Manipulation of Single DNA Molecules through Nano-fludic Devices: Simulation and Theory

Nanofludic platforms such as solid-state nanopores and nanochannels enable the manipulation of DNA molecules and have the potential to be a low-cost and high-efficiency DNA sequencing device. DNA nanopore translocation is a process where DNA moves from one chamber to another through a nanopore. To get into the pore, the molecule entropy decreases and free energy increases. In order to thread the DNA throughout the pore, an electric bias is applied to overcome the entropic energy barrier. The occupation of DNA impedes the ion transport and creates a blockage current of which the amplitude and duration provide the information on the DNA sequence since different bases (or base pairs) can be discriminated through different magnitude of blockage. Mining DNA sequence from the electric current profile requires an accurate knowledge of the passage time of a given base along the molecule. Our model assumes that the translocation process at high fields proceeds too fast for the chain to relax, and thus the distribution of translocation times of a given monomer are controlled by the initial conformation of the chain (the distribution of its loops). The model predicts the translocation time distribution is determined by the distribution of initial conformation as well as by the thermal fluctuations to the conformation during the translocation process. Narrow nanochannels require high threshold electric fields to achieve DNA translocation, leading to short dwell times of DNA in these channels. Nano-funnels integrated with nano-channels reduce the free energy barrier and lower the threshold electric field required for DNA translocation. A focused electric field within the funnel increases the electric force on the DNA, compresses the molecule, and increases the osmotic pressure at the nano-channel entrance which facilitates the entry at lower electric fields. Besides controlling the speed of the molecule's movement, appropriately designed nano-funnels such as parabolic shaped ones can also function as tweezers that allow the trapping and stable control of the position of the DNA molecule. A combination of a series of nano-funnels devices enable a wider range of location and speed manipulation and can assist genome mapping and sequencing when equipped with base detector.Doctor of Philosoph

Enhanced nanochannel translocation and localization of genomic DNA molecules using three-dimensional nanofunnels

The ability to precisely control the transport of single DNA molecules through a nanoscale channel is critical to DNA sequencing and mapping technologies that are currently under development. Here we show how the electrokinetically driven introduction of DNA molecules into a nanochannel is facilitated by incorporating a three-dimensional nanofunnel at the nanochannel entrance. Individual DNA molecules are imaged as they attempt to overcome the entropic barrier to nanochannel entry through nanofunnels with various shapes. Theoretical modeling of this behavior reveals the pushing and pulling forces that result in up to a 30-fold reduction in the threshold electric field needed to initiate nanochannel entry. In some cases, DNA molecules are stably trapped and axially positioned within a nanofunnel at sub-threshold electric field strengths, suggesting the utility of nanofunnels as force spectroscopy tools. These applications illustrate the benefit of finely tuning nanoscale conduit geometries, which can be designed using the theoretical model developed here.Forcing a DNA molecule into a nanoscale channel requires overcoming the free energy barrier associated with confinement. Here, the authors show that DNA injected through a funnel-shaped entrance more efficiently enters the nanochannel, thanks to facilitating forces generated by the nanofunnel geometry

Association of psychological distress, smoking and genetic risk with the incidence of lung cancer: a large prospective population-based cohort study

BackgroundEmerging evidence suggests a potential link between psychological distress (anxiety and depression) and lung cancer risk, however, it is unclear whether other factors such as tobacco smoking and genetic susceptibility modify the association.MethodsWe included 405,892 UK Biobank participants free of cancer at baseline. Psychological distress was measured using the Patient Health Questionnaire-4 (PHQ-4). A polygenic risk score (PRS) was calculated using 18 lung cancer-associated genetic loci. Multivariable Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsDuring a median follow-up of 7.13 years, 1754 lung cancer cases were documented. The higher score of psychological distress was associated with an increased risk of lung cancer (HRper 1-SD= 1.07, 95% CI: 1.02-1.11) after adjustment for smoking and other confounders. Mediation analysis revealed that 16.8% (95% CI: 13.0%-20.6%) of the distress-lung cancer association was mediated by smoking. Compared with never smokers with no distress, participants with heavy smoking and high distress had the highest risk of lung cancer (HR=18.57, 95% CI: 14.51-23.76). Both multiplicative and additive interactions were observed between smoking and psychological distress in lung cancer. Furthermore, the greatest relative increase in risk was observed among those with high genetic risk and high distress (HR=1.87, 95%CI: 1.50-2.33), and there was a significant additive interaction between the PRS and psychological distress.ConclusionOur results indicate that psychological distress was associated with an elevated risk of incident lung cancer, and such relation was modified by tobacco smoking and genetic susceptibility

Social integration and utilization of national basic public health services among China's internal migrants with chronic diseases: A structural equation modelling approach

Internal migrants with chronic diseases (IMCDs) are a specific subgroup of the internal migrants, but few studies have focused on health service utilization among this group. Social integration is an essential element in the maintenance of health and well-being in migrants. However, the measurement of social integration remains inconsistent. This study aimed to measure social integration more comprehensively and evaluate the association between social integration and National Basic Public Health Services (NBPHS) utilization among IMCDs in China, thereby providing theoretical support for health promotion among IMCDs. The data of this study were obtained from the China Migrants Dynamic Survey (CMDS) in 2017. A total of 9272 internal migrants who self-reported hypertension and/or type 2 diabetes were included in the analysis. Four factors were extracted through exploratory factor analysis to measure the social integration of IMCDs: psychological identity, community involvement, social security, and sociocultural adaptation. The results show the IMCDs underutilized NBPHS, with 26.80 % stating that they have not used any of the services in the NBPHS. We confirmed the positive association between social integration and NBPHS use among IMCDs. The social integration of IMCDs in developed regions was relatively worse than in developing regions, further exacerbating the underutilization of NBPHS in developed regions. Therefore, targeted government measures and supportive policies are necessary, especially in developed regions, to encourage IMCDs to participate in social organizations and community activities and stimulate their active participation in the NBPHS

Fuzzy Neural Network Dynamic Inverse Control Strategy for Quadrotor UAV Based on Atmospheric Turbulence

Quadrotor UAV is vulnerable to external interference, which affects search and rescue. In this paper, a fuzzy neural network dynamic inverse controller (FNN-DIC) is designed to eliminate the instability of the attitude angle caused by atmospheric turbulence. Considering the complexity of atmospheric turbulence, the component model of atmospheric turbulence is obtained firstly based on the Dryden model, using Gaussian white noise as a random input signal and a designed shaping filter. Combined with the Newton-Euler equation, a nonlinear dynamic model for the quadrotor UAV with atmospheric disturbance is established. While the traditional nonlinear dynamic inverse cancels the nonlinearity of the controlled object, it relies on precise mathematical models. The fuzzy neural network can adaptively compensate for the inaccurate part of the model and the inverse error of the model caused by the external disturbance, and the stability of the control system is strictly proved by using the Lyapunov function. The experiments are carried out on the simulation platform, and the results show that the FNN method can ensure that the quadrotor UAV can still fly smoothly against strong disturbances, and that robustness of the system is significantly improved

Fuzzy Neural Network Dynamic Inverse Control Strategy for Quadrotor UAV Based on Atmospheric Turbulence

Quadrotor UAV is vulnerable to external interference, which affects search and rescue. In this paper, a fuzzy neural network dynamic inverse controller (FNN-DIC) is designed to eliminate the instability of the attitude angle caused by atmospheric turbulence. Considering the complexity of atmospheric turbulence, the component model of atmospheric turbulence is obtained firstly based on the Dryden model, using Gaussian white noise as a random input signal and a designed shaping filter. Combined with the Newton-Euler equation, a nonlinear dynamic model for the quadrotor UAV with atmospheric disturbance is established. While the traditional nonlinear dynamic inverse cancels the nonlinearity of the controlled object, it relies on precise mathematical models. The fuzzy neural network can adaptively compensate for the inaccurate part of the model and the inverse error of the model caused by the external disturbance, and the stability of the control system is strictly proved by using the Lyapunov function. The experiments are carried out on the simulation platform, and the results show that the FNN method can ensure that the quadrotor UAV can still fly smoothly against strong disturbances, and that robustness of the system is significantly improved

Construction of predictive model for osteoporosis related factors among postmenopausal women on the basis of logistic regression and Bayesian network

Osteoporosis is a prevalent chronic disease that often goes unnoticed in postmenopausal women. Early identification of risk factors for osteoporosis in postmenopausal women is essential. This study aimed to develop predictive models for osteoporosis-related factors among postmenopausal women in the U.S. and explore the influencing factors. In this cross-sectional study, we included 4417 postmenopausal women from the NHANES (2009–2010, 2013–2014, and 2017–2020). Through multiple regression analysis, we found that age, minutes of sedentary activity, prednisone or cortisone usage, arthritis, bone loss around teeth, and trouble sleeping were risk factors for osteoporosis after menopause. Conversely, height, BMI, and age at the last menstrual period were identified as protective factors. The findings from the Bayesian network analysis indicated that several factors influenced osteoporosis, including age, BMI, bone loss around teeth, prednisone or cortisone usage, arthritis, and age at the last menstrual period. On the other hand, minutes of sedentary activity and height might have indirect effects, while trouble sleeping may not have a significant impact. Both logistic regression and Bayesian network models demonstrated good predictive capabilities in predicting osteoporosis among postmenopausal women. In addition, Bayesian networks offer a more intuitive depiction of the intricate network risk mechanism between diseases and factors

Resilient and event-triggered control of stochastic jump systems under deception and denial of service attacks

This article investigates the resilient and event-triggered control problem of stochastic jump systems subject to randomly occurring denial of service (DoS) attacks and deception attacks. First, a novel resilient and memory event-triggered scheme (RMETS) is proposed. The influence caused by DoS attacks is characterized as an uncertainty of the triggering condition. Under the RMETS, the desired security performance of the system and limited network resources can be well balanced while stochastic deception and DoS attacks occur. Second, by using the Lyapunov theory and the linear matrix inequality method, the resilient controller and the proposed RMETS are co-designed. Sufficient conditions are established to ensure the security performance under the two types of attacks. Finally, numerical and practical examples are rendered to illustrate the effectiveness of the developed approach.Yihao Xu, Senchun Chai, Peng Shi, Baihai Zhang, Yanqian Wan