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Replicating dendritic cells transmit internalized antigen to progeny for presentation (36.19)

2007· article· en· W24129850 on OpenAlexaff
Jun Diao, Erin Winter, Wenhao Chen, Mark S. Cattral

Bibliographic record

VenueThe Journal of Immunology · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsAntigenAntigen presentationBiologyCell biologyDendritic cellSpleenPopulationAntigen processingAdoptive cell transferImmunologyImmune systemT cellMedicine

Abstract

fetched live from OpenAlex

Abstract During steady state conditions spleen dendritic cells (DC) turnover every 2–3 days. Recent evidence indicates that local proliferation of spleen DC contributes substantially to their homeostasis. We and others have shown that the majority of these dividing DC arise from a distinct population of replication-competent immediate conventional DC precursors (cDCp). cDCp generate exclusive conventional DC that continue to replicate for several generations. The objective of this study was to determine whether DC can replicate after capturing antigen, and whether replication provides a mechanism for disseminating antigen to their progeny. Real-time confocal microscopy revealed that replicating DC internalize and directly transfer model antigens to successive generations of progeny. Soluble protein antigen (ovalbumin) inherited by DC progeny in vitro or in vivo was presented effectively to OT-1 T cells. Other mechanisms of inter-DC antigen transfer (e.g. exosomes, cell membrane exchange) did not contribute to antigen acquisition by DC progeny. Our results suggest that replication of antigen-bearing DC is a fundamental behavior and may provide a novel mechanism for increasing the frequency of antigen-bearing DC, and duration of antigen presentation.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.019
GPT teacher head0.301
Teacher spread0.282 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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