Evidence map›Paper›PMID 38333558›Full record

ReviewPsychoradiology2024

Exploring Alzheimer's disease: a comprehensive brain connectome-based survey.

Lu Zhang, Junqi Qu, Haotian Ma, Tong Chen, Tianming Liu, Dajiang Zhu

Erratum issuedOpen access · diamondAbstract readReview
In one paragraph

Review in Psychoradiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
6.5field-weighted citation impact, top 3% 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, 19 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Lu ZhangDepartment of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.ORCID https://orcid.org/0000-0001-9072-5854
Junqi QuDepartment of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
Haotian MaDepartment of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
Tong ChenDepartment of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
Tianming LiuDepartment of Computer Science, The University of Georgia, Athens, GA 30602, USA.
Dajiang ZhuDepartment of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
The University of Texas at Arlington · USUniversity of Georgia · US

Funding

Mapping Trajectories of Alzheimer's Progression via Personalized Brain Anchor-nodesR01AG075582 · NIA · UNIVERSITY OF TEXAS ARLINGTON · PI Gang Li, Dajiang Zhu · 2022 to 2026
$2.7M
Developing an Individualized Deep Connectome Framework for ADRD AnalysisRF1NS128534 · NINDS · UNIVERSITY OF TEXAS ARLINGTON · PI LI, GANG, LIU, TIANMING · 2022 to 2022
$1.7M
NIA NIH HHS R01 AG075582NINDS NIH HHS RF1 NS128534
6 · The paper itself

Abstract

Dementia is an escalating global health challenge, with Alzheimer's disease (AD) at its forefront. Substantial evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent dissemination throughout the broader area along the brain network, leading to disruptions in both individual brain regions and their interconnections. Although a comprehensive understanding of the neurodegeneration-brain network link is lacking, it is undeniable that brain networks play a pivotal role in the development and progression of AD. To thoroughly elucidate the intricate network of elements and connections constituting the human brain, the concept of the brain connectome was introduced. Research based on the connectome holds immense potential for revealing the mechanisms underlying disease development, and it has become a prominent topic that has attracted the attention of numerous researchers. In this review, we aim to systematically summarize studies on brain networks within the context of AD, critically analyze the strengths and weaknesses of existing methodologies, and offer novel perspectives and insights, intending to serve as inspiration for future research.

Indexed as

Alzheimer's diseasebrain-connectomedeep graph neural networksgraph theory

Identifiers

PMID38333558
PMCPMC10848159
OpenAlexW4390857929

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.