Evidence map›Paper›PMID 33762883›Full record

ArticleChemical engineering journal (Lausanne, Switzerland : 1996)2021

Inhalable nanovaccine with biomimetic coronavirus structure to trigger mucosal immunity of respiratory tract against COVID-19.

Bin Zheng, Wenchang Peng, Mingming Guo, Mengqian Huang, Yuxuan Gu, Tao Wang, Guangjian Ni, Dong Ming

Abstract read
In one paragraph

Article in Chemical engineering journal (Lausanne, Switzerland : 1996), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. Nanotechnology of inhalable vaccines for enhancing mucosal immunity.Drug delivery and translational research · 2024
    Review
  15. Article
  16. Article
  17. SIgA in various pulmonary diseases.European journal of medical research · 2023
    Review
  18. Review
  19. Inside-out assembly of viral antigens for the enhanced vaccination.Signal transduction and targeted therapy · 2023
    Article
  20. Recent advances in respiratory immunization: A focus on COVID-19 vaccines.Journal of controlled release : official journal of the Controlled Release Society · 2023
    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

8 authors.

Bin ZhengAcademy of Medical Engineering and Translational Medicine, Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China.
Wenchang PengAcademy of Medical Engineering and Translational Medicine, Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China.
Mingming GuoAcademy of Medical Engineering and Translational Medicine, Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China.
Mengqian HuangSchool of Life Sciences, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China.
Yuxuan GuAcademy of Medical Engineering and Translational Medicine, Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China.
Tao WangSchool of Life Sciences, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China.
Guangjian NiAcademy of Medical Engineering and Translational Medicine, Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China.
Dong MingAcademy of Medical Engineering and Translational Medicine, Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic caused by SARS-CoV-2 seriously threatens global public health. It has previously been confirmed that SARS-CoV-2 is mainly transmitted between people through "respiratory droplets". Therefore, the respiratory tract mucosa is the first barrier to prevent virus invasion. It is very important to stimulate mucosal immunity to protect the body from respiratory virus infection. Inspired by this, we designed a bionic-virus nanovaccine, which can induce mucosal immunity by nasal delivery to prevent virus infection from respiratory tract. The nanovaccine that mimic virosome is composed of poly(I:C) mimicking viral genetic material as immune adjuvant, biomimetic pulmonary surfactant (bio-PS) liposomes as capsid structure of virus and the receptor binding domains (RBDs) of SARS-CoV-2 as "spike" to completely simulate the structure of the coronavirus. The nanovaccine can be administered by inhaling to imitate the process of SARS-CoV-2 infection through the respiratory tract. Our results demonstrated that the inhalable nanovaccine with bionic virus-like structure has a stronger mucosal protective effect than routine muscle and subcutaneous inoculation. In particular, high titer of secretory immunoglobulin A (sIgA) was detected in respiratory secretions, which effectively neutralize the virus and prevent it from entering the body through the respiratory tract. Through imitating the structure and route of infection, this inhalable nanovaccine strategy might inspire a new approach to the precaution of respiratory viruses.

Indexed as

Bionic coronavirus structureCOVID-19Inhalable nanovaccineRespiratory mucosal immunitySARS-CoV-2

Identifiers

PMID33762883
PMCPMC7972832

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.