Investigation of the sequence constitution of miRNA and siRNA

MicroRNAs (miRNAs) and small-interfering RNAs (siRNAs) are small non-coding RNAs that play important regulatory roles in animals and plants. The primary sequences of 9164 miRNAs and 14238 siRNAs were analyzed to determine the occurrence of each nucleotide in specific positions of the sequences. The results show that there are positions in which the composition is not completely random. In general the nucleotide cytosine is underrepresented in both miRNA and siRNA sequences, while the nucleotides uracil and adenine are overrepresented in miRNAs and siRNAs, respectively. Possible implications between these findings and the biological functions of small non-coding RNAs are discussed.Keywords: microRNA, RNA primary sequence, ur

The compositional and mineralogical analysis of fired pigments in Nasca pottery from Cahuachi (Peru) by the combined use of the portable PIXE-alpha and portable XRD techniques

Abstract An analytical protocol based on the combined use of the portable PIXE-alpha (Particle Induced X-ray Emission) and XRD (X-ray Diffraction) non destructive techniques developed at the LANDIS laboratory (Laboratorio di Analisi Non Distruttive) of the INFN–CNR (Istituto Nazionale di Fisica Nucleare–Consiglio Nazionale delle Ricerche) in Catania (Italy), was applied for the characterisation of the surface paints of some archaeological fragments of Nasca pottery from the Ceremonial Centre of Cahuachi in Southern Peru. Measurements were carried out on the black, white, red, orange and grey pigments; quantitative information on the chemical composition as well as on the mineralogical phases present on the paints were obtained. Results allowed to make some considerations about the materials and the manufacturing technique used to realise such fired pigments. It should be noted that during firing the precursor minerals composing the pigments undergo a phase transformation and their identification presents some difficulties

Phenolic composition of hydrophilic extract of manna from sicilian Fraxinus angustifolia vahl and its reducing, antioxidant and anti-inflammatory activity in vitro

Manna, a very singular vegetable product derived from the spontaneous solidification of the sap of some Fraxinus species, has long been known for its mild laxative and emollient properties. In this work, a hydro-alcoholic extract of manna (HME) from Sicilian Fraxinus angustifolia Vahl was investigated using HPLC-DAD to find phenol components and using chemical and biological in vitro assays to determine its reducing, antioxidant and anti-inflammatory capacity. We identified elenolic acid, tyrosol, hydroxytyrosol, catechin, fraxetin, verbascoside, gallic acid, procyanidin-B1, and luteolin 3,7 glucoside, in order of abundance. Measurements of total antioxidant activity by Folin-Ciocalteu reaction and ferric reducing ability (FRAP), as well as of scavenger activity towards ABTS•+, DPPH•, and perferryl-myoglobin radicals, showed that the phytocomplex effectively reduced oxidants with different standard potentials. When compared with vitamin E, HME also behaved as an efficient chain-breaking antioxidant against lipoperoxyl radicals from methyl linoleate. In cellular models for oxidative stress, HME counteracted membrane lipid oxidation of human erythrocytes stimulated by tert-butyl hydroperoxide and prevented the generation of reactive oxygen species, as well as the GSH decay in IL-1β–activated intestinal normal-like cells. Moreover, in this in vitro intestinal bowel disease model, HME reduced the release of the pro-inflammatory cytokines IL-6 and IL-8. These findings may suggest that manna acts as an antioxidant and anti-inflammatory natural product in humans, beyond its well-known effects against constipation

The 3550 year BP-1944 A.D.magma-plumbing system of Somma-Vesuvius: constraints on its behaviour and present state through a review of Sr-Nd isotope data

Vesuvius, dominating the densely-populated Neapolitan area, is one of the most dangerous volcanoes in the World. Its destructive power derives from energetic subplinian and plinian eruptions, such as the one which occurred in 79 A.D. Generally such large-scale events follow a long period of quiescence; a behaviour interpreted as the gradual build-up of magma volumes between periods of major activity. After the 1631 subplinian eruption until the last 1944 A.D. eruption, it experienced an almost continuous and less energetic explosive/effusive activity. The erupted magmas are characterized by undersaturated potassic to ultrapotassic nature, and compositional and Sr-isotopic variability. Furthermore geobarometric studies indicate two different crystallization depths located at 4 and >11 km, respectively. According to most of the recent literature, the eruptions were triggered by the injection in a shallower magma chamber, of isotopically distinct magma batches derived from heterogeneous mantle source(s) and/or contamination processes occurred within the deep reservoir. In our review of petrochemical data, we consider the period between the 3550 years BP plinian eruption and the 472 A.D. sub-plinian eruption, which includes 79 A.D. event, and the most recent period of activity which started in 1631 A.D. and lasted up to the 1944 A.D. eruption, characterized by a near continuous effusive/explosive activity. For both periods we identify a correlation between Sr-isotopical features of magmas and their crystallization depth. In particular, we show that pyroxenes have Sr-isotopic ratios lower than 0.7074 and an equilibrium crystallization depth of 22-11 km. Moreover feldspars have higher 87Sr/86Sr values (0.7075-7) and an equilibrium crystallization depth of about 4 km. Therefore the most radiogenic magmas did not derive from a deeper reservoir but their higher Sr-isotopic ratios have been acquired at a shallower depth likely by crustal contamination during magma evolution. In contrast, the lower Sr-isotope compositions characterise the less contaminated magmas coming from deeper crustal levels. On the basis of this evidence, the temporal Sr-isotopical variation of magma which erupted in the 1631-1944 A.D. period probably derives from the progressive withdrawal of the shallow magma chamber, which was completely empty before the 1805-1944 A.D. period of volcanism. Therefore the effusive and explosive events of the most recent 1805-1944 A.D. period were fed directly by the deep reservoir located at a depth exceding 11 km

Human mobility from theory to practice: Data, models and applications

The inclusion of tracking technologies in personal devices opened the doors to the analysis of large sets of mobility data like GPS traces and call detail records. This tutorial presents an overview of both modeling principles of human mobility and machine learning models applicable to specific problems. We review the state of the art of five main aspects in human mobility: (1) human mobility data landscape; (2) key measures of individual and collective mobility; (3) generative models at the level of individual, population and mixture of the two; (4) next location prediction algorithms; (5) applications for social good. For each aspect, we show experiments and simulations using the Python library "scikit-mobility" developed by the presenters of the tutorial

Understanding peace through the world news

Peace is a principal dimension of well-being and is the way out of inequity and violence. Thus, its measurement has drawn the attention of researchers, policymakers, and peacekeepers. During the last years, novel digital data streams have drastically changed the research in this field. The current study exploits information extracted from a new digital database called Global Data on Events, Location, and Tone (GDELT) to capture peace through the Global Peace Index (GPI). Applying predictive machine learning models, we demonstrate that news media attention from GDELT can be used as a proxy for measuring GPI at a monthly level. Additionally, we use explainable AI techniques to obtain the most important variables that drive the predictions. This analysis highlights each country’s profile and provides explanations for the predictions, and particularly for the errors and the events that drive these errors. We believe that digital data exploited by researchers, policymakers, and peacekeepers, with data science tools as powerful as machine learning, could contribute to maximizing the societal benefits and minimizing the risks to peace.Peace is a principal dimension of well-being and is the way out of inequity and violence. Thus, its measurement has drawn the attention of researchers, policymakers, and peacekeepers. During the last years, novel digital data streams have drastically changed the research in this field. The current study exploits information extracted from a new digital database called Global Data on Events, Location, and Tone (GDELT) to capture peace through the Global Peace Index (GPI). Applying predictive machine learning models, we demonstrate that news media attention from GDELT can be used as a proxy for measuring GPI at a monthly level. Additionally, we use explainable AI techniques to obtain the most important variables that drive the predictions. This analysis highlights each country’s profile and provides explanations for the predictions, and particularly for the errors and the events that drive these errors. We believe that digital data exploited by researchers, policymakers, and peacekeepers, with data science tools as powerful as machine learning, could contribute to maximizing the societal benefits and minimizing the risks to peace