Evidence map›Paper›PMID 41419422›Full record

ArticleGM crops & food2026

Comprehensive risk assessment revealed some physiological indicators responding to various GM-crop consumption.

Yangyi Wang, Ruizhe Wu, Ken Cheng, Dunjie Yao, Qiuhan Wu, Haoyue Yong, Haoyu Sun, Xinwei Zhou, Wanjun Zhang, Rong Yuan and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in GM crops & food, 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

14 authors.

Yangyi WangKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Ruizhe WuKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Ken ChengSchool of Environment, Tsinghua University Beijing, China.
Dunjie YaoKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Qiuhan WuKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Haoyue YongKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Haoyu SunKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Xinwei ZhouKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Wanjun ZhangKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Rong YuanOil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture Wuhan, China.
Fuying MaKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Libin ZhangKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Li SuKey Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology Wuhan, China.
Xinhua ZengOil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetically modified (GM) crops have been provided as food and feed in over 70 countries in the world. But the concern is persisting on their comprehensive effects on human health status as feedstock. Physiological indicators detected in human beings or animals were explored to assess the health status after GM crop consumption. Here, a mammalian physiological indicators data set with seven metrics containing 25 physiological indicators was constructed by extracting the experimental raw data from the open access research articles published from January 2000 to September 2024 on GM maize, rice, and soybean consumption. To overcome the experimental heterogeneity in disparate model animals, limited animal number in each independent research, and statistical errors caused by different statistical methods, the multi-sourced data correlation analysis with DerSimonian and Laird random-effect model was employed. The result revealed that the concentration of glucose increased after nutritionally changed maize consumption (GLU,

Indexed as

Crops, AgriculturalFood, Genetically ModifiedPlants, Genetically ModifiedAnimalsFood SafetyGlycine maxHumansOryzaRisk AssessmentZea maysDerSimonian and Laird random-effects modelGenetically modified crophealth statusphysiological indicatorrisk assessment

Identifiers

PMID41419422
PMCPMC12721096

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LicenceCC BY
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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.