Impaired Interleukin-2 Synthesis and T Cell Proliferation Following Antibody-mediated CD3 and CD2 or CD28 Cross-linking in<i>Trans</i>: Evidence that T Cell Activation Requires the Engagement of Costimulatory Molecules Within the Immunological Synapse
Bibliographic record
Abstract
Although the T cell costimulatory molecules CD2 and CD28 are enriched within the immunological synapse (IS), it has been suggested that costimulatory molecules need not be localized to the contact site between a T cell and an antigen-presenting cell (APC) in order to costimulate T cell activation. To determine whether CD2 or CD28 engagement outside of the IS is sufficient to costimulate T cell activation, we compared mouse T cell responses to anti-CD3 and anti-CD2 monoclonal antibodies (mAbs) or anti-CD3 and anti-CD28 mAbs immobilized on the same, i.e., in cis, or on different, i.e., in trans, 10 micron polystyrene microspheres. In comparison to T cells that were stimulated with co-immobilized anti-CD3 and anti-CD2 or anti-CD28 mAbs, DNA synthesis, interleukin (IL)-2 production, and cellular proliferation were all severely impaired following T cell stimulation with anti-CD3 and anti-CD2 mAbs or anti-CD3 and anti-CD28 mAbs on different microspheres. Deficient cellular proliferation and IL-2 synthesis by T cells that experienced CD3 and CD2 or CD28 cross-linking in trans provides evidence that costimulatory molecules must function in the context of the IS for optimal T cell activation.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".