Estimating the likelihood of epilepsy from clinically noncontributory electroencephalograms using computational analysis: A retrospective, multisite case-control study.

OBJECTIVE: This study was undertaken to validate a set of candidate biomarkers of seizure susceptibility in a retrospective, multisite case-control study, and to determine the robustness of these biomarkers derived from routinely collected electroencephalography (EEG) within a large cohort (both epilepsy and common alternative conditions such as nonepileptic attack disorder). METHODS: The database consisted of 814 EEG recordings from 648 subjects, collected from eight National Health Service sites across the UK. Clinically noncontributory EEG recordings were identified by an experienced clinical scientist (N = 281; 152 alternative conditions, 129 epilepsy). Eight computational markers (spectral [n = 2], network-based [n = 4], and model-based [n = 2]) were calculated within each recording. Ensemble-based classifiers were developed using a two-tier cross-validation approach. We used standard regression methods to assess whether potential confounding variables (e.g., age, gender, treatment status, comorbidity) impacted model performance. RESULTS: We found levels of balanced accuracy of 68% across the cohort with clinically noncontributory normal EEGs (sensitivity =61%, specificity =75%, positive predictive value =55%, negative predictive value =79%, diagnostic odds ratio =4.64, area under receiver operated characteristics curve =.72). Group level analysis found no evidence suggesting any of the potential confounding variables significantly impacted the overall performance. SIGNIFICANCE: These results provide evidence that the set of biomarkers could provide additional value to clinical decision-making, providing the foundation for a decision support tool that could reduce diagnostic delay and misdiagnosis rates. Future work should therefore assess the change in diagnostic yield and time to diagnosis when utilizing these biomarkers in carefully designed prospective studies.

Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability.

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy-so-called interictal epileptiform activity-with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.

Variation in Carotid Artery Stenosis Measurements Among Facilities Seeking Carotid Stenting Facility Accreditation.

BACKGROUND: Based on the inclusion criteria of clinical trials, the degree of cervical carotid artery stenosis is often used as an indication for stent placement in the setting of extracranial carotid atherosclerotic disease. However, the rigor and consistency with which stenosis is measured outside of clinical trials are unclear. In an agreement study using a cross-sectional sample, we compared the percent stenosis as measured by real-world physician operators to that measured by independent expert reviewers. METHODS: As part of the carotid stenting facility accreditation review, images were obtained from 68 cases of patients who underwent carotid stent placement. Data collected included demographics, stroke severity measures, and the documented degree of stenosis, termed operator-reported stenosis (ORS), by 34 operators from 14 clinical sites. The ORS was compared with reviewer-measured stenosis (RMS) as assessed by 5 clinicians experienced in treating carotid artery disease. RESULTS: The median ORS was 90.0% (interquartile range, 80.0%-90.0%) versus a median RMS of 61.1% (interquartile range, 49.8%-73.6%), with a median difference of 21.8% (interquartile range, 13.7%-34.4%), P<0.001. The median difference in ORS and RMS for asymptomatic versus symptomatic patients was not statistically different (24.6% versus 19.6%; P=0.406). The median difference between ORS and RMS for facilities granted initial accreditation was smaller compared with facilities whose accreditation was delayed (17.9% versus 25.5%, P=0.035). The intraclass correlation between ORS and RMS was 0.16, indicating poor agreement. If RMS measurements were used, 72% of symptomatic patients and 10% of asymptomatic patients in the population examined would meet the Centers for Medicare and Medicaid Services criteria for stent placement. CONCLUSIONS: Real-world operators tend to overestimate carotid artery stenosis compared with external expert reviewers. Measurements from facilities granted initial accreditation were closer to expert measurements than those from facilities whose accreditation was delayed. Since decisions regarding carotid revascularization are often based on percent stenosis, such measuring discrepancies likely lead to increased procedural utilization.

Nuclear Modification of Transverse Momentum Dependent Parton Distribution Functions by a Global QCD Analysis.

We perform the first simultaneous global QCD extraction of the transverse momentum dependent (TMD) parton distribution functions and the TMD fragmentation functions in nuclei. We have considered the world set of data from semi-inclusive electron-nucleus deep inelastic scattering and Drell-Yan dilepton production. In total, this data set consists of 90 data points from HERMES, Fermilab, RHIC, and LHC. Working at next-to-leading order and next-to-next-to-leading logarithmic accuracy, we achieve a χ^{2}/d.o.f.=1.196. In this analysis, we perform the first extraction of nuclear modified TMDs and compare these to those in free nucleons. We also make predictions for the ongoing JLab 12 GeV program and future electron-ion collider measurements.

Retrospective review of the epidemiology, microbiology, management and outcomes of intra-cranial abscesses at a neurosurgical tertiary referral centre, 2018-2020.

BACKGROUND: Intracranial abscesses are rare but serious, and are associated with significant morbidity and mortality. Due to both the rarity and severity of these infections, well-controlled trials have not been reported in the literature, and optimal management is a matter for expert opinion. Advances in surgical management have improved outcomes and increased rates of microbiological diagnosis. However, the approach to antimicrobial chemotherapy varies considerably, including the choice of antibiotic, the duration of treatment, and the timing of oral switch. METHODS: We conducted a retrospective review of 43 cases of intracranial abscesses from a large, tertiary neurosurgical centre in London, UK, between 2018 and 2020, including 29 primary intra-parenchymal abscesses, 11 subdural abscesses and 3 extradural abscesses. RESULTS: The majority of cases had surgical intervention; 6/43 (14%) required repeat intervention (all intra-parenchymal abscesses). A microbiological diagnosis was made in 83% of cases. Intravenous antibiotics were given for a median of 33 days (IQR 23-44 days), with a variable duration of oral follow-on antibiotics. Total duration of antibiotic treatment ranged from 0 to 467 days. Only three patients from our cohort are known to have died. CONCLUSION: Shorter courses of intravenous antibiotics for brain abscesses were not associated with increased mortality. In the absence of well-controlled trials, a national registry of intracranial abscesses would provide invaluable data to inform optimal treatment.

Domino-like transient dynamics at seizure onset in epilepsy.

The International League Against Epilepsy (ILAE) groups seizures into "focal", "generalized" and "unknown" based on whether the seizure onset is confined to a brain region in one hemisphere, arises in several brain region simultaneously, or is not known, respectively. This separation fails to account for the rich diversity of clinically and experimentally observed spatiotemporal patterns of seizure onset and even less so for the properties of the brain networks generating them. We consider three different patterns of domino-like seizure onset in Idiopathic Generalized Epilepsy (IGE) and present a novel approach to classification of seizures. To understand how these patterns are generated on networks requires understanding of the relationship between intrinsic node dynamics and coupling between nodes in the presence of noise, which currently is unknown. We investigate this interplay here in the framework of domino-like recruitment across a network. In particular, we use a phenomenological model of seizure onset with heterogeneous coupling and node properties, and show that in combination they generate a range of domino-like onset patterns observed in the IGE seizures. We further explore the individual contribution of heterogeneous node dynamics and coupling by interpreting in-vitro experimental data in which the speed of onset can be chemically modulated. This work contributes to a better understanding of possible drivers for the spatiotemporal patterns observed at seizure onset and may ultimately contribute to a more personalized approach to classification of seizure types in clinical practice.

SUMOylation of PCNA by PIAS1 and PIAS4 promotes template switch in the chicken and human B cell lines.

DNA damage tolerance (DDT) releases replication blockage caused by damaged nucleotides on template strands employing two alternative pathways, error-prone translesion DNA synthesis (TLS) and error-free template switch (TS). Lys164 of proliferating cell nuclear antigen (PCNA) is SUMOylated during the physiological cell cycle. To explore the role for SUMOylation of PCNA in DDT, we characterized chicken DT40 and human TK6 B cells deficient in the PIAS1 and PIAS4 small ubiquitin-like modifier (SUMO) E3 ligases. DT40 cells have a unique advantage in the phenotypic analysis of DDT as they continuously diversify their immunoglobulin (Ig) variable genes by TLS and TS [Ig gene conversion (GC)], both relieving replication blocks at abasic sites without accompanying by DNA breakage. Remarkably, PIAS1-/-/PIAS4-/- cells displayed a multifold decrease in SUMOylation of PCNA at Lys164 and over a 90% decrease in the rate of TS. Likewise, PIAS1-/-/PIAS4-/- TK6 cells showed a shift of DDT from TS to TLS at a chemosynthetic UV lesion inserted into the genomic DNA. The PCNAK164R/K164R mutation caused a ∼90% decrease in the rate of Ig GC and no additional impact on PIAS1-/-/PIAS4-/- cells. This epistatic relationship between the PCNAK164R/K164R and the PIAS1-/-/PIAS4-/- mutations suggests that PIAS1 and PIAS4 promote TS mainly through SUMOylation of PCNA at Lys164. This idea is further supported by the data that overexpression of a PCNA-SUMO1 chimeric protein restores defects in TS in PIAS1-/-/PIAS4-/- cells. In conclusion, SUMOylation of PCNA at Lys164 promoted by PIAS1 and PIAS4 ensures the error-free release of replication blockage during physiological DNA replication in metazoan cells.

Motivational Interviewing to Promote the Effectiveness of Selective Prevention: an Integrated School-Based Approach.

School Mental Health prevention approaches that use multi-tiered systems are advancing rapidly. However, there is a relative shortage of effective selective prevention programs feasible to implement within the school context. To optimize the effectiveness of selective prevention in this context, a Motivational Interviewing (MI)-based prevention program for an adolescent student population was developed and tested. Footprints utilizes MI to increase engagement in modular Cognitive-Behavioral Therapy and to promote academic protective factors. In this study, forty-three adolescents were randomly assigned to Footprints or a treatment-as-usual waitlist control. Participants in the experimental condition demonstrated significant increases in behavioral and emotional functioning, self-efficacy to regulate behaviors, positive expectations for success, academic motivation, and grades in mathematics. Simultaneously, Footprints received high ratings for feasibility and acceptability within a dynamic school context. This exploratory efficacy evaluation provides initial support for MI's potential to promote the effectiveness of school-based prevention programs and warrants further study.

Changing practice to using pre-filled syringes for flushing IV cannulas.

In the UK, the Medicines and Healthcare products Regulatory Agency classifies 'pre-filled syringes' for flushing Intravenous (IV) cannulas and IV access devices as 'borderline' devices and offers some advice on how control measures can help mitigate risks. The Medicines Act (1968) and Medical Device Regulations try to address the legal position of these devices and allow each employer to identify those groups of staff allowed to use them. In turn, this may help address anomalies around the need to prescribe and document their use. This article describes how one large university health board in Wales implemented a change in products and practice and explores the issues around adopting and using CE-marked pre-filled, sterile syringes of 0.9% sodium chloride in place of manually drawing up an IV flush (the CE mark indicates devices that conforms with European legal requirements). Whether the use of individual components or a single pre-filled device can lead to a streamlined and cost-effective way to manage the flushing of IV cannula and vascular access devices was explored. Additional risk factors were identified, and the legal status clarified in line with current guidelines and regulations. As 0.9% sodium chloride in ampoules and vials is classified as a prescription-only medicine, the administration needs control via formal prescription or a patient group direction. Adopting and using these pre-filled syringes as CE-marked medical devices requires careful consideration and sign-off from each employing authority, before implementing them for flushing IV cannulas and IV access devices.

Dynamic responses of the adrenal steroidogenic regulatory network.

The hypothalamic-pituitary-adrenal axis is a dynamic system regulating glucocorticoid hormone synthesis in the adrenal glands. Many key factors within the adrenal steroidogenic pathway have been identified and studied, but little is known about how these factors function collectively as a dynamic network of interacting components. To investigate this, we developed a mathematical model of the adrenal steroidogenic regulatory network that accounts for key regulatory processes occurring at different timescales. We used our model to predict the time evolution of steroidogenesis in response to physiological adrenocorticotropic hormone (ACTH) perturbations, ranging from basal pulses to larger stress-like stimulations (e.g., inflammatory stress). Testing these predictions experimentally in the rat, our results show that the steroidogenic regulatory network architecture is sufficient to respond to both small and large ACTH perturbations, but coupling this regulatory network with the immune pathway is necessary to explain the dissociated dynamics between ACTH and glucocorticoids observed under conditions of inflammatory stress.

Epilepsy surgery: Evaluating robustness using dynamic network models.

Epilepsy is one of the most common neurological conditions affecting over 65 million people worldwide. Over one third of people with epilepsy are considered refractory: they do not respond to drug treatments. For this significant cohort of people, surgery is a potentially transformative treatment. However, only a small minority of people with refractory epilepsy are considered suitable for surgery, and long-term seizure freedom is only achieved in half the cases. Recently, several computational approaches have been proposed to support presurgical planning. Typically, these approaches use a dynamic network model to explore the potential impact of surgical resection in silico. The network component of the model is informed by clinical imaging data and is considered static thereafter. This assumption critically overlooks the plasticity of the brain and, therefore, how continued evolution of the brain network post-surgery may impact upon the success of a resection in the longer term. In this work, we use a simplified dynamic network model, which describes transitions to seizures, to systematically explore how the network structure influences seizure propensity, both before and after virtual resections. We illustrate key results in small networks, before extending our findings to larger networks. We demonstrate how the evolution of brain networks post resection can result in a return to increased seizure propensity. Our results effectively determine the robustness of a given resection to possible network reconfigurations and so provide a potential strategy for optimizing long-term seizure freedom.

Classifying dynamic transitions in high dimensional neural mass models: A random forest approach.

Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understand how dynamics change when parameters are varied. Despite being considered low dimensional in comparison to micro-scale, neuronal network models, with regards to understanding the relationship between parameters and dynamics, NMMs are still prohibitively high dimensional for classical approaches such as numerical continuation. Therefore, we need alternative methods to characterise dynamics of NMMs in high dimensional parameter spaces. Here, we introduce a statistical framework that enables the efficient exploration of the relationship between model parameters and selected features of the simulated, emergent model dynamics of NMMs. We combine the classical machine learning approaches of trees and random forests to enable studying the effect that varying multiple parameters has on the dynamics of a model. The method proceeds by using simulations to transform the mathematical model into a database. This database is then used to partition parameter space with respect to dynamic features of interest, using random forests. This allows us to rapidly explore dynamics in high dimensional parameter space, capture the approximate location of qualitative transitions in dynamics and assess the relative importance of all parameters in the model in all dimensions simultaneously. We apply this method to a commonly used NMM in the context of transitions to seizure dynamics. We find that the inhibitory sub-system is most crucial for the generation of seizure dynamics, confirm and expand previous findings regarding the ratio of excitation and inhibition, and demonstrate that previously overlooked parameters can have a significant impact on model dynamics. We advocate the use of this method in future to constrain high dimensional parameter spaces enabling more efficient, person-specific, model calibration.

Evolving dynamic networks: An underlying mechanism of drug resistance in epilepsy?

At least one-third of all people with epilepsy have seizures that remain poorly controlled despite an increasing number of available anti-epileptic drugs (AEDs). Often, there is an initial good response to a newly introduced AED, which may last up to months, eventually followed by the return of seizures thought to be due to the development of tolerance. We introduce a framework within which the interplay between AED response and brain networks can be explored to understand the development of tolerance. We use a computer model for seizure generation in the context of dynamic networks, which allows us to generate an 'in silico' electroencephalogram (EEG). This allows us to study the effect of changes in excitability network structure and intrinsic model properties on the overall seizure likelihood. Within this framework, tolerance to AEDs - return of seizure-like activity - may occur in 3 different scenarios: 1) the efficacy of the drug diminishes while the brain network remains relatively constant; 2) the efficacy of the drug remains constant, but connections between brain regions change; 3) the efficacy of the drug remains constant, but the intrinsic excitability within brain regions varies dynamically. We argue that these latter scenarios may contribute to a deeper understanding of how drug resistance to AEDs may occur.

An optimal strategy for epilepsy surgery: Disruption of the rich-club?

Surgery is a therapeutic option for people with epilepsy whose seizures are not controlled by anti-epilepsy drugs. In pre-surgical planning, an array of data modalities, often including intra-cranial EEG, is used in an attempt to map regions of the brain thought to be crucial for the generation of seizures. These regions are then resected with the hope that the individual is rendered seizure free as a consequence. However, post-operative seizure freedom is currently sub-optimal, suggesting that the pre-surgical assessment may be improved by taking advantage of a mechanistic understanding of seizure generation in large brain networks. Herein we use mathematical models to uncover the relative contribution of regions of the brain to seizure generation and consequently which brain regions should be considered for resection. A critical advantage of this modeling approach is that the effect of different surgical strategies can be predicted and quantitatively compared in advance of surgery. Herein we seek to understand seizure generation in networks with different topologies and study how the removal of different nodes in these networks reduces the occurrence of seizures. Since this a computationally demanding problem, a first step for this aim is to facilitate tractability of this approach for large networks. To do this, we demonstrate that predictions arising from a neural mass model are preserved in a lower dimensional, canonical model that is quicker to simulate. We then use this simpler model to study the emergence of seizures in artificial networks with different topologies, and calculate which nodes should be removed to render the network seizure free. We find that for scale-free and rich-club networks there exist specific nodes that are critical for seizure generation and should therefore be removed, whereas for small-world networks the strategy should instead focus on removing sufficient brain tissue. We demonstrate the validity of our approach by analysing intra-cranial EEG recordings from a database comprising 16 patients who have undergone epilepsy surgery, revealing rich-club structures within the obtained functional networks. We show that the postsurgical outcome for these patients was better when a greater proportion of the rich club was removed, in agreement with our theoretical predictions.

Aspiration Thrombectomy After Intravenous Alteplase Versus Intravenous Alteplase Alone.

BACKGROUND AND PURPOSE: Thrombectomy, primarily with stent retrievers with or without adjunctive aspiration, provided clinical benefit across multiple prospective randomized trials. Whether this benefit is exclusive to stent retrievers is unclear. METHODS: THERAPY (The Randomized, Concurrent Controlled Trial to Assess the Penumbra System's Safety and Effectiveness in the Treatment of Acute Stroke; NCT01429350) was an international, multicenter, prospective, randomized (1:1), open label, blinded end point evaluation, concurrent controlled clinical trial of aspiration thrombectomy after intravenous alteplase (IAT) administration compared with intravenous-alteplase alone in patients with large vessel ischemic stroke because of a thrombus length of ≥8 mm. The primary efficacy end point was the percent of patients achieving independence at 90 days (modified Rankin Scale score, 0-2; intention-to-treat analysis). The primary safety end point was the rate of severe adverse events (SAEs) by 90 days (as treated analysis). Patients were randomized 1:1 across 36 centers in 2 countries (United States and Germany). RESULTS: Enrollment was halted after 108 (55 IAT and 53 intravenous) patients (of 692 planned) because of external evidence of the added benefit of endovascular therapy to intravenous-alteplase alone. Functional independence was achieved in 38% IAT and 30% intravenous intention-to-treat groups (P=0.52). Intention-to-treat ordinal modified Rankin Scale odds ratio was 1.76 (95% confidence interval, 0.86-3.59; P=0.12) in favor of IAT. Secondary efficacy analyses all demonstrated a consistent direction of effect toward benefit of IAT. No differences in symptomatic intracranial hemorrhage rates (9.3% IAT versus 9.7% intravenous, P=1.0) or 90-day mortality (IAT: 12% versus intravenous: 23.9%, P=0.18) were observed. CONCLUSIONS: THERAPY did not achieve its primary end point in this underpowered sample. Directions of effect for all prespecified outcomes were both internally and externally consistent toward benefit. It is possible that an alternate method of thrombectomy, primary aspiration, will benefit selected patients harboring large vessel occlusions. Further study on this topic is indicated. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01429350.

A computational biomarker of idiopathic generalized epilepsy from resting state EEG.

Epilepsy is one of the most common serious neurologic conditions. It is characterized by the tendency to have recurrent seizures, which arise against a backdrop of apparently normal brain activity. At present, clinical diagnosis relies on the following: (1) case history, which can be unreliable; (2) observation of transient abnormal activity during electroencephalography (EEG), which may not be present during clinical evaluation; and (3) if diagnostic uncertainty occurs, undertaking prolonged monitoring in an attempt to observe EEG abnormalities, which is costly. Herein, we describe the discovery and validation of an epilepsy biomarker based on computational analysis of a short segment of resting-state (interictal) EEG. Our method utilizes a computer model of dynamic networks, where the network is inferred from the extent of synchrony between EEG channels (functional networks) and the normalized power spectrum of the clinical data. We optimize model parameters using a leave-one-out classification on a dataset comprising 30 people with idiopathic generalized epilepsy (IGE) and 38 normal controls. Applying this scheme to all 68 subjects we find 100% specificity at 56.7% sensitivity, and 100% sensitivity at 65.8% specificity. We believe this biomarker could readily provide additional support to the diagnostic process.

The origin of glucocorticoid hormone oscillations.

Oscillating levels of adrenal glucocorticoid hormones are essential for optimal gene expression, and for maintaining physiological and behavioural responsiveness to stress. The biological basis for these oscillations is not known, but a neuronal "pulse generator" within the hypothalamus has remained a popular hypothesis. We demonstrate that pulsatile hypothalamic activity is not required for generating ultradian glucocorticoid oscillations. We show that a constant level of corticotrophin-releasing hormone (CRH) can activate a dynamic pituitary-adrenal peripheral network to produce ultradian adrenocorticotrophic hormone and glucocorticoid oscillations with a physiological frequency. This oscillatory response to CRH is dose dependent and becomes disrupted for higher levels of CRH. These data suggest that glucocorticoid oscillations result from a sub-hypothalamic pituitary-adrenal system, which functions as a deterministic peripheral hormone oscillator with a characteristic ultradian frequency. This constitutes a novel mechanism by which the level, rather than the pattern, of CRH determines the dynamics of glucocorticoid hormone secretion.

Dynamics on networks: the role of local dynamics and global networks on the emergence of hypersynchronous neural activity.

Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3-6 Hz) and low-alpha (6-9 Hz) bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80% predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic stratification of people with epilepsy leading to improved diagnostics and therapeutics.

Posttreatment variables improve outcome prediction after intra-arterial therapy for acute ischemic stroke.

BACKGROUND: There are multiple clinical and radiographic factors that influence outcomes after endovascular reperfusion therapy (ERT) in acute ischemic stroke (AIS). We sought to derive and validate an outcome prediction score for AIS patients undergoing ERT based on readily available pretreatment and posttreatment factors. METHODS: The derivation cohort included 511 patients with anterior circulation AIS treated with ERT at 10 centers between September 2009 and July 2011. The prospective validation cohort included 223 patients with anterior circulation AIS treated in the North American Solitaire Acute Stroke registry. Multivariable logistic regression identified predictors of good outcome (modified Rankin score ≤2 at 3 months) in the derivation cohort; model ß coefficients were used to assign points and calculate a risk score. Discrimination was tested using C statistics with 95% confidence intervals (CIs) in the derivation and validation cohorts. Calibration was assessed using the Hosmer-Lemeshow test and plots of observed to expected outcomes. We assessed the net reclassification improvement for the derived score compared to the Totaled Health Risks in Vascular Events (THRIVE) score. Subgroup analysis in patients with pretreatment Alberta Stroke Program Early CT Score (ASPECTS) and posttreatment final infarct volume measurements was also performed to identify whether these radiographic predictors improved the model compared to simpler models. RESULTS: Good outcome was noted in 186 (36.4%) and 100 patients (44.8%) in the derivation and validation cohorts, respectively. Combining readily available pretreatment and posttreatment variables, we created a score (acronym: SNARL) based on the following parameters: symptomatic hemorrhage [2 points: none, hemorrhagic infarction (HI)1-2 or parenchymal hematoma (PH) type 1; 0 points: PH2], baseline National Institutes of Health Stroke Scale score (3 points: 0-10; 1 point: 11-20; 0 points: >20), age (2 points: <60 years; 1 point: 60-79 years; 0 points: >79 years), reperfusion (3 points: Thrombolysis In Cerebral Ischemia score 2b or 3) and location of clot (1 point: M2; 0 points: M1 or internal carotid artery). The SNARL score demonstrated good discrimination in the derivation (C statistic 0.79, 95% CI 0.75-0.83) and validation cohorts (C statistic 0.74, 95% CI 0.68-0.81) and was superior to the THRIVE score (derivation cohort: C statistic 0.65, 95% CI 0.60-0.70; validation cohort: C-statistic 0.59, 95% CI 0.52-0.67; p < 0.01 in both cohorts) but was inferior to a score that included age, ASPECTS, reperfusion status and final infarct volume (C statistic 0.86, 95% CI 0.82-0.91; p = 0.04). Compared with the THRIVE score, the SNARL score resulted in a net reclassification improvement of 34.8%. CONCLUSIONS: Among AIS patients treated with ERT, pretreatment scores such as the THRIVE score provide only fair prognostic information. Inclusion of posttreatment variables such as reperfusion and symptomatic hemorrhage greatly influences outcome and results in improved outcome prediction.

A novel genotoxicity assay of carbon nanotubes using functional macrophage receptor with collagenous structure (MARCO)-expressing chicken B lymphocytes.

Although carbon nanotubes (CNTs) are promising nanomaterials, their potential carcinogenicity is a major concern. We previously established a genetic method of analyzing genotoxicity of chemical compounds, where we evaluated their cytotoxic effect on the DT40 lymphoid cell line comparing DNA-repair-deficient isogenic clones with parental wild-type cells. However, application of our DT40 system for the cytotoxic and genotoxic evaluation of nanomaterials seemed to be difficult, because DT40 cells only poorly internalized nanoparticles. To solve this problem, we have constructed a chimeric gene encoding a trans-membrane receptor consisting of the 5' region of the transferrin receptor (TR) gene (to facilitate internalization of nanoparticles) and the 3' region of the macrophage receptor with collagenous structure (MARCO) gene (which is a receptor for environmental particles). We expressed the resulting MARCO-TR chimeric receptor on DNA-repair-proficient wild-type cells and mutants deficient in base excision repair (FEN1 (-/-)) and translesion DNA synthesis (REV3 (-/-)). We demonstrated that the chimera mediates uptake of particles such as fluorescence-tagged polystyrene particles and multi-walled carbon nanotubes (MWCNTs), with very poor uptake of those particles by DT40 cells not expressing the chimera. MWCNTs were cytotoxic and this effect was greater in FEN1 (-/-)and REV3 (-/-) cells than in wild-type cells. Furthermore, MWCNTs induced greater oxidative damage (measured as 8-OH-dG formation) and a larger number of mitotic chromosomal aberrations in repair-deficient cells compared to repair-proficient cells. Taken together, our novel assay system using the chimeric receptor-expressing DT40 cells provides a sensitive method to screen for genotoxicity of CNTs and possibly other nanomaterials.