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Objectives: Radiomics is the high-throughput extraction of mineable and—possibly—reproducible quantitative imaging features from medical imaging. The aim of this work is to perform an unbiased bibliometric analysis on Radiomics 10 years after the first work became available, to highlight its status, pitfalls, and growing interest. Methods: Scopus database was used to investigate all the available English manuscripts about Radiomics. R Bibliometrix package was used for data analysis: a cumulative analysis of document categories, authors affiliations, country scientific collaborations, institution collaboration networks, keyword analysis, comprehensive of co-occurrence network, thematic map analysis, and 2021 sub-analysis of trend topics was performed. Results: A total of 5623 articles and 16,833 authors from 908 different sources have been identified. The first available document was published in March 2012, while the most recent included was released on the 31st of December 2021. China and USA were the most productive countries. Co-occurrence network analysis identified five words clusters based on top 50 authors' keywords: Radiomics, computed tomography, radiogenomics, deep learning, tomography. Trend topics analysis for 2021 showed an increased interest in artificial intelligence (n = 286), nomogram (n = 166), hepatocellular carcinoma (n = 125), COVID-19 (n = 63), and X-ray computed (n = 60). Conclusions: Our work demonstrates the importance of bibliometrics in aggregating information that otherwise would not be available in a granular analysis, detecting unknown patterns in Radiomics publications, while highlighting potential developments to ensure knowledge dissemination in the field and its future real-life applications in the clinical practice. Clinical relevance statement: This work aims to shed light on the state of the art in radiomics, which offers numerous tangible and intangible benefits, and to encourage its integration in the contemporary clinical practice for more precise imaging analysis. Key Points: • ML-based bibliometric analysis is fundamental to detect unknown pattern of data in Radiomics publications. • A raising interest in the field, the most relevant collaborations, keywords co-occurrence network, and trending topics have been investigated. • Some pitfalls still exist, including the scarce standardization and the relative lack of homogeneity across studies. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and its related containment measures—mainly physical distancing and isolation—are having detrimental consequences on the mental health of the general population worldwide. In particular, frustration, loneliness, and worries about the future are common reactions and represent well-known risk factors for several mental disorders, including anxiety, affective, and post-traumatic stress disorders. The vast majority of available studies have been conducted in China, where the pandemic started. Italy has been severely hit by the pandemic, and the socio-cultural context is completely different from Eastern countries. Therefore, there is the need for methodologically rigorous studies aiming to evaluate the impact of COVID-19 and quarantine measures on the mental health of the Italian population. In fact, our results will help us to develop appropriate interventions for managing the psychosocial consequences of pandemic. The "COVID-IT-mental health trial" is a no-profit, not-funded, national, multicentric, cross-sectional population-based trial which has the following aims: a) to evaluate the impact of COVID-19 pandemic and its containment measures on mental health of the Italian population; b) to identify the main areas to be targeted by supportive long-term interventions for the different categories of people exposed to the pandemic. Data will be collected through a web-platform using validated assessment tools. Participants will be subdivided into four groups: a) Group 1—COVID-19 quarantine group. This group includes the general population which are quarantined but not isolated, i.e., those not directly exposed to contagion nor in contact with COVID-19+ individuals; b) Group 2—COVID-19+ group, which includes isolated people directly/indirectly exposed to the virus; c) Group 3—COVID-19 healthcare staff group, which includes first- and second-line healthcare professionals; d) Group 4—COVID-19 mental health, which includes users of mental health services and all those who had already been diagnosed with a mental disorder. Mental health services worldwide are not prepared yet to manage the short- and long-term consequences of the pandemic. It is necessary to have a clear picture of the impact that this new stressor will have on mental health and well-being in order to develop and disseminate appropriate interventions for the general population and for the other at-risk groups. [ABSTRACT FROM AUTHOR]

A field trial conducted on the melon cultivar Huanghemi irrigated with saline water was carried out in Minqin County in the 2-year period, 2007 and 2008. In three irrigation treatments, different saline water concentrations were applied, that is 0.8 g l−1 (Control C), 2 g l−1 (Treatment S1) and 5 g l−1 (Treatment S2), reproducing the natural groundwater concentration in the county. The electrical conductivity of the saline water was as follows: 1.00, 2.66 and 7.03 dS m−1, respectively. The aims of the study were (i) to monitor water consumption and water potential, (ii) assess, during the whole crop cycle, some growth parameters and their relations for estimating the morpho-functional plant response irrigated with saline water and (iii) determine the ion concentration in different plant tissues to evaluate which mechanism the plant activates in the presence of high salt concentrations. Under salinity stress, the plants sustained the concentration of Ca, Mg and K, but at a level not sufficient to limit the Na adsorption. Therefore, the melon yield decreased and it was determined by a displacement of the ratio K/Na and by a lower [ABSTRACT FROM AUTHOR]

Abstract: This study evaluated the content of heavy metals in samples of eye shadows. Samples were manufactured in different countries (China, Italy, and USA). The content of Pb was measured by flame-atomic absorption spectrometry (F-AAS). The quantification of cadmium, cobalt, chromium, and nickel was performed by inductively coupled plasma-mass spectrometry (ICP-MS). The analyses were preceded by microwave-assisted acid digestion of the eye shadows. In many samples the lead was present within 20μgg−1, the value indicated as safe in good manufacturing practice, but it exceed this limit in four Chinese samples. The levels of cadmium, chromium and cobalt were always low and within acceptable and safe concentrations for the products made in Italy and USA, but the nickel concentrationexceeded the safe limit in many Chinese eye shadows. The overall results indicate that eye shadows are likely harmful when they are made according to current regulations, while products imported from China can be harmful. Therefore, major quality controls are recommended for products designed to enter in direct and long contact with the skin of eyelids when imported from countries with different regulations. [Copyright &y& Elsevier]