The Selection of DNA Aptamers for the Prevention of Alpha-Synuclein Aggregation as a Therapeutic Tool in Parkinson's Disease
Bibliographic record
Abstract
Parkinson's disease is among the most common neurodegenerative disorders with a global rate of incidence of about 17 per 100,000 person-years.While Parkinson's disease research and treatment options continue to grow, there remain many unanswered questions and unexplored potential therapeutics.The addition of improved preventative therapeutic options could greatly benefit the current arsenal of clinical treatments.One proposed mechanism for potential therapeutics has been the prevention of the aggregation of alpha-synuclein.Alpha-synuclein misfolding and aggregation are considered hallmarks for the progression of Parkinson's disease.Aptamer based treatments could be well suited to this application.Aptamers are single stranded oligonucleotides which bind to a specific chemical target with high affinity and specificity.Aptamers have demonstrated their capacity to inhibit the aggregation of proteins implicated in other neurogenerative disorders.Aptamer sequences are discovered through a process known as SELEX (the systematic evolution of ligands by exponential enrichment).Here, starting pools of aptamer candidates are derived from a 2010 SELEX by Tsukakoshi et al. in which aptamers were selected for affinity towards alpha-synuclein.These pools, coupled with a novel SELEX method which employs the aggregation of alpha-synuclein, has yielded promising results towards the use of aptamers for the prevention of alpha-synuclein aggregation.Based on the combination of sequencing data, the probability of forming a G-quadruplex structure, and preliminary in vitro aggregation prevention assays, the aptamer ASYN2 has been selected as an introductory candidate for in vivo testing.Comparisons of sequence distributions among various SELEX pool by MiSeq sequencing has revealed that ASYN2 likely holds the capacity to inhibit alpha-synuclein aggregation.Gquadruplex secondary structure prediction software predicted a strong possibility of G-quadruplex formation within ASYN2.Within a preliminary in vitro alpha-synuclein aggregation inhibition assay, iii ASYN2 out-performed the other candidates and the established M5-15 aptamer by producing the smallest set of alpha-synuclein morphologies with the smallest diversity in sizes.
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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 | 0.000 | 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".