The Regulatory Role of MeAIB in Protein Metabolism and the mTOR Signaling Pathway in Porcine Enterocytes.

Amino acid transporters play an important role in cell growth and metabolism. MeAIB, a transporter-selective substrate, often represses the adaptive regulation of sodium-coupled neutral amino acid transporter 2 (SNAT2), which may act as a receptor and regulate cellular amino acid contents, therefore modulating cellular downstream signaling. The aim of this study was to investigate the effects of MeAIB to SNAT2 on cell proliferation, protein turnover, and the mammalian target of rapamycin (mTOR) signaling pathway in porcine enterocytes. Intestinal porcine epithelial cells (IPEC)-J2 cells were cultured in a high-glucose Dulbecco's modified Eagle's (DMEM-H) medium with 0 or 5 mmoL/L System A amino acid analogue (MeAIB) for 48 h. Cells were collected for analysis of proliferation, cell cycle, protein synthesis and degradation, intracellular free amino acids, and the expression of key genes involved in the mTOR signaling pathway. The results showed that SNAT2 inhibition by MeAIB depleted intracellular concentrations of not only SNAT2 amino acid substrates but also of indispensable amino acids (methionine and leucine), and suppressed cell proliferation and impaired protein synthesis. MeAIB inhibited mTOR phosphorylation, which might be involved in three translation regulators, EIF4EBP1, IGFBP3, and DDIT4 from PCR array analysis of the 84 genes related to the mTOR signaling pathway. These results suggest that SNAT2 inhibition treated with MeAIB plays an important role in regulating protein synthesis and mTOR signaling, and provide some information to further clarify its roles in the absorption of amino acids and signal transduction in the porcine small intestine

A comparison of time preference functional forms: Evidence from a field experiment

A comprehensive understanding of individual-level discounting behaviours is crucial because of its implications for designing financial incentive interventions encouraging health behaviors. This paper estimates mixture models to determine probabilistically the discounting functional form which has the best fit to discounting behaviours, on the basis of a series of incentive-compatible time and risk preference field experiments conducted among 176 civil servants in Belfast, Northern Ireland. Time preference was structurally estimated while controlling for risk preference, background consumption, and probability weighting. The results suggested that future monetary incentives were discounted hyperbolically rather than exponentially and that a generalised hyperbolic form had the best fit among a series of alternative functional forms. Our results also showed that the failure to adopt an appropriate type of functional form led to significantly different discount rates and misleading associations between time preference and real-world behaviours such as smoking. Identifying the best-fit discounting functional form may be a useful tool to improve the effectiveness of financial incentive interventions such that more immediate rewards should be provided to the target population with a higher degree of time-inconsistency.Keywords: Hyperbolic discounting; Time preference; Risk preference; Mixture models; Smokin

Data-driven train set crash dynamics simulation

© 2016 Informa UK Limited, trading as Taylor & Francis GroupTraditional finite element (FE) methods are arguably expensive in computation/simulation of the train crash. High computational cost limits their direct applications in investigating dynamic behaviours of an entire train set for crashworthiness design and structural optimisation. On the contrary, multi-body modelling is widely used because of its low computational cost with the trade-off in accuracy. In this study, a data-driven train crash modelling method is proposed to improve the performance of a multi-body dynamics simulation of train set crash without increasing the computational burden. This is achieved by the parallel random forest algorithm, which is a machine learning approach that extracts useful patterns of force–displacement curves and predicts a force–displacement relation in a given collision condition from a collection of offline FE simulation data on various collision conditions, namely different crash velocities in our analysis. Using the FE simulation results as a benchmark, we compared our method with traditional multi-body modelling methods and the result shows that our data-driven method improves the accuracy over traditional multi-body models in train crash simulation and runs at the same level of efficiency

Contra-Directional Expression of Serum Homocysteine and Uric Acid as Important Biomarkers of Multiple System Atrophy Severity: A Cross-Sectional Study

Aims. There is evidence suggesting that inflammatory responses play a critical role in the pathogenesis of multiple system atrophy (MSA). Whether inflammatory mediators can be used as reliable biomarkers to detect the severity and progression of MSA remains largely unknown. Methods. We performed a cross-sectional study that included 47 patients with MSA and 50 healthy age-matched controls. Serum levels of homocysteine (Hcy), uric acid (UA) and C-reactive protein (CRP) were measured. These levels positively correlated with the severity of MSA, based on both motor and non-motor symptoms (NMS). Several scales were used to rate the severity of MSA, including the Unified multiple system atrophy rating scale (UMSARS), Parkinson’s disease sleep scale (PDSS), Non-motor Symptoms Scale (NMSS), the Schwab & England Activities of Daily Living Scale (ADL), Webster Scale, modified Hoehn and Yahr staging scale (H&Y), and the Mini-Mental State Examination (MMSE). Receiver Operating Characteristic (ROC) curves was applied to map the diagnostic accuracy of MSA against healthy subjects. Results. Compared with healthy subjects, we found that serum Hcy was higher, UA was lower, and CRP levels were unchanged in MSA patients. These findings were especially prominent in male patients. No significant differences of serum Hcy and UA were observed between patients of MSA and PD. Interestingly, there was a significant correlation between Hcy levels and MSA severity such as movement dysfunction, declined cognition, and cardiovascular symptoms. Additionally, the ROC curve for the combination of Hcy and UA (AUC 0.736) showed potential diagnostic value in discriminating MSA from healthy subjects. Conclusions. Our findings suggest that the inflammatory mediators Hcy and UA may play important roles in the pathogenesis of MSA. The measurement of serum Hcy and UA levels could then be a useful tool to accurately distinguish MSA from healthy subjects