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Mixtures of organic micropollutants exacerbated in vitro neurotoxicity of prymnesins and contributed to aquatic toxicity during a toxic algal bloom

In summer 2022 an enormous fish kill was observed in the Oder River as a consequence of prymnesins produced by an algal bloom. An investigation of the exposure of aquatic life and human cells to the contaminated Oder water revealed the presence of neurotoxicants, which are attributed to B-type prymnesins, with minor contributions by organic micropollutants.

Beate I. Escher
Jörg Ahlheim
Elisabeth Varga
ResearchOpen Access06 Sept 2024
Nature Water

Volume: 2, P: 889-898
Author Correction: Mixtures of organic micropollutants exacerbated in vitro neurotoxicity of prymnesins and contributed to aquatic toxicity during a toxic algal bloom

Beate I. Escher
Jörg Ahlheim
Elisabeth Varga
Amendments and CorrectionsOpen Access17 Sept 2024
Nature Water

Volume: 2, P: 1039
Reactivity-based identification of oxygen containing functional groups of chemicals applied as potential classifier in non-target analysis

Milena Latz
Alexander Böhme
Nadin Ulrich
ResearchOpen Access20 Dec 2023
Scientific Reports

Volume: 13, P: 1-9
Exploring the octanol–water partition coefficient dataset using deep learning techniques and data augmentation

Deep neural networks are potent tools for computational chemistry, but experimental feed data can limit their reach. Here the authors develop deep neural network data augmentation models to predict octanol–water partition coefficients (log P) of a variety of tautomers.

Nadin Ulrich
Kai-Uwe Goss
Andrea Ebert
ResearchOpen Access14 Jun 2021
Communications Chemistry

Volume: 4, P: 1-10

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Mixtures of organic micropollutants exacerbated in vitro neurotoxicity of prymnesins and contributed to aquatic toxicity during a toxic algal bloom

Author Correction: Mixtures of organic micropollutants exacerbated in vitro neurotoxicity of prymnesins and contributed to aquatic toxicity during a toxic algal bloom

Reactivity-based identification of oxygen containing functional groups of chemicals applied as potential classifier in non-target analysis

Exploring the octanol–water partition coefficient dataset using deep learning techniques and data augmentation

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