Evidence map›Paper›PMID 40959230›Full record

ArticlePathogens & immunity2019

Identification and Quantification by Targeted Metabolomics of Antibiotic-Responsive Urinary Small Phenolic Molecules Derived from the Intestinal Microbiota in Mice.

Mark E Obrenovich, George E Jaskiw, Renliang Zhang, Belinda Willard, Curtis J Donskey

Abstract read
In one paragraph

Article in Pathogens & immunity, 2019. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Mark E ObrenovichPathology and Laboratory Medicine Service; Louis Stokes Cleveland Department of Veterans Affairs Medical Center; Cleveland, Ohio.
George E JaskiwPsychiatry Service, Louis Stokes Cleveland Department of Veteran's Affairs Medical Center, Cleveland, Ohio.
Renliang ZhangProteomics and Metabolomics Core; Lerner Research Institute; Cleveland Clinic Foundation; Cleveland, Ohio.
Belinda WillardProteomics and Metabolomics Core; Lerner Research Institute; Cleveland Clinic Foundation; Cleveland, Ohio.
Curtis J DonskeySchool of Medicine; Case Western Reserve University; Cleveland, Ohio.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Urinary levels of small molecules generated by the gut microbiota (GMB) constitute potential biomarkers for the state of the GMB. Such metabolites include numerous small phenolic molecules linked to anaerobic bacteria, particularly Methods: CF-1 (female mice) were treated over 2 consecutive days with either i) vehicle, ii) one of 2 different antibiotic regimens (clindamycin or piperacillin/tazobactam) known to inhibit intestinal anaerobes and promote colonization by Results: We identified over 25 compounds, many of which had not been previously reported in mouse urine. Eleven small phenolic molecules showed significant antibiotic-related changes. Urinary levels of the hydroxyphenylpropionic acids were suppressed by clindamycin and pipera-cillin/tazobactam treatment, but were elevated in aztreonam-treated mice. In addition, aztreonam treatment was associated with elevated levels of the dihydroxyhydrocinnamic acids. Conclusions: Profiles of differential changes in urinary small phenolic molecules may provide an index of anaerobic bacterial species in the GMB and could prove useful in monitoring susceptibility to overgrowth of pathogens such as

Indexed as

anaerobesantibioticsautismaztreonamclindamycinmicemicrobiotaphenolicpiperacillin/tazobactamschizophrenia

Identifiers

PMID40959230
PMCPMC12435579

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.