T-cell receptor repertoires of wild mice
Bibliographic record
Abstract
This data repository hosts the repertoires of the mice investigated in the study: The T-cell receptor repertoire of wild mice. Study Abstract: Here we characterize the T-cell receptor (TCR) repertoire of wild mice to provide a resource for eco-immunology and to better understand wild animals’ immune state. While laboratory mice are central to immunological research, their immune systems differ significantly from those of their wild counterparts who are exposed to more intense immunological stimulation from a broader range of infections. We performed high-throughput sequencing of the TCR alpha and beta chains of CD4+ and CD8+ T-cells isolated from 65 wild Mus musculus domesticus captured at two UK sites. We analysed repertoire richness and diversity in relation to mouse age, sex, and sample location. The results show that wild mice have large TCR repertoires. We found that repertoire richness, which measures the breadth of the repertoire, was not significantly affected by mouse age or sex, suggesting that wild mice maintain the capacity to respond to novel antigens throughout their lives. In contrast, repertoire diversity (measured by Shannon’s index) was significantly higher in males than females and decreased with age. This low diversity, coupled with constant richness, points to female and older mice having comparatively more highly abundant clones in their repertoires, likely because of chronic exposure to persistent pathogens in their environment. Individual mice shared a considerable number of TCR sequences, with greater sharing observed between mice from the same location, suggesting that local environmental pressures shape the TCR repertoire. These findings provide a novel and valuable description of the wild mouse TCR, revealing an immune system that balances maintaining a broad response capacity with developing strong, lasting responses to infections in the natural environment.
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 | 0.002 | 0.001 |
| 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) | 0.004 | 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".