The electroclinical features and surgical outcomes of inferior perisylvian epilepsy

Selected Biomarkers of Oxidative Stress and Energy Metabolism Disorders in Neurological Diseases

Neurological diseases can be broadly divided according to causal factors into circulatory system disorders leading to ischemic stroke; degeneration of the nerve cells leading to neurodegenerative diseases, such as Alzheimer's (AD) and Parkinson's (PD) diseases, and immune system disorders; bioelectric activity (epileptic) problems; and genetically determined conditions as well as viral and bacterial infections developing inflammation. Regardless of the cause of neurological diseases, they are usually accompanied by disturbances of the central energy in a completely unexplained mechanism. The brain makes up only 2% of the human body's weight; however, while working, it uses as much as 20% of the energy obtained by the body. The energy requirements of the brain are very high, and regulatory mechanisms in the brain operate to ensure adequate neuronal activity. Therefore, an understanding of neuroenergetics is rapidly evolving from a "neurocentric" view to a more integrated picture involving cooperativity between structural and molecular factors in the central nervous system. This article reviewed selected molecular biomarkers of oxidative stress and energy metabolism disorders such as homocysteine, DNA damage such as 8-oxo2dG, genetic variants, and antioxidants such as glutathione in selected neurological diseases including ischemic stroke, AD, PD, and epilepsy. This review summarizes our and others' recent research on oxidative stress in neurological disorders. In the future, the diagnosis and treatment of neurological diseases may be substantially improved by identifying specific early markers of metabolic and energy disorders.

Clinical features of automatisms and correlation with the seizure onset zones: A cluster analysis of 74 surgically-treated cases

OBJECTIVES

To identify semiologic features of automatisms correlating to different seizure onset zones (SOZ).

METHODS

In total, 204 seizures from 74 patients with either oral or manual automatisms were assessed. Patients were divided into four groups depending on the SOZ into frontal, posterior, neocortical temporal, and mesial temporal cortex groups. A k-means analysis was applied on 11 semiologic features on a multi-criteria scale. Then, the resulting clinical patterns were correlated with the SOZs determined by presurgical anatomy-electroclinical data (25 cases with stereo-EEG).

RESULTS

Four clinical patterns of automatisms with different accompanying symptoms were identified. The clinical features of clusters 1 and 4 were mostly found in temporal epilepsy whereas clusters 2 and 3 were more frequent in extratemporal epilepsy. Cluster 1 was significantly correlated with mesial temporal lobe epilepsy (p = .017) and was characterised by aura, postictal confusion, short automatisms delay. Cluster 3 included 1/3 patients with frontal lobe epilepsy and was characterised by emotionality. Cluster 4 was related to neocortical temporal lobe epilepsy and characterised by dystonia and short automatism delay (p = .011).

CONCLUSION

The distinct semiologic patterns of automatisms may provide information which may allow clinicians to define the SOZs. These findings could improve diagnostic accuracy and surgical outcome.