Evidence map›Paper›PMID 39035776›Full record

ArticleFrontiers in neuroscience2024

Topological regularization of networks in temporal lobe epilepsy: a structural MRI study.

Yini Chen, Lu Sun, Shiyao Wang, Beiyan Guan, Jingyu Pan, Yiwei Qi, Yufei Li, Nan Yang, Hongsen Lin, Ying Wang and 1 more

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. Review
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

11 authors.

Yini Chen *Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
Lu Sun *Department of Neurology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Shiyao Wang *Department of Neurology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Beiyan GuanDepartment of Neurology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Jingyu PanDepartment of Neurology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Yiwei QiDepartment of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
Yufei LiDepartment of Neurology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Nan YangDepartment of Neurology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Hongsen LinDepartment of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
Ying WangDepartment of Neurology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Bo SunDepartment of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Patients with temporal lobe epilepsy (TLE) often exhibit neurocognitive disorders; however, we still know very little about the pathogenesis of cognitive impairment in patients with TLE. Therefore, our aim is to detect changes in the structural connectivity networks (SCN) of patients with TLE. Methods: Thirty-five patients with TLE were compared with 47 normal controls (NC) matched according to age, gender, handedness, and education level. All subjects underwent thin-slice T1WI scanning of the brain using a 3.0 T MRI. Then, a large-scale structural covariance network was constructed based on the gray matter volume extracted from the structural MRI. Graph theory was then used to determine the topological changes in the structural covariance network of TLE patients. Results: Although small-world networks were retained, the structural covariance network of TLE patients exhibited topological irregularities in regular architecture as evidenced by an increase in the small world properties ( Conclusion: The objective of this study is to investigate the potential neurobiological mechanisms associated with temporal lobe epilepsy through graph theoretical analysis, and to examine the topological characteristics and robustness of gray matter structural networks at the network level.

Indexed as

connectomegraph theorygray matter volumestructural covariance networktemporal lobe epilepsy

Identifiers

PMID39035776
PMCPMC11259028

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