Article in Journal of medical imaging (Bellingham, Wash.), 2024. 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
–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.
Kuan-Jui SuTulane University, School of Medicine, Center for Biomedical Informatics and Genomics, New Orleans, Louisiana, United States.
Hui ShenTulane University, School of Medicine, Center for Biomedical Informatics and Genomics, New Orleans, Louisiana, United States.
Hong-Wen DengTulane University, School of Medicine, Center for Biomedical Informatics and Genomics, New Orleans, Louisiana, United States.
Yu-Ping WangTulane University, Department of Biomedical Engineering, New Orleans, Louisiana, United States.
Funding
Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Ning Liu · 2016 to 2026
$25.3M
Trans-omics Integration of Multi-omics Studies for OsteoporosisU19AG055373 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI HONG-WEN DENG · 2017 to 2026
$24.3M
Transcranial Direct Current Stimulation for Treatment of Auditory Verbal HalluciP20GM103472 · NIGMS · THE MIND RESEARCH NETWORK · PI BEDRICK, EDWARD J · 2012 to 2017
$14.3M
Multivariate methods for identifying multitask/multimodal brain imaging biomarkersR01EB006841 · NIBIB · THE MIND RESEARCH NETWORK · PI VINCE D CALHOUN, Sergey Plis · 2007 to 2026
$9.8M
Intensive Lifestyle Intervention, Metabolomics, and Risk of Frailty Fracture in Overweight or Obese Patients with Type 2 DiabetesR01AG068232 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI JOHNSON, KAREN C, ZHAO, QI · 2021 to 2025
$3.1M
Identification of Metabolomic Profiles for Sarcopenia Traits in Older Whites and BlacksR01AG061917 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI SHEN, HUI, ZHAO, QI · 2019 to 2023
$3.0M
Unified multivariate data-driven solutions for static and dynamic brain connectivityR01EB020407 · NIBIB · THE MIND RESEARCH NETWORK · PI ADALI, TULAY, CALHOUN, VINCE D · 2015 to 2018
$2.7M
Integration of brain imaging with genomic and epigenomic dataR01MH104680 · NIMH · TULANE UNIVERSITY OF LOUISIANA · PI CALHOUN, VINCE D, DENG, HONG-WEN · 2014 to 2017
$2.1M
Integration of fMRI imaging, genomics, network and biological knowledgeR01MH107354 · NIMH · TULANE UNIVERSITY OF LOUISIANA · PI WANG, YU-PING · 2015 to 2018
$1.9M
Integration of multiscale genomic data for comprehensive analysis of complex diseR01GM109068 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI WANG, YU-PING · 2014 to 2018
$1.6M
Integration of brain imaging and multi-omics data for improved diagnosis and prediction of mental disordersR56MH124925 · NIMH · TULANE UNIVERSITY OF LOUISIANA · PI WANG, YU-PING · 2021 to 2022
Purpose: Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been observed in children, in which high connectivity among all brain regions changes to a more modular structure with maturation. We examine FC changes in older adults after 2 years of aging in the UK Biobank (UKB) longitudinal cohort. Approach: We process fMRI connectivity data using the Power264 atlas and then test whether the average internetwork FC changes in the 2722-subject longitudinal cohort are statistically significant using a Bonferroni-corrected Results: We find a 6.8% average increase in somatomotor network (SMT)-visual network (VIS) connectivity from younger to older scans (corrected Conclusions: We conclude that SMT-VIS connectivity increases with age in the UKB longitudinal cohort and that resting state FC increases with age in the UKB cross-sectional cohort.
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.
Somatomotor-visual resting state functional connectivity increases after 2 years in the UK Biobank longitudinal cohort. · full record | OpenQuestion