Evidence map›Paper›PMID 38660712›Full record

ArticleAmerican journal of physiology. Renal physiology2024

Resting-state MRI reveals spontaneous physiological fluctuations in the kidney and tracks diabetic nephropathy in rats.

Edwin J Baldelomar, Darya Morozov, Leslie D Wilson, Cihat Eldeniz, Hongyu An, Jennifer R Charlton, Adam Q Bauer, Shella D Keilholz, Monica L Hulbert, Kevin M Bennett

Open access · greenAbstract read
In one paragraph

Article in American journal of physiology. Renal physiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 2 citations in OpenAlex.

  1. Are noninvasive measurements of nephron number achievable in humans?Current opinion in nephrology and hypertension · 2026
    Review
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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

10 authors at 3 institutions in 1 country.

Edwin J BaldelomarMallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States.ORCID 0000-0002-3482-373X
Darya MorozovMallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States.
Leslie D WilsonDivision of Comparative Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States.
Cihat EldenizMallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States.
Hongyu AnMallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States.ORCID 0000-0001-6459-2269
Jennifer R CharltonDivision of Nephrology, Department of Pediatrics, University of Virginia, Charlottesville, Virginia, United States.ORCID 0000-0002-2225-535X
Adam Q BauerMallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States.
Shella D KeilholzCoulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States.ORCID 0000-0001-5737-1660
Monica L HulbertDivision of Pediatric Hematology/Oncology, Washington University School of Medicine in St. Louis, Missouri, United States.
Kevin M BennettMallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States.ORCID 0000-0003-1706-4660
Washington University in St. Louis · USGeorgia Institute of Technology · USUniversity of Virginia · US

Funding

WU P&FP30DK020579 · NIDDK · WASHINGTON UNIVERSITY · PI David W Piston · 2013 to 2026
$27.1M
Imaging and Reversibility of Cellular and Network Metabolic Dysfunction in Alzheimer's DiseaseRF1AG079503 · NIA · WASHINGTON UNIVERSITY · PI BAUER, ADAM Q, GOYAL, MANU S · 2022 to 2022
$2.2M
OPTOGENETIC MAPPING OF CELL SPECIFIC CONNECTIONS IN THE MOUSE BRAIN AFTER STROKER01NS102870 · NINDS · WASHINGTON UNIVERSITY · PI BAUER, ADAM Q · 2018 to 2022
$2.1M
Determining the efficacy of therapeutic interventions after stroke from cell specific functional connectomesR01NS126326 · NINDS · WASHINGTON UNIVERSITY · PI ADAM Q BAUER · 2023 to 2026
$1.8M
Resting state MRI to map autoregulation of the kidneyR21DK134104 · NIDDK · WASHINGTON UNIVERSITY · PI BENNETT, KEVIN M · 2022 to 2023
$679k
HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) DK134104HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) DK134104-S1NIDDK NIH HHS P30 DK020579NIDDK NIH HHS R21 DK134104NINDS NIH HHS R01 NS102870NINDS NIH HHS R01 NS126326Washington University School of Medicine in St. Louis (WUSM) Diabetes Research Center Pilot and Feasibility grantWUSM | Mallinckrodt Institute of Radiology (MIR) Pilot fund
6 · The paper itself

Abstract

The kidneys maintain fluid-electrolyte balance and excrete waste in the presence of constant fluctuations in plasma volume and systemic blood pressure. The kidneys perform these functions to control capillary perfusion and glomerular filtration by modulating the mechanisms of autoregulation. An effect of these modulations are spontaneous, natural fluctuations in glomerular perfusion. Numerous other mechanisms can lead to fluctuations in perfusion and flow. The ability to monitor these spontaneous physiological fluctuations in vivo could facilitate the early detection of kidney disease. The goal of this work was to investigate the use of resting-state magnetic resonance imaging (rsMRI) to detect spontaneous physiological fluctuations in the kidney. We performed rsMRI of rat kidneys in vivo over 10 min, applying motion correction to resolve time series in each voxel. We observed spatially variable, spontaneous fluctuations in rsMRI signal between 0 and 0.3 Hz, in frequency bands associated with autoregulatory mechanisms. We further applied rsMRI to investigate changes in these fluctuations in a rat model of diabetic nephropathy. Spectral analysis was performed on time series of rsMRI signals in the kidney cortex and medulla. The power from spectra in specific frequency bands from the cortex correlated with severity of glomerular pathology caused by diabetic nephropathy. Finally, we investigated the feasibility of using rsMRI of the human kidney in two participants, observing the presence of similar, spatially variable fluctuations. This approach may enable a range of preclinical and clinical investigations of kidney function and facilitate the development of new therapies to improve outcomes in patients with kidney disease.

Indexed as

Diabetic NephropathiesKidneyMagnetic Resonance ImagingRats, Sprague-DawleyAnimalsDiabetes Mellitus, ExperimentalHomeostasisHumansMaleRatsRenal Circulationkidney autoregulationMRIphysiologytubuloglomerular feedback

Identifiers

PMID38660712
PMCPMC11390131
OpenAlexW4395455476

What Socratic holds

Textmetadata
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 Socratic graph.