Psoriasis and fibromyalgia: a systematic review

Psoriasis is a chronic inflammatory cutaneous condition characterized by several comorbidities, including musculoskeletal disorders. While the association with psoriatic arthritis has been widely addressed in literature, the aim of the present systematic review was to identify all available evidence on the relationship between psoriasis and fibromyalgia, a musculoskeletal syndrome primarily characterized by chronic widespread pain. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and MedLine and Web of Science (WOS) databases were searched for literature up to March 2023. After the removal of duplicate records, a total of 11 articles were deemed eligible for inclusion in a qualitative synthesis. Our results suggested that psoriatic patients had a higher prevalence of fibromyalgia (8–30%), with a very high impact on symptoms of psoriasis. Moreover, fibromyalgic patients had a slightly increased prevalence of psoriasis (2.2–6.7%) compared to the control groups. Finally, several studies demonstrated the substantial impact of fibromyalgia on psoriatic outcome measures in patients with concomitant psoriatic arthritis. In conclusion, available data support a potential interplay between psoriasis and fibromyalgia, but further research is encouraged in this area. © 2024 by the authors

Evoluzioni normative e giurisprudenziali in materia di giuoco con vincita di denaro

L’articolo esamina l’evoluzione della normativa e della giurisprudenza costituzionale in materia di giuoco con vincita di denaro in Italia. Si evidenzia come la “liberalizzazione” del settore, avvenuta a partire dagli anni ’90, con la conseguente diffusione del giuoco abbia fatto emergere una pluralità di valori costituzionali e di conseguenza la necessità di un loro bilanciamento, da parte del legislatore e della Corte costituzionale.The article examines the evolution of legislation and constitutional decisions regarding gambling in Italy. It highlights how the "liberalization" of the sector, which began in the 1990s, and the consequent spread of gambling, have brought to light a plurality of constitutional values, thus necessitating a balancing act by both the legislature and the Constitutional Court

De novo assembly and annotation of Popillia japonica’s genome with initial clues to its potential as an invasive pest

Background The spread of Popillia japonica in non-native areas (USA, Canada, the Azores islands, Italy and Switzerland) poses a significant threat to agriculture and horticulture, as well as to endemic floral biodiversity, entailing that appropriate control measures must be taken to reduce its density and limit its further spread. In this context, the availability of a high quality genomic sequence for the species is liable to foster basic research on the ecology and evolution of the species, as well as on possible biotechnologically-oriented and genetically-informed control measures. Results The genomic sequence presented and described here is an improvement with respect to the available draft sequence in terms of completeness and contiguity, and includes structural and functional annotations. A comparative analysis of gene families of interest, related to the species ecology and potential for polyphagy and adaptability, revealed a contraction of gustatory receptor genes and a paralogous expansion of some subgroups/subfamilies of odorant receptors, ionotropic receptors and cytochrome P450s. Conclusions The new genomic sequence as well as the comparative analyses data may provide a clue to explain the staggering invasive potential of the species and may serve to identify targets for potential biotechnological applications aimed at its control

Exposure to nanoplastics and nanomaterials either single and combined affects the gill-associated microbiome of the Antarctic soft-shelled clam Laternula elliptica

Nanoplastics and engineering nanomaterials (ENMs) are contaminants of emerging concern (CECs), increasingly being detected in the marine environment and recognized as a potential threat for marine biota at the global level including in polar areas. Few studies have assessed the impact of these anthropogenic nanoparticles in the microbiome of marine invertebrates, however combined exposure resembling natural scenarios has been overlooked. The present study aimed to evaluate the single and combined effects of polystyrene nanoparticles (PS NP) as proxy for nanoplastics and nanoscale titanium dioxide (nano-TiO2) on the prokaryotic communities associated with the gill tissue of the Antarctic soft-shell clam Laternula elliptica, a keystone species of marine benthos Wild-caught specimens were exposed to two environmentally relevant concentrations of carboxylated PS NP (PS-COOH NP, ∼62 nm size) and nano-TiO2 (Aeroxide P25, ∼25 nm) as 5 and 50 μg/L either single and combined for 96h in a semi-static condition.Our findings show a shift in microbiome composition in gills of soft-shell clams exposed to PS NP and nano-TiO2 either alone and in combination with a decrease in the relative abundance of OTU1 (Spirochaetaceae). In addition, an increase of gammaproteobacterial OTUs affiliated to MBAE14 and Methylophagaceae (involved in ammonia denitrification and associated with low-quality water), and the OTU Colwellia rossensis (previously recorded in polluted waters) was observed. Our results suggest that nanoplastics and nano-TiO2 alone and in combination induce alterations in microbiome composition by promoting the increase of negative taxa over beneficial ones in the gills of the Antarctic soft-shell clam. An increase of two low abundance OTUs in PS-COOH NPs exposed clams was also observed. A predicted gene function analysis revealed that sugar, lipid, protein and DNA metabolism were the main functions affected by either PS-COOH NP and nano-TiO2 exposure. The molecular functions involved in the altered affiliated OTUs are novel for nano-CEC exposures

An Efficient Ray-Based Modeling Approach for Scattering from Reconfigurable Intelligent Surfaces

Reconfigurable Intelligent Surfaces (RISs), which can be implemented using metasurface technology or reflect/ transmit antenna array technology, have garnered significant attention in research studies focused on both their technological aspects and potential applications. While various modeling approaches have been proposed - ranging from electromagnetic simulations and analytical integral formulations to simplified approaches based on scattering matrix theory - there remains a great need for efficient and electromagnetically-consistent macroscopic models that can accurately simulate scattering from RISs, particularly for realistic simulations of RIS-based wireless networks. Building on previous work based on the characterization of the RIS through a surface impedance (or spatial modulation) function and a few parameters, in the present paper we propose a fully ray-based approach for the computation of the re-radiated field that can be easily embedded in efficient, forward ray tracing (also known as ray launching) models. We validate the proposed model by comparison to well established methods available in the literature. Results show that, although the considered method is based on a completely different formulation and is much more efficient than integral formulation methods, results are almost indistinguishable in some benchmark cases

The Enigma of Norbormide, a Rattus-Selective Toxicant

Norbormide (NRB) is a Rattus-selective toxicant, which was serendipitously discovered in 1964 and formerly marketed as an eco-friendly rodenticide that was deemed harmless to non-Rattus species. However, due to inconsistent efficacy and the emergence of second-generation anticoagulants, its usage declined, with registration lapsing in 2003. NRBs' lethal action in rats entails irreversible vasoconstriction of peripheral arteries, likely inducing cardiac damage: however, the precise chain of events leading to fatality and the target organs involved remain elusive. This unique contractile effect is exclusive to rat arteries and is induced solely by the endo isomers of NRB, hinting at a specific receptor involvement. Understanding NRB's mechanism of action is crucial for developing species-selective toxicants as alternatives to the broad-spectrum ones currently in use. Recent research efforts have focused on elucidating its cellular mechanisms and sites of action using novel NRB derivatives. The key findings are as follows: NRB selectively opens the rat mitochondrial permeability transition pore, which may be a factor that contributes to its lethal effect; it inhibits rat vascular K-ATP channels, which potentially controls its Rattus-selective vasoconstricting activity; and it possesses intracellular binding sites in both sensitive and insensitive cells, as revealed by fluorescent derivatives. These studies have led to the development of a prodrug with enhanced pharmacokinetic and toxicological profiles, which is currently undergoing registration as a novel efficacious eco-sustainable Rattus-selective toxicant. The NRB-fluorescent derivatives also show promise as non-toxic probes for intracellular organelle labelling. This review documents in more detail these developments and their implications

Composite Graph Neural Networks for Molecular Property Prediction

Graph Neural Networks have proven to be very valuable models for the solution of a wide variety of problems on molecular graphs, as well as in many other research fields involving graph-structured data. Molecules are heterogeneous graphs composed of atoms of different species. Composite graph neural networks process heterogeneous graphs with multiple-state-updating networks, each one dedicated to a particular node type. This approach allows for the extraction of information from s graph more efficiently than standard graph neural networks that distinguish node types through a one-hot encoded type of vector. We carried out extensive experimentation on eight molecular graph datasets and on a large number of both classification and regression tasks. The results we obtained clearly show that composite graph neural networks are far more efficient in this setting than standard graph neural networks

Studio degli effetti della vegetazione sulla stabilità dei pendii e sullo sviluppo delle frane superficiali

Rainfall-induced shallow landslides are among the most common gravitational mass movements on natural and artificial slopes; due to high frequency, high propagation velocity and lack of warning signs represent one of the most dangerous and destructive instability phenomena occurring in the world. The interest of the scientific community in this process has grown in the last three decades with the aim to perform shallow landslide susceptibility assessments at regional scale. The assessment of shallow landslide susceptibility by physically based methods usually focus on the parametrization of hydraulic and geotechnical features of soils, while the role of vegetation is generally overlooked. Instead the implementation of shallow landslide susceptibility models should consider both the engineering geological properties and vegetational characters of hillslope deposits. In this PhD thesis a fieldwork-based method is proposed to acquire, process and spatialize engineering geological, above-ground and below-ground vegetation features of hillslope deposits. The main goal of this research consists on characterizing the comprehensive role (at both macro and micro-scale) of vegetation towards the occurrence of shallow landslides. The thesis is organized in the following main topics: characterization of engineering geological properties and vegetational features of hillslope deposits in stable and unstable areas (i.e., shallow landslides), assessment of the correlations between structural roots cell components and shallow landslides occurrence through the application of spectroscopic techniques, implementation and comparison of shallow landslide susceptibility modelling by means of two different physically-based methods (pSHALSTAB and SlideforMAP susceptibility models) which differ in the implementation of the vegetation contribution. The study areas are both the Garfagnana and Cardoso basins (Northern Apennines, Italy). The Garfagnana study area extends for about 240 km2 along the Serchio River valley, parallel to the eastern margin of the Apuan Alps and the Northern Apennines Ridge, reaching the maximum altitude of about 1985 m a. s. l., with an average slope of 25°. The Cardoso study area (≃ 13 km2) is a small mountain sub-basin of the Versilia river located in the southern Apuan Alps, reaching the maximum altitude of 1858 m a. s. l., with an average slope of 38°. Fieldwork and laboratory tasks aimed at mapping engineering geology and vegetational characters of hillslope deposits were carried out for a set of hundreds of measurement sites, with the acquisition of hillslope deposit depth, geotechnical horizons, unit weight, above-ground and below-ground vegetation features as well as soil and roots samples for laboratory analysis. Root samples were analyzed through the implementation of different spectroscopic techniques (Raman, Fourier Transform Infrared-FTIR and elemental Laser Induced Breakdown Spectroscopy-LIBS). In order to obtain the map distribution of engineering geology parameters, a spatial analysis has been performed by clustering morphometric variables stratified as a function of bedrock lithological units. As for the below-ground vegetation results, the application of the Root Bundle Model (RBMw) showed that the lateral root reinforcement slightly increases with increasing stem size and slightly decreases with increasing distances from the stem. According to the RBMw results, most of the basal root reinforcement concentrates in the shallower slope deposit layers and decreases sharply with increasing depth. Differences in terms of root density (RAR) moving from unstable (i.e., shallow landslides) to more stable locations were observed. In order to implement the lateral root reinforcement into the infinite slope model and limit equilibrium approach the new parameter “equivalent root cohesion” has been defined. This parameter considering both the lateral root depth and the extension of the shallow landslide basal surface, shows magnitudes (few kPa) of the additional root cohesion commonly adopted in the literature. Root density data showed a moderate relationship with the hillslope deposit saturated hydraulic conductivity, with a decrease of root density and saturated hydraulic conductivity as the distance from the tree increases and the hillslope deposit depth increases. Differences in terms of lignin, cellulose and nutrient contents moving from unstable (i.e., shallow landslides) to more stable locations were observed using Raman, FTIR and LIBS techniques. Based on these experimental results spectroscopic portable techniques might be suitable to detect differences in the biochemical composition of wood depending on vegetational parameters, as well as to provide information for shallow landslide prediction. Shallow landslide susceptibility analysis was performed using two different physically based models: pSHALSTAB and SlideforMAP. The comparison between modelled unstable areas and the distribution of observed landslides was quantitatively performed in terms of ROC curve analysis. Performances of both models are comparable or even better than other physically based models described in literature, with AUROC values higher than 0.7 (numeric threshold generally considered as a reasonable prediction). Despite the fact that, especially for the SlideforMAP model, the bedrock geology controls the quality of the output maps (with lower reliability resulting for carbonate bedrock areas), the application of SlideforMAP allowed us to simulate different vegetation scenarios related to the Garfagnana basin and to depict protective and potential forests, suggesting the application of this model as a reliable tool in sustainable forest management and bioengineering studies

Modeling and Analyzing Reaction Systems in Maude

Reaction Systems (RSs) are a successful computational framework for modeling systems inspired by biochemistry. An RS defines a set of rules (reactions) over a finite set of entities (e.g., molecules, proteins, genes, etc.). A computation in this system is performed by rewriting a finite set of entities (a computation state) using all the enabled reactions in the RS, thereby producing a new set of entities (a new computation state). The number of entities in the reactions and in the computation states can be large, making the analysis of RS behavior difficult without a proper automated support. In this paper, we use the Maude language-a programming language based on rewriting logic-to define a formal executable semantics for RSs, which can be used to precisely simulate the system behavior as well as to perform reachability analysis over the system computation space. Then, by enriching the proposed semantics, we formalize a forward slicer algorithm for RSs that allows us to observe the evolution of the system on both the initial input and a fragment of it (the slicing criterion), thus facilitating the detection of forward causality and influence relations due to the absence/presence of some entities in the slicing criterion. The pursued approach is illustrated by a biological reaction system that models a gene regulation network for controlling the process of differentiation of T helper lymphocytes