Evidence map›Paper›PMID 41884229›Full record

ReviewSynthetic and systems biotechnology2026

Advances in vehicles for in situ delivery: From classical vectors to biologically inspired structures.

Hengyi Wang, Xiaoyan Tang, Xinyao Pan, Hongjie Tang, Jie Gao, Qi Li

Abstract readReview
In one paragraph

Review in Synthetic and systems biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Hengyi WangCollege of Life Sciences, Sichuan Normal University, Chengdu, 610101, China.
Xiaoyan TangCollege of Life Sciences, Sichuan Normal University, Chengdu, 610101, China.
Xinyao PanCollege of Life Sciences, Sichuan Normal University, Chengdu, 610101, China.
Hongjie TangCollege of Life Sciences, Sichuan Normal University, Chengdu, 610101, China.
Jie GaoCollege of Life Sciences, Sichuan Normal University, Chengdu, 610101, China.
Qi LiCollege of Life Sciences, Sichuan Normal University, Chengdu, 610101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emerging fields of synthetic biology and gene therapy rely on delivery systems to introduce the nucleic acids and proteins into recipient cells. Hence, the development of delivery tools with high specificity, strong manufacturability, and low immunogenicity can advance these fields. In this review, we summarize recent advances in the development of delivery systems for proteins and nucleic acids. First, we outline viral vector-based delivery tools, including lentivirus, adenovirus, and adeno-associated virus-based delivery technologies, discussing their advantages and limitations. Next, we summarize the advantages and disadvantages of non-viral vector-based delivery tools, including delivery strategies based on lipid nanoparticles, polyethyleneimine, exosomes, cell-penetrating peptides, virus-like particles, gold nanoparticles, and mesoporous silica nanoparticles. Lastly, we examine the specific principles and functional potential of novel delivery systems, including the Arc, PNMA2, SEND, PVC, and Coacervate systems. Overall, this review provides a systematic assessment of the mechanisms of action, current application progress, and future prospects for viral vectors, non-viral vectors, and novel delivery tools. Moreover, this review will serve as a reference for technological development and theoretical research in the fields of synthetic biology and gene therapy.

Indexed as

Gene deliveryGene therapySynthetic biologyTargeted delivery

Identifiers

PMID41884229
PMCPMC13011059

What Socratic 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 Socratic graph.