Long-term benefits of TUDCA supplement in ARSACS zebrafish model
Bibliographic record
Abstract
Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is an early-onset neurodevelopmental and neurodegenerative disorder characterized by ataxia, spasticity, and peripheral neuropathy. However, several studies have highlighted that some patients also experience cognitive, emotional and social deficits, suggesting a more complex clinical picture that extends beyond motor symptoms. Building on these findings, this study aimed to: (i) investigate locomotor, social and cognitive deficits in adult sacs -/- zebrafish versus wild-type (WT) controls through behavioural tests; (ii) identify molecular patterns associated with the adult disease phenotype using transcriptomic and proteomic analyses of sacs -/- and WT brains; (iii) evaluate the effectiveness of long-term treatment with tauroursodeoxycholic acid (TUDCA) on behavioural outcomes and omics profiles in the zebrafish sacs -/- model. Our findings indicate impairments in cognitive, social, and emotional behaviors in aged sacs -/- zebrafish, which resemble some deficits observed in human patients. Transcriptomic and proteomic analyses of adult brains identified alterations in genes related to circadian rhythms and neuroinflammation. Notably, disruptions in sleep and circadian rhythms are frequently reported in individuals with cerebellar ataxia and may contribute to cognitive and behavioral changes. Long-term treatment with TUDCA, a neuroprotective molecule, was associated with partial improvements in social and cognitive behaviors and modifications in omics profiles in the zebrafish model. These results support the potential of further exploring TUDCA in future preclinical and clinical studies, while also emphasizing the need for additional investigations to better understand its mechanisms of action.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".