| High-throughput effect-directed analysis of androgenic compounds in hospital wastewater: identifying effect drivers through non-target screening supported by toxicity prediction
Alvarez-Mora, I., Muratuly, A., Johann, S., Arturi, K., Jünger, F., Huber, C., … Muz, M. (2025). High-throughput effect-directed analysis of androgenic compounds in hospital wastewater: identifying effect drivers through non-target screening supported by toxicity prediction. Environmental Science and Technology. https://doi.org/10.1021/acs.est.4c09942 |
| Progress, applications, and challenges in high-throughput effect-directed analysis for toxicity driver identification — is it time for HT-EDA?
Alvarez-Mora, I., Arturi, K., Béen, F., Buchinger, S., El Mais, A. E. R., Gallampois, C., … Muz, M. (2025). Progress, applications, and challenges in high-throughput effect-directed analysis for toxicity driver identification — is it time for HT-EDA? Analytical and Bioanalytical Chemistry, 417, 451-472. https://doi.org/10.1007/s00216-024-05424-4 |
| MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data
Arturi, K., Harris, E. J., Gasser, L., Escher, B. I., Braun, G., Bosshard, R., & Hollender, J. (2025). MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data. Journal of Cheminformatics, 17, 14 (20 pp.). https://doi.org/10.1186/s13321-025-00950-4 |
| Insights into respiratory illness at the population level through parallel analysis of pharmaceutical and viral markers in wastewater
Baumgartner, S., Salvisberg, M., Schmidhalter, P., Julian, T. R., Ort, C., & Singer, H. (2025). Insights into respiratory illness at the population level through parallel analysis of pharmaceutical and viral markers in wastewater. Nature Water, 3, 580-589. https://doi.org/10.1038/s44221-025-00437-4 |
| Relationship between antihistamine residues in wastewater and airborne pollen concentrations: insights into population-scale pollinosis response
Baumgartner, S., Salvisberg, M., Clot, B., Crouzy, B., Schmid-Grendelmeier, P., Singer, H., & Ort, C. (2025). Relationship between antihistamine residues in wastewater and airborne pollen concentrations: insights into population-scale pollinosis response. Science of the Total Environment, 964, 178515 (9 pp.). https://doi.org/10.1016/j.scitotenv.2025.178515 |
| Effect-directed analysis of genotoxicants in food packaging based on HPTLC fractionation, bioassays, and toxicity prediction with machine learning
Bergmann, A. J., Arturi, K., Schönborn, A., Hollender, J., & Vermeirssen, E. L. M. (2025). Effect-directed analysis of genotoxicants in food packaging based on HPTLC fractionation, bioassays, and toxicity prediction with machine learning. Analytical and Bioanalytical Chemistry, 417, 131-142. https://doi.org/10.1007/s00216-024-05632-y |
| Predictive modeling of biodegradation pathways using transformer architectures
Brydon, L., Zhang, K., Dobbie, G., Taškova, K., & Wicker, J. S. (2025). Predictive modeling of biodegradation pathways using transformer architectures. Journal of Cheminformatics, 17, 21 (16 pp.). https://doi.org/10.1186/s13321-025-00969-7 |
| Towards a universal scaling method for predicting equilibrium constants of polyoxometalates
Buils, J., Garay-Ruiz, D., Petrus, E., Segado-Centellas, M., & Bo, C. (2025). Towards a universal scaling method for predicting equilibrium constants of polyoxometalates. Digital Discovery, 4(4), 970-978. https://doi.org/10.1039/d4dd00358f |
| Bird's-eye view: current understanding and future perspectives on the biodefluorination of per- and polyfluoroalkyl substances (PFAS)
Che, S., Liu, H., Zhang, S., & Yu, Y. (2025). Bird's-eye view: current understanding and future perspectives on the biodefluorination of per- and polyfluoroalkyl substances (PFAS). Water Research X, 28, 100356 (11 pp.). https://doi.org/10.1016/j.wroa.2025.100356 |
| Unveiling industrial emissions in a large European river: insights from data mining of high-frequency measurements
Chonova, T., Ruppe, S., Langlois, I., Griesshaber, D. S., Loos, M., Honti, M., … Singer, H. (2025). Unveiling industrial emissions in a large European river: insights from data mining of high-frequency measurements. Water Research, 268, 122745 (13 pp.). https://doi.org/10.1016/j.watres.2024.122745 |
| Read-across of biotransformation potential between activated sludge and the terrestrial environment: toward making it practical and plausible
Coll, C., Screpanti, C., Hafner, J., Zhang, K., & Fenner, K. (2025). Read-across of biotransformation potential between activated sludge and the terrestrial environment: toward making it practical and plausible. Environmental Science and Technology, 59(3), 1790-1800. https://doi.org/10.1021/acs.est.4c09306 |
| GLOSSAQUA: a global dataset of size spectra across aquatic ecosystems
Ersoy, Z., Evangelista, C., Larrañaga, A., Perkins, D. M., Sánchez-Hernández, J., Chonova, T., … Arranz, I. (2025). GLOSSAQUA: a global dataset of size spectra across aquatic ecosystems. Ecology, 106(3), e70050 (3 pp.). https://doi.org/10.1002/ecy.70050 |
| Differential biotransformation ability may alter fish biodiversity in polluted waters
Franco, M. E., Hollender, J., & Schirmer, K. (2025). Differential biotransformation ability may alter fish biodiversity in polluted waters. Environment International, 195, 109254 (9 pp.). https://doi.org/10.1016/j.envint.2025.109254 |
| Realistic exposure scenarios in combined sewer overflows: how temporal resolution and selection of micropollutants impact risk assessment
Furrer, V., Junghans, M., Singer, H., & Ort, C. (2025). Realistic exposure scenarios in combined sewer overflows: how temporal resolution and selection of micropollutants impact risk assessment. Water Research, 278, 123318 (9 pp.). https://doi.org/10.1016/j.watres.2025.123318 |
| Source-specific dynamics of organic micropollutants in combined sewer overflows
Furrer, V., Froemelt, A., Singer, H., & Ort, C. (2025). Source-specific dynamics of organic micropollutants in combined sewer overflows. Water Research, 279, 123416 (9 pp.). https://doi.org/10.1016/j.watres.2025.123416 |
| Seasonality of cyanobacteria and eukaryotes in Lake Geneva and the impacts of cyanotoxins on growth of the model ciliate<em> Tetrahymena pyriformis</em>
Ismail, N., Seguin, P., Pricam, L., Janssen, E. M. L., Kohn, T., Ibelings, B. W., & Carratalà, A. (2025). Seasonality of cyanobacteria and eukaryotes in Lake Geneva and the impacts of cyanotoxins on growth of the model ciliate Tetrahymena pyriformis. Aquatic Toxicology, 279, 107262 (11 pp.). https://doi.org/10.1016/j.aquatox.2025.107262 |
| Preserving the biotransformation potential of activated sludge in time: toward reproducible incubation experiments for persistence assessment
Kalt, M., Udressy, C. I., Yu, Y., Colliquet, A., & Fenner, K. (2025). Preserving the biotransformation potential of activated sludge in time: toward reproducible incubation experiments for persistence assessment. Environmental Science and Technology, 59(9), 4597-4607. https://doi.org/10.1021/acs.est.4c08657 |
| Time-efficient approach for environmental transformation and bioavailability assessment of isotopically enriched nanoparticles to increase environmental relevance
Kuehr, S., Kaegi, R., Raths, J., Sinnet, B., Kipf, M., Philipp, M., … Georgantzopoulou, A. (2025). Time-efficient approach for environmental transformation and bioavailability assessment of isotopically enriched nanoparticles to increase environmental relevance. Science of the Total Environment, 971, 178997 (8 pp.). https://doi.org/10.1016/j.scitotenv.2025.178997 |
| Suspect and nontarget screening of organic micropollutants in Swiss sewage sludge: a nationwide survey
Lara-Martín, P. A., Schinkel, L., Eberhard, Y., Giger, W., Berg, M., & Hollender, J. (2025). Suspect and nontarget screening of organic micropollutants in Swiss sewage sludge: a nationwide survey. Environmental Science and Technology, 59(15), 7688-7698. https://doi.org/10.1021/acs.est.4c13217 |
| Machine learning reveals signatures of promiscuous microbial amidases for micropollutant biotransformations
Marti, T. D., Schweizer, D., Yu, Y., Schärer, M. R., Probst, S. I., & Robinson, S. L. (2025). Machine learning reveals signatures of promiscuous microbial amidases for micropollutant biotransformations. ACS Environmental Au, 5(1), 114-127. https://doi.org/10.1021/acsenvironau.4c00066 |
