Ligand-induced growth and compaction of CD36 nanoclusters enriched in Fyn induces Fyn signaling
Bibliographic record
Abstract
Nanoclustering is an emerging organizational principle for membrane-associated proteins. The functional consequences of nanoclustering for receptor signaling remain largely unknown. Here, we applied quantitative multi-channel high- and super-resolution imaging to analyze the endothelial cell surface receptor CD36, the clustering of which upon binding to multivalent ligands, such as the anti-angiogenic factor thrombospondin-1 (TSP-1), is thought to be crucial for signaling. We found that a substantial fraction of unligated CD36 exists in nanoclusters, which not only promote TSP-1 binding but are also enriched with the downstream effector Fyn. Exposure to multivalent ligands (TSP-1 or anti-CD36 IgM) that result in larger and denser CD36 clusters activates Fyn. Conversely, pharmacological perturbations that prevent the enhancement of CD36 clustering by TSP-1 abrogate Fyn activation. In both cases, there is no detectable change in Fyn enrichment at CD36 nanoclusters. These observations reveal a crucial role for the basal organization of a receptor into nanoclusters that are enriched with the signal-transducing downstream effectors of that receptor, such that enhancement of clustering by multivalent ligands is necessary and sufficient to activate the downstream effector without the need for its de novo recruitment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".