The diverse roles of C-type lectin-like receptors in immunity
Bibliographic record
Abstract
Our understanding of the C-type lectin-like receptors (CTLRs) and their functions in immunity have continued to expand from their initial roles in pathogen recognition. There are now clear examples of CTLRs acting as scavenger receptors, sensors of cell death and cell transformation, and regulators of immune responses and homeostasis. This range of function reflects an extensive diversity in the expression and signaling activity between individual CTLR members of otherwise highly conserved families. Adding to this diversity is the constant discovery of new receptor binding capabilities and receptor-ligand interactions, distinct cellular expression profiles, and receptor structures and signaling mechanisms which have expanded the defining roles of CTLRs in immunity. The natural killer cell receptors exemplify this functional diversity with growing evidence of their activity in other immune populations and tissues. Here, we broadly review select families of CTLRs encoded in the natural killer cell gene complex (NKC) highlighting key receptors that demonstrate the complex multifunctional capabilities of these proteins. We focus on recent evidence from research on the NKRP1 family of CTLRs and their interaction with the related C-type lectin (CLEC) ligands which together exhibit essential immune functions beyond their defined activity in natural killer (NK) cells. The ever-expanding evidence for the requirement of CTLR in numerous biological processes emphasizes the need to better understand the functional potential of these receptor families in immune defense and pathological conditions.
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 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) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".