ReviewScientific reports2023
A proof-of-concept assay for quantitative and optical assessment of drug-induced toxicity in renal organoids.
Review in Scientific reports, 2023. 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, 11 citations in OpenAlex.
- KiGEP: a quantitative algorithm for calculating human kidney similarity and nephrotoxicity in human kidney organoids.Experimental & molecular medicine · 2026Article
- Organoids in drug development: from predictive models to regulatory integration.Drug discovery today · 2026Review
- Kidney Organoids in Drug Development: Integrating Technological Advances and Standardization for Effective Implementation.Advanced healthcare materials · 2026Review
- Advances in Cytotoxicity Testing: From In Vitro Assays to In Silico Models.International journal of molecular sciences · 2025Review
- Landscape of human organoids: Ideal model in clinics and research.Innovation (Cambridge (Mass.)) · 2024Review
- Exploring the promising potential of induced pluripotent stem cells in cancer research and therapy.Molecular cancer · 2023Review
- Progress of Induced Pluripotent Stem Cell-Derived Renal Organoids in Clinical Application.Kidney diseases (Basel, Switzerland)Review
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kidneys are complex organs, and reproducing their function and physiology in a laboratory setting remains difficult. During drug development, potential compounds may exhibit unexpected nephrotoxic effects, which imposes a significant financial burden on pharmaceutical companies. As a result, there is an ongoing need for more accurate model systems. The use of renal organoids to simulate responses to nephrotoxic insults has the potential to bridge the gap between preclinical drug efficacy studies in cell cultures and animal models, and the stages of clinical trials in humans. Here we established an accessible fluorescent whole-mount approach for nuclear and membrane staining to first provide an overview of the organoid histology. Furthermore, we investigated the potential of renal organoids to model responses to drug toxicity. For this purpose, organoids were treated with the chemotherapeutic agent doxorubicin for 48 h. When cell viability was assessed biochemically, the organoids demonstrated a significant, dose-dependent decline in response to the treatment. Confocal microscopy revealed visible tubular disintegration and a loss of cellular boundaries at high drug concentrations. This observation was further reinforced by a dose-dependent decrease of the nuclear area in the analyzed images. In contrast to other approaches, in this study, we provide a straightforward experimental framework for drug toxicity assessment in renal organoids that may be used in early research stages to assist screen for potential adverse effects of compounds.
Indexed as
Identifiers
What Socratic 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 Socratic graph.