Differential Protein Expression in Sugarcane during Sugarcane-Sporisorium scitamineum Interaction Revealed by 2-DE and MALDI-TOF-TOF/MS

To understand the molecular basis of a specific plant-pathogen interaction, it is important to identify plant proteins that respond to the pathogen attack. Two sugarcane varieties, NCo376 and Ya71-374, were used in this study. By applying 2-dimensional electrophoresis (2-DE), the protein expression profile of sugarcane after inoculating with Sporisorium scitamineum was analyzed. In total, 23 differentially expressed proteins were identified by MALDI-TOF-TOF/MS. Bioinformatics analysis revealed that the functions of these 20 differential proteins were associated with such functions as photosynthesis, signal transduction, and disease resistance, while the function of the remaining three proteins was not determined. From above, we can assume that the protein regulatory network during the interaction between sugarcane and S. scitamineum is complicated. This represents the first proteomic investigation focused on highlighting the alterations of the protein expression profile in sugarcane exposed to S. scitamineum, and it provides reference information on sugarcane response to S. scitamineum stress at the protein level

Modeling and estimating the capacity of urban transportation network with rapid transit

To study the impact of the rapid transit on the capacity of current urban transportation system, a two-mode network capacity model, including the travel modes of automobile and transit, is developed based on the well-known road network capacity model. It considers that the travel demand accompanying with the regional development will increase in a variable manner on the trip distribution, of which the travel behavior is represented using the combined model split/trip distribution/traffic assignment model. Additionally, the choices of the travel routes, trip destinations and travel modes are formulated as a hierarchical logit model. Using this combined travel demand model in the lower level, the network capacity problem is formulated as a bi-level programming problem. The latest technique of sensitivity analysis is employed for the solution of the bi-level problem in a heuristic search. Numerical computations are demonstrated on an example network, and the before-and-after comparisons of building the new transit lines on the integrated transportation network are shown by the results

Robust Evaluation for Transportation Network Capacity under Demand Uncertainty

As more and more cities in worldwide are facing the problems of traffic jam, governments have been concerned about how to design transportation networks with adequate capacity to accommodate travel demands. To evaluate the capacity of a transportation system, the prescribed origin and destination (O-D) matrix for existing travel demand has been noticed to have a significant effect on the results of network capacity models. However, the exact data of the existing O-D demand are usually hard to be obtained in practice. Considering the fluctuation of the real travel demand in transportation networks, the existing travel demand is represented as uncertain parameters which are defined within a bounded set. Thus, a robust reserve network capacity (RRNC) model using min–max optimization is formulated based on the demand uncertainty. An effective heuristic approach utilizing cutting plane method and sensitivity analysis is proposed for the solution of the RRNC problem. Computational experiments and simulations are implemented to demonstrate the validity and performance of the proposed robust model. According to simulation experiments, it is showed that the link flow pattern from the robust solutions to network capacity problems can reveal the probability of high congestion for each link. Document type: Articl

Robust Evaluation for Transportation Network Capacity under Demand Uncertainty

As more and more cities in worldwide are facing the problems of traffic jam, governments have been concerned about how to design transportation networks with adequate capacity to accommodate travel demands. To evaluate the capacity of a transportation system, the prescribed origin and destination (O-D) matrix for existing travel demand has been noticed to have a significant effect on the results of network capacity models. However, the exact data of the existing O-D demand are usually hard to be obtained in practice. Considering the fluctuation of the real travel demand in transportation networks, the existing travel demand is represented as uncertain parameters which are defined within a bounded set. Thus, a robust reserve network capacity (RRNC) model using min–max optimization is formulated based on the demand uncertainty. An effective heuristic approach utilizing cutting plane method and sensitivity analysis is proposed for the solution of the RRNC problem. Computational experiments and simulations are implemented to demonstrate the validity and performance of the proposed robust model. According to simulation experiments, it is showed that the link flow pattern from the robust solutions to network capacity problems can reveal the probability of high congestion for each link

Characterization of Pure Ductal Carcinoma In Situ on Dynamic Contrast-Enhanced MR Imaging: Do Nonhigh Grade and High Grade Show Different Imaging Features?

To characterize imaging features of pure DCIS on dynamic contrast-enhanced MR imaging (DCE-MRI), 31 consecutive patients (37-81 years old, mean 56), including 2 Grade I, 16 Grade II, and 13 Grade III, were studied. MR images were reviewed retrospectively and the morphological appearances and kinetic features of breast lesions were categorized according to the ACR BI-RADS breast MRI lexicon. DCE-MRI was a sensitive imaging modality in detecting pure DCIS. MR imaging showed enhancing lesions in 29/31 (94%) cases. Pure DCIS appeared as mass type or non-mass lesions on MRI with nearly equal frequency. The 29 MR detected lesions include 15 mass lesions (52%), and 14 lesions showing non-mass-like lesions (48%). For the mass lesions, the most frequent presentations were irregular shape (50%), irregular margin (50%) and heterogeneous enhancement (67%). For the non-mass-like lesions, the clumped internal enhancement pattern was the dominate feature, seen in 9/14 cases (64%). Regarding enhancement kinetic curve, 21/29 (78%) lesions showed suspicious malignant type kinetics. No significant difference was found in morphology (P > .05), tumor size (P = 0.21), and kinetic characteristics (P = .38) between non-high grade (I+II) and high-grade (III) pure DCIS

Estimating the Capacity of Urban Transportation Networks with an Improved Sensitivity Based Method

The throughput of a given transportation network is always of interest to the traffic administrative department, so as to evaluate the benefit of the transportation construction or expansion project before its implementation. The model of the transportation network capacity formulated as a mathematic programming with equilibrium constraint (MPEC) well defines this problem. For practical applications, a modified sensitivity analysis based (SAB) method is developed to estimate the solution of this bilevel model. The high-efficient origin-based (OB) algorithm is extended for the precise solution of the combined model which is integrated in the network capacity model. The sensitivity analysis approach is also modified to simplify the inversion of the Jacobian matrix in large-scale problems. The solution produced in every iteration of SAB is restrained to be feasible to guarantee the success of the heuristic search. From the numerical experiments, the accuracy of the derivatives for the linear approximation could significantly affect the converging of the SAB method. The results also show that the proposed method could obtain good suboptimal solutions from different starting points in the test examples

The Parameters Affecting Antimicrobial Efficiency of Antimicrobial Blue Light Therapy: A Review and Prospect

Antimicrobial blue light (aBL) therapy is a novel non-antibiotic antimicrobial approach which works by generating reactive oxygen species. It has shown excellent antimicrobial ability to various microbial pathogens in many studies. However, due to the variability of aBL parameters (e.g., wavelength, dose), there are differences in the antimicrobial effect across different studies, which makes it difficult to form treatment plans for clinical and industrial application. In this review, we summarize research on aBL from the last six years to provide suggestions for clinical and industrial settings. Furthermore, we discuss the damage mechanism and protection mechanism of aBL therapy, and provide a prospect about valuable research fields related to aBL therapy