Nutraceutical Aspects of Selected Wild Edible Plants of the Italian Central Apennines

All over the world, wild edible plants are an essential source of chemical components that justify their use in folk medicine. The aim of this review is to document and summarize the knowledge of ten wild plants analyzed in a previous study for their ethnomedical significance. Achillea millefolium, Borago officinalis, Foeniculum vulgare, Gentiana lutea, Juniperus communis, Laurus nobilis, Malva sylvestris, Satureja montana, Silybum marianum and Urtica dioica were the subjects of our study. They are commonly found in the central Italian Apennines and the Mediterranean basin. Phytochemicals contained in wild plants, such as phenols, polyphenols, flavonoids, condensed tannins, carotenoids, etc., are receiving increasing attention, as they exert a wide range of biological activities with resulting benefits for human health. Based on the 353 studies we reviewed, we focused our study on the following: (a) the ethnobotanical practices and bioactive phytochemicals; (b) the composition of polyphenols and their role as antioxidants; (c) the methodologies commonly used to assess antioxidant activity; (d) the most advanced spectroscopic and spectrometric techniques used to visualize and characterize all components (metabolomic fingerprinting). The potential of pure compounds and extracts to be used as nutraceuticals has also been highlighted through a supposed mechanism of action

Data requirements and scientific efforts for reliable large-scale assessment of landslide hazard in urban areas

Landslides in urban areas are conceived as phenomena capable of tearing the physical structure as well as the networks of socio-economic, cultural, material and immaterial relations that make up the life of cities. Landslide hazard analysis is usually mandatory for proper land use planning and management. Nevertheless, in some cases (e.g., municipality of Rome in Italy) regulatory plans lack detailed thematic mapping of geohazard-related data. In Italy, the safety of urban areas has become a very important issue in the last decade, therefore projects of national interest have been funded for the mitigation of geological risks. Shallow landslides are common mass movements in urban areas. They can be triggered by earthquakes, heavy rains or induced by proximity to specific urban assets, like road cuts or retaining walls. Reliable quantification of landslide hazardous areas is often associated with the existence of static specific predisposing factors, such as local terrain variables, land use, lithology, proximity to roads and streams as well as dynamic factors related to trigger (e.g., antecedent rainfalls). Predictive multivariate statistical analysis, among which Machine Learning (ML) models, takes as input several predisposing and conditioning factors that may reveal patterns with the spatial and temporal distribution of different types of landslides. Therefore, ancillary landslide databases are the key-data to investigate the distribution, types, pattern, recurrence, and statistics of slope failures and consequently to determine the overall landslide hazard. However, the amount and quality of available data may be inadequate to build accurate large-scale predictive models. Open-source landslide inventories are often incomplete in spatial and temporal terms, with heterogeneous geometries, thus generating a data sparse environment consisting of a variety of low-accuracy datasets that need to be integrated and cross-validated to gain reliability. In this study, the adoption of a combined approach based on GIS tools and Machine Learning techniques allowed to estimate landslide susceptibility based on both real and synthetic Landslide Initiation Points (LIPs). Open-source landslide inventories have been collected, cross-validated, and integrated in a unique database, thus creating a richer data product that contains the strengths but overcomes the weakness of each contributing dataset. As the number of LIPs was too low to train reliable ML models, we developed a methodology based on the features of occurred landslides in order to derive synthetic LIPs to boost the original database by three times. This approach has been applied to the Metropolitan area of Rome (Lazio, Central Italy), where rainfall-induced shallow landslides have been widely overlooked. The final database with LIPs and predisposing factors has been used to create and validate different ML models and the most accurate one was then deployed to estimate landslide susceptibility for the whole area of the municipality of Rome with a resolution of 5 meters. The obtained results were then compared with pre-existing, regional, national, and European scale susceptibility maps to assess their reliability in case more detailed studies are not available. Eventually, rainfall probability curves were estimated to evaluate the temporal dependence of rainfall-induced shallow landslides

New methods for thalassemia screening: TGA/chemometrics test is not influenced by the aging of blood samples

The coupling of Thermogravimetry (TG) in conjuction with chemometrics was investigated for the first time to evaluate the capabilities of this novel test to provide the screening of thalassemia in blood samples stored at 4 °C until 15 days. Healthy donors were considered as reference subjects and a typical thermal behaviour as a function of aging was estimated and compared to thermal behaviour of thalassemia subjects. Diagnosis of thalassemia was made at the Day-Hospital Thalassemia of S. Eugenio Hospital through a comprehensive assessment of clinical presentation and hematological and molecular analysis. Despite blood changes with aging, the application of the TGA/Chemometrics test reveal that healthy and thalassemic population may be significantly differentiated after 15 days from blood collection with a 100% of correct classification rate. This new method applied to aged samples was able to discriminate thalassemia in transfused patients that is generally not possible by the common first level protocol used for thalassemia screening, and in δβ-thalassemias, and β-thalassemia combined with Hb Lepore, usually requiring the molecular analysis for diagnosis. This study, for the first time, describes a screening method for thalassemia able to detect thalassemia on whole blood samples stored for 15 days. In conclusion TGA/Chemometrics screening test for thalassemia is not influenced by the aging of blood samples and this approach could open the way to prevention programs for thalassemia also in the developing countries where expertise and facilities for their control are extremely limited or in situation involving delayed analyses

Effects of EOs vs. Antibiotics on E. coli Strains Isolated from Drinking Waters of Grazing Animals in the Upper Molise Region, Italy

The health and safety of grazing animals was the subject of microbiological monitoring on natural source of drinking waters in the upper Molise region, Italy. Surface water samples, on spring-summer season, were collected and submitted to analyses using sterile membrane filtration, cultural medium, and incubation. The level of environmental microbial contamination (Total viable microbial count, yeasts and fungi) and faecal presence (Total and faecal coliforms, E. coli, and Salmonellae spp.) were carried out. By the selective microbiological screening, twenty-three E. coli strains from drinking waters were isolated and submitted to further studies to evaluate antibiotic resistance by antibiograms vs. three animal and two diffuse human antibiotics. Furthermore, after a fine chemical characterization by GC and GC-MS, three Essential Oils (EOs) of aromatic plants (Timus vulgaris, Melaleuca alternifolia, Cinnamomun verum) aromatograms were performed and results statistically compared. The effects of EOs vs. antibiotics on E. coli strains isolated from drinking waters showed a total absence of microbial resistance. In our experimental conditions, even if some suggestions will be further adopted for better managements of grazing animals, because the health and safety represent a guarantee for both animals and humans

The Polygalacturonase-Inhibiting Protein PGIP2 of Phaseolus vulgaris Has Evolved a Mixed Mode of Inhibition of Endopolygalacturonase PG1 of Botrytis cinerea

Botrytis cinerea is a phytopathogenic fungus that causes gray mold in >1,000 plant species. During infection, it secretes several endopolygalacturonases (PGs) to degrade cell wall pectin, and among them, BcPG1 is constitutively expressed and is an important virulence factor. To counteract the action of PGs, plants express polygalacturonase-inhibiting proteins (PGIPs) that have been shown to inhibit a variety of PGs with different inhibition kinetics, both competitive and noncompetitive. The PG-PGIP interaction promotes the accumulation of oligogalacturonides, fragments of the plant cell wall that are general elicitors of plant defense responses. Here, we characterize the enzymatic activity of BcPG1 and investigate its interaction with PGIP isoform 2 from Phaseolus vulgaris (PvPGIP2) by means of inhibition assays, homology modeling, and molecular docking simulations. Our results indicate a mixed mode of inhibition. This is compatible with a model for the interaction where PvPGIP2 binds the N-terminal portion of BcPG1, partially covering its active site and decreasing the enzyme affinity for the substrate. The structural framework provided by the docking model is confirmed by site-directed mutagenesis of the residues that distinguish PvPGIP2 from the isoform PvPGIP1. The finding that PvPGIP2 inhibits BcPG1 with a mixed-type kinetics further indicates the versatility of PGIPs to evolve different recognition specificities