Evidence map›Paper›PMID 33552923›Full record

ArticleToxicology reports2021

Presence of antibacterial substances, nitrofuran metabolites and other chemicals in farmed pangasius and tilapia in Bangladesh: Probabilistic health risk assessment.

Md Mehedi Alam, Mohammad Mahfujul Haque

Abstract read
In one paragraph

Article in Toxicology reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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  3. Review
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  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Md Mehedi AlamDepartment of Aquaculture, Bangladesh Agricultural University, Mymensingh, Bangladesh.
Mohammad Mahfujul HaqueDepartment of Aquaculture, Bangladesh Agricultural University, Mymensingh, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intensive feeding and the use of drugs and other chemicals for enhancing yield characterised commercial pangasius and tilapia aquaculture in Bangladesh. The residual presence of prohibited antibacterial substances, nitrofuran metabolites and other chemicals (ANCs) in fish, and their effect on public health are a concern for consumers. This study collected samples from 15 pangasius and 15 tilapia ponds to assess the contamination of ANCs, including pesticides, dyes and heavy metals in fish flesh, and heavy metals in feed, sediments and water. Antibacterial substances, nitrofuran metabolites and dyes in fish flesh were detected using LC-MS/MS. Organochlorine pesticides and heavy metals were detected applying GC-MS and AAS, respectively. We found very low residue of the most ANCs in pangasius and tilapia flesh, however, both species contained heavy metals, particularly lead (Pb) and chromium (Cr). The level of metal contamination was affected by the age of the pond; the highest concentration of Pb was in pangasius from old ponds (> 10 years), and the highest concentration of Cr was found in pangasius from new ponds (< 10 years), and tilapia from old ponds. The feed sampled in this study, particularly the commercial pellet and farm-made feed, were highly contaminated with heavy metals. Pond water and sediments were contaminated by heavy metals; fish, water and sediment samples from older ponds had higher concentrations of heavy metals. The concentration of these heavy metals in fish flesh above regulatory limits poses potential risks to human health. To ensure the production of safe fish for human consumption, commercial aquaculture in Bangladesh requires a functional regulatory framework.

Indexed as

Antibacterial substancesAquacultureHeavy metalsHuman health risksPesticides

Identifiers

PMID33552923
PMCPMC7844123

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Registered trials

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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.