Distinct Etiological Roles for Myocytes and Motor Neurons in a Mouse Model of Kennedy's Disease/Spinobulbar Muscular Atrophy
Bibliographic record
Abstract
Polyglutamine (polyQ) expansion of the androgen receptor (AR) causes Kennedy's disease/spinobulbar muscular atrophy (KD/SBMA) through poorly defined cellular mechanisms. Although KD/SBMA has been thought of as a motor neuron disease, recent evidence indicates a key role for skeletal muscle. To resolve which early aspects of the disease can be caused by neurogenic or myogenic mechanisms, we made use of the tet-On and Cre-loxP genetic systems to selectively and acutely express polyQ AR in either motor neurons (NeuroAR) or myocytes (MyoAR) of transgenic mice. After 4 weeks of transgene induction in adulthood, deficits in gross motor function were seen in NeuroAR mice, but not MyoAR mice. Conversely, reduced size of fast glycolytic fibers and alterations in expression of candidate genes were observed only in MyoAR mice. Both NeuroAR and MyoAR mice exhibited reduced oxidative capacity in skeletal muscles, as well as a shift in fast fibers from oxidative to glycolytic. Markers of oxidative stress were increased in the muscle of NeuroAR mice and were reduced in motor neurons of both NeuroAR and MyoAR mice. Despite secondary pathology in skeletal muscle and behavioral deficits, no pathological signs were observed in motor neurons of NeuroAR mice, possibly due to relatively low levels of polyQ AR expression. These results indicate that polyQ AR in motor neurons can produce secondary pathology in muscle. Results also support both neurogenic and myogenic contributions of polyQ AR to several acute aspects of pathology and provide further evidence for disordered cellular respiration in KD/SBMA skeletal muscle.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".