Marx for his times. Book Review of: 'Karl Marx : greatness and illusion' by Gareth Stedman Jones

Potential downstream targets for CD274. RNA-sequencing was performed with WT and CD274-null LICs, and the candidate genes related to proliferation and cell cycle was analyzed. (PDF 116 kb

Congestion Pricing for Aircraft Pushback Slot Allocation

<div><p>In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the “external cost of surface congestion” is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm.</p></div

An isogenic experimental model identifies b-catenin as a molecular target in ovarian cancer metastasis

Session - Tumor Biology: no. 650This journal suppl. entitled: Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LAOvarian cancer metastasis is closely associated with unfavorable outcomes, yet the underlying mechanisms remain obscure. Here we establish an isogenic model that could mimic the spontaneous metastasis of human ovarian cancer. Given that tumor cells are heterogeneous in nature, an isogenic pair of highly metastatic (HM) and non-metastatic (NM) cell lines with opposite metastatic capabilities was derived using in vitro and in vivo selection. Incorporation of the luciferase gene into the cell pair allowed non-invasive monitoring of the metastatic events by bioluminescent imaging in vivo. Orthotopic implantation of HM into the ovarian bursa of NOD/SCID mice resulted in metastases within the peritoneum with ascites formation, thus representing the major dissemination pattern of human ovarian cancer cells. However, NM failed to form detectable metastases, although it was tumorigenic at the ovarian bursa. In comparison with NM, HM displayed higher spheroid-forming ability and had higher expression of stemness marker genes, which are characteristics of cancer stem-like population. By proteomic profiling and pathway analysis, HM is found to be enriched in the oncogenic β-catenin signaling, a pathway elevated in ovarian cancer metastases. Tumor initiation and metastasis of HM was dramatically impaired when β-catenin was specifically knocked down. We further demonstrated that β-catenin could down-regulate the expression of Dicer, a major component of the microRNA machinery. These results together suggest that this model could help to delineate the molecular mechanisms for ovarian cancer metastasis, and provide clinically relevant insights to target metastasizing ovarian cancer cells. ©2016 American Association for Cancer Research

Pairwise <i>F</i>_ST (below diagonal) and associated <i>P</i> (above diagonal) values among populations of <i>A. personatus</i>.

*<p>, significant at <i>P</i><0.05 by the permutation test; **, significant <i>P</i> values after Bonferroni correction.</p

Figure 5

<p>The observed pairwise differences (bars), and the expected mismatch distributions under the sudden expansion model (solid line) for two lineages.</p

Delay time for each aircraft.

<p>Delay time for each aircraft.</p

Effects of digital countdown timer on intersection safety and efficiency: A systematic review

<p><b>Objective:</b> To investigate the available evidence referring to the effectiveness of digital countdown timers (DCTs) in improving the safety and operational efficiency of signalized intersection.</p> <p><b>Methods:</b> A systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement guidelines. Relevant literature was searched from electronic databases using key terms. Based on study selection and methodological quality assessment, 14 studies were included in the review. Findings of the studies were synthesized in a narrative analysis.</p> <p><b>Results:</b> Three types of DCT had different effects on intersection safety and operational efficiency. Green signal countdown timers (GSCTs) reduced red light violations, type I dilemma zone distributions, and rear-end collision likelihood but increased crossing after yellow onset and had mixed impacts on type II dilemma zone distributions and intersection capacity. In contrast, red signal countdown timers (RSCTs) increased intersection capacity, although their effectiveness in reducing red light violations dissipated over time. Likewise, continuous countdown timers (CCTs) significantly enhanced intersection capacity but had mixed influences on red light violations and crossing after yellow onset.</p> <p><b>Conclusions:</b> Due to the limited and inconsistent evidence regarding DCTs' effects on intersection safety and efficiency, it is not sufficient to recommend any type of DCT to be installed at signalized intersections to improve safety and operational efficiency. Nevertheless, it is apparent that both RSCTs and CCTs enhance intersection capacity, though their impacts on intersection safety are unclear. Future studies need to further verify those anticipated safe and operational benefits of DCTs with enriched field observation data.</p

Distribution of transversion haplotypes among populations in lineage A.

<p>Distribution of transversion haplotypes among populations in lineage A.</p

Results of simulation performed using IDDE algorithm.

<p>Results of simulation performed using IDDE algorithm.</p

Distribution of transversion haplotypes among populations in lineage B.

<p>Distribution of transversion haplotypes among populations in lineage B.</p