Investors attention and network spillover for commodity market forecasting

This paper explores the role of network spillovers in commodity market forecasting and proposes a novel factor-augmented dynamic network model. We focus on a novel network definition based on investors’ attention to commodities, positing that commodities exhibit spillovers if they share a similar level of interest. To this aim, we employ Google Trends search data as an instrumental measure for attention. The results reveal that including attention-driven spillovers significantly enhances the forecasting accuracy of commodities’ returns

Multiway clustering with time-varying parameters.

This paper proposes a clustering approach for multivariate time series with time-varying parameters in a multiway framework. Although clustering techniques based on time series distribution characteristics have been extensively studied, methods based on time-varying parameters have only recently been explored and are missing for multivariate time series. This paper fills the gap by proposing a multiway approach for distribution-based clustering of multivariate time series. To show the validity of the proposed clustering procedure, we provide both a simulation study and an application to real air quality time series data. [Abstract copyright: © The Author(s) 2022.

Clustering networked funded European research activities through rank-size laws

This paper treats a well-established public evaluation problem, which is the analysis of the funded research projects. We specifically deal with the collection of the research actions funded by the European Union over the 7th Framework Programme for Research and Technological Development and Horizon 2020. The reference period is 2007–2020. The study is developed through three methodological steps. First, we consider the networked scientific institutions by stating a link between two organizations when they are partners in the same funded project. In doing so, we build yearly complex networks. We compute four nodal centrality measures with relevant, informative content for each of them. Second, we implement a rank-size procedure on each network and each centrality measure by testing four meaningful classes of parametric curves to fit the ranked data. At the end of such a step, we derive the best fit curve and the calibrated parameters. Third, we perform a clustering procedure based on the best-fit curves of the ranked data for identifying regularities and deviations among years of research and scientific institutions. The joint employment of the three methodological approaches allows a clear view of the research activity in Europe in recent years

Chloroquine supplementation increases the cytotoxic effect of curcumin against Her2/neu overexpressing breast cancer cells in vitro and in vivo in nude mice while counteracts it in immune competent mice

Autophagy is usually a pro-survival mechanism in cancer cells, especially in the course of chemotherapy, thus autophagy inhibition may enhance the chemotherapy-mediated anti-cancer effect. However, since autophagy is strongly involved in the immunogenicity of cell death by promoting ATP release, its inhibition may reduce the immune response against tumors, negatively influencing the overall outcome of chemotherapy. In this study, we evaluated the in vitro and in vivo anti-cancer effect of curcumin (CUR) against Her2/neu overexpressing breast cancer cells (TUBO) in the presence or in the absence of the autophagy inhibitor chloroquine (CQ). We found that TUBO cell death induced by CUR was increased in vitro by CQ and slightly in vivo in nude mice. Conversely, CQ counteracted the Cur cytotoxic effect in immune competent mice, as demonstrated by the lack of in vivo tumor regression and the reduction of overall mice survival as compared with CUR-treated mice. Immunohistochemistry analysis revealed the presence of a remarkable FoxP3 T cell infiltrate within the tumors in CUR/CQ treated mice and a reduction of T cytotoxic cells, as compared with single CUR treatment. These findings suggest that autophagy is important to elicit anti-tumor immune response and that autophagy inhibition by CQ reduces such response also by recruiting T regulatory (Treg) cells in the tumor microenvironment that may be pro-tumorigenic and might counteract CUR-mediated anti-cancer effects

XPS characterization of niobium for RF cavities

none4A. Daccà; G. Gemme; L. Mattera; R. ParodiA., Daccà; G., Gemme; Mattera, Lorenzo; R., Parod

Entropy-based fuzzy clustering of interval-valued time series

This paper proposes a fuzzy C-medoids-based clustering method with entropy regularization to solve the issue of grouping complex data as interval-valued time series. The dual nature of the data, that are both time-varying and interval-valued, needs to be considered and embedded into clustering techniques. In this work, a new dissimilarity measure, based on Dynamic Time Warping, is proposed. The performance of the new clustering procedure is evaluated through a simulation study and an application to financial time series

Fuzzy clustering with entropy regularization for interval-valued data with an application to scientific journal citations

In recent years, the research of statistical methods to analyze complex structures of data has increased. In particular, a lot of attention has been focused on the interval-valued data. In a classical cluster analysis framework, an interesting line of research has focused on the clustering of interval-valued data based on fuzzy approaches. Following the partitioning around medoids fuzzy approach research line, a new fuzzy clustering model for interval-valued data is suggested. In particular, we propose a new model based on the use of the entropy as a regularization function in the fuzzy clustering criterion. The model uses a robust weighted dissimilarity measure to smooth noisy data and weigh the center and radius components of the interval-valued data, respectively. To show the good performances of the proposed clustering model, we provide a simulation study and an application to the clustering of scientific journals in research evaluation

In vitro and in vivo inhibition of breast cancer cell growth by targeting the Hedgehog/GLI pathway with SMO (GDC-0449) or GLI (GANT-61) inhibitors.

Aberrant Hedgehog (Hh)/glioma-associated oncogene (GLI) signaling has been implicated in cancer progression. Here, we analyzed GLI1, Sonic Hedgehog (Shh) and NF-κB expression in 51 breast cancer (ductal carcinoma) tissues using immunohistochemistry. We found a positive correlation between nuclear GLI1 expression and tumor grade in ductal carcinoma cases. Cytoplasmic Shh staining significantly correlated with a lower tumor grade. Next, the in vitro effects of two Hh signaling pathway inhibitors on breast cancer cell lines were evaluated using the Smoothened (SMO) antagonist GDC-0449 and the direct GLI1 inhibitor GANT-61. GDC-0449 and GANT-61 exhibited the following effects: a) inhibited breast cancer cell survival; b) induced apoptosis; c) inhibited Hh pathway activity by decreasing the mRNA expression levels of GLI1 and Ptch and inhibiting the nuclear translocation of GLI1; d) increased/decreased EGFR and ErbB2 protein expression, reduced p21- Ras and ERK1/ERK2 MAPK activities and inhibited AKT activation; and e) decreased the nuclear translocation of NF-κB. However, GANT-61 exerted these effects more effectively than GDC-0449. The in vivo antitumor activities of GDC-0449 and GANT- 61 were analyzed in BALB/c mice that were subcutaneously inoculated with mouse breast cancer (TUBO) cells. GDC-0449 and GANT-61 suppressed tumor growth of TUBO cells in BALB/c mice to different extents. These findings suggest that targeting the Hh pathway using antagonists that act downstream of SMO is a more efficient strategy than using antagonists that act upstream of SMO for interrupting Hh signaling in breast cancer

Increased IGF-1: IGFBP-3 ratio in patients with hepatocellular carcinoma

BACKGROUND: The development of hepatocellular carcinoma in liver cirrhosis is associated with altered synthesis and secretion of several growth factors. AIM: The aim of this prospective study was to investigate the potential implication of IGF-I and its major binding protein (IGFBP-3) in the development of hepatocellular carcinoma. PATIENTS AND METHODS: IGF-I and IGFBP-3 were measured in 150 healthy subjects, 40 patients with liver cirrhosis and 63 with liver cirrhosis and untreated hepatocellular carcinoma. The ratio between IGF-I and IGFBP-3 was also calculated. RESULTS: Serum IGF-I (70 ± 10 and 65 ± 7 vs. 185 ± 6.4 μg/l, P < 0.001) and IGFBP-3 levels (1225 ± 113 and 984 ± 67 vs. 3017 ± 80 μg/l, P < 0.001) were lower in patients with liver cirrhosis, without or with hepatocellular carcinoma, than in controls. Age was negatively correlated with IGF-I levels In patients with liver cirrhosis (r = -0.6; P = 0.0002) as well as in controls (r = -0.8, P < 0.0001), but not in patients with hepatocellular carcinoma (r = -0.2; P = 0.2). Additionally, in patients with liver cirrhosis (r = -0.54; P = 0.0003) and more weakly in those with hepatocellular carcinoma (r = -0.24; P = 0.04) IGF-I levels were negatively correlated with liver failure measured according with Child class. Despite patients with class C hepatocellular carcinoma being older than those in the same functional class with cirrhosis (64 ± 2 vs. 57 ± 2 years, P < 0.01), they had a significantly increased IGF-I : IGFBP-3 ratio (0.18 ± 0.05 vs. 0.41 ± 0.09, P = 0.04), due mostly to increased IGF-I levels (27.1 ± 5.6 vs. 42 ± 6.2 μg/l) as IGFBP-3 levels were similar to patients with cirrhosis (734 ± 81 vs. 679 ± 83 μg/l). CONCLUSIONS: Hepatocellular carcinoma is associated with a higher IGF-I : IGFBP-3 ratio than that found in patients with liver cirrhosis and a similar degree of liver failure