Hierarchical Regulation of CTLA-4 Dimer-Based Lattice Formation and Its Biological Relevance for T Cell Inactivation
Bibliographic record
Abstract
CTLA-4 is an activation-induced, homodimeric inhibitory receptor in T cells. Recent crystallographic reports have suggested that it may form lattice-like arrays on the cell surface upon binding B7.1/B7.2 (CD80, CD86) molecules. To test the biological relevance of these CTLA-4-B7 lattices, we introduced a C122A point mutation in human CTLA-4, because this residue was shown to be essential for dimerization in solution. Surprisingly, we found that up to 35% of C122A CTLA-4 dimerized in human T lymphocytes. Moreover, C122A CTLA-4 partitioned within lipid rafts, colocalized with the TCR in the immunological synapse, and inhibited T cell activation. C122-independent dimerization of CTLA-4 involved N-glycosylation, because further mutation of the N78 and N110 glycosylation sites abrogated dimerization. Despite being monomeric, the N78A/N110A/C122A triple mutant CTLA-4 localized in the immunological synapse and inhibited T cell activation. Such functionality correlated with B7-induced dimerization of these mutant molecules. Based on these data, we propose a model of hierarchical regulation of CTLA-4 oligomerization by which B7 binding ultimately determines the formation of dimer-dependent CTLA-4 lattices that may be necessary for triggering B7-dependent T cell inactivation.
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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) | 0.001 | 0.000 |
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.
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".