Endothelial progenitor cells and vascular health: effects of lifestyle's modifications

During the last years increasing evidence showed that bone marrow-derived cells with angiogenic capability, named endothelial progenitor cells (EPCs), possess the capacity to home to sites of vascular injury, so contributing to the neoangiogenesis in vivo and to the maintenance of the homeostasis of vascular endothelium. Currently, potent triggers for the mobilisation of EPCs from bone-marrow are known. In addition to some pharmacological treatment such as statins, erythropoietin, PPAR-gamma agonists and angiotensin-II receptor antagonists, the effects of healthy lifestyle, via mobilization and functional improvement of EPC, is increasingly recognized. In this review we analyze, the effects of lifestyle interventions on EPCs. In particular we will focus on physical activity and cardiac rehabilitation protocols, weight reduction, and smoking cessation. Moreover, the negative effects of depression, mood disturbances and type D-personality on EPCs are also considered

One-class support vector machines identify the language and default mode regions as common patterns of structural alterations in young children with autism spectrum disorders

The identification of reliable brain endophenotypes of autism spectrum disorders (ASD) has been hampered to date by the heterogeneity in the neuroanatomical abnormalities detected in this condition. To handle the complexity of neuroimaging data and to convert brain images in informative biomarkers of pathology, multivariate analysis techniques based on Support Vector Machines (SVM) have been widely used in several disease conditions. They are usually trained to distinguish patients from healthy control subjects by making a binary classification. Here, we propose the use of the One-Class Classification (OCC) or Data Description method that, in contrast to two-class classification, is based on a description of one class of objects only. This approach, by defining a multivariate normative rule on one class of subjects, allows recognizing examples from a different category as outliers. We applied the OCC to 314 regional features extracted from brain structural Magnetic Resonance Imaging (MRI) scans of young children with ASD (21 males and 20 females) and control subjects (20 males and 20 females), matched on age [range: 22-72 months of age; mean = 49 months] and non-verbal intelligence quotient (NVIQ) [range: 31-123; mean = 73]. We demonstrated that a common pattern of features characterize the ASD population. The OCC SVM trained on the group of ASD subjects showed the following performances in the ASD vs. controls separation: the area under the receiver operating characteristic curve (AUC) was 0.74 for the male and 0.68 for the female population, respectively. Notably, the ASD vs. controls discrimination results were maximized when evaluated on the subsamples of subjects with NVIQ = 70, leading to AUC = 0.81 for the male and AUC = 0.72 for the female populations, respectively. Language regions and regions from the default mode network-posterior cingulate cortex, pars opercularis and pars triangularis of the inferior frontal gyrus, and transverse temporal gyrus-contributed most to distinguishing individuals with ASD from controls, arguing for the crucial role of these areas in the ASD pathophysiology. The observed brain patterns associate preschoolers with ASD independently of their age, gender and NVIQ and therefore they are expected to constitute part of the ASD brain endophenotype

Urinary Cytology: Potential Role in Canine Urinary Tract Infections

The diagnosis of urinary tract infections (UTIs) requires a concomitant evaluation of clinical signs and urine culture, which is of fundamental to start an appropriate antibiotic treatment. Several factors, such as subclinical bacteriuria or pre-analytical errors, may make the interpretation of urine culture difficult. The aim of the study was to evaluate the association between the finding of neutrophils and bacteria in unstained and stained canine urine sediment and the presence of clinical signs and positive urine culture. Urine samples from 35 dogs with clinical signs of UTI and 55 asymptomatic dogs with risk factors for UTI were prospectively collected by cystocentesis, divided into three aliquots, and submitted for: (1) physical and chemical Dipstick analysis and unstained urinary sediment (casts, crystals, bacteria, leucocytes, cells, parasites); (2) stained urinary sediment (extra/intracellular bacteria, degenerated and non-degenerated neutrophils); (3) qualitative and quantitative urine culture and antimicrobial sensitivity-test. The association between unstained and stained findings of urinary sediment and urine culture was tested. Sensibility, specificity, and positive/negative predictive values in diagnosing positive urine cultures of bacteria at unstained and stained evaluation were compared. Both wet-mount bacteriuria and the cytological presence of intracellular and extracellular bacteria, neutrophils, and degenerated neutrophils were successively associated with positive urine culture (p < 0.001). The presence of intracellular bacteria was the only independent predictor of positive urine culture. Total bacterial count did not differ significantly between symptomatic and asymptomatic dogs. Detection of extracellular and intracellular bacteriuria at stained urinary sediment significantly improved the sensibility of predicting positive urine culture. Cytologic evaluation of urinary sediment may be helpful in detecting signs of active inflammation, thus enhancing the clinical relevance of a positive urine culture

Out-of-equilibrium collective oscillation as phonon condensation in a model protein

In the first part of the present paper (theoretical), the activation of out-of-equilibrium collective oscillations of a macromolecule is described as a classical phonon condensation phenomenon. If a macromolecule is modeled as an open system, that is, it is subjected to an external energy supply and is in contact with a thermal bath to dissipate the excess energy, the internal nonlinear couplings among the normal modes make the system undergo a non-equilibrium phase transition when the energy input rate exceeds a threshold value. This transition takes place between a state where the energy is incoherently distributed among the normal modes, to a state where the input energy is channeled into the lowest frequency mode entailing a coherent oscillation of the entire molecule. The model put forward in the present work is derived as the classical counterpart of a quantum model proposed long time ago by H. Fr\"ohlich in the attempt to explain the huge speed of enzymatic reactions. In the second part of the present paper (experimental), we show that such a phenomenon is actually possible. Two different and complementary THz near-field spectroscopic techniques, a plasmonic rectenna, and a micro-wire near-field probe, have been used in two different labs to get rid of artefacts. By considering a aqueous solution of a model protein, the BSA (Bovine Serum Albumin), we found that this protein displays a remarkable absorption feature around 0.314 THz, when driven in a stationary out-of-thermal equilibrium state by means of optical pumping. The experimental outcomes are in very good qualitative agreement with the theory developed in the first part, and in excellent quantitative agreement with a theoretical result allowing to identify the observed spectral feature with a collective oscillation of the entire molecule.Comment: 49 pages, 10 figures; Physical Review X, (2018) in pres

Alterations of selected serum biochemical and urinary parameters in dogs with chronic enteropathy

Background: No specific study on concurrent nephropathy has been conducted in dogs with chronic enteropathy (CE), except for soft-coated Wheaten Terriers. Moreover, limited information exists regarding the urinary profile in dogs with CE.Aim: To describe, compare, and discuss the alterations in selected serum biochemical and urinary parameters in dogs with CE.Methods: Multicentric retrospective study on dogs with CE diagnosed after exclusion of extra-gastrointestinal diseases. In addition, dogs with azotemia and lower urinary tract diseases were excluded. Information on canine chronic enteropathy clinical activity index (CCECAI) score, muscular condition score (MCS), presence of glycosuria, proteinuria [urine protein-to-creatinine (UPC) ratio > 0.5], and/or cylindruria (>1–2 casts/hpf) at diagnosis were gleaned from the medical records. Dogs were retrospectively classified as food-responsive enteropathy, immunosuppressant-responsive enteropathy, or nonresponsive enteropathy based on the presence of gastrointestinal histological inflammation and the treatment response. In addition, based on the serum albumin concentration (ALB), dogs were classified as having protein-losing enteropathy (PLE).Results: Ninety CE dogs were included. Fifty-two dogs had mild-to-severely decreased MCS and 38 dogs showed altered urinary parameters. No significant associations were found between CCECAI and altered urinary parameters. No significant association was found between PLE dogs and altered urinary parameters. PLE dogs showed higher prevalence of proteinuria than non-PLE dogs (p = 0.03; OR = 2.8; 95% CI = 1–6.8).Conclusion: Despite the presence of altered urinary profile in dogs with CE, further studies are needed to explore a possible link between gastrointestinal and renal inflammation

Multi-scale analysis of lung computed tomography images

A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.Comment: 18 pages, 12 low-resolution figure

Active incremental recognition of human activities in a streaming context

​Recognising human activities from streaming sources poses unique challenges to learning algorithms. Predictive models need to be scalable, incrementally trainable, and must remain bounded in size even when the data stream is arbitrarily long. In order to achieve high accuracy even in complex and dynamic environments methods should be also nonparametric, i.e., their structure should adapt in response to the incoming data. Furthermore, as tuning is problematic in a streaming setting, suitable approaches should be parameterless (as initially tuned parameter values may not prove optimal for future streams). Here, we present an approach to the recognition of human actions from streaming data which meets all these requirements by: (1) incrementally learning a model which adaptively covers the feature space with simple and local classifiers; (2) employing an active learning strategy to reduce annotation requests; (3) achieving good accuracy within a fixed model size. Although in this work we focus on human activity recognition, our approach is completely independent from the feature extraction and can deal with any supervised matrix (set of feature vectors). Hence, it can be adapted to a wide range of applications (e.g., speech recognition, image classification, object recognition, pose recognition, and image matching). Extensive experiments on standard benchmarks show that our approach is competitive with state-of-the-art non-incremental methods, while outperforming the existing active incremental baselines