Epilepsy is a prevalent neurological disorder among women globally, often requiring long-term treatment. Hormonal fluctuations in women with epilepsy (WWE) can have reciprocal effects on epilepsy and antiseizure medications (ASMs), posing significant challenges for WWE. Notably, WWE commonly experience endocrine alterations such as thyroid dysfunctions, low bone metabolism, and reproductive hormone irregularities. On the one hand, the presence of hormones in women with epilepsy affects their susceptibility to epilepsy as well as the metabolism of antiseizure medications in various ways. On the other hand, epilepsy itself and the use of antiseizure medications impact the production, secretion, and metabolism of hormones, resulting in low fertility, increased risk of pregnancy complications, negative offspring outcomes, and so on. In order to develop more precise treatment strategies in the future, it is necessary to comprehend the explicit relationships between hormones, epilepsy, and antiseizure medications, as well as to elucidate the currently known mechanisms underlying these interactions.

Improving the efficiency of antiseizure medication entering the brain is the key to reducing its peripheral toxicity. A combination of intranasal administration and nanomedicine presents a practical approach for treating epileptic seizures via bypassing the blood-brain barrier. In this study, phenytoin (PHT) loaded layered double hydroxide nanoparticles (BSA-LDHs-PHT) were fabricated via a coprecipitation − hydrothermal method for epileptic seizure control. In this study, we expound on the preparation method and characterization of BSA-LDHs-PHT. In-vitro drug release experiment shows both rapid and continuous drug release from BSA-LDHs-PHT, which is crucial for acute seizure control and chronic epilepsy therapy. In-vivo biodistribution assays after intranasal administration indicate excellent brain targeting ability of BSA-LDHs. Compared to BSA-Cyanine5.5, BSA-LDHs-Cyanine5.5 were associated with a higher brain/peripheral ratio across all tested time points. Following intranasal delivery with small doses of BSA-LDHs-PHT, the latency of seizures in the pentylenetetrazole-induced mouse models was effectively improved. Collectively, the present study successfully designed and applied BSA-LDHs-PHT as a promising strategy for treating epileptic seizures with an enhanced therapeutic effect.

Epilepsy is a common neurological disease worldwide, characterized by recurrent seizures. There is currently no cure for epilepsy. However, seizures can be controlled by drugs and surgeries in about 70% of epileptic patients. A timely and accurate prediction of seizures can prevent injuries during seizures and improve the patients’ quality of life. In this paper, we proposed an intelligent epileptic prediction system based on Synchrosqueezed Wavelet Transform (SWT) and Multi-Level Feature Convolutional Neural Network (MLF-CNN) for smart healthcare IoT network. In this system, we used SWT to map EEG signals to the frequency domain, which was able to measure the energy changes in EEG signals caused by seizures within a well-defined Time-Frequency (TF) plane. MLF-CNN was then applied to extract multi-level features from the processed EEG signals and classify the different seizure segments. The performance of our proposed system was evaluated with the publicly available CHB-MIT dataset and our private ZJU4H dataset. The system achieved an accuracy of 96.99% and 94.25%, a sensitivity of 96.48% and 97.76%, a specificity of 97.46% and 94.07% and a false prediction rate (FPR/h) of 0.031 and 0.049 FPR/h on the CHB-MIT dataset and the ZJU4H dataset, respectively.

Epilepsy is a prevalent chronic neurological disorder that can significantly impact patients’ lives. The incidence and risk of psychosis in individuals with epilepsy are notably higher than in the general population, adversely affecting both the management and rehabilitation of epilepsy and further diminishing patients’ quality of life. This review provides an overview of the classification and clinical features of psychosis of epilepsy, with the aim of offering insights and references for the clinical diagnosis and treatment of various types of psychosis of epilepsy. Additionally, we examine the potential pathophysiological mechanisms underlying the psychosis of epilepsy from three perspectives: neuroimaging, neurobiology, and genetics. The alterations in brain structure and function, neurotransmitters, neuroinflammatory mediators, and genetic factors discussed in this review may offer insights into the onset and progression of psychotic symptoms in epilepsy patients and are anticipated to inform the identification of novel therapeutic targets in the future.

Objective: Children with self‐limited epilepsy characterized by centrotemporal spikes (SeLECTS) exhibit cognitive deficits in memory during the active phase, but there is currently a lack of studies and techniques to assess their memory development after well‐controlled seizures. In this study, we employed eye‐tracking techniques to investigate visual memory and its association with clinical factors and global intellectual ability, aiming to identify potential risk factors by examining encoding and recognition processes.Methods: A total of 26 recruited patients diagnosed with SeLECTS who had been seizure‐free for at least 2 years, along with 24 control subjects, underwent Wechsler cognitive assessment and an eye‐movement‐based memory task while video‐electroencephalographic (EEG) data were recorded. Fixation and pupil data related to eye movements were utilized to detect distinct memory processes and subsequently to compare the cognitive performance of patients exhibiting different regression patterns on EEG.Results: The findings revealed persistent impairments in visual memory among children with SeLECTS after being well controlled, primarily observed in the recognition stage rather than the encoding phase. Furthermore, the age at onset, frequency of seizures, and interictal epileptiform discharges exhibited significant correlations with eye movement data.Significance: Children with SeLECTS exhibit persistent recognition memory impairment after being well controlled for the disease. Controlling the frequency of seizures and reducing prolonged epileptiform activity may improve memory cognitive development. The application of the eye‐tracking technique may provide novel insights into exploring memory cognition as well as underlying mechanisms associated with pediatric epilepsy.

Cognitive dysfunction is one of the common comorbidities of epilepsy. More than 60 % of epilepsy patients may experience impairment in learning, memory, attention, and executive control. At present, it can only control the symptoms of seizures, and there is no specific treatment for cognitive impairment. Deep brain stimulation (DBS) has been used to treat intractable epilepsy, with proven safety. Recently data suggests that DBS can not only improve the seizure control, but also improved cognitive function. This review summarizes the effects of DBS on cognitive impairment in epilepsy, including the current status and application of DBS, the influence of different DBS targets on brain of DBS on cognitive impairment in epilepsy, the possible mechanisms of DBS on cognitive impairment and its future prospects. It provides a theoretical basis for its further clinical application in epilepsy patients with cognitive dysfunction.