Prefrontal Cortex-Mediated Impairments in a Genetic Model of NMDA Receptor Hypofunction Are Reversed by the Novel M<sub>1</sub>PAM VU6004256
Bibliographic record
Abstract
Abnormalities in the signaling of the N -methyl- d -aspartate subtype of the glutamate receptor (NMDAR) within cortical and limbic brain regions are thought to underlie many of the complex cognitive and affective symptoms observed in individuals with schizophrenia. The M 1 muscarinic acetylcholine receptor (mAChR) subtype is a closely coupled signaling partner of the NMDAR. Accumulating evidence suggests that development of selective positive allosteric modulators (PAMs) of the M 1 receptor represent an important treatment strategy for the potential normalization of disruptions in NMDAR signaling in patients with schizophrenia. In the present studies, we evaluated the effects of the novel and highly potent M 1 PAM, VU6004256, in ameliorating selective prefrontal cortical (PFC)-mediated physiologic and cognitive abnormalities in a genetic mouse model of global reduction in the NR1 subunit of the NMDAR (NR1 knockdown [KD]). Using slice-based extracellular field potential recordings, deficits in muscarinic agonist-induced long-term depression (LTD) in layer V of the PFC in the NR1 KD mice were normalized with bath application of VU6004256. Systemic administration of VU6004256 also reduced excessive pyramidal neuron firing in layer V PFC neurons in awake, freely moving NR1 KD mice. Moreover, selective potentiation of M 1 by VU6004256 reversed the performance impairments of NR1 KD mice observed in two preclinical models of PFC-mediated learning, specifically the novel object recognition and cue-mediated fear conditioning tasks. VU6004256 also produced a robust, dose-dependent reduction in the hyperlocomotor activity of NR1 KD mice. Taken together, the current findings provide further support for M 1 PAMs as a novel therapeutic approach for the PFC-mediated impairments in schizophrenia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".