Evidence map›Paper›PMID 36005595›Full record

ArticleMetabolites2022

Evaluation of Normalization Approaches for Quantitative Analysis of Bile Acids in Human Feces.

Hans-Frieder Schött, Esther W L Chua, Sartaj Ahmad Mir, Bo Burla, Anne K Bendt, Markus R Wenk

Abstract read
In one paragraph

Article in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Evaluation of normalization strategies for GC-based metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2024
    Article
  6. 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

6 authors.

Hans-Frieder SchöttSingapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore.
Esther W L ChuaSingapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore.ORCID 0000-0002-5049-0920
Sartaj Ahmad MirSingapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore.ORCID 0000-0001-6032-0936
Bo BurlaSingapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore.ORCID 0000-0002-5918-3249
Anne K BendtSingapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore.ORCID 0000-0001-8198-6104
Markus R WenkSingapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative analysis of bile acids in human feces can potentially help to better understand the influence of the gut microbiome and diet on human health. Feces is a highly heterogeneous sample matrix, mainly consisting of water and indigestible solid material (as plant fibers) that show high inter-individual variability. To compare bile acid concentrations among different individuals, a reliable normalization approach is needed. Here, we compared the impact of three normalization approaches, namely sample wet weight, dry weight, and protein concentration, on the absolute concentrations of fecal bile acids. Bile acid concentrations were determined in 70 feces samples from healthy humans. Our data show that bile acid concentrations normalized by the three different approaches are substantially different for each individual sample. Fecal bile acid concentrations normalized by wet weight show the narrowest distribution. Therefore, our analysis will provide the basis for the selection of a suitable normalization approach for the quantitative analysis of bile acids in feces.

Indexed as

bile acidsdry weightfecal lipidshuman feceshuman stoollipidsnormalizationprotein contentwet weight

Identifiers

PMID36005595
PMCPMC9416035

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.