Early striatal hyperexcitability in an <i>in vitro</i> human striatal microcircuit model carrying the Parkinson’s <i>GBA-N370S</i> mutation
Bibliographic record
Abstract
Abstract Understanding medium spiny neuron (MSN) physiology is essential to understand motor impairments in Parkinson’s disease (PD) given the architecture of the basal ganglia. Here, we developed a custom three-chamber microfluidic platform and established a cortico-striato-nigral microcircuit recapitulating the striatal presynaptic triad in vitro using induced pluripotent stem cell (iPSC)-derived neurons. We found that, although cortical glutamatergic projections facilitated MSN synaptic activity, dopaminergic transmission was essential for excitability maturation of MSNs in vitro . Replacement of wild-type iPSC-dopamine neurons (iPSC-DaNs) in the striatal microcircuit with those carrying the PD-related GBA-N370S mutation induced early hyperexcitability in iPSC-MSNs through reduction of voltage-gated sodium and potassium intrinsic currents. Such deficits were resolved in aged cultures or with antagonism of protein kinase A activity in nigrostriatal iPSC-DaNs. Hence, our results highlight the unique utility of modelling striatal neurons in a modular and highly physiological circuit which is essential to reveal mechanistic insights of the loss of electrical functional integrity in the striata of GBA1 PD patients.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".