Combination of density-clustering and supervised classification for event identification in single-molecule force spectroscopy data

Single-molecule force spectroscopy(SMFS)measurements of the dynamics of biomolecules typically require identifying massive events and states from large data sets,such as extracting rupture forces from force-extension curves(FECs)in pulling experiments and identifying states from extension-time trajectories(ETTs)in force-clamp experiments.The former is often accomplished manually and hence is time-consuming and laborious while the latter is always impeded by the presence of baseline drift.In this study,we attempt to accurately and automatically identify the events and states from SMFS experiments with a machine learning approach,which combines clustering and classification for event identification of SMFS(ACCESS).As demonstrated by analysis of a series of data sets,ACCESS can extract the rupture forces from FECs containing multiple unfolding steps and classify the rupture forces into the corresponding conformational transitions.Moreover,ACCESS successfully identifies the unfolded and folded states even though the ETTs display severe nonmonotonic baseline drift.Besides,ACCESS is straightforward in use as it requires only three easy-to-interpret parameters.As such,we anticipate that ACCESS will be a useful,easy-to-implement and high-performance tool for event and state identification across a range of single-molecule experiments.

Theoretical study of overstretching DNA–RNA hybrid duplex

DNA–RNA hybrid(DRH) plays important roles in many biological processes. Here, we use a thermodynamic theory to analyze the free energy and unpeeling properties of the overstretching transition for the DRH molecule and compare the results with double-helix DNA. We report that the RNA strand of DRH is easier to get unpeeled than the DNA strand while the difficulty in unpeeling the double helix DNA lies in between. We also investigate the sequence effect, such as GC content and purine content, on the properties of unpeeling the DRH. Further, to study the temperature effect, the forcetemperature phase diagram of DRH and DNA are calculated and compared. Finally, using a kinetic model, we calculate the force–extension curves in the DRH stretching and relaxation process under different pulling rates and temperatures. Our results show that both pulling rate and temperature have important influences on the stretching and relaxation kinetics of unpeeling the DRH. Putting all these results together, our work provides a comprehensive view of both the thermodynamics and kinetics in DRH overstretching.

基于光电导航的智能移动测量小车设计

提出了一种智能车设计,该智能车设计采用飞思卡尔K60 MCU为核心处理器件,通过CMOS摄像头获取跑道路径并配置主动蓝光照明系统辅助照明,实现精确导航。智能车行走时,该智能车配备的激光检测模块实现对跑道两旁红色中华铅笔的数量测量以及智能车行驶过程中进出隧道的检测。而光电编码器的反馈信号既可经PID算法控制智能车的行驶速度,同时在隧道里也可凭此计算出隧道长度。实验结果表明,该智能车设计合理、电路稳定,可快速平稳行驶和准确测量,在智能车测量应用方面具有重要意义。