Evidence map›Paper›PMID 36176461›Full record

ReviewFrontiers in endocrinology2022

Review of

Asma Sellami, Manon Réau, Matthieu Montes, Nathalie Lagarde

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. SynergisticiScience · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. VenomPred 2.0: A NovelJournal of chemical information and modeling · 2024
    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

4 authors at 1 institution in 1 country.

Asma SellamiLaboratoire GBCM, EA 7528, Conservatoire National des Arts et Métiers, Hésam Université, Paris, France.
Manon RéauLaboratoire GBCM, EA 7528, Conservatoire National des Arts et Métiers, Hésam Université, Paris, France.
Matthieu MontesLaboratoire GBCM, EA 7528, Conservatoire National des Arts et Métiers, Hésam Université, Paris, France.
Nathalie LagardeLaboratoire GBCM, EA 7528, Conservatoire National des Arts et Métiers, Hésam Université, Paris, France.
Conservatoire National des Arts et Métiers · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Being in the center of both therapeutic and toxicological concerns, NRs are widely studied for drug discovery application but also to unravel the potential toxicity of environmental compounds such as pesticides, cosmetics or additives. High throughput screening campaigns (HTS) are largely used to detect compounds able to interact with this protein family for both therapeutic and toxicological purposes. These methods lead to a large amount of data requiring the use of computational approaches for a robust and correct analysis and interpretation. The output data can be used to build predictive models to forecast the behavior of new chemicals based on their

Indexed as

Drug DiscoveryPesticidesHigh-Throughput Screening AssaysLigandsReceptors, Cytoplasmic and NuclearLigandsPesticidesReceptors, Cytoplasmic and Nucleardockingendocrine disrupting chemicalsin siliconuclear receptorspharmacophore modelQSAR

Identifiers

PMID36176461
PMCPMC9513233
OpenAlexW4296017871

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.