Evidence map›Paper›PMID 29326584›Full record

ArticleFrontiers in pharmacology2017

A Combined LC-MS Metabolomics- and 16S rRNA Sequencing Platform to Assess Interactions between Herbal Medicinal Products and Human Gut Bacteria

Eva-Maria Pferschy-Wenzig, Kaisa Koskinen, Christine Moissl-Eichinger, Rudolf Bauer

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2017. 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
1.3field-weighted citation impact, top 19% 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

10 citing papers in PubMed, 25 citations in OpenAlex.

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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

4 authors at 3 institutions in 1 country.

Eva-Maria Pferschy-WenzigDepartment of Pharmacognosy, Institute of Pharmaceutical Sciences, Universtity of Graz, Graz, Austria.
Kaisa KoskinenSection of Infectious Diseases and Tropical Medicine, Department of Internal Medicine, Medical University of Graz, Graz, Austria.
Christine Moissl-EichingerSection of Infectious Diseases and Tropical Medicine, Department of Internal Medicine, Medical University of Graz, Graz, Austria.
Rudolf BauerDepartment of Pharmacognosy, Institute of Pharmaceutical Sciences, Universtity of Graz, Graz, Austria.
University of Graz · ATBioTechMed-Graz · ATMedical University of Graz · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Herbal preparations are complex mixtures of natural products, many of which are able to reach the distal gut due to low oral bioavailability. There, they can influence the microbial communities, and can be metabolized into potentially absorbable bioactive compounds by the intestinal bacteria. This aspect has often been disregarded when searching for the active principles of medicinal plants and herbal medicinal products. The aim of this study was to establish an interdisciplinary platform to unravel interactions of herbal medicine and intestinal microbiota, using a combined LC-MS metabolomics and 16S rRNA microbiome sequencing approach. Willow bark extract (WBE), a herbal medicinal product with a long history of traditional use and a well-established anti-inflammatory activity, was incubated with human fecal suspension under anoxic conditions. Samples were taken after 0.5, 4, and 24 h of incubation. Microbiome analyses revealed that incubation with WBE had a marked effect on microbial community composition and functions. For example, the proportion of

Indexed as

16S rRNA sequencinggut microbiomeherbal medicinal producthuman gut bacteriaLC-MS metabolomicswillow bark extract

Identifiers

PMID29326584
PMCPMC5733343
OpenAlexW2774055894

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.