The evolution of the class A scavenger receptors
Bibliographic record
Abstract
BACKGROUND: The class A scavenger receptors are a subclass of a diverse family of proteins defined based on their ability to bind modified lipoproteins. The 5 members of this family are strikingly variable in their protein structure and function, raising the question as to whether it is appropriate to group them as a family based on their ligand binding abilities. RESULTS: To investigate these relationships, we defined the domain architecture of each of the 5 members followed by collecting and annotating class A scavenger receptor mRNA and amino acid sequences from publicly available databases. Phylogenetic analyses, sequence alignments, and permutation tests revealed a common evolutionary ancestry of these proteins, indicating that they form a protein family. We postulate that 4 distinct gene duplication events and subsequent domain fusions, internal repeats, and deletions are responsible for the diverse protein structures and functions of this family. Despite variation in domain structure, there are highly conserved regions across all 5 members, indicating the possibility that these regions may represent key conserved functional motifs. CONCLUSIONS: We have shown with significant evidence that the 5 members of the class A scavenger receptors form a protein family. We have indicated that these receptors have a common origin which may provide insight into future functional work with these proteins.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".