ArticleScientific data2025
Global mercury dataset with predicted methylmercury concentrations in seafoods during 1995-2022.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Enzyme-cascade-amplified colorimetric biosensing platform for sub-nanomolar methylmercury in environmental waters.RSC advances · 2026Article
- Global mercury dataset with predicted methylmercury concentrations in seafoods during 1995-2022.Scientific data · 2025Article
- Mercury exposure, epigenetic modifications, and genetic susceptibility: insights from molecular docking and population analysis.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Mercury exposure poses significant threats to human health, particularly in its organic form, methylmercury (MeHg). Diet is the main pathway for human MeHg exposure, especially through seafood consumption. In this context, numerous studies have established seafood MeHg concentration datasets to assess MeHg-related health risks from seafood consumption. However, existing datasets are limited to specific regions and short-term observations, making it difficult to support continuous and dynamic assessments of global MeHg-related health risks. This study takes a bottom-up approach to construct a global seafood MeHg concentration dataset during 1995-2022. Firstly, it compiles a long-term time series marine-scale dataset of seafood MeHg concentrations, based on the reported seafood mercury concentrations from existing literature and machine learning methods. Subsequently, this study used the seafood catch volumes of each nation in different marine areas as weights to estimate the national-scale seafood MeHg concentrations. This dataset can provide essential data support for environmental impact assessment of mercury and its compounds as mentioned in Articles 12 and 19 of the Minamata Convention on Mercury.
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Registered trials
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