Withania somnifera Reverses Transactive Response DNA Binding Protein 43 Proteinopathy in a Mouse Model of Amyotrophic Lateral Sclerosis/Frontotemporal Lobar Degeneration
Bibliographic record
Abstract
Abnormal cytoplasmic mislocalization of transactive response DNA binding protein 43 (TARDBP or TDP-43) in degenerating neurons is a hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with ubiquitin-positive inclusions (FTLD-U). Our previous work suggested that nuclear factor kappa B (NF-κB) may constitute a therapeutic target for TDP-43-mediated disease. Here, we investigated the effects of root extract of Withania somnifera (Ashwagandha), an herbal medicine with anti-inflammatory properties, in transgenic mice expressing a genomic fragment encoding human TDP-43 A315T mutant. Ashwagandha extract was administered orally to hTDP-43 A315T mice for a period of 8 weeks starting at 64 and 48 weeks of age for males and females, respectively. The treatment of hTDP-43 A315T mice ameliorated their motor performance on rotarod test and cognitive function assessed by the passive avoidance test. Microscopy examination of tissue samples revealed that Ashwagandha treatment of hTDP-43 A315T mice improved innervation at neuromuscular junctions, attenuated neuroinflammation, and reduced NF-κB activation. Remarkably, Ashwagandha treatment reversed the cytoplasmic mislocalization of hTDP-43 in spinal motor neurons and in brain cortical neurons of hTDP-43 A315T mice and it reduced hTDP-43 aggregation. In vitro evidence is presented that the neuronal rescue of TDP-43 mislocalization may be due to the indirect effect of factors released from microglial cells exposed to Ashwagandha. These results suggest that Ashwagandha and its constituents might represent promising therapeutics for TDP-43 proteinopathies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".