ReviewYonsei medical journal2018
Bioactive Compounds for the Treatment of Renal Disease.
Review in Yonsei medical journal, 2018. 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, 18 citations in OpenAlex.
- Development and intra-renal delivery of renal progenitor organoids for effective integration in vivo.Stem cells translational medicine · 2025Article
- Sustainability and role of plant-based diets in chronic kidney disease prevention and treatment.Frontiers in pharmacology · 2025Review
- Investigating the Effect of Secretome Secreted from Adult Rat Kidney-Derived Stem Cells on the Expression of miR375, miR494 and Tissue Changes in Glycerol-Induced Acute Kidney Injury.Advanced biomedical research · 2025Article
- Review
- Acute kidney disease: an overview of the epidemiology, pathophysiology, and management.Kidney research and clinical practice · 2023Article
- Autophagy-induced mesenchymal stem cell-derived extracellular vesicles ameliorated renal fibrosis in anBioImpacts : BI · 2023Article
- Long Non-Coding RNA RMRP Contributes to Sepsis-Induced Acute Kidney Injury.Yonsei medical journal · 2021Article
- The Role of Hormones and Trophic Factors as Components of Preservation Solutions in Protection of Renal Function before Transplantation: A Review of the Literature.Molecules (Basel, Switzerland) · 2020Review
- Dietary Components That May Influence the Disturbed Gut Microbiota in Chronic Kidney Disease.Nutrients · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kidney diseases including acute kidney injury and chronic kidney disease are among the largest health issues worldwide. Dialysis and kidney transplantation can replace a significant portion of renal function, however these treatments still have limitations. To overcome these shortcomings, a variety of innovative efforts have been introduced, including cell-based therapies. During the past decades, advances have been made in the stem cell and developmental biology, and tissue engineering. As part of such efforts, studies on renal cell therapy and artificial kidney developments have been conducted, and multiple therapeutic interventions have shown promise in the pre-clinical and clinical settings. More recently, therapeutic cell-secreting secretomes have emerged as a potential alternative to cell-based approaches. This approach involves the use of renotropic factors, such as growth factors and cytokines, that are produced by cells and these factors have shown effectiveness in facilitating kidney function recovery. This review focuses on the renotropic functions of bioactive compounds that provide protective and regenerative effects for kidney tissue repair, based on the available data in the literature.
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.