Role of Nrf2 in Disease: Novel Molecular Mechanisms and Therapeutic Approaches – Pulmonary Disease/Asthma
Bibliographic record
Abstract
Nuclear factor erythroid 2-related factor 2 (Nrf2) is a major transcription factor involved in redox homeostasis and in the response induced by oxidative injury. Nrf2 is present in an inactive state in the cytoplasm of cells. Its activation by internal or external stimuli, such as infections or pollution, leads to the transcription of more than 500 elements through its binding to the antioxidant response element. The lungs are particularly susceptible to factors that generate oxidative stress such as infections, allergens and hyperoxia. Nrf2 has a crucial protective role against these ROS. Oxidative stress and subsequent activation of Nrf2 have been demonstrated in many human respiratory diseases affecting the airways, including asthma and chronic obstructive pulmonary disease (COPD), or the pulmonary parenchyma such as acute respiratory distress syndrome (ARDS) and pulmonary fibrosis. Several compounds, both naturally occurring and synthetic, have been identified as Nrf2 inducers and enhance the activation of Nrf2 and expression of Nrf2-dependent genes. These inducers have proven particularly effective at reducing the severity of the oxidative stress-driven lung injury in various animal models. In humans, these compounds offer promise as potential therapeutic strategies for the management of respiratory pathologies associated with oxidative stress but there is thus far little evidence of efficacy through human trials. The purpose of this review is to summarize the involvement of Nrf2 and its inducers in ARDS, COPD, asthma and lung fibrosis in both human and in experimental models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".