A new differential evolution using a bilevel optimization model for solving generalized multi-point dynamic aggregation problems

The multi-point dynamic aggregation problem (MPDAP) comes mainly from real-world applications, which is characterized by dynamic task assignation and routing optimization with limited resources. Due to the dynamic allocation of tasks, more than one optimization objective, limited resources, and other factors involved, the computational complexity of both route programming and resource allocation optimization is a growing problem. In this manuscript, a task scheduling problem of fire-fighting robots is investigated and solved, and serves as a representative multi-point dynamic aggregation problem. First, in terms of two optimized objectives, the cost and completion time, a new bilevel programming model is presented, in which the task cost is taken as the leader's objective. In addition, in order to effectively solve the bilevel model, a differential evolution is developed based on a new matrix coding scheme. Moreover, some percentage of high-quality solutions are applied in mutation and selection operations, which helps to generate potentially better solutions and keep them into the next generation of population. Finally, the experimental results show that the proposed algorithm is feasible and effective in dealing with the multi-point dynamic aggregation problem

Study on Unconventional Emergency Scenario Design: Taking Life-Rescuing of Dongfang Turbine Co., Ltd. in Wenchuan Earthquake for Example

Unconventional emergencies have attracted widespread concern in academic field due to its high uncertainty, huge destructiveness and complex management, and studies on unconventional emergencies shall change from “prediction-response” to “scenario-response”. By taking the life-rescuing of Dongfang Turbine Co., Ltd. in Wenchuan Earthquake for example, this paper divides scenarios in accordance with the specific investigations, and proposes several considerations about the unconventional emergency scenario study

Multi-strategy self-learning particle swarm optimization algorithm based on reinforcement learning

The trade-off between exploitation and exploration is a dilemma inherent to particle swarm optimization (PSO) algorithms. Therefore, a growing body of PSO variants is devoted to solving the balance between the two. Among them, the method of self-adaptive multi-strategy selection plays a crucial role in improving the performance of PSO algorithms but has yet to be well exploited. In this research, with the aid of the reinforcement learning technique to guide the generation of offspring, a novel self-adaptive multi-strategy selection mechanism is designed, and then a multi-strategy self-learning PSO algorithm based on reinforcement learning (MPSORL) is proposed. First, the fitness value of particles is regarded as a set of states that are divided into several state subsets non-uniformly. Second, the ε-greedy strategy is employed to select the optimal strategy for each particle. The personal best particle and the global best particle are then updated after executing the strategy. Subsequently, the next state is determined. Thus, the value of the Q-table, as a scheme adopted in self-learning, is reshaped by the reward value, the action and the state in a non-stationary environment. Finally, the proposed algorithm is compared with other state-of-the-art algorithms on two well-known benchmark suites and a real-world problem. Extensive experiments indicate that MPSORL has better performance in terms of accuracy, convergence speed and non-parametric tests in most cases. The multi-strategy selection mechanism presented in the manuscript is effective

Prevalence of lymph node metastases in superficial esophageal squamous cell carcinoma

ObjectiveEndoscopic treatment of superficial esophageal carcinoma has been increasingly conducted around the world. Because no lymph nodes are removed in such a procedure, the risk of lymph node metastases (LNMs) should be clearly understood. The aim of the present study was to accurately clarify the pattern of lymphatic spread in patients with superficial esophageal squamous cell carcinoma and analyze the factors potentially related to LNMs.MethodsThe pattern of lymphatic spread was studied in 189 patients who had undergone radical lymphadenectomy from 2006 to 2011. The risk factors associated with LNMs were determined by multivariate logistic regression analysis. According to the depth of tumor invasion, mucosal tumors were classified as M1, M2, and M3 and submucosal tumors as SM1, SM2, and SM3.ResultsA total of 4252 lymph nodes were resected (average, 23 ± 9; range, 12-68). LNMs occurred in 49 patients (25.9%). The frequency of LNMs was 4.3% in those with mucosal and 33.1% in those with submucosal cancer. LNMs were found in 0%, 0%, 11.8%, 24.0%, 20.5%, and 43.8% of the M1, M2, M3, SM1, SM2, and SM3 cancer, respectively. For submucosal cancer, SM3 cancer (P = .006) and lymphovascular invasion (P = .001) were significant independent risk factors for LNMs. Paratracheal nodes were the most frequently involved. “Skip” metastases occurred in 20 of 49 patients (40.8%).ConclusionsEndoscopic treatment can be attempted when the tumor is limited to the lamina propria mucosa. However, 2-field radical lymphadenectomy with careful upper mediastinal lymph node resection should be conducted for submucosal squamous cell carcinoma

Classification related to immunogenic cell death predicts prognosis, immune microenvironment characteristics, and response to immunotherapy in lower-grade gliomas

BackgroundImmunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG).Materials and methodsWe identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation.Results32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells.ConclusionWe established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy

First Report of a Foodborne Salmonella enterica Serovar Gloucester (4:i:l,w) ST34 Strain Harboring blaCTX–M–55 and qnrS Genes Located in IS26-Mediated Composite Transposon

Extended-spectrum β-lactamases (ESBLs) production and (fluoro)quinolone (FQ) resistance among Salmonella pose a public health threat. The objective of this study was the phenotypic and genotypic characterization of an ESBL-producing and nalidixic acid-resistant Salmonella enterica serovar Gloucester isolate (serotype 4:i:l,w) of sequence type 34 (ST34) from ready-to-eat (RTE) meat products in China. Whole-genome short and long read sequencing (HiSeq and MinION) results showed that it contained blaCTX–M–55, qnrS1, and tetB genes, with blaCTX–M–55 and qnrS1 located in chromosomal IS26-mediated composite transposon (IS26–qnrS1–IS3–Tn3–orf–blaCTX–M–55–ISEcp1–IS26). The same genetic structure was found in the chromosome of S. enterica subsp. enterica serovar Typhimurium strain and in several plasmids of Escherichia coli, indicating that the IS26-mediated composite transposon in the chromosome of S. Gloucester may originate from plasmids of E. coli and possess the ability to disseminate to Salmonella and other bacterial species. Besides, the structural unit qnrS1–IS3–Tn3–orf–blaCTX–M–55 was also observed to be linked with ISKpn19 in both the chromosomes and plasmids of various bacteria species, highlighting the contribution of the insertion sequences (IS26 and ISKpn19) to the co-dissemination of blaCTX–M–55 and qnrS1. To our knowledge, this is the first description of chromosomal blaCTX–M–55 and qnrS in S. Gloucester from RTE meat products. Our work expands the host range and provides additional evidence of the co-transfer of blaCTX–M–55 and qnrS1 among different species of Salmonella through the food chain

Arsenic trioxide exerts synergistic effects with cisplatin on non-small cell lung cancer cells via apoptosis induction

<p>Abstract</p> <p>Background</p> <p>Despite multidisciplinary treatment, lung cancer remains a highly lethal disease due to poor response to chemotherapy. The identification of therapeutic agents with synergistic effects with traditional drugs is an alternative for lung cancer therapy. In this study, the synergistic effects of arsenic trioxide (As₂O₃) with cisplatin (DDP) on A549 and H460 non-small cell lung cancer (NSCLC) cells were explored.</p> <p>Methods</p> <p>A549 and H460 human lung cancer cells were treated with As₂O₃and/or DDP. Cell growth curves, cell proliferation, cell cycle, and apoptosis of human cancer cell lines were determined by the 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT) method, clonogenic assay, and flow cytometry (FCM). Apoptosis was further assessed by TUNEL staining. Cell cycle and apoptosis related protein p21, cyclin D1, Bcl-2, bax, clusterin, and caspase-3 were detected by western blot.</p> <p>Results</p> <p>MTT and clonogenic assay showed As₂O₃within 10^-2μM to 10 μM exerted inhibition on the proliferation of NSCLC cells, and 2.5 μM As₂O₃exerted synergistic inhibition on proliferation with 3 μg/ml DDP. The combination indices (CI) for A549 and H460 were 0.5 and 0.6, respectively, as confirmed by the synergism of As₂O₃with DDP. FCM showed As₂O₃did not affect the cell cycle. The G0/G1 fraction ranged from 57% to 62% for controlled A549 cells and cells treated with As₂O₃and/or DDP. The G0/G1 fraction ranged from 37% to 42% for controlled H460 cells and cells treated with As₂O₃and/or DDP. FCM and TUNEL staining illustrated that the combination of As₂O₃and DDP provoked synergistic effects on apoptosis induction based on the analysis of the apoptosis index. Western blotting revealed that the expression of cell cycle related protein p21 and cyclin D1 were not affected by the treatments, whereas apoptosis related protein bax, Bcl-2, and clusterin were significantly regulated by As₂O₃and/or DDP treatments compared with controls. The expression of caspase-3 in cells treated with the combination of As₂O₃and DDP did not differ from that in cells treated with a single agent.</p> <p>Conclusion</p> <p>As₂O₃exerted synergistic effects with DDP on NSCLC cells, and the synergistic effects were partly due to the induction of caspase-independent apoptosis.</p