The in vivo Use of Dopamine Binding Aptamers in a Mouse Model of Dopamine Dysregulation
Bibliographic record
Abstract
In the development of central nervous system therapeutics, delivery of agents across the blood-brain barrier remains one of the biggest challenges.In the present study, a liposome, surface-modified with an aptamer for the transferrin receptor, was used to facilitate delivery of a dopamine and norepinephrine binding aptamer from the periphery into the brain.Repeated, systemic administration of the modified aptamer produced no behavioral or neurodegenerative effects.In a behavioral experiment using cocaine administration to induce elevated concentrations of dopamine, systemic pretreatment with the aptamer-loaded liposomes reduced cocaine-induced hyperlocomotion.Systemic pretreatment with the transferrin-negative liposome control nor transferrin-positive liposomes loaded with either a non-binding aptamer or a random oligonucleotide did not alter cocaine-induced hyperlocomotion.RT-PCR was used to detect the aptamer in brain tissue, confirming the delivery of the aptamer payload across the blood-brain barrier.Differential distribution within the brain of rhodamine fluorescence based on the presence or absence of the transferrin receptor aptamer on the surface of the rhodamine-tagged liposomes was observed.Results suggest that systemic administration of the modified liposomes led to delivery of the aptamer into the brain.The potential of this multi-aptamer payload/targeting system is not restricted to dopamine or norepinephrine and could be easily modified with any aptamer for a variety of neural targets.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".