Memory impairment in the D2.<i>mdx</i> mouse model of Duchenne muscular dystrophy is prevented by the adiponectin receptor agonist ALY688
Bibliographic record
Abstract
NEW FINDINGS: What is the central question of this study? Can adiponectin receptor agonism improve recognition memory in a mouse model of Duchenne muscular dystrophy? What is the main finding and its importance? Short-term treatment with the new adiponectin receptor agonist ALY688 improves recognition memory in D2.mdx mice. This finding suggests that further investigation into adiponectin receptor agonism is warranted, given that there remains an unmet need for clinical approaches to treat this cognitive dysfunction in people with Duchenne muscular dystrophy. ABSTRACT: Memory impairments have been well documented in people with Duchenne muscular dystrophy (DMD). However, the underlying mechanisms are poorly understood, and there is an unmet need to develop new therapies to treat this condition. Using a novel object recognition test, we show that recognition memory impairments in D2.mdx mice are completely prevented by daily treatment with the new adiponectin receptor agonist ALY688 from day 7 to 28 of age. In comparison to age-matched wild-type mice, untreated D2.mdx mice demonstrated lower hippocampal mitochondrial respiration (carbohydrate substrate), greater serum interleukin-6 cytokine content and greater hippocampal total tau and Raptor protein contents. Each of these measures was partly or fully preserved after treatment with ALY688. Collectively, these results indicate that adiponectin receptor agonism improves recognition memory in young D2.mdx mice.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".