RIP Kinase death pathways regulate B cell homeostasis and splenic architecture
Bibliographic record
Abstract
Abstract Receptor-interacting protein kinase (RIPK) 1, RIPK3, and Caspase-8, are essential adapter proteins in death receptor-induced apoptosis and programmed necrosis. Apoptosis and necroptosis are crucial for normal cell development, homeostasis, and immune responses. RIP kinases and Caspase-8 form parts of multiprotein complexes like the Death-Inducing Signaling Complex (DISC) and the necrosome, thus mediating signaling events in these cell death pathways. We compared RipK3−/−, RipK1−/−RipK3−/−Caspase-8−/−, RipK3−/−Caspase-8−/−, and RIPK1 kinase-dead (RIPK1kd) mice to define the role of RIP kinase inflammatory pathways and Caspase-8 in immune responses and lymphocyte development. Preliminary studies show that lack of RIPK1 and Caspase-8, but not RIPK3, leads to the accumulation of Marginal Zone (MZ) B cells. Evidence from mixed-bone marrow chimera experiments reveals an intrinsic requirement for RIPK1 and caspase 8 in normal B cell differentiation post-T2 B cell status. Immunofluorescence showed splenic architecture disorganization in the T cell zone and MZB populations in RIPK-deficient mice. Surprisingly, humoral immune responses to T-dependent and T-independent antigens were largely normal, but immunization-induced splenic GC formation was diminished in mice lacking both Caspase-8 and RIPK3. Elucidation of cell development/death in the context of RIPK1 (whose ubiquitination status influences cellular homeostasis) could lead to better priming of B cells for chemotherapy-induced apoptosis. Previous studies also suggest human RIP kinases are potential therapeutic targets for treating a wide range of autoimmune, inflammatory, and neurodegenerative diseases.
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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".