Cutting Edge: Identification of a Novel Chemokine Receptor That Binds Dendritic Cell- and T Cell-Active Chemokines Including ELC, SLC, and TECK
Bibliographic record
Abstract
Searching for new receptors of dendritic cell- and T cell-active chemokines, we used a combination of techniques to interrogate orphan chemokine receptors. We report here on human CCX CKR, previously represented only by noncontiguous expressed sequence tags homologous to bovine PPR1, a putative gustatory receptor. We employed a two-tiered process of ligand assignment, where immobilized chemokines constructed on stalks (stalkokines) were used as bait for adhesion of cells expressing CCX CKR. These cells adhered to stalkokines representing ELC, a chemokine previously thought to bind only CCR7. Adhesion was abolished in the presence of soluble ELC, SLC (CCR7 ligands), and TECK (a CCR9 ligand). Complete ligand profiles were further determined by radiolabeled ligand binding and competition with >80 chemokines. ELC, SLC, and TECK comprised high affinity ligands (IC50 <15 nM); lower affinity ligands include BLC and vMIP-II (IC50 <150 nM). With its high affinity for CC chemokines and homology to CC receptors, we provisionally designate this new receptor CCR10.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".