ReviewCurrent opinion in organ transplantation2009
Deconvoluting the 'omics' for organ transplantation.
Review in Current opinion in organ transplantation, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Recent Progress and Future Direction for the Application of Multiomics Data in Clinical Liver Transplantation.Journal of clinical and translational hepatology · 2022Review
- A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients.Scientific reports · 2017Article
- Proteomics for rejection diagnosis in renal transplant patients: Where are we now?World journal of transplantation · 2016Review
- Lipidomics comparing DCD and DBD liver allografts uncovers lysophospholipids elevated in recipients undergoing early allograft dysfunction.Scientific reports · 2015Article
- Longitudinal analysis of whole blood transcriptomes to explore molecular signatures associated with acute renal allograft rejection.Bioinformatics and biology insights · 2014Article
- Proteomics and metabolomics in renal transplantation-quo vadis?Transplant international : official journal of the European Society for Organ Transplantation · 2013Review
- Proteomic analysis reveals innate immune activity in intestinal transplant dysfunction.Transplantation · 2011Article
- Assessment of kidney organ quality and prediction of outcome at time of transplantation.Seminars in immunopathology · 2011Review
- Identifying biomarkers as diagnostic tools in kidney transplantation.Expert review of molecular diagnostics · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
purpose of reviewThe desire for biomarkers for diagnosis and prognosis of diseases has never been greater. With the availability of genome data and an increased availability of proteome data, the discovery of biomarkers has become increasingly feasible. This article reviews some recent applications of the many evolving 'omic technologies to organ transplantation. RECENT
findingsWith the advancement of many high-throughput 'omic techniques such as genomics, metabolomics, antibiomics, peptidomics, and proteomics, efforts have been made to understand potential mechanisms of specific graft injuries and develop novel biomarkers for acute rejection, chronic rejection, and operational tolerance. SUMMARY: The translation of potential biomarkers from the laboratory bench to the clinical bedside is not an easy task and will require the concerted effort of the immunologists, molecular biologists, transplantation specialists, geneticists, and experts in bioinformatics. Rigorous prospective validation studies will be needed using large sets of independent patient samples. The appropriate and timely exploitation of evolving 'omic technologies will lay the cornerstone for a new age of translational research for organ transplant monitoring.
Indexed as
Identifiers
What 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.