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Neuroblastoma is a childhood cancer believed to result from dysfunctional development. Its origin during embryogenesis remains poorly understood. The lack of appropriate models has hindered in-depth mapping of tumor-driving events. Here, we identify a novel tumor-suppressor gene that predicts poor survival in high-risk disease, by applying bulk and single cell RNA sequencing data of neuroblastoma and human fetal adrenal glands. Trunk neural crest-specific MOXD1 discriminates cell populations during normal and tumor development, with implications for deciphering neuroblastoma cell origin. We created an embryonic conditional knockout model and show that cell type-specific loss ofMOXD1leads to disrupted organ homeostasis and failed adrenal gland formation, home for neuroblastoma. We show that MOXD1 is a tumor suppressor gene in zebrafish, chick, and micein vivomodels.One-Sentence SummaryNeural crest-specific MOXD1 is ade novotumor-suppressor gene in childhood cancers arising during embryogenesis.

In this work, it is presented a procedure to find some 3 × 3 dimensional matrices whose integer powers can be characterized by generalized Fibonacci numbers. Moreover, some numerical examples are given to exemplify the procedure established.

Background: Pancreatic Ductal Adenocarcinoma (PDAC) lacks effective treatment options beyond chemotherapy. Although molecular subtypes such as classical and QM (quasi-mesenchymal)/basal-like with transcriptome-based distinct signatures have been identified, deduced therapeutic strategies and targets remain elusive. Gene expression data show enrichment of glycolytic genes in the more aggressive and therapy resistant QM subtype. However, whether the glycolytic transcripts are translated into functional glycolysis that could further be explored for metabolic targeting in QM subtype is still not known. Methods: We used different patient-derived PDAC model systems (conventional and primary patient derived cells, patient derived xenografts (PDX) and patient FFPE samples) and performed transcriptional and functional metabolic analysis. These included: RNAseq and Illumina HT12 bead array, in vitro Seahorse metabolic flux assays and metabolic drug targeting, and in vivo hyperpolarized [1-13C]pyruvate and [1-13C]lactate magnetic resonance spectroscopy (HP-MRS) in PDAC xenografts. Results: We found that glycolytic metabolic dependencies are not unambiguously functionally exposed in all QM PDACs. Metabolic analysis demonstrated functional metabolic heterogeneity in patient-derived primary cells and less so in conventional cell lines independent of molecular subtype. Importantly, we observed that the glycolytic product lactate is actively imported in the PDAC cells and used in mitochondrial oxidation in both classical and QM PDAC cells, although more actively in the QM cell lines. By using hyperpolarized 13C-magnetic resonance spectroscopy (HP-MRS), we were able to non-invasively identify highly glycolytic PDAC xenografts by detecting the last glycolytic enzymatic step and prominent intra-tumoral [1‑13C]pyruvate and [1-13C]lactate interconversion in vivo.Conclusion: Our study adds functional metabolic phenotyping to transcriptome-based analysis and proposes a functional approach to identify highly glycolytic PDACs as candidates for anti-metabolic therapeutic avenues.

Pheochromocytomas (PCCs) and paragangliomas (PGLs) are rare neuroendocrine tumors. PGLs can further be divided into sympathetic (sPGLs) and head-and-neck (HN-PGLs). There are virtually no treatment options, and no cure, for metastatic PCCs and PGLs (PPGLs). Here, we composed a tissue microarray (TMA) consisting of 149 PPGLs, reflecting clinical features and presenting as a useful resource. Mutations in the pseudohypoxic marker EPAS1/HIF-2α correlates to an aggressive tumor phenotype. We show that HIF-2α unexpectedly localized to the cytoplasm in PPGLs. This subcompartmentalized protein expression differed between tumor subtypes, and strongly correlated to proliferation. Half of all sPGLs were metastatic at time of diagnosis. Cytoplasmic HIF-2α was strongly expressed in metastatic sPGLs and predicted poor outcome in this subgroup. We propose that cytoplasmic HIF-2α expression serves as a useful clinical marker to differentiate subtypes and predicting outcome, and hence can be used for improved targeted treatment in PPGLs.

In the study, it has been developed a method for deriving special matrices of 3x3 dimensions, whose powers are related to Fibonacci and Lucas numbers, and some special matrices have been found via the method developed. Also, it has been given some identities related to the matrices found.

In traditional networking architecture, for each problem a specific protocol is dedicated to network devices and these devices are configured manually. Since they are hardware-based, the implementation of new ideas and technologies to these devices is very difficult. However, today's increasing use of smartphones and other mobile data devices has increased the data traffic, and with the addition of service diversity and the needs of users, the existing network structure has become much more complex. Software Defined Networks (SDN) is a new network paradigm that allows a programmable central controller mechanism which separates the control plane from the data plane. With the advantage of a centralized control mechanism, SDN ensures that network structures can respond more quickly to current demands, be more flexible and reprogrammable. In addition, all these processes are implemented at a lower cost compared to traditional networking architecture. To evaluate the performance of SDN architectures, testbeds are used by researchers. In this paper, a small-scale and cost-effective SDN testbed is designed and implemented. The testing environment is realized using Raspberry Pi 3, Floodlight and Open vSwitch. Controller performance has been observed with the MACtracker application.