Evidence map›Paper›PMID 35423743›Full record

ArticleRSC advances2021

Total and bioaccessible heavy metals in cabbage from major producing cities in Southwest China: health risk assessment and cytotoxicity.

Mengying Li, Yishu Qin, Chengchen Wang, Kun Wang, Zhihua Deng, Wumei Xu, Ping Xiang, Lena Q Ma

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 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
1.2field-weighted citation impact, top 24% of its field
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, 29 citations in OpenAlex.

  1. Article
  2. Article
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  4. Review
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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

8 authors at 3 institutions in 2 countries.

Mengying LiInstitute of Environmental Remediation and Human Health, School of Ecology and Environment, Southwest Forestry University Kunming 650224 China ping_xiang@126.com.
Yishu QinInstitute of Environmental Remediation and Human Health, School of Ecology and Environment, Southwest Forestry University Kunming 650224 China ping_xiang@126.com.
Chengchen WangInstitute of Environmental Remediation and Human Health, School of Ecology and Environment, Southwest Forestry University Kunming 650224 China ping_xiang@126.com.
Kun WangInstitute of Environmental Remediation and Human Health, School of Ecology and Environment, Southwest Forestry University Kunming 650224 China ping_xiang@126.com.
Zhihua DengInstitute of Environmental Remediation and Human Health, School of Ecology and Environment, Southwest Forestry University Kunming 650224 China ping_xiang@126.com.
Wumei XuYunnan Provincial Observation and Research Station of Soil Degradation and Restoration for Cultivating Plateau Traditional Chinese Medicinal Plants, Yunnan Normal University Kunming 650500 China.
Ping XiangInstitute of Environmental Remediation and Human Health, School of Ecology and Environment, Southwest Forestry University Kunming 650224 China ping_xiang@126.com.ORCID https://orcid.org/0000-0002-0870-8551
Lena Q MaInstitute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University Hangzhou 310058 China lqma@zju.edu.cn.
Kunming University · CNHangzhou Academy of Agricultural Sciences · CNYunnan Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Green leafy vegetables are economical and nutritious, but they may be contaminated with heavy metals. In this study, we assessed the total and bioaccessible concentrations of As, Cd, Pb and Cr in a popular vegetable cabbage (

Identifiers

PMID35423743
PMCPMC8697116
OpenAlexW3149496542

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.