Evidence map›Paper›PMID 40333333›Full record

ArticleVaccines2025

Adjuvant Templating Improves On-Target/Off-Target Antibody Ratio Better than Linker Addition for M2-Derived Peptide Amphiphile Micelle Vaccines.

Megan C Schulte, Adam C Boll, Natalie L Conomos, Farnoushsadat Rezaei, Agustin T Barcellona, Adam G Schrum, Bret D Ulery

Abstract read
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In one paragraph

Article in Vaccines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Megan C SchulteDepartment of Chemical and Biomedical Engineering, University of Missouri, Columbia, MI 65211, USA.
Adam C BollDepartment of Chemical and Biomedical Engineering, University of Missouri, Columbia, MI 65211, USA.
Natalie L ConomosDepartment of Biological Sciences, University of Missouri, Columbia, MI 65211, USA.
Farnoushsadat RezaeiDepartment of Chemical and Biomedical Engineering, University of Missouri, Columbia, MI 65211, USA.
Agustin T BarcellonaDepartment of Chemical and Biomedical Engineering, University of Missouri, Columbia, MI 65211, USA.
Adam G SchrumDepartment of Chemical and Biomedical Engineering, University of Missouri, Columbia, MI 65211, USA.
Bret D UleryDepartment of Chemical and Biomedical Engineering, University of Missouri, Columbia, MI 65211, USA.ORCID 0000-0003-0854-1859

Funding

University of Missouri System No Grant Number
6 · The paper itself

Abstract

backgroundPeptide amphiphile micelles (PAMs) are a promising lipid-based nanotechnology currently in development for a variety of applications ranging from atherosclerosis to cancer therapy. Especially relevant for immune applications, PAMs improve trafficking through lymphatic vessels, enhance uptake by antigen-presenting cells, and inhibit the protease-mediated degradation of cargo. However, the creation of the peptide amphiphiles (PAs) necessary to induce micellization often requires modifying an immunotarget peptide with non-native moieties, which can induce the production of off-target antibodies.

methodsPAs containing different linkers between the antigen and non-native flanking regions were synthesized and physically characterized. BALB/c mice were then subcutaneously immunized on days 0 and 14 with these formulations and ELISAs were conducted on the sera collected from vaccinated mice on day 35 to evaluate antibody responses.

resultsWe determined that Palm

conclusionsWhile the linkers tested did not completely eliminate the production of off-target antibodies elicited by the PAMs, the inclusion of a Pam

Indexed as

influenzaM2micellepeptide amphiphilevaccine

Identifiers

PMID40333333
PMCPMC12031025

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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.