inflammation and tissue remodelling. Lung tissue from an HP patient was analysed using single-cell transcriptomics, flow cytometry, and gene expression profiling. The tissue revealed diverse cell types like macrophages, T cells, fibroblasts, and regulatory T cells (Tregs). CD39-expressing Tregs exhibited heightened ATP hydrolysis capacity and regulatory gene expression. CD39hi cells displayed markers of both Tregs and proinflammatory Th17 cells, suggesting transitional properties. Communication networks involving molecules like SPP1, collagen, CSF1, and IL-1β were identified, hinting at interactions between cell types in HP pathogenesis. This research provides insights into the immune response and cell interactions in chronic HP. CD39-expressing cells dual nature as Tregs and Th17 cells suggests a role in modulating lung inflammation, potentially affecting disease progression. These findings lay the groundwork for further research, underscoring CD39-expressing cells as potential therapeutic targets in HP.
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Affiliation(s)
- Tharushi Ayanthika de Silva
- Centre for Genomics and Personalised Health, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4000, Australia
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD 4000, Australia
| | - Simon Apte
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD 4000, Australia
- Facility of Clinical Medicine, The University of Queensland, Brisbane, QLD 4000, Australia
| | - Joanne Voisey
- Centre for Genomics and Personalised Health, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4000, Australia
| | - Kirsten Spann
- Centre for Immunology and Infection Control, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4000, Australia
| | - Maxine Tan
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD 4000, Australia
- Facility of Clinical Medicine, The University of Queensland, Brisbane, QLD 4000, Australia
| | - Chandima Divithotawela
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD 4000, Australia
| | - Daniel Chambers
- Centre for Genomics and Personalised Health, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4000, Australia
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD 4000, Australia
- Facility of Clinical Medicine, The University of Queensland, Brisbane, QLD 4000, Australia
| | - Brendan O’Sullivan
- Centre for Genomics and Personalised Health, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4000, Australia
- Queensland Lung Transplant Service, Ground Floor, Clinical Sciences Building, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD 4000, Australia
- Facility of Clinical Medicine, The University of Queensland, Brisbane, QLD 4000, Australia
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6
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Aalbers J, Akerib DS, Akerlof CW, Al Musalhi AK, Alder F, Alqahtani A, Alsum SK, Amarasinghe CS, Ames A, Anderson TJ, Angelides N, Araújo HM, Armstrong JE, Arthurs M, Azadi S, Bailey AJ, Baker A, Balajthy J, Balashov S, Bang J, Bargemann JW, Barry MJ, Barthel J, Bauer D, Baxter A, Beattie K, Belle J, Beltrame P, Bensinger J, Benson T, Bernard EP, Bhatti A, Biekert A, Biesiadzinski TP, Birch HJ, Birrittella B, Blockinger GM, Boast KE, Boxer B, Bramante R, Brew CAJ, Brás P, Buckley JH, Bugaev VV, Burdin S, Busenitz JK, Buuck M, Cabrita R, Carels C, Carlsmith DL, Carlson B, Carmona-Benitez MC, Cascella M, Chan C, Chawla A, Chen H, Cherwinka JJ, Chott NI, Cole A, Coleman J, Converse MV, Cottle A, Cox G, Craddock WW, Creaner O, Curran D, Currie A, Cutter JE, Dahl CE, David A, Davis J, Davison TJR, Delgaudio J, Dey S, de Viveiros L, Dobi A, Dobson JEY, Druszkiewicz E, Dushkin A, Edberg TK, Edwards WR, Elnimr MM, Emmet WT, Eriksen SR, Faham CH, Fan A, Fayer S, Fearon NM, Fiorucci S, Flaecher H, Ford P, Francis VB, Fraser ED, Fruth T, Gaitskell RJ, Gantos NJ, Garcia D, Geffre A, Gehman VM, Genovesi J, Ghag C, Gibbons R, Gibson E, Gilchriese MGD, Gokhale S, Gomber B, Green J, Greenall A, Greenwood S, van der Grinten MGD, Gwilliam CB, Hall CR, Hans S, Hanzel K, Harrison A, Hartigan-O'Connor E, Haselschwardt SJ, Hernandez MA, Hertel SA, Heuermann G, Hjemfelt C, Hoff MD, Holtom E, Hor JYK, Horn M, Huang DQ, Hunt D, Ignarra CM, Jacobsen RG, Jahangir O, James RS, Jeffery SN, Ji W, Johnson J, Kaboth AC, Kamaha AC, Kamdin K, Kasey V, Kazkaz K, Keefner J, Khaitan D, Khaleeq M, Khazov A, Khurana I, Kim YD, Kocher CD, Kodroff D, Korley L, Korolkova EV, Kras J, Kraus H, Kravitz S, Krebs HJ, Kreczko L, Krikler B, Kudryavtsev VA, Kyre S, Landerud B, Leason EA, Lee C, Lee J, Leonard DS, Leonard R, Lesko KT, Levy C, Li J, Liao FT, Liao J, Lin J, Lindote A, Linehan R, Lippincott WH, Liu R, Liu X, Liu Y, Loniewski C, Lopes MI, Lopez Asamar E, López Paredes B, Lorenzon W, Lucero D, Luitz S, Lyle JM, Majewski PA, Makkinje J, Malling DC, Manalaysay A, Manenti L, Mannino RL, Marangou N, Marzioni MF, Maupin C, McCarthy ME, McConnell CT, McKinsey DN, McLaughlin J, Meng Y, Migneault J, Miller EH, Mizrachi E, Mock JA, Monte A, Monzani ME, Morad JA, Morales Mendoza JD, Morrison E, Mount BJ, Murdy M, Murphy ASJ, Naim D, Naylor A, Nedlik C, Nehrkorn C, Neves F, Nguyen A, Nikoleyczik JA, Nilima A, O'Dell J, O'Neill FG, O'Sullivan K, Olcina I, Olevitch MA, Oliver-Mallory KC, Orpwood J, Pagenkopf D, Pal S, Palladino KJ, Palmer J, Pangilinan M, Parveen N, Patton SJ, Pease EK, Penning B, Pereira C, Pereira G, Perry E, Pershing T, Peterson IB, Piepke A, Podczerwinski J, Porzio D, Powell S, Preece RM, Pushkin K, Qie Y, Ratcliff BN, Reichenbacher J, Reichhart L, Rhyne CA, Richards A, Riffard Q, Rischbieter GRC, Rodrigues JP, Rodriguez A, Rose HJ, Rosero R, Rossiter P, Rushton T, Rutherford G, Rynders D, Saba JS, Santone D, Sazzad ABMR, Schnee RW, Scovell PR, Seymour D, Shaw S, Shutt T, Silk JJ, Silva C, Sinev G, Skarpaas K, Skulski W, Smith R, Solmaz M, Solovov VN, Sorensen P, Soria J, Stancu I, Stark MR, Stevens A, Stiegler TM, Stifter K, Studley R, Suerfu B, Sumner TJ, Sutcliffe P, Swanson N, Szydagis M, Tan M, Taylor DJ, Taylor R, Taylor WC, Temples DJ, Tennyson BP, Terman PA, Thomas KJ, Tiedt DR, Timalsina M, To WH, Tomás A, Tong Z, Tovey DR, Tranter J, Trask M, Tripathi M, Tronstad DR, Tull CE, Turner W, Tvrznikova L, Utku U, Va'vra J, Vacheret A, Vaitkus AC, Verbus JR, Voirin E, Waldron WL, Wang A, Wang B, Wang JJ, Wang W, Wang Y, Watson JR, Webb RC, White A, White DT, White JT, White RG, Whitis TJ, Williams M, Wisniewski WJ, Witherell MS, Wolfs FLH, Wolfs JD, Woodford S, Woodward D, Worm SD, Wright CJ, Xia Q, Xiang X, Xiao Q, Xu J, Yeh M, Yin J, Young I, Zarzhitsky P, Zuckerman A, Zweig EA. First Dark Matter Search Results from the LUX-ZEPLIN (LZ) Experiment. Phys Rev Lett 2023; 131:041002. [PMID: 37566836 DOI: 10.1103/physrevlett.131.041002] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 03/06/2023] [Accepted: 06/07/2023] [Indexed: 08/13/2023]
Abstract
The LUX-ZEPLIN experiment is a dark matter detector centered on a dual-phase xenon time projection chamber operating at the Sanford Underground Research Facility in Lead, South Dakota, USA. This Letter reports results from LUX-ZEPLIN's first search for weakly interacting massive particles (WIMPs) with an exposure of 60 live days using a fiducial mass of 5.5 t. A profile-likelihood ratio analysis shows the data to be consistent with a background-only hypothesis, setting new limits on spin-independent WIMP-nucleon, spin-dependent WIMP-neutron, and spin-dependent WIMP-proton cross sections for WIMP masses above 9 GeV/c^{2}. The most stringent limit is set for spin-independent scattering at 36 GeV/c^{2}, rejecting cross sections above 9.2×10^{-48} cm at the 90% confidence level.
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Affiliation(s)
- J Aalbers
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - D S Akerib
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - C W Akerlof
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - A K Al Musalhi
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - F Alder
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - A Alqahtani
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - S K Alsum
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - C S Amarasinghe
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - A Ames
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - T J Anderson
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - N Angelides
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - H M Araújo
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - J E Armstrong
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - M Arthurs
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - S Azadi
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - A J Bailey
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - A Baker
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - J Balajthy
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - S Balashov
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - J Bang
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - J W Bargemann
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - M J Barry
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Barthel
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - D Bauer
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - A Baxter
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - K Beattie
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Belle
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - P Beltrame
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - J Bensinger
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - T Benson
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - E P Bernard
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - A Bhatti
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - A Biekert
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - T P Biesiadzinski
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - H J Birch
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - B Birrittella
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - G M Blockinger
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - K E Boast
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - B Boxer
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - R Bramante
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - C A J Brew
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - P Brás
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - J H Buckley
- Washington University in St. Louis, Department of Physics, St. Louis, Missouri 63130-4862, USA
| | - V V Bugaev
- Washington University in St. Louis, Department of Physics, St. Louis, Missouri 63130-4862, USA
| | - S Burdin
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - J K Busenitz
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - M Buuck
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - R Cabrita
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - C Carels
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - D L Carlsmith
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - B Carlson
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - M C Carmona-Benitez
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - M Cascella
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - C Chan
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - A Chawla
- Royal Holloway, University of London, Department of Physics, Egham, TW20 0EX, United Kingdom
| | - H Chen
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J J Cherwinka
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - N I Chott
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - A Cole
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Coleman
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - M V Converse
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - A Cottle
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - G Cox
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - W W Craddock
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - O Creaner
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D Curran
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - A Currie
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - J E Cutter
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - C E Dahl
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
- Northwestern University, Department of Physics & Astronomy, Evanston, Illinois 60208-3112, USA
| | - A David
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - J Davis
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - T J R Davison
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - J Delgaudio
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - S Dey
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - L de Viveiros
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - A Dobi
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J E Y Dobson
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - E Druszkiewicz
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - A Dushkin
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - T K Edberg
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - W R Edwards
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - M M Elnimr
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - W T Emmet
- Yale University, Department of Physics, New Haven, Connecticut 06511-8499, USA
| | - S R Eriksen
- University of Bristol, H.H. Wills Physics Laboratory, Bristol, BS8 1TL, United Kingdom
| | - C H Faham
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - A Fan
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - S Fayer
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - N M Fearon
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - S Fiorucci
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - H Flaecher
- University of Bristol, H.H. Wills Physics Laboratory, Bristol, BS8 1TL, United Kingdom
| | - P Ford
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - V B Francis
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - E D Fraser
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - T Fruth
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - R J Gaitskell
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - N J Gantos
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D Garcia
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - A Geffre
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - V M Gehman
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Genovesi
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - C Ghag
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - R Gibbons
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - E Gibson
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - M G D Gilchriese
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - S Gokhale
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - B Gomber
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - J Green
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - A Greenall
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - S Greenwood
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | | | - C B Gwilliam
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - C R Hall
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - S Hans
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - K Hanzel
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - A Harrison
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - E Hartigan-O'Connor
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - S J Haselschwardt
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - M A Hernandez
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - S A Hertel
- University of Massachusetts, Department of Physics, Amherst, Massachusetts 01003-9337, USA
| | - G Heuermann
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - C Hjemfelt
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - M D Hoff
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - E Holtom
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - J Y-K Hor
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - M Horn
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - D Q Huang
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D Hunt
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - C M Ignarra
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - R G Jacobsen
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - O Jahangir
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - R S James
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - S N Jeffery
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - W Ji
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - J Johnson
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - A C Kaboth
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
- Royal Holloway, University of London, Department of Physics, Egham, TW20 0EX, United Kingdom
| | - A C Kamaha
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
- University of Califonia, Los Angeles, Department of Physics and Astronomy, Los Angeles, California 90095-1547
| | - K Kamdin
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - V Kasey
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - K Kazkaz
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - J Keefner
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - D Khaitan
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - M Khaleeq
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - A Khazov
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - I Khurana
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - Y D Kim
- IBS Center for Underground Physics (CUP), Yuseong-gu, Daejeon, Korea
| | - C D Kocher
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D Kodroff
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - L Korley
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - E V Korolkova
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - J Kras
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - H Kraus
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - S Kravitz
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - H J Krebs
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - L Kreczko
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - B Krikler
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - V A Kudryavtsev
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - S Kyre
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - B Landerud
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - E A Leason
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - C Lee
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - J Lee
- IBS Center for Underground Physics (CUP), Yuseong-gu, Daejeon, Korea
| | - D S Leonard
- IBS Center for Underground Physics (CUP), Yuseong-gu, Daejeon, Korea
| | - R Leonard
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - K T Lesko
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - C Levy
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - J Li
- IBS Center for Underground Physics (CUP), Yuseong-gu, Daejeon, Korea
| | - F-T Liao
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - J Liao
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - J Lin
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - A Lindote
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - R Linehan
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - W H Lippincott
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - R Liu
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - X Liu
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - Y Liu
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - C Loniewski
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - M I Lopes
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - E Lopez Asamar
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - B López Paredes
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - W Lorenzon
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - D Lucero
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - S Luitz
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - J M Lyle
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - P A Majewski
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - J Makkinje
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D C Malling
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - A Manalaysay
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - L Manenti
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - R L Mannino
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - N Marangou
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - M F Marzioni
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - C Maupin
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - M E McCarthy
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - C T McConnell
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D N McKinsey
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - J McLaughlin
- Northwestern University, Department of Physics & Astronomy, Evanston, Illinois 60208-3112, USA
| | - Y Meng
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - J Migneault
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - E H Miller
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - E Mizrachi
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - J A Mock
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - A Monte
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - M E Monzani
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
- Vatican Observatory, Castel Gandolfo, V-00120, Vatican City State
| | - J A Morad
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - J D Morales Mendoza
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - E Morrison
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - B J Mount
- Black Hills State University, School of Natural Sciences, Spearfish, South Dakota 57799-0002, USA
| | - M Murdy
- University of Massachusetts, Department of Physics, Amherst, Massachusetts 01003-9337, USA
| | - A St J Murphy
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - D Naim
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - A Naylor
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - C Nedlik
- University of Massachusetts, Department of Physics, Amherst, Massachusetts 01003-9337, USA
| | - C Nehrkorn
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - F Neves
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - A Nguyen
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - J A Nikoleyczik
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - A Nilima
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - J O'Dell
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - F G O'Neill
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - K O'Sullivan
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - I Olcina
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - M A Olevitch
- Washington University in St. Louis, Department of Physics, St. Louis, Missouri 63130-4862, USA
| | - K C Oliver-Mallory
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - J Orpwood
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - D Pagenkopf
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - S Pal
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - K J Palladino
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - J Palmer
- Royal Holloway, University of London, Department of Physics, Egham, TW20 0EX, United Kingdom
| | - M Pangilinan
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - N Parveen
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - S J Patton
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - E K Pease
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - B Penning
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - C Pereira
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - G Pereira
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - E Perry
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - T Pershing
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - I B Peterson
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - A Piepke
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - J Podczerwinski
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - D Porzio
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - S Powell
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - R M Preece
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - K Pushkin
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - Y Qie
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - B N Ratcliff
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - J Reichenbacher
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - L Reichhart
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - C A Rhyne
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - A Richards
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - Q Riffard
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - G R C Rischbieter
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - J P Rodrigues
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - A Rodriguez
- Black Hills State University, School of Natural Sciences, Spearfish, South Dakota 57799-0002, USA
| | - H J Rose
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - R Rosero
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - P Rossiter
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - T Rushton
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - G Rutherford
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D Rynders
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - J S Saba
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D Santone
- Royal Holloway, University of London, Department of Physics, Egham, TW20 0EX, United Kingdom
| | - A B M R Sazzad
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - R W Schnee
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - P R Scovell
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - D Seymour
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - S Shaw
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - T Shutt
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - J J Silk
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - C Silva
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - G Sinev
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - K Skarpaas
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - W Skulski
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - R Smith
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - M Solmaz
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - V N Solovov
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - P Sorensen
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Soria
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - I Stancu
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - M R Stark
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - A Stevens
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - T M Stiegler
- Texas A&M University, Department of Physics and Astronomy, College Station, Texas 77843-4242, USA
| | - K Stifter
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - R Studley
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - B Suerfu
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - T J Sumner
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - P Sutcliffe
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - N Swanson
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - M Szydagis
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - M Tan
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - D J Taylor
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - R Taylor
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - W C Taylor
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D J Temples
- Northwestern University, Department of Physics & Astronomy, Evanston, Illinois 60208-3112, USA
| | - B P Tennyson
- Yale University, Department of Physics, New Haven, Connecticut 06511-8499, USA
| | - P A Terman
- Texas A&M University, Department of Physics and Astronomy, College Station, Texas 77843-4242, USA
| | - K J Thomas
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D R Tiedt
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - M Timalsina
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - W H To
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - A Tomás
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - Z Tong
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - D R Tovey
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - J Tranter
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - M Trask
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - M Tripathi
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - D R Tronstad
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - C E Tull
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - W Turner
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - L Tvrznikova
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
- Yale University, Department of Physics, New Haven, Connecticut 06511-8499, USA
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - U Utku
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - J Va'vra
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - A Vacheret
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - A C Vaitkus
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - J R Verbus
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - E Voirin
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - W L Waldron
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - A Wang
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - B Wang
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - J J Wang
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - W Wang
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
- University of Massachusetts, Department of Physics, Amherst, Massachusetts 01003-9337, USA
| | - Y Wang
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - J R Watson
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - R C Webb
- Texas A&M University, Department of Physics and Astronomy, College Station, Texas 77843-4242, USA
| | - A White
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D T White
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - J T White
- Texas A&M University, Department of Physics and Astronomy, College Station, Texas 77843-4242, USA
| | - R G White
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - T J Whitis
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - M Williams
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - W J Wisniewski
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - M S Witherell
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - F L H Wolfs
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - J D Wolfs
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - S Woodford
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - D Woodward
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - S D Worm
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - C J Wright
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - Q Xia
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - X Xiang
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - Q Xiao
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - J Xu
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - M Yeh
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - J Yin
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - I Young
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - P Zarzhitsky
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - A Zuckerman
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - E A Zweig
- University of Califonia, Los Angeles, Department of Physics and Astronomy, Los Angeles, California 90095-1547
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Tan M, Ma W, Yang Y, Duan S, Jin L, Wu Y, Li M. Predictive value of peritumour radiomics in the diagnosis of benign and malignant pulmonary nodules with halo sign. Clin Radiol 2023; 78:e52-e62. [PMID: 36460488 DOI: 10.1016/j.crad.2022.09.130] [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: 07/12/2022] [Revised: 09/05/2022] [Accepted: 09/26/2022] [Indexed: 12/03/2022]
Abstract
AIM To evaluate peritumour radiomics in predicting benign and malignant pulmonary nodules with halo sign. MATERIALS AND METHODS In this retrospective study, 305 pulmonary nodules with halo sign (benign, 120; adenocarcinoma, 185) were collected. Manual segmentation was used to mark the gross tumour volume (GTV) and the peritumour volume (PTV) was established by uniform dilation (1 cm) of the tumour area in three dimensions. The GTV and PTV radiomic features were combined to produce the gross tumour and peritumour volume (GPTV). The minimum-redundancy maximum-relevance (mRMR) feature ranking method and least absolute shrinkage and selection operator (LASSO) algorithm were used to eliminate redundant radiomic features. Predictive models combined with clinical features and radiomic signatures were established. Multivarible logistic regression analysis was used to establish the combined model and develop a nomogram. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of the model. RESULTS In the testing cohort, the area under the ROC curve (AUC) of the GTV, PTV, and GPTV radiomic models was 0.701 (95% CI: 0.589-0.814), 0.674 (95% CI: 0.557-0.791) and 0.755 (95% CI: 0.643-0.867), respectively. The AUC of the nomogram model based on clinical and GPTV radiomic signatures was 0.804 (95% CI: 0.707-0.901). CONCLUSION The nomogram model based on clinical and GPTV radiomic signatures can better predict benign and malignant pulmonary nodules with halo signs, demonstrating that the model has potential as a convenient and effective auxiliary diagnostic tool for radiologists.
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Affiliation(s)
- M Tan
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China; Department of Radiology, Chengdu Second People's Hospital, Chengdu, China
| | - W Ma
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China; Department of Radiology, Shanghai Chest Hospital, Shanghai, China
| | - Y Yang
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - S Duan
- GE Healthcare, Shanghai, China
| | - L Jin
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Y Wu
- Department of Thoracic Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
| | - M Li
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
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Bo H, Zhang Y, Dong J, Li XY, Liu J, Tan M, Zhao X, Wang DY. [Distribution and gene characteristics of H3, H4 and H6 subtypes of low pathogenic avian influenza viruses in environment related avian influenza viruses during 2014-2021 in China]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:1549-1553. [PMID: 36372742 DOI: 10.3760/cma.j.cn112150-20220810-00803] [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: 06/16/2023]
Abstract
Objective: To analyze the characteristics of low pathogenic H3, H4 and H6 subtypes of avian influenza viruses in environment related avian influenza viruses in China from 2014 to 2021. Methods: Surveillance sites were located in 31 provinces, autonomous region and municipalities to collect environmental samples related to avian influenza, detect the nucleic acid detection of influenza A virus, isolate virus, deeply sequence, analyze pathogenicity related molecular sites, and determine the distribution and variation characteristics of common H3, H4 and H6 subtypes of avian influenza virus in different regions, places and sample types. Results: A total of 388 645 samples were collected. The positive rate of low pathogenic H3 (0.56‰) and H6 (0.53‰) was higher than that of H4 (0.09‰). The positive rate of H4 subtype virus in live poultry market was higher than that in other places, and the difference was statistically significant. The positive rate of H3 and H6 subtypes in sewage samples was higher than that in other samples, and the difference was statistically significant. The positive rate of H3, H4 and H6 viruses in the south was higher than that in the north, and the difference was statistically significant. December was the most active time for virus. The analysis of pathogenicity related molecular sites showed that H3, H4 and H6 subtypes of viruses combined with avian influenza virus receptors, and some gene sites related to increased pathogenicity had mutations. Conclusion: The H3, H4 and H6 subtypes of low pathogenic avian influenza viruses have a high isolation positive rate in the live poultry market and sewage. The distribution of the three subtypes of viruses has obvious regional and seasonal characteristics, and the genetic characteristics still show the feature of low pathogenic avian influenza.
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Affiliation(s)
- H Bo
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206,China
| | - Y Zhang
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206,China
| | - J Dong
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206,China
| | - X Y Li
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206,China
| | - J Liu
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206,China
| | - M Tan
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206,China
| | - X Zhao
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206,China
| | - D Y Wang
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206,China
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Akamatsu H, Yang JH, Wakuda K, Hawkins J, Yanes R, Homann O, Tan M, Finger E, Borghaei H. 384P Prevalence of fibroblast growth factor receptor 2b (FGFR2b) protein overexpression in squamous non-small cell lung cancer (sqNSCLC). Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.421] [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: 12/07/2022] Open
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Liew A, Lee CC, Subramaniam V, Lan BL, Tan M. Gradual Self-Training via Confidence and Volume Based Domain Adaptation for Multi Dataset Deep Learning-Based Brain Metastases Detection Using Nonlocal Networks on MRI Images. J Magn Reson Imaging 2022; 57:1728-1740. [PMID: 36208095 DOI: 10.1002/jmri.28456] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/20/2022] [Accepted: 09/20/2022] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Research suggests that treatment of multiple brain metastases (BMs) with stereotactic radiosurgery shows improvement when metastases are detected early, providing a case for BM detection capabilities on small lesions. PURPOSE To demonstrate automatic detection of BM on three MRI datasets using a deep learning-based approach. To improve the performance of the network is iteratively co-trained with datasets from different domains. A systematic approach is proposed to prevent catastrophic forgetting during co-training. STUDY TYPE Retrospective. POPULATION A total of 156 patients (105 ground truth and 51 pseudo labels) with 1502 BM (BrainMetShare); 121 patients with 722 BM (local); 400 patients with 447 primary gliomas (BrATS). Training/pseudo labels/validation data were distributed 84/51/21 (BrainMetShare). Training/validation data were split: 121/23 (local) and 375/25 (BrATS). FIELD STRENGTH/SEQUENCE A 5 T and 3 T/T1 spin-echo postcontrast (T1-gradient echo) (BrainMetShare), 3 T/T1 magnetization prepared rapid acquisition gradient echo postcontrast (T1-MPRAGE) (local), 0.5 T, 1 T, and 1.16 T/T1-weighted-fluid-attenuated inversion recovery (T1-FLAIR) (BrATS). ASSESSMENT The ground truth was manually segmented by two (BrainMetShare) and four (BrATS) radiologists and manually annotated by one (local) radiologist. Confidence and volume based domain adaptation (CAVEAT) method of co-training the three datasets on a 3D nonlocal convolutional neural network (CNN) architecture was implemented to detect BM. STATISTICAL TESTS The performance was evaluated using sensitivity and false positive rates per patient (FP/patient) and free receiver operating characteristic (FROC) analysis at seven predefined (1/8, 1/4, 1/2, 1, 2, 4, and 8) FPs per scan. RESULTS The sensitivity and FP/patient from a held-out set registered 0.811 at 2.952 FP/patient (BrainMetShare), 0.74 at 3.130 (local), and 0.723 at 2.240 (BrATS) using the CAVEAT approach with lesions as small as 1 mm being detected. DATA CONCLUSION Improved sensitivities at lower FP can be achieved by co-training datasets via the CAVEAT paradigm to address the problem of data sparsity. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Andrea Liew
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Bandar Sunway, Malaysia
| | - Chun Cheng Lee
- Radiology Department, Sunway Medical Centre, Bandar Sunway, Malaysia
| | | | - Boon Leong Lan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Bandar Sunway, Malaysia.,Advanced Engineering Platform, School of Engineering, Monash University Malaysia, Bandar Sunway, Malaysia
| | - Maxine Tan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Bandar Sunway, Malaysia.,School of Electrical and Computer Engineering, The University of Oklahoma, Norman, Oklahoma, USA
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Tan M, Dinh D, Gayed D, Liang D, Brennan A, Duffy S, Clark D, Ajani A, Oqueli E, Roberts L, Reid C, Freeman M, Chandrasekhar J. Associations between DAPT score and long-term mortality post PCI. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.1378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Introduction
The dual antiplatelet therapy (DAPT) score was developed to identify patients more likely to derive benefit (score ≥2) or harm (score <2) from DAPT beyond 1-year post PCI. There is no study which looked at the DAPT score and long term outcomes post PCI in Australia.
Purpose
We sought to examine long-term mortality after PCI by the DAPT score in patients treated with DAPT per local guidelines.
Methods
We examined data from the MIG PCI database from 2005 to 2018 in whom the DAPT score could be derived and grouped them as score ≥2 or <2. Long-term mortality was assessed from National Death Index linkage. The primary endpoint was long-term mortality examined using survival analysis. Secondary endpoints included 30-day ischaemic outcomes and in-hospital major bleeding.
Results
Out of 27,740 patients in the study, 9,401 (33.9%) had DAPT score ≥2. They were younger and included more females and higher prevalence of renal impairment. DAPT score ≥2 patients had higher in-hospital major bleeding, 30-day mortality, MI and target vessel revascularisation. DAPT score ≥2 patients had lower long-term survival to 12 years (p<0.001 for all).
Conclusion
A third of all-comer PCI patients had DAPT score ≥2 with greater short-term risk of ischaemic and bleeding outcomes, as well as long-term mortality. Theoretically, those with DAPT score ≥2 would benefit from longer duration of DAPT as ischaemic risk outweighs bleeding risk. However, given our finding of increased short-term bleeding risk and long-term mortality, dynamic bleeding risk assessment should be undertaken to guide pharmacotherapy strategies.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- M Tan
- Eastern Health , Melbourne , Australia
| | - D Dinh
- Monash University , Melbourne , Australia
| | - D Gayed
- Eastern Health , Melbourne , Australia
| | - D Liang
- Eastern Health , Melbourne , Australia
| | - A Brennan
- Monash University , Melbourne , Australia
| | - S Duffy
- Alfred Health , Melbourne , Australia
| | - D Clark
- Austin Hospital , Melbourne , Australia
| | - A Ajani
- Royal Melbourne Hospital , Melbourne , Australia
| | - E Oqueli
- Ballarat Health , Melbourne , Australia
| | - L Roberts
- Eastern Health , Melbourne , Australia
| | - C Reid
- Curtin University , Perth , Australia
| | - M Freeman
- Eastern Health , Melbourne , Australia
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Kouli O, Murray V, Bhatia S, Cambridge WA, Kawka M, Shafi S, Knight SR, Kamarajah SK, McLean KA, Glasbey JC, Khaw RA, Ahmed W, Akhbari M, Baker D, Borakati A, Mills E, Thavayogan R, Yasin I, Raubenheimer K, Ridley W, Sarrami M, Zhang G, Egoroff N, Pockney P, Richards T, Bhangu A, Creagh-Brown B, Edwards M, Harrison EM, Lee M, Nepogodiev D, Pinkney T, Pearse R, Smart N, Vohra R, Sohrabi C, Jamieson A, Nguyen M, Rahman A, English C, Tincknell L, Kakodkar P, Kwek I, Punjabi N, Burns J, Varghese S, Erotocritou M, McGuckin S, Vayalapra S, Dominguez E, Moneim J, Salehi M, Tan HL, Yoong A, Zhu L, Seale B, Nowinka Z, Patel N, Chrisp B, Harris J, Maleyko I, Muneeb F, Gough M, James CE, Skan O, Chowdhury A, Rebuffa N, Khan H, Down B, Fatimah Hussain Q, Adams M, Bailey A, Cullen G, Fu YXJ, McClement B, Taylor A, Aitken S, Bachelet B, Brousse de Gersigny J, Chang C, Khehra B, Lahoud N, Lee Solano M, Louca M, Rozenbroek P, Rozitis E, Agbinya N, Anderson E, Arwi G, Barry I, Batchelor C, Chong T, 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Wyn-Griffiths F, Brew A, Kaur G, Soni D, Tickle A, Akbar Z, Appleyard T, Figg K, Jayawardena P, Johnson A, Kamran Siddiqui Z, Lacy-Colson J, Oatham R, Rowlands B, Sludden E, Turnbull C, Allin D, Ansar Z, Azeez Z, Dale VH, Garg J, Horner A, Jones S, Knight S, McGregor C, McKenna J, McLelland T, Packham-Smith A, Rowsell K, Spector-Hill I, Adeniken E, Baker J, Bartlett M, Chikomba L, Connell B, Deekonda P, Dhar M, Elmansouri A, Gamage K, Goodhew R, Hanna P, Knight J, Luca A, Maasoumi N, Mahamoud F, Manji S, Marwaha PK, Mason F, Oluboyede A, Pigott L, Razaq AM, Richardson M, Saddaoui I, Wijeyendram P, Yau S, Atkins W, Liang K, Miles N, Praveen B, Ashai S, Braganza J, Common J, Cundy A, Davies R, Guthrie J, Handa I, Iqbal M, Ismail R, Jones C, Jones I, Lee KS, Levene A, Okocha M, Olivier J, Smith A, Subramaniam E, Tandle S, Wang A, Watson A, Wilson C, Chan XHF, Khoo E, Montgomery C, Norris M, Pugalenthi PP, Common T, Cook E, Mistry H, Shinmar HS, Agarwal G, Bandyopadhyay S, Brazier B, Carroll L, Goede A, Harbourne A, Lakhani A, Lami M, Larwood J, Martin J, Merchant J, Pattenden S, Pradhan A, Raafat N, Rothwell E, Shammoon Y, Sudarshan R, Vickers E, Wingfield L, Ashworth I, Azizi S, Bhate R, Chowdhury T, Christou A, Davies L, Dwaraknath M, Farah Y, Garner J, Gureviciute E, Hart E, Jain A, Javid S, Kankam HK, Kaur Toor P, Kaz R, Kermali M, Khan I, Mattson A, McManus A, Murphy M, Nair K, Ngemoh D, Norton E, Olabiran A, Parry L, Payne T, Pillai K, Price S, Punjabi K, Raghunathan A, Ramwell A, Raza M, Ritehnia J, Simpson G, Smith W, Sodeinde S, Studd L, Subramaniam M, Thomas J, Towey S, Tsang E, Tuteja D, Vasani J, Vio M, Badran A, Adams J, Anthony Wilkinson J, Asvandi S, Austin T, Bald A, Bix E, Carrick M, Chander B, Chowdhury S, Cooper Drake B, Crosbie S, D Portela S, Francis D, Gallagher C, Gillespie R, Gravett H, Gupta P, Ilyas C, James G, Johny J, Jones A, Kinder F, MacLeod C, Macrow C, Maqsood-Shah A, Mather J, McCann L, McMahon R, Mitham E, Mohamed M, Munton E, Nightingale K, O'Neill K, Onyemuchara I, Senior R, Shanahan A, Sherlock J, Spyridoulias A, Stavrou C, Stokes D, Tamang R, Taylor E, Trafford C, Uden C, Waddington C, Yassin D, Zaman M, Bangi S, Cheng T, Chew D, Hussain N, Imani-Masouleh S, Mahasivam G, McKnight G, Ng HL, Ota HC, Pasha T, Ravindran W, Shah K, Vishnu K S, Zaman S, Carr W, Cope S, Eagles EJ, Howarth-Maddison M, Li CY, Reed J, Ridge A, Stubbs T, Teasdaled D, Umar R, Worthington J, Dhebri A, Kalenderov R, Alattas A, Arain Z, Bhudia R, Chia D, Daniel S, Dar T, Garland H, Girish M, Hampson A, Kyriacou H, Lehovsky K, Mullins W, Omorphos N, Vasdev N, Venkatesh A, Waldock W, Bhandari A, Brown G, Choa G, Eichenauer CE, Ezennia K, Kidwai Z, Lloyd-Thomas A, Macaskill Stewart A, Massardi C, Sinclair E, Skajaa N, Smith M, Tan I, Afsheen N, Anuar A, Azam Z, Bhatia P, Davies-kelly N, Dickinson S, Elkawafi M, Ganapathy M, Gupta S, Khoury EG, Licudi D, Mehta V, Neequaye S, Nita G, Tay VL, Zhao S, Botsa E, Cuthbert H, Elliott J, Furlepa M, Lehmann J, Mangtani A, Narayan A, Nazarian S, Parmar C, Shah D, Shaw C, Zhao Z, Beck C, Caldwell S, Clements JM, French B, Kenny R, Kirk S, Lindsay J, McClung A, McLaughlin N, Watson S, Whiteside E, Alyacoubi S, Arumugam V, Beg R, Dawas K, Garg S, Lloyd ER, Mahfouz Y, Manobharath N, Moonesinghe R, Morka N, Patel K, Prashar J, Yip S, Adeeko ES, Ajekigbe F, Bhat A, Evans C, Farrugia A, Gurung C, Long T, Malik B, Manirajan S, Newport D, Rayer J, Ridha A, Ross E, Saran T, Sinker A, Waruingi D, Allen R, Al Sadek Y, Alves do Canto Brum H, Asharaf H, Ashman M, Balakumar V, Barrington J, Baskaran R, Berry A, Bhachoo H, Bilal A, Boaden L, Chia WL, Covell G, Crook D, Dadnam F, Davis L, De Berker H, Doyle C, Fox C, Gruffydd-Davies M, Hafouda Y, Hill A, Hubbard E, Hunter A, Inpadhas V, Jamshaid M, Jandu G, Jeyanthi M, Jones T, Kantor C, Kwak SY, Malik N, Matt R, McNulty P, Miles C, Mohomed A, Myat P, Niharika J, Nixon A, O'Reilly D, Parmar K, Pengelly S, Price L, Ramsden M, Turnor R, Wales E, Waring H, Wu M, Yang T, Ye TTS, Zander A, Zeicu C, Bellam S, Francombe J, Kawamoto N, Rahman MR, Sathyanarayana A, Tang HT, Cheung J, Hollingshead J, Page V, Sugarman J, Wong E, Chiong J, Fung E, Kan SY, Kiang J, Kok J, Krahelski O, Liew MY, Lyell B, Sharif Z, Speake D, Alim L, Amakye NY, Chandrasekaran J, Chandratreya N, Drake J, Owoso T, Thu YM, Abou El Ela Bourquin B, Alberts J, Chapman D, Rehnnuma N, Ainsworth K, Carpenter H, Emmanuel T, Fisher T, Gabrel M, Guan Z, Hollows S, Hotouras A, Ip Fung Chun N, Jaffer S, Kallikas G, Kennedy N, Lewinsohn B, Liu FY, Mohammed S, Rutherfurd A, Situ T, Stammer A, Taylor F, Thin N, Urgesi E, Zhang N, Ahmad MA, Bishop A, Bowes A, Dixit A, Glasson R, Hatta S, Hatt K, Larcombe S, Preece J, Riordan E, Fegredo D, Haq MZ, Li C, McCann G, Stewart D, Baraza W, Bhullar D, Burt G, Coyle J, Deans J, Devine A, Hird R, Ikotun O, Manchip G, Ross C, Storey L, Tan WWL, Tse C, Warner C, Whitehead M, Wu F, Court EL, Crisp E, Huttman M, Mayes F, Robertson H, Rosen H, Sandberg C, Smith H, Al Bakry M, Ashwell W, Bajaj S, Bandyopadhyay D, Browlee O, Burway S, Chand CP, Elsayeh K, Elsharkawi A, Evans E, Ferrin S, Fort-Schaale A, Iacob M, I K, Impelliziere Licastro G, Mankoo AS, Olaniyan T, Otun J, Pereira R, Reddy R, Saeed D, Simmonds O, Singhal G, Tron K, Wickstone C, Williams R, Bradshaw E, De Kock Jewell V, Houlden C, Knight C, Metezai H, Mirza-Davies A, Seymour Z, Spink D, Wischhusen S. Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study. Lancet Digit Health 2022; 4:e520-e531. [PMID: 35750401 DOI: 10.1016/s2589-7500(22)00069-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 01/07/2022] [Accepted: 04/06/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. METHODS We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). FINDINGS In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]). INTERPRETATION In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. FUNDING British Journal of Surgery Society.
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Yang Y, Tan M, Ma W, Duan S, Huang X, Jin L, Tang L, Li M. Preoperative prediction of the degree of differentiation of lung adenocarcinoma presenting as sub-solid or solid nodules with a radiomics nomogram. Clin Radiol 2022; 77:e680-e688. [PMID: 35718542 DOI: 10.1016/j.crad.2022.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 05/05/2022] [Accepted: 05/19/2022] [Indexed: 11/29/2022]
Abstract
AIM To develop and validate a radiomics nomogram for prediction of degree of differentiation in lung adenocarcinoma presenting as sub-solid or solid nodules. MATERIALS AND METHODS A total of 438 patients with histopathologically confirmed adenocarcinoma (248 non-poorly differentiated and 190 poorly differentiated) were divided into training cohort (n=235) and internal validation cohort (n=203) according to surgery sequence. Sixty patients form public TCIA dataset were selected for external validation. One thousand, two hundred and eighteen radiomics features were extracted from each volumetric region of interest and a least absolute shrinkage and selection operator logistic regression was applied to select meaningful radiomic features for building a radiomics score (Rad-score) model. A nomogram model incorporating the Rad-score and type was established after multivariable logistic regression. The discrimination efficiency, calibration efficacy, and clinical utility value of the nomogram were evaluated. RESULTS The Rad-score model could predict the differentiation degree of lung adenocarcinoma with an area under the curve (AUC) of 0.83 (95% confidence interval [CI]: 0.78-0.89) in the internal validation cohort. The AUC of the nomogram and radiographic model was 0.86 (95% CI: 0.80-0.91), 0.78 (95% CI: 0.72-0.84) in the internal validation cohort respectively. The AUC of the nomogram in the external validation cohort was 0.73 (95% CI: 0.58-0.88). Delong's test showed that the nomogram performed better than radiographic features alone (p=0.001). CONCLUSIONS The proposed radiomics nomogram has the potential to predict the differentiation degree of lung adenocarcinoma preoperatively.
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Affiliation(s)
- Y Yang
- Department of Radiology, Huadong Hospital Affiliated with Fudan University, Shanghai, China
| | - M Tan
- Department of Radiology, Huadong Hospital Affiliated with Fudan University, Shanghai, China
| | - W Ma
- Department of Radiology, Huadong Hospital Affiliated with Fudan University, Shanghai, China
| | - S Duan
- GE Healthcare, Shanghai, China
| | - X Huang
- Department of Radiology, Huadong Hospital Affiliated with Fudan University, Shanghai, China
| | - L Jin
- Department of Radiology, Huadong Hospital Affiliated with Fudan University, Shanghai, China
| | - L Tang
- Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - M Li
- Department of Radiology, Huadong Hospital Affiliated with Fudan University, Shanghai, China.
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Li S, Nguyen TL, Nguyen-Dumont T, Dowty JG, Dite GS, Ye Z, Trinh HN, Evans CF, Tan M, Sung J, Jenkins MA, Giles GG, Hopper JL, Southey MC. Genetic Aspects of Mammographic Density Measures Associated with Breast Cancer Risk. Cancers (Basel) 2022; 14:cancers14112767. [PMID: 35681745 PMCID: PMC9179294 DOI: 10.3390/cancers14112767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 04/27/2022] [Accepted: 05/30/2022] [Indexed: 11/26/2022] Open
Abstract
Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05−0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the “white but not bright area” (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer.
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Affiliation(s)
- Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
| | - Tuong L. Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Tu Nguyen-Dumont
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
- Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3051, Australia
| | - James G. Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Gillian S. Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
- Genetic Technologies Limited, Fitzroy, VIC 3065, Australia
| | - Zhoufeng Ye
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Ho N. Trinh
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Christopher F. Evans
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Maxine Tan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Bandar Sunway 47500, Malaysia;
- School of Electrical and Computer Engineering, The University of Oklahoma, Norman, OK 73019, USA
| | - Joohon Sung
- Department of Public Health Sciences, Division of Genome and Health Big Data, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea;
| | - Mark A. Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Graham G. Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
- Correspondence:
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
- Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3051, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
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Zhang L, Shi FY, Qin Q, Liu GX, Zhang HW, Yan J, Tan M, Wang LZ, Xue D, Hu CH, Zhang Z, She JJ. [Relationship between preoperative inflammatory indexes and prognosis of patients with rectal cancer and establishment of prognostic nomogram prediction model]. Zhonghua Zhong Liu Za Zhi 2022; 44:402-409. [PMID: 35615796 DOI: 10.3760/cma.j.cn112152-20200630-00612] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
Objective: To compare the prognostic evaluation value of preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII) in rectal cancer patients. Nomogram survival prediction model based on inflammatory markers was constructed. Methods: The clinical and survival data of 585 patients with rectal cancer who underwent radical resection in the First Affiliated Hospital of Xi'an Jiao tong University from January 2013 to December 2016 were retrospectively analyzed. The optimal cut-off values of NLR, PLR, LMR, and SII were determined by the receiver operating characteristic (ROC) curve. The relationship between different NLR, PLR, LMR and SII levels and the clinic pathological characteristics of the rectal cancer patients were compared. Cox proportional risk model was used for univariate and multivariate regression analysis. Nomogram prediction models of overall survival (OS) and disease-free survival (DFS) of patients with rectal cancer were established by the R Language software. The internal validation and accuracy of the nomograms were determined by the calculation of concordance index (C-index). Calibration curve was used to evaluate nomograms' efficiency. Results: The optimal cut-off values of preoperative NLR, PLR, LMR and SII of OS for rectal cancer patients were 2.44, 134.88, 4.70 and 354.18, respectively. There was statistically significant difference in tumor differentiation degree between the low NLR group and the high NLR group (P<0.05), and there were statistically significant differences in T stage, N stage, TNM stage, tumor differentiation degree and preoperative carcinoembryonic antigen (CEA) level between the low PLR group and the high PLR group (P<0.05). There was statistically significant difference in tumor differentiation degree between the low LMR group and the high LMR group (P<0.05), and there were statistically significant differences in T stage, N stage, TNM stage, tumor differentiation degree and preoperative CEA level between the low SII group and the high SII group (P<0.05). The multivariate Cox regression analysis showed that the age (HR=2.221, 95%CI: 1.526-3.231), TNM stage (Ⅲ grade: HR=4.425, 95%CI: 1.848-10.596), grade of differentiation (HR=1.630, 95%CI: 1.074-2.474), SII level (HR=2.949, 95%CI: 1.799-4.835), and postoperative chemoradiotherapy (HR=2.123, 95%CI: 1.506-2.992) were independent risk factors for the OS of patients with rectal cancer. The age (HR=2.107, 95%CI: 1.535-2.893), TNM stage (Ⅲ grade, HR=2.850, 95%CI: 1.430-5.680), grade of differentiation (HR=1.681, 95%CI: 1.150-2.457), SII level (HR=2.309, 95%CI: 1.546-3.447), and postoperative chemoradiotherapy (HR=1.837, 95%CI: 1.369-2.464) were independent risk factors of the DFS of patients with rectal cancer. According to the OS and DFS nomograms predict models of rectal cancer patients established by multivariate COX regression analysis, the C-index were 0.786 and 0.746, respectively. The calibration curve of the nomograms showed high consistence of predict and actual curves. Conclusions: Preoperative NLR, PLR, LMR and SII levels are all correlated with the prognosis of rectal cancer patients, and the SII level is an independent prognostic risk factor for patients with rectal cancer. Preoperative SII level can complement with the age, TNM stage, differentiation degree and postoperative adjuvant chemoradiotherapy to accurately predict the prognosis of rectal cancer patients, which can provide reference and help for clinical decision.
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Affiliation(s)
- L Zhang
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - F Y Shi
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Q Qin
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - G X Liu
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - H W Zhang
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - J Yan
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - M Tan
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - L Z Wang
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - D Xue
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - C H Hu
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Z Zhang
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - J J She
- Department of General Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
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Christopoulos P, Prawitz T, Hong JL, Lin H, Hernandez L, Jin S, Tan M, Proskorovsky I, Lin J, Zhang P, Patel J, Ou SH, Thomas M, Stenzinger A. 36P Indirect comparison of mobocertinib trial data vs real-world data in patients with EGFR exon 20 insertion (ex20ins)+ non-small cell lung cancer (NSCLC). Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.02.045] [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: 11/01/2022] Open
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Salter C, Flores JMF, Schofield E, Tan M, Mulhall J. Prevalence and Severity of Obstructive Sleep Apnea in Men with Polycythemia on Testosterone Therapy. J Sex Med 2022. [DOI: 10.1016/j.jsxm.2022.01.018] [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: 11/15/2022]
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Martinez JMF, Salter CA, Ruiz K, Benfante N, Schofield E, Tan M, Laudone V, Mulhall JP. Does the Risk of Obstructive Sleep Apnea (OSA) Affect Erectile Function Recovery (EFR) After Radical Prostatectomy (RP)? J Sex Med 2022. [DOI: 10.1016/j.jsxm.2022.01.092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Jacklin C, Tan M, Sravanam S, Harrison C. Appraisal of International Guidelines for Cutaneous Melanoma Management using the AGREE II assessment tool. JPRAS Open 2022; 31:114-122. [PMID: 35024406 PMCID: PMC8732330 DOI: 10.1016/j.jpra.2021.11.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 11/17/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND The evidence base behind new melanoma treatments is rapidly accumulating. This is not necessarily reflected in current guidance. A recent UK-based expert consensus statement, published in JPRAS, has called for updates to the widely accepted 2015 National Institute for Health and Care Excellence (NICE) guideline for melanoma (NG14). We aimed to compare the quality of NG14 to all other melanoma guidelines published since. METHODS We conducted a systematic search of PubMed, Medline, and online clinical practice guideline databases to identify melanoma guidelines published between 29th July 2015 and 23rd August 2021 providing recommendations for adjuvant treatment, radiotherapy, surgical management, or follow-up care. Three authors independently assessed the quality of identified guidelines using the Appraisal of Guidelines for Research & Evaluation Instrument II (AGREE II) assessment tool, which measures six domains of guideline development. Inter-rater reliability was assessed by Kendall's coefficient of concordance (W). RESULTS Twenty-nine guidelines were included and appraised with excellent concordance (Kendall's W for overall guideline score 0.88, p<0.001). Overall, melanoma guidelines scored highly in the domains of 'Scope and purpose' and 'Clarity of presentation', but poorly in the 'Applicability' domain. The NICE guideline on melanoma (NG14) achieved the best overall scores. CONCLUSION Melanoma treatment has advanced since NG14 was published, however, the NICE melanoma guideline is of higher quality than more recent alternatives. The planned update of NG14 in 2022 is in demand.
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Affiliation(s)
- C. Jacklin
- Medical Sciences Divisional Office, University of Oxford, Level 3, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - M. Tan
- Academic Section of Vascular Surgery, Department of Surgery and Cancer, Imperial College, London
| | - S. Sravanam
- Medical Sciences Divisional Office, University of Oxford, Level 3, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - C.J. Harrison
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
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20
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Tan M, Chapman C, Jones C, Lalondrelle S. Confirmation of Improvement in Target Dose Dosimetry for Image-guided Adaptive Brachytherapy in Cervical Cancer. Clin Oncol (R Coll Radiol) 2022. [DOI: 10.1016/j.clon.2022.01.031] [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: 11/03/2022]
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21
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Chan JSK, Zhou J, Li A, Tan M, Wong WT, Ciobanu A, Gkouziouta A, Letsas K, Liu T, Liu Y, Zhang Q, Tse G. Clustering analysis based on automated electrocardiographic measurements to identify prognostically distinct phenotypes in patients hospitalized for heart failure: a retrospective cohort study. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehab849.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: None.
Background
Heart failure (HF) is a heterogeneous disease with complex structural and electrophysiological derangements of the heart. Attempts to classify HF from the electrophysiological perspective are lacking.
Purpose
To use electrocardiographic (ECG) data for phenotypic classification of patients with HF.
Methods
In this retrospective cohort study, all adult patients hospitalized for HF during 2010-2016 at a tertiary center were included. Automated measurements of the first ECG obtained during the index admission were recorded. K-means clustering using premorbid conditions and selected ECG measurements were used to classify the cohort into four mutually exclusive clusters. The primary (all-cause and cardiovascular mortality) and secondary (ventricular arrhythmia (VA)) outcomes were compared between clusters using Cox regression analysis.
Results
In total, 2849 patients (1363 males, age 75.1 ± 13.4 years) were included. Over a mean follow-up period of 5.37 ± 4.10 years, all-cause and cardiovascular mortality occurred in 2071 (72.7%) and 600 (21.1%) patients respectively, while VA occurred in 110 patients (3.9%). Cluster 1 was characterised by a low heart rate and low ventricular activation time (VAT). Cluster 2 was characterised by old age, low absolute QRS area, and high QTc and QT dispersion. Cluster 3 was characterised by young age, and left ventricular hypertrophy (LVH), and few had history of VA. Cluster 4 was characterised by wide QRS, hypertension, ischaemic heart disease, high VAT, and high absolute T wave area. Cluster 4 had the highest and cluster 1 the lowest risks of all-cause (hazard ratio (HR) 2.96 [1.09, 1.50], p = 0.003; Figure A) and cardiovascular mortality (HR 2.90 [1.15, 2.11], p = 0.004; Figure B). Meanwhile, cluster 2 had the highest risk of VA (HR 2.23 [1.09, 3.85], p = 0.025; Figure C) while clusters 1 and 3 similarly had the lowest risks.
Conclusion
HF presents with clinically and electrophysiologically distinct phenotypes. Clustering analysis is useful in identifying HF phenotypes which are prognostically significant. Abstract Figures A, B, and C
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Affiliation(s)
- J S K Chan
- Prince of Wales Hospital, Shatin, New Territories, Hong Kong
| | - J Zhou
- City University of Hong Kong, School of Data Science, Kowloon, Hong Kong
| | - A Li
- University of Calgary, Faculty of Science, Calgary, Canada
| | - M Tan
- University of Toronto, Toronto, Canada
| | - W T Wong
- The Chinese University of Hong Kong, School of Life Science, Hong Kong, China
| | - A Ciobanu
- Carol Davila University Of Medicine And Pharm, Faculty of Medicine, Bucharest, Romania
| | - A Gkouziouta
- Onassis Cardiac Surgery Center, Heart Failure and Transplant Unit, Athens, Greece
| | - K Letsas
- Evangelismos Hospital, Second Department of Cardiology, Laboratory of Cardiac Electrophysiology, Athens, Greece
| | - T Liu
- 2nd Hospital of Tianjin Medical University, Department of Cardiology, Tianjin Institute of Cardiology, Tianjin, China
| | - Y Liu
- The First Affiliated Hospital of Dalian Medical University, Heart Failure and Structural Cardiology Division, Dalian, China
| | - Q Zhang
- City University of Hong Kong, School of Data Science, Kowloon, Hong Kong
| | - G Tse
- Kent and Medway Medical School, Canterbury, United Kingdom of Great Britain & Northern Ireland
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22
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Mackintosh JA, Pietsch M, Lutzky V, Enever D, Bancroft S, Apte SH, Tan M, Yerkovich ST, Dickinson JL, Pickett HA, Selvadurai H, Grainge C, Goh NS, Hopkins P, Glaspole I, Reynolds PN, Wrobel J, Jaffe A, Corte TJ, Chambers DC. TELO-SCOPE study: a randomised, double-blind, placebo-controlled, phase 2 trial of danazol for short telomere related pulmonary fibrosis. BMJ Open Respir Res 2021; 8:8/1/e001127. [PMID: 34857525 PMCID: PMC8640666 DOI: 10.1136/bmjresp-2021-001127] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 11/15/2021] [Indexed: 11/17/2022] Open
Abstract
Introduction Recent discoveries have identified shortened telomeres and related mutations in people with pulmonary fibrosis (PF). There is evidence to suggest that androgens, including danazol, may be effective in lengthening telomeres in peripheral blood cells. This study aims to assess the safety and efficacy of danazol in adults and children with PF associated with telomere shortening. Methods and analysis A multi-centre, double-blind, placebo-controlled, randomised trial of danazol will be conducted in subjects aged >5 years with PF associated with age-adjusted telomere length ≤10th centile measured by flow fluorescence in situ hybridisation; or in children, a diagnosis of dyskeratosis congenita. Adult participants will receive danazol 800 mg daily in two divided doses or identical placebo capsules orally for 12 months, in addition to standard of care (including pirfenidone or nintedanib). Paediatric participants will receive danazol 2 mg/kg/day orally in two divided doses or identical placebo for 6 months. If no side effects are encountered, the dose will be escalated to 4 mg/kg/day (maximum 800 mg daily) orally in two divided doses for a further 6 months. The primary outcome is change in absolute telomere length in base pairs, measured using the telomere shortest length assay (TeSLA), at 12 months in the intention to treat population. Ethics and dissemination Ethics approval has been granted in Australia by the Metro South Human Research Ethics Committee (HREC/2020/QMS/66385). The study will be conducted and reported according to Standard Protocol Items: Recommendations for Interventional Trials guidelines. Results will be published in peer-reviewed journals and presented at international and national conferences. Trial registration numbers NCT04638517; Australian New Zealand Clinical Trials Registry (ACTRN12620001363976p).
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Affiliation(s)
- John A Mackintosh
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia
| | - Maria Pietsch
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia
| | - Viviana Lutzky
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia
| | - Debra Enever
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia
| | - Sandra Bancroft
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia
| | - Simon H Apte
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia.,Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Maxine Tan
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia
| | - Stephanie T Yerkovich
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia.,Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Joanne L Dickinson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Hilda A Pickett
- Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - Hiran Selvadurai
- Department of Respiratory Medicine, The Children's Hospital at Westmead, Sydney, New South Wales, Australia.,Discipline of Paediatrics and Child Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Christopher Grainge
- Department of Respiratory Medicine, John Hunter Hospital, Newcastle, New South Wales, Australia
| | - Nicole S Goh
- Respiratory and Sleep Medicine Department, Austin Health, Heidelberg, Victoria, Australia.,Institute for Breathing and Sleep, Melbourne, Victoria, Australia.,Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Peter Hopkins
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia.,Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Ian Glaspole
- Department of Allergy and Respiratory Medicine, Alfred Hospital, Melbourne, Victoria, Australia
| | - Paul N Reynolds
- Department of Respiratory Medicine, Royal Adelaide Hospital, Adelaide, South Australia, Australia
| | - Jeremy Wrobel
- Advanced Lung Disease Unit, Fiona Stanley Hospital, Murdoch, Western Australia, Australia.,Department of Medicine, University of Notre Dame, Perth, Western Australia, Australia
| | - Adam Jaffe
- School of Women's and Children's Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Tamera J Corte
- Respiratory Medicine, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Daniel C Chambers
- Queensland Lung Transplant Service, Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Queensland, Australia.,Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
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23
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Graham C, Tan M, Chew D, Gale C, Fox K, Bagai A, Henderson M, Quraishi A, Dery J, Cheema A, Fisher H, Brieger D, Lutchmedial S, Lavi S, Wong B, Cieza T, Mehta S, Goodman S, Yan A. USE AND OUTCOME OF DUAL ANTIPLATELET THERAPY FOR ACUTE CORONARY SYNDROME IN PATIENTS WITH CHRONIC KIDNEY DISEASE: INSIGHTS FROM THE CANADIAN OBSERVATIONAL ANTIPLATELET STUDY (COAPT), A MULTICENTRE PROSPECTIVE COHORT STUDY. Can J Cardiol 2021. [DOI: 10.1016/j.cjca.2021.07.041] [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: 11/26/2022] Open
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24
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Goodman S, Bagai A, Tan M, Andrade J, Spindler C, Malek-Marzban P, Har B, Yip A, Paniagua M, Elbarouni B, Bainey K, Paradis J, Maranda R, Cantor W, Doucet M, Khan R, Eisenberg M, Dery J, Schwalm J, Madan M, Lam A, Hameed A, Noronha L, Cieza T, Matteau A, Roth S, So D, Lavi S, Glanz A, Gao D, Tahiliani R, Welsh R, Kim H, Robinson S, Daneault B, Chong A, Le May M, Ahooja V, Gregoire J, Nadeau P, Laksman Z, Heilbron B, Bonakdar H, Yung D, Yan A. ANTITHROMBOTIC THERAPIES IN CANADIAN ATRIAL FIBRILLATION PATIENTS WITH CONCOMITANT CORONARY ARTERY DISEASE: INSIGHTS FROM THE CONNECT AF+PCI-I AND -II PROGRAMS. Can J Cardiol 2021. [DOI: 10.1016/j.cjca.2021.07.030] [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: 11/24/2022] Open
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25
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Shetty G, Datta U, Rea I, Rai S, Hwang MJ, Hoar F, Sintler M, Mirza M, Husain A, Tan M. Rapid implementation of triaging system for assessment of breast referrals from primary care centres during the COVID-19 pandemic. Ann R Coll Surg Engl 2021; 103:576-582. [PMID: 34464568 DOI: 10.1308/rcsann.2021.0155] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVE The aim of this study was to establish a triaging system for assessment of breast referrals from primary care to ensure safe and effective breast services without compromising breast cancer management. BACKGROUND COVID-19 was officially declared a global pandemic on 11 March 2020, and with no effective treatment available, preventing spread has been paramount. Previously, all referrals from primary care were seen in the rapid-access breast clinic (RABC). Clinic appointments exposed patients and healthcare professionals to risk. METHOD Initial triage during the lockdown was in line with national governing body guidance, rejected low risk referrals and streamed remaining patients through a telephone consultation to RABC or discharge. A modified triage pathway streamed all patients through virtual triage to RABC, telephone clinic or discharge with advice and guidance categories. Demographics, reasons for referral and outcomes data were collected and presented as median with range and frequency with percentages. RESULTS Initial triage (23 March-23 April 2020) found fewer referrals with a higher percentage of breast cancer diagnoses. Modified triage (22 June-17 July 2020) resulted in a 35.1% (99/282) reduction in RABC attendance. Overall cancer detection rate remained similar at 4.2% of all referrals pre-COVID (18/429) and 4.3% (12/282) during modified triage. After six months follow-up of patients not seen in RABC during the modified triage pathway, 18 patients were re-referred to RABC and none were diagnosed with cancer. CONCLUSION A modified triage pathway has the potential to improve triage efficiency and prevent unnecessary visits during the COVID-19 pandemic. Further refinement of pathway is feasible in collaboration with primary care.
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Affiliation(s)
- G Shetty
- Sandwell and West Birmingham NHS Trust, UK.,Kasturba Medical College Mangalore & Manipal Academy of Health Education, Manipal, India
| | - U Datta
- Sandwell and West Birmingham NHS Trust, UK
| | - I Rea
- Sandwell and West Birmingham NHS Trust, UK
| | - S Rai
- Sandwell and West Birmingham NHS Trust, UK
| | - M-J Hwang
- Sandwell and West Birmingham NHS Trust, UK.,North West Wales NHS Trust, UK
| | - F Hoar
- Sandwell and West Birmingham NHS Trust, UK
| | - M Sintler
- Sandwell and West Birmingham NHS Trust, UK
| | - M Mirza
- Sandwell and West Birmingham NHS Trust, UK
| | - A Husain
- Sandwell and West Birmingham NHS Trust, UK
| | - M Tan
- Sandwell and West Birmingham NHS Trust, UK
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26
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Gu F, Tan M, Chen Y, Li X, Xu Y. O-183 Increased Risk Of Hypertensive Disorders Of Pregnancy In Hormone Replacement Therapy Cycle - A Multicenter Cohort Study In Frozen Blastocyst Transfer In Ovulatory Women. Hum Reprod 2021. [DOI: 10.1093/humrep/deab127.084] [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: 11/12/2022] Open
Abstract
Abstract
Study question
Is hormone replacement therapy cycle (HRT) associated with a higher risk of adverse perinatal outcomes than natural cycle (NC) during frozen embryo transfer (FET)?
Summary answer
Higher rates of hypertensive disorders of pregnancy (HDPs) and macrosomia were detected in HRT-FET as compared to NC-FET in ovulatory women.
What is known already
Live-birth rates after HRT-FET and NC-FET are found to be comparable. Recent data showed that pregnancies following HRT-FET are associated with higher risks of HDPs. However, the results might be influenced by selection bias as patients with ovulation disorder were more prone to receive HRT than ovulatory women. As is known, patients with ovulation disorder might have more endocrine disturbances than ovulatory women, which could be associated with adverse obstetrical outcomes.
Study design, size, duration
Four large reproductive medical centers in Guangdong province, Southeast of China, took part in this multicenter retrospective cohort study. Patients with regular cycles (25-35 days), who underwent either HRT or NC blastocyst FET and delivered after 20 weeks of gestation between January 2017 and December 2019 were analyzed. Preimplantation genetic testing (PGT) cycles, multiple pregnancies and cases with type II diabetes or preconceptional hypertension were excluded. Each patient only contributed one cycle per cohort.
Participants/materials, setting, methods
Treatment cycles from each patient were linked to their obstetrical medication record and a comprehensive chart review was done to investigate their perinatal outcomes. Maternal and neonatal outcomes were compared between NC-FET and HRT-FET cycles. Multiple logistic regression analyses were performed to adjust the confounding factors including baseline demographics (maternal age, BMI, education level, parity, type of infertility and cause of infertility), as well as IVF characteristics (insemination method and embryo cryopreservation duration).
Main results and the role of chance
A total of 406 cases from NC-FET and 602 cases from HRT-FET were included. A multiple logistic regression analysis showed that pregnancies after HRT-FET had increased odds of HDPs [adjusted odds ratio (aOR) 2.44, 95% confidence interval (CI), 1.39–4.29] in comparison to pregnancies after NC-FET. Singletons born after HRT-FET were at increased risk of macrosomia compared to NC group (aOR 2.74, 95%CI 1.10–6.87). No significant difference could be seen regarding other obstetrical complications including gestational diabetes, placenta previa, placental abruption and postpartum hemorrhage between HRT-FET and NC-FET. No significant differences were noticed for preterm birth and low birthweight between the different endometrial protocols.
Limitations, reasons for caution
Our study was retrospective in nature, and some cases were excluded due to missing data.
Wider implications of the findings
Pregnancies following HRT-FET are associated with higher risks of HDPs and macrosomia in ovulatory women. Physicians should be cautious on the decision of the endometrium preparation for FET, especially for those who can ovulate normally.
Trial registration number
2018YFC100310
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Affiliation(s)
- F Gu
- The First Affiliated Hospital of Sun Yatsen university, Center for Reproductive Medicine, Guangzhou, China
| | - M Tan
- Jiangmen Central Hospital, Affiliated Hospital of Sun Yat-sen University- Guangdong., Center for reproductive medicine
| | - Y Chen
- Shunde Women and Children‘s Hospital of Guangdong Medical University, center for reproductive medicine, Shunde, China
| | - X Li
- Shenzhen Martinity&Child Healthcare Hospital, center for reproductive medicine, Shenzhen, China
| | - Y Xu
- The First Affiliated Hospital of Sun Yatsen university, Center for Reproductive Medicine, Guangzhou, China
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Liew A, Lee CC, Lan BL, Tan M. CASPIANET++: A multidimensional Channel-Spatial Asymmetric attention network with Noisy Student Curriculum Learning paradigm for brain tumor segmentation. Comput Biol Med 2021; 136:104690. [PMID: 34352452 DOI: 10.1016/j.compbiomed.2021.104690] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 07/20/2021] [Accepted: 07/24/2021] [Indexed: 11/16/2022]
Abstract
Convolutional neural networks (CNNs) have been used quite successfully for semantic segmentation of brain tumors. However, current CNNs and attention mechanisms are stochastic in nature and neglect the morphological indicators used by radiologists to manually annotate regions of interest. In this paper, we introduce a channel and spatial wise asymmetric attention (CASPIAN) by leveraging the inherent structure of tumors to detect regions of saliency. To demonstrate the efficacy of our proposed layer, we integrate this into a well-established convolutional neural network (CNN) architecture to achieve higher Dice scores, with less GPU resources. Also, we investigate the inclusion of auxiliary multiscale and multiplanar attention branches to increase the spatial context crucial in semantic segmentation tasks. The resulting architecture is the new CASPIANET++, which achieves Dice Scores of 91.19%, 87.6% and 81.03% for whole tumor, tumor core and enhancing tumor respectively. Furthermore, driven by the scarcity of brain tumor data, we investigate the Noisy Student method for segmentation tasks. Our new Noisy Student Curriculum Learning paradigm, which infuses noise incrementally to increase the complexity of the training images exposed to the network, further boosts the enhancing tumor region to 81.53%. Additional validation performed on the BraTS2020 data shows that the Noisy Student Curriculum Learning method works well without any additional training or finetuning.
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Affiliation(s)
- Andrea Liew
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Bandar Sunway, 47500, Malaysia
| | - Chun Cheng Lee
- Radiology Department, Sunway Medical Centre, Bandar Sunway, 47500, Malaysia
| | - Boon Leong Lan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Bandar Sunway, 47500, Malaysia; Advanced Engineering Platform, School of Engineering, Monash University Malaysia, Bandar Sunway, 47500, Malaysia
| | - Maxine Tan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Bandar Sunway, 47500, Malaysia; School of Electrical and Computer Engineering, The University of Oklahoma, Norman, OK, 73019, USA.
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Tan M, Jian W, Liang Q, Li S, Cui H. [Comparison of different evaluation systems for assessing disease severity and treatment efficacy in patients with chronic obstructive pulmonary disease]. Nan Fang Yi Ke Da Xue Xue Bao 2021; 41:1119-1124. [PMID: 34308866 DOI: 10.12122/j.issn.1673-4254.2021.07.23] [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: 11/24/2022]
Abstract
OBJECTIVE To compare the practicability and clinical value of different evaluation systems for assessing disease severity and treatment efficacy in patients with chronic obstructive pulmonary disease (COPD). METHODS We retrospectively analyzed the clinical data of 28 patients with acute exacerbation of COPD admitted to our hospital between November, 2020 and January, 2021. All the patients were assessed with percentage of predicted forced expiratory volume in 1 second (FEV1% pred), COPD assessment test (CAT), modified British Medical Research Council (mMRC), baseline dyspnea index (BDI), clinical COPD questionnaire (CCQ), St. George's respiratory questionnaire (SGRQ), BODE index, Hamilton Depression Rating Scale (HDRS) at admission and with CAT, mMRC, transition dyspnea index (TDI), CCQ, SGRQ, and HDRS at 1 month after discharge. The correlations among FEV1% pred, CAT, mMRC, BDI, CCQ, SGRQ, BODE and HDRS at admission were analyzed. We also compared the TDI and scores of CAT, mMRC, CCQ, SGRQ, and HDRS at 1 month after discharge among the patients using single (n=8), dual (n=10) or triple inhaled medications (n=10) after discharge. RESULTS Among these patients, FEV1% pred was moderately correlated with SGRQ and BDI (r=-0.66, r=0.61; P < 0.01), and CCQ activity score was closely correlated with mMRC, SGRQ activity score and BDI (r=0.82, r=0.92, r=-0.89; P < 0.01). SGRQ activity score was closely correlated with mMRC and BDI (r=0.84, r=-0.91; P < 0.01), and SGRQ symptom score was closely correlated with BODE (r=0.80, P < 0.01). SGRQ impact score was moderately correlated with HDRS (r=0.57, P < 0.01). In all the 28 patients, all the evaluation scores except for CCQ mental score and HDRS improved significantly after treatment (P < 0.05). At 1 month after discharge, CCQ total score decreased significantly in single therapy group (P < 0.05); CAT, mMRC, CCQ and SGRQ improved obviously in dual therapy group (P < 0.05); CCQ and SGRQ scores decreased significantly in triple therapy group (P < 0.05); the TDI did not differ significantly among the 3 groups (P>0.05). CONCLUSION For patients with COPD, BDI and TDI are recommended over mMRC for assessing dyspnea. CAT, CCQ and SGRQ allow sensitive assessment of the treatment efficacy to serve as routine evaluation tests, and among them SGRQ is the most comprehensive and is thus recommended when sufficient time is allowed. BODE is relatively complex but highly valuable for predicting the patients'survival outcomes. HDRS is recommended for routine screening of depression in patients with COPD.
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Affiliation(s)
- M Tan
- Department of Respiratory and Critical Care Medicine, Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - W Jian
- 77228 Troop of PLA, Dali 671003, China
| | - Q Liang
- Department of Respiratory and Critical Care Medicine, Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - S Li
- Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen 518100, China
| | - H Cui
- Department of Respiratory and Critical Care Medicine, Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
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29
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Pedersen A, Greenhalgh M, Tan M, Terry R, Royle C, Royles K. 534 ADVANCED COMMUNICATION SKILLS: TEACHING DURING A PANDEMIC. Age Ageing 2021. [DOI: 10.1093/ageing/afab117.12] [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: 11/12/2022] Open
Abstract
Abstract
Introduction
In the first wave of the COVID-19 pandemic, it was recognised there would be an increased demand on clinicians to provide patients and relatives with bad news. The national ban on hospital visiting rapidly changed the way in which this news would be delivered. In recognition of these new challenges, our team sought to design a teaching course that could be implemented quickly and cost effectively, with the aim of improving clinician’s confidence around these difficult skills.
Methods
A teaching programme was created using senior geriatric and palliative care clinicians as simulated patients, open to any grade and speciality. Learners were required to break bad news (BBN) without any visual feedback, to simulate skills required when using the telephone. Surveys were collected to determine self–assessed confidence across four domains (Table 1) before, immediately after and 4–20 weeks after the course. Participants were asked to rank their confidence for each skill on a 5 point scale with 1 being very unsure and 5 being very confident.
Results
Pre-teaching scores showed an average of 3 (neither confident nor unsure) across all domains. After the course all domains improved, most notably around discussing end of life (EoL) care and discussing information over the phone.
Conclusion
This project has highlighted a lack of confidence across all skill levels when it comes to BBN. This confidence is easily improved by a short, cost-effective teaching course. It remains to be seen if this improved confidence translates to better communication with relatives.
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Robbins D, Noviski M, Tan M, Guiducci C, Ingallinera T, Karr D, Kelly A, Konst Z, Tenn-Mcclellan A, Mckinnell J, Perez L, Hansen G, Rountree R. POS0006 NX-5948, A SELECTIVE DEGRADER OF BTK, SIGNIFICANTLY REDUCES INFLAMMATION IN A MODEL OF AUTOIMMUNE DISEASE. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.1675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:Aberrant activation of B cells and autoantibody mediated tissue damage are hallmarks of autoimmune diseases such as systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Therefore, novel treatments that prevent autoantibody generation or antibody-mediated end organ tissue damage are of high interest. Bruton’s tyrosine kinase (BTK) transduces signals downstream of the B cell receptor (BCR), toll-like receptors, and Fc receptors in B cells and myeloid cells [1]. Overexpression of BTK in B cells leads to hyperactive BCR signaling, plasma cell generation, autoantibody secretion, and an SLE-like disease in mice [2]. Conversely, reducing BTK expression in B cells can ameliorate disease in Lyn-deficient mice.[3] BTK inhibitors, such as evobrutinib, have entered clinical studies for the treatment of autoimmune diseases.[4]Objectives:Small molecule-induced protein degradation offers a unique approach to target BTK; this approach simultaneously eliminates both BTK kinase activity and BTK-mediated scaffolding interactions in the signalosome. Chimeric Targeting Molecules (CTMs) are small molecules that catalyze ubiquitylation and proteasomal degradation of target proteins and are comprised of a ubiquitin ligase binding element (“harness”), a linker, and a target binding element (“hook”). NX-5948 is a CTM that contains a BTK hook linked to a cereblon (CRBN) harness. We examined the activity of NX-5948 in a collagen-induced arthritis model as part of an assessment of its potential as a drug candidate for autoimmune disease.Methods:Cellular degradation of BTK, Aiolos and Ikaros as well as induction of CD69 and CD86 was determined using flow cytometry. Degradation of BTK in CD-1 mice or cynomolgus monkey was determined using flow cytometry analysis. In a collagen-induced arthritis (CIA) model, mice were vaccinated with type II collagen and treated before the onset of symptoms. Serum cytokine and anti-type II collagen antibody levels were determined using Luminex and ELISA, respectively.Results:In human PBMCs, NX-5948 degrades BTK at sub-nanomolar concentrations and inhibits BCR signaling as measured by CD69 and CD86 induction in anti-IgM-stimulated B cells with similar potency. Oral administration of NX-5948 in mice leads to BTK degradation to <10% of baseline levels in circulating and splenic B cells. NX-5948 also promotes potent BTK degradation in cynomolgus monkeys, and it can suppress BTK levels to <10% of baseline levels after a single oral dose as low as 10 mg/kg.Unlike IMiD drugs such as lenalidomide, the CRBN harness of NX-5948 was designed to avoid the degradation of known CRBN neo-substrates Aiolos (IKZF3) and Ikaros (IKZF1). In primary human T cells, NX-5948 induces minimal degradation of Aiolos and Ikaros and does not promote IL-2 secretion suggesting that NX-5948 does not convey IMiD activity associated with agents such as lenalidomide.We examined the activity of NX-5948 in a mouse CIA model compared to that of the BTK inhibitor ibrutinib or dexamethasone as a positive control. In mice treated with NX-5948, symptoms of arthritis were resolved, and a significant reduction in arthritis clinical score was observed. Treatment with NX-5948 resulted in a reduction in anti-type II collagen titer and serum levels of the pro-inflammatory cytokine IL-6. Treatment with NX-5948 yielded superior anti-inflammatory activity relative to ibrutinib and similar activity to dexamethasone. Treatment with NX-5948 was well-tolerated and, unlike dexamethasone, did not promote body weight loss.Conclusion:Degradation of BTK by NX-5948 shows robust activity in a CIA model compared to existing agents tested as controls. These findings provide support for further investigation of NX-5948 in additional models of autoimmune disease to inform plans for clinical development.References:[1]Crofford et al. 2016. Expert Rev Clin Immunol 12: 763–773.[2]Kil et al. 2012. Blood 119: 3744-3756.[3]Whyburn et al. 2003. J Immunol 171: 1850-1858.[4]Haselmayer, et. Al. 2019. J Immunol 202: 2888-2906.Disclosure of Interests:DANIEL ROBBINS Shareholder of: Nurix therapeutics, Employee of: Nurix therapeutics, Mark Noviski Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, May Tan Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Cristiana Guiducci Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Timothy Ingallinera Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Dane Karr Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Aileen Kelly Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Zef Konst Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Austin Tenn-McClellan Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Jenny McKinnell Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Luz Perez Employee of: Nurix Therapeutics, Gwenn Hansen Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics, Ryan Rountree Shareholder of: Nurix Therapeutics, Employee of: Nurix Therapeutics
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Abstract
PURPOSE In recent years, Non-Local-based methods have been successfully applied to lung nodule classification. However, these methods offer 2D attention or limited 3D attention to low-resolution feature maps. Moreover, they still depend on a convenient local filter such as convolution as full 3D attention is expensive to compute and requires a big dataset, which might not be available. METHODS We propose to use 3D Axial-Attention, which requires a fraction of the computing power of a regular Non-Local network (i.e., self-attention). Unlike a regular Non-Local network, the 3D Axial-Attention network applies the attention operation to each axis separately. Additionally, we solve the invariant position problem of the Non-Local network by proposing to add 3D positional encoding to shared embeddings. RESULTS We validated the proposed method on 442 benign nodules and 406 malignant nodules, extracted from the public LIDC-IDRI dataset by following a rigorous experimental setup using only nodules annotated by at least three radiologists. Our results show that the 3D Axial-Attention model achieves state-of-the-art performance on all evaluation metrics, including AUC and Accuracy. CONCLUSIONS The proposed model provides full 3D attention, whereby every element (i.e., pixel) in the 3D volume space attends to every other element in the nodule effectively. Thus, the 3D Axial-Attention network can be used in all layers without the need for local filters. The experimental results show the importance of full 3D attention for classifying lung nodules.
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Affiliation(s)
- Mundher Al-Shabi
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, 47500, Bandar Sunway, Selangor, Malaysia.
| | - Kelvin Shak
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, 47500, Bandar Sunway, Selangor, Malaysia
| | - Maxine Tan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, 47500, Bandar Sunway, Selangor, Malaysia
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, 73019, USA
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Divithotawela C, Pham A, Bell PT, Ledger EL, Tan M, Yerkovich S, Grant M, Hopkins PM, Wells TJ, Chambers DC. Inferior outcomes in lung transplant recipients with serum Pseudomonas aeruginosa specific cloaking antibodies. J Heart Lung Transplant 2021; 40:951-959. [PMID: 34226118 DOI: 10.1016/j.healun.2021.05.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 04/21/2021] [Accepted: 05/24/2021] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Chronic Lung Allograft Dysfunction (CLAD) limits long-term survival following lung transplantation. Colonization of the allograft by Pseudomonas aeruginosa is associated with an increased risk of CLAD and inferior overall survival. Recent experimental data suggests that 'cloaking' antibodies targeting the O-antigen of the P. aeruginosa lipopolysaccharide cell wall (cAbs) attenuate complement-mediated bacteriolysis in suppurative lung disease. METHODS In this retrospective cohort analysis of 123 lung transplant recipients, we evaluated the prevalence, risk factors and clinical impact of serum cAbs following transplantation. RESULTS cAbs were detected in the sera of 40.7% of lung transplant recipients. Cystic fibrosis and younger age were associated with increased risk of serum cAbs (CF diagnosis, OR 6.62, 95% CI 2.83-15.46, p < .001; age at transplant, OR 0.69, 95% CI 0.59-0.81, p < .001). Serum cAbs and CMV mismatch were both independently associated with increased risk of CLAD (cAb, HR 4.34, 95% CI 1.91-9.83, p < .001; CMV mismatch (D+/R-), HR 5.40, 95% CI 2.36-12.32, p < .001) and all-cause mortality (cAb, HR 2.75, 95% CI 1.27-5.95, p = .010, CMV mismatch, HR 3.53, 95% CI 1.62-7.70, p = .002) in multivariable regression analyses. CONCLUSIONS Taken together, these findings suggest a potential role for 'cloaking' antibodies targeting P. aeruginosa LPS O-antigen in the immunopathogenesis of CLAD.
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Affiliation(s)
| | - Amy Pham
- The University of Queensland, Diamantina Institute, The University of Queensland, Wooloongabba, Australia
| | - Peter T Bell
- Queensland Lung Transplant Service, The Prince Charles Hospital, Brisbane, Australia; School of Medicine, The University of Queensland, Brisbane, Australia
| | - Emma L Ledger
- The University of Queensland, Diamantina Institute, The University of Queensland, Wooloongabba, Australia
| | - Maxine Tan
- Queensland Lung Transplant Service, The Prince Charles Hospital, Brisbane, Australia
| | | | - Michelle Grant
- Queensland Lung Transplant Service, The Prince Charles Hospital, Brisbane, Australia
| | - Peter M Hopkins
- Queensland Lung Transplant Service, The Prince Charles Hospital, Brisbane, Australia; School of Medicine, The University of Queensland, Brisbane, Australia
| | - Timothy J Wells
- The University of Queensland, Diamantina Institute, The University of Queensland, Wooloongabba, Australia; Australian Infectious Diseases Research Centre, University of Queensland, Brisbane, Australia
| | - Daniel C Chambers
- Queensland Lung Transplant Service, The Prince Charles Hospital, Brisbane, Australia; School of Medicine, The University of Queensland, Brisbane, Australia.
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Jacklin C, Harrison C, Tan M, Sravanam S. 646 Appraisal of International Guidelines for Malignant Melanoma Management Using the AGREE II Assessment Tool. Br J Surg 2021. [DOI: 10.1093/bjs/znab134.309] [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: 11/13/2022]
Abstract
Abstract
Background
Recently, the widely accepted NICE guidelines for melanoma management have been challenged by a UK-based expert consensus statement. A review of alternative clinical practice guidelines (CPGs) could guide future CPG updates and developments. The AGREE II tool assesses CPGs across six domains: ‘Scope and purpose’, ‘Stakeholder involvement’, ‘Rigour of development’, ‘Clarity of presentation’, ‘Applicability’, and ‘Editorial independence’.
Method
We conducted a systematic search of Pubmed, Medline and online CPG databases to identify melanoma CPGs published between January 2014 and March 2020 providing recommendations for: adjuvant treatment, radiotherapy, surgical management, or follow-up care. Three authors independently assessed the quality of identified CPGs using the AGREE II assessment tool. Inter-rater reliability was assessed by Kendall’s coefficient of concordance (W).
Results
Twenty-nine CPGs were included and appraised with excellent reliability (Kendall’s W for overall GPC score 0.85, p < 0.001). Overall, melanoma CPGs scored highly in the scope and purpose and clarity of presentation domains, and poorly in the applicability domain. The NICE guideline achieved the best overall scores.
Conclusions
The NICE melanoma CPGs are higher quality than alternatives but should be updated to reflect recent landmark trials. The AGREE II tool is currently limited by its incapacity to compare guidelines to latest evidence.
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Affiliation(s)
- C Jacklin
- University of Oxford, Oxford, United Kingdom
| | - C Harrison
- University of Oxford, Oxford, United Kingdom
| | - M Tan
- Imperial College London, London, United Kingdom
| | - S Sravanam
- University of Oxford, Oxford, United Kingdom
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Ekwe A, Au R, McEnroe B, Tan M, Saldan A, Henden A, Zhang P, Hutchins C, Henderson A, Mudie K, Western R, Fuery M, Kennedy G, Hill G, Tey S. Clinical scale facs-sorting and expansion of regulatory t cells (TREGS) for phase i clinical trial. Cytotherapy 2021. [DOI: 10.1016/s1465324921006150] [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: 10/21/2022]
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Machin M, Salim S, Tan M, Onida S, Davies AH, Shalhoub J. Surgical and non-surgical approaches in the management of lower limb post-thrombotic syndrome. Expert Rev Cardiovasc Ther 2021; 19:191-200. [PMID: 33455484 DOI: 10.1080/14779072.2021.1876563] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Introduction: Post-thrombotic syndrome (PTS) is a common lifelong condition affecting up to 50% of those suffering from deep vein thrombosis (DVT). PTS compromises function and quality of life with subsequent venous ulceration in up to 29% of those affected.Areas covered: A literature review of surgical and non-surgical approaches in the prevention and treatment of PTS was undertaken. Notable areas include the use of percutaneous endovenous interventions and the use of graduated compression stockings (GCS) after acute proximal DVT.Expert opinion: In patients with acute iliofemoral DVT, we think it is important to have a frank conversation with the patient about catheter-directed thrombolysis, aiming to reduce the severity of PTS experienced. We advocate ultrasound-accelerated thrombolysis with adjunctive procedures, such as deep venous stenting for proximal iliofemoral DVT. For patients with isolated femoral DVT, we believe that anticoagulation and GCS should be recommended. In patients with established PTS, we recommend GCS for symptomatic relief. We recommend that patients engage in regular exercise where possible with the prospect of gaining symptomatic relief. For those with severe PTS that has a significant effect on quality of life, we discuss the patient's case at a multi-disciplinary team meeting to plan for endovenous intervention.
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Affiliation(s)
- M Machin
- Academic Section of Vascular Surgery, Department of Surgery & Cancer, Imperial College London, London, UK.,Imperial Vascular Unit, Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
| | - S Salim
- Academic Section of Vascular Surgery, Department of Surgery & Cancer, Imperial College London, London, UK.,Imperial Vascular Unit, Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
| | - M Tan
- Academic Section of Vascular Surgery, Department of Surgery & Cancer, Imperial College London, London, UK.,Imperial Vascular Unit, Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
| | - S Onida
- Academic Section of Vascular Surgery, Department of Surgery & Cancer, Imperial College London, London, UK.,Imperial Vascular Unit, Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
| | - A H Davies
- Academic Section of Vascular Surgery, Department of Surgery & Cancer, Imperial College London, London, UK
| | - J Shalhoub
- Academic Section of Vascular Surgery, Department of Surgery & Cancer, Imperial College London, London, UK.,Imperial Vascular Unit, Imperial College Healthcare NHS Trust, Charing Cross Hospital, London, UK
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Tan M, Al-Shabi M, Chan WY, Thomas L, Rahmat K, Ng KH. Comparison of two-dimensional synthesized mammograms versus original digital mammograms: a quantitative assessment. Med Biol Eng Comput 2021; 59:355-367. [PMID: 33447988 DOI: 10.1007/s11517-021-02313-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 01/07/2021] [Indexed: 12/13/2022]
Abstract
This study objectively evaluates the similarity between standard full-field digital mammograms and two-dimensional synthesized digital mammograms (2DSM) in a cohort of women undergoing mammography. Under an institutional review board-approved data collection protocol, we retrospectively analyzed 407 women with digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) examinations performed from September 1, 2014, through February 29, 2016. Both FFDM and 2DSM images were used for the analysis, and 3216 available craniocaudal (CC) and mediolateral oblique (MLO) view mammograms altogether were included in the dataset. We analyzed the mammograms using a fully automated algorithm that computes 152 structural similarity, texture, and mammographic density-based features. We trained and developed two different global mammographic image feature analysis-based breast cancer detection schemes for 2DSM and FFDM images, respectively. The highest structural similarity features were obtained on the coarse Weber Local Descriptor differential excitation texture feature component computed on the CC view images (0.8770) and MLO view images (0.8889). Although the coarse structures are similar, the global mammographic image feature-based cancer detection scheme trained on 2DSM images outperformed the corresponding scheme trained on FFDM images, with area under a receiver operating characteristic curve (AUC) = 0.878 ± 0.034 and 0.756 ± 0.052, respectively. Consequently, further investigation is required to examine whether DBT can replace FFDM as a standalone technique, especially for the development of automated objective-based methods.
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Affiliation(s)
- Maxine Tan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia. .,School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, 73019, USA.
| | - Mundher Al-Shabi
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia
| | - Wai Yee Chan
- Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia
| | - Leya Thomas
- Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia
| | - Kartini Rahmat
- Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia
| | - Kwan Hoong Ng
- Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia
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Liang D, Dinh D, Gayed D, Tan M, Clark D, Duffy S, Brennan A, Ajani A, Oquiel E, Roberts L, Cooke J, Reid C, Chandrasekhar J, Freeman M. Are Public Holidays, Sporting Events and Significant Historical Events Triggers of ST-elevation Myocardial Infarction (STEMI) Presentations in Victoria? A Melbourne Interventional Group (MIG) Observational Study. Heart Lung Circ 2021. [DOI: 10.1016/j.hlc.2021.06.257] [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: 11/26/2022]
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Papaioannou A, McCloskey E, Bell A, Ngui D, Mehan U, Tan M, Goldin L, Langer A. Use of an electronic medical record dashboard to identify gaps in osteoporosis care. Arch Osteoporos 2021; 16:76. [PMID: 33893868 PMCID: PMC8068625 DOI: 10.1007/s11657-021-00919-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 03/17/2021] [Indexed: 02/03/2023]
Abstract
UNLABELLED Using an electronic medical record (EMR)-based dashboard, this study explored osteoporosis care gaps in primary care. Eighty-four physicians shared their practice activities related to bone mineral density testing, 10-year fracture risk calculation and treatment for those at high risk. Significant gaps in fracture risk calculation and osteoporosis management were identified. PURPOSE To identify care gaps in osteoporosis management focusing on Canadian clinical practice guidelines (CPG) related to bone mineral density (BMD) testing, 10-year fracture risk calculation and treatment for those at high risk. METHODS The ADVANTAGE OP EMR tool consists of an interactive algorithm to facilitate assessment and management of fracture risk using CPG. The FRAX® and Canadian Association of Radiologists and Osteoporosis Canada (CAROC) tools were embedded to facilitate 10-year fracture risk calculation. Physicians managed patients as clinically indicated but with EMR reminders of guideline recommendations; participants shared practice level data on management activities after 18-month use of the tool. RESULTS Eighty-four physicians (54%) of 154 who agreed to participate in this study shared their aggregate practice activities. Across all practices, there were 171,310 adult patients, 40 years of age and older, of whom 17,214 (10%) were at elevated risk for fracture. Sixty-two percent of patients potentially at elevated risk for fractures did not have BMD testing completed; most common reasons for this were intention to order BMD later (48%), physician belief that BMD was not required (15%) and patient refusal (20%). For patients with BMD completed, fracture risk was calculated in 29%; 19% were at high risk, of whom 37% were not treated with osteoporosis medications as recommended by CPG. CONCLUSION Despite access to CPG and fracture risk calculators through the ADVANTAGE OP EMR tool, significant gaps remain in fracture risk calculation and osteoporosis management. Additional strategies are needed to address this clinical inertia among family physicians.
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Affiliation(s)
- A. Papaioannou
- McMaster University, Hamilton, Ontario Canada ,GERAS Centre for Aging Research, St. Peter’s Hospital, Hamilton Health Sciences, 88 Maplewood Ave, Hamilton, Ontario L8M 1W9 Canada
| | - E. McCloskey
- Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK
| | - A. Bell
- Department of Family and Community Medicine, University of Toronto, Ontario, Canada
| | - D. Ngui
- University of British Columbia, Vancouver, British Columbia Canada
| | - U. Mehan
- McMaster University, Hamilton, Ontario Canada ,Centre for Family Medicine Family Health Team, Kitchener, Ontario Canada
| | - M. Tan
- Canadian Centre for Professional Development in Health and Medicine, Toronto, Ontario Canada
| | - L. Goldin
- Canadian Centre for Professional Development in Health and Medicine, Toronto, Ontario Canada
| | - A. Langer
- Canadian Centre for Professional Development in Health and Medicine, Toronto, Ontario Canada
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Gayed D, Dinh D, Liang D, Tan M, Oquiel E, Duffy S, Ajani A, Brennan A, Clark D, Roberts L, Reid C, Freeman M. Is There a Mortality Benefit of Statin Use for Secondary Prevention of Coronary Artery Disease (CAD) in an Older Population? Insights from the Melbourne Interventional Group (MIG) Registry. Heart Lung Circ 2021. [DOI: 10.1016/j.hlc.2021.06.302] [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: 11/24/2022]
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Tan M, Dinh D, Gayed D, Liang D, Brennan A, Duffy S, Clark D, Ajani A, Oqueli E, Roberts L, Reid C, Freeman M, Chandrasekhar J. Associations Between DAPT Score and Long-term Mortality Post PCI. Heart Lung Circ 2021. [DOI: 10.1016/j.hlc.2021.06.260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Lim SM, Tan M, Sze YL, Au L. Letter to the Editor: Effects of the COVID-19 Pandemic on COVID-19 Negative Geriatric Patients with Hip Fractures. J Frailty Aging 2020; 10:75-76. [PMID: 33331628 PMCID: PMC7548523 DOI: 10.14283/jfa.2020.54] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Since December 2019, the novel coronavirus (COVID-19) had affected millions globally, particularly putting elderly and persons with chronic diseases at risk (1). 95% of all COVID-19 deaths in Singapore are older adults (2). As public health policymakers try to control the pandemic by focusing resources on COVID-19, the general population fear contracting coronavirus from hospitals, resulting in changes in their healthcare seeking behaviour. We describe two cases demonstrating the direct and indirect impact of COVID-19 to our geriatric patients in Singapore who have sustained hip fractures.
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Affiliation(s)
- S M Lim
- Dr Seok Mei Lim, Division of Geriatric Medicine, Ng Teng Fong General Hospital, 1 Jurong East Street 21, Singapore 609606, Email address: , Tel: +65 6716 2000, Fax: +65 6716 5500
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Tan M, Nyamundanda G, Fontana E, Hazell S, Ragulan C, Jones K, Abah B, Jacobs T, Bowes J, Sadanandam A, Huddart R. PO-1207: Exploring molecular subtype as a biomarker of radiation response in muscle-invasive bladder cancer. Radiother Oncol 2020. [DOI: 10.1016/s0167-8140(21)01225-1] [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: 11/15/2022]
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Hafeez S, Warren-Oseni K, Jones K, Amir E, Komel K, Dearnaley D, Harris V, Horwich A, Khan A, Kumar P, Lalondrelle S, McDonald F, Tan M, Thompson A, McNair H, Hansen V, Huddart R. Dose Escalated Adaptive Bladder Radiotherapy: Clinical Outcomes of a Phase I Study. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Luo Y, Wang P, Gu X, Ye J, Lin J, Tan M, Luo PT, Luo JT, Huang M. Placement of pelvic mesh prior to pelvic radiotherapy using FlexDex™ - a video vignette. Colorectal Dis 2020; 22:1458-1459. [PMID: 32336011 PMCID: PMC7818471 DOI: 10.1111/codi.15083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 04/02/2020] [Indexed: 02/08/2023]
Affiliation(s)
- Y. Luo
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - P. Wang
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - X. Gu
- Department of SurgeryThe People’s Hospital of Gaoming DistrictFoshanChina
| | - J. Ye
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - J. Lin
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - M. Tan
- SEOX Financial Quotient (Guangzhou) Education Technology LtdGuangzhouChina
| | - P. T. Luo
- Class 9 Grade 3The Affiliated Foreign Language School of SCNUGuangzhouChina
| | - J. T. Luo
- Class 6 Grade 1The Affiliated Foreign Language School of SCNUGuangzhouChina
| | - M. Huang
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
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Luo Y, Wang P, Gu X, Ye J, Lin J, Tan M, Luo PT, Luo JT, Huang M. Three-trocar tubeless natural orifice specimen extraction surgery in rectosigmoid cancer - a video vignette. Colorectal Dis 2020; 22:0. [PMID: 32336013 PMCID: PMC7818471 DOI: 10.1111/codi.15081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 03/26/2020] [Indexed: 02/08/2023]
Affiliation(s)
- Y. Luo
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - P. Wang
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - X. Gu
- Department of SurgeryThe People’s Hospital of Gaoming DistrictFoshanChina
| | - J. Ye
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - J. Lin
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
| | - M. Tan
- SEOX Financial Quotient (Guangzhou) Education Technology LtdGuangzhouChina
| | - P. T. Luo
- Class 9 Grade 3The Affiliated Foreign Language School of SCNUGuangzhouChina
| | - J. T. Luo
- Class 6 Grade 1The Affiliated Foreign Language School of SCNUGuangzhouChina
| | - M. Huang
- Department of Colorectal SurgeryGuangdong Institute of GastroenterologyGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseSupported by National Key Clinical DisciplineThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouChina
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Kirkwood J, Dummer R, Hauschild A, Santinami M, Atkinson V, Sileni VC, Larkin J, Nyakas M, Haydon A, Dutriaux C, Schachter J, Robert C, Mortier L, Banerjee H, Haas T, Tan M, Lau M, Schadendorf D, Long G, Mandala' M. 1100P Restricted mean survival time (RMST) and cure-rate modeling in estimating survival benefit with adjuvant dabrafenib (D) plus trametinib (T) treatment in melanoma. Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.1223] [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: 10/23/2022] Open
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Windon M, D'Souza G, Waterboer T, Rooper L, Westra W, Troy T, Pardoll D, Tan M, Yavvari S, Kiess A, Miles B, Mydlarz W, Ha P, Bender N, Eisele D, Fakhry C. Risk Factors for Human Papillomavirus-Positive Nonoropharyngeal Squamous Cell Carcinoma. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2019.11.176] [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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He L, Liu L, Guan S, Zheng X, Ge H, Yin C, Shen Y, Tan M, Wang C, Gao Y, Xiong W. Palmatine alleviates hyperalgesia by inhibiting the expression of calcitonin gene-related peptide in the trigeminal ganglion of rats with chronic constriction injury of the infraorbital nerve. Br J Oral Maxillofac Surg 2020; 58:443-450. [PMID: 32139146 DOI: 10.1016/j.bjoms.2020.01.031] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 01/31/2020] [Indexed: 12/22/2022]
Abstract
Trigeminal neuralgia is one of the most common of the neuropathic pains, and it can seriously influence patients' quality of life. Calcitonin gene-related peptide (CGRP) is a type of nociceptive neurotransmitter that is expressed in neurons of the trigeminal ganglion and plays a major part in transmitting pain. The rat model of trigeminal neuralgia was established by causing a chronic constriction injury of the infraorbital nerve (CCI-ION). Male Sprague-Dawley rats (n=24) were randomly divided into a sham control group (sham, n=6), sham-treated with palmatine group (sham+palmatine, n=6), trigeminal nerve model group (TN, n=6), and trigeminal nerve treated with palmatine group (TN+palmatine, n=6). Fifteen days after the operation the mechanical response threshold was decreased in the TN group compared with the sham group. From postoperative day 7 to day 15, the mechanical response threshold in the TN+palmatine group significantly increased compared with the TN group. On postoperative day 15 the results of quantitative polymerase chain reaction (qPCR), immunohistochemical staining, and western blotting showed an obvious increase in expression of CGRP and its receptors, serum concentrations of interleukin-1β (IL-1β), and tumour necrosis factor-α (TNF-α), and phosphorylation of protein kinase C (PKC) in the trigeminal ganglia of the TN group compared with the sham group, but these increases could be down-regulated by treatment with palmatine. Palmatine might therefore have therapeutic potential for the treatment of trigeminal neuralgia by inhibiting the expression of CGRP and its receptors in trigeminal ganglia, suppressing the serum concentrations of IL-1β and TNF-α, and decreasing the phosphorylation of PKC in the trigeminal ganglia of affected rats.
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Affiliation(s)
- L He
- Affiliated Stomatological Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - L Liu
- Affiliated Stomatological Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - S Guan
- Department of Physiology, Basic Medical College, Nanchang University, Nanchang, Jiangxi, China
| | - X Zheng
- Queen Mary college of grade 2015, Nanchang University, Nanchang, Jiangxi, China
| | - H Ge
- Department of Physiology, Basic Medical College, Nanchang University, Nanchang, Jiangxi, China
| | - C Yin
- Affiliated Stomatological Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Y Shen
- Department of Physiology, Basic Medical College, Nanchang University, Nanchang, Jiangxi, China
| | - M Tan
- Department of Physiology, Basic Medical College, Nanchang University, Nanchang, Jiangxi, China
| | - C Wang
- Second Clinic Medical College of Grade 2017, Nanchang University, Nanchang, Jiangxi, China
| | - Y Gao
- Department of Physiology, Basic Medical College, Nanchang University, Nanchang, Jiangxi, China; Jiangxi Provincial Key Laboratory of Autonomic Nervous Function and Disease, Nanchang, Jiangxi, China
| | - W Xiong
- Affiliated Stomatological Hospital of Nanchang University, Nanchang, Jiangxi, China; Jiangxi Provincial Key Laboratory of Oral Biomedicine, Nanchang, Jiangxi, China.
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Liao X, Li YJ, Zhong F, Chen Y, Tan M, Liao YR, Gao Y. [Clinical analysis of seven cases with primary hyperoxaluria type 1 in children]. Zhonghua Er Ke Za Zhi 2020; 58:129-134. [PMID: 32102150 DOI: 10.3760/cma.j.issn.0578-1310.2020.02.012] [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 investigate the clinical, imaging and molecular characteristics of primary hyperoxaluria type 1 (PH1) in children and to sum up existing evidence for further understanding the phenotype-genotype correlation of infantile PH1. Methods: This retrospective analysis was based on the medical records of children with PH1 diagnosed by gene test in the Department of Nephrology, Guangzhou Women and Children's Medical Center from June 2016 to May 2019. Targeted exome sequencing was performed on tubular disease-related genes of the probands and Sanger sequencing was conducted to validate suspected pathogenic variants of family members. Logistic regression analysis of NC and CCr was adopted to show the relation between NC and renal function. The literature review was conducted, and the clinical, imaging and molecular biogenetic characteristics of the disease were analyzed and summarized. Results: A total of 7 children from 6 families were enrolled. The median age of onset was 5 months. The median age of diagnosis was 8 months. Five cases had progressed to end-stage renal disease (ESRD), one case had chronic kidney disease (CKD) stage 1, and the other one had CKD stage 2. Four cases died, one case maintained on hemodialysis, and the other two non-dialysis cases were followed up. Among the 7 cases, 4 patients had infantile PH1, 1 patient had child and adolescent type, 1 patient had family type and the other one had unknown classification. There were two siblings (the younger brother had uremia and the sister had normal renal function) who had the delayed diagnosis for 5 and 3 years respectively. All patients in this cohort had proteinuria and microscopic hematuria, but no patients had gross hematuria. Three cases had hypercalciuria. Comprehensive diagnostic imaging evaluation include CT scan, MR scan, radiography and ultrasound led to the diagnosis of nephrocalcinosis (NC) in 5 cases, including 4 cases of simple NL and 1 case of NC with nephrolithiasis (NL), 1 case of multiple NL and 1 case of microcrystal deposition in renal medulla. However, only one case of NC was identified by ultrasound, the other 4 cases of NC were identified by radiograph examination. In the logistic regression analysis involving NC and creatinine clearnce rate (CCr), the results showed that NC was an independent risk factor for renal dysfunction (OR 2.5, 95%CI 0.7-1.2, P<0.05). All the 7 cases had AGXT gene variant, including homozygous variant in 4 cases and compound heterozygous variant in 3 cases. A total of 9 variant genotypes were found, and exon 6 variants were found in 4 children. Among them, there were 3 cases with c.679_680delAA. To our knowledge, both c.679_680delAA and c.190A>T in the cohort have not been reported previously. Conclusions: Infantile PH1 is the most common type of PH1 in children, which progresses rapidly or even begins with renal failure, with poor prognosis. It is also highly heterogeneous in phenotype and genotype. NC is an independent risk factor leading to renal failure. Radiograph examination showed high specificity for the diagnosis of NC. At present, the misdiagnosis and delayed diagnosis of PH1 are still common in China. It is of great significance to carry out quantitative determination of uric oxalate in order to reduce the misdiagnosis rate and enhance follow-up technologies for evaluating the therapeutic effect.
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Affiliation(s)
- X Liao
- Department of Nephrology, Guangzhou Women and Children's Medical Center, Guangzhou 510120, China
| | - Y J Li
- Department of Nephrology, Guangzhou Women and Children's Medical Center, Guangzhou 510120, China
| | - F Zhong
- Department of Nephrology, Guangzhou Women and Children's Medical Center, Guangzhou 510120, China
| | - Y Chen
- Department of Nephrology, Guangzhou Women and Children's Medical Center, Guangzhou 510120, China
| | - M Tan
- Department of Nephrology, Guangzhou Women and Children's Medical Center, Guangzhou 510120, China
| | - Y R Liao
- Department of Nephrology, Guangzhou Women and Children's Medical Center, Guangzhou 510120, China
| | - Y Gao
- Department of Nephrology, Guangzhou Women and Children's Medical Center, Guangzhou 510120, China
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Moosburner MA, Gholami P, McCarthy JK, Tan M, Bielinski VA, Allen AE. Multiplexed Knockouts in the Model Diatom Phaeodactylum by Episomal Delivery of a Selectable Cas9. Front Microbiol 2020; 11:5. [PMID: 32047486 PMCID: PMC6997545 DOI: 10.3389/fmicb.2020.00005] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 01/03/2020] [Indexed: 11/13/2022] Open
Abstract
Marine diatoms are eukaryotic microalgae that play significant ecological and biogeochemical roles in oceans. They also have significant potential as organismal platforms for exploitation to address biotechnological and industrial goals. In order to address both modes of research, sophisticated molecular and genetic tools are required. We presented here new and improved methodologies for introducing CRISPR-Cas9 to the model diatom Phaeodactylum tricornutum cells and a streamlined protocol for genotyping mutant cell lines with previously unknown phenotypes. First, bacterial-conjugation was optimized for the delivery of Cas9 by transcriptionally fusing Cas9 to a selectable marker by the 2A peptide. An episome cloning strategy using both negative and positive selection was developed to streamline CRISPR-episome assembly. Next, cell line picking and genotyping strategies, that utilize manual sequencing curation, TIDE sequencing analysis, and a T7 endonuclease assay, were developed to shorten the time required to generate mutants. Following this new experimental pipeline, both single-gene and two-gene knockout cell lines were generated at mutagenesis efficiencies of 48% and 25%, respectively. Lastly, a protocol for precise gene insertions via CRISPR-Cas9 targeting was developed using particle-bombardment transformation methods. Overall, the novel Cas9 episome design and improved genotyping methods presented here allow for quick and easy genotyping and isolation of Phaeodactylum mutant cell lines (less than 3 weeks) without relying on a known phenotype to screen for mutants.
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Affiliation(s)
- Mark Andrew Moosburner
- Integrative Oceanography Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States.,J. Craig Venter Institute, La Jolla, CA, United States
| | | | | | - Maxine Tan
- Integrative Oceanography Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States.,J. Craig Venter Institute, La Jolla, CA, United States
| | | | - Andrew E Allen
- Integrative Oceanography Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States.,J. Craig Venter Institute, La Jolla, CA, United States
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