Evidence map›Paper›PMID 42292815›Full record

ArticleFrontiers in pharmacology2026

Evaluation of exogenous residual contamination in Traditional Chinese Medicine formula granules and the three-dimensional risk assessment using HI-P-CV method.

Lin Lin, Guangzhen Liu, Lejun Tan, Fengrui Yu, Guixue Mei, Yongqiang Lin

Abstract read
In one paragraph

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

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

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5 · Who and what money

Authors and funding

6 authors.

Lin LinShandong Institute for Food and Drug Control, Jinan, China.
Guangzhen LiuShandong Institute for Food and Drug Control, Jinan, China.
Lejun TanShandong Institute for Food and Drug Control, Jinan, China.
Fengrui YuShandong Institute for Food and Drug Control, Jinan, China.
Guixue MeiShandong Institute for Food and Drug Control, Jinan, China.
Yongqiang LinNational Institutes for Food and Drug Control, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The residues of heavy metals, pesticides and mycotoxins in 42 types of traditional Chinese medicine formula granules (TCMFGs) were determined by inductively coupled plasma mass spectrometry (ICP-MS), high-performance liquid chromatography tandem mass spectrometry (HPLC-MS) and gas chromatography tandem mass spectrometry (GC-MS). The results showed that the detection rate of seven types of heavy metals was 100%. Among the 143 types of pesticides, 78 were detected, with an average detection rate of 24.72%. Of the 57 types of mycotoxins, 14 were detected, with an average detection rate of 38.30%. Using the hazard index method, a three-dimensional risk assessment framework based on hazard index (HI), prevalence (P), and variability (CV) (HI-P-CV framework) is established. The HI values were 0.73 for heavy metals, 0.03 for pesticides and 0.54 for mycotoxins, individually. The CV values were 59.15%, 59.54% and 42.57%, respectively. The model revealed significant variation in contamination levels among three categories of residues in TCMFGs, indicating hidden risks. Cumulative dietary risk assessment identified 18 varieties with potential health risks, including 10 high-risk varieties. The average cumulative dietary risk was 1.3, indicating a relatively high overall risk of exogenous residue contamination in TCMFGs. Profile analysis indicated that varieties with aerial medicinal parts tend to accumulate heavy metals and should be prioritized for heavy metal contamination monitoring. Varieties with underground medicinal parts, which are rich in polysaccharides, are more susceptible to fungi contamination. The detection of banned pesticides and widespread presence of plant growth regulators highlight the need for stricter regulation of pesticide use.

Indexed as

GC-MShazard index methodheavy metalsHI-P-CV three-dimensional evaluationHPLC-MSICP-MSmycotoxinspesticides

Identifiers

PMID42292815
PMCPMC13253469

What Socratic holds

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LicenceCC BY
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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 Socratic graph.