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Record W3009091764 · doi:10.1002/jlb.4mr0220-446r

Innate immune memory of tissue-resident macrophages and trained innate immunity: Re-vamping vaccine concept and strategies

2020· review· en· W3009091764 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Leukocyte Biology · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
FundersCanadian Institutes of Health Research
KeywordsInnate immune systemBiologyImmunological memoryImmunityImmunologyImmune systemAcquired immune systemMacrophageGenetics

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.335
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it