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Record W1909166718

Expression and recognition of HLA-DR/Her-2 complexes on carcinoma cells

2006· dissertation· en· W1909166718 on OpenAlexfundno aff
Nicole J. Whittle

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2006
Typedissertation
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsnot available
FundersDivision of Graduate EducationMemorial University of Newfoundland
KeywordsCytokineHuman leukocyte antigenEpitopeclone (Java method)BiologyImmune systemCancer researchCellMolecular biologyImmunologyAntigenGeneBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Cancer patients frequently generate cellular immune response to Her-2, a protein implicated in promoting tumor growth. While 40% of cancers express HLA class II, the ability of class II⁺ tumor cells to process endogenous Her-2 and present immunogenic peptides for CD4⁺ T cell recognition is unknown. We addressed this question using a CD4⁺ T cell clone (TCL-6Dn) restricted to Her-2 peptide 883-899 (p883) presented by HLA-DRβ*0401. We measured the proliferation and cytokine response of TCL-6Dn to p883-loaded and Her-2⁺ tumor cells. Our results showed that TCL-6Dn proliferated strongly to p883-loaded DCs, yet TCL-6Dn lysed tumor cells in a p883-specific manner. Cytokine production analysis showed that TCL-6Dn recognized p883 and produced IFN-γ, GM-CSF, TNF-α and IL-4. Tumor cell lysis was mediated by a soluble factor produced by TCL-6Dn, but cell contact increased lysis. Furthermore, we provide evidence that p883 is a naturally processed HLA class II epitope presented by cancer cells.

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 score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.026
GPT teacher head0.251
Teacher spread0.225 · 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
Published2006
Admission routes1
Has abstractyes

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