Transcriptional Profile of Muscle following Acute Induction of Symptoms in a Mouse Model of Kennedy's Disease/Spinobulbar Muscular Atrophy
Bibliographic record
Abstract
BACKGROUND: Kennedy's disease/Spinobulbar muscular atrophy (KD/SBMA) is a degenerative neuromuscular disease affecting males. This disease is caused by polyglutamine expansion mutations of the androgen receptor (AR) gene. Although KD/SBMA has been traditionally considered a motor neuron disease, emerging evidence points to a central etiological role of muscle. We previously reported a microarray study of genes differentially expressed in muscle of three genetically unique mouse models of KD/SBMA but were unable to detect those which are androgen-dependent or are associated with onset of symptoms. METHODOLOGY/PRINCIPAL FINDINGS: In the current study we examined the time course and androgen-dependence of transcriptional changes in the HSA-AR transgenic (Tg) mouse model, in which females have a severe phenotype after acute testosterone treatment. Using microarray analysis we identified differentially expressed genes at the onset and peak of muscle weakness in testosterone-treated Tg females. We found both transient and persistent groups of differentially expressed genes and analysis of gene function indicated functional groups such as mitochondrion, ion and nucleotide binding, muscle development, and sarcomere maintenance. CONCLUSIONS/SIGNIFICANCE: By comparing the current results with those from the three previously reported models we were able to identify KD/SBMA candidate genes that are androgen dependent, and occur early in the disease process, properties which are promising for targeted therapeutics.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".