Evidence map›Paper›PMID 34528222›Full record

ArticlePlanta medica2021

Treating Chronic Wounds Using Photoactive Metabolites: Data Mining the Chinese Pharmacopoeia for Potential Lead Species.

Francesca Scotti, Linru Mou, Chen Huang, Anthony Booker, Caroline Weckerle, Caroline Maake, Michael Heinrich

Open access · bronzeAbstract read
In one paragraph

Article in Planta medica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 28% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Wound healing and photodynamic potential ofFrontiers in pharmacology · 2025
    Article
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 at 2 institutions in 2 countries.

Francesca ScottiResearch Group "Pharmacognosy and Phytotherapy", UCL School of Pharmacy, London, UK.
Linru MouResearch Group "Pharmacognosy and Phytotherapy", UCL School of Pharmacy, London, UK.
Chen HuangResearch Group "Pharmacognosy and Phytotherapy", UCL School of Pharmacy, London, UK.
Anthony BookerResearch Group "Pharmacognosy and Phytotherapy", UCL School of Pharmacy, London, UK.
Caroline WeckerleInstitute of Systematic and Evolutionary Botany, University of Zürich, Zürich, Switzerland.
Caroline MaakeInstitute of Anatomy, University of Zürich, Zürich, Switzerland.
Michael HeinrichResearch Group "Pharmacognosy and Phytotherapy", UCL School of Pharmacy, London, UK.ORCID 0000-0003-2611-6303
University College London · GBUniversity of Zurich · CH

Funding

1284 Velux Stiftung
6 · The paper itself

Abstract

Efficient wound treatment that addresses associated infections and inflammation remains one of the big unmet needs, especially in low- and middle-income countries. One strategy for securing better healthcare can be using medicinal plants if sufficient evidence on their safety and therapeutic benefits can be ascertained. A unique novel opportunity could be photo-enhanced wound treatment with a combination of light-sensitive plant preparations and local exposure to daylight. Data mining strategies using existing resources offer an excellent basis for developing such an approach with many potential plant candidates. In the present analysis, we researched the 535 botanical drugs included in the Chinese pharmacopeia and identified 183 medicinal plant species, 82 for treating open wounds caused by trauma and 101 for inflammatory skin conditions. After further screening for reports on the presence of known photoactive compounds, we determined a core group of 10 scientifically lesser-known botanical species that may potentially be developed into more widely used topical preparations for photodynamic treatment of infected wounds. Our predictive approach may contribute to developing a more evidence-based use of herbal medicines.

Indexed as

Plants, MedicinalChinaData MiningMedicine, TraditionalPlant PreparationsPlant Preparations

Identifiers

PMID34528222
PMCPMC8585569
OpenAlexW3198824838

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.