Local changes in lipid environment of T cell receptor microclusters regulate membrane binding by the CD3epsilon cytoplasmic domain (P1103)
Bibliographic record
Abstract
Abstract The CD3epsilon and zeta cytoplasmic domains of the T cell receptor bind to the inner leaflet of the plasma membrane, and a previous NMR structure showed that both tyrosines of the CD3epsilon Immuno-tyrosine based activation motif partition into the bilayer. Electrostatic interactions between acidic phospholipids and clusters of basic CD3epsilon residues were previously shown to be essential for CD3epsilon and zeta membrane binding. Phosphatidylserine is the most abundant negatively charged lipid on the inner leaflet of the plasma membrane and makes a major contribution to membrane binding by the CD3epsilon cytoplasmic domain. Here we show that T cell receptor triggering by peptide-MHC complexes induces dissociation of the CD3epsilon cytoplasmic domain from the plasma membrane. Release of the CD3epsilon cytoplasmic domain from the membrane is accompanied by a substantial focal reduction in negative charge and phosphatidylserine density in T cell receptor microclusters. The localized reduction in phosphatidylserine density is explained by reduced diffusion of this lipid into synapses. These changes in the lipid composition of T cell receptor microclusters even occur when receptor signaling is blocked with a Src kinase inhibitor. Local changes in the lipid composition of the microclusters thus render the CD3epsilon cytoplasmic domain accessible during early stages of T cell activation.
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 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".