Concurrent coupling of atomistic simulation and mesoscopic hydrodynamics for flows over soft multi-functional surfaces

We develop an efficient parallel multiscale method that bridges the atomistic and mesoscale regimes, from nanometer to micron and beyond, via concurrent coupling of atomistic simulation and mesoscopic dynamics. In particular, we combine an all-atom molecular dynamics (MD) description for specific atomistic details in the vicinity of the functional surface, with a dissipative particle dynamics (DPD) approach that captures mesoscopic hydrodynamics in the domain away from the functional surface. In order to achieve a seamless transition in dynamic properties we endow the MD simulation with a DPD thermostat, which is validated against experimental results by modeling water at different temperatures. We then validate the MD-DPD coupling method for transient Couette and Poiseuille flows, demonstrating that the concurrent MD-DPD coupling can resolve accurately the continuum-based analytical solutions. Subsequently, we simulate shear flows over polydimethylsiloxane (PDMS)-grafted surfaces (polymer brushes) for various grafting densities, and investigate the slip flow as a function of the shear stress. We verify that a "universal" power law exists for the sliplength, in agreement with published results. Having validated the MD-DPD coupling method, we simulate time-dependent flows past an endothelial glycocalyx layer (EGL) in a microchannel. Coupled simulation results elucidate the dynamics of EGL changing from an equilibrium state to a compressed state under shear by aligning the molecular structures along the shear direction. MD-DPD simulation results agree well with results of a single MD simulation, but with the former more than two orders of magnitude faster than the latter for system sizes above one micron.Comment: 11 pages, 12 figure

The genetic diversity and geographical separation study of Oncomelania hupensis populations in mainland China using microsatellite loci

© 2016 Guan et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. The attached file is the published version of the article.NHM Repositor

Increasing trans-cleavage catalytic efficiency of Cas12a and Cas13a with chemical enhancers: Application to amplified nucleic acid detection

The exceptional programable trans-cleavage ability of type V and VI CRISPR/Cas nucleases paved the way for ultrasensitive CRISPR/Cas based sensing of nucleic acid and alternative targets. However, the enhancement of the trans-cleavage activity of Cas effector with organic chemical agents has not been explored thus far. We report here chemically enhanced trans-cleavage activity of Cas12a and Cas13a nucleases which improves sensor performance in CRISPR/Cas biosensing. Improved trans-ssDNA cleavage of Cas12a and trans-ssRNA cleavage of Cas13a were demonstrated by using sulfhydryl reductants and non-ionic surfactants. DTT and PVA were demonstrated to be the most effective chemical enhancers in both cases. By using a fluorescence resonance energy transfer (FRET)-based intramolecular distance measurements, we identified the mechanism of this enhancement to be the conformation change of the ribonucleoprotein and quantified it to be major (about 50% increase of a relevant intramolecular distance). These chemical enhancers have been integrated into the established CRISPR/Cas biosensing protocols without additional modifications. For the detection of Helicobacter Pylori DNA and SARS-CoV-2 RNA, we found a decreased reaction time by 75–83% and 4–6-fold increased sensitivity. These results indicate that chemical enhancers provide a versatile and broadly applicable approach to break through the barriers of long reaction time and sensitivity in CRISPR/Cas sensors

A simple and versatile CRISPR/Cas12a-based immunosensing platform: Towards attomolar level sensitivity for small protein diagnostics

Recent advances in CRISPR/Cas biosensing have led to impressive performance in sensitivity, specificity, and speed for nucleic acid detection. However, the remarkable advantages (such as universality, ultralow, attomolar detection limits) of CRISPR/Cas biosensing systems are limited in testing non-nucleic acid targets. Herein, by synthesizing a functional hybrid conjugate of antibody and single strand DNA oligonucleotide, we had successfully demonstrated the capability to integrate CRISPR/Cas12a-based signal amplification into different types of immunoassay schemes without the need for any additional recognition molecule or molecular synthesis during the detection process, thus providing a simple but generally applicable approach to improve the conventional immunoassays with attomolar sensitivity for small protein detections, referred as the CRISPR-based Universal Immunoassay Signal Enhancer (CRUISE). CRUISE is capable of being integrated into various immunoassays either through the primary antibody or the secondary antibody, with sensitivity down to 1 fg mL−1 (∼50 aM) and 6 logs of linear range for detecting cytokines, such as IFN-γ and EGFR, under 3–4 h. It has a 103 times higher sensitivity compared to a commercial IFN-γ ELISA kit, but uses the same experimental scheme. The same 1 fg mL−1 sensitivity along with 6 logs of linear range was realized for IFN-γ detection in human plasma samples. We are expecting that our CRUISE provides an alternative but simple, user-friendly and effective strategy for those who rely on the use of immunoassays, while struggling with the limits of their sensitivity or detection ranges

Fractional SEIR Model and Data-Driven Predictions of COVID-19 Dynamics of Omicron Variant

We study the dynamic evolution of COVID-19 cased by the Omicron variant via a fractional susceptible-exposedinfected-removed (SEIR) model. Preliminary data suggest that the symptoms of Omicron infection are not prominent and the transmission is therefore more concealed, which causes a relatively slow increase in the detected cases of the new infected at the beginning of the pandemic. To characterize the specific dynamics, the Caputo-Hadamard fractional derivative is adopted to refined the classical SEIR model. Based on the reported data, we infer the fractional order, timedependent parameters, as well as unobserved dynamics of the fractional SEIR model via fractional physics-informed neural networks (fPINNs). Then, we make short-time predictions using the learned fractional SEIR model