基于杂交链式反应辅助多重信号放大的端粒酶灵敏检测

端粒酶是真核细胞维持端粒长度的关键逆转录酶,其生物活性的高低可以为多种癌症的临床诊断和预后治疗提供有价值的信息.本研究以人宫颈癌细胞(HeLa细胞)裂解液中的端粒酶为研究对象,通过借助杂交链式反应辅助多重信号放大策略,提出了一种新颖、灵敏的检测端粒酶电化学方法.首先将端粒酶的延伸引物自组装在金电极表面,当端粒酶存在时,端粒酶能够催化引物的延伸,产生与发卡环探针H1部分互补的序列,进而引发杂交链式反应,形成由两个发卡环探针(H1和H2)交替杂交而形成的DNA长链.由于H1和H2末端均修饰有生物素,加入链霉亲和素修饰辣根过氧化物酶后,辣根过氧化物酶被被连接到电极表面,催化邻苯二胺氧化生成2,3-二氨基吩嗪,产生显著的电化学信号.实验结果表明,本研究建立的端粒酶电化学检测方法高效、可行,线性范围宽,灵敏度高,可以检测每毫升10个HeLa细胞裂解液中的端粒酶.本方法具有较好的选择性,能有效区分端粒酶和对照蛋白.     

Selection of aptamers for signal transduction proteins by capillary electrophoresis

High‐affinity aptamers for important signal transduction proteins, i.e. Cdc42‐GTP, p21‐activated kinase1 (PAK1) and MRCK (myotonic dystrophy kinase‐related Cdc42‐binding kinase) α were successfully selected in the low micro‐ to nanomolar range using non‐systematic evolution of ligands by exponential enrichment (SELEX) with at least three orders of magnitude enhancement from their respective bulk affinity of naïve DNA library. In the non‐SELEX procedure, CE was used as a highly efficient affinity method to select aptamers for the desired molecular target through a process that involved repetitive steps of partitioning, known as non‐equilibrium CE of equilibrium mixtures with no PCR amplification between successive steps. Various non‐SELEX conditions including the type, concentration and pH of the run buffer were optimized. Other considerations such as salt composition of selection buffer, protein concentration and sample injection size were also studied for high stringency during selection. After identifying the best enriched aptamer pool, randomly selected clones from the aptamer pool were sequenced to obtain the individual DNA sequences. The dissociation constants (K_d) of these sequences were in the low micromolar to nanomolar range, indicating high affinity to the respective proteins. The best binders were also subjected to sequence alignment to generate a phylogenetic tree. No significant consensus region based on approximately 50 sequences for each protein was observed, suggesting the high efficiency of non‐SELEX for the selection of numerous unique sequences with high selectivity.     

无人机光电载荷图像处理器的设计

介绍了无人机载设备的技术特点及机载小型图像处理器的组成。采用TI公司的数字信号处理器芯片为核心处理器,配合现场可编程逻辑器件(FPGA)与外部管理微控制单元(MCU)来实现目标数据的采集与处理,设计了适用于无人机光电载荷的超小型图像处理器系统。针对机载设备的特点,设计时充分考虑了体积、重量、功耗等要求。该系统已应用于多台套机载光电载荷中,工作稳定可靠,满足无人侦察机对捕捉和定位目标的要求。     

基于小波变换和高斯拟合的在线谱图综合处理方法

微小型移动式现场在线检测技术是分析仪器发展的新领域。针对复杂工作环境中谱图存在强噪声干扰、谱峰重叠、不规则峰形等严重影响仪器的定性和定量准确度的瓶颈技术,提出了一种基于小波变换和高斯拟合相结合的谱图在线综合处理方法,用自研的仪器对甲苯和全氟三丁胺两种典型化合物的谱图进行了处理,并与实验室分析仪器普遍应用的算法进行了对比分析。结果表明,综合方法能够有效解决强噪声干扰、谱峰重叠、不规则峰形问题,提高仪器的定性和定量准确性,同时能够实现数据压缩,满足仪器的在线实时检测要求。综合方法处理甲苯特征峰的平均信噪比(SNR)较移动平滑方法提高了1.3倍,峰位误差ΔM降低了3.6倍,处理全氟三丁胺谱图的数据压缩比为197∶1。     

An Ant Colony Optimisation algorithm for solving the asymmetric traffic assignment problem

In this paper we propose an Ant Colony Optimisation (ACO) algorithm for defining the signal settings on urban networks following a local approach. This consists in optimising the signal settings of each intersection of an urban network as a function only of traffic flows at the accesses to the same intersection, taking account of the effects of signal settings on costs and on user route choices. This problem, also known as Local Optimisation of Signal Settings (LOSS), has been widely studied in the literature and can be formulated as an asymmetric assignment problem. The proposed ACO algorithm is based on two kinds of behaviour of artificial ants which allow the LOSS problem to be solved: traditional behaviour based on the response to pheromones for simulating user route choice, and innovative behaviour based on the pressure of an ant stream for solving the signal setting definition problem. Our results on real-scale networks show that the proposed approach allows the solution to be obtained in less time but with the same accuracy as in traditional MSA (Method of Successive Averages) approaches.     

Macromodeling of high-speed interconnects by positive interpolation of vertical segments

In this paper a novel macromodeling scheme is presented to model the per unit of length (p.u.l.) parameters of uniform transmission lines. In particular, it is focused on single on-chip interconnects, because their p.u.l. parameters are influenced by the presence of semiconductor (s) and as such exhibit a strong frequency-dependency, making the modeling process harder. Starting from a set of very accurate tabulated data samples, obtained by two-dimensional electromagnetic modeling, rational models for the four p.u.l. parameters are constructed. The novelty of the approach lies in the fact that the rational models are positive by construction and that a controllable accuracy is obtained. These models can then further be used to construct multivariate models, e.g., for variability analysis. Here, the novel scheme is applied to an on-chip inverted embedded microstrip line, of which the signal integrity behavior is assessed in both the frequency and the time domain, demonstrating the applicability of the macromodels.     

Signal modeling using the gradient search

This letter presents a new method for continuous signal modeling. Firstly, the continuous signal can be represented as a function of the trigonometric functional extension (Fourier series). Fourier series of the signal are parameterized by the fundamental frequency and unknown parameters. Then, the gradient-based iterative identification algorithm is derived, for estimating parameters of the signal model with known and unknown frequencies, separately. Finally, the simulation results indicate that the proposed algorithm is effective.     

A Dynamic Programming Algorithm for the Fused Lasso and L 0-Segmentation

We propose a dynamic programming algorithm for the one-dimensional Fused Lasso Signal Approximator (FLSA). The proposed algorithm has a linear running time in the worst case. A similar approach is developed for the task of least squares segmentation, and simulations indicate substantial performance improvement over existing algorithms. Examples of R and C implementations are provided in the online Supplementary materials, posted on the journal web site.     

Optimal control of self-organized dynamics in cellular signal transduction

We demonstrate how model-based optimal control can be exploited in biological and biochemical modelling applications in several ways. In the first part, we apply optimal control to a detailed kinetic model of a glycolysis oscillator, which plays a central role in immune cells, in order to analyse potential regulatory mechanisms in the dynamics of associated signalling pathways. We demonstrate that the formulation of inverse problems with the aim to determine specific time-dependent input stimuli can provide important insight into dynamic regulations of self-organized cellular signal transduction. In the second part, we present an optimal control study aimed at target-oriented manipulation of a biological rhythm, an internal clock mechanism related to the circadian oscillator. This oscillator is responsible for the approximate endogenous 24 h (latin: circa dies) day-night rhythm in many organisms. On the basis of a kinetic model for the fruit fly Drosophila, we compute switching light stimuli via mixed-integer optimal control that annihilate the oscillations for a fixed time interval. Insight gained from such model-based specific manipulation may be promising in biomedical applications.     

Mechano-Activated Self-Immolation of Hydrogels via Signal Amplification

Cellular organisms possess intricate mechano-adaptive systems that enable them to sense forces and process them with (bio)chemical circuits for functional adaptation. Inspired by such processes, this study introduces a hydrogel system capable of mechanically activated and chemically transduced self-destruction. Our judiciously designed hydrogels can mechanically generate radicals that are processed and amplified in a self-propagating radical de-crosslinking reaction, ultimately leading to mechanically triggered self-immolation. We put such systems to work in mechano-induced debonding, and in a bilayer actuator, where swelling-induced bending generates sufficient force for selective degradation of one layer, leading to autonomous self-regulation associated with unbending. Our work helps define design criteria for molecularly controlled adaptive and self-regulating materials with embodied mechano-chemical information processing, and showcases their potential for adhesives and soft robotics.