329 results on '"Bengtsson‐Palme, Johan"'
Search Results
2. Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes
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Inda-Díaz, Juan Salvador, Lund, David, Parras-Moltó, Marcos, Johnning, Anna, Bengtsson-Palme, Johan, and Kristiansson, Erik
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- 2023
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3. Towards monitoring of antimicrobial resistance in the environment: For what reasons, how to implement it, and what are the data needs?
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Bengtsson-Palme, Johan, Abramova, Anna, Berendonk, Thomas U., Coelho, Luis Pedro, Forslund, Sofia K., Gschwind, Rémi, Heikinheimo, Annamari, Jarquín-Díaz, Víctor Hugo, Khan, Ayaz Ali, Klümper, Uli, Löber, Ulrike, Nekoro, Marmar, Osińska, Adriana D., Ugarcina Perovic, Svetlana, Pitkänen, Tarja, Rødland, Ernst Kristian, Ruppé, Etienne, Wasteson, Yngvild, Wester, Astrid Louise, and Zahra, Rabaab
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- 2023
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4. A global baseline for qPCR-determined antimicrobial resistance gene prevalence across environments
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Abramova, Anna, Berendonk, Thomas U., and Bengtsson-Palme, Johan
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- 2023
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5. Fluoroquinolone-Specific Resistance Trajectories inE. coliand their Dependence on the SOS-Response
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Teichmann, Lisa, primary, Luitwieler, Sam, additional, Bengtsson-Palme, Johan, additional, and ter Kuile, Benno, additional
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- 2024
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6. Large expert-curated database for benchmarking document similarity detection in biomedical literature search
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Brown, Peter, Tan, Aik-Choon, El-Esawi, Mohamed A, Liehr, Thomas, Blanck, Oliver, Gladue, Douglas P, Almeida, Gabriel MF, Cernava, Tomislav, Sorzano, Carlos O, Yeung, Andy WK, Engel, Michael S, Chandrasekaran, Arun Richard, Muth, Thilo, Staege, Martin S, Daulatabad, Swapna V, Widera, Darius, Zhang, Junpeng, Meule, Adrian, Honjo, Ken, Pourret, Olivier, Yin, Cong-Cong, Zhang, Zhongheng, Cascella, Marco, Flegel, Willy A, Goodyear, Carl S, van Raaij, Mark J, Bukowy-Bieryllo, Zuzanna, Campana, Luca G, Kurniawan, Nicholas A, Lalaouna, David, Hüttner, Felix J, Ammerman, Brooke A, Ehret, Felix, Cobine, Paul A, Tan, Ene-Choo, Han, Hyemin, Xia, Wenfeng, McCrum, Christopher, Dings, Ruud PM, Marinello, Francesco, Nilsson, Henrik, Nixon, Brett, Voskarides, Konstantinos, Yang, Long, Costa, Vincent D, Bengtsson-Palme, Johan, Bradshaw, William, Grimm, Dominik G, Kumar, Nitin, Martis, Elvis, Prieto, Daniel, Sabnis, Sandeep C, Amer, Said EDR, Liew, Alan WC, Perco, Paul, Rahimi, Farid, Riva, Giuseppe, Zhang, Chongxing, Devkota, Hari P, Ogami, Koichi, Basharat, Zarrin, Fierz, Walter, Siebers, Robert, Tan, Kok-Hian, Boehme, Karen A, Brenneisen, Peter, Brown, James AL, Dalrymple, Brian P, Harvey, David J, Ng, Grace, Werten, Sebastiaan, Bleackley, Mark, Dai, Zhanwu, Dhariwal, Raman, Gelfer, Yael, Hartmann, Marcus D, Miotla, Pawel, Tamaian, Radu, Govender, Pragashnie, Gurney-Champion, Oliver J, Kauppila, Joonas H, Zhang, Xiaolei, Echeverría, Natalia, Subhash, Santhilal, Sallmon, Hannes, Tofani, Marco, Bae, Taeok, Bosch, Oliver, Cuív, Páraic O, Danchin, Antoine, Diouf, Barthelemy, Eerola, Tuomas, Evangelou, Evangelos, Filipp, Fabian V, Klump, Hannes, Kurgan, Lukasz, Smith, Simon S, Terrier, Olivier, Tuttle, Neil, and Ascher, David B
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Cancer ,Generic health relevance ,RELISH Consortium ,Data Format ,Library and Information Studies - Abstract
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.
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- 2019
7. Taxonomic annotation of public fungal ITS sequences from the built environment – a report from an April 10–11, 2017 workshop (Aberdeen, UK)
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Nilsson, R Henrik, Taylor, Andy FS, Adams, Rachel I, Baschien, Christiane, Bengtsson-Palme, Johan, Cangren, Patrik, Coleine, Claudia, Daniel, Heide-Marie, Glassman, Sydney I, Hirooka, Yuuri, Irinyi, Laszlo, Iršėnaitė, Reda, Martin-Sanchez, Pedro M, Meyer, Wieland, Oh, Seung-Yoon, Sampaio, Jose Paulo, Seifert, Keith A, Sklenář, Frantisek, Stubbe, Dirk, Suh, Sung-Oui, Summerbell, Richard, Svantesson, Sten, Unterseher, Martin, Visagie, Cobus M, Weiss, Michael, Woudenberg, Joyce HC, Wurzbacher, Christian, Van den Wyngaert, Silke, Yilmaz, Neriman, Yurkov, Andrey, Kõljalg, Urmas, and Abarenkov, Kessy
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Microbiology ,Biological Sciences ,Indoor mycobiome ,built environment ,molecular identification ,fungi ,taxonomy ,systematics ,sequence annotation ,metadata ,open data ,Ecology ,Plant biology - Abstract
Recent DNA-based studies have shown that the built environment is surprisingly rich in fungi. These indoor fungi - whether transient visitors or more persistent residents - may hold clues to the rising levels of human allergies and other medical and building-related health problems observed globally. The taxonomic identity of these fungi is crucial in such pursuits. Molecular identification of the built mycobiome is no trivial undertaking, however, given the large number of unidentified, misidentified, and technically compromised fungal sequences in public sequence databases. In addition, the sequence metadata required to make informed taxonomic decisions - such as country and host/substrate of collection - are often lacking even from reference and ex-type sequences. Here we report on a taxonomic annotation workshop (April 10-11, 2017) organized at the James Hutton Institute/University of Aberdeen (UK) to facilitate reproducible studies of the built mycobiome. The 32 participants went through public fungal ITS barcode sequences related to the built mycobiome for taxonomic and nomenclatural correctness, technical quality, and metadata availability. A total of 19,508 changes - including 4,783 name changes, 14,121 metadata annotations, and the removal of 99 technically compromised sequences - were implemented in the UNITE database for molecular identification of fungi (https://unite.ut.ee/) and shared with a range of other databases and downstream resources. Among the genera that saw the largest number of changes were Penicillium, Talaromyces, Cladosporium, Acremonium, and Alternaria, all of them of significant importance in both culture-based and culture-independent surveys of the built environment.
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- 2018
8. Microbial model communities: To understand complexity, harness the power of simplicity
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Bengtsson-Palme, Johan
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- 2020
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9. Industrial wastewater treatment plant enriches antibiotic resistance genes and alters the structure of microbial communities
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Bengtsson-Palme, Johan, Milakovic, Milena, Švecová, Helena, Ganjto, Marin, Jonsson, Viktor, Grabic, Roman, and Udikovic-Kolic, Nikolina
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- 2019
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10. Development of early life gut resistome and mobilome across gestational ages and microbiota-modifying treatments
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Bargheet, Ahmed, primary, Klingenberg, Claus, additional, Esaiassen, Eirin, additional, Hjerde, Erik, additional, Cavanagh, Jorunn Pauline, additional, Bengtsson-Palme, Johan, additional, and Pettersen, Veronika Kuchařová, additional
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- 2023
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11. Assessment and Management of Risks Associated With Antibiotic Resistance in the Environment
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Bengtsson-Palme, Johan, primary
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- 2019
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12. List of Contributors
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Bengtsson-Palme, Johan, primary, Brocal, Francisco, additional, Brown, R. Stephen, additional, Courtier, Audrey, additional, De Battista, Margot, additional, González, Cristina, additional, Gotti, Alberto, additional, Götz, Konrad, additional, Hania, Patricia, additional, Hull, Matthew S., additional, Jaeger, Laura, additional, Janin, Myriam, additional, Karakitsios, Spyros P., additional, Liss, Steven N., additional, Majury, Anna, additional, McAllister, Tim A., additional, Michon, Julien, additional, Petrovic, Tamas, additional, Potkonjak, Aleksandar, additional, Rateau, Patrick, additional, Roig, Benoit, additional, Sanderson, Haley, additional, Sarigiannis, Denis A., additional, Savic, Sara, additional, A. Sebastián, Miguel, additional, Stein, Melina, additional, Strelau, Linda, additional, Sunderer, Georg, additional, Techer, Isabelle, additional, Thireau, Véronique, additional, Valette, Armance, additional, Vidaurre, Rodrigo, additional, Weiss, Karine, additional, Winker, Martina, additional, and Zekic-Stosic, Marina, additional
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- 2019
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13. Structure and function of the global topsoil microbiome
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Bahram, Mohammad, Hildebrand, Falk, Forslund, Sofia K., Anderson, Jennifer L., Soudzilovskaia, Nadejda A., Bodegom, Peter M., and Bengtsson-Palme, Johan
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Soil microbiology -- Identification and classification ,Bacteria ,pH ,Bacterial genetics ,Soil structure ,Fungi ,Precipitation (Meteorology) ,Soil acidity ,Environmental associations ,Microbial drug resistance ,Soil carbon ,Niches (Ecology) ,Oceans ,Marine biology ,Genes ,Microorganisms ,Soils ,Environmental issues ,Science and technology ,Zoology and wildlife conservation - Abstract
Soils harbour some of the most diverse microbiomes on Earth and are essential for both nutrient cycling and carbon storage. To understand soil functioning, it is necessary to model the global distribution patterns and functional gene repertoires of soil microorganisms, as well as the biotic and environmental associations between the diversity and structure of both bacterial and fungal soil communities.sup.1-4. Here we show, by leveraging metagenomics and metabarcoding of global topsoil samples (189 sites, 7,560 subsamples), that bacterial, but not fungal, genetic diversity is highest in temperate habitats and that microbial gene composition varies more strongly with environmental variables than with geographic distance. We demonstrate that fungi and bacteria show global niche differentiation that is associated with contrasting diversity responses to precipitation and soil pH. Furthermore, we provide evidence for strong bacterial-fungal antagonism, inferred from antibiotic-resistance genes, in topsoil and ocean habitats, indicating the substantial role of biotic interactions in shaping microbial communities. Our results suggest that both competition and environmental filtering affect the abundance, composition and encoded gene functions of bacterial and fungal communities, indicating that the relative contributions of these microorganisms to global nutrient cycling varies spatially.Metagenomic, chemical and biomass analyses of topsoil samples from around the world reveal spatial and environmental trends in microbial community composition and genetic diversity., Author(s): Mohammad Bahram [sup.1] [sup.2] [sup.3] , Falk Hildebrand [sup.4] , Sofia K. Forslund [sup.4] [sup.16] [sup.17] , Jennifer L. Anderson [sup.2] , Nadejda A. Soudzilovskaia [sup.5] , Peter M. [...]
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- 2018
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14. Metaxa, Overview
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Bengtsson-Palme, Johan, Hartmann, Martin, Eriksson, K. Martin, Nilsson, R. Henrik, and Nelson, Karen E., editor
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- 2015
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15. A Risk Management Framework for Emergence of Novel Antibiotic Resistance Determinants
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Heß, Stefanie, primary and Bengtsson-Palme, Johan, additional
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- 2023
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16. Strategies for Taxonomic and Functional Annotation of Metagenomes
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Bengtsson-Palme, Johan, primary
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- 2018
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17. Contributors
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Asha, Santhi, primary, Bacci, Giovanni, additional, Bargiela, Rafael, additional, Becerra, Manuel, additional, Bengtsson-Palme, Johan, additional, Beraud, Mélanie, additional, Boulund, Fredrik, additional, Chan, Chia Sing, additional, Chan, Kok-Gan, additional, Citlali, Fonseca-García, additional, Dave, Bharti P., additional, DeCastro, María-Eugenia, additional, Desgarennes, Damaris, additional, Dieleman, Levinus A., additional, Escuder-Rodríguez, Juan-José, additional, Ferrer, Manuel, additional, Flores-Núñez, Víctor M., additional, Foster, James A., additional, Goh, Kian Mau, additional, González-Siso, María-Isabel, additional, Gosai, Haren B., additional, Griffin, Timothy J., additional, Halgamuge, Saman K., additional, Jagtap, Pratik D., additional, Jayasundara, Duleepa, additional, Jonsson, Viktor, additional, Joshi, Chaitanya G., additional, Jovel, Juan, additional, Kadnikov, Vitaly V., additional, Kamalakkannan, Ranganathan, additional, Kao, Dina, additional, Kimura, Nobutada, additional, Kothari, Ramesh K., additional, Krishnaveni, Muthan, additional, Kristiansson, Erik, additional, Liew, Kok Jun, additional, Lim, Chia Chiu, additional, Ma, Zhanshan (Sam), additional, Mardanov, Andrey V., additional, Martínez-Martínez, Mónica, additional, Mary Josephine Punitha, Stanislaus, additional, Mason, Andrew L., additional, Matallana-Surget, Sabine, additional, Méndez-García, Celia, additional, Mootapally, Chandrashekar, additional, Nagarajan, Muniyandi, additional, Nathani, Neelam M., additional, Partida-Martínez, Laila P., additional, Pereira, Mariana Buongermino, additional, Prabhu, Vandana R., additional, Ramazzotti, Matteo, additional, Rank, Jalpa K., additional, Ravin, Nikolai V., additional, Rodríguez-Belmonte, Esther, additional, Salleh, Madihah Md, additional, Sani, Rajesh Kumar, additional, Sharmin Vini, Stephen, additional, Tang, Sen-Lin, additional, Wattiez, Ruddy, additional, Wei, Kwek Yan, additional, Wine, Eytan, additional, and Zhbannikov, Ilya Y., additional
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- 2018
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18. The global groundwater resistome: core ARGs and their dynamics - anin silicore-analysis of publicly available groundwater metagenomes
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Kampouris, Ioannis D., primary, Berendonk, Thomas U., additional, Bengtsson-Palme, Johan, additional, and Klümper, Uli, additional
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- 2022
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19. Microbial and human transcriptome in vaginal fluid at midgestation: Association with spontaneous preterm delivery
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Wikström, Tove, primary, Abrahamsson, Sanna, additional, Bengtsson‐Palme, Johan, additional, Ek, Joakim, additional, Kuusela, Pihla, additional, Rekabdar, Elham, additional, Lindgren, Peter, additional, Wennerholm, Ulla‐Britt, additional, Jacobsson, Bo, additional, Valentin, Lil, additional, and Hagberg, Henrik, additional
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- 2022
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20. Using metagenomics to investigate human and environmental resistomes
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Bengtsson-Palme, Johan, Larsson, D. G. Joakim, and Kristiansson, Erik
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- 2017
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21. Maternal gut and breast milk microbiota affect infant gut antibiotic resistome and mobile genetic elements
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Pärnänen, Katariina, Karkman, Antti, Hultman, Jenni, Lyra, Christina, Bengtsson-Palme, Johan, Larsson, D. G. Joakim, Rautava, Samuli, Isolauri, Erika, Salminen, Seppo, Kumar, Himanshu, Satokari, Reetta, and Virta, Marko
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- 2018
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22. The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always
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Bengtsson-Palme, Johan
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- 2018
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23. The European technical report on aquatic effect-based monitoring tools under the water framework directive
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Wernersson, Ann-Sofie, Carere, Mario, Maggi, Chiara, Tusil, Petr, Soldan, Premysl, James, Alice, Sanchez, Wilfried, Dulio, Valeria, Broeg, Katja, Reifferscheid, Georg, Buchinger, Sebastian, Maas, Hannie, Van Der Grinten, Esther, O’Toole, Simon, Ausili, Antonella, Manfra, Loredana, Marziali, Laura, Polesello, Stefano, Lacchetti, Ines, Mancini, Laura, Lilja, Karl, Linderoth, Maria, Lundeberg, Tove, Fjällborg, Bengt, Porsbring, Tobias, Larsson, DG Joakim, Bengtsson-Palme, Johan, Förlin, Lars, Kienle, Cornelia, Kunz, Petra, Vermeirssen, Etienne, Werner, Inge, Robinson, Craig D, Lyons, Brett, Katsiadaki, Ioanna, Whalley, Caroline, den Haan, Klaas, Messiaen, Marlies, Clayton, Helen, Lettieri, Teresa, Carvalho, Raquel Negrão, Gawlik, Bernd Manfred, Hollert, Henner, Di Paolo, Carolina, Brack, Werner, Kammann, Ulrike, and Kase, Robert
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- 2015
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24. A global baseline for qPCR-determined antimicrobial resistance gene prevalence across environments
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Abramova, Anna, primary, Berendonk, Thomas U., additional, and Bengtsson-Palme, Johan, additional
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- 2022
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25. Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 9: Polymyxins: colistin
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I., Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Indústries Alimentàries, Funcionalitat i Seguretat Alimentària, Koutsoumanis K., Allende A., Alvarez-Ordoñez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., and Peixe L.
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663/664 ,medicine.drug_class ,Veterinary (miscellaneous) ,Polymyxin ,Growth promotion ,TP1-1185 ,Plant Science ,Biology ,Microbiology ,Non target ,Antibiotic resistance ,growth promotion ,medicine ,TX341-641 ,antimicrobial resistance ,colistin ,yield increase ,Animal health ,Nutrition. Foods and food supply ,business.industry ,Chemical technology ,sub-inhibitory concentration ,sub‐inhibitory concentration ,Contamination ,Feed Antimicrobial Resistance Selection Concentration (FARSC) ,Antimicrobial ,food-producing animal ,Biotechnology ,Colistin ,Animal Science and Zoology ,Parasitology ,business ,Food Science ,medicine.drug - Abstract
The specific concentrations of colistin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of colistin in feed that showed to have an effect on growth promotion/increased yield were reported. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials. info:eu-repo/semantics/publishedVersion
- Published
- 2021
26. Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 13: Diaminopyrimidines: trimethoprim
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I., Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Indústries Alimentàries, Funcionalitat i Seguretat Alimentària, Koutsoumanis K., Allende A., Alvarez-Ordoñez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., and Peixe L.
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Complete data ,663/664 ,Veterinary (miscellaneous) ,Growth promotion ,TP1-1185 ,Plant Science ,Biology ,Microbiology ,Trimethoprim ,Non target ,Antibiotic resistance ,growth promotion ,medicine ,TX341-641 ,antimicrobial resistance ,yield increase ,Animal health ,Nutrition. Foods and food supply ,business.industry ,Chemical technology ,sub-inhibitory concentration ,food-producing animals ,Biol5012 ,food‐producing animals ,sub‐inhibitory concentration ,Contamination ,Feed Antimicrobial Resistance Selection Concentration (FARSC) ,Antimicrobial ,food-producing animal ,Biotechnology ,Scientific Opinion ,Animal Science and Zoology ,Parasitology ,business ,Food Science ,medicine.drug - Abstract
The specific concentrations of trimethoprim in non-target feed for food-producing animals below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for trimethoprim was estimated. Uncertainties and data gaps associated to the levels reported were addressed. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. No suitable data for the assessment were available. It was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC for trimethoprim. info:eu-repo/semantics/publishedVersion
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- 2021
27. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 12: Tetracyclines: tetracycline, chlortetracycline, oxytetracycline, and doxycycline
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Indústries Alimentàries, Funcionalitat i Seguretat Alimentària, Koutsoumanis K., Allende A., Alvarez-Ordonez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., and Peixe L.
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Chlortetracycline ,663/664 ,Tetracycline ,Veterinary (miscellaneous) ,Growth promotion ,TP1-1185 ,Plant Science ,Oxytetracycline ,Biology ,Microbiology ,Antibiotic resistance ,growth promotion ,medicine ,TX341-641 ,antimicrobial resistance ,Food science ,chlortetracycline ,tetracycline ,Doxycycline ,doxycycline ,Nutrition. Foods and food supply ,Chemical technology ,food-producing animals ,Contamination ,Antimicrobial ,food-producing animal ,Animal Science and Zoology ,Parasitology ,oxytetracycline ,Food Science ,medicine.drug - Abstract
The specific concentrations of tetracycline, chlortetracycline, oxytetracycline and doxycycline in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for these four tetracyclines was estimated. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for tetracycline, chlortetracycline, oxytetracycline, whilst for doxycycline no suitable data for the assessment were available. Uncertainties and data gaps associated with the levels reported were addressed. It was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC for these antimicrobials. info:eu-repo/semantics/publishedVersion
- Published
- 2021
28. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 10: Quinolones: flumequine and oxolinic acid
- Author
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Koutsoumanis K., Allende A., Alvarez-Ordoñez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., Peixe L., Indústries Alimentàries, and Funcionalitat i Seguretat Alimentària
- Subjects
663/664 ,Veterinary (miscellaneous) ,Growth promotion ,flumequine ,TP1-1185 ,Plant Science ,Microbiology ,Non target ,Antibiotic resistance ,growth promotion ,oxolinic acid ,Oxolinic acid ,medicine ,TX341-641 ,Food science ,antimicrobial resistance ,Food8822 ,yield increase ,Animal health ,Nutrition. Foods and food supply ,Chemical technology ,sub-inhibitory concentration ,food-producing animals ,food‐producing animals ,Contamination ,sub‐inhibitory concentration ,Antimicrobial ,food-producing animal ,Scientific Opinion ,Flumequine ,Environmental science ,Animal Science and Zoology ,Parasitology ,Food Science ,medicine.drug - Abstract
The specific concentrations of flumequine and oxolinic acid in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data are available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. No suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials. info:eu-repo/semantics/publishedVersion
- Published
- 2021
29. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 4: β‐Lactams: amoxicillin and penicillin V
- Author
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Indústries Alimentàries, Funcionalitat i Seguretat Alimentària, Koutso111umanis K., Allende A., Alvarez-Ordonez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., and Peixe L.
- Subjects
663/664 ,Veterinary (miscellaneous) ,Growth promotion ,TP1-1185 ,Plant Science ,Biology ,Microbiology ,Antibiotic resistance ,Non target ,growth promotion ,β lactams ,medicine ,TX341-641 ,antimicrobial resistance ,Food science ,yield increase ,amoxicillin ,Nutrition. Foods and food supply ,sub-inhibitory concentration ,Chemical technology ,food-producing animals ,Biol5012 ,food‐producing animals ,sub‐inhibitory concentration ,Contamination ,Amoxicillin ,penicillin V ,Antimicrobial ,food-producing animal ,Penicillin ,Scientific Opinion ,Animal Science and Zoology ,Parasitology ,Food Science ,medicine.drug - Abstract
The specific concentrations of amoxicillin and penicillin V in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for amoxicillin, whilst for penicillin V no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these two antimicrobials. info:eu-repo/semantics/publishedVersion
- Published
- 2021
30. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 6: Macrolides: tilmicosin, tylosin and tylvalosin
- Author
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Koutsoumanis K., Allende A., Alvarez-Ordoñez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., Peixe L., Indústries Alimentàries, and Funcionalitat i Seguretat Alimentària
- Subjects
663/664 ,Veterinary (miscellaneous) ,Growth promotion ,TP1-1185 ,Plant Science ,Tylosin ,Biology ,tilmicosin ,Microbiology ,chemistry.chemical_compound ,Antibiotic resistance ,Non target ,growth promotion ,TX341-641 ,antimicrobial resistance ,Food science ,Tilmicosin ,yield increase ,tylosin ,Nutrition. Foods and food supply ,Chemical technology ,food-producing animals ,tylvalosin ,Contamination ,Antimicrobial ,food-producing animal ,chemistry ,Animal Science and Zoology ,Parasitology ,Tylvalosin ,Food Science - Abstract
The specific concentrations of tilmicosin, tylosin and tylvalosin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield, were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for tilmicosin and tylosin, whilst for tylvalosin no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these three antimicrobials. info:eu-repo/semantics/publishedVersion
- Published
- 2021
31. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 11: Sulfonamides
- Author
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I., Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Koutsoumanis K., Allende A., Alvarez-Ordoñez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., Peixe L., Indústries Alimentàries, and Funcionalitat i Seguretat Alimentària
- Subjects
Sulfamerazine ,663/664 ,Veterinary (miscellaneous) ,Growth promotion ,TP1-1185 ,Plant Science ,Sulfonamide ,Microbiology ,Antibiotic resistance ,Non target ,growth promotion ,medicine ,TX341-641 ,antimicrobial resistance ,Food science ,yield increase ,Sulfonamides ,Animal health ,Nutrition. Foods and food supply ,Chemical technology ,sub-inhibitory concentration ,food‐producing animals ,food-producing animals ,sub‐inhibitory concentration ,Contamination ,Antimicrobial ,food-producing animal ,Sulfathiazole ,Environmental science ,Animal Science and Zoology ,Parasitology ,Food Science ,medicine.drug - Abstract
The specific concentrations of sulfonamides in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data are available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were identified for three sulfonamides: sulfamethazine, sulfathiazole and sulfamerazine. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials. info:eu-repo/semantics/publishedVersion
- Published
- 2021
32. What Is the Role of the Environment in the Emergence of Novel Antibiotic Resistance Genes? A Modeling Approach
- Author
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Bengtsson-Palme, Johan, primary, Jonsson, Viktor, additional, and Heß, Stefanie, additional
- Published
- 2021
- Full Text
- View/download PDF
33. Improving ITS sequence data for identification of plant pathogenic fungi
- Author
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Nilsson, R. Henrik, Hyde, Kevin D., Pawłowska, Julia, Ryberg, Martin, Tedersoo, Leho, Aas, Anders Bjørnsgard, Alias, Siti A., Alves, Artur, Anderson, Cajsa Lisa, Antonelli, Alexandre, Arnold, A. Elizabeth, Bahnmann, Barbara, Bahram, Mohammad, Bengtsson-Palme, Johan, Berlin, Anna, Branco, Sara, Chomnunti, Putarak, Dissanayake, Asha, Drenkhan, Rein, Friberg, Hanna, Frøslev, Tobias Guldberg, Halwachs, Bettina, Hartmann, Martin, Henricot, Beatrice, Jayawardena, Ruvishika, Jumpponen, Ari, Kauserud, Håvard, Koskela, Sonja, Kulik, Tomasz, Liimatainen, Kare, Lindahl, Björn D., Lindner, Daniel, Liu, Jian-Kui, Maharachchikumbura, Sajeewa, Manamgoda, Dimuthu, Martinsson, Svante, Neves, Maria Alice, Niskanen, Tuula, Nylinder, Stephan, Pereira, Olinto Liparini, Pinho, Danilo Batista, Porter, Teresita M., Queloz, Valentin, Riit, Taavi, Sánchez-García, Marisol, de Sousa, Filipe, Stefańczyk, Emil, Tadych, Mariusz, Takamatsu, Susumu, Tian, Qing, Udayanga, Dhanushka, Unterseher, Martin, Wang, Zheng, Wikee, Saowanee, Yan, Jiye, Larsson, Ellen, Larsson, Karl-Henrik, Kõljalg, Urmas, and Abarenkov, Kessy
- Published
- 2014
- Full Text
- View/download PDF
34. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications
- Author
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Nilsson, Rolf Henrik, Larsson, Karl-Henrik, Taylor, Andy F S, Bengtsson-Palme, Johan, Jeppesen, Thomas S, Schigel, Dmitry, Kennedy, Peter, Picard, Kathryn, Glöckner, Frank Oliver, Tedersoo, Leho, Saar, Irja, Kõljalg, Urmas, and Abarenkov, Kessy
- Subjects
Fungi ,Database Issue ,Computational Biology ,DNA Barcoding, Taxonomic ,Genomics ,Genome, Fungal ,Web Browser ,Databases, Nucleic Acid ,Software - Abstract
UNITE (https://unite.ut.ee/) is a web-based database and sequence management environment for the molecular identification of fungi. It targets the formal fungal barcodethe nuclear ribosomal internal transcribed spacer(ITS) regionand offers all approximate to 1 000000 public fungal ITS sequences for reference. These are clustered into approximate to 459000 species hypotheses and assigned digital object identifiers (DOIs) to promote unambiguous reference across studies. In-house and web-based third-party sequence curation and annotation have resulted in more than 275000 improvements to the data over the past 15 years. UNITE serves as a data provider for a range of metabarcoding software pipelines and regularly exchanges data with all major fungal sequence databases and other community resources. Recent improvements include redesigned handling of unclassifiable species hypotheses, integration with the taxonomic backbone of the Global Biodiversity Information Facility, and support for an unlimited number of parallel taxonomic classification systems.
- Published
- 2018
35. Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 5: Lincosamides: lincomycin
- Author
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Indústries Alimentàries, Funcionalitat i Seguretat Alimentària, Koutsoumanis K., Allende A., Alvarez-Ordonez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., and Peixe L.
- Subjects
663/664 ,medicine.drug_class ,Veterinary (miscellaneous) ,Growth promotion ,Plant Science ,TP1-1185 ,Biology ,Microbiology ,Antibiotic resistance ,Non target ,growth promotion ,medicine ,TX341-641 ,Food science ,antimicrobial resistance ,yield increase ,Lincosamides ,Animal health ,Nutrition. Foods and food supply ,sub-inhibitory concentration ,Chemical technology ,Biol5012 ,food‐producing animals ,food-producing animals ,Contamination ,sub‐inhibitory concentration ,Antimicrobial ,Feed Antimicrobial Resistance Selection Concentration (FARSC) ,food-producing animal ,Lincomycin ,Scientific Opinion ,Animal Science and Zoology ,Parasitology ,lincomycin ,Food Science ,medicine.drug - Abstract
The specific concentrations of lincomycin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of lincomycin in feed that showed to have an effect on growth promotion/increased yield were reported. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for lincomycin. info:eu-repo/semantics/publishedVersion
- Published
- 2021
36. Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 2: Aminoglycosides/aminocyclitols: apramycin, paromomycin, neomycin and spectinomycin
- Author
-
EFSA Panel on Biological Hazards (BIOHAZ), Allende, Ana, Koutsoumanis, Konstantinos, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Allende A., Koutsoumanis K., Alvarez-Ordoñez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., Peixe L., Indústries Alimentàries, and Funcionalitat i Seguretat Alimentària
- Subjects
Spectinomycin ,663/664 ,spectinomycin ,Veterinary (miscellaneous) ,Growth promotion ,Paromomycin ,TP1-1185 ,Plant Science ,Biology ,Apramycin ,Microbiology ,Antibiotic resistance ,growth promotion ,medicine ,TX341-641 ,Food science ,antimicrobial resistance ,Nutrition. Foods and food supply ,Chemical technology ,neomycin ,food-producing animals ,Neomycin ,Contamination ,Antimicrobial ,food-producing animal ,Animal Science and Zoology ,Parasitology ,paromomycin ,Food Science ,medicine.drug ,apramycin - Abstract
The specific concentrations of apramycin, paromomycin, neomycin and spectinomycin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield, were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC for these antimicrobials, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for apramycin and neomycin, whilst for paromomycin and spectinomycin, no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these four antimicrobials. info:eu-repo/semantics/publishedVersion
- Published
- 2021
37. Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 3: Amprolium
- Author
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EFSA Panel on Biological Hazards (BIOHAZ), Koutsoumanis, Konstantinos, Allende, Ana, Alvarez-Ordóñez, Avelino, Bolton, Declan, Bover-Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson-Palme, Johan, Bouchard, Damien, Ferran, Aude, Kouba, Maryline, López Puente, Secundino, López-Alonso, Marta, Nielsen, Søren Saxmose, Pechová, Alena, Petkova, Mariana, Girault, Sebastien, Broglia, Alessandro, Guerra, Beatriz, Innocenti, Matteo Lorenzo, Liébana, Ernesto, López-Gálvez, Gloria, Manini, Paola, Stella, Pietro, Peixe, Luisa, Koutsoumanis K., Allende A., Alvarez-Ordoñez A., Bolton D., Bover-Cid S., Chemaly M., Davies R., De Cesare A., Herman L., Hilbert F., Lindqvist R., Nauta M., Ru G., Simmons M., Skandamis P., Suffredini E., Andersson D.I., Bampidis V., Bengtsson-Palme J., Bouchard D., Ferran A., Kouba M., Lopez Puente S., Lopez-Alonso M., Nielsen S.S., Pechova A., Petkova M., Girault S., Broglia A., Guerra B., Innocenti M.L., Liebana E., Lopez-Galvez G., Manini P., Stella P., Peixe L., Indústries Alimentàries, and Funcionalitat i Seguretat Alimentària
- Subjects
663/664 ,Veterinary (miscellaneous) ,Growth promotion ,TP1-1185 ,Plant Science ,Biology ,Microbiology ,chemistry.chemical_compound ,Antibiotic resistance ,Non target ,Amprolium ,growth promotion ,TX341-641 ,Food science ,antimicrobial resistance ,yield increase ,Animal health ,Nutrition. Foods and food supply ,Chemical technology ,Biol5012 ,food‐producing animals ,food-producing animals ,Feed Antimicrobial Resistance Selection Concentration (FARSC), growth promotion ,Contamination ,Antimicrobial ,Feed Antimicrobial Resistance Selection Concentration (FARSC) ,food-producing animal ,Scientific Opinion ,subinhibitory concentration ,chemistry ,Animal Science and Zoology ,Parasitology ,Food Science ,amprolium - Abstract
The specific concentrations of amprolium in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC for amprolium, it was not possible to conclude the assessment. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of amprolium in feed that showed to have an effect on growth promotion/increased yield were reported. The lack of antibacterial activity at clinically relevant concentrations for amprolium suggests that further studies relating to bacterial resistance are not a priority. info:eu-repo/semantics/publishedVersion
- Published
- 2021
38. Metaxa, Overview
- Author
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Bengtsson-Palme, Johan, primary, Hartmann, Martin, additional, Eriksson, K. Martin, additional, and Nilsson, R Henrik, additional
- Published
- 2014
- Full Text
- View/download PDF
39. Microbial Community Interactions Are Sensitive to Small Changes in Temperature
- Author
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Burman, Emil, primary and Bengtsson-Palme, Johan, additional
- Published
- 2021
- Full Text
- View/download PDF
40. BacMet: antibacterial biocide and metal resistance genes database
- Author
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Pal, Chandan, Bengtsson-Palme, Johan, Rensing, Christopher, Kristiansson, Erik, and Larsson, Joakim D. G.
- Published
- 2014
- Full Text
- View/download PDF
41. The Organelle in the Ointment: cryptic mitochondria account for many unknown sequences in cross-species microbiome comparisons
- Author
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Sonett, Dylan, primary, Brown, Tanya, additional, Bengtsson-Palme, Johan, additional, Padilla-Gamiño, Jacqueline L., additional, and Zaneveld, Jesse R., additional
- Published
- 2021
- Full Text
- View/download PDF
42. Microbial retention and resistances in stormwater quality improvement devices treating road runoff
- Author
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Liguori, Renato, primary, Rommel, Steffen H., additional, Bengtsson-Palme, Johan, additional, Helmreich, Brigitte, additional, and Wurzbacher, Christian, additional
- Published
- 2021
- Full Text
- View/download PDF
43. CAFE: a software suite for analysis of paired-sample transposon insertion sequencing data
- Author
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Abramova, Anna, primary, Osińska, Adriana, additional, Kunche, Haveela, additional, Burman, Emil, additional, and Bengtsson-Palme, Johan, additional
- Published
- 2021
- Full Text
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44. Critical knowledge gaps and research needs related to the environmental dimensions of antibiotic resistance
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Larsson, D.G. Joakim, Andremont, Antoine, Bengtsson-Palme, Johan, Brandt, Kristian Koefoed, de Roda Husman, Ana Maria, Fagerstedt, Patriq, Fick, Jerker, Flach, Carl-Fredrik, Gaze, William H., Kuroda, Makoto, Kvint, Kristian, Laxminarayan, Ramanan, Manaia, Celia M., Nielsen, Kaare Magne, Plant, Laura, Ploy, Marie-Cécile, Segovia, Carlos, Simonet, Pascal, Smalla, Kornelia, Snape, Jason, Topp, Edward, van Hengel, Arjon J., Verner-Jeffreys, David W., Virta, Marko P.J., Wellington, Elizabeth M., Wernersson, Ann-Sofie, Sub RIVM, dIRAS RA-I&I RA, Horizon 2020, Sub RIVM, dIRAS RA-I&I RA, Department of Microbiology, Helsinki Institute of Sustainability Science (HELSUS), Antibiotic resistance in human impacted environments, Doctoral Programme in Microbiology and Biotechnology, University of Gothenburg (GU), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Copenhagen = Københavns Universitet (KU), Department of Chemistry, Umeå University, University of Exeter, Center for Disease Dynamics, Economics & Policy (CDDEP), Anti-infectieux : supports moléculaires des résistances et innovations thérapeutiques (RESINFIT), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-CHU Limoges, Instituto de Salud Carlos III [Madrid] (ISC), Ampère, Département Bioingénierie (BioIng), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institute for Plant Virology, Microbiology and Biosafety, Federal Biological Research Centre for Agriculture and Forestry, Berlin and Braunschweig (BBA), Agriculture and Agri-Food [Ottawa] (AAFC), JRC Institute for Reference Materials and Measurements [Geel] (IRMM), European Commission - Joint Research Centre [Geel] (JRC), Unión Europea. Comisión Europea. H2020, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC), CHU Limoges-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), and Veritati - Repositório Institucional da Universidade Católica Portuguesa
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0301 basic medicine ,Value (ethics) ,Antimicrobial resistance markers ,Psychological intervention ,Infektionsmedicin ,POLICY INTERVENTIONS ,Environmental pollution ,010501 environmental sciences ,Antimicrobial resistance ,01 natural sciences ,HORIZONTAL GENE-TRANSFER ,Environmental Microbiology ,lcsh:Environmental sciences ,Risk management ,Risk assessment ,General Environmental Science ,lcsh:GE1-350 ,2. Zero hunger ,PROTECTION GOALS ,Bacterial Infections ,Anti-Bacterial Agents ,3. Good health ,Risk assessments ,ESCHERICHIA-COLI ,BACTERIA ,Infectious diseases ,RISK-ASSESSMENT ,Infectious Medicine ,030106 microbiology ,Resistance (psychoanalysis) ,03 medical and health sciences ,Antibiotic resistance ,WASTE-WATER ,Drug Resistance, Bacterial ,Animals ,Humans ,Environmental planning ,1172 Environmental sciences ,0105 earth and related environmental sciences ,PATHOGENS ,Bacteria ,business.industry ,[SPI.NRJ]Engineering Sciences [physics]/Electric power ,Research needs ,EVOLUTION ,13. Climate action ,business - Abstract
There is growing understanding that the environment plays an important role both in the transmission of antibiotic resistant pathogens and in their evolution. Accordingly, researchers and stakeholders world-wide seek to further explore the mechanisms and drivers involved, quantify risks and identify suitable interventions. There is a clear value in establishing research needs and coordinating efforts within and across nations in order to best tackle this global challenge. At an international workshop in late September 2017, scientists from 14 countries with expertise on the environmental dimensions of antibiotic resistance gathered to define critical knowledge gaps. Four key areas were identified where research is urgently needed: 1) the relative contributions of different sources of antibiotics and antibiotic resistant bacteria into the environment; 2) the role of the environment, and particularly anthropogenic inputs, in the evolution of resistance; 3) the overall human and animal health impacts caused by exposure to environmental resistant bacteria; and 4) the efficacy and feasibility of different technological, social, economic and behavioral interventions to mitigate environmental antibiotic resistance.1. The workshop was organized and supported by the Joint Programming Initiative on Antimicrobial Resistance (JPIAMR), the Swedish Research Council (SRC) and the Centre for Antibiotic Resistance Research at University of Gothenburg, Sweden (CARe). This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement JPI-EC-AMR No 681055. Individual member states of the JPIAMR also covered travel costs for participants. Sí
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- 2018
45. Substrate-bound outward-open structure of a Na+-coupled sialic acid symporter reveals a new Na+ site
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Wahlgren, Weixiao Y., Dunevall, Elin, North, Rachel A., Paz, Aviv, Scalise, Mariafrancesca, Bisignano, Paola, Bengtsson-Palme, Johan, Goyal, Parveen, Claesson, Elin, Caing-Carlsson, Rhawnie, Andersson, Rebecka, Beis, Konstantinos, Nilsson, Ulf J., Farewell, Anne, Pochini, Lorena, Indiveri, Cesare, Grabe, Michael, Dobson, Renwick C. J., Abramson, Jeff, Ramaswamy, S., Friemann, Rosmarie, Biotechnology and Biological Sciences Research Council (BBSRC), and Medical Research Council (MRC)
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Protein Folding ,Science ,Organic Anion Transporters ,DOPAMINE TRANSPORTER ,VIRULENCE FACTOR ,HAEMOPHILUS-INFLUENZAE ,Article ,Substrate Specificity ,MD Multidisciplinary ,CRYSTAL-STRUCTURE ,Amino Acid Sequence ,lcsh:Science ,Science & Technology ,Sequence Homology, Amino Acid ,Symporters ,Sodium ,BETAINE TRANSPORTER BETP ,MACROMOLECULAR CRYSTALLOGRAPHY ,N-Acetylneuraminic Acid ,Multidisciplinary Sciences ,carbohydrates (lipids) ,X-RAY STRUCTURES ,ESCHERICHIA-COLI ,MOLECULAR-DYNAMICS ,SEROTONIN TRANSPORTER ,Science & Technology - Other Topics ,lcsh:Q - Abstract
Many pathogenic bacteria utilise sialic acids as an energy source or use them as an external coating to evade immune detection. As such, bacteria that colonise sialylated environments deploy specific transporters to mediate import of scavenged sialic acids. Here, we report a substrate-bound 1.95 Å resolution structure and subsequent characterisation of SiaT, a sialic acid transporter from Proteus mirabilis. SiaT is a secondary active transporter of the sodium solute symporter (SSS) family, which use Na+ gradients to drive the uptake of extracellular substrates. SiaT adopts the LeuT-fold and is in an outward-open conformation in complex with the sialic acid N-acetylneuraminic acid and two Na+ ions. One Na+ binds to the conserved Na2 site, while the second Na+ binds to a new position, termed Na3, which is conserved in many SSS family members. Functional and molecular dynamics studies validate the substrate-binding site and demonstrate that both Na+ sites regulate N-acetylneuraminic acid transport., Sialic acid transporters (SiaT) are required for sialic acid uptake in a number of human pathogens and are of interest as targets for antimicrobial drug development. Here the authors present the substrate bound SiaT structure from the uropathogen Proteus mirabilis and provide insights into the mechanism of sialic acid transport.
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- 2018
46. Chapter 10 - Assessment and Management of Risks Associated With Antibiotic Resistance in the Environment
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Bengtsson-Palme, Johan
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- 2019
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47. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 3: Amprolium.
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Koutsoumanis, Konstantinos, Allende, Ana, Alvarez‐Ordóñez, Avelino, Bolton, Declan, Bover‐Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson‐Palme, Johan, and Bouchard, Damien
- Abstract
The specific concentrations of amprolium in non‐target feed for food‐producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC for amprolium, it was not possible to conclude the assessment. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of amprolium in feed that showed to have an effect on growth promotion/increased yield were reported. The lack of antibacterial activity at clinically relevant concentrations for amprolium suggests that further studies relating to bacterial resistance are not a priority. [ABSTRACT FROM AUTHOR]
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- 2021
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48. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 2: Aminoglycosides/aminocyclitols: apramycin, paromomycin, neomycin and spectinomycin.
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Allende, Ana, Koutsoumanis, Konstantinos, Alvarez‐Ordóñez, Avelino, Bolton, Declan, Bover‐Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson‐Palme, Johan, and Bouchard, Damien
- Abstract
The specific concentrations of apramycin, paromomycin, neomycin and spectinomycin in non‐target feed for food‐producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield, were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC for these antimicrobials, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for apramycin and neomycin, whilst for paromomycin and spectinomycin, no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these four antimicrobials. [ABSTRACT FROM AUTHOR]
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- 2021
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49. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 13: Diaminopyrimidines: trimethoprim.
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Koutsoumanis, Konstantinos, Allende, Ana, Alvarez‐Ordóñez, Avelino, Bolton, Declan, Bover‐Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson‐Palme, Johan, and Bouchard, Damien
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The specific concentrations of trimethoprim in non‐target feed for food‐producing animals below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for trimethoprim was estimated. Uncertainties and data gaps associated to the levels reported were addressed. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. No suitable data for the assessment were available. It was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC for trimethoprim. [ABSTRACT FROM AUTHOR]
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- 2021
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50. Maximum levels of cross‐contamination for 24 antimicrobial active substances in non‐target feed. Part 12: Tetracyclines: tetracycline, chlortetracycline, oxytetracycline, and doxycycline.
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Koutsoumanis, Konstantinos, Allende, Ana, Alvarez‐Ordóñez, Avelino, Bolton, Declan, Bover‐Cid, Sara, Chemaly, Marianne, Davies, Robert, De Cesare, Alessandra, Herman, Lieve, Hilbert, Friederike, Lindqvist, Roland, Nauta, Maarten, Ru, Giuseppe, Simmons, Marion, Skandamis, Panagiotis, Suffredini, Elisabetta, Andersson, Dan I, Bampidis, Vasileios, Bengtsson‐Palme, Johan, and Bouchard, Damien
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The specific concentrations of tetracycline, chlortetracycline, oxytetracycline and doxycycline in non‐target feed for food‐producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for these four tetracyclines was estimated. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for tetracycline, chlortetracycline, oxytetracycline, whilst for doxycycline no suitable data for the assessment were available. Uncertainties and data gaps associated with the levels reported were addressed. It was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC for these antimicrobials. [ABSTRACT FROM AUTHOR]
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- 2021
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