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Bacteria commonly form aggregates in a range of coral species [termed coral-associated microbial aggregates (CAMAs)], although these structures remain poorly characterized despite extensive efforts studying the coral microbiome. Here, we comprehensively characterize CAMAs associated with

The effect of phosphorus-containing ligands on the structure, energetics and properties of the (CdSe)n clusters (n = 3, 6, and 10) with different number of PH3 and PMe3 ligands were studied by using density functional theory calculations. The P atom in the ligand interacts with Cd and forms a strong Cd–P coordination bond. The introduction of ligands does not change the cluster architecture, but leads to considerable changes in Cd–Se bondlength, charge distribution, binding energy, HOMO–LUMO gap and optical absorption. The ligand influence is enhanced with increasing ligand coverage. A blueshift in absorption band was predicted for the clusters with increasing ligands, resulting from the electron donating characteristics of the ligands that hamper electron transition from Se to Cd. As P-containing ligands are often used in the preparation of CdSe nanocrystals, our calculations reveal the influence of ligand-cluster interaction on the cluster geometrical and electronic properties, which would be helpful for the nanocrystal design and synthesis.

A Lagrangian relaxation (LR) approach was presented which is with machine capacity relaxation and operation precedence relaxation for solving a flexible job shop (FJS) scheduling problem from the steelmaking-refining-continuous casting process. Unlike the full optimization of LR problems in traditional LR approaches, the machine capacity relaxation is optimized asymptotically, while the precedence relaxation is optimized approximately due to the NP-hard nature of its LR problem. Because the standard subgradient algorithm (SSA) cannot solve the Lagrangian dual (LD) problem within the partial optimization of LR problem, an effective deflected-conditional approximate subgradient level algorithm (DCASLA) was developed, named as Lagrangian relaxation level approach. The efficiency of the DCASLA is enhanced by a deflected-conditional epsilon-subgradient to weaken the possible zigzagging phenomena. Computational results and comparisons show that the proposed methods improve significantly the efficiency of the LR approach and the DCASLA adopting capacity relaxation strategy performs best among eight methods in terms of solution quality and running time.

There are many types of disturbances that upset the plan in steelmaking and continuous casting (SCC) production, including processing time variation, temperature variation, quality variation, machine failures, which could cause the static schedule to become inefficient and even infeasible. It is necessary to adjust the schedule or generate a new executable schedule upon the occurrence of unanticipated disruptions and changes. Two rescheduling methods are presented: the partial rescheduling and complete rescheduling. The former refers to the right shift partial rescheduling based on continuous casting, the partial rescheduling based on case-based reasoning and man-computer interaction. The latter refers to the complete rescheduling considering changeable processing time, the complete rescheduling considering changeable processing time and production path. The mathematical models of two class complete rescheduling are formulated, and the solving methods are also given. The intelligent rescheduling system for SCC production with these methods is successfully applied to one large steel plant, and rapidly optimal rescheduling is achieved when disturbances occur.

With the development of the hardware in Chinese iron industry, scheduling technology is becoming key obstacles that hold back the further development in iron enterprise. And the scheduling theory about the process of steelmaking-continuous casting can’t fit the actual production. To improve this situation, we manage to develop the system the combine the editable Gantt chart and optimization models. On one hand, this system can use Gantt chart to show dispatcher real-time schedule and allow dispatcher reschedule on Gantt chart. On the other hand, the system can detect the change dispatcher made and use the optimization model to complete the whole schedule. In a word, this system takes advantage of the scheduling ability of dispatcher and the high speed calculation of computer to reschedule efficiently.

Germination followed by seedling growth constitutes two essential steps in the initiation of a new life cycle in plants, and in cereals, completion of these steps is regulated by sugar starvation and the hormone gibberellin. A calcium-dependent protein kinase 1 gene (OsCDPK1) was identified by differential screening of a cDNA library derived from sucrose-starved rice suspension cells. The expression of OsCDPK1 was found to be specifically activated by sucrose starvation among several stress conditions tested as well as activated transiently during post-germination seedling growth. In gain- and loss-of-function studies performed with transgenic rice overexpressing a constitutively active or RNA interference gene knockdown construct, respectively, OsCDPK1 was found to negatively regulate the expression of enzymes essential for GA biosynthesis. In contrast, OsCDPK1 activated the expression of a 14-3-3 protein, GF14c. Overexpression of either constitutively active OsCDPK1 or GF14c enhanced drought tolerance in transgenic rice seedlings. Hence, our studies demonstrated that OsCDPK1 transduces the post-germination Ca(2+) signal derived from sugar starvation and GA, refines the endogenous GA concentration and prevents drought stress injury, all essential functions to seedling development at the beginning of the life cycle in rice.

In the steelmaking and continuous casting (SMCC) production process, operation time delay may lead to casting break or processing conflict so that the initial scheduling plan becomes unrealizable. Existing research methods are difficult to guarantee the accuracy of the model and successful application to actual applications. The rescheduling problem in response to operation time delay is firstly analyzed. This is then followed by the establishment of a novel multi-objective nonlinear programming model (MONPM). In specifications, a three-stage rescheduling method is proposed including the batches splitting (BS), forward scheduling method (FSM) and backward scheduling method (BSM). As a result, the real-time application shows that the proposed rescheduling method efficiently ensures the continuous casting and dramatically shortens the redundant waiting time for molten steel in very short rescheduling time.

To explore the role of Rac1 in the SDF-1-induced migration and invasion of glioma cells with a specific Rac1 inhibitor.Human glioma cell lines U251 treated with SDF-1 or/and specific Rac1 inhibitor were used. The migration and invasion capacities of cells in 2D cell migration/3D invasion assay were assessed. Western blot was employed to detect the levels of Rac1 and GAPDH in cell lysates and the Rac1 activity measured by Rac1 activation assays. Immunofluorescence was used to identify the expression and intracellular location of Rac1 in U251 cells.SDF-1 significantly increased the migration and invasion capacities of U251 cells (P0.05). The stimulation of SDF-1 boosted the activity of Rac1 versus the unstimulated cells (P0.05). And Rac1 was recruited to protruding edge in SDF-1-stimulated cells. Inhibition of Rac1 with specific Rac1 inhibitor decreased the migration and invasion capacities of SDF-1-induced U251 cells (P0.05). In comparison with the SDF-1 treated group, the activity of Rac1 significantly decreased (P0.05) and the recruitment of Rac1 to protruding edge significantly decreased in the NSC23766 pre-treated group.This study provides novel evidence that Rac1 modulates the SDF-1-induced migration and invasion of glioma cells. It suggests that the inhibition of Rac1 activation may be a new therapeutic target for glioma.

Recent studies have suggested that cancer stem cells cause tumor recurrence based on their resistance to radiotherapy and chemotherapy. Although the highly invasive nature of glioblastoma cells is also implicated in the failure of current therapies, it is not clear whether cancer stem cells are involved in invasiveness. This study aimed to assess invasive ability of glioma stem cells (GSCs) derived from C6 glioma cell line and the distribution patterns of GSCs in Sprague-Dawley (SD) rat brain tumor.Serum-free medium culture and magnetic isolation were used to gain purely CD133(+) GSCs. The invasive ability of CD133(+) and CD133(-) C6 cells were determined using matrigel invasion assay. Immunohistochemical staining for stem cell markers and luxol fast blue staining for white matter tracts were performed to show the distribution patterns of GSCs in brain tumor of rats and the relationship among GSCs, vessels, and white matter tracts. The results of matrigel invasion assay were estimated using the Student's t test and the analysis of Western blotting was performed using the one-way analysis of variance (ANOVA) test.CD133(+) GSCs (number: 85.3 ± 4.0) were significantly more invasive in vitro than matched CD133(-) cells (number: 25.9 ± 3.1) (t = 14.5, P0.005). GSCs invaded into the brain diffusely and located in perivascular niche of tumor-brain interface or resided within perivascular niche next to white fiber tracts. The polarity of glioma cells containing GSCs was parallel to the white matter tracts.Our data suggest that CD133(+) GSCs exhibit more aggressive invasion in vitro and GSCs in vivo probably disseminate along the long axis of blood vessels and transit through the white matter tracts. The therapies targeting GSCs invasion combined with traditional glioblastoma multiforme therapeutic paradigms might be a new approach for avoiding malignant glioma recurrence.

To investigate the expression of CD133 and CD34 in different parts of glioblastoma and its margin and explore the invasive path of glioma stem cells within the tumor and surrounding tissue.The surgical specimens were collected from the core of mass, junctional zones between tumor and peritumoral edematous areas and edematous areas in 52 patients with glioblastoma. Immunohistochemical cell staining and Western blot were employed to evaluate the expression of CD133 in different specimens while immunohistochemistry was used to detect the CD34-microvessel postforming. A correlation analysis was performed between them.The expression of CD133 was not detected in the control groups while the scores were 7.3 ± 1.4, 5.2 ± 1.1, 2.7 ± 1.0 in junctional zones, tumor cores and edematous areas with immunohistochemistry and 0.79 ± 0.03, 0.38 ± 0.01, 0.20 ± 0.04 with Western blot respectively. There were significant differences between different groups (P0.05). Under light microscope, the CD133-positive cells frequently forming perivascular pseudorosettes were dense in junctional zones and mostly clustered near the microvessels in tumor cores and scattered in edematous areas. At a high magnification (200×), the CD34-MVD (/HP) values were 31.3 ± 4.0, 21.8 ± 2.6, 15.3 ± 2.4, 4.7 ± 1.5 respectively in junctional zones, tumor cores, edematous areas and control tissues. Significant differences were also found in these groups (P0.05). The expression level of CD133-positive cell was positively correlated with the distribution of CD34-microvessels (r = 0.948, P0.05).Glioma stem cells tend to assemble in the junctional zones where the microvessels are enriched. There is probably an intimate nourishing relationship with the microvessels. The distribution of glioma stem cells may be related with the invasiveness within glioblastoma.

This paper proposes a novel method for the stochastic multi-attribute decision making problems, in which the attribute weights are partial known. The deviation of attribution values and decision maker's subjective information is combined to obtain the weights of attribution by a goal programming model. Furthermore, the expected utility and decision-maker's attitudes toward risk are considered to determine the ranking order of all alternatives. Finally, a numerical example is used to show the effectiveness and applicability of the developed method.