ReviewSeminars in nephrology2022
Identifying Common Molecular Mechanisms in Experimental and Human Acute Kidney Injury.
Review in Seminars in nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 13 citations in OpenAlex.
- Association between HALP score and in-hospital outcomes in patients with acute kidney injury: a retrospective cohort study.Scientific reports · 2026Article
- Transition from acute kidney injury to chronic kidney disease: molecular mechanisms and therapeutic interventions.Molecular biomedicine · 2026Review
- Krüppel-Like Factor 6 Induces RNA Polymerase II Subunit RPB1 to Promote Kidney Injury.Journal of the American Society of Nephrology : JASN · 2025Article
- Comparison of sepsis-associated acute kidney injury with different degrees and causes reveals patterns in mitochondrial metabolism and immune infiltration changes.Scientific reports · 2025Article
- Nfkb1 Removal from Proximal Tubule Cells Improves Renal Tubular Outcomes Following Ischemia Reperfusion Injury.Kidney360 · 2025Article
- Pax inhibition: stressing proximal tubule for successful repair.American journal of physiology. Renal physiology · 2025Article
- Permanent defects in renal medullary structure and function after reversal of urinary obstruction.JCI insight · 2025Article
- Nanomedicine for Acute Kidney Injury: Precision Delivery Strategies, Therapeutic Breakthroughs, Challenges, and Future Perspectives.International journal of nanomedicine · 2025Review
- Epithelial cell states associated with kidney and allograft injury.Nature reviews. Nephrology · 2024Review
- How to Best Protect Kidneys for Transplantation-Mechanistic Target.Journal of clinical medicine · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Acute kidney injury (AKI) is a highly prevalent, heterogeneous syndrome, associated with increased short- and long-term mortality. A multitude of different factors cause AKI including ischemia, sepsis, nephrotoxic drugs, and urinary tract obstruction. Upon injury, the kidney initiates an intrinsic repair program that can result in adaptive repair with regeneration of damaged nephrons and functional recovery of epithelial activity, or maladaptive repair and persistence of damaged epithelial cells with a characteristic proinflammatory, profibrotic molecular signature. Maladaptive repair is linked to disease progression from AKI to chronic kidney disease. Despite extensive efforts, no therapeutic strategies provide consistent benefit to AKI patients. Since kidney biopsies are rarely performed in the acute injury phase in humans, most of our understanding of AKI pathophysiology is derived from preclinical AKI models. This raises the question of how well experimental models of AKI reflect the molecular and cellular mechanisms underlying human AKI? Here, we provide a brief overview of available AKI models, discuss their strengths and limitations, and consider important aspects of the AKI response in mice and humans, with a particular focus on the role of proximal tubule cells in adaptive and maladaptive repair.
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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 OpenQuestion graph.