Pridopidine rescues BDNF/TrkB trafficking dynamics and synapse homeostasis in a Huntington disease brain-on-a-chip model
Bibliographic record
Abstract
Huntington disease (HD) is a neurodegenerative disorder caused by polyglutamine-encoding CAG repeat expansion in the huntingtin ( HTT ) gene. HTT is involved in the axonal transport of vesicles containing brain-derived neurotrophic factor (BDNF). In HD, diminished BDNF transport leads to reduced BDNF delivery to the striatum, contributing to striatal and cortical neuronal death. Pridopidine is a selective and potent sigma-1 receptor (S1R) agonist currently in clinical development for HD. The S1R is located at the endoplasmic reticulum (ER)-mitochondria interface, where it regulates key cellular pathways commonly impaired in neurodegenerative diseases. We used a microfluidic device that reconstitutes the corticostriatal network, allowing the investigation of presynaptic dynamics, synaptic morphology and transmission, and postsynaptic signaling. Culturing primary neurons from the HD mouse model Hdh CAG140/+ provides a “disease-on-a-chip” platform ideal for investigating pathogenic mechanisms and drug activity. Pridopidine rescued the trafficking of BDNF and TrkB resulting in an increased neurotrophin signaling at the synapse. This increased the capacity of HD neurons to release glutamate and restored homeostasis at the corticostriatal synapse. These data suggest that pridopidine enhances the availability of corticostriatal BDNF via S1R activation, leading to neuroprotective effects.
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 | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".