Evidence map›Paper›PMID 38996568›Full record

ReviewCurrent opinion in chemical biology2024

Rational design of lipid nanoparticles: overcoming physiological barriers for selective intracellular mRNA delivery.

Yu Zhao, Zeyu Morgan Wang, Donghui Song, Mengting Chen, Qiaobing Xu

Abstract readReview
In one paragraph

Review in Current opinion in chemical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Yu ZhaoDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155, USA.
Zeyu Morgan WangDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155, USA.
Donghui SongDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155, USA.
Mengting ChenDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155, USA.
Qiaobing XuDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155, USA. Electronic address: Qiaobing.Xu@tufts.edu.

Funding

ROS-responsive Chemical Modification of Protein and Its DeliveryR01EB027170 · NIBIB · TUFTS UNIVERSITY MEDFORD · PI XU, QIAOBING · 2018 to 2022
$1.4M
NIBIB NIH HHS R01 EB027170
6 · The paper itself

Abstract

This review introduces the typical delivery process of messenger RNA (mRNA) nanomedicines and concludes that the delivery involves a at least four-step SCER cascade and that high efficiency at every step is critical to guarantee high overall therapeutic outcomes. This SCER cascade process includes selective organ-targeting delivery, cellular uptake, endosomal escape, and cytosolic mRNA release. Lipid nanoparticles (LNPs) have emerged as a state-of-the-art vehicle for in vivo mRNA delivery. The review emphasizes the importance of LNPs in achieving selective, efficient, and safe mRNA delivery. The discussion then extends to the technical and clinical considerations of LNPs, detailing the roles of individual components in the SCER cascade process, especially ionizable lipids and helper phospholipids. The review aims to provide an updated overview of LNP-based mRNA delivery, outlining recent innovations and addressing challenges while exploring future developments for clinical translation over the next decade.

Indexed as

LipidsNanoparticlesRNA, MessengerAnimalsGene Transfer TechniquesHumansLiposomesLipid NanoparticlesLipidsLiposomesRNA, MessengerCellular uptakeCytosolic mRNA releaseEndosomal escapeLipid nanoparticleTargeted mRNA delivery

Identifiers

PMID38996568
PMCPMC11323194

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.