DDO1002, an NRF2–KEAP1 inhibitor, improves hematopoietic stem cell aging and stress response
Bibliographic record
Abstract
Oxidative stress diminishes the functionality of hematopoietic stem cells (HSCs) as age advances, with heightened reactive oxygen species (ROS) levels exacerbating DNA damage, cellular senescence, and hematopoietic impairment. DDO1002, a potent inhibitor of the NRF2-KEAP1 pathway, modulates the expression of antioxidant genes. Yet, the extent to which it mitigates hematopoietic decline post-total body irradiation (TBI) or in the context of aging remains to be elucidated. Our study has elucidated the role of DDO1002 in modulating NRF2 activity, which, in turn, activates the NRF2-driven antioxidant response element (ARE) signaling cascade. This activation can diminish intracellular levels of ROS, thereby attenuating cellular senescence. In addition, DDO1002 has been demonstrated to ameliorate DNA damage and avert HSC apoptosis, underscoring its potential to mitigate hematopoietic injury precipitated by TBI. Competitive transplantation assay revealed that the administration of DDO1002 can improve the reconstitution and self-renewal capacity of HSCs in aged mice. Single-cell sequencing analysis elucidated that DDO1002 treatment attenuated intracellular inflammatory signaling pathways and mitigated ROS pathway in aged HSCs, suggesting its potential to restore the viability of these cells. Consequently, DDO1002 effectively activated the NRF2-ARE pathway, delaying cellular senescence and ameliorating impaired hematopoiesis, thereby demonstrating its potential as a therapeutic agent for age-related hematopoietic disorders.
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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) | 0.001 | 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 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".