Molecules, Vol. 25, Pages 1575: Antagonism of Histamine H3 receptors Alleviates Pentylenetetrazole-Induced Kindling and Associated Memory Deficits by Mitigating Oxidative Stress, Central Neurotransmitters, and c-Fos Protein Expression in Rats

Molecules, Vol. 25, Pages 1575: Antagonism of Histamine H3 receptors Alleviates Pentylenetetrazole-Induced Kindling and Associated Memory Deficits by Mitigating Oxidative Stress, Central Neurotransmitters, and c-Fos Protein Expression in Rats Molecules doi: 10.3390/molecules25071575 Authors: Alaa Alachkar Sheikh Azimullah Mohamed Lotfy Ernest Adeghate Shreesh K. Ojha Rami Beiram Dorota Łażewska Katarzyna Kieć-Kononowicz Bassem Sadek Histamine H3 receptors (H3Rs) are involved in several neuropsychiatric diseases including epilepsy. Therefore, the effects of H3R antagonist E177 (5 and 10 mg/kg, intraperitoneal (i.p.)) were evaluated on the course of kindling development, kindling-induced memory deficit, oxidative stress levels (glutathione (GSH), malondialdehyde (MDA), catalase (CAT), and superoxide dismutase (SOD)), various brain neurotransmitters (histamine (HA), acetylcholine (ACh), γ-aminobutyric acid (GABA)), and glutamate (GLU), acetylcholine esterase (AChE) activity, and c-Fos protein expression in pentylenetetrazole (PTZ, 40 mg/kg) kindled rats. E177 (5 and 10 mg/kg, i.p.) significantly decreased seizure score, increased step-through latency (STL) time in inhibitory avoidance paradigm, and decreased transfer latency time (TLT) in elevated plus maze (all P < 0.05). Moreover, E177 mitigated oxidative stress by significantly increasing GSH, CAT, and SOD, and decreasing the abnormal level of MDA (all P < 0.05). Furthermore,...
Source: Molecules - Category: Chemistry Authors: Tags: Article Source Type: research

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Authors: Zhang B, Wang W, Xiao Y, Xiao S, Chen S, Chen S, Xu G, Che W Abstract Electroencephalography (EEG) plays an import role in monitoring the brain activities of patients with epilepsy and has been extensively used to diagnose epilepsy. Clinically reading tens or even hundreds of hours of EEG recordings is very time consuming. Therefore, automatic detection of seizure is of great importance. But the huge diversity of EEG signals belonging to different patients makes the task of seizure detection much challenging, for both human experts and automation methods. We propose three deep transfer convolutional neural...
Source: Computational and Mathematical Methods in Medicine - Category: Statistics Tags: Comput Math Methods Med Source Type: research
Authors: Bi A, Ying W, Zhao L Abstract The diagnosis and treatment of epilepsy is a significant direction for both machine learning and brain science. This paper newly proposes a fast enhanced exemplar-based clustering (FEEC) method for incomplete EEG signal. The algorithm first compresses the potential exemplar list and reduces the pairwise similarity matrix. By processing the most complete data in the first stage, FEEC then extends the few incomplete data into the exemplar list. A new compressed similarity matrix will be constructed and the scale of this matrix is greatly reduced. Finally, FEEC optimizes the new ...
Source: Computational and Mathematical Methods in Medicine - Category: Statistics Tags: Comput Math Methods Med Source Type: research
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Source: Neurocomputing - Category: Neuroscience Source Type: research
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Jul 24, 2020. . Sponsored by RME Collaborative (Rural Medical Education)
Source: Rural events via the Rural Assistance Center - Category: Rural Health Source Type: events
Publication date: September 2020Source: Epilepsy &Behavior, Volume 110Author(s): Andrija Javor, Laura Zamarian, Gerhard Ransmayr, Manuela Prieschl, Melanie Bergmann, Gerald Walser, Gerhard Luef, Wolfgang Prokop, Margarete Delazer, Iris Unterberger
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Source: Neurogenetics - Category: Genetics & Stem Cells Source Type: research
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Source: Parkinsonism and Related Disorders - Category: Neurology Authors: Tags: Correspondence Source Type: research
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Source: Molecular Genetics & Genomic Medicine - Category: Genetics & Stem Cells Authors: Tags: ORIGINAL ARTICLE Source Type: research
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