Comparison of uridine and N1-methylpseudouridine mRNA platforms in development of an Andes virus vaccine
Bibliographic record
Abstract
The rodent-borne Andes virus (ANDV) causes a severe disease in humans. We developed an ANDV mRNA vaccine based on the M segment of the viral genome, either with regular uridine (U-mRNA) or N1-methylpseudouridine (m1Ψ-mRNA). Female mice immunized by m1Ψ-mRNA developed slightly greater germinal center (GC) responses than U-mRNA-immunized mice. Single cell RNA and BCR sequencing of the GC B cells revealed similar levels of activation, except an additional cluster of cells exhibiting interferon response in animals vaccinated with U-mRNA but not m1Ψ-mRNA. Similar immunoglobulin class-switching and somatic hypermutations were observed in response to the vaccines. Female Syrian hamsters were immunized via a prime-boost regimen with two doses of each vaccine. The titers of glycoprotein-binding antibodies were greater for U-mRNA construct than for m1Ψ-mRNA construct; however, the titers of ANDV-neutralizing antibodies were similar. Vaccinated animals were challenged with a lethal dose of ANDV, along with a naïve control group. All control animals and two animals vaccinated with a lower dose of m1Ψ-mRNA succumbed to infection whereas other vaccinated animals survived without evidence of virus replication. The data demonstrate the development of a protective vaccine against ANDV and the lack of a substantial effect of m1Ψ modification on immunogenicity and protection in rodents.
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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".