Innate immune memory of tissue-resident macrophages and trained innate immunity: Re-vamping vaccine concept and strategies
Bibliographic record
Abstract
In the past few years, our understanding of immunological memory has evolved remarkably due to a growing body of new knowledge in innate immune memory and immunity. Immunological memory now encompasses both innate and adaptive immune memory. The hypo-reactive and hyper-reactive types of innate immune memory lead to a suppressed and enhanced innate immune protective outcome, respectively. The latter is also named trained innate immunity (TII). The emerging information on innate immune memory has not only shed new light on the mechanisms of host defense but is also revolutionizing our long-held view of vaccination and vaccine strategies. Our current review will examine recent progress and knowledge gaps in innate immune memory with a focus on tissue-resident Mϕs, particularly lung Mϕs, and their relationship to local antimicrobial innate immunity. We will also discuss the impact of innate immune memory and TII on our understanding of vaccine concept and strategies and the significance of respiratory mucosal route of vaccination against respiratory pathogens.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".