Evidence map›Paper›PMID 26170919›Full record

ArticleExperimental and therapeutic medicine2015

Differential expression and therapeutic efficacy of microRNA-346 in diabetic nephropathy mice.

Yong Zhang, Hou-Qin Xiao, Yang Wang, Zhuo-Shun Yang, Long-Jun Dai, Yan-Cheng Xu

Open access · diamondAbstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 25% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

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  10. [The Role of TGF-β1/SMAD in Diabetic Nephropathy: Mechanisms and Research Development].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023
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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

6 authors at 4 institutions in 1 country.

Yong ZhangDepartment of Endocrinology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China ; Department of Nephrology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, P.R. China.
Hou-Qin XiaoDepartment of Nephrology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, P.R. China.
Yang WangThe Research Center for High Altitude Medicine, Medical College, Qinghai University, Xining, Qinghai 810001, P.R. China.
Zhuo-Shun YangHubei Key Laboratory of Stem Cell Research, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, P.R. China.
Long-Jun DaiHubei Key Laboratory of Stem Cell Research, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, P.R. China ; Department of Surgery, University of British Columbia, Vancouver, BC V5Z 1M9, Canada.
Yan-Cheng XuDepartment of Endocrinology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China.
Hubei University of Medicine · CNQinghai University · CNWuhan University · CNZhongnan Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic nephropathy (DN) is a major cause of end-stage renal disease, in which the SMAD signaling pathway plays an important role. The aim of the present study was to identify differentially expressed microRNAs (miRNAs) during the progression of DN and to investigate a selected miRNA in relation to SMAD3/4 and its therapeutic efficacy. The miRNA microarray was used to identify differentially expressed miRNAs in

Indexed as

diabetesdiabetic nephropathymicroRNA-346microRNA microarray

Identifiers

PMID26170919
PMCPMC4486891
OpenAlexW2087759328

What OpenQuestion holds

Textmetadata
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.