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The physiological role of autophagy in the progression of liver diseases is still debated. To understand the clinical relevance of autophagy in primary e secondary hepatic tumors, we analyzed the expression of mTOR (mammalian target of rapamycin), a key regulator of autophagy; Raptor (regulatory-associated protein of mTOR); ULK1 (Unc-51 like kinase 1) determinant in the autophagy initiation; LC3 (microtubule-associated protein 1A/1B-light chain 3), a specific marker of autophagosomes; and p62, a selective autophagy receptor. Samples from subjects with chronic hepatitis (n.58), cirrhosis (n.12), hepatocellular carcinoma (HCC, n.56), metastases (n.48) from colorectal cancer and hyperplasia or gallbladder stones (n.7), the latter considered as controls, were examined. Gene expression analysis was carried out in n.213 tissues by absolute q-PCR, while protein expression by Western Blot in n.191 lysates, including tumoral, surrounding tumoral and normal tissues. Nonparametric statistical tests were used for comparing expression levels in the above-mentioned groups. Subgroup analysis was performed considering viral infection and chemotherapy treatment. The mTOR transcriptional level was significantly lower in metastases compared to HCC (P = 0.0001). p-mTOR(Ser2448) and LC3II/LC3I protein levels were significantly higher in metastases compared to HCC (P = 0.008 and PConclusions:the different expression of proteins considered, owning their interaction and diverse tissue microenvironment, indicate an impairment of the autophagy flux in primary liver tumors that is critical for the promotion of tumorigenesis process and a coexistence of autophagy inhibition and activation mechanisms in secondary liver tumors. Differences in mTOR and LC3 transcripts emerged in tumor-free tissues, therefore particular attention should be considered in selecting the control group.

Objectives: The goal of this study was to assess the diagnostic performance of coronary computed tomography angiography (CTA) alone, adenosine-stress myocardial perfusion assessed by computed tomography (CTP) alone, and coronary CTA + CTP by using a 16-cm Z-axis coverage scanner versus invasive coronary angiography (ICA) and fractional flow reserve (FFR) as the clinical standard. Background: Diagnostic performance of coronary CTA for in-stent restenosis detection is still challenging. Recently, CTP showed additional diagnostic power over coronary CTA in patients with suspected coronary artery disease. However, few data are available on CTP performance in patients with previous stent implantation. Methods: Consecutive stable patients with previous coronary stenting referred for ICA were enrolled. All patients underwent stress myocardial CTP and rest CTP + coronary CTA. Invasive FFR was performed during ICA when clinically indicated. The diagnostic rate and diagnostic accuracy of coronary CTA, CTP, and coronary CTA + CTP were evaluated in stent-, territory-, and patient-based analyses. Results: In the 150 enrolled patients (132 men; mean age 65.1 ± 9.1 years), the CTP diagnostic rate was significantly higher than that of coronary CTA in all analyses (territory based [96.7% vs. 91.1%; p < 0.0001] and patient based [96% vs. 68%; p < 0.0001]). When ICA was used as gold standard, CTP diagnostic accuracy was significantly higher than that of coronary CTA in all analyses (territory based [92.1% vs. 85.5%, p < 0.03] and patient based [86.7% vs. 76.7%, p < 0.03]). The concordant coronary CTA + CTP assessment exhibited the highest diagnostic accuracy values versus ICA (95.8% in the territory-based analysis). The diagnostic accuracy of CTP was significantly higher than that of coronary CTA (75% vs. 30.5%; p < 0.001). The radiation exposure of coronary CTA + CTP was 4.15 ± 1.5 mSv. Conclusions: In patients with coronary stents, CTP significantly improved the diagnostic rate and accuracy of coronary CTA alone compared with both ICA and invasive FFR as gold standard.

The main purpose of this paper is to describe a software platform dedicated to sea surveillance, capable of detecting and identifying illegal maritime traffic. This platform results from the cascade pipeline of several image processing algorithms that input Radar or Optical imagery captured by satellite-borne sensors and try to identify vessel targets in the scene and provide quantitative descriptors about their shape and motion. This platform is innovative since it integrates in its architecture heterogeneous data and data processing solutions with the goal of identifying navigating vessels in a unique and completely automatic processing streamline. More in detail, the processing chain consists of: (i) the detection of target vessels in an input map, (ii) the estimation of each vessel&rsquo, s most descriptive geometrical and scatterometric (for radar images) features, (iii) the estimation of the kinematics of each vessel, (iv) the prediction of each vessel&rsquo, s forthcoming route, and (v) the visualization of the results in a dedicated webGIS interface. The resulting platform represents a novel tool to counteract unauthorized fishing and tackle irregular migration and the related smuggling activities.