Evidence map›Paper›PMID 41565980›Full record

ArticleScientific reports2026

Distinguishing microplastics from microplastic-like particles in the marine fish from Qatar.

Samah Dib, Arafa Mohamed, Fatima A Al-Khayat, S Veerasingam, V M Aboobacker, Jassim A Al-Khayat, P Vethamony

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Samah DibUNESCO Chair in Marine Sciences, Environmental Science Center, Qatar University, P.O. Box: 2713, Doha, Qatar.
Arafa MohamedDepartment of Biological and Environmental Sciences, Qatar University, P.O. Box: 2713, Doha, Qatar.
Fatima A Al-KhayatDepartment of Biological and Environmental Sciences, Qatar University, P.O. Box: 2713, Doha, Qatar.
S VeerasingamUNESCO Chair in Marine Sciences, Environmental Science Center, Qatar University, P.O. Box: 2713, Doha, Qatar.
V M AboobackerUNESCO Chair in Marine Sciences, Environmental Science Center, Qatar University, P.O. Box: 2713, Doha, Qatar.
Jassim A Al-KhayatUNESCO Chair in Marine Sciences, Environmental Science Center, Qatar University, P.O. Box: 2713, Doha, Qatar.
P VethamonyUNESCO Chair in Marine Sciences, Environmental Science Center, Qatar University, P.O. Box: 2713, Doha, Qatar. pvethamony@qu.edu.qa.

Funding

Qatar University QUCG-ESC-23/24-252
6 · The paper itself

Abstract

Microplastic (MP) pollution poses a significant threat to marine ecosystems. This study assessed MP accumulation in the gastrointestinal tracts of 170 individuals from four commercially important fish species in Qatar along with their level of risk. MP-like particles were extracted via chemical digestion and density separation, and analysed using stereomicroscopy. Fibers were the dominant MP shape, with blue being the most common colour. The polymer composition of MP-like particles was further analysed using µ-Raman spectroscopy, which confirmed only 7 particles (4.12% of the total 170 fish samples) as MPs (> 70% match with polymer library databases). Polymer analysis confirmed the presence of polyethylene (PE) and polypropylene (PP) in the fish digestive tracts. The mean abundance was 0.070 ± 0.090 MPs/g of fish gut, a level relatively low compared to other regions of the Gulf and globally. The herbivorous Siganus canaliculatus ingested more MPs than the three carnivorous species, but this difference was not statistically significant (p > 0.05).

Indexed as

Arabian gulfFish gastrointestinal tractsMicroplasticsRaman spectroscopyRisk assessment

Identifiers

PMID41565980
PMCPMC12901314

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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.