Evidence map›Paper›PMID 34512547›Full record

ArticleFrontiers in endocrinology2021

Diffusion Tensor Imaging in Rat Models of Preclinical Diabetic Nephropathy: A Preliminary Study.

Xiaoyan Hu, Min Kuang, Bo Peng, Yang Yang, Wei Lin, Wenbo Li, Yinghua Wu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
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

7 authors at 2 institutions in 1 country.

Xiaoyan HuDepartment of Radiology, Chengdu First People's Hospital, Chengdu, China.
Min KuangDepartment of Radiology, Chengdu Second People's Hospital, Chengdu, China.
Bo PengDepartment of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Yang YangDepartment of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Wei LinDepartment of Radiology, Chengdu First People's Hospital, Chengdu, China.
Wenbo LiDepartment of Radiology, Chengdu First People's Hospital, Chengdu, China.
Yinghua WuSichuan General Practitioner Training Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Chengdu Second People's Hospital · CNChengdu University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to investigate the value of diffusion tensor imaging to assess renal injury in a rat model of preclinical diabetic nephropathy. Methods: Twenty-eight male Sprague Dawley rats were divided into two groups: the normal control (NC) group of 10 rats and the diabetic nephropathy (DN) group of 18 rats. Eight weeks after diabetes induction by streptozotocin, 3.0-T magnetic resonance (MR) imaging (b = 0 and 600 s/mm Results: All DN group animals developed hyperglycemia, polyuria, and emaciation. Serum creatinine was not significantly different between the groups ( Conclusions: Increased apparent diffusion coefficients and decreased fractional anisotropy values on diffusion tensor imaging were associated with preclinical DN. Diffusion tensor imaging may be useful in early, non-invasive, quantitative detection, and therapy monitoring of DN.

Indexed as

AnisotropyAnimalsDiabetes Mellitus, ExperimentalDiabetes Mellitus, Type 2Diabetic NephropathiesDiffusion Tensor ImagingMaleRatsRats, Sprague-Dawleyapparent diffusion coefficientdiabetic nephropathydiffusion tensor imagingfractional anisotropykidney

Identifiers

PMID34512547
PMCPMC8429902
OpenAlexW3197927909

What OpenQuestion holds

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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.