Evidence map›Paper›PMID 33246128›Full record

ArticleNeuroImage2021

Spectral guided sparse inverse covariance estimation of metabolic networks in Parkinson's disease.

Phoebe G Spetsieris, David Eidelberg

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

17 citing papers in PubMed, 26 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Functional Brain Networks to Evaluate Treatment Responses in Parkinson's Disease.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023
    Article
  5. Article
  6. Review
  7. Article
  8. Stereotyped Relationship Between Motor and Cognitive Metabolic Networks in Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2022
    Article
  9. Article
  10. Early disturbance of dynamic synchronization and neurovascular coupling in cognitively normal Parkinson's disease.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022
    Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. 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

2 authors at 1 institution in 1 country.

Phoebe G SpetsierisCenter for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY 11030, USA.
David EidelbergCenter for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY 11030, USA. Electronic address: deidelbe@northwell.edu.
Center for Neurosciences · US

Funding

Statistics and Data Management CoreP50NS071675 · NINDS · FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH · PI EIDELBERG, DAVID · 2010 to 2014
$9.3M
NINDS NIH HHS P50 NS071675
6 · The paper itself

Abstract

In neurodegenerative disorders, a clearer understanding of the underlying aberrant networks facilitates the search for effective therapeutic targets and potential cures. [

Indexed as

AdultAgedBrainCase-Control StudiesFemaleFluorodeoxyglucose F18Functional NeuroimagingHumansImage Processing, Computer-AssistedMaleMiddle AgedNeural PathwaysParkinson DiseasePositron-Emission TomographyPrincipal Component AnalysisRadiopharmaceuticalsFluorodeoxyglucose F18RadiopharmaceuticalsGraphical lasso (GLASSO)Metabolic functional connectivityParkinson's disease (PD)Positron emission tomography (PET)Principal component analysis (PCA)Sparse inverse covariance estimation (SICE)

Identifiers

PMID33246128
PMCPMC8409106
OpenAlexW3109648071

What OpenQuestion holds

Textmetadata
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.