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Record W4412464627 · doi:10.1038/s41541-025-01213-x

IL-12 mRNA-LNP promotes dermal resident memory CD4+ T cell development

2025· article· en· W4412464627 on OpenAlexaff
Anabel Zabala-Peñafiel, Claudia Gonzalez-Lombana, Mohamad‐Gabriel Alameh, Laís Amorim Sacramento, Zhirong Mou, Anthony T. Phan, Emily Aunins, Ying K. Tam, Jude E. Uzonna, Drew Weissman, Christopher A. Hunter, Phillip Scott

Bibliographic record

Venuenpj Vaccines · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsAcuitas Therapeutics (Canada)University of Manitoba
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthUniversity of Pennsylvania
KeywordsMessenger RNACell biologyBiologyComputational biologyGeneticsGene

Abstract

fetched live from OpenAlex

Dermal resident memory CD4 + T cells (dTrm) provide protection against vector-borne infections. However, the factors that promote their development remain unclear. We tested if an mRNA vaccine, encoding a protective leishmanial antigen, induced dTrm cells. The mRNA vaccine induced robust systemic T-cell responses, but few Trm cells were found in the skin. Since IL-12 promotes Th1 responses, we tested whether IL-12 mRNA combined with the mRNA vaccine could enhance dTrm cell development. This combination significantly expanded Leishmania -specific Th1 cells expressing skin-homing molecules and memory T cell markers in the draining lymph node. Additionally, higher numbers of dTrm cells were maintained in the skin, and mice exhibited functional immunity indicated by a delayed hypersensitivity response and protection upon challenge with Leishmania . These findings highlight IL-12 as a key driver of CD4 + dTrm development, enabling their global seeding across the skin, and underscore the potential of IL-12-enhanced mRNA vaccines to generate durable immunity against cutaneous leishmaniasis and other skin-targeted infections.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.223
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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