Missed opportunities: Managing achievement and difference in an urban public college preparatory magnet high school
Bibliographic record
Abstract
Regulatory T (Treg) cells play an important role in the regulation of immune responses but whether Treg will induce tolerance in transplant recipients in the clinic remains unknown. Our previous studies have shown that TCRαβ(+)CD3(+)CD4⁻CD8⁻NK1.1⁻ (double negative, DN) T cells suppress T cell responses and prolong allograft survival in a single locus MHC-mismatched mouse model. In this study, we investigated the role of DNT cells in a more robust, fully MHC-mismatched BALB/c to C57BL/6 transplantation model, which may be more clinically relevant. Adoptive transfer of DNT cells in combination with short-term rapamycin treatment (days 1-9) induced long-term heart allograft survival (101±31 vs. 39±13 days rapamycin alone, p<0.01). Furthermore adoptive transfer DNT cells augmented CD4+Foxp3+ Treg cells accumulation in transplant recipients while depletion of CD4(+) Treg cells by anti-CD25 inhibited the effect of DNT cells on long-term graft survival (48±12 days vs. 101±31 days, p<0.001). In conclusion, DNT cells combined with short-term immunosuppression can prolong allograft survival, which may be through the accumulation of CD4(+)Foxp3(+) Treg cells in the recipient. Our result suggests that allograft tolerance may require the co-existence of different type Treg cell phenotypes which are affected by current immunosuppression.
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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 | 0.000 | 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) | 0.000 | 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 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".