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4. The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Author

Mohammed Taha, Hiba, Aalizadeh, Reza, Alygizakis, Nikiforos, Antignac, Jean-Philippe, Arp, Hans Peter H., Bade, Richard, Baker, Nancy, Belova, Lidia, Bijlsma, Lubertus, Bolton, Evan E., Brack, Werner, Celma, Alberto, Chen, Wen-Ling, Cheng, Tiejun, Chirsir, Parviel, Čirka, Ľuboš, D’Agostino, Lisa A., Djoumbou Feunang, Yannick, Dulio, Valeria, Fischer, Stellan, Gago-Ferrero, Pablo, Galani, Aikaterini, Geueke, Birgit, Głowacka, Natalia, Glüge, Juliane, Groh, Ksenia, Grosse, Sylvia, Haglund, Peter, Hakkinen, Pertti J., Hale, Sarah E., Hernandez, Felix, Janssen, Elisabeth M.-L., Jonkers, Tim, Kiefer, Karin, Kirchner, Michal, Koschorreck, Jan, Krauss, Martin, Krier, Jessy, Lamoree, Marja H., Letzel, Marion, Letzel, Thomas, Li, Qingliang, Little, James, Liu, Yanna, Lunderberg, David M., Martin, Jonathan W., McEachran, Andrew D., McLean, John A., Meier, Christiane, Meijer, Jeroen, Menger, Frank, Merino, Carla, Muncke, Jane, Muschket, Matthias, Neumann, Michael, Neveu, Vanessa, Ng, Kelsey, Oberacher, Herbert, O’Brien, Jake, Oswald, Peter, Oswaldova, Martina, Picache, Jaqueline A., Postigo, Cristina, Ramirez, Noelia, Reemtsma, Thorsten, Renaud, Justin, Rostkowski, Pawel, Rüdel, Heinz, Salek, Reza M., Samanipour, Saer, Scheringer, Martin, Schliebner, Ivo, Schulz, Wolfgang, Schulze, Tobias, Sengl, Manfred, Shoemaker, Benjamin A., Sims, Kerry, Singer, Heinz, Singh, Randolph R., Sumarah, Mark, Thiessen, Paul A., Thomas, Kevin V., Torres, Sonia, Trier, Xenia, van Wezel, Annemarie P., Vermeulen, Roel C. H., Vlaanderen, Jelle J., von der Ohe, Peter C., Wang, Zhanyun, Williams, Antony J., Willighagen, Egon L., Wishart, David S., Zhang, Jian, Thomaidis, Nikolaos S., Hollender, Juliane, Slobodnik, Jaroslav, and Schymanski, Emma L.

Published
2022
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6. ELIXIR and Toxicology: a community in development

Author

Martens, Marvin, primary, Stierum, Rob, additional, Schymanski, Emma L., additional, Evelo, Chris T., additional, Aalizadeh, Reza, additional, Aladjov, Hristo, additional, Arturi, Kasia, additional, Audouze, Karine, additional, Babica, Pavel, additional, Berka, Karel, additional, Bessems, Jos, additional, Blaha, Ludek, additional, Bolton, Evan E., additional, Cases, Montserrat, additional, Damalas, Dimitrios Ε., additional, Dave, Kirtan, additional, Dilger, Marco, additional, Exner, Thomas, additional, Geerke, Daan P., additional, Grafström, Roland, additional, Gray, Alasdair, additional, Hancock, John M., additional, Hollert, Henner, additional, Jeliazkova, Nina, additional, Jennen, Danyel, additional, Jourdan, Fabien, additional, Kahlem, Pascal, additional, Klanova, Jana, additional, Kleinjans, Jos, additional, Kondic, Todor, additional, Kone, Boï, additional, Lynch, Iseult, additional, Maran, Uko, additional, Martinez Cuesta, Sergio, additional, Ménager, Hervé, additional, Neumann, Steffen, additional, Nymark, Penny, additional, Oberacher, Herbert, additional, Ramirez, Noelia, additional, Remy, Sylvie, additional, Rocca-Serra, Philippe, additional, Salek, Reza M., additional, Sallach, Brett, additional, Sansone, Susanna-Assunta, additional, Sanz, Ferran, additional, Sarimveis, Haralambos, additional, Sarntivijai, Sirarat, additional, Schulze, Tobias, additional, Slobodnik, Jaroslav, additional, Spjuth, Ola, additional, Tedds, Jonathan, additional, Thomaidis, Nikolaos, additional, Weber, Ralf J.M., additional, van Westen, Gerard J.P., additional, Wheelock, Craig E., additional, Williams, Antony J., additional, Witters, Hilda, additional, Zdrazil, Barbara, additional, Županič, Anže, additional, and Willighagen, Egon L., additional

Published
2023
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9. Exposure to secondhand and thirdhand smoke in private vehicles: Measurements in air and dust samples

Author

Fernández, Esteve, Castellano, Yolanda, Fu, Marcela, Ballbè, Montse, Amalia, Beladenta, Tigova, Olena, López, Maria José, Continente, Xavier, Arechavala, Teresa, Henderson, Elisabet, Gallus, Silvano, Lugo, Alessandra, Liu, Xiaoqiu, Borroni, Elisa, Stival, Chiara, Colombo, Paolo, Semple, Sean, O'Donnell, Rachel, Dobson, Ruaraidh, Clancy, Luke, Keogan, Sheila, Byrne, Hannah, Behrakis, Panagiotis, Tzortzi, Anna, Vardavas, Constantine, Vyzikidou, Vergina Konstantina, Bakelas, Gerasimos, Mattiampa, George, Boffi, Roberto, Ruprecht, Ario, De Marco, Cinzia, Borgini, Alessandro, Veronese, Chiara, Bertoldi, Martina, Tittarelli, Andrea, Gorini, Giuseppe, Carreras, Giulia, Cortini, Barbara, Verdi, Simona, Lachi, Alessio, Chellini, Elisabetta, López Nicolás, Ángel, Trapero-Bertran, Marta, Celdrán Guerrero, Daniel, Radu-Loghin, Cornel, Nguyen, Dominick, Starchenko, Polina, Soriano, Joan B., Ancochea, Julio, Alonso, Tamara, Pastor, María Teresa, Erro, Marta, Roca, Ana, Pérez, Patricia, Castillo, Elena García, López-González, Laura, Navas-Acién, Ana, Cortés-Francisco, Núria, and Ramírez, Noelia

Published
2023
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12. The NORMAN Suspect List Exchange (NORMAN-SLE) : facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Author

Taha, Hiba Mohammed, Aalizadeh, Reza, Alygizakis, Nikiforos, Antignac, Jean-Philippe, Arp, Hans Peter H., Bade, Richard, Baker, Nancy, Belova, Lidia, Bijlsma, Lubertus, Bolton, Evan E., Brack, Werner, Celma, Alberto, Chen, Wen-Ling, Cheng, Tiejun, Chirsir, Parviel, Čirka, Ľuboš, D'Agostino, Lisa A., Feunang, Yannick Djoumbou, Dulio, Valeria, Fischer, Stellan, Gago-Ferrero, Pablo, Galani, Aikaterini, Geueke, Birgit, Głowacka, Natalia, Glüge, Juliane, Groh, Ksenia, Grosse, Sylvia, Haglund, Peter, Hakkinen, Pertti J., Hale, Sarah E., Hernandez, Felix, Janssen, Elisabeth M.-L., Jonkers, Tim, Kiefer, Karin, Kirchner, Michal, Koschorreck, Jan, Krauss, Martin, Krier, Jessy, Lamoree, Marja H., Letzel, Marion, Letzel, Thomas, Li, Qingliang, Little, James, Liu, Yanna, Lunderberg, David M., Martin, Jonathan W., McEachran, Andrew D., McLean, John A., Meier, Christiane, Meijer, Jeroen, Menger, Frank, Merino, Carla, Muncke, Jane, Muschket, Matthias, Neumann, Michael, Neveu, Vanessa, Ng, Kelsey, Oberacher, Herbert, O'Brien, Jake, Oswald, Peter, Oswaldova, Martina, Picache, Jaqueline A., Postigo, Cristina, Ramirez, Noelia, Reemtsma, Thorsten, Renaud, Justin, Rostkowski, Pawel, Rüdel, Heinz, Salek, Reza M., Samanipour, Saer, Scheringer, Martin, Schliebner, Ivo, Schulz, Wolfgang, Schulze, Tobias, Sengl, Manfred, Shoemaker, Benjamin A., Sims, Kerry, Singer, Heinz, Singh, Randolph R., Sumarah, Mark, Thiessen, Paul A., Thomas, Kevin V., Torres, Sonia, Trier, Xenia, van Wezel, Annemarie P., Vermeulen, Roel C. H., Vlaanderen, Jelle J., von der Ohe, Peter C., Wang, Zhanyun, Williams, Antony J., Willighagen, Egon L., Wishart, David S., Zhang, Jian, Thomaidis, Nikolaos S., Hollender, Juliane, Slobodnik, Jaroslav, Schymanski, Emma L., Taha, Hiba Mohammed, Aalizadeh, Reza, Alygizakis, Nikiforos, Antignac, Jean-Philippe, Arp, Hans Peter H., Bade, Richard, Baker, Nancy, Belova, Lidia, Bijlsma, Lubertus, Bolton, Evan E., Brack, Werner, Celma, Alberto, Chen, Wen-Ling, Cheng, Tiejun, Chirsir, Parviel, Čirka, Ľuboš, D'Agostino, Lisa A., Feunang, Yannick Djoumbou, Dulio, Valeria, Fischer, Stellan, Gago-Ferrero, Pablo, Galani, Aikaterini, Geueke, Birgit, Głowacka, Natalia, Glüge, Juliane, Groh, Ksenia, Grosse, Sylvia, Haglund, Peter, Hakkinen, Pertti J., Hale, Sarah E., Hernandez, Felix, Janssen, Elisabeth M.-L., Jonkers, Tim, Kiefer, Karin, Kirchner, Michal, Koschorreck, Jan, Krauss, Martin, Krier, Jessy, Lamoree, Marja H., Letzel, Marion, Letzel, Thomas, Li, Qingliang, Little, James, Liu, Yanna, Lunderberg, David M., Martin, Jonathan W., McEachran, Andrew D., McLean, John A., Meier, Christiane, Meijer, Jeroen, Menger, Frank, Merino, Carla, Muncke, Jane, Muschket, Matthias, Neumann, Michael, Neveu, Vanessa, Ng, Kelsey, Oberacher, Herbert, O'Brien, Jake, Oswald, Peter, Oswaldova, Martina, Picache, Jaqueline A., Postigo, Cristina, Ramirez, Noelia, Reemtsma, Thorsten, Renaud, Justin, Rostkowski, Pawel, Rüdel, Heinz, Salek, Reza M., Samanipour, Saer, Scheringer, Martin, Schliebner, Ivo, Schulz, Wolfgang, Schulze, Tobias, Sengl, Manfred, Shoemaker, Benjamin A., Sims, Kerry, Singer, Heinz, Singh, Randolph R., Sumarah, Mark, Thiessen, Paul A., Thomas, Kevin V., Torres, Sonia, Trier, Xenia, van Wezel, Annemarie P., Vermeulen, Roel C. H., Vlaanderen, Jelle J., von der Ohe, Peter C., Wang, Zhanyun, Williams, Antony J., Willighagen, Egon L., Wishart, David S., Zhang, Jian, Thomaidis, Nikolaos S., Hollender, Juliane, Slobodnik, Jaroslav, and Schymanski, Emma L.

Abstract

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov

Published
2022
Full Text
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13. The NORMAN Suspect List Exchange (NORMAN-SLE): Facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Author

IRAS OH Epidemiology Chemical Agents, Mohammed Taha, Hiba, Aalizadeh, Reza, Alygizakis, Nikiforos, Antignac, Jean-Philippe, Arp, Hans Peter H, Bade, Richard, Baker, Nancy, Belova, Lidia, Bijlsma, Lubertus, Bolton, Evan E, Brack, Werner, Celma, Alberto, Chen, Wen-Ling, Cheng, Tiejun, Chirsir, Parviel, Čirka, Ľuboš, D'Agostino, Lisa A, Djoumbou Feunang, Yannick, Dulio, Valeria, Fischer, Stellan, Gago-Ferrero, Pablo, Galani, Aikaterini, Geueke, Birgit, Głowacka, Natalia, Glüge, Juliane, Groh, Ksenia, Grosse, Sylvia, Haglund, Peter, Hakkinen, Pertti J, Hale, Sarah E, Hernandez, Felix, Janssen, Elisabeth M-L, Jonkers, Tim, Kiefer, Karin, Kirchner, Michal, Koschorreck, Jan, Krauss, Martin, Krier, Jessy, Lamoree, Marja H, Letzel, Marion, Letzel, Thomas, Li, Qingliang, Little, James, Liu, Yanna, Lunderberg, David M, Martin, Jonathan W, McEachran, Andrew D, McLean, John A, Meier, Christiane, Meijer, Jeroen, Menger, Frank, Merino, Carla, Muncke, Jane, Muschket, Matthias, Neumann, Michael, Neveu, Vanessa, Ng, Kelsey, Oberacher, Herbert, O'Brien, Jake, Oswald, Peter, Oswaldova, Martina, Picache, Jaqueline A, Postigo, Cristina, Ramirez, Noelia, Reemtsma, Thorsten, Renaud, Justin, Rostkowski, Pawel, Rüdel, Heinz, Salek, Reza M, Samanipour, Saer, Scheringer, Martin, Schliebner, Ivo, Schulz, Wolfgang, Schulze, Tobias, Sengl, Manfred, Shoemaker, Benjamin A, Sims, Kerry, Singer, Heinz, Singh, Randolph R, Sumarah, Mark, Thiessen, Paul A, Thomas, Kevin V, Torres, Sonia, Trier, Xenia, van Wezel, Annemarie P, Vermeulen, Roel C H, Vlaanderen, Jelle J, von der Ohe, Peter C, Wang, Zhanyun, Williams, Antony J, Willighagen, Egon L, Wishart, David S, Zhang, Jian, Thomaidis, Nikolaos S, Hollender, Juliane, Slobodnik, Jaroslav, Schymanski, Emma L, IRAS OH Epidemiology Chemical Agents, Mohammed Taha, Hiba, Aalizadeh, Reza, Alygizakis, Nikiforos, Antignac, Jean-Philippe, Arp, Hans Peter H, Bade, Richard, Baker, Nancy, Belova, Lidia, Bijlsma, Lubertus, Bolton, Evan E, Brack, Werner, Celma, Alberto, Chen, Wen-Ling, Cheng, Tiejun, Chirsir, Parviel, Čirka, Ľuboš, D'Agostino, Lisa A, Djoumbou Feunang, Yannick, Dulio, Valeria, Fischer, Stellan, Gago-Ferrero, Pablo, Galani, Aikaterini, Geueke, Birgit, Głowacka, Natalia, Glüge, Juliane, Groh, Ksenia, Grosse, Sylvia, Haglund, Peter, Hakkinen, Pertti J, Hale, Sarah E, Hernandez, Felix, Janssen, Elisabeth M-L, Jonkers, Tim, Kiefer, Karin, Kirchner, Michal, Koschorreck, Jan, Krauss, Martin, Krier, Jessy, Lamoree, Marja H, Letzel, Marion, Letzel, Thomas, Li, Qingliang, Little, James, Liu, Yanna, Lunderberg, David M, Martin, Jonathan W, McEachran, Andrew D, McLean, John A, Meier, Christiane, Meijer, Jeroen, Menger, Frank, Merino, Carla, Muncke, Jane, Muschket, Matthias, Neumann, Michael, Neveu, Vanessa, Ng, Kelsey, Oberacher, Herbert, O'Brien, Jake, Oswald, Peter, Oswaldova, Martina, Picache, Jaqueline A, Postigo, Cristina, Ramirez, Noelia, Reemtsma, Thorsten, Renaud, Justin, Rostkowski, Pawel, Rüdel, Heinz, Salek, Reza M, Samanipour, Saer, Scheringer, Martin, Schliebner, Ivo, Schulz, Wolfgang, Schulze, Tobias, Sengl, Manfred, Shoemaker, Benjamin A, Sims, Kerry, Singer, Heinz, Singh, Randolph R, Sumarah, Mark, Thiessen, Paul A, Thomas, Kevin V, Torres, Sonia, Trier, Xenia, van Wezel, Annemarie P, Vermeulen, Roel C H, Vlaanderen, Jelle J, von der Ohe, Peter C, Wang, Zhanyun, Williams, Antony J, Willighagen, Egon L, Wishart, David S, Zhang, Jian, Thomaidis, Nikolaos S, Hollender, Juliane, Slobodnik, Jaroslav, and Schymanski, Emma L

Published
2022

14. The NORMAN Suspect List Exchange (NORMAN-SLE):facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Author

Mohammed Taha, Hiba, Aalizadeh, Reza, Alygizakis, Nikiforos, Antignac, Jean Philippe, Arp, Hans Peter H., Bade, Richard, Baker, Nancy, Belova, Lidia, Bijlsma, Lubertus, Bolton, Evan E., Brack, Werner, Celma, Alberto, Chen, Wen Ling, Cheng, Tiejun, Chirsir, Parviel, Čirka, Ľuboš, D’Agostino, Lisa A., Djoumbou Feunang, Yannick, Dulio, Valeria, Fischer, Stellan, Gago-Ferrero, Pablo, Galani, Aikaterini, Geueke, Birgit, Głowacka, Natalia, Glüge, Juliane, Groh, Ksenia, Grosse, Sylvia, Haglund, Peter, Hakkinen, Pertti J., Hale, Sarah E., Hernandez, Felix, Janssen, Elisabeth M.L., Jonkers, Tim, Kiefer, Karin, Kirchner, Michal, Koschorreck, Jan, Krauss, Martin, Krier, Jessy, Lamoree, Marja H., Letzel, Marion, Letzel, Thomas, Li, Qingliang, Little, James, Liu, Yanna, Lunderberg, David M., Martin, Jonathan W., McEachran, Andrew D., McLean, John A., Meier, Christiane, Meijer, Jeroen, Menger, Frank, Merino, Carla, Muncke, Jane, Muschket, Matthias, Neumann, Michael, Neveu, Vanessa, Ng, Kelsey, Oberacher, Herbert, O’Brien, Jake, Oswald, Peter, Oswaldova, Martina, Picache, Jaqueline A., Postigo, Cristina, Ramirez, Noelia, Reemtsma, Thorsten, Renaud, Justin, Rostkowski, Pawel, Rüdel, Heinz, Salek, Reza M., Samanipour, Saer, Scheringer, Martin, Schliebner, Ivo, Schulz, Wolfgang, Schulze, Tobias, Sengl, Manfred, Shoemaker, Benjamin A., Sims, Kerry, Singer, Heinz, Singh, Randolph R., Sumarah, Mark, Thiessen, Paul A., Thomas, Kevin V., Torres, Sonia, Trier, Xenia, van Wezel, Annemarie P., Vermeulen, Roel C.H., Vlaanderen, Jelle J., von der Ohe, Peter C., Wang, Zhanyun, Williams, Antony J., Willighagen, Egon L., Wishart, David S., Zhang, Jian, Thomaidis, Nikolaos S., Hollender, Juliane, Slobodnik, Jaroslav, Schymanski, Emma L., Mohammed Taha, Hiba, Aalizadeh, Reza, Alygizakis, Nikiforos, Antignac, Jean Philippe, Arp, Hans Peter H., Bade, Richard, Baker, Nancy, Belova, Lidia, Bijlsma, Lubertus, Bolton, Evan E., Brack, Werner, Celma, Alberto, Chen, Wen Ling, Cheng, Tiejun, Chirsir, Parviel, Čirka, Ľuboš, D’Agostino, Lisa A., Djoumbou Feunang, Yannick, Dulio, Valeria, Fischer, Stellan, Gago-Ferrero, Pablo, Galani, Aikaterini, Geueke, Birgit, Głowacka, Natalia, Glüge, Juliane, Groh, Ksenia, Grosse, Sylvia, Haglund, Peter, Hakkinen, Pertti J., Hale, Sarah E., Hernandez, Felix, Janssen, Elisabeth M.L., Jonkers, Tim, Kiefer, Karin, Kirchner, Michal, Koschorreck, Jan, Krauss, Martin, Krier, Jessy, Lamoree, Marja H., Letzel, Marion, Letzel, Thomas, Li, Qingliang, Little, James, Liu, Yanna, Lunderberg, David M., Martin, Jonathan W., McEachran, Andrew D., McLean, John A., Meier, Christiane, Meijer, Jeroen, Menger, Frank, Merino, Carla, Muncke, Jane, Muschket, Matthias, Neumann, Michael, Neveu, Vanessa, Ng, Kelsey, Oberacher, Herbert, O’Brien, Jake, Oswald, Peter, Oswaldova, Martina, Picache, Jaqueline A., Postigo, Cristina, Ramirez, Noelia, Reemtsma, Thorsten, Renaud, Justin, Rostkowski, Pawel, Rüdel, Heinz, Salek, Reza M., Samanipour, Saer, Scheringer, Martin, Schliebner, Ivo, Schulz, Wolfgang, Schulze, Tobias, Sengl, Manfred, Shoemaker, Benjamin A., Sims, Kerry, Singer, Heinz, Singh, Randolph R., Sumarah, Mark, Thiessen, Paul A., Thomas, Kevin V., Torres, Sonia, Trier, Xenia, van Wezel, Annemarie P., Vermeulen, Roel C.H., Vlaanderen, Jelle J., von der Ohe, Peter C., Wang, Zhanyun, Williams, Antony J., Willighagen, Egon L., Wishart, David S., Zhang, Jian, Thomaidis, Nikolaos S., Hollender, Juliane, Slobodnik, Jaroslav, and Schymanski, Emma L.

Abstract

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.

Published
2022

17. Additional file 2 of The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Author

Mohammed Taha, Hiba, Aalizadeh, Reza, Alygizakis, Nikiforos, Antignac, Jean-Philippe, Arp, Hans Peter H., Bade, Richard, Baker, Nancy, Belova, Lidia, Bijlsma, Lubertus, Bolton, Evan E., Brack, Werner, Celma, Alberto, Chen, Wen-Ling, Cheng, Tiejun, Chirsir, Parviel, Čirka, Ľuboš, D’Agostino, Lisa A., Djoumbou Feunang, Yannick, Dulio, Valeria, Fischer, Stellan, Gago-Ferrero, Pablo, Galani, Aikaterini, Geueke, Birgit, Głowacka, Natalia, Glüge, Juliane, Groh, Ksenia, Grosse, Sylvia, Haglund, Peter, Hakkinen, Pertti J., Hale, Sarah E., Hernandez, Felix, Janssen, Elisabeth M.-L., Jonkers, Tim, Kiefer, Karin, Kirchner, Michal, Koschorreck, Jan, Krauss, Martin, Krier, Jessy, Lamoree, Marja H., Letzel, Marion, Letzel, Thomas, Li, Qingliang, Little, James, Liu, Yanna, Lunderberg, David M., Martin, Jonathan W., McEachran, Andrew D., McLean, John A., Meier, Christiane, Meijer, Jeroen, Menger, Frank, Merino, Carla, Muncke, Jane, Muschket, Matthias, Neumann, Michael, Neveu, Vanessa, Ng, Kelsey, Oberacher, Herbert, O’Brien, Jake, Oswald, Peter, Oswaldova, Martina, Picache, Jaqueline A., Postigo, Cristina, Ramirez, Noelia, Reemtsma, Thorsten, Renaud, Justin, Rostkowski, Pawel, Rüdel, Heinz, Salek, Reza M., Samanipour, Saer, Scheringer, Martin, Schliebner, Ivo, Schulz, Wolfgang, Schulze, Tobias, Sengl, Manfred, Shoemaker, Benjamin A., Sims, Kerry, Singer, Heinz, Singh, Randolph R., Sumarah, Mark, Thiessen, Paul A., Thomas, Kevin V., Torres, Sonia, Trier, Xenia, van Wezel, Annemarie P., Vermeulen, Roel C. H., Vlaanderen, Jelle J., von der Ohe, Peter C., Wang, Zhanyun, Williams, Antony J., Willighagen, Egon L., Wishart, David S., Zhang, Jian, Thomaidis, Nikolaos S., Hollender, Juliane, Slobodnik, Jaroslav, and Schymanski, Emma L.

Subjects
Pharmacology, Ecology, 39999 Chemical Sciences not elsewhere classified, FOS: Chemical sciences, FOS: Biological sciences, Computational Biology, Marine Biology, Biochemistry, Molecular Biology, Biotechnology, Cancer
Abstract

Additional file 2: Overview of the NORMAN-SLE website (DOCX format) as of 30 May 2022 [82].

Published
2022
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22. ELIXIR and Toxicology: a community in development

Author

Martens, Marvin, primary, Stierum, Rob, additional, Schymanski, Emma L., additional, Evelo, Chris T., additional, Aalizadeh, Reza, additional, Aladjov, Hristo, additional, Arturi, Kasia, additional, Audouze, Karine, additional, Babica, Pavel, additional, Berka, Karel, additional, Bessems, Jos, additional, Blaha, Ludek, additional, Bolton, Evan E., additional, Cases, Montserrat, additional, Damalas, Dimitrios Ε., additional, Dave, Kirtan, additional, Dilger, Marco, additional, Exner, Thomas, additional, Geerke, Daan P., additional, Grafström, Roland, additional, Gray, Alasdair, additional, Hancock, John M., additional, Hollert, Henner, additional, Jeliazkova, Nina, additional, Jennen, Danyel, additional, Jourdan, Fabien, additional, Kahlem, Pascal, additional, Klanova, Jana, additional, Kleinjans, Jos, additional, Kondic, Todor, additional, Kone, Boï, additional, Lynch, Iseult, additional, Maran, Uko, additional, Martinez Cuesta, Sergio, additional, Ménager, Hervé, additional, Neumann, Steffen, additional, Nymark, Penny, additional, Oberacher, Herbert, additional, Ramirez, Noelia, additional, Remy, Sylvie, additional, Rocca-Serra, Philippe, additional, Salek, Reza M., additional, Sallach, Brett, additional, Sansone, Susanna-Assunta, additional, Sanz, Ferran, additional, Sarimveis, Haralambos, additional, Sarntivijai, Sirarat, additional, Schulze, Tobias, additional, Slobodnik, Jaroslav, additional, Spjuth, Ola, additional, Tedds, Jonathan, additional, Thomaidis, Nikolaos, additional, Weber, Ralf J.M., additional, van Westen, Gerard J.P., additional, Wheelock, Craig E., additional, Williams, Antony J., additional, Witters, Hilda, additional, Zdrazil, Barbara, additional, Županič, Anže, additional, and Willighagen, Egon L., additional

Published
2021
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23. Baseline Risk of Metabolic Syndrome Among Participants Post Stroke Enrolled in an Intensive Lifestyle Intervention to Promote Weight-Loss

Author

Driver, Simon, primary, Swank, Chad, additional, Froehlich-Grobe, Katherine, additional, McShan, Evan Elizabeth, additional, Calhoun, Stephanie, additional, Brown, Sharon, additional, Ramirez, Noelia, additional, Bennett, Monica, additional, Callender, Librada, additional, Miro, Danielle, additional, Dubiel, Rosemary, additional, and Mukkamala, Sridevi, additional

Published
2021
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24. Environmental Cheminformatics: Case study of Thirdhand Smoke in House Dust

Author

Schymanski, Emma L, Torres, Sonia, and Ramirez, Noelia

Subjects
thirdhand smoke, non-target screening, environmental metabolomics
Abstract

Environmental Cheminformatics: Case Study of Thirdhand Smoke in House Dust Keynote: https://rfmf-mpf-2020.sciencesconf.org/ Emma L. SCHYMANSKI1; Sonia TORRES2; Noelia RAMIREZ2 1 Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg 2 University Rovira y Virgili, Tarragona, Spain Introduction The environment and the chemicals to which we are exposed is incredibly complex. Household dust samples contain a summary of household exposure to various chemicals, suitable for exploration using high resolution mass spectrometry (HR-MS). Target and non-target HR-MS analysis for third hand smoke (THS) was performed on 75 dust samples (33 smoker, 42 non-smoker households) in Tarragona, Spain, focusing on tobacco-specific nitrosamines, which have been associated with higher health risk [1]. Technological and methodological innovation Primarily open access/source metabolomics and environmental workflows for HR-MS data analysis were used to interrogate the non-target data. A list of substances in THS was compiled for suspect screening, while an XCMS-based [2] workflow was used to prioritize non-target features of interest that were significantly different between smoker and non-smoker samples. Data was extracted using RMassBank [3], features were annotated using MassBank and MetFrag [4], searching in PubChem and CompTox. Results and impact This case study will be used to demonstrate the potential (pros and cons) of various environmental cheminformatics approaches to interpret non-target data, and highlight challenges still facing the field, such as limited coverage of mass spectral libraries [5]. A number of other European and world-wide initiatives will be covered to demonstrate the power of HR-MS and “environmental cheminformatics” to reveal information about the exposome and move to “near real-time” analysis. References [1] Ramírez N. et al. 2014. Environment International. 71, 139-147 [2] Smith, C.A. et al. 2006. Analytical Chemistry. 78, 779-787 [3] Stravs, M.A. et al. 2013. Journal of Mass Spectrometry. 48, 89-99 [4] Ruttkies, C. et al. 2016. Journal of Cheminformatics. 8, 3 [5] Frainay C. et al. 2018. Metabolites. 8, 51 &nbsp

Published
2020
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27. A self-consistent, multivariate method for the determination of gas-phase rate coefficients, applied to reactions of atmospheric VOCs and the hydroxyl radical

Author

Shaw, Jacob T., Lidster, Richard T., Cryer, Danny R., Ramirez, Noelia, Whiting, Fiona C., Boustead, Graham A., Whalley, Lisa K., Ingham, Trevor, Rickard, Andrew R., Dunmore, Rachel E., Heard, Dwayne E., Lewis, Ally C., Carpenter, Lucy J., Hamilton, Jacqui F., and DIllon, Terry J.

Abstract

Gas-phase rate coefficients are fundamental to understanding atmospheric chemistry, yet experimental data are not available for the oxidation reactions of many of the thousands of volatile organic compounds (VOCs) observed in the troposphere. Here, a new experimental method is reported for the simultaneous study of reactions between multiple different VOCs and OH, the most important daytime atmospheric radical oxidant. This technique is based upon established relative rate concepts but has the advantage of a much higher throughput of target VOCs. By evaluating multiple VOCs in each experiment, and through measurement of the depletion in each VOC after reaction with OH, the OH + VOC reaction rate coefficients can be derived. Results from experiments conducted under controlled laboratory conditions were in good agreement with the available literature for the reaction of 19 VOCs, prepared in synthetic gas mixtures, with OH. This approach was used to determine a rate coefficient for the reaction of OH with 2,3-dimethylpent-1-ene for the first time; k = 5.7 (±0.3) × 10−11 cm3 molecule−1 s−1. In addition, a further seven VOCs had only two, or fewer, individual OH rate coefficient measurements available in the literature. The results from this work were in good agreement with those measurements. A similar dataset, at an elevated temperature of 323 (±10) K, was used to determine new OH rate coefficients for 12 aromatic, 5 alkane, 5 alkene and 3 monoterpene VOC + OH reactions. In OH relative reactivity experiments that used ambient air at the University of York, a large number of different VOCs were observed, of which 23 were positively identified. Due to difficulties with detection limits and fully resolving peaks, only 19 OH rate coefficients were derived from these ambient air samples, including 10 reactions for which data were previously unavailable at the elevated reaction temperature of T = 323 (±10) K.

Published
2018

28. A self-consistent, multi-variate method for the determination of gas phase rate coefficients, applied to reactions of atmospheric VOCs and the hydroxyl radical

Author

Shaw, Jacob Thomas, Lidster, Richard Terence, Cryer, Danny R., Ramirez, Noelia, Bousted, Graham, Whalley, Lisa K., Ingham, Trevor, Rickard, Andrew Robert, Dunmore, Rachel Ellen, Heard, Dwayne E., Lewis, Alastair, Carpenter, Lucy Jane, Hamilton, Jacqueline Fiona, and Dillon, Terry James

Abstract

Gas-phase rate coefficients are fundamental to understanding atmospheric chemistry, yet experimental data are not available for the oxidation reactions of many of the thousands of volatile organic compounds (VOCs) observed in the troposphere. Here a new experimental method is reported for the simultaneous study of reactions between multiple different VOCs and OH, the most important daytime atmospheric radical oxidant. This technique is based upon established relative rate concepts but has the advantage of a much higher throughput of target VOCs. By evaluating multiple VOCs in each experiment, and through measurement of the depletion in each VOC after reaction with OH, the OH + VOC reaction rate coefficients can be derived. Results from experiments conducted under controlled laboratory conditions were in good agreement with the available literature for the reaction of nineteen VOCs, prepared in synthetic gas mixtures, with OH. This approach was used to determine a rate coefficient for the reaction of OH with 2,3-dimethylpent-1-ene for the first time; k = 5.7 (±0.3) × 10–11–cm3 molecule−1 s−1. In addition, a further seven VOCs had only two, or fewer, individual OH rate coefficient measurements available in the literature. The results from this work were in good agreement with those measurements. A similar dataset, at an elevated temperature of 323 (±10) K, was used to determine new OH rate coefficients for twelve aromatic, five alkane, five alkene and three monoterpene VOC + OH reactions. In OH relative reactivity experiments that used ambient air at the University of York, a large number of different VOCs were observed, of which 23 were positively identified. 19 OH rate coefficients were derived from these ambient air samples, including ten reactions for which data was previously unavailable at the elevated reaction temperature of T = 323 (±10) K.

Published
2017

29. Supplementary material to "A self-consistent, multi-variate method for the determination of gas phase rate coefficients, applied to reactions of atmospheric VOCs and the hydroxyl radical"

Author

Shaw, Jacob T., primary, Lidster, Richard T., additional, Cryer, Danny R., additional, Ramirez, Noelia, additional, Boustead, Graham A., additional, Whalley, Lisa K., additional, Ingham, Trevor, additional, Rickard, Andrew R., additional, Dunmore, Rachel E., additional, Heard, Dwayne E., additional, Lewis, Ally C., additional, Carpenter, Lucy J., additional, Hamilton, Jacqui F., additional, and Dillon, Terry J., additional

Published
2017
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30. A self-consistent, multi-variate method for the determination of gas phase rate coefficients, applied to reactions of atmospheric VOCs and the hydroxyl radical

Author

Shaw, Jacob T., primary, Lidster, Richard T., additional, Cryer, Danny R., additional, Ramirez, Noelia, additional, Boustead, Graham A., additional, Whalley, Lisa K., additional, Ingham, Trevor, additional, Rickard, Andrew R., additional, Dunmore, Rachel E., additional, Heard, Dwayne E., additional, Lewis, Ally C., additional, Carpenter, Lucy J., additional, Hamilton, Jacqui F., additional, and Dillon, Terry J., additional

Published
2017
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32. eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics

Author

Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics, Domingo Almenara, Xavier, Brezmes, Jesus, Vinaixa, Maria, Samino, Sara, Ramirez, Noelia, Ramon Krauel, Marta, Lerin, Carles, Díaz, Marta, Ibañez, Lourdes, Correig, Xavier, Perera Lluna, Alexandre, Yanes, Óscar, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics, Domingo Almenara, Xavier, Brezmes, Jesus, Vinaixa, Maria, Samino, Sara, Ramirez, Noelia, Ramon Krauel, Marta, Lerin, Carles, Díaz, Marta, Ibañez, Lourdes, Correig, Xavier, Perera Lluna, Alexandre, and Yanes, Óscar

Abstract

Gas chromatography coupled to mass spectrometry (GC/MS) has been a long-standing approach used for identifying small molecules due to the highly reproducible ionization process of electron impact ionization (EI). However, the use of GC-EI MS in untargeted metabolomics produces large and complex data sets characterized by coeluting compounds and extensive fragmentation of molecular ions caused by the hard electron ionization. In order to identify and extract quantitative information on metabolites across multiple biological samples, integrated computational workflows for data processing are needed. Here we introduce eRah, a free computational tool written in the open language R composed of five core functions: (i) noise filtering and baseline removal of GC/MS chromatograms, (ii) an innovative compound deconvolution process using multivariate analysis techniques based on compound match by local covariance (CMLC) and orthogonal signal deconvolution (OSD), (iii) alignment of mass spectra across samples, (iv) missing compound recovery, and (v) identification of metabolites by spectral library matching using publicly available mass spectra. eRah outputs a table with compound names, matching scores and the integrated area of compounds for each sample. The automated capabilities of eRah are demonstrated by the analysis of GC-time-of-flight (TOF) MS data from plasma samples of adolescents with hyperinsulinaemic androgen excess and healthy controls. The quantitative results of eRah are compared to centWave, the peak-picking algorithm implemented in the widely used XCMS package, MetAlign, and ChromaTOF software. Significantly dysregulated metabolites are further validated using pure standards and targeted analysis by GC-triple quadrupole (QqQ) MS, LC-QqQ, and NMR. eRah is freely available at http://CRAN.R-project.org/package=erah., Postprint (author's final draft)

Published
2016

33. Automated resolution of chromatographic signals by independent component analysis-orthogonal signal deconvolution in comprehensive gas chromatography/mass spectrometry-based metabolomics

Author

Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics, Domingo Almenara, Xavier, Perera Lluna, Alexandre, Ramirez, Noelia, Brezmes, Jesus, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics, Domingo Almenara, Xavier, Perera Lluna, Alexandre, Ramirez, Noelia, and Brezmes, Jesus

Abstract

Comprehensive gas chromatography-mass spectrometry (GC x GC-MS) provides a different perspective in metabolomics profiling of samples. However, algorithms for GCx GC-MS data processing are needed in order to automatically process the data and extract the purest information about the compounds appearing in complex biological samples. This study shows the capability of independent component analysis-orthogonal signal deconvolution (ICA-OSD), an algorithm based on blind source separation and distributed in an R package called osd, to extract the spectra of the compounds appearing in GCx GC-MS chromatograms in an automated manner. We studied the performance of ICA-OSD by the quantification of 38 metabolites through a set of 20 Jurkat cell samples analyzed by GCx GC-MS. The quantification by ICA-OSD was compared with a supervised quantification by selective ions, and most of the R2 coefficients of determination were in good agreement (R-2>0.90) while up to 24 cases exhibited an excellent linear relation (R-2>0.95). We concluded that ICA-OSD can be used to resolve co-eluted compounds in GC x GC-MS. (C) 2016 Elsevier Ireland Ltd. All rights reserved., Postprint (author's final draft)

Published
2016

34. Colaboradores

Author

Adalia Bartolomé, Ramón, Aguilar Salmerón, Raquel, Aguiló Mir, Sira, Aibar Gallizo, Jesús, Alemany Gonzalez, Xavier, Alobid Alobid, Isam, Alonso Viladot, José Ramón, Amigó Tadín, Montserrat, Antolín Santaliestra, Albert, Arroyave Hoyos, Claudia-Lucía, Bajo Bajo, Ángel, Barceló Martín, Bernardino, Blanch Andreu, Jordi, Bragulat Baur, Ernesto, Broto Sumalla, Antoni, Bruguera Cortada, Miquel, Bruguera Soler, Pol, Brunet Serra, Mercè, Burillo Putze, Guillermo, Caldentey Adrover, Guillem, Capdevila Reniu, Aina, Casals Mercadal, Gregori, Castellà Kastner, Montserrat, Castro Rebollo, Pedro, Cibeira López, M.ª Teresa, Cirera Lorenzo, Isabel, Climent Díaz, Benjamín, Coll Vinent, Blanca, Compta Hirnyj, Yaroslau, Conejo Menor, José Luis, Córdoba Ruiz, Francisca, Corominas García, Núria, Cruz Landeira, Angelines, Cruz Ramos, África de la, Mora Cañizo, Lorena de la, Oliva Urieta, Susana de la, Domínguez Panadero, Verónica, Dueñas Laita, Antonio, Escoda Turon, Ona, Escorsell Mañosa, Àngels, Fernández Bonifacio, Rosa, Gamarra Martínez, Edurne Fernández de, Fernández de Larrea, Carlos, Fernández Galán, Esther, Fernández Gómez, Javier, Fernández Guerrero, Inés María, Fernández Méndez, Sara, Fernández Solà, Joaquim, Ferrer Dufol, Ana, Flores Umanzor, Eduardo, Galicia Paredes, Miguel, Garcia Gibert, Lidia, García Martínez, Ana, García Peláez, Milagros, Garrabou Tornos, Glòria, Gené Badia, Manel, Giavedoni, Priscila, Gil Espinosa, Víctor, Gispert Ametller, Maria Àngels, Gómez Angelats, Elisenda, Gomez Calzada, Ubier Eduardo, Gómez Durán, Esperanza L., Gómez Gerbolés, Montserrat, Presa, Bernardino González de la, Huerta García, Arturo, Inglés Torruella, Joan, Izquierdo Domínguez, Adriana, Jerez Lienas, Alba, Jiménez Hernández, Sònia, López Barbeito, Beatriz, López Herrero, Nuria, Lamas, Manuel López-Rivadulla, Mallolas Masferrer, Josep, Marco Hernández, Javier, Marés Díaz, Lourdes, Marrón Moya, Teresa, Martín Pascual, Mayte, Martín Pérez, Beatriz, Martín Sierra, Cristina, Martínez Nadal, Gemma, Martínez Sánchez, Lídia, Mas Ordeig, Antoni, Mascaró Galy, José Manuel, Medallo Muñiz, Jordi, Mencías Rodríguez, Emilio, Méndez Liz, M.ª José, Miró Andreu, Òscar, Monclús Cols, Ester, Monforte Castro, Sandra, Monsalve Maestro, Concepción, Montori Palacín, Elisabet, Monzó Cárcel, Juan Antonio, Morén Núñez, Constanza, Mullol Miret, Joaquim, Muñoz Bermúdez, Rosana, Nicolás Arfelis, José María, Nogué Xarau, Santiago, Nogués Sabaté, Anna, Nolla Salas, Joan, Olaya Acosta, Hernando-Andrés, Ortega Romero, Mar, Ortiz Ballujera, Patricia, Ortuño Ramírez, Noelia, Palao Doménech, Ricardo, Pallàs Villaronga, Oriol, Paredes Zapata, David, Parés Darnaculleta, Albert, Pellicé Ariño, Martina, Perelló Carbonell, Rafael, Pinillos Echeverría, Miguel Ángel, López de Alda, Arrate Placer, López de Briñas, Esteban Poch, Prieto Arruñada, José Antonio, Puiguriguer Ferrando, Jordi, Reverter Segura, Enric, Rodríguez Villar, Camino, Ruiz Izquierdo, Jessica, Salgado García, Emilio, Sánchez Marcos, Carolina, Sánchez Sánchez, Miquel, Sanz Gallen, Pere, Soler Cata, Victoria, Soy Muner, Dolors, Spencer Vicent, Felipe, Supervía Caparrós, August, To Figueras, Jordi, Toro Blanch, Cristina, Torra Santamaria, Mercè, Torras Sanvicens, Josep, Uría Álvarez, Elisabet, Varela Pérez, Pilar, Vázquez López, Francisco, Vàzquez Vallejo, Mireia, Velasco Amigó, Verónica, Vendrell Jordà, Marina, Vidal Pérez, Óscar, and Xipell Badals, Carolina

Published
2019
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35. eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics

Author

Domingo-Almenara, Xavier, primary, Brezmes, Jesus, additional, Vinaixa, Maria, additional, Samino, Sara, additional, Ramirez, Noelia, additional, Ramon-Krauel, Marta, additional, Lerin, Carles, additional, Díaz, Marta, additional, Ibáñez, Lourdes, additional, Correig, Xavier, additional, Perera-Lluna, Alexandre, additional, and Yanes, Oscar, additional

Published
2016
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36. Compound identification in gas chromatography/mass spectrometry-based metabolomics by blind source separation

Author

Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics, Domingo Almenara, Xavier, Perera Lluna, Alexandre, Ramirez, Noelia, Canellas, Nicolau, Correig, Xavier, Brezmes, Jesus, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics, Domingo Almenara, Xavier, Perera Lluna, Alexandre, Ramirez, Noelia, Canellas, Nicolau, Correig, Xavier, and Brezmes, Jesus

Abstract

Metabolomics GC-MS samples involve high complexity data that must be effectively resolved to produce chemically meaningful results. Multivariate curve resolution-alternating least squares (MCR-ALS) is the most frequently reported technique for that purpose. More recently, independent component analysis (ICA) has been reported as an alternative to MCR. Those algorithms attempt to infer a model describing the observed data and, therefore, the least squares regression used in MCR assumes that the data is a linear combination of that model. However, due to the high complexity of real data, the construction of a model to describe optimally the observed data is a critical step and these algorithms should prevent the influence from outlier data. This study proves independent component regression (ICR) as an alternative for GC-MS compound identification. Both ICR and MCR though require least squares regression to correctly resolve the mixtures. In this paper, a novel orthogonal signal deconvolution (OSD) approach is introduced, which uses principal component analysis to determine the compound spectra. The study includes a compound identification comparison between the results by ICA-OSD, MCR-OSD, ICR and MCR-ALS using pure standards and human serum samples. Results shows that ICR may be used as an alternative to multivariate curve methods, as ICR efficiency is comparable to MCR-ALS. Also, the study demonstrates that the proposed OSD approach achieves greater spectral resolution accuracy than the traditional least squares approach when compounds elute under undue interference of biological matrices. (C) 2015 Elsevier B.V. All rights reserved., Postprint (published version)

Published
2015

37. Determination of volatile organic compounds in industrial wastewater plant air emissions by multi-sorbent adsorption and thermal desorption-gas chromatography-mass spectrometry.

Author

Ramirez, Noelia, Marce, Rosa Maria, and Borrull, Francesc

Subjects
*VOLATILE organic compounds, *SEWAGE disposal plants, *INDUSTRIAL waste purification, *THERMAL desorption, *GAS chromatography/Mass spectrometry (GC-MS), *AIR quality management, *POLARITY (Chemistry)
Abstract

This paper describes the process of determining the presence of volatile organic compounds in air emissions from industrial wastewater treatment plants (WWTP). The analytical method, based on thermal desorption-gas chromatography-mass spectrometry, was developed to simultaneously determine of 99 volatile organic compounds (VOCs) in air samples. This method is rapid, environmentally-friendly (since no organic solvents are used to extract the analytes) and compatible with a large range of thermally stable polar and apolar compounds. The target VOCs were selected on the basis of their occurrence in real samples and their adverse effects on the environment and human health. To cover the wide range of target compounds, multisorbent tubes filled with Tenax TA and Carbograph 1TD were used. Method validation showed good repeatabilities, low detection limits, a high linear range and good recoveries. At a fixed sample volume of 600 mL no significant losses for any of the target compounds were found in the samples. Stability during storage indicated that samples must be keep refrigerated at 4°C and analysed within three days of collection. Real samples were taken from air emissions of an industrial wastewater treatment plant located in the Southern Industrial Area of Tarragona (Spain) with the aim of studying its contribution as a source of atmospheric VOCs. This WWTP collects wastewater from several chemical factories which produce isocyanates, polyurethanes, chlorinated organics and functional chemicals among other products. Samples from the collecting tank after the primary sedimentation showed higher VOC concentrations than samples from the secondary treatment tank. The most abundant VOCs found in these emissions are included in the USEPA List of Hazardous Air Pollutants. The highest values correspond to acrylonitrile (up to 1843 µg m-3) and styrene (up to 573.70 µg m-3). The levels of chloroform, 1,4-dioxane, ethylbenzene, 1,2,3-trimethylbenzene and 1,4-diethylbenzene were also high. [ABSTRACT FROM AUTHOR]

Published
2011
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