A TCR β-Chain Motif Biases toward Recognition of Human CD1 Proteins
Bibliographic record
Abstract
Abstract High-throughput TCR sequencing allows interrogation of the human TCR repertoire, potentially connecting TCR sequences to antigenic targets. Unlike the highly polymorphic MHC proteins, monomorphic Ag-presenting molecules such as MR1, CD1d, and CD1b present Ags to T cells with species-wide TCR motifs. CD1b tetramer studies and a survey of the 27 published CD1b-restricted TCRs demonstrated a TCR motif in humans defined by the TCR β-chain variable gene 4-1 (TRBV4-1) region. Unexpectedly, TRBV4-1 was involved in recognition of CD1b regardless of the chemical class of the carried lipid. Crystal structures of two CD1b-specific TRBV4-1+ TCRs show that germline-encoded residues in CDR1 and CDR3 regions of TRBV4-1–encoded sequences interact with each other and consolidate the surface of the TCR. Mutational studies identified a key positively charged residue in TRBV4-1 and a key negatively charged residue in CD1b that is shared with CD1c, which is also recognized by TRBV4-1 TCRs. These data show that one TCR V region can mediate a mechanism of recognition of two related monomorphic Ag-presenting molecules that does not rely on a defined lipid Ag.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".