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Record W1747486222 · doi:10.4049/jimmunol.168.11.5709

In Vivo Generation of Cytotoxic T Cells from Epitopes Displayed on Peptide-Based Delivery Vehicles

2002· article· en· W1747486222 on OpenAlexafffund
Kim S. Kawamura, Ruey‐Chyi Su, Linh T. Nguyen, Alisha R. Elford, Pamela S. Ohashi, Jean Gariépy

Bibliographic record

VenueThe Journal of Immunology · 2002
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversity of Toronto
FundersNational Cancer InstituteCanadian Institutes of Health Research
KeywordsCTL*EpitopeCytotoxic T cellIn vivoMHC class IPeptideMajor histocompatibility complexCell biologyBiologyIn vitroAntigenChemistryImmunologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

The development of nonviral, peptide-based constructs able to elicit protective in vivo CTL responses represents a major challenge in the design of future vaccines. We report the design of branched peptide delivery vehicles, termed loligomers, that facilitate the import, processing, and presentation of CTL epitopes onto nascent MHC class I molecules. These complexes are then effectively displayed on the surface of APCs. The intracellular delivery of CTL epitopes by loligomers prolonged the expression of Ag-MHC class I complexes on the surface of APCs in comparison with free CTL epitope alone. Furthermore, the injection of CTL epitope-containing loligomers into mice led to the generation of in vivo CTL responses and the induction of autoimmune disease in an animal model. Synthetic epitope-carrying, peptide-based delivery vehicles may represent useful components to be included in the formulation of future vaccines.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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

Citations9
Published2002
Admission routes2
Has abstractyes

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