Validation of IKK<i>β</i> as therapeutic target in airway inflammatory disease by adenoviral‐mediated delivery of dominant‐negative IKK<i>β</i> to pulmonary epithelial cells
Bibliographic record
Abstract
Asthma is an inflammatory disease of the lungs and the transcription factor NF-kappa B regulates the production of numerous inflammatory mediators that may have a role in the pathogenesis of asthma. Hence, the signalling pathways leading to NF-kappa B activation are considered prime targets for novel anti-inflammatory therapies. The prevention of NF-kappa B activity in mice, through the knockout of IKK beta or p65, causes fatal liver degeneration in utero making it difficult to determine the full implications of inhibiting NF-kappaB activity in tissues physiologically relevant to human diseases. This study used adenovirus delivery of a dominant inhibitor of NF-kappaB (I kappa B alpha delta N) and dominant-negative IKK alpha (IKK alpha(KM)) and IKK beta (IKK beta(KA)) to investigate the role of the individual IKKs in NF-kappa B activation and inflammatory gene transcription by human pulmonary A549 cells. Overexpression of IKK beta(KA) or I kappa B alpha delta N prevented NF-kappa B-dependent transcription and DNA binding. IKK beta(KA) also prevented I kappa B alpha kinase activity. Similarly, IKK beta(KA) and I kappa B alpha delta N overexpression also inhibited IL-1beta- and TNF alpha-dependent increases in ICAM-1, IL-8 and GM-CSF in addition to IL-1beta-mediated increases in cyclooxygenase-2 expression, whereas IKK alpha(KM) overexpression had little effect on these outputs. IKK beta(KA) also reduced cell viability and induced caspase-3 and PARP cleavage regardless of the stimuli, indicating the induction of apoptosis. This effect seemed to be directly related to IKK beta kinase activity since I kappa B alpha delta N only induced PARP cleavage in TNF alpha-treated cells. These results demonstrate that inhibition of IKK beta and NF-kappa B suppresses inflammatory mediator production and reduces A549 cell viability. Thus, novel therapies that target IKK beta could have potent anti-inflammatory effects and may be beneficial in the treatment of certain cancers.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".