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Record W1479969085 · doi:10.4049/jimmunol.1202529

Identification of Pathogenic T Cell Epitopes Near Cathepsin Cleavage Sites in Thyroglobulin

2013· article· en· W1479969085 on OpenAlexafffund
Panayota Kolypetri, Hong Jiang, George Carayanniotis

Bibliographic record

VenueThe Journal of Immunology · 2013
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Institutes of Health Research
KeywordsThyroglobulinEpitopeCleavage (geology)Identification (biology)Computational biologyMolecular biologyBiologyAntigenImmunologyAntibodyBotany

Abstract

fetched live from OpenAlex

Experimental autoimmune thyroiditis, induced in mice after challenge with thyroglobulin (Tg), is known to be under the genetic control of the H2A(k) locus. Because cathepsins are known to influence proteolytic processing of Tg in vivo, we examined in this study whether putative H2A(k)-binding Tg epitopes, located near cathepsin cleavage sites within mouse Tg, have immunopathogenic properties. Cathepsin L, B, and D cleavage sites in mouse Tg were predicted based on homology with known cathepsin cleavage sites in rabbit Tg. We used an algorithm-based approach to identify H2A(k)-binding motifs within 20-aa residue segments adjacent to cathepsin cleavage sites, and five 12mer peptides encompassing these sequences were synthesized. Two of them, p2369 (aa 2369-2380) and p2439 (aa 2439-2450) were immunogenic, eliciting significant proliferative T cell responses using lymph node cells from peptide-primed mice and production of IL-2 and IFN-γ in recall assays in vitro. Both peptides induced experimental autoimmune thyroiditis upon direct challenge of CBA/J mice with peptide in CFA and by adoptive transfer of peptide-primed lymph node cells into naive recipient hosts, but neither peptide was characterized as dominant.

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 score0.001
Threshold uncertainty score0.002

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.253
Teacher spread0.243 · 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

Citations3
Published2013
Admission routes2
Has abstractyes

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