CD40 Ligand Preferentially Modulates Immune Response and Enhances Protection against Influenza Virus
Bibliographic record
Abstract
CD40L, a key regulator of the immune system, was studied as both a targeting ligand and a molecular adjuvant in nucleoprotein (NP)-based host defense against influenza in mouse models with different genetic backgrounds. Adenoviral vectors secreting NP-CD40L fusion protein (denoted as rAd-SNP40L) afforded full protection of immunocompetent and immunocompromised mice (CD40L(-/-) and CD4(-/-)) against lethal influenza infection. Mechanistically, rAd-SNP40L preferentially induced early and persistent B cell germinal center formation, and accelerated Ig isotype-switching and Th1-skewed, NP-specific Ab response. Moreover, it drastically augmented primary and memory NP-specific CTL activity and polyfunctional CD8(+) T cells. The markedly enhanced nonneutralizing Abs and CTLs significantly reduced viral burdens in the lungs of mice upon lethal virus challenge. Data generated from CD40L(-/-) and CD4(-/-) mice revealed that the protection was indeed CD40L mediated but CD4(+) T cell independent, demonstrating the viability of the fusion Ags in protecting immunodeficient hosts. Notably, a single dose of rAd-SNP40L completely protected mice from lethal viral challenge 4 mo after immunization, representing the first report, to our knowledge, on NP in conjunction with a molecular adjuvant inducing a robust and long-lasting memory immune response against influenza. This platform is characterized by an increased in vivo load of CD40-targeted Ag upon the secretion of the fusion protein from adenovirus-infected cells and may represent a promising strategy to enhance the breadth, durability, and potency of Ag-specific immune responses.
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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".