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Abstract Background Plankton is the essential ecological category that occupies the lower levels of aquatic trophic networks, representing a good indicator of environmental change. However, most studies deal with distribution of single species or taxa and do not take into account the complex of biological interactions of the real world that rule the ecological processes. Results This study focused on analyzing Antarctic marine phytoplankton, mesozooplankton, and microzooplankton, examining their biological interactions and co-existences. Field data yielded 1053 biological interaction values, 762 coexistence values, and 15 zero values. Six phytoplankton assemblages and six copepod species were selected based on their abundance and ecological roles. Using 23 environmental descriptors, we modelled the distribution of taxa to accurately represent their occurrences. Sampling was conducted during the 2016–2017 Italian National Antarctic Programme (PNRA) ‘P-ROSE’ project in the East Ross Sea. Machine learning techniques were applied to the occurrence data to generate 48 predictive species distribution maps (SDMs), producing 3D maps for the entire Ross Sea area. These models quantitatively predicted the occurrences of each copepod and phytoplankton assemblage, providing crucial insights into potential variations in biotic and trophic interactions, with significant implications for the management and conservation of Antarctic marine resources. The Receiver Operating Characteristic (ROC) results indicated the highest model efficiency, for Cyanophyta (74%) among phytoplankton assemblages and Paralabidocera antarctica (83%) among copepod communities. The SDMs revealed distinct spatial heterogeneity in the Ross Sea area, with an average Relative Index of Occurrence values of 0.28 (min: 0; max: 0.65) for phytoplankton assemblages and 0.39 (min: 0; max: 0.71) for copepods. Conclusion The results of this study are essential for a science-based management for one of the world’s most pristine ecosystems and addressing potential climate-induced alterations in species interactions. Our study emphasizes the importance of considering biological interactions in planktonic studies, employing open access and machine learning for measurable and repeatable distribution modelling, and providing crucial ecological insights for informed conservation strategies in the face of environmental change.

In type 2 diabetes (T2D), several differences have been described between men and women, concerning risk factors, clinical manifestations and chronic complications. The impact of gender on the efficacy and safety of hypoglycaemic drugs is still to be clarified. Some data suggest that GLP1-RAs may have greater efficacy on body weight in women, but comparable efficacy on glycaemic control and cardiovascular risk (CVD) in both sexes. The aim of our study was to evaluate in real-life clinical practice the possible influence of gender on the effectiveness and safety of GLP1-RAs long-acting therapy in T2D outpatients. In this single-centre observational study, we evaluated laboratory parameters, chronic complications, hypoglycaemic episodes, and any adverse events of subjects with T2D who started treatment with GLP1-RAs long-acting between 1 June 2018 and 31 May 2019, in add on to metformin or other hypoglycaemic drugs, and who practiced this therapy for at least two years. In the present analysis, 391 subjects with T2D were included (men 59.3%, women 40.7%), with a mean age of 64.1 years and mean duration of diabetes of 18.4 years. At baseline, patients were on average obese (BMI 32.8 kg/m2) with an inadequate glycaemic control (HbA1c 7.8%). Women had higher BMI values than men; glycaemic control was similar in both genders. After two years of follow-up, therapy with GLP1-RAs long-acting determined a significant reduction of BMI and blood pressure values, HbA1c, fasting glucose and GPT levels and an improvement in lipid profile. The reduction observed in BMI values was significantly greater in T2D women than in men. At stepwise regression analysis, female gender was among the independent predictors of the effectiveness of GLP1-RAs in terms of BMI reduction, together with fasting blood glucose, but not in terms of reduction of HbA1c levels, which was significantly associated with baseline blood glucose levels and metformin use, irrespective of gender. Overall, the treatment with GLP1-RAs was well tolerated, and only mild gastro-intestinal adverse events were observed (n=22; 5.6%, 14 men and 12 women P0.05), in both genders. In conclusion, in real-life clinical practice, the therapy with GLP1-RAs long-acting is safe and effective in both men and women, and it seems to be associated with a more beneficial effect on body weight in women than in men.

The ubiquitous presence of microplastics (MPs) in the environment is a major concern for the conservation of biodiversity. Numerous studies show the detrimental effects of MPs on marine species, especially because of their small size and their capacity to absorb organic contaminants from their surroundings. The bivalve mollusk Cerastoderma glaucum (Bruguière, 1789), because of its wide geographic distribution and immobile feeding habits, can be used as a sentinel and bioindicator species. By examining the presence, localization, and co-localization of Toll-like receptor 2 (TLR2) and inducible nitric oxide synthetase (iNOS), this study aims to evaluate the response of the internal defense system of C. glaucum to pristine MPs through the employment of confocal microscopy and bioinformatics techniques. The results show haemocytes immunoreactive to the antibodies tested; in particular, a higher number of TLR2-positive haemocytes can be observed in the group exposed to pristine MPs. These findings suggest that haemocytes can play a key biomarker role as sentinels to environmental pollutants. Furthermore, bioinformatics analyses on the antibodies tested confirmed an evolutionary conservation of these molecules. These data highlight the critical role of phagocytosis in identifying ecosystem damage and are helpful in developing biosensors with less negative effects on the environments in which they are applied.

Acoustic data were collected by means of Simrad EK60 scientific echosounder on board the research vessel “Italica” in the Ross Sea during the 2016/2017 austral summer as part of the P-Rose and CELEBeR projects, within the framework of the Italian National Research Program in Antarctica (PNRA). Sampling activities also involved the collection of vertical hydrological profiles using the SBE 9/11plus oceanographic probe. Acoustic data were processed to extract three specific scattering structures linked to Euphausia superba, Euphausia crystallorophias and the so called Sound-Scattering Layers (SSLs; continuous and low-density acoustic structures constituted by different taxa). Four different sectors of the study area were considered: two southern coastal sectors (between the Drygalski Ice Tongue and Coulman Island), a northern sector (~30 nmi East of Cape Hallett) and an offshore one spanning about 2 degrees of latitude from Coulman Island south to the Drygalski Ice Tongue. The vertical structure of each group in each area was then analyzed in relation to the observed environmental conditions. Obtained results highlighted the presence of different vertical structures (both environmental and acoustic) among areas, except for the two southern coastal sectors that were found similar. GAM modelling permitted to evidence specific relationships between the environmental factors and the vertical distribution of the considered acoustic groups, letting to hypothesize the presence of trophic relationships and differences in SSL species composition among areas. The advantages of acoustic techniques to implement opportunistic monitoring strategies in endangered ecosystems are also discussed.

Studies based on fish early life stages can provide information on spawning grounds and nursery areas, helping to determine the implications for stock biomass fluctuations of recruitment variability. This study describes the composition, abundance, spatial distribution and differences in day/night vertical distribution of ichthyoplankton in the southern Adriatic Sea. Samples were collected within the framework of the COCONET project (Towards COast to COast NETworks of marine protected areas) from 9 to 18 May 2013 by the R/V Urania, using the electronic multinet EZ-NET BIONESS (Bedford Institute of Oceanography Net Environmental Sampling System). A total of 20 species, belonging to 20 genera and 13 families, were identified. Of the collected larvae, 74.3% were meso- or bathypelagic species, 24.7% were epipelagic and 0.9% were demersal. The community was dominated by Gonostomatidae, followed by Engraulidae, Myctophidae and Photychthaidae. The most abundant species was Cyclothone braueri (45.6%), followed by Engraulis encrasicolus, Ceratoscopelus maderensis, Cyclothone pygmaea, Vinciguerria attenuata and Myctophum punctatum. An inshore/offshore increasing gradient in biodiversity and abundance was observed. Different weighted mean depths (WMDs) were observed for larvae and juveniles. No diel vertical migrations were observed. The high abundance of meso- or bathypelagic species in the upper 100 m confirms the epipelagic zone as an important environment for the development of the larval stages of these fish.

Abstract Background The genus Sporothrix belongs to the order Ophiostomatales and contains mainly saprobic soil and plant fungi, although pathogenic species capable of causing human infections are also present. The whole-genomes of disease-causing species have already been sequenced and annotated but no comprehensive genomic resources for environmental Sporothrix species are available, thus limiting our understanding of the evolutionary origin of virulence-related genes and pathogenicity. Result The genome assembly of four environmental Sporothrix species resulted in genome size of ~ 30.9 Mbp in Sporothrix phasma, ~ 35 Mbp in S. curviconia, ~ 38.7 Mbp in S. protearum, and ~ 39 Mbp in S. variecibatus, with a variable gene content, ranging from 8142 (S. phasma) to 9502 (S. variecibatus). The analysis of mobile genetic elements showed significant differences in the content of transposable elements within the sequenced genomes, with the genome of S. phasma lacking several class I and class II transposons, compared to the other Sporothrix genomes investigated. Moreover, the comparative analysis of orthologous genes shared by clinical and environmental Sporothrix genomes revealed the presence of 3622 orthogroups shared by all species, whereas over 4200 genes were species-specific single-copy gene products. Carbohydrate-active enzyme analysis revealed a total of 2608 protein-coding genes containing single and/or multiple CAZy domains, resulting in no statistically significant differences among pathogenic and environmental species. Nevertheless, some families were not found in clinical species. Furthermore, for each sequenced Sporothrix species, the mitochondrial genomes was assembled in a single circular DNA molecule, ranging from 25,765 bp (S. variecibatus) to 58,395 bp (S. phasma). Conclusion In this study, we present four annotated genome assemblies generated using PacBio SMRT sequencing data from four environmental species: S. curviconia, S. phasma, S. protearum and S. variecibatus with the aim to provide a starting point for future comparative genome evolution studies addressing species diversification, ecological/host adaptation and origin of pathogenic lineages within the genus Sporothrix.

Sea ice is a key habitat in the high latitude Southern Ocean and is predicted to change in its extent, thickness and duration in coming decades. The sea-ice cover is instrumental in mediating ocean–atmosphere exchanges and provides an important substrate for organisms from microbes and algae to predators. Antarctic krill, Euphausia superba, is reliant on sea ice during key phases of its life cycle, particularly during the larval stages, for food and refuge from their predators, while other small grazers, including copepods and amphipods, either live in the brine channel system or find food and shelter at the ice-water interface and in gaps between rafted ice blocks. Fish, such as the Antarctic silverfish Pleuragramma antarcticum, use platelet ice (loosely-formed frazil crystals) as an essential hatching and nursery ground. In this paper, we apply the framework of the Marine Ecosystem Assessment for the Southern Ocean (MEASO) to review current knowledge about relationships between sea ice and associated primary production and secondary consumers, their status and the drivers of sea-ice change in this ocean. We then use qualitative network modelling to explore possible responses of lower trophic level sea-ice biota to different perturbations, including warming air and ocean temperatures, increased storminess and reduced annual sea-ice duration. This modelling shows that pelagic algae, copepods, krill and fish are likely to decrease in response to warming temperatures and reduced sea-ice duration, while salp populations will likely increase under conditions of reduced sea-ice duration and increased number of days of >0°C. Differences in responses to these pressures between the five MEASO sectors were also explored. Greater impacts of environmental pressures on ice-related biota occurring presently were found for the West and East Pacific sectors (notably the Ross Sea and western Antarctic Peninsula), with likely flow-on effects to the wider ecosystem. All sectors are expected to be impacted over coming decades. Finally, we highlight priorities for future sea ice biological research to address knowledge gaps in this field.

The current study compared the faecal microbiota composition of two pig breeds (autochthonous vs. commercial) to understand what happens after the integration of liquid whey in the diet and what the role of the host genetic is. The trial was conducted for 60 days, and the faecal microbiota composition was investigated at three time points, T0, T1 (after 30 days) and T2 (after 60 days) in 30 female pigs (20 commercial crossbred and 10 Nero Siciliano pigs). The animals were divided into four groups (two control and two treatment groups). Generally, in both breeds, Firmicutes (51%) and Bacteroidota (36%) were the most abundant phylum whereas Prevotella, Treponema and Lactobacillus were the most abundant genera. The two breeds have a different reaction to a liquid whey diet. In fact, as shown by PERMANOVA analysis, the liquid whey significantly (p < 0.001) affects the microbiota composition of crossbreeds while not having an effect on the microbiota of the Nero Siciliano. Despite this, in both breeds Bifidobacterium and Ruminococcus have been positively influenced by liquid whey and they promote intestinal health, improve immunity, increase performance, and feed efficiency. In conclusion, the integration of liquid whey had a different effect on the Nero Siciliano and crossbred pig breeds, emphasizing the importance of the host genetic profile in determining the faecal bacterial composition.

Cybersecurity education and training are essential prerequisites of achieving a secure and privacy-friendly digital environment. Both professionals and the general public widely acknowledge the need for high-quality university education programs and professional training courses. However, guides, recommendations, practical tools, and good examples that could help institutions design appropriate cybersecurity programs are still missing. In particular, a comprehensive method to identify skills needed by cybersecurity work roles offered on the job market is missing. This paper aims to provide practical tools and strategies to help higher education providers design good cybersecurity curricula. First, we analyze the content of 89 existing study programs worldwide, collect recommendations of renowned institutions within and outside the EU, and provide a comprehensive survey accompanied by a dynamic web application called Education Map. Based on the knowledge about the current state in cybersecurity education, we design the SPARTA Cybersecurity Skills Framework that provides the currently missing link between work roles and required expertise and shows how to develop a curriculum that reflects job market requirements. Finally, we provide a practical tool that implements the framework and helps education and training providers design new study programs and analyze existing ones by considering the requirements of cybersecurity work roles.

Here, we sequenced the faecal microbiome of a local pig breed by using whole-metagenome sequencing. Metagenomic data revealed that the faecal microbiome consists of a complex and intricate admixture of microbes belonging to all domains of life, including viruses. Most of sequencing reads were mapped to multiple reference sequences of Bacteria (99.35%) whereas the remaining reads (0.65%) were assigned to different microbes belonging to Archaea, Eukarya, and viruses. The predominant bacterial phylum was Firmicutes (∼86%), whereas Ascomycota division (fungi) was the most abundant eukaryotic phyla found. BLAST homology search showed that viral reads could be assigned to a total of 13 viral families of which 7 were present in all metagenomes. Bioinformatics analysis identified a catalogue of microbial genes encoding 231,428 unique proteins grouped in 3,169 functional groups and involved in 275 biochemical pathways. This study represents a first attempt to explore the faecal microbiome of a local pig breed in order to expand our knowledge about the taxonomic and functional profiles of microbes associated with this rare and endangered-maintained pig breed.Highlights Sequenced the faecal microbiome of a local pig breed by using whole-metagenome sequencing. Bioinformatics analysis identified a catalogue of microbial genes. The predominant bacterial phylum was Firmicutes (∼86%), whereas Ascomycota division (fungi) was the most abundant eukaryotic phyla found.

Distributional data on planktic copepods (Crustacea, Copepoda) collected in the framework of the IIIrd, Vth, and Xth Expeditions of the Italian National Antarctic Program (PNRA) to the Ross Sea sector from 1987 to 1995 are here provided. Sampling was performed with BIONESS and WP2 nets at 94 sampling stations at depths of 0–1,000 m, with a special focus on the Terra Nova Bay area. Altogether, this dataset comprises 6,027 distributional records, out of which 5,306 were obtained by digitizing original data reports and 721 are based on physical museum vouchers curated by the Italian National Antarctic Museum (MNA, Section of Genoa). The MNA samples include 8,224 individual specimens that were identified to the lowest possible taxonomic level. They belong to four orders, 25 families, 52 genera, and 82 morphological units (out of which 17 could be determined at the genus level only). A variety of environmental data were also recorded at each of the sampling stations, and we report original abundances (ind/m3) to enable future species distribution modelling. From a biogeographic point of view, the distributional data here reported represented new records for the Global Biogeographic Information Facility (GBIF) registry. In particular, 62% of the total number of species are new records for the Ross Sea sector and another 28% new records for the Antarctic region.

The Covid19 pandemic has significantly impacted on our lives, triggering a strong reaction resulting in vaccines, more effective diagnoses and therapies, policies to contain the pandemic outbreak, to name but a few. A significant contribution to their success comes from the computer science and information technology communities, both in support to other disciplines and as the primary driver of solutions for, e.g., diagnostics, social distancing, and contact tracing. In this work, we surveyed the Italian computer science and engineering community initiatives against the Covid19 pandemic. The 128 responses thus collected document the response of such a community during the first pandemic wave in Italy (February-May 2020), through several initiatives carried out by both single researchers and research groups able to promptly react to Covid19, even remotely. The data obtained by the survey are here reported, discussed and further investigated by Natural Language Processing techniques, to generate semantic clusters based on embedding representations of the surveyed activity descriptions. The resulting clusters have been then used to extend an existing Covid19 taxonomy with the classification of related research activities in computer science and information technology areas, summarizing this work contribution through a reproducible survey-to-taxonomy methodology.

Decentralized blockchain platforms have enabled the secure exchange of crypto-assets without the intermediation of trusted authorities. To this purpose, these platforms rely on a peer-to-peer network of byzantine nodes, which collaboratively maintain an append-only ledger of transactions, called blockchain. Transactions represent the actions required by users, e.g. the transfer of some units of crypto-currency to another user, or the execution of a smart contract which distributes crypto-assets according to its internal logic. Part of the nodes of the peer-to-peer network compete to append transactions to the blockchain. To do so, they group the transactions sent by users into blocks, and update their view of the blockchain state by executing these transactions in the chosen order. Once a block of transactions is appended to the blockchain, the other nodes validate it, re-executing the transactions in the same order. The serial execution of transactions does not take advantage of the multi-core architecture of modern processors, so contributing to limit the throughput. In this paper we develop a theory of transaction parallelism for blockchains, which is based on static analysis of transactions and smart contracts. We illustrate how blockchain nodes can use our theory to parallelize the execution of transactions. Initial experiments on Ethereum show that our technique can improve the performance of nodes.

Sea ice is a major driver of biological activity in the Southern Ocean. Its cycle of growth and decay determines life history traits; food web interactions; and populations of many small, ice-associated organisms. The regional ocean modelling system (ROMS) for sea ice in the western Ross Sea has highlighted two modes of sea ice duration: fast-melting years when water temperature warms quickly in early spring and sea ice melts out in mid-November, and slow-melting years when water temperature remains below 0 °C and sea ice persists through most of December. Ice-associated and pelagic biota in Terra Nova Bay, Ross Sea, were studied intensively over a 3-week period in November 1997 as part of the PIPEX (Pack-Ice Plankton Experiment) campaign. The sea ice environment in November 1997 exhibited features of a slow-melting year, and the ice cover measured 0.65 m in late November. Phytoplankton abundance and diversity increased in the second half of November, concomitant with warming air and water temperatures, melting sea ice and progressive deepening of a still weak pycnocline. Water column phytoplankton was dominated by planktonic species, both in abundance and diversity, although there was also some input from benthic species. Pelagic zooplankton were typical of a nearshore Antarctic system, with the cyclopoid copepod Oithona similis representing at least 90% of total abundance. There was an increase in numbers coinciding with the period of ice thinning. Conversely, ice-associated species such as the calanoid copepods Stephos longipes and Paralabidocera antarctica decreased over time and were found in low numbers once the water temperatures increased. Stratified sampling under the sea ice, to 20 m, revealed that P. antarctica was mainly found in close association with the under-ice surface, while S. longipes, O. similis, and the calanoid copepod Metridia gerlachei were dispersed more evenly.

Migraine is a common brain-disorder that affects 15% of the population. Converging evidence shows that migraine is associated with gastrointestinal disorders. However, the mechanisms underlying the interaction between the gut and brain in patients with migraine are not clear. In this study, we evaluated the role of the short-chain fatty acids (SCFAs) as sodium propionate (SP) and sodium butyrate (SB) on microbiota profile and intestinal permeability in a mouse model of migraine induced by nitroglycerine (NTG). The mice were orally administered SB and SP at the dose of 10, 30 and 100 mg/kg, 5 min after NTG intraperitoneal injections. Behavioral tests were used to evaluate migraine-like pain. Histological and molecular analyses were performed on the intestine. The composition of the intestinal microbiota was extracted from frozen fecal samples and sequenced with an Illumina MiSeq System. Our results demonstrated that the SP and SB treatments attenuated hyperalgesia and pain following NTG injection. Moreover, SP and SB reduced histological damage in the intestine and restored intestinal permeability and the intestinal microbiota profile. These results provide corroborating evidence that SB and SP exert a protective effect on central sensitization induced by NTG through a modulation of intestinal microbiota, suggesting the potential application of SCFAs as novel supportive therapies for intestinal disfunction associated with migraine.

Zooplankton is a fundamental group in aquatic ecosystems representing the base of the food chain. It forms a link between the lower trophic levels with secondary consumers and shows marked fluctuations in populations with environmental change, especially reacting to heating and water acidification. Marine copepods account for approx. 70% of the abundance of zooplankton and are a target of monitoring activities in key areas such as the Southern Ocean. In this study, we have used FAIR-inspired legacy data (dating back to the 1980s) collected in the Ross Sea by the Italian National Antarctic Program at GBIF.org. Together with other open-access GIS data sources and tools, it allows one to generate, for the first time, three-dimensional predictive distribution maps for twenty-six copepod species. These predictive maps were obtained by applying machine learning techniques to grey literature data, which were visualized in open-source GIS platforms. In a Species Distribution Modeling (SDM) framework, we used machine learning with three types of algorithms (TreeNet, RandomForest, and Ensemble) to analyze the presence and absence of copepods in different areas and depth classes as a function of environmental descriptors obtained from the Polar Macroscope Layers present in Quantartica. The models allow, for the first time, to map-predict the food chain per depth class in quantitative terms, showing the relative index of occurrence (RIO) in 3Dimensions and identifying the presence of each copepod species analyzed in the Ross Sea, a globally-relevant wilderness area of conservation concern. Our results show marked geographical preferences that vary with species and trophic strategy. This study demonstrates that machine learning is a successful method in accurately predicting the Antarctic copepod presence, also providing useful data to orient future sampling and the management of wildlife and conservation.

The design of IoT systems could benefit from the combination of two different analyses. We perform a first analysis to approximate how data flow across the system components, while the second analysis checks their communication soundness. We show how the combination of these two analyses yields further benefits hardly achievable by separately using each of them. We exploit two independently developed tools for the analyses. Firstly, we specify IoT systems in IoT-LySa, a simple specification language featuring asynchronous multicast communication of tuples. The values carried by the tuples are drawn from a term-algebra obtained by a parametric signature. The analysis of communication soundness is supported by ChorGram, a tool developed to verify the compatibility of communicating finite-state machines. In order to combine the analyses we implement an encoding of IoT-LySa processes into communicating machines. This encoding is not completely straightforward because IoT-LySa has multicast communications with data, while communication machines are based on point-to-point communications where only finitely many symbols can be exchanged. To highlight the benefits of our approach we appeal to a simple yet illustrative example.

An investigation on microplankton composition and spatial distribution has been carried out around Italian seas. The analysis of 53 samples, collected in 2017 at two depths in 27 different stations, has led to a scenario of horizontal distribution of microplankton. Dinophyta and Ciliophora were chosen as representatives of the whole microplankton community. A total of 60 genera were identified. Cluster analysis of data regarding taxa presence and abundance led us to recognize that similarities between surface stations were more evident than those between deep ones. Furthermore, we conducted an inter-annual comparison with available data from the South Adriatic Sea (2013, 2015). The higher dissimilarity between deep sea samples was also confirmed in a relatively smaller geographic area. The dissimilarity of deep-sea samples does not correspond to a higher habitat diversification, in terms of abiotic parameters. It has been suggested that the negligible biological connectivity in the deep, for those micro-organisms not able to perform wide spatial migrations, could produce such a biological diversification.

The Internet of Things (IoT) is smartifying our everyday life. Our starting point is IoT-LySa, a calculus for describing IoT systems, and its static analysis, which will be presented at Coordination 2016. We extend the mentioned proposal in order to begin an investigation about security issues, in particular for the static verification of secrecy and some other security properties.

Context-Oriented Programming languages provide us with primitive constructs to adapt program behaviour depending on the evolution of their operational environment, namely the context. In previous work we proposed ML_CoDa, a context-oriented language with two-components: a declarative constituent for programming the context and a functional one for computing. This paper describes an extension of ML_CoDa to deal with adaptation to unpredictable context changes notified by asynchronous events.

Context-Oriented programming languages provide us with primitive constructs to adapt program behaviour depending on the evolution of their operational environment, namely the context. In previous work we proposed ML_CoDa, a context-oriented language with two-components: a declarative constituent for programming the context and a functional one for computing. This paper describes the implementation of ML_CoDa as an extension of F#.

Hortaea werneckii, an extreme halotolerant black yeast in the order of Capnodiales, was recently isolated from different stations and depths in the Mediterranean Sea, where it was shown to be the dominant fungal species. In order to explore the genome characteristics of these Mediterranean isolates, we carried out a de-novo sequencing of the genome of one strain isolated at a depth of 3400 m (MC873) and a re-sequencing of one strain taken from a depth of 2500 m (MC848), whose genome was previously sequenced but was highly fragmented. A comparative phylogenomic analysis with other published H. werneckii genomes was also carried out to investigate the evolution of the strains from the deep sea in this environment. A high level of genome completeness was obtained for both genomes, for which genome duplication and an extensive level of heterozygosity (~4.6%) were observed, supporting the recent hypothesis that a genome duplication caused by intraspecific hybridization occurred in most H. werneckii strains. Phylogenetic analyses showed environmental and/or geographical specificity, suggesting a possible evolutionary adaptation of marine H. werneckii strains to the deep sea environment. We release high-quality genome assemblies from marine H. werneckii strains, which provides additional data for further genomics analysis, including niche adaptation, fitness and evolution studies.

Candida tropicalis is a pathogenic yeast that has emerged as an important cause of candidemia especially in elderly patients with hematological malignancies. Infections caused by this species are mainly reported from Latin America and Asian-Pacific countries although recent epidemiological data revealed that C. tropicalis accounts for 6–16.4% of the Candida bloodstream infections (BSIs) in Italy by representing a relevant issue especially for patients receiving long-term hospital care. The aim of this study was to describe the genetic diversity of C. tropicalis isolates contaminating the hands of healthcare workers (HCWs) and hospital environments and/or associated with BSIs occurring in patients with different neurological disorders and without hematological disease. A total of 28 C. tropicalis isolates were genotyped using multilocus sequence typing analysis of six housekeeping (ICL1, MDR1, SAPT2, SAPT4, XYR1, and ZWF1) genes and data revealed the presence of only eight diploid sequence types (DSTs) of which 6 (75%) were completely new. Four eBURST clonal complexes (CC2, CC10, CC11, and CC33) contained all DSTs found in this study and the CC33 resulted in an exclusive, well-defined, clonal cluster from Italy. In conclusion, C. tropicalis could represent an important cause of BSIs in long-term hospitalized patients with no underlying hematological disease. The findings of this study also suggest a potential horizontal transmission of a specific C. tropicalis clone through hands of HCWs and expand our understanding of the molecular epidemiology of this pathogen whose population structure is still far from being fully elucidated as its complexity increases as different categories of patients and geographic areas are examined.

The Internet of Things (IoT) offers the infrastructure of the information society. It hosts smart objects that automatically collect and exchange data of various kinds, directly gathered from sensors or generated by aggregations. Suitable coordination primitives and analysis mechanisms are in order to design and reason about IoT systems, and to intercept the implied technological shifts. We address these issues from a foundational point of view. To study them, we define IoT-LySa, a process calculus endowed with a static analysis that tracks the provenance and the manipulation of IoT data, and how they flow in the system. The results of the analysis can be used by a designer to check the behaviour of smart objects, in particular to verify non-functional properties, among which security.

Context Oriented Programming (COP) concerns the ability of programs to adapt to changes in their running environment. A number of programming languages endowed with COP constructs and features have been developed. However, some foundational issues remain unclear. This paper proposes adopting static analysis techniques to reason on and predict how programs adapt their behaviour. We introduce a core functional language, ContextML, equipped with COP primitives for manipulating contexts and for programming behavioural variations. In particular, we specify the dispatching mechanism, used to select the program fragments to be executed in the current active context. Besides the dynamic semantics we present an annotated type system. It guarantees that the well-typed programs adapt to any context, i.e. the dispatching mechanism always succeeds at run-time.

BACKGROUND:In this study we report the genetic characterization, including expression analysis, of the genes involved in the uptake (NGT1) and catabolism (HXK1/NAG5, DAC1/NAG2, NAG1) of the aminosugar N-acetylglucosamine (GlcNAc) in Candida africana, a pathogenic biovariant of Candida albicans that is naturally unable to assimilate the GlcNAc. RESULTS:DNA sequence analysis of these genes revealed a number of characteristic nucleotide substitutions including a unique and distinctive guanine insertion that shifts the reading frame and generates a premature stop codon (TGA) 154 bp downstream of the ATG start codon of the HXK1 gene encoding the GlcNAc-kinase, a key enzyme of the GlcNAc catabolic pathway. However, all examined genes produced transcripts even though different levels of expression were observed among the Candida isolates examined. In particular, we found an HXK1-idependent relationship of the NGT1 gene and a considerable influence of the GlcNAc-kinase functionality on the transcription of the DAC1 and NAG1 genes. Additional phenotypic analysis revealed that C. africana isolates are hyperfilamentous in the first 24-48h of growth on filament-inducing media and revert to the yeast morphological form after 72h of incubation on these media. CONCLUSIONS:Our results show that C. africana is a natural HXK1 mutant, displaying a number of phenotypic characteristics distinct from typical C. albicans isolates.

Types-and-effects are type systems, which allow one to express general semantic properties and to statically reason about program's execution. They have been widely exploited to specify static analyses, for example to track computational side effects, exceptions and communications in concurrent programs. In this paper we adopt abstract interpretation techniques to reconstruct (following the Cousot's methodology) a types-and-effects system developed to handle security problems of a multi-tier web language. Our reconstruction allows us to show that this types-and-effects system is not sound with respect to the semantics of the language. In addition, we correct the soundness issues in the analysis and systematically construct a correct analyser.

In this review we focus on research performed by Italian scientists on pelagic communities, from microzooplankton to micronekton, mainly in the Italian Seas. We considered published data, mostly as grey literature, and unpublished ones. Firstly we describe data collected over a time span of more than 30 years, during several cruises all around the Italian peninsula on zooplankton composition and distribution. We identified rare vs. common species, which enhanced biodiversity of the pelagic ecosystem. Time series, some also very long, allowed us to describe seasonal recurrent patterns, interannual fluctuations and recent shifts driven by climatic changes. More recently Italian researches were processes oriented and we analyzed results obtained on the impact of predation of both micro- and mesozooplankton on both autotrophic and heterotrophic preys. Carbon fluxes through zooplankton components were variable in space and time, but accounted for important phytoplankton losses, and when this resource became scarce they relied on heterotrophic production. Through respiration measurements of mesozooplankton another aspect of the C flux was estimated showing an increase in C demand in the most oligotrophic area. Egg production by copepods appeared to be mostly controlled by temperature and quantity/quality of available food.

In recent years, jellyfish blooms have attracted considerable scientific interest for their potential impacts on human activities and ecosystem functioning, with much attention paid to jellyfish as predators and to gelatinous biomass as a carbon sink. Other than qualitative data and observations, few studies have quantified direct predation of fish on jellyfish to clarify whether they may represent a seasonally abundant food source. Here we estimate predation frequency by the commercially valuable Mediterranean bogue, Boops boops on the mauve stinger jellyfish, Pelagia noctiluca, in the Strait of Messina (NE Sicily). A total of 1054 jellyfish were sampled throughout one year to quantify predation by B. boops from bite marks on partially eaten jellyfish and energy density of the jellyfish. Predation by B. boops in summer was almost twice that in winter, and they selectively fed according to medusa gender and body part. Calorimetric analysis and biochemical composition showed that female jellyfish gonads had significantly higher energy content than male gonads due to more lipids and that gonads had six-fold higher energy content than the somatic tissues due to higher lipid and protein concentrations. Energetically, jellyfish gonads represent a highly rewarding food source, largely available to B. boops throughout spring and summer. During the remainder of the year, when gonads were not very evident, fish predation switched towards less-selective foraging on the somatic gelatinous biomass. P. noctiluca, the most abundant jellyfish species in the Mediterranean Sea and a key planktonic predator, may represent not only a nuisance for human leisure activities and a source of mortality for fish eggs and larvae, but also an important resource for fish species of commercial value, such as B. boops.

Benthic macroinvertebrates are important components of aquatic river ecosystems. These organisms are often used for biological monitoring since they are good indicators of the aquatic freshwater environment health status which can be negatively affected by human, agricultural and industrial activities. Many studies focused on the use of observed changes in macroinvertebrate communities or populations, but studies using biochemical biomarkers in these species are almost absent. The aim of this paper was to test the employment of ecotoxicological biomarkers in Ephemeroptera larvae to assess the water quality of the Alcantara river (Sicily) from its headwater to its mouth. This river represents the main source of potable water for all the counties situated in the Alcantara valley and for the city of Messina, and is the primary irrigation source for the large surrounding agricultural lands. Acetylcholinesterase activity (AChE) and Benzo(a)pyrene monooxygenase (BPMO) activity were evaluated in Serratella ignita (Ephemerellidae) larvae from different sampling sites along the river to show the potential presence of xenobiotic substances. Environmental parameters, such as temperature, dissolved oxygen, pH, conductivity and flow velocity, were also measured at different sampling sites. The biomarker approach in invertebrates represents an early warning signal of ecotoxicological alterations, providing information on which contaminants exert toxic effects on different biota. The results showed that the highest inhibition of AChE activity in S. ignita larvae was in Randazzo and Castiglione di Sicilia villages (i.e. high and medium level of the river). Here, agricultural activities are intense, with high production of fruit, olives, citrus and the heaviest usage of fertilizers, pesticides, and neurotoxic substances like organophosphate insecticides and carbammates in all the Alcantara valley. Regarding BPMO activity, the highest value was recovered in S. ignita larvae from the river mouth, which was characterised by the highest entry of water run off of streets and loaded with xenobiotic lipophilic compounds. Both AChE and BPMO were not linked to water temperature values. The data reported in the present work represent the first attempt to monitor levels of two widely recognised enzymatic biomarkers in benthic macroinvertebrates. Results indicate the possible use of this approach in macroinvertebrate larvae to study the health status of Alcantara river. The river appears to be impacted by contamination mainly from waste discharges and, upstream, from large pasture areas. Considering the world-wide distribution of S. ignita, the biomarker approach used to assess water quality may be applicable not only to Alcantara river, but also to other lotic ecosystems.

This note reports on some joint work with I. Scherbak, aiming to overview a connection between generalized wronskians (of fundamental systems of solutions of linear ordinary differential equations with constant coefficients) and the intersection theory of complex Grassmann varieties. Detailed computations are performed in the easiest case of the intersection theory of the grassmannian of lines in projective spaces.

Abstract The autochthonous pig breeds represent an important genetic reserve to be utilized mainly for the production of typical products. In order to explore its genetic variability, here we present for the first time the whole genome sequencing and SNPs discovery in a male domestic Nero Siciliano pig compared to the last pig reference genome Sus scrofa11.1. A total of 346.8 million paired reads were generated by sequencing. After quality control, 99.03% of the reads were mapped to the reference genome, and over 11 million variants were detected. Additionally, we evaluated sequence diversity in 21 fitness-related loci selected based on their biological function and/or their proximity to relevant QTLs. We focused on genes that have been related to environmental adaptation and reproductive traits in previous studies regarding local breeds. A total of 6,747 variants were identified resulting in a rate of 1 variant every ~276 bases. Among these variants 1,132 were novel to the dbSNP151 database. This study represents a first step in the genetic characterization of Nero Siciliano pig and also provides a platform for future comparative studies between this and other swine breeds.

Climate change and biological invasions are rapidly reshuffling species distribution, restructuring the biological communities of many ecosystems worldwide. Tracking these transformations in the marine environment is crucial, but our understanding of climate change effects and invasive species dynamics is often hampered by the practical challenge of surveying large geographical areas. Here, we focus on the Mediterranean Sea, a hot spot for climate change and biological invasions to investigate recent spatiotemporal changes in fish abundances and distribution. To this end, we accessed the local ecological knowledge (LEK) of small-scale and recreational fishers, reconstructing the dynamics of fish perceived as "new" or increasing in different fishing areas. Over 500 fishers across 95 locations and nine different countries were interviewed, and semiquantitative information on yearly changes in species abundance was collected. Overall, 75 species were mentioned by the respondents, mostly warm-adapted species of both native and exotic origin. Respondents belonging to the same biogeographic sectors described coherent spatial and temporal patterns, and gradients along latitudinal and longitudinal axes were revealed. This information provides a more complete understanding of the shifting distribution of Mediterranean fishes and it also demonstrates that adequately structured LEK methodology might be applied successfully beyond the local scale, across national borders and jurisdictions. Acknowledging this potential through macroregional coordination could pave the way for future large-scale aggregations of individual observations, increasing our potential for integrated monitoring and conservation planning at the regional or even global level. This might help local communities to better understand, manage, and adapt to the ongoing biotic transformations driven by climate change and biological invaders., (© 2019 John Wiley & Sons Ltd.)