Evidence map›Paper›PMID 36286056›Full record

ReviewCurrent issues in molecular biology2022

Lipid Nanoparticles: A Novel Gene Delivery Technique for Clinical Application.

Ryuichi Mashima, Shuji Takada

Open access · goldAbstract readReview
In one paragraph

Review in Current issues in molecular biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
4.5field-weighted citation impact, top 4% of its field
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

29 citing papers in PubMed, 56 citations in OpenAlex.

  1. Article
  2. Review
  3. Contrast Agents for Enhanced Bioimaging: A Comprehensive Review.Chembiochem : a European journal of chemical biology · 2026
    Review
  4. Article
  5. Nature Inspired Delivery Vehicles for CRISPR-Based Genome Editing.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Review
  18. RNA Structure: Past, Future, and Gene Therapy Applications.International journal of molecular sciences · 2024
    Review
  19. Review
  20. Article
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

2 authors at 1 institution in 1 country.

Ryuichi MashimaDepartment of Clinical Laboratory Medicine, National Center for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo 157-8535, Japan.
Shuji TakadaDepartment of Systems BioMedicine, National Research Institute for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo 157-8535, Japan.
National Center For Child Health and Development · JP

Funding

Japan Agency for Medical Research and Development 22ae0201004h0005Japan Society for the Promotion of Science 22K07927
6 · The paper itself

Abstract

Lipid nanoparticles (LNPs) are an emerging vehicle for gene delivery that accommodate both nucleic acid and protein. Based on the experience of therapeutic liposomes, current LNPs have been developed based on the chemistry of lipids and RNA and on the biology of human disease. LNPs have been used for the development of Onpattro, an siRNA drug for transthyretin-mediated amyloidosis, in 2018. The subsequent outbreak of COVID-19 required a vaccine for its suppression. LNP-based vaccine production received much attention for this and resulted in great success. In this review, the essential technology of LNP gene delivery has been described according to the chemistry for LNP production and biology for its clinical application.

Indexed as

genome editinglipid nanoparticlelipidsRNA modification

Identifiers

PMID36286056
PMCPMC9600891
OpenAlexW4306836145

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.