Improved Durability to SARS-CoV-2 Vaccine Immunity following Coimmunization with Molecular Adjuvant Adenosine Deaminase-1
Bibliographic record
Abstract
Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines have demonstrated strong immunogenicity and protection against severe disease, concerns about the duration and breadth of these responses remain. In this study, we show that codelivery of plasmid-encoded adenosine deaminase-1 (pADA) with SARS-CoV-2 spike glycoprotein DNA enhances immune memory and durability in vivo. Coimmunized mice displayed increased spike-specific IgG of higher affinity and neutralizing capacity as compared with plasmid-encoded spike-only-immunized animals. Importantly, pADA significantly improved the longevity of these enhanced responses in vivo. This coincided with durable increases in frequencies of plasmablasts, receptor-binding domain-specific memory B cells, and SARS-CoV-2-specific T follicular helper cells. Increased spike-specific T cell polyfunctionality was also observed. Notably, animals coimmunized with pADA had significantly reduced viral loads compared with their nonadjuvanted counterparts in a SARS-CoV-2 infection model. These data suggest that pADA enhances immune memory and durability and supports further translational studies.
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 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 | 0.001 |
| 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".