Comparative sequence analysis of morbillivirus receptors and its implication in host range expansion
Bibliographic record
Abstract
SLAM (CD150) and nectin-4 are the major morbillivirus receptors responsible for virus pathogenesis and host range expansion. Recently, morbillivirus infections have been reported in unnatural hosts, including endangered species, posing a threat to their conservation. To understand the host range expansion of morbilliviruses, we generated the full-length sequences of morbillivirus receptors (goat, sheep, and dog SLAM, and goat nectin-4) and tried to correlate their role in determining host tropism. A high level of amino acid identity was observed between the sequences of related species, and phylogenetic reconstruction showed that the receptor sequences of carnivores, marine mammals, and small ruminants grouped separately. Analysis of the ligand binding region (V region; amino acid residues 52-136) of SLAM revealed high amino acid identity between small ruminants and bovine SLAMs. Comparison of canine SLAM with ruminants and non-canids SLAM revealed appreciable changes, including charge alterations. Significant differences between feline SLAM and canine SLAM have been reported. The binding motifs of nectin-4 genes (FPAG motif and amino acid residues 60, 62, and 63) were found to be conserved in sheep, goat, and dog. The differences reported in the binding region may be responsible for the level of susceptibility or resistance of a species to a particular morbillivirus.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".