Simplified Aeroelastic Model for Fluid Structure Interaction between Microcantilever Sensors and Fluid Surroundings

Fluid-structural coupling occurs when microcantilever sensors vibrate in a fluid. Due to the complexity of the mechanical characteristics of microcantilevers and lack of high-precision microscopic mechanical testing instruments, effective methods for studying the fluid-structural coupling of microcantilevers are lacking, especially for non-rectangular microcantilevers. Here, we report fluid-structure interactions (FSI) of the cable-membrane structure via a macroscopic study. The simplified aeroelastic model was introduced into the microscopic field to establish a fluid-structure coupling vibration model for microcantilever sensors. We used the finite element method to solve the coupled FSI system. Based on the simplified aeroelastic model, simulation analysis of the effects of the air environment on the vibration of the commonly used rectangular microcantilever was also performed. The obtained results are consistent with the literature. The proposed model can also be applied to the auxiliary design of rectangular and non-rectangular sensors used in fluid environments.     

Unconventional Sequence Requirement for Viral Late Gene Core Promoters of Murine Gammaherpesvirus 68

Infection with the human gammaherpesviruses, Epstein-Barr virus (EBV) and Kaposi''s sarcoma-associated herpesvirus (KSHV), is associated with several cancers. During lytic replication of herpesviruses, viral genes are expressed in an ordered cascade. However, the mechanism by which late gene expression is regulated has not been well characterized in gammaherpesviruses. In this study, we have investigated the cis element that mediates late gene expression during de novo lytic infection with murine gammaherpesvirus 68 (MHV-68). A reporter system was established and used to assess the activity of viral late gene promoters upon infection with MHV-68. It was found that the viral origin of lytic replication, orilyt, must be on the reporter plasmid to support activation of the late gene promoter. Furthermore, the DNA sequence required for the activation of late gene promoters was mapped to a core element containing a distinct TATT box and its neighboring sequences. The critical nucleotides of the TATT box region were determined by systematic mutagenesis in the reporter system, and the significance of these nucleotides was confirmed in the context of the viral genome. In addition, EBV and KSHV late gene core promoters could be activated by MHV-68 lytic replication, indicating that the mechanisms controlling late gene expression are conserved among gammaherpesviruses. Therefore, our results on MHV-68 establish a solid foundation for mechanistic studies of late gene regulation.     

Targeting Homologous Recombination in Notch-Driven C. elegans Stem Cell and Human Tumors

Mammalian NOTCH1-4 receptors are all associated with human malignancy, although exact roles remain enigmatic. Here we employ glp-1(ar202), a temperature-sensitive gain-of-function C. elegans NOTCH mutant, to delineate NOTCH-driven tumor responses to radiotherapy. At ≤20°C, glp-1(ar202) is wild-type, whereas at 25°C it forms a germline stem cell⁄progenitor cell tumor reminiscent of human cancer. We identify a NOTCH tumor phenotype in which all tumor cells traffic rapidly to G2⁄M post-irradiation, attempt to repair DNA strand breaks exclusively via homology-driven repair, and when this fails die by mitotic death. Homology-driven repair inactivation is dramatically radiosensitizing. We show that these concepts translate directly to human cancer models.     

Comprehensible Predictive Modeling Using Regularized Logistic Regression and Comorbidity Based Features

Different studies have demonstrated the importance of comorbidities to better understand the origin and evolution of medical complications. This study focuses on improvement of the predictive model interpretability based on simple logical features representing comorbidities. We use group lasso based feature interaction discovery followed by a post-processing step, where simple logic terms are added. In the final step, we reduce the feature set by applying lasso logistic regression to obtain a compact set of non-zero coefficients that represent a more comprehensible predictive model. The effectiveness of the proposed approach was demonstrated on a pediatric hospital discharge dataset that was used to build a readmission risk estimation model. The evaluation of the proposed method demonstrates a reduction of the initial set of features in a regression model by 72%, with a slight improvement in the Area Under the ROC Curve metric from 0.763 (95% CI: 0.755–0.771) to 0.769 (95% CI: 0.761–0.777). Additionally, our results show improvement in comprehensibility of the final predictive model using simple comorbidity based terms for logistic regression.     

Effects of dietary protein intake on the oxidation of glutamate,glutamine, glucose and palmitate in tissues of largemouth bass (Micropterus salmoides)

Largemouth bass (Micropterus salmoides, a carnivorous fish native to North America) prefers to utilize amino acids as energy sources rather than glucose and fatty acids. However, little is known about the nutritional regulation of substrate oxidation in the fish. Therefore, this study was conducted to determine whether the oxidation of glutamate, glutamine, glucose and palmitate in its tissues might be influenced by dietary protein intake. Juvenile largemouth bass (initial weight 18.3 ± 0.1 g) were fed three isocaloric diets containing 40%, 45% and 50% protein for 8 weeks. The growth performance, energy retention, and lipid retention of juvenile fish increased with increasing dietary protein levels. The rate of oxidation of glutamate by the intestine was much greater than that of glutamine, explaining why increasing the dietary protein content from 40% to 50% had no effect on the serum concentration of glutamate but increased that of glutamine in the fish. The liver of fish fed the 50% protein diet had a higher (P < 0.05) rate of glutamine oxidation than that in the 40% and 45% protein groups. In contrast, augmenting dietary protein content from 40% to 45% increased (P < 0.05) both glutamine and glutamate oxidation in the proximal intestine of the fish and renal glutamine oxidation, without changes in intestinal or renal AA oxidation between the 45% and 50% protein groups. Furthermore, the rates of glucose oxidation in the liver, kidney, and intestine of largemouth bass were decreased in response to an  increase in dietary  protein content   from 40% to 45% and a concomitant decrease in dietary starch content from 22.3% to 15.78%, but did not differ between the 45% and 50% protein groups.   The rates of oxidation of glucose in skeletal muscle and those of palmitate in all tissues (except for the  kidney) were not affected by the diets. Collectively, these results indicate that the largemouth bass can regulate substrate metabolism in a  tissue-specific manner to favor protein and lipid gains as dietary protein content increases from 40% to 50% and have a lower ability to oxidize fatty acids and glucose than amino acids regardless of the dietary protein intake. 

     

Screening of significant biomarkers related with prognosis of liver cancer by lncRNA-associated ceRNAs analysis

This study aimed to identify significant biomarkers related to the prognosis of liver cancer using long noncoding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) analysis. Differentially expressed mRNA and lncRNAs between liver cancer and paracancerous tissues were screened, and the functions of these mRNAs were predicted by gene ontology and pathway enrichment analyses. A ceRNA network consisting of differentially expressed mRNAs and lncRNAs was constructed. LncRNA FENDRR and lncRNA HAND2-AS1 were hub nodes in the ceRNA network. A risk score assessment model consisting of eight genes (PDE2A, ESR1, FBLN5, ALDH8A1, AKR1D1, EHHADH, ADRA1A, and GNE) associated with prognosis were developed. Multivariate Cox regression suggested that both pathologic_T and risk group could be regarded as independent prognostic factors. Furthermore, a nomogram model consisting of pathologic_T and risk group showed a good prediction ability for predicting the survival rate of liver cancer patients. The nomogram model consisting of pathologic_T and a risk score assessment model could be regarded as an independent factor for predicting prognosis of liver cancer.