Visual Abstract

Spreading depression is characterized by slow, propagating wave of cellular depolarization (SD) and is wildly associated with migraine, stroke, and traumatic brain injury. Seizures and spreading depression (or spreading depolarization, SD) have long been reported to coincide in acute seizure induction experiments. However, SD has not been observed associated with spotaneous seizures in animal or clinical recordings. Recently, advances in acquisition systems for neurointensive care units have made routine observations of SD possible. In clinical epilepsy, SD has been suggested as a candidate mechanism for migraine/headache like events following seizures as well as for post-ictal generalized suppression. In animal models of epilepsy, seizure-induced brainstem SD has also been demonstrated as a mechanism of sudden unexplained death in epilepsy (SUDEP). The interplay between seizures and SD has also been suggested in computational models, where the two are components of the repetoir of neuronal activity.However, the spatiotemporal dynamics of SD with respect to spontaneous seizures in chronically epileptic brain remains ambigous. We analyzed continuous long-term DC sensitive EEG measurements from two fundamentally different animal models of chronic epilepsy. We found that SD was associated with approximately one-third of all spontaneous seizures in each model. Additionally, SDs participated in the organization of seizure clusters. These findings demonstrate that the underlying dynamic of epileptic events is broader than seizures alone.Significance StatementSpreading depression is characterized by slow, propagating wave of cellular spreading depolarization (SD) and is wildly associated with migraine, stroke, and traumatic brain injury. Although recently the linkage between SD and induced seizures has been recognized, the mechanistic relationship between SD and spontaneous seizures remains poorly understood. Here, we utilized long-term, stable, near-DC measurements of the brain activity in two fundamentally different animal models of epilepsy to investigate the SD-seizure interplay. We found that SD is a frequent phenomenon in the epileptic brain, in these models is associated with more than a third of all seizures, and appears to connect seizures in seizure clusters. Although in one model SD stereotypically propagates out from a single focus in the hippocampus, depression of the field-potentials is observed synchronously across much of the hippocampus. These observations highlight the value of stable DC measurements for accurate understanding of SD and its propagation. We found that spontaneous ictal events that include both seizures and SD are frequent in animal models of epilepsy. These findings suggest that SD could be a valuable target for treatment and control of epilepsy.

A strong association of gemcitabine to acute coronary syndrome (ACS) is not currently established in the literature. In this series, we highlight that both patients with gemcitabine-related ACS were more than 50 years old, had underlying coronary artery disease and suffered from metastatic cancer. However, further prospective studies are required to validate the significance of these observations.

Extensive clinical and experimental evidence links sleep–wake regulation and state of vigilance (SOV) to neurological disorders including schizophrenia and epilepsy. To understand the bidirectional coupling between disease severity and sleep disturbances, we need to investigate the underlying neurophysiological interactions of the sleep–wake regulatory system (SWRS) in normal and pathological brains. We utilized unscented Kalman filter based data assimilation (DA) and physiologically based mathematical models of a sleep–wake regulatory network synchronized with experimental measurements to reconstruct and predict the state of SWRS in chronically implanted animals. Critical to applying this technique to real biological systems is the need to estimate the underlying model parameters. We have developed an estimation method capable of simultaneously fitting and tracking multiple model parameters to optimize the reconstructed system state. We add to this fixed-lag smoothing to improve reconstruction of random input to the system and those that have a delayed effect on the observed dynamics. To demonstrate application of our DA framework, we have experimentally recorded brain activity from freely behaving rodents and classified discrete SOV continuously for many-day long recordings. These discretized observations were then used as the “noisy observables” in the implemented framework to estimate time-dependent model parameters and then to forecast future state and state transitions from out-of-sample recordings.

The BCR-ABL tyrosine kinase inhibitor dasatinib is a potent treatment for chronic myeloid leukemia (CML). However, it is associated with pulmonary toxicities. Commonly reported dasatinib related pulmonary toxicities include pleural effusion, lung parenchymal abnormalities, and pulmonary hypertension. Diffuse alveolar hemorrhage (DAH) during treatment with dasatinib is very rare. To the best of our knowledge there are only two cases reported. Here we report a 57-year-old Caucasian woman who developed acute hypoxic respiratory failure while on dasatinib for treatment of CML. She was diagnosed with DAH suspected to be secondary to dasatinib, after other common etiologies were ruled out. There was full recovery after stopping dasatinib and treatment with corticosteroids. Keywords: Dasatinib, pulmonary toxicity, diffuse alveolar hemorrhage, chronic myeloid leukemia