Influenza virus antigenic variation, host antibody production and new approach to control epidemics

Influenza is an infectious disease and can lead to life-threatening complications like pneumonia. The disease is caused by three types of RNA viruses called influenza types A, B and C, each consisting of eight negative single-stranded RNA-segments encoding 11 proteins. Current annual vaccines contain two type A strains and one type B strain and are capable of inducing strong antibody responses to both the surface glycoprotein hemagglutinin and the neuraminidase. While these vaccines are protective against vaccine viruses they are not effective against newly emerging viruses that contain antigenic variations known as antigenic drift and shift. In nature, environmental selection pressure generally plays a key role in selecting antigenic changes in the antigen determining spots of hemagglutinin, resulting in changes in the antigenicity of the virus. Recently, a new technology has been developed where influenza-specific IgG+ antibody-secreting plasma cells can be isolated and cloned directly from vaccinated humans and high affinity monoclonal antibodies can be produced within several weeks after vaccination. The new technology holds great promise for the development of effective passive antibody therapy to limit the spread of influenza viruses in a timely manner

Effect of engine thrust on nonlinear flutter of wings

The propulsion of wing-mounted engine is a typical follower force and may cause significant influences upon wing flutter characteristics. An integrated flutter analysis method has been presented, within which the effects of engine thrusts and geometrical nonlinearities are both considered. Firstly the method has been applied to evaluate the effects of thrusts on the flutter boundary of a high-altitude, long-endurance aircraft wing. The numerical results have an excellent agreement with the published ones. Furthermore the finite element model of a wing carrying two engines has been established, and the influences of propulsion magnitude and position on wing flutter speed are mainly investigated. The results indicated that the effects of engine thrusts are indispensable for wing flutter analysis

Aeroelastic tailoring of high-aspect-ratio composite joined-wing UAV

For the high-aspect-ratio composite joined-wing UAV, as the geometric nonlinear significant effect, nonlinear aeroelastic analysis method should be applied when study its aeroelastic tailoring method. In the paper, based on the secondary development of MSC/Nastran software with Direct matrix abstraction programme language, with the adopting the multidisciplinary design optimization platform Isight software integrating the MSC/Nastran software analysis, modules of the static aeroelastic analysis, nonlinear static analysis and flutter analysis, a nonlinear aeroelastic tailoring method for high –aspect-ratio composite joined-wing UAV has been presented. Example show that, the method proposed in this paper not only can solve nonlinear aeroelastic tailoring of high-aspect-ratio composite joined-wing UAV problem, but also can be applied to complex engineering structure

Estimating Effects of Long-Term Treatments

Estimating the effects of long-term treatments in A/B testing presents a significant challenge. Such treatments -- including updates to product functions, user interface designs, and recommendation algorithms -- are intended to remain in the system for a long period after their launches. On the other hand, given the constraints of conducting long-term experiments, practitioners often rely on short-term experimental results to make product launch decisions. It remains an open question how to accurately estimate the effects of long-term treatments using short-term experimental data. To address this question, we introduce a longitudinal surrogate framework. We show that, under standard assumptions, the effects of long-term treatments can be decomposed into a series of functions, which depend on the user attributes, the short-term intermediate metrics, and the treatment assignments. We describe the identification assumptions, the estimation strategies, and the inference technique under this framework. Empirically, we show that our approach outperforms existing solutions by leveraging two real-world experiments, each involving millions of users on WeChat, one of the world's largest social networking platforms

Clarification of the role of N-glycans on the common beta-subunit of the human IL-3, IL-5 and GM-CSF receptors and the murine IL-3 beta-receptor in ligand-binding and receptor activation

Granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin (IL)-3 and IL-5 are related cytokines that play key roles in regulating the differentiation, proliferation, survival and activation of myeloid blood cells. The cell surface receptors for these cytokines are composed of cytokine-specific α-subunits and a common β-receptor (βc), a shared subunit that is essential for receptor signaling in response to GM-CSF, IL-3 and IL-5. Previous studies have reached conflicting conclusions as to whether N-glycosylation of the βc-subunit is necessary for functional GM-CSF, IL-3 and IL-5 receptors. We sought to clarify whether βc N-glycosylation plays a role in receptor function, since all structural studies of human βc to date have utilized recombinant protein lacking N-glycosylation at Asn328. Here, by eliminating individual N-glycans in human βc and the related murine homolog, βIL-3, we demonstrate unequivocally that ligand-binding and receptor activation are not critically dependent on individual N-glycosylation sites within the β-subunit although the data do not preclude the possibility that N-glycans may exert some sort of fine control. These studies support the biological relevance of the X-ray crystal structures of the human βc domain 4 and the complete ectodomain, both of which lack N-glycosylation at Asn328

High-throughput discovery of chemical structure-polarity relationships combining automation and machine learning techniques

As an essential attribute of organic compounds, polarity has a profound influence on many molecular properties such as solubility and phase transition temperature. Thin layer chromatography (TLC) represents a commonly used technique for polarity measurement. However, current TLC analysis presents several problems, including the need for a large number of attempts to obtain suitable conditions, as well as irreproducibility due to non-standardization. Herein, we describe an automated experiment system for TLC analysis. This system is designed to conduct TLC analysis automatically, facilitating high-throughput experimentation by collecting large experimental data under standardized conditions. Using these datasets, machine learning (ML) methods are employed to construct surrogate models correlating organic compounds' structures and their polarity using retardation factor (Rf). The trained ML models are able to predict the Rf value curve of organic compounds with high accuracy. Furthermore, the constitutive relationship between the compound and its polarity can also be discovered through these modeling methods, and the underlying mechanism is rationalized through adsorption theories. The trained ML models not only reduce the need for empirical optimization currently required for TLC analysis, but also provide general guidelines for the selection of conditions, making TLC an easily accessible tool for the broad scientific community

Simple Way To Fabricate Novel Paper-Based Valves Using Plastic Comb Binding Spines

A novel strategy for fabricating the paper-based valves on microfluidic paper-based analytical devices (mu PADs) was described to control fluid in a user-friendly way. Initial prototypes of 3D mu PADs manipulate the spatial distribution of fluid within the device. The movable paper channel in a different layer could be achieved using the channel's connection or disconnection to realize the valve function using plastic comb binding spines (PCBS). The entire valve manipulation process was similar to a desk calendar that can be flipped over and turned back. It is notable that this kind of PCBS valve can control a fluid in a simple and easy way without the timing setting or any trigger, and this advantage makes it user-friendly for untrained users to carry out the complex and high throughput operations. The reusable plastic comb binding spines greatly reduce the cost of fabricating paper-based valves. To evaluate the performance, the actual samples of Fe (II) and nitrite were successfully analyzed. We hope this method will introduce a new approach to fabrication of paper-based valves on mu PADs in the future

Different activation signatures in the primary sensorimotor and higher-level regions for haptic three-dimensional curved surface exploration

Haptic object perception begins with continuous exploratory contact, and the human brain needs to accumulate sensory information continuously over time. However, it is still unclear how the primary sensorimotor cortex (PSC) interacts with these higher-level regions during haptic exploration over time. This functional magnetic resonance imaging (fMRI) study investigates time-dependent haptic object processing by examining brain activity during haptic 3D curve and roughness estimations. For this experiment, we designed sixteen haptic stimuli (4 kinds of curves x 4 varieties of roughness) for the haptic curve and roughness estimation tasks. Twenty participants were asked to move their right index and middle fingers along the surface twice and to estimate one of the two features -roughness or curvature -depending on the task instruction. We found that the brain activity in several higher-level regions (e.g., the bilateral posterior parietal cortex) linearly increased as the number of curves increased during the haptic exploration phase. Surprisingly, we found that the contralateral PSC was parametrically modulated by the number of curves only during the late exploration phase but not during the early exploration phase. In contrast, we found no similar parametric modulation activity patterns during the haptic roughness estimation task in either the contralateral PSC or in higher-level regions. Thus, our findings suggest that haptic 3D object perception is processed across the cortical hierarchy, whereas the contralateral PSC interacts with other higher-level regions across time in a manner that is dependent upon the features of the object