Type‐I interferons inhibit Delta‐like‐1‐dependent T cell development and increase apoptosis of developing thymocytes in vitro
Bibliographic record
Abstract
Individuals with HIV/AIDS exhibit a gradual depletion of CD4 + T cells in the periphery and a chronic loss of T cells within the thymus. Strikingly, the thymus from these individuals exhibits increased levels of type‐I interferons (IFNs): α(s) and β, suggesting that developing thymocytes are susceptible to apoptosis through increased production of type‐I IFNs. To determine whether type‐I IFNs directly effect T cell development, we cultured fetal liver‐derived mouse hematopoietic stem cells (HSCs) on OP9‐DL1 cells and examined through flow cytometry the CD4 − CD8 − double negative (DN) and CD4 + CD8 + double positive (DP) T cell populations that emerged. Specifically, addition of type‐1 IFNs reduced cellularity and blocked T cell differentiation at the DN1 to DN2 transition in a dose‐dependent manner. Type‐I IFNs mediated their effects directly to the HSCs independent of the OP9‐DL1 cells, as HSCs obtained from IFN‐receptor deficient (IFN AR −/− ) mice, but not IFN‐receptor sufficient (IFN AR +/+ ) mice, were refractive to IFN treatment, exhibited increased cellularity, and progressed to the DP stage. Increased apoptosis over time was observed in IFN‐susceptible, but not IFN‐insensitive fetal liver cells. These in vitro studies have also been extended to the development of human T cells from cord blood‐derived HSCs. Supported by grants from the OHTN and CIHR.
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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 | 0.001 |
| 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".