Evidence map›Paper›PMID 42256071›Full record

ArticleMaterials today. Bio2026

A membrane-fused theranostic nanoplatform for real-time ROS imaging and mitochondrial resuscitation-driven barrier repair in acute kidney injury.

Fan Wu, Yi Shen, Liang Dong, Wei Nie, Wei Xue

Abstract read
In one paragraph

Article in Materials today. Bio, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Fan WuDepartment of Urology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, China.
Yi ShenSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
Liang DongDepartment of Urology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, China.
Wei NieAffiliated Hospital 6 of Nantong University, Yancheng, 224001, China.
Wei XueDepartment of Urology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective management of Acute Kidney Injury (AKI) is currently limited by the lack of unified platforms capable of simultaneous diagnosis and structural repair. Addressing this challenge, a biomimetic theranostic nanoplatform, Lipoic Acid-loaded Exosome-Like Nanoparticles (EXLNPs), was engineered via a membrane fusion strategy wherein the homing capability of MSC-derived (Mesenchymal Stem Cells-derived) exosomes is synergized with the high-loading efficiency of synthetic liposomes. Upon administration, EXLNPs acted as a self-reporting diagnostic agent, exhibiting real-time fluorescence activation in response to high-ROS microenvironments, which correlated accurately with injury severity. Therapeutically, the membrane-fused EXLNPs outperformed native exosomes by orchestrating a precision "detect-and-repair" cascade. They effectively scavenged ROS to reverse mitochondrial metabolic collapse, thereby restoring the oxidative phosphorylation capacity and ATP production essential for the energy-dependent re-assembly of epithelial tight junctions (Occludin 1 and 15, CLDN1 and 15). This restoration of the mitochondrial-barrier axis significantly ameliorated tubular necrosis and recovered renal function in ischemic AKI models. These findings demonstrate that this bio-synthetic hybrid strategy offers a potent, clinically relevant solution for the precision diagnosis and metabolic reprogramming of acute renal diseases.

Indexed as

Acute kidney injuryExosome-liposome hybridsMembrane fusionMitochondrial resuscitationTheranosticsTight junction assembly

Identifiers

PMID42256071
PMCPMC13240824

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Registered trials

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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.