[Animal Modeling - Efficacy Evaluation] - Other Gene Knockout and Transgenic Animal Models

  (1) The progressive myoclonic epilepsy syndrome model is a cystatin B gene knockout mouse model. The Cystatin B gene encodes an inhibitor of the Cystatin protein kinase, Cystatin B. Knocking out the gene prevents the expression of Cystatin B, and U-L PME patients have mutations and functional deletions in this gene. There is a special overlap in the neural phenotype between cystatin knockout mice and U-L type PME patients.

  (2) The Sharker type delayed rectifier potassium channel gene knockout mouse model is a gene knockout model designed based on the fact that K+channel blockade can lead to epilepsy. This type of animal exhibits severe tonic clonic seizures, which can easily lead to early death.

  (3) A staggering mouse model of epilepsy with aA subunit mutation that alters the Ca2+channel subunit gene with high voltage activity; Sleepy mice with β 4 subunit mutation; Stargazer mice with gamma 2 subunit mutation. The mutations in these subunit genes lead to increased excitability of mouse brain neuronal membranes, making them more susceptible to epilepsy.

  (4) The epileptic seizures in the transgenic Q54 mouse model began at 2 months of age, accompanied by restricted behavior and rigid repetitive movements. Continuous EEG monitoring revealed localized epileptic activity in the hippocampus, even extending to the cortex. Pathological examination revealed significant cell loss and gliosis in the CA1 to 3 and portal regions of the hippocampus. Transgenic Q54 mice provide a genetic model in which SCN2A was found to be a candidate gene for human epilepsy.

  Gene knockout and transgenic epilepsy models have the advantage of studying the interaction of epilepsy related genes, which other types of models do not have. However, the expression of each gene is related to its genetic background. Many literature also points out that knockout or implanted genes have different phenotypes in different vector gene backgrounds. Therefore, researchers need to consider these influencing factors when evaluating experimental data.