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Improved therapy‐success prediction with GSS estimated from clinical HIV‐1 sequences
In: Journal of the International AIDS Society, Volume 17, Issue 4S3
ISSN: 1758-2652
IntroductionRules‐based HIV‐1 drug‐resistance interpretation (DRI) systems disregard many amino‐acid positions of the drug's target protein. The aims of this study are (1) the development of a drug‐resistance interpretation system that is based on HIV‐1 sequences from clinical practice rather than hard‐to‐get phenotypes, and (2) the assessment of the benefit of taking all available amino‐acid positions into account for DRI.Materials and MethodsA dataset containing 34,934 therapy‐naïve and 30,520 drug‐exposed HIV‐1 pol sequences with treatment history was extracted from the EuResist database and the Los Alamos National Laboratory database. 2,550 therapy‐change‐episode baseline sequences (TCEB) were assigned to test set A. Test set B contains 1,084 TCEB from the HIVdb TCE repository. Sequences from patients absent in the test sets were used to train three linear support vector machines to produce scores that predict drug exposure pertaining to each of 20 antiretrovirals: the first one uses the full amino‐acid sequences (DEfull), the second one only considers IAS drug‐resistance positions (DEonlyIAS), and the third one disregards IAS drug‐resistance positions (DEnoIAS). For performance comparison, test sets A and B were evaluated with DEfull, DEnoIAS, DEonlyIAS, geno2pheno[resistance], HIVdb, ANRS, HIV‐GRADE, and REGA. Clinically‐validated cut‐offs were used to convert the continuous output of the first four methods into susceptible‐intermediate‐resistant (SIR) predictions. With each method, a genetic susceptibility score (GSS) was calculated for each therapy episode in each test set by converting the SIR prediction for its compounds to integer: S=2, I=1, and R=0. The GSS were used to predict therapy success as defined by the EuResist standard datum definition. Statistical significance was assessed using a Wilcoxon signed‐rank test.ResultsA comparison of the therapy‐success prediction performances among the different interpretation systems for test set A can be found in Table 1, while those for test set B are found in Figure 1. Therapy‐success prediction of first‐line therapies with DEnoIAS performed better than DEonlyIAS (p<10–16).ConclusionsTherapy success prediction benefits from the consideration of all available mutations. The increase in performance was largest in first‐line therapies with transmitted drug‐resistance mutations.
Digitalisierung und Demokratie
Die Digitalisierung spielt bei den Prozessen und Entwicklungen in einer Demokratie eine immer größere Rolle. Denn Digitalisierung erweitert die Möglichkeiten der Information, Kommunikation und Partizipation. Gleichzeitig können digitale Technologien zu einer schnellen Verbreitung von Falschinformationen beitragen und bergen ein Potenzial für Meinungsmanipulation, zum Beispiel vor Wahlen. Dieses Spannungsfeld ist Thema der Stellungnahme "Digitalisierung und Demokratie". Darin analysieren die Autorinnen und Autoren Aspekte des Zusammenspiels von Digitalisierung und Demokratie. Darauf aufbauend formulieren sie Handlungsempfehlungen zur Gestaltung künftiger Entwicklungen durch Politik, Recht und Zivilgesellschaft.
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Coronavirus-Pandemie – Die Krise nachhaltig überwinden: Dritte Ad-hoc-Stellungnahme zur COVID-19-Pandemie ; Coronavirus Pandemic – Sustainable Ways to Overcome the Crisis : 3rd Ad-hoc Statement
Die Nationale Akademie der Wissenschaften Leopoldina hat eine dritte Ad-hoc-Stellungnahme zur COVID-19-Pandemie veröffentlicht. Das Papier mit dem Titel "Coronavirus-Pandemie – Die Krise nachhaltig überwinden" behandelt die psychologischen, sozialen, rechtlichen, pädagogischen und wirtschaftlichen Aspekte der Pandemie und beschreibt Strategien, die zu einer schrittweisen Rückkehr in die gesellschaftliche Normalität beitragen können. ; The German National Academy of Sciences Leopoldina has published a third ad-hoc-statement on the COVID-19 pandemic. The paper entitled "Coronavirus Pandemic - Sustainable Ways to Overcome the Crisis" deals with the psychological, social, legal, educational, and economic aspects of the pandemic and describes strategies that may contribute to a gradual return to normality.
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Digitalisierung und Demokratie
Die Digitalisierung spielt bei den Prozessen und Entwicklungen in einer Demokratie eine immer größere Rolle. Denn Digitalisierung erweitert die Möglichkeiten der Information, Kommunikation und Partizipation. Gleichzeitig können digitale Technologien zu einer schnellen Verbreitung von Falschinformationen beitragen und bergen ein Potenzial für Meinungsmanipulation, zum Beispiel vor Wahlen. Dieses Spannungsfeld ist Thema der Stellungnahme "Digitalisierung und Demokratie". Darin analysieren die Autorinnen und Autoren Aspekte des Zusammenspiels von Digitalisierung und Demokratie. Darauf aufbauend formulieren sie Handlungsempfehlungen zur Gestaltung künftiger Entwicklungen durch Politik, Recht und Zivilgesellschaft.
Making sense of big data in health research:Towards an EU action plan
In: Auffray , C , Balling , R , Barroso , I , Bencze , L , Benson , M , Bergeron , J , Bernal-Delgado , E , Blomberg , N , Bock , C , Conesa , A , Del Signore , S , Delogne , C , Devilee , P , Di Meglio , A , Eijkemans , M , Flicek , P , Graf , N , Grimm , V , Guchelaar , H J , Guo , Y K , Gut , I G , Hanbury , A , Hanif , S , Hilgers , R D , Honrado , Á , Hose , D R , Houwing-Duistermaat , J , Hubbard , T , Janacek , S H , Karanikas , H , Kievits , T , Kohler , M , Kremer , A , Lanfear , J , Lengauer , T , Maes , E , Meert , T , Müller , W , Nickel , D , Oledzki , P , Pedersen , B , Petkovic , M , Pliakos , K , Rattray , M , i Màs , J R , Schneider , R , Sengstag , T , Serra-Picamal , X , Spek , W , Vaas , L A I , van Batenburg , O , Vandelaer , M , Varnai , P , Villoslada , P , Vizcaíno , J A , Wubbe , J P M & Zanetti , G 2016 , ' Making sense of big data in health research : Towards an EU action plan ' , Genome medicine , vol. 8 , no. 1 , 71 . https://doi.org/10.1186/s13073-016-0323-y
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
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Making sense of big data in health research: Towards an EU action plan
In: http://orbilu.uni.lu/handle/10993/28371
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
BASE
Making sense of big data in health research : Towards an EU action plan
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
BASE
Making sense of big data in health research:Towards an EU action plan
In: Auffray , C , Balling , R , Barroso , I , Bencze , L , Benson , M , Bergeron , J , Bernal-Delgado , E , Blomberg , N , Bock , C , Conesa , A , Del Signore , S , Delogne , C , Devilee , P , Di Meglio , A , Eijkemans , M , Flicek , P , Graf , N , Grimm , V , Guchelaar , H-J , Guo , Y-K , Gut , I G , Hanbury , A , Hanif , S , Hilgers , R-D , Honrado , Á , Hose , D R , Houwing-Duistermaat , J , Hubbard , T , Janacek , S H , Karanikas , H , Kievits , T , Kohler , M , Kremer , A , Lanfear , J , Lengauer , T , Maes , E , Meert , T , Müller , W , Nickel , D , Oledzki , P , Pedersen , B , Petkovic , M , Pliakos , K , Rattray , M , I Màs , J R , Schneider , R , Sengstag , T , Serra-Picamal , X , Spek , W , Vaas , L A I , van Batenburg , O , Vandelaer , M , Varnai , P , Villoslada , P , Vizcaíno , J A , Wubbe , J P M & Zanetti , G 2016 , ' Making sense of big data in health research : Towards an EU action plan ' Genome Medicine , vol 8 , no. 1 , pp. 71 . DOI:10.1186/s13073-016-0323-y
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
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Erratum to:Making sense of big data in health research: Towards an EU action plan [Genome Med., 8 (2016) (71)]
In: Auffray , C , Balling , R , Barroso , I , Bencze , L , Benson , M , Bergeron , J , Bernal-Delgado , E , Blomberg , N , Bock , C , Conesa , A , Del Signore , S , Delogne , C , Devilee , P , Di Meglio , A , Eijkemans , M , Flicek , P , Graf , N , Grimm , V , Guchelaar , H J , Guo , Y K , Gut , I G , Hanbury , A , Hanif , S , Hilgers , R D , Honrado , Á , Hose , D R , Houwing-Duistermaat , J , Hubbard , T , Janacek , S H , Karanikas , H , Kievits , T , Kohler , M , Kremer , A , Lanfear , J , Lengauer , T , Maes , E , Meert , T , Müller , W , Nickel , D , Oledzki , P , Pedersen , B , Petkovic , M , Pliakos , K , Rattray , M , i Màs , J R , Schneider , R , Sengstag , T , Serra-Picamal , X , Spek , W , Vaas , L A I , van Batenburg , O , Vandelaer , M , Varnai , P , Villoslada , P , Vizcaíno , J A , Wubbe , J P M & Zanetti , G 2016 , ' Erratum to : Making sense of big data in health research: Towards an EU action plan [Genome Med., 8 (2016) (71)] ' , Genome medicine , vol. 8 , no. 1 , 118 . https://doi.org/10.1186/s13073-016-0376-y
The published article [1] has two points of confusion in the section entitled "Technical challenges related to the management of electronic health records". Firstly, the International Rare Diseases Research Consortium (IRDiRC) has developed policies and guidelines on approaches to data sharing meant to enable and improve the development of diagnoses and therapies for rare diseases. However, at present, IRDiRC has not developed best practices for the management of electronic health records (EHRs). Secondly, RARE-Bestpractices is a European Commission 7th Framework Programme (FP7) funded initiative, independent of IRDiRC. RARE-Bestpractices contributes to IRDiRC goals and objectives; however the initiative itself is not sponsored nor connected to IRDiRC.
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Making sense of big data in health research: Towards an EU action plan
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health arid healthcare for all Europearis. ; Funding Agencies|European Union [115568, 603160, 282510, 664691, 115749, 305033, 305397, 288028, 242189, 211601]; European Molecular Biology Laboratory; Wellcome Trust [WT098051]; [115372]; [257082]; [291814]; [291728]; [321567]; [262055]; [115446]; [602552]; [644753]; [634143]; [261357]; [305280]; [115525]; [2011 23 02]; [270089]; [278433]; [602525]; [201418]; [242135]; [260558]; [223411]; [305626]; [115621]; [611388]; [306000]; [354457]; [305564]; [115010]; [269978]
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Making sense of big data in health research: Towards an EU action plan
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
BASE