SUMMARY In human glioblastomas (hGBMs), tumor-propagating cells with stem-like characteristics (TPCs) represent a key therapeutic target. We found that the EphA2 receptor tyrosine kinase is overexpressed in hGBM TPCs. Cytofluorimetric sorting into EphA2High and EphA2Low populations demonstrated that EphA2 expression correlates with the size and tumor-propagating ability of the TPC pool in hGBMs. Both, ephrinA1-Fc, which caused EphA2 downregulation in TPCs, and siRNA-mediated knockdown of EPHA2 expression suppressed TPCs self-renewal ex vivo and intracranial tumorigenicity, pointing to EphA2 downregulation as a causal event in the loss of TPCs tumorigenicity. Infusion of ephrinA1-Fc into intracranial xenografts elicited strong tumor-suppressing effects, suggestive of therapeutic applications.

This paper addresses the prediction of epileptic seizures from the online analysis of EEG data. This problem is of paramount importance for the realization of monitoring/control units to be implanted on drug-resistant epileptic patients. The proposed solution relies in a novel way on autoregressive modeling of the EEG time series and combines a least-squares parameter estimator for EEG feature extraction along with a support vector machine (SVM) for binary classification between preictal/ictal and interictal states. This choice is characterized by low computational requirements compatible with a real-time implementation of the overall system. Moreover, experimental results on the Freiburg dataset exhibited correct prediction of all seizures (100 % sensitivity) and, due to a novel regularization of the SVM classifier based on the Kalman filter, also a low false alarm rate.

The incidence of post-traumatic hydrocephalus (PTH) has been reported to be 0.7-51.4%, and we have frequently observed the development of PTH in patients undergoing decompressive craniectomy (DC). For this reason we performed a retrospective review of a consecutive series of patients undergoing DC after traumatic brain injury (TBI). From January 2006 to December 2009, 41 patients underwent DC after closed head injury. Study outcomes focused specifically on the development of hydrocephalus after DC. Variables described by other authors to be associated with PTH were studied, including advanced age, the timing of cranioplasty, higher score on the Fisher grading system, low post-resuscitation Glasgow Coma Scale (GCS) score, and cerebrospinal fluid (CSF) infection. We also analyzed the influence of the area of craniotomy and the distance of craniotomy from the midline. Logistic regression was used with hydrocephalus as the primary outcome measure. Of the nine patients who developed hydrocephalus, eight patients (89%) had undergone craniotomy with the superior limit <25 mm from the midline. This association was statistically significant (p = 0.01 - Fisher's exact test). Logistic regression analysis showed that the only factor independently associated with the development of hydrocephalus was the distance from the midline. Patients with craniotomy whose superior limit was <25 mm from the midline had a markedly increased risk of developing hydrocephalus (OR = 17). Craniectomy with a superior limit too close to the midline can predispose patients undergoing DC to the development of hydrocephalus. We therefore suggest performing wide DCs with the superior limit >25 mm from the midline.

Early-to-middle SUV tumor ratio and Tpeak were the best indices for assessing the grading of gliomas. Since early-to-middle ratio derives from the first 35 minutes of the dynamic acquisition, the PET study could last half an hour instead of 1 hour. By logistic regression, it is possible to assess the individual probability of high-grade, useful for prognosis and treatment.

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