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Record W4293490440 · doi:10.1016/j.xpro.2022.101652

Protocol for isolation and characterization of lung tissue resident memory T cells and airway trained innate immunity after intranasal vaccination in mice

2022· article· en· W4293490440 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

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsVaccinationImmunologyBronchoalveolar lavageInnate immune systemNasal administrationAcquired immune systemImmunityMedicineImmune systemAirwayAlveolar macrophageLungBiologyMacrophageInternal medicine

Abstract

fetched live from OpenAlex

Vaccination route dictates the quality and localization of immune responses within tissues. Intranasal vaccination seeds tissue-resident adaptive immunity, alongside trained innate responses within the lung/airways, critical for superior protection against SARS-CoV-2. This protocol encompasses intranasal vaccination in mice, step-by-step bronchoalveolar lavage for both cellular and acellular airway components, lung mononuclear cell isolation, and detailed flow cytometric characterization of lung tissue-resident memory T cell responses, and airway macrophage-trained innate immunity. For complete details on the use and execution of this protocol, please refer to Afkhami et al. (2022).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.250
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.304
Teacher spread0.290 · 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