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Adhikari K, Teare GF, Belon AP, Lee B, Kim MO, Nykiforuk C. Screening, brief intervention, and referral to treatment for tobacco consumption, alcohol misuse, and physical inactivity: an equity-informed rapid review. Public Health 2024; 226:237-247. [PMID: 38091812 DOI: 10.1016/j.puhe.2023.11.001] [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: 12/30/2022] [Revised: 09/26/2023] [Accepted: 11/01/2023] [Indexed: 01/15/2024]
Abstract
OBJECTIVE This rapid review systematically synthesizes evidence of the effectiveness of the Screening, Brief Intervention, and Referral (SBIR/T) approach for tobacco use, alcohol misuse, and physical inactivity. STUDY DESIGN This was a rapid review. METHODS We searched primary studies between 2012 and 2022 in seven electronic databases. The search strategy used concepts related to alcohol-related disorders, intoxication, cigarette, nicotine, physical activity, exercise, sedentary, screening, therapy, and referral. We reviewed both title/abstract and full-text using a priori set inclusion and exclusion criteria to identify the eligible studies. We appraised study quality, extracted data, and summarized the characteristics of the included studies. We applied health equity lenses in the synthesis. RESULTS Of the 44 included studies, most focused on alcohol misuse. SBIR/T improved patients' attitudes toward alcohol behavior change, improved readiness and referral initiation for change, and effectively reduced alcohol consumption. Few studies pertained to smoking and physical inactivity. Most studies on smoking demonstrated effectiveness pertaining to patients' acceptance of referral recommendations, improved readiness and attempts to quitting smoking, and reduced or cessation of smoking. Findings were mixed about the effectiveness of SBIR/T in improving physical activity. Minimal studies exist on the impacts of SBIR/T for these three risk factors on healthcare resource use or costs. Studies considering diverse population characteristics in the design and effectiveness assessment of the SBIR/T intervention are lacking. CONCLUSIONS More research on the impacts of SBIR/T on tobacco use, alcohol misuse, and physical inactivity is required to inform the planning and delivery of SBIR/T for general and disadvantaged populations.
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Affiliation(s)
- K Adhikari
- Provincial Population and Public Health, Alberta Health Services, Canada; Department of Community Health Sciences, University of Calgary, Canada.
| | - G F Teare
- Provincial Population and Public Health, Alberta Health Services, Canada; Department of Community Health Sciences, University of Calgary, Canada
| | - A P Belon
- Centre for Healthy Communities, School of Public Health, University of Alberta, Canada
| | - B Lee
- Centre for Healthy Communities, School of Public Health, University of Alberta, Canada
| | - M O Kim
- Centre for Healthy Communities, School of Public Health, University of Alberta, Canada
| | - C Nykiforuk
- Centre for Healthy Communities, School of Public Health, University of Alberta, Canada
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Oguntuyo KY, Haas GD, Azarm KD, Stevens CS, Brambilla L, Kowdle S, Avanzato VA, Pryce R, Freiberg AN, Bowden TA, Lee B. Structure guided mutagenesis of Henipavirus Receptor Binding Proteins reveals molecular determinants of receptor usage and antibody binding epitopes. bioRxiv 2023:2023.11.22.568281. [PMID: 38045373 PMCID: PMC10690272 DOI: 10.1101/2023.11.22.568281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Nipah virus (NiV) is a highly lethal, zoonotic henipavirus (HNV) that causes respiratory and neurological signs and symptoms in humans. Similar to other paramyxoviruses, HNVs mediate entry into host cells through the concerted actions of two surface glycoproteins: a receptor binding protein (RBP) that mediates attachment and a fusion glycoprotein (F) that triggers fusion in an RBP-dependent manner. NiV uses ephrin-B2 (EFNB2) and ephrin-B3 (EFNB3) as entry receptors. Ghana virus (GhV), a novel HNV identified in a Ghanaian bat, use EFNB2 but not EFNB3. In this study, we employ a structure-informed approach to identify receptor interfacing residues and systematically introduce GhV-RBP residues into a NiV-RBP backbone to uncover the molecular determinants of EFNB3 usage. We reveal two regions that severely impair EFNB3 binding by NiV-RBP and EFNB3-mediated entry by NiV pseudotyped viral particles. Further analyses uncovered two point mutations (NiVN557SGhV and NiVY581TGhV) pivotal for this phenotype. Moreover, we identify NiV interaction with Y120 of EFNB3 as important for usage of this receptor. Beyond these EFNB3-related findings, we reveal two domains that restrict GhV binding of EFNB2, identify the HNV-head as an immunodominant target for polyclonal and monoclonal antibodies, and describe putative epitopes for GhV and NiV-specific monoclonal antibodies. Cumulatively, the work presented here generates useful reagents and tools that shed insight to residues important for NiV usage of EFNB3, reveals regions critical for GhV binding of EFNB2, and describes putative HNV antibody binding epitopes.
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Affiliation(s)
- K Y Oguntuyo
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - G D Haas
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - K D Azarm
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - C S Stevens
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - L Brambilla
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - S Kowdle
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - V A Avanzato
- Division of Structural Biology, Wellcome Center for Human Genetics, University of Oxford, OX3 7BN Oxford, United Kingdom
| | - R Pryce
- Division of Structural Biology, Wellcome Center for Human Genetics, University of Oxford, OX3 7BN Oxford, United Kingdom
| | - A N Freiberg
- Department of Pathology, University of Texas Medical Branch, Galveston, TX, USA
| | - T A Bowden
- Division of Structural Biology, Wellcome Center for Human Genetics, University of Oxford, OX3 7BN Oxford, United Kingdom
| | - B Lee
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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3
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Nasief HG, Parchur AK, Antunes JT, Lee B, Nelson AS, Paulson ES, Li A. Integrating a Tool to Automatically Determine Necessity of Online Adaptive Replanning. Int J Radiat Oncol Biol Phys 2023; 117:e701. [PMID: 37786057 DOI: 10.1016/j.ijrobp.2023.06.2187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) As online adaptive replanning (OLAR) is labor-intensive and time-consuming, it's desirable to determine when OLAR is necessary before OLAR is initiated. We have previously reported a novel method to automatically determine the necessity of OLAR using machine leaning algorithms based on the structural similarity maps (SSIM) and wavelet texture maps (WMT) extracted from the daily MRI during MR-guided adaptive radiation therapy (MRgART). This study aims to integrate this method into a commercial software platform that has been used during our routine MRgART. MATERIALS/METHODS The method of automatically determining the necessity of OLAR based on daily MRI was implemented and integrated into the software platform through a specifically developed workflow. The obtained workflow was tested using 25 daily MRI sets acquired from 5 patients with pancreatic cancer in the following procedure: 1) rigidly registering the daily and reference MRIs, 2) identifying the region enclosed by the 50-100% iso-dose surfaces on the daily MRI by transferring the iso-dose surfaces from the reference to the daily MRIs, 3) launching our in-house codes to calculate significant changes in textures extracted from SSIM and WMT maps, 4) inputting the feature values into the pre-trained classifier models for SSIM and WMT, and 5) outputting results considering the WMT based prediction as the primary indicator and the SSIM-based as the secondary (validation) indicator on whether OLAR is needed for the daily MRI. RESULTS The execution of the developed workflow was fast and can be used to streamline the process. It provides the ability to scroll through the images for better decision making while providing quantitative prediction within 30-38 seconds. Eighty percent of the daily MRIs required OLAR. The SSIM map displayed was able to successfully captured the areas of similarity between the reference and daily MRIs and the WMT prediction agreed with the prediction class. CONCLUSION The integration of the prediction method for automatically determining the necessity of OLAR based on two independent machine learning classifiers into a commercially available software is feasible and can be used to streamline the process of MRgART. With larger verification studies, this workflow-based tool may be developed into a generalized tool that assist in OLAR using different platforms.
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Affiliation(s)
- H G Nasief
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - A K Parchur
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | | | - B Lee
- MIM Software Inc, Cleveland, OH
| | | | - E S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
| | - A Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI
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Welikhe P, Williams MR, King K, Bos J, Akland M, Baffaut C, Beck EG, Bierer A, Bosch DD, Brooks ES, Buda AR, Cavigelli M, Faulkner J, Feyereisen GW, Fortuna A, Gamble J, Hanrahan BR, Hussain MZ, Kovar JL, Lee B, Leytem AB, Liebig MA, Line D, Macrae ML, Moorman TB, Moriasi D, Mumbi R, Nelson N, Ortega-Pieck A, Osmond D, Penn C, Pisani O, Reba ML, Smith DR, Unrine J, Webb P, White KE, Wilson H, Witthaus LM. Uncertainty in phosphorus fluxes and budgets across the U.S. long-term agroecosystem research network. J Environ Qual 2023. [PMID: 37145888 DOI: 10.1002/jeq2.20485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 02/28/2023] [Accepted: 04/21/2023] [Indexed: 05/07/2023]
Abstract
Phosphorus (P) budgets can be useful tools for understanding nutrient cycling and quantifying the effectiveness of nutrient management planning and policies; however, uncertainties in agricultural nutrient budgets are not often quantitatively assessed. The objective of this study was to evaluate uncertainty in P fluxes (fertilizer/manure application, atmospheric deposition, irrigation, crop removal, surface runoff, leachate) and the propagation of these uncertainties to annual P budgets. Data from 56 cropping systems in the P-FLUX database, which spans diverse rotations and landscapes across the U.S. and Canada, were evaluated. Results showed that across cropping systems, average annual P budget was 22.4 kg P ha-1 (range = -32.7 to 340.6 kg P ha-1 ), with an average uncertainty of 13.1 kg P ha-1 (range = 1.0 to 87.1 kg P ha-1 ). Fertilizer/manure application and crop removal were the largest P fluxes across cropping systems and, as a result, accounted for the largest fraction of uncertainty in annual budgets (61 and 37%, respectively). Remaining fluxes individually accounted for <2% of the budget uncertainty. Uncertainties were large enough that determining whether P was increasing, decreasing, or not changing was inconclusive in 39% of the budgets evaluated. Findings indicate that more careful and/or direct measurements of inputs, outputs, and stocks are needed. Recommendations for minimizing uncertainty in P budgets based on the results of the study were developed. Quantifying, communicating, and constraining uncertainty in budgets among production systems and multiple geographies is critical for engaging stakeholders, developing local and national strategies for P reduction, and informing policy. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- P Welikhe
- Department of Agronomy, Purdue University
- National Soil Erosion Research Laboratory, USDA-ARS
| | - M R Williams
- National Soil Erosion Research Laboratory, USDA-ARS
| | - K King
- Soil Drainage Research Unit, USDA-ARS
| | - J Bos
- National Soil Erosion Research Laboratory, USDA-ARS
| | - M Akland
- Department of Plant and Soil Sciences, University of Kentucky
| | - C Baffaut
- Cropping Systems and Water Quality Research Unit, USDA-ARS
| | | | - A Bierer
- Northwest Irrigation and Soils Research Lab, USDA-ARS
| | - D D Bosch
- Southeast Watershed Research Laboratory, USDA-ARS
| | - E S Brooks
- Department of Soil and Water Resources, University of Idaho
| | - A R Buda
- Pasture Systems and Watershed Management Research Unit, USDA-ARS
| | - M Cavigelli
- Sustainable Agricultural Systems Lab, USDA-ARS
| | - J Faulkner
- Department of Plant and Soil Science, University of Vermont
| | | | - A Fortuna
- Grazinglands Research Laboratory, USDA-ARS
| | - J Gamble
- Plant Science Research Unit, USDA-ARS
| | | | - M Z Hussain
- W.K. Kellogg Biological Station, Michigan State University
| | - J L Kovar
- National Laboratory for Agriculture and the Environment, USDA-ARS
| | - B Lee
- Department of Plant and Soil Sciences, University of Kentucky
| | - A B Leytem
- Northwest Irrigation and Soils Research Lab, USDA-ARS
| | - M A Liebig
- Northern Great Plains Research Laboratory, USDA-ARS
| | - D Line
- Department of Crop and Soil Sciences, North Carolina State University
| | - M L Macrae
- Department of Geography and Environmental Management, University of Waterloo
| | - T B Moorman
- National Laboratory for Agriculture and the Environment, USDA-ARS
| | - D Moriasi
- Grazinglands Research Laboratory, USDA-ARS
| | - R Mumbi
- Department of Agronomy, Purdue University
- National Soil Erosion Research Laboratory, USDA-ARS
| | - N Nelson
- Department of Agronomy, Kansas State University
| | - A Ortega-Pieck
- Department of Soil and Water Resources, University of Idaho
| | - D Osmond
- Department of Crop and Soil Sciences, North Carolina State University
| | - C Penn
- National Soil Erosion Research Laboratory, USDA-ARS
| | - O Pisani
- Southeast Watershed Research Laboratory, USDA-ARS
| | - M L Reba
- Delta Water Management Research Unit, USDA-ARS
| | - D R Smith
- Grassland, Soil and Water Research Laboratory, USDA-ARS
| | - J Unrine
- Department of Plant and Soil Sciences, University of Kentucky
- Kentucky Water Resources Research Institute
| | - P Webb
- Department of Crop, Soil, and Environmental Sciences, University of Arkansas
| | - K E White
- Sustainable Agricultural Systems Lab, USDA-ARS
| | - H Wilson
- Agriculture and Agri-Food Canada, Science and Technology Branch, Brandon Research and Development Centre
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Khan SU, Ullah I, Ullah N, Shah S, Affendi ME, Lee B. A novel CT image de-noising and fusion based deep learning network to screen for disease (COVID-19). Sci Rep 2023; 13:6601. [PMID: 37088788 PMCID: PMC10122759 DOI: 10.1038/s41598-023-33614-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 04/15/2023] [Indexed: 04/25/2023] Open
Abstract
A COVID-19, caused by SARS-CoV-2, has been declared a global pandemic by WHO. It first appeared in China at the end of 2019 and quickly spread throughout the world. During the third layer, it became more critical. COVID-19 spread is extremely difficult to control, and a huge number of suspected cases must be screened for a cure as soon as possible. COVID-19 laboratory testing takes time and can result in significant false negatives. To combat COVID-19, reliable, accurate and fast methods are urgently needed. The commonly used Reverse Transcription Polymerase Chain Reaction has a low sensitivity of approximately 60% to 70%, and sometimes even produces negative results. Computer Tomography (CT) has been observed to be a subtle approach to detecting COVID-19, and it may be the best screening method. The scanned image's quality, which is impacted by motion-induced Poisson or Impulse noise, is vital. In order to improve the quality of the acquired image for post segmentation, a novel Impulse and Poisson noise reduction method employing boundary division max/min intensities elimination along with an adaptive window size mechanism is proposed. In the second phase, a number of CNN techniques are explored for detecting COVID-19 from CT images and an Assessment Fusion Based model is proposed to predict the result. The AFM combines the results for cutting-edge CNN architectures and generates a final prediction based on choices. The empirical results demonstrate that our proposed method performs extensively and is extremely useful in actual diagnostic situations.
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Affiliation(s)
- Sajid Ullah Khan
- Multimedia Information Processing Lab, Department of Information and Communication Engineering, Chosun University, Gwangju, South Korea
| | - Imdad Ullah
- Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Najeeb Ullah
- Department of Computer Science, University of Engineering &Technology, Mardan, KPK, Pakistan
| | - Sajid Shah
- EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia
| | - Mohammed El Affendi
- EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia
| | - Bumshik Lee
- Multimedia Information Processing Lab, Department of Information and Communication Engineering, Chosun University, Gwangju, South Korea.
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Go SM, Lee B, Ahn C, Jeong SH, Jo NR, Park SM, Lee M, Tran DN, Jung EM, Lee SD, Jeung EB. Initial phase establishment of an in vitro method for developmental neurotoxicity test using Ki-67 in human neural progenitor cells. J Physiol Pharmacol 2023; 74. [PMID: 37453095 DOI: 10.26402/jpp.2023.2.07] [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] [Received: 11/26/2022] [Accepted: 04/30/2023] [Indexed: 07/18/2023]
Abstract
Building a precise alternative neurotoxicological test is of great importance to respond to societal and ethical requirements. In this study, a new developmental neurotoxicity test (DNT) was established with the human neural progenitor cell line. ReNcell CX cells were exposed to neurotoxic chemicals (aphidicolin, hydroxyurea, cytosine arabinoside, 5-fluorouracil, and ochratoxin A) or non-neurotoxic chemicals (sodium gluconate, sodium bicarbonate, penicillin G, and saccharin). Propidium iodide (PI) was used to evaluate cell viability. BrdU and Ki-76 were employed to determine cell proliferation. Based on the cell viability and proliferation, mathematical models were built by linear discriminant analysis. Furthermore, the neurotoxic-considered chemicals inhibited cell cycle progression at the protein level, supporting the biomolecular rationale for the predictive model. Overall, these results show that the new test method can be used to determine the potential developmental neurotoxicants or new drug candidates.
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Affiliation(s)
- S M Go
- Laboratory of Veterinary Biochemistry and Molecular Biology, College of Veterinary Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea
| | - B Lee
- Laboratory of Veterinary Biochemistry and Molecular Biology, College of Veterinary Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea
| | - C Ahn
- Laboratory of Veterinary Physiology, College of Veterinary Medicine, Jeju National University, Jeju, 63243, Republic of Korea
| | - S H Jeong
- Laboratory of Veterinary Biochemistry and Molecular Biology, College of Veterinary Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea
| | - N R Jo
- Department of Information and Statistics, College of Natural Sciences, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea
| | - S M Park
- Laboratory of Veterinary Biochemistry and Molecular Biology, College of Veterinary Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea
| | - M Lee
- Laboratory of Veterinary Biochemistry and Molecular Biology, College of Veterinary Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea
| | - D N Tran
- Laboratory of Veterinary Biochemistry and Molecular Biology, College of Veterinary Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea
| | - E-M Jung
- Department of Molecular Biology, College of Natural Sciences, Pusan National University, Busan 46241, Republic of Korea
| | - S D Lee
- Department of Information and Statistics, College of Natural Sciences, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea
| | - E-B Jeung
- Laboratory of Veterinary Biochemistry and Molecular Biology, College of Veterinary Medicine, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea.
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Gamlin CR, Schneider-Mizell CM, Mallory M, Elabbady L, Gouwens N, Williams G, Mukora A, Dalley R, Bodor A, Brittain D, Buchanan J, Bumbarger D, Kapner D, Kinn S, Mahalingam G, Seshamani S, Takeno M, Torres R, Yin W, Nicovich PR, Bae JA, Castro MA, Dorkenwald S, Halageri A, Jia Z, Jordan C, Kemnitz N, Lee K, Li K, Lu R, Macrina T, Mitchell E, Mondal SS, Mu S, Nehoran B, Popovych S, Silversmith W, Turner NL, Wong W, Wu J, Yu S, Berg J, Jarsky T, Lee B, Seung HS, Zeng H, Reid RC, Collman F, da Costa NM, Sorensen SA. Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types. bioRxiv 2023:2023.03.22.533857. [PMID: 36993629 PMCID: PMC10055412 DOI: 10.1101/2023.03.22.533857] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types 1 . Neural cell types have previously been defined by morphology 2, 3 , electrophysiology 4, 5 , transcriptomic expression 6-8 , connectivity 9-13 , or even a combination of such modalities 14-16 . More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells 17-20 . Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex 21 . It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type 22, 23 known to be Somatostatin positive (Sst+) 24, 25 , were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types.
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8
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Hossain S, Lee B. NG-GAN: A Robust Noise-Generation Generative Adversarial Network for Generating Old-Image Noise. Sensors (Basel) 2022; 23:251. [PMID: 36616850 PMCID: PMC9823480 DOI: 10.3390/s23010251] [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] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
Numerous old images and videos were captured and stored under unfavorable conditions. Hence, old images and videos have uncertain and different noise patterns compared with those of modern ones. Denoising old images is an effective technique for reconstructing a clean image containing crucial information. However, obtaining noisy-clean image pairs for denoising old images is difficult and challenging for supervised learning. Preparing such a pair is expensive and burdensome, as existing denoising approaches require a considerable number of noisy-clean image pairs. To address this issue, we propose a robust noise-generation generative adversarial network (NG-GAN) that utilizes unpaired datasets to replicate the noise distribution of degraded old images inspired by the CycleGAN model. In our proposed method, the perception-based image quality evaluator metric is used to control noise generation effectively. An unpaired dataset is generated by selecting clean images with features that match the old images to train the proposed model. Experimental results demonstrate that the dataset generated by our proposed NG-GAN can better train state-of-the-art denoising models by effectively denoising old videos. The denoising models exhibit significantly improved peak signal-to-noise ratios and structural similarity index measures of 0.37 dB and 0.06 on average, respectively, on the dataset generated by our proposed NG-GAN.
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Ko R, Yu Z, Prajapati S, Lee B, Albert R, Daniel A, Nguyen Q, Choi S, Msaouel P, Kudchadker R, Gomez D, Tang C. Neuromuscular Toxicity and Dose-Volume Relationships Following SBRT for Bone Oligometastases: Post-Hoc Analysis of Two Ongoing Clinical Trials. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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10
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Lee B, Kim BG, Baraki TG, Kim JS, Lee YJ, Lee SJ, Hong SJ, Ahn CM, Shin DH, Kim BK, Ko YG, Choi DH, Honh MK, Jang YS. Stent expansion evaluated by optical coherence tomography and subsequent outcomes. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.1203] [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: 11/12/2022] Open
Abstract
Abstract
Background
Regarding stent expansion indexes, previous optical coherence tomography (OCT) studies have shown minimal stent area (MSA) to be most predictive of adverse events.
Purpose
We sought to evaluate the impact of various stent expansion indexes by post-stent OCT on long-term clinical outcomes, and hence to find OCT-defined optimal stent expansion criteria.
Methods
Of the patients registered in the Yonsei OCT registry, a total of 1071 patients with 1123 native coronary artery lesions treated with new-generation drug-eluting stents under the OCT guidance and analyzable final post-stent OCT were included. Stent expansion indexes and different suboptimal stent expansion criteria were evaluated for their association with device-oriented clinical endpoints (DoCE) including cardiac death, target vessel-related myocardial infarction (TVMI) or stent thrombosis, and target lesion revascularization. Major safety events (MSE) included cardiac death, TVMI or stent thrombosis.
Results
The median follow-up period was 40.6 (interquartile range 22.0–50.0) months. As a continuous variable, MSA, adaptive volumetric stent expansion (stent volume/adaptive reference lumen volume) and overall volumetric stent expansion (stent volume/post-stent lumen volume) were significantly predictive of DoCE. As a categorical criteria, MSA <5.0 mm2 (hazard ratio [HR] 3.80; 95% confidence interval [CI] 1.53–9.45), MSA/distal reference lumen area <90% (HR 2.13; 95% CI 1.10–4.14), and overall volumetric stent expansion ≥96.6% (HR 2.38; 95% CI 1.09–5.22) were independently associated with DoCE after adjusting for confounders, and a total malapposition volume ≥7.0 mm3 (HR 3.38; 95% CI 1.05–10.93) was linked to MSE.
Conclusions
This OCT study highlights that sufficient stent expansion to achieve adequate absolute MSA and relative MSA by distal reference lumen area and alleviate significant malapposition is important to improve clinical outcome, but overall stent overexpansion may have deleterious effect.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- B Lee
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - B G Kim
- Sanggye Paik Hospital , Seoul , Korea (Republic of)
| | - T G Baraki
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - J S Kim
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - Y J Lee
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - S J Lee
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - S J Hong
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - C M Ahn
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - D H Shin
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - B K Kim
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - Y G Ko
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - D H Choi
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - M K Honh
- Severance Hospital, Cardiology , Seoul , Korea (Republic of)
| | - Y S Jang
- Cha Bundang Medical Center, cardiology , Seongnam , Korea (Republic of)
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Kwon S, Choi EK, Lee SR, Ahn HJ, Lee B, Oh S, Lip GYH. Atrial fibrillation detection in ambulatory patients using a smart ring powered by deep learning analysis of continuous photoplethysmography monitoring. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.415] [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: 11/12/2022] Open
Abstract
Abstract
Background
Atrial fibrillation (AF) detection could be effective with photoplethysmography (PPG) signal monitoring by a wearable device.
Purpose
We aimed to validate the performance of AF detection among ambulatory patients who underwent electrical cardioversion for AF using a smart ring capable of continuous PPG monitoring and deep learning analysis.
Methods
In this prospective single-arm study, participants who underwent successful electrical cardioversion for AF were enrolled. The participants equipped a smart ring (CardioTracker, Sky Labs Inc., Seongnam, Republic of Korea) after the electrical cardioversion. The smart ring then continuously monitored PPG over 14 days to detect AF recurrence. The smart ring alarmed AF episodes based on deep learning analysis of PPG. The participants were asked to measure at least three daily ECGs using the smart ring to validate AF recurrence detected by PPG. All ECG snapshots were recorded along with lead I and saved with simultaneous PPG. ECG data were examined by the three cardiologists independently (SK, SRL, and EKC). The monitoring time, analyzable proportions of monitored signals, detection rates of AF episodes, and the diagnostic performance of PPG-based deep learning were evaluated. At the end of the monitoring, a survey on the use of the smart ring was performed.
Results
A total of 35 participants (mean age 58.9 years, male 74.3%) were enrolled. Figure 1 illustrates an example of PPG monitoring and PPG-ECG snapshots by the smart ring. The study participation period was a median of 14 days and the wearing time of the smart ring was a median of 9.2 days (IQR 7.1–11.5 days). Signal artifacts during daily activity decreased the analyzable proportions of monitored PPG by 68.5%. Irregular pulse episodes were detected by the smart ring in 29 (82.9%) participants after a median of 1 day from the cardioversion (Figure 2). A total of 2532 PPG-ECG snapshots were acquired and 1623 (64.1%) were interpretable by both the cardiologists (using ECG) and the deep learning analysis (using PPG). Comparing PPG by simultaneous ECG, the performance of AF detection by the smart ring was 98.7% for sensitivity, 97.8% for specificity, 2.2% for false positives, and 1.3% for false negatives (Figure 2). After using the smart ring, 76.9% of the participants responded that they had no discomfort in using the smart ring in daily activity and another 76.9% responded that it was helpful to monitor their disease.
Conclusion
Despite the signal artifacts during daily activity, AF detection with PPG monitoring by a smart ring could be effective for AF screening among ambulatory patients.
Funding Acknowledgement
Type of funding sources: Private company. Main funding source(s): This work was supported by Sky Labs Inc, Seongnam, Republic of Korea, and by the grant No. 0320202040 from the Seoul National University Hospital Research Fund.
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Affiliation(s)
- S Kwon
- Seoul National University Hospital , Seoul , Korea (Republic of)
| | - E K Choi
- Seoul National University Hospital , Seoul , Korea (Republic of)
| | - S R Lee
- Seoul National University Hospital , Seoul , Korea (Republic of)
| | - H J Ahn
- Seoul National University Hospital , Seoul , Korea (Republic of)
| | - B Lee
- Sky Labs Inc. , Seongnam , Korea (Republic of)
| | - S Oh
- Seoul National University Hospital , Seoul , Korea (Republic of)
| | - G Y H Lip
- Liverpool Heart and Chest Hospital , Liverpool , United Kingdom
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Mynard N, McGraw T, Lee B, Villena-Vargas J, Chow O, Harrison S, Port J, Altorki N. EP02.04-004 Time to Surgery After Neoadjuvant Immunotherapy: Not a Day Too Soon. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.389] [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: 10/14/2022]
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Lee B, Bang Y, Lim S, Kang S, Park C, Kim H, Kim T. 067 Dissecting circulating regulatory T cells in severe Korean psoriasis patients by mass cytometry. J Invest Dermatol 2022. [DOI: 10.1016/j.jid.2022.05.121] [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: 10/17/2022]
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14
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Wahid S, Lee B, Kim I. Effect of purified docosahexaenoic acid supplementation
on production performance, meat quality,
and intestinal microbiome of finishing pigs. J Anim Feed Sci 2022. [DOI: 10.22358/jafs/150033/2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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15
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Naing A, Mamdani H, Barve M, Johnson M, Wolff R, Kim D, Yang S, Lee B, Adebanjo T, Georgevitch R, Ferrando-Martinez S, Haymaker C, Chaney M, Fan J, Kim R, Pant S. P-48 Phase 2a study of NT-I7, a long-acting interleukin-7, plus pembrolizumab: Cohort of subjects with checkpoint inhibitor-naïve advanced pancreatic cancer. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.138] [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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16
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Kim R, Mamdani H, Barve M, Johnson M, Sahin I, Kopetz S, Yang S, Lee B, Adebanjo T, Georgevitch R, Ferrando-Martinez S, Chaney M, Fan J, Naing A. P-54 Phase 2a study of NT-I7, a long-acting interleukin-7, plus pembrolizumab: Cohort of subjects with checkpoint inhibitor-naïve advanced MSS-colorectal cancer. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.144] [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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McKenzie J, Kosmider S, Wong R, To Y, Shapiro J, Dunn C, Burge M, Hong W, Caird S, Lim S, Wong H, Lee B, Gibbs P, Wong V. P-187 Epidermal growth factor receptor inhibitors (EGFRi) in patients with left-side, RAS wildtype metastatic colorectal cancer: Clinician use and outcomes for patients. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.277] [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: 11/17/2022] Open
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Tay SH, Stephenson M, Allameen NA, Narayanan S, Lee B, Mak A. POS0763 A MULTIMODAL MAGNETIC RESONANCE IMAGING STUDY OF COGNITIVE FUNCTION IN SYSTEMIC LUPUS ERYTHEMATOSUS: A MACHINE LEARNING APPROACH. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.3452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BackgroundSystemic lupus erythematosus (SLE) is a multisystem autoimmune disorder that can affect the central nervous system. Cognitive dysfuncion is the most common neuropsyhiatric event in SLE patients, yet it is also one of the hardest to diagnose.ObjectivesTo investigate if multimodal imaging to assess anatomical magnetic resonance imaging (MRI) abnormalities in the brains of SLE patients can predict cognitive function.MethodsSubjects underwent voxel-based morphometry (VBM), magnetization transfer imaging (MTI), and dynamic contrast-enhanced (DCE) MRI. Automated Neuropsychological Assessment Metrics (ANAM) was used to assess cognitive function in this cross-sectional study and the primary measure was the total throughput score (TTS). TTS is the total of the throughput scores for each of the 8 ANAM subtests: (i) code substitution learning (CSL); (ii) code substitution immediate (CSI); (iii) code substitution delayed (CSD); (iv) spatial processing (SP); (v) matching to sample (MSP); (vi) running memory continuous performance test (CPT); (vii) mathematical processing (MTH) and (viii) memory search (MS). Olfactory assessment was done using the University of Pennsylvania Smell Identification Test. We used a machine learning-based model (i.e. GLMnet) to predict TTS. Subjects with active SLE disease or above 40 years old were excluded.ResultsThirty SLE patients [26 female, 32.0 (26.8-37.0) years] without clinically overt neuropsychiatric manifestations and 10 healthy controls (HCs) [9 females, 27.0 (23.0-31.5) years] were enrolled in this study. Both groups had comparable cognitive and olfactory functions. No significant differences were observed in VBM, MTR, olfactory blub and tract (OBT) volume in SLE patients compared to HCs. We observed increased blood-brain barrier (BBB) permeability parameters (Ktrans and PS) in several regions of SLE patients. DCE-MRI perfusion parameters such as perfusion (F) and vp but not permeability measures were associated with TTS. In particular, F right amygdala correlated with TTS in SLE patients (r = 0.636, FDR p < 0.05) (Table 1). Using GLMnet, we trained a multimodal MRI model comprising of VBM, MTR, DCE-MRI and OBT volume parameters to predict TTS in SLE patients (r = 0.998, p < 0.0005) (Figure 1).Figure 1.Machine learning-based models to predict cognitive function.Table 1.Correlation between ANAM tests with perfusion (F) in SLE patients, ranked in descending order of statistical significance for TTS.VariableTTSCSLCSICSDSPMSPCPTMTHMSF right amygdala0.636‡*0.520‡0.3370.437†0.559‡0.3230.633‡0.412†0.598‡F left entorhinal0.504‡0.422†0.3660.416†0.3050.1850.530‡0.1860.416†F left amygdale0.495‡0.400†0.1890.378†0.3300.2370.491‡0.376†0.449†F choroid0.469†0.384†0.2160.413†0.458†0.2020.456†0.3400.406†plexusF right rostal anterior cingulate0.453†0.3010.1180.2960.393†0.2140.547‡0.420†0.383†F right entorhinal0.448†0.368†0.2320.3120.376†0.1560.438†0.2710.407†F cerebellum white matter0.427†0.3580.2010.370†0.2730.0780.449†0.2900.297F left hippocampus0.427†0.3550.1340.390†0.3560.2030.511‡0.3360.332F brain stem0.407†0.2980.1380.2750.2940.1530.478‡0.3080.369†F right insula0.407†0.3080.0740.3000.3240.1760.437†0.3230.347F left parietal0.400†0.2630.0920.2540.2940.2240.487‡0.2740.332F ventricles0.396†0.3030.0830.3210.370†0.1920.477‡0.2860.361F right temporal0.395†0.2800.1130.2810.2880.1670.477‡0.3220.331F right hippocampus0.395†0.3070.0770.3250.3560.1900.486‡0.3570.339F right parietal0.376†0.2490.0820.2740.2830.1390.460†0.2550.311F right parahippocampal gyrus0.375†0.3530.1190.3020.3410.2410.3530.2080.273† p < 0.05, ‡ p < 0.01, *FDR p < 0.05ConclusionThese findings suggest that the BBB may be affected early in the course of cognitive dysfunction, even preceding detectable changes in other MRI sequences and machine learning algorithms can be used to predict TTS measures, even in asymptomatic SLE patients.ReferencesNil.Disclosure of InterestsSen Hee Tay: None declared, Mary Stephenson: None declared, Nur Azizah Allameen: None declared, Sriram Narayanan: None declared, Bernett Lee: None declared, Anselm Mak Speakers bureau: JnJ Apr 2019 and GSK Jan 2022, Grant/research support from: GSK - The Supported Studies Programme
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Williams MR, Welikhe P, Bos J, King K, Akland M, Augustine D, Baffaut C, Beck EG, Bierer A, Bosch DD, Boughton E, Brandani C, Brooks E, Buda A, Cavigelli M, Faulkner J, Feyereisen G, Fortuna A, Gamble J, Hanrahan B, Hussain M, Kohmann M, Kovar J, Lee B, Leytem A, Liebig M, Line D, Macrae M, Moorman T, Moriasi D, Nelson N, Ortega-Pieck A, Osmond D, Pisani O, Ragosta J, Reba M, Saha A, Sanchez J, Silveira M, Smith D, Spiegal S, Swain H, Unrine J, Webb P, White K, Wilson H, Yasarer L. P-FLUX: A phosphorus budget dataset spanning diverse agricultural production systems in the United States and Canada. J Environ Qual 2022; 51:451-461. [PMID: 35373848 DOI: 10.1002/jeq2.20351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 03/22/2022] [Indexed: 06/14/2023]
Abstract
Quantifying spatial and temporal fluxes of phosphorus (P) within and among agricultural production systems is critical for sustaining agricultural production while minimizing environmental impacts. To better understand P fluxes in agricultural landscapes, P-FLUX, a detailed and harmonized dataset of P inputs, outputs, and budgets, as well as estimated uncertainties for each P flux and budget, was developed. Data were collected from 24 research sites and 61 production systems through the Long-term Agroecosystem Research (LTAR) network and partner organizations spanning 22 U.S. states and 2 Canadian provinces. The objectives of this paper are to (a) present and provide a description of the P-FLUX dataset, (b) provide summary analyses of the agricultural production systems included in the dataset and the variability in P inputs and outputs across systems, and (c) provide details for accessing the dataset, dataset limitations, and an example of future use. P-FLUX includes information on select site characteristics (area, soil series), crop rotation, P inputs (P application rate, source, timing, placement, P in irrigation water, atmospheric deposition), P outputs (crop removal, hydrologic losses), P budgets (agronomic budget, overall budget), uncertainties associated with each flux and budget, and data sources. Phosphorus fluxes and budgets vary across agricultural production systems and are useful resources to improve P use efficiency and develop management strategies to mitigate environmental impacts of agricultural systems. P-FLUX is available for download through the USDA Ag Data Commons (https://doi.org/10.15482/USDA.ADC/1523365).
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Affiliation(s)
- M R Williams
- National Soil Erosion Research Laboratory, USDA-ARS, West Lafayette, IN, USA
| | - P Welikhe
- National Soil Erosion Research Laboratory, USDA-ARS, West Lafayette, IN, USA
- Dep. of Agronomy, Purdue Univ., West Lafayette, IN, USA
| | - J Bos
- National Soil Erosion Research Laboratory, USDA-ARS, West Lafayette, IN, USA
| | - K King
- Soil Drainage Research Unit, USDA-ARS, Columbus, OH, USA
| | - M Akland
- Dep. of Plant and Soil Sciences, Univ. of Kentucky, Lexington, KY, USA
| | - D Augustine
- Rangeland Resources Research Unit, USDA-ARS, Fort Collins, CO, USA
| | - C Baffaut
- Cropping Systems and Water Quality Research Unit, USDA-ARS, Columbia, MO, USA
| | - E G Beck
- Kentucky Geological Survey, Univ. of Kentucky, Henderson, KY, USA
| | - A Bierer
- Northwest Irrigation and Soils Research Lab, USDA-ARS, Kimberly, ID, USA
| | - D D Bosch
- Southeast Watershed Research Laboratory, USDA-ARS, Tifton, GA, USA
| | - E Boughton
- Buck Island Ranch, Archbold Biological Station, Lake Placid, FL, USA
| | - C Brandani
- Dep. of Animal and Range Science, New Mexico State Univ., Las Cruces, NM, USA
| | - E Brooks
- Dep. of Soil and Water Resources, Univ. of Idaho, Moscow, ID, USA
| | - A Buda
- Systems and Watershed Management Research Unit, USDA-ARS, University Park, PA, USA
| | - M Cavigelli
- Sustainable Agricultural Systems Laboratory, USDA-ARS, Beltsville, MD, USA
| | - J Faulkner
- Dep. of Plant and Soil Science, Univ. of Vermont, Burlington, VT, USA
| | - G Feyereisen
- Soil and Water Management Unit, USDA-ARS, St. Paul, MN, USA
| | - A Fortuna
- Grazinglands Research Laboratory, USDA-ARS, El Reno, OK, USA
| | - J Gamble
- Soil and Water Management Unit, USDA-ARS, St. Paul, MN, USA
| | - B Hanrahan
- Soil Drainage Research Unit, USDA-ARS, Columbus, OH, USA
| | - M Hussain
- W.K. Kellogg Biological Station, Michigan State Univ., Hickory Corners, MI, USA
| | - M Kohmann
- Range Cattle Research and Education Center, Univ. of Florida, Ona, FL, USA
| | - J Kovar
- Agroecosystems Management Research, USDA-ARS, Ames, IA, USA
| | - B Lee
- Dep. of Plant and Soil Sciences, Univ. of Kentucky, Lexington, KY, USA
| | - A Leytem
- Northwest Irrigation and Soils Research Lab, USDA-ARS, Kimberly, ID, USA
| | - M Liebig
- Northern Great Plains Research Laboratory, USDA-ARS, Mandan, ND, USA
| | - D Line
- Dep. of Crop and Soil Sciences, North Carolina State Univ., Raleigh, NC, USA
| | - M Macrae
- Dep. of Geography and Environmental Management, Univ. of Waterloo, Waterloo, ON, Canada
| | - T Moorman
- Agroecosystems Management Research, USDA-ARS, Ames, IA, USA
| | - D Moriasi
- Grazinglands Research Laboratory, USDA-ARS, El Reno, OK, USA
| | - N Nelson
- Dep. of Agronomy, Kansas State Univ., Manhattan, KS, USA
| | - A Ortega-Pieck
- Dep. of Soil and Water Resources, Univ. of Idaho, Moscow, ID, USA
| | - D Osmond
- Dep. of Crop and Soil Sciences, North Carolina State Univ., Raleigh, NC, USA
| | - O Pisani
- Southeast Watershed Research Laboratory, USDA-ARS, Tifton, GA, USA
| | - J Ragosta
- USDA-ARS, Jornada Experimental Range, Las Cruces, NM, USA
| | - M Reba
- USDA-ARS, Delta Water Management Research Unit, Arkansas State Univ., Jonesboro, AR, USA
| | - A Saha
- Buck Island Ranch, Archbold Biological Station, Lake Placid, FL, USA
| | - J Sanchez
- Range Cattle Research and Education Center, Univ. of Florida, Ona, FL, USA
| | - M Silveira
- Range Cattle Research and Education Center, Univ. of Florida, Ona, FL, USA
| | - D Smith
- Grassland, Soil and Water Research Laboratory, USDA-ARS, Temple, TX, USA
| | - S Spiegal
- USDA-ARS, Jornada Experimental Range, Las Cruces, NM, USA
| | - H Swain
- Buck Island Ranch, Archbold Biological Station, Lake Placid, FL, USA
| | - J Unrine
- Dep. of Plant and Soil Sciences, Univ. of Kentucky, Lexington, KY, USA
| | - P Webb
- Dep. of Crop, Soil, and Environmental Sciences, Univ. of Arkansas, Fayetteville, AR, USA
| | - K White
- Sustainable Agricultural Systems Laboratory, USDA-ARS, Beltsville, MD, USA
| | - H Wilson
- Science and Technology Branch, Brandon Research and Development Centre, Agriculture and Agri-Food Canada, Brandon, MB, Canada
| | - L Yasarer
- National Sedimentation Laboratory, USDA-ARS, Oxford, MS, USA
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Fuzeta M, Bernardes N, Roefs M, van de Wakker S, Olijve W, Lin Y, Jung S, Lee B, Milligan W, Huang M, Fernandes-Platzgummer A, Vader P, Sluijter J, Cabral J, da Silva C. Exosomes/EVs: SCALABLE BIOREACTOR PRODUCTION AND ANGIOGENIC POTENTIAL OF EXTRACELLULAR VESICLES DERIVED FROM HUMAN MESENCHYMAL STROMAL CELLS. Cytotherapy 2022. [DOI: 10.1016/s1465-3249(22)00257-2] [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: 12/01/2022]
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Lee B, Yamanakkanavar N, Malik MA, Choi JY. Correction: Automatic segmentation of brain MRI using a novel patch-wise U-net deep architecture. PLoS One 2022; 17:e0264231. [PMID: 35157733 PMCID: PMC8843221 DOI: 10.1371/journal.pone.0264231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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22
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Afuape N, Lee B, Castellanos M, Ballecer C, Desai N. A Case of Small Bowel Obstruction Following Appendectomy. J Minim Invasive Gynecol 2021. [DOI: 10.1016/j.jmig.2021.09.356] [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: 10/20/2022]
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Vuong W, Ganguly S, Balyimez A, Halima A, Kerr C, Lee B, Klein E, Day M, Tomlins S, Gupta S, Ornstein M, Tendulkar R, Stephans K, Ciezki J, Grivas P, Maciejewski J, Jha B, Mian O. Identification of Putative Gene-Target Modulators of Radiosensitivity in Bladder Cancer Cell Lines (BlaCCL). Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Jalali A, Gard G, Banks S, Dunn C, Wong HL, Wong R, Lee M, Gately L, Loft M, Shapiro JD, Kosmider S, Tie J, Ananda S, Yeung JM, Jennens R, Lee B, McKendrick J, Lim L, Khattak A, Gibbs P. Initial experience of TAS-102 chemotherapy in Australian patients with Chemo-refractory metastatic colorectal cancer. Curr Probl Cancer 2021; 46:100793. [PMID: 34565601 DOI: 10.1016/j.currproblcancer.2021.100793] [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: 05/06/2021] [Revised: 08/09/2021] [Accepted: 08/20/2021] [Indexed: 11/24/2022]
Abstract
For patients with refractory metastatic colorectal cancer (mCRC) treatment with Trifluridine/Tipiracil, also known as TAS-102, improves overall survival. This study aims to investigate the efficacy and safety of TAS-102 in a real-world population from Victoria, Australia. A retrospective analysis of prospectively collected data from the Treatment of Recurrent and Advanced Colorectal Cancer (TRACC) registry was undertaken. The characteristics and outcomes of patients receiving TAS-102 were assessed and compared to those enrolled in the registration study (RECOURSE). Across 13 sites, 107 patients were treated with TAS-102. The median age was 60 years (range: 31-83), compared to 63 for RECOURSE. Comparing registry TAS-102-treated and RECOURSE patients, 75% vs 100% were ECOG performance status 0-1, 74% vs 79% had initiated treatment more than 18 months from diagnosis of metastatic disease and 36% vs 49% were RAS wild-type. Median time on treatment was 10.4 weeks (range: 1.7-32). Median progression-free survival (PFS) was 3.3 months compared to 2 months in RECOURSE, while median overall survival was the same at 7.1 months. Two patients (2.3%) had febrile neutropenia and there were no treatment-related deaths, where TAS-102 dose at treatment initiation was at clinician discretion.TRACC registry patients treated with TAS-102 were younger than those from the RECOURSE trial, with similar overall survival observed. Less strict application of RECIST criteria and less frequent imaging may have contributed to an apparently longer PFS.
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Affiliation(s)
- A Jalali
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia; Department of Medical Oncology, Western Health, VIC, Australia; Department of Medical Oncology, Latrobe Regional Hospital, VIC, Australia.
| | - G Gard
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia
| | - S Banks
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia
| | - C Dunn
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia
| | - H L Wong
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia; Department of Medical Oncology, Peter MacCallum Cancer Centre, VIC, Australia
| | - R Wong
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia; Department of Medical Oncology, Eastern Health, VIC, Australia; Eastern Health Clinical School, Monash University, VIC, Australia
| | - M Lee
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia; Department of Medical Oncology, Western Health, VIC, Australia; Department of Medical Oncology, Eastern Health, VIC, Australia; Eastern Health Clinical School, Monash University, VIC, Australia
| | - L Gately
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia
| | - M Loft
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia
| | - J D Shapiro
- Department of Medical Oncology, Cabrini Hospital, VIC, Australia
| | - S Kosmider
- Department of Medical Oncology, Western Health, VIC, Australia
| | - J Tie
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia; Department of Medical Oncology, Western Health, VIC, Australia; Department of Medical Oncology, Peter MacCallum Cancer Centre, VIC, Australia
| | - S Ananda
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia; Department of Medical Oncology, Western Health, VIC, Australia; Department of Medical Oncology, Peter MacCallum Cancer Centre, VIC, Australia; Department of Medical Oncology, Epworth Health, VIC, Australia
| | - J M Yeung
- Department of Surgery, Western Health, University of Melbourne, VIC, Australia; Western Health Chronic Disease Alliance, Western Health, VIC, Australia
| | - R Jennens
- Department of Medical Oncology, Epworth Health, VIC, Australia
| | - B Lee
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia; Department of Medical Oncology, Peter MacCallum Cancer Centre, VIC, Australia; Department of Medical Oncology, Northern Health, VIC, Australia
| | - J McKendrick
- Department of Medical Oncology, Eastern Health, VIC, Australia; Department of Medical Oncology, Epworth Health, VIC, Australia
| | - L Lim
- Department of Medical Oncology, Eastern Health, VIC, Australia
| | - A Khattak
- Department of Medical Oncology, Fiona Stanley Hospital, WA, Australia
| | - P Gibbs
- Division of Personalised Oncology, Walter and Eliza Hall Institute of Medical Research, VIC, Australia; Department of Medical Oncology, Western Health, VIC, Australia
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Yamanakkanavar N, Lee B. A novel M-SegNet with global attention CNN architecture for automatic segmentation of brain MRI. Comput Biol Med 2021; 136:104761. [PMID: 34426168 DOI: 10.1016/j.compbiomed.2021.104761] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [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: 05/27/2021] [Revised: 08/04/2021] [Accepted: 08/09/2021] [Indexed: 11/25/2022]
Abstract
In this paper, we propose a novel M-SegNet architecture with global attention for the segmentation of brain magnetic resonance imaging (MRI). The proposed architecture consists of a multiscale deep network at the encoder side, deep supervision at the decoder side, a global attention mechanism, different sizes of convolutional kernels, and combined-connections with skip connections and pooling indices. The multiscale side input layers were used to support deep layers for extracting the discriminative information and the upsampling layer at the decoder side provided deep supervision, which reduced the gradient problem. The global attention mechanism is utilized to capture rich contextual information in the decoder stage by integrating local features with their respective global dependencies. In addition, multiscale convolutional kernels of different sizes were used to extract abundant semantic features from brain MRI scans in the encoder and decoder modules. Moreover, combined-connections were used to pass features from the encoder to the decoder path to recover the spatial information lost during downsampling and makes the model converge faster. Furthermore, we adopted uniform non-overlapping input patches to focus on fine details for the segmentation of brain MRI. We verified the proposed architecture on publicly accessible datasets for the task of segmentation of brain MRI. The experimental results show that the proposed model outperforms conventional methods by achieving an average Dice similarity coefficient score of 0.96.
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Affiliation(s)
- Nagaraj Yamanakkanavar
- Department of Information and Communications Engineering, Chosun University, Gwangju 61452, South Korea
| | - Bumshik Lee
- Department of Information and Communications Engineering, Chosun University, Gwangju 61452, South Korea.
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Nicol LE, Coghlan RF, Cuthbertson D, Nagamani SCS, Lee B, Olney RC, Horton W, Orwoll E. Alterations of a serum marker of collagen X in growing children with osteogenesis imperfecta. Bone 2021; 149:115990. [PMID: 33932621 PMCID: PMC8217291 DOI: 10.1016/j.bone.2021.115990] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 04/12/2021] [Accepted: 04/25/2021] [Indexed: 11/21/2022]
Abstract
Abnormalities in the structure and/or processing of type I collagen cause osteogenesis imperfecta and result in bone fragility, abnormal bone growth and short stature. Type I collagen is expressed in the growth plate but the mechanisms by which abnormalities in collagen I contribute to growth plate dysfunction and growth retardation are unknown. The non-collagenous domain (NC1) of type X collagen (CXM) is released from the hypertrophic zone of active growth plates and is a marker for new endochondral bone formation. Serum CXM levels are strongly correlated with the rate of growth in healthy children. We hypothesized that CXM levels in children with OI would be abnormal when compared to normally growing children. Using participants from the Brittle Bone Disease Consortium Natural History Study we analyzed the distribution of CXM over the ages of 8 months to 40 years in 187 subjects with OI (89 type I and 98 types III/IV) as well as analyzed the relationship between growth velocity and CXM levels in a subset of 100 children <16 years old with OI (44 type I and 56 types III/IV). CXM levels in both control and OI children demonstrated a similar pattern of variation by age with higher levels in early life and puberty followed by a post-pubertal drop. However, there was greater variability within the OI cohort and the relationship with growth velocity was weaker. The ratio of CXM level to growth velocity was elevated in children with type III/IV OI compared to controls. These results suggest that the relationship between hypertrophic zone function and the end point of skeletal growth is disrupted in OI.
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Affiliation(s)
- L E Nicol
- Department of Pediatrics, Division of Pediatric Endocrinology, Oregon Health & Science University, Portland, OR, USA; Shriner's Hospital for Children, Portland, OR, USA.
| | - R F Coghlan
- Shriners Hospitals for Children, Research Center, Portland, OR, USA
| | - D Cuthbertson
- Health Informatics Institute, University of South Florida, Tampa, FL, USA
| | - Sandesh C S Nagamani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA; Texas Children's Hospital, Houston, TX, USA
| | - B Lee
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA; Texas Children's Hospital, Houston, TX, USA
| | - R C Olney
- Nemours Children's Specialty Care, Jacksonville, FL, USA
| | - W Horton
- Shriners Hospitals for Children, Research Center, Portland, OR, USA
| | - E Orwoll
- Department of Medicine, Bone and Mineral Unit, Oregon Health & Science University, Portland, OR, USA
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Kindschuh M, Radeos M, Lee B, Jeong J, Yap W, Ostrovsky A, Calandro D, Juliano P. 73 Reducing Door-to-Provider Time By Creating a Triage Liaison Physician Line in an Urban Emergency Department During the COVID-19 Pandemic. Ann Emerg Med 2021. [PMCID: PMC8335512 DOI: 10.1016/j.annemergmed.2021.07.075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Takagi H, Leipsic J, Lin F, Shaw L, Lee S, Andreini D, Al-Mallah M, Budoff M, Cademartiri F, Chinnaiyan K, Choi J, Conte E, Marques H, Gonçalves P, Gottlieb I, Hadamitzky M, Maffei E, Pontone G, Shin S, Kim Y, Lee B, Chun E, Sung J, Virmani R, Samady H, Stone P, Berman D, Min J, Narula J, Bax J, Chang H. Association Of Tube Voltage With Plaque Composition On Coronary Ct Angiography: Results From Paradigm Registry. J Cardiovasc Comput Tomogr 2021. [DOI: 10.1016/j.jcct.2021.06.297] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Iyer D, Gorman W, Wood T, Blanco C, Lorente M, Nguyen D, Lee B, Kiedaisch B, Lee P. Umbilical cord blood (UCB)-derived natural killer (NK) cells provide a highly scalable source for gene circuit engineered allogeneic CAR-NK therapies. Cytotherapy 2021. [DOI: 10.1016/s1465324921004084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Paller A, Tham K, Lefferdink R, Duan K, Lim S, Ibler E, Chima M, Kim H, Wu B, Abu-Zayed H, Rangel S, Guttman-Yassky E, Lee B, Common J. 206 The distinct skin microbiota of congenital ichthyoses. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.227] [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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Borys B, Dang T, Kanwar S, Colter J, Worden H, Blatchford A, Lee B, Kallos M, Jung S. Using computational fluid dynamics to characterize optimal hydrodynamic conditions for scalable manufacturing of human ipsc aggregates in vertical-wheel bioreactors. Cytotherapy 2021. [DOI: 10.1016/s1465324921004746] [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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Wood T, Bakir A, Blanco C, Iyer D, Kiedaisch B, Gorman W, Lorente M, Lee B, Nguyen D, Lee P. Development of a scalable GMP-Ready manufacturing process for gene circuit engineered allogeneic CAR-NK cell therapy for cancer. Cytotherapy 2021. [DOI: 10.1016/s1465324921005855] [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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Grossi JVM, Lee B, Belyansky I, Carbonell AM, Cavazzola LT, Novitsky YW, Ballecer CD. Critical view of robotic-assisted transverse abdominal release (r-TAR). Hernia 2021; 25:1715-1725. [PMID: 33797679 DOI: 10.1007/s10029-021-02391-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 03/08/2021] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Establishing straightforward and reproducible steps to describe the technique performed with the aid of the robotic system for complex hernia surgery is key for good outcomes. Even using the description of open surgery as a parameter for performing the robotic technique, it is important to stress the particularities of this access. To describe the steps to perform robotic-assisted TAR (r-TAR) in a standardized technique, with a critical and safe view of all the anatomical structures. DESCRIPTION OF THE TECHNIQUE We defined 8 landmarks for the critical view of safety in r-TAR which include: (1) patient position, trocar and docking; (2) posterior rectus sheath mobilization; (3) transversus abdominis release (TAR)-Top-down technique; (4) transversus abdominis release (TAR)-bottom-up technique and mesh insertion; (5) contralateral trocar insertion and redocking, 6) posterior sheath closure; (7) final mesh positioning; and (8) anterior defect closure and drains. DISCUSSION Complex hernia surgery using a robotic-assisted posterior component separation requires well-established steps so the procedure can be reproducible and achieve better results.
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Affiliation(s)
- J V M Grossi
- Department of Surgery, Moinhos de Vento Hospital, Porto Alegre, Brazil.
| | - B Lee
- Creighton University School of Medicine-Phoenix, Phoenix, USA
| | - I Belyansky
- Department of Surgery, Anne Arundel Medical Center, 2000 Medical Parkway, Belcher, Pavilion, Suite106, Annapolis, MD, 21401, USA
| | - A M Carbonell
- Department of Surgery, Division of Minimal Access and Bariatric Surgery, Greenville Health System, University of South Carolina School of Medicine, Greenville, SC, USA
| | - L T Cavazzola
- Department of Surgery, Clinicas de Porto Alegre Hospital, Porto Alegre, Brazil
| | | | - C D Ballecer
- Creighton University School of Medicine-Phoenix, Phoenix, USA
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Chiu H, Hann P, Lee B, Saunders S, Freeborn G, Levin A. POS-313 BETTER TOGETHER: A PROVINCIAL STRATEGY TO IMPROVE COLLABORATIVE GOAL-SETTING IN ADULTS WITH CHRONIC KIDNEY DISEASE. Kidney Int Rep 2021. [DOI: 10.1016/j.ekir.2021.03.329] [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] Open
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Chiu H, Koo W, Bennett L, Spensley R, Sadler J, Lee B, Freeborn G. POS-312 PATIENT AND FAMILY ENGAGEMENT IN A PROVINCIAL KIDNEY NETWORK: WHAT HAVE WE LEARNED SO FAR? Kidney Int Rep 2021. [DOI: 10.1016/j.ekir.2021.03.328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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Rahouma M, Harrison S, Wish J, Kamel M, Lee B, Chow O, Morsi M, Port J, Altorki N, Stiles B. P08.04 Progress in Early Stage Lung Cancer Among Economically Disadvantaged Patients. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.01.423] [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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Duong L, Radley HG, Lee B, Dye DE, Pixley FJ, Grounds MD, Nelson DJ, Jackaman C. Macrophage function in the elderly and impact on injury repair and cancer. Immun Ageing 2021; 18:4. [PMID: 33441138 PMCID: PMC7805172 DOI: 10.1186/s12979-021-00215-2] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 01/01/2021] [Indexed: 02/07/2023]
Abstract
Older age is associated with deteriorating health, including escalating risk of diseases such as cancer, and a diminished ability to repair following injury. This rise in age-related diseases/co-morbidities is associated with changes to immune function, including in myeloid cells, and is related to immunosenescence. Immunosenescence reflects age-related changes associated with immune dysfunction and is accompanied by low-grade chronic inflammation or inflammageing. This is characterised by increased levels of circulating pro-inflammatory cytokines such as tumor necrosis factor (TNF), interleukin (IL)-1β and IL-6. However, in healthy ageing, there is a concomitant age-related escalation in anti-inflammatory cytokines such as transforming growth factor-β1 (TGF-β1) and IL-10, which may overcompensate to regulate the pro-inflammatory state. Key inflammatory cells, macrophages, play a role in cancer development and injury repair in young hosts, and we propose that their role in ageing in these scenarios may be more profound. Imbalanced pro- and anti-inflammatory factors during ageing may also have a significant influence on macrophage function and further impact the severity of age-related diseases in which macrophages are known to play a key role. In this brief review we summarise studies describing changes to inflammatory function of macrophages (from various tissues and across sexes) during healthy ageing. We also describe age-related diseases/co-morbidities where macrophages are known to play a key role, focussed on injury repair processes and cancer, plus comment briefly on strategies to correct for these age-related changes.
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Affiliation(s)
- L Duong
- Curtin Medical School, Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Kent Street, 6102, Bentley, Western Australia, Australia
| | - H G Radley
- Curtin Medical School, Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Kent Street, 6102, Bentley, Western Australia, Australia
| | - B Lee
- Curtin Medical School, Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Kent Street, 6102, Bentley, Western Australia, Australia
| | - D E Dye
- Curtin Medical School, Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Kent Street, 6102, Bentley, Western Australia, Australia
| | - F J Pixley
- School of Biomedical Sciences, University of Western Australia, 6009, Nedlands, Western Australia, Australia
| | - M D Grounds
- School of Human Sciences, University of Western Australia, 6009, Nedlands, Western Australia, Australia
| | - D J Nelson
- Curtin Medical School, Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Kent Street, 6102, Bentley, Western Australia, Australia
| | - C Jackaman
- Curtin Medical School, Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Kent Street, 6102, Bentley, Western Australia, Australia.
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Hazell SZ, Fu W, Hu C, Voong KR, Lee B, Peterson V, Feliciano JL, Nicholas LH, McNutt TR, Han P, Hales RK. Financial toxicity in lung cancer: an assessment of magnitude, perception, and impact on quality of life. Ann Oncol 2021; 31:96-102. [PMID: 31912803 DOI: 10.1016/j.annonc.2019.10.006] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [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: 08/19/2019] [Revised: 09/29/2019] [Accepted: 10/08/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Advances in lung cancer therapy have resulted in improved clinical outcomes. Unfortunately, advances can come at a financial cost to patients and their families that poses a significant risk to overall quality of life (QoL). Financial distress has been shown to be associated with increased symptom burden and decreased treatment compliance but the magnitude of financial distress is not well characterized in lung cancer populations. PATIENTS AND METHODS Patients with stage II-IV newly diagnosed lung cancer and starting first-line therapy were recruited at a tertiary academic institution between July 2018 and April 2019. The comprehensive score for financial toxicity (COST) was used to assess financial toxicity and the Functional Assessment of Cancer Therapy-Lung (FACT-L) was used to assess QoL. Associations between financial toxicity and baseline variables were assessed using multivariable linear regression and correlations were assessed using the Pearson correlation. RESULTS In this study, 143 consecutive patients were approached and 91.6% agreed to participate (N = 131). The median age was 65 years (35-90); 52.7% were male (n = 69), and 75.6% were white (n = 99). The inability to afford basic necessities and having <1 month of savings was associated with increased financial toxicity (P < 0.001) after adjusting for other factors such as age, race, insurance, and income. There was also a trend toward increased financial toxicity among those who were employed but on sick leave (P = 0.06). Increased financial toxicity was correlated with a decrease in QoL (correlation coefficient 0.41, P < 0.001). Patients' anticipated out-of-pocket (OOP) expenses for the upcoming 6 months ranged from $0 to $50 000 (median $2150). However, there was no correlation between anticipated OOP expenses and either financial toxicity or QoL. CONCLUSIONS These data identify key factors for identifying at-risk patients and builds a framework for exploring the benefit of financial counseling interventions, which may improve QoL and oncologic outcomes.
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Affiliation(s)
- S Z Hazell
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, USA
| | - W Fu
- Division of Biostatistics and Bioinformatics, Johns Hopkins University School of Medicine, Baltimore, USA
| | - C Hu
- Division of Biostatistics and Bioinformatics, Johns Hopkins University School of Medicine, Baltimore, USA
| | - K R Voong
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, USA
| | - B Lee
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, USA
| | - V Peterson
- Department of Medical Oncology, Johns Hopkins University School of Medicine, Baltimore, USA
| | - J L Feliciano
- Department of Medical Oncology, Johns Hopkins University School of Medicine, Baltimore, USA
| | - L H Nicholas
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
| | - T R McNutt
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, USA
| | - P Han
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, USA
| | - R K Hales
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, USA.
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Lakomy D, Vedam S, Yang J, Wang J, Lee B, Sobremonte A, Castillo P, Hughes N, Mohammedsaid M, Jhingran A, Klopp A, Fuller C, Choi S, Lin L. Single-institution Experience Utilizing MR-Linac for Gynecologic Malignancies. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2343] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Vuong W, Balyimez A, Ganguly S, Laximi S, Kerr C, Lee B, Klein E, Day M, Tomlins S, Gupta S, Ornstein M, Tendulkar R, Stephans K, Ciezki J, Grivas P, Maciejewski J, Jha B, Mian O. Transcriptomic and Mutational Analyses Identify Biological Processes Correlated with Bladder Cancer Cell Line (BlaCCL) Radiation Response. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.1759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Lee N, Lee K, Kim K, Hong J, Yim G, Seong S, Lee B, Lee J, Lim S, Ouh Y, Kim Y. Risk of occult atypical hyperplasia or cancer in women with non-atypical endometrial hyperplasia. Gynecol Oncol 2020. [DOI: 10.1016/j.ygyno.2020.05.356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Shin H, Chay D, Yang W, Cho H, Jeon S, Lee B, Han G, Lee E, Kim J. Cancer-associated protein Tetraspanin1 increases cell growth through AMPK in atypical endometriosis. Gynecol Oncol 2020. [DOI: 10.1016/j.ygyno.2020.05.197] [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]
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Lau P, Feran B, Smith L, Lasocki A, Molania R, Smith K, Weppler A, Angel C, Kee D, Bhave P, Lee B, Yeang HA, Vergara I, Kok D, Drummond K, Neeson P, Sheppard K, Papenfuss T, Sandhu S, McArthur G. 1079MO Progression of BRAF mutant CNS metastases are associated with a transcriptional network bearing similarities with the innate PD-1 resistant signature (IPRES). Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.1203] [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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Owen CN, Shoushtari AN, Chauhan D, Palmieri DJ, Lee B, Rohaan MW, Mangana J, Atkinson V, Zaman F, Young A, Hoeller C, Hersey P, Dummer R, Khattak MA, Millward M, Patel SP, Haydon A, Johnson DB, Lo S, Blank CU, Sandhu S, Carlino MS, Larkin JMG, Menzies AM, Long GV. Management of early melanoma recurrence despite adjuvant anti-PD-1 antibody therapy ☆. Ann Oncol 2020; 31:1075-1082. [PMID: 32387454 PMCID: PMC9211001 DOI: 10.1016/j.annonc.2020.04.471] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Revised: 04/13/2020] [Accepted: 04/23/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Anti-programmed cell death protein 1 (PD-1) antibodies (PD1) prolong recurrence-free survival in high-risk resected melanoma; however, approximately 25%-30% of patients recur within 1 year. This study describes the pattern of recurrence, management and outcomes of patients who recur with adjuvant PD1 therapy. PATIENTS AND METHODS Consecutive patients from 16 centres who recurred having received adjuvant PD1 therapy for resected stage III/IV melanoma were studied. Recurrence characteristics, management and outcomes were examined; patients with mucosal melanoma were analysed separately. RESULTS Melanoma recurrence occurred in 147 (17%) of ∼850 patients treated with adjuvant PD1. In those with cutaneous melanoma (n = 136), median time to recurrence was 4.6 months (range 0.3-35.7); 104 (76%) recurred during (ON) adjuvant PD1 after a median 3.2 months and 32 (24%) following (OFF) treatment cessation after a median 12.5 months, including in 21 (15%) who ceased early for toxicity. Fifty-nine (43%) recurred with locoregional disease only and 77 (57%) with distant disease. Of those who recurred locally, 22/59 (37%) subsequently recurred distantly. Eighty-nine (65%) patients received systemic therapy after recurrence. Of those who recurred ON adjuvant PD1, none (0/6) responded to PD1 alone; 8/33 assessable patients (24%) responded to ipilimumab (alone or in combination with PD1) and 18/23 (78%) responded to BRAF/MEK inhibitors. Of those who recurred OFF adjuvant PD1, two out of five (40%) responded to PD1 monotherapy, two out of five (40%) responded to ipilimumab-based therapy and 9/10 (90%) responded to BRAF/MEK inhibitors. CONCLUSIONS Most patients who recur early despite adjuvant PD1 develop distant metastases. In those who recur ON adjuvant PD1, there is minimal activity of further PD1 monotherapy, but ipilimumab (alone or in combination with PD1) and BRAF/MEK inhibitors have clinical utility. Retreatment with PD1 may have activity in select patients who recur OFF PD1.
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Affiliation(s)
- C N Owen
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia
| | | | - D Chauhan
- The Royal Marsden NHS Foundation Trust, London, UK
| | - D J Palmieri
- Westmead Hospital and Blacktown Hospitals, Sydney, Australia
| | - B Lee
- Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, Australia
| | - M W Rohaan
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - J Mangana
- University Hospital Zurich, Zürich, Switzerland
| | - V Atkinson
- Greenslopes Private Hospital, Princess Alexandra Hospital and The University of Queensland, Brisbane, Australia
| | - F Zaman
- The Alfred Hospital, Melbourne, Australia
| | - A Young
- Vanderbilt University Medical Center, Nashville, USA
| | - C Hoeller
- Medical University of Vienna, Vienna, Austria
| | - P Hersey
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia
| | - R Dummer
- University Hospital Zurich, Zürich, Switzerland
| | - M A Khattak
- Fiona Stanley Hospital, The University of Western Australia, Perth, Australia
| | - M Millward
- School of Medicine and Pharmacology, Nedlands, Australia
| | - S P Patel
- The University of Texas MD Anderson Cancer Center, Houston, USA
| | - A Haydon
- The Alfred Hospital, Melbourne, Australia
| | - D B Johnson
- Vanderbilt University Medical Center, Nashville, USA
| | - S Lo
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia
| | - C U Blank
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - S Sandhu
- Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, Australia
| | - M S Carlino
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia; Westmead Hospital and Blacktown Hospitals, Sydney, Australia
| | - J M G Larkin
- The Royal Marsden NHS Foundation Trust, London, UK
| | - A M Menzies
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia; Royal North Shore and Mater Hospitals, Sydney, Australia
| | - G V Long
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia; Royal North Shore and Mater Hospitals, Sydney, Australia.
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Adare A, Afanasiev S, Aidala C, Ajitanand NN, Akiba Y, Akimoto R, Al-Ta'ani H, Alexander J, Angerami A, Aoki K, Apadula N, Aramaki Y, Asano H, Aschenauer EC, Atomssa ET, Awes TC, Azmoun B, Babintsev V, Bai M, Bannier B, Barish KN, Bassalleck B, Bathe S, Baublis V, Baumgart S, Bazilevsky A, Belmont R, Berdnikov A, Berdnikov Y, Bing X, Blau DS, Boyle K, Brooks ML, Buesching H, Bumazhnov V, Butsyk S, Campbell S, Castera P, Chen CH, Chi CY, Chiu M, Choi IJ, Choi JB, Choi S, Choudhury RK, Christiansen P, Chujo T, Chvala O, Cianciolo V, Citron Z, Cole BA, Connors M, Csanád M, Csörgő T, Dairaku S, Datta A, Daugherity MS, David G, Denisov A, Deshpande A, Desmond EJ, Dharmawardane KV, Dietzsch O, Ding L, Dion A, Donadelli M, Drapier O, Drees A, Drees KA, Durham JM, Durum A, D'Orazio L, Edwards S, Efremenko YV, Engelmore T, Enokizono A, Esumi S, Eyser KO, Fadem B, Fields DE, Finger M, Finger M, Fleuret F, Fokin SL, Frantz JE, Franz A, Frawley AD, Fukao Y, Fusayasu T, Gainey K, Gal C, Garishvili A, Garishvili I, Glenn A, Gong X, Gonin M, Goto Y, Granier de Cassagnac R, Grau N, Greene SV, Grosse Perdekamp M, Gunji T, Guo L, Gustafsson HÅ, Hachiya T, Haggerty JS, Hahn KI, Hamagaki H, Hanks J, Hashimoto K, Haslum E, Hayano R, He X, Hemmick TK, Hester T, Hill JC, Hollis RS, Homma K, Hong B, Horaguchi T, Hori Y, Huang S, Ichihara T, Iinuma H, Ikeda Y, Imrek J, Inaba M, Iordanova A, Isenhower D, Issah M, Isupov A, Ivanischev D, Jacak BV, Javani M, Jia J, Jiang X, Johnson BM, Joo KS, Jouan D, Kamin J, Kaneti S, Kang BH, Kang JH, Kang JS, Kapustinsky J, Karatsu K, Kasai M, Kawall D, Kazantsev AV, Kempel T, Khanzadeev A, Kijima KM, Kim BI, Kim C, Kim DJ, Kim EJ, Kim HJ, Kim KB, Kim YJ, Kim YK, Kinney E, Kiss Á, Kistenev E, Klatsky J, Kleinjan D, Kline P, Komatsu Y, Komkov B, Koster J, Kotchetkov D, Kotov D, Král A, Krizek F, Kunde GJ, Kurita K, Kurosawa M, Kwon Y, Kyle GS, Lacey R, Lai YS, Lajoie JG, Lebedev A, Lee B, Lee DM, Lee J, Lee KB, Lee KS, Lee SH, Lee SR, Leitch MJ, Leite MAL, Leitgab M, Lewis B, Lim SH, Linden Levy LA, Litvinenko A, Liu MX, Love B, Maguire CF, Makdisi YI, Makek M, Malakhov A, Manion A, Manko VI, Mannel E, Masumoto S, McCumber M, McGaughey PL, McGlinchey D, McKinney C, Mendoza M, Meredith B, Miake Y, Mibe T, Mignerey AC, Milov A, Mishra DK, Mitchell JT, Miyachi Y, Miyasaka S, Mohanty AK, Moon HJ, Morrison DP, Motschwiller S, Moukhanova TV, Murakami T, Murata J, Nagae T, Nagamiya S, Nagle JL, Nagy MI, Nakagawa I, Nakamiya Y, Nakamura KR, Nakamura T, Nakano K, Nattrass C, Nederlof A, Nihashi M, Nouicer R, Novitzky N, Nyanin AS, O'Brien E, Ogilvie CA, Okada K, Oskarsson A, Ouchida M, Ozawa K, Pak R, Pantuev V, Papavassiliou V, Park BH, Park IH, Park SK, Pate SF, Patel L, Pei H, Peng JC, Pereira H, Peresedov V, Peressounko DY, Petti R, Pinkenburg C, Pisani RP, Proissl M, Purschke ML, Qu H, Rak J, Ravinovich I, Read KF, Reynolds R, Riabov V, Riabov Y, Richardson E, Roach D, Roche G, Rolnick SD, Rosati M, Rukoyatkin P, Sahlmueller B, Saito N, Sakaguchi T, Samsonov V, Sano M, Sarsour M, Sawada S, Sedgwick K, Seidl R, Sen A, Seto R, Sharma D, Shein I, Shibata TA, Shigaki K, Shimomura M, Shoji K, Shukla P, Sickles A, Silva CL, Silvermyr D, Sim KS, Singh BK, Singh CP, Singh V, Slunečka M, Soltz RA, Sondheim WE, Sorensen SP, Soumya M, Sourikova IV, Stankus PW, Stenlund E, Stepanov M, Ster A, Stoll SP, Sugitate T, Sukhanov A, Sun J, Sziklai J, Takagui EM, Takahara A, Taketani A, Tanaka Y, Taneja S, Tanida K, Tannenbaum MJ, Tarafdar S, Taranenko A, Tennant E, Themann H, Todoroki T, Tomášek L, Tomášek M, Torii H, Towell RS, Tserruya I, Tsuchimoto Y, Tsuji T, Vale C, van Hecke HW, Vargyas M, Vazquez-Zambrano E, Veicht A, Velkovska J, Vértesi R, Virius M, Vossen A, Vrba V, Vznuzdaev E, Wang XR, Watanabe D, Watanabe K, Watanabe Y, Watanabe YS, Wei F, Wei R, White SN, Winter D, Wolin S, Woody CL, Wysocki M, Yamaguchi YL, Yang R, Yanovich A, Ying J, Yokkaichi S, You Z, Younus I, Yushmanov IE, Zajc WA, Zelenski A, Zolin L. Erratum: Evolution of π^{0} Suppression in Au+Au Collisions from sqrt[s_{NN}]=39 to 200 GeV [Phys. Rev. Lett. 109, 152301 (2012)]. Phys Rev Lett 2020; 125:049901. [PMID: 32794791 DOI: 10.1103/physrevlett.125.049901] [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] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Indexed: 06/11/2023]
Abstract
This corrects the article DOI: 10.1103/PhysRevLett.109.152301.
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Yamanakkanavar N, Choi JY, Lee B. MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer's Disease: A Survey. Sensors (Basel) 2020; 20:E3243. [PMID: 32517304 PMCID: PMC7313699 DOI: 10.3390/s20113243] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 05/25/2020] [Accepted: 06/03/2020] [Indexed: 02/07/2023]
Abstract
Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid of magnetic resonance imaging (MRI). It is important to identify patients with Alzheimer's disease (AD) early so that preventative measures can be taken. A detailed analysis of the tissue structures from segmented MRI leads to a more accurate classification of specific brain disorders. Several segmentation methods to diagnose AD have been proposed with varying complexity. Segmentation of the brain structure and classification of AD using deep learning approaches has gained attention as it can provide effective results over a large set of data. Hence, deep learning methods are now preferred over state-of-the-art machine learning methods. We aim to provide an outline of current deep learning-based segmentation approaches for the quantitative analysis of brain MRI for the diagnosis of AD. Here, we report how convolutional neural network architectures are used to analyze the anatomical brain structure and diagnose AD, discuss how brain MRI segmentation improves AD classification, describe the state-of-the-art approaches, and summarize their results using publicly available datasets. Finally, we provide insight into current issues and discuss possible future research directions in building a computer-aided diagnostic system for AD.
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Affiliation(s)
- Nagaraj Yamanakkanavar
- Department of Information and Communications Engineering, Chosun University, Gwangju 61452, Korea;
| | - Jae Young Choi
- Division of Computer & Electronic Systems Engineering, Hankuk University of Foreign Studies, Yongin 17035, Korea;
| | - Bumshik Lee
- Department of Information and Communications Engineering, Chosun University, Gwangju 61452, Korea;
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Lee B. Response to letter to the editor re posterior urethral valves are more common in boys with hypospadias. J Pediatr Urol 2020; 16:305. [PMID: 32513444 DOI: 10.1016/j.jpurol.2020.03.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 11/17/2022]
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Lee Y, Lee B. 0789 Decreased Sigma Band Power During NREM Sleep in REM Sleep Behavior Disorder. Sleep 2020. [DOI: 10.1093/sleep/zsaa056.785] [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] Open
Abstract
Abstract
Introduction
REM sleep Behavior Disorder (RBD) is characterized by dream enacting behaviors and a loss of atonia during REM sleep. Early detection of RBD is important because it is considered premonitory symptoms neurodegenerative disorders. In this study, we investigated the slow and fast sigma band power of patients with RBD using frequency analysis.
Methods
Twenty patients who were diagnosed as RBD according to the ICSD-3 criteria and 20 age-matched controls who underwent polysomnography (PSG) for other sleep disorders (insomnia, snoring) and showed normal to mild obstructive sleep apnea (OSA). NREM sleep EEG data was extracted and N1 sleep data was excluded to minimize arousal artifact. Fast Fourier transform-based spectral power analysis was used to compute the power spectral densities of the EEG in the MATLAB environment. The sigma bands were divided into 2 discrete bands: slow sigma (11 to 13 Hz) and- fast sigma (13 to 15 Hz). Mann-Whitney U test by SPSS was used.
Results
RBD patients (61.9 ± 7.1 years old; 12 men) had a significantly lower sigma band power than the control group (61.5 ± 1.1 years old; 11 men) in central region (p = 0.028). Particularly, the slow sigma band power showed a bigger difference in all regions except O1 (F3 = 0.017, F4 = 0.027, C3 = 0.004, C4 = 0.009, O2 = 0.017).
Conclusion
Sigma power was lower in the RBD patients than in the control. It suggests that RBD has impaired cortical activity. Thus, decreased spindle activity during NREM sleep may be a potential biomarker of RBD.
Support
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Affiliation(s)
- Y Lee
- Dept. of Clinical Neurosciences Laboratory, ASAN Medical Center, Seoul, KOREA, REPUBLIC OF
| | - B Lee
- Dept. of Psychiatry, Korea University Anam Hospital, Seoul, KOREA, REPUBLIC OF
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Fuzeta M, Oliveira F, Costa A, Fernandes-Platzgummer A, Jung S, Tseng R, Milligan W, Lee B, Bernardes N, Gaspar D, Cabral J, da Silva C. Scalable Production of Human Mesenchymal Stromal Cell (MSC)-Derived Extracellular Vesicles in Microcarrier-based Bioreactors under Xeno(geneic)-free Conditions. Cytotherapy 2020. [DOI: 10.1016/j.jcyt.2020.03.499] [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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Defever E, Mwaanga O, Lee B, Jones M. Evaluation of practice to promote physical activity in schools in a unitary authority in England. Public Health 2020; 182:155-160. [PMID: 32320906 DOI: 10.1016/j.puhe.2020.02.014] [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: 07/08/2019] [Revised: 01/24/2020] [Accepted: 02/25/2020] [Indexed: 11/30/2022]
Abstract
OBJECTIVES To explore what actually happens in relation to physical activity promotion in primary and junior schools within one unitary authority and to relate this to Public Health England (PHE) promising principles of practice to promote physical activity in schools. STUDY DESIGN A qualitative approach was undertaken to explore practice in all primary and junior schools in the unitary authority of Southampton. METHODS All primary (n = 36) and junior (n = 8) schools in Southampton were involved in the study. Publicly available primary physical education and sport premium (PESP) funding reports (n = 36) alongside a school survey (n = 14) were collated. The collated qualitative data set was semantically coded and then a multilayered approach including identification, reviewing, defining and naming meaningful and important themes were inductively developed. The inductively developed themes were then fitted in relation to PHE eight promising principles. RESULTS There was evidence of practice across all eight promising principles although this varied in depth and scale. There was one set of data that did not fit appropriately within the PHE eight promising principles and warranted its own category broadly termed 'rewards to recognise physical activity'. There was widespread evidence of PESP funding providing increased provision, variety and quality of sport opportunities but limited evidence of physical activity practice or programmes targeting the least active. Two different approaches in relation to ensuring a skilled workforce materialised continuing professional development which reflected in impact statements linked to increased confidence to deliver and quality of physical education versus outsourcing to specialists with little impact cited other than offering specialist or diverse sports. CONCLUSIONS The study demonstrated that the PHE eight promising principles of practice was a useful framework in relation to current practice, although a ninth promising principle of rewarding physically active behaviour should be considered. The two key themes that need to be addressed for the ambitions established in the new school sport and activity action plan to be deliverable, with PESP funding as a driver, are skilled workforce and development of a wider understanding of what physical activity is.
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Affiliation(s)
| | | | - B Lee
- Solent University, Southampton, UK
| | - M Jones
- Plymouth Marjon University, Plymouth, UK.
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