Post-ischaemic silencing of p66Shc reduces ischaemia/reperfusion brain injury and its expression correlates to clinical outcome in stroke.

AIM: Constitutive genetic deletion of the adaptor protein p66(Shc) was shown to protect from ischaemia/reperfusion injury. Here, we aimed at understanding the molecular mechanisms underlying this effect in stroke and studied p66(Shc) gene regulation in human ischaemic stroke. METHODS AND RESULTS: Ischaemia/reperfusion brain injury was induced by performing a transient middle cerebral artery occlusion surgery on wild-type mice. After the ischaemic episode and upon reperfusion, small interfering RNA targeting p66(Shc) was injected intravenously. We observed that post-ischaemic p66(Shc) knockdown preserved blood-brain barrier integrity that resulted in improved stroke outcome, as identified by smaller lesion volumes, decreased neurological deficits, and increased survival. Experiments on primary human brain microvascular endothelial cells demonstrated that silencing of the adaptor protein p66(Shc) preserves claudin-5 protein levels during hypoxia/reoxygenation by reducing nicotinamide adenine dinucleotide phosphate oxidase activity and reactive oxygen species production. Further, we found that in peripheral blood monocytes of acute ischaemic stroke patients p66(Shc) gene expression is transiently increased and that this increase correlates with short-term neurological outcome. CONCLUSION: Post-ischaemic silencing of p66(Shc) upon reperfusion improves stroke outcome in mice while the expression of p66(Shc) gene correlates with short-term outcome in patients with ischaemic stroke.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

BACKGROUND AND PURPOSE: Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. MATERIALS AND METHODS: This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. RESULTS: ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. CONCLUSIONS: Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology.