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HCC Development Is Associated to Peripheral Insulin Resistance in a Mouse Model of NASH
No full textNAFLD is the most common liver disease worldwide but it is the potential evolution to NASH and eventually to hepatocellular carcinoma (HCC), even in the absence of cirrhosis, that makes NAFLD of such clinical importance. Aim: we aimed to create a mouse model reproducing the pathological spectrum of NAFLD and to investigate the role of possible co-factors in promoting HCC. Methods: mice were treated with a choline-deficient L-amino-acid-defined-diet (CDAA) or its control (CSAA diet) and subjected to a low-dose i.p. injection of CCl4 or vehicle. Insulin resistance was measured by the euglycemic-hyperinsulinemic clamp method. Steatosis, fibrosis and HCC were evaluated by histological and molecular analysis. Results: CDAA-treated mice showed peripheral insulin resistance at 1 month. At 1-3 months, extensive steatosis and fibrosis were observed in CDAA and CDAA+CCl4 groups. At 6 months, equal increase in steatosis and fibrosis was observed between the two groups, together with the appearance of tumor. At 9 months of treatment, the 100% of CDAA+CCl4 treated mice revealed tumor versus 40% of CDAA mice. Insulin-like Growth Factor-2 (IGF-2) and Osteopontin (SPP-1) were increased in CDAA mice versus CSAA. Furthermore, Immunostaining for p-AKT, p-c-Myc and Glypican-3 revealed increased positivity in the tumors. Conclusions: the CDAA model promotes the development of HCC from NAFLD-NASH in the presence of insulin resistance but in the absence of cirrhosis. Since this condition is increasingly recognized in humans, our study provides a model that may help understanding mechanisms of carcinogenesis in NAFLD
Interactive simulator for e-Learning environments: a teaching software for health care professionals
Get PDFThere is an established tradition of cardiovascular simulation tools, but the application of this kind of technology in the e-Learning arena is a novel approach. This paper presents an e-Learning environment aimed at teaching the interaction of cardiovascular and lung systems to health-care professionals. Heart-lung interaction must be analyzed while assisting patients with severe respiratory problems or with heart failure in intensive care unit. Such patients can be assisted by mechanical ventilatory assistance or by thoracic artificial lung. "In silico" cardiovascular simulator was experimented during a training course given to graduate students of the School of Specialization in Cardiology at \u27Sapienza\u27 University in Rome. The training course employed CARDIOSIM(C): a numerical simulator of the cardiovascular system. Such simulator is able to reproduce pathophysiological conditions of patients affected by cardiovascular and/or lung disease. In order to study the interactions among the cardiovascular system, the natural lung and the thoracic artificial lung (TAL), the numerical model of this device has been implemented. After having reproduced a patient\u27s pathological condition, TAL model was applied in parallel and hybrid model during the training course. Results obtained during the training course show that TAL parallel assistance reduces right ventricular end systolic (diastolic) volume, but increases left ventricular end systolic (diastolic) volume. The percentage changes induced by hybrid TAL assistance on haemodynamic variables are lower than those produced by parallel assistance. Only in the case of the mean pulmonary arterial pressure, there is a percentage reduction which, in case of hybrid assistance, is greater (about 40%) than in case of parallel assistance (20-30%). At the end of the course, a short questionnaire was submitted to students in order to assess the quality of the course. The feedback obtained was positive, showing good results with respect to the degree of students\u27 learning and the ease of use of the software simulator
Novel epigenetic target therapy for prostate cancer: a preclinical study.
Get PDFEpigenetic events are critical contributors to the pathogenesis of cancer, and targeting epigenetic mechanisms represents a novel strategy in anticancer therapy. Classic demethylating agents, such as 5-Aza-29-deoxycytidine (Decitabine), hold the potential for reprograming somatic cancer cells demonstrating high therapeutic efficacy in haematological malignancies. On the other hand, epigenetic treatment of solid tumours often gives rise to undesired cytotoxic side effects. Appropriate delivery systems able to enrich Decitabine at the site of action and improve its bioavailability would reduce the incidence of toxicity on healthy tissues. In this work we provide preclinical evidences of a safe, versatile and efficient targeted epigenetic therapy to treat hormone sensitive (LNCap) and hormone refractory (DU145) prostate cancers. A novel Decitabine formulation, based on the use of engineered erythrocyte (Erythro-Magneto-Hemagglutinin Virosomes, EMHVs) drug delivery system (DDS) carrying this drug, has been refined. Inside the EMHVs, the drug was shielded from the environment and phosphorylated in its active form. The novel magnetic EMHV DDS, endowed with fusogenic protein, improved the stability of the carried drug and exhibited a high efficiency in confining its delivery at the site of action in vivo by applying an external static magnetic field. Here we show that Decitabine loaded into EMHVs induces a significant tumour mass reduction in prostate cancer xenograft models at a concentration, which is seven hundred times lower than the therapeutic dose, suggesting an improved pharmacokinetics/pharmacodynamics of drug. These results are relevant for and discussed in light of developing personalised autologous therapies and innovative clinical approach for the treatment of solid tumours
Experimental Integration of Autoregulation Unit for Left Ventricular Assist Devices in a Cardiovascular Hybrid Simulator.
No full textIn this paper, an Autoregulation Unit (ARU) for left ventricular sensorized assist devices (LVAD) has been used with a cardiovascular hybrid simulator mimicking physiological and pathological patient conditions. The functionalities of the ARU have been demonstrating for the successful receiving and visualization of system parameters, sending of commands for LVAD speed changes, and enabling of the autonomous flow control algorithm. Experiments of speed changes and autoregulation are reported, showing the feasibility of the approach for both local and remote control of a LVAD
Effects of Sapropterin on Endothelium-Dependent Vasodilation in Patients With CADASIL: A Randomized Controlled Trial
Get PDFBackground and Purpose-Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a rare autosomal dominant disorder caused by NOTCH3 mutations, is characterized by vascular smooth muscle and endothelial cells abnormalities, altered vasoreactivity, and recurrent lacunar infarcts. Vasomotor function may represent a key factor for disease progression. Tetrahydrobiopterin, essential cofactor for nitric oxide synthesis in endothelial cells, ameliorates endothelial function. We assessed whether supplementation with sapropterin, a synthetic tetrahydrobiopterin analog, improves endothelium-dependent vasodilation in CADASIL patients
Word Processing for Arabic Language. A reappraisal of morphology induction through adaptive memory self-organisation strategies
Get PDFModelling the mental lexicon focuses on processing and storage dynamics, since lexical organisation relies on the process of input recoding and adaptive strategies for long-term memory organisation. A fundamental issue in word processing is represented by the emergence of the morphological organisation level in the lexicon, based on paradigmatic relations between fully-stored word forms. Morphology induction can be defined as the task of identifying morphological formatives within morphologically complex word forms. In the computational framework we propose here (TSOMs), based on Self-Organising Maps with Hebbian connections defined over a temporal layer, the identification/perception of surface morphological relations involves the alignment of recoded representations of morphologically-related input words. Facing a non-concatenative morphology such as the Arabic inflectional system prompts a reappraisal of morphology induction through adaptive organisation strategies, which affect both lexical representations and long-term storage. We will show how a strongly adaptive self-organisation during training is conducive to emergent relations between stored word forms, and to high accuracy rates in generalising knowledge of stored words to unknown forms
Word Processing for Arabic Language: A reappraisal of morphology induction through adaptive memory self-organisation strategies
No full textModelling the mental lexicon focuses on processing and storage dynamics, since lexical organisation relies on the process of input recoding and adaptive strategies for long-term memory organisation. A fundamental issue in word processing is represented by the emergence of the morphological organisation level in the lexicon, based on paradigmatic relations between fully-stored word forms. Morphology induction can be defined as the task of identifying morphological formatives within morphologically complex word forms. In the computational framework we propose here (TSOMs), based on Self-Organising Maps with Hebbian connections defined over a temporal layer, the identification/perception of surface morphological relations involves the alignment of recoded representations of morphologically-related input words. Facing a non-concatenative morphology such as the Arabic inflectional system prompts a reappraisal of morphology induction through adaptive organisation strategies, which affect both lexical representations and long-term storage. We will show how a strongly adaptive self-organisation during training is conducive to emergent relations between stored word forms, and to high accuracy rates in generalising knowledge of stored words to unknown forms
Perception of typicality in the lexicon: wordlikeness, lexical density and morphonotactic constraints
Get PDFThe extent to which a symbolic time-series (a sequence of sounds or letters) is a typical word of a language, referred to as WORDLIKENESS, has been shown to have effects in speech perception and production, reading proficiency, lexical development and lexical access, short-term and long-term verbal memory. Two quantitative models have been suggested to account for these effects: serial phonotactic probabilities (the likelihood for a given symbolic sequence to appear in the lexicon) and lexical density (the extent to which other words can be obtained from a target word by changing, deleting or inserting one or more symbols in the target). The two measures are highly correlated and thus easy to be confounded in measuring their effects in lexical tasks. In this paper, we propose a computational model of lexical organisation, based on Self-Organising Maps with Hebbian connections defined over a temporal layer (TSOMs), providing a principled algorithmic account of effects of lexical acquisition, processing and access, to further investigate these issues. In particular, we show that (morpho-)phonotactic probabilities and lexical density, though correlated in lexical organisation, can be taken to focus on different aspects of speakers\u27 word processing behaviour and thus provide independent cognitive contributions to our understanding of the principles of perception of typicality that govern lexical organisation