ReviewNature reviews. Nephrology2009
Application of proteomic analysis to the study of renal diseases.
Review in Nature reviews. Nephrology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Urine hepcidin has additive value in ruling out cardiopulmonary bypass-associated acute kidney injury: an observational cohort study.Critical care (London, England) · 2011Trial
- Integrative multi-omics profiling for early diagnosis, stratification and personalized management of chronic kidney disease: a new paradigm.Clinical and experimental medicine · 2025Review
- Urinary alpha-1 antitrypsin and CD59 glycoprotein predict albuminuria development in hypertensive patients under chronic renin-angiotensin system suppression.Cardiovascular diabetology · 2016Article
- Reactive oxygen species, vascular Noxs, and hypertension: focus on translational and clinical research.Antioxidants & redox signaling · 2014Review
- Serum aminoacylase-1 is a novel biomarker with potential prognostic utility for long-term outcome in patients with delayed graft function following renal transplantation.Kidney international · 2013Article
- Systems biology of kidney diseases.Kidney international · 2012Review
- New pharmacological treatments for improving renal outcomes in diabetes.Nature reviews. Nephrology · 2010Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Proteomics-based approaches are generating considerable data in clinical nephrology covering almost all aspects of the discipline. Proteomic experiments commonly involve fractionation and protein separation, followed by mass spectrometric analysis to identify proteins and peptides. Biostatistical and bioinformatical input is essential in such experiments, from initial experimental design to analysis of data. Standardization of procedures is an important research objective. Depending on study design, results can lead to biomarker discovery, mechanistic insight and identification of potential avenues for therapeutic intervention and treatment evaluation. Understanding proteomic information and its place in current clinical research and practice is fundamental. This Review describes proteomic experimentation and the concepts behind it, and gives an overview of its application to important areas in clinical nephrology including acute kidney injury, chronic kidney disease, end-stage renal disease, genetic diseases and fluid and electrolyte disorders, with a particular focus on biomarker discovery. The importance of future developments, such as the establishment of an infrastructure for a 'biomarker pipeline' with structured validation pathways for candidate biomarkers and development of clinical assays, is also discussed and some future perspectives are presented.
Indexed as
Identifiers
19859072What OpenQuestion holds
Registered trials
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.