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Purpose: Long noncoding RNAs (lncRNAs) might be closely associated with hepatocellular carcinoma (HCC) progression and could serve as diagnostic and prognostic markers. This study aimed to investigate lncRNA-based diagnostic biomarkers for hepatitis B virus (HBV)-associated HCC. Materials and Methods: High‐throughput transcriptome sequencing was conducted on the liver tissues of 15 patients with HBV-associated liver diseases (5 with chronic hepatitis B [CHB], 5 with liver cirrhosis [LC], and 5 with HCC). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to analyze lncRNA expressions. Potential diagnostic performance for HBV-associated HCC screening was evaluated. Results: Through trend analysis and functional analysis, we found that 8 lncRNAs were gradually upregulated and 1 lncRNA was progressively downregulated by regulation of target mRNAs and downstream HCC-associated signaling pathways. The validation of dysregulated lncRNAs in peripheral blood mononuclear cells (PBMCs) and HCC tissues by qRT-PCR revealed that ADAMTSL4-AS1, SOCS2-AS1, and AC067931 were significantly increased in HCC compared with CHB and cirrhosis. Moreover, differentially expressed lncRNAs were aberrantly elevated in Huh7, Hep3B, HepG2, and HepG2.215 cells compared with LX2 cells. Furthermore, ADAMTSL4-AS1, SOCS2-AS1, and AC067931 were identified as novel biomarkers for HBV-associated HCC. For distinguishing HCC from CHB, ADAMTSL4-AS1, AC067931, and SOCS2-AS1 combined with alpha-fetoprotein (AFP) had an area under the curve (AUC) of 0.945 (sensitivity, 83.9%; specificity, 89.8%). Similarly, for distinguishing HCC from LC, this combination had an AUC of 0.871 (sensitivity, 91.1%; specificity, 68.2%). Furthermore, this combination showed the highest diagnostic ability to distinguish HCC from CHB and LC (AUC, 0.905; sensitivity, 91.1%; specificity, 75.3%). In particular, this combination identified AFP-negative (AFP < 20 ng/mL) (AUC = 0.814), small (AUC = 0.909), and early stage (AUC = 0.863) tumors. Conclusion: ADAMTSL4-AS1, SOCS2-AS1, and AC067931 combined with AFP in PBMCs may serve as a noninvasive diagnostic biomarker for HBV-associated HCC, especially AFP-negative, small, and early stage HCC. [ABSTRACT FROM AUTHOR]

This paper proposes a novel inertia-enhanced distributed control method to complement the inertia of microgrids. The rate of change of frequency (RoCoF) and the rate of change of voltage (RoCoV) are employed in this paper to quantify the frequency inertia and voltage inertia, respectively. Then, a fully distributed algorithm with constrained changing rates is proposed. By bounding the changing rates of frequency and voltage during the consensus control, the algorithm can address the consensus problem while enhancing the inertia of microgrids. Compared with most inertia control methods, the proposed method can utilize the reserve power of scattered DGs to supply inertia. Besides, it performs better under disturbances and delays than conventional distributed control methods. The effectiveness of the proposed method is validated by several cases in MATLAB/Simulation and a hardware experiment. [ABSTRACT FROM AUTHOR]

Lacticaseibacillus rhamnosus is a recognized probiotic that is widely used in scientific research and clinical applications. This study found that the Lacticaseibacillus rhamnosus GG (LGG) strain can reduce the adhesion of Escherichia coli (E. coli) to primary chicken intestinal epithelial cells by 75.7% and inhibit 41.7% of the E. coli that adhere to intestinal epithelial cells. Additionally, LGG showed strong inhibitory ability on the growth of E. coli , Staphylococcus aureus , Salmonella Paratyphi B, and Salmonella Enteritidis in vitro. Furthermore, the influence of LGG on the growth performance, intestinal flora, immunity, and disease resistance of chickens was explored. Chickens fed with LGG exhibited increased average daily weight gain and concentrations of sIgA, IgG, and IgM than did controls. After 21 days of feeding, a diet with LGG increased the diversity of intestinal microbiota and maintained intestinal health. Moreover, LGG promoted immunologic barriers by upregulating cytokines and chemokines via the Toll-like receptor. The major pro-inflammatory factors, including Myd88 , NF- κ B , Il6 , and Il8 , were upregulated compared to controls. After being challenged with E. coli , the survival rate of chickens fed with LGG was significantly higher than those in the control group, and decreased numbers of E. coli were detected in the heart and lungs of the LGG group. In summary, oral administration of LGG to chickens could improve growth performance, maintain intestinal homeostasis, and enhance innate immune response and disease resistance. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether area under the curve (AUC) of oral glucose tolerance test (OGTT) could work as a predictor of outcomes of gestational diabetes mellitus (GDM) on condition that blood glucose is controlled., Methods: A total of 1 796 women who had a standard antenatal care in Peking University First Hospital and gave single live births from July 1, 2011 to December 31, 2 013 were included. They should be diagnosed of GDM by the diagnosis criteria of gestational diabetes published by the Ministry of Health of PRC and diabetes pre-pregnancy excluded. Data were analyzed with SPSS 17.0, grouping by AUC., Results: (1) Women with higher AUC had a rising trend of age and a downward trend of gestational weight gain, however, not statistically significant [specifically, in the four group of less than 15.00 mmol · L⁻¹ · h⁻¹, 15.00 to 16.79 mmol · L⁻¹ · h⁻¹, 16.80 to 17.99 mmol · L⁻¹ · h⁻¹ and 18.00 mmol · L⁻¹ · h⁻¹ or more, gestational weight gain was (15.3 ± 5.2), (14.1 ± 4.8), (13.5 ± 4.7) and (13.1 ± 4.8) kg]. The prevalence of macrosomia raised while AUC increased. Those with an AUC of lower than 15.00 (mmol · L⁻¹ · h⁻¹) had a lower risk of macrosomia (P = 0.04). But those with an AUC of 18.00 (mmol · L⁻¹ · h⁻¹) or more had a higher risk of macrosomia (P = 0.02). There was a rising trend in premature birth and preeclampsia with AUC increasing but not significant (the prevalence of premature birth was 4.38%, 5.36%, 7.71% and 7.94% while that of preeclampsia was 2.85%, 4.69%, 4.67% and 5.08% in these four groups). (2) The prevalence of macrosomia was 12.76% (54/423) when overweight pre-pregnancy, significantly higher compared with 5.87% (65/1 107) in normal group. The prevalence of preeclampsia was 5.91% (25/423) and 3.34% (37/1 107) in those two groups, which was also significantly different. The obese group had a statistically highest prevalence of preeclampsia of 9.23% (12/130). (3) AUC (P < 0.05, OR = 1.113, 95% CI: 1.008-1.218), as well as gestational weight gain (P < 0.05, OR = 1.520, 95% CI: 1.279-1.806) and pre-pregnancy BMI (P < 0.05, OR = 1.183, 95% CI: 1.125-1.243) made a difference in the prevalence of macrosomia. Meanwhile, pre-pregnancy BMI made sense in the prevalence of premature labor (P < 0.05, OR = 1.059, 95% CI: 1.003-1.119) and preeclampsia (P < 0.01, OR = 1.202, 95% CI: 1.123-1.286)., Conclusions: AUC, as well as pre-pregnancy BMI and gestational weight gain have a significant impact on outcomes of GDM, macrosomia especially, though blood glucose is controlled. Meanwhile, AUC might be considered as a predictor of macrosomia.