Evidence map›Paper›PMID 34257700›Full record

ArticleComputational and mathematical methods in medicine2021

The Association between the rs312457 Genotype of the SLC16a13 Gene and Diabetes Mellitus in a Chinese Population.

Hui Zheng, Suying Pu, Yu Zhang, Yujuan Fan, Jialin Yang

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 34% 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

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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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
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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 2 institutions in 1 country.

Hui ZhengDepartment of Endocrinology and Metabolism, Minhang Hospital, Fudan University, 170 Xin-Song Road, Shanghai 201199, China.
Suying PuDepartment of Neurology, Shanghai Xuhui District Dahua Hospital, 909 LaoHuMin Road, Shanghai 200237, China.
Yu ZhangDepartment of Endocrinology and Metabolism, Minhang Hospital, Fudan University, 170 Xin-Song Road, Shanghai 201199, China.
Yujuan FanDepartment of Endocrinology and Metabolism, Minhang Hospital, Fudan University, 170 Xin-Song Road, Shanghai 201199, China.
Jialin YangDepartment of Endocrinology and Metabolism, Minhang Hospital, Fudan University, 170 Xin-Song Road, Shanghai 201199, China.ORCID https://orcid.org/0000-0001-6767-9028
Fudan University · CNDahua Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSLC16a genes encode H + -coupled monocarboxylate transporters (MCTs). MCTs are involved in maintaining interstitial fluids' pH and regulating insulin's binding affinity to its receptor, which is a potential mechanism for the onset of diabetes. In this research, we make explorations of the association between the rs312457 genotype of the SLC16a13 gene and diabetes in the Chinese population.

methodsIt included 384 type 2 diabetes patients and 1,468 healthy control subjects in total. We measured the anthropometric parameters, glycaemic index, homeostasis model assessment-B cell (HOMA-%B), lipid profile, and homeostasis model assessment-insulin resistance (HOMA-IR). The associations between the rs312457 genotype and type 2 diabetes were analyzed.

resultsThe rs312457 genotype was markedly in relation to type 2 diabetes (

conclusionOur results revealed that the rs312457 genotype of the SLC16a13 gene was correlated with the development of diabetes mellitus in the Chinese population.

Indexed as

AdultAgedAsian PeopleCase-Control StudiesChinaComputational BiologyDiabetes Mellitus, Type 2FemaleGenetic Predisposition to DiseaseGenotypeHumansInsulin ResistanceMaleMiddle AgedMonocarboxylic Acid TransportersPolymorphism, Single NucleotideMonocarboxylic Acid TransportersSlc16a13 protein, human

Identifiers

PMID34257700
PMCPMC8257359
OpenAlexW3173450099

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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.