Development of an mRNA-lipid nanoparticle vaccine against Lyme disease
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".