Effects of modified CD80 on the co-stimulation of T cell
Bibliographic record
Abstract
In accordance with the two-signal model, optimal T cell activation can only occur in the presence of a primary antigen specific signal, provided by the T cell receptor, and a second co-stimulatory signal. The most potent co-stimulatory molecules identified to date are the CD28/CTLA-4 receptors with their CD80/CD86 ligands, found on T cells and antigen presenting cells (APC) respectively. Many studies have implicated the V-domain of CD80 and CD86 to be responsible for the direct interaction with CD28/CTLA-4. Conversely, few studies have shown that the C-domain CD80 is crucial for the interaction and ultimate suppression of T cell activation and proliferation by binding to CTLA4. The thesis herein identifies amino acids located in the C-domain of CD80 that proves critical for the binding of CTLA-4. This particular mutant, N5-6, exhibits a preferential binding to CTLA-4. We observe 7-fold enhanced binding to CTLA-4 while maintaining its conventional binding to CD28. Functionally, this mutant is still capable of activating T cells via CD28. Interestingly, binding to CD28 is not inhibited by the presence of soluble CTLA-4 as a competitive inhibitor despite its greater affinity. As a DNA vaccine, this mutant, along with other mutants exhibiting differential binding to CD28/CTLA-4, can be used as a means modulate T cell responses. This can provide a therapeutic approach to the treatment of autoimmunity or aid in the eradication of reservoir cells in HIV and HSV infections.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".