Evidence map›Paper›PMID 29291762›Full record

ReviewSeminars in nephrology2018

Advances in Renal Cell Imaging.

Georgina Gyarmati, Hiroyuki Kadoya, Ju-Young Moon, James L Burford, Nariman Ahmadi, Inderbir S Gill, Young-Kwon Hong, Bálint Dér, János Peti-Peterdi

Abstract readReview
In one paragraph

Review in Seminars in nephrology, 2018. 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
–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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. A new view of macula densa cell protein synthesis.American journal of physiology. Renal physiology · 2021
    Article
  6. Review
  7. A new view of macula densa cell microanatomy.American journal of physiology. Renal physiology · 2021
    Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. 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

9 authors.

Georgina GyarmatiDepartment of Physiology and Neuroscience, Department of Medicine, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA.
Hiroyuki KadoyaDepartment of Physiology and Neuroscience, Department of Medicine, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA; Department of Nephrology and Hypertension, Kawasaki Medical School, Kurashiki, Japan.
Ju-Young MoonDepartment of Physiology and Neuroscience, Department of Medicine, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA; Division of Nephrology, Department of Internal Medicine, Kyung Hee University, College of Medicine, Seoul, Korea.
James L BurfordDepartment of Physiology and Neuroscience, Department of Medicine, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA.
Nariman AhmadiInstitute of Urology, Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA.
Inderbir S GillInstitute of Urology, Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA.
Young-Kwon HongDepartment of Surgery and Biochemistry and Molecular Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA.
Bálint DérDepartment of Physiology and Neuroscience, Department of Medicine, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA.
János Peti-PeterdiDepartment of Physiology and Neuroscience, Department of Medicine, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA. Electronic address: petipete@usc.edu.

Funding

Multiphoton Imaging of the Juxtaglomerular ApparatusR01DK064324 · NIDDK · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JANOS PETI-PETERDI · 2004 to 2026
$8.4M
Novel imaging approach to study podocyte function in vivoR01DK100944 · NIDDK · UNIVERSITY OF SOUTHERN CALIFORNIA · PI PETI-PETERDI, JANOS · 2014 to 2017
$1.5M
NIDDK NIH HHS R01 DK064324NIDDK NIH HHS R01 DK100944
6 · The paper itself

Abstract

A great variety of cell imaging technologies are used routinely every day for the investigation of kidney cell types in applications ranging from basic science research to drug development and pharmacology, clinical nephrology, and pathology. Quantitative visualization of the identity, density, and fate of both resident and nonresident cells in the kidney, and imaging-based analysis of their altered function, (patho)biology, metabolism, and signaling in disease conditions, can help to better define pathomechanism-based disease subgroups, identify critical cells and structures that play a role in the pathogenesis, critically needed biomarkers of disease progression, and cell and molecular pathways as targets for novel therapies. Overall, renal cell imaging has great potential for improving the precision of diagnostic and treatment paradigms for individual acute kidney injury or chronic kidney disease patients or patient populations. This review highlights and provides examples for some of the recently developed renal cell optical imaging approaches, mainly intravital multiphoton fluorescence microscopy, and the new knowledge they provide for our better understanding of renal pathologies.

Indexed as

Cell LineageHumansHyaluronan ReceptorsKidneyMicroscopy, Fluorescence, MultiphotonHyaluronan Receptorscalcium signalingcell metabolismGenetic cell fate trackingischemia-reperfusion injurymultiplex imaging fibrosis

Identifiers

PMID29291762
PMCPMC5773263

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.