A Lagrangian Relaxation Approach Based on a Time-Space-State Network for Railway Crew Scheduling

The crew scheduling problem is an important and difficult problem in railway crew management. In this paper, we focus on the railway crew scheduling problem with time window constraints caused by meal break rules. To solve this optimization problem, a solution method is proposed based on a time-space-state network and Lagrangian relaxation. In this method, the "hard constraints" corresponding to the crew rules are described as the state of vertices in the time-space-state network. Based on the network, this problem is modeled as a network flow model, referred to as an initial model. To break the symmetry and improve the strength of the formulation, five valid inequalities are added. To solve the problem, we relax the coupling constraints by Lagrangian relaxation. The resulting subproblems are shortest path problems in the time-space-state networks. We propose a Lagrangian heuristic to find a feasible solution. Finally, the solution method is tested on real-world instances from an intercity rail line and a regional railway network in China. We discuss the effects of additional valid inequalities and the effects of different length of meal time windows

Latexin expression is downregulated in human gastric carcinomas and exhibits tumor suppressor potential

<p>Abstract</p> <p>Background</p> <p>Latexin, also known as endogenous carboxypeptidase inhibitor (CPI), has been found to inhibit mouse stem cell populations and lymphoma cell proliferation, demonstrating its potential role as a tumor suppressor. Our previous study also suggested a correlation between latexin expression and malignant transformation of immortalized human gastric epithelial cells. Here, we examined latexin expression in human gastric carcinomas and investigated the effect of differential latexin expression on proliferation of gastric cancer cells <it>in vitro </it>and <it>in vivo</it>.</p> <p>Methods</p> <p>Monoclonal antibody against human latexin was prepared and immunohistochemical analysis was performed to detect latexin expression in 41 paired gastric carcinomas and adjacent normal control tissues. Human gastric cancer cells MGC803 (latexin negative) stably transfected with LXN gene and BGC823 cells (latexin positive) stably transfected with antisense LXN gene were established for anchorage-dependent colony formation assay and tumorigenesis assay in nude mice. Differentially expressed genes in response to exogeneous latexin expression were screened using microarray analysis and identified by RT-PCR. Bisulfite sequencing was performed to analyze the correlation of the methylation status of LXN promoter with latexin expression in cell lines.</p> <p>Results</p> <p>Immunohistochemical analysis showed significantly reduced latexin expression in gastric carcinomas (6/41, 14.6%) compared to control tissues (31/41, 75.6%) (<it>P </it>< 0.05). Overexpression of LXN gene in MGC803 cells inhibited colony formation and tumor growth in nude mice. Conversely, BGC823 cells transfected with antisense LXN gene exhibited enhanced tumor growth and colony formation. Additionally, several tumor related genes, including Maspin, WFDC1, SLPI, S100P, and PDGFRB, were shown to be differentially expressed in MGC803 cells in response to latexin expression. Differential expression of Maspin and S100P was also identified in BGC823 cells while latexin expression was downregulated. Further bisulfite sequencing of the LXN gene promoter indicated CpG hypermethylation was correlated with silencing of latexin expression in human cells.</p> <p>Conclusions</p> <p>Latexin expression was reduced in human gastric cancers compared with their normal control tissues. The cellular and molecular evidences demonstrated the inhibitory effect of latexin in human gastric cancer cell growth and tumorigenicity. These results strongly suggest the possible involvement of latexin expression in tumor suppression.</p

A 115-bp MethyLight assay for detection of p16 (CDKN2A) methylation as a diagnostic biomarker in human tissues

<p>Abstract</p> <p>Background</p> <p><it>p16 </it>Methylation is a potential biomarker for prediction of malignant transformation of epithelial dysplasia. A probe-based, quantitative, methylation-specific PCR (MSP) called MethyLight may become an eligible method for detecting this marker clinically. We studied oral mucosa biopsies with epithelial dysplasia from 78 patients enrolled in a published 4-years' followup cohort, in which cancer risk for patients with <it>p16 </it>methylation-positive dysplasia was significantly higher than those without <it>p16 </it>methylation (by 150-bp MSP and bisulfite sequencing; +133 ~ +283, transcription starting site, +1). The <it>p16 </it>methylation status in samples (<it>N </it>= 102) containing sufficient DNA was analyzed by the 70-bp classic (+238 ~ +307) and 115-bp novel (+157 ~ +272) MethyLight assays, respectively.</p> <p>Results</p> <p><it>p16 </it>Methylation was detectable in 75 samples using the classic MethyLight assay. The methylated-<it>p16 </it>positive rate and proportion of methylated-<it>p16 </it>by the MethyLight in MSP-positive samples were higher than those in MSP-negative samples (positive rate: 37/44 vs. 38/58, <it>P</it>=0.035, two-sided; proportion [median]: 0.78 vs. 0.02, <it>P <</it>0.007). Using the published results of MSP as a golden standard, we found sensitivity, specificity, and accuracy for this MethyLight assay to be 70.5%, 84.5%, and 55.0%, respectively. Because amplicon of the classic MethyLight procedure only partially overlapped with the MSP amplicon, we further designed a 115-bp novel MethyLight assay in which the amplicon on the sense-strand fully overlapped with the MSP amplicon on the antisense-strand. Using the 115-bp MethyLight assay, we observed methylated-<it>p16 </it>in 26 of 44 MSP-positive samples and 2 of 58 MSP-negative ones (<it>P </it>= 0.000). These results were confirmed with clone sequencing. Sensitivity, specificity, and accuracy using the 115-bp MethyLight assay were 59.1%, 98.3%, and 57.4%, respectively. Significant differences in the oral cancer rate were observed during the followup between patients (≥60 years) with and without methylated-<it>p16 </it>as detected by the 115-bp MethyLight assay (6/8 vs. 6/22, P = 0.034, two-sided).</p> <p>Conclusions</p> <p>The 115-bp MethyLight assay is a useful and practical assay with very high specificity for the detection of <it>p16 </it>methylation clinically.</p

Polycomb CBX7 Directly Controls Trimethylation of Histone H3 at Lysine 9 at the p16 Locus

BACKGROUND: H3K9 trimethylation (H3K9me3) and binding of PcG repressor complex-1 (PRC1) may play crucial roles in the epigenetic silencing of the p16 gene. However, the mechanism of the initiation of this trimethylation is unknown. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we found that upregulating the expression of PRC1 component Cbx7 in gastric cancer cell lines MGC803 and BGC823 led to significantly suppress the expression of genes within the p16-Arf-p15 locus. H3K9me3 formation was observed at the p16 promoter and Regulatory Domain (RD). CBX7 and SUV39H2 binding to these regions were also detectable in the CBX7-stably upregulated cells. CBX7-SUV39H2 complexes were observed within nucleus in bimolecular fluorescence complementation assay (BiFC). Mutations of the chromodomain or deletion of Pc-box abolished the CBX7-binding and H3K9me3 formation, and thus partially repressed the function of CBX7. SiRNA-knockdown of Suv39h2 blocked the repressive effect of CBX7 on p16 transcription. Moreover, we found that expression of CBX7 in gastric carcinoma tissues with p16 methylation was significantly lower than that in their corresponding normal tissues, which showed a negative correlation with transcription of p16 in gastric mucosa. CONCLUSION/SIGNIFICANCE: These results demonstrated for the first time, to our knowledge, that CBX7 could initiate H3K9me3 formation at the p16 promoter

Unsupervised Feature Transfer for Batch Process Based on Geodesic Flow Kernel

The problem of misalignment of the original measurement model is caused by nonlinear, time-varying characteristic of the batch process. In this paper, a method based on geodesic flow kernel (GFK) for feature transfer is proposed. By mapping data into the manifold space, the feature transfer from source domain to target domain is implemented. Distribution adaptation of real-time data and modeling data is performed to reduce the distribution difference between them. The historical data through distribution adaptation is used to establish a regression model to predict the real-time data, by which the unsupervised batch process soft sensor modeling is realized. The application of predicting the concentration of penicillin between different batches during the fermentation of penicillin demonstrated that the prediction accuracy of the model can be improved more effectively than the traditional soft sensor method.Accepted Author ManuscriptTransport Engineering and Logistic