Evidence map›Paper›PMID 34277875›Full record

ArticleReports of biochemistry & molecular biology2021

Uncoupling Protein 2 Expression Modulates Obesity in Chronic Kidney Disease Patients.

Salma Ahmed Shawky, Osama Gaber, Ezzat Mostafa, Walaa Mohamed Sarhan

Open access · goldAbstract read
In one paragraph

Article in Reports of biochemistry & molecular biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

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  4. Coding Variants of theReports of biochemistry & molecular biology · 2022
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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

4 authors at 1 institution in 1 country.

Salma Ahmed ShawkyMedical Biochemistry and Molecular Biology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Osama GaberMedical Biochemistry and Molecular Biology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Ezzat MostafaInternal Medicine Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Walaa Mohamed SarhanMedical Biochemistry and Molecular Biology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Zagazig University · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObesity is a multifactorial metabolic disease resulting from behavioral and genetic factors. Obesity is linked to diabetes mellitus and hypertension, which are considered as major risk factors for chronic kidney disease (CKD); moreover, it has a direct effect on developing CKD and end stage renal disease (ESRD). Here was aimed to examine the association between uncoupling protein 2 (UCP2) gene expression and obesity in CKD patients.

methodsUCP2 gene expression was analyzed by real time polymerase chain reaction (RT-PCR) in 93 participants divided into three groups. The groups included 31 non-obese CKD patients, 31 obese CKD patients, and 31 healthy, age-matched, unrelated volunteers as a control group.

resultsUCP2 gene expression was significantly relevant when comparing the non-obese CKD and obese CKD groups to the control group (p< 0.001). No significant association was found when the groups were compared by gender; Chi-square (X2) was 2.38 and p= 0.304. A significant negative correlation was found between UCP2 gene expression and BMI in CKD (p< 0.05).

conclusionThese results indicate that UCP2 gene expression plays a significant role as a risk factor for obesity in CKD patients.

Indexed as

Chronic Kidney Disease (CKD)ObesityReal-Time Polymerase Chain Reaction (RT-PCR)Uncoupling Protein 2 (UCP2) Gene Expression

Identifiers

PMID34277875
PMCPMC8279717
OpenAlexW3164130508

What OpenQuestion holds

Textmetadata
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Registered trials

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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.