Evidence map›Paper›PMID 33365261›Full record

ArticleMethodsX2021

High-throughput quantification of ochronotic pigment formation in

Jessie Neuckermans, Sien Lequeue, Alan Mertens, Steven Branson, Ulrich Schwaneberg, Joery De Kock

Open access · goldAbstract read
In one paragraph

Article in MethodsX, 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
0.1field-weighted citation impact, top 53% 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, 2 citations in OpenAlex.

  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

6 authors at 2 institutions in 2 countries.

Jessie NeuckermansDepartment of In Vitro Toxicology and Dermato-Cosmetology, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Sien LequeueDepartment of In Vitro Toxicology and Dermato-Cosmetology, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Alan MertensLehrstuhl für Biotechnologie, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany.
Steven BransonDepartment of In Vitro Toxicology and Dermato-Cosmetology, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Ulrich SchwanebergLehrstuhl für Biotechnologie, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany.
Joery De KockDepartment of In Vitro Toxicology and Dermato-Cosmetology, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Vrije Universiteit Brussel · BERWTH Aachen University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

4-hydroxyphenylpyruvate dioxygenase (HPD) is a key enzyme in the catabolism of tyrosine and therefore of great importance as a drug target to treat tyrosine-related inherited metabolic disorders (TIMD). Inhibition of this enzyme is therapeutically applied to prevent accumulation of toxic metabolites in TIMD patients. Nowadays an ex-herbicide, nitisinone, is used for this purpose and many more inhibitors are being explored and need to be tested. Here, we describe a colorimetric bacterial whole-cell screening system that allows quantifying the inhibitory effects of new human HPD inhibitors in a high-throughput and robust fashion. For this high-throughput screening (HTS) system we rely on the capability of recombinant

Indexed as

4-Hydroxyphenylpyruvate dioxygenaseBacterial cell cultureColorimetricHigh-throughput screeningInhibitor testingIn VitroOchronotic pigmentTyrosinemia

Identifiers

PMID33365261
PMCPMC7749435
OpenAlexW3112255398

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.