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Record W1975869283 · doi:10.1038/icb.2014.96

Lymphocyte repertoire selection and intracellular self/non‐self‐discrimination: historical overview

2014· review· en· W1975869283 on OpenAlexafffund
Donald R. Forsdyke

Bibliographic record

VenueImmunology and Cell Biology · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsQueen's University
FundersQueen's University
KeywordsIntracellularExtracellularBiologyMajor histocompatibility complexNegative selectionReceptorCell biologyGeneticsImmune systemGenomeGene

Abstract

fetched live from OpenAlex

Immunological self/non-self-discrimination is conventionally seen as an extracellular event, involving interactions been receptors on T cells pre-educated to discriminate and peptides bound to major histocompatibility complex proteins (pMHCs). Mechanisms by which non-self peptides might first be sorted intracellularly to distinguish them from the vast excess of self-peptides have long been called for. Recent demonstrations of endogenous peptide-specific clustering of pMHCs on membrane rafts are indicative of intracellular enrichment before surface display. The clustering could follow the specific aggregation of a foreign protein that exceeded its solubility limit in the crowded intracellular environment. Predominantly entropy-driven, this homoaggregation would colocalize identical peptides, thus facilitating their collective presentation. Concentrations of self-proteins are fine-tuned over evolutionary time to avoid this. Disparate observations, such as pyrexia and female susceptibility to autoimmune disease, can be explained in terms of the need to cosegregate cognate pMHC complexes internally before extracellular display.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2014
Admission routes2
Has abstractyes

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