Arginine-Glycine-Aspartate–Binding Integrins as Therapeutic and Diagnostic Targets
Bibliographic record
Abstract
Arginine-glycine-aspartate (RGD)-binding integrins, including αvβ1, αvβ3, αvβ5, αvβ6, αvβ8, α5β1, αIIbβ3, and α8β1, recognize the tripeptide motif RGD in their ligands. RGD-binding integrins are involved in various cell functions, including cell proliferation, survival, differentiation, and motility that are critically important to both health and disease. The diagnostic and therapeutic value of some RGD-binding integrin inhibitors are either clinically proven or at different stages of development. In this review, we first summarized the structure and signaling characteristics of RGD-binding integrins. We then discussed the functions of RGD-binding integrins and their association with human disease. Finally, we recapitulated the research efforts and clinical trials of targeting RGD-binding integrins for the diagnosis and treatment of human disease. This comprehensive review of the current advances in RGD-binding integrins could assist scientists and clinicians in gaining a complete understanding of this group of molecules. It can also contribute to the design of new projects to further advance this field of research and to better apply the research results to benefit patients in clinical practice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".