Evidence map›Paper›PMID 36411688›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2022

Alteration in topological organization characteristics of gray matter covariance networks in patients with prediabetes.

Lingling Deng, Huasheng Liu, Wen Liu, Yunjie Liao, Qi Liang, Wei Wang

Open access · greenAbstract read
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 56% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 1 country.

Lingling DengDepartment of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China. 307027521@qq.com.
Huasheng LiuDepartment of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China.
Wen LiuDepartment of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China.
Yunjie LiaoDepartment of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China.
Qi LiangDepartment of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China. csuliangqi10@163.com.
Wei WangDepartment of Radiology, Third Xiangya Hospital, Central South University, Changsha 410013, China.
Central South University · CNThird Xiangya Hospital · CN

Funding

the Major Scientific and Technological Project of Hunan Province 2018SK2010the National Key Research and Development Program 2019YFA0110703
6 · The paper itself

Abstract

objectivesPrediabetes is associated with an increased risk of cognitive impairment and neurodegenerative diseases. However, the exact mechanism of prediabetes-related brain diseases has not been fully elucidated. The brain structure of patients with prediabetes has been damaged to varying degrees, and these changes may affect the topological characteristics of large-scale brain networks. The structural covariance of connected gray matter has been demonstrated valuable in inferring large-scale structural brain networks. The alterations of gray matter structural covariance networks in prediabetes remain unclear. This study aims to examine the topological features and robustness of gray matter structural covariance networks in prediabetes.

methodsA total of 48 subjects were enrolled in this study, including 23 patients with prediabetes (the PD group) and 25 age-and sex-matched healthy controls (the Ctr group). All subjects' high-resolution 3D T

resultsThe network in both groups followed small-world characteristics, showing that Sigma was greater than 1, the Lambda was much higher than 1, and Gamma was close to 1. Compared with the Ctr group, the network of the PD group showed increased Sigma, Lambda, and Gamma across a range of network sparsity. The Gamma of the PD group was significantly higher than that in the Ctr group in the network sparsity range of 0.12-0.16, but there was no difference between the 2 groups (all

conclusionsThe prediabetic gray matter network shows an increased average clustering coefficient and local efficiency, and is more vulnerable to random damage than the healthy control, suggesting that the topological characteristics of the prediabetes grey matter covariant network have changed (network separation enhanced and network robustness reduced), which may provide new insights into the brain damage relevant to the disease.

Indexed as

Gray MatterPrediabetic StateBrainCerebral CortexHumansMagnetic Resonance Imaginggraph theoretical analysisgray matter volumeprediabetesstructural covariance networktopological measures

Identifiers

PMID36411688
PMCPMC10930362
OpenAlexW4309664838

What OpenQuestion holds

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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.