Microglia-derived IL-1β triggers p53-mediated cell cycle arrest and apoptosis in neural precursor cells
Why this work is in the frame
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Bibliographic record
Abstract
Neurogenesis persists in the adult brain and can contribute to learning and memory processes and potentially to regeneration and repair of the affected nervous system. Deregulated neurogenesis has been observed in neuropathological conditions including neurodegenerative diseases, trauma and stroke. However, the survival of neural precursor cells (NPCs) and newly born neurons is adversely affected by the inflammatory environment that arises as a result of microglial activation associated with injury or disease processes. In the present study, we have investigated the mechanisms by which microglia affect NPC proliferation and survival. Importantly, we demonstrate that interleukin-1β (IL-1β) produced by lipopolysaccharide/interferon-γ-activated microglia is necessary to induce cell cycle arrest and apoptosis in NPCs in vitro. Mechanistically, we show that IL-1β activates the tumor suppressor p53 through an oxidative stress-dependent mechanism resulting in p53-mediated induction of the cyclin-dependent kinase inhibitor p21 and the proapoptotic Bcl-2 (B-cell lymphoma-2) family members Puma (p53-upregulated modulator of apoptosis) and Noxa. Furthermore, we demonstrate that cell cycle arrest and apoptosis induced by recombinant IL-1β or activated microglia is attenuated in p53-deficient NPCs. Finally, we have determined that IL-1β induces NPC death via the p53-dependent induction of Puma leading to the activation of a Bax (Bcl-2-associated X protein)-mediated mitochondrial apoptotic pathway. In summary, we have elucidated a novel role for p53 in the regulation of NPC proliferation and survival during neuroinflammatory conditions that could be targeted to promote neurogenesis and repair in a number of neurological conditions.
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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 it