Investigation of CD36 interactome provides insights into multimolecular complexes necessary for anti-angiogenic signalling
Bibliographic record
Abstract
Signal transduction is a fundamental process that enables cells to adapt to external cues and organize adequate responses including survival, death, growth, and homeostasis. A key mechanism modulating signal transduction relies on the formation of multimolecular complexes optimized for specificity, modularity and signal amplification. The scavenger receptor CD36, which binds diverse ligands in different cellular contexts, illustrates this principle. To uncover the nature of CD36 multimolecular complexes, we employed a proximity biotinylation labeling approach on human endothelial cells, where CD36 binds to thrombospondin-1 (TSP-1) to initiate a signaling cascade promoting programmed cell death. Using biotin capture and mass spectrometry protein identification, we uncovered a list of proteins in the vicinity of CD36. This list of candidates was refined by proximity ligation assays. The relationship between key CD36 interacting molecules, in particular active integrin beta-1 (ITGB1) and CD9, was further decoded by conditional colocalization analysis, providing support for their association within a tri-molecular complex. The implication of selected candidates in the signaling function of CD36 was further evaluated using shRNA knockdown, revealing that active ITGB1 is essential for Fyn activation downstream of CD36, with the tetraspanin playing a connecting role between CD36 and active ITGB1. Our approach to investigating CD36 complexes emphasizes the complexity and fundamental role of protein-protein interactions and coordination in the context of transmembrane signal transduction.
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) | 0.002 | 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".