The elevated toxicity of the biodegradation product (guanylurea) from metformin and the antagonistic pattern recognition of combined toxicity: Insight from the pharmaceutical risk assessment and the simulated wastewater treatment

Gao, Fan; Wen, Hao; Feng, Sen; Li, Meng; Zhu, Lingyun; Zhang, Yongzhi; Xi, Yilong; Xiang, Xianling

doi:10.1016/j.scitotenv.2023.164747

Cited by 5 publications

(2 citation statements)

References 63 publications

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“…A similar result was seen in Ussery et al (2019), where guanylurea imposed limitations in growth at the ng·L −1 level compared to impacts of metformin seen in µg·L −1 exposures. A recent study has positioned guanylurea as a more toxic compound to zooplankton than metformin (Gao et al 2023), but the results of this study suggest that guanylurea and metformin are more or less equivalent in their impact to larval development.…”

Section: Discussionmentioning

confidence: 56%

Metformin and guanylurea reduce survival, but have limited sublethal effects in larval zebrafish (Danio rerio)

Williams,

Thompson,

Masood

et al. 2023

Preprint

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Metformin is the most common first-line oral therapeutic agent used in the treatment of type-2 diabetes, one of the most prevalent chronic diseases in North America. Post excretion, the compound enters wastewater treatment plants where it is partially bio-transformed by bacteria into guanylurea. Both metformin and guanylurea enter freshwater environments in wastewater effluent where they are available for uptake by aquatic biota. However, our understanding of the effects of metformin and guanylurea on aquatic life is limited. We tested the hypothesis that metformin and guanylurea can influence the development of zebrafish (Danio rerio), by assessing morphometrics, cardiac development, energetic state, and behaviour of early larvae. Embryos were exposed to environmentally relevant (0.4, 4, 40 μg·L−1) and supra-environmental (400 and 4000 μg·L−1) concentrations of metformin and guanylurea from the 4-cell stage (3 hours post fertilization; hpf), until first feed (120 hpf). Exposures to 40 μg·L−1and higher of both metformin and guanylurea increased mortality. Metformin delayed hatching at the highest concentration tested (4000 μg·L−1). The incidence of spinal curvature increased with exposure to both chemicals at supra-environmental levels (400 and 4000 μg·L−1for metformin; 400 μg·L−1for guanylurea). Metformin and guanylurea exposure imposed slight bradycardia in early development, but did not alter oxygen consumption, ATP levels, carbohydrate levels, general swimming, light-dark movement, startle response, or thigmotaxis, irrespective of exposure concentration. The results suggest similar and low sensitivities of larval fish to both metformin and guanylurea. Apart from a small increase in mortality, these compounds impart a modest impact to the early-life stages of zebrafish that are largely limited to supra-environmental concentrations.

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Section: Discussionmentioning

confidence: 56%

Metformin and guanylurea reduce survival, but have limited sublethal effects in larval zebrafish (Danio rerio)

Williams,

Thompson,

Masood

et al. 2023

Preprint

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“…In addition, other artificial intelligence application tools such as expert systems (Wu et al 2021), fuzzy logic (Mazhar et al 2019), artificial neuro-fuzzy inference systems (Nam et al 2023), support vector machine (Zhang et al 2023b), knowledge-based systems (Liu et al 2023), ruled-based systems (Victor et al 2005), fuzzy logic control (Santín et al 2018), pattern recognition (Gao et al 2023), swarm intelligence (Negi et al 2023), genetic algorithm (Aparna and Swarnalatha 2023), reinforcement learning (Wang et al 2023a), hybrid systems (Tariq et al 2021), and so on have gained its purposes in process control systems and prediction of water quality characteristics.…”

Section: Assessment Of Water Qualitymentioning

confidence: 99%

Artificial intelligence and machine learning for the optimization of pharmaceutical wastewater treatment systems: a review

Ganthavee,

Trzcinski

2024

Environ Chem Lett

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The access to clean and drinkable water is becoming one of the major health issues because most natural waters are now polluted in the context of rapid industrialization and urbanization. Moreover, most pollutants such as antibiotics escape conventional wastewater treatments and are thus discharged in ecosystems, requiring advanced techniques for wastewater treatment. Here we review the use of artificial intelligence and machine learning to optimize pharmaceutical wastewater treatment systems, with focus on water quality, disinfection, renewable energy, biological treatment, blockchain technology, machine learning algorithms, big data, cyber-physical systems, and automated smart grid power distribution networks. Artificial intelligence allows for monitoring contaminants, facilitating data analysis, diagnosing water quality, easing autonomous decision-making, and predicting process parameters. We discuss advances in technical reliability, energy resources and wastewater management, cyber-resilience, security functionalities, and robust multidimensional performance of automated platform and distributed consortium, and stabilization of abnormal fluctuations in water quality parameters.

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Modeling mixtures interactions in environmental toxicology

Liu,

Sayes

2024

Environmental Toxicology and Pharmacology

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The elevated toxicity of the biodegradation product (guanylurea) from metformin and the antagonistic pattern recognition of combined toxicity: Insight from the pharmaceutical risk assessment and the simulated wastewater treatment

Cited by 5 publications

References 63 publications

Metformin and guanylurea reduce survival, but have limited sublethal effects in larval zebrafish (Danio rerio)

Metformin and guanylurea reduce survival, but have limited sublethal effects in larval zebrafish (Danio rerio)

Artificial intelligence and machine learning for the optimization of pharmaceutical wastewater treatment systems: a review

Modeling mixtures interactions in environmental toxicology

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