The extracellular matrix protein SC1/hevin localizes to excitatory synapses following status epilepticus in the rat lithium‐pilocarpine seizure model
Bibliographic record
Abstract
The epileptic brain is characterized by increased susceptibility to neuronal hyperexcitability. The rat lithium-pilocarpine model, which mimics many features of temporal lobe epilepsy, has been used to study processes leading to the development of recurrent seizures. After a prolonged seizure episode, termed status epilepticus (SE), neural changes occur during a period known as epileptogenesis and include neuronal cell death, reactive gliosis, axonal sprouting, and synaptogenesis. Extracellular matrix adhesion molecules are important regulators of synaptogenesis and axonal sprouting resulting from SE. SC1, also known as hevin, is an antiadhesive extracellular matrix molecule that localizes to synapses in the mammalian brain. In this study, the distribution of SC1 protein in neurons following SE was examined using the lithium-pilocarpine model. SC1 protein levels in neuronal cell bodies showed a transient decrease at 1 day post-SE, which coincided with an increase of SC1 in the synapse-rich neuropil that was identified with the synaptic marker synaptophysin. Immunoelectron microscopy confirmed the decrease of SC1 signal in neurons at 1 day post-SE and showed that SC1 remained localized to postsynaptic elements throughout the seizure time course. Increased colocalization of SC1 was detected with the excitatory synaptic markers vesicular glutamate transporter 1 (VGLUT1), AMPA receptor subunit GluR1, and N-methyl-D-aspartate receptor subunit NR1, but not with the inhibitory synaptic markers vesicular gamma-aminobutyric acid (GABA) transporter (VGAT) and GABA(A) receptor subunit beta2 (GABA(A) beta2), which could reflect enhanced association of SC1 with excitatory synapses. These findings suggest that SC1 may be involved in synaptic modifications underlying epileptogenesis.
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 | 0.001 | 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) | 0.001 | 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".