Evidence map›Paper›PMID 42909371›Full record

ReviewTheranostics2026

Cell-derived biomimetic nanomedicines: Emerging theranostic platforms for precision management of atherosclerosis.

Xingji Liu, Zhiyue Wang, Jiaqi Lu, Jie Sheng, Longjiang Zhang

Abstract readReview
In one paragraph

Review in Theranostics, 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.

Xingji LiuDepartment of Radiology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, Jiangsu 210008, China.
Zhiyue WangDepartment of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu 210008, China.
Jiaqi LuDepartment of Radiology, Jinling Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210008, China.
Jie ShengDepartment of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu 210008, China.
Longjiang ZhangDepartment of Radiology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, Jiangsu 210008, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atherosclerosis (AS), driven by complex cellular interactions, remains a leading cause of mortality worldwide. Conventional therapies often lack diseased blood vessels specificity, limiting therapy efficacy while increasing off-target toxicity. Boasting the biological advantages of cell-derived camouflages, these biomimetic nanomedicines outperform traditional drugs in intraplaque accumulation, circulation half-life and anti-AS efficacy. Current cell-derived biomimetic nanomedicines include whole-cell carriers, cell membrane-coated nanoparticles (NPs), and extracellular vesicles (EVs), all exploitable as novel platforms for plaque imaging and treatment. This review introduces the cellular mechanisms of AS pathology, examines recent advances in biomimetic strategies for AS theranostics and discusses the major barriers in clinical translation including biomaterial design, manufacturing consistency, safety evaluation, and large-scale production.

Indexed as

AtherosclerosisBiomimetic MaterialsBiomimeticsPrecision MedicineTheranostic NanomedicineAnimalsDrug Delivery SystemsHumansNanoparticlesatherosclerosisbiomimetic nanoparticlesclinical translationdrug delivery systemstheranostics

Identifiers

PMID42909371
PMCPMC13684933

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.