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Background Using DNA as a storage medium is appealing due to the information density and longevity of DNA, especially in the era of data explosion. A significant challenge in the DNA data storage area is to deal with the noises introduced in the channel and control the trade-off between the redundancy of error correction codes and the information storage density. As running DNA data storage experiments in vitro is still expensive and time-consuming, a simulation model is needed to systematically optimize the redundancy to combat the channel's particular noise structure. Results Here, we present DeSP, a systematic DNA storage error Simulation Pipeline, which simulates the errors generated from all DNA storage stages and systematically guides the optimization of encoding redundancy. It covers both the sequence lost and the within-sequence errors in the particular context of the data storage channel. With this model, we explained how errors are generated and passed through different stages to form final sequencing results, analyzed the influence of error rate and sampling depth to final error rates, and demonstrated how to systemically optimize redundancy design in silico with the simulation model. These error simulation results are consistent with the in vitro experiments. Conclusions DeSP implemented in Python is freely available on Github (https://github.com/WangLabTHU/DeSP). It is a flexible framework for systematic error simulation in DNA storage and can be adapted to a wide range of experiment pipelines.

Low-enriched uranium alloyed with 10 wt.% molybdenum (U-10Mo) has been identified as a promising alternative to high-enriched uranium. Manufacturing U-10Mo alloy involves multiple complex thermomechanical processes that pose challenges for computational modeling. This paper describes the application of integrated computational materials engineering (ICME) concepts to integrate three individual modeling components, viz. homogenization, microstructure-based finite element method for hot rolling, and carbide particle distribution, to simulate the early-stage processes of U-10Mo alloy manufacture. The resulting integrated model enables information to be passed between different model components and leads to improved understanding of the evolution of the microstructure. This ICME approach is then used to predict the variation in the thickness of the Zircaloy-2 barrier as a function of the degree of homogenization and to analyze the carbide distribution, which can affect the recrystallization, hardness, and fracture properties of U-10Mo in subsequent processes.

Non-matching interfaces occur in large computational models of complicated structures when different discretizations are used in different regions of the problem domain. Presence of non-matching interfaces, for instance, between two or more finite element meshes of different refinement, or between a meshfree region and a finite element region, can lead to erroneous results. In this work, a variationally consistent coupling method is developed to ensure that such patch tests are passed for any choice of numerical integration over the interface. This is achieved by constructing an integration constraint over the non-matching interface and by modifying the approximation basis functions for the adjacent discretizations in a way that guarantees passing the patch test. Numerical examples are presented to verify the formulation and study the performance of the proposed method.

Background Chemoresistance is one of the main causes of poor prognosis in pancreatic cancer patients. Understanding the mechanisms implicated in chemoresistance of pancreatic cancer is critical to improving patient outcomes. Recent evidences indicate that the long noncoding RNAs (lncRNAs) are involving in chemoresistance of pancreatic cancer. However, the mechanisms of lncRNAs contribute to resistance in pancreatic cancer and remain largely unknown. The objective of this study is to construct a chemoresistance-related lncRNA-associated competing endogenous RNA (ceRNA) network of pancreatic cancer and identify the key lncRNAs in regulating chemoresistance of the network. Methods Firstly, lncRNA expression profiling of gemcitabine-resistant pancreatic cancer cells was performed to identify lncRNAs related to chemoresistance by microarray analysis. Secondly, with insights into the mechanism of ceRNA, we used a bioinformatics approach to construct a chemoresistance-related lncRNAs-associated ceRNA network. We then identified the topological key lncRNAs in the ceRNA network and demonstrated its function or mechanism in chemoresistance of pancreatic cancer using molecular biological methods. Further studies evaluated its expression to assess its potential association with survival in patients with pancreatic cancer. Results Firstly, we demonstrated that lncRNAs were dysregulated in gemcitabine-resistant pancreatic cancer cells. We then constructed a chemoresistance-related lncRNA-associated ceRNA network and proposed that lncRNA Homo sapiens glutathione S-transferase mu 3, transcript variant 2 and noncoding RNA (GSTM3TV2; NCBI Reference Sequence: NR_024537.1) might act as a key ceRNA to enhance chemoresistance by upregulating L-type amino acid transporter 2 (LAT2) and oxidized low-density lipoprotein receptor 1(OLR1) in pancreatic cancer. Further studies demonstrated that GSTM3TV2, overexpressed in gemcitabine-resistant cells, enhanced the gemcitabine resistance of pancreatic cancer cells in vitro and in vivo. Mechanistically, we identified that GSTM3TV2 upregulated LAT2 and OLR1 by competitively sponging let-7 to promote gemcitabine resistance. In addition, we revealed that the expression levels of GSTM3TV2 were significantly increased in pancreatic cancer tissues and were associated with poor prognosis. Conclusion Our results suggest that GSTM3TV2 is a crucial oncogenic regulator involved in chemoresistance and could be a new therapeutic target or prognostic marker in pancreatic cancer.

Based on previous studies, an improved non-slagging spouting-cyclone combustor with two-stage combustion, organized in perpendicularly vortexing flows, is developed for clean coal combustion applied in small-size industrial furnaces and domestic furnaces. The isothermal model test and the combustion test give some encouraging results. In this study, further improvement of the geometrical configuration was made, a visualization method and a LDA system were used to study the gas-particle flow behavior, and the temperature and gas composition in combustion experiments were measured by using thermocouples and a COSA-6000-CD Portable Stack Analyzer. Stronger recirculation in the spouting zone and the strongly swirling effect in the cyclone zone were obtained in the improved combustor. The combustion temperature distribution is uniform. These results indicate that the improved geometrical configuration of the combustor is favorable to the stabilization of coal flame and the intensification of coal combustion, and it provides a basis for the practical application of this technique.

A combustion set-up of an innovative nonslagging cyclone combustor called “Spouting-Cyclone Combustor (SCC)”, with two-stage combustion, organized in orthogonal vortex flows; was established and the experimental studies on the fast ignition and stable combustion of coarse coal particles in this combustor were carried out. The flame temperature versus ignition time and the practical fast ignition procedure were obtained; The stable coal combustion can be achieved after a short period ignition, and the temperature fields in SCC were obtained. These results show that it is possible to obtain highly efficient and clean combustion of unground coal particles by using this technology.

The gas and particle time-averaged velocity and RMS fluctuation velocity of swirling gas-particle flows in a spouting-cyclone combustor were measured by a hot-ball probe and a conventional LDV system. The results show large velocity slip between the two phases both in tangential and axial directions and high nonisotropic turbulence of the two phases were also observed which is favorable to coal combustion. The particle RMS fluctuation velocity is higher than the gas RMS fluctuation velocity only in some regions of the flow field.