Epilepsy Benchmarks Area I: Understanding the Causes of the Epilepsies and Epilepsy-Related Neurologic, Psychiatric, and Somatic Conditions

Technological Vanguard: the outstanding performance of the LTY-CNN model for the early prediction of epileptic seizures

BACKGROUND

Epilepsy is a common neurological disorder that affects approximately 60 million people worldwide. Characterized by unpredictable neural electrical activity abnormalities, it results in seizures with varying intensity levels. Electroencephalography (EEG), as a crucial technology for monitoring and predicting epileptic seizures, plays an essential role in improving the quality of life for people with epilepsy.

METHOD

This study introduces an innovative deep learning model, a lightweight triscale yielding convolutional neural network" (LTY-CNN), that is specifically designed for EEG signal analysis. The model integrates a parallel convolutional structure with a multihead attention mechanism to capture complex EEG signal features across multiple scales and enhance the efficiency achieved when processing time series data. The lightweight design of the LTY-CNN enables it to maintain high performance in environments with limited computational resources while preserving the interpretability and maintainability of the model.

RESULTS

In tests conducted on the SWEC-ETHZ and CHB-MIT datasets, the LTY-CNN demonstrated outstanding performance. On the SWEC-ETHZ dataset, the LTY-CNN achieved an accuracy of 99.9%, an area under the receiver operating characteristic curve (AUROC) of 0.99, a sensitivity of 99.9%, and a specificity of 98.8%. Furthermore, on the CHB-MIT dataset, it recorded an accuracy of 99%, an AUROC of 0.932, a sensitivity of 99.1%, and a specificity of 93.2%. These results signify the remarkable ability of the LTY-CNN to distinguish between epileptic seizures and nonseizure events. Compared to other existing epilepsy detection classifiers, the LTY-CNN attained higher accuracy and sensitivity.

CONCLUSION

The high accuracy and sensitivity of the LTY-CNN model demonstrate its significant potential for epilepsy management, particularly in terms of predicting and mitigating epileptic seizures. Its value in personalized treatments and widespread clinical applications reflects the broad prospects of deep learning in the health care sector. This also highlights the crucial role of technological innovation in enhancing the quality of life experienced by patients.

Identification of degradation products of brivaracetam using liquid chromatography quadrupole time-of-flight tandem mass spectrometry: Degradation pathway elucidation

RATIONALE

Pyrrolidone-based drugs find widespread use in treating conditions such as epilepsy and Alzheimer's disease, and in various other medical applications. Brivaracetam, the latest generation of pyrrolidone drugs, has exhibited significant promise owing to chemical structure modifications. Its affinity to the SV2A receptor is double that of the previous-generation drug, levetiracetam. Consequently, brivaracetam holds substantial potential for diverse applications. As a novel drug not yet included in the pharmacopeias of developed nations, comprehensive analysis and research are necessary to guarantee its safe utilization in clinical settings.

METHODS

A liquid chromatography quadrupole time-of-flight tandem mass spectrometry (LC/QTOFMS) method has been developed to effectively separate, identify and characterize both the degradation products and process-related substances of brivaracetam. Stress testing of the sample was carried out following the guidelines outlined in ICH Q1A(R2). The structures of these impurities were identified through positive electrospray ionization QTOF high-resolution MS and NMR spectroscopy. Additionally, the formation mechanism of each degradation product is thoroughly discussed.

RESULTS

Under the analytical conditions outlined in this paper, brivaracetam and its degradation products were effectively separated. Thirteen degradation products were detected and characterized, shedding light on their origins and degradation pathways. Among these, three degradation products align with previously reported impurities, and two unreported degradation products were synthesized and confirmed through NMR spectroscopy. The stress testing results revealed the instability of brivaracetam under acidic, alkaline, oxidative and thermal stress conditions, while it exhibited relative stability under photolytic stress conditions.

CONCLUSION

The study developed an analytical method for brivaracetam that enabled the effective detection and separation of brivaracetam and its 13 degradation products. This method addresses a gap in both current domestic and foreign drug standards. The structures of all the major degradation products were characterized by high-resolution LC/QTOFMS, which is essential for quality control during the drug production process, stability evaluation and the establishment of proper storage conditions.

Shaping the future of European epilepsy research: Final meeting report from EPICLUSTER

Collaboration is essential to the conduct of basic, applied and clinical research and its translation into the technologies and treatments urgently needed to improve the lives of people living with brain diseases and the health professionals who care for them. EPICLUSTER was formed in 2019 by the European Brain Research Area (EBRA) to support the coordination of epilepsy research in Europe. A key objective was to provide a platform to discuss shared research priorities by bringing together scientists and clinicians with multiple stakeholders including patient organisations and industry and the networks and infrastructures that provide healthcare and support research. Additional objectives were to facilitate access and sharing of data and biosamples, working together to ensure epilepsy is a priority for research funding, and embedding a culture of public and patient involvement (PPI) among epilepsy researchers. In this meeting report, we summarise the shared research priorities discussed by the leadership of EPICLUSTER at the recent final meeting. We also briefly review the discussion on patient and industry priorities, guidance on starting PPI for epilepsy researchers, and the sustainability of funding and infrastructures needed to ensure a comprehensive stakeholder-embedded community for epilepsy research.

Translocation of High Mobility Group Box 1 From the Nucleus to the Cytoplasm in Depressed Patients With Epilepsy

Depression is a common psychiatric comorbidity in patients with epilepsy, especially those with temporal lobe epilepsy (TLE). The aim of this study was to assess changes in high mobility group box protein 1 (HMGB1) expression in epileptic patients with and without comorbid depression. Sixty patients with drug-resistant TLE who underwent anterior temporal lobectomy were enrolled. Anterior hippocampal samples were collected after surgery and analyzed by immunofluorescence (n  = 7/group). We also evaluated the expression of HMGB1 in TLE patients with hippocampal sclerosis and measured the level of plasma HMGB1 by enzyme-linked immunosorbent assay. The results showed that 28.3% of the patients (17/60) had comorbid depression. HMGB1 was ubiquitously expressed in all subregions of the anterior hippocampus. The ratio of HMGB1-immunoreactive neurons and astrocytes was significantly increased in both TLE patients with hippocampal sclerosis and TLE patients with comorbid depression compared to patients with TLE only. The ratio of cytoplasmic to nuclear HMGB1-positive neurons in the hippocampus was higher in depressed patients with TLE than in nondepressed patients, which suggested that more HMGB1 translocated from the nucleus to the cytoplasm in the depressed group. There was no significant difference in the plasma level of HMGB1 among patients with TLE alone, TLE with hippocampal sclerosis, and TLE with comorbid depression. The results of the study revealed that the translocation of HMGB1 from the nucleus to the cytoplasm in hippocampal neurons may play a previously unrecognized role in the initiation and amplification of epilepsy and comorbid depression. The direct targeting of neural HMGB1 is a promising approach for anti-inflammatory therapy.

Non-Cell Autonomous Epileptogenesis in Focal Cortical Dysplasia

OBJECTIVE

Low-level somatic mosaicism in the brain has been shown to be a major genetic cause of intractable focal epilepsy. However, how a relatively few mutation-carrying neurons are able to induce epileptogenesis at the local network level remains poorly understood.

METHODS

To probe the origin of epileptogenesis, we measured the excitability of neurons with MTOR mutation and nearby nonmutated neurons recorded by whole-cell patch-clamp and array-based electrodes comparing the topographic distribution of mutation. Computational simulation is used to understand neural network-level changes based on electrophysiological properties. To examine the underlying mechanism, we measured inhibitory and excitatory synaptic inputs in mutated neurons and nearby neurons by electrophysiological and histological methods using the mouse model and postoperative human brain tissue for cortical dysplasia. To explain non-cell-autonomous hyperexcitability, an inhibitor of adenosine kinase was injected into mice to enhance adenosine signaling and to mitigate hyperactivity of nearby nonmutated neurons.

RESULTS

We generated mice with a low-level somatic mutation in MTOR presenting spontaneous seizures. The seizure-triggering hyperexcitability originated from nonmutated neurons near mutation-carrying neurons, which proved to be less excitable than nonmutated neurons. Interestingly, the net balance between excitatory and inhibitory synaptic inputs onto mutated neurons remained unchanged. Additionally, we found that inhibition of adenosine kinase, which affects adenosine metabolism and neuronal excitability, reduced the hyperexcitability of nonmutated neurons.

INTERPRETATION

This study shows that neurons carrying somatic mutations in MTOR lead to focal epileptogenesis via non-cell-autonomous hyperexcitability of nearby nonmutated neurons. ANN NEUROL 2021;90:285-299.

Impact of Stress on Epilepsy: Focus on Neuroinflammation-A Mini Review

Epilepsy, one of the most common neurological disorders worldwide, is characterized by recurrent seizures and subsequent brain damage. Despite strong evidence supporting a deleterious impact on seizure occurrence and outcome severity, stress is an overlooked component in people with epilepsy. With regard to stressor duration and timing, acute stress can be protective in epileptogenesis, while chronic stress often promotes seizure occurrence in epilepsy patients. Preclinical research suggests that chronic stress promotes neuroinflammation and leads to a depressive state. Depression is the most common psychiatric comorbidity in people with epilepsy, resulting in a poor quality of life. Here, we summarize studies investigating acute and chronic stress as a seizure trigger and an important factor that worsens epilepsy outcomes and psychiatric comorbidities. Mechanistic insight into the impact of stress on epilepsy may create a window of opportunity for future interventions targeting neuroinflammation-related disorders.