Withaferin-A Treatment Alleviates TAR DNA-Binding Protein-43 Pathology and Improves Cognitive Function in a Mouse Model of FTLD
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Withaferin-A, an active withanolide derived from the medicinal herbal plant Withania somnifera induces autophagy, reduces TDP-43 proteinopathy, and improves cognitive function in transgenic mice expressing mutant TDP-43 modelling FTLD. TDP-43 is a nuclear DNA/RNA-binding protein with cellular functions in RNA transcription and splicing. Abnormal cytoplasmic aggregates of TDP-43 occur in several neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD), and limbic-predominant age-related TDP-43 encephalopathy (LATE). To date, no effective treatment is available for TDP-43 proteinopathies. Here, we tested the effects of withaferin-A (WFA), an active withanolide extracted from the medicinal herbal plant Withania somnifera, in a transgenic mouse model of FTLD expressing a genomic fragment encoding mutant TDP-43G348C. WFA treatment ameliorated the cognitive performance of the TDP-43G348C mice, and it reduced NF-κB activity and neuroinflammation in the brain. WFA alleviated TDP-43 pathology while it boosted the levels of the autophagic marker LC3BII in the brain. These data suggest that WFA and perhaps other autophagy inducers should be considered as potential therapy for neurodegenerative diseases with TDP-43 pathology.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it