基于融合信息的癌症相关基因选择方法

基因表达数据的出现,为人类从分子生物学的角度研究和探索癌症的发病机理提供了广阔的前景,利用基因表达数据发现与癌症相关的基因对于癌症的诊断和治疗具有重要的意义。在过去的十几年里,已经有很多种计算方法被成功地用于从基因表达数据中找出与癌症相关的关键基因,然而,不同的方法从不同的角度刻画基因对不同类型样本的区分能力,它们选择出来的关键基因可能不一致,这将给医学解释和应用带来困扰。现提出一种融合的方法,即将基因在不同方面对样本的判别能力结合起来,首先计算每个基因的信息增益、全局判别能力和局部判别能力,再用它们的识别率进行加权,进而计算每个基因的综合判别能力,最后筛选出判别能力最高的基因子集作为关键基因子集。实验结果表明,此方法得到了比采用单独一种评价标准更好的识别效果。     

基于相容关系的基因选择方法

有效的基因选择是对基因表达数据进行分析的重要内容。粗糙集作为一种软计算方法能够保持在数据集分类能力不变的基础上,对属性进行约简。由于基因表达数据的连续性,为了避免运用粗糙集方法所必需的离散化过程带来的信息丢失,将相容粗糙集应用于基因的特征选取,提出了基于相容关系的基因选择方法。首先,通过i检验对基因表达数据进行排列,选择评分靠前的若干基因;然后,通过相容粗糙集对这些基因进一步约简。在两个标准的基因表达数据上进行了实验,结果表明该方法是可行性和有效性的。     

A multi-objective strategy in genetic algorithms for gene selection of gene expression data

A microarray machine offers the capacity to measure the expression levels of thousands of genes simultaneously. It is used to collect information from tissue and cell samples regarding gene expression differences that could be useful for cancer classification. However, the urgent problems in the use of gene expression data are the availability of a huge number of genes relative to the small number of available samples, and the fact that many of the genes are not relevant to the classification. It has been shown that selecting a small subset of genes can lead to improved accuracy in the classification. Hence, this paper proposes a solution to the problems by using a multiobjective strategy in a genetic algorithm. This approach was tried on two benchmark gene expression data sets. It obtained encouraging results on those data sets as compared with an approach that used a single-objective strategy in a genetic algorithm. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Selecting informative genes from microarray data by using hybrid methods for cancer classification

Gene expression technology, namely microarrays, offers the ability to measure the expression levels of thousands of genes simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of an efficient cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the number of tissue samples. These data also have noisy genes. It has been shown in literature reviews that selecting a small subset of informative genes can lead to improved classification accuracy. Therefore, this paper aims to select a small subset of informative genes that are most relevant for cancer classification. To achieve this aim, an approach using two hybrid methods has been proposed. This approach is assessed and evaluated on two well-known microarray data sets, showing competitive results. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Surface Control and Electrical Tuning of MXene Electrode for Flexible Self-Powered Human–Machine Interaction

MXene materials emerge as promising candidates for energy harvesting and storage application. In this study, the effect of the surface chemistry on the work function of MXenes, which determines the performance of MXene-based triboelectric nanogenerator (TENG), is elucidated. First-principles calculations reveal that the surface functional group greatly influences MXene work function:  OH termination reduces the work function with respect to that of bare surface, while  F and  Cl increase it. Then, work functions are experimentally determined by Kelvin probe force microscopy. The MXene prepared by gentle etching at 40 °C for 48 h (GE_40/48) has the largest work function. Furthermore, an electron-cloud potential-well model is established to explain the mechanism of electron emission-dominated charge transfer and assemble a triboelectric device to verify experimentally its conclusions. It is found that GE_40/48 has the best performance with a 281 V open-circuit voltage, 9.7 µA short-current current, and storing 1.019 µC of charge, which is consistent with the model. Last, a patterned TENG is demonstrated for self-powered human–machine interaction application. This finding enhances the understanding of the inherent mechanism between the surface structure and the output performance of MXene-based TENG, which can be applied to other TENG based on 2D materials.     

Mild Binding of Protein to C2N Monolayer Reveals Its Suitable Biocompatibility

The development of biocompatible nanomaterials for smart drug delivery and bioimaging has attracted great interest in recent years in biomedical fields. Here, the interaction between the recently reported nitrogenated graphene (C₂N) and a prototypical protein (villin headpiece HP35) utilizing atomistic molecular dynamics simulations is studied. The simulations reveal that HP35 can form a stable binding with the C₂N monolayer. Although the C₂N–HP35 attractive interactions are constantly preserved, the binding strength between C₂N and the protein is mild and does not cause significant distortion in the protein's structural integrity. This intrinsic biofriendly property of native C₂N is distinct from several widely studied nanomaterials, such as graphene, carbon nanotubes, and MoS₂, which can induce severe protein denaturation. Interestingly, once the protein is adsorbed onto C₂N surface, its transverse migration is highly restricted at the binding sites. This restriction is orchestrated by C₂N's periodic porous structure with negatively charged “holes,” where the basic residues—such as lysine—can form stable interactions, thus functioning as “anchor points” in confining the protein displacement. It is suggested that the mild, immobilized protein attraction and biofriendly aspects of C₂N would make it a prospective candidate in bio‐ and medical‐related applications.     

Photonic Reactions Leading to Fluorescence in a Polymeric System Induced by the Photothermal Effect of Magnetite Nanoparticles Using a 780 nm Multiphoton Laser

Recently, polymer‐coated magnetite (Fe₃O₄) nanoparticles (NPs) are extensively studied for applications in therapeutics or diagnostics using photothermal effect. Therefore, it is essential to understand the interactions between Fe₃O₄ NPs and polymers when optical stimuli are applied. Herein, the photonic reactions of Fe₃O₄ NPs and polymer composites upon application of a 780 nm multiphoton laser are analyzed. The photonic reactions produce unique results including fluorescence from conformationally changed polymer and low‐temperature phase transformation of Fe₃O₄ NPs. Typically, π‐conjugated chains are formed, inducing fluorescence through a series of main and side‐chain cleavage reactions of polymers with the aliphatic chain. In addition, fluorescence is detected in the cellular system by photonic reactions between Fe₃O₄ NPs and biomolecules. After multiphoton laser irradiation, light emission is detected near the intracellular Fe₃O₄ NPs, and a stronger intensity is observed in large‐sized NPs.     

A particle‐based moving interface method (PMIM) for modeling the large deformation of boundaries in soft matter systems

The mechanics of the interaction between a fluid and a soft interface undergoing large deformations appear in many places, such as in biological systems or industrial processes. We present an Eulerian approach that describes the mechanics of an interface and its interactions with a surrounding fluid via the so‐called Navier boundary condition. The interface is modeled as a curvilinear surface with arbitrary mechanical properties across which discontinuities in pressure and tangential fluid velocity can be accounted for using a modified version of the extended finite element method. The coupling between the interface and the fluid is enforced through the use of Lagrange multipliers. The tracking and evolution of the interface are then handled in a Lagrangian step with the grid‐based particle method. We show that this method is ideal to describe large membrane deformations and Navier boundary conditions on the interface with velocity/pressure discontinuities. The validity of the model is assessed by evaluating the numerical convergence for a axisymmetrical flow past a spherical capsule with various surface properties. We show the effect of slip length on the shear flow past a two‐dimensional capsule and simulate the compression of an elastic membrane lying on a viscous fluid substrate. Copyright © 2015 John Wiley & Sons, Ltd.     

Investigation of Ablation Efficiency of Stainless Steel Using Pulsed Lasers in Burst Mode

Due to its high corrosion resistance and mechanical properties, stainless steel is commonly used in various industrial applications. Although different types of stainless steel are similar in their chemical composition, they can differ significantly in their thermal diffusivity. This property is relevant in the ability of a material to conduct heat and thus, in laser processing. In this frame, this study compares the ablation efficiency and characteristics of polished stainless steel samples of the alloys AISI 304, AISI 420, and AISI 316Ti. They are irradiated with single ultrashort pulses having pulse durations between 250 fs and 10 ps as well as using GHz burst modii. The goal is to investigate the differences in both the ablation threshold and the ablation rate to improve the ablation efficiency. The results show that shorter pulse durations lead to a more efficient ablation process. On the other hand, GHz bursts are found to be, in general, less efficient. In addition, there is a significant difference in the surface morphology depending on the process parameters. The differences in the thermal diffusivity do not significantly influence the ablation threshold fluence but surface morphology and the ablation rate.