Abscisic Acid Enhances Motor and Cognitive Function in the 3‐Acetylpyridine Mouse Model of Cerebellar Ataxia
Bibliographic record
Abstract
Cerebellar ataxia is a debilitating neurodegenerative disorder characterized by impaired motor coordination and balance with limited treatment options. Abscisic acid (ABA), a phytohormone detected in mammalian brains, has shown neuroprotective properties. This study investigated the effects of ABA on motor, cognitive, and affective deficits in a mouse model of cerebellar ataxia in which male Swiss mice received a single intraperitoneal injection of 3-acetylpyridine (3-AP; 60 mg/kg), which leads to the loss of climbing fiber input to Purkinje neurons leading to cerebellar degeneration. In ABA-treated groups, ABA (10 or 15 μg/mouse) was intracerebroventricularly applied for four consecutive days. Behavioral testing consisted of open field, footprint analysis, wire grip, rotarod, tail suspension, elevated plus maze, Morris water maze, and the passive avoidance assay. Cerebellar brain-derived neurotrophic factor (BDNF) levels were measured using ELISA. As expected, 3-AP-treated mice exhibited significant motor impairments, increased anxiety-like and depressive-like behaviors, and cognitive deficits. ABA treatment, particularly at the 15 μg/mouse dose, significantly improved motor coordination, locomotor activity, memory, and spatial and passive avoidance learning as well as reduced anxiety-like and depressive-like behaviors. Behavioral changes were associated with normalization of the 3-AP-induced increases in cerebellar BDNF levels. This study demonstrates that ABA can ameliorate motor, cognitive, and affective deficits in a mouse model of cerebellar ataxia, which could involve BDNF and be due to neuroprotective effects in the cerebellum. By extension, our data suggest that ABA may have therapeutic potential in the management of cerebellar ataxia and other cerebellar disorders.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".