Transplantable zebrafish models of neuroendocrine tumors

Neuroendocrine tumors (NETs)are rare neoplasms whose incidence is increasing. NETs constitute a heterogeneous group of tumors. Their clinical features, functional properties, and clinical course are different on the basis of their site of origin. Due to the heterogeneity of these tumors, a coordinated multidisciplinary approach is required in these patients. However, medical doctor encounters many difficulties when providing care for patients with NETs. This review provides an overview of the state of the art of zebrafish model in the cancer research with a main focus on NETs

Tales from Dubna’s Oakwood: Bogoliubov, Pontecorvo, and the JINR Seminars

Not much has been said about the scientific milieu in which Bru- no Pontecorvo worked after his emigration to the USSR (1950): the Joint Institute for Nuclear Research (JINR) in Dubna. In this paper, we begin to fill this gap by focusing on some of the distinguished scientists he interacted with, besides direct collaborations, paying particular attention to Nikolai N. Bogoliubov around 1957

Existence of positive solutions of a superlinear boundary value problem with indefinite weight

We deal with the existence of positive solutions for a two-point boundary value problem associated with the nonlinear second order equation $u''+a(x)g(u)=0$. The weight $a(x)$ is allowed to change its sign. We assume that the function $g\colon\mathopen{[}0,+\infty\mathclose{[}\to\mathbb{R}$ is continuous, $g(0)=0$ and satisfies suitable growth conditions, so as the case $g(s)=s^{p}$, with $p>1$, is covered. In particular we suppose that $g(s)/s$ is large near infinity, but we do not require that $g(s)$ is non-negative in a neighborhood of zero. Using a topological approach based on the Leray-Schauder degree we obtain a result of existence of at least a positive solution that improves previous existence theorems.Comment: 12 pages, 4 PNG figure

Performance evaluation of a piezoelectric energy harvester based on flag-flutter

In the last few decades, piezoelectric (PZT) materials have played a vital role in the aerospace industry because of their energy harvesting capability. PZT energy harvesters (PEH) absorb the energy from an operational environment and can transform it into useful energy to drive nano/micro-electronic components. In this research work, a PEH based on the flag-flutter mechanism is presented. This mechanism is based on fluid-structure interaction (FSI). The flag is subjected to the axial airflow in the subsonic wind tunnel. The performance evaluation of the harvester and aeroelastic analysis is investigated numerically and experimentally. A novel solution is presented to extract energy from Limit Cycle Oscillations (LCOs) phenomenon by means of PZT transduction. The PZT patch absorbs the flow-induced structural vibrations and transforms it into electrical energy. Furthermore, the optimal resistance and length of the flag is predicted to maximize the energy harvesting. Different configurations of flag i.e., with Aluminium (Al) patch and PZT patch for flutter mode vibration mode are studied numerically and experimentally. The bifurcation diagram is constructed for the experimental campaign for the flutter instability of a cantilevered flag in subsonic wind-tunnel. Moreover, the flutter boundary conditions are analysed for reduced critical velocity and frequency. The designed PZT energy harvester via flag-flutter mechanism is suitable for energy harvesting in aerospace engineering applications to drive wireless sensors. The maximum output power that can be generated from the designed harvester is 6.72 mW and the optimal resistance is predicted to be 0.33 MΩ

ADAP2 in heart development: a candidate gene for the occurrence of cardiovascular malformations in NF1 microdeletion syndrome

Background Cardiovascular malformations have a higher incidence in patients with NF1 microdeletion syndrome compared to NF1 patients with intragenic mutation, presumably owing to haploinsufficiency of one or more genes included in the deletion interval and involved in heart development. In order to identify which genes could be responsible for cardiovascular malformations in the deleted patients, we carried out expression studies in mouse embryos and functional studies in zebrafish. Methods and results The expression analysis of three candidate genes included in the NF1 deletion interval, ADAP2, SUZ12 and UTP6, performed by in situ hybridisation, showed the expression of ADAP2 murine ortholog in heart during fundamental phases of cardiac morphogenesis. In order to investigate the role of ADAP2 in cardiac development, we performed loss-of-function experiments of zebrafish ADAP2 ortholog, adap2, by injecting two different morpholino oligos (adap2-MO and UTR-adap2-MO). adap2-MOs-injected embryos (morphants) displayed in vivo circulatory and heart shape defects. The molecular characterisation of morphants with cardiac specific markers showed that the injection of adap2-MOs causes defects in heart jogging and looping. Additionally, morphological and molecular analysis of adap2 morphants demonstrated that the loss of adap2 function leads to defective valvulogenesis, suggesting a correlation between ADAP2 haploinsufficiency and the occurrence of valve defects in NF1-microdeleted patients. Conclusions Overall, our findings indicate that ADAP2 has a role in heart development, and might be a reliable candidate gene for the occurrence of cardiovascular malformations in patients with NF1 microdeletion and, more generally, for the occurrence of a subset of congenital heart defects

Dysregulation of NIPBL leads to impaired RUNX1 expression and hematopoietic defects

The transcription factor RUNX1, a pivotal regulator of HSCs and haematopoiesis, is a frequent target of chromosomal translocations, point mutations or altered gene/protein dosage. These modifications lead or contribute to the development of myelodysplasia, leukaemia or platelet disorders. A better understanding of how regulatory elements contribute to fine-tune the RUNX1 expression in haematopoietic tissues could improve our knowledge of the mechanisms responsible for normal haematopoiesis and malignancy insurgence. The cohesin RAD21 was reported to be a regulator of RUNX1 expression in the human myeloid HL60 cell line and during primitive haematopoiesis in zebrafish. In our study, we demonstrate that another cohesin, NIPBL, exerts positive regulation of RUNX1 in three different contexts in which RUNX1 displays important functions: in megakaryocytes derived from healthy donors, in bone marrow samples obtained from adult patients with acute myeloid leukaemia and during zebrafish haematopoiesis. In this model, we demonstrate that alterations in the zebrafish orthologue nipblb reduce runx1 expression with consequent defects in its erythroid and myeloid targets such as gata1a and spi1b in an opposite way to rad21. Thus, also in the absence of RUNX1 translocation or mutations, additional factors such as defects in the expression of NIPBL might induce haematological diseases

Multi-Cloud Portable Application Deployment with VEP

Leveraging the plethora of available Infrastructure-as-a-Service (IaaS) solutions proves to be a hard task for users who should face the complexity of dealing with heterogeneous systems, either in terms of resources or APIs. Application portability is the mean to reduce the burden of adapting applications for specific IaaS types and escape po-tential vendor lock-in. The Virtual Execution Platform (VEP) is a cloud middleware software that interfaces multiple IaaS clouds and presents end-users with an interface facilitating deployment and life cycle man-agement of distributed applications made up of several inter-networked virtual machines. This paper presents the design of VEP and experi-mental results that evaluate its scalability in deploying applications on OpenNebula and OpenStack clouds

Zebrafish as a Model to Investigate Dynamin 2-Related Diseases

Mutations in the dynamin-2 gene (DNM2) cause autosomal dominant centronuclear myopathy (CNM) and dominant intermediate Charcot-Marie-Tooth (CMT) neuropathy type B (CMTDIB). As the relation between these DNM2-related diseases is poorly understood, we used zebrafish to investigate the effects of two different DNM2 mutations. First we identified a new alternatively spliced zebrafish dynamin-2a mRNA (dnm2a-v2) with greater similarity to human DNM2 than the deposited sequence. Then we knocked-down the zebrafish dnm2a, producing defects in muscle morphology. Finally, we expressed two mutated DNM2 mRNA by injecting zebrafish embryos with human mRNAs carrying the R522H mutation, causing CNM, or the G537C mutation, causing CMT. Defects arose especially in secondary motor neuron formation, with incorrect branching in embryos injected with CNM-mutated mRNA, and total absence of branching in those injected with CMT-mutated mRNA. Muscle morphology in embryos injected with CMT-mutated mRNA appeared less regularly organized than in those injected with CNM-mutated mRNA. Our results showing, a continuum between CNM and CMTDIB phenotypes in zebrafish, similarly to the human conditions, confirm this animal model to be a powerful tool to investigate mutations of DNM2 in vivo

A predictive decision support system for coronavirus disease 2019 response management and medical logistic planning

Objective: Coronavirus disease 2019 demonstrated the inconsistencies in adequately responding to biological threats on a global scale due to a lack of powerful tools for assessing various factors in the formation of the epidemic situation and its forecasting. Decision support systems have a role in overcoming the challenges in health monitoring systems in light of current or future epidemic outbreaks. This paper focuses on some applied examples of logistic planning, a key service of the Earth Cognitive System for Coronavirus Disease 2019 project, here presented, evidencing the added value of artificial intelligence algorithms towards predictive hypotheses in tackling health emergencies. Methods: Earth Cognitive System for Coronavirus Disease 2019 is a decision support system designed to support healthcare institutions in monitoring, management and forecasting activities through artificial intelligence, social media analytics, geo- spatial analysis and satellite imaging. The monitoring, management and prediction of medical equipment logistic needs rely on machine learning to predict the regional risk classification colour codes, the emergency rooms attendances, and the fore- cast of regional medical supplies, synergically enhancing geospatial and temporal dimensions. Results: The overall performance of the regional risk colour code classifier yielded a high value of the macro-average F1-score (0.82) and an accuracy of 85%. The prediction of the emergency rooms attendances for the Lazio region yielded a very low root mean square error (<11 patients) and a high positive correlation with the actual values for the major hos- pitals of the Lazio region which admit about 90% of the region’s patients. The prediction of the medicinal purchases for the regions of Lazio and Piemonte has yielded a low root mean squared percentage error of 16%. Conclusions: Accurate forecasting of the evolution of new cases and drug utilisation enables the resulting excess demand throughout the supply chain to be managed more effectively. Forecasting during a pandemic becomes essential for effective government decision-making, managing supply chain resources, and for informing tough policy decisions