Epilepsy is one of the three most prevalent neurological disorders. A significant proportion of patients suffering from epilepsy can be effectively treated if their seizures are detected in a timely manner. However, detection of most seizures requires the attention of trained neurologists—a scarce resource. Therefore, there is a need for an automatic seizure detection capability. A tunable non-patient-specific, non-seizure-specific method is proposed to detect the presence and locality of a seizure using electroencephalography (EEG) signals. This multifaceted computational approach is based on a network model of the brain and a distance metric based on the spectral profiles of EEG signals. This computationally time-efficient and cost-effective automated epileptic seizure detection algorithm has a median latency of 8 s, a median sensitivity of 83%, and a median false alarm rate of 2.9%. Hence, it is capable of being used in portable EEG devices to aid in the process of detecting and monitoring epileptic patients.

Motion techniques, such as highlighting communication items via flip and/or zoom motion, may support BCI-AAC success and comfort for those using P300 brain–computer interface techniques for augmentative and alternative communication device access (BCI-AAC). However, the utilization of motion in P300-BCI-AAC for children is largely unexplored. Therefore, the aims of this investigation are to provide initial insights into the impacts of functional pictorial symbol animation on (a) event-related potentials underlying P300-BCI-AAC performance and (b) children’s user experience. Participants completed two conditions: (1) a static item condition, and (2) a functional animation condition. Following completion, participants completed Likert scale ratings of factors like visual appeal. Animation significantly increased parieto-occipital P200/P300 amplitudes and delayed parieto-occipital N200, P200/P300, and N400 latencies. Further, animation raised ratings of visual appeal to a level approaching significance. Static highlighting significantly increased N400 amplitudes. Findings provide early insights into neural activity underlying P300-BCI-AAC highlighting of pictorial symbols via animation in children and justify further evaluation.

Seizures affect a significant portion of the world's population and while a small proportion of the seizures are easy to detect, the vast majority are subtle enough to require the expertise of a neurologist. In this paper, we present a multifaceted computational approach to detecting the presence and locality of a seizure using Electroencephalography (EEG) signals. We test the proposed approach using a variety of signals and demonstrate the efficacy of the approach.

G protein–coupled receptor 84 (GPR84) is a medium-chain free fatty acid receptor predominantly expressed in myeloid cells. Previous studies have identified GPR84 as an enhancer of the pro-inflammatory myeloid cell responses and a regulator of metabolic homeostasis. However, the role of GPR84 in T-cell function and metabolism remains largely unexplored. This study tested the effect of GPR84 modulation on CD8+ T-cell function and metabolism in vitro and examined its effect on antitumor function in adoptive cellular therapy models. Pharmacologic antagonism with GLPG1205 or genetic deletion of GPR84 promoted T-cell differentiation, proliferation, cytokine production, and cytotoxicity, whereas agonism with DL175 reduced these functions. These functional changes were paralleled by changes in metabolic activity. Antagonism and genetic deletion increased glucose uptake, glycolysis, oxidative phosphorylation, and ATP production, which enhanced the overall cell energetic fitness, whereas agonism resulted in a quiescent energetic profile. Furthermore, antagonism or deletion of GPR84 in antigen-specific CD8+ T cells in adoptive cellular therapy models enhanced their antitumor effects in vivo. Thus, GPR84 inhibition improves CD8+ T-cell function and may further enhance adoptive cellular therapies.