Evidence map›Paper›PMID 31011947›Full record

ArticleBrain imaging and behavior2020

Altered large-scale functional brain networks in neurological Wilson's disease.

Rixing Jing, Yongsheng Han, Hewei Cheng, Yongzhu Han, Kai Wang, Daniel Weintraub, Yong Fan

Open access · greenAbstract read
In one paragraph

Article in Brain imaging and behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 19% 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

13 citing papers in PubMed, 21 citations in OpenAlex.

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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

7 authors at 5 institutions in 2 countries.

Rixing JingNational Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Yongsheng HanInstitute of Neurology, Anhui University of Chinese Medicine, Hefei, Anhui Province, China.
Hewei ChengDepartment of Biomedical Engineering, School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing, China.
Yongzhu HanInstitute of Neurology, Anhui University of Chinese Medicine, Hefei, Anhui Province, China.
Kai WangDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China.
Daniel WeintraubSection of Geriatric Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Yong FanDepartment of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. yong.fan@ieee.org.ORCID http://orcid.org/0000-0001-9869-4685
Anhui University of Traditional Chinese Medicine · CNUniversity of Pennsylvania · USAnhui Medical University · CNChinese Academy of Sciences · CNChongqing University of Posts and Telecommunications · CN

Funding

Personalized Functional Network Modeling to Characterize and Predict Psychopathology in YouthR01EB022573 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI Yong Fan, Theodore Satterthwaite · 2016 to 2026
$6.0M
Center for the Development of Novel Medications for Cocaine DependenceU54DA039002 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI KAMPMAN, KYLE MATTHEW · 2014 to 2018
$5.1M
Targeting dopamine D3 receptors in cocaine addictionR01DA039215 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI CHILDRESS, ANNA ROSE · 2016 to 2019
$2.5M
Anhui Provincial Science and Technology Project 15011d04009Clinical Research Key Project of Anhui University of Chinese Medicine 2014lckf02006National Basic Research Program of China 2015CB856404National Natural Science Foundation of China (CN) 61473296NIBIB NIH HHS R01 EB022573NIDA NIH HHS R01 DA039215NIDA NIH HHS U54 DA039002NIH HHS EB022573
6 · The paper itself

Abstract

Wilson's disease patients with neurological symptoms have motor symptoms and cognitive deficits, including frontal executive, visuospatial processing, and memory impairments. Although the brain structural abnormalities associated with Wilson's disease have been documented, it remains largely unknown how Wilson's disease affects large-scale functional brain networks. In this study, we investigated functional brain networks in Wilson's disease. Particularly, we analyzed resting state functional magnetic resonance images of 30 Wilson's disease patients and 26 healthy controls. First, functional brain networks for each participant were extracted using an independent component analysis method. Then, a computationally efficient pattern classification method was developed to identify discriminative brain functional networks associated with Wilson's disease. Experimental results indicated that Wilson's disease patients, compared with healthy controls, had altered large-scale functional brain networks, including the dorsal anterior cingulate cortex and basal ganglia network, the middle frontal gyrus, the dorsal striatum, the inferior parietal lobule, the precuneus, the temporal pole, and the posterior lobe of cerebellum. Classification models built upon these networks distinguished between neurological WD patients and HCs with accuracy up to 86.9% (specificity: 86.7%, sensitivity: 89.7%). The classification scores were correlated with the United Wilson's Disease Rating Scale measures and durations of disease of the patients. These results suggest that Wilson's disease patients have multiple aberrant brain functional networks, and classification scores derived from these networks are associated with severity of clinical symptoms.

Indexed as

Hepatolenticular DegenerationNervous System DiseasesBrainGray MatterHumansMagnetic Resonance ImagingBiomarkersFunctional magnetic resonance imagesLarge-scale functional brain networksMachine learningWilson’s disease

Identifiers

PMID31011947
PMCPMC6810801
OpenAlexW2941718088

What OpenQuestion holds

Textmetadata
LicenceTDM
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.