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RANKL/RANK/OPG system consists of three essential signaling molecules: i) the receptor activator of nuclear factor (NF)-kB-ligand (RANKL), ii) the receptor activator of NF-kB (RANK), and iii) the soluble decoy receptor osteoprotegerin (OPG). Although this system is critical for the regulation of osteoclast differentiation/activation and calcium release from the skeleton, different studies have elucidated its specific role in mammary gland physiology and hormone-driven epithelial proliferation during pregnancy. Of note, several data suggest that progesterone induces mammary RANKL expression in mice and humans. In turn, RANKL controls cell proliferation in breast epithelium under physiological conditions typically associated with higher serum progesterone levels, such as luteal phase of the menstrual cycle and pregnancy. Hence, RANKL/RANK system can be regarded as a major downstream mediator of progesterone-driven mammary epithelial cells proliferation, potentially contributing to breast cancer initiation and progression. Expression of RANKL, RANK, and OPG has been detected in breast cancer cell lines and in human primary breast cancers. To date, dysregulation of RANKL/RANK/OPG system at the skeletal level has been widely documented in the context of metastatic bone disease. In fact, RANKL inhibition through the RANKL-blocking human monoclonal antibody denosumab represents a well-established therapeutic option to prevent skeletal-related events in metastatic bone disease and adjuvant therapy-induced bone loss in breast cancer. On the other hand, the exact role of OPG in breast tumorigenesis is still unclear. This review focuses on molecular mechanisms linking RANKL/RANK/OPG system to mammary tumorigenesis, highlighting pre-clinical and clinical evidence for the potential efficacy of RANKL inhibition as a prevention strategy and adjuvant therapy in breast cancer settings.

Type 1 diabetes (T1D) is a chronic autoimmune disease leading to immune-mediated destruction of pancreatic beta cells, resulting in the need for insulin therapy. The incidence of T1D is increasing worldwide, thus prompting researchers to investigate novel immunomodulatory strategies to halt autoimmunity and modify disease progression. T1D is considered as a multifactorial disease, in which genetic predisposition and environmental factors interact to promote the triggering of autoimmune responses against beta cells. Over the last decades, it has become clear that vitamin D exerts anti-inflammatory and immunomodulatory effects, apart from its well-established role in the regulation of calcium homeostasis and bone metabolism. Importantly, the global incidence of vitamin D deficiency is also dramatically increasing and epidemiologic evidence suggests an involvement of vitamin D deficiency in T1D pathogenesis. Polymorphisms in genes critical for vitamin D metabolism have also been shown to modulate the risk of T1D. Moreover, several studies have investigated the role of vitamin D (in different doses and formulations) as a potential adjuvant immunomodulatory therapy in patients with new-onset and established T1D. This review aims to present the current knowledge on the immunomodulatory effects of vitamin D and summarize the clinical interventional studies investigating its use for prevention or treatment of T1D.

Data mining is a promising new tool in mineral exploration. Here, we combined data-mining procedures with spatial prediction modeling for gold exploration targeting in the Buhweju area in southwestern Uganda. It was employed in a data-rich context of unavoidably partly redundant and correlated information that offered challenges in extracting significant relationships. Our study utilized a database of co-registered digital maps related to gold mineralization. It comprised Landsat TM, Shuttle Radar Topographic Mission (SRTM), and geophysical (radiometric and magnetic) datasets for geological and structural mapping. The locations of 15 orogenic gold deposits and 87 gold occurrences were obtained from the Geological Survey of Uganda database. These were considered direct evidence of the presence of gold mineralization. The geological and geophysical settings at the gold deposit/occurrences locations were based on geological units as host rocks, contacts, and structural elements, together with continuous field values of geophysics, radiometry, and other remotely sensed imagery. A gold exploration targeting proposition ( T p ) was defined as: “That a point p within the study area contains a gold deposit given the presence of spatial evidence.” All outstanding combinations of spatial evidence were obtained using empirical likelihood ratios. With a data-mining strategy, the ratios were filtered and modeled to identify stronger spatial associations, to rank the study area according to the likelihood of future discoveries, to represent ranking quality, to estimate associated uncertainty, and to select prospective target areas. The empirical likelihood ratios facilitated a transparent strategy for generating prediction patterns and extracting small prospective target areas with higher likelihood of discovery and lower-ranking uncertainty. Conclusions are provided on the knowledge extraction for prospectivity with further data and the challenges of reducing the arbitrariness of decisional steps.

This contribution discusses the problem of providing measures of significance of prediction results when the predictions were generated from spatial databases for landslide hazard mapping. The spatial databases usually contain map information on lithologic units, land-cover units, topographic elevation and derived attributes (slope, aspect, etc.) and the distribution in space and in time of clearly identified mass movements. In prediction modelling we transform the multi-layered database into an aggregation of functional values to obtain an index of propensity of the land to failure. Assuming then that the information in the database is sufficiently representative of the typical conditions in which the mass movements originated in space and in time, the problem then, is to confirm the validity of the results of some models over other ones, or of particular experiments that seem to use more significant data. A core point of measuring the significance of a prediction is that it allows interpreting the results. Without a validation no interpretation is possible, no support of the method or of the input information can be provided. In particular with validation, the added value can be assessed of a prediction either in a fixed time interval, or in an open-ended time or within the confined space of a study area. Validation must be of guidance in data collection and field practice for landslide hazard mapping.

Background Multiple studies regarding the use of Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) in patients with non-compressible torso injuries and uncontrolled haemorrhagic shock were recently published. To date, the clinical evidence of the efficacy of REBOA is still debated. We aimed to conduct a systematic review assessing the clinical efficacy and safety of REBOA in patients with major trauma and uncontrolled haemorrhagic shock. Methods We systematically searched MEDLINE (PubMed), EMBASE and CENTRAL up to June 2020. All randomized controlled trials and observational studies that investigated the use of REBOA compared to resuscitative thoracotomy (RT) with/without REBOA or no-REBOA were eligible. We followed the PRISMA and MOOSE guidelines. Two authors independently extracted data and appraised the risk of bias of included studies. Effect sizes were pooled in a meta-analysis using random-effects models. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation methodology. Primary outcomes were mortality, volume of infused blood components, health-related quality of life, time to haemorrhage control and any adverse effects. Secondary outcomes were improvement in haemodynamic status and failure/success of REBOA technique. Results We included 11 studies (5866 participants) ranging from fair to good quality. REBOA was associated with lower mortality when compared to RT (aOR 0.38; 95% CI 0.20–0.74), whereas no difference was observed when REBOA was compared to no-REBOA (aOR 1.40; 95% CI 0.79–2.46). No significant difference in health-related quality of life between REBOA and RT ( p = 0.766). The most commonly reported complications were amputation, haematoma and pseudoaneurysm. Sparse data and heterogeneity of reporting for all other outcomes prevented any estimate. Conclusions Our findings on overall mortality suggest a positive effect of REBOA among non-compressible torso injuries when compared to RT but no differences compared to no-REBOA. Variability in indications and patient characteristics prevents any conclusion deserving further investigation. REBOA should be promoted in specific training programs in an experimental setting in order to test its effectiveness and a randomized trial should be planned.

Emerging evidence shows that individuals with COVID-19 who survive the acute phase of illness may experience lingering symptoms in the following months. There is no clear indication as to whether these symptoms persist for a short time before resolving or if they persist for a long time. In this review, we will describe the symptoms that persist over time and possible predictors in the acute phase that indicate long-term persistence. Based on the literature available to date, fatigue/weakness, dyspnea, arthromyalgia, depression, anxiety, memory loss, slowing down, difficulty concentrating and insomnia are the most commonly reported persistent long-term symptoms. The extent and persistence of these in long-term follow-up is not clear as there are still no quality studies available. The evidence available today indicates that female subjects and those with a more severe initial disease are more likely to suffer permanent sequelae one year after the acute phase. To understand these complications, and to experiment with interventions and treatments for those at greater risk, we must first understand the physio-pathological mechanisms that sustain them.

This contribution exposes the relative uncertainties associated with prediction patterns of landslide susceptibility. The patterns are based on relationships between direct and indirect spatial evidence of landslide occurrences. In a spatial database constructed for the modeling, direct evidence is the presence of landslide trigger areas, while indirect evidence is the presence of corresponding multivariate context in the form of digital maps. Five mathematical modeling functions are applied to capture and integrate evidence, indirect and direct, for separating landslide-presence areas from the areas of landslide assumed absence. Empirical likelihood ratios are used first to represent the spatial relationships. These are then combined by the models into prediction scores, ordered, equal-area ranked, displayed, and synthesized as prediction-rate curves. A critical task is assessing how uncertainty levels vary across the different prediction patterns, i.e., the modeling results visualized as fixed, colored groups of ranks. This is obtained by a strategy of iterative cross validation that uses only part of the direct evidence to model the pattern and the rest to validate it as a predictor. The conducted experiments in a mountainous area in northern Italy point at a research challenge that can now be confronted with relative rank-based statistics and iterative cross-validation processes. The uncertainty properties of prediction patterns are mostly unknown nevertheless they are critical for interpreting and justifying prediction results.

A modular X-ray scanning system was developed, to fill in the gap between portable instruments (with a limited analytical area) and mobile instruments (with large analytical areas, and sometimes bulky and difficult to transport). The scanner has been compared to a commercial tabletop instrument, by analysing a Portuguese tile (azulejo) from the 17th century. Complementary techniques were used to achieve a throughout characterisation of the sample in a complete non-destructive approach. The complexity of the acquired X-ray fluorescence (XRF) spectra, due to inherent sample stratigraphy, has been resolved using Monte Carlo simulations, and Raman spectroscopy, as the most suitable technique to complement the analysis of azulejos colours, yielding satisfactory results. The colouring agents were identified as cobalt blue and a Zn-modified Naples-yellow. The stratigraphy of the area under study was partially modelled with Monte Carlo simulations. The scanners performance has been compared by evaluating the images outputs and the global spectrum.

On behalf of Italian Society of Emergency Medicine (SIMEU), Association of Italian Hospital Dermatologists Venereologists and Public Health (ADOI) and Italian Skin Ulcer Association (AIUC).Early diagnosis and treatment of burn patients are a key issue in the emergency setting. With the aim of assisting physicians in the diagnosis and subsequent management of burns in emergency departments (EDs), a Nominal Group Technique (NGT) was designated. A group of 6 Italian experts (2 emergency physicians, 2 emergency medicine nurses, and 2 dermatologists chief of a burn center) developed a consensus document based on the available evidence and their clinical experience on the fundamental steps to be followed in the ED in the management of patients with a mild to moderate degree burn. The expert consensus statement proposed can assist emergency physicians in applying the results of clinical studies and clinical experience to routine care settings, providing guidance on all aspects of 7 steps: prehospital treatment, centralization criteria, transport (equipment and composition of the healthcare team), management of ED phase, clinical evaluation, treatment of pain and disposition.

Systemic inflammation represents a shared pathophysiological mechanism which underlies the frequent clinical associations among chronic inflammatory rheumatic diseases (CIRDs), insulin resistance, type 2 diabetes (T2D), and chronic diabetes complications, including cardiovascular disease. Therefore, targeted anti-inflammatory therapies are attractive and highly desirable interventions to concomitantly reduce rheumatic disease activity and to improve glucose control in patients with CIRDs and comorbid T2D. Therapeutic approaches targeting inflammation may also play a role in the prevention of prediabetes and diabetes in patients with CIRDs, particularly in those with traditional risk factors and/or on high-dose corticosteroid therapy. Recently, several studies have shown that different disease-modifying antirheumatic drugs (DMARDs) used for the treatment of CIRDs exert antihyperglycemic properties by virtue of their anti-inflammatory, insulin-sensitizing, and/or insulinotropic effects. In this view, DMARDs are promising drug candidates that may potentially reduce rheumatic disease activity, ameliorate glucose control, and at the same time, prevent the development of diabetes-associated cardiovascular complications and metabolic dysfunctions. In light of their substantial antidiabetic actions, some DMARDs (such as hydroxychloroquine and anakinra) could be alternatively termed “diabetes-modifying antirheumatic drugs”, since they may be repurposed for co-treatment of rheumatic diseases and comorbid T2D. However, there is a need for future randomized controlled trials to confirm the beneficial metabolic and cardiovascular effects as well as the safety profile of distinct DMARDs in the long term. This narrative review aims to discuss the current knowledge about the mechanisms behind the antihyperglycemic properties exerted by a variety of DMARDs (including synthetic and biologic DMARDs) and the potential use of these agents as antidiabetic medications in clinical settings.