Evidence map›Paper›PMID 28507477›Full record

ArticleEXCLI journal2017

Enzymatic hydrolysate from velvet antler suppresses adipogenesis in 3T3-L1 cells and attenuates obesity in high-fat diet-fed mice.

Yuling Ding, Yanmei Wang, Byong-Tae Jeon, Sang-Ho Moon, Seung-Hong Lee

Open access · greenAbstract read
In one paragraph

Article in EXCLI journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.7field-weighted citation impact, top 23% 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

12 citing papers in PubMed, 13 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Yuling DingDepartment of Animal Bio and Applied Chemistry, Konkuk University, Chungju, 27478, Republic of Korea.
Yanmei WangJilin Sino-Rok Institue of Animal Science, Changchun, 130-600, China.
Byong-Tae JeonDivision of Food Bioscience and Korea Nokyong Research Center, Konkuk University, Chungju, 27478, Republic of Korea.
Sang-Ho MoonDivision of Food Bioscience and Korea Nokyong Research Center, Konkuk University, Chungju, 27478, Republic of Korea.
Seung-Hong LeeDivision of Food Bioscience and Korea Nokyong Research Center, Konkuk University, Chungju, 27478, Republic of Korea.
Konkuk University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of the current study was to investigate the potential anti-obesity activity of an enzymatic hydrolysate of velvet antler in inhibiting adipogenesis in 3T3-L1 cells and in high-fat diet (HFD)-fed obese mice. The enzymatic hydrolysate was prepared using the commercial food grade protease, Protamex. The velvet antler Protamex hydrolysate (VAPH) indicated profound inhibitory effects on adipogenesis dose-dependently by decreasing the accumulation of triglycerides and down-regulating expression levels of adipogenesis-related proteins C/EBPα, SREBP-1, and PPARγ. In a mouse model of HFD-induced obesity, oral administration of VAPH (100 and 300 mg/kg for 13 weeks) significantly reduced the body weight gain that had resulted from the HFD. VAPH treatment also lowered the serum glucose and triglyceride levels, while increasing the HDL-C level. Furthermore, the treatment greatly reduced hepatic lipid droplet accumulation as well as the size of adipocytes. Current findings demonstrate that VAPH has profound anti-obesity effects and could be an effective candidate for preventing obesity and obesity-related chronic diseases.

Indexed as

3T3-L1 cellsanti-obesity effectenzymatic hydrolysatehigh-fat dietvelvet antler

Identifiers

PMID28507477
PMCPMC5427470
OpenAlexW2766019596

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.