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    An evolutionary multiobjective strategy for the effective management of groundwater resources

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    This paper introduces a modelling approach aimed at the management of groundwater re-sources based on a hybrid multiobjective paradigm, namely the Evolutionary Polynomial Re-gression. Multiobjective modelling in hybrid evolutionary computing enables the user (a) to find a set of feasible symbolic models, (b) to make a robust choice of models and (c) to improve the computational efficiency developing simultaneously a set of models with diverse structural parsimony levels. Moreover the methodology here presented proves to be particularly fit to those cases where the input to the process and the boundary conditions are not easily accessible. The multiobjective approach is based on the Pareto dominance criterion and it is fully integrated into the Evolutionary Polynomial Regression paradigm. This approach proves to be effective for modelling groundwater systems, which usually requires (a) accurate analyses of the underlying physical phenomena, (b) reliable forecasts under different hypothetical sce-narios and (c) good generalisation features of the models identified. For these reasons it is important to construct easily interpretable models which are specialized for well defined pur-poses. The introduced methodology is tested on a case study concerned with the determination of the dynamical relationship between rainfall height and groundwater levels for a shallow unconfined aquifer located in southeast of Italy, which is climatically a Mediterranean zone

    A role for quercetin in coronavirus disease 2019 (COVID-19)

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    Several months ago, an outbreak of pneumonia of unknown aetiology was detected in Wuhan City (China) and the aetiological agent of the atypical pneumonia was isolated by the Chinese authorities as novel coronavirus (2019-nCoV or SARS-CoV-2). The WHO announced this new disease was to be known as “COVID-19.” When looking for new antiviral compounds, knowledge of the main viral proteins is fundamental. The major druggable targets of SARS-CoV-2 include 3-chymotrypsin-like protease (3CLpro), papain-like protease (PLpro), RNA-dependent RNA polymerase, and spike (S) protein. Quercetin inhibits 3CLpro and PLpro with a docking binding energy corresponding to −6.25 and −4.62 kcal/mol, respectively. Quercetin has a theoretical, but significant, capability to interfere with SARS-CoV-2 replication, with the results showing this to be the fifth best compound out of 18 candidates. On the basis of the clinical COVID-19 manifestations, the multifaceted aspect of quercetin as both antiinflammatory and thrombin-inhibitory actions, should be taken into consideration

    Nutraceutical Approach to Preventing Coronavirus Disease 2019 and Related Complications

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    Introduction Several months ago, Chinese authorities identified an atypical pneumonia in Wuhan city, province of Hubei (China) caused by a novel coronavirus (2019-nCoV or SARS-CoV-2). The WHO announced this new disease was to be known as "COVID-19". Evidence Acquisition Several approaches are currently underway for the treatment of this disease, but a specific cure remains to be established. Evidence Synthesis This review will describe how the use of selected nutraceuticals could be helpful, in addition to pharmacological therapy, in preventing some COVID-19-related complications in infected patients. Conclusions Even if a specific and effective cure for COVID-19 still has some way to go, selected nutraceuticals could be helpful, in addition to pharmacological therapy, in preventing some COVID-19-related complications in infected patients

    Efficient multi-objective optimal design of water distribution networks on a budget of simulations using hybrid algorithms

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    The design of water distribution networks is a large-scale combinatorial, non-linear optimisation problem, involving many complex implicit constraint sets, such as nodal mass balance and energy conservation, which are commonly satisfied through the use of hydraulic network solvers. These problem properties have motivated several prior studies to use stochastic search optimisation, because these derivative-free global search algorithms have been shown to obtain higher quality solutions for large network design problems. Global stochastic search methods, however, require many iterations to be performed in order to achieve a satisfactory solution, and each iteration may involve running computationally expensive simulations. Recently, this problem has been compounded by the evident need to embrace more than a single measure of performance into the design process, since by nature multiobjective optimisation methods require even more iterations. The use of metamodels as surrogates for the expensive simulation functions has been investigated as a possible remedy to this problem. However, the identification of reliable surrogates is not always a viable alternative. Under these circumstances, methods that are capable of achieving a satisfactory level of performance with a limited number of function evaluations represent a valuable alternative. This paper represents a first step towards filling this gap. Two recently introduced multi-objective, hybrid algorithms, ParEGO and LEMMO, are tested on the design problem of a real medium-size network in Southern Italy, and a real large-size network in the UK under a scenario of a severely restricted number of function evaluations. The results obtained suggest that the use of both algorithms, in particular LEMMO, could be successfully extended to the efficient design of large-scale water distribution networks

    A naturally-inspired, curcumin-based lecithin formulation (Meriva® formulated as the finished product Algocur®) alleviates the osteo-muscular pain conditions in rugby players

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    Curcumin is one of the most investigated phytochemical products because of its low toxicity and its broad spectrum of bioactivity, including anti-inflammatory and analgesic properties. A new delivery form of curcumin, resorting to phosphatidylcholine (Meriva®, formulated as the finished product Algocur®) has been developed to increase its bioavailability. In this study, we tested the efficacy and safety of a Meriva®-based product in rugby players suffering by different osteo-muscular pain conditions PATIENTS AND METHODS: In this pilot study, 50 male rugby players with osteo-muscular pain due to traumatic injuries, physical overload or acute episode of chronic pain were recruited and treated with conventional analgesic drugs (n = 25) or Meriva®-based product (n = 25) for a maximum of 10 days. The pain perception and the functio laesa were evaluated at baseline and after 1, 3, 6, 10 and 20 days from the initiation of the treatment protocol. Treatment tolerability, compliance, and adverse events were also reported

    Polyphenols and Cannabidiol Modulate Transcriptional Regulation of Th1/Th2 Inflammatory Genes Related to Canine Atopic Dermatitis

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    Canine atopic dermatitis (AD) is a multifactorial allergic disease associated with immune and abnormal skin barrier dysfunction and it is one of the primary causes of pruritus. Using a novel in vitro model of AD, here we tried to revert the alteration of transcriptional regulation of AD canine key genes testing a nutraceutical mixture containing flavonoids, stilbene, and cannabinoids, which are already well-known for their applications within dermatology diseases. The nutraceutical mixture induced in inflamed cells a significant downregulation (p < 0.05) of the gene expression of ccl2, ccl17, and tslp in keratinocytes and of ccl2, ccl17, and il31ra in monocytes. Consistent with the observed alterations of tslp, ccl2, ccl17, and il31ra messenger RNA (mRNA) levels, a significant increase (p < 0.05) of DNA methylation at specific CpG sites on the gene regulatory regions was found. These results lay the foundation for the use of these natural bioactives in veterinary medicine and provide a model for deeper understanding of their mechanisms of action, with potential translation to human research
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