We initiate the study of graph sketching, i.e., algorithms that use a limited number of linear measurements of a graph to determine the properties of the graph. While a graph on n nodes is essentially O(n 2 )-dimensional, we show the existence of a distribution over random projections into d-dimensional "sketch" space (d n 2 ) such that the relevant properties of the original graph can be inferred from the sketch with high probability. Specifically, we show that:including connectivity, k-connectivity, bipartiteness, and to return any constant approximation of the weight of the minimum spanning tree.2. d = O(n 1+γ ) suffices to compute graph sparsifiers, the exact MST, and approximate the maximum weighted matchings if we permit O(1/γ)-round adaptive sketches, i.e., a sequence of projections where each projection may be chosen dependent on the outcome of earlier sketches.Our results have two main applications, both of which have the potential to give rise to fruitful lines of further research. First, our results can be thought of as giving the first compressed-sensing style algorithms for graph data. Secondly, our work initiates the study of dynamic graph streams. There is already extensive literature on processing massive graphs in the data-stream model. However, the existing work focuses on graphs defined by a sequence of inserted edges and does not consider edge deletions. We think this is a curious omission given the existing work on both dynamic graphs in the non-streaming setting and dynamic geometric streaming. Our results include the first dynamic graph semi-streaming algorithms for connectivity, spanning trees, sparsification, and matching problems.

The GM/WM ratio correlates with the outcome of hypoxic ischaemic encephalopathy and may be useful as an objective early predictor of vegetative state or death in comatose patients after cardiac arrest.

Mild cognitive impairment (MCI) has been defined as a transitional state between normal aging and Alzheimer disease. Diffusion tensor imaging (DTI) can estimate the microstructural integrity of white matter tracts in MCI. We evaluated the microstructural changes in the white matter of MCI patients with DTI. We recruited 11 patients with MCI who met the working criteria of MCI and 11 elderly normal controls. The mean diffusivity (MD) and fractional anisotropy (FA) were measured in 26 regions of the brain with the regions of interest (ROIs) method. In the MCI patients, FA values were significantly decreased in the hippocampus, the posterior limb of the internal capsule, the splenium of corpus callosum, and in the superior and inferior longitudinal fasciculus compared to the control group. MD values were significantly increased in the hippocampus, the anterior and posterior limbs of the internal capsules, the splenium of the corpus callosum, the right frontal lobe, and in the superior and the inferior longitudinal fasciculus. Microstructural changes of several corticocortical tracts associated with cognition were identified in patients with MCI. FA and MD values of DTI may be used as novel biomarkers for the evaluation of neurodegenerative disorders.

Pure neuronal and mixed neuronal-glial tumors of the central nervous system are uncommon but fascinating because they are less aggressive than the more common glial tumors and their prognosis is excellent. Neurologic manifestations are varied and include seizures, symptoms of increased intracranial pressure, and neurologic deficits according to tumor location. Many neuronal tumors of the central nervous system demonstrate characteristic radiologic findings. At magnetic resonance (MR) imaging, gangliocytomas demonstrate low signal intensity on T1-weighted images, high signal intensity on T2-weighted images, and frequent enhancement on gadolinium-enhanced T1-weighted images. Characteristic MR imaging findings of Lhermitte-Duclos disease are a nonenhancing mass in a cerebellar hemisphere with a striated pattern. Central neurocytomas are typically located in the lateral ventricles near the foramen of Monro with a characteristic attachment to the septum pellucidum. Ganglioneurocytoma is a rare variant of central neurocytoma that is characterized by differentiation toward ganglion cells. In ganglioglioma, a well-defined cystic mass with a solid mural nodule is typically seen. Extension of enhancement to the leptomeninges is characteristic of desmoplastic infantile ganglioglioma and correlates with the firm dural attachment of the solid component. Dysembryoplastic neuroepithelial tumor has a well-demarcated, multilobulated or gyriform appearance.

Previous studies have shown an association between late-onset depression (LOD) and cognitive impairment in older adults. However, the neural correlates of this relationship are not yet clear. The aim of this study was to investigate the differences in both cortical thickness and subcortical volumes between drug-naive LOD patients and healthy controls and explore the relationship between LOD and cognitive impairments. A total of 48 elderly, drug-naive patients with LOD and 47 group-matched healthy control subjects underwent 3T MRI scanning, and the cortical thickness was compared between the groups in multiple locations, across the continuous cortical surface. The subcortical volumes were also compared on a structure-by-structure basis. Subjects with LOD exhibited significantly decreased cortical thickness in the rostral anterior cingulate cortex, the medial orbitofrontal cortex, dorsolateral prefrontal cortex, the superior and middle temporal cortex, and the posterior cingulate cortex when compared with healthy subjects (all p<0.05, false discovery rate corrected). Reduced volumes of the right hippocampus was also observed in LOD patients when compared with healthy controls (p<0.001). There were significant correlations between memory functions and cortical thickness of medial temporal, isthmus cingulate, and precuneus (p<0.001). This study was the first study to explore the relationships between the cortical thickness/subcortical volumes and cognitive impairments of drug-naive patients with LOD. These structural changes might explain the neurobiological mechanism of LOD as a risk factor of dementia.

Typically, reversible posterior leukoencephalopathy syndrome (RPLS) involves the parieto-occipital lobes. When regions of the brain other than the parieto-occipital lobes are predominantly involved, the syndrome can be called atypical RPLS. The purpose of this study is to find radiological and pathophysiological features of atypical RPLS by using diffusion-weighted imaging (D-WI). We retrospectively reviewed seven patients (two with eclampsia, one with cyclosporine neurotoxicity, and four with hypertensive encephalopathy) with atypical MR manifestations of RPLS. Changes in signal intensity on T2-weighted imaging (T2-WI) and D-WI, and ADC ratio, were analyzed. In patients with atypical manifestation of RPLS, high signal intensities on T2-WI were noted in the frontal lobe, basal ganglia, thalamus, brainstem, and subcortical white matter in regions other than the parieto-occipital lobes. These areas of increased signal intensities on T2-WI showed increased ADC values, representing vasogenic edema in all seven patients. This result should be very useful in differentiating atypical RPLS from other metabolic brain disorders that affect the same sites with cytotoxic edema.

In this paper we study linear programming based approaches to the maximum matching problem in the semi-streaming model. The semi-streaming model has been considered as one of the models for efficient processing massive graphs. In this model edges are presented sequentially, possibly in an adversarial order, and we are only allowed to use a small space. The allowed space is near linear in the number of vertices (and sublinear in the number of edges) of the input graph.In recent years, there have been several new and exciting results in the semi-streaming model. However broad techniques such as linear programming have not been adapted to this model. In this paper we present several techniques to adapt and optimize linear programming based approaches in the semi-streaming model. We use the maximum matching problem as a foil to demonstrate the effectiveness of adapting such tools in this model and as a consequence we improve almost all previous results on the semi-streaming maximum matching problem. We also prove new results on interesting variants.

A BS TRACT: Background: Growing evidence suggests an association between imaging biomarkers of small vessel disease and future cognitive decline in Parkinson's disease (PD). Recently, magnetic resonance imaging-visible perivascular space (PVS) has been considered as an imaging biomarker of small vessel disease, but its effect on cognitive decline in PD is yet to be investigated. Objective: The objective of this study was to evaluate whether PVS can independently predict cognitive decline in PD. Methods: A total of 271 PD patients were divided into 106 patients with intact cognition (PD-IC) and 165 patients with mild cognitive impairment (PD-MCI). After a mean follow-up of 5.0 AE 2.3 years, 18 PD-IC patients showed cognitive decline to PD-MCI and 34 PD-MCI patients showed cognitive decline to dementia. PVS was rated in the basal ganglia (BG) and centrum semiovale using a 4-point visual scale and then classified as high (score ≥ 2) or low (score < 2) according to severity. Lacunes and white matter hyperintensity severity were also assessed. Independent risk factors for cognitive decline were investigated using multivariable logistic regression analysis. Results: In all patients, higher BG-PVS and white matter hyperintensity severity, higher levodopa-equivalent dose, hypertension, and lower Mini-Mental State Examination score were independent positive predictors of future cognitive decline. In the PD-IC subgroup, higher BG-PVS severity, hypertension, and more severe depressive symptoms were predictors of cognitive conversion. In the PD-MCI subgroup, higher BG-PVS and white matter hyperintensity severity, and lower Mini-Mental State Examination score were predictors of cognitive decline. Conclusions: BG-PVS may be a useful imaging marker for predicting cognitive decline in PD.