Metabolomics has been shown to be an effective tool for disease diagnosis, biomarker screening and characterization of biological pathways. A total of 140 subjects were included in this study; urine metabolomes of patients with liver cirrhosis (LC, n = 40), patients with hepatocellular carcinoma (HCC; n = 55) and healthy male subjects (n = 45) as a control group were studied. Gas chromatography/mass spectrometry-based urine metabolomics profiles were investigated for all participants. Diagnostic models were constructed with a combination of marker metabolites, using principal components analysis and receiver operator characteristic curves. A total of 57 peaks could be auto-identified of which 13 marker metabolites (glycine, serine, threonine, proline, urea, phosphate, pyrimidine, arabinose, xylitol, hippuric acid, citric acid, xylonic acid and glycerol) were responsible for the separation of HCC group from healthy subjects. Also, eight markers metabolites (glycine, serine, threonine, proline, citric acid, urea, xylitol and arabinose) showed significant differences between the LC group and healthy subjects. No significant difference was detected between HCC and LC groups regarding all these metabolites. Metabolomic profile using GC-MS established an optimized diagnostic model to discriminate between HCC patients and healthy subjects; also it could be useful for diagnosis of LC patients. However, it failed to differentiate between HCC and LC patients.

Background/AimsAscites is a dreadful complication of liver cirrhosis associated with short survival. Large volume paracentesis (LVP) is used to treat tense or refractory ascites. Paracentesis induced circulatory dysfunction (PICD) develops if no plasma expanders are given with ominous complications. To study the effect of ascites flow rate on PICD development.MethodsSixty patients with cirrhosis and tense ascites underwent LVP of 8 L were randomized into 3 equal groups of different flow rate extraction; group I (80 mL/minute), group II (180 mL/minute) and group III (270 mL/minute). Plasma renin activity (PRA) was measured baseline and on day six. PICD was defined as increase in PRA >50% of the pretreatment value.ResultsIn group I through 3; the mean age was (52.5±9.4 vs. 56.4±8.5 vs. 55.8±7.1 years; P>0.05), mean arterial pressure (81.4±5.6 vs. 81.5±7 vs. 79.5±7.2 mmHg; P>0.05), MELD (17.6±4.1 vs. 15.8±4.1 vs. 14.7±4.5). Baseline PRA was comparable (1,366.0±1244.9 vs. 1,151.3±1,444.8 vs. 951.9±1,088 pg/mL; P>0.05). There was no statistically significant (P>0.05) flow mediated changes (Δ) of creatinine (0.23±0.27 vs. 0.38±0.33 vs. 0.26±0.18 mg/dL), MELD (1.25±5.72 vs. 1.70±2.18 vs. 1.45±2.21) or PRA (450.93±614.10 vs. 394.61±954.64 vs. 629.51±1,116.46 pg/mL). PICD was detected in a similar frequency in the three groups (P>0.05). On univariate logistic analysis only female sex was a fairly significant PICD predictor (Wald 3.85, odds ratio 3.14; P=0.05).ConclusionsThe ascites flow rate does not correlate with PICD development.

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Aim: Transforming growth factor (TGF) is overexpressed by tumor cells like other proteins and growth factors. TGF-β1 is then activated in the extracellular compartment but is unable to control cell proliferation because of the absence or low level of TGF-β1 receptors on the plasma membrane of malignant hepatocytes. This potential mechanism might interrupt the autocrine regulation loop of TGF-β1 and its blocking effect on cell proliferation. TGF-β1 is a multifunctional cytokine involved in the regulation of growth and differentiation of both normal and transformed cells. This study aimed to evaluate the association of serum levels of TGF-β1 with disease severity. Methods: A total of 180 subjects were classified into 6 groups according to Barcelona clinic liver cancer (BCLC) classification, 30 patients each: early (BCLC 0 and A), intermediate (BCLC B), advanced stage (BCLC C), and terminal stage (BCLC D) of hepatocellular carcinoma as well as 1 group of patients with cirrhosis only and 1 control group. Serum levels of TGF β1 were measured. Results: Serum levels of TGF-β1 were significantly higher in patients with HCC (1,687.47 ± 1,462.81 pg/mL) than cirrhotics (487.98 ± 344.23 pg/mL, P < 0.001) and controls (250.16 ± 284.61 pg/mL, P < 0.001). Conclusion: TGF-β1 may have a role in tumor growth and progression.