Evidence map›Paper›PMID 33770452›Full record

ArticlePharmaceutical biology2021

Anti-inflammatory, expectorant, and antitussive properties of

Jin-Ryul Hu, Chul-Jong Jung, Seong-Min Ku, Dae-Hwa Jung, Khawaja Muhammad Imran Bashir, Sae-Kwang Ku, Jae-Suk Choi

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Antioxidants (Basel, Switzerland) · 2022
    Article
  4. Article
  5. 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

7 authors at 2 institutions in 1 country.

Jin-Ryul HuDepartment of Histology and Anatomy, College of Korean Medicine, Daegu Haany University, Gyeongsan-si, Republic of Korea.
Chul-Jong JungOkchundang Inc, Ulsan, Republic of Korea.
Seong-Min KuOkchundang Inc, Ulsan, Republic of Korea.
Dae-Hwa JungDepartment of Pharmaceutical Engineering, Daegu Haany University, Gyeongsan, Republic of Korea.
Khawaja Muhammad Imran BashirGerman Engineering Research Center for Life Science Technologies in Medicine and Environment, Busan, Republic of Korea.ORCID https://orcid.org/0000-0002-6830-2588
Sae-Kwang KuDepartment of Histology and Anatomy, College of Korean Medicine, Daegu Haany University, Gyeongsan-si, Republic of Korea.ORCID https://orcid.org/0000-0003-1269-3804
Jae-Suk ChoiDepartment of in Food Biotechnology, College of Medical and Life Sciences, Silla University, Busan, Republic of Korea.ORCID https://orcid.org/0000-0002-8151-6054
Daegu Haany University · KRSilla University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

context

objectiveThe anti-inflammatory, expectorant, and antitussive properties of KOG were examined using animal models of respiratory diseases. MATERIALS AND

methodsKOG (100, 200, and 400 mg/kg) was orally administered to ICR mice (

resultsKOG (400 mg/kg) treated mice showed 31.29% and 30.72% (

conclusionsKOG may be a potential therapeutic agent for the treatment of various respiratory diseases, particularly those caused by environmental toxins.

Indexed as

Administration, OralAnimalsAnti-Inflammatory AgentsAntitussive AgentsCoughDisease Models, AnimalDose-Response Relationship, DrugExpectorantsInflammationMaleMiceMice, Inbred ICRPhytotherapyPlant ExtractsAnti-Inflammatory AgentsAntitussive AgentsExpectorantsPlant Extractsrespiratory diseaserodent experimentTraditional mixed herb

Identifiers

PMID33770452
PMCPMC8008926
OpenAlexW3138357071

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.