Evidence map›Paper›PMID 36168329›Full record

ReviewActa pharmaceutica Sinica. B2023

Localized delivery of nanomedicine and antibodies for combating COVID-19.

Bin Tu, Yanrong Gao, Xinran An, Huiyuan Wang, Yongzhuo Huang

Abstract readReview
In one paragraph

Review in Acta pharmaceutica Sinica. B, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Construction of a localized immune nicheActa pharmaceutica Sinica. B · 2026
    Article
  2. Review
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  4. Review
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  6. Review
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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.

Bin TuState Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Yanrong GaoState Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Xinran AnState Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Huiyuan WangState Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Yongzhuo HuangState Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been a major health burden in the world. So far, many strategies have been investigated to control the spread of COVID-19, including social distancing, disinfection protocols, vaccines, and antiviral treatments. Despite the significant achievement, due to the constantly emerging new variants, COVID-19 is still a great challenge to the global healthcare system. It is an urgent demand for the development of new therapeutics and technologies for containing the wild spread of SARS-CoV-2. Inhaled administration is useful for the treatment of lung and respiratory diseases, and enables the drugs to reach the site of action directly with benefits of decreased dose, improved safety, and enhanced patient compliance. Nanotechnology has been extensively applied in the prevention and treatment of COVID-19. In this review, the inhaled nanomedicines and antibodies, as well as intranasal nanodrugs, for the prevention and treatment of COVID-19 are summarized.

Indexed as

AntibodyCOVID-19Intranasal deliveryNanomedicineOrally-inhaled deliverySARS-CoV-2

Identifiers

PMID36168329
PMCPMC9502448

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.