Non-alcoholic liver disease (NAFLD) defines liver abnormalities ranging from simple steatosis to nonalcoholic steatohepatitis with or without cirrhosis development, occurring in the absence of significant alcohol consumption, use of teratogenic medication, or hereditary disorders. The association between NAFLD and metabolic syndrome is well documented and widely recognized. Obesity, type 2 diabetes mellitus (T2DM), and dyslipidemia are the most common metabolic risk factors associated with NAFLD. Among the components of metabolic syndrome, current evidence strongly indicates obesity and diabetes as hepatocellular carcinoma (HCC) risk factors. There is also growing evidence that suggests an increased risk of HCC in NAFLD patients, even surpassing other etiologies in some high-income countries. Epidemiologic data demonstrate a parallel rise in prevalence of obesity, diabetes, NAFLD, and HCC. As obesity and its related diseases have steadily afflicted larger populations, HCC incidence is expected to increase in the future. Pathophysiologic mechanisms that underlie NAFLD development and subsequent progression to nonalcoholic steatohepatitis and cirrhosis (insulin resistance and hyperinsulinemia, oxidative stress, hepatic stellate cell activation, cytokine/adipocytokine signaling pathways, and genetic and environmental factors) appear to play a significant role in the development of NAFLD-related HCC. However, a comprehensive view of molecular mechanisms linking obesity, T2DM, and NAFLD-related HCC, as well as the exact sequence of molecular events, is still not understood in its entirety. Good-quality data are still necessary, and efforts should continue towards better understanding the underlying carcinogenic mechanisms of NAFLD-related HCC. In this paper, we aimed to centralize the most important links supporting these relationships, focusing on obesity, T2DM, and NAFLD-related HCC, as well as point out the major gaps in knowledge regarding the underlying molecular mechanisms behind them.

This study aimed to evaluate the subacute effect of two types of Ag-NPs(EG-AgNPs and PVP-EG-AgNPs) on antioxidant/pro-oxidant balance in rats. Seventy Wistar rats (35 males and 35 females) were divided in 7 groups and intraperitoneally exposed for 28 days to 0, 1, 2 and 4 mg/kg bw/day EG-Ag-NPs and 1, 2 and 4 mg/kg bw/day PVP- EG-Ag-NPs. After 28 days, the blood was collected, and the total antioxidant capacity (TAC), thiobarbituric reactive species (TBARS),protein carbonyl (PROTC) levels, reduced glutathione (GSH) levels and catalase (CAT) activity were determined. EG-Ag-NPs determined protective antioxidant effects in a dose-dependent manner. The exposure to the 4 mg/kg bw/day EG-Ag-NPs determines both in males and females a significant increase in TAC and CAT and a significant decrease in TBARS and PROTC only in females. The PVP-EG-AgNPs showed a different trend compared to EG-AgNPs. At 4 mg/kg bw/day the PVP-EG-AgNPs induce increased PROTC levels and decreased GSH (males and females) and TAC levels (males). The different mechanisms of EG-AgNPs and PVP-EG-AgNPs on antioxidant-/pro-oxidant balance can be explained by the influence of coating agent used for the preparation of the nanoparticles in the formation and composition of protein corona that influence their pathophysiology in the organism.

Purpose: To assess the value of contrast-enhanced ultrasound (CEUS) for differentiating malignant from benign focal liver lesions (FLLs) and for diagnosing different FLL types. Material and Methods: CEUS performed in 14 Romanian centers was prospectively collected between February 2011 and June 2012. The inclusion criteria were: age > 18 years; patients diagnosed with 1 – 3 de novo FLLs on B-mode ultrasound; reference method (computed tomography (CT), magnetic resonance imaging (MRI) or biopsy) available; patient’s informed consent. FLL lesions were characterized during CEUS according to the European Federation of Societies for Ultrasound in Medicine and Biology guidelines. For statistical analysis, indeterminate FLLs at CEUS were rated as false classifications. Results: A total number of 536 cases were included in the final analysis, 344 malignant lesions (64.2 %) and 192 benign lesions (35.8 %). The reference method was: CT/MRI – 379 cases (70.7 %), pathological exam – 150 cases (27.9 %) and aspiration of liver abscesses – 7 cases (1.4 %). CEUS was conclusive in 89.3 % and inconclusive in 10.7 % of cases. To differentiate between malignant and benign FLLs, CEUS had 85.7 % sensitivity, 85.9 % specificity, 91.6 % positive predictive value, 77.1 % negative predictive value and 85.8 % accuracy. The CEUS accuracy for differentiation between malignant and benign liver lesions was similar in tumors with diameter ≤ 2 cm and those with diameter > 2 cm. Conclusion: CEUS represents a useful method in clinical practice for differentiating between malignant and benign FLLs detected on standard ultrasonography, and the results of this study are in concordance with previous multicenter studies: DEGUM (Germany) and STIC (France). Ziel: Bewertung des kontrastverstärkten Ultraschalls (CEUS) zur Differenzierung zwischen malignen und gutartigen fokalen Leberläsionen (FLL) und bei der Diagnose verschiedener FLL-Typen. Material und Methoden: CEUS wurde in 14 rumänischen Zentren von Februar 2011 bis Juni prospektiv durchgeführt und erfasst. Die Einschlusskriterien waren: Alter > 18 Jahre; Diagnose von 1 – 3 FLL de novo im B-Bild; verfügbare Referenzmethode (Computertomografie – CT, Magnetresonanz-Tomografie – MRT oder Biopsie); Einverständniserklärung des Patienten („informed consent“). Die FLL-Läsionen wurden während des CEUS gemäß den Richtlinien der „European Federation of Societies for Ultrasound in Medicine and Biology“ charakterisiert. Für die statistische Auswertung wurden durch CEUS nicht bestimmbare FLLs als falsche Klassifizierungen gewertet. Ergebnisse: Insgesamt wurden 536 Fälle in die Endanalyse eingeschlossen, 344 maligne (64,2 %) und 192 benigne Läsionen (35,8 %). Die Referenzmethoden waren: CT/MRT – 379 Fälle (70,7 %), pathologische Untersuchung – 150 Fälle (27,9 %) und Aspiration von Leberabszessen – 7 Fälle (1,4 %). In 89,3 % der Fälle war CEUS eindeutig und in 10,7 % nicht eindeutig. Bei der Differenzierung zwischen malignen und gutartigen FLLs betrug die Sensitivität des CEUS 85,7 %, die Spezifität 85,9 %, der positive Vorhersagewert 91,6 %, der negative Vorhersagewert 77,1 % und die Genauigkeit 85,8 %. Die Genauigkeit des CEUS bei der Differenzierung zwischen malignen und benignen Leberläsionen war bei Tumoren mit einem Durchmesser von < 2 cm und > 2 cm Durchmesser gleich. Schlussfolgerung: CEUS ist in der klinischen Praxis eine nützlich, um maligne und benigne FLL, die in einer Standard-US-Untersuchung entdeckt wurden, zu differenzieren. Die Ergebnisse dieser Studie stimmen mit früheren Multizenter-Studien aus Deutschland (DEGUM) und Frankreich (STIC) überein.

Psychosocial stress and liver disease status

To study the role of time-intensity curve (TIC) analysis parameters in a complex system of neural networks designed to classify liver tumors. We prospectively included 112 patients with hepatocellular carcinoma (HCC) (n = 41), hypervascular (n = 20) and hypovascular (n = 12) liver metastases, hepatic hemangiomas (n = 16) or focal fatty changes (n = 23) who underwent contrast-enhanced ultrasonography in the Research Center of Gastroenterology and Hepatology, Craiova, Romania. We recorded full length movies of all contrast uptake phases and post-processed them offline by selecting two areas of interest (one for the tumor and one for the healthy surrounding parenchyma) and consecutive TIC analysis. The difference in maximum intensities, the time to reaching them and the aspect of the late/portal phase, as quantified by the neural network and a ratio between median intensities of the central and peripheral areas were analyzed by a feed forward back propagation multi-layer neural network which was trained to classify data into five distinct classes, corresponding to each type of liver lesion. The neural network had 94.45% training accuracy (95% CI: 89.31%-97.21%) and 87.12% testing accuracy (95% CI: 86.83%-93.17%). The automatic classification process registered 93.2% sensitivity, 89.7% specificity, 94.42% positive predictive value and 87.57% negative predictive value. The artificial neural networks (ANN) incorrectly classified as hemangyomas three HCC cases and two hypervascular metastases, while in turn misclassifying four liver hemangyomas as HCC (one case) and hypervascular metastases (three cases). Comparatively, human interpretation of TICs showed 94.1% sensitivity, 90.7% specificity, 95.11% positive predictive value and 88.89% negative predictive value. The accuracy and specificity of the ANN diagnosis system was similar to that of human interpretation of the TICs (P = 0.225 and P = 0.451, respectively). Hepatocellular carcinoma cases showed contrast uptake during the arterial phase followed by wash-out in the portal and first seconds of the late phases. For the hypovascular metastases did not show significant contrast uptake during the arterial phase, which resulted in negative differences between the maximum intensities. We registered wash-out in the late phase for most of the hypervascular metastases. Liver hemangiomas had contrast uptake in the arterial phase without agent wash-out in the portal-late phases. The focal fatty changes did not show any differences from surrounding liver parenchyma, resulting in similar TIC patterns and extracted parameters. Neural network analysis of contrast-enhanced ultrasonography - obtained TICs seems a promising field of development for future techniques, providing fast and reliable diagnostic aid for the clinician.