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Migraine is one of the most common neurological disorders in the US. Currently, the diagnosis and management of migraine are based primarily on subjective self-reported measures, which compromises the reliability of clinical diagnosis and the ability to robustly discern candidacy for available therapies and track treatment response. In this study, we used a computational pipeline for the automated, rapid, high-throughput, and objective analysis of encephalography (EEG) data at Cleveland Clinic to identify signatures that correlate with migraine. We performed two independent analyses, a prospective analysis (n = 62 subjects) and a retrospective age-matched analysis on a larger cohort (n = 734) obtained from the sleep registry at Cleveland Clinic. In the prospective analysis, no significant difference between migraine and control groups was detected in the mean power spectral density (PSD) of an all-electrodes montage in the frequency range of 1-32 Hz, whereas a significant PSD increase in single occipital electrodes was found at 12 Hz in migraine patients. We then trained machine learning models on the binary classification of migraine versus control using EEG power features, resulting in high accuracies (82-83%) with occipital electrodes' power at 12 Hz ranking highest in the contribution to the model's performance. Further retrospective analysis also showed a consistent increase in power from occipital electrodes at 12 and 13 Hz in migraine patients. These results demonstrate distinct and localized changes in brain activity measured by EEG that can potentially serve as biomarkers in the diagnosis and personalized therapy for individuals with migraine., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Brain resection is curative for a subset of patients with drug resistant epilepsy but up to half will fail to achieve sustained seizure freedom in the long term. There is a critical need for accurate prediction tools to identify patients likely to have recurrent postoperative seizures. Results from preclinical models and intracranial EEG in humans suggest that the window of time immediately before and after a seizure ("peri-ictal") represents a unique brain state with implications for clinical outcome prediction. Using a dataset of 294 patients who underwent temporal lobe resection for seizures, we show that machine learning classifiers can make accurate predictions of postoperative seizure outcome using 5 min of peri-ictal scalp EEG data that is part of universal presurgical evaluation (AUC 0.98, out-of-group testing accuracy > 90%). This is the first approach to seizure outcome prediction that employs a routine non-invasive preoperative study (scalp EEG) with accuracy range likely to translate into a clinical tool. Decision curve analysis (DCA) shows that compared to the prevalent clinical-variable based nomogram, use of the EEG-augmented approach could decrease the rate of unsuccessful brain resections by 20%., (© 2024. The Author(s).)

Background: Brainstem tumors represent ∼10% of pediatric brain tumors, ∼80% of these are diffuse midline glioma. Given invariably poor prognosis in diffuse midline glioma, there continues to be immense variation worldwide in performing biopsy of these lesions. Several contemporary studies in recent years have provided new data to elucidate the safety profile of biopsy and an updated meta-analysis is thus indicated., Methods: We found 29 studies of pediatric brainstem biopsy in the last 20 years (2003-2023, 1002 children). We applied meta-analysis of proportions using a random-effects model to generate point estimates, confidence intervals, and measures of heterogeneity., Results: Eighty-seven percent of procedures were stereotactic needle biopsies (of these, 62% with a frame, 14% without frame, and 24% robotic.) Biopsy resulted in a histological diagnosis ("technical yield") in 96.8% of cases (95% CI 95.4-98.2). Temporary complications were seen in 6% (95 CI 4-8), with the most common neurological complications being 1) cranial nerve dysfunction, 2) worsening or new ataxia, and 3) limb weakness. Permanent complications (excluding death) were seen in 1% (95% CI 0.5-2), most commonly including cranial nerve dysfunction and limb weakness. Five deaths were reported in the entire pooled cohort of 1002 children (0.5%)., Conclusions: When counseling families on the merits of brainstem biopsy in children, it is reasonable to state that permanent morbidity is rare (<2%). If biopsy is performed specifically to facilitate enrollment in clinical trials requiring a molecular diagnosis, the risks of biopsy outlined here should be weighed against potential benefits of trial enrollment., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

One of the goals in improving the design of compact portable micronuclear heat pipe reactors is to enhance their operating life so that they can generate maximum power within safe nuclear, thermal, and mechanical limits and with minimal human intervention. This work carries out an analysis to estimate the effect of non-uniform fuel enrichment and thermo-mechanical performance of a 1 MW thermal power uranium nitride fueled Micro Nuclear Heat Pipe Reactor (MNHPR). For neutronic and thermo-mechanical analyses, the open-source Monte Carlo code OpenMC and the COMSOL Multiphysics codes are used. The neutron flux distribution and subsequent fuel temperature, heat transport, stresses and strains are estimated. The analysis of core power distribution shows an uneven power distribution resulting in hot spots. The maximum fuel centerline temperature of 1353 K at the highest peaking factor 1.22 is within the safety limit. However, the high temperature results in higher thermal stress and subsequent displacement of 119 μ m that exceeds the 100 μ m fuel-clad gap. Power peaking thus significantly limits the maximum allowed operating power. In this study it is found that non-uniform placement of the fuel reduces power peaking and enhances the overall core performance. It is recommended to consider each fuel ring as a separate zone and gradually change the fuel enrichment in each zone. The non-uniform distribution of the fuel follows the gradual increase of enrichment from ring 1 to ring 5 with max enrichment in ring 5, and then a drop in the enrichment to mitigate any peaking in ring 6 due to its proximity to the reflector. From ring 1 to ring 6 fuel of 60-62-70-70-75-65 percent enrichment is recommended. The proposed fuel strategy mitigates power peaking in the core and enhances the maximum safe operating power level by 15 % from 775 kW to 893 kW without physical design change., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)