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Record W4385496703 · doi:10.1016/j.ymthe.2023.07.022

Development of an mRNA-lipid nanoparticle vaccine against Lyme disease

2023· article· en· W4385496703 on OpenAlex
Matthew Pine, Gunjan Arora, Thomas Hart, Emily Bettini, Brian T. Gaudette, Hiromi Muramatsu, István Tombácz, Taku Kambayashi, Ying K. Tam, Dustin Brisson, David Allman, Michela Locci, Drew Weissman, Erol Fikrig, Norbert Pardi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Therapy · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsAcuitas Therapeutics (Canada)
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood InstituteNational Institutes of HealthPolytechnique MontréalUniversity of PennsylvaniaBurroughs Wellcome FundNational Institute of Allergy and Infectious DiseasesSteven and Alexandra Cohen FoundationHoward Hughes Medical Institute
KeywordsLyme diseaseVirologyMessenger RNALYMEBiologyImmunologyBorrelia burgdorferiAntibodyBiochemistryGene

Abstract

fetched live from OpenAlex

Lyme disease is the most common vector-borne infectious disease in the United States, in part because a vaccine against it is not currently available for humans. We propose utilizing the lipid nanoparticle-encapsulated nucleoside-modified mRNA (mRNA-LNP) platform to generate a Lyme disease vaccine like the successful clinical vaccines against SARS-CoV-2. Of the antigens expressed by Borrelia burgdorferi, the causative agent of Lyme disease, outer surface protein A (OspA) is the most promising candidate for vaccine development. We have designed and synthesized an OspA-encoding mRNA-LNP vaccine and compared its immunogenicity and protective efficacy to an alum-adjuvanted OspA protein subunit vaccine. OspA mRNA-LNP induced superior humoral and cell-mediated immune responses in mice after a single immunization. These potent immune responses resulted in protection against bacterial infection. Our study demonstrates that highly efficient mRNA vaccines can be developed against bacterial targets.

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.

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 categoriesnone
Consensus categoriesnone
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 score0.061
Threshold uncertainty score0.858

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.251
Teacher spread0.238 · 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