Showing papers by "Radboud University Nijmegen published in 2021"
Daniel J. Klionsky1, Amal Kamal Abdel-Aziz2, Sara Abdelfatah3, Mahmoud Abdellatif4 +2980 more•Institutions (777)
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
1,129 citations
National Institutes of Health1, University of Cambridge2, Wellcome Trust Sanger Institute3, Rockefeller University4, University of California, Davis5, Leibniz Association6, Seoul National University7, University of Southern California8, European Bioinformatics Institute9, Dresden University of Technology10, Max Planck Society11, University of St Andrews12, Radboud University Nijmegen13, University of Massachusetts Amherst14, University of Adelaide15, University of Missouri16, East Carolina University17, University of Queensland18, Clemson University19, University of Otago20, University of Arizona21, Natural History Museum22, Bangor University23, University of Konstanz24, Harvard University25, Northeastern University26, National Museum of Natural History27, University of Antwerp28, University of Graz29, University of Florida30, University of Basel31, University of California, Santa Cruz32, Zoological Society of San Diego33, Pacific Biosciences34, Pompeu Fabra University35, University of Maryland, College Park36, Harbin Institute of Technology37, University of Chicago38, Oregon Health & Science University39, Monash University Malaysia Campus40, Qatar Airways41, University of Milan42, Goethe University Frankfurt43, Pennsylvania State University44, University of Los Andes45, University of Copenhagen46, Norwegian University of Science and Technology47, Agency for Science, Technology and Research48, Royal Ontario Museum49, Smithsonian Institution50, Howard Hughes Medical Institute51, Walter Reed Army Institute of Research52, University of East Anglia53, University College Dublin54, University of Illinois at Urbana–Champaign55, La Trobe University56, University of California, San Diego57, Nova Southeastern University58
TL;DR: The Vertebrate Genomes Project (VGP) as mentioned in this paper is an international effort to generate high quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.
Abstract: High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species1-4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.
647 citations
TL;DR: The Rectal cancer And Preoperative Induction therapy followed by Dedicated Operation (RAPIDO) trial aimed to reduce distant metastases without compromising locoregional control.
Abstract: Summary Background Systemic relapses remain a major problem in locally advanced rectal cancer. Using short-course radiotherapy followed by chemotherapy and delayed surgery, the Rectal cancer And Preoperative Induction therapy followed by Dedicated Operation (RAPIDO) trial aimed to reduce distant metastases without compromising locoregional control. Methods In this multicentre, open-label, randomised, controlled, phase 3 trial, participants were recruited from 54 centres in the Netherlands, Sweden, Spain, Slovenia, Denmark, Norway, and the USA. Patients were eligible if they were aged 18 years or older, with an Eastern Cooperative Oncology Group (ECOG) performance status of 0–1, had a biopsy-proven, newly diagnosed, primary, locally advanced rectal adenocarcinoma, which was classified as high risk on pelvic MRI (with at least one of the following criteria: clinical tumour [cT] stage cT4a or cT4b, extramural vascular invasion, clinical nodal [cN] stage cN2, involved mesorectal fascia, or enlarged lateral lymph nodes), were mentally and physically fit for chemotherapy, and could be assessed for staging within 5 weeks before randomisation. Eligible participants were randomly assigned (1:1), using a management system with a randomly varying block design (each block size randomly chosen to contain two to four allocations), stratified by centre, ECOG performance status, cT stage, and cN stage, to either the experimental or standard of care group. All investigators remained masked for the primary endpoint until a prespecified number of events was reached. Patients allocated to the experimental treatment group received short-course radiotherapy (5 × 5 Gy over a maximum of 8 days) followed by six cycles of CAPOX chemotherapy (capecitabine 1000 mg/m2 orally twice daily on days 1–14, oxaliplatin 130 mg/m2 intravenously on day 1, and a chemotherapy-free interval between days 15–21) or nine cycles of FOLFOX4 (oxaliplatin 85 mg/m2 intravenously on day 1, leucovorin [folinic acid] 200 mg/m2 intravenously on days 1 and 2, followed by bolus fluorouracil 400 mg/m2 intravenously and fluorouracil 600 mg/m2 intravenously for 22 h on days 1 and 2, and a chemotherapy-free interval between days 3–14) followed by total mesorectal excision. Choice of CAPOX or FOLFOX4 was per physician discretion or hospital policy. Patients allocated to the standard of care group received 28 daily fractions of 1·8 Gy up to 50·4 Gy or 25 fractions of 2·0 Gy up to 50·0 Gy (per physician discretion or hospital policy), with concomitant twice-daily oral capecitabine 825 mg/m2 followed by total mesorectal excision and, if stipulated by hospital policy, adjuvant chemotherapy with eight cycles of CAPOX or 12 cycles of FOLFOX4. The primary endpoint was 3-year disease-related treatment failure, defined as the first occurrence of locoregional failure, distant metastasis, new primary colorectal tumour, or treatment-related death, assessed in the intention-to-treat population. Safety was assessed by intention to treat. This study is registered with the EudraCT, 2010-023957-12, and ClinicalTrials.gov , NCT01558921 , and is now complete. Findings Between June 21, 2011, and June 2, 2016, 920 patients were enrolled and randomly assigned to a treatment, of whom 912 were eligible (462 in the experimental group; 450 in the standard of care group). Median follow-up was 4·6 years (IQR 3·5–5·5). At 3 years after randomisation, the cumulative probability of disease-related treatment failure was 23·7% (95% CI 19·8–27·6) in the experimental group versus 30·4% (26·1–34·6) in the standard of care group (hazard ratio 0·75, 95% CI 0·60–0·95; p=0·019). The most common grade 3 or higher adverse event during preoperative therapy in both groups was diarrhoea (81 [18%] of 460 patients in the experimental group and 41 [9%] of 441 in the standard of care group) and neurological toxicity during adjuvant chemotherapy in the standard of care group (16 [9%] of 187 patients). Serious adverse events occurred in 177 (38%) of 460 participants in the experimental group and, in the standard of care group, in 87 (34%) of 254 patients without adjuvant chemotherapy and in 64 (34%) of 187 with adjuvant chemotherapy. Treatment-related deaths occurred in four participants in the experimental group (one cardiac arrest, one pulmonary embolism, two infectious complications) and in four participants in the standard of care group (one pulmonary embolism, one neutropenic sepsis, one aspiration, one suicide due to severe depression). Interpretation The observed decreased probability of disease-related treatment failure in the experimental group is probably indicative of the increased efficacy of preoperative chemotherapy as opposed to adjuvant chemotherapy in this setting. Therefore, the experimental treatment can be considered as a new standard of care in high-risk locally advanced rectal cancer. Funding Dutch Cancer Foundation, Swedish Cancer Society, Spanish Ministry of Economy and Competitiveness, and Spanish Clinical Research Network.
586 citations
University of Cologne1, University of Genoa2, Post Graduate Institute of Medical Education and Research3, Westmead Hospital4, University of Sydney5, Federal University of São Paulo6, Medical University of Graz7, University of California, San Diego8, Innsbruck Medical University9, University of Lagos10, McGill University Health Centre11, Fudan University12, Radboud University Nijmegen13, University of Rennes14, Duke University15, University of Texas Health Science Center at San Antonio16, University of Texas at Austin17, Federal University of Paraná18, University of Texas Health Science Center at Houston19, Cardiff University20, Center for Infectious Disease Research and Policy21
TL;DR: It is proposed to be defined as possible, probable, or proven on the basis of sample validity and thus diagnostic certainty, and recommended first-line therapy is either voriconazole or isavuconazole, while azole resistance is a concern.
Abstract: Severe acute respiratory syndrome coronavirus 2 causes direct damage to the airway epithelium, enabling aspergillus invasion. Reports of COVID-19-associated pulmonary aspergillosis have raised concerns about it worsening the disease course of COVID-19 and increasing mortality. Additionally, the first cases of COVID-19-associated pulmonary aspergillosis caused by azole-resistant aspergillus have been reported. This article constitutes a consensus statement on defining and managing COVID-19-associated pulmonary aspergillosis, prepared by experts and endorsed by medical mycology societies. COVID-19-associated pulmonary aspergillosis is proposed to be defined as possible, probable, or proven on the basis of sample validity and thus diagnostic certainty. Recommended first-line therapy is either voriconazole or isavuconazole. If azole resistance is a concern, then liposomal amphotericin B is the drug of choice. Our aim is to provide definitions for clinical research and up-to-date recommendations for clinical management of the diagnosis and treatment of COVID-19-associated pulmonary aspergillosis.
519 citations
TL;DR: In this article, the population of 47 compact binary mergers detected with a false-alarm rate of 0.614 were dynamically assembled, and the authors found that the BBH rate likely increases with redshift, but not faster than the star formation rate.
Abstract: We report on the population of 47 compact binary mergers detected with a false-alarm rate of 0.01 are dynamically assembled. Third, we estimate merger rates, finding RBBH = 23.9-+8.614.3 Gpc-3 yr-1 for BBHs and RBNS = 320-+240490 Gpc-3 yr-1 for binary neutron stars. We find that the BBH rate likely increases with redshift (85% credibility) but not faster than the star formation rate (86% credibility). Additionally, we examine recent exceptional events in the context of our population models, finding that the asymmetric masses of GW190412 and the high component masses of GW190521 are consistent with our models, but the low secondary mass of GW190814 makes it an outlier.
468 citations
TL;DR: In this article, the authors reported the observation of gravitational waves from two compact binary coalescences in LIGO's and Virgo's third observing run with properties consistent with neutron star-black hole (NSBH) binaries.
Abstract: We report the observation of gravitational waves from two compact binary coalescences in LIGO’s and Virgo’s third observing run with properties consistent with neutron star–black hole (NSBH) binaries. The two events are named GW200105_162426 and GW200115_042309, abbreviated as GW200105 and GW200115; the first was observed by LIGO Livingston and Virgo and the second by all three LIGO–Virgo detectors. The source of GW200105 has component masses 8.9−1.5+1.2 and 1.9−0.2+0.3M⊙ , whereas the source of GW200115 has component masses 5.7−2.1+1.8 and 1.5−0.3+0.7M⊙ (all measurements quoted at the 90% credible level). The probability that the secondary’s mass is below the maximal mass of a neutron star is 89%–96% and 87%–98%, respectively, for GW200105 and GW200115, with the ranges arising from different astrophysical assumptions. The source luminosity distances are 280−110+110 and 300−100+150Mpc , respectively. The magnitude of the primary spin of GW200105 is less than 0.23 at the 90% credible level, and its orientation is unconstrained. For GW200115, the primary spin has a negative spin projection onto the orbital angular momentum at 88% probability. We are unable to constrain the spin or tidal deformation of the secondary component for either event. We infer an NSBH merger rate density of 45−33+75Gpc−3yr−1 when assuming that GW200105 and GW200115 are representative of the NSBH population or 130−69+112Gpc−3yr−1 under the assumption of a broader distribution of component masses.
374 citations
Icahn School of Medicine at Mount Sinai1, Pontifical Catholic University of Chile2, VU University Medical Center3, Cedars-Sinai Medical Center4, Vita-Salute San Raffaele University5, University of Sydney6, Mayo Clinic7, Freeman Hospital8, Newcastle University9, National University of Singapore10, Radboud University Nijmegen11, Kolling Institute of Medical Research12, Macquarie University13, Royal North Shore Hospital14, Jagiellonian University Medical College15, University of Washington Medical Center16, University of Antioquia17, Vancouver General Hospital18, University of Cape Town19
TL;DR: In this paper, the authors presented the first effort of its kind to connect stakeholders, to ignite global awareness of sex-related and gender-related disparities in cardiovascular disease, and to provide a springboard for future research.
354 citations
University Medical Center Groningen1, European Bioinformatics Institute2, Netherlands Cancer Institute3, Georgia Institute of Technology4, Leipzig University5, Johns Hopkins University6, NHS Blood and Transplant7, University of Cambridge8, Garvan Institute of Medical Research9, University of Tartu10, Ontario Institute for Cancer Research11, University of Washington12, Public Health Research Institute13, University of Chicago14, Greifswald University Hospital15, Ludwig Maximilian University of Munich16, University of Bristol17, Erasmus University Rotterdam18, Luleå University of Technology19, University of Westminster20, Royal Devon and Exeter Hospital21, University of Lausanne22, Swiss Institute of Bioinformatics23, University of Dundee24, University of Geneva25, Agency for Science, Technology and Research26, University of Queensland27, Leiden University Medical Center28, Radboud University Nijmegen29, University of Liège30, University of Oxford31, Menzies Research Institute32, Icahn School of Medicine at Mount Sinai33, Ikerbasque34, VU University Amsterdam35, Stanford University36, Turku University Hospital37, University of Turku38, Maastricht University39, Karolinska Institutet40, Utrecht University41, University of Helsinki42, National Institutes of Health43, Technische Universität München44, Wellcome Trust Sanger Institute45, German Cancer Research Center46, Westlake University47, University of New South Wales48
TL;DR: In this article, the authors performed cis-and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium.
Abstract: Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.
344 citations
TL;DR: Aghanim et al. as mentioned in this paper used the same data set to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.
Abstract: Author(s): Aghanim, N; Akrami, Y; Ashdown, M; Aumont, J; Baccigalupi, C; Ballardini, M; Banday, AJ; Barreiro, RB; Bartolo, N; Basak, S; Battye, R; Benabed, K; Bernard, JP; Bersanelli, M; Bielewicz, P; Bock, JJ; Bond, JR; Borrill, J; Bouchet, FR; Boulanger, F; Bucher, M; Burigana, C; Butler, RC; Calabrese, E; Cardoso, JF; Carron, J; Challinor, A; Chiang, HC; Chluba, J; Colombo, LPL; Combet, C; Contreras, D; Crill, BP; Cuttaia, F; De Bernardis, P; De Zotti, G; Delabrouille, J; Delouis, JM; DI Valentino, E; DIego, JM; Dore, O; Douspis, M; Ducout, A; Dupac, X; Dusini, S; Efstathiou, G; Elsner, F; Enslin, TA; Eriksen, HK; Fantaye, Y; Farhang, M; Fergusson, J; Fernandez-Cobos, R; Finelli, F; Forastieri, F; Frailis, M; Fraisse, AA; Franceschi, E; Frolov, A; Galeotta, S; Galli, S; Ganga, K; Genova-Santos, RT; Gerbino, M; Ghosh, T; Gonzalez-Nuevo, J; Gorski, KM; Gratton, S; Gruppuso, A; Gudmundsson, JE; Hamann, J; Handley, W; Hansen, FK; Herranz, D; Hildebrandt, SR; Hivon, E; Huang, Z; Jaffe, AH; Jones, WC; Karakci, A; Keihanen, E; Keskitalo, R; Kiiveri, K; Kim, J; Kisner, TS | Abstract: In the original version, the bounds given in Eqs. (87a) and (87b) on the contribution to the early-time optical depth, (15,30), contained a numerical error in deriving the 95th percentile from the Monte Carlo samples. The corrected 95% upper bounds are: τ(15,30) l 0:018 (lowE, flat τ(15, 30), FlexKnot), (1) τ(15, 30) l 0:023 (lowE, flat knot, FlexKnot): (2) These bounds are a factor of 3 larger than the originally reported results. Consequently, the new bounds do not significantly improve upon previous results from Planck data presented in Millea a Bouchet (2018) as was stated, but are instead comparable. Equations (1) and (2) give results that are now similar to those of Heinrich a Hu (2021), who used the same Planck 2018 data to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.
344 citations
University of Göttingen1, Örebro University2, Guy's and St Thomas' NHS Foundation Trust3, King's College London4, Charité5, Claude Bernard University Lyon 16, University of Jena7, Radboud University Nijmegen8, Agence Nationale de la Recherche9, University Hospital Heidelberg10, University of Duisburg-Essen11, University of Amsterdam12, Carlos III Health Institute13, University of Bern14, University of Barcelona15, National and Kapodistrian University of Athens16, Hebron University17, University of Modena and Reggio Emilia18, University of Medicine and Pharmacy of Craiova19, University of Bonn20
TL;DR: The authors reviewed the intricacies of COVID-19 pathophysiology, its various phenotypes, and the anti-SARS-CoV-2 host response at the humoral and cellular levels.
325 citations
TL;DR: The data recorded by these instruments during their first and second observing runs are described, including the gravitational-wave strain arrays, released as time series sampled at 16384 Hz.
RWTH Aachen University1, Bayer HealthCare Pharmaceuticals2, Martin Luther University of Halle-Wittenberg3, Heidelberg University4, Boston Children's Hospital5, Radboud University Nijmegen6, University of Edinburgh7, University of Hamburg8, Monash University9, Erasmus University Rotterdam10, Molecular Medicine Partnership Unit11
TL;DR: Using single-cell RNA sequencing, the transcriptomes of cells from the proximal and non-proximal tubules of healthy and fibrotic human kidneys are profiled to map the entire human kidney and identify distinct subpopulations of pericytes and fibroblasts as the main cellular sources of scar-forming myofibro Blasts during human kidney fibrosis.
Abstract: Kidney fibrosis is the hallmark of chronic kidney disease progression; however, at present no antifibrotic therapies exist1-3. The origin, functional heterogeneity and regulation of scar-forming cells that occur during human kidney fibrosis remain poorly understood1,2,4. Here, using single-cell RNA sequencing, we profiled the transcriptomes of cells from the proximal and non-proximal tubules of healthy and fibrotic human kidneys to map the entire human kidney. This analysis enabled us to map all matrix-producing cells at high resolution, and to identify distinct subpopulations of pericytes and fibroblasts as the main cellular sources of scar-forming myofibroblasts during human kidney fibrosis. We used genetic fate-tracing, time-course single-cell RNA sequencing and ATAC-seq (assay for transposase-accessible chromatin using sequencing) experiments in mice, and spatial transcriptomics in human kidney fibrosis, to shed light on the cellular origins and differentiation of human kidney myofibroblasts and their precursors at high resolution. Finally, we used this strategy to detect potential therapeutic targets, and identified NKD2 as a myofibroblast-specific target in human kidney fibrosis.
State University of New York Upstate Medical University1, Heidelberg University2, University of Melbourne3, Capital Medical University4, Harvard University5, Monash University, Clayton campus6, Icahn School of Medicine at Mount Sinai7, Montreal Children's Hospital8, Universidade Federal do Rio Grande do Sul9, Peking University10, University of Southampton11, University of Toronto12, University of Washington13, King Khalid University14, King's College London15, Aga Khan University16, Karolinska Institutet17, Radboud University Nijmegen18, Vrije Universiteit Brussel19, University of Nottingham20, Aarhus University21, University of Cologne22, Trinity College, Dublin23, University of Würzburg24, University of Bergen25, University Medical Center Groningen26, University of Wyoming27, University of California, San Francisco28, University of California, Berkeley29, Nottinghamshire Healthcare NHS Foundation Trust30, Duke University31, University of Amsterdam32, Örebro University33, Chongqing Medical University34, Tel Aviv University35, Washington University in St. Louis36, Federal University of Rio de Janeiro37, University College Cork38, University of British Columbia39, University of Pittsburgh40, Oregon Health & Science University41, University of Montpellier42, University of Ibadan43, University of São Paulo44, Hebrew University of Jerusalem45, University of Sydney46, Jawaharlal Institute of Postgraduate Medical Education and Research47, University of Canterbury48, Autonomous University of Barcelona49, Stellenbosch University50, University of California, Davis51, National Medical College52, Hofstra University53, University of Texas Health Science Center at Houston54, University of Southern Denmark55, University of California, Irvine56, Cardiff University57, Okinawa Institute of Science and Technology58, HU University of Applied Sciences Utrecht59, Katholieke Universiteit Leuven60, University of the Free State61, University of Turin62, Johns Hopkins University63, University of Zurich64
TL;DR: In this article, the authors presented 208 empirically supported statements about ADHD using meta-analysis, which allow for firm statements about the nature, course, outcome causes and treatments for disorders that are useful for reducing misconceptions and stigma.
Kazunori Akiyama1, Kazunori Akiyama2, Kazunori Akiyama3, Juan-Carlos Algaba4 +291 more•Institutions (72)
TL;DR: In this article, the authors present a list of authors who have contributed to the work of the authors of this paper: Akiyama, Kazunori; Algaba, Juan Carlos; Alberdi, Antxon; Alef, Walter; Anantua, Richard; Asada, Keiichi; Azulay, Rebecca; Baczko, Anne-Kathrin; Ball, David; Balokovic, Mislav; Barrett, John; Benson, Bradford A.; Bintley, Dan; Blackburn, Lindy; Blundell
Abstract: Full list of authors: Akiyama, Kazunori; Algaba, Juan Carlos; Alberdi, Antxon; Alef, Walter; Anantua, Richard; Asada, Keiichi; Azulay, Rebecca; Baczko, Anne-Kathrin; Ball, David; Balokovic, Mislav; Barrett, John; Benson, Bradford A.; Bintley, Dan; Blackburn, Lindy; Blundell, Raymond; Boland, Wilfred; Bouman, Katherine L.; Bower, Geoffrey C.; Boyce, Hope Bremer, Michael; Brinkerink, Christiaan D.; Brissenden, Roger; Britzen, Silke; Broderick, Avery E.; Broguiere, Dominique; Bronzwaer, Thomas; Byun, Do-Young; Carlstrom, John E.; Chael, Andrew; Chan, Chi-kwan; Chatterjee, Shami; Chatterjee, Koushik; Chen, Ming-Tang; Chen, Yongjun; Chesler, Paul M.; Cho, Ilje; Christian, Pierre; Conway, John E.; Cordes, James M.; Crawford, Thomas M.; Crew, Geoffrey B.; Cruz-Osorio, Alejandro; Cui, Yuzhu; Davelaar, Jordy; De Laurentis, Mariafelicia; Deane, Roger; Dempsey, Jessica; Desvignes, Gregory; Dexter, Jason; Doeleman, Sheperd S.; Eatough, Ralph P.; Falcke, Heino; Farah, Joseph; Fish, Vincent L.; Fomalont, Ed; Ford, H. Alyson; Fraga-Encinas, Raquel; Friberg, Per; Fromm, Christian M.; Fuentes, Antonio; Galison, Peter; Gammie, Charles F.; Garcia, Roberto; Gelles, Zachary; Gentaz, Olivier; Georgiev, Boris; Goddi, Ciriaco; Gold, Roman; Gomez, Jose L.; Gomez-Ruiz, Arturo I.; Gu, Minfeng; Gurwell, Mark; Hada, Kazuhiro; Haggard, Daryl; Hecht, Michael H.; Hesper, Ronald; Himwich, Elizabeth; Ho, Luis C.; Ho, Paul; Honma, Mareki; Huang, Chih-Wei L.; Huang, Lei; Hughes, David H.; Ikeda, Shiro; Inoue, Makoto; Issaoun, Sara; James, David J.; Jannuzi, Buell T.; Janssen, Michael; Jeter, Britton; Jiang, Wu; Jimenez-Rosales, Alejandra; Johnson, Michael D.; Jorstad, Svetlana; Jung, Taehyun; Karami, Mansour; Karuppusamy, Ramesh; Kawashima, Tomohisa; Keating, Garrett K.; Kettenis, Mark; Kim, Dong-Jin; Kim, Jae-Young; Kim, Jongsoo; Kim, Junhan; Kino, Motoki; Koay, Jun Yi; Kofuji, Yutaro; Koch, Patrick M.; Koyama, Shoko; Kramer, Michael; Kramer, Carsten; Krichbaum, Thomas P.; Kuo, Cheng-Yu; Lauer, Tod R.; Lee, Sang-Sung; Levis, Aviad; Li, Yan-Rong; Li, Zhiyuan; Lindqvist, Michael; Lico, Rocco; Lindahl, Greg; Liu, Jun; Liu, Kuo; Liuzzo, Elisabetta; Lo, Wen-Ping; Lobanov, Andrei P.; Loinard, Laurent; Lonsdale, Colin; Lu, Ru-Sen; MacDonald, Nicholas R.; Mao, Jirong; Marchili, Nicola; Markoff, Sera; Marrone, Daniel P.; Marscher, Alan P.; Marti-Vidal, Ivan; Matsushita, Satoki; Matthews, Lynn D.; Medeiros, Lia; Menten, Karl M.; Mizuno, Izumi; Mizuno, Yosuke; Moran, James M.; Moriyama, Kotaro; Moscibrodzka, Monika; Muller, Cornelia; Musoke, Gibwa; Mus Mejias, Alejandro; Michalik, Daniel; Nadolski, Andrew; Nagai, Hiroshi; Nagar, Neil M.; Nakamura, Masanori; Narayan, Ramesh; Narayanan, Gopal; Natarajan, Iniyan; Nathanail, Antonios; Neilsen, Joey; Neri, Roberto; Ni, Chunchong; Noutsos, Aristeidis; Nowak, Michael A.; Okino, Hiroki; Olivares, Hector; Ortiz-Leon, Gisela N.; Oyama, Tomoaki; Ozel, Feryal; Palumbo, Daniel C. M.; Park, Jongho; Patel, Nimesh; Pen, Ue-Li; Pesce, Dominic W.; Pietu, Vincent; Plambeck, Richard; PopStefanija, Aleksandar; Porth, Oliver; Potzl, Felix M.; Prather, Ben; Preciado-Lopez, Jorge A.; Psaltis, Dimitrios; Pu, Hung-Yi; Ramakrishnan, Venkatessh; Rao, Ramprasad; Rawlings, Mark G.; Raymond, Alexander W.; Rezzolla, Luciano; Ricarte, Angelo; Ripperda, Bart; Roelofs, Freek; Rogers, Alan; Ros, Eduardo; Rose, Mel; Roshanineshat, Arash; Rottmann, Helge; Roy, Alan L.; Ruszczyk, Chet; Rygl, Kazi L. J.; Sanchez, Salvador; Sanchez-Arguelles, David; Sasada, Mahito; Savolainen, Tuomas; Schloerb, F. Peter; Schuster, Karl-Friedrich; Shao, Lijing; Shen, Zhiqiang; Small, Des; Sohn, Bong Won; SooHoo, Jason; Sun, He; Tazaki, Fumie; Tetarenko, Alexandra J.; Tiede, Paul; Tilanus, Remo P. J.; Titus, Michael; Toma, Kenji; Torne, Pablo; Trent, Tyler; Traianou, Efthalia; Trippe, Sascha; van Bemmel, Ilse; van Langevelde, Huib Jan; van Rossum, Daniel R.; Wagner, Jan; Ward-Thompson, Derek; Wardle, John; Weintroub, Jonathan; Wex, Norbert; Wharton, Robert; Wielgus, Maciek; Wong, George N.; Wu, Qingwen; Yoon, Doosoo; Young, Andre; Young, Ken; Younsi, Ziri; Yuan, Feng; Yuan, Ye-Fei; Zensus, J. Anton; Zhao, Guang-Yao; Zhao, Shan-Shan; Event Horizon Telescope Collaboration.-- This is an open access article, original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
TL;DR: This comprehensive health assessment revealed severe problems in several health domains in a substantial number of ex-COVID-19 patients, and longer follow-up studies are warranted to elucidate natural trajectories and to find predictors of complicated long-term trajectories of recovery.
Abstract: BACKGROUND: Long-term health sequelae of coronavirus disease 2019 (COVID-19) may be multiple but have thus far not been systematically studied. METHODS: All patients discharged after COVID-19 from the Radboud University Medical Center, Nijmegen, the Netherlands, were consecutively invited to a multidisciplinary outpatient facility. Also, nonadmitted patients with mild disease but with symptoms persisting >6 weeks could be referred by general practitioners. Patients underwent a standardized assessment including measurements of lung function, chest computed tomography (CT)/X-ray, 6-minute walking test, body composition, and questionnaires on mental, cognitive, health status, and quality of life (QoL). RESULTS: 124 patients (59â
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14 years, 60% male) were included: 27 with mild, 51 with moderate, 26 with severe, and 20 with critical disease. Lung diffusion capacity was below the lower limit of normal in 42% of discharged patients. 99% of discharged patients had reduced ground-glass opacification on repeat CT imaging, and normal chest X-rays were found in 93% of patients with mild disease. Residual pulmonary parenchymal abnormalities were present in 91% of discharged patients and correlated with reduced lung diffusion capacity. Twenty-two percent had low exercise capacity, 19% low fat-free mass index, and problems in mental and/or cognitive function were found in 36% of patients. Health status was generally poor, particularly in the domains functional impairment (64%), fatigue (69%), and QoL (72%). CONCLUSIONS: This comprehensive health assessment revealed severe problems in several health domains in a substantial number of ex-COVID-19 patients. Longer follow-up studies are warranted to elucidate natural trajectories and to find predictors of complicated long-term trajectories of recovery.
Icahn School of Medicine at Mount Sinai1, Radboud University Nijmegen2, Technische Universität München3, Niigata University4, National and Kapodistrian University of Athens5, Université Paris-Saclay6, Medical University of Vienna7, University of Texas Southwestern Medical Center8, Charles University in Prague9, I.M. Sechenov First Moscow State Medical University10, Samsung Medical Center11, Fudan University12, Aarhus University Hospital13, Guy's and St Thomas' NHS Foundation Trust14, Rambam Health Care Campus15, University of North Carolina at Chapel Hill16, Bristol-Myers Squibb17
TL;DR: In this article, the role of adjuvant treatment in high-risk muscle-invasive urothelial carcinoma after radical surgery was not clear, and a phase 3, multicenter, double-blind, randomized, controlled trial was conducted.
Abstract: Background The role of adjuvant treatment in high-risk muscle-invasive urothelial carcinoma after radical surgery is not clear. Methods In a phase 3, multicenter, double-blind, randomized, controlled trial, we assigned patients with muscle-invasive urothelial carcinoma who had undergone radical surgery to receive, in a 1:1 ratio, either nivolumab (240 mg intravenously) or placebo every 2 weeks for up to 1 year. Neoadjuvant cisplatin-based chemotherapy before trial entry was allowed. The primary end points were disease-free survival among all the patients (intention-to-treat population) and among patients with a tumor programmed death ligand 1 (PD-L1) expression level of 1% or more. Survival free from recurrence outside the urothelial tract was a secondary end point. Results A total of 353 patients were assigned to receive nivolumab and 356 to receive placebo. The median disease-free survival in the intention-to-treat population was 20.8 months (95% confidence interval [CI], 16.5 to 27.6) with nivolumab and 10.8 months (95% CI, 8.3 to 13.9) with placebo. The percentage of patients who were alive and disease-free at 6 months was 74.9% with nivolumab and 60.3% with placebo (hazard ratio for disease recurrence or death, 0.70; 98.22% CI, 0.55 to 0.90; P Conclusions In this trial involving patients with high-risk muscle-invasive urothelial carcinoma who had undergone radical surgery, disease-free survival was longer with adjuvant nivolumab than with placebo in the intention-to-treat population and among patients with a PD-L1 expression level of 1% or more. (Funded by Bristol Myers Squibb and Ono Pharmaceutical; CheckMate 274 ClinicalTrials.gov number, NCT02632409.).
University of Groningen1, Erasmus University Rotterdam2, Katholieke Universiteit Leuven3, Chinese Academy of Sciences4, University of Surrey5, King's College London6, University of Toronto7, Avera Health8, Karolinska Institutet9, University of Copenhagen10, University of Greifswald11, University of Kiel12, Yeshiva University13, Sungkyunkwan University14, University of Tartu15, Weizmann Institute of Science16, Copenhagen University Hospital17, University of Texas Health Science Center at Houston18, University of Alabama at Birmingham19, Stockholm University20, University of Michigan21, VU University Amsterdam22, University of Oxford23, University of Bristol24, University of Amsterdam25, Maastricht University26, University of California, San Diego27, University of Eastern Finland28, National Institutes of Health29, University of California, Los Angeles30, Linköping University31, Harvard University32, Radboud University Nijmegen33, University of North Carolina at Chapel Hill34, Ewha Womans University35, Fred Hutchinson Cancer Research Center36, National Research Council37
TL;DR: In this article, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts) and found high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples.
Abstract: To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10−8) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10−20), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10−10 < P < 5 × 10−8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.
National and Kapodistrian University of Athens1, University of Ioannina2, Aristotle University of Thessaloniki3, University of Brescia4, Vita-Salute San Raffaele University5, University of Genoa6, Humanitas University7, University of Patras8, University of Bonn9, Radboud University Nijmegen10, Copenhagen University Hospital11, Democritus University of Thrace12
TL;DR: The SAVE-MORE trial as discussed by the authors evaluated the efficacy and safety of anakinra, an IL-1α/β inhibitor, in 594 patients with COVID-19 at risk of progressing to respiratory failure.
Abstract: Early increase of soluble urokinase plasminogen activator receptor (suPAR) serum levels is indicative of increased risk of progression of coronavirus disease 2019 (COVID-19) to respiratory failure. The SAVE-MORE double-blind, randomized controlled trial evaluated the efficacy and safety of anakinra, an IL-1α/β inhibitor, in 594 patients with COVID-19 at risk of progressing to respiratory failure as identified by plasma suPAR ≥6 ng ml−1, 85.9% (n = 510) of whom were receiving dexamethasone. At day 28, the adjusted proportional odds of having a worse clinical status (assessed by the 11-point World Health Organization Clinical Progression Scale (WHO-CPS)) with anakinra, as compared to placebo, was 0.36 (95% confidence interval 0.26–0.50). The median WHO-CPS decrease on day 28 from baseline in the placebo and anakinra groups was 3 and 4 points, respectively (odds ratio (OR) = 0.40, P < 0.0001); the respective median decrease of Sequential Organ Failure Assessment (SOFA) score on day 7 from baseline was 0 and 1 points (OR = 0.63, P = 0.004). Twenty-eight-day mortality decreased (hazard ratio = 0.45, P = 0.045), and hospital stay was shorter. The SAVE-MORE phase 3 study demonstrates the efficacy of anakinra, an IL-1α/β inhibitor, in patients with COVID-19 and high serum levels of soluble plasminogen activator receptor.
26 Feb 2021
TL;DR: In this paper, the authors present traits of medical imaging, highlight clinical needs and technical challenges in medical imaging and describe how emerging trends in deep learning are addressing these issues, and conclude with a discussion and presentation of promising future directions.
Abstract: Since its renaissance, deep learning (DL) has been widely used in various medical imaging tasks and has achieved remarkable success in many medical imaging applications, thereby propelling us into the so-called artificial intelligence (AI) era. It is known that the success of AI is mostly attributed to the availability of big data with annotations for a single task and the advances in high-performance computing. However, medical imaging presents unique challenges that confront DL approaches. In this survey article, we first present traits of medical imaging, highlight both clinical needs and technical challenges in medical imaging, and describe how emerging trends in DL are addressing these issues. We cover the topics of network architecture, sparse and noisy labels, federating learning, interpretability, uncertainty quantification, and so on. Then, we present several case studies that are commonly found in clinical practice, including digital pathology and chest, brain, cardiovascular, and abdominal imaging. Rather than presenting an exhaustive literature survey, we instead describe some prominent research highlights related to these case study applications. We conclude with a discussion and presentation of promising future directions.
University of Bonn1, Hewlett-Packard2, Radboud University Nijmegen3, National and Kapodistrian University of Athens4, University of Kiel5, University of Tübingen6, Saarland University7, Boston Children's Hospital8, Technische Universität München9, University of Cologne10, University Hospital Bonn11, RWTH Aachen University12, Stanford University13
TL;DR: Wang et al. as mentioned in this paper proposed Swarm Learning, a decentralized machine learning approach that unifies edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator.
Abstract: Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.
TL;DR: In the field of histopathology, deep learning algorithms have been developed that perform similarly to trained pathologists for tasks such as tumor detection and grading, but despite these promising results, very few algorithms have reached clinical implementation, challenging the balance between hope and hype for these new techniques as discussed by the authors.
Abstract: Machine learning techniques have great potential to improve medical diagnostics, offering ways to improve accuracy, reproducibility and speed, and to ease workloads for clinicians. In the field of histopathology, deep learning algorithms have been developed that perform similarly to trained pathologists for tasks such as tumor detection and grading. However, despite these promising results, very few algorithms have reached clinical implementation, challenging the balance between hope and hype for these new techniques. This Review provides an overview of the current state of the field, as well as describing the challenges that still need to be addressed before artificial intelligence in histopathology can achieve clinical value.
TL;DR: In this paper, the authors investigated whether focal boosting of the macroscopic visible tumor with external beam radiotherapy increases biochemical disease-free survival (bDFS) in patients with localized localized cancer.
Abstract: PURPOSEThis study investigates whether focal boosting of the macroscopic visible tumor with external beam radiotherapy increases biochemical disease-free survival (bDFS) in patients with localized ...
McGill University1, Bandim Health Project2, Washington University in St. Louis3, University of Chicago4, Radboud University Nijmegen5, Dresden University of Technology6, University of Melbourne7, Baylor College of Medicine8, Eindhoven University of Technology9, Icahn School of Medicine at Mount Sinai10, University of Cape Town11, Rockefeller University12, Pasteur Institute13, Harvard University14, German Center for Neurodegenerative Diseases15, University of Naples Federico II16, New York University17, Trinity College, Dublin18, National Institutes of Health19, Vanderbilt University20, University of Bonn21, Aix-Marseille University22, University of Southern Denmark23, Cornell University24, Memorial Sloan Kettering Cancer Center25, East Tennessee State University26, Broad Institute27, Massachusetts Institute of Technology28
TL;DR: A common framework is established that describes the experimental standards for defining trained immunity in both in vitro and in vivo settings, as well as in experimental models and human subjects.
Abstract: The similarities and differences between trained immunity and other immune processes are the subject of intense interrogation. Therefore, a consensus on the definition of trained immunity in both in vitro and in vivo settings, as well as in experimental models and human subjects, is necessary for advancing this field of research. Here we aim to establish a common framework that describes the experimental standards for defining trained immunity.
TL;DR: NeuroKit2 as discussed by the authors is an open-source, community-driven, and user-centered Python package for neurophysiological signal processing, which includes high-level functions that enable data processing in a few lines of code using validated pipelines.
Abstract: NeuroKit2 is an open-source, community-driven, and user-centered Python package for neurophysiological signal processing. It provides a comprehensive suite of processing routines for a variety of bodily signals (e.g., ECG, PPG, EDA, EMG, RSP). These processing routines include high-level functions that enable data processing in a few lines of code using validated pipelines, which we illustrate in two examples covering the most typical scenarios, such as an event-related paradigm and an interval-related analysis. The package also includes tools for specific processing steps such as rate extraction and filtering methods, offering a trade-off between high-level convenience and fine-tuned control. Its goal is to improve transparency and reproducibility in neurophysiological research, as well as foster exploration and innovation. Its design philosophy is centred on user-experience and accessibility to both novice and advanced users.
University of Toronto1, University of São Paulo2, King Saud University3, Medical College of Wisconsin4, University College Dublin5, Mater Misericordiae University Hospital6, Université de Sherbrooke7, Libin Cardiovascular Institute of Alberta8, Ottawa Hospital Research Institute9, Queen's University10, University of Vermont11, University of Vermont Medical Center12, Université de Montréal13, University of Alberta14, Radboud University Nijmegen15, University of British Columbia16, University of Bern17
TL;DR: In this paper, the authors evaluated the effects of therapeutic heparin compared with prophylactic hepharmin among moderately ill patients with covid-19 admitted to hospital wards.
Abstract: Objective To evaluate the effects of therapeutic heparin compared with prophylactic heparin among moderately ill patients with covid-19 admitted to hospital wards. Design Randomised controlled, adaptive, open label clinical trial. Setting 28 hospitals in Brazil, Canada, Ireland, Saudi Arabia, United Arab Emirates, and US. Participants 465 adults admitted to hospital wards with covid-19 and increased D-dimer levels were recruited between 29 May 2020 and 12 April 2021 and were randomly assigned to therapeutic dose heparin (n=228) or prophylactic dose heparin (n=237). Interventions Therapeutic dose or prophylactic dose heparin (low molecular weight or unfractionated heparin), to be continued until hospital discharge, day 28, or death. Main outcome measures The primary outcome was a composite of death, invasive mechanical ventilation, non-invasive mechanical ventilation, or admission to an intensive care unit, assessed up to 28 days. The secondary outcomes included all cause death, the composite of all cause death or any mechanical ventilation, and venous thromboembolism. Safety outcomes included major bleeding. Outcomes were blindly adjudicated. Results The mean age of participants was 60 years; 264 (56.8%) were men and the mean body mass index was 30.3 kg/m2. At 28 days, the primary composite outcome had occurred in 37/228 patients (16.2%) assigned to therapeutic heparin and 52/237 (21.9%) assigned to prophylactic heparin (odds ratio 0.69, 95% confidence interval 0.43 to 1.10; P=0.12). Deaths occurred in four patients (1.8%) assigned to therapeutic heparin and 18 patients (7.6%) assigned to prophylactic heparin (0.22, 0.07 to 0.65; P=0.006). The composite of all cause death or any mechanical ventilation occurred in 23 patients (10.1%) assigned to therapeutic heparin and 38 (16.0%) assigned to prophylactic heparin (0.59, 0.34 to 1.02; P=0.06). Venous thromboembolism occurred in two patients (0.9%) assigned to therapeutic heparin and six (2.5%) assigned to prophylactic heparin (0.34, 0.07 to 1.71; P=0.19). Major bleeding occurred in two patients (0.9%) assigned to therapeutic heparin and four (1.7%) assigned to prophylactic heparin (0.52, 0.09 to 2.85; P=0.69). Conclusions In moderately ill patients with covid-19 and increased D-dimer levels admitted to hospital wards, therapeutic heparin was not significantly associated with a reduction in the primary outcome but the odds of death at 28 days was decreased. The risk of major bleeding appeared low in this trial. Trial registration ClinicalTrials.gov NCT04362085.
Kazunori Akiyama1, Kazunori Akiyama2, Kazunori Akiyama3, Juan-Carlos Algaba4 +292 more•Institutions (73)
TL;DR: In this article, the authors present a list of the authors who contributed to the development of this work, including: Akiyama, Kazunori; Algaba, Juan Carlos; Alberdi, Antxon; Anantua, Richard; Asada, Keiichi; Azulay, Rebecca; Baczko, Anne-Kathrin; Ball, David; Balokovic, Mislav; Barrett, John; Benson, Bradford A; Bintley, Dan; Bunderwood, Nissim; Bower, Geoffrey C;
Abstract: Full list of authors: Akiyama, Kazunori; Algaba, Juan Carlos; Alberdi, Antxon; Alef, Walter; Anantua, Richard; Asada, Keiichi; Azulay, Rebecca; Baczko, Anne-Kathrin; Ball, David; Balokovic, Mislav; Barrett, John; Benson, Bradford A.; Bintley, Dan; Blackburn, Lindy; Blundell, Raymond; Boland, Wilfred; Bouman, Katherine L.; Bower, Geoffrey C.; Boyce, Hope Bremer, Michael; Brinkerink, Christiaan D.; Brissenden, Roger; Britzen, Silke; Broderick, Avery E.; Broguiere, Dominique; Bronzwaer, Thomas; Byun, Do-Young; Carlstrom, John E.; Chael, Andrew; Chan, Chi-kwan; Chatterjee, Shami; Chatterjee, Koushik; Chen, Ming-Tang; Chen, Yongjun; Chesler, Paul M.; Cho, Ilje; Christian, Pierre; Conway, John E.; Cordes, James M.; Crawford, Thomas M.; Crew, Geoffrey B.; Cruz-Osorio, Alejandro; Cui, Yuzhu; Davelaar, Jordy; De Laurentis, Mariafelicia; Deane, Roger; Dempsey, Jessica; Desvignes, Gregory; Dexter, Jason; Doeleman, Sheperd S.; Eatough, Ralph P.; Falcke, Heino; Farah, Joseph; Fish, Vincent L.; Fomalont, Ed; Ford, H. Alyson; Fraga-Encinas, Raquel; Freeman, William T.; Friberg, Per; Fromm, Christian M.; Fuentes, Antonio; Galison, Peter; Gammie, Charles F.; Garcia, Roberto; Gentaz, Olivier; Georgiev, Boris; Goddi, Ciriaco; Gold, Roman; Gomez, Jose L.; Gomez-Ruiz, Arturo I.; Gu, Minfeng; Gurwell, Mark; Hada, Kazuhiro; Haggard, Daryl; Hecht, Michael H.; Hesper, Ronald; Ho, Luis C.; Ho, Paul; Honma, Mareki; Huang, Chih-Wei L.; Huang, Lei; Hughes, David H.; Ikeda, Shiro; Inoue, Makoto; Issaoun, Sara; James, David J.; Jannuzi, Buell T.; Janssen, Michael; Jeter, Britton; Jiang, Wu; Jimenez-Rosales, Alejandra; Johnson, Michael D.; Jorstad, Svetlana; Jung, Taehyun; Karami, Mansour; Karuppusamy, Ramesh; Kawashima, Tomohisa; Keating, Garrett K.; Kettenis, Mark; Kim, Dong-Jin; Kim, Jae-Young; Kim, Jongsoo; Kim, Junhan; Kino, Motoki; Koay, Jun Yi; Kofuji, Yutaro; Koch, Patrick M.; Koyama, Shoko; Kramer, Michael; Kramer, Carsten; Krichbaum, Thomas P.; Kuo, Cheng-Yu; Lauer, Tod R.; Lee, Sang-Sung; Levis, Aviad; Li, Yan-Rong; Li, Zhiyuan; Lindqvist, Michael; Lico, Rocco; Lindahl, Greg; Liu, Jun; Liu, Kuo; Liuzzo, Elisabetta; Lo, Wen-Ping; Lobanov, Andrei P.; Loinard, Laurent; Lonsdale, Colin; Lu, Ru-Sen; MacDonald, Nicholas R.; Mao, Jirong; Marchili, Nicola; Markoff, Sera; Marrone, Daniel P.; Marscher, Alan P.; Marti-Vidal, Ivan; Matsushita, Satoki; Matthews, Lynn D.; Medeiros, Lia; Menten, Karl M.; Mizuno, Izumi; Mizuno, Yosuke; Moran, James M.; Moriyama, Kotaro; Moscibrodzka, Monika; Muller, Cornelia; Musoke, Gibwa; Mejias, Alejandro Mus; Michalik, Daniel; Nadolski, Andrew; Nagai, Hiroshi; Nagar, Neil M.; Nakamura, Masanori; Narayan, Ramesh; Narayanan, Gopal; Natarajan, Iniyan; Nathanail, Antonios; Neilsen, Joey; Neri, Roberto; Ni, Chunchong; Noutsos, Aristeidis; Nowak, Michael A.; Okino, Hiroki; Olivares, Hector; Ortiz-Leon, Gisela N.; Oyama, Tomoaki; Ozel, Feryal; Palumbo, Daniel C. M.; Park, Jongho; Patel, Nimesh; Pen, Ue-Li; Pesce, Dominic W.; Pietu, Vincent; Plambeck, Richard; PopStefanija, Aleksandar; Porth, Oliver; Potzl, Felix M.; Prather, Ben; Preciado-Lopez, Jorge A.; Psaltis, Dimitrios; Pu, Hung-Yi; Ramakrishnan, Venkatessh; Rao, Ramprasad; Rawlings, Mark G.; Raymond, Alexander W.; Rezzolla, Luciano; Ricarte, Angelo; Ripperda, Bart; Roelofs, Freek; Rogers, Alan; Ros, Eduardo; Rose, Mel; Roshanineshat, Arash; Rottmann, Helge; Roy, Alan L.; Ruszczyk, Chet; Rygl, Kazi L. J.; Sanchez, Salvador; Sanchez-Arguelles, David; Sasada, Mahito; Savolainen, Tuomas; Schloerb, F. Peter; Schuster, Karl-Friedrich; Shao, Lijing; Shen, Zhiqiang; Small, Des; Sohn, Bong Won; SooHoo, Jason; Sun, He; Tazaki, Fumie; Tetarenko, Alexandra J.; Tiede, Paul; Tilanus, Remo P. J.; Titus, Michael; Toma, Kenji; Torne, Pablo; Trent, Tyler; Traianou, Efthalia; Trippe, Sascha; van Bemmel, Ilse; van Langevelde, Huib Jan; van Rossum, Daniel R.; Wagner, Jan; Ward-Thompson, Derek; Wardle, John; Weintroub, Jonathan; Wex, Norbert; Wharton, Robert; Wielgus, Maciek; Wong, George N.; Wu, Qingwen; Yoon, Doosoo; Young, Andre; Young, Ken; Younsi, Ziri; Yuan, Feng; Yuan, Ye-Fei; Zensus, J. Anton; Zhao, Guang-Yao; Zhao, Shan-Shan; Event Horizon Telescope Collaboration.-- This is an open access article, original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
TL;DR: In this paper, the authors defined essential action points (summarized in Box 1), among which is advocating the inclusion of CKD patients in clinical trials testing the efficacy of drugs and vaccines to prevent severe COVID-19.
Abstract: Diabetes, hypertension and cardiovascular disease have been listed as risk factors for severe coronavirus disease 2019 (COVID-19) since the first report of the disease in January 2020. However, this report did not mention chronic kidney disease (CKD) nor did it provide information on the relevance of estimated glomerular filtration rate (eGFR) or albuminuria. As the disease spread across the globe, information on larger populations with greater granularity on risk factors emerged. The recently published OpenSAFELY project analysed factors associated with COVID-19 death in 17 million patients. The picture that arose differs significantly from initial reports. For example, hypertension is not an independent risk factor for COVID-19 death [adjusted hazard ratio (aHR) 0.89], but renal disease very much is. Dialysis (aHR 3.69), organ transplantation (aHR 3.53) and CKD (aHR 2.52 for patients with eGFR <30 mL/min/1.73 m 2) represent three of the four comorbidities associated with the highest mortality risk from COVID-19. The risk associated with CKD Stages 4 and 5 is higher than the risk associated with diabetes mellitus (aHR range 1.31–1.95, depending upon glycaemic control) or chronic heart disease (aHR 1.17). In another recent publication, the Global Burden of Disease collaboration identified that worldwide, CKD is the most prevalent risk factor for severe COVID-19. Moreover, the distribution of risk factors for COVID-19 mortality appears to be different in patients with CKD when compared with the general population. The high prevalence of CKD in combination with the elevated risk of mortality from COVID-19 in CKD necessitates urgent action for this group of patients. This article defines essential action points (summarized in Box 1), among which is advocating the inclusion of CKD patients in clinical trials testing the efficacy of drugs and vaccines to prevent severe COVID-19.
TL;DR: This work proposes a deep convolutional neural network model, Simple Fully Convolutional Network (SFCN), for accurate prediction of brain age using T1-weighted structural MRI data, which achieved state-of-the-art performance in UK Biobank data.
TL;DR: In this paper, the authors examined the use of DAGs in applied health research to inform recommendations for improving their transparency and utility in future research and made several recommendations to improve the reporting and use of the DAG.
Abstract: Background Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal effects. This review examined the use of DAGs in applied health research to inform recommendations for improving their transparency and utility in future research. Methods Original health research articles published during 1999–2017 mentioning ‘directed acyclic graphs’ (or similar) or citing DAGitty were identified from Scopus, Web of Science, Medline and Embase. Data were extracted on the reporting of: estimands, DAGs and adjustment sets, alongside the characteristics of each article’s largest DAG. Results A total of 234 articles were identified that reported using DAGs. A fifth (n = 48, 21%) reported their target estimand(s) and half (n = 115, 48%) reported the adjustment set(s) implied by their DAG(s). Two-thirds of the articles (n = 144, 62%) made at least one DAG available. DAGs varied in size but averaged 12 nodes [interquartile range (IQR): 9–16, range: 3–28] and 29 arcs (IQR: 19–42, range: 3–99). The median saturation (i.e. percentage of total possible arcs) was 46% (IQR: 31–67, range: 12–100). 37% (n = 53) of the DAGs included unobserved variables, 17% (n = 25) included ‘super-nodes’ (i.e. nodes containing more than one variable) and 34% (n = 49) were visually arranged so that the constituent arcs flowed in the same direction (e.g. top-to-bottom). Conclusion There is substantial variation in the use and reporting of DAGs in applied health research. Although this partly reflects their flexibility, it also highlights some potential areas for improvement. This review hence offers several recommendations to improve the reporting and use of DAGs in future research.