Methods: Using a pilocarpine-induced epileptic mouse model, sensory-motor and visual cortical slices were prepared, and the whole-cell patch clamp technique was used to record spontaneous inhibitory post-synaptic currents (sIPSCs).
Results: The primary finding was that the mean amplitude of sIPSC from the sensory-motor cortex increased significantly in epileptic mice when the recording pipette contained MK-801 compared to control mice, whereas the mean sIPSC frequency was not significantly different, indicating that post-synaptic mechanisms are involved. However, there was no significant pre-synaptic inhibition through preNMDARs in the acute brain slices from pilocarpine-induced epileptic mice.
Conclusion: In the acute case of epilepsy, a compensatory mechanism of post-synaptic inhibition, possibly from ambient GABA, was observed through changes in the amplitude without significant changes in the frequency of sIPSC compared to control mice. The role of preNMDAR-mediated inhibition in epileptogenesis during the chronic condition or in the juvenile stage warrants further investigation.
METHODS: Knee image is first oversegmented to produce homogeneous superpixels. Then, a ranking model is developed to rank the superpixels according to their affinities to standard priors, wherein background superpixels would have lower ranking values. Finally, seed labels are generated on the background superpixel using Fuzzy C-Means method.
RESULTS: SAGE has achieved better interobserver DSCs of 0.94 ± 0.029 and 0.93 ± 0.035 in healthy and OA knee segmentation, respectively. Good segmentation performance has been reported in femoral (Healthy: 0.94 ± 0.036 and OA: 0.93 ± 0.034), tibial (Healthy: 0.91 ± 0.079 and OA: 0.88 ± 0.095) and patellar (Healthy: 0.88 ± 0.10 and OA: 0.84 ± 0.094) cartilage segmentation. Besides, SAGE has demonstrated greater mean readers' time of 80 ± 19 s and 80 ± 27 s in healthy and OA knee segmentation, respectively.
CONCLUSIONS: SAGE enhances the efficiency of segmentation process and attains satisfactory segmentation performance compared to manual and random walks segmentation. Future works should validate SAGE on progressive image data cohort using OA biomarkers.