Pilot trial of perampanel on peritumoral hyperexcitability and clinical outcomes in newly diagnosed high-grade glioma

Background Glutamatergic neuron-glioma synaptogenesis and peritumoral hyperexcitability promote glioma growth in a positive feedback loop. The objective of this study was to evaluate the feasibility and estimated effect sizes of the AMPA-R antagonist, perampanel, on intraoperative electrophysiologic hyperexcitability and clinical outcomes. Methods An open-label trial was performed comparing perampanel to standard of care (SOC) in patients undergoing resection of newly-diagnosed radiologic high-grade glioma. Perampanel was administered as a pre-operative loading dose followed by maintenance therapy until progressive disease or up to 12-months. SOC treatment involved levetiracetam for 7-days or as clinically indicated. The primary outcome of hyperexcitability was defined by intra-operative electrocorticography high frequency oscillation (HFO) rates. Seizure-freedom and overall survival (OS) were estimated by the Kaplan-Meier method. Tissue concentrations of perampanel, levetiracetam, and metabolites were measured by mass spectrometry. Results HFO rates were similar between perampanel-treated and SOC cohorts. The trial was terminated early after interim analysis for futility, and outcomes assessed in 11 patients (7 perampanel-treated, 4 SOC). Over a median 281 days of post-enrollment follow-up, 27% of patients had seizures, including 14% treated with perampanel and 50% treated with SOC. OS in perampanel-treated patients was similar to a glioblastoma reference cohort (p=0.81). Glutamate concentrations in surface biopsies were positively correlated with HFO rates in adjacent electrode contacts and were not significantly associated with treatment assignment or drug concentrations. Conclusions A peri-operative loading regimen of perampanel was safe and well-tolerated, with similar peritumoral hyperexcitability as in levetiracetam-treated patients. Maintenance anti-glutamatergic therapy was not observed to impact survival outcomes.

Comparative analysis of patients with new onset refractory status epilepticus preceded by fever (febrile infection-related epilepsy syndrome) versus without prior fever: An interim analysis

Febrile infection-related epilepsy syndrome (FIRES) is a subset of new onset refractory status epilepticus (NORSE) that involves a febrile infection prior to the onset of the refractory status epilepticus. It is unclear whether FIRES and non-FIRES NORSE are distinct conditions. Here, we compare 34 patients with FIRES to 30 patients with non-FIRES NORSE for demographics, clinical features, neuroimaging, and outcomes. Because patients with FIRES were younger than patients with non-FIRES NORSE (median = 28 vs. 48 years old, p = .048) and more likely cryptogenic (odds ratio = 6.89), we next ran a regression analysis using age or etiology as a covariate. Respiratory and gastrointestinal prodromes occurred more frequently in FIRES patients, but no difference was found for non-infection-related prodromes. Status epilepticus subtype, cerebrospinal fluid (CSF) and magnetic resonance imaging findings, and outcomes were similar. However, FIRES cases were more frequently cryptogenic; had higher CSF interleukin 6, CSF macrophage inflammatory protein-1 alpha (MIP-1a), and serum chemokine ligand 2 (CCL2) levels; and received more antiseizure medications and immunotherapy. After controlling for age or etiology, no differences were observed in presenting symptoms and signs or inflammatory biomarkers, suggesting that FIRES and non-FIRES NORSE are very similar conditions.

Observation of Seven Astrophysical Tau Neutrino Candidates with IceCube

We report on a measurement of astrophysical tau neutrinos with 9.7 yr of IceCube data. Using convolutional neural networks trained on images derived from simulated events, seven candidate ν_{τ} events were found with visible energies ranging from roughly 20 TeV to 1 PeV and a median expected parent ν_{τ} energy of about 200 TeV. Considering backgrounds from astrophysical and atmospheric neutrinos, and muons from π^{±}/K^{±} decays in atmospheric air showers, we obtain a total estimated background of about 0.5 events, dominated by non-ν_{τ} astrophysical neutrinos. Thus, we rule out the absence of astrophysical ν_{τ} at the 5σ level. The measured astrophysical ν_{τ} flux is consistent with expectations based on previously published IceCube astrophysical neutrino flux measurements and neutrino oscillations.

Surgical management of status epilepticus: A systematic review

Status Epilepticus (SE), unresponsive to medical management, is associated with high morbidity and mortality. Surgical management is typically considered in these refractory cases. The best surgical approach for affected patients remains unclear; however, given the lack of controlled trials exploring the role of surgery. We performed a systematic review according to PRIMSA guidelines, including case reports and series describing surgical interventions for patients in SE. Cases (157 patients, median age 12.9 years) were followed for a median of 12 months. Patients were in SE for a median of 21 days before undergoing procedures including: focal resection (36.9%), functional hemispherectomy (21%), lobar resection (12.7%), vagus nerve stimulation (VNS) (12.7%), deep brain stimulation (DBS) (6.4%), multiple subpial transection (MST) (3.8%), responsive neurostimulation (RNS) (1.9%), and cortical stimulator placement (1.27%), with 24 patients undergoing multiple procedures. Multiple SE semiologies were identified. 47.8% of patients had focal seizures, and 65% of patients had focal structural abnormalities on MRI. SE persisted for 36.8 ± 47.7 days prior to surgical intervention. SE terminated following surgery in 81.5%, terminated with additional adjuncts in 10.2%, continued in 1.9%, and was not specified in 6.4% of patients. Long-term seizure outcomes were favorable, with the majority improved and 51% seizure-free. Eight patients passed away in follow-up, of which three were in SE. Seizures emerging from one hemisphere were both more likely to immediately terminate (OR 4.7) and lead to long-term seizure-free status (OR 3.9) compared to nonunilateral seizures. No other predictors, including seizure focality, SE duration, or choice of surgical procedure, were predictors of SE termination. Surgical treatment of SE can be effective in terminating SE and leading to sustained seizure freedom, with many different procedures showing efficacy if matched appropriately with SE semiology and etiology. PLAIN LANGUAGE SUMMARY: Patients with persistent seizures (Status Epilepticus) that do not stop following medications can be treated effectively with surgery. Here, we systematically review the entirety of existing literature on surgery for treating status epilepticus to better identify how and when surgery is used and what patients do after surgery.

Glioma genetic profiles associated with electrophysiologic hyperexcitability

BACKGROUND

Distinct genetic alterations determine glioma aggressiveness, however, the diversity of somatic mutations contributing to peritumoral hyperexcitability and seizures over the course of the disease is uncertain. This study aimed to identify tumor somatic mutation profiles associated with clinically significant hyperexcitability.

METHODS

A single center cohort of adults with WHO grades 1-4 glioma and targeted exome sequencing (n = 1716) was analyzed and cross-referenced with a validated EEG database to identify the subset of individuals who underwent continuous EEG monitoring (n = 206). Hyperexcitability was defined by the presence of lateralized periodic discharges and/or electrographic seizures. Cross-validated discriminant analysis models trained exclusively on recurrent somatic mutations were used to identify variants associated with hyperexcitability.

RESULTS

The distribution of WHO grades and tumor mutational burdens were similar between patients with and without hyperexcitability. Discriminant analysis models classified the presence or absence of EEG hyperexcitability with an overall accuracy of 70.9%, regardless of IDH1 R132H inclusion. Predictive variants included nonsense mutations in ATRX and TP53, indel mutations in RBBP8 and CREBBP, and nonsynonymous missense mutations with predicted damaging consequences in EGFR, KRAS, PIK3CA, TP53, and USP28. This profile improved estimates of hyperexcitability in a multivariate analysis controlling for age, sex, tumor location, integrated pathologic diagnosis, recurrence status, and preoperative epilepsy. Predicted somatic mutation variants were over-represented in patients with hyperexcitability compared to individuals without hyperexcitability and those who did not undergo continuous EEG.

CONCLUSION

These findings implicate diverse glioma somatic mutations in cancer genes associated with peritumoral hyperexcitability. Tumor genetic profiling may facilitate glioma-related epilepsy prognostication and management.

The International Cardiac Arrest Research Consortium Electroencephalography Database

OBJECTIVES

To develop the International Cardiac Arrest Research (I-CARE), a harmonized multicenter clinical and electroencephalography database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest.

DESIGN

Multicenter cohort, partly prospective and partly retrospective.

SETTING

Seven academic or teaching hospitals from the United States and Europe.

PATIENTS

Individuals 16 years old or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous electroencephalography monitoring were included.

INTERVENTIONS

Not applicable.

MEASUREMENTS AND MAIN RESULTS

Clinical and electroencephalography data were harmonized and stored in a common Waveform Database-compatible format. Automated spike frequency, background continuity, and artifact detection on electroencephalography were calculated with 10-second resolution and summarized hourly. Neurologic outcome was determined at 3-6 months using the best Cerebral Performance Category (CPC) scale. This database includes clinical data and 56,676 hours (3.9 terabytes) of continuous electroencephalography data for 1,020 patients. Most patients died ( n = 603, 59%), 48 (5%) had severe neurologic disability (CPC 3 or 4), and 369 (36%) had good functional recovery (CPC 1-2). There is significant variability in mean electroencephalography recording duration depending on the neurologic outcome (range, 53-102 hr for CPC 1 and CPC 4, respectively). Epileptiform activity averaging 1 Hz or more in frequency for at least 1 hour was seen in 258 patients (25%) (19% for CPC 1-2 and 29% for CPC 3-5). Burst suppression was observed for at least 1 hour in 207 (56%) and 635 (97%) patients with CPC 1-2 and CPC 3-5, respectively.

CONCLUSIONS

The I-CARE consortium electroencephalography database provides a comprehensive real-world clinical and electroencephalography dataset for neurophysiology research of comatose patients after cardiac arrest. This dataset covers the spectrum of abnormal electroencephalography patterns after cardiac arrest, including epileptiform patterns and those in the ictal-interictal continuum.

Automated detection of immune effector cell-associated neurotoxicity syndrome via quantitative EEG

OBJECTIVE

To develop an automated, physiologic metric of immune effector cell-associated neurotoxicity syndrome among patients undergoing chimeric antigen receptor-T cell therapy.

METHODS

We conducted a retrospective observational cohort study from 2016 to 2020 at two tertiary care centers among patients receiving chimeric antigen receptor-T cell therapy with a CD19 or B-cell maturation antigen ligand. We determined the daily neurotoxicity grade for each patient during EEG monitoring via chart review and extracted clinical variables and outcomes from the electronic health records. Using quantitative EEG features, we developed a machine learning model to detect the presence and severity of neurotoxicity, known as the EEG immune effector cell-associated neurotoxicity syndrome score.

RESULTS

The EEG immune effector cell-associated neurotoxicity syndrome score significantly correlated with the grade of neurotoxicity with a median Spearman's R2 of 0.69 (95% CI of 0.59-0.77). The mean area under receiving operator curve was greater than 0.85 for each binary discrimination level. The score also showed significant correlations with maximum ferritin (R2 0.24, p = 0.008), minimum platelets (R2 -0.29, p = 0.001), and dexamethasone usage (R2 0.42, p < 0.0001). The score significantly correlated with duration of neurotoxicity (R2 0.31, p < 0.0001).

INTERPRETATION

The EEG immune effector cell-associated neurotoxicity syndrome score possesses high criterion, construct, and predictive validity, which substantiates its use as a physiologic method to detect the presence and severity of neurotoxicity among patients undergoing chimeric antigen receptor T-cell therapy.

Alcoholic Solvent-Mediated Excited-State Proton Transfer Dynamics of a Novel Dihydroxynaphthalene Dye

The excited-state proton transfer (ESPT) reaction is an important primary photochemical process because it is closely related to photophysical properties. Although ESPT research in aqueous solutions is predominant, alcoholic solvent-mediated ESPT studies are also significant in terms of photoacid-based reactions. Especially, the research for dihydroxynaphthalenes (DHNs) has been largely neglected due to the challenging data interpretation of two hydroxyl groups. A novel fluorescent dye, resveratrone, synthesized by light irradiation of resveratrol, which is famous for its antioxidant properties, can be regarded as a type of DHN, and it has distinctive optical properties, including high quantum yield, a large two-photon absorption coefficient, a large Stokes shift, and very high biocompatibility. In this study, we investigate the overall kinetics of the optical properties of resveratrone and find evidence for alcoholic solvent-mediated ESPT involvement in the radiative properties of resveratrone with a large Stokes shift. Our investigation provides an opportunity to revisit the overlooked photophysical properties of intriguing photoacid behavior and the large Stokes shift of the dihydroxynaphthalene dye.

Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest

BACKGROUND AND OBJECTIVES

Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest.

METHODS

Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months.

RESULTS

One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery.

DISCUSSION

Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.

The International Cardiac Arrest Research (I-CARE) Consortium Electroencephalography Database

Objective

To develop a harmonized multicenter clinical and electroencephalography (EEG) database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest.

Design

Multicenter cohort, partly prospective and partly retrospective.

Setting

Seven academic or teaching hospitals from the U.S. and Europe.

Patients

Individuals aged 16 or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous EEG monitoring were included.

Interventions

not applicable.

Measurements and Main Results

Clinical and EEG data were harmonized and stored in a common Waveform Database (WFDB)-compatible format. Automated spike frequency, background continuity, and artifact detection on EEG were calculated with 10 second resolution and summarized hourly. Neurological outcome was determined at 3-6 months using the best Cerebral Performance Category (CPC) scale. This database includes clinical and 56,676 hours (3.9 TB) of continuous EEG data for 1,020 patients. Most patients died (N=603, 59%), 48 (5%) had severe neurological disability (CPC 3 or 4), and 369 (36%) had good functional recovery (CPC 1-2). There is significant variability in mean EEG recording duration depending on the neurological outcome (range 53-102h for CPC 1 and CPC 4, respectively). Epileptiform activity averaging 1 Hz or more in frequency for at least one hour was seen in 258 (25%) patients (19% for CPC 1-2 and 29% for CPC 3-5). Burst suppression was observed for at least one hour in 207 (56%) and 635 (97%) patients with CPC 1-2 and CPC 3-5, respectively.

Conclusions

The International Cardiac Arrest Research (I-CARE) consortium database provides a comprehensive real-world clinical and EEG dataset for neurophysiology research of comatose patients after cardiac arrest. This dataset covers the spectrum of abnormal EEG patterns after cardiac arrest, including epileptiform patterns and those in the ictal-interictal continuum.

Observation of high-energy neutrinos from the Galactic plane

The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth's atmosphere, is unknown. Because of deflection by interstellar magnetic fields, cosmic rays produced within the Milky Way arrive at Earth from random directions. However, cosmic rays interact with matter near their sources and during propagation, which produces high-energy neutrinos. We searched for neutrino emission using machine learning techniques applied to 10 years of data from the IceCube Neutrino Observatory. By comparing diffuse emission models to a background-only hypothesis, we identified neutrino emission from the Galactic plane at the 4.5σ level of significance. The signal is consistent with diffuse emission of neutrinos from the Milky Way but could also arise from a population of unresolved point sources.

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs

BACKGROUND AND OBJECTIVES

The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as "ictal-interictal-injury continuum" (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC.

METHODS

This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as "seizure (SZ)," "lateralized periodic discharges (LPDs)," "generalized periodic discharges (GPDs)," "lateralized rhythmic delta activity (LRDA)," "generalized rhythmic delta activity (GRDA)," or "other." EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability.

RESULTS

Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds.

DISCUSSION

Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

Development of Expert-Level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation

BACKGROUND AND OBJECTIVES

Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as "ictal-interictal-injury continuum" (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns.

METHODS

We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes.

RESULTS

SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and "other" classes, SPaRCNet exceeds the following percentages of 20 experts-ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively.

DISCUSSION

SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

Abstract 542: Synthetic lethal targeting of AURKA in head and neck squamous cell carcinoma

The purpose of this study was to identify new combination strategies for improving treatment of head and neck squamous cell carcinomas (HNSCCs). HNSCCs often express high levels of Aurora kinase A (AURKA), most studied as a kinase important for mitotic progression in normal cells. Notably the overexpression of AURKA in many cancers allows it to act throughout the cell cycle, acquiring new cancer-promoting activities. While several AURKA inhibitors are in clinical trials, limited efficacy is observed with single treatment, causing us to evaluate potential AURKA combination therapeutic combinations. Particularly relevant to HNSCC, which often overexpress and depend on EGFR, overexpression of AURKA can promote resistance to EGFR inhibitors by mechanisms variously identified as including activation of the EGFR effectors AKT, ERK, and BIM. Using viability and clonogenic assays, we have found that the AURKA inhibitor VIC-1911 synergizes with the EGFR inhibitors afatinib and erlotinib in multiple HNSCC cell lines and retains activity in HNSCC cell models selected for resistance to these EGFR inhibitors. However, AURKA inhibition increases levels of AURKA protein and its protein-stabilizing partner TPX2, counteracting drug effect. We also combined inhibition of AURKA with inhibition of WEE1, a regulator of the G2/M checkpoint, finding this dual inhibition enhanced levels of apoptosis in EGFR inhibitor resistant HNSCC cell lines. Intriguingly, one recent study reported AURKA can also modulate the glycolytic signaling pathway, increasing the cancer-promoting Warburg effect. We have found that inhibition of AURKA can significantly reduce glycolytic flux in HNSCC cell lines and alter expression and phosphorylation of key glycolytic enzymes. Dual inhibition of AURKA in combination with inhibitors of glycolytic enzymes, or enzymes regulating oxidative phosphorylation, showed marked synergy. These and other results investigating AURKA signaling mechanisms in HNSCC demonstrate that the non-canonical functions of AURKA include viable therapeutic targets that can enhance the efficacy of AURKA inhibition in HNSCC.

Citation Format: Flaviane N da Silva, Theodore Nguyen, Jong Woo Lee, Barbara Burtness, Erica Golemis. Synthetic lethal targeting of AURKA in head and neck squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 542.

Abstract 1563: Concomitant inhibition of Aurora kinase A and WEE1 kinases results in synergistic tumor control and heightens DNA replication stress in head and neck and lung carcinomas

Human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) and lung cancer mainly harbor disruptive mutations in TP53 and/or CDKN2A tumor suppressor genes, which are associated with refractoriness to treatment as well as poor prognosis and survival. Mutational loss of TP53 function fosters elevated expression of Aurora kinase A (AURKA) that plays a crucial role in mitotic progression at G2/M and stabilizes DNA replication forks at S phase. We have previously demonstrated that combined inhibition of AURKA and WEE1, a G2/M checkpoint kinase induced by replication stress, results in synergistic anti-tumor effects in HNSCC in vitro and in vivo. We have now further confirmed synergy using the highly selective AURKA inhibitor VIC1911 in HNSCC and lung cancers harboring TP53 mutations and explored mechanisms of cell death. VIC1911 and adavosertib combination synergistically suppressed cell growth and survival in both 2D- and 3D-culture systems relative to vehicle or single-agent treatment in TP53-mutated HNSCC FaDu and CAL27, and lung cancer A549 and NCI-H358 cells, with no observable toxicity in normal cells, predicting a favorable therapeutic index. Furthermore, combination treatment accelerated mitotic entry and resulted in accumulation of mitotic catastrophe, as demonstrated by time-lapse imaging, and apoptotic cell death as evidenced by cleaved PARP assays. Notably, we found that combination VIC1911 and adavosertib in HNSCC cells drastically slowed and stalled progression of replication forks in DNA fiber analysis (Mean: DMSO=3.117; adavosertib=1.495; VIC1911=0.9757; combination=0.5548 kb/min; P &lt;0.0001) and amplified DNA damage as measured by γH2AX, indicating induction of severe replication stress. In vivo, this combination resulted in significant tumor regression in both HNSCC and lung adenocarcinoma patient-derived and cancer cell-derived xenografted mice compared with either vehicle or single-agent treatment. Taken together, these results suggest that AURKA inhibition increases dependency on WEE1 by enhancing replication stress and mitotic catastrophe, and support clinical evaluation of combined AURKA and WEE1 inhibition as a novel and effective treatment for HNSCC and lung cancer patients with elevated AURKA expression.

Citation Format: Jong Woo Lee, Sundong Kim, Sebastian Cruz-Gomez, Jackie Shi, Cindy Yang, Barbara Burtness. Concomitant inhibition of Aurora kinase A and WEE1 kinases results in synergistic tumor control and heightens DNA replication stress in head and neck and lung carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1563.

Safe Use of Cenobamate in Super Refractory Status Epilepticus: A Case Series

Cenobamate is an effective new adjunctive antiseizure medication (ASM) for treatment resistant focal epilepsy. It has broad spectrum anticonvulsant activity and may be a useful medication for super refractory status epilepticus (SRSE), but has not yet been studied in generalized seizures or an inpatient setting. Here we describe 2 SRSE cases where cenobamate was added safely to other treatments. It was uptitrated slowly to reduce the risk of hypersensitivity reactions which have been observed previously with rapid increasing dosages. Both patients achieved seizure control and liberation from intensive care. They have remained seizure free with continued treatment and have not experienced any side effects attributable to cenobamate. Cenobamate warrants further examination in patients with refractory status epilepticus.

Multimodal Prediction of Favorable Outcome After Cardiac Arrest: A Cohort Study

OBJECTIVES

Prognostic guidelines after cardiac arrest (CA) focus on unfavorable outcome prediction; favorable outcome prognostication received less attention. Our aim was to identify favorable outcome predictors and combine them into a multimodal model.

DESIGN

Retrospective analysis of prospectively collected data (January 2016 to June 2021).

SETTING

Two academic hospitals (Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland; Brigham and Women's Hospital, Boston, MA).

PATIENTS

Four hundred ninety-nine consecutive comatose adults admitted after CA.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

CA variables (initial rhythm, time to return of spontaneous circulation), clinical examination (Full Outline of UnResponsiveness [FOUR] score at 72 hr, early myoclonus), electroencephalography (EEG) (reactivity, continuity, epileptiform features, and prespecified highly malignant patterns), somatosensory-evoked potentials, quantified pupillometry, and serum neuron-specific enolase (NSE) were retrieved. Neurologic outcome was assessed at 3 months using Cerebral Performance Category (CPC); 1 and 2 were considered as favorable outcome. Predictive performance of each variable toward favorable outcomes were calculated, and most discriminant items were combined to obtain a multimodal prognostic score, using multivariable ordinal logistic regression, receiving operator characteristic curves, and cross-validation. Our analysis identified a prognostic score including six modalities (1 point each): 1) early (12-36 hr) EEG not highly malignant, 2) early EEG background reactivity, 3) late (36-72 hr) EEG background reactivity and 4) continuity, 5) peak serum NSE within 48 hours less than or equal to 41 µg/L, and 6) FOUR score greater than or equal to 5 at 72 hours. At greater than or equal to 4 out of 6 points, sensitivity for CPC 1-2 was 97.5% (95% CI, 92.9-99.5%) and accuracy was 77.5% (95% CI, 72.7-81.8%); area under the curve was 0.88 (95% CI, 0.85-0.91). The score showed similar performances in the validation cohort.

CONCLUSIONS

This study describes and externally validates a multimodal score, including clinical, EEG and biological items available within 72 hours, showing a high performance in identifying early comatose CA survivors who will reach functional independence at 3 months.

Search for the Pair Production of Dark Particles X with K_{L}^{0}→XX, X→γγ

We present the first search for the pair production of dark particles X via K_{L}^{0}→XX with X decaying into two photons using the data collected by the KOTO experiment. No signal was observed in the mass range of 40-110  MeV/c^{2} and 210-240  MeV/c^{2}. This sets upper limits on the branching fractions as B(K_{L}^{0}→XX)<(1-4)×10^{-7} and B(K_{L}^{0}→XX)<(1-2)×10^{-6} at the 90% confidence level for the two mass regions, respectively.

Quantitative epileptiform burden and electroencephalography background features predict post-traumatic epilepsy

BACKGROUND

Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Electroencephalography aids early post-traumatic seizure diagnosis, but its optimal utility for PTE prediction remains unknown. We aim to evaluate the contribution of quantitative electroencephalograms to predict first-year PTE (PTE1).

METHODS

We performed a multicentre, retrospective case-control study of patients with TBI. 63 PTE1 patients were matched with 63 non-PTE1 patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1 using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities.

RESULTS

In the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE1 risk based on multivariable logistic regression analysis (area under the receiver operating characteristic curve, AUC (95% CI) 0.69 (0.60 to 0.78)). Among 116 (92%) patients with available CT reports, adding quantitative electroencephalography features to a combined mechanism and CT model improved performance (AUC (95% CI), 0.71 (0.61 to 0.80) vs 0.61 (0.51 to 0.72)).

CONCLUSIONS

Epileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE1 prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

Glioma genetic profiles associated with electrophysiologic hyperexcitability

Distinct genetic alterations determine glioma aggressiveness, however the diversity of somatic mutations contributing to peritumoral hyperexcitability and seizures is uncertain. In a large cohort of patients with sequenced gliomas (n=1716), we used discriminant analysis models to identify somatic mutation variants associated with electrographic hyperexcitability in a subset with continuous EEG recording (n=206). Overall tumor mutational burdens were similar between patients with and without hyperexcitability. A cross-validated model trained exclusively on somatic mutations classified the presence or absence of hyperexcitability with an overall accuracy of 70.9%, and improved estimates of hyperexcitability and anti-seizure medication failure in multivariate analysis incorporating traditional demographic factors and tumor molecular classifications. Somatic mutation variants of interest were also over-represented in patients with hyperexcitability compared to internal and external reference cohorts. These findings implicate diverse mutations in cancer genes associated with the development of hyperexcitability and response to treatment.

Association between postictal EEG suppression, postictal autonomic dysfunction, and sudden unexpected death in epilepsy: Evidence from intracranial EEG

OBJECTIVE

The association between postictal electroencephalogram (EEG) suppression (PES), autonomic dysfunction, and Sudden Unexpected Death in Epilepsy (SUDEP) remains poorly understood. We compared PES on simultaneous intracranial and scalp-EEG and evaluated the association of PES with postictal heart rate variability (HRV) and SUDEP outcome.

METHODS

Convulsive seizures were analyzed in patients with drug-resistant epilepsy at 5 centers. Intracranial PES was quantified using the Hilbert transform. HRV was quantified using root mean square of successive differences of interbeat intervals, low-frequency to high-frequency power ratio, and RR-intervals.

RESULTS

There were 64 seizures from 63 patients without SUDEP and 11 seizures from 6 SUDEP patients. PES occurred in 99% and 87% of seizures on intracranial-EEG and scalp-EEG, respectively. Mean PES duration in intracranial and scalp-EEG was similar. Intracranial PES was regional (<90% of channels) in 46% of seizures; scalp PES was generalized in all seizures. Generalized PES showed greater decrease in postictal parasympathetic activity than regional PES. PES duration and extent were similar between patients with and without SUDEP.

CONCLUSIONS

Regional intracranial PES can be present despite scalp-EEG demonstrating generalized or no PES. Postictal autonomic dysfunction correlates with the extent of PES.

SIGNIFICANCE

Intracranial-EEG demonstrates changes in autonomic regulatory networks not seen on scalp-EEG.

Forecasting immune effector cell-associated neurotoxicity syndrome after chimeric antigen receptor t-cell therapy

BACKGROUND

Immune effector cell-associated neurotoxicity syndrome (ICANS) is a clinical and neuropsychiatric syndrome that can occur days to weeks following administration chimeric antigen receptor (CAR) T-cell therapy. Manifestations of ICANS range from encephalopathy and aphasia to cerebral edema and death. Because the onset and time course of ICANS is currently unpredictable, prolonged hospitalization for close monitoring following CAR T-cell infusion is a frequent standard of care.

METHODS

This study was conducted at Brigham and Women's Hospital from April 2015 to February 2020. A cohort of 199 hospitalized patients treated with CAR T-cell therapy was used to develop a combined hidden Markov model and lasso-penalized logistic regression model to forecast the course of ICANS. Model development was done using leave-one-patient-out cross validation.

RESULTS

Among the 199 patients included in the analysis 133 were male (66.8%), and the mean (SD) age was 59.5 (11.8) years. 97 patients (48.7%) developed ICANS, of which 59 (29.6%) experienced severe grades 3-4 ICANS. Median time of ICANS onset was day 9. Selected clinical predictors included maximum daily temperature, C reactive protein, IL-6, and procalcitonin. The model correctly predicted which patients developed ICANS and severe ICANS, respectively, with area under the curve of 96.7% and 93.2% when predicting 5 days ahead, and area under the curve of 93.2% and 80.6% when predicting the entire future risk trajectory looking forward from day 5. Forecasting performance was also evaluated over time horizons ranging from 1 to 7 days, using metrics of forecast bias, mean absolute deviation, and weighted average percentage error.

CONCLUSION

The forecasting model accurately predicts risk of ICANS following CAR T-cell infusion and the time course ICANS follows once it has begun.Cite Now.

EEG-based grading of immune effector cell-associated neurotoxicity syndrome

CAR-T cell therapy is an effective cancer therapy for multiple refractory/relapsed hematologic malignancies but is associated with substantial toxicity, including Immune Effector Cell Associated Neurotoxicity Syndrome (ICANS). Improved detection and assessment of ICANS could improve management and allow greater utilization of CAR-T cell therapy, however, an objective, specific biomarker has not been identified. We hypothesized that the severity of ICANS can be quantified based on patterns of abnormal brain activity seen in electroencephalography (EEG) signals. We conducted a retrospective observational study of 120 CAR-T cell therapy patients who had received EEG monitoring. We determined a daily ICANS grade for each patient through chart review. We used visually assessed EEG features and machine learning techniques to develop the Visual EEG-Immune Effector Cell Associated Neurotoxicity Syndrome (VE-ICANS) score and assessed the association between VE-ICANS and ICANS. We also used it to determine the significance and relative importance of the EEG features. We developed the Visual EEG-ICANS (VE-ICANS) grading scale, a grading scale with a physiological basis that has a strong correlation to ICANS severity (R = 0.58 [0.47-0.66]) and excellent discrimination measured via area under the receiver operator curve (AUC = 0.91 for ICANS ≥ 2). This scale shows promise as a biomarker for ICANS which could help to improve clinical care through greater accuracy in assessing ICANS severity.

Search for Unstable Sterile Neutrinos with the IceCube Neutrino Observatory

We present a search for an unstable sterile neutrino by looking for a resonant signal in eight years of atmospheric ν_{μ} data collected from 2011 to 2019 at the IceCube Neutrino Observatory. Both the (stable) three-neutrino and the 3+1 sterile neutrino models are disfavored relative to the unstable sterile neutrino model, though with p values of 2.8% and 0.81%, respectively, we do not observe evidence for 3+1 neutrinos with neutrino decay. The best-fit parameters for the sterile neutrino with decay model from this study are Δm_{41}^{2}=6.7_{-2.5}^{+3.9}  eV^{2}, sin^{2}2θ_{24}=0.33_{-0.17}^{+0.20}, and g^{2}=2.5π±1.5π, where g is the decay-mediating coupling. The preferred regions of the 3+1+decay model from short-baseline oscillation searches are excluded at 90% C.L.

Circularly polarized light-sensitive, hot electron transistor with chiral plasmonic nanoparticles

The quantitative detection of circularly polarized light (CPL) is necessary in next-generation optical communication carrying high-density information and in phase-controlled displays exhibiting volumetric imaging. In the current technology, multiple pixels of different wavelengths and polarizers are required, inevitably resulting in high loss and low detection efficiency. Here, we demonstrate a highly efficient CPL-detecting transistor composed of chiral plasmonic nanoparticles with a high Khun's dissymmetry (g-factor) of 0.2 and a high mobility conducting oxide of InGaZnO. The device successfully distinguished the circular polarization state and displayed an unprecedented photoresponsivity of over 1 A/W under visible CPL excitation. This observation is mainly attributed to the hot electron generation in chiral plasmonic nanoparticles and to the effective collection of hot electrons in the oxide semiconducting transistor. Such characteristics further contribute to opto-neuromorphic operation and the artificial nervous system based on the device successfully performs image classification work. We anticipate that our strategy will aid in the rational design and fabrication of a high-performance CPL detector and opto-neuromorphic operation with a chiral plasmonic structure depending on the wavelength and circular polarization state.

Strong Constraints on Neutrino Nonstandard Interactions from TeV-Scale ν_{μ} Disappearance at IceCube

We report a search for nonstandard neutrino interactions (NSI) using eight years of TeV-scale atmospheric muon neutrino data from the IceCube Neutrino Observatory. By reconstructing incident energies and zenith angles for atmospheric neutrino events, this analysis presents unified confidence intervals for the NSI parameter ε_{μτ}. The best-fit value is consistent with no NSI at a p value of 25.2%. With a 90% confidence interval of -0.0041≤ε_{μτ}≤0.0031 along the real axis and similar strength in the complex plane, this result is the strongest constraint on any NSI parameter from any oscillation channel to date.

Early EEG hyperexcitability is associated with decreased survival in newly diagnosed IDH-wildtype glioma

PURPOSE

The relationship between peritumoral neuronal activity, early onset clinical seizures, and glioma survival outcomes remains poorly understood. Hyperexcitability on continuous EEG in the peri-operative period was studied as a prognostic biomarker in patients with newly diagnosed IDH-wildtype diffuse glioma.

METHODS

A retrospective observational cohort study was performed including adults with newly diagnosed diffuse glioma, absence of IDH1/2 mutations, and continuous EEG monitoring prior to chemoradiation and within 1 month of initial resection. EEG hyperexcitability was defined by the presence of lateralized periodic discharges and/or electrographic seizures. The primary outcome of overall survival was estimated using the Kaplan-Meier method and compared between groups using multivariate Cox proportional hazards model.

RESULTS

There were 424 patients without continuous EEG and 32 with continuous EEG, of whom lateralized periodic discharges and/or electrographic seizures were seen in 17 (53%). Peri-operative EEG hyperexcitability was associated with decreased overall survival in multivariate analysis [median 12.5 (95% CI 6.2-25.6] months with hyperexcitability versus median 19.9 [95% CI 8.9-53.5] months without hyperexcitability, p = 0.043). Compared to patients without continuous EEG, overall survival was decreased in patients with hyperexcitability (p < 0.0001) and similar in patients without hyperexcitability (p = 0.193). Patients with and without hyperexcitability had similar rates of exposure to anti-seizure medication at baseline, and in long-term follow-up had no difference in number of medications required for seizure control.

CONCLUSIONS

These findings indicate the potential prognostic value of a clinical EEG biomarker of glioma aggressiveness prior to the initiation of chemoradiation.

Enhanced Extraction Efficiency of Flavonoids from Pyrus ussuriensis Leaves with Deep Eutectic Solvents

In this study, deep eutectic solvents (DESs) were synthesized using different ratios of choline chloride (CC) and dicarboxylic acids, and their eutectic temperatures were determined. The DES synthesized using CC and glutaric acid (GA), which showed a higher extraction efficiency than conventional solvents, was used for the extraction of flavonoid components from Pyrus ussuriensis leaves (PUL), and the extraction efficiency was evaluated using the response surface methodology. The flavonoid components rutin, hyperoside, and isoquercitrin were identified through high-performance liquid chromatography (HPLC), equipped with a Waters 2996 PDA detector, and HPLC mass spectrometry (LC-MS/MS) analyses. The optimum extraction was achieved at a temperature of 30 °C using DES in a concentration of 30.85 wt.% at a stirring speed of 1113 rpm and an extraction time of 1 h. The corresponding flavonoid content was 217.56 μg/mL. The results were verified by performing three reproducibility experiments, and a high significance, with a confidence range of 95%, was achieved. In addition, the PUL extracts exhibited appreciable antioxidant activity. The results showed that the extraction process using the DES based on CC and GA in a 1:1 molar ratio could effectively improve the yield of flavonoids from PUL.

Neurological Prognostication After Hypoglycemic Coma: Role of Clinical and EEG Findings

BACKGROUND

Hypoglycemic coma (HC) is an uncommon but severe clinical condition associated with poor neurological outcome. There is a dearth of robust neurological prognostic factors after HC. On the other hand, there is an increasing body of literature on reliable prognostic markers in the postanoxic coma, a similar-albeit not identical-situation. The objective of this study was thus to investigate the use and predictive value of these markers in HC.

METHODS

We conducted a retrospective, multicenter, cohort study within five centers of the Critical Care EEG Monitoring Research Consortium. We queried our electroencephalography (EEG) databases to identify all patients undergoing continuous EEG monitoring after admission to an intensive care unit with HC (defined as Glasgow Coma Scale < 8 on admission and a first blood glucose level < 50 mg/dL or not documented but in an obvious clinical context) between 01/01/2010 and 12/31/2020. We studied the association of findings at neurological examination (Glasgow Coma Scale motor subscale, pupillary light and corneal reflexes) and at continuous EEG monitoring(highly malignant patterns, reactivity, periodic discharges, seizures) with best neurological outcome within 3 months after hospital discharge, defined by the Cerebral Performance Category as favorable (1-3: recovery of consciousness) versus unfavorable (4-5: lack of recovery of consciousness).

RESULTS

We identified 60 patients (30 [50%] women; age 62 [51-72] years). Thirty-one and 29 patients had a favorable and unfavorable outcome, respectively. The presence of pupillary reflexes (24 [100%] vs. 17 [81%]; p value 0.04) and a motor subscore > 2 (22 [92%] vs. 12 [63%]; p value 0.03) at 48-72 h were associated with a favorable outcome. A highly malignant EEG pattern was observed in 7 of 29 (24%) patients with unfavorable outcome versus 0 of 31 (0%) with favorable outcome, whereas the presence of EEG reactivity was observed in 28 of 31 (90%) patients with favorable outcome versus 13 of 29 (45%) with unfavorable outcome (p < 0.001 for comparison of all background categories).

CONCLUSIONS

This preliminary study suggests that highly malignant EEG patterns might be reliable prognostic markers of unfavorable outcome after HC. Other EEG findings, including lack of EEG reactivity and seizures and clinical findings appear less accurate. These findings should be replicated in a larger multicenter prospective study.

Skin manifestations and clinical features of drug reaction with eosinophilia and systemic symptoms (DRESS): A retrospective multicenter study of 125 patients

BACKGROUND

Drug reaction with eosinophilia and systemic symptoms (DRESS) is a severe adverse drug reaction generally accompanied by skin manifestations as the first and most frequent symptoms. However, skin manifestations and associated clinical features of DRESS have not been fully explored and evaluated.

OBJECTIVES

This study aimed to describe the skin manifestations of DRESS in detail and analyze their association with demographic characteristics and extra-cutaneous clinical features.

METHODS

We conducted this retrospective study on patients with DRESS diagnosed between September 2009 and August 2021 at three medical institutes and validated using the RegiSCAR score. Data regarding demographics, skin manifestations, and clinical characteristics were retrieved through thorough chart reviews.

RESULTS

Among 182 potential cases of DRESS, the validated 125 cases were analyzed. A widespread rash extending over more than 50% of the body surface area was observed in 122 patients (97.6%) and typical facial edema was experienced by 67 patients (53.6%). Polymorphous maculopapules were the most common rash morphology (106, 84.8%): specifically, exfoliative (59, 47.2%), urticarial (57, 45.6%), and purpuric forms (39, 31.2%) were common. Mucosal involvement was observed in 41 patients (32.8%). Patients with carboxamide antiepileptics (carbamazepine and oxcarbazepine) experienced more edema (P = .014) and typical facial edema than those with allopurinol (P = .021). The RegiSCAR score was higher in patients with purpura (P < .01).

CONCLUSIONS

Skin manifestations of DRESS exhibit a wide range of skin lesions and can vary according to the culprit drugs. Early suspicion and prompt intervention are needed to improve prognosis.

Magnetic Resonance Spectroscopy of Hypoxic-Ischemic Encephalopathy After Cardiac Arrest

BACKGROUND AND OBJECTIVES

To correlate brain metabolites with clinical outcome using magnetic resonance spectroscopy (MRS) in patients undergoing targeted temperature management (TTM) after cardiac arrest and assess their relationships to MRI and EEG variables.

METHODS

A prospective cohort of 50 patients was studied. The primary outcome was coma recovery to follow commands. Comparison of MRS measures in the posterior cingulate gyrus, parietal white matter, basal ganglia, and brainstem were also made to 25 normative controls.

RESULTS

Fourteen of 50 patients achieved coma recovery before hospital discharge. There was a significant decrease in total N-acetylaspartate (NAA/Cr) and an increase in lactate/creatine (Lac/Cr) in patients who did not recover, with changes most prominent in the posterior cingulate gyrus. Patients who recovered had decrease in NAA/Cr as compared to controls. NAA/Cr had a strong monotonic relationship with MRI cortical apparent diffusion coefficient (ADC); Lac level exponentially increased with decreasing ADC. EEG suppression/burst suppression was strongly associated with Lac elevation.

DISCUSSION

NAA and Lac changes are associated with clinical/MRI/EEG changes consistent with hypoxic-ischemic encephalopathy (HIE) and are most prominent in the posterior cingulate gyrus. NAA/Cr decrease observed in patients with good outcomes suggests mild HIE in patients asymptomatic at hospital discharge. The appearance of cortical Lac represents a deterioration of aerobic energy metabolism and is associated with EEG background suppression, synaptic transmission failure, and severe, potentially irreversible HIE.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that in patients undergoing TTM after cardiac arrest, brain MRS-determined decrease in total NAA/Cr and an increase in Lac/Cr are associated with an increased risk of not recovering.

Regional Distribution of Brain Injury After Cardiac Arrest: Clinical and Electrographic Correlates

BACKGROUND AND OBJECTIVES

Disorders of consciousness, EEG background suppression, and epileptic seizures are associated with poor outcome after cardiac arrest. Our objective was to identify the distribution of diffusion MRI-measured anoxic brain injury after cardiac arrest and to define the regional correlates of disorders of consciousness, EEG background suppression, and seizures.

METHODS

We analyzed patients from a single-center database of unresponsive patients who underwent diffusion MRI after cardiac arrest (n = 204). We classified each patient according to recovery of consciousness (command following) before discharge, the most continuous EEG background (burst suppression vs continuous), and the presence or absence of seizures. Anoxic brain injury was measured with the apparent diffusion coefficient (ADC) signal. We identified ADC abnormalities relative to controls without cardiac arrest (n = 48) and used voxel lesion symptom mapping to identify regional associations with disorders of consciousness, EEG background suppression, and seizures. We then used a bootstrapped lasso regression procedure to identify robust, multivariate regional associations with each outcome variable. Last, using area under receiver operating characteristic curves, we then compared the classification ability of the strongest regional associations to that of brain-wide summary measures.

RESULTS

Compared to controls, patients with cardiac arrest demonstrated ADC signal reduction that was most significant in the occipital lobes. Disorders of consciousness were associated with reduced ADC most prominently in the occipital lobes but also in deep structures. Regional injury more accurately classified patients with disorders of consciousness than whole-brain injury. Background suppression mapped to a similar set of brain regions, but regional injury could no better classify patients than whole-brain measures. Seizures were less common in patients with more severe anoxic injury, particularly in those with injury to the lateral temporal white matter.

DISCUSSION

Anoxic brain injury was most prevalent in posterior cerebral regions, and this regional pattern of injury was a better predictor of disorders of consciousness than whole-brain injury measures. EEG background suppression lacked a specific regional association, but patients with injury to the temporal lobe were less likely to have seizures. Regional patterns of anoxic brain injury are relevant to the clinical and electrographic sequelae of cardiac arrest and may hold importance for prognosis.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that disorders of consciousness after cardiac arrest are associated with widely lower ADC values on diffusion MRI and are most strongly associated with reductions in occipital ADC.

Effects of Anatomical or Non-Anatomical Resection of Hepatocellular Carcinoma on Survival Outcome

Background: The relative benefit of anatomical resection (AR) versus non-anatomical resection (NAR) in hepatocellular carcinoma (HCC) remains controversial. This study compared the survival outcomes and recurrence rates of HCCs analysed according to tumour size and the extent of resection. Methods: Consecutive patients with HCC who underwent curative resection at Asan Medical Center between January 1999 and December 2009 were included in this study. We performed propensity score matching (PSM) according to tumour size to compare the survival outcomes between AR and NAR. A total of 986 patients were analysed; 812 and 174 patients underwent AR and NAR, respectively. Results: Before PSM, regardless of tumour size, the AR group demonstrated significantly better 5-year overall survival (OS) and recurrence-free survival (RFS) than the NAR group (p < 0.001). After PSM, the AR group demonstrated better OS and RFS rates than the NAR group when tumour size was less than 5 cm, but there was no significant difference in the OS and RFS rates between the two groups when tumour size was equal to or greater than 5 cm. In tumours less than 5 cm in size, AR was the most significant factor associated with OS and RFS. However, this prognostic effect of AR was not demonstrated in tumours with sizes equal to or greater than 5 cm. Conclusion: In patients with HCCs smaller than 5 cm, AR reduced the risk of tumour recurrence and improved OS. In HCCs larger than 5 cm, AR and NAR showed comparable survival outcomes.

Search for Relativistic Magnetic Monopoles with Eight Years of IceCube Data

We present an all-sky 90% confidence level upper limit on the cosmic flux of relativistic magnetic monopoles using 2886 days of IceCube data. The analysis was optimized for monopole speeds between 0.750c and 0.995c, without any explicit restriction on the monopole mass. We constrain the flux of relativistic cosmic magnetic monopoles to a level below 2.0×10^{-19}  cm^{-2} s^{-1} sr^{-1} over the majority of the targeted speed range. This result constitutes the most strict upper limit to date for magnetic monopoles with β≳0.8 and up to β∼0.995 and fills the gap between existing limits on the cosmic flux of nonrelativistic and ultrarelativistic magnetic monopoles.

Ultrasensitive Near-Infrared Circularly Polarized Light Detection Using 3D Perovskite Embedded with Chiral Plasmonic Nanoparticles

Chiral organic ligand-incorporated low-dimensional metal-halide perovskites have received increasing attention for next-generation photodetectors because of the direct detection capability of circularly polarized light (CPL), which overcomes the requirement for subsidiary optical components in conventional CPL photodetectors. However, most chiral perovskites have been based on low-dimensional structures that confine chiroptical responses to the ultraviolet (UV) or short-wavelength visible region and limit photocurrent due to their wide bandgap and poor charge transport. Here, chiroptical properties of 3D Cs_0.05 FA_0.5 MA_0.45 Pb_0.5 Sn_0.5 I₃ polycrystalline films are achieved by incorporating chiral plasmonic gold nanoparticles (AuNPs) into the mixed PbSn perovskite, without sacrificing its original optoelectronic properties. CPL detectors fabricated using chiral AuNP-embedded perovskite films can operate without external power input; they exhibit remarkable chirality in the near-infrared (NIR) region with a high anisotropy factor of responsivity (g_res ) of 0.55, via giant plasmon resonance shift of chiral plasmonic AuNPs. In addition, a CPL detector array fabricated on a plastic substrate demonstrates highly sensitive self-powered NIR detection with superior flexibility and durability.

Predicting Neurological Outcome from Electroencephalogram Dynamics in Comatose Patients after Cardiac Arrest with Deep Learning

OBJECTIVE

Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches largely rely on snapshots of the EEG, without taking advantage of temporal information.

METHODS

We present a recurrent deep neural network with the goal of capturing temporal dynamics from longitudinal EEG data to predict long-term neurological outcomes. We utilized a large international dataset of continuous EEG recordings from 1,038 cardiac arrest patients from seven hospitals in Europe and the US. Poor outcome was defined as a Cerebral Performance Category (CPC) score of 3-5, and good outcome as CPC score 0-2 at 3 to 6-months after cardiac arrest. Model performance is evaluated using 5-fold cross validation.

RESULTS

The proposed approach provides predictions which improve over time, beginning from an area under the receiver operating characteristic curve (AUC-ROC) of 0.78 (95% CI: 0.72-0.81) at 12 hours, and reaching 0.88 (95% CI: 0.85-0.91) by 66 h after cardiac arrest. At 66 h, (sensitivity, specificity) points of interest on the ROC curve for predicting poor outcomes were (32,99)%, (55,95)%, and (62,90)%, (99,23)%, (95,47)%, and (90,62)%; whereas for predicting good outcome, the corresponding operating points were (17,99)%, (47,95)%, (62,90)%, (99,19)%, (95,48)%, (70,90)%. Moreover, the model provides predicted probabilities that closely match the observed frequencies of good and poor outcomes (calibration error 0.04).

CONCLUSIONS AND SIGNIFICANCE

These findings suggest that accounting for EEG trend information can substantially improve prediction of neurologic outcomes for patients with coma following cardiac arrest.

Predicting neurological outcome in comatose patients after cardiac arrest with multiscale deep neural networks

OBJECTIVE

Electroencephalography (EEG) is an important tool for neurological outcome prediction after cardiac arrest. However, the complexity of continuous EEG data limits timely and accurate interpretation by clinicians. We develop a deep neural network (DNN) model to leverage complex EEG trends for early and accurate assessment of cardiac arrest coma recovery likelihood.

METHODS

We developed a multiscale DNN combining convolutional neural networks (CNN) and recurrent neural networks (long short-term memory [LSTM]) using EEG and demographic information (age, gender, shockable rhythm) from a multicenter cohort of 1,038 cardiac arrest patients. The CNN learns EEG feature representations while the multiscale LSTM captures short-term and long-term EEG dynamics on multiple time scales. Poor outcome is defined as a Cerebral Performance Category (CPC) score of 3-5 and good outcome as CPC score 1-2 at 3-6 months after cardiac arrest. Performance is evaluated using area under the receiver operating characteristic curve (AUC) and calibration error.

RESULTS

Model performance increased with EEG duration, with AUC increasing from 0.83 (95% Confidence Interval [CI] 0.79-0.87 at 12h to 0.91 (95%CI 0.88-0.93) at 66h. Sensitivity of good and poor outcome prediction was 77% and 75% at a specificity of 90%, respectively. Sensitivity of poor outcome was 50% at a specificity of 99%. Predicted probability was well matched to the observation frequency of poor outcomes, with a calibration error of 0.11 [0.09-0.14].

CONCLUSIONS

These results demonstrate that incorporating EEG evolution over time improves the accuracy of neurologic outcome prediction for patients with coma after cardiac arrest.

Effects of hydrogenated fat-spray-coated β-carotene supplement on plasma β-carotene concentration and conception rate after embryo transfer in Hanwoo beef cows

We hypothesised that hydrogenated fat (HF)-spray-coated β-carotene (βC) supplement could be used to increase plasma βC concentration and conception rates after embryo transfer (ET) in Hanwoo beef cows. In Experiment 1, 12 multiparous Hanwoo cows were fed one of four experimental diets in a triplicate 4 × 4 Latin square design for a 28-day period. Treatments included no βC addition (control), HF-uncoated βC (HFuβC), HF-spray-coated βC (HFβC), and HF-spray-coated βC and vitamin A (HFβCA). The cows under βC-supplemented treatments were fed 400 mg/day of βC, and a daily intake for vitamin A of HFβCA treatment was 30 000 IU/day as retinyl acetate. Blood was collected on days 0, 26, 27, and 28 to analyse βC and other metabolite concentrations. In Experiment 2, 199 Hanwoo cows with low fertility were randomly assigned to either control (n = 99) or HFβC treatments (n = 100) based on the results of Experiment 1. The oestrus of the cows was synchronised for ET. The HFβC group was fed from 4 weeks before to 4 weeks after ET with a daily intake of 400 mg βC. Pregnancy for conception rates was diagnosed on day 60 after ET, and blood was collected for βC concentrations on the day before ET. Supplementing βC resulted in a high plasma βC concentration (P < 0.001). Supplementing HFβC or HFβCA resulted in higher βC concentrations than HFuβC (P < 0.001); however, there was no difference between HFβC and HFβCA groups. Plasma retinol concentration was lower in the HFβCA treatment than in the control and HFβC groups (P < 0.05). Blood metabolites were unaffected by the treatments. The retinol:βC ratio was lower in the βC-supplemented treatments than in the controls, and was lower in HFβC and HFβCA than in HFuβC groups (P < 0.001). Plasma βC concentration was positively correlated with plasma high-density lipoprotein, low-density lipoprotein, and total cholesterol (P < 0.05). Plasma retinol concentration was negatively associated with plasma protein (P < 0.01), but positively associated with plasma creatinine (P < 0.001) and urea (P < 0.01). Supplementing HFβC to low-fertility cows resulted in higher plasma βC concentration (P < 0.001) and conception rates (P = 0.024) than those in the controls. In conclusion, HFβC had a better bioavailability than HFuβC, and an increase in conception rates by supplementing HFβC may be beneficial for producing more calves given the low pregnancy rates of bovine ET in Korea.

Solar background noise mitigation using the orbital angular momentum mode in vertical FSO downlink transmissions

Free-space optical communication (FSO) is used to provide network configuration flexibility. A network-flying platform-based vertical FSO connection can be employed to enhance mobile network coverage and capacity. Solar background noise can be a potential risk that disrupts the seamless connection in the vertical FSO downlink channel. In this paper, we propose signal transmission using an orbital angular momentum (OAM) beam. The OAM demodulation process can filter sunlight out of the optical receiver except for the signal corresponding to the azimuthal state. We experimentally verified that most of the solar background noise could be reduced. To verify the feasibility of the proposed scheme in a vertical FSO channel, we modeled a FSO vertical downlink with an OAM modulation/demodulation process.

CSF lipocalin-2 increases early in subarachnoid hemorrhage are associated with neuroinflammation and unfavorable outcome

Lipocalin-2 mediates neuro-inflammation and iron homeostasis in vascular injuries of the central nervous system (CNS) and is upregulated in extra-CNS systemic inflammation. We postulate that cerebrospinal fluid (CSF) and blood lipocalin-2 levels are associated with markers of inflammation and functional outcome in subarachnoid hemorrhage (SAH). We prospectively enrolled 67 SAH subjects, serially measured CSF and plasma lipocalin-2, matrix metallopeptidase 9 (MMP-9), interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) on post-SAH days 1-5 and assessed outcome by modified Rankin Scale (mRS) every 3 months. Unfavorable outcome is defined as mRS > 2. Twenty non-SAH patients undergoing lumbar drain trial were enrolled as controls. Lipocalin-2 was detectable in the CSF and significantly higher in SAH compared to controls (p < 0.0001). Higher CSF LCN2 throughout post-SAH days 1-5 was associated with unfavorable outcome at 3 (p = 0.0031) and 6 months (p = 0.014). Specifically, higher CSF lipocalin-2 on post-SAH days 3 (p = 0.036) and 5 (p = 0.016) were associated with unfavorable 3-month outcome. CSF lipocalin-2 levels positively correlated with CSF IL-6, TNF-α and MMP-9 levels. Higher plasma lipocalin-2 levels over time were associated with worse 6-month outcome. Additional studies are required to understand the role of lipocalin-2 in SAH and to validate CSF lipocalin-2 as a potential biomarker for SAH outcome.

Microscale dynamics of electrophysiological markers of epilepsy

OBJECTIVE

Interictal discharges (IIDs) and high frequency oscillations (HFOs) are established neurophysiologic biomarkers of epilepsy, while microseizures are less well studied. We used custom poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) microelectrodes to better understand these markers' microscale spatial dynamics.

METHODS

Electrodes with spatial resolution down to 50 µm were used to record intraoperatively in 30 subjects. IIDs' degree of spread and spatiotemporal paths were generated by peak-tracking followed by clustering. Repeating HFO patterns were delineated by clustering similar time windows. Multi-unit activity (MUA) was analyzed in relation to IID and HFO timing.

RESULTS

We detected IIDs encompassing the entire array in 93% of subjects, while localized IIDs, observed across < 50% of channels, were seen in 53%. IIDs traveled along specific paths. HFOs appeared in small, repeated spatiotemporal patterns. Finally, we identified microseizure events that spanned 50-100 µm. HFOs covaried with MUA, but not with IIDs.

CONCLUSIONS

Overall, these data suggest that irritable cortex micro-domains may form part of an underlying pathologic architecture which could contribute to the seizure network.

SIGNIFICANCE

These results, supporting the possibility that epileptogenic cortex comprises a mosaic of irritable domains, suggests that microscale approaches might be an important perspective in devising novel seizure control therapies.

Analysis of morphological characteristics of IDH-mutant/wildtype brain tumors using whole-lesion phenotype analysis

Background

Although IDH-mutant tumors aggregate to the frontotemporal regions, the clustering pattern of IDH-wildtype tumors is less clear. As voxel-based lesion-symptom mapping (VLSM) has several limitations for solid lesion mapping, a new technique, whole-lesion phenotype analysis (WLPA), is developed. We utilize WLPA to assess spatial clustering of tumors with IDH mutation from The Cancer Genome Atlas and The Cancer Imaging Archive.

Methods

The degree of tumor clustering segmented from T1 weighted images is measured to every other tumor by a function of lesion similarity to each other via the Hausdorff distance. Each tumor is ranked according to the degree to which its neighboring tumors show identical phenotypes, and through a permutation technique, significant tumors are determined. VLSM was applied through a previously described method.

Results

A total of 244 patients of mixed-grade gliomas (WHO II-IV) are analyzed, of which 150 were IDH-wildtype and 139 were glioblastomas. VLSM identifies frontal lobe regions that are more likely associated with the presence of IDH mutation but no regions where IDH-wildtype was more likely to be present. WLPA identifies both IDH-mutant and -wildtype tumors exhibit statistically significant spatial clustering.

Conclusion

WLPA may provide additional statistical power when compared with VLSM without making several potentially erroneous assumptions. WLPA identifies tumors most likely to exhibit particular phenotypes, rather than producing anatomical maps, and may be used in conjunction with VLSM to understand the relationship between tumor morphology and biologically relevant tumor phenotypes.

EEG findings in CART T associated neurotoxicity: clinical and radiological correlations

BACKGROUND

While EEG is frequently reported as abnormal after CAR T cell therapy, its clinical significance remains unclear. We aim to systematically describe EEG features in a large single-center cohort and correlate them with clinical and radiological findings.

METHODS

We retrospectively identified patients undergoing CAR T cell therapy who had continuous EEG. Neurotoxicity grades, detailed neurological symptoms, and brain MRI or FDG-PET were obtained. Correlation between clinical and radiological findings and EEG features was assessed.

RESULTS

In 81 patients with median neurotoxicity grade 3 (IQR 2-3), diffuse EEG background slowing was the most common finding and correlated with neurotoxicity severity (p <0.001). A total of 42 patients had rhythmic or periodic patterns, 16 of them within the ictal-interictal-continuum (IIC), 5 with clinical seizures, and 3 with only electrographic seizures. Focal EEG abnormalities, consisting of lateralized periodic discharges (LPD, n=1), lateralized rhythmic delta activity (LRDA, n=6), or focal slowing (n=19), were found in 22 patients. All patients with LRDA, LPD, and 10/19 patients with focal slowing had focal clinical symptoms concordant with these EEG abnormalities. In addition, these focal EEG changes often correlated with PET hypometabolism or MRI hypoperfusion, in absence of a structural lesion.

CONCLUSION

In adult patients experiencing neurotoxicity after CAR T cell infusion, EEG degree of background disorganization correlated with neurotoxicity severity. IIC patterns and focal EEG abnormalities are frequent and often correlate with focal clinical symptoms and with PET-hypometabolism/MRI-hypoperfusion, without structural lesion. The etiology of these findings remains to be elucidated.

Microscale Physiological Events on the Human Cortical Surface

Despite ongoing advances in our understanding of local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their "intermediate" microscale local circuit dynamics. Here, we utilized ultra-high-density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single-unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper cortical layers. These second and third types were also observed in rodents, nonhuman primates, and semi-chronic recordings from humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that the proper combination of high-resolution microelectrodes and analytic techniques can capture neuronal dynamics that lay between somatic action potentials and aggregate population activity. Understanding intermediate microscale dynamics in relation to single-cell and network dynamics may reveal important details about activity in the full cortical circuit.

SNO and EANO practice guideline update: Anticonvulsant prophylaxis in patients with newly diagnosed brain tumors

OBJECTIVE

To update the 2000 American Academy of Neurology (AAN) practice parameter on anticonvulsant prophylaxis in patients with newly diagnosed brain tumors.

METHODS

Following the 2017 AAN methodologies, a systematic literature review utilizing PubMed, EMBASE, Cochrane, and Web of Science databases was performed. The studies were rated based on the AAN therapeutic or causation classification of evidence (Class I-IV).

RESULTS

Thirty-seven articles were selected for final analysis. There were limited high level, Class I studies and mostly Class II and III studies. The AAN affirmed the value of these guidelines.

RECOMMENDATIONS

In patients with newly diagnosed brain tumors who have not had a seizure, clinicians should not prescribe anti-epileptic drugs (AEDs) to reduce the risk of seizures (Level A). In brain tumor patients undergoing surgery, there is insufficient evidence to recommend prescribing AEDs to reduce the risk of seizures in the peri- or postoperative period (Level C). There is insufficient evidence to support prescribing valproic acid or levetiracetam with the intent to prolong progression-free or overall survival (Level C). Physicians may consider use of levetiracetam over older AEDs to reduce side effects (Level C). There is insufficient evidence to support using tumor location, histology, grade, molecular/imaging features, when deciding whether or not to prescribe prophylactic AEDs (Level U).