Evidence map›Paper›PMID 27126880›Full record

ReviewDiabetes & metabolism journal2016

Serotonin as a New Therapeutic Target for Diabetes Mellitus and Obesity.

Chang Myung Oh, Sangkyu Park, Hail Kim

Open access · goldAbstract readReview
In one paragraph

Review in Diabetes & metabolism journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed
11.3field-weighted citation impact, top 1% 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

59 citing papers in PubMed, 119 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

3 authors at 3 institutions in 1 country.

Chang Myung OhDepartment of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Sangkyu ParkDepartment of Biochemistry, Catholic Kwandong University College of Medicine, Gangneung, Korea.
Hail KimGraduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea. hailkim@kaist.edu.ORCID http://orcid.org/0000-0002-6652-1349
Catholic Kwandong University · KRKorea Advanced Institute of Science and Technology · KRSeoul National University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Serotonin (5-hydroxytryptamine [5-HT]) is a monoamine that has various functions in both neuronal and non-neuronal systems. In the central nervous system, 5-HT regulates mood and feeding behaviors as a neurotransmitter. Thus, there have been many trials aimed at increasing the activity of 5-HT in the central nervous system, and some of the developed methods are already used in the clinical setting as anti-obesity drugs. Unfortunately, some drugs were withdrawn due to the development of unwanted peripheral side effects, such as valvular heart disease and pulmonary hypertension. Recent studies revealed that peripheral 5-HT plays an important role in metabolic regulation in peripheral tissues, where it suppresses adaptive thermogenesis in brown adipose tissue. Inhibition of 5-HT synthesis reduced the weight gain and improved the metabolic dysfunction in a diet-induced obesity mouse model. Genome-wide association studies also revealed genetic associations between the serotonergic system and obesity. Several genetic polymorphisms in tryptophan hydroxylase and 5-HT receptors were shown to have strong associations with obesity. These results support the clinical significance of the peripheral serotonergic system as a therapeutic target for obesity and diabetes.

Indexed as

Diabetes mellitusObesitySerotonin

Identifiers

PMID27126880
PMCPMC4853228
OpenAlexW2342631563

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.