Although caffeine supplementation has a beneficial effect on people with neurological disorders, its implications for oxidative damage related to seizures are not well documented. Thus the aim of this study was to investigate the effects of two weeks caffeine supplementation (6mg/kg; p.o.) on seizures and neurochemical alterations induced by pentylenetetrazol (PTZ 60mg/kg i.p.). Statistical analyses showed that long-term rather than single dose caffeine administration decreased the duration of PTZ-induced seizures in adult male Wistar rats as recorded by cortical electroencephalographic (EEG) and behavioral analysis. The quantification of EEG recordings also revealed that caffeine supplementation protected against a wave increase induced by PTZ. Neurochemical analyses revealed that caffeine supplementation increased glutathione (GSH) content per se and protected against the increase in the levels of thiobarbituric acid reactive substances (TBARS) and oxidized diclorofluoresceine diacetate (DCFH-DA). Also, caffeine prevent the decrease in GSH content and Na(+), K(+)-ATPase activity induced by PTZ. Our data also showed that the infusion of L-buthionine sulfoximine (BSO; 3.2μmol/site i.c.v), an inhibitor of GSH synthesis, two days before injecting PTZ reversed the anticonvulsant effect caused by caffeine. BSO infusion also decreased GSH content and Na(+), K(+)-ATPase activity. However, it increased DCFH-DA oxidation and TBARS per se and reversed the protective effect of caffeine. Results presented in this paper support the neuroprotective effects of low long-term caffeine exposure to epileptic damage and suggest that the increase in the cerebral GSH content caused by caffeine supplementation may provide a new therapeutic approach to the control of seizure.

Traumatic brain injury (TBI) is a leading cause of disability worldwide, triggering chronic neurodegeneration underlying cognitive and mood disorder still without therapeutic prospects. Based on our previous observations that guanosine (GUO) attenuates short-term neurochemical alterations caused by TBI, this study investigated the effects of chronical GUO treatment in behavioral, molecular, and morphological disturbances 21 days after trauma. Rats subject to TBI displayed mood (anxiety-like) and memory dysfunction. This was accompanied by a decreased expression of both synaptic (synaptophysin) and plasticity proteins (BDNF and CREB), a loss of cresyl violet-stained neurons, and increased astrogliosis and microgliosis in the hippocampus. Notably, chronic GUO treatment (7.5 mg/kg i.p. daily starting 1 h after TBI) prevented all these TBI-induced long-term behavioral, neurochemical, and morphological modifications. This neuroprotective effect of GUO was abrogated in the presence of the adenosine A receptor antagonist DPCPX (1 mg/kg) but unaltered by the adenosine A receptor antagonist SCH58261 (0.05 mg/kg). These findings show that a chronic GUO treatment prevents the long-term mood and memory dysfunction triggered by TBI, which involves adenosinergic receptors.

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MicroRNAs perform important roles in the post-transcriptional regulation of gene expression. Sequencing as well as functional studies using antisense oligonucleotides indicate important roles for microRNAs during the development of epilepsy through targeting transcripts involved in neuronal structure, gliosis and inflammation. MicroRNA-22 (miR-22) has been reported to protect against the development of epileptogenic brain networks through suppression of neuroinflammatory signalling. Here, we used mice with a genetic deletion of miR-22 to extend these insights. Mice lacking miR-22 displayed normal behaviour and brain structure and developed similar status epilepticus after intraamygdala kainic acid compared to wildtype animals. Continuous EEG monitoring after status epilepticus revealed, however, an accelerated and exacerbated epilepsy phenotype whereby spontaneous seizures began sooner, occurred more frequently and were of longer duration in miR-22-deficient mice. RNA sequencing analysis of the hippocampus during the period of epileptogenesis revealed a specific suppression of inflammatory signalling in the hippocampus of miR-22-deficient mice. Taken together, these findings indicate a role for miR-22 in establishing early inflammatory responses to status epilepticus. Inflammatory signalling may serve anti-epileptogenic functions and cautions the timing of anti-inflammatory interventions for the treatment of status epilepticus.

Dravet Syndrome (DS) is a catastrophic form of paediatric epilepsy mainly caused by non-inherited mutations in the SCN1A gene. DS patients suffer severe and life-threatening focal and generalised seizures which are often refractory to available anti-seizure medication. Antisense oligonucleotides (ASOs) based approaches may offer treatment opportunities in DS. MicroRNAs are short non-coding RNAs that play a key role in brain structure and function by post-transcriptionally regulating gene expression, including ion channels.Inhibiting microRNA-134 (miR-134) using an antimiR ASO (Ant-134) has been shown to reduce evoked seizures in juvenile and adult mice and reduce epilepsy development in models of focal epilepsy. The present study investigated the levels of miR-134 and whether Ant-134 could protect against hyperthermia-induced seizures, spontaneous seizures and mortality (SUDEP) in F1.Scn1a(+/-) tm1kea mice. At P17, animals were intracerebroventricular injected with 0.1 -1 nmol of Ant-134 and subject to a hyperthermia challenge at P18. A second cohort of P21 F1.Scn1a(+/-) tm1kea mice received Ant-134 and were followed by video and EEG monitoring until P28 to track the incidence of spontaneous seizures and SUDEP. Hippocampal and cortical levels of miR-134 were similar between wildtype and F1.Scn1a(+/-) tm1kea mice. Moreover, Ant-134 had no effect on hyperthermia-induced seizures, spontaneous seizures and SUDEP incidence were unchanged in Ant-134 treated DS mice. These findings suggest that targeting miR-134 does not have therapeutic applications in DS. 2 Significance StatementSeveral preclinical models of epilepsy have implicated miR-134 as a therapeutic target for seizure control and anti-epileptogenesis. The present study here explored whether targeting miR-134 has effects on seizures and mortality in a mouse model of Dravet Syndrome. The results indicate that suppression of miR-134 using an antimiR did not protect against hyperthermiainduced seizures, spontaneous seizures or SUDEP in F1.Scn1a(+/-) tm1kea mice.The findings suggest that miR-134 is not a therapeutic target in DS.

Objective. Electroencephalography (EEG) is a key tool for non-invasive recording of brain activity and the diagnosis of epilepsy. EEG monitoring is also widely employed in rodent models to track epilepsy development and evaluate experimental therapies and interventions. Whereas automated seizure detection algorithms have been developed for clinical EEG, preclinical versions face challenges of inter-model differences and lack of EEG standardization, leaving researchers relying on time-consuming visual annotation of signals. Approach. In this study, a machine learning-based seizure detection approach, ‘Epi-AI’, which can semi-automate EEG analysis in multiple mouse models of epilepsy was developed. Twenty-six mice with a total EEG recording duration of 6451 h were used to develop and test the Epi-AI approach. EEG recordings were obtained from two mouse models of kainic acid-induced epilepsy (Models I and III), a genetic model of Dravet syndrome (Model II) and a pilocarpine mouse model of epilepsy (Model IV). The Epi-AI algorithm was compared against two threshold-based approaches for seizure detection, a local Teager-Kaiser energy operator (TKEO) approach and a global Teager-Kaiser energy operator-discrete wavelet transform (TKEO-DWT) combination approach. Main results. Epi-AI demonstrated a superior sensitivity, 91.4%–98.8%, and specificity, 93.1%–98.8%, in Models I–III, to both of the threshold-based approaches which performed well on individual mouse models but did not generalise well across models. The performance of the TKEO approach in Models I–III ranged from 66.9%–91.3% sensitivity and 60.8%–97.5% specificity to detect spontaneous seizures when compared with expert annotations. The sensitivity and specificity of the TKEO-DWT approach were marginally better than the TKEO approach in Models I–III at 73.2%–80.1% and 75.8%–98.1%, respectively. When tested on EEG from Model IV which was not used in developing the Epi-AI approach, Epi-AI was able to identify seizures with 76.3% sensitivity and 98.1% specificity. Significance. Epi-AI has the potential to provide fast, objective and reproducible semi-automated analysis of multiple types of seizure in long-duration EEG recordings in rodents.