Evidence map›Paper›PMID 36678637›Full record

ArticlePharmaceutics2022

Influence of Lipid Composition of Cationic Liposomes 2X3-DOPE on mRNA Delivery into Eukaryotic Cells.

Vera Vysochinskaya, Sergey Shishlyannikov, Yana Zabrodskaya, Elena Shmendel, Sergey Klotchenko, Olga Dobrovolskaya, Nina Gavrilova, Darya Makarova, Marina Plotnikova, Ekaterina Elpaeva and 4 more

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

14 authors at 3 institutions in 2 countries.

Vera VysochinskayaSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.
Sergey ShishlyannikovSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.ORCID 0000-0002-6377-7445
Yana ZabrodskayaSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.ORCID 0000-0003-2012-9461
Elena ShmendelLomonosov Institute of Fine Chemical Technologies, MIREA-Russian Technological University, 86 Vernadsky Ave, 119571 Moscow, Russia.
Sergey KlotchenkoSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.ORCID 0000-0003-0289-6560
Olga DobrovolskayaSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.ORCID 0000-0001-6654-1107
Nina GavrilovaSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.ORCID 0000-0002-7825-9130
Darya MakarovaLomonosov Institute of Fine Chemical Technologies, MIREA-Russian Technological University, 86 Vernadsky Ave, 119571 Moscow, Russia.
Marina PlotnikovaSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.
Ekaterina ElpaevaSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.
Andrey GorshkovSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.
Dmitry MoshkoffInstitute of Biomedical Systems and Biotechnology, Peter the Great Saint Petersburg Polytechnic University, 29 Ulitsa Polytechnicheskaya, 194064 St. Petersburg, Russia.
Mikhail MaslovLomonosov Institute of Fine Chemical Technologies, MIREA-Russian Technological University, 86 Vernadsky Ave, 119571 Moscow, Russia.ORCID 0000-0002-5372-1325
Andrey VasinSmorodintsev Research Institute of Influenza, 15/17 Ulitsa Professora Popova, 197376 St. Petersburg, Russia.ORCID 0000-0002-1391-7139
Research Institute of Influenza · RUPeter the Great St. Petersburg Polytechnic University · RUMIREA - Russian Technological University · RU

Funding

Ministry of Health of the Russian Federation 056-00112-22-03the Ministry of Science and Higher Education of the Russian Federation under the strategic aca-demic leadership program "Priority 2030" 075-15-2021-1190the Ministry of Science and Higher Education of the Russian Federation under the strategic aca-demic leadership program "Priority 2030" 075-15-2021-1333
6 · The paper itself

Abstract

The design of cationic liposomes for efficient mRNA delivery can significantly improve mRNA-based therapies. Lipoplexes based on polycationic lipid 1,26-bis(cholest-5-en-3β-yloxycarbonylamino)-7,11,16,20-tetraazahexacosane tetrahydrochloride (2X3) and helper lipid 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) were formulated in different molar ratios (1:1, 1:2, 1:3) to efficiently deliver model mRNAs to BHK-21 and A549. The objective of this study was to examine the effect of 2X3-DOPE composition as well as lipid-to-mRNA ratio (amino-to-phosphate group ratio, N/P) on mRNA transfection. We found that lipoplex-mediated transfection efficiency depends on both liposome composition and the N/P ratio. Lipoplexes with an N/P ratio of 10/1 showed nanometric hydrodynamic size, positive ζ potential, maximum loading, and transfection efficiency. Liposomes 2X3-DOPE (1:3) provided the superior delivery of both mRNA coding firefly luciferase and mRNA-eGFP into BHK-21 cells and A549 cells, compared with commercial Lipofectamine MessengerMax.

Indexed as

cationic lipidsliposomesmRNAnon-viral delivery systemstransfection

Identifiers

PMID36678637
PMCPMC9860636
OpenAlexW4313362326

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.