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Record W2087265337 · doi:10.1002/eji.200425309

Frontline: Peripheral priming of alloreactive T cells by the direct pathway of allorecognition

2004· article· en· W2087265337 on OpenAlexafffund
Myriam Baratin, Karina Bonin, Claude Daniel

Bibliographic record

VenueEuropean Journal of Immunology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsInstitut National de la Recherche Scientifique
FundersCanadian Institutes of Health ResearchArmand-Frappier Foundation
KeywordsAllorecognitionPriming (agriculture)BiologyImmunologyImmune systemLymphContext (archaeology)Lymphatic systemSensitizationT cellAntigenDirect pathway of movementImmune tolerancePathologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Recent studies, though controversial, have suggested that secondary lymphoid organs may not constitute an essential site for the initiation of immune responses to transplant antigens. However, this issue has never been examined in the context of direct and indirect allorecognition. Here, we characterized immune responses arising in draining lymph nodes and skin allografts, in a murine model based on a single T cell clonotype where these two pathways can be independently studied. In this model, graft rejection by the direct or the indirect pathway occurred with similar kinetics, although initiation of the alloreactive responses was clearly different. During indirect responses, expansion and activation of alloreactive T cells were first observed in draining lymph nodes, at day 7 post-transplant, and graft-infiltrating T cells were observed later, at day 11. In striking contrast, directly activated alloreactive T cells were detected at an early stage inside the graft, and only later in the draining lymph nodes, after skin allograft rejection was almost completed. These results suggest that sensitization of naive T cells through the direct pathway could take place outside secondary lymphoid organs.

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 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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 teacher head, 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

Citations20
Published2004
Admission routes2
Has abstractyes

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