Correlation between parodontal indexes and orthodontic retainers: prospective study in a group of 16 patients

Purpose. Fixed retainers are used to stabilize dental elements after orthodontic treatment. Being it a permanent treatment, it is necessary to instruct patients about a constant and continuous monitoring of their periodontal conditions and a correct oral hygiene. The aim of this study was to highlight the possible adverse effects of bonded retainers on parameters correlated to the health conditions of periodontal tissues. Materials and methods. We selected 16 patients, under treatment in the Orthodontics Department of University of Bari Dental School, who had undergone a lingual retainer insertion at the end of the orthodontic treatment. The patients were then divided into two groups (Control Group and Study Group) and monitored for 3 and 36 months, respectively. The following indexes were taken into consideration: gingival index (GI), plaque index (PI) and the presence of calculus (Calculus Index, CI), the probing depth and the presence of gingival recession on the six inferior frontal dental elements. Results. After the observation was carried out, any of the patients showed periodontal sockets and gingival recession. In the Study Group, only 1 patient had a PI score=3, the 7 left had scores between 0.66 and 2.83. In the Control Group, one patient had score=0, the other ones showed values between 0.5 and 1.66. The mean GI in the Study Group peaked at a score of 2.83, the minimum was 0.66; whereas in the Control Group the maximum value was 2 and the minimum 0.66. The CI in the Group Study was between 1 and 2. In the Control Group it was absent in only 1 patient, whereas in the remaining 7, it had a value between 0.3 and 1. The clinical data were studied by means of the Wilcoxon test. We found a statistically significant difference for what concerns the Plaque Indexes (PI) (P>0.05) and Calculus Indexes (CI) (P>0.1) in both groups, with higher scores in the Study Group, having retainers for 36 months. Any statistically significant difference was calculated for the GI. Conclusions. We can therefore conclude that patients with lingual retainers need periodontal hygiene and treatment as to prevent, in the course of time, periodontal damages non-detectable in short-term

High prevalence of hepatitis C virus infection in patients with B-cell lymphoproliferative disorders in Italy.

Starting from the observation that a number of consecutive patients with non-Hodgkin's lymphoma (NHL) resulted positive for hepatitis C virus (HCV) antibodies on routine testing, we set up a survey for HCV contact prevalence in all patients with lymphoproliferative disorders (LPD) followed in our institution. We searched for HCV antibodies by a thirdgeneration ELISA technique, followed by a confirmation test (RIBA III); serum viral RNA and HCV genotype were investigated by a RT-PCR technique. We screened a total of 315 patients suffering from B-NHL (91), multiple myeloma (56), MGUS (48), chronic lymphocytic leukemia (57), Waldentrom's macroglobulinemia (13), Hodgkin's disease (HD)(43), and T-NHL (9). While only I of 52 patients with a non-B-LPD (HD or T-NHL) had signs of HCV contact (i.e., 1.9%, which is in the range of the normal population in the South of Italy), 59 of 263 patients with a B-LPD (22.4%) had HCV antibodies or RNA, or both, with no major differences among the various types of disorders, except for WM, in which the rate was higher (61.5%). The same prevalence was found for patients tested at diagnosis or during the follow-up, and in transfused or never-transfused patients. Only a few patients were aware of having a liver disease; one-half of HCV-positive patients never had transaminase increase. A review of data from Central and Northern Italy is included, showing similar findings; a report from Japan has confirmed such an association, while limited surveys in England have not revealed any correlation. These findings may have important biological and clinical implications

Speeding up node label learning in unbalanced biomolecular networks through a parallel and sparse GPU­based Hopfield model

"Motivation" - In network biology and medicine several problems can be modeled as node label inference in partially labeled networks. Nodes are biomedical entities (e.g. genes, patients) and connections represent a notion of functional similarity between entities. Usually, the class being predicted is represented through a labeling vector highly unbalanced towards negatives: that is only few positive instances (those associated with the class) are available. This fosters the adoption of imbalance­aware methodologies to accurately predict node labels. In addition, input data can be large­sized, since we may have millions of instances (e.g. in multi­species protein networks), thus requiring the design of efficient and scalable methodologies. To address these problems, a parametric neural algorithm based on the Hopfield model, COSNet [1,2,3], has been proposed, leveraging the minimization of a Hopfield network energy through the usual sequential dynamics to achieve an asymptotically stable attractor representing a valuable prediction. In this study, we propose a sparse and partially parallel implementation of COSNet, for sparse networks, which decomposes the input net in independent sets of neurons, each processed concurrently by hardware accelerators, like modern GPUs, while still keeping the overall dynamics sequential. "Methods" - The Hopfield dynamics is decomposed in independent tasks by solving the graph coloring problem, that is assigning colors to the graph vertices so that adjacent vertices receive different colors. Thus, the units of the neural network are split into clusters of independent neurons, which are sequentially updated, whereas the single units within each cluster are updated simultaneously. We simulate the algorithm on GPUs achieving a significant speed up with respect to the original sequential implementation and, at the same time, lowering memory requirements thanks to compressed memorization strategies, thus opening the possibility to face with prediction issues on big size instances. Also, a cooperative CPU multithreading – GPU model have been implemented, where the computations over different functional classes are carried independently by assigning each class to a different CPU thread. "Results" - We tested both COSNet and COSNet­GPU on partially labeled networks containing genes belonging to D. melanogaster and Homo sapiens organisms for predicting respectively the Gene Ontology (GO) and the Human Phenotype Ontology (HPO) terms with 10­50 annotated genes. The algorithm behavior has been measured in terms of execution time and memory consumption. Table 1 summarizes the results in term of speed­up and memory usage, when performing a 3­fold cross validation procedure. The results show significant reductions in both execution times and memory consumption, and interestingly the improvement factors increases more than linearly with the number of nodes/genes. This also corroborates the fact that the proposed implementation nicely scales on big data

A Web Graphical Tool for the Integration of Unbalanced Biomolecular Networks

1 MOTIVATION - The automated protein function prediction problem (AFP) is mainly characterized by the unbalance between annotated and unannotated genes and the integration of multiple data sources. The “informativeness” of each network/source may depend on the considered protein function, and neglecting the unbalance between annotated and unannotated proteins may thereby lead to strong decay in performance. Recently, the UNIPred algorithm [1] was proposed to integrate in a function-specific fashion the input networks by automatically handling the data imbalance. A relevant challenge in this context is the appropriate visualization and interpretation of the resulting network. Indeed, the network size can be extremely big and their simple visualization, with off-theshelf graphical visualization tools (e.g. GraphViz, GeneMania) produces a cloud of points hard to interpret and handle within a browser (lack of memory). To face the problem, here we propose a web-tool implementing UNIPred and introducing an approximate visualization of the graph. Having the system embedded different levels of abstraction, the user can both decide the part of the graph to explore, and click on the corresponding part to obtain a new enhanced visualization. 2. METHODS - The different input networks have been represented and stored according to the relational model. Efficient PL/SQL procedures calculate subgraphs centered on a vertex and with a given radius. An R software gathers the networks from the database, integrate them according to the UNIPred algorithm and store the results back in the database. Relying on this infrastructure, a web graphical tool has been implemented that offers different facilities to the user for the network management, their integration, visualization and exploration. In particular, both ``vertex-centric" exact and approximate visualizations are provided. With ``vertex-centric" [2] visualization approach we mean that the user can specify a vertex, named target, he wishes to explore the result of the integration, and the size of the subnetwork to extract. The extracted network can be shown to the user when its size is small and the available canvas is big enough for its visualization. Otherwise, approximate visualization techniques are used. For example, the target node can be connected with bubbles of different sizes that distribute the nodes of the subgraph relying on the weight of the outgoing edges and the distance from the target. Clicking on one of the bubbles, the visualization can be then expanded by showing other bubbles or single nodes. 3 RESULTS - We have realized a Web tool offering different facilities for the exploration of protein networks, their efficient integration using the UNIPred algorithm in a Web-based environment, and the exploration of the resulting network by means of a vertex-centric visualization approach. The visualization can be exact or approximate depending on the size of the network and of the drawing canvas. In the left part of Figure 1 a target is shown in the center and then four bubbles that partition the vertex at distance 1 from the target depending on the weight of the outgoing edges. This representation points out how much the co-functionality confidence degree has been propagated (or not) from the target node. Moreover, by clicking on one of the bubbles, it is split again in 4 parts, thus allowing multiple “vertex-centric” views at different resolution levels

WIN55,212-2-induced expression of Mir-29b1 favours the suppression of osteosarcoma cell migration in a SPARC-independent manner

WIN55,212-2 (WIN) is a synthetic agonist of cannabinoid receptors that displays promising antitumour properties. The aim of this study is to demonstrate that WIN is able to block the migratory ability of osteosarcoma cells and characterize the mechanisms involved. Using wound healing assay and zymography, we showed that WIN affects cell migration and reduces the activity of the metalloproteases MMP2 and MMP9. This effect seemed to be independent of secreted protein acidic and rich in cysteine (SPARC), a matricellular protein involved in tissue remodeling and extracellular matrix deposition. SPARC release was indeed prevented by WIN, and SPARC silencing by RNA interference did not influence the effect of the cannabinoid on cell migration. WIN also increased the release of extracellular vesicles and dramatically upregulated miR-29b1, a key miRNA that modulates cell proliferation and migration. Interestingly, reduced cell migration was observed in stably miR-29b1-transfected cells, similarly to WIN-treated cells. Finally, we show the absence of SPARC in the extracellular vesicles released by osteosarcoma cells and no changes in SPARC level in miR-29b1 overexpressing cells. Overall, these findings suggest that WIN markedly affects cell migration, dependently on miR-29b1 and independently of SPARC, and can thus be considered as a potential innovative therapeutic agent in the treatment of osteosarcoma

Psychological treatments and psychotherapies in the neurorehabilitation of pain. Evidences and recommendations from the italian consensus conference on pain in neurorehabilitation

BACKGROUND: It is increasingly recognized that treating pain is crucial for effective care within neurological rehabilitation in the setting of the neurological rehabilitation. The Italian Consensus Conference on Pain in Neurorehabilitation was constituted with the purpose identifying best practices for us in this context. Along with drug therapies and physical interventions, psychological treatments have been proven to be some of the most valuable tools that can be used within a multidisciplinary approach for fostering a reduction in pain intensity. However, there is a need to elucidate what forms of psychotherapy could be effectively matched with the specific pathologies that are typically addressed by neurorehabilitation teams. OBJECTIVES: To extensively assess the available evidence which supports the use of psychological therapies for pain reduction in neurological diseases. METHODS: A systematic review of the studies evaluating the effect of psychotherapies on pain intensity in neurological disorders was performed through an electronic search using PUBMED, EMBASE, and the Cochrane Database of Systematic Reviews. Based on the level of evidence of the included studies, recommendations were outlined separately for the different conditions. RESULTS: The literature search yielded 2352 results and the final database included 400 articles. The overall strength of the recommendations was medium/low. The different forms of psychological interventions, including Cognitive-Behavioral Therapy, cognitive or behavioral techniques, Mindfulness, hypnosis, Acceptance and Commitment Therapy (ACT), Brief Interpersonal Therapy, virtual reality interventions, various forms of biofeedback and mirror therapy were found to be effective for pain reduction in pathologies such as musculoskeletal pain, fibromyalgia, Complex Regional Pain Syndrome, Central Post-Stroke pain, Phantom Limb Pain, pain secondary to Spinal Cord Injury, multiple sclerosis and other debilitating syndromes, diabetic neuropathy, Medically Unexplained Symptoms, migraine and headache. CONCLUSIONS: Psychological interventions and psychotherapies are safe and effective treatments that can be used within an integrated approach for patients undergoing neurological rehabilitation for pain. The different interventions can be specifically selected depending on the disease being treated. A table of evidence and recommendations from the Italian Consensus Conference on Pain in Neurorehabilitation is also provided in the final part of the pape

Analysis of the impact of intermittent distribution by modelling the network-filling process

In many countries, users acquire private tanks to reduce their vulnerability to water scarcity. In such conditions, water managers often apply intermittent distribution in order to reduce the water volumes supplied to the users. This practice modifies the hydraulic behaviour of the network and determines competition among users that need to collect enough water resource for their uses. Intermittent distribution is thus responsible for the inequality that can occur among users: those located in advantaged positions of the network are able to obtain water resources soon after the service period begins, while others have to wait much longer, after the network is full. This paper analyses the inequalities that take part when intermittent distribution is applied in water scarcity scenarios. Considering the complexity of the process, the analysis was performed by means of an unsteady numerical model. The model was applied to a real case study which provided interesting insights into the network filling process, helping to highlight the advantaged and disadvantaged areas of the network in different water scarcity scenarios