Mitigation of ALS Pathology by Neuron-Specific Inhibition of Nuclear Factor Kappa B Signaling
Bibliographic record
Abstract
To investigate the role of neuronal NF-κB activity in pathogenesis of amyotrophic lateral sclerosis (ALS), we generated transgenic mice with neuron-specific expression of a super-repressor form of the NF-κB inhibitor (IκBα-SR), which were then crossed with mice of both sexes, expressing ALS-linked gene mutants for TAR DNA-binding protein (TDP-43) and superoxide dismutase 1 (SOD1). Remarkably, neuronal expression of IκBα-SR transgene in mice expressing TDP-43A315T or TDP-43G348C mice led to a decrease in cytoplasmic to nuclear ratio of human TDP-43. The mitigation of TDP-43 neuropathology by IκBα-SR, which is likely due to an induction of autophagy, was associated with amelioration of cognitive and motor deficits as well as reduction of motor neuron loss and gliosis. Neuronal suppression of NF-κB activity in SOD1G93A mice also resulted in neuroprotection with reduction of misfolded SOD1 levels and significant extension of life span. The results suggest that neuronal NF-κB signaling constitutes a novel therapeutic target for ALS disease and related disorders with TDP-43 proteinopathy. SIGNIFICANCE STATEMENT This study reports that neuron-specific expression of IκB super-repressor mitigated behavioral and pathologic changes in transgenic mouse models of amyotrophic lateral sclerosis expressing mutant forms of either Tar DNA-binding protein 43 or superoxide dismutase. The results suggest that neuronal NF-κB signaling constitutes a novel therapeutic target for amyotrophic lateral sclerosis and related disorders with Tar DNA-binding protein 43 proteinopathy.
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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".