Searching for diversity. An overview on board of Italian Cultural Organizations.

Diversity takes on different meanings and synonymous; actually, the theme has been strongly debated in the era of globalization, migration and because of the affirmation of human rights and gender policies. Many studies are related to the analysis of board diversity within the forprofit organizations. Indeed, there is paucity of studies that linked the topic to the role of demographic and non-demographic diversity among cultural organizations and NPOs sector. Italian cultural institutions have been grouped together in a website by the private association AICI. The website was used in the present study in order to map organizations and their boards in terms of multiple diversity variables such visible and invisible parameters. Hereby, diversity is explored among board members of 102 private foundations and associations, including dimensions like age, gender, nationality, educational and professional background. One of the main finds of the research highlights how Italian cultural organizations have a low degree of diversity within the boards of directors

Attribute selection via multi-objective evolutionary computation applied to multi-skill contact center data classification

Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We propose the application of the multi-objective evolutionary algorithm ENORA to the task of feature selection for multi-class classification of data extracted from an integrated multi-channel multi-skill contact center, which include technical, service and central data for each session. Additionally, we propose a methodology to integrate feature selection for classification, model evaluation, and decision making to choose the most satisfactory model according to a "a posteriori" process in a multi-objective context. We check out our results by comparing the performance and the classification rate against the well-known multi-objective evolutionary algorithm NSGA-II. Finally, the best obtained solution is validated by a data expert’s semantic interpretation of the classifier

Hydroxyapatite nanocrystals as a smart, pH sensitive, delivery system for kiteplatin

Hydroxyapatite (HA) nanocrystals are important inorganic constituents of biological hard tissues in vertebrates and have been proposed as a bone substitute or a coating material for prostheses in biomedicine. Hydroxyapatite is also amenable for its capacity to bind to a great variety of biomolecules and therapeutic agents. As drug carriers, apatite nanoparticles also have the advantage of pH dependent solubility and low toxicity. Thus HA nanoparticles are negligibly soluble at physiological pH but their dissolution is accelerated at lower pH such as that typically found in the vicinity of tumors. In the present study we have investigated the adsorption on and the release from biomimetic HA nanoparticles of two platinum derivatives of cis-1,4-diaminocyclohexane ([PtX2(cis-1,4-DACH)], X2 = Cl2 (1) and 1,1-cyclobutanedicarboxylate (CBDCA, 2)). The first of the two compounds proved to be active against colon cancer cells also resistant to oxaliplatin. The release has been investigated as a function of pH to mimic the different physiological environments of healthy tissues and tumors, and the in vitro cytotoxicity of the releasates from the HA matrices has been assessed against various human cancer cell lines. The results fully confirmed the potential of 1-loaded HA nanoparticles as bone-specific drug delivery devices

Design and Synthesis of a cADPR Mimic as a Novel Tool for Monitoring the Intracellular Ca2+ Concentration

Cyclic ADP-ribose (cADPR, 1, Figure 1) is a naturally occurring metabolite of NAD+ capable of mobilizing Ca2+ ions from intracellular stores. It was firstly isolated from sea urchin egg extract, but it was later established that it is also produced in many other mammalian cells, including pancreatic β-cells, T-lymphocytes, smooth and cardiac muscle cells, and cerebellar neurons, acting as a Ca2+-mobilizing agent. For this activity, cADPR has been classified as a second messenger that, by activating the ryanodine receptors of the sarcoplasmatic reticulum, is able to mobilize the calcium ions from intracellular stores. cADPR is involved in many physiological processes related to variation in the Ca2+ concentration, such as synaptic homeostasis in neurons as well as fertilization and cellular proliferation. This cyclic nucleotide, characterized by a very labile glycosidic bond at N1, is also rapidly hydrolysed in neutral aqueous solutions to inactive ADP-ribose. Matsuda and co-workers [1] were the first to synthesize new analogues of cADPR in which the adenine base is replaced by a hypoxanthine ring. This kind of modification produced the cyclic inosine diphosphate ribose (cIDPR), which proved to be stable in hydrolytic physiological conditions and showed significant Ca2+ mobilizing activity. Many modifications regarding the northern and southern ribose, as well as the purine base of cADPR, have been proposed so far. In our laboratories, we have synthesized several analogues of cIDPR [2–7]. In particular, the analogue with the northern ribose replaced by a pentyl chain (cpIDP) showed interesting Ca2+ mobilizing activity on the neuronal PC12 cell line [2]. Starting from these results, we report here the synthesis of the novel analogue 2, in which the “northern” ribose of cIDPR is replaced by a 2″,3″-dihydroxy pentyl chain. The effect of the presence of the diol moiety on the intracellular Ca2+ release will be assessed in due course

Predicting brain age with complex networks: From adolescence to adulthood.

In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brain scans (in the age range 7-64years). We introduce a structural connectivity model of the human brain: MRI scans are divided in rectangular boxes and Pearson's correlation is measured among them in order to obtain a complex network model. Brain connectivity is then characterized through few and easy-to-interpret centrality measures; finally, brain age is predicted by feeding a compact deep neural network. The proposed approach is accurate, robust and computationally efficient, despite the large and heterogeneous dataset used. Age prediction accuracy, in terms of correlation between predicted and actual age r=0.89and Mean Absolute Error MAE =2.19years, compares favorably with results from state-of-the-art approaches. On an independent test set including 262 subjects, whose scans were acquired with different scanners and protocols we found MAE =2.52. The only imaging analysis steps required in the proposed framework are brain extraction and linear registration, hence robust results are obtained with a low computational cost. In addition, the network model provides a novel insight on aging patterns within the brain and specific information about anatomical districts displaying relevant changes with aging

Infective Endocarditis: A Focus on Oral Microbiota

Infective endocarditis (IE) is an inflammatory disease usually caused by bacteria entering the bloodstream and settling in the heart lining valves or blood vessels. Despite modern antimicrobial and surgical treatments, IE continues to cause substantial morbidity and mortality. Thus, primary prevention and enhanced diagnosis remain the most important strategies to fight this disease. In this regard, it is worth noting that for over 50 years, oral microbiota has been considered one of the significant risk factors for IE. Indeed, among the disparate recommendations from the American heart association and the European Society of Cardiology, there are good oral hygiene and prophylaxis for high-risk patients undergoing dental procedures. Thus, significant interest has grown in the role of oral microbiota and it continues to be a subject of research interest, especially if we consider that antimicrobial treatments can generate drug-resistant mutant bacteria, becoming a severe social problem. This review will describe the current knowledge about the relationship between oral microbiota, dental procedures, and IE. Further, it will discuss current methods used to prevent IE cases that originate from oral pathogens and how these should be focused on improving oral hygiene, which remains the significant persuasible way to prevent bacteremia and systemic disorders

PNA-based graphene oxide/porous silicon hybrid biosensor: towards a label-free optical assay for Brugada Syndrome

Peptide nucleic acid (PNA) is a synthetic DNA mimic that outperforms the properties of traditional oligonucleotides (ONs). On account of its outstanding features, such as remarkable binding affinity towards complementary DNA or RNA as well as high thermal and chemical stability, PNA has been proposed as a valuable alternative to the ON probe in gene-sensor design. In this study, a hybrid transducer made-up of graphene oxide (GO) nano-sheets covalently grafted onto a porous silicon (PSi) matrix has been investigated for the early detection of a genetic cardiac disorder, the Brugada syndrome (BS). A functionalization strategy towards the realization of a potential PNA-based device is described. A peptide nucleic acid (PNA), able to detect the SCN5A associated with the BS has been properly synthesized and used as a bioprobe for the realization of a proof-of-concept label-free optical PNA-biosensor. PSi reflectance and GO photoluminescence (PL) signals were simultaneously exploited for the monitoring of the device functionalization and response

Bioconjugation of a PNA Probe to Zinc Oxide Nanowires for Label-Free Sensing

Zinc oxide nanowires (ZnONWs) are largely used in biosensing applications due to their large specific surface area, photoluminescence emission and electron mobility. In this work, the surfaces of ZnONWs are modified by covalent bioconjugation of a peptidic nucleic acid (PNA) probe whose sequence is properly chosen to recognize a complementary DNA (cDNA) strand corresponding to a tract of the CD5 mRNA, the main prognostic marker of chronic lymphatic leukemia. The interaction between PNA and cDNA is preliminarily investigated in solution by circular dichroism, CD melting, and polyacrylamide gel electrophoresis. After the immobilization of the PNA probe on the ZnONW surface, we demonstrate the ability of the PNA-functionalized ZnONW platform to detect cDNA in the μM range of concentration by electrical, label-free measurements. The specificity of the sensor is also verified against a non-complementary DNA sequence. These preliminary results highlight the potential application of PNA-bioconjugated ZnONWs to label-free biosensing of tumor markers