ReviewRenal failure2024
Single-cell RNA sequencing in diabetic kidney disease: a literature review.
Review in Renal failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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
13 citing papers in PubMed.
- Integrated multicompartment urinary long non-coding RNAs profiling (cellular, cell-free, and extracellular vesicle) for better differential diagnosis of biopsy-proven diabetic and non-diabetic kidney disease beyond conventional markers.BMJ open diabetes research & care · 2026Article
- Cell-Type-Specific and Variety-Specific Responses to Salt Stress in Wheat Root Revealed by Single-Cell Transcriptomics.Plant biotechnology journal · 2026Article
- Diabetic kidney disease: integrating multi-omics insights, artificial intelligence, and novel therapeutics for precision medicine.Frontiers in genetics · 2026Review
- Baicalein attenuates extracellular matrix remodeling via FN1 in diabetic kidney disease: a multi-omics, machine-learning and mesangial-cell rescue study.Frontiers in pharmacology · 2026Article
- The dual role of ion channels in diabetic kidney disease: a translational paradigm for biomarkers and target discovery - reviews and prospects.American journal of translational research · 2026Review
- Recalibrating cell fate: targeting the mitochondrial signaling hub with natural active compounds to inhibit regulated cell death in diabetic kidney disease.Frontiers in physiology · 2026Review
- Kidney diseases and single-cell sequencing research: a bibliometric analysis from 2015 to 2024.Renal failure · 2025Review
- Sodium-glucose cotransporter 2 inhibitors alleviate renal fibrosis in diabetic kidney disease by inhibiting Hmgcs2 and Btg2 in proximal tubular cells.Journal of translational medicine · 2025Article
- Combination of ATRAP deletion and angiotensin II accelerates DKD progression, which may also accelerate DKD research.Hypertension research : official journal of the Japanese Society of Hypertension · 2025Article
- Emerging technologies for early risk stratification and precision management of diabetic kidney disease: a multimodal framework integrating digital phenotypes and clinical biomarkers.Frontiers in endocrinology · 2025Review
- Editorial: Cell cross-talk in diabetic kidney diseases, volume III.Frontiers in medicine · 2025Article
- Targeting ion channel networks in diabetic kidney disease: from molecular crosstalk to precision therapeutics and clinical innovation.Frontiers in medicine · 2025Review
- Single-Cell Sequencing Uncovers a TMSB10-Expressing Fibroblast Subpopulation Driving Renal Fibrosis in Diabetic Nephropathy.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD), and its pathogenesis has not been clarified. Current research suggests that DKD involves multiple cell types and extra-renal factors, and it is particularly important to clarify the pathogenesis and identify new therapeutic targets. Single-cell RNA sequencing (scRNA-seq) technology is high-throughput sequencing of the transcriptomes of individual cells at the single-cell level, which is an effective technology for exploring the development of diseases by comparing genetic information, reflecting the differences in genetic information between cells, and identifying different cell subpopulations. Accumulating evidence supports the role of scRNA-seq in revealing the pathogenesis of diabetes and strengthening our understanding of the molecular mechanisms of DKD. We reviewed the scRNA-seq data this time. Then, we analyzed and discussed the applications of scRNA-seq technology in DKD research, including annotation of cell types, identification of novel cell types (or subtypes), identification of intercellular communication, analysis of cell differentiation trajectories, gene expression detection, and analysis of gene regulatory networks, and lastly, we explored the future perspectives of scRNA-seq technology in DKD research.
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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.