Astrophysics in S.Co.P.E

S.Co.P.E. is one of the four projects funded by the Italian Government in order to provide Southern Italy with a distributed computing infrastructure for fundamental science. Beside being aimed at building the infrastructure, S.Co.P.E. is also actively pursuing research in several areas among which astrophysics and observational cosmology. We shortly summarize the most significant results obtained in the first two years of the project and related to the development of middleware and Data Mining tools for the Virtual Observatory

N-(3-Ethoxy-phenyl)-4-pyrrolidin-1-yl-3-trifluoromethyl-benzamide (EPPTB) prevents 3-iodothyronamine (T1AM)-induced neuroprotection against kainic acid toxicity

Thyroid hormone and thyroid hormone metabolites, including 3-iodothyronamine (T1AM) and 3-iodothyroacetic acid (TA1), activate AKT signaling in hippocampal neurons affording protection from excitotoxic damage. We aim to explore whether the mechanism of T1AM neuroprotection against kainic acid (KA)-induced excitotoxicity included the activation of the trace amine associated receptor isoform 1 (TAAR1), one of T1AM targets. Rat organotypic hippocampal slices were exposed to vehicle (Veh) or to 5 μM kA for 24 h in the absence or presence of 0.1, 1 and 10 μM T1AM or to 0.1, 1 and 10 μM T1AM and 1 μM N-(3-Ethoxy-phenyl)-4-pyrrolidin-1-yl-3-trifluoromethyl-benzamide (EPPTB), the only available TAAR1 antagonist, or to 1 μM T1AM in the absence or in the presence of 10 μM LY294002, an inhibitor of phosphoinositide 3-kinases (PI3Ks). Cell death was evaluated by measuring propidium iodide (PI) levels of fluorescence 24 h after treatment. In parallel, the expression levels of p-AKT and p-PKA were evaluated by Western blot analysis of slice lysates. The activity of mitochondrial monoamine oxidases (MAO) was assayed fluorimetrically. 24 h exposure of slices to T1AM resulted in the activation of AKT and PKA. KA exposure induced cell death in the CA3 region and significantly reduced p-AKT and p-PKA levels. The presence of 1 and 10 μM T1AM significantly protected neurons from death and conserved both kinase levels with the essential role of AKT in neuroprotection. Furthermore, EPPTB prevented T1AM-induced neuroprotection, activation of PKA and AKT. Of note, in the presence of EPPTB T1AM degradation by MAO was reduced. Our results indicate that the neuroprotection offered by T1AM depends, as for TA1, on AKT activation but do not allow to conclusively indicate TAAR1 as the target implicated. Graphical abstrac

3-iodothyronamine affects thermogenic substrates’ mobilization in brown adipocytes

We investigated the effect of 3-iodothyronamine (T1AM) on thermogenic substrates in brown adipocytes (BAs). BAs isolated from the stromal fraction of rat brown adipose tissue were exposed to an adipogenic medium containing insulin in the absence (M) or in the presence of 20 nM T1AM (M+T1AM) for 6 days. At the end of the treatment, the expression of p-PKA/PKA, p-AKT/AKT, p-AMPK/AMPK, p-CREB/CREB, p-P38/P38, type 1 and 3 beta adrenergic receptors (β1–β3AR), GLUT4, type 2 deiodinase (DIO2), and uncoupling protein 1 (UCP-1) were evaluated. The effects of cell conditioning with T1AM on fatty acid mobilization (basal and adrenergic-mediated), glucose uptake (basal and insulin-mediated), and ATP cell content were also analyzed in both cell populations. When compared to cells not exposed, M+T1AM cells showed increased p-PKA/PKA, p-AKT/AKT, p-CREB/CREB, p-P38/P38, and p-AMPK/AMPK, downregulation of DIO2 and β1AR, and upregulation of glycosylated β3AR, GLUT4, and adiponectin. At basal conditions, glycerol release was higher for M+T1AM cells than M cells, without any significant differences in basal glucose uptake. Notably, in M+T1AM cells, adrenergic agonists failed to activate PKA and lipolysis and to increase ATP level, but the glucose uptake in response to insulin exposure was more pronounced than in M cells. In conclusion, our results suggest that BAs conditioning with T1AM promote a catabolic condition promising to fight obesity and insulin resistance

Adaptive filtering for removing nonstationary physiological noise from resting state fMRI BOLD signals

fMRI is used to investigate brain functional connectivity after removing nonneural components by General Linear Model (GLM) approach with a reference ventricle-derived signal as covariate. Ventricle signals are related to low-frequency modulations of cardiac and respiratory rhythms, which are nonstationary activities. Herein, we employed an adaptive filtering approach to improve removing physiological noise from BOLD signals. Comparisons between filtering approaches were performed by evaluating the amount of removed signal variance and the connectivity between homologous contralateral regions of interest (ROIs). The global connectivity between ROIs was estimated with a generalized correlation named RV coefficient. The mean ROI decrease of variance was -52% and -11%, for adaptive filtering and GLM, respectively. Adaptive filtering led to higher connectivity between grey matter ROIs than that obtained with GLM. Thus, adaptive filtering is a feasible method for removing the physiological noise in the low frequency band and to highlight resting state functional networks

CLaSPS: a new methodology for Knowledge extraction from complex astronomical dataset

In this paper we present the Clustering-Labels-Score Patterns Spotter (CLaSPS), a new methodology for the determination of correlations among astronomical observables in complex datasets, based on the application of distinct unsupervised clustering techniques. The novelty in CLaSPS is the criterion used for the selection of the optimal clusterings, based on a quantitative measure of the degree of correlation between the cluster memberships and the distribution of a set of observables, the labels, not employed for the clustering. In this paper we discuss the applications of CLaSPS to two simple astronomical datasets, both composed of extragalactic sources with photometric observations at different wavelengths from large area surveys. The first dataset, CSC+, is composed of optical quasars spectroscopically selected in the SDSS data, observed in the X-rays by Chandra and with multi-wavelength observations in the near-infrared, optical and ultraviolet spectral intervals. One of the results of the application of CLaSPS to the CSC+ is the re-identification of a well-known correlation between the alphaOX parameter and the near ultraviolet color, in a subset of CSC+ sources with relatively small values of the near-ultraviolet colors. The other dataset consists of a sample of blazars for which photometric observations in the optical, mid and near infrared are available, complemented for a subset of the sources, by Fermi gamma-ray data. The main results of the application of CLaSPS to such datasets have been the discovery of a strong correlation between the multi-wavelength color distribution of blazars and their optical spectral classification in BL Lacs and Flat Spectrum Radio Quasars and a peculiar pattern followed by blazars in the WISE mid-infrared colors space. This pattern and its physical interpretation have been discussed in details in other papers by one of the authors.Comment: 18 pages, 9 figures, accepted for publication in Ap

Fibrosing Progressive Interstitial Lung Disease in Rheumatoid Arthritis: A Multicentre Italian Study

Background: The INBUILD study demonstrated the efficacy of nintedanib in the treatment of progressive fibrosing interstitial lung disease different to idiopathic pulmonary fibrosis, including rheumatoid arthritis (RA)-related ILD. Nevertheless, the prevalence of RA-ILD patients that may potentially benefit from nintedanib remains unknown. Objectives and methods: The aim of the present multicentre study was to investigate the prevalence and possible associated factors of fibrosing progressive patterns in a cross-sectional cohort of RA-ILD patients. Results: One hundred and thirty-four RA-ILD patients with a diagnosis of RA-ILD, who were confirmed at high-resolution computed tomography and with a follow-up of at least 24 months, were enrolled. The patients were defined as having a progressive fibrosing ILD in case of a relative decline in forced vital capacity > 10% predicted and/or an increased extent of fibrotic changes on chest imaging in a 24-month period. Respiratory symptoms were excluded to reduce possible bias due to the retrospective interpretation of cough and dyspnea. According to radiologic features, ILD was classified as usual interstitial pneumonia (UIP) in 50.7% of patients, nonspecific interstitial pneumonia in 19.4%, and other patterns in 29.8%. Globally, a fibrosing progressive pattern was recorded in 36.6% of patients (48.5% of patients with a fibrosing pattern) with a significant association to the UIP pattern. Conclusion: We observed that more than a third of RA-ILD patients showed a fibrosing progressive pattern and might benefit from antifibrotic treatment. This study shows some limitations, such as the retrospective design. The exclusion of respiratory symptoms' evaluation might underestimate the prevalence of progressive lung disease but increases the value of results.Background: The INBUILD study demonstrated the efficacy of nintedanib in the treatment of progressive fibrosing interstitial lung disease different to idiopathic pulmonary fibrosis, including rheumatoid arthritis (RA)-related ILD. Nevertheless, the prevalence of RA-ILD patients that may potentially benefit from nintedanib remains unknown. Objectives and methods: The aim of the present multicentre study was to investigate the prevalence and possible associated factors of fibrosing progressive patterns in a cross-sectional cohort of RA-ILD patients. Results: One hundred and thirty-four RA-ILD patients with a diagnosis of RA-ILD, who were confirmed at high-resolution computed tomography and with a follow-up of at least 24 months, were enrolled. The patients were defined as having a progressive fibrosing ILD in case of a relative decline in forced vital capacity > 10% predicted and/or an increased extent of fibrotic changes on chest imaging in a 24-month period. Respiratory symptoms were excluded to reduce possible bias due to the retrospective interpretation of cough and dyspnea. According to radiologic features, ILD was classified as usual interstitial pneumonia (UIP) in 50.7% of patients, nonspecific interstitial pneumonia in 19.4%, and other patterns in 29.8%. Globally, a fibrosing progressive pattern was recorded in 36.6% of patients (48.5% of patients with a fibrosing pattern) with a significant association to the UIP pattern. Conclusion: We observed that more than a third of RA-ILD patients showed a fibrosing progressive pattern and might benefit from antifibrotic treatment. This study shows some limitations, such as the retrospective design. The exclusion of respiratory symptoms’ evaluation might underestimate the prevalence of progressive lung disease but increases the value of results

Tisochrysis lutea F&M-M36 Mitigates Risk Factors of Metabolic Syndrome and Promotes Visceral Fat Browning through β3-Adrenergic Receptor/UCP1 Signaling

Pre-metabolic syndrome (pre-MetS) may represent the best transition phase to start treatments aimed at reducing cardiometabolic risk factors of MetS. In this study, we investigated the effects of the marine microalga Tisochrysis lutea F&M-M36 (T. lutea) on cardiometabolic components of pre-MetS and its underlying mechanisms. Rats were fed a standard (5% fat) or a high-fat diet (20% fat) supplemented or not with 5% of T. lutea or fenofibrate (100 mg/Kg) for 3 months. Like fenofibrate, T. lutea decreased blood triglycerides (p < 0.01) and glucose levels (p < 0.01), increased fecal lipid excretion (p < 0.05) and adiponectin (p < 0.001) without affecting weight gain. Unlike fenofibrate, T. lutea did not increase liver weight and steatosis, reduced renal fat (p < 0.05), diastolic (p < 0.05) and mean arterial pressure (p < 0.05). In visceral adipose tissue (VAT), T. lutea, but not fenofibrate, increased the β3-adrenergic receptor (β3ADR) (p < 0.05) and Uncoupling protein 1 (UCP-1) (p < 0.001) while both induced glucagon-like peptide-1 receptor (GLP1R) protein expression (p < 0.001) and decreased interleukin (IL)-6 and IL-1β gene expression (p < 0.05). Pathway analysis on VAT whole-gene expression profiles showed that T. lutea up-regulated energy-metabolism-related genes and down-regulated inflammatory and autophagy pathways. The multitarget activity of T. lutea suggests that this microalga could be useful in mitigating risk factors of MetS

Selective HCN1 block as a strategy to control oxaliplatin-induced neuropathy

Chemotherapy-Induced Peripheral Neuropathy (CIPN) is the most frequent adverse effect of pharmacological cancer treatments. The occurrence of neuropathy prevents the administration of fully-effective drug regimen, affects negatively the quality of life of patients, and may lead to therapy discontinuation. CIPN is currently treated with anticonvulsants, antidepressants, opioids and non-opioid analgesics, all of which are flawed by insufficient anti-hyperalgesic efficacy or addictive potential. Understandably, developing new drugs targeting CIPN-specific pathogenic mechanisms would dramatically improve efficacy and tolerability of anti-neuropathic therapies. Neuropathies are associated to aberrant excitability of DRG neurons due to the alteration in the expression or function of a variety of ion channels. In this regard, Hyperpolarization-activated Cyclic Nucleotide-gated (HCN) channels are overexpressed in inflammatory and neuropathic pain states, and HCN blockers have been shown to reduce neuronal excitability and to ameliorate painful states in animal models. However, HCN channels are critical in cardiac action potential, and HCN blockers used so far in pre-clinical models do not discriminate between cardiac and non-cardiac HCN isoforms. In this work, we show an HCN current gain of function in DRG neurons from oxaliplatin-treated rats. Biochemically, we observed a downregulation of HCN2 expression and an upregulation of the HCN regulatory beta-subunit MirP1. Finally, we report the efficacy of the selective HCN1 inhibitor MEL57A in reducing hyperalgesia and allodynia in oxaliplatin-treated rats without cardiac effects. In conclusion, this study strengthens the evidence for a disease-specific role of HCN1 in CIPN, and proposes HCN1-selective inhibitors as new-generation pain medications with the desired efficacy and safety profile

Gastric normal adjacent mucosa versus healthy and cancer tissues: Distinctive transcriptomic profiles and biological features

Gastric cancer (GC) is a leading cause of cancer-related deaths in the world. Molecular heterogeneity is a major determinant for the clinical outcomes and an exhaustive tumor classification is currently missing. Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies, nevertheless a recently published paper described the unique characteristics of the NAT in several tumor types. Little is known about the global gene expression profile of gastric NAT (gNAT) which could be an effective tool for a more realistic definition of GC molecular signature. Here, we integrated data of 512 samples from the Genotype- Tissue Expression project (GETx) and The Cancer Genome Atlas (TCGA) to analyze the transcriptome of healthy gastric tissues, gNAT, and GC samples. We validated TCGA-GETx data mining through inHouse gNAT and GC expression dataset. Differential gene expression together with pathway enrichment analyses, indeed, led to different results when using the gNAT or the healthy tissue as control. Based on our analyses, gNAT showed a peculiar gene signature and biological features, like the estrogen receptor pathways activation, suggesting a molecular behavior partially different from both healthy and GC tissues. Therefore, using gNAT as healthy control tissue in the characterization of tumor associated biological processes and pathways could lead to suboptimal results

Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case

Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use of this new approach. The usage of machine learning methods, however is still far from trivial and many problems still need to be solved. Using the evaluation of photometric redshifts as a case study, we outline the main problems and some ongoing efforts to solve them.Comment: 13 pages, 3 figures, Springer's Communications in Computer and Information Science (CCIS), Vol. 82