Fourth order transport model on Yin-Yang grid by multi-moment constrained finite volume scheme

AbstractA fourth order transport model is proposed for global computation with the application of multi-moment constrained finite volume (MCV) scheme and Yin-Yang overset grid. Using multi-moment concept, local degrees of freedom (DOFs) are point-wisely defined within each mesh element to build a cubic spatial reconstruction. The updating formulations for local DOFs are derived by adopting multi moments as constraint conditions, including volume-integrated average (VIA), point value (PV) and first order derivative value (DV). Using Yin-Yang grid eliminates the polar singularities and results in a quasi-uniform mesh over the whole globe. Each component of Yin-Yang grid is a part of the LAT-LON grid, an orthogonal structured grid, where the MCV formulations designed for Cartesian grid can be applied straightforwardly to develop the high order numerical schemes. Proposed MCV model is checked by widely used benchmark tests. The numerical results show that the present model has fourth order accuracy and is competitive to most existing ones

Predictive assembling model reveals the self-adaptive elastic properties of lamellipodial actin networks for cell migration

Branched actin network supports cell migration through extracellular microenvironments. However, it is unknown how intracellular proteins adapt the elastic properties of the network to the highly varying extracellular resistance. Here we develop a three-dimensional assembling model to simulate the realistic self-assembling process of the network by encompassing intracellular proteins and their dynamic interactions. Combining this multiscale model with finite element method, we reveal that the network can not only sense the variation of extracellular resistance but also self-adapt its elastic properties through remodeling with intracellular proteins. Such resistance-adaptive elastic behaviours are versatile and essential in supporting cell migration through varying extracellular microenvironments. The bending deformation mechanism and anisotropic Poisson’s ratios determine why lamellipodia persistently evolve into sheet-like structures. Our predictions are confirmed by published experiments. The revealed self-adaptive elastic properties of the networks are also applicable to the endocytosis, phagocytosis, vesicle trafficking, intracellular pathogen transport and dendritic spine formation

Mcm5 Represses Endodermal Migration through Cxcr4a-itgb1b Cascade Instead of Cell Cycle Control

Minichromosome maintenance protein 5 (MCM5) is a critical cell cycle regulator; its role in DNA replication is well known, but whether it is involved in the regulation of organogenesis in a cell cycle-independent way, is far from clear. In this study, we found that a loss of mcm5 function resulted in a mildly smaller liver, but that mcm5 overexpression led to liver bifida. Further, the data showed that mcm5 overexpression delayed endodermal migration in the ventral–dorsal axis and induced the liver bifida. Cell cycle analysis showed that a loss of mcm5 function, but not overexpression, resulted in cell cycle delay and increased cell apoptosis during gastrulation, implying that liver bifida was not the result of a cell cycle defect. In terms of its mechanism, our data proves that mcm5 represses the expression of cxcr4a, which sequentially causes a decrease in the expression of itgb1b during gastrulation. The downregulation of the cxcr4a-itgb1b cascade leads to an endodermal migration delay during gastrulation, as well as to the subsequent liver bifida during liver morphogenesis. In conclusion, our results suggest that in a cell cycle-independent way, mcm5 works as a gene expression regulator, either partially and directly, or indirectly repressing the expression of cxcr4a and the downstream gene itgb1b, to coordinate endodermal migration during gastrulation and liver location during liver organogenesis

Exploratory analysis of protein translation regulatory networks using hierarchical random graphs

Abstract Background Protein translation is a vital cellular process for any living organism. The availability of interaction databases provides an opportunity for researchers to exploit the immense amount of data in silico such as studying biological networks. There has been an extensive effort using computational methods in deciphering the transcriptional regulatory networks. However, research on translation regulatory networks has caught little attention in the bioinformatics and computational biology community. Results In this paper, we present an exploratory analysis of yeast protein translation regulatory networks using hierarchical random graphs. We derive a protein translation regulatory network from a protein-protein interaction dataset. Using a hierarchical random graph model, we show that the network exhibits well organized hierarchical structure. In addition, we apply this technique to predict missing links in the network. Conclusions The hierarchical random graph mode can be a potentially useful technique for inferring hierarchical structure from network data and predicting missing links in partly known networks. The results from the reconstructed protein translation regulatory networks have potential implications for better understanding mechanisms of translational control from a system’s perspective

Electrochim. Acta

An ethylene glycol (EG)-based approach has been developed for the synthesis of Pt/C catalysts with uniform Pt nanoparticles. A number of characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and electrochemical measurements are used to characterize the as-prepared Pt catalysts. The well-dispersed Pt nanoparticles with average size of approximate 2 nm could be obtained in the EG/water mixture with volume ratio of 1/1, which display higher activity for methanol oxidation than that of the Pt/C products prepared at other EG/water volume ratios (0:1, 2:1, and 1:0). In particular, the performance of the Pt nanoparticles prepared at EG/water volume ratio of 1/1 in the membrane electrode assembly for direct methanol fuel cells has also been evaluated and benchmarked by commercial Pt/C catalysts. This study offers a vivid example to synthesize Pt nanoparticles with fine size and good catalytic activity by simply tuning the solvent ratio in colloidal chemistry methods. (C) 2013 Elsevier Ltd. All rights reserved.An ethylene glycol (EG)-based approach has been developed for the synthesis of Pt/C catalysts with uniform Pt nanoparticles. A number of characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and electrochemical measurements are used to characterize the as-prepared Pt catalysts. The well-dispersed Pt nanoparticles with average size of approximate 2 nm could be obtained in the EG/water mixture with volume ratio of 1/1, which display higher activity for methanol oxidation than that of the Pt/C products prepared at other EG/water volume ratios (0:1, 2:1, and 1:0). In particular, the performance of the Pt nanoparticles prepared at EG/water volume ratio of 1/1 in the membrane electrode assembly for direct methanol fuel cells has also been evaluated and benchmarked by commercial Pt/C catalysts. This study offers a vivid example to synthesize Pt nanoparticles with fine size and good catalytic activity by simply tuning the solvent ratio in colloidal chemistry methods. (C) 2013 Elsevier Ltd. All rights reserved

AN ANALYSIS OF INFLUENCING FACTORS FOR SHORT-TERM PROGNOSIS AFTER ENDOVASCULAR TREATMENT IN ELDERLY PATIENTS WITH POSTERIOR CIRCULATION INFARCTION

Objective To explore the influencing factors for short-term prognosis after endovascular treatment in elderly patients with posterior circulation infarction (POCI). Methods A retrospective analysis was performed on the clinical data of 50 elderly patients with POCI who received endovascular treatment in the Nuclear Industry 416 Hospital from January 2019 to December 2020. The clinical data included patients’ preoperative general status (age, sex, smoking history, and alcohol abuse history), past disease history (diabetes, hypertension, hyperuricemia, and transient ischemic attack), post-onset indicators [onset-to-door time (ODT), door-to-needle time (DNT), NIH Stroke Scale (NIHSS) on admission], and postoperative conditions (immediate postoperative NIHSS, revascularization, and postoperative complications). The patients were divided into good prognosis group and poor prognosis group according to modified Rankin Scale (mRS) score 90 d after endovascular treatment and were analyzed for the differences in the above indicators. Meanwhile, a multivariate logistic regression analysis was performed on the influencing factors for patients’ short-term prognosis after endovascular treatment. Results There were 20 and 30 patients in the good prognosis group and poor prognosis group, respectively, demonstrating significant differences between the two groups in nine indicators [systolic blood pressure, glycosylated hemoglobin (HbA1c), serum uric acid, total cholesterol, postoperative modified Thrombolysis in Cerebral Infarction (mTICI) grade, preoperative NIHSS score, immediate postoperative NIHSS score, ODT, and postoperative stroke-related pneumonia] (t=2.30-4.13,χ2=6.35,7.07,P<0.05). The multivariate logistic regression analysis showed that HbA1c ≥6.5%, serum uric acid ≥420 mmol/L (male) or 360 mmol/L (female), postoperative mTICI grade (blood vessel obstruction), and immediate postoperative NIHSS score ≥10 were risk factors for patients’ short-term prognosis after endovascular treatment (P<0.05). Conclusion HbA1c, serum uric acid, postoperative mTICI grade, and immediate postoperative NIHSS score are possible influencing factors for short-term prognosis after endovascular treatment in patients with POCI. It is important to enhance postoperative assessments of the above indicators and to receive active treatment for optimal outcomes