The serine protease inhibitor neuroserpin is required for normal synaptic plasticity and regulates learning and social behavior
Bibliographic record
Abstract
The serine protease inhibitor neuroserpin regulates the activity of tissue-type plasminogen activator (tPA) in the nervous system. Neuroserpin expression is particularly prominent at late stages of neuronal development in most regions of the central nervous system (CNS), whereas it is restricted to regions related to learning and memory in the adult brain. The physiological expression pattern of neuroserpin, its high degree of colocalization with tPA within the CNS, together with its dysregulation in neuropsychiatric disorders, suggest a role in formation and refinement of synapses. In fact, studies in cell culture and mice point to a role for neuroserpin in dendritic branching, spine morphology, and modulation of behavior. In this study, we investigated the physiological role of neuroserpin in the regulation of synaptic density, synaptic plasticity, and behavior in neuroserpin-deficient mice. In the absence of neuroserpin, mice show a significant decrease in spine-synapse density in the CA1 region of the hippocampus, while expression of the key postsynaptic scaffold protein PSD-95 is increased in this region. Neuroserpin-deficient mice show decreased synaptic potentiation, as indicated by reduced long-term potentiation (LTP), whereas presynaptic paired-pulse facilitation (PPF) is unaffected. Consistent with altered synaptic plasticity, neuroserpin-deficient mice exhibit cognitive and sociability deficits in behavioral assays. However, although synaptic dysfunction is implicated in neuropsychiatric disorders, we do not detect alterations in expression of neuroserpin in fusiform gyrus of autism patients or in dorsolateral prefrontal cortex of schizophrenia patients. Our results identify neuroserpin as a modulator of synaptic plasticity, and point to a role for neuroserpin in learning and memory.
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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) | 0.000 | 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) | 0.001 | 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".