Evidence map›Paper›PMID 35317843›Full record

ReviewChinese medicine2022

Strategies for molecular authentication of herbal products: from experimental design to data analysis.

Hoi-Yan Wu, Pang-Chui Shaw

Abstract readReview
In one paragraph

Review in Chinese medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Rapid authentication of endangeredFrontiers in plant science · 2025
    Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
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.

Hoi-Yan WuLi Dak Sum Yip Yio Chin R & D Centre for Chinese Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
Pang-Chui ShawLi Dak Sum Yip Yio Chin R & D Centre for Chinese Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China. pcshaw@cuhk.edu.hk.ORCID http://orcid.org/0000-0001-6848-5073

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular herbal authentication has gained worldwide popularity in the past decade. DNA-based methods, including DNA barcoding and species-specific amplification, have been adopted for herbal identification by various pharmacopoeias. Development of next-generating sequencing (NGS) drastically increased the throughput of sequencing process and has sped up sequence collection and assembly of organelle genomes, making more and more reference sequences/genomes available. NGS allows simultaneous sequencing of multiple reads, opening up the opportunity of identifying multiple species from one sample in one go. Two major experimental approaches have been applied in recent publications of identification of herbal products by NGS, the PCR-dependent DNA metabarcoding and PCR-free genome skimming/shotgun metagenomics. This review provides a brief introduction of the use of DNA metabarcoding and genome skimming/shotgun metagenomics in authentication of herbal products and discusses some important considerations in experimental design for botanical identification by NGS, with a specific focus on quality control, reference sequence database and different taxon assignment programs. The potential of quantification or abundance estimation by NGS is discussed and new scientific findings that could potentially interfere with accurate taxon assignment and/or quantification is presented.

Indexed as

DNA metabarcodingGenome2-IDGenome skimmingHerbal productsKrakenMolecular authenticationNext-generation sequencingQuality control

Identifiers

PMID35317843
PMCPMC8939074

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.