ReviewRSC pharmaceutics2025
Biomimetic nanoparticles for targeted therapy of liver disease.
Review in RSC pharmaceutics, 2025. 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
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
10 citing papers in PubMed.
- Biomimetic Targeted Drug Delivery for Liver Failure in Abdominal Sepsis: Focus on Autologous Erythrocyte Ghosts.International journal of molecular sciences · 2026Review
- Reengineering statin therapy to protect skeletal muscle: nanocarrier strategies for mitigating mitochondrial dysfunction and myotoxicity.Inflammation and regeneration · 2026Review
- Functional Reclassification of Lipid-Based Drug Delivery Systems and Advances in Formulation Strategies and Manufacturing Challenges.AAPS PharmSciTech · 2026Review
- A novel Kupffer cell-targeting nanoparticle system to Mitigate alcohol-associated liver disease.Biomaterials · 2026Article
- Hepatotropic Nanomedicine and Targeted Nanocarriers for Liver Diseases and Hepatocellular Carcinoma.International journal of nanomedicine · 2026Review
- The Mechanism and Application of Traditional Chinese Medicine Nano-Formulations in the Treatment of Renal Fibrosis.International journal of nanomedicine · 2026Review
- Biomimetic Polymer-Based Nanomaterials for Immune-Responsive Hepatocellular Carcinoma Therapy.International journal of nanomedicine · 2026Review
- Nanomedicines in the Treatment of Liver Fibrosis: A Review.International journal of nanomedicine · 2025Review
- Endoplasmic Reticulum-Targeting Natural Compounds: A Novel Frontier in Alleviating Liver Fibrosis.Drug design, development and therapy · 2025Review
- Immune-modulatory biomimetic nanoparticles: Advances in design, mechanisms, and nanomedicine applications.BioImpacts : BI · 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
6 authors.
Funding
Abstract
Liver fibrosis is a progressive and fatal condition characterized by stiffness and scarring of the liver due to excessive buildup of extracellular matrix (ECM) proteins. If left untreated, it can progress to liver cirrhosis and hepatocellular carcinoma (HCC)-one of the fastest-rising causes of cancer mortality in the United States. Despite the increased prevalence of liver fibrosis due to infections, exposure to toxins, and unhealthy lifestyles, there are no effective treatments available. Recent advances in nanomedicine can lead to more targeted and effective strategies for treating liver diseases than existing treatments. In particular, the use of biomimetic nanoparticles (NPs) such as liposomes and cell-membrane-coated NPs is of interest. NPs functionalized with cell membranes mimic the properties of the source cell used and provide inherent immune evasion ability, homologous adhesion, and prolonged circulation. This review explores the types of biomimetic coatings, different cargoes delivered through biomimetic NPs for various treatment modalities, and the type of core NPs used for targeting liver fibrosis and HCC.
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.