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BackgroundThis study aims to construct and verify a nomogram model for microvascular invasion (MVI) based on hepatocellular carcinoma (HCC) tumor characteristics and differential protein expressions, and explore the clinical application value of the prediction model.MethodsThe clinicopathological data of 200 HCC patients were collected and randomly divided into training set and validation set according to the ratio of 7:3. The correlation between MVI occurrence and primary disease, age, gender, tumor size, tumor stage, and immunohistochemical characteristics of 13 proteins, including GPC3, CK19 and vimentin, were statistically analyzed. Univariate and multivariate analyzes identified risk factors and independent risk factors, respectively. A nomogram model that can be used to predict the presence of MVI was subsequently constructed. Then, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were conducted to assess the performance of the model.ResultsMultivariate logistic regression analysis indicated that tumor size, GPC3, P53, RRM1, BRCA1, and ARG were independent risk factors for MVI. A nomogram was constructed based on the above six predictors. ROC curve, calibration, and DCA analysis demonstrated the good performance and the clinical application potential of the nomogram model.ConclusionsThe predictive model constructed based on the clinical characteristics of HCC tumors and differential protein expression patterns could be helpful to improve the accuracy of MVI diagnosis in HCC patients.

Hyperlipidemia is a common metabolic disorder that can lead to cardiovascular disease. PDK4 is a key enzyme that regulates glucose and fatty acid metabolism and homeostasis. The aim of this study is to explore the correlation between PDK4 expression and dyslipidemia in obese children, and to find new therapeutic targets for hyperlipidemia in children. The expression of PDK4 in serum was detected by qRT-PCR. Receiver operating characteristic curve was used to analyze the relationship between PDK4 and dyslipidemia. Upstream miRNAs of PDK4 were predicted by the database and verified by dual luciferase reporter gene assay and detected by qRT-PCR. The hyperlipidemia mouse model was established by high-fat diet (HFD) feeding, and the metabolic disorders of mice were detected. PDK4 is poorly expressed in the serum of obese children. The upstream of PDK4 may be inhibited by miR-107, miR-27a-3p, and miR-106b-5p, which are highly expressed in the serum of obese children. Overexpression of PDK4 improves lipid metabolism in HFD mice. miR-27a-3p silencing upregulates PDK4 to improve lipid metabolism. In conclusion, PDK4 has a diagnostic effect on dyslipidemia in children, while lipid metabolism in hyperlipidemic mice could be mitigated by upregulation of PDK4, which was inhibited by miR-107, miR-27a-3p and miR-106b-5p on upstream. [ABSTRACT FROM AUTHOR]

Hydrogen sulfide (H2S) is a crucial endogenous signaling component in organisms that is involved in redox homeostasis and numerous biological processes. Modern medical research has confirmed that hydrogen sulfide plays an important role in the pathogenesis of many diseases. Herein, a fluorescent probe Eu(ttbd)3abt based on europium(III) complex was designed and synthesized for the detection of H2S. Eu(ttbd)3abt exhibited significant quenching for H2S at long emission wavelength (625 nm), with rapid detection ability (less than 2 min), high sensitivity [limit of detection (LOD) = 0.41 μM], and massive Stokes shift (300 nm). Additionally, this probe showed superior selectivity for H2S despite the presence of other possible interference species such as biothiols. Furthermore, the probe Eu(ttbd)3abt was successfully applied to detect H2S in water samples. [ABSTRACT FROM AUTHOR]