Quantification and Modeling of Tripartite CD2-, CD58FC Chimera (Alefacept)-, and CD16-mediated Cell Adhesion
Bibliographic record
Abstract
Alefacept is a chimeric protein combining CD58 immunoglobulin-like domain 1 with human IgG1 Fc. Alefacept mediates adhesion by bridging CD2 on T cells to activating Fc receptors on effector cells, but the equilibrium binding parameters have not been determined. Alefacept mediated T cell killing by NK cells and adhesion between CD2- and CD16-expressing cells at an optimum concentration of 100 nM. We introduce novel measurements with supported planer bilayers, from which key two-dimensional and three-dimensional parameters can be determined by data fitting. Alefacept competitively inhibited cell bilayer adhesion mediated by the CD2-CD58 interaction. Alefacept mediated maximal adhesion of CD2(+) T cells to CD16B, an Fc receptor, in planar bilayers at 500 nM. A mechanistic model for alefacept-mediated cell-bilayer adhesion allowed fitting of the data and determination of two-dimensional binding parameters. These included the density of bonds in the adhesion area, which grew to maintain a consistent average bond density of 200 molecules/microm(2) and two-dimensional association constants of 3.1 and 630 microm(2) for bivalently and monovalently bound forms of alefacept, respectively. The maximum number of CD16 bound and the fit value of 4,350 CD2 per cell are much lower than the 40,000 CD2 per cell measured with anti-CD2 Fab. These results suggest that additional information is needed to correctly predict Alefacept-mediated bridge formation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".