Impairment and Restoration of Homeostatic Plasticity in Cultured Cortical Neurons From a Mouse Model of Huntington Disease
Bibliographic record
Abstract
gene. The onset of symptoms is preceded by synaptic dysfunction. Homeostatic synaptic plasticity (HSP) refers to processes that maintain the stability of networks of neurons, thought to be required to enable new learning and cognitive flexibility. One type of HSP is synaptic scaling, in which the strength of all of the synapses onto a cell increases or decreases following changes in the cell's level of activity. Several pathways implicated in synaptic scaling are dysregulated in HD, including brain-derived neurotrophic factor (BDNF) and calcium signaling. Here, we investigated whether HSP is disrupted in cortical neurons from an HD mouse model. We treated cultured cortical neurons from wild-type (WT) FVB/N or YAC128 HD mice with tetrodotoxin (TTX) for 48 h to silence action potentials and then recorded miniature excitatory postsynaptic currents. In WT cultures, these increased in both amplitude and frequency after TTX treatment, and further experiments showed that this was a result of insertion of AMPA receptors and formation of new synapses, respectively. Manipulation of BDNF concentration in the culture medium revealed that BDNF signaling contributed to these changes. In contrast to WT cortical neurons, YAC128 cultures showed no response to action potential silencing. Strikingly, we were able to restore the TTX-induced changes in YAC128 cultures by treating them with pridopidine, a drug which enhances BDNF signaling through stimulation of the sigma-1 receptor (S1R), and with the S1R agonist 3-PPP. These data provide evidence for disruption of HSP in cortical neurons from an HD mouse model that is restored by stimulation of S1R. Our results suggest a potential new direction for developing therapy to mitigate cognitive deficits in 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".