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The study of natural language using a network approach has made it possible to characterize novel properties ranging from the level of individual words to phrases or sentences. A natural way to quantitatively evaluate similarities and differences between spoken and written language is by means of a multiplex network defined in terms of a similarity distance between words. Here, we use a multiplex representation of words based on orthographic or phonological similarity to evaluate their structure. We report that from the analysis of topological properties of networks, there are different levels of local and global similarity when comparing written vs. spoken structure across 12 natural languages from 4 language families. In particular, it is found that differences between the phonetic and written layers is markedly higher for French and English, while for the other languages analyzed, this separation is relatively smaller. We conclude that the multiplex approach allows us to explore additional properties of the interaction between spoken and written language.

Malware is a sophisticated, malicious, and sometimes unidentifiable application on the network. The classifying network traffic method using machine learning shows to perform well in detecting malware. In the literature, it is reported that this good performance can depend on a reduced set of network features. This study presents an empirical evaluation of two statistical methods of reduction and selection of features in an Android network traffic dataset using six supervised algorithms: Naïve Bayes, support vector machine, multilayer perceptron neural network, decision tree, random forest, and K-nearest neighbors. The principal component analysis (PCA) and logistic regression (LR) methods with p value were applied to select the most representative features related to the time properties of flows and features of bidirectional packets. The selected features were used to train the algorithms using binary and multiclass classification. For performance evaluation and comparison metrics, precision, recall, F-measure, accuracy, and area under the curve (AUC-ROC) were used. The empirical results show that random forest obtains an average accuracy of 96% and an AUC-ROC of 0.98 in binary classification. For the case of multiclass classification, again random forest achieves an average accuracy of 87% and an AUC-ROC over 95%, exhibiting better performance than the other machine learning algorithms. In both experiments, the 13 most representative features of a mixed set of flow time properties and bidirectional network packets selected by LR were used. In the case of the other five classifiers, their results in terms of precision, recall, and accuracy, are competitive with those obtained in related works, which used a greater number of input features. Therefore, it is empirically evidenced that the proposed method for the selection of features, based on statistical techniques of reduction and extraction of attributes, allows improving the identification performance of malware traffic, discriminating it from the benign traffic of Android applications.

Background: Current evidence indicates that a stem cell-like sub-population within malignant glioblastomas, that overexpress members of the adenosine triphosphate-binding cassette (ABC) family transporters, is responsible for multidrug resistance and tumour relapse. Eradication of the brain tumour stem cell (BTSC) compartment is therefore essential to achieve a stable and long-lasting remission. Methods: Melatonin actions were analysed by viability cell assays, flow cytometry, quantitative PCR for mRNA expression, western blot for protein expression and quantitative and qualitative promoter methylation methods. Results: Combinations of melatonin and chemotherapeutic drugs (including temozolomide, current treatment for malignant gliomas) have a synergistic toxic effect on BTSCs and A172 malignant glioma cells. This effect is correlated with a downregulation of the expression and function of the ABC transporter ABCG2/BCRP. Melatonin increased the methylation levels of the ABCG2/BCRP promoter and the effects on ABCG2/BCRP expression and function were prevented by preincubation with a DNA methyltransferase inhibitor. Conclusion: Our results point out a possible relationship between the downregulation of ABCG2/BCRP function and the synergistic toxic effect of melatonin and chemotherapeutic drugs. Melatonin could be a promising candidate to overcome multidrug resistance in the treatment of glioblastomas, and thus improve the efficiency of current therapies.

The influence of coastal submarine groundwater discharges (SGD) on the distribution and abundance of seagrass meadows was investigated. In 2012, hydrological variability, nutrient variability in sediments and the biotic characteristics of two seagrass beds, one with SGD present and one without, were studied. Findings showed that SGD inputs were related with one dominant seagrass species. To further understand this, a generalized additive model (GAM) was used to explore the relationship between seagrass biomass and environment conditions (water and sediment variables). Salinity range (21–35.5 PSU) was the most influential variable (85%), explaining why H. wrightii was the sole plant species present at the SGD site. At the site without SGD, GAM could not be performed since environmental variables could not explain a total variance of > 60%. This research shows the relevance of monitoring SGD inputs in coastal karstic areas since they significantly affect biotic characteristics of seagrass beds.

Parasitoids are known to exploit volatile cues emitted by plants after herbivore attack to locate their hosts. Feeding and oviposition of a polyphagous herbivore can induce the emission of odor blends that differ among distant plant species, and parasitoids have evolved an incredible ability to discriminate them and locate their hosts relying on olfactive cues. We evaluated the host searching behavior of the egg parasitoid Cosmocomoidea annulicornis (Ogloblin) (Hymenoptera: Mymaridae) in response to odors emitted by two taxonomically distant host plants, citrus and Johnson grass, after infestation by the sharpshooter Tapajosa rubromarginata (Signoret) (Hemiptera: Cicadellidae), vector of Citrus Variegated Chlorosis. Olfactory response of female parasitoids toward plants with no herbivore damage and plants with feeding damage, oviposition damage, and parasitized eggs was tested in a Y-tube olfactometer. In addition, volatiles released by the two host plant species constitutively and under herbivore attack were characterized. Females of C. annulicornis were able to detect and significantly preferred plants with host eggs, irrespectively of plant species. However, wasps were unable to discriminate between plants with healthy eggs and those with eggs previously parasitized by conspecifics. Analysis of plant volatiles induced after sharpshooter attack showed only two common volatiles between the two plant species, indole and β-caryophyllene. Our results suggest that this parasitoid wasp uses common chemical cues released by many different plants after herbivory at long range and, once on the plant, other more specific chemical cues could trigger the final decision to oviposit.

Designing and building molecular machines at the nanometre scale is a conceptual and synthetic challenge. Rotation of a single molecule has been observed but controlling the direction of the rotation has so far proved difficult. The step-by-step rotation of a molecular gear mounted on an atomic-scale axis is now controlled by a scanning tunnelling microscope. Gears are microfabricated down to diameters of a few micrometres. Natural macromolecular motors, of tens of nanometres in diameter, also show gear effects 1 . At a smaller scale, the random rotation of a single-molecule rotor encaged in a molecular stator has been observed 2 , demonstrating that a single molecule can be rotated with the tip of a scanning tunnelling microscope 3 , 4 (STM). A self-assembled rack-and-pinion molecular machine where the STM tip apex is the rotation axis of the pinion was also tested 5 . Here, we present the mechanics of an intentionally constructed molecule-gear on a Au(111) surface, mounting and centring one hexa- t -butyl-pyrimidopentaphenylbenzene molecule on one atom axis. The combination of molecular design, molecular manipulation and surface atomic structure selection leads to the construction of a fundamental component of a planar single-molecule mechanical machine. The rotation of our molecule-gear is step-by-step and totally under control, demonstrating nine stable stations in both directions.

Oncolytic adenoviruses, such as Delta-24-RGD (Δ24RGD), are replication-competent viruses that are genetically engineered to induce selective cancer cell lysis. In cancer cells, Δ24RGD induces massive autophagy, which is required for efficient cell lysis and adenoviral spread. Understanding the cellular mechanisms underlying the regulation of autophagy in cells treated with oncolytic adenoviruses may provide new avenues to improve the therapeutic effect. In this work, we showed that cancer cells infected with Δ24RGDundergo autophagy despite the concurrent activation of the AKT/mTOR pathway. Moreover, adenovirus replication induced sustained activation of JNK proteins in vitro . ERK1/2 phosphorylation remained unchanged during adenoviral infection, suggesting specificity of JNK activation. Using genetic ablation and pharmacological inactivation of JNK, we unequivocally demonstrated that cells infected with Δ24RGD required JNK activation. Thus, genetic co-ablation of JNK1 and JNK2 genes or inhibition of JNK kinase function rendered Δ24RGD–treated cells resistant to autophagy. Accordingly, JNK activation induced phosphorylation of Bcl-2 and prevented the formation of Bcl-2/Beclin 1 autophagy suppressor complexes. Using an orthotopic model of human glioma xenograft, we showed that treatment with Δ24RGD induced phosphorylation and nuclear translocation of JNK, as well as phosphorylation of Bcl-2. Collectively, our data identified JNK proteins as an essential mechanistic link between Δ24RGD infection and autophagy in cancer cells. Activation of JNK without inactivation of the AKT/mTOR pathway constitutes a distinct molecular signature of autophagy regulation that differentiates Δ24RGD adenovirus from the mechanism used by other oncolytic viruses to induce autophagy and provides a new rationale for the combination of oncolytic viruses and chemotherapy.

In this paper, we present a new integration approach for managing Information Technology variables within enterprise architecture in an integrated way. Additionially, a novel method based on fuzzy logic for cause-effect variable analysis is proposed as a useful support decision-making tool for companies in order to know the main actions they must perform for increasing their benefits. This is employed to assess the Integration Management System in Enterprises, based on Enterprise Architecture and Information Technology. We show as fuzzy logic plays an important role in this area due to these variables can be affected for multifactorial elements impregnated with uncertainty. The knowledge given by the experts is translated into dependence rules, which have also been analyzed from a fuzzy point of view using a combination of two fuzzy techniques, namely, fuzzy relation equation theory and fuzzy graph. Firstly, fuzzy dependence rules are computed from fuzzy relation equations and, secondly, an analysis based on incidence subgraph is performed. The result is a strategic plan automatically generated from the data captured of each enterprise in which the most import variables to be improved are detailed.

The fiber-modified adenoviral vector Δ-24-RGD (D24RGD) offers vast therapeutic potential. Direct injection of D24RGD has been used to successfully target ovarian tumors in mice. However, systemic toxicity, especially in the liver, profoundly limits the efficacy of direct viral vector delivery. Mesenchymal stem cells (MSC) have the ability to function as a vector for targeted gene therapy because of their preferential engraftment into solid tumors and participation in tumor stroma formation. We show that MSC-guided delivery of D24RGD is specific and efficient and reduces the overall systemic toxicity in mice to negligible levels compared with D24RGD alone. In our model, we found efficient targeted delivery of MSC-D24RGD to both breast and ovarian cell lines. Furthermore, immunohistochemical staining for adenoviral hexon protein confirmed negligible levels of systemic toxicity in mice that were administered MSC-D24RGD compared with those that were administered D24RGD. These data suggest that delivery of D24RGD through MSC not only increases the targeted delivery efficiency, but also reduces the systemic exposure of the virus, thereby reducing overall systemic toxicity to the host and ultimately enhancing its value as an anti-tumor therapeutic candidate.

Ceftaroline is a broad-spectrum antibiotic with activity against methicillin-resistant Staphylococcus aureus (MRSA) strains. Ceftaroline susceptibility of an MRSA set archived between 1994 and 2003 in the Geneva University Hospitals detected a high percentage (66 %) of ceftaroline resistance in clonotypes ST228 and ST247 and correlated with mutations in PBP2a. The ceftaroline mechanism of action is based on the inhibition of PBP2a; thus, the identification of PBP2a mutations of recently circulating clonotypes in our institution was investigated. We analyzed ceftaroline susceptibility in MRSA isolates (2013 and 2014) and established that resistant strains correlated with PBP2a mutations and specific clonotypes. Ninety-six MRSA strains were analyzed from independent patients and were isolated from blood cultures (23 %), deep infections (38.5 %), and superficial (skin or wound) infections (38.5 %). This sample showed a ceftaroline minimum inhibitory concentration (MIC) range between 0.25 and 2 μg/ml and disk diameters ranging from 10 to 30 mm, with a majority of strains showing diameters ≥20 mm. Based on the European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints, 76 % (73/96) of isolates showed susceptibility to ceftaroline. Nevertheless, we still observed 24 % (23/96) of resistant isolates (MIC = 2 μg/ml). All resistant isolates were assigned to clonotype ST228 and carried the N146K mutation in PBP2a. Only two ST228 isolates showed ceftaroline susceptibility. The decreasing percentage of ceftaroline-resistant isolates in our hospital can be explained by the decline of ST228 clonotype circulating in our hospital since 2008. We present evidence that ceftaroline is active against recent MRSA strains from our hospital; however, the presence of PBP2a variants in particular clonotypes may affect ceftaroline efficacy.