Immunomodulators as adjuvants for vaccines and antimicrobial therapy
Bibliographic record
Abstract
A highly effective strategy for combating infectious diseases is to enhance host defenses using immunomodulators, either preventatively, through vaccination, or therapeutically. The effectiveness of many vaccines currently in use is due in part to adjuvants, molecules that have little immunogenicity by themselves but which help enhance and appropriately skew the immune response to an antigen. The development of new vaccines necessitates the development of new types of adjuvants to ensure an appropriate immune response. Herein, we review commonly used vaccine adjuvants and discuss promising adjuvant candidates. We also discuss various other immunomodulators (namely cytokines, Toll-like receptor agonists, and host defense peptides) that are, or have potential to be, useful for antimicrobial therapies that exert their effects by boosting host immune responses rather than targeting pathogens directly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".