CD40 cross-linking induces migration of renal tumor cell through nuclear factor of activated T cells (NFAT) activation

CD40 crosslinking plays an important role in regulating cell migration, adhesion and proliferation in renal cell carcinoma (RCC). CD40/CD40L interaction on RCC cells activates different intracellular pathways but the molecular mechanisms leading to cell scattering are not yet clearly defined. Aim of our study was to investigate the main intracellular pathways activated by CD40 ligation and their specific involvement in RCC cell migration. CD40 ligation increased the phosphorylation of extracellular signal-regulated kinase (ERK), c-Jun NH (2)-terminal kinase (JNK) and p38 MAPK. Furthermore, CD40 crosslinking activated different transcriptional factors on RCC cell lines: AP-1, NFkB and some members of the Nuclear Factor of Activated T cells (NFAT) family. Interestingly, the specific inhibition of NFAT factors by cyclosporine A, completely blocked RCC cell motility induced by CD40 ligation. In tumor tissue, we observed a higher expression of NFAT factors and in particular an increased activation and nuclear migration of NFATc4 on RCC tumor tissues belonging to patients that developed metastases when compared to those who did not. Moreover, CD40-CD40L interaction induced a cytoskeleton reorganization and increased the expression of integrin β1 on RCC cell lines, and this effect was reversed by cyclosporine A and NFAT inhibition. These data suggest that CD40 ligation induces the activation of different intracellular signaling pathways, in particular the NFATs factors, that could represent a potential therapeutic target in the setting of patients with metastatic RCC

Development of a mathematical model for online microextraction by packed sorbent under equilibrium conditions and its application for polycyclic aromatic hydrocarbon determination in water by gas chromatography–mass spectrometry

In this work, partition equilibriums and extraction rates of different polycyclic aromatic hydrocarbons (PAHs) have been calculated by multivariate nonlinear regression from data obtained after microextraction by packed sorbent (MEPS) of 16 PAHs from water samples. The MEPS gas chromatography-mass spectrometry (MEPS-GC-MS) method has been optimized investigating the partitioning parameters for a priori prediction of solute sorption equilibrium, recoveries, pre-concentration effects in aqueous and solvent systems. Finally, real samples from sea, agricultural irrigation wells, streams and tap water were analyzed. Detection (S/N ≥ 3) and quantification (S/N ≥ 10) limits were strictly dependent on the volume of water and methanol used during the extraction process. Under the experimental conditions used, these values range from 0.5 to 2 ng L^(-1) and from 1.6 to 6.2 ng L^(-1), respectively. The reasonably good correlation between the logarithm of the partition MEPS-water constants (log K_(meps/water) ) and the logarithm of the octanol-water partition coefficients (log K_(ow) ) (R^2 = 0.807) allows a rough estimation of K ow from the measure of K_(meps/water)

Discovery privacy threats via device de-anonymization in LoRaWAN

LoRaWAN (Long Range WAN) is one of the well-known emerging technologies for the Internet of Things (IoT). Many IoT applications involve simple devices that transmit their data toward network gateways or access points that, in their turn, redirect data to application servers. While several security issues have been addressed in the LoRaWAN specification v1.1, there are still some aspects that may undermine privacy and security of the interconnected IoT devices. In this paper, we tackle a privacy aspect related to LoRaWAN device identity. The proposed approach, by monitoring the network traffic in LoRaWAN, is able to derive, in a probabilistic way, the unique identifier of the IoT device from the temporal address assigned by the network. In other words, the method identifies the relationship between the LoRaWAN DevAddress and the device manufacturer DevEUI. The proposed approach, named DEVIL (DEVice Identification and privacy Leakage), is based on temporal patterns arising in the packets transmissions. The paper presents also a detailed study of two real datasets: i) one derived by IoT devices interconnected to a prominent network operator in Italy; ii) one taken from the literature (the LoED dataset in Bhatia et al. (2020)). DEVIL is evaluated on the first dataset while the second is analyzed to support the hypothesis under the DEVIL operation. The results of our analysis, compared with other literature approaches, show how device identification through DEVIL can expose IoT devices to privacy leakage. Finally, the paper also provides some guidelines to mitigate the user re-identification threats

Determination of essential and toxic element in south and central italian honey samples by inductively coupled plasma mass spectrometry.

According to the definition set by the European Union Council Directive 2001/110/EC, “honey is the natural sweet substance produced by honey bees, Apis mellifera, from the nectar of plants (blossoms) or from the secretions of living parts of plants or excretions of plant sucking insects on the living parts of plants, which honey bees collect, transform by combining with specific substances of their own, deposit, dehydrate, store and leave in the honey comb to ripen and mature.” Honeybees are continuously exposed to potential pollutants present in widespread foraging areas, and the influence of industrial pollution on bee health has been widely documented (Leita, Muhlbachova,Cesco, Barbattini, & Mondini, 1996). This makes honey a matter of interest in food safety studies, particularly bearing in mind that the majority of consumers are children. Honey is composed mainly from carbohydrates (75%), lesser amounts of water and a great number of minor components. Minor constituents include enzymes, acids, essential and toxic metals and unidentified substances. Regarding metal contents, previous investigations have shown that their presence depend mainly on the botanical origin of honey, light blossom honeys having a lower content than dark honeys, e.g. honeydew, chestnut and heather (Gonzalez-Miret et al. 2005). In order to assure food safety, honey should have a low content of undesirable contaminants (Frazzoli, D'Ilio, & Bocca, 2007). Inductively coupled plasma-based techniques (ICP-AES and ICP-MS) have been applied as multi-elemental techniques for the determination of heavy metals in honey and other sweeteners (Frazzoli, D'Ilio, & Bocca, 2007). These techniques enabled the determination of heavy metals and trace elements in honey owing to their wide range linearity, superior sensitivity and high efficiency. The aims of this study were the identification and quantification of toxic and essential elements in 70 honey samples collected from 10 different provinces of Central and South Italy. The content level of 24 elements (Hg, Tl, Pb, Cd, Cr, U, Ti, Ba, Sb, Al, As, V, Ge, Sn, Be, Sr, Ca, Fe, Mn, Co, Zn, Cu, Se, Mo) were determined using Microwave Assisted Extraction coupled with Inductively Coupled Plasma Mass Spectrometry (MAE-ICP-MS). Results demonstrated that although samples are not completely contaminant free, heavy metal intake from honey is well below the recommended dose. Furthermore, chemometric methods highlighted differences among honeys depending from their geographical and botanical origins

Effects of different Surface Treatments on Physicochemical and Biochemical Porperties in Canestrato Pugliese Cheese During Ripening

SALAMANCA (SPAIN

Essential oil characterization of Prunus spinosa L., Salvia officinalis L., Eucalyptus globulus L., Melissa officinalis L. and Mentha x piperita L. by a volatolomic approach

In this study a volatolomic approach is proposed for the characterization of the volatile organic compound (VOC) composition of essential oils (EOs) extracted from common aromatic plants. Five species (Prunus spinosa L., Salvia officinalis L., Eucalyptus globulus L., Melissa officinalis L. and Mentha x piperita L.), particularly widespread in Southern Italy, were selected as recognized sources of natural bioactive compounds with beneficial properties. Hydro distillation and solid-liquid extraction with ethanol at different percentages were used to obtain EOs, and their extraction capabilities were compared analyzing chromatographic profiles obtained by headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography - mass spectrometry (GC-MS). The analytical procedure was optimized in term of SPME fiber, adsorption time and desorption time. GC-MS analyses were performed allowing the profiling of the VOC fingerprint in each plant extract. Experimental data were processed by a statistical multivariate approach (Analysis of Variance and Principal Component Analysis obtained for compounds and chemical classes), confirming that EO aroma profiles were statistically different for each of the selected five plants. The proposed volatolomic approach has proved to be an easy and efficient tool to study the aroma profile, allowing the collection of specific information and opening new perspectives and opportunities for the detection and identification of VOCs in agricultural and ecological applications

Influenza delle Muffe sulla Qualità del Canestrato Pugliese

CERNOBBIO (COMO