Suppressive activity of CD4+Foxp3+ regulatory T cells in an animal model of spontaneous CD8+ T cell-mediated demyelinating disease
Bibliographic record
Abstract
Dr. Fournier's laboratory has generated a mouse strain (L31 mice) that spontaneously develops a CD8+ T cell-mediated demyelinating disease in the central nervous system. In this model of dysregulated costimulation, CD4+ T cells have a regulatory role. A subset of CD4+ regulatory T cells that express the transcription factor Foxp3 have been shown to regulate autoimmune responses. In order to investigate this population's role in disease development, the goal of my M.Sc research project was to functionally characterize the CD4+Foxp3+ regulatory T cell population in L31 mice.We found that regulatory T cells from L31 mice were impaired in their ability to suppress the proliferation of effector T cells in vitro. In part, this was because B7.2 (CD86) expression impeded regulatory T cell suppressive activity. However, regulatory T cells delayed the onset of neurological symptoms in vivo. Although L31 Treg are not suppressive in vitro, our in vivo data suggest that they have a regulatory function in L31 disease development. This dichotomy could provide insights into the mechanisms by which these regulatory T cells control disease development in L31 mice.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".