Evidence map›Paper›PMID 28559960›Full record

ReviewAmerican journal of translational research2017

Medicinal plants for the treatment of obesity: ethnopharmacological approach and chemical and biological studies.

Luciano Mamede de Freitas Junior, Eduardo B de Almeida

Open access · greenAbstract readReview
In one paragraph

Review in American journal of translational research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

34 citing papers in PubMed, 73 citations in OpenAlex.

  1. Trial
  2. Real-time PCR to targetFood chemistry. Molecular sciences · 2026
    Article
  3. A Herbal Pair ofFood science & nutrition · 2026
    Article
  4. Pilot Trial ofCurrent developments in nutrition · 2026
    Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Food science & nutrition · 2024
    Article
  10. Review
  11. Article
  12. Review
  13. Review
  14. Review
  15. In Vivo Pharmacodynamics ofPharmaceuticals (Basel, Switzerland) · 2023
    Article
  16. Article
  17. Heliyon · 2023
    Article
  18. The Antioxidant Activity ofAntioxidants (Basel, Switzerland) · 2022
    Article
  19. Deep ensemble learning for automatic medicinal leaf identification.International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management · 2022
    Article
  20. 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

2 authors at 2 institutions in 2 countries.

Luciano Mamede de Freitas JuniorFederal University of Maranhao, Biological and Health Sciences CenterAv. dos Portugueses, 1966, Campus do Bacanga, CEP 65085-580, São Luís, MA, Brazil.
Eduardo B de AlmeidaLaboratory of Botanical Studies, Biological and Health Sciences CenterAv. dos Portugueses, 1966, Campus do Bacanga, CEP 65085-580, São Luís, MA, Brazil.
Portuguese Army · PTUniversidade Federal do Maranhão · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity is a global epidemic that has shown a steady increase in morbimortality indicators; it is considered a social problem and entails serious health risks. One of the alternatives in the treatment of obesity is the traditional use of medicinal plants, which supports the research and development of obesity phytotherapy. In this article, we provide information about ethnopharmacological species used to treat obesity, through an electronic search of the periodical databases

Indexed as

anti-obesity medicinesreduction dietWeight loss

Identifiers

PMID28559960
PMCPMC5446492
OpenAlexW2954597130

What OpenQuestion holds

Textmetadata
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.