ArticleBMC bioinformatics2022
Assessment of potential human health risks in aquatic products based on the heavy metal hazard decision tree.
Article in BMC bioinformatics, 2022. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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, 16 citations in OpenAlex.
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- An unbiased, sustainable, evidence-informed Universal Food Guide: a timely template for national food guides.Nutrition journal · 2024Review
- Zigzag boron nitride nanotube functionalization as a sensor for the recognition of group IIA (MgJournal of molecular modeling · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundNaturally existing and human-produced heavy metals are released into the environment and cannot be completely decomposed by microorganisms, but they continue to accumulate in water and sediments, causing organisms to be exposed to heavy metals.
resultsThis study designs and proposes heavy metal hazard decision trees for aquatic products, which are divided into seven categories including pelagic fishes, inshore fishes, other fishes, crustaceans, shellfish, cephalopods, and algae. Based on these classifications, representative fresh and processed seafood products are at the root of the heavy metal hazard decision trees. This study uses 2,107 cases of eating 556 cooked fresh or processed seafood product samples. The constructions of the proposed decision trees consist of 12 heavy metals, which include inorganic arsenic (iAs), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), strontium (Sr), thallium (Tl), and zinc (Zn). The heavy metal concentrations in cooked fresh and processed seafood product samples are subjected to a food safety risk assessment.
conclusionsThe results indicate the relationships among the seven categories of aquatic products, the relationships among 12 heavy metals in aquatic products, and the relationships among potential human health risks. Finally, the proposed heavy metal hazard decision trees for aquatic products can be used as a reference model for researchers and engineers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.