Evidence map›Paper›PMID 38516300›Full record

ArticleBiophysics reports2023

Surface engineering of lipid nanoparticles: targeted nucleic acid delivery and beyond.

Yi Lin, Qiang Cheng, Tuo Wei

Abstract read
In one paragraph

Article in Biophysics reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Bioactive lipid-derived nanoparticles for RNA delivery.Materials today (Kidlington, England) · 2026
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  12. In Vivo CAR-T Therapies-A New Era of Programmable Immunity.International journal of molecular sciences · 2026
    Review
  13. Review
  14. Review
  15. Exosomes as Emerging Nanocarriers for Targeted Cancer Therapy.International journal of nanomedicine · 2026
    Review
  16. Article
  17. Article
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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

3 authors.

Yi LinState Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.
Qiang ChengDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China.
Tuo WeiState Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Harnessing surface engineering strategies to functionalize nucleic acid-lipid nanoparticles (LNPs) for improved performance has been a hot research topic since the approval of the first siRNA drug, patisiran, and two mRNA-based COVID-19 vaccines, BNT162b2 and mRNA-1273. Currently, efforts have been mainly made to construct targeted LNPs for organ- or cell-type-specific delivery of nucleic acid drugs by conjugation with various types of ligands. In this review, we describe the surface engineering strategies for nucleic acid-LNPs, considering ligand types, conjugation chemistries, and incorporation methods. We then outline the general purification and characterization techniques that are frequently used following the engineering step and emphasize the specific techniques for certain types of ligands. Next, we comprehensively summarize the currently accessible organs and cell types, as well as the other applications of the engineered LNPs. Finally, we provide considerations for formulating targeted LNPs and discuss the challenges of successfully translating the "proof of concept" from the laboratory into the clinic. We believe that addressing these challenges could accelerate the development of surface-engineered LNPs for targeted nucleic acid delivery and beyond.

Indexed as

Lipid nanoparticlesNucleic acid deliverySurface engineeringTargeted delivery

Identifiers

PMID38516300
PMCPMC10951480

What OpenQuestion holds

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LicenceCC BY
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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.