The decline of the Aeolian wall lizard, Podarcis raffonei : causes and conservation proposals

Investigations carried out in the Aeolian Islands (off north-east Sicily) during 1989–99 gathered evidence strongly indicating that the endemic Aeolian wall lizard Podarcis raffonei is close to extinction. Competitive exclusion by the lizard Podarcis sicula, which has been introduced by man, habitat degradation, and possibly reduced genetic variability and inbreeding, were the main causes for the decline of the species. For the Aeolian wall lizard to recover from its threatened status and to prevent further decimation of populations, collection and trade in the species should be prohibited, and an education programme for local people should be promoted. An integrated project involving habitat protection and captive breeding is needed to secure the species in the wild for the future

Corticobasal syndrome: neuroimaging and neurophysiological advances

Corticobasal degeneration (CBD) is a neurodegenerative condition characterized by 4R-tau protein deposition in several brain regions that clinically manifests itself as a heterogeneous atypical parkinsonism typically expressing in the adulthood. The prototypical clinical phenotype of CBD is corticobasal syndrome (CBS). Important insights into the pathophysiological mechanisms underlying motor and higher cortical symptoms in CBS have been gained by using advanced neuroimaging and neurophysiological techniques. Structural and functional neuroimaging studies often showed asymmetric cortical and subcortical abnormalities, mainly involving perirolandic and parietal regions and basal ganglia structures. Neurophysiological investigations including electroencephalography and somatosensory evoked potentials provided useful information on the origin of myoclonus and on cortical sensory loss. Transcranial magnetic stimulation demonstrated heterogeneous and asymmetric changes in the excitability and plasticity of primary motor cortex and abnormal hemispheric connectivity. Neuroimaging and neurophysiological abnormalities in multiple brain areas reflect the asymmetric neurodegeneration, leading to the asymmetric motor and higher cortical symptoms in CBS. This article is protected by copyright. All rights reserved

Modulation of network activity and induction of homeostatic synaptic plasticity by enzymatic removal of heparan sulfates

Heparan sulfates (HSs) are complex and highly active molecules that are required for synaptogenesis and long-term potentiation. A deficit in HSs leads to autistic phenotype in mice. Here, we investigated the long-term effect of heparinase I, which digests highly sulfated HSs, on the spontaneous bioelectrical activity of neuronal networks in developing primary hippocampal cultures. We found that chronic heparinase treatment led to a significant reduction of the mean firing rate of neurons, particularly during the period of maximal neuronal activity. Furthermore, firing pattern in heparinasetreated cultures often appeared as epileptiform bursts, with long periods of inactivity between them. These changes in network activitywere accompanied by an increase in the frequency and amplitude of miniature postsynaptic excitatory currents, which could be described by a linear up-scaling of current amplitudes. Biochemically, we observed an upregulation in the expression of the glutamate receptor subunit GluA1, but not GluA2, and a strong increase in autophosphorylation of a and b Ca2\ufe/calmodulin-dependent protein kinase II (CaMKII), without changes in the levels of kinase expression. These data suggest that a deficit in HSs triggers homeostatic synaptic plasticity and drastically affects functional maturation of neural network

Automatic segmentation of optical coherence tomography pullbacks of coronary arteries treated with bioresorbable vascular scaffolds: Application to hemodynamics modeling

Automatic algorithms for stent struts segmentation in optical coherence tomography (OCT) images of coronary arteries have been developed over the years, particularly with application on metallic stents. The aim of this study is three-fold: (1) to develop and to validate a segmentation algorithm for the detection of both lumen contours and polymeric bioresorbable scaffold struts from 8-bit OCT images, (2) to develop a method for automatic OCT pullback quality assessment, and (3) to demonstrate the applicability of the segmentation algorithm for the creation of patient-specific stented coronary artery for local hemodynamics analysis

Bradykinesia and dystonia

Background: Bradykinesia has been reported in patients with dystonia. Despite this, the pathophysiological mechanisms of bradykinesia in dystonia remain largely unknown. Methods: We here performed a comprehensive literature search and reviewed clinical and experimental studies on bradykinesia in patients with dystonia. Results: Many studies have documented the presence of bradykinesia in patients with idiopathic and inherited isolated dystonia, regardless of the presence of parkinsonism. In addition, bradykinesia has been observed as a side effect in dystonic patients who have undergone deep brain stimulation, in those with functional dystonia as well as in those with combined dystonia, e.g., dystonia-parkinsonism. These clinical and experimental findings support the hypothesis that dysfunction in a brain network involving the basal ganglia, primary sensorimotor cortex, and cerebellum may play a key role in the pathophysiology of both bradykinesia and dystonia. Conclusion: Bradykinesia is frequently observed in dystonia. We may gain insights into the pathophysiological underpinnings of two distinct movement disorders by investigating this issue. Furthermore, a deeper understanding of bradykinesia in dystonia may have terminological implications in this field

Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance

Purpose To evaluate stability and machine learning-based classification performance of radiomic features of spine bone tumors using diffusion- and T2-weighted magnetic resonance imaging (MRI). Material and methods This retrospective study included 101 patients with histology-proven spine bone tumor (22 benign; 38 primary malignant; 41 metastatic). All tumor volumes were manually segmented on morphologic T2-weighted sequences. The same region of interest (ROI) was used to perform radiomic analysis on ADC map. A total of 1702 radiomic features was considered. Feature stability was assessed through small geometrical transformations of the ROIs mimicking multiple manual delineations. Intraclass correlation coefficient (ICC) quantified feature stability. Feature selection consisted of stability-based (ICC > 0.75) and significance-based selections (ranking features by decreasing Mann-Whitney p-value). Class balancing was performed to oversample the minority (i.e., benign) class. Selected features were used to train and test a support vector machine (SVM) to discriminate benign from malignant spine tumors using tenfold cross-validation. Results A total of 76.4% radiomic features were stable. The quality metrics for the SVM were evaluated as a function of the number of selected features. The radiomic model with the best performance and the lowest number of features for classifying tumor types included 8 features. The metrics were 78% sensitivity, 68% specificity, 76% accuracy and AUC 0.78. Conclusion SVM classifiers based on radiomic features extracted from T2- and diffusion-weighted imaging with ADC map are promising for classification of spine bone tumors. Radiomic features of spine bone tumors show good reproducibility rates