CXCR4, un récepteur de chimiokine aux multiples talents
Bibliographic record
Abstract
CXCR4 is a clinically relevant chemokine receptor that has first gained attention as one of the cofactors for HIV entry into target cells. Moreover, the receptor is involved in cancer cell migration to distant metastatic sites and immune effector recruitment in inflammatory diseases such as asthma and rheumatoid arthritis. Unfortunately, pharmacologic intervention is complicated by the vital function of CXCR4 in the organism. The most prominent of these functions is its role in stem cell homing. The CXCR4 chemokine ligand, produced by bone marrow stromal cells, leads both to migration of hematopoietic stem cells towards this niche and their retention in this compartment. As models of G-protein coupled receptor (GPCR) activation evolve, it becomes clear that multiple factors modulate the functional outcome of ligand binding to a receptor. Modulation of GPCR activity, for example by allosteric ligands, may permit more subtle therapeutic approaches adapted to long term treatment. In addition, GPCR signalling can be altered by hetero-oligomerization of GPCRs. In this perspective, it might be possible to achieve modulation of GPCR signalling by also targeting the oligomerization partner of a given receptor. This approach is described using the example of strategies that aim at the optimization of stem cell homing in the context of cord blood-derived hematopoietic stem cell transplantation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".