Evidence map›Paper›PMID 42028278›Full record

ArticleMaterials today. Bio2026

Advancements in nanomaterial-based adjuvants for animal vaccines.

Linyi Dai, Lei Yang, Vitalii Nedosekov, Jing Ma, Weihuan Fang, Huapeng Feng, Jianhong Shu, Yulong He

Abstract read
In one paragraph

Article in Materials today. Bio, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Linyi DaiCollege of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
Lei YangInstitute of Sericulture and Tea, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China.
Vitalii NedosekovResearch Center of Animal Vaccines and Diagnostic Reagents, Zhejiang Sci-Tech University Shaoxing, Academy of Biomedicine, Shaoxing, 312090, China.
Jing MaCollege of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
Weihuan FangInstitute of Preventive Veterinary Medicine, Zhejiang University, Hangzhou, 310058, China.
Huapeng FengCollege of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
Jianhong ShuCollege of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
Yulong HeCollege of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, 310018, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Designing adjuvants with immunostimulatory effects is crucial for enhancing the efficacy of various vaccines, controlling the outbreak and prevalence of animal infectious diseases. The rapid advancement of nanomaterials in recent years has opened new avenues for developing veterinary vaccine adjuvants. Adjuvants prepared from nanomaterials offer multiple advantages difficult to achieve with traditional adjuvants. This review summarizes the immunological mechanisms of nanoadjuvants, focusing on recent advances in inorganic nanomaterials, organic and polymeric nanomaterials, as well as hybrid and composite nanomaterials as potential veterinary vaccine adjuvants. It categorizes various nanomaterial adjuvants based on target species, diseases, and administration routes, and provides design recommendations, where appropriate, for the selection of appropriate adjuvant platforms tailored to specific species, pathogens, vaccine types, and delivery methods.

Indexed as

AdjuvantsCross-presentationLymph node targetingMucosal immunityNanomaterialsVeterinary vaccines

Identifiers

PMID42028278
PMCPMC13101784

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.