Evidence map›Paper›PMID 42722685›Full record

ArticleNature communications2026

pH-Sensitive Amino Lipid-Driven Pore Formation Enables Endosomal Escape of Lipid Nanoparticles.

Akhil Pratap Singh, Kana Shibata, Yusuke Miyazaki, Wataru Shinoda

Abstract read
In one paragraph

Article in Nature communications, 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

4 authors.

Akhil Pratap Singh *Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama, 700-8530, Japan.
Kana Shibata *Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan.
Yusuke MiyazakiResearch Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama, 700-8530, Japan.ORCID http://orcid.org/0000-0002-8072-9111
Wataru ShinodaResearch Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama, 700-8530, Japan. shinoda@okayama-u.ac.jp.ORCID http://orcid.org/0000-0002-3388-9227

Funding

MEXT | Japan Society for the Promotion of Science (JSPS) JP21H01880, JP24H00038, JP24H00843, JP25K01729
6 · The paper itself

Abstract

Lipid nanoparticles (LNPs) have transformed nucleic acid delivery for vaccines and gene therapies, yet their efficiency remains limited by incomplete endosomal escape. While experimental studies have revealed endosomal membrane disruption facilitating cytosolic release, the molecular basis of this process remains poorly understood. Here, we employ molecular simulations to elucidate how LNPs fuse with the endosomal membrane and release their payloads. We identify multiple fusion pathways, with a dominant stalk-pore mechanism. Our simulations reproduce and rationalize key experimental observations, including the transfer of ionizable lipids from LNPs to the membrane, which promotes nucleic acid reorientation and facilitates stalk formation and expansion. Furthermore, lipid shape, pH sensitivity, membrane tension, and nucleic acid encapsulation emerge as critical molecular determinants of endosomal escape efficiency. These findings advance our mechanistic understanding of intracellular delivery and provide a framework for the rational design of LNPs with improved performance for gene therapies and RNA vaccines.

Indexed as

EndosomesLipidsNanoparticlesHydrogen-Ion ConcentrationLiposomesMolecular Dynamics SimulationLipid NanoparticlesLipidsLiposomes

Identifiers

PMID42722685
PMCPMC13562567

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.