Usage of Psilocybin to Treat Huntington's Disease: A Research Protocol
Bibliographic record
Abstract
Introduction: Huntington’s Disease (HD) is a progressive, neurodegenerative disease that causes significant amounts of neuron death in the brain. It is a genetic disorder, resulting from the over-repetition of the CAG sequence in the gene that codes for the huntingtin protein. Currently, there are no viable cures or treatments to slow or stop the progression of this disorder, making it a target candidate for treatment research. However, given the difficulty and complexity of in treating the genetic cause of HD in adults, a more viable approach may involve treating the resulting neurodegeneration with neuroprotective compounds, such as psilocybin. As such, our study proposes the usage of psilocybin to treat HD due to its neuroprotective, neurotrophic, and neuroplastic effects, resulting in a decreased rate of neuron loss and increased synaptic density. Methods: We propose an in-vivo experiment using several groups of zQ175 knock-in (KI) mice, which will mimic HD in the mice. Following 8 weeks, the mice’s brains will be extracted at different time intervals to analyze the progression of neuronal death using histology and immunohistochemistry, which should inform us about the progression of HD in the different groups of mice. Moreover, throughout this experiment, the motor control of the mice will be observed using the rotarod test, the raised beam test, and the footprint test. Data from these tests will act as behavioral markers for HD, providing an alternate source of information on the progression of HD in the mice. Expected Results: KI mice are expected to have lower rates of neuronal death, higher amounts of synaptic density, and higher scores on average across the three motor behavior tests, compared to the non-treated KI mice. Discussion: These results could provide insight into potential treatments for slowing the progression of HD. If successful, possible next steps could be to determine the efficacy of psilocybin in clinical trials for HD. Conclusion: This study is expected to provide information on the usage of psilocybin as a treatment for HD. If the expected results are obtained, psilocybin may help improve the quality of life for those afflicted with HD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".