Neutralizing Antibodies and CD8 <sup>+</sup> T Lymphocytes both Contribute to Immunity to Adenovirus Serotype 5 Vaccine Vectors
Bibliographic record
Abstract
The high prevalence of preexisting immunity to adenovirus serotype 5 (Ad5) in human populations will likely limit the immunogenicity and clinical utility of recombinant Ad5 vector-based vaccines for human immunodeficiency virus type 1 and other pathogens. Ad5-specific neutralizing antibodies (NAbs) are thought to contribute substantially to anti-Ad5 immunity, but the potential importance of Ad5-specific T lymphocytes in this setting has not been fully characterized. Here we assess the relative contributions of Ad5-specific humoral and cellular immune responses in blunting the immunogenicity of a rAd5-Env vaccine in mice. Adoptive transfer of Ad5-specific NAbs resulted in a dramatic abrogation of Env-specific immune responses following immunization with rAd5-Env. Interestingly, adoptive transfer of Ad5-specific CD8(+) T lymphocytes also resulted in a significant and durable suppression of rAd5-Env immunogenicity. These data demonstrate that NAbs and CD8(+) T lymphocytes both contribute to immunity to Ad5. Novel adenovirus vectors that are currently being developed to circumvent the problem of preexisting anti-Ad5 immunity should therefore be designed to evade both humoral and cellular Ad5-specific immune responses.
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) | 0.001 | 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".