ArticleVaccines2023
Intradermal Vaccination against Influenza with a STING-Targeted Nanoparticle Combination Adjuvant Induces Superior Cross-Protective Humoral Immunity in Swine Compared with Intranasal and Intramuscular Immunization.
Article in Vaccines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Advancing intradermal vaccine delivery: Focus on hollow microneedles and skin models.Human vaccines & immunotherapeutics · 2026Review
- AFrontiers in immunology · 2026Article
- Progress Update on STING Agonists as Vaccine Adjuvants.Vaccines · 2025Review
- The Evaluation of a Porcine Circovirus Type 2 (PCV2) Intradermal Vaccine Against a PCV2 Field Strain.Vaccines · 2025Article
- Influenza-specific antibody-mediated and complement-dependent cellular cytotoxicity-inducing antibodies in vaccinated and infected pigs.Frontiers in immunology · 2025Article
- Intradermal vaccination with a phytoglycogen nanoparticle and STING agonist induces cytotoxic T lymphocyte-mediated antitumor immunity.NPJ vaccines · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
Abstract
The development of cross-protective vaccines against the zoonotic swine influenza A virus (swIAV), a potential pandemic-causing agent, continues to be an urgent global health concern. Commercially available vaccines provide suboptimal cross-protection against circulating subtypes of swIAV, which can lead to worldwide economic losses and poor zoonosis deterrence. The limited efficacy of current swIAV vaccines demands innovative strategies for the development of next-generation vaccines. Considering that intramuscular injection is the standard route of vaccine administration in both human and veterinary medicine, the exploration of alternative strategies, such as intradermal vaccination, presents a promising avenue for vaccinology. This investigation demonstrates the first evaluation of a direct comparison between a commercially available multivalent swIAV vaccine and monovalent whole inactivated H1N2 swine influenza vaccine, delivered by intradermal, intranasal, and intramuscular routes. The monovalent vaccines were adjuvanted with NanoST, a cationic phytoglycogen-based nanoparticle that is combined with the STING agonist ADU-S100. Upon heterologous challenge, intradermal vaccination generated a stronger cross-reactive nasal and serum antibody response in pigs compared with intranasal and intramuscular vaccination. Antibodies induced by intradermal immunization also had higher avidity compared with the other routes of vaccination. Bone marrow from intradermally and intramuscularly immunized pigs had both IgG and IgA virus-specific antibody-secreting cells. These studies reveal that NanoST is a promising adjuvant system for the intradermal administration of STING-targeted influenza vaccines.
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Registered trials
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.