Evidence map›Paper›PMID 39055217›Full record

ArticleFood science & nutrition2024

Bee (

Hyun-Jun Jang, Hyun-Yong Kim, Ji Hyo Lyu, Subramanian Muthamil, Ung Cheol Shin, Hyo Seon Kim, Jieun Jeong, Suwhan Chang, Yun Kyung Lee, Jun Hong Park

Abstract read
In one paragraph

Article in Food science & nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Bee (Food science & nutrition · 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

10 authors.

Hyun-Jun JangHerbal Medicine Resources Research Center Korea Institute of Oriental Medicine Naju Korea.ORCID https://orcid.org/0000-0002-2261-0067
Hyun-Yong KimHerbal Medicine Resources Research Center Korea Institute of Oriental Medicine Naju Korea.
Ji Hyo LyuHerbal Medicine Resources Research Center Korea Institute of Oriental Medicine Naju Korea.
Subramanian MuthamilHerbal Medicine Resources Research Center Korea Institute of Oriental Medicine Naju Korea.
Ung Cheol ShinHerbal Medicine Resources Research Center Korea Institute of Oriental Medicine Naju Korea.
Hyo Seon KimHerbal Medicine Resources Research Center Korea Institute of Oriental Medicine Naju Korea.
Jieun JeongLaboratory of Integrative Oncolomics, Department of Biomedical Science, College of Medicine University of Ulsan Seoul Korea.
Suwhan ChangLaboratory of Integrative Oncolomics, Department of Biomedical Science, College of Medicine University of Ulsan Seoul Korea.
Yun Kyung LeeLaboratory of Integrative Oncolomics, Department of Biomedical Science, College of Medicine University of Ulsan Seoul Korea.
Jun Hong ParkHerbal Medicine Resources Research Center Korea Institute of Oriental Medicine Naju Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cachexia is associated with various diseases, such as heart disease, infectious disease, and cancer. In particular, cancer-associated cachexia (CAC) accounts for more than 20% of mortality in cancer patients worldwide. Adipose tissue in CAC is characterized by adipocyte atrophy, mainly due to excessively increased lipolysis and impairment of adipogenesis. CAC is well known for the loss of skeletal muscle mass and/or fat mass. CAC induces severe metabolic alterations, including protein, lipid, and carbohydrate metabolism. The objectives of this study were to evaluate the effects of bee wax (

Indexed as

adipocytesadipogenesisbee waxcancer‐associated cachexialipolysisoxygen consumption

Identifiers

PMID39055217
PMCPMC11266878

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.