Bim is a candidate gene in the regulation of merocytic dendritic cell proportion
Bibliographic record
Abstract
Abstract In contrast to conventional dendritic cells (cDC), when merocytic DC (mcDC) present antigens (Ag) derived from apoptotic bodies, T cell anergy is reversed rather than induced. Although helpful to tumour clearance, reversing T cell anergy is detrimental in autoimmunity. Interestingly, mcDC are present in higher proportion in type 1 diabetes (T1D)-prone NOD mice than in B6 mice. Recently, we found that the Idd13 T1D locus is linked to the control of mcDC number. Indeed, NOD.B6-Idd13 congenic mice are resistant to T1D and have the same low number of mcDC as the parental B6 mice. Thus, we hypothesize that defining the genetic factor implicated in the regulation of mcDC number could help maintain self-tolerance and prevent T1D onset. Within the Idd13 locus, both B2m and Bim are likely candidate genes. By exploiting both B2m−/−and Bim−/−mice, we show that B2m does not affect mcDC number while mcDC were significantly increased in Bim−/−mice. Competitive hematopoietic chimera validate Bim as an intrinsic factor implicated in the regulation of mcDC proportion. In line with a role for Bim in regulating mcDC number, we demonstrate that the caspase activity and Bcl2 expression is not differentially expressed between the different mouse model, suggesting that Bim is implicated in mcDC proportion regulation via a caspase-independent pathway. Together, these data demonstrate that Bim, encoded within the Idd13 locus on the chromosome 2 modulates the number of mcDC. Identifying factors that facilitate apoptosis of mcDC may help prevent autoimmunity. Still, whether restoring Bim expression in NOD mice would prevent T1D remains to be addressed.
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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) | 0.002 | 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".